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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0258983c9b059ccec072195ce6e1f212887933f0 | [
"if context is None:\n context = {}\nsuper(building_fill_insurance, self).view_init(cr, uid, fields_list, context=context)\nif len(context.get('active_ids', [])) > 1:\n raise osv.except_osv(_('Error!'), _('You cannot perform this operation on more than one building.'))\nif context.get('active_id', False):\n ... | <|body_start_0|>
if context is None:
context = {}
super(building_fill_insurance, self).view_init(cr, uid, fields_list, context=context)
if len(context.get('active_ids', [])) > 1:
raise osv.except_osv(_('Error!'), _('You cannot perform this operation on more than one build... | building_fill_insurance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class building_fill_insurance:
def view_init(self, cr, uid, fields_list, context=None):
"""Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @... | stack_v2_sparse_classes_36k_train_025600 | 4,027 | no_license | [
{
"docstring": "Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @return: New arch of view with new columns.",
"name": "view_init",
"signature": "def v... | 2 | stack_v2_sparse_classes_30k_train_013752 | Implement the Python class `building_fill_insurance` described below.
Class description:
Implement the building_fill_insurance class.
Method signatures and docstrings:
- def view_init(self, cr, uid, fields_list, context=None): Creates view dynamically and adding fields at runtime. @param self: The object pointer. @pa... | Implement the Python class `building_fill_insurance` described below.
Class description:
Implement the building_fill_insurance class.
Method signatures and docstrings:
- def view_init(self, cr, uid, fields_list, context=None): Creates view dynamically and adding fields at runtime. @param self: The object pointer. @pa... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class building_fill_insurance:
def view_init(self, cr, uid, fields_list, context=None):
"""Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class building_fill_insurance:
def view_init(self, cr, uid, fields_list, context=None):
"""Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @return: New ar... | the_stack_v2_python_sparse | v_7/GDS/shamil_v3/building_management_6.1/wizard/building_fill_insurance.py | musabahmed/baba | train | 0 | |
f0f80f3716b3efd0a35fd3914efbf09ed4d9e0d2 | [
"from h5py import File as h5\nself.preexisting_slice = preexisting_slice\nself.incoming_slice = incoming_slice\nself.received_slices = []\nself.bins = np.squeeze(np.array(eval(bins)))\nself.frames_per_block = frames_per_block\nself.outputs = outputs\npdist = np.zeros(self.bins.size - 1, dtype=[('lower bound', 'f4')... | <|body_start_0|>
from h5py import File as h5
self.preexisting_slice = preexisting_slice
self.incoming_slice = incoming_slice
self.received_slices = []
self.bins = np.squeeze(np.array(eval(bins)))
self.frames_per_block = frames_per_block
self.outputs = outputs
... | Coroutine class; accumulates Blocks of data and performs analysis once complete dataset is present; may then be sent to a Block_Acceptor | Hist_Block_Accumulator | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Hist_Block_Accumulator:
"""Coroutine class; accumulates Blocks of data and performs analysis once complete dataset is present; may then be sent to a Block_Acceptor"""
def __init__(self, preexisting_slice, incoming_slice, bins, frames_per_block, outputs, attrs={}, **kwargs):
"""Initia... | stack_v2_sparse_classes_36k_train_025601 | 28,607 | permissive | [
{
"docstring": "Initializes accumulator **Arguments:** :*preexisting_slice*: Slice containing frame indices whose results were included in *outputs* before this invocation of program :*incoming_slice*: Slice containting frame indices whose results are to be added to *outputs* during this invocation of program :... | 3 | stack_v2_sparse_classes_30k_train_005375 | Implement the Python class `Hist_Block_Accumulator` described below.
Class description:
Coroutine class; accumulates Blocks of data and performs analysis once complete dataset is present; may then be sent to a Block_Acceptor
Method signatures and docstrings:
- def __init__(self, preexisting_slice, incoming_slice, bin... | Implement the Python class `Hist_Block_Accumulator` described below.
Class description:
Coroutine class; accumulates Blocks of data and performs analysis once complete dataset is present; may then be sent to a Block_Acceptor
Method signatures and docstrings:
- def __init__(self, preexisting_slice, incoming_slice, bin... | 9e86e996ed7958a348012c053fa957d94729be8a | <|skeleton|>
class Hist_Block_Accumulator:
"""Coroutine class; accumulates Blocks of data and performs analysis once complete dataset is present; may then be sent to a Block_Acceptor"""
def __init__(self, preexisting_slice, incoming_slice, bins, frames_per_block, outputs, attrs={}, **kwargs):
"""Initia... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Hist_Block_Accumulator:
"""Coroutine class; accumulates Blocks of data and performs analysis once complete dataset is present; may then be sent to a Block_Acceptor"""
def __init__(self, preexisting_slice, incoming_slice, bins, frames_per_block, outputs, attrs={}, **kwargs):
"""Initializes accumul... | the_stack_v2_python_sparse | secondary/pdist.py | KarlTDebiec/MDclt | train | 0 |
94115ff2095dcfa76bde980484cb447ce6beb69b | [
"pass\nres = []\ntry:\n all = models.Position.objects.all()\n for postion in all:\n res.append({'name': postion.name, 'salary': postion.salary, 'experience': postion.experience, 'education': postion.education, 'keyword': postion.keyword, 'company': postion.company, 'add_time': postion.add_time.strftime... | <|body_start_0|>
pass
res = []
try:
all = models.Position.objects.all()
for postion in all:
res.append({'name': postion.name, 'salary': postion.salary, 'experience': postion.experience, 'education': postion.education, 'keyword': postion.keyword, 'company':... | Position | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Position:
def get(self, request):
"""获取简历列表"""
<|body_0|>
def post(self, request):
"""新增职位"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pass
res = []
try:
all = models.Position.objects.all()
for postion in ... | stack_v2_sparse_classes_36k_train_025602 | 1,855 | no_license | [
{
"docstring": "获取简历列表",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "新增职位",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019822 | Implement the Python class `Position` described below.
Class description:
Implement the Position class.
Method signatures and docstrings:
- def get(self, request): 获取简历列表
- def post(self, request): 新增职位 | Implement the Python class `Position` described below.
Class description:
Implement the Position class.
Method signatures and docstrings:
- def get(self, request): 获取简历列表
- def post(self, request): 新增职位
<|skeleton|>
class Position:
def get(self, request):
"""获取简历列表"""
<|body_0|>
def post(se... | d7acdadc07e5c33e4d46168fa4b435fc24b36aa1 | <|skeleton|>
class Position:
def get(self, request):
"""获取简历列表"""
<|body_0|>
def post(self, request):
"""新增职位"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Position:
def get(self, request):
"""获取简历列表"""
pass
res = []
try:
all = models.Position.objects.all()
for postion in all:
res.append({'name': postion.name, 'salary': postion.salary, 'experience': postion.experience, 'education': postion.e... | the_stack_v2_python_sparse | djangoProject/rcw/Position/position.py | Asenli/Recruitment | train | 0 | |
a341395cfa7e686427a468eb93a365b762be5257 | [
"args = self.comments_filter.parse_args()\nitems_per_page = 20\npage_number = args['page']\nif page_number < 1:\n return abort(HTTPStatus.BAD_REQUEST, message=\"'page' must be > 0\")\nitems_query = Thesis.query.join(Thesis.comment_backref).filter(ThesisComment.thesis_id == thesis_id).order_by(Thesis.created_at.a... | <|body_start_0|>
args = self.comments_filter.parse_args()
items_per_page = 20
page_number = args['page']
if page_number < 1:
return abort(HTTPStatus.BAD_REQUEST, message="'page' must be > 0")
items_query = Thesis.query.join(Thesis.comment_backref).filter(ThesisComment... | ThesisComments | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThesisComments:
def get(self, thesis_id):
"""Get comments of the thesis * User can view comments of thesis * View with pagination"""
<|body_0|>
def post(self, thesis_id):
"""Create a new thesis comment * User with permission to **"create theses"** can create a new co... | stack_v2_sparse_classes_36k_train_025603 | 3,272 | permissive | [
{
"docstring": "Get comments of the thesis * User can view comments of thesis * View with pagination",
"name": "get",
"signature": "def get(self, thesis_id)"
},
{
"docstring": "Create a new thesis comment * User with permission to **\"create theses\"** can create a new comment * **Comment is a t... | 2 | null | Implement the Python class `ThesisComments` described below.
Class description:
Implement the ThesisComments class.
Method signatures and docstrings:
- def get(self, thesis_id): Get comments of the thesis * User can view comments of thesis * View with pagination
- def post(self, thesis_id): Create a new thesis commen... | Implement the Python class `ThesisComments` described below.
Class description:
Implement the ThesisComments class.
Method signatures and docstrings:
- def get(self, thesis_id): Get comments of the thesis * User can view comments of thesis * View with pagination
- def post(self, thesis_id): Create a new thesis commen... | dce87ffe395ae4bd08b47f28e07594e1889da819 | <|skeleton|>
class ThesisComments:
def get(self, thesis_id):
"""Get comments of the thesis * User can view comments of thesis * View with pagination"""
<|body_0|>
def post(self, thesis_id):
"""Create a new thesis comment * User with permission to **"create theses"** can create a new co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThesisComments:
def get(self, thesis_id):
"""Get comments of the thesis * User can view comments of thesis * View with pagination"""
args = self.comments_filter.parse_args()
items_per_page = 20
page_number = args['page']
if page_number < 1:
return abort(HTTP... | the_stack_v2_python_sparse | src/backend/app/api/public/theses/thesis/thesis_comments.py | aimanow/sft | train | 0 | |
092d7f1d4fbcb6c5d20129cfa6bed7e8e4c36b25 | [
"if n == 0:\n return []\n\ndef generate(l, r):\n res = []\n for i in range(l, r + 1):\n for ll in generate(l, i - 1):\n for rr in generate(i + 1, r):\n root = TreeNode(i)\n root.left = ll\n root.right = rr\n res += (root,)\n r... | <|body_start_0|>
if n == 0:
return []
def generate(l, r):
res = []
for i in range(l, r + 1):
for ll in generate(l, i - 1):
for rr in generate(i + 1, r):
root = TreeNode(i)
root.left =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generateTrees(self, n):
""":type n: int :rtype: List[TreeNode]"""
<|body_0|>
def generateTrees2(self, n):
""":type n: int :rtype: List[TreeNode]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 0:
return []
... | stack_v2_sparse_classes_36k_train_025604 | 1,507 | no_license | [
{
"docstring": ":type n: int :rtype: List[TreeNode]",
"name": "generateTrees",
"signature": "def generateTrees(self, n)"
},
{
"docstring": ":type n: int :rtype: List[TreeNode]",
"name": "generateTrees2",
"signature": "def generateTrees2(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateTrees(self, n): :type n: int :rtype: List[TreeNode]
- def generateTrees2(self, n): :type n: int :rtype: List[TreeNode] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateTrees(self, n): :type n: int :rtype: List[TreeNode]
- def generateTrees2(self, n): :type n: int :rtype: List[TreeNode]
<|skeleton|>
class Solution:
def generate... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def generateTrees(self, n):
""":type n: int :rtype: List[TreeNode]"""
<|body_0|>
def generateTrees2(self, n):
""":type n: int :rtype: List[TreeNode]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generateTrees(self, n):
""":type n: int :rtype: List[TreeNode]"""
if n == 0:
return []
def generate(l, r):
res = []
for i in range(l, r + 1):
for ll in generate(l, i - 1):
for rr in generate(i + 1, r... | the_stack_v2_python_sparse | generateTrees.py | NeilWangziyu/Leetcode_py | train | 2 | |
743ec0f5efa603002d9e45b1993bd523adf56d43 | [
"super(CustomResNet152, self).__init__()\nself.dim = dim\nresnet = torchvision.models.resnet152(pretrained=True)\nmodules = list(resnet.children())[:-2]\nself.resnet = nn.Sequential(*modules)\nself.conv = nn.Conv2d(2048, self.dim, kernel_size=(1, 1), stride=(1, 1), bias=False)\nif train_resnet:\n for i, child in... | <|body_start_0|>
super(CustomResNet152, self).__init__()
self.dim = dim
resnet = torchvision.models.resnet152(pretrained=True)
modules = list(resnet.children())[:-2]
self.resnet = nn.Sequential(*modules)
self.conv = nn.Conv2d(2048, self.dim, kernel_size=(1, 1), stride=(1,... | Image encoder that computes both its image embedding and its convolutional feature map | CustomResNet152 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomResNet152:
"""Image encoder that computes both its image embedding and its convolutional feature map"""
def __init__(self, dim=1024, train_resnet=False):
"""Initializes image encoder based on ResNet :param dim: length of the UniVSE space embeddings :param train_resnet: sets bac... | stack_v2_sparse_classes_36k_train_025605 | 20,277 | no_license | [
{
"docstring": "Initializes image encoder based on ResNet :param dim: length of the UniVSE space embeddings :param train_resnet: sets backbone's weights as trainable if true",
"name": "__init__",
"signature": "def __init__(self, dim=1024, train_resnet=False)"
},
{
"docstring": "Forward pass of t... | 2 | stack_v2_sparse_classes_30k_train_021538 | Implement the Python class `CustomResNet152` described below.
Class description:
Image encoder that computes both its image embedding and its convolutional feature map
Method signatures and docstrings:
- def __init__(self, dim=1024, train_resnet=False): Initializes image encoder based on ResNet :param dim: length of ... | Implement the Python class `CustomResNet152` described below.
Class description:
Image encoder that computes both its image embedding and its convolutional feature map
Method signatures and docstrings:
- def __init__(self, dim=1024, train_resnet=False): Initializes image encoder based on ResNet :param dim: length of ... | bc4fe571775e982975d6ecac82253e94de9dcd2b | <|skeleton|>
class CustomResNet152:
"""Image encoder that computes both its image embedding and its convolutional feature map"""
def __init__(self, dim=1024, train_resnet=False):
"""Initializes image encoder based on ResNet :param dim: length of the UniVSE space embeddings :param train_resnet: sets bac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomResNet152:
"""Image encoder that computes both its image embedding and its convolutional feature map"""
def __init__(self, dim=1024, train_resnet=False):
"""Initializes image encoder based on ResNet :param dim: length of the UniVSE space embeddings :param train_resnet: sets backbone's weigh... | the_stack_v2_python_sparse | models/univse/model.py | strategist922/UniVSE | train | 0 |
af9816297dd3a3ca58c1e068123a39d3cc83fda7 | [
"self.turns = turns\nself.length = length\nself.radius = diameter / 2.0\nself.current = current\nself.use_biot_savart = use_biot_savart",
"phi = np.linspace(0, 2 * np.pi * self.turns, 10000)\nsPhi = np.sin(phi)\ncPhi = np.cos(phi)\nlx = self.radius * sPhi\nly = self.radius * cPhi\nlz = self.length / 2 * (phi / (n... | <|body_start_0|>
self.turns = turns
self.length = length
self.radius = diameter / 2.0
self.current = current
self.use_biot_savart = use_biot_savart
<|end_body_0|>
<|body_start_1|>
phi = np.linspace(0, 2 * np.pi * self.turns, 10000)
sPhi = np.sin(phi)
cPhi... | A coil parametrized by number of turns, length, diameter and current. You can calculate the magnetic field cause by the coil at any point in space. | Coil | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Coil:
"""A coil parametrized by number of turns, length, diameter and current. You can calculate the magnetic field cause by the coil at any point in space."""
def __init__(self, turns, length, diameter, current, use_biot_savart=False):
"""Generates a coil objsect. Parameters: * turn... | stack_v2_sparse_classes_36k_train_025606 | 2,858 | permissive | [
{
"docstring": "Generates a coil objsect. Parameters: * turns: int * length: float * diameter: float * current: float",
"name": "__init__",
"signature": "def __init__(self, turns, length, diameter, current, use_biot_savart=False)"
},
{
"docstring": "The magnetic field of the coil Assume Biot-Sav... | 3 | stack_v2_sparse_classes_30k_train_018469 | Implement the Python class `Coil` described below.
Class description:
A coil parametrized by number of turns, length, diameter and current. You can calculate the magnetic field cause by the coil at any point in space.
Method signatures and docstrings:
- def __init__(self, turns, length, diameter, current, use_biot_sa... | Implement the Python class `Coil` described below.
Class description:
A coil parametrized by number of turns, length, diameter and current. You can calculate the magnetic field cause by the coil at any point in space.
Method signatures and docstrings:
- def __init__(self, turns, length, diameter, current, use_biot_sa... | 40fe7f0892a5f4600d863658f748906bff050b67 | <|skeleton|>
class Coil:
"""A coil parametrized by number of turns, length, diameter and current. You can calculate the magnetic field cause by the coil at any point in space."""
def __init__(self, turns, length, diameter, current, use_biot_savart=False):
"""Generates a coil objsect. Parameters: * turn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Coil:
"""A coil parametrized by number of turns, length, diameter and current. You can calculate the magnetic field cause by the coil at any point in space."""
def __init__(self, turns, length, diameter, current, use_biot_savart=False):
"""Generates a coil objsect. Parameters: * turns: int * leng... | the_stack_v2_python_sparse | FreeInductionDecay/simulation/coil.py | renereimann/FID_Simulation | train | 0 |
ecc393ae1bed5f81482a5b70b2ab9ba42f2d07f0 | [
"x1 = u[0]\nx2 = u[1]\ndfdu = np.array([[0, 1], [-2 * self.params.mu * x1 * x2 - 1, self.params.mu * (1 - x1 ** 2)]])\nreturn dfdu",
"me = self.dtype_u(2)\nme[:] = spsolve(sp.eye(2) - factor * dfdu, rhs)\nreturn me"
] | <|body_start_0|>
x1 = u[0]
x2 = u[1]
dfdu = np.array([[0, 1], [-2 * self.params.mu * x1 * x2 - 1, self.params.mu * (1 - x1 ** 2)]])
return dfdu
<|end_body_0|>
<|body_start_1|>
me = self.dtype_u(2)
me[:] = spsolve(sp.eye(2) - factor * dfdu, rhs)
return me
<|end_bo... | vanderpol_jac | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class vanderpol_jac:
def eval_jacobian(self, u):
"""Evaluation of the Jacobian of the right-hand side Args: u: space values Returns: Jacobian matrix"""
<|body_0|>
def solve_system_jacobian(self, dfdu, rhs, factor, u0, t):
"""Simple linear solver for (I-dtA)u = rhs Args: df... | stack_v2_sparse_classes_36k_train_025607 | 1,228 | permissive | [
{
"docstring": "Evaluation of the Jacobian of the right-hand side Args: u: space values Returns: Jacobian matrix",
"name": "eval_jacobian",
"signature": "def eval_jacobian(self, u)"
},
{
"docstring": "Simple linear solver for (I-dtA)u = rhs Args: dfdu: the Jacobian of the RHS of the ODE rhs: rig... | 2 | stack_v2_sparse_classes_30k_train_012194 | Implement the Python class `vanderpol_jac` described below.
Class description:
Implement the vanderpol_jac class.
Method signatures and docstrings:
- def eval_jacobian(self, u): Evaluation of the Jacobian of the right-hand side Args: u: space values Returns: Jacobian matrix
- def solve_system_jacobian(self, dfdu, rhs... | Implement the Python class `vanderpol_jac` described below.
Class description:
Implement the vanderpol_jac class.
Method signatures and docstrings:
- def eval_jacobian(self, u): Evaluation of the Jacobian of the right-hand side Args: u: space values Returns: Jacobian matrix
- def solve_system_jacobian(self, dfdu, rhs... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class vanderpol_jac:
def eval_jacobian(self, u):
"""Evaluation of the Jacobian of the right-hand side Args: u: space values Returns: Jacobian matrix"""
<|body_0|>
def solve_system_jacobian(self, dfdu, rhs, factor, u0, t):
"""Simple linear solver for (I-dtA)u = rhs Args: df... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class vanderpol_jac:
def eval_jacobian(self, u):
"""Evaluation of the Jacobian of the right-hand side Args: u: space values Returns: Jacobian matrix"""
x1 = u[0]
x2 = u[1]
dfdu = np.array([[0, 1], [-2 * self.params.mu * x1 * x2 - 1, self.params.mu * (1 - x1 ** 2)]])
return df... | the_stack_v2_python_sparse | pySDC/projects/parallelSDC/Van_der_Pol_implicit_Jac.py | Parallel-in-Time/pySDC | train | 30 | |
19288c71780eeb1c96984cfd00fca7a05bbf909d | [
"self.name = None\nself.explanation = None\nself.detect = self.remove = self.avoid = None\nself.numdice = self.diesize = None\nself.extrainfo = None",
"type = random.randint(1, 100)\nif type <= 11:\n return ExplosiveTrap(level)\nelif type <= 30:\n return MissileTrap(level)\nelif type <= 45:\n return GasT... | <|body_start_0|>
self.name = None
self.explanation = None
self.detect = self.remove = self.avoid = None
self.numdice = self.diesize = None
self.extrainfo = None
<|end_body_0|>
<|body_start_1|>
type = random.randint(1, 100)
if type <= 11:
return Explos... | Abstract class used to define common code for all potential Traps. | Trap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trap:
"""Abstract class used to define common code for all potential Traps."""
def __init__(self):
"""Initialize all common values to None."""
<|body_0|>
def newtrap(level):
"""Class method: generate and return a new Trap of random type."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_025608 | 14,223 | no_license | [
{
"docstring": "Initialize all common values to None.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Class method: generate and return a new Trap of random type.",
"name": "newtrap",
"signature": "def newtrap(level)"
},
{
"docstring": "Return a descrip... | 3 | stack_v2_sparse_classes_30k_test_000516 | Implement the Python class `Trap` described below.
Class description:
Abstract class used to define common code for all potential Traps.
Method signatures and docstrings:
- def __init__(self): Initialize all common values to None.
- def newtrap(level): Class method: generate and return a new Trap of random type.
- de... | Implement the Python class `Trap` described below.
Class description:
Abstract class used to define common code for all potential Traps.
Method signatures and docstrings:
- def __init__(self): Initialize all common values to None.
- def newtrap(level): Class method: generate and return a new Trap of random type.
- de... | 32583de92c11c7008db6095ebc25b4e5edf8e0f9 | <|skeleton|>
class Trap:
"""Abstract class used to define common code for all potential Traps."""
def __init__(self):
"""Initialize all common values to None."""
<|body_0|>
def newtrap(level):
"""Class method: generate and return a new Trap of random type."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trap:
"""Abstract class used to define common code for all potential Traps."""
def __init__(self):
"""Initialize all common values to None."""
self.name = None
self.explanation = None
self.detect = self.remove = self.avoid = None
self.numdice = self.diesize = None
... | the_stack_v2_python_sparse | elvenfire/labyrinth/traps.py | elven-fire/elvenfire | train | 0 |
b856f7747b21d720bd74a737b9d136c9062871ca | [
"assert fanouts, 'fanouts must be specified'\nconfig = dict(fanouts=fanouts)\nconfig.update(kwargs)\nsuper().__init__(config=config)\nself.fanouts = fanouts\nself.fanouts_list = get_fanouts_list(fanouts)",
"fans = {}\nif 'ids' in inputs:\n fans['ids'] = torch.split(inputs['ids'], self.fanouts_list, dim=-1)\nif... | <|body_start_0|>
assert fanouts, 'fanouts must be specified'
config = dict(fanouts=fanouts)
config.update(kwargs)
super().__init__(config=config)
self.fanouts = fanouts
self.fanouts_list = get_fanouts_list(fanouts)
<|end_body_0|>
<|body_start_1|>
fans = {}
... | \\brief transform to convert bipartites \\details a bipartite is a dict: \\code{.py} dict( src=tensor, dst=tensor, src_feature=tensor, dst_feature=tensor, edge_weight=tensor, ) \\endcode \\par examples \\code{.py} >>> from galileo.pytorch import BipartiteTransform >>> bt = BipartiteTransform([2,3]) >>> res = bt.transfo... | BipartiteTransform | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BipartiteTransform:
"""\\brief transform to convert bipartites \\details a bipartite is a dict: \\code{.py} dict( src=tensor, dst=tensor, src_feature=tensor, dst_feature=tensor, edge_weight=tensor, ) \\endcode \\par examples \\code{.py} >>> from galileo.pytorch import BipartiteTransform >>> bt = ... | stack_v2_sparse_classes_36k_train_025609 | 4,264 | permissive | [
{
"docstring": "\\\\param fanouts number of multi hop",
"name": "__init__",
"signature": "def __init__(self, fanouts: list, **kwargs)"
},
{
"docstring": "\\\\param inputs dict(ids=tensor,feature=tensor,edge_weight=tensor) \\\\return list of bipartite\\\\n items in bipartites are arranged in the ... | 2 | null | Implement the Python class `BipartiteTransform` described below.
Class description:
\\brief transform to convert bipartites \\details a bipartite is a dict: \\code{.py} dict( src=tensor, dst=tensor, src_feature=tensor, dst_feature=tensor, edge_weight=tensor, ) \\endcode \\par examples \\code{.py} >>> from galileo.pyto... | Implement the Python class `BipartiteTransform` described below.
Class description:
\\brief transform to convert bipartites \\details a bipartite is a dict: \\code{.py} dict( src=tensor, dst=tensor, src_feature=tensor, dst_feature=tensor, edge_weight=tensor, ) \\endcode \\par examples \\code{.py} >>> from galileo.pyto... | 48099ec3f0331196c6812208ceb080ba618a588b | <|skeleton|>
class BipartiteTransform:
"""\\brief transform to convert bipartites \\details a bipartite is a dict: \\code{.py} dict( src=tensor, dst=tensor, src_feature=tensor, dst_feature=tensor, edge_weight=tensor, ) \\endcode \\par examples \\code{.py} >>> from galileo.pytorch import BipartiteTransform >>> bt = ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BipartiteTransform:
"""\\brief transform to convert bipartites \\details a bipartite is a dict: \\code{.py} dict( src=tensor, dst=tensor, src_feature=tensor, dst_feature=tensor, edge_weight=tensor, ) \\endcode \\par examples \\code{.py} >>> from galileo.pytorch import BipartiteTransform >>> bt = BipartiteTran... | the_stack_v2_python_sparse | galileo/framework/pytorch/python/transforms/bipartite.py | 2012fang1/galileo | train | 0 |
80d4c817b15a509f9577ee94fdc236477bf53318 | [
"if title is not None:\n try:\n manager = plt.get_current_fig_manager()\n manager.window.title(title)\n except:\n pass",
"plt.show._needmain = False\nif p.filename is not None:\n fullname = p.filename + p.filename_suffix + str(topo.sim.time()) + '.' + p.file_format\n plt.savefig(n... | <|body_start_0|>
if title is not None:
try:
manager = plt.get_current_fig_manager()
manager.window.title(title)
except:
pass
<|end_body_0|>
<|body_start_1|>
plt.show._needmain = False
if p.filename is not None:
... | Parameterized command for plotting using Matplotlib/Pylab. | PylabPlotCommand | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PylabPlotCommand:
"""Parameterized command for plotting using Matplotlib/Pylab."""
def _set_windowtitle(self, title):
"""Helper function to set the title (if not None) of this PyLab plot window."""
<|body_0|>
def _generate_figure(self, p):
"""Helper function to d... | stack_v2_sparse_classes_36k_train_025610 | 26,497 | permissive | [
{
"docstring": "Helper function to set the title (if not None) of this PyLab plot window.",
"name": "_set_windowtitle",
"signature": "def _set_windowtitle(self, title)"
},
{
"docstring": "Helper function to display a figure on screen or save to a file. p should be a ParamOverrides instance conta... | 2 | stack_v2_sparse_classes_30k_train_021154 | Implement the Python class `PylabPlotCommand` described below.
Class description:
Parameterized command for plotting using Matplotlib/Pylab.
Method signatures and docstrings:
- def _set_windowtitle(self, title): Helper function to set the title (if not None) of this PyLab plot window.
- def _generate_figure(self, p):... | Implement the Python class `PylabPlotCommand` described below.
Class description:
Parameterized command for plotting using Matplotlib/Pylab.
Method signatures and docstrings:
- def _set_windowtitle(self, title): Helper function to set the title (if not None) of this PyLab plot window.
- def _generate_figure(self, p):... | 1e097e2df9938a6ce9f48cefbf25672cbbf9a4db | <|skeleton|>
class PylabPlotCommand:
"""Parameterized command for plotting using Matplotlib/Pylab."""
def _set_windowtitle(self, title):
"""Helper function to set the title (if not None) of this PyLab plot window."""
<|body_0|>
def _generate_figure(self, p):
"""Helper function to d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PylabPlotCommand:
"""Parameterized command for plotting using Matplotlib/Pylab."""
def _set_windowtitle(self, title):
"""Helper function to set the title (if not None) of this PyLab plot window."""
if title is not None:
try:
manager = plt.get_current_fig_manage... | the_stack_v2_python_sparse | topo/command/pylabplot.py | ioam/topographica | train | 43 |
e66098fb2b562982364cec65e504aacad82e3ffe | [
"test_node = java_group.JavaGroup(self.TEST_GRP_1)\nself.assertEqual(test_node.name, self.TEST_GRP_1)\nself.assertEqual(test_node.classes, {})",
"test_node = java_group.JavaGroup(self.TEST_GRP_1)\nmock_class_node = create_mock_java_class()\ntest_node.add_class(mock_class_node)\nself.assertEqual(test_node.classes,... | <|body_start_0|>
test_node = java_group.JavaGroup(self.TEST_GRP_1)
self.assertEqual(test_node.name, self.TEST_GRP_1)
self.assertEqual(test_node.classes, {})
<|end_body_0|>
<|body_start_1|>
test_node = java_group.JavaGroup(self.TEST_GRP_1)
mock_class_node = create_mock_java_class... | Unit tests for dependency_analysis.class_dependency.JavaGroup. | TestJavaPackage | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestJavaPackage:
"""Unit tests for dependency_analysis.class_dependency.JavaGroup."""
def test_initialization(self):
"""Tests that JavaGroup is initialized correctly."""
<|body_0|>
def test_add_class(self):
"""Tests adding a single class to this group."""
... | stack_v2_sparse_classes_36k_train_025611 | 4,390 | permissive | [
{
"docstring": "Tests that JavaGroup is initialized correctly.",
"name": "test_initialization",
"signature": "def test_initialization(self)"
},
{
"docstring": "Tests adding a single class to this group.",
"name": "test_add_class",
"signature": "def test_add_class(self)"
},
{
"doc... | 6 | stack_v2_sparse_classes_30k_val_001143 | Implement the Python class `TestJavaPackage` described below.
Class description:
Unit tests for dependency_analysis.class_dependency.JavaGroup.
Method signatures and docstrings:
- def test_initialization(self): Tests that JavaGroup is initialized correctly.
- def test_add_class(self): Tests adding a single class to t... | Implement the Python class `TestJavaPackage` described below.
Class description:
Unit tests for dependency_analysis.class_dependency.JavaGroup.
Method signatures and docstrings:
- def test_initialization(self): Tests that JavaGroup is initialized correctly.
- def test_add_class(self): Tests adding a single class to t... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class TestJavaPackage:
"""Unit tests for dependency_analysis.class_dependency.JavaGroup."""
def test_initialization(self):
"""Tests that JavaGroup is initialized correctly."""
<|body_0|>
def test_add_class(self):
"""Tests adding a single class to this group."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestJavaPackage:
"""Unit tests for dependency_analysis.class_dependency.JavaGroup."""
def test_initialization(self):
"""Tests that JavaGroup is initialized correctly."""
test_node = java_group.JavaGroup(self.TEST_GRP_1)
self.assertEqual(test_node.name, self.TEST_GRP_1)
sel... | the_stack_v2_python_sparse | tools/android/dependency_analysis/java_group_unittest.py | chromium/chromium | train | 17,408 |
b60a6a5ee1df3d8df5d337fc02020953eb5bed6a | [
"super().__init__()\nlayers = []\ndilation = 1\nfirst_causal = CausalCNNLayer(in_channels, out_channels=hidden_out_channels, kernel_size=kernel_size, dilation=dilation, layer='first', up_or_down_sample=True)\nlayers += [first_causal]\nfor i in range(n_layers - 2):\n dilation *= 2\n layers += [CausalCNNLayer(i... | <|body_start_0|>
super().__init__()
layers = []
dilation = 1
first_causal = CausalCNNLayer(in_channels, out_channels=hidden_out_channels, kernel_size=kernel_size, dilation=dilation, layer='first', up_or_down_sample=True)
layers += [first_causal]
for i in range(n_layers - ... | Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
def __init__(self, n_layers, hidden_out_channels, kernel_size, last_out_channels, rep_length, in_channels=1):
"""The encoder architecture as proposed in Fig. 2 of the paper. :param n_layers: number of causal convolutional layers :param hidden_out_channels: output/input channels ... | stack_v2_sparse_classes_36k_train_025612 | 8,666 | no_license | [
{
"docstring": "The encoder architecture as proposed in Fig. 2 of the paper. :param n_layers: number of causal convolutional layers :param hidden_out_channels: output/input channels of the hidden causal layers :param kernel_size: kernel size of each convolution :param last_out_channels: output channels size of ... | 2 | stack_v2_sparse_classes_30k_train_020746 | Implement the Python class `Encoder` described below.
Class description:
Implement the Encoder class.
Method signatures and docstrings:
- def __init__(self, n_layers, hidden_out_channels, kernel_size, last_out_channels, rep_length, in_channels=1): The encoder architecture as proposed in Fig. 2 of the paper. :param n_... | Implement the Python class `Encoder` described below.
Class description:
Implement the Encoder class.
Method signatures and docstrings:
- def __init__(self, n_layers, hidden_out_channels, kernel_size, last_out_channels, rep_length, in_channels=1): The encoder architecture as proposed in Fig. 2 of the paper. :param n_... | 84b9ac79439657c04033cadb51c6145ad7e2f4b3 | <|skeleton|>
class Encoder:
def __init__(self, n_layers, hidden_out_channels, kernel_size, last_out_channels, rep_length, in_channels=1):
"""The encoder architecture as proposed in Fig. 2 of the paper. :param n_layers: number of causal convolutional layers :param hidden_out_channels: output/input channels ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
def __init__(self, n_layers, hidden_out_channels, kernel_size, last_out_channels, rep_length, in_channels=1):
"""The encoder architecture as proposed in Fig. 2 of the paper. :param n_layers: number of causal convolutional layers :param hidden_out_channels: output/input channels of the hidden ... | the_stack_v2_python_sparse | src/encoder.py | lhvu2/reproducibility_NeurIPS19 | train | 0 | |
78a01a7de1097deaa87c2b54306a0366133ebe55 | [
"self.variables = tf.trainable_variables()\nself.input_pl = tf.placeholder(tf.float32, [None, observation_space], name='Input_PL')\nnet = tf.layers.dense(self.input_pl, 100, activation=tf.nn.tanh, kernel_initializer=tf.random_normal_initializer(stddev=0.1))\nnet = tf.layers.dense(net, 100, activation=tf.nn.tanh, ke... | <|body_start_0|>
self.variables = tf.trainable_variables()
self.input_pl = tf.placeholder(tf.float32, [None, observation_space], name='Input_PL')
net = tf.layers.dense(self.input_pl, 100, activation=tf.nn.tanh, kernel_initializer=tf.random_normal_initializer(stddev=0.1))
net = tf.layers.... | Network | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Network:
def inference_value(self, observation_space):
"""Creates a neural-network value function approximator Args: observation_space: observation space of the environment Returns: Nothing, the network is usable only after calling this method"""
<|body_0|>
def inference_pol... | stack_v2_sparse_classes_36k_train_025613 | 2,684 | no_license | [
{
"docstring": "Creates a neural-network value function approximator Args: observation_space: observation space of the environment Returns: Nothing, the network is usable only after calling this method",
"name": "inference_value",
"signature": "def inference_value(self, observation_space)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_008827 | Implement the Python class `Network` described below.
Class description:
Implement the Network class.
Method signatures and docstrings:
- def inference_value(self, observation_space): Creates a neural-network value function approximator Args: observation_space: observation space of the environment Returns: Nothing, t... | Implement the Python class `Network` described below.
Class description:
Implement the Network class.
Method signatures and docstrings:
- def inference_value(self, observation_space): Creates a neural-network value function approximator Args: observation_space: observation space of the environment Returns: Nothing, t... | 372469a84226f339b3a1b13bdd76c7b15db54093 | <|skeleton|>
class Network:
def inference_value(self, observation_space):
"""Creates a neural-network value function approximator Args: observation_space: observation space of the environment Returns: Nothing, the network is usable only after calling this method"""
<|body_0|>
def inference_pol... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Network:
def inference_value(self, observation_space):
"""Creates a neural-network value function approximator Args: observation_space: observation space of the environment Returns: Nothing, the network is usable only after calling this method"""
self.variables = tf.trainable_variables()
... | the_stack_v2_python_sparse | PPO/scripts/neural_net.py | jonrosner/ReinforcementLearning | train | 3 | |
7ec2ba9610b0c5e517be0370da7b8c28c46077a6 | [
"self.max_batch_size = max_batch_size\nself.max_seq_length = max_seq_length\nself.device = device\nself.distribution_cls = Categorical if distribution_cls is None else distribution_cls",
"number_batches = (num_samples + self.max_batch_size - 1) // self.max_batch_size\nremaining_samples = num_samples\nactions = to... | <|body_start_0|>
self.max_batch_size = max_batch_size
self.max_seq_length = max_seq_length
self.device = device
self.distribution_cls = Categorical if distribution_cls is None else distribution_cls
<|end_body_0|>
<|body_start_1|>
number_batches = (num_samples + self.max_batch_si... | Sampler for a SmilesRNN models. Does not return SMILES strings directly, but instead the actions (i.e. which SMILES character to select). Those values are more general and are for instance necessary for other RL algorithms. The class will sample the RNN model multiple times if the number of desired samples is larger th... | ActionSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionSampler:
"""Sampler for a SmilesRNN models. Does not return SMILES strings directly, but instead the actions (i.e. which SMILES character to select). Those values are more general and are for instance necessary for other RL algorithms. The class will sample the RNN model multiple times if t... | stack_v2_sparse_classes_36k_train_025614 | 3,326 | permissive | [
{
"docstring": "Args: max_batch_size: maximal batch size for the RNN model max_seq_length: max length for a sampled SMILES string device: cuda | cpu distribution_cls: distribution type to sample from. If None, will be a multinomial distribution. Useful for testing purposes.",
"name": "__init__",
"signat... | 3 | stack_v2_sparse_classes_30k_test_001114 | Implement the Python class `ActionSampler` described below.
Class description:
Sampler for a SmilesRNN models. Does not return SMILES strings directly, but instead the actions (i.e. which SMILES character to select). Those values are more general and are for instance necessary for other RL algorithms. The class will s... | Implement the Python class `ActionSampler` described below.
Class description:
Sampler for a SmilesRNN models. Does not return SMILES strings directly, but instead the actions (i.e. which SMILES character to select). Those values are more general and are for instance necessary for other RL algorithms. The class will s... | 44d24c53f3acf9266eb2fb06dbff909836549291 | <|skeleton|>
class ActionSampler:
"""Sampler for a SmilesRNN models. Does not return SMILES strings directly, but instead the actions (i.e. which SMILES character to select). Those values are more general and are for instance necessary for other RL algorithms. The class will sample the RNN model multiple times if t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActionSampler:
"""Sampler for a SmilesRNN models. Does not return SMILES strings directly, but instead the actions (i.e. which SMILES character to select). Those values are more general and are for instance necessary for other RL algorithms. The class will sample the RNN model multiple times if the number of ... | the_stack_v2_python_sparse | smiles_lstm_hc/action_sampler.py | BenevolentAI/guacamol_baselines | train | 108 |
c12e21e4857541b39113fe70d8605e3fe6c26398 | [
"self.ssm = ssm\nself.shoulder_anchor = shoulder_anchor\nself.kin_chain = kin_chain\nif 0:\n goal_cache_block = kwargs.pop('goal_cache_block')\n self.cached_data = pickle.load(open('/storage/assist_params/tentacle_cache_%d.pkl' % goal_cache_block))\nelse:\n self.cached_data = pickle.load(open('/storage/ass... | <|body_start_0|>
self.ssm = ssm
self.shoulder_anchor = shoulder_anchor
self.kin_chain = kin_chain
if 0:
goal_cache_block = kwargs.pop('goal_cache_block')
self.cached_data = pickle.load(open('/storage/assist_params/tentacle_cache_%d.pkl' % goal_cache_block))
... | Determine the goal state of a redundant system by look-up-table, i.e. redundancy is collapsed by arbitrary mapping between redudnant target space and configuration space TODO: since multiprocessing is not required for this class, it needs to do a better job of hiding the multiprocessing. | PlanarMultiLinkJointGoalCached | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlanarMultiLinkJointGoalCached:
"""Determine the goal state of a redundant system by look-up-table, i.e. redundancy is collapsed by arbitrary mapping between redudnant target space and configuration space TODO: since multiprocessing is not required for this class, it needs to do a better job of h... | stack_v2_sparse_classes_36k_train_025615 | 13,329 | permissive | [
{
"docstring": "Constructor for PlanarMultiLinkJointGoalCached Parameters ---------- ssm : state_space_models.StateSpace instance shoulder_anchor : np.ndarray of shape (3,) Position of the manipulator anchor kin_chain : robot_arms.KinematicChain instance Object representing the kinematic chain linkages (D-H par... | 2 | null | Implement the Python class `PlanarMultiLinkJointGoalCached` described below.
Class description:
Determine the goal state of a redundant system by look-up-table, i.e. redundancy is collapsed by arbitrary mapping between redudnant target space and configuration space TODO: since multiprocessing is not required for this ... | Implement the Python class `PlanarMultiLinkJointGoalCached` described below.
Class description:
Determine the goal state of a redundant system by look-up-table, i.e. redundancy is collapsed by arbitrary mapping between redudnant target space and configuration space TODO: since multiprocessing is not required for this ... | a0e296aa663b49e767c9ebb274defb54b301eb12 | <|skeleton|>
class PlanarMultiLinkJointGoalCached:
"""Determine the goal state of a redundant system by look-up-table, i.e. redundancy is collapsed by arbitrary mapping between redudnant target space and configuration space TODO: since multiprocessing is not required for this class, it needs to do a better job of h... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlanarMultiLinkJointGoalCached:
"""Determine the goal state of a redundant system by look-up-table, i.e. redundancy is collapsed by arbitrary mapping between redudnant target space and configuration space TODO: since multiprocessing is not required for this class, it needs to do a better job of hiding the mul... | the_stack_v2_python_sparse | riglib/bmi/goal_calculators.py | carmenalab/brain-python-interface | train | 9 |
2481c6e91a9ed020ba39e63a3921e3875236f751 | [
"count = 0\nfor i in range(1, len(nums)):\n if nums[i] < nums[i - 1]:\n count += 1\n if i + 1 < len(nums) and i - 2 >= 0:\n if nums[i + 1] < nums[i - 1] and nums[i - 2] > nums[i]:\n return False\n if count > 1:\n return False\nreturn True",
"cnt = 0\nfor i in r... | <|body_start_0|>
count = 0
for i in range(1, len(nums)):
if nums[i] < nums[i - 1]:
count += 1
if i + 1 < len(nums) and i - 2 >= 0:
if nums[i + 1] < nums[i - 1] and nums[i - 2] > nums[i]:
return False
if c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtyp... | stack_v2_sparse_classes_36k_train_025616 | 1,452 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "checkPossibility",
"signature": "def checkPossibility(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "checkPossibility",
"signature": "def checkPossibility(self, nums)"
},
{
"docstring": "... | 3 | stack_v2_sparse_classes_30k_train_002312 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :t... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtyp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
count = 0
for i in range(1, len(nums)):
if nums[i] < nums[i - 1]:
count += 1
if i + 1 < len(nums) and i - 2 >= 0:
if nums[i + 1] < nums[i... | the_stack_v2_python_sparse | 0665_Non-decreasing_Array.py | bingli8802/leetcode | train | 0 | |
77e016971c8c69db2c7ba79b403544d6b42e4be2 | [
"if not all([start_line.is_init, end_line.is_init]):\n return (-1, datetime.timedelta(0))\nif start_line.type != cls.__DIALOGUE or end_line.type != cls.__DIALOGUE:\n return (-1, datetime.timedelta(0))\nlines_duration = datetime.datetime.combine(datetime.datetime.today(), end_line.start_time) - datetime.dateti... | <|body_start_0|>
if not all([start_line.is_init, end_line.is_init]):
return (-1, datetime.timedelta(0))
if start_line.type != cls.__DIALOGUE or end_line.type != cls.__DIALOGUE:
return (-1, datetime.timedelta(0))
lines_duration = datetime.datetime.combine(datetime.datetime... | AssScriptLineTool | [
"Python-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssScriptLineTool:
def check_continuous(cls, start_line: AssScriptLine, end_line: AssScriptLine, style_mode: bool) -> Tuple[int, datetime.timedelta]:
"""判断该行两行是否是连轴(即前轴结束时间等于后轴开始时间) :param start_line: 前轴 :param end_line: 后轴 :param style_mode: 是否启用样式判断 True: 两行样式不同不进行比较, 直接返回0 False: 两行样式... | stack_v2_sparse_classes_36k_train_025617 | 27,833 | permissive | [
{
"docstring": "判断该行两行是否是连轴(即前轴结束时间等于后轴开始时间) :param start_line: 前轴 :param end_line: 后轴 :param style_mode: 是否启用样式判断 True: 两行样式不同不进行比较, 直接返回0 False: 两行样式不同也会进行比较 :return: [判断结果, 轴间时间差] 1: 连轴 0: 非连轴 -1: 错误",
"name": "check_continuous",
"signature": "def check_continuous(cls, start_line: AssScriptLine, end_... | 3 | stack_v2_sparse_classes_30k_train_006676 | Implement the Python class `AssScriptLineTool` described below.
Class description:
Implement the AssScriptLineTool class.
Method signatures and docstrings:
- def check_continuous(cls, start_line: AssScriptLine, end_line: AssScriptLine, style_mode: bool) -> Tuple[int, datetime.timedelta]: 判断该行两行是否是连轴(即前轴结束时间等于后轴开始时间) ... | Implement the Python class `AssScriptLineTool` described below.
Class description:
Implement the AssScriptLineTool class.
Method signatures and docstrings:
- def check_continuous(cls, start_line: AssScriptLine, end_line: AssScriptLine, style_mode: bool) -> Tuple[int, datetime.timedelta]: 判断该行两行是否是连轴(即前轴结束时间等于后轴开始时间) ... | 53a6683fccb0618e306abe9e103cec78445f3796 | <|skeleton|>
class AssScriptLineTool:
def check_continuous(cls, start_line: AssScriptLine, end_line: AssScriptLine, style_mode: bool) -> Tuple[int, datetime.timedelta]:
"""判断该行两行是否是连轴(即前轴结束时间等于后轴开始时间) :param start_line: 前轴 :param end_line: 后轴 :param style_mode: 是否启用样式判断 True: 两行样式不同不进行比较, 直接返回0 False: 两行样式... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssScriptLineTool:
def check_continuous(cls, start_line: AssScriptLine, end_line: AssScriptLine, style_mode: bool) -> Tuple[int, datetime.timedelta]:
"""判断该行两行是否是连轴(即前轴结束时间等于后轴开始时间) :param start_line: 前轴 :param end_line: 后轴 :param style_mode: 是否启用样式判断 True: 两行样式不同不进行比较, 直接返回0 False: 两行样式不同也会进行比较 :retu... | the_stack_v2_python_sparse | omega_miya/plugins/zhoushen_hime/utils.py | yekang-wu/omega-miya | train | 0 | |
275740dfb7a544d777b30ce37861a05a5218ae9c | [
"from pyraf import iraf\nfrom iraf import stsdas, analysis, dither\niraf.unlearn('blot')",
"from pyraf import iraf\nfrom iraf import stsdas, analysis, dither\niraf.blot(data=in_data, outdata=out_data, scale=drizzle_params['PSCALE'], coeffs=coeffs, outnx=out_nx, outny=out_ny, interpol=mult_drizzle_par['blot_interp... | <|body_start_0|>
from pyraf import iraf
from iraf import stsdas, analysis, dither
iraf.unlearn('blot')
<|end_body_0|>
<|body_start_1|>
from pyraf import iraf
from iraf import stsdas, analysis, dither
iraf.blot(data=in_data, outdata=out_data, scale=drizzle_params['PSCALE'... | Class to wrap the blot command | Blot | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Blot:
"""Class to wrap the blot command"""
def __init__(self):
"""Initializes the class"""
<|body_0|>
def run(self, in_data, out_data, coeffs, out_nx, out_ny, drizzle_params, mult_drizzle_par):
"""Do the actual blot Currently only the iraf version of blot is invo... | stack_v2_sparse_classes_36k_train_025618 | 23,324 | permissive | [
{
"docstring": "Initializes the class",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Do the actual blot Currently only the iraf version of blot is invoked.",
"name": "run",
"signature": "def run(self, in_data, out_data, coeffs, out_nx, out_ny, drizzle_params, ... | 2 | stack_v2_sparse_classes_30k_train_017560 | Implement the Python class `Blot` described below.
Class description:
Class to wrap the blot command
Method signatures and docstrings:
- def __init__(self): Initializes the class
- def run(self, in_data, out_data, coeffs, out_nx, out_ny, drizzle_params, mult_drizzle_par): Do the actual blot Currently only the iraf ve... | Implement the Python class `Blot` described below.
Class description:
Class to wrap the blot command
Method signatures and docstrings:
- def __init__(self): Initializes the class
- def run(self, in_data, out_data, coeffs, out_nx, out_ny, drizzle_params, mult_drizzle_par): Do the actual blot Currently only the iraf ve... | 043c173fd5497c18c2b1bfe8bcff65180bca3996 | <|skeleton|>
class Blot:
"""Class to wrap the blot command"""
def __init__(self):
"""Initializes the class"""
<|body_0|>
def run(self, in_data, out_data, coeffs, out_nx, out_ny, drizzle_params, mult_drizzle_par):
"""Do the actual blot Currently only the iraf version of blot is invo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Blot:
"""Class to wrap the blot command"""
def __init__(self):
"""Initializes the class"""
from pyraf import iraf
from iraf import stsdas, analysis, dither
iraf.unlearn('blot')
def run(self, in_data, out_data, coeffs, out_nx, out_ny, drizzle_params, mult_drizzle_par):... | the_stack_v2_python_sparse | stsdas/pkg/analysis/slitless/axe/axesrc/dither.py | spacetelescope/stsdas_stripped | train | 1 |
2d6016ad74e95bab6ce19e84b71737774b33e54b | [
"self._tracks = config.track_store\nself._albums = config.album_store\nself._artists = config.artist_store\nself._genres = config.genre_store\nself._search = config.search\nself._id_cache = config.id_cache",
"self._tracks.reload()\nself._albums.reload()\nself._artists.reload()\nself._genres.reload()\nself._search... | <|body_start_0|>
self._tracks = config.track_store
self._albums = config.album_store
self._artists = config.artist_store
self._genres = config.genre_store
self._search = config.search
self._id_cache = config.id_cache
<|end_body_0|>
<|body_start_1|>
self._tracks.r... | Methods for querying in-memory stores of audio metadata. | AvalonMetadataService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AvalonMetadataService:
"""Methods for querying in-memory stores of audio metadata."""
def __init__(self, config):
"""Set each of the in-memory stores to be used."""
<|body_0|>
def reload(self):
"""Reload in-memory stores from the database. :return: This object :r... | stack_v2_sparse_classes_36k_train_025619 | 7,085 | permissive | [
{
"docstring": "Set each of the in-memory stores to be used.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Reload in-memory stores from the database. :return: This object :rtype: AvalonApiEndpoints",
"name": "reload",
"signature": "def reload(self)"
... | 6 | stack_v2_sparse_classes_30k_train_004693 | Implement the Python class `AvalonMetadataService` described below.
Class description:
Methods for querying in-memory stores of audio metadata.
Method signatures and docstrings:
- def __init__(self, config): Set each of the in-memory stores to be used.
- def reload(self): Reload in-memory stores from the database. :r... | Implement the Python class `AvalonMetadataService` described below.
Class description:
Methods for querying in-memory stores of audio metadata.
Method signatures and docstrings:
- def __init__(self, config): Set each of the in-memory stores to be used.
- def reload(self): Reload in-memory stores from the database. :r... | 2291f8457ca86f2e963d518abbdce04af02d9054 | <|skeleton|>
class AvalonMetadataService:
"""Methods for querying in-memory stores of audio metadata."""
def __init__(self, config):
"""Set each of the in-memory stores to be used."""
<|body_0|>
def reload(self):
"""Reload in-memory stores from the database. :return: This object :r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AvalonMetadataService:
"""Methods for querying in-memory stores of audio metadata."""
def __init__(self, config):
"""Set each of the in-memory stores to be used."""
self._tracks = config.track_store
self._albums = config.album_store
self._artists = config.artist_store
... | the_stack_v2_python_sparse | avalon/web/services.py | 56quarters/avalonms | train | 0 |
a6c1f1f2f26cce07df3a254f09746128ddd37c65 | [
"self.q = deque([(0, 0)])\nself.food = food[::-1]\nself.w = width\nself.h = height",
"r, c = self.q[-1]\nif direction == 'U':\n nr, nc = (r - 1, c)\nelif direction == 'L':\n nr, nc = (r, c - 1)\nelif direction == 'R':\n nr, nc = (r, c + 1)\nelse:\n nr, nc = (r + 1, c)\nif self.food and [nr, nc] == sel... | <|body_start_0|>
self.q = deque([(0, 0)])
self.food = food[::-1]
self.w = width
self.h = height
<|end_body_0|>
<|body_start_1|>
r, c = self.q[-1]
if direction == 'U':
nr, nc = (r - 1, c)
elif direction == 'L':
nr, nc = (r, c - 1)
e... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k_train_025620 | 1,600 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | 3129438b032d3aeb87c6ac5c4733df0ebc1272ba | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | solu/353. Design Snake Game.py | coolmich/py-leetcode | train | 3 | |
0d95949e900a2914e7da4d36065d6def2de59020 | [
"cache_len = 100000\nself.random_prob_cache = np.random.random(size=(cache_len,))\nself.random_prob_ptr = cache_len - 1",
"value = self.random_prob_cache[self.random_prob_ptr]\nself.random_prob_ptr -= 1\nif self.random_prob_ptr == -1:\n self.reset_random_prob()\nreturn value",
"token = self.token_list[self.t... | <|body_start_0|>
cache_len = 100000
self.random_prob_cache = np.random.random(size=(cache_len,))
self.random_prob_ptr = cache_len - 1
<|end_body_0|>
<|body_start_1|>
value = self.random_prob_cache[self.random_prob_ptr]
self.random_prob_ptr -= 1
if self.random_prob_ptr ==... | A base class that generate multiple random numbers at the same time. | EfficientRandomGen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
<|body_0|>
def get_random_prob(self):
"""Get a random number."""
... | stack_v2_sparse_classes_36k_train_025621 | 14,026 | no_license | [
{
"docstring": "Generate many random numbers at the same time and cache them.",
"name": "reset_random_prob",
"signature": "def reset_random_prob(self)"
},
{
"docstring": "Get a random number.",
"name": "get_random_prob",
"signature": "def get_random_prob(self)"
},
{
"docstring": ... | 3 | stack_v2_sparse_classes_30k_train_013937 | Implement the Python class `EfficientRandomGen` described below.
Class description:
A base class that generate multiple random numbers at the same time.
Method signatures and docstrings:
- def reset_random_prob(self): Generate many random numbers at the same time and cache them.
- def get_random_prob(self): Get a ran... | Implement the Python class `EfficientRandomGen` described below.
Class description:
A base class that generate multiple random numbers at the same time.
Method signatures and docstrings:
- def reset_random_prob(self): Generate many random numbers at the same time and cache them.
- def get_random_prob(self): Get a ran... | 778156466bc06ab1e4ecd1661d8ad8b98023afca | <|skeleton|>
class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
<|body_0|>
def get_random_prob(self):
"""Get a random number."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
cache_len = 100000
self.random_prob_cache = np.random.random(size=(cache_len,))
s... | the_stack_v2_python_sparse | data/gen_uda_dataset.py | mainliufeng/models | train | 0 |
0b7fde72254b169d482aa8028c5740f58cf7cefc | [
"n = len(nums)\npreSum = [0] * (n + 1)\nfor i in range(1, n + 1):\n preSum[i] = preSum[i - 1] + nums[i - 1]\nres = 1\nrmq = RMQ(nums)\nfor i in range(n):\n for j in range(i, n):\n res = max(res, nums[rmq.minRange(i, j)] * (preSum[j + 1] - preSum[i]))\nreturn res",
"n = len(nums)\npreSum = [0] * (n + ... | <|body_start_0|>
n = len(nums)
preSum = [0] * (n + 1)
for i in range(1, n + 1):
preSum[i] = preSum[i - 1] + nums[i - 1]
res = 1
rmq = RMQ(nums)
for i in range(n):
for j in range(i, n):
res = max(res, nums[rmq.minRange(i, j)] * (preS... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSumMinProductTLE(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSumMinProduct(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
preSum = [... | stack_v2_sparse_classes_36k_train_025622 | 3,107 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSumMinProductTLE",
"signature": "def maxSumMinProductTLE(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSumMinProduct",
"signature": "def maxSumMinProduct(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSumMinProductTLE(self, nums): :type nums: List[int] :rtype: int
- def maxSumMinProduct(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 maxSumMinProductTLE(self, nums): :type nums: List[int] :rtype: int
- def maxSumMinProduct(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
de... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def maxSumMinProductTLE(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSumMinProduct(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 maxSumMinProductTLE(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
preSum = [0] * (n + 1)
for i in range(1, n + 1):
preSum[i] = preSum[i - 1] + nums[i - 1]
res = 1
rmq = RMQ(nums)
for i in range(n):
... | the_stack_v2_python_sparse | M/MaximumSubarrayMin-Product.py | bssrdf/pyleet | train | 2 | |
4f814e2b99f75ea2db6556de9f7993f4e938cc3b | [
"self.cpus = []\nself.stats = []\nsuper().__init__('/proc/cpuinfo')\nself.read()",
"for cpu_lines in self.content.split('\\n\\n'):\n if not cpu_lines:\n continue\n self.cpus.append(CpuDetails(cpu_lines))",
"print(' '.join(first_cpu.details['model name'][1:]) + ':')\nprint('\\t' + first_cpu.details[... | <|body_start_0|>
self.cpus = []
self.stats = []
super().__init__('/proc/cpuinfo')
self.read()
<|end_body_0|>
<|body_start_1|>
for cpu_lines in self.content.split('\n\n'):
if not cpu_lines:
continue
self.cpus.append(CpuDetails(cpu_lines))
<... | Object represents the /proc/cpuinfo file. | ProcCpuInfo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcCpuInfo:
"""Object represents the /proc/cpuinfo file."""
def __init__(self):
"""Read file by calling base class constructor then parse the contents."""
<|body_0|>
def read(self):
"""Parses contents of /proc/cpuinfo"""
<|body_1|>
def dump_coalesce... | stack_v2_sparse_classes_36k_train_025623 | 5,579 | permissive | [
{
"docstring": "Read file by calling base class constructor then parse the contents.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Parses contents of /proc/cpuinfo",
"name": "read",
"signature": "def read(self)"
},
{
"docstring": "Print a selected sub... | 4 | stack_v2_sparse_classes_30k_train_008328 | Implement the Python class `ProcCpuInfo` described below.
Class description:
Object represents the /proc/cpuinfo file.
Method signatures and docstrings:
- def __init__(self): Read file by calling base class constructor then parse the contents.
- def read(self): Parses contents of /proc/cpuinfo
- def dump_coalesced(se... | Implement the Python class `ProcCpuInfo` described below.
Class description:
Object represents the /proc/cpuinfo file.
Method signatures and docstrings:
- def __init__(self): Read file by calling base class constructor then parse the contents.
- def read(self): Parses contents of /proc/cpuinfo
- def dump_coalesced(se... | 5fc781852dcdf55c3a807e97692224a28c0913f6 | <|skeleton|>
class ProcCpuInfo:
"""Object represents the /proc/cpuinfo file."""
def __init__(self):
"""Read file by calling base class constructor then parse the contents."""
<|body_0|>
def read(self):
"""Parses contents of /proc/cpuinfo"""
<|body_1|>
def dump_coalesce... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcCpuInfo:
"""Object represents the /proc/cpuinfo file."""
def __init__(self):
"""Read file by calling base class constructor then parse the contents."""
self.cpus = []
self.stats = []
super().__init__('/proc/cpuinfo')
self.read()
def read(self):
"""... | the_stack_v2_python_sparse | proc_scraper/proc_cpuinfo.py | EwanC/pyProc | train | 0 |
5cf53a8bdb3640698c1f305be5e6512b420fe8dd | [
"self.nb = None\nself.pages = {}\nif local:\n self.local = local\n self.local.view = self\nelse:\n self.local = FigureSettingController(parent, self, setting)\nGeneralDialog.__init__(self, parent, title='Figure Setting', style=wx.DEFAULT_DIALOG_STYLE | wx.RESIZE_BORDER, controller=controller, local=self.lo... | <|body_start_0|>
self.nb = None
self.pages = {}
if local:
self.local = local
self.local.view = self
else:
self.local = FigureSettingController(parent, self, setting)
GeneralDialog.__init__(self, parent, title='Figure Setting', style=wx.DEFAULT_... | Modify figure setting. | FigureSettingDialog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FigureSettingDialog:
"""Modify figure setting."""
def __init__(self, parent, controller=None, setting=None, local=None, btn_flags=wx.OK | wx.CANCEL, **kwargs):
"""Figure setting dialog. :param parent: :param controller: :param setting: :param btn_flags: :param kwargs: :return:"""
... | stack_v2_sparse_classes_36k_train_025624 | 8,601 | no_license | [
{
"docstring": "Figure setting dialog. :param parent: :param controller: :param setting: :param btn_flags: :param kwargs: :return:",
"name": "__init__",
"signature": "def __init__(self, parent, controller=None, setting=None, local=None, btn_flags=wx.OK | wx.CANCEL, **kwargs)"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_002728 | Implement the Python class `FigureSettingDialog` described below.
Class description:
Modify figure setting.
Method signatures and docstrings:
- def __init__(self, parent, controller=None, setting=None, local=None, btn_flags=wx.OK | wx.CANCEL, **kwargs): Figure setting dialog. :param parent: :param controller: :param ... | Implement the Python class `FigureSettingDialog` described below.
Class description:
Modify figure setting.
Method signatures and docstrings:
- def __init__(self, parent, controller=None, setting=None, local=None, btn_flags=wx.OK | wx.CANCEL, **kwargs): Figure setting dialog. :param parent: :param controller: :param ... | e78511f30935b006385b571472487bb081aa36d8 | <|skeleton|>
class FigureSettingDialog:
"""Modify figure setting."""
def __init__(self, parent, controller=None, setting=None, local=None, btn_flags=wx.OK | wx.CANCEL, **kwargs):
"""Figure setting dialog. :param parent: :param controller: :param setting: :param btn_flags: :param kwargs: :return:"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FigureSettingDialog:
"""Modify figure setting."""
def __init__(self, parent, controller=None, setting=None, local=None, btn_flags=wx.OK | wx.CANCEL, **kwargs):
"""Figure setting dialog. :param parent: :param controller: :param setting: :param btn_flags: :param kwargs: :return:"""
self.nb ... | the_stack_v2_python_sparse | boaui/chart/dlg.py | JoenyBui/boa-gui | train | 0 |
35eb14f18f7d14b130427e4c9492aa8f7a77a4b4 | [
"super().__init__(self._jv, nf=1, nx=1, maxderiv=None, zlevel=None)\nself.v = v\nreturn",
"nd, nvar = dfun.ndnvar(deriv, var, self.nx)\nif out is None:\n base_shape = X.shape[1:]\n out = np.ndarray((nd, self.nf) + base_shape, dtype=X.dtype)\nx = X[0]\nkfact = 1.0\nfor k in range(nd):\n dk = scipy.special... | <|body_start_0|>
super().__init__(self._jv, nf=1, nx=1, maxderiv=None, zlevel=None)
self.v = v
return
<|end_body_0|>
<|body_start_1|>
nd, nvar = dfun.ndnvar(deriv, var, self.nx)
if out is None:
base_shape = X.shape[1:]
out = np.ndarray((nd, self.nf) + bas... | Bessel functions of the first kind. | BesselJ | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BesselJ:
"""Bessel functions of the first kind."""
def __init__(self, v):
"""Bessel function of the first kind, :math:`J_{\\nu}(x)`. Parameters ---------- v : float The real order parameter."""
<|body_0|>
def _jv(self, X, deriv=0, out=None, var=None):
"""Bessel f... | stack_v2_sparse_classes_36k_train_025625 | 39,055 | permissive | [
{
"docstring": "Bessel function of the first kind, :math:`J_{\\\\nu}(x)`. Parameters ---------- v : float The real order parameter.",
"name": "__init__",
"signature": "def __init__(self, v)"
},
{
"docstring": "Bessel function of the first kind, Jv. Derivative array eval function.",
"name": "... | 2 | stack_v2_sparse_classes_30k_train_014944 | Implement the Python class `BesselJ` described below.
Class description:
Bessel functions of the first kind.
Method signatures and docstrings:
- def __init__(self, v): Bessel function of the first kind, :math:`J_{\\nu}(x)`. Parameters ---------- v : float The real order parameter.
- def _jv(self, X, deriv=0, out=None... | Implement the Python class `BesselJ` described below.
Class description:
Bessel functions of the first kind.
Method signatures and docstrings:
- def __init__(self, v): Bessel function of the first kind, :math:`J_{\\nu}(x)`. Parameters ---------- v : float The real order parameter.
- def _jv(self, X, deriv=0, out=None... | c6341a58331deef3728cc43c627c556139deb673 | <|skeleton|>
class BesselJ:
"""Bessel functions of the first kind."""
def __init__(self, v):
"""Bessel function of the first kind, :math:`J_{\\nu}(x)`. Parameters ---------- v : float The real order parameter."""
<|body_0|>
def _jv(self, X, deriv=0, out=None, var=None):
"""Bessel f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BesselJ:
"""Bessel functions of the first kind."""
def __init__(self, v):
"""Bessel function of the first kind, :math:`J_{\\nu}(x)`. Parameters ---------- v : float The real order parameter."""
super().__init__(self._jv, nf=1, nx=1, maxderiv=None, zlevel=None)
self.v = v
r... | the_stack_v2_python_sparse | nitrogen/special.py | bchangala/nitrogen | train | 11 |
46136400afd7e1ac5c4038c1809eb220f148fc9a | [
"self.surface = surface\nself.clock = pygame.time.Clock()\nself.lives = 3\nself.current_level = 1\nself.is_alive = True\nself.is_paused = False\nself.level = 1",
"if self.lives > 0:\n self.is_alive = True\n self.draw()",
"background = pygame.image.load(os.path.join('sky.jpg'))\ncontroller = Controller()\n... | <|body_start_0|>
self.surface = surface
self.clock = pygame.time.Clock()
self.lives = 3
self.current_level = 1
self.is_alive = True
self.is_paused = False
self.level = 1
<|end_body_0|>
<|body_start_1|>
if self.lives > 0:
self.is_alive = True
... | Game Loop | GameLoop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameLoop:
"""Game Loop"""
def __init__(self, surface):
"""Constructor"""
<|body_0|>
def new_game(self):
"""Resets the Game"""
<|body_1|>
def draw(self):
"""Contains main game loop"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_025626 | 2,269 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, surface)"
},
{
"docstring": "Resets the Game",
"name": "new_game",
"signature": "def new_game(self)"
},
{
"docstring": "Contains main game loop",
"name": "draw",
"signature": "def draw(self... | 3 | stack_v2_sparse_classes_30k_train_013109 | Implement the Python class `GameLoop` described below.
Class description:
Game Loop
Method signatures and docstrings:
- def __init__(self, surface): Constructor
- def new_game(self): Resets the Game
- def draw(self): Contains main game loop | Implement the Python class `GameLoop` described below.
Class description:
Game Loop
Method signatures and docstrings:
- def __init__(self, surface): Constructor
- def new_game(self): Resets the Game
- def draw(self): Contains main game loop
<|skeleton|>
class GameLoop:
"""Game Loop"""
def __init__(self, sur... | 9918cd301178e3f5d5b6e37be60b9709ad203a09 | <|skeleton|>
class GameLoop:
"""Game Loop"""
def __init__(self, surface):
"""Constructor"""
<|body_0|>
def new_game(self):
"""Resets the Game"""
<|body_1|>
def draw(self):
"""Contains main game loop"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameLoop:
"""Game Loop"""
def __init__(self, surface):
"""Constructor"""
self.surface = surface
self.clock = pygame.time.Clock()
self.lives = 3
self.current_level = 1
self.is_alive = True
self.is_paused = False
self.level = 1
def new_ga... | the_stack_v2_python_sparse | GameLoop.py | eastcoastcoder/PygameSideScroller | train | 1 |
37119a1e4fcf78928ffd6a3406988d2262d5a4ab | [
"create_database()\nadd_customer(1738, 'Bartholomew', 'Simpson', '742 Evergreen Terrace', 12065554682, 'Bartman99@aol.com', True, 101.5)\ntest_customer = Customer.get(Customer.customer_id == 1738)\nself.assertEqual(1738, test_customer.customer_id)\nself.assertEqual('Bartholomew', test_customer.first_name)\nself.ass... | <|body_start_0|>
create_database()
add_customer(1738, 'Bartholomew', 'Simpson', '742 Evergreen Terrace', 12065554682, 'Bartman99@aol.com', True, 101.5)
test_customer = Customer.get(Customer.customer_id == 1738)
self.assertEqual(1738, test_customer.customer_id)
self.assertEqual('B... | CustomerTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerTest:
def test_add_customer(self):
"""Verify that the attributes have been appropriately assigned"""
<|body_0|>
def test_search_customer(self):
"""Verify that customers can be searched for correctly"""
<|body_1|>
def test_delete_customer(self):
... | stack_v2_sparse_classes_36k_train_025627 | 3,689 | no_license | [
{
"docstring": "Verify that the attributes have been appropriately assigned",
"name": "test_add_customer",
"signature": "def test_add_customer(self)"
},
{
"docstring": "Verify that customers can be searched for correctly",
"name": "test_search_customer",
"signature": "def test_search_cus... | 5 | null | Implement the Python class `CustomerTest` described below.
Class description:
Implement the CustomerTest class.
Method signatures and docstrings:
- def test_add_customer(self): Verify that the attributes have been appropriately assigned
- def test_search_customer(self): Verify that customers can be searched for corre... | Implement the Python class `CustomerTest` described below.
Class description:
Implement the CustomerTest class.
Method signatures and docstrings:
- def test_add_customer(self): Verify that the attributes have been appropriately assigned
- def test_search_customer(self): Verify that customers can be searched for corre... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class CustomerTest:
def test_add_customer(self):
"""Verify that the attributes have been appropriately assigned"""
<|body_0|>
def test_search_customer(self):
"""Verify that customers can be searched for correctly"""
<|body_1|>
def test_delete_customer(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomerTest:
def test_add_customer(self):
"""Verify that the attributes have been appropriately assigned"""
create_database()
add_customer(1738, 'Bartholomew', 'Simpson', '742 Evergreen Terrace', 12065554682, 'Bartman99@aol.com', True, 101.5)
test_customer = Customer.get(Custo... | the_stack_v2_python_sparse | students/kevin_t/Lesson4/test_basic_operations.py | JavaRod/SP_Python220B_2019 | train | 1 | |
5509880c30c2e03ca6eb42ad32018c39fb5939ed | [
"self.api: MicroBotApiClient = client\nself.data: dict[str, Any] = {}\nself.ble_device = ble_device\nsuper().__init__(hass, _LOGGER, ble_device.address, bluetooth.BluetoothScanningMode.ACTIVE)",
"if (adv := parse_advertisement_data(service_info.device, service_info.advertisement)):\n self.data = adv.data\n ... | <|body_start_0|>
self.api: MicroBotApiClient = client
self.data: dict[str, Any] = {}
self.ble_device = ble_device
super().__init__(hass, _LOGGER, ble_device.address, bluetooth.BluetoothScanningMode.ACTIVE)
<|end_body_0|>
<|body_start_1|>
if (adv := parse_advertisement_data(servi... | Class to manage fetching data from the MicroBot. | MicroBotDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MicroBotDataUpdateCoordinator:
"""Class to manage fetching data from the MicroBot."""
def __init__(self, hass: HomeAssistant, client: MicroBotApiClient, ble_device: BLEDevice) -> None:
"""Initialize."""
<|body_0|>
def _async_handle_bluetooth_event(self, service_info: blu... | stack_v2_sparse_classes_36k_train_025628 | 1,824 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, client: MicroBotApiClient, ble_device: BLEDevice) -> None"
},
{
"docstring": "Handle a Bluetooth event.",
"name": "_async_handle_bluetooth_event",
"signature": "def _async_handle_bluet... | 2 | stack_v2_sparse_classes_30k_train_021291 | Implement the Python class `MicroBotDataUpdateCoordinator` described below.
Class description:
Class to manage fetching data from the MicroBot.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, client: MicroBotApiClient, ble_device: BLEDevice) -> None: Initialize.
- def _async_handle_bluetoo... | Implement the Python class `MicroBotDataUpdateCoordinator` described below.
Class description:
Class to manage fetching data from the MicroBot.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, client: MicroBotApiClient, ble_device: BLEDevice) -> None: Initialize.
- def _async_handle_bluetoo... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class MicroBotDataUpdateCoordinator:
"""Class to manage fetching data from the MicroBot."""
def __init__(self, hass: HomeAssistant, client: MicroBotApiClient, ble_device: BLEDevice) -> None:
"""Initialize."""
<|body_0|>
def _async_handle_bluetooth_event(self, service_info: blu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MicroBotDataUpdateCoordinator:
"""Class to manage fetching data from the MicroBot."""
def __init__(self, hass: HomeAssistant, client: MicroBotApiClient, ble_device: BLEDevice) -> None:
"""Initialize."""
self.api: MicroBotApiClient = client
self.data: dict[str, Any] = {}
se... | the_stack_v2_python_sparse | homeassistant/components/keymitt_ble/coordinator.py | home-assistant/core | train | 35,501 |
7ec1f539b037030ff9f2e0873c40613a11543f6e | [
"args = product_parser.parse_args()\ninvalid_data = validate_product_data(args)\nif invalid_data:\n return invalid_data\nproduct_name = args['product_name']\nproduct_category = args['product_category']\nProduct.add_product(cursor, product_name, product_category, user_id)\nreturn ({'message': 'Product added succe... | <|body_start_0|>
args = product_parser.parse_args()
invalid_data = validate_product_data(args)
if invalid_data:
return invalid_data
product_name = args['product_name']
product_category = args['product_category']
Product.add_product(cursor, product_name, produc... | Displays a list of all products and lets you POST to add new products. | ProductList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductList:
"""Displays a list of all products and lets you POST to add new products."""
def post(user_id, self):
"""Creates a new Product."""
<|body_0|>
def get(user_id, self):
"""List all Products"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_025629 | 4,088 | permissive | [
{
"docstring": "Creates a new Product.",
"name": "post",
"signature": "def post(user_id, self)"
},
{
"docstring": "List all Products",
"name": "get",
"signature": "def get(user_id, self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012510 | Implement the Python class `ProductList` described below.
Class description:
Displays a list of all products and lets you POST to add new products.
Method signatures and docstrings:
- def post(user_id, self): Creates a new Product.
- def get(user_id, self): List all Products | Implement the Python class `ProductList` described below.
Class description:
Displays a list of all products and lets you POST to add new products.
Method signatures and docstrings:
- def post(user_id, self): Creates a new Product.
- def get(user_id, self): List all Products
<|skeleton|>
class ProductList:
"""Di... | f806b8aa989393b4d2b1967c5be99ee3c4b5b9b6 | <|skeleton|>
class ProductList:
"""Displays a list of all products and lets you POST to add new products."""
def post(user_id, self):
"""Creates a new Product."""
<|body_0|>
def get(user_id, self):
"""List all Products"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductList:
"""Displays a list of all products and lets you POST to add new products."""
def post(user_id, self):
"""Creates a new Product."""
args = product_parser.parse_args()
invalid_data = validate_product_data(args)
if invalid_data:
return invalid_data
... | the_stack_v2_python_sparse | app/api/v2/views/products_views.py | koitoror/StoreManager | train | 1 |
cf5a9c2ae802eab03e95c07333c1929a45337ad9 | [
"super().__init__()\nself.sub_blocks = nn.ModuleList()\nfor i in range(sub_blocks):\n self.sub_blocks.append(SubBlock(kernels=kernels, gate_channels=gate_channels, residual_channels=residual_channels))\nself.skip_convs = nn.Conv1d(in_channels=residual_channels, out_channels=skip_channels, kernel_size=1)\nself.di... | <|body_start_0|>
super().__init__()
self.sub_blocks = nn.ModuleList()
for i in range(sub_blocks):
self.sub_blocks.append(SubBlock(kernels=kernels, gate_channels=gate_channels, residual_channels=residual_channels))
self.skip_convs = nn.Conv1d(in_channels=residual_channels, out... | Блок, состоящий из нескольких маленьких блоков и последующим уменьшением размерности. Имеет два выхода: - Основной с уменьшенной в два раза размерностью; - Скип для суммирования последнего значения слоя с остальными скипами и расчета общего выходного значения. | Block | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Block:
"""Блок, состоящий из нескольких маленьких блоков и последующим уменьшением размерности. Имеет два выхода: - Основной с уменьшенной в два раза размерностью; - Скип для суммирования последнего значения слоя с остальными скипами и расчета общего выходного значения."""
def __init__(self,... | stack_v2_sparse_classes_36k_train_025630 | 13,064 | permissive | [
{
"docstring": ":param sub_blocks: Количество маленьких блоков в блоке. :param kernels: Размер сверток в signal и gate сверточных слоях. :param gate_channels: Количество каналов в signal и gate сверточных слоях маленьких блоков. :param residual_channels: Количество каналов на входе и по обходному пути маленьких... | 2 | null | Implement the Python class `Block` described below.
Class description:
Блок, состоящий из нескольких маленьких блоков и последующим уменьшением размерности. Имеет два выхода: - Основной с уменьшенной в два раза размерностью; - Скип для суммирования последнего значения слоя с остальными скипами и расчета общего выходно... | Implement the Python class `Block` described below.
Class description:
Блок, состоящий из нескольких маленьких блоков и последующим уменьшением размерности. Имеет два выхода: - Основной с уменьшенной в два раза размерностью; - Скип для суммирования последнего значения слоя с остальными скипами и расчета общего выходно... | 3a67544fd4c1bce39d67523799b76c9adfd03969 | <|skeleton|>
class Block:
"""Блок, состоящий из нескольких маленьких блоков и последующим уменьшением размерности. Имеет два выхода: - Основной с уменьшенной в два раза размерностью; - Скип для суммирования последнего значения слоя с остальными скипами и расчета общего выходного значения."""
def __init__(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Block:
"""Блок, состоящий из нескольких маленьких блоков и последующим уменьшением размерности. Имеет два выхода: - Основной с уменьшенной в два раза размерностью; - Скип для суммирования последнего значения слоя с остальными скипами и расчета общего выходного значения."""
def __init__(self, sub_blocks: ... | the_stack_v2_python_sparse | poptimizer/dl/models/wave_net.py | tjlee/poptimizer | train | 0 |
bc7b2384045e28fe1f1254b8c95c8a36dcc45273 | [
"try:\n params, is_json = (request.json, True)\nexcept ValueError:\n params, is_json = (None, False)\nif not params:\n params, is_json = (request.params, False)\nreturn (params, is_json)",
"if name == ParameterType.TOKEN_NAME:\n token_name = ADMIN_TOKEN_NAME if request_api_type() == API_ADMIN else CAB... | <|body_start_0|>
try:
params, is_json = (request.json, True)
except ValueError:
params, is_json = (None, False)
if not params:
params, is_json = (request.params, False)
return (params, is_json)
<|end_body_0|>
<|body_start_1|>
if name == Parame... | Actual class which responsible for validation. Actually check_params decorator just puts everything in it and relies on it during the processing. | ParameterValidator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParameterValidator:
"""Actual class which responsible for validation. Actually check_params decorator just puts everything in it and relies on it during the processing."""
def request_params():
"""Detects where do we have incoming arguments and returns them. :return tuple of paramete... | stack_v2_sparse_classes_36k_train_025631 | 8,864 | permissive | [
{
"docstring": "Detects where do we have incoming arguments and returns them. :return tuple of parameters (dict-like structure) and sign were they JSONed or not. This is required if we have different rules for processing form-data and simple JSON.",
"name": "request_params",
"signature": "def request_pa... | 5 | stack_v2_sparse_classes_30k_train_008354 | Implement the Python class `ParameterValidator` described below.
Class description:
Actual class which responsible for validation. Actually check_params decorator just puts everything in it and relies on it during the processing.
Method signatures and docstrings:
- def request_params(): Detects where do we have incom... | Implement the Python class `ParameterValidator` described below.
Class description:
Actual class which responsible for validation. Actually check_params decorator just puts everything in it and relies on it during the processing.
Method signatures and docstrings:
- def request_params(): Detects where do we have incom... | bc0cfe3067bf1cbf26789f7443a36e7cdd2ac869 | <|skeleton|>
class ParameterValidator:
"""Actual class which responsible for validation. Actually check_params decorator just puts everything in it and relies on it during the processing."""
def request_params():
"""Detects where do we have incoming arguments and returns them. :return tuple of paramete... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParameterValidator:
"""Actual class which responsible for validation. Actually check_params decorator just puts everything in it and relies on it during the processing."""
def request_params():
"""Detects where do we have incoming arguments and returns them. :return tuple of parameters (dict-like... | the_stack_v2_python_sparse | backend/api/check_params.py | omarabdalhamid/boss | train | 0 |
fb3cf46adde7104d72d81c615a020da853bcfc97 | [
"self.url = url\nself.realm = realm\nself.extra = extra or dict()\nself.make = make\nself.context_factory = context_factory\nservice.MultiService.__init__(self)\nself.setupService()",
"is_secure, host, port, resource, path, params = parse_ws_url(self.url)\n\ndef create():\n cfg = ComponentConfig(self.realm, se... | <|body_start_0|>
self.url = url
self.realm = realm
self.extra = extra or dict()
self.make = make
self.context_factory = context_factory
service.MultiService.__init__(self)
self.setupService()
<|end_body_0|>
<|body_start_1|>
is_secure, host, port, resource... | A WAMP application as a twisted service. The application object provides a simple way of creating, debugging and running WAMP application components inside a traditional twisted application This manages application lifecycle of the wamp connection using startService and stopService Using services also allows to create ... | Service | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Service:
"""A WAMP application as a twisted service. The application object provides a simple way of creating, debugging and running WAMP application components inside a traditional twisted application This manages application lifecycle of the wamp connection using startService and stopService Us... | stack_v2_sparse_classes_36k_train_025632 | 32,181 | permissive | [
{
"docstring": ":param url: The WebSocket URL of the WAMP router to connect to (e.g. `ws://somehost.com:8090/somepath`) :type url: unicode :param realm: The WAMP realm to join the application session to. :type realm: unicode :param make: A factory that produces instances of :class:`autobahn.asyncio.wamp.Applica... | 2 | stack_v2_sparse_classes_30k_train_018017 | Implement the Python class `Service` described below.
Class description:
A WAMP application as a twisted service. The application object provides a simple way of creating, debugging and running WAMP application components inside a traditional twisted application This manages application lifecycle of the wamp connectio... | Implement the Python class `Service` described below.
Class description:
A WAMP application as a twisted service. The application object provides a simple way of creating, debugging and running WAMP application components inside a traditional twisted application This manages application lifecycle of the wamp connectio... | 5cee0a8c4180a3108538b4e4ce945a18726595a6 | <|skeleton|>
class Service:
"""A WAMP application as a twisted service. The application object provides a simple way of creating, debugging and running WAMP application components inside a traditional twisted application This manages application lifecycle of the wamp connection using startService and stopService Us... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Service:
"""A WAMP application as a twisted service. The application object provides a simple way of creating, debugging and running WAMP application components inside a traditional twisted application This manages application lifecycle of the wamp connection using startService and stopService Using services ... | the_stack_v2_python_sparse | venv/Lib/site-packages/autobahn/twisted/wamp.py | zoelesv/Smathchat | train | 9 |
e48ac31f3bf396712a9ee8b36c5064b423a5e5c0 | [
"if tolerance_in_millis > MAX_NORMAL_REQUEST_TOLERANCE_IN_MILLIS:\n warnings.warn('Provided tolerance value {} exceeds the maximum allowed value {}. Maximum value will be used instead'.format(tolerance_in_millis, MAX_NORMAL_REQUEST_TOLERANCE_IN_MILLIS))\n tolerance_in_millis = MAX_NORMAL_REQUEST_TOLERANCE_IN_... | <|body_start_0|>
if tolerance_in_millis > MAX_NORMAL_REQUEST_TOLERANCE_IN_MILLIS:
warnings.warn('Provided tolerance value {} exceeds the maximum allowed value {}. Maximum value will be used instead'.format(tolerance_in_millis, MAX_NORMAL_REQUEST_TOLERANCE_IN_MILLIS))
tolerance_in_millis ... | Verifier that performs request timestamp verification. This is a concrete implementation of :py:class:`AbstractVerifier` class, handling the request timestamp verification of the input request. The verification follows the mechanism explained here : https://developer.amazon.com/docs/custom-skills/host-a-custom-skill-as... | TimestampVerifier | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimestampVerifier:
"""Verifier that performs request timestamp verification. This is a concrete implementation of :py:class:`AbstractVerifier` class, handling the request timestamp verification of the input request. The verification follows the mechanism explained here : https://developer.amazon.... | stack_v2_sparse_classes_36k_train_025633 | 22,604 | permissive | [
{
"docstring": "Verifier that performs request timestamp verification. This is a concrete implementation of :py:class:`AbstractVerifier` class, handling the request timestamp verification of the input request. The verification follows the mechanism explained here: https://developer.amazon.com/docs/custom-skills... | 2 | stack_v2_sparse_classes_30k_train_002436 | Implement the Python class `TimestampVerifier` described below.
Class description:
Verifier that performs request timestamp verification. This is a concrete implementation of :py:class:`AbstractVerifier` class, handling the request timestamp verification of the input request. The verification follows the mechanism exp... | Implement the Python class `TimestampVerifier` described below.
Class description:
Verifier that performs request timestamp verification. This is a concrete implementation of :py:class:`AbstractVerifier` class, handling the request timestamp verification of the input request. The verification follows the mechanism exp... | 7e13ca69b240985584dff6ec633a27598a154ca1 | <|skeleton|>
class TimestampVerifier:
"""Verifier that performs request timestamp verification. This is a concrete implementation of :py:class:`AbstractVerifier` class, handling the request timestamp verification of the input request. The verification follows the mechanism explained here : https://developer.amazon.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimestampVerifier:
"""Verifier that performs request timestamp verification. This is a concrete implementation of :py:class:`AbstractVerifier` class, handling the request timestamp verification of the input request. The verification follows the mechanism explained here : https://developer.amazon.com/docs/cust... | the_stack_v2_python_sparse | ask-sdk-webservice-support/ask_sdk_webservice_support/verifier.py | alexa/alexa-skills-kit-sdk-for-python | train | 560 |
5506e67886bb29824549239834bd756d862ac8d9 | [
"countS = collections.Counter(s)\nsingle = [ch for ch, i in countS.items() if i == 1]\nprint(single)\nif not single:\n return -1\nfor i in range(len(s)):\n if s[i] in single:\n return i",
"for ch in s:\n if s.count(ch) == 1:\n return s.index(ch)\nreturn -1"
] | <|body_start_0|>
countS = collections.Counter(s)
single = [ch for ch, i in countS.items() if i == 1]
print(single)
if not single:
return -1
for i in range(len(s)):
if s[i] in single:
return i
<|end_body_0|>
<|body_start_1|>
for ch ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def firstUniqChar(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def firstUniqChar2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
countS = collections.Counter(s)
single = [ch for ch, i i... | stack_v2_sparse_classes_36k_train_025634 | 645 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "firstUniqChar",
"signature": "def firstUniqChar(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "firstUniqChar2",
"signature": "def firstUniqChar2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstUniqChar(self, s): :type s: str :rtype: int
- def firstUniqChar2(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 firstUniqChar(self, s): :type s: str :rtype: int
- def firstUniqChar2(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def firstUniqChar(self, s):
... | a13e7faaf55cd68249267e46a91e93c97e3190c2 | <|skeleton|>
class Solution:
def firstUniqChar(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def firstUniqChar2(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 firstUniqChar(self, s):
""":type s: str :rtype: int"""
countS = collections.Counter(s)
single = [ch for ch, i in countS.items() if i == 1]
print(single)
if not single:
return -1
for i in range(len(s)):
if s[i] in single:
... | the_stack_v2_python_sparse | LeetCode/String/387.py | xiaojkql/Algorithm-Data-Structure | train | 1 | |
0d21d88901fb3236f329c7fd586e1173054e22a8 | [
"super(GANLoss, self).__init__()\nself.register_buffer('real_label', torch.tensor(target_real_label))\nself.register_buffer('fake_label', torch.tensor(target_fake_label))\nself.gan_mode = gan_mode\nif gan_mode == 'lsgan':\n self.loss = nn.MSELoss()\nelif gan_mode == 'vanilla':\n self.loss = nn.BCEWithLogitsLo... | <|body_start_0|>
super(GANLoss, self).__init__()
self.register_buffer('real_label', torch.tensor(target_real_label))
self.register_buffer('fake_label', torch.tensor(target_fake_label))
self.gan_mode = gan_mode
if gan_mode == 'lsgan':
self.loss = nn.MSELoss()
e... | Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input. | GANLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GANLoss:
"""Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input."""
def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=0.0):
"""Initialize the GANLoss class. Parameters: ga... | stack_v2_sparse_classes_36k_train_025635 | 22,730 | no_license | [
{
"docstring": "Initialize the GANLoss class. Parameters: gan_mode (str) - - the type of GAN objective. It currently supports vanilla, lsgan, and wgangp. target_real_label (bool) - - label for a real image target_fake_label (bool) - - label of a fake image Note: Do not use sigmoid as the last layer of Discrimin... | 3 | stack_v2_sparse_classes_30k_train_020391 | Implement the Python class `GANLoss` described below.
Class description:
Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input.
Method signatures and docstrings:
- def __init__(self, gan_mode, target_real_label=1.0, target_fake... | Implement the Python class `GANLoss` described below.
Class description:
Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input.
Method signatures and docstrings:
- def __init__(self, gan_mode, target_real_label=1.0, target_fake... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class GANLoss:
"""Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input."""
def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=0.0):
"""Initialize the GANLoss class. Parameters: ga... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GANLoss:
"""Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input."""
def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=0.0):
"""Initialize the GANLoss class. Parameters: gan_mode (str) ... | the_stack_v2_python_sparse | generated/test_junyanz_BicycleGAN.py | jansel/pytorch-jit-paritybench | train | 35 |
a2791858ef9dcbbeafa4164908e82fdc7143d774 | [
"self.num_points = num_points\nself.x_values = [0]\nself.y_values = [0]",
"while len(self.x_values) < self.num_points:\n x_step = get_step()\n y_step = get_step()\n y_direction = choice([1, -1])\n y_distance = choice([0, 1, 2, 3, 4])\n y_step = y_direction * y_distance\n if x_step == 0 and y_ste... | <|body_start_0|>
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
<|end_body_0|>
<|body_start_1|>
while len(self.x_values) < self.num_points:
x_step = get_step()
y_step = get_step()
y_direction = choice([1, -1])
y_dista... | 一个生成随机漫步数的类 | RandomWalk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomWalk:
"""一个生成随机漫步数的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
"""计算随机漫步包含的所有点"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.num_points = num_points
self.x_values = [0]
... | stack_v2_sparse_classes_36k_train_025636 | 1,320 | no_license | [
{
"docstring": "初始化随机漫步的属性",
"name": "__init__",
"signature": "def __init__(self, num_points=5000)"
},
{
"docstring": "计算随机漫步包含的所有点",
"name": "fill_walk",
"signature": "def fill_walk(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000997 | Implement the Python class `RandomWalk` described below.
Class description:
一个生成随机漫步数的类
Method signatures and docstrings:
- def __init__(self, num_points=5000): 初始化随机漫步的属性
- def fill_walk(self): 计算随机漫步包含的所有点 | Implement the Python class `RandomWalk` described below.
Class description:
一个生成随机漫步数的类
Method signatures and docstrings:
- def __init__(self, num_points=5000): 初始化随机漫步的属性
- def fill_walk(self): 计算随机漫步包含的所有点
<|skeleton|>
class RandomWalk:
"""一个生成随机漫步数的类"""
def __init__(self, num_points=5000):
"""初始化... | 3eb10d5f571ec79d1de3085bdc90b504abedcc63 | <|skeleton|>
class RandomWalk:
"""一个生成随机漫步数的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
"""计算随机漫步包含的所有点"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomWalk:
"""一个生成随机漫步数的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
def fill_walk(self):
"""计算随机漫步包含的所有点"""
while len(self.x_values) < self.num_points:
x_s... | the_stack_v2_python_sparse | project/data_analysis/random/random_walk.py | hjacks/Python-Learning | train | 0 |
181e254549a4346a3fc907bbc5cd16627bf4660a | [
"self.required_queries, self._enc, self._dec, self.key_len = (required_queries, encrypt, decrypt, key_len)\nself.key = ''\nself.ciphertexts = []",
"self.answered_queries = 0\nself.key = random_string(self.key_len)\nself.ciphertexts = []\nself.win = False",
"self.answered_queries += 1\nc = self._enc(self.key, m)... | <|body_start_0|>
self.required_queries, self._enc, self._dec, self.key_len = (required_queries, encrypt, decrypt, key_len)
self.key = ''
self.ciphertexts = []
<|end_body_0|>
<|body_start_1|>
self.answered_queries = 0
self.key = random_string(self.key_len)
self.ciphertext... | This game tests the integrity of a ciphertext. It is to be used to test to see if the decryption algorithm only decrypts authentic messages that have been sent by the sender. The Adversary has access to an encryption oracle (enc) and a decryption oracle (dec) that it uses to see if it won. | GameINTCTXT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameINTCTXT:
"""This game tests the integrity of a ciphertext. It is to be used to test to see if the decryption algorithm only decrypts authentic messages that have been sent by the sender. The Adversary has access to an encryption oracle (enc) and a decryption oracle (dec) that it uses to see i... | stack_v2_sparse_classes_36k_train_025637 | 2,233 | no_license | [
{
"docstring": ":param encrypt: Encryption function that takes inputs, a key k of key_len length and a message. :param decrypt: Decryption function to match encryption function. :param key_len: Length of key used by encrypt and decrypt.",
"name": "__init__",
"signature": "def __init__(self, required_que... | 4 | stack_v2_sparse_classes_30k_train_004210 | Implement the Python class `GameINTCTXT` described below.
Class description:
This game tests the integrity of a ciphertext. It is to be used to test to see if the decryption algorithm only decrypts authentic messages that have been sent by the sender. The Adversary has access to an encryption oracle (enc) and a decryp... | Implement the Python class `GameINTCTXT` described below.
Class description:
This game tests the integrity of a ciphertext. It is to be used to test to see if the decryption algorithm only decrypts authentic messages that have been sent by the sender. The Adversary has access to an encryption oracle (enc) and a decryp... | 9014f5a9bf7021bef9f5cc4aa5b16424ca83dee9 | <|skeleton|>
class GameINTCTXT:
"""This game tests the integrity of a ciphertext. It is to be used to test to see if the decryption algorithm only decrypts authentic messages that have been sent by the sender. The Adversary has access to an encryption oracle (enc) and a decryption oracle (dec) that it uses to see i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameINTCTXT:
"""This game tests the integrity of a ciphertext. It is to be used to test to see if the decryption algorithm only decrypts authentic messages that have been sent by the sender. The Adversary has access to an encryption oracle (enc) and a decryption oracle (dec) that it uses to see if it won."""
... | the_stack_v2_python_sparse | src/playcrypt/games/game_int_ctxt.py | UCSDCSE107/playcrypt | train | 2 |
511062e06b9989773830a2374c789d7ff53d0478 | [
"ret: list[list[str | bytes]] = []\nfor f in flows:\n ret.append([extract(c, f) for c in cuts])\nreturn ret",
"append = False\nif path.startswith('+'):\n append = True\n epath = os.path.expanduser(path[1:])\n path = mitmproxy.types.Path(epath)\ntry:\n if len(cuts) == 1 and len(flows) == 1:\n ... | <|body_start_0|>
ret: list[list[str | bytes]] = []
for f in flows:
ret.append([extract(c, f) for c in cuts])
return ret
<|end_body_0|>
<|body_start_1|>
append = False
if path.startswith('+'):
append = True
epath = os.path.expanduser(path[1:])
... | Cut | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cut:
def cut(self, flows: Sequence[flow.Flow], cuts: mitmproxy.types.CutSpec) -> mitmproxy.types.Data:
"""Cut data from a set of flows. Cut specifications are attribute paths from the base of the flow object, with a few conveniences - "port" and "host" retrieve parts of an address tuple,... | stack_v2_sparse_classes_36k_train_025638 | 5,777 | permissive | [
{
"docstring": "Cut data from a set of flows. Cut specifications are attribute paths from the base of the flow object, with a few conveniences - \"port\" and \"host\" retrieve parts of an address tuple, \".header[key]\" retrieves a header value. Return values converted to strings or bytes: SSL certificates are ... | 3 | null | Implement the Python class `Cut` described below.
Class description:
Implement the Cut class.
Method signatures and docstrings:
- def cut(self, flows: Sequence[flow.Flow], cuts: mitmproxy.types.CutSpec) -> mitmproxy.types.Data: Cut data from a set of flows. Cut specifications are attribute paths from the base of the ... | Implement the Python class `Cut` described below.
Class description:
Implement the Cut class.
Method signatures and docstrings:
- def cut(self, flows: Sequence[flow.Flow], cuts: mitmproxy.types.CutSpec) -> mitmproxy.types.Data: Cut data from a set of flows. Cut specifications are attribute paths from the base of the ... | 33a81a0eadc0196e5352ac9aa5189ac4deea3d64 | <|skeleton|>
class Cut:
def cut(self, flows: Sequence[flow.Flow], cuts: mitmproxy.types.CutSpec) -> mitmproxy.types.Data:
"""Cut data from a set of flows. Cut specifications are attribute paths from the base of the flow object, with a few conveniences - "port" and "host" retrieve parts of an address tuple,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cut:
def cut(self, flows: Sequence[flow.Flow], cuts: mitmproxy.types.CutSpec) -> mitmproxy.types.Data:
"""Cut data from a set of flows. Cut specifications are attribute paths from the base of the flow object, with a few conveniences - "port" and "host" retrieve parts of an address tuple, ".header[key]... | the_stack_v2_python_sparse | mitmproxy/addons/cut.py | mhils/mitmproxy | train | 2 | |
ce59f9e44547322cec6f4250b5685d3b9656e9ce | [
"super(InputEnsemble, self).store(ens)\nself.temperature.store(ens.temp)\nself.pressure.store(ens.pext)\nself.stress.store(ens.stressext)\nself.eens.store(ens.eens)\nself.bias.store(ens.bcomp)\nself.bias_weights.store(ens.bweights)\nself.hamiltonian_weights.store(ens.hweights)\nself.time.store(ens.time)",
"super(... | <|body_start_0|>
super(InputEnsemble, self).store(ens)
self.temperature.store(ens.temp)
self.pressure.store(ens.pext)
self.stress.store(ens.stressext)
self.eens.store(ens.eens)
self.bias.store(ens.bcomp)
self.bias_weights.store(ens.bweights)
self.hamiltoni... | Ensemble input class. Handles generating the appropriate ensemble class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: mode: An optional string giving the mode of ensemble to be simulated. Defaults to 'unknown'. Fields: temperature: An optional float... | InputEnsemble | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputEnsemble:
"""Ensemble input class. Handles generating the appropriate ensemble class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: mode: An optional string giving the mode of ensemble to be simulated. Defaults to 'unknown... | stack_v2_sparse_classes_36k_train_025639 | 4,582 | no_license | [
{
"docstring": "Takes an ensemble instance and stores a minimal representation of it. Args: ens: An ensemble object.",
"name": "store",
"signature": "def store(self, ens)"
},
{
"docstring": "Creates an ensemble object. Returns: An ensemble object of the appropriate mode and with the appropriate ... | 2 | null | Implement the Python class `InputEnsemble` described below.
Class description:
Ensemble input class. Handles generating the appropriate ensemble class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: mode: An optional string giving the mode of ensembl... | Implement the Python class `InputEnsemble` described below.
Class description:
Ensemble input class. Handles generating the appropriate ensemble class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: mode: An optional string giving the mode of ensembl... | 57f255266d4668bafef0881d1e7cbf8a27270ddd | <|skeleton|>
class InputEnsemble:
"""Ensemble input class. Handles generating the appropriate ensemble class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: mode: An optional string giving the mode of ensemble to be simulated. Defaults to 'unknown... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InputEnsemble:
"""Ensemble input class. Handles generating the appropriate ensemble class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: mode: An optional string giving the mode of ensemble to be simulated. Defaults to 'unknown'. Fields: te... | the_stack_v2_python_sparse | ipi/inputs/ensembles.py | i-pi/i-pi | train | 170 |
b38e295eb475155030ffe767babec1574ca5628a | [
"list_url = BASE_URL + '/snapshot/list'\npayload = {'token': test_token}\noutput = requests.post(list_url, json=payload)\ntest_snapshot_id = output.json()['snapshots'][0]['id']\npayload = {'token': test_token, 'id': test_snapshot_id}\noutput = requests.delete(url, json=payload)\nexpected_output = 'The snapshot has ... | <|body_start_0|>
list_url = BASE_URL + '/snapshot/list'
payload = {'token': test_token}
output = requests.post(list_url, json=payload)
test_snapshot_id = output.json()['snapshots'][0]['id']
payload = {'token': test_token, 'id': test_snapshot_id}
output = requests.delete(u... | TestDeleteSnapshot | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDeleteSnapshot:
def test_delete_working(self):
"""this test will pass the snapshot/load method"""
<|body_0|>
def test_delete_missing_parameter(self):
"""this test will fail because of missing parameters"""
<|body_1|>
def test_delete_not_existing_snap... | stack_v2_sparse_classes_36k_train_025640 | 1,900 | permissive | [
{
"docstring": "this test will pass the snapshot/load method",
"name": "test_delete_working",
"signature": "def test_delete_working(self)"
},
{
"docstring": "this test will fail because of missing parameters",
"name": "test_delete_missing_parameter",
"signature": "def test_delete_missing... | 4 | null | Implement the Python class `TestDeleteSnapshot` described below.
Class description:
Implement the TestDeleteSnapshot class.
Method signatures and docstrings:
- def test_delete_working(self): this test will pass the snapshot/load method
- def test_delete_missing_parameter(self): this test will fail because of missing ... | Implement the Python class `TestDeleteSnapshot` described below.
Class description:
Implement the TestDeleteSnapshot class.
Method signatures and docstrings:
- def test_delete_working(self): this test will pass the snapshot/load method
- def test_delete_missing_parameter(self): this test will fail because of missing ... | ba1e287dbc63e34bf9feb80b65b02c1db93ce91c | <|skeleton|>
class TestDeleteSnapshot:
def test_delete_working(self):
"""this test will pass the snapshot/load method"""
<|body_0|>
def test_delete_missing_parameter(self):
"""this test will fail because of missing parameters"""
<|body_1|>
def test_delete_not_existing_snap... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDeleteSnapshot:
def test_delete_working(self):
"""this test will pass the snapshot/load method"""
list_url = BASE_URL + '/snapshot/list'
payload = {'token': test_token}
output = requests.post(list_url, json=payload)
test_snapshot_id = output.json()['snapshots'][0]['... | the_stack_v2_python_sparse | pytest_suit/routes/snapshot/test_zdeleteSnapshot.py | HotMaps/Hotmaps-toolbox-service | train | 4 | |
fe851e8badd441176ab25aecc4257dc9083d6f81 | [
"headers = {'Content-Type': 'application/json', 'Authorization': 'Bearer {}'.format(sendgrid_api_key)}\ndata = {'personalizations': [{'to': [{'email': 'recipient@example.com'}]}], 'from': {'email': 'sendeexampexample@example.com'}, 'subject': 'HelloWorld!', 'content': [{'type': 'text/plain', 'value': 'Howdy!'}]}\nr... | <|body_start_0|>
headers = {'Content-Type': 'application/json', 'Authorization': 'Bearer {}'.format(sendgrid_api_key)}
data = {'personalizations': [{'to': [{'email': 'recipient@example.com'}]}], 'from': {'email': 'sendeexampexample@example.com'}, 'subject': 'HelloWorld!', 'content': [{'type': 'text/plai... | Helper Class. Contains methods used by Sendgrid Resource classes | SendgridHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SendgridHelper:
"""Helper Class. Contains methods used by Sendgrid Resource classes"""
def send_test_request(sendgrid_api_key: str) -> requests.Response:
"""Send POST request to the Sendgrid test endpoint containing the the supplied API key :param sendgrid_api_key: Key whose validity... | stack_v2_sparse_classes_36k_train_025641 | 6,487 | permissive | [
{
"docstring": "Send POST request to the Sendgrid test endpoint containing the the supplied API key :param sendgrid_api_key: Key whose validity is to be tested :return: The HTTP response received from Sendgrid",
"name": "send_test_request",
"signature": "def send_test_request(sendgrid_api_key: str) -> r... | 2 | stack_v2_sparse_classes_30k_train_007079 | Implement the Python class `SendgridHelper` described below.
Class description:
Helper Class. Contains methods used by Sendgrid Resource classes
Method signatures and docstrings:
- def send_test_request(sendgrid_api_key: str) -> requests.Response: Send POST request to the Sendgrid test endpoint containing the the sup... | Implement the Python class `SendgridHelper` described below.
Class description:
Helper Class. Contains methods used by Sendgrid Resource classes
Method signatures and docstrings:
- def send_test_request(sendgrid_api_key: str) -> requests.Response: Send POST request to the Sendgrid test endpoint containing the the sup... | 5d123691d1f25d0b85e20e4e8293266bf23c9f8a | <|skeleton|>
class SendgridHelper:
"""Helper Class. Contains methods used by Sendgrid Resource classes"""
def send_test_request(sendgrid_api_key: str) -> requests.Response:
"""Send POST request to the Sendgrid test endpoint containing the the supplied API key :param sendgrid_api_key: Key whose validity... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SendgridHelper:
"""Helper Class. Contains methods used by Sendgrid Resource classes"""
def send_test_request(sendgrid_api_key: str) -> requests.Response:
"""Send POST request to the Sendgrid test endpoint containing the the supplied API key :param sendgrid_api_key: Key whose validity is to be tes... | the_stack_v2_python_sparse | Analytics/resources/sendgrid_management.py | thanosbnt/SharingCitiesDashboard | train | 0 |
97a1a0e68ec3b3f2029ead4eafaeaecc280acde9 | [
"ParticleFilter.__init__(self, number_of_particles, limits, process_noise, measurement_noise)\nself.maximum_number_of_particles = max_number_particles\nself.sum_likelihoods_threshold = sum_likelihoods_threshold",
"new_particles = []\nsum_likelihoods = 0\nnumber_of_new_particles = 0\nwhile sum_likelihoods < self.s... | <|body_start_0|>
ParticleFilter.__init__(self, number_of_particles, limits, process_noise, measurement_noise)
self.maximum_number_of_particles = max_number_particles
self.sum_likelihoods_threshold = sum_likelihoods_threshold
<|end_body_0|>
<|body_start_1|>
new_particles = []
sum... | Notes: * State is (x, y, heading), where x and y are in meters and heading in radians * State space assumed limited size in each dimension, world is cyclic (hence leaving at x_max means entering at x_min) | AdaptiveParticleFilterSl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaptiveParticleFilterSl:
"""Notes: * State is (x, y, heading), where x and y are in meters and heading in radians * State space assumed limited size in each dimension, world is cyclic (hence leaving at x_max means entering at x_min)"""
def __init__(self, number_of_particles, limits, process... | stack_v2_sparse_classes_36k_train_025642 | 3,982 | no_license | [
{
"docstring": "Initialize the adaptive particle filter using sum of likelihoods sampling proposed explained in [1,2]. [1] Straka, Ondrej, and Miroslav Simandl. \"A survey of sample size adaptation techniques for particle filters.\" IFAC Proceedings Volumes 42.10 (2009): 1358-1363. [2] Koller, Daphne, and Raya ... | 2 | stack_v2_sparse_classes_30k_train_018090 | Implement the Python class `AdaptiveParticleFilterSl` described below.
Class description:
Notes: * State is (x, y, heading), where x and y are in meters and heading in radians * State space assumed limited size in each dimension, world is cyclic (hence leaving at x_max means entering at x_min)
Method signatures and d... | Implement the Python class `AdaptiveParticleFilterSl` described below.
Class description:
Notes: * State is (x, y, heading), where x and y are in meters and heading in radians * State space assumed limited size in each dimension, world is cyclic (hence leaving at x_max means entering at x_min)
Method signatures and d... | 4e5197c38a9d241d9ea06c06ab9fc893ffb8c70b | <|skeleton|>
class AdaptiveParticleFilterSl:
"""Notes: * State is (x, y, heading), where x and y are in meters and heading in radians * State space assumed limited size in each dimension, world is cyclic (hence leaving at x_max means entering at x_min)"""
def __init__(self, number_of_particles, limits, process... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdaptiveParticleFilterSl:
"""Notes: * State is (x, y, heading), where x and y are in meters and heading in radians * State space assumed limited size in each dimension, world is cyclic (hence leaving at x_max means entering at x_min)"""
def __init__(self, number_of_particles, limits, process_noise, measu... | the_stack_v2_python_sparse | core/particle_filters/adaptive_particle_filter_sl.py | eternalamit5/Learning-Nuggets | train | 0 |
f424e80554bee1e0d789ebdf3c796eb198698c7e | [
"if not user_data:\n user_data = {'owner': f'{ANONYMOUS_SESSION} session', 'name': f'{ANONYMOUS_SESSION}', 'token': f'{ANONYMOUS_SESSION}'}\nself.ctx = ProjectCloneContext().load({**user_data, **request_data}, unknown=EXCLUDE)\nself.git_url = self.ctx['url_with_auth']\nself.branch = self.ctx['branch']",
"url =... | <|body_start_0|>
if not user_data:
user_data = {'owner': f'{ANONYMOUS_SESSION} session', 'name': f'{ANONYMOUS_SESSION}', 'token': f'{ANONYMOUS_SESSION}'}
self.ctx = ProjectCloneContext().load({**user_data, **request_data}, unknown=EXCLUDE)
self.git_url = self.ctx['url_with_auth']
... | Parent controller for all controllers with remote support. | RemoteProject | [
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteProject:
"""Parent controller for all controllers with remote support."""
def __init__(self, user_data, request_data):
"""Construct remote controller."""
<|body_0|>
def remote_url(self):
"""Construct project metadata remote path."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_025643 | 2,664 | permissive | [
{
"docstring": "Construct remote controller.",
"name": "__init__",
"signature": "def __init__(self, user_data, request_data)"
},
{
"docstring": "Construct project metadata remote path.",
"name": "remote_url",
"signature": "def remote_url(self)"
},
{
"docstring": "Retrieve project... | 3 | null | Implement the Python class `RemoteProject` described below.
Class description:
Parent controller for all controllers with remote support.
Method signatures and docstrings:
- def __init__(self, user_data, request_data): Construct remote controller.
- def remote_url(self): Construct project metadata remote path.
- def ... | Implement the Python class `RemoteProject` described below.
Class description:
Parent controller for all controllers with remote support.
Method signatures and docstrings:
- def __init__(self, user_data, request_data): Construct remote controller.
- def remote_url(self): Construct project metadata remote path.
- def ... | e0ff587f507d049eeeb873e8488ba8bb10ac1a15 | <|skeleton|>
class RemoteProject:
"""Parent controller for all controllers with remote support."""
def __init__(self, user_data, request_data):
"""Construct remote controller."""
<|body_0|>
def remote_url(self):
"""Construct project metadata remote path."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RemoteProject:
"""Parent controller for all controllers with remote support."""
def __init__(self, user_data, request_data):
"""Construct remote controller."""
if not user_data:
user_data = {'owner': f'{ANONYMOUS_SESSION} session', 'name': f'{ANONYMOUS_SESSION}', 'token': f'{A... | the_stack_v2_python_sparse | renku/ui/service/controllers/utils/remote_project.py | SwissDataScienceCenter/renku-python | train | 30 |
bec1708975a581c9b0a899f17034f4d5d908db00 | [
"self.embedding_size = embedding_size\nself.utterance_max = utterance_max\nself.num_actions = num_actions\nsuper().__init__()\nself.h1 = nn.Embedding(num_actions, embedding_size)\nself.d2e = nn.Embedding(vocab_size, embedding_size)\nself.rnn = nn.GRUCell(embedding_size, embedding_size)\nself.e2d = nn.Linear(embeddi... | <|body_start_0|>
self.embedding_size = embedding_size
self.utterance_max = utterance_max
self.num_actions = num_actions
super().__init__()
self.h1 = nn.Embedding(num_actions, embedding_size)
self.d2e = nn.Embedding(vocab_size, embedding_size)
self.rnn = nn.GRUCell... | takes in a discrete action (1-in-k), converts to utterance | Speaker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Speaker:
"""takes in a discrete action (1-in-k), converts to utterance"""
def __init__(self, embedding_size, utterance_max, vocab_size, num_actions):
"""Note that vocab_size includes terminator character 0"""
<|body_0|>
def forward(self, actions, global_idxes):
"... | stack_v2_sparse_classes_36k_train_025644 | 16,840 | permissive | [
{
"docstring": "Note that vocab_size includes terminator character 0",
"name": "__init__",
"signature": "def __init__(self, embedding_size, utterance_max, vocab_size, num_actions)"
},
{
"docstring": "This agent will receive the image of the world x might have been sieved. global_idxes too. but g... | 2 | stack_v2_sparse_classes_30k_train_004397 | Implement the Python class `Speaker` described below.
Class description:
takes in a discrete action (1-in-k), converts to utterance
Method signatures and docstrings:
- def __init__(self, embedding_size, utterance_max, vocab_size, num_actions): Note that vocab_size includes terminator character 0
- def forward(self, a... | Implement the Python class `Speaker` described below.
Class description:
takes in a discrete action (1-in-k), converts to utterance
Method signatures and docstrings:
- def __init__(self, embedding_size, utterance_max, vocab_size, num_actions): Note that vocab_size includes terminator character 0
- def forward(self, a... | 0286849d42d56a382820d4118b72cf6585e23160 | <|skeleton|>
class Speaker:
"""takes in a discrete action (1-in-k), converts to utterance"""
def __init__(self, embedding_size, utterance_max, vocab_size, num_actions):
"""Note that vocab_size includes terminator character 0"""
<|body_0|>
def forward(self, actions, global_idxes):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Speaker:
"""takes in a discrete action (1-in-k), converts to utterance"""
def __init__(self, embedding_size, utterance_max, vocab_size, num_actions):
"""Note that vocab_size includes terminator character 0"""
self.embedding_size = embedding_size
self.utterance_max = utterance_max
... | the_stack_v2_python_sparse | mll/run_mll.py | Sandy4321/compositional-inductive-bias | train | 0 |
18d0197d5e7f99f59394ce50735a3f99f7c55b26 | [
"dp = [[0 for _ in range(n)] for _ in range(m)]\nfor i in range(m):\n dp[i][0] = 1\nfor j in range(n):\n dp[0][j] = 1\nfor i in range(1, m):\n for j in range(1, n):\n dp[i][j] = dp[i - 1][j] + dp[i][j - 1]\nprint(dp)\nreturn dp[-1][-1]",
"dp = [1] * n\nfor i in range(1, m):\n for j in range(1, ... | <|body_start_0|>
dp = [[0 for _ in range(n)] for _ in range(m)]
for i in range(m):
dp[i][0] = 1
for j in range(n):
dp[0][j] = 1
for i in range(1, m):
for j in range(1, n):
dp[i][j] = dp[i - 1][j] + dp[i][j - 1]
print(dp)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""动态规划， 空间复杂度O(M * N) 时间复杂度O(M * N) dp[i][j] = dp[i - 1][j] + dp[i][j - 1] :param m: :param n: :return:"""
<|body_0|>
def uniquePaths1(self, m: int, n: int) -> int:
"""根据观察，当前坐标的值只与左边和上面的值相关，和其他无关 :param m: :pa... | stack_v2_sparse_classes_36k_train_025645 | 1,665 | no_license | [
{
"docstring": "动态规划， 空间复杂度O(M * N) 时间复杂度O(M * N) dp[i][j] = dp[i - 1][j] + dp[i][j - 1] :param m: :param n: :return:",
"name": "uniquePaths",
"signature": "def uniquePaths(self, m: int, n: int) -> int"
},
{
"docstring": "根据观察，当前坐标的值只与左边和上面的值相关，和其他无关 :param m: :param n: :return:",
"name": "u... | 2 | stack_v2_sparse_classes_30k_train_007052 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 动态规划， 空间复杂度O(M * N) 时间复杂度O(M * N) dp[i][j] = dp[i - 1][j] + dp[i][j - 1] :param m: :param n: :return:
- def uniquePaths1(self, m: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 动态规划， 空间复杂度O(M * N) 时间复杂度O(M * N) dp[i][j] = dp[i - 1][j] + dp[i][j - 1] :param m: :param n: :return:
- def uniquePaths1(self, m: in... | 9acba92695c06406f12f997a720bfe1deb9464a8 | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""动态规划， 空间复杂度O(M * N) 时间复杂度O(M * N) dp[i][j] = dp[i - 1][j] + dp[i][j - 1] :param m: :param n: :return:"""
<|body_0|>
def uniquePaths1(self, m: int, n: int) -> int:
"""根据观察，当前坐标的值只与左边和上面的值相关，和其他无关 :param m: :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""动态规划， 空间复杂度O(M * N) 时间复杂度O(M * N) dp[i][j] = dp[i - 1][j] + dp[i][j - 1] :param m: :param n: :return:"""
dp = [[0 for _ in range(n)] for _ in range(m)]
for i in range(m):
dp[i][0] = 1
for j in range(n):
... | the_stack_v2_python_sparse | datastructure/dp_exercise/UniquePaths.py | yinhuax/leet_code | train | 0 | |
95db108faa8810da1b4e78c4be66ecd787466d71 | [
"config = Config()\ndirectory = config.agent_cache_directory(PATTOO_API_AGENT_NAME)\nself._batch_id = int(time.time() * 1000)\nself._data = files.read_json_files(directory, die=False, age=age, count=batch_size)\nself.files = len(self._data)",
"_cache = {}\nresult = []\nfor filepath, json_data in sorted(self._data... | <|body_start_0|>
config = Config()
directory = config.agent_cache_directory(PATTOO_API_AGENT_NAME)
self._batch_id = int(time.time() * 1000)
self._data = files.read_json_files(directory, die=False, age=age, count=batch_size)
self.files = len(self._data)
<|end_body_0|>
<|body_star... | Process ingest cache data. | Cache | [
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cache:
"""Process ingest cache data."""
def __init__(self, batch_size=500, age=0):
"""Initialize the class. Args: batch_size: Number of files to read age: Minimum age of files to be read per batch Returns: None"""
<|body_0|>
def records(self):
"""Create PattooDBr... | stack_v2_sparse_classes_36k_train_025646 | 8,665 | permissive | [
{
"docstring": "Initialize the class. Args: batch_size: Number of files to read age: Minimum age of files to be read per batch Returns: None",
"name": "__init__",
"signature": "def __init__(self, batch_size=500, age=0)"
},
{
"docstring": "Create PattooDBrecord objects from cache directory. Args:... | 4 | null | Implement the Python class `Cache` described below.
Class description:
Process ingest cache data.
Method signatures and docstrings:
- def __init__(self, batch_size=500, age=0): Initialize the class. Args: batch_size: Number of files to read age: Minimum age of files to be read per batch Returns: None
- def records(se... | Implement the Python class `Cache` described below.
Class description:
Process ingest cache data.
Method signatures and docstrings:
- def __init__(self, batch_size=500, age=0): Initialize the class. Args: batch_size: Number of files to read age: Minimum age of files to be read per batch Returns: None
- def records(se... | 57bd3e82e49d51e3426b13ad53ed8326a735ce29 | <|skeleton|>
class Cache:
"""Process ingest cache data."""
def __init__(self, batch_size=500, age=0):
"""Initialize the class. Args: batch_size: Number of files to read age: Minimum age of files to be read per batch Returns: None"""
<|body_0|>
def records(self):
"""Create PattooDBr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cache:
"""Process ingest cache data."""
def __init__(self, batch_size=500, age=0):
"""Initialize the class. Args: batch_size: Number of files to read age: Minimum age of files to be read per batch Returns: None"""
config = Config()
directory = config.agent_cache_directory(PATTOO_A... | the_stack_v2_python_sparse | pattoo/ingest/files.py | palisadoes/pattoo | train | 0 |
7a5a7bd6c640be015635d1ebcce9f243eb59337d | [
"super(LCALayer, self).__init__()\nrequire_grad = False\nself.leak = leak\nself.competition = competition\nself.self_excitation = self_excitation\nself.noise = noise\nself.time_step_size = time_step_size\nself.non_decision_time = non_decision_time\nself._sqrt_step_size = torch.sqrt(torch.tensor(0.001, requires_grad... | <|body_start_0|>
super(LCALayer, self).__init__()
require_grad = False
self.leak = leak
self.competition = competition
self.self_excitation = self_excitation
self.noise = noise
self.time_step_size = time_step_size
self.non_decision_time = non_decision_time... | LCALayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LCALayer:
def __init__(self, threshold: Union[float, None]=1.0, leak: float=0.1, competition: float=0.1, self_excitation: float=0.0, non_decision_time: float=0.0, activation_function: Callable=torch.relu, noise: Union[float, torch.Tensor, None]=1.0, time_step_size: float=0.01):
"""Args: ... | stack_v2_sparse_classes_36k_train_025647 | 12,763 | permissive | [
{
"docstring": "Args: threshold: The threshold that accumulators must reach to stop integration. If None, accumulators will never stop integrating even when the pass the threshold. leak: The decay rate, which reflects leakage of the activation. competition: The weight to apply for inhibitory influence from othe... | 2 | stack_v2_sparse_classes_30k_train_004642 | Implement the Python class `LCALayer` described below.
Class description:
Implement the LCALayer class.
Method signatures and docstrings:
- def __init__(self, threshold: Union[float, None]=1.0, leak: float=0.1, competition: float=0.1, self_excitation: float=0.0, non_decision_time: float=0.0, activation_function: Call... | Implement the Python class `LCALayer` described below.
Class description:
Implement the LCALayer class.
Method signatures and docstrings:
- def __init__(self, threshold: Union[float, None]=1.0, leak: float=0.1, competition: float=0.1, self_excitation: float=0.0, non_decision_time: float=0.0, activation_function: Call... | 424971b04d55a2cddbae4c05a0aae2d7b3502c20 | <|skeleton|>
class LCALayer:
def __init__(self, threshold: Union[float, None]=1.0, leak: float=0.1, competition: float=0.1, self_excitation: float=0.0, non_decision_time: float=0.0, activation_function: Callable=torch.relu, noise: Union[float, torch.Tensor, None]=1.0, time_step_size: float=0.01):
"""Args: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LCALayer:
def __init__(self, threshold: Union[float, None]=1.0, leak: float=0.1, competition: float=0.1, self_excitation: float=0.0, non_decision_time: float=0.0, activation_function: Callable=torch.relu, noise: Union[float, torch.Tensor, None]=1.0, time_step_size: float=0.01):
"""Args: threshold: The... | the_stack_v2_python_sparse | Scripts/Debug/stability_flexibility/pytorch_lca.py | PrincetonUniversity/PsyNeuLink | train | 79 | |
92942f69195622cb3268a1ee33d3d1bb9e93bbeb | [
"super().__init__()\nnout_new = nout - nin\nself.eesp = VGGBlock(nin, nout_new, stride=2, down_method='avg')\nself.avg = nn.AvgPool2d(kernel_size=3, padding=1, stride=2)\nif reinf:\n self.inp_reinf = nn.Sequential(CBR(config_inp_reinf, config_inp_reinf, 3, 1), CB(config_inp_reinf, nout, 1, 1))\nself.act = nn.PRe... | <|body_start_0|>
super().__init__()
nout_new = nout - nin
self.eesp = VGGBlock(nin, nout_new, stride=2, down_method='avg')
self.avg = nn.AvgPool2d(kernel_size=3, padding=1, stride=2)
if reinf:
self.inp_reinf = nn.Sequential(CBR(config_inp_reinf, config_inp_reinf, 3, 1... | Down-sampling fucntion that has three parallel branches: (1) avg pooling, (2) EESP block with stride of 2 and (3) efficient long-range connection with the input. The output feature maps of branches from (1) and (2) are concatenated and then additively fused with (3) to produce the final output. | DownSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DownSampler:
"""Down-sampling fucntion that has three parallel branches: (1) avg pooling, (2) EESP block with stride of 2 and (3) efficient long-range connection with the input. The output feature maps of branches from (1) and (2) are concatenated and then additively fused with (3) to produce the... | stack_v2_sparse_classes_36k_train_025648 | 8,682 | permissive | [
{
"docstring": ":param nin: number of input channels :param nout: number of output channels :param k: # of parallel branches :param r_lim: A maximum value of receptive field allowed for EESP block :param reinf: Use long range shortcut connection with the input or not.",
"name": "__init__",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_006162 | Implement the Python class `DownSampler` described below.
Class description:
Down-sampling fucntion that has three parallel branches: (1) avg pooling, (2) EESP block with stride of 2 and (3) efficient long-range connection with the input. The output feature maps of branches from (1) and (2) are concatenated and then a... | Implement the Python class `DownSampler` described below.
Class description:
Down-sampling fucntion that has three parallel branches: (1) avg pooling, (2) EESP block with stride of 2 and (3) efficient long-range connection with the input. The output feature maps of branches from (1) and (2) are concatenated and then a... | d00a290cb1c86cb079acef69f914805737cb3696 | <|skeleton|>
class DownSampler:
"""Down-sampling fucntion that has three parallel branches: (1) avg pooling, (2) EESP block with stride of 2 and (3) efficient long-range connection with the input. The output feature maps of branches from (1) and (2) are concatenated and then additively fused with (3) to produce the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DownSampler:
"""Down-sampling fucntion that has three parallel branches: (1) avg pooling, (2) EESP block with stride of 2 and (3) efficient long-range connection with the input. The output feature maps of branches from (1) and (2) are concatenated and then additively fused with (3) to produce the final output... | the_stack_v2_python_sparse | affspec/models/vgg.py | BeibinLi/affspec | train | 0 |
fcf437862b7f1393ea00a41c133cae5ac445f875 | [
"far = 0\ncur = 0\nl = 0\nfor h in hours:\n if h > 8:\n cur += 1\n else:\n cur -= 1\n if cur > 0:\n l += 1\n else:\n cur = 0\n l = 0\n far = max(far, l)\nreturn far",
"totals = [0]\nfor i in hours:\n if i > 8:\n a = 1\n else:\n a = -1\n tota... | <|body_start_0|>
far = 0
cur = 0
l = 0
for h in hours:
if h > 8:
cur += 1
else:
cur -= 1
if cur > 0:
l += 1
else:
cur = 0
l = 0
far = max(far, l)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestWPI(self, hours):
""":type hours: List[int] :rtype: int"""
<|body_0|>
def longestWPI(self, hours):
""":type hours: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
far = 0
cur = 0
l = 0
... | stack_v2_sparse_classes_36k_train_025649 | 1,066 | no_license | [
{
"docstring": ":type hours: List[int] :rtype: int",
"name": "longestWPI",
"signature": "def longestWPI(self, hours)"
},
{
"docstring": ":type hours: List[int] :rtype: int",
"name": "longestWPI",
"signature": "def longestWPI(self, hours)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestWPI(self, hours): :type hours: List[int] :rtype: int
- def longestWPI(self, hours): :type hours: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestWPI(self, hours): :type hours: List[int] :rtype: int
- def longestWPI(self, hours): :type hours: List[int] :rtype: int
<|skeleton|>
class Solution:
def longestWP... | d8ed762d1005975f0de4f07760c9671195621c88 | <|skeleton|>
class Solution:
def longestWPI(self, hours):
""":type hours: List[int] :rtype: int"""
<|body_0|>
def longestWPI(self, hours):
""":type hours: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestWPI(self, hours):
""":type hours: List[int] :rtype: int"""
far = 0
cur = 0
l = 0
for h in hours:
if h > 8:
cur += 1
else:
cur -= 1
if cur > 0:
l += 1
els... | the_stack_v2_python_sparse | longest-well-performing-interval/solution.py | uxlsl/leetcode_practice | train | 0 | |
6c3b0896585a2b834791b7db54084116cb9587fc | [
"self.ide = identity_element\nself.lide = lazy_ide\nself.func = segfunc\nn = len(ls)\nself.num = 2 ** (n - 1).bit_length()\nself.tree = [self.ide] * (2 * self.num)\nself.lazy = [self.lide] * (2 * self.num)\nfor i, l in enumerate(ls):\n self.tree[i + self.num - 1] = l\nfor i in range(self.num - 2, -1, -1):\n s... | <|body_start_0|>
self.ide = identity_element
self.lide = lazy_ide
self.func = segfunc
n = len(ls)
self.num = 2 ** (n - 1).bit_length()
self.tree = [self.ide] * (2 * self.num)
self.lazy = [self.lide] * (2 * self.num)
for i, l in enumerate(ls):
s... | SegmentTreeForRMQandRUQ | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegmentTreeForRMQandRUQ:
def __init__(self, ls: list, segfunc=min, identity_element=2 ** 63, lazy_ide=None):
"""セグ木 一次元のリストlsを受け取り初期化する。O(len(ls)) 区間のルールはsegfuncによって定義される identity elementは単位元。e.g., 最小値を求めたい→inf, 和→0, 積→1, gcd→0 [単位元](https://ja.wikipedia.org/wiki/%E5%8D%98%E4%BD%8D%E5%85... | stack_v2_sparse_classes_36k_train_025650 | 23,273 | no_license | [
{
"docstring": "セグ木 一次元のリストlsを受け取り初期化する。O(len(ls)) 区間のルールはsegfuncによって定義される identity elementは単位元。e.g., 最小値を求めたい→inf, 和→0, 積→1, gcd→0 [単位元](https://ja.wikipedia.org/wiki/%E5%8D%98%E4%BD%8D%E5%85%83)",
"name": "__init__",
"signature": "def __init__(self, ls: list, segfunc=min, identity_element=2 ** 63, laz... | 4 | null | Implement the Python class `SegmentTreeForRMQandRUQ` described below.
Class description:
Implement the SegmentTreeForRMQandRUQ class.
Method signatures and docstrings:
- def __init__(self, ls: list, segfunc=min, identity_element=2 ** 63, lazy_ide=None): セグ木 一次元のリストlsを受け取り初期化する。O(len(ls)) 区間のルールはsegfuncによって定義される ident... | Implement the Python class `SegmentTreeForRMQandRUQ` described below.
Class description:
Implement the SegmentTreeForRMQandRUQ class.
Method signatures and docstrings:
- def __init__(self, ls: list, segfunc=min, identity_element=2 ** 63, lazy_ide=None): セグ木 一次元のリストlsを受け取り初期化する。O(len(ls)) 区間のルールはsegfuncによって定義される ident... | 74915a40ac157f89fe400e3f98e9bf3c10012cd7 | <|skeleton|>
class SegmentTreeForRMQandRUQ:
def __init__(self, ls: list, segfunc=min, identity_element=2 ** 63, lazy_ide=None):
"""セグ木 一次元のリストlsを受け取り初期化する。O(len(ls)) 区間のルールはsegfuncによって定義される identity elementは単位元。e.g., 最小値を求めたい→inf, 和→0, 積→1, gcd→0 [単位元](https://ja.wikipedia.org/wiki/%E5%8D%98%E4%BD%8D%E5%85... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SegmentTreeForRMQandRUQ:
def __init__(self, ls: list, segfunc=min, identity_element=2 ** 63, lazy_ide=None):
"""セグ木 一次元のリストlsを受け取り初期化する。O(len(ls)) 区間のルールはsegfuncによって定義される identity elementは単位元。e.g., 最小値を求めたい→inf, 和→0, 積→1, gcd→0 [単位元](https://ja.wikipedia.org/wiki/%E5%8D%98%E4%BD%8D%E5%85%83)"""
... | the_stack_v2_python_sparse | algorithm/SegmentTree.py | masakiaota/kyoupuro | train | 1 | |
19d551af3bfd772b663c03f924486fe33ec262bb | [
"samples = [sample]\nfilter_task = filter_gene_results.s(samples, cls.tool_result_name, top_n)\npersist_signature = persist_task.s(sample['analysis_result'], cls.result_name)\ntask_chain = chain(filter_task, persist_signature)\nresult = task_chain.delay()\nreturn result",
"analysis_result_uuid = sample_group.anal... | <|body_start_0|>
samples = [sample]
filter_task = filter_gene_results.s(samples, cls.tool_result_name, top_n)
persist_signature = persist_task.s(sample['analysis_result'], cls.result_name)
task_chain = chain(filter_task, persist_signature)
result = task_chain.delay()
retu... | Tasks for generating virulence results. | GenericGeneWrangler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenericGeneWrangler:
"""Tasks for generating virulence results."""
def help_run_generic_sample(cls, sample, top_n, persist_task):
"""Gather single sample and process."""
<|body_0|>
def help_run_generic_gene_group(cls, sample_group, samples, top_n, persist_task):
... | stack_v2_sparse_classes_36k_train_025651 | 1,502 | permissive | [
{
"docstring": "Gather single sample and process.",
"name": "help_run_generic_sample",
"signature": "def help_run_generic_sample(cls, sample, top_n, persist_task)"
},
{
"docstring": "Gather and process samples.",
"name": "help_run_generic_gene_group",
"signature": "def help_run_generic_g... | 2 | stack_v2_sparse_classes_30k_train_001465 | Implement the Python class `GenericGeneWrangler` described below.
Class description:
Tasks for generating virulence results.
Method signatures and docstrings:
- def help_run_generic_sample(cls, sample, top_n, persist_task): Gather single sample and process.
- def help_run_generic_gene_group(cls, sample_group, samples... | Implement the Python class `GenericGeneWrangler` described below.
Class description:
Tasks for generating virulence results.
Method signatures and docstrings:
- def help_run_generic_sample(cls, sample, top_n, persist_task): Gather single sample and process.
- def help_run_generic_gene_group(cls, sample_group, samples... | 609cd57c626c857c8efde8237a1f22f4d1e6065d | <|skeleton|>
class GenericGeneWrangler:
"""Tasks for generating virulence results."""
def help_run_generic_sample(cls, sample, top_n, persist_task):
"""Gather single sample and process."""
<|body_0|>
def help_run_generic_gene_group(cls, sample_group, samples, top_n, persist_task):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenericGeneWrangler:
"""Tasks for generating virulence results."""
def help_run_generic_sample(cls, sample, top_n, persist_task):
"""Gather single sample and process."""
samples = [sample]
filter_task = filter_gene_results.s(samples, cls.tool_result_name, top_n)
persist_si... | the_stack_v2_python_sparse | app/display_modules/generic_gene_set/wrangler.py | MetaGenScope/metagenscope-server | train | 0 |
392ff58f88c21793686ad0f92b2f2ec8b8acc3cf | [
"if not self.name and self.path:\n self.name = filter_repo_name(Path(self.path).name)\nself.slug = normalize_to_ascii(self.name)",
"if not is_ascii(href):\n raise UnicodeError(f'`{href}` is not a valid Git remote')\nurl_regexes = _REPOSITORY_URLS\ngitlab_url = os.environ.get('GITLAB_BASE_URL', None)\nif git... | <|body_start_0|>
if not self.name and self.path:
self.name = filter_repo_name(Path(self.path).name)
self.slug = normalize_to_ascii(self.name)
<|end_body_0|>
<|body_start_1|>
if not is_ascii(href):
raise UnicodeError(f'`{href}` is not a valid Git remote')
url_rege... | Parser for common Git URLs. | GitURL | [
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GitURL:
"""Parser for common Git URLs."""
def __attrs_post_init__(self):
"""Derive basic information."""
<|body_0|>
def parse(cls, href) -> 'GitURL':
"""Derive URI components."""
<|body_1|>
def instance_url(self):
"""Get the url of the git in... | stack_v2_sparse_classes_36k_train_025652 | 5,059 | permissive | [
{
"docstring": "Derive basic information.",
"name": "__attrs_post_init__",
"signature": "def __attrs_post_init__(self)"
},
{
"docstring": "Derive URI components.",
"name": "parse",
"signature": "def parse(cls, href) -> 'GitURL'"
},
{
"docstring": "Get the url of the git instance.... | 4 | null | Implement the Python class `GitURL` described below.
Class description:
Parser for common Git URLs.
Method signatures and docstrings:
- def __attrs_post_init__(self): Derive basic information.
- def parse(cls, href) -> 'GitURL': Derive URI components.
- def instance_url(self): Get the url of the git instance.
- def i... | Implement the Python class `GitURL` described below.
Class description:
Parser for common Git URLs.
Method signatures and docstrings:
- def __attrs_post_init__(self): Derive basic information.
- def parse(cls, href) -> 'GitURL': Derive URI components.
- def instance_url(self): Get the url of the git instance.
- def i... | e0ff587f507d049eeeb873e8488ba8bb10ac1a15 | <|skeleton|>
class GitURL:
"""Parser for common Git URLs."""
def __attrs_post_init__(self):
"""Derive basic information."""
<|body_0|>
def parse(cls, href) -> 'GitURL':
"""Derive URI components."""
<|body_1|>
def instance_url(self):
"""Get the url of the git in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GitURL:
"""Parser for common Git URLs."""
def __attrs_post_init__(self):
"""Derive basic information."""
if not self.name and self.path:
self.name = filter_repo_name(Path(self.path).name)
self.slug = normalize_to_ascii(self.name)
def parse(cls, href) -> 'GitURL':
... | the_stack_v2_python_sparse | renku/domain_model/git.py | SwissDataScienceCenter/renku-python | train | 30 |
793dc852a1128d3a11be4b305f63a7e7d303057b | [
"self.summary_file = []\nself.path_params = []\nif release in ['DR17', 'MPL-11']:\n files = ['GZD_auto', 'gzUKIDSS', 'gz']\n version_DR17 = {'GZD_auto': 'v1_0_1', 'gzUKIDSS': 'v1_0_1', 'gz': 'v2_0_1'}\n for file in files:\n params = {'file': file, 'ver': version_DR17[file]}\n self.path_params... | <|body_start_0|>
self.summary_file = []
self.path_params = []
if release in ['DR17', 'MPL-11']:
files = ['GZD_auto', 'gzUKIDSS', 'gz']
version_DR17 = {'GZD_auto': 'v1_0_1', 'gzUKIDSS': 'v1_0_1', 'gz': 'v2_0_1'}
for file in files:
params = {'fil... | Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (GZ) data for SDSS galaxies has bee... | GZVAC | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GZVAC:
"""Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (G... | stack_v2_sparse_classes_36k_train_025653 | 5,257 | permissive | [
{
"docstring": "Sets the path to the GalaxyZoo summary file. Sets the paths to the GalaxyZoom summary file(s). For DR15 this is a single summary file, while for DR17, this has been split into three files, so ``self.summary_file`` and ``self.path_params`` return lists for DR17.",
"name": "set_summary_file",
... | 2 | stack_v2_sparse_classes_30k_train_003244 | Implement the Python class `GZVAC` described below.
Class description:
Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morpholog... | Implement the Python class `GZVAC` described below.
Class description:
Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morpholog... | db4c536a65fb2f16fee05a4f34996a7fd35f0527 | <|skeleton|>
class GZVAC:
"""Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (G... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GZVAC:
"""Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (GZ) data for S... | the_stack_v2_python_sparse | python/marvin/contrib/vacs/galaxyzoo.py | sdss/marvin | train | 56 |
779ae7d01395d19afa0dbde3c54428f5919fe12e | [
"power = None\nrqt_url = self.server_conf['base_url']\nrqt_url += '/rpc/getpowerstat.asp'\ncookies = {'SessionCookie': session}\nself.log.debug('[%s]: Getting power at %s', self.name, rqt_url)\nresponse = requests.get(rqt_url, cookies=cookies, verify=False)\nif response.status_code == 200:\n json_str = self.clea... | <|body_start_0|>
power = None
rqt_url = self.server_conf['base_url']
rqt_url += '/rpc/getpowerstat.asp'
cookies = {'SessionCookie': session}
self.log.debug('[%s]: Getting power at %s', self.name, rqt_url)
response = requests.get(rqt_url, cookies=cookies, verify=False)
... | Collect power consumption via DELL INTEL GUI/API. | INTELGUICollector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class INTELGUICollector:
"""Collect power consumption via DELL INTEL GUI/API."""
def get_intel_power(self, session):
"""Get Power value form INTEL."""
<|body_0|>
def clean_json(self, str_json, var_name):
"""Clean returned pseudo JSON by Intel Web Console."""
<|... | stack_v2_sparse_classes_36k_train_025654 | 5,677 | no_license | [
{
"docstring": "Get Power value form INTEL.",
"name": "get_intel_power",
"signature": "def get_intel_power(self, session)"
},
{
"docstring": "Clean returned pseudo JSON by Intel Web Console.",
"name": "clean_json",
"signature": "def clean_json(self, str_json, var_name)"
},
{
"doc... | 5 | stack_v2_sparse_classes_30k_val_000853 | Implement the Python class `INTELGUICollector` described below.
Class description:
Collect power consumption via DELL INTEL GUI/API.
Method signatures and docstrings:
- def get_intel_power(self, session): Get Power value form INTEL.
- def clean_json(self, str_json, var_name): Clean returned pseudo JSON by Intel Web C... | Implement the Python class `INTELGUICollector` described below.
Class description:
Collect power consumption via DELL INTEL GUI/API.
Method signatures and docstrings:
- def get_intel_power(self, session): Get Power value form INTEL.
- def clean_json(self, str_json, var_name): Clean returned pseudo JSON by Intel Web C... | a872f095f256b0dd63d292301426f0a807c04abb | <|skeleton|>
class INTELGUICollector:
"""Collect power consumption via DELL INTEL GUI/API."""
def get_intel_power(self, session):
"""Get Power value form INTEL."""
<|body_0|>
def clean_json(self, str_json, var_name):
"""Clean returned pseudo JSON by Intel Web Console."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class INTELGUICollector:
"""Collect power consumption via DELL INTEL GUI/API."""
def get_intel_power(self, session):
"""Get Power value form INTEL."""
power = None
rqt_url = self.server_conf['base_url']
rqt_url += '/rpc/getpowerstat.asp'
cookies = {'SessionCookie': sessi... | the_stack_v2_python_sparse | server-collector/collectors/power/intel_gui_collector.py | bherard/energyrecorder | train | 2 |
073bcb2e6b33b8e0dff49321fe20eb755b27092c | [
"self.active_directories = active_directories\nself.all = all\nself.clusters = clusters\nself.file = file\nself.groups = groups\nself.partitions = partitions\nself.principal_sources = principal_sources\nself.protection_jobs = protection_jobs\nself.protection_policies = protection_policies\nself.protection_sources =... | <|body_start_0|>
self.active_directories = active_directories
self.all = all
self.clusters = clusters
self.file = file
self.groups = groups
self.partitions = partitions
self.principal_sources = principal_sources
self.protection_jobs = protection_jobs
... | Implementation of the 'ImportConfigurations' model. ImportConfigurations struct used for ImportConfig endpoint. This is the form of the request. Attributes: active_directories (list of string): Selective import of active directories. all (list of string): List of which entities to import all. clusters (list of long|int... | ImportConfigurations | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImportConfigurations:
"""Implementation of the 'ImportConfigurations' model. ImportConfigurations struct used for ImportConfig endpoint. This is the form of the request. Attributes: active_directories (list of string): Selective import of active directories. all (list of string): List of which en... | stack_v2_sparse_classes_36k_train_025655 | 5,519 | permissive | [
{
"docstring": "Constructor for the ImportConfigurations class",
"name": "__init__",
"signature": "def __init__(self, active_directories=None, all=None, clusters=None, file=None, groups=None, partitions=None, principal_sources=None, protection_jobs=None, protection_policies=None, protection_sources=None... | 2 | null | Implement the Python class `ImportConfigurations` described below.
Class description:
Implementation of the 'ImportConfigurations' model. ImportConfigurations struct used for ImportConfig endpoint. This is the form of the request. Attributes: active_directories (list of string): Selective import of active directories.... | Implement the Python class `ImportConfigurations` described below.
Class description:
Implementation of the 'ImportConfigurations' model. ImportConfigurations struct used for ImportConfig endpoint. This is the form of the request. Attributes: active_directories (list of string): Selective import of active directories.... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ImportConfigurations:
"""Implementation of the 'ImportConfigurations' model. ImportConfigurations struct used for ImportConfig endpoint. This is the form of the request. Attributes: active_directories (list of string): Selective import of active directories. all (list of string): List of which en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImportConfigurations:
"""Implementation of the 'ImportConfigurations' model. ImportConfigurations struct used for ImportConfig endpoint. This is the form of the request. Attributes: active_directories (list of string): Selective import of active directories. all (list of string): List of which entities to imp... | the_stack_v2_python_sparse | cohesity_management_sdk/models/import_configurations.py | cohesity/management-sdk-python | train | 24 |
88bd740155449e770a6ef7688cb0a67d0f33730a | [
"self.expand_filters = {x.lower(): (x not in use_expand_hidden, x) for x in use_expand}\nself.use_expand = use_expand\nself.use_expand_hidden = use_expand_hidden\nself.known_flags = {}",
"ue_dict = {}\nusel = []\nef = self.expand_filters\nkf = self.known_flags\nfor flag in use:\n data = kf.get(flag)\n if da... | <|body_start_0|>
self.expand_filters = {x.lower(): (x not in use_expand_hidden, x) for x in use_expand}
self.use_expand = use_expand
self.use_expand_hidden = use_expand_hidden
self.known_flags = {}
<|end_body_0|>
<|body_start_1|>
ue_dict = {}
usel = []
ef = self.... | use_expand_filter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class use_expand_filter:
def __init__(self, use_expand, use_expand_hidden):
""":type use_expand: iterable of strings :param use_expand: names of use-expanded variables. :type use_expand_hidden: set of strings :param use_expand_hidden: names of use-expanded vars that should not be added to the ... | stack_v2_sparse_classes_36k_train_025656 | 21,000 | permissive | [
{
"docstring": ":type use_expand: iterable of strings :param use_expand: names of use-expanded variables. :type use_expand_hidden: set of strings :param use_expand_hidden: names of use-expanded vars that should not be added to the dict.",
"name": "__init__",
"signature": "def __init__(self, use_expand, ... | 2 | stack_v2_sparse_classes_30k_train_016731 | Implement the Python class `use_expand_filter` described below.
Class description:
Implement the use_expand_filter class.
Method signatures and docstrings:
- def __init__(self, use_expand, use_expand_hidden): :type use_expand: iterable of strings :param use_expand: names of use-expanded variables. :type use_expand_hi... | Implement the Python class `use_expand_filter` described below.
Class description:
Implement the use_expand_filter class.
Method signatures and docstrings:
- def __init__(self, use_expand, use_expand_hidden): :type use_expand: iterable of strings :param use_expand: names of use-expanded variables. :type use_expand_hi... | ad4c3d51a2aff49ed898382c58baa852f47e17b9 | <|skeleton|>
class use_expand_filter:
def __init__(self, use_expand, use_expand_hidden):
""":type use_expand: iterable of strings :param use_expand: names of use-expanded variables. :type use_expand_hidden: set of strings :param use_expand_hidden: names of use-expanded vars that should not be added to the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class use_expand_filter:
def __init__(self, use_expand, use_expand_hidden):
""":type use_expand: iterable of strings :param use_expand: names of use-expanded variables. :type use_expand_hidden: set of strings :param use_expand_hidden: names of use-expanded vars that should not be added to the dict."""
... | the_stack_v2_python_sparse | src/pkgcore/ebuild/formatter.py | pkgcore/pkgcore | train | 107 | |
19eba7f6d685ad9ced4caed6f71b2d671bfccada | [
"resp = self.client.get(reverse('music_collection:delete_collection'))\nself.assertRedirects(resp, reverse('accounts:login') + '?next=' + reverse('music_collection:delete_collection'))\nself.login('user')\ntrack = MusicTrack(title='to be deleted', user=self.user)\ntrack.save()\nresp = self.client.post(reverse('musi... | <|body_start_0|>
resp = self.client.get(reverse('music_collection:delete_collection'))
self.assertRedirects(resp, reverse('accounts:login') + '?next=' + reverse('music_collection:delete_collection'))
self.login('user')
track = MusicTrack(title='to be deleted', user=self.user)
tra... | Test behaviour related to account POST method | TestAccountMethod | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAccountMethod:
"""Test behaviour related to account POST method"""
def test_user_track_deletion(self):
"""Verify that track deletion works correctly"""
<|body_0|>
def test_user_account_deletion(self):
"""Verify that account deletion behaves as expected"""
... | stack_v2_sparse_classes_36k_train_025657 | 3,810 | no_license | [
{
"docstring": "Verify that track deletion works correctly",
"name": "test_user_track_deletion",
"signature": "def test_user_track_deletion(self)"
},
{
"docstring": "Verify that account deletion behaves as expected",
"name": "test_user_account_deletion",
"signature": "def test_user_accou... | 2 | stack_v2_sparse_classes_30k_train_017636 | Implement the Python class `TestAccountMethod` described below.
Class description:
Test behaviour related to account POST method
Method signatures and docstrings:
- def test_user_track_deletion(self): Verify that track deletion works correctly
- def test_user_account_deletion(self): Verify that account deletion behav... | Implement the Python class `TestAccountMethod` described below.
Class description:
Test behaviour related to account POST method
Method signatures and docstrings:
- def test_user_track_deletion(self): Verify that track deletion works correctly
- def test_user_account_deletion(self): Verify that account deletion behav... | e2d6a0336c7934cae71f833cb34a1f5f21db2d02 | <|skeleton|>
class TestAccountMethod:
"""Test behaviour related to account POST method"""
def test_user_track_deletion(self):
"""Verify that track deletion works correctly"""
<|body_0|>
def test_user_account_deletion(self):
"""Verify that account deletion behaves as expected"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAccountMethod:
"""Test behaviour related to account POST method"""
def test_user_track_deletion(self):
"""Verify that track deletion works correctly"""
resp = self.client.get(reverse('music_collection:delete_collection'))
self.assertRedirects(resp, reverse('accounts:login') + ... | the_stack_v2_python_sparse | accounts/tests_views.py | gbip/djRDO | train | 3 |
6d2ae52ab67cbbead0a4a8d76e3caf238532b57c | [
"filters = dict(request.args)\npage = int(filters.pop('page', 1))\nlimit = int(filters.pop('limit', 2))\npaginated_users = UserModel.query.paginate(page, limit, error_out=False)\nresponse = create_pagination(items=paginated_users, schema=user_short_list_schema, page=page, limit=limit, query_params=filters, base_url... | <|body_start_0|>
filters = dict(request.args)
page = int(filters.pop('page', 1))
limit = int(filters.pop('limit', 2))
paginated_users = UserModel.query.paginate(page, limit, error_out=False)
response = create_pagination(items=paginated_users, schema=user_short_list_schema, page=p... | Resource for retrieving exists and adding new users | UserList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserList:
"""Resource for retrieving exists and adding new users"""
def get(cls) -> Tuple[Dict, int]:
"""Method for retrieving list of all Users Returns ------- Tuple[Dict, int] Response message and status code"""
<|body_0|>
def post(cls):
"""Method for creating ... | stack_v2_sparse_classes_36k_train_025658 | 5,979 | no_license | [
{
"docstring": "Method for retrieving list of all Users Returns ------- Tuple[Dict, int] Response message and status code",
"name": "get",
"signature": "def get(cls) -> Tuple[Dict, int]"
},
{
"docstring": "Method for creating new User Returns ------- Tuple[Dict, int] Response message and status ... | 2 | stack_v2_sparse_classes_30k_train_019863 | Implement the Python class `UserList` described below.
Class description:
Resource for retrieving exists and adding new users
Method signatures and docstrings:
- def get(cls) -> Tuple[Dict, int]: Method for retrieving list of all Users Returns ------- Tuple[Dict, int] Response message and status code
- def post(cls):... | Implement the Python class `UserList` described below.
Class description:
Resource for retrieving exists and adding new users
Method signatures and docstrings:
- def get(cls) -> Tuple[Dict, int]: Method for retrieving list of all Users Returns ------- Tuple[Dict, int] Response message and status code
- def post(cls):... | 51e4d69f88c120cfc587fd007f21528a7bd661a0 | <|skeleton|>
class UserList:
"""Resource for retrieving exists and adding new users"""
def get(cls) -> Tuple[Dict, int]:
"""Method for retrieving list of all Users Returns ------- Tuple[Dict, int] Response message and status code"""
<|body_0|>
def post(cls):
"""Method for creating ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserList:
"""Resource for retrieving exists and adding new users"""
def get(cls) -> Tuple[Dict, int]:
"""Method for retrieving list of all Users Returns ------- Tuple[Dict, int] Response message and status code"""
filters = dict(request.args)
page = int(filters.pop('page', 1))
... | the_stack_v2_python_sparse | flask_app/resources/user.py | Kyrylo-Kotelevets/Flask_Events | train | 0 |
6bdc62e4e294afedd8066db2a224373c030a7c6f | [
"super(ProtocolMapperTestBase, self).setUp()\nself.Reinitialize(path_method='my_method', content_type='application/x-google-protobuf')\nself.request_message = Request1()\nself.request_message.integer_field = 1\nself.request_message.string_field = u'something'\nself.request_message.enum_field = Enum1.VAL1\nself.resp... | <|body_start_0|>
super(ProtocolMapperTestBase, self).setUp()
self.Reinitialize(path_method='my_method', content_type='application/x-google-protobuf')
self.request_message = Request1()
self.request_message.integer_field = 1
self.request_message.string_field = u'something'
... | Base class for basic protocol mapper tests. | ProtocolMapperTestBase | [
"Apache-2.0",
"BSD-3-Clause",
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtocolMapperTestBase:
"""Base class for basic protocol mapper tests."""
def setUp(self):
"""Reinitialize test specifically for protocol buffer mapper."""
<|body_0|>
def testBuildRequest(self):
"""Test request building."""
<|body_1|>
def testBuildRe... | stack_v2_sparse_classes_36k_train_025659 | 46,517 | permissive | [
{
"docstring": "Reinitialize test specifically for protocol buffer mapper.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test request building.",
"name": "testBuildRequest",
"signature": "def testBuildRequest(self)"
},
{
"docstring": "Test response building... | 4 | stack_v2_sparse_classes_30k_train_011538 | Implement the Python class `ProtocolMapperTestBase` described below.
Class description:
Base class for basic protocol mapper tests.
Method signatures and docstrings:
- def setUp(self): Reinitialize test specifically for protocol buffer mapper.
- def testBuildRequest(self): Test request building.
- def testBuildRespon... | Implement the Python class `ProtocolMapperTestBase` described below.
Class description:
Base class for basic protocol mapper tests.
Method signatures and docstrings:
- def setUp(self): Reinitialize test specifically for protocol buffer mapper.
- def testBuildRequest(self): Test request building.
- def testBuildRespon... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ProtocolMapperTestBase:
"""Base class for basic protocol mapper tests."""
def setUp(self):
"""Reinitialize test specifically for protocol buffer mapper."""
<|body_0|>
def testBuildRequest(self):
"""Test request building."""
<|body_1|>
def testBuildRe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtocolMapperTestBase:
"""Base class for basic protocol mapper tests."""
def setUp(self):
"""Reinitialize test specifically for protocol buffer mapper."""
super(ProtocolMapperTestBase, self).setUp()
self.Reinitialize(path_method='my_method', content_type='application/x-google-pro... | the_stack_v2_python_sparse | third_party/catapult/third_party/gsutil/third_party/protorpc/protorpc/webapp/service_handlers_test.py | metux/chromium-suckless | train | 5 |
fd0fe70f34dc2fbb534ad9a2f078e5f2b8a7922e | [
"n = len(matrix)\ndp = [[0] * n for _ in range(n)]\nfor j in range(n):\n dp[n - 1][j] = matrix[n - 1][j]\nfor i in range(n - 2, -1, -1):\n for j in range(n):\n if j == 0:\n dp[i][j] = matrix[i][j] + min(dp[i + 1][j], dp[i + 1][j + 1])\n elif j == n - 1:\n dp[i][j] = matrix[... | <|body_start_0|>
n = len(matrix)
dp = [[0] * n for _ in range(n)]
for j in range(n):
dp[n - 1][j] = matrix[n - 1][j]
for i in range(n - 2, -1, -1):
for j in range(n):
if j == 0:
dp[i][j] = matrix[i][j] + min(dp[i + 1][j], dp[i +... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minFallingPathSum(self, matrix):
""":type matrix: List[List[int]] :rtype: int"""
<|body_0|>
def minFallingPathSumOnSpace(self, matrix):
""":type matrix: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = le... | stack_v2_sparse_classes_36k_train_025660 | 2,649 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: int",
"name": "minFallingPathSum",
"signature": "def minFallingPathSum(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: int",
"name": "minFallingPathSumOnSpace",
"signature": "def minFallingPathSumOnSpace(self, ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minFallingPathSum(self, matrix): :type matrix: List[List[int]] :rtype: int
- def minFallingPathSumOnSpace(self, matrix): :type matrix: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minFallingPathSum(self, matrix): :type matrix: List[List[int]] :rtype: int
- def minFallingPathSumOnSpace(self, matrix): :type matrix: List[List[int]] :rtype: int
<|skeleton... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def minFallingPathSum(self, matrix):
""":type matrix: List[List[int]] :rtype: int"""
<|body_0|>
def minFallingPathSumOnSpace(self, matrix):
""":type matrix: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minFallingPathSum(self, matrix):
""":type matrix: List[List[int]] :rtype: int"""
n = len(matrix)
dp = [[0] * n for _ in range(n)]
for j in range(n):
dp[n - 1][j] = matrix[n - 1][j]
for i in range(n - 2, -1, -1):
for j in range(n):
... | the_stack_v2_python_sparse | M/MinimumFallingPathSum.py | bssrdf/pyleet | train | 2 | |
b95670ff22b9de6cf668d3774cb43df9d095cd82 | [
"self._privkey = privkey\nself._account = account\nself._messages = messages\nself._sign_mode = sign_mode\nself._fee = fee\nself._memo = memo\nself._chain_id = chain_id\nself._pubkey = privkey_to_pubkey(self._privkey)",
"for m in serialized_messages:\n slot = self._tx.body.messages.add()\n slot.Pack(m, type... | <|body_start_0|>
self._privkey = privkey
self._account = account
self._messages = messages
self._sign_mode = sign_mode
self._fee = fee
self._memo = memo
self._chain_id = chain_id
self._pubkey = privkey_to_pubkey(self._privkey)
<|end_body_0|>
<|body_start_... | A bluzelle transaction. | Transaction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transaction:
"""A bluzelle transaction."""
def __init__(self, *, privkey: bytes, account: Any, messages: List[Message], sign_mode: SignMode, fee: Fee, memo: str=None, chain_id: str='') -> None:
"""Args: privkey: the input private key to sign the raw transaction. account: required to ... | stack_v2_sparse_classes_36k_train_025661 | 6,951 | permissive | [
{
"docstring": "Args: privkey: the input private key to sign the raw transaction. account: required to create the signer data. messages: input bluzelle messages to be included in the transaction. sign_mode: for creating the raw transaction, a :term:`SignModeHandler` with the same supported mode should be used t... | 6 | stack_v2_sparse_classes_30k_train_010254 | Implement the Python class `Transaction` described below.
Class description:
A bluzelle transaction.
Method signatures and docstrings:
- def __init__(self, *, privkey: bytes, account: Any, messages: List[Message], sign_mode: SignMode, fee: Fee, memo: str=None, chain_id: str='') -> None: Args: privkey: the input priva... | Implement the Python class `Transaction` described below.
Class description:
A bluzelle transaction.
Method signatures and docstrings:
- def __init__(self, *, privkey: bytes, account: Any, messages: List[Message], sign_mode: SignMode, fee: Fee, memo: str=None, chain_id: str='') -> None: Args: privkey: the input priva... | c38a07458a36305457680196e8c47372008db5ab | <|skeleton|>
class Transaction:
"""A bluzelle transaction."""
def __init__(self, *, privkey: bytes, account: Any, messages: List[Message], sign_mode: SignMode, fee: Fee, memo: str=None, chain_id: str='') -> None:
"""Args: privkey: the input private key to sign the raw transaction. account: required to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Transaction:
"""A bluzelle transaction."""
def __init__(self, *, privkey: bytes, account: Any, messages: List[Message], sign_mode: SignMode, fee: Fee, memo: str=None, chain_id: str='') -> None:
"""Args: privkey: the input private key to sign the raw transaction. account: required to create the si... | the_stack_v2_python_sparse | bluzelle/cosmos/_transaction.py | hhio618/bluzelle-py | train | 3 |
b6d751bee3e871bce59453d32b8c4bb19b1aa645 | [
"self.parser = reqparse.RequestParser()\nself.parser.add_argument('token')\nsuper(Contract, self).__init__()",
"args = self.parser.parse_args()\ntoken = args['token']\ndata = me.getAllContracts()\nprint('Contract', data)\nl = [o.__dict__ for o in data]\nreturn {'result_code': 'success', 'data': l}"
] | <|body_start_0|>
self.parser = reqparse.RequestParser()
self.parser.add_argument('token')
super(Contract, self).__init__()
<|end_body_0|>
<|body_start_1|>
args = self.parser.parse_args()
token = args['token']
data = me.getAllContracts()
print('Contract', data)
... | 合约 | Contract | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Contract:
"""合约"""
def __init__(self):
"""初始化"""
<|body_0|>
def get(self):
"""查询"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.parser = reqparse.RequestParser()
self.parser.add_argument('token')
super(Contract, self).__ini... | stack_v2_sparse_classes_36k_train_025662 | 24,002 | permissive | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "查询",
"name": "get",
"signature": "def get(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001088 | Implement the Python class `Contract` described below.
Class description:
合约
Method signatures and docstrings:
- def __init__(self): 初始化
- def get(self): 查询 | Implement the Python class `Contract` described below.
Class description:
合约
Method signatures and docstrings:
- def __init__(self): 初始化
- def get(self): 查询
<|skeleton|>
class Contract:
"""合约"""
def __init__(self):
"""初始化"""
<|body_0|>
def get(self):
"""查询"""
<|body_1|>
... | c316649161086da2543d39bf0455d0f793cdd08f | <|skeleton|>
class Contract:
"""合约"""
def __init__(self):
"""初始化"""
<|body_0|>
def get(self):
"""查询"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Contract:
"""合约"""
def __init__(self):
"""初始化"""
self.parser = reqparse.RequestParser()
self.parser.add_argument('token')
super(Contract, self).__init__()
def get(self):
"""查询"""
args = self.parser.parse_args()
token = args['token']
dat... | the_stack_v2_python_sparse | WebTrader/webServer.py | webclinic017/riskBacktestingPlatform | train | 0 |
60eecbc9886dc6e7e022d5c87830e49e1975c31f | [
"self.flavor = flavor\nself.nucleon = nucleon\nself.ip = input_dict",
"self.mp = self.ip['mproton']\nself.mn = self.ip['mneutron']\nif self.nucleon == 'p':\n if self.flavor == 'u':\n return 3 / 4 * self.mp * self.ip['f2up']\n if self.flavor == 'd':\n return 3 / 4 * self.mp * self.ip['f2dp']\n ... | <|body_start_0|>
self.flavor = flavor
self.nucleon = nucleon
self.ip = input_dict
<|end_body_0|>
<|body_start_1|>
self.mp = self.ip['mproton']
self.mn = self.ip['mneutron']
if self.nucleon == 'p':
if self.flavor == 'u':
return 3 / 4 * self.mp ... | FTwist2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FTwist2:
def __init__(self, flavor, nucleon, input_dict):
"""The twist-two nuclear form factors Return the twist-two nuclear form factors Arguments --------- flavor = 'u', 'd', 's', 'g' -- the "quark" flavor (up, down, strange, or gluon contribution) nucleon = 'p', 'n' -- the nucleon (pr... | stack_v2_sparse_classes_36k_train_025663 | 18,337 | permissive | [
{
"docstring": "The twist-two nuclear form factors Return the twist-two nuclear form factors Arguments --------- flavor = 'u', 'd', 's', 'g' -- the \"quark\" flavor (up, down, strange, or gluon contribution) nucleon = 'p', 'n' -- the nucleon (proton or neutron) input_dict (optional) -- a dictionary of hadronic ... | 2 | stack_v2_sparse_classes_30k_train_016070 | Implement the Python class `FTwist2` described below.
Class description:
Implement the FTwist2 class.
Method signatures and docstrings:
- def __init__(self, flavor, nucleon, input_dict): The twist-two nuclear form factors Return the twist-two nuclear form factors Arguments --------- flavor = 'u', 'd', 's', 'g' -- the... | Implement the Python class `FTwist2` described below.
Class description:
Implement the FTwist2 class.
Method signatures and docstrings:
- def __init__(self, flavor, nucleon, input_dict): The twist-two nuclear form factors Return the twist-two nuclear form factors Arguments --------- flavor = 'u', 'd', 's', 'g' -- the... | 4a714e4701f817fdc96e10e461eef7c4756ef71d | <|skeleton|>
class FTwist2:
def __init__(self, flavor, nucleon, input_dict):
"""The twist-two nuclear form factors Return the twist-two nuclear form factors Arguments --------- flavor = 'u', 'd', 's', 'g' -- the "quark" flavor (up, down, strange, or gluon contribution) nucleon = 'p', 'n' -- the nucleon (pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FTwist2:
def __init__(self, flavor, nucleon, input_dict):
"""The twist-two nuclear form factors Return the twist-two nuclear form factors Arguments --------- flavor = 'u', 'd', 's', 'g' -- the "quark" flavor (up, down, strange, or gluon contribution) nucleon = 'p', 'n' -- the nucleon (proton or neutro... | the_stack_v2_python_sparse | directdm/num/single_nucleon_form_factors.py | DirectDM/directdm-py | train | 6 | |
4f82f91ab1f488430fc02cbf2ce83bb80035d80b | [
"if isinstance(key, int):\n return PriorityLevel(key)\nif key not in PriorityLevel._member_map_:\n extend_enum(PriorityLevel, key, default)\nreturn PriorityLevel[key]",
"if not (isinstance(value, int) and 0 <= value <= 7):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nextend_enum(cl... | <|body_start_0|>
if isinstance(key, int):
return PriorityLevel(key)
if key not in PriorityLevel._member_map_:
extend_enum(PriorityLevel, key, default)
return PriorityLevel[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 7):
... | [PriorityLevel] Priority levels defined in IEEE 802.1p. | PriorityLevel | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PriorityLevel:
"""[PriorityLevel] Priority levels defined in IEEE 802.1p."""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_025664 | 1,411 | permissive | [
{
"docstring": "Backport support for original codes.",
"name": "get",
"signature": "def get(key, default=-1)"
},
{
"docstring": "Lookup function used when value is not found.",
"name": "_missing_",
"signature": "def _missing_(cls, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018909 | Implement the Python class `PriorityLevel` described below.
Class description:
[PriorityLevel] Priority levels defined in IEEE 802.1p.
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found. | Implement the Python class `PriorityLevel` described below.
Class description:
[PriorityLevel] Priority levels defined in IEEE 802.1p.
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found.
<|skelet... | 90cd07d67df28d5c5ab0585bc60f467a78d9db33 | <|skeleton|>
class PriorityLevel:
"""[PriorityLevel] Priority levels defined in IEEE 802.1p."""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PriorityLevel:
"""[PriorityLevel] Priority levels defined in IEEE 802.1p."""
def get(key, default=-1):
"""Backport support for original codes."""
if isinstance(key, int):
return PriorityLevel(key)
if key not in PriorityLevel._member_map_:
extend_enum(Priori... | the_stack_v2_python_sparse | pcapkit/const/vlan/priority_level.py | stjordanis/PyPCAPKit | train | 0 |
117a79bd4bcfeaacc71ad35b57d565728415de0c | [
"cache_policy = 'apt-cache policy '\ntry:\n c = cache_policy + str(package['package name'])\n proc = subprocess.Popen(c, shell=True, stdout=subprocess.PIPE)\n shell_output = proc.stdout.read()\nexcept subprocess.CalledProcessError as e:\n shell_output = e.output\nreturn shell_output",
"try:\n subpr... | <|body_start_0|>
cache_policy = 'apt-cache policy '
try:
c = cache_policy + str(package['package name'])
proc = subprocess.Popen(c, shell=True, stdout=subprocess.PIPE)
shell_output = proc.stdout.read()
except subprocess.CalledProcessError as e:
she... | BashConnector | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BashConnector:
def apt_cache(cls, package: {}) -> str:
"""Script uses apt-cache policy (ubuntu program) to gather information for a package (installed or not and version). Assumes that it is installed since any version after 14 has it by default. :param package: json object representing ... | stack_v2_sparse_classes_36k_train_025665 | 2,408 | permissive | [
{
"docstring": "Script uses apt-cache policy (ubuntu program) to gather information for a package (installed or not and version). Assumes that it is installed since any version after 14 has it by default. :param package: json object representing package :return: The output of executed apt-cache policy program."... | 4 | stack_v2_sparse_classes_30k_train_004582 | Implement the Python class `BashConnector` described below.
Class description:
Implement the BashConnector class.
Method signatures and docstrings:
- def apt_cache(cls, package: {}) -> str: Script uses apt-cache policy (ubuntu program) to gather information for a package (installed or not and version). Assumes that i... | Implement the Python class `BashConnector` described below.
Class description:
Implement the BashConnector class.
Method signatures and docstrings:
- def apt_cache(cls, package: {}) -> str: Script uses apt-cache policy (ubuntu program) to gather information for a package (installed or not and version). Assumes that i... | f4e3c2e47aa53f6592a573f840a83e5d2c519f8d | <|skeleton|>
class BashConnector:
def apt_cache(cls, package: {}) -> str:
"""Script uses apt-cache policy (ubuntu program) to gather information for a package (installed or not and version). Assumes that it is installed since any version after 14 has it by default. :param package: json object representing ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BashConnector:
def apt_cache(cls, package: {}) -> str:
"""Script uses apt-cache policy (ubuntu program) to gather information for a package (installed or not and version). Assumes that it is installed since any version after 14 has it by default. :param package: json object representing package :retur... | the_stack_v2_python_sparse | src/bash_connector.py | guve4e/package-installer-ubuntu | train | 1 | |
da94067534fe0d909b4cddfb4a5d47467b9dd595 | [
"global COMPANY_CONN\ncursor = None\ntry:\n cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)\n sql = 'insert into lie_brand(brand_name, brand_desc, site_url)values(%(brand_name)s, %(brand_desc)s, %(site_url)s)'\n cursor.execute(sql, lieBrand)\n COMPANY_CONN.commit()\nexcept Exception as e:\n... | <|body_start_0|>
global COMPANY_CONN
cursor = None
try:
cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)
sql = 'insert into lie_brand(brand_name, brand_desc, site_url)values(%(brand_name)s, %(brand_desc)s, %(site_url)s)'
cursor.execute(sql, lieBran... | LieBrand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LieBrand:
def addLieBrand(cls, lieBrand):
"""method: addBrand params: lieBrand-type: LieBrand"""
<|body_0|>
def get_brand_id_by_brand_name(cls, brand_name):
"""method: get_brand_id_by_brand_name params: brand_name-type: str return: brand_id return-type: int"""
... | stack_v2_sparse_classes_36k_train_025666 | 13,174 | no_license | [
{
"docstring": "method: addBrand params: lieBrand-type: LieBrand",
"name": "addLieBrand",
"signature": "def addLieBrand(cls, lieBrand)"
},
{
"docstring": "method: get_brand_id_by_brand_name params: brand_name-type: str return: brand_id return-type: int",
"name": "get_brand_id_by_brand_name",... | 2 | stack_v2_sparse_classes_30k_train_014579 | Implement the Python class `LieBrand` described below.
Class description:
Implement the LieBrand class.
Method signatures and docstrings:
- def addLieBrand(cls, lieBrand): method: addBrand params: lieBrand-type: LieBrand
- def get_brand_id_by_brand_name(cls, brand_name): method: get_brand_id_by_brand_name params: bra... | Implement the Python class `LieBrand` described below.
Class description:
Implement the LieBrand class.
Method signatures and docstrings:
- def addLieBrand(cls, lieBrand): method: addBrand params: lieBrand-type: LieBrand
- def get_brand_id_by_brand_name(cls, brand_name): method: get_brand_id_by_brand_name params: bra... | 1e49a6e13ea4b11427f47999c13a609be9ae3ecf | <|skeleton|>
class LieBrand:
def addLieBrand(cls, lieBrand):
"""method: addBrand params: lieBrand-type: LieBrand"""
<|body_0|>
def get_brand_id_by_brand_name(cls, brand_name):
"""method: get_brand_id_by_brand_name params: brand_name-type: str return: brand_id return-type: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LieBrand:
def addLieBrand(cls, lieBrand):
"""method: addBrand params: lieBrand-type: LieBrand"""
global COMPANY_CONN
cursor = None
try:
cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)
sql = 'insert into lie_brand(brand_name, brand_desc, site... | the_stack_v2_python_sparse | rsonline/server/db/company/mysql_client.py | yunhao-qing/PythonScrapy | train | 0 | |
0aa14ca1d2a0bf318dd438e9cc9202e99008e204 | [
"new_user = get_user_model().objects.create_user(email, nickname, password)\nnew_user.is_active = False\nnew_user.save()\nregistration_profile = self.create_profile(new_user)\nregistration_profile.send_activation_email(site)\nreturn new_user",
"salt = hashlib.sha1(str(random.random())).hexdigest()[:5]\nemail = us... | <|body_start_0|>
new_user = get_user_model().objects.create_user(email, nickname, password)
new_user.is_active = False
new_user.save()
registration_profile = self.create_profile(new_user)
registration_profile.send_activation_email(site)
return new_user
<|end_body_0|>
<|b... | 继承自RegistrationManager, 自定义用户字段 | CustomRegistrationManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomRegistrationManager:
"""继承自RegistrationManager, 自定义用户字段"""
def create_inactive_user(self, email, nickname, password, site, send_email=True):
"""新建一个未激活的用户"""
<|body_0|>
def create_profile(self, user):
"""通过用户的电子邮件地址创建一个唯一的和用户绑定的激活码"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_025667 | 6,648 | no_license | [
{
"docstring": "新建一个未激活的用户",
"name": "create_inactive_user",
"signature": "def create_inactive_user(self, email, nickname, password, site, send_email=True)"
},
{
"docstring": "通过用户的电子邮件地址创建一个唯一的和用户绑定的激活码",
"name": "create_profile",
"signature": "def create_profile(self, user)"
}
] | 2 | null | Implement the Python class `CustomRegistrationManager` described below.
Class description:
继承自RegistrationManager, 自定义用户字段
Method signatures and docstrings:
- def create_inactive_user(self, email, nickname, password, site, send_email=True): 新建一个未激活的用户
- def create_profile(self, user): 通过用户的电子邮件地址创建一个唯一的和用户绑定的激活码 | Implement the Python class `CustomRegistrationManager` described below.
Class description:
继承自RegistrationManager, 自定义用户字段
Method signatures and docstrings:
- def create_inactive_user(self, email, nickname, password, site, send_email=True): 新建一个未激活的用户
- def create_profile(self, user): 通过用户的电子邮件地址创建一个唯一的和用户绑定的激活码
<|s... | d52681a84bc75615dcfd7a373e579833e1ebece8 | <|skeleton|>
class CustomRegistrationManager:
"""继承自RegistrationManager, 自定义用户字段"""
def create_inactive_user(self, email, nickname, password, site, send_email=True):
"""新建一个未激活的用户"""
<|body_0|>
def create_profile(self, user):
"""通过用户的电子邮件地址创建一个唯一的和用户绑定的激活码"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomRegistrationManager:
"""继承自RegistrationManager, 自定义用户字段"""
def create_inactive_user(self, email, nickname, password, site, send_email=True):
"""新建一个未激活的用户"""
new_user = get_user_model().objects.create_user(email, nickname, password)
new_user.is_active = False
new_use... | the_stack_v2_python_sparse | citi/apps/account/models.py | doraemonext/citi | train | 0 |
51fd6a76068091ba345bcdc0c9ec1feb8a73a787 | [
"if len(matrix) == 0:\n return False\nif len(matrix[0]) == 0:\n return False\nrow = self.vertical_search(matrix, target)\nreturn self.horizontal_search(matrix[row], target)",
"low, high = (0, len(matrix) - 1)\nwhile low <= high:\n mid = (low + high) // 2\n if matrix[mid][0] <= target <= matrix[mid][-1... | <|body_start_0|>
if len(matrix) == 0:
return False
if len(matrix[0]) == 0:
return False
row = self.vertical_search(matrix, target)
return self.horizontal_search(matrix[row], target)
<|end_body_0|>
<|body_start_1|>
low, high = (0, len(matrix) - 1)
... | Runtime: 36 ms, faster than 96.37% of Python3 online submissions for Search a 2D Matrix. Memory Usage: 14 MB, less than 33.84% of Python3 online submissions for Search a 2D Matrix. | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Runtime: 36 ms, faster than 96.37% of Python3 online submissions for Search a 2D Matrix. Memory Usage: 14 MB, less than 33.84% of Python3 online submissions for Search a 2D Matrix."""
def searchMatrix(self, matrix, target):
"""Simple approach Args: matrix: 2D matrix to l... | stack_v2_sparse_classes_36k_train_025668 | 3,400 | no_license | [
{
"docstring": "Simple approach Args: matrix: 2D matrix to look a target from target: an integer value to look for Returns: bool: True if target exists in the matrix, otherwise False",
"name": "searchMatrix",
"signature": "def searchMatrix(self, matrix, target)"
},
{
"docstring": "This determine... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Runtime: 36 ms, faster than 96.37% of Python3 online submissions for Search a 2D Matrix. Memory Usage: 14 MB, less than 33.84% of Python3 online submissions for Search a 2D Matrix.
Method signatures and docstrings:
- def searchMatrix(self, matr... | Implement the Python class `Solution` described below.
Class description:
Runtime: 36 ms, faster than 96.37% of Python3 online submissions for Search a 2D Matrix. Memory Usage: 14 MB, less than 33.84% of Python3 online submissions for Search a 2D Matrix.
Method signatures and docstrings:
- def searchMatrix(self, matr... | 01fe893ba2e37c9bda79e3081c556698f0b6d2f0 | <|skeleton|>
class Solution:
"""Runtime: 36 ms, faster than 96.37% of Python3 online submissions for Search a 2D Matrix. Memory Usage: 14 MB, less than 33.84% of Python3 online submissions for Search a 2D Matrix."""
def searchMatrix(self, matrix, target):
"""Simple approach Args: matrix: 2D matrix to l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Runtime: 36 ms, faster than 96.37% of Python3 online submissions for Search a 2D Matrix. Memory Usage: 14 MB, less than 33.84% of Python3 online submissions for Search a 2D Matrix."""
def searchMatrix(self, matrix, target):
"""Simple approach Args: matrix: 2D matrix to look a target ... | the_stack_v2_python_sparse | LeetCode/74_search_a_2d_matrix.py | KKosukeee/CodingQuestions | train | 1 |
e5589c30c1bf51aa2e5dbf9d91f5635bcc666dfa | [
"super().__init__(option, shortcut, replacer)\nself._section = replace_section\nself._label = replace_label",
"if not self.replacer:\n raise ValueError('LinkChoice requires a replacer')\nkwargs = {}\nif self._section:\n kwargs['section'] = self.replacer._new.section\nelse:\n kwargs['section'] = self.repl... | <|body_start_0|>
super().__init__(option, shortcut, replacer)
self._section = replace_section
self._label = replace_label
<|end_body_0|>
<|body_start_1|>
if not self.replacer:
raise ValueError('LinkChoice requires a replacer')
kwargs = {}
if self._section:
... | A choice returning a mix of the link new and current link. | LinkChoice | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkChoice:
"""A choice returning a mix of the link new and current link."""
def __init__(self, option: str, shortcut: str, replacer: Optional['pywikibot.bot.InteractiveReplace'], replace_section: bool, replace_label: bool) -> None:
"""Initializer."""
<|body_0|>
def hand... | stack_v2_sparse_classes_36k_train_025669 | 20,559 | permissive | [
{
"docstring": "Initializer.",
"name": "__init__",
"signature": "def __init__(self, option: str, shortcut: str, replacer: Optional['pywikibot.bot.InteractiveReplace'], replace_section: bool, replace_label: bool) -> None"
},
{
"docstring": "Handle by either applying the new section or label.",
... | 2 | stack_v2_sparse_classes_30k_train_009614 | Implement the Python class `LinkChoice` described below.
Class description:
A choice returning a mix of the link new and current link.
Method signatures and docstrings:
- def __init__(self, option: str, shortcut: str, replacer: Optional['pywikibot.bot.InteractiveReplace'], replace_section: bool, replace_label: bool) ... | Implement the Python class `LinkChoice` described below.
Class description:
A choice returning a mix of the link new and current link.
Method signatures and docstrings:
- def __init__(self, option: str, shortcut: str, replacer: Optional['pywikibot.bot.InteractiveReplace'], replace_section: bool, replace_label: bool) ... | 5c01e6bfcd328bc6eae643e661f1a0ae57612808 | <|skeleton|>
class LinkChoice:
"""A choice returning a mix of the link new and current link."""
def __init__(self, option: str, shortcut: str, replacer: Optional['pywikibot.bot.InteractiveReplace'], replace_section: bool, replace_label: bool) -> None:
"""Initializer."""
<|body_0|>
def hand... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkChoice:
"""A choice returning a mix of the link new and current link."""
def __init__(self, option: str, shortcut: str, replacer: Optional['pywikibot.bot.InteractiveReplace'], replace_section: bool, replace_label: bool) -> None:
"""Initializer."""
super().__init__(option, shortcut, re... | the_stack_v2_python_sparse | pywikibot/bot_choice.py | wikimedia/pywikibot | train | 432 |
31a647c915319ffba6bc73ac60ce50e7fd899993 | [
"def unpreorder(root):\n if not root:\n return\n unpreorder(root.right)\n root.val += self.preNUm\n self.preNUm = root.val\n unpreorder(root.left)\nunpreorder(root)\nreturn root",
"if not root:\n return root\nstack = []\ncheck_node = root\nwhile check_node != None or stack != []:\n whi... | <|body_start_0|>
def unpreorder(root):
if not root:
return
unpreorder(root.right)
root.val += self.preNUm
self.preNUm = root.val
unpreorder(root.left)
unpreorder(root)
return root
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def convertBST1(self, root):
""":type root: TreeNode :rtype: TreeNode 以右->根->左的顺序遍历二叉树，将遍历顺序的前一个结点的累加值记录起来，和当前结点相加，得到当前结点的累加值。"""
<|body_0|>
def convertBST2(self, root):
"""NOT :param root: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_025670 | 1,395 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: TreeNode 以右->根->左的顺序遍历二叉树，将遍历顺序的前一个结点的累加值记录起来，和当前结点相加，得到当前结点的累加值。",
"name": "convertBST1",
"signature": "def convertBST1(self, root)"
},
{
"docstring": "NOT :param root: :return:",
"name": "convertBST2",
"signature": "def convertBST2(self, roo... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def convertBST1(self, root): :type root: TreeNode :rtype: TreeNode 以右->根->左的顺序遍历二叉树，将遍历顺序的前一个结点的累加值记录起来，和当前结点相加，得到当前结点的累加值。
- def convertBST2(self, root): NOT :param root: :retur... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def convertBST1(self, root): :type root: TreeNode :rtype: TreeNode 以右->根->左的顺序遍历二叉树，将遍历顺序的前一个结点的累加值记录起来，和当前结点相加，得到当前结点的累加值。
- def convertBST2(self, root): NOT :param root: :retur... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def convertBST1(self, root):
""":type root: TreeNode :rtype: TreeNode 以右->根->左的顺序遍历二叉树，将遍历顺序的前一个结点的累加值记录起来，和当前结点相加，得到当前结点的累加值。"""
<|body_0|>
def convertBST2(self, root):
"""NOT :param root: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def convertBST1(self, root):
""":type root: TreeNode :rtype: TreeNode 以右->根->左的顺序遍历二叉树，将遍历顺序的前一个结点的累加值记录起来，和当前结点相加，得到当前结点的累加值。"""
def unpreorder(root):
if not root:
return
unpreorder(root.right)
root.val += self.preNUm
s... | the_stack_v2_python_sparse | convertBST.py | NeilWangziyu/Leetcode_py | train | 2 | |
337d251bede5507040fc47825a050dc47343107c | [
"self.parent = None\nself.value = value\nself.left = left\nself.right = right\nif left:\n self.left.parent = self\nif right:\n self.right.parent = self",
"vals = [self.value]\nif self.left:\n vals = vals + self.left.nodeValues()\nif self.right:\n vals = vals + self.right.nodeValues()\nreturn vals"
] | <|body_start_0|>
self.parent = None
self.value = value
self.left = left
self.right = right
if left:
self.left.parent = self
if right:
self.right.parent = self
<|end_body_0|>
<|body_start_1|>
vals = [self.value]
if self.left:
... | Node class for a binary tree. | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
<|body_0|>
def nodeValues(self):
"""Get all the values in the tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.paren... | stack_v2_sparse_classes_36k_train_025671 | 1,543 | no_license | [
{
"docstring": "Initialize the node.",
"name": "__init__",
"signature": "def __init__(self, value, left=None, right=None)"
},
{
"docstring": "Get all the values in the tree.",
"name": "nodeValues",
"signature": "def nodeValues(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017021 | Implement the Python class `Node` described below.
Class description:
Node class for a binary tree.
Method signatures and docstrings:
- def __init__(self, value, left=None, right=None): Initialize the node.
- def nodeValues(self): Get all the values in the tree. | Implement the Python class `Node` described below.
Class description:
Node class for a binary tree.
Method signatures and docstrings:
- def __init__(self, value, left=None, right=None): Initialize the node.
- def nodeValues(self): Get all the values in the tree.
<|skeleton|>
class Node:
"""Node class for a binar... | 97eae3ee806756f4d646d600f434b1e68164ad34 | <|skeleton|>
class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
<|body_0|>
def nodeValues(self):
"""Get all the values in the tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
self.parent = None
self.value = value
self.left = left
self.right = right
if left:
self.left.parent = self
if right:
... | the_stack_v2_python_sparse | Python/2019_05_20_Problem_125_Sum_Node_Pair_to_k.py | BaoCaiH/Daily_Coding_Problem | train | 0 |
a6c04a168a49dfff790389c9f8ec0395dbc5554d | [
"candidates.sort()\nl = len(candidates)\nsub_sum = {}\nfor i in range(1, target + 1):\n v_combine = set()\n for j in range(l):\n if candidates[j] > i:\n break\n elif candidates[j] == i:\n s = set()\n s.add(candidates[j])\n v_combine.add(s)\n els... | <|body_start_0|>
candidates.sort()
l = len(candidates)
sub_sum = {}
for i in range(1, target + 1):
v_combine = set()
for j in range(l):
if candidates[j] > i:
break
elif candidates[j] == i:
s =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum(self, candidates, target: int):
"""使用动态规划 1 从小到大遍历target 1 遍历数组，直到>target, 2 每到一个数i，找到target-i对应的解集 :param candidates: :param target: :return:"""
<|body_0|>
def combinationSum1(self, candidates, target: int):
"""使用dfs+回溯 dfs逻辑：输入为target、"... | stack_v2_sparse_classes_36k_train_025672 | 2,421 | no_license | [
{
"docstring": "使用动态规划 1 从小到大遍历target 1 遍历数组，直到>target, 2 每到一个数i，找到target-i对应的解集 :param candidates: :param target: :return:",
"name": "combinationSum",
"signature": "def combinationSum(self, candidates, target: int)"
},
{
"docstring": "使用dfs+回溯 dfs逻辑：输入为target、",
"name": "combinationSum1",
... | 2 | stack_v2_sparse_classes_30k_train_001512 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates, target: int): 使用动态规划 1 从小到大遍历target 1 遍历数组，直到>target, 2 每到一个数i，找到target-i对应的解集 :param candidates: :param target: :return:
- def combinationSu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates, target: int): 使用动态规划 1 从小到大遍历target 1 遍历数组，直到>target, 2 每到一个数i，找到target-i对应的解集 :param candidates: :param target: :return:
- def combinationSu... | 4a27fdd976268bf4daf8eee447efd754f1e0bb02 | <|skeleton|>
class Solution:
def combinationSum(self, candidates, target: int):
"""使用动态规划 1 从小到大遍历target 1 遍历数组，直到>target, 2 每到一个数i，找到target-i对应的解集 :param candidates: :param target: :return:"""
<|body_0|>
def combinationSum1(self, candidates, target: int):
"""使用dfs+回溯 dfs逻辑：输入为target、"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def combinationSum(self, candidates, target: int):
"""使用动态规划 1 从小到大遍历target 1 遍历数组，直到>target, 2 每到一个数i，找到target-i对应的解集 :param candidates: :param target: :return:"""
candidates.sort()
l = len(candidates)
sub_sum = {}
for i in range(1, target + 1):
v... | the_stack_v2_python_sparse | combination-sum.py | Angel888/suanfa | train | 0 | |
b109a65af3708dd7e63cff75920566269d1b8d97 | [
"super(CollectNAgent, self).__init__(minRoundValue)\nself.minRoundValue = minRoundValue\nself.name = 'CollectNAgent'",
"if gameState.round().roundTreasureValues[self.player_id] >= self.minRoundValue:\n return TURN_BACK\nelse:\n return GO_FORWARD"
] | <|body_start_0|>
super(CollectNAgent, self).__init__(minRoundValue)
self.minRoundValue = minRoundValue
self.name = 'CollectNAgent'
<|end_body_0|>
<|body_start_1|>
if gameState.round().roundTreasureValues[self.player_id] >= self.minRoundValue:
return TURN_BACK
else:
... | classdocs | CollectNAgent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectNAgent:
"""classdocs"""
def __init__(self, minRoundValue):
"""Constructor"""
<|body_0|>
def decide(self, gameState):
"""Returns true if the agent goes forward, returns false if the agent turns back"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_025673 | 743 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, minRoundValue)"
},
{
"docstring": "Returns true if the agent goes forward, returns false if the agent turns back",
"name": "decide",
"signature": "def decide(self, gameState)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009850 | Implement the Python class `CollectNAgent` described below.
Class description:
classdocs
Method signatures and docstrings:
- def __init__(self, minRoundValue): Constructor
- def decide(self, gameState): Returns true if the agent goes forward, returns false if the agent turns back | Implement the Python class `CollectNAgent` described below.
Class description:
classdocs
Method signatures and docstrings:
- def __init__(self, minRoundValue): Constructor
- def decide(self, gameState): Returns true if the agent goes forward, returns false if the agent turns back
<|skeleton|>
class CollectNAgent:
... | 2c7ac2952dc2203ee3687581eb45396229e8df87 | <|skeleton|>
class CollectNAgent:
"""classdocs"""
def __init__(self, minRoundValue):
"""Constructor"""
<|body_0|>
def decide(self, gameState):
"""Returns true if the agent goes forward, returns false if the agent turns back"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollectNAgent:
"""classdocs"""
def __init__(self, minRoundValue):
"""Constructor"""
super(CollectNAgent, self).__init__(minRoundValue)
self.minRoundValue = minRoundValue
self.name = 'CollectNAgent'
def decide(self, gameState):
"""Returns true if the agent goes... | the_stack_v2_python_sparse | incanGold/agent/CollectNAgent.py | GrandAdmiralGergar/IncanGold | train | 0 |
e3127fae9ed3aaecfe2c2ea1d139c54ce3299f10 | [
"url = await super()._api_url()\ncomponent = self._parameter('component')\nbranch = self._parameter('branch')\nreturn URL(f'{url}/api/project_analyses/search?project={component}&branch={branch}')",
"url = await super()._landing_url(responses)\ncomponent = self._parameter('component')\nbranch = self._parameter('br... | <|body_start_0|>
url = await super()._api_url()
component = self._parameter('component')
branch = self._parameter('branch')
return URL(f'{url}/api/project_analyses/search?project={component}&branch={branch}')
<|end_body_0|>
<|body_start_1|>
url = await super()._landing_url(respo... | Base class for collectors that use the SonarQube project analyses endpoint. | SonarQubeProjectAnalysesBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SonarQubeProjectAnalysesBase:
"""Base class for collectors that use the SonarQube project analyses endpoint."""
async def _api_url(self) -> URL:
"""Extend to add the project analyses path and parameters."""
<|body_0|>
async def _landing_url(self, responses: SourceRespons... | stack_v2_sparse_classes_36k_train_025674 | 5,057 | permissive | [
{
"docstring": "Extend to add the project analyses path and parameters.",
"name": "_api_url",
"signature": "async def _api_url(self) -> URL"
},
{
"docstring": "Extend to add the project activity path and parameters.",
"name": "_landing_url",
"signature": "async def _landing_url(self, res... | 2 | null | Implement the Python class `SonarQubeProjectAnalysesBase` described below.
Class description:
Base class for collectors that use the SonarQube project analyses endpoint.
Method signatures and docstrings:
- async def _api_url(self) -> URL: Extend to add the project analyses path and parameters.
- async def _landing_ur... | Implement the Python class `SonarQubeProjectAnalysesBase` described below.
Class description:
Base class for collectors that use the SonarQube project analyses endpoint.
Method signatures and docstrings:
- async def _api_url(self) -> URL: Extend to add the project analyses path and parameters.
- async def _landing_ur... | 5d9952bf0bd47895824fa78428d3e4f4d6b5d9b3 | <|skeleton|>
class SonarQubeProjectAnalysesBase:
"""Base class for collectors that use the SonarQube project analyses endpoint."""
async def _api_url(self) -> URL:
"""Extend to add the project analyses path and parameters."""
<|body_0|>
async def _landing_url(self, responses: SourceRespons... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SonarQubeProjectAnalysesBase:
"""Base class for collectors that use the SonarQube project analyses endpoint."""
async def _api_url(self) -> URL:
"""Extend to add the project analyses path and parameters."""
url = await super()._api_url()
component = self._parameter('component')
... | the_stack_v2_python_sparse | components/collector/src/source_collectors/sonarqube/base.py | ICTU/quality-time | train | 43 |
dba4b6386680fd1a6827e97d1680475c6be4da78 | [
"self.aurora_params = aurora_params\nself.custom_tag_vec = custom_tag_vec\nself.instance_type = instance_type\nself.key_pair_name = key_pair_name\nself.network_security_groups = network_security_groups\nself.proxy_vm_subnet = proxy_vm_subnet\nself.proxy_vm_vpc = proxy_vm_vpc\nself.rds_params = rds_params\nself.regi... | <|body_start_0|>
self.aurora_params = aurora_params
self.custom_tag_vec = custom_tag_vec
self.instance_type = instance_type
self.key_pair_name = key_pair_name
self.network_security_groups = network_security_groups
self.proxy_vm_subnet = proxy_vm_subnet
self.proxy_... | Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores. Proto containing the parameters required for r... | DeployVMsToAWSParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeployVMsToAWSParams:
"""Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores... | stack_v2_sparse_classes_36k_train_025675 | 6,685 | permissive | [
{
"docstring": "Constructor for the DeployVMsToAWSParams class",
"name": "__init__",
"signature": "def __init__(self, aurora_params=None, custom_tag_vec=None, instance_type=None, key_pair_name=None, network_security_groups=None, proxy_vm_subnet=None, proxy_vm_vpc=None, rds_params=None, region=None, subn... | 2 | stack_v2_sparse_classes_30k_train_000002 | Implement the Python class `DeployVMsToAWSParams` described below.
Class description:
Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This fiel... | Implement the Python class `DeployVMsToAWSParams` described below.
Class description:
Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This fiel... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class DeployVMsToAWSParams:
"""Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeployVMsToAWSParams:
"""Implementation of the 'DeployVMsToAWSParams' model. Contains AWS specific information needed to identify various resources when converting and deploying a VM to AWS. Attributes: aurora_params (DeployDBInstancesToRDSParams): This field will be populated for Aurora restores. Proto conta... | the_stack_v2_python_sparse | cohesity_management_sdk/models/deploy_vms_to_aws_params.py | cohesity/management-sdk-python | train | 24 |
8ee7b1947e3933d394e8244375cea3e346504307 | [
"print('***DEBUG PARAMS PARAMS: |%s|' % param)\nparam = param[0]\nif param.get('getFields'):\n return [{'name': {'type': 'string'}}]\nsearch_args = []\np_name = param.get('p_name')\nif p_name:\n search_args.extend([('name', 'ilike', p_name)])\nids = self.search(cr, uid, search_args)\nresult = []\nfor partner ... | <|body_start_0|>
print('***DEBUG PARAMS PARAMS: |%s|' % param)
param = param[0]
if param.get('getFields'):
return [{'name': {'type': 'string'}}]
search_args = []
p_name = param.get('p_name')
if p_name:
search_args.extend([('name', 'ilike', p_name)]... | res_partner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class res_partner:
def report_custom_data_params(self, cr, uid, *param):
"""Custom data method for 'params' report. 'param' is a tuple where the first element is a dict with any report parameters (keyed by the parameter name) and other environmental info. In this example the report has a singl... | stack_v2_sparse_classes_36k_train_025676 | 2,925 | no_license | [
{
"docstring": "Custom data method for 'params' report. 'param' is a tuple where the first element is a dict with any report parameters (keyed by the parameter name) and other environmental info. In this example the report has a single defined parameter 'p_name' which is a string. The code below uses 'ilike' to... | 2 | stack_v2_sparse_classes_30k_train_021566 | Implement the Python class `res_partner` described below.
Class description:
Implement the res_partner class.
Method signatures and docstrings:
- def report_custom_data_params(self, cr, uid, *param): Custom data method for 'params' report. 'param' is a tuple where the first element is a dict with any report parameter... | Implement the Python class `res_partner` described below.
Class description:
Implement the res_partner class.
Method signatures and docstrings:
- def report_custom_data_params(self, cr, uid, *param): Custom data method for 'params' report. 'param' is a tuple where the first element is a dict with any report parameter... | 7f36c019ed5405bfdff809c43ae74fb369cd1fd6 | <|skeleton|>
class res_partner:
def report_custom_data_params(self, cr, uid, *param):
"""Custom data method for 'params' report. 'param' is a tuple where the first element is a dict with any report parameters (keyed by the parameter name) and other environmental info. In this example the report has a singl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class res_partner:
def report_custom_data_params(self, cr, uid, *param):
"""Custom data method for 'params' report. 'param' is a tuple where the first element is a dict with any report parameters (keyed by the parameter name) and other environmental info. In this example the report has a single defined para... | the_stack_v2_python_sparse | dme_pentaho_example/models/res_partner.py | turbodavid/dme | train | 0 | |
d823f6c27a4692da6243b17732c3ae4ceb1d6125 | [
"if not root:\n return True\nqueue = deque([(root.left, root.right)])\nwhile queue:\n node1, node2 = queue.popleft()\n if not node1 and (not node2):\n continue\n if not node1 or not node2:\n return False\n if node1.val != node2.val:\n return False\n queue.popleft((node1.left, ... | <|body_start_0|>
if not root:
return True
queue = deque([(root.left, root.right)])
while queue:
node1, node2 = queue.popleft()
if not node1 and (not node2):
continue
if not node1 or not node2:
return False
... | BinaryTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryTree:
def is_symmetric(self, root: 'TreeNode') -> bool:
"""Approach: Iterative Time Complexity: O(N) Space Complexity: O(1) :param root: :return:"""
<|body_0|>
def depth_first_search(self, node1: 'TreeNode', node2: 'TreeNode') -> bool:
"""Depth First Search fun... | stack_v2_sparse_classes_36k_train_025677 | 1,789 | no_license | [
{
"docstring": "Approach: Iterative Time Complexity: O(N) Space Complexity: O(1) :param root: :return:",
"name": "is_symmetric",
"signature": "def is_symmetric(self, root: 'TreeNode') -> bool"
},
{
"docstring": "Depth First Search function. :param node1: :param node2: :return:",
"name": "dep... | 3 | stack_v2_sparse_classes_30k_train_013862 | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def is_symmetric(self, root: 'TreeNode') -> bool: Approach: Iterative Time Complexity: O(N) Space Complexity: O(1) :param root: :return:
- def depth_first_search(self, node1:... | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def is_symmetric(self, root: 'TreeNode') -> bool: Approach: Iterative Time Complexity: O(N) Space Complexity: O(1) :param root: :return:
- def depth_first_search(self, node1:... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class BinaryTree:
def is_symmetric(self, root: 'TreeNode') -> bool:
"""Approach: Iterative Time Complexity: O(N) Space Complexity: O(1) :param root: :return:"""
<|body_0|>
def depth_first_search(self, node1: 'TreeNode', node2: 'TreeNode') -> bool:
"""Depth First Search fun... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryTree:
def is_symmetric(self, root: 'TreeNode') -> bool:
"""Approach: Iterative Time Complexity: O(N) Space Complexity: O(1) :param root: :return:"""
if not root:
return True
queue = deque([(root.left, root.right)])
while queue:
node1, node2 = queue... | the_stack_v2_python_sparse | revisited/trees/symmetric_tree.py | Shiv2157k/leet_code | train | 1 | |
7dd716d0ff7099f1188f3fcf9610367c7c3ac02a | [
"self.Wz = np.random.normal(size=(i + h, h))\nself.Wr = np.random.normal(size=(i + h, h))\nself.Wh = np.random.normal(size=(i + h, h))\nself.Wy = np.random.normal(size=(h, o))\nself.bz = np.zeros((1, h))\nself.br = np.zeros((1, h))\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"U = np.hstack((h_prev, ... | <|body_start_0|>
self.Wz = np.random.normal(size=(i + h, h))
self.Wr = np.random.normal(size=(i + h, h))
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.normal(size=(h, o))
self.bz = np.zeros((1, h))
self.br = np.zeros((1, h))
self.bh = np.zeros((1... | GRU cell class | GRUCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRUCell:
"""GRU cell class"""
def __init__(self, i, h, o):
"""Constructor"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Method that performs forward propagation for one time step"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.Wz = np.ra... | stack_v2_sparse_classes_36k_train_025678 | 1,172 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, i, h, o)"
},
{
"docstring": "Method that performs forward propagation for one time step",
"name": "forward",
"signature": "def forward(self, h_prev, x_t)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005623 | Implement the Python class `GRUCell` described below.
Class description:
GRU cell class
Method signatures and docstrings:
- def __init__(self, i, h, o): Constructor
- def forward(self, h_prev, x_t): Method that performs forward propagation for one time step | Implement the Python class `GRUCell` described below.
Class description:
GRU cell class
Method signatures and docstrings:
- def __init__(self, i, h, o): Constructor
- def forward(self, h_prev, x_t): Method that performs forward propagation for one time step
<|skeleton|>
class GRUCell:
"""GRU cell class"""
d... | 131be8fcf61aafb5a4ddc0b3853ba625560eb786 | <|skeleton|>
class GRUCell:
"""GRU cell class"""
def __init__(self, i, h, o):
"""Constructor"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Method that performs forward propagation for one time step"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GRUCell:
"""GRU cell class"""
def __init__(self, i, h, o):
"""Constructor"""
self.Wz = np.random.normal(size=(i + h, h))
self.Wr = np.random.normal(size=(i + h, h))
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.normal(size=(h, o))
self.bz ... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/2-gru_cell.py | zahraaassaad/holbertonschool-machine_learning | train | 1 |
5e9a09c25e1dad121013fa8bef9931501f9475ea | [
"arr = []\n\ndef traverse(node):\n if node:\n arr.append(str(node.val))\n for c in node.children:\n traverse(c)\n arr.append('#')\ntraverse(root)\nreturn ' '.join(arr)",
"if not data:\n return\ntoken = collections.deque(data.split())\n\ndef helper(token):\n root = Node(int... | <|body_start_0|>
arr = []
def traverse(node):
if node:
arr.append(str(node.val))
for c in node.children:
traverse(c)
arr.append('#')
traverse(root)
return ' '.join(arr)
<|end_body_0|>
<|body_start_1|>
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_025679 | 2,283 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def deserialize(self, ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | 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: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | aac41ddd2ec5f6e5c0f46659696ed5b67769bde2 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|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: Node :rtype: str"""
arr = []
def traverse(node):
if node:
arr.append(str(node.val))
for c in node.children:
traverse(c)
a... | the_stack_v2_python_sparse | serialize_deserialize.py | aroraakshit/coding_prep | train | 8 | |
bec1119c569c6da9e6c901a6e438eddff70b3dfe | [
"self.mol = mol\nself.ff = ff\nself.top = topology.BaseTopology(mol, ff)",
"ligand_masses = [a.GetMass() for a in self.mol.GetAtoms()]\nligand_coords = get_romol_conf(self.mol)\nhost_bps, host_masses = openmm_deserializer.deserialize_system(host_system, cutoff=1.2)\nnum_host_atoms = host_coords.shape[0]\nhgt = to... | <|body_start_0|>
self.mol = mol
self.ff = ff
self.top = topology.BaseTopology(mol, ff)
<|end_body_0|>
<|body_start_1|>
ligand_masses = [a.GetMass() for a in self.mol.GetAtoms()]
ligand_coords = get_romol_conf(self.mol)
host_bps, host_masses = openmm_deserializer.deserial... | AbsoluteFreeEnergy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbsoluteFreeEnergy:
def __init__(self, mol, ff):
"""Compute the absolute free energy of a molecule via 4D decoupling. Parameters ---------- mol: rdkit mol Ligand to be decoupled ff: ff.Forcefield Ligand forcefield"""
<|body_0|>
def prepare_host_edge(self, ff_params, host_sys... | stack_v2_sparse_classes_36k_train_025680 | 8,594 | permissive | [
{
"docstring": "Compute the absolute free energy of a molecule via 4D decoupling. Parameters ---------- mol: rdkit mol Ligand to be decoupled ff: ff.Forcefield Ligand forcefield",
"name": "__init__",
"signature": "def __init__(self, mol, ff)"
},
{
"docstring": "Prepares the host-edge system Para... | 2 | stack_v2_sparse_classes_30k_train_011913 | Implement the Python class `AbsoluteFreeEnergy` described below.
Class description:
Implement the AbsoluteFreeEnergy class.
Method signatures and docstrings:
- def __init__(self, mol, ff): Compute the absolute free energy of a molecule via 4D decoupling. Parameters ---------- mol: rdkit mol Ligand to be decoupled ff:... | Implement the Python class `AbsoluteFreeEnergy` described below.
Class description:
Implement the AbsoluteFreeEnergy class.
Method signatures and docstrings:
- def __init__(self, mol, ff): Compute the absolute free energy of a molecule via 4D decoupling. Parameters ---------- mol: rdkit mol Ligand to be decoupled ff:... | 74efe28bfe4fe72a995a764bf3afe635b01bfc73 | <|skeleton|>
class AbsoluteFreeEnergy:
def __init__(self, mol, ff):
"""Compute the absolute free energy of a molecule via 4D decoupling. Parameters ---------- mol: rdkit mol Ligand to be decoupled ff: ff.Forcefield Ligand forcefield"""
<|body_0|>
def prepare_host_edge(self, ff_params, host_sys... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbsoluteFreeEnergy:
def __init__(self, mol, ff):
"""Compute the absolute free energy of a molecule via 4D decoupling. Parameters ---------- mol: rdkit mol Ligand to be decoupled ff: ff.Forcefield Ligand forcefield"""
self.mol = mol
self.ff = ff
self.top = topology.BaseTopology(... | the_stack_v2_python_sparse | fe/free_energy.py | jchodera/timemachine | train | 0 | |
62faaccf74199d4800fa9dd50b65ab42be2e855f | [
"self.num_parallel_calls = tf.convert_to_tensor(num_parallel_calls, tf.int32)\nif times.dtype is not float_type:\n times = tf.cast(times, float_type)\nself.times = times\nself.slice_size = index_feed.step\nself.Nt = tf.shape(self.times)[0]\nself.index_feed = index_feed\nself.time_feed = index_feed.feed.map(self.... | <|body_start_0|>
self.num_parallel_calls = tf.convert_to_tensor(num_parallel_calls, tf.int32)
if times.dtype is not float_type:
times = tf.cast(times, float_type)
self.times = times
self.slice_size = index_feed.step
self.Nt = tf.shape(self.times)[0]
self.index... | TimeFeed | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeFeed:
def __init__(self, index_feed: IndexFeed, times, num_parallel_calls=10):
"""Create a time feed :param index_feed: IndexFeed Pulse of this feed :param times: float_type, Tensor, [Nt, 1] Times to slice :param num_parallel_calls:"""
<|body_0|>
def get_times_slice(self... | stack_v2_sparse_classes_36k_train_025681 | 18,860 | permissive | [
{
"docstring": "Create a time feed :param index_feed: IndexFeed Pulse of this feed :param times: float_type, Tensor, [Nt, 1] Times to slice :param num_parallel_calls:",
"name": "__init__",
"signature": "def __init__(self, index_feed: IndexFeed, times, num_parallel_calls=10)"
},
{
"docstring": "G... | 2 | stack_v2_sparse_classes_30k_train_009783 | Implement the Python class `TimeFeed` described below.
Class description:
Implement the TimeFeed class.
Method signatures and docstrings:
- def __init__(self, index_feed: IndexFeed, times, num_parallel_calls=10): Create a time feed :param index_feed: IndexFeed Pulse of this feed :param times: float_type, Tensor, [Nt,... | Implement the Python class `TimeFeed` described below.
Class description:
Implement the TimeFeed class.
Method signatures and docstrings:
- def __init__(self, index_feed: IndexFeed, times, num_parallel_calls=10): Create a time feed :param index_feed: IndexFeed Pulse of this feed :param times: float_type, Tensor, [Nt,... | 2997d60d8cf07f875e42c0b5f07944e9ab7e9d33 | <|skeleton|>
class TimeFeed:
def __init__(self, index_feed: IndexFeed, times, num_parallel_calls=10):
"""Create a time feed :param index_feed: IndexFeed Pulse of this feed :param times: float_type, Tensor, [Nt, 1] Times to slice :param num_parallel_calls:"""
<|body_0|>
def get_times_slice(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeFeed:
def __init__(self, index_feed: IndexFeed, times, num_parallel_calls=10):
"""Create a time feed :param index_feed: IndexFeed Pulse of this feed :param times: float_type, Tensor, [Nt, 1] Times to slice :param num_parallel_calls:"""
self.num_parallel_calls = tf.convert_to_tensor(num_par... | the_stack_v2_python_sparse | bayes_filter/feeds.py | Joshuaalbert/bayes_filter | train | 0 | |
0938ab1f0e3157cf9a2201e635bde5cd2e150b3c | [
"if pos >= neg:\n return True\nelse:\n return False",
"if pos >= 1:\n return True\nelse:\n return False",
"if neg == 0:\n return True\nelse:\n return False",
"self.iterable = iterable\nself.funcs = funcs\nself.judge = judge",
"for itr in self.iterable:\n pos = 0\n neg = 0\n for fu... | <|body_start_0|>
if pos >= neg:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
if pos >= 1:
return True
else:
return False
<|end_body_1|>
<|body_start_2|>
if neg == 0:
return True
else:
... | Класс фильтрации элементов последовательности, удовлетворяющих условиям указанных функций. Содержит функции judge_half, judge_any, judge_all, __init__, __iter__. | MultiFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiFilter:
"""Класс фильтрации элементов последовательности, удовлетворяющих условиям указанных функций. Содержит функции judge_half, judge_any, judge_all, __init__, __iter__."""
def judge_half(pos, neg):
"""Функция допускает элемент, если его допускает хотя бы половина фукнций. Ар... | stack_v2_sparse_classes_36k_train_025682 | 6,096 | no_license | [
{
"docstring": "Функция допускает элемент, если его допускает хотя бы половина фукнций. Аргументы: pos - счетчик количества функций, которые допускают элемент neg - счетчик количества функций, которые не допускают элемент",
"name": "judge_half",
"signature": "def judge_half(pos, neg)"
},
{
"docs... | 5 | stack_v2_sparse_classes_30k_train_016585 | Implement the Python class `MultiFilter` described below.
Class description:
Класс фильтрации элементов последовательности, удовлетворяющих условиям указанных функций. Содержит функции judge_half, judge_any, judge_all, __init__, __iter__.
Method signatures and docstrings:
- def judge_half(pos, neg): Функция допускает... | Implement the Python class `MultiFilter` described below.
Class description:
Класс фильтрации элементов последовательности, удовлетворяющих условиям указанных функций. Содержит функции judge_half, judge_any, judge_all, __init__, __iter__.
Method signatures and docstrings:
- def judge_half(pos, neg): Функция допускает... | 721292862254019dad95a28e2a0a2765d711d4fb | <|skeleton|>
class MultiFilter:
"""Класс фильтрации элементов последовательности, удовлетворяющих условиям указанных функций. Содержит функции judge_half, judge_any, judge_all, __init__, __iter__."""
def judge_half(pos, neg):
"""Функция допускает элемент, если его допускает хотя бы половина фукнций. Ар... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiFilter:
"""Класс фильтрации элементов последовательности, удовлетворяющих условиям указанных функций. Содержит функции judge_half, judge_any, judge_all, __init__, __iter__."""
def judge_half(pos, neg):
"""Функция допускает элемент, если его допускает хотя бы половина фукнций. Аргументы: pos ... | the_stack_v2_python_sparse | Lesson_14_Multifilter.py | MORVf/Lessons_python_part2 | train | 0 |
4d081d89afadb1a371d35ef2e19eefe7529b3f9a | [
"super().__init__(individual_generator)\nif k < 1:\n raise ValueError(f'Number of crossover points must be greater than 0. {k} was given')\nself.k = k",
"child_chromosomes = self._cross_chromosomes(parent_1.chromosome, parent_2.chromosome)\nchild_1 = self.individual_generator.generate(child_chromosomes[0])\nch... | <|body_start_0|>
super().__init__(individual_generator)
if k < 1:
raise ValueError(f'Number of crossover points must be greater than 0. {k} was given')
self.k = k
<|end_body_0|>
<|body_start_1|>
child_chromosomes = self._cross_chromosomes(parent_1.chromosome, parent_2.chromo... | k-point crossover class | PointCrossover | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointCrossover:
"""k-point crossover class"""
def __init__(self, individual_generator, k):
"""Initialize the crossover :param individual_generator: Generator that will be used to generate children :param k: Number of crossover points"""
<|body_0|>
def cross(self, parent_... | stack_v2_sparse_classes_36k_train_025683 | 2,148 | no_license | [
{
"docstring": "Initialize the crossover :param individual_generator: Generator that will be used to generate children :param k: Number of crossover points",
"name": "__init__",
"signature": "def __init__(self, individual_generator, k)"
},
{
"docstring": "Return 2 children made by k-point crosso... | 3 | stack_v2_sparse_classes_30k_train_004086 | Implement the Python class `PointCrossover` described below.
Class description:
k-point crossover class
Method signatures and docstrings:
- def __init__(self, individual_generator, k): Initialize the crossover :param individual_generator: Generator that will be used to generate children :param k: Number of crossover ... | Implement the Python class `PointCrossover` described below.
Class description:
k-point crossover class
Method signatures and docstrings:
- def __init__(self, individual_generator, k): Initialize the crossover :param individual_generator: Generator that will be used to generate children :param k: Number of crossover ... | 30d87754ed22aa5aab7103d912c414f5a6150a34 | <|skeleton|>
class PointCrossover:
"""k-point crossover class"""
def __init__(self, individual_generator, k):
"""Initialize the crossover :param individual_generator: Generator that will be used to generate children :param k: Number of crossover points"""
<|body_0|>
def cross(self, parent_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointCrossover:
"""k-point crossover class"""
def __init__(self, individual_generator, k):
"""Initialize the crossover :param individual_generator: Generator that will be used to generate children :param k: Number of crossover points"""
super().__init__(individual_generator)
if k ... | the_stack_v2_python_sparse | crossovers/point_crossover.py | Yabk/SF-Evolution | train | 0 |
57ad9353804ab6249758f22eb525d8391aac71f8 | [
"self.ActivePixelSensorObj = ActivePixelSensor(netlist, simulator)\nself.netlist = self.ActivePixelSensorObj.netlist\nself.which_simulator = self.ActivePixelSensorObj.which_simulator\npass",
"self.assertIsInstance(self.netlist, string)\nself.assertIsInstance(self.which_simulator, string)\npass"
] | <|body_start_0|>
self.ActivePixelSensorObj = ActivePixelSensor(netlist, simulator)
self.netlist = self.ActivePixelSensorObj.netlist
self.which_simulator = self.ActivePixelSensorObj.which_simulator
pass
<|end_body_0|>
<|body_start_1|>
self.assertIsInstance(self.netlist, string)
... | TestActivePixelSensorTypes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestActivePixelSensorTypes:
def setUp(self):
"""Setup function TestTypes for class ActivePixelSensor"""
<|body_0|>
def test_types(self):
"""Function to test data types for class ActivePixelSensor"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.... | stack_v2_sparse_classes_36k_train_025684 | 930 | no_license | [
{
"docstring": "Setup function TestTypes for class ActivePixelSensor",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Function to test data types for class ActivePixelSensor",
"name": "test_types",
"signature": "def test_types(self)"
}
] | 2 | null | Implement the Python class `TestActivePixelSensorTypes` described below.
Class description:
Implement the TestActivePixelSensorTypes class.
Method signatures and docstrings:
- def setUp(self): Setup function TestTypes for class ActivePixelSensor
- def test_types(self): Function to test data types for class ActivePixe... | Implement the Python class `TestActivePixelSensorTypes` described below.
Class description:
Implement the TestActivePixelSensorTypes class.
Method signatures and docstrings:
- def setUp(self): Setup function TestTypes for class ActivePixelSensor
- def test_types(self): Function to test data types for class ActivePixe... | 825a0eab64be709efe161b9a48eb54c4bc5c1bef | <|skeleton|>
class TestActivePixelSensorTypes:
def setUp(self):
"""Setup function TestTypes for class ActivePixelSensor"""
<|body_0|>
def test_types(self):
"""Function to test data types for class ActivePixelSensor"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestActivePixelSensorTypes:
def setUp(self):
"""Setup function TestTypes for class ActivePixelSensor"""
self.ActivePixelSensorObj = ActivePixelSensor(netlist, simulator)
self.netlist = self.ActivePixelSensorObj.netlist
self.which_simulator = self.ActivePixelSensorObj.which_simu... | the_stack_v2_python_sparse | WFS_devel/WFS_class_devel/test_ActivePixelSensor.py | wenh81/vlc_simulator | train | 0 | |
4b2af1b09f9eab5edf36653f2fcdbf4d46479c60 | [
"date_format = get_date_format(range_type)\nhealth = cls.objects.filter(user=user).order_by('related_date')\nif range_type in (ChartTimeRange.YEAR, ChartTimeRange.MONTH):\n date = datetime.strptime(date_str, date_format)\n health = health.filter(related_date__year=date.strftime('%Y'))\n if range_type == Ch... | <|body_start_0|>
date_format = get_date_format(range_type)
health = cls.objects.filter(user=user).order_by('related_date')
if range_type in (ChartTimeRange.YEAR, ChartTimeRange.MONTH):
date = datetime.strptime(date_str, date_format)
health = health.filter(related_date__ye... | Health | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Health:
def get_health_by_date(cls, user, range_type, date_str):
"""Get queryset of health datas by range :param user: user object :param range_type: dates range type - week, month or year :param date_str: date string :return: queryset of health datas :rtype: queryset"""
<|body_0... | stack_v2_sparse_classes_36k_train_025685 | 5,178 | no_license | [
{
"docstring": "Get queryset of health datas by range :param user: user object :param range_type: dates range type - week, month or year :param date_str: date string :return: queryset of health datas :rtype: queryset",
"name": "get_health_by_date",
"signature": "def get_health_by_date(cls, user, range_t... | 3 | stack_v2_sparse_classes_30k_train_001147 | Implement the Python class `Health` described below.
Class description:
Implement the Health class.
Method signatures and docstrings:
- def get_health_by_date(cls, user, range_type, date_str): Get queryset of health datas by range :param user: user object :param range_type: dates range type - week, month or year :par... | Implement the Python class `Health` described below.
Class description:
Implement the Health class.
Method signatures and docstrings:
- def get_health_by_date(cls, user, range_type, date_str): Get queryset of health datas by range :param user: user object :param range_type: dates range type - week, month or year :par... | 3e2cf3b28ebcb6f87aa8db4073813eed7b7e3b8b | <|skeleton|>
class Health:
def get_health_by_date(cls, user, range_type, date_str):
"""Get queryset of health datas by range :param user: user object :param range_type: dates range type - week, month or year :param date_str: date string :return: queryset of health datas :rtype: queryset"""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Health:
def get_health_by_date(cls, user, range_type, date_str):
"""Get queryset of health datas by range :param user: user object :param range_type: dates range type - week, month or year :param date_str: date string :return: queryset of health datas :rtype: queryset"""
date_format = get_date... | the_stack_v2_python_sparse | app/health/models.py | v0y/sport-tracker-with-acziwments | train | 1 | |
2ec8bf069ad3cb19ae038c139c25629bbc1c95d3 | [
"self.count = 0\nself.helper(root, 0, sum)\nreturn self.count",
"if not node:\n return\nif partial + node.val == target:\n self.count += 1\nself.helper(node.left, partial + node.val, target)\nself.helper(node.right, partial + node.val, target)\nself.helper(node.left, 0, target)\nself.helper(node.right, 0, t... | <|body_start_0|>
self.count = 0
self.helper(root, 0, sum)
return self.count
<|end_body_0|>
<|body_start_1|>
if not node:
return
if partial + node.val == target:
self.count += 1
self.helper(node.left, partial + node.val, target)
self.helper... | Solution2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def helper(self, node, partial, target):
"""recursively iterate all nodes and check if previous sum plus current node can achieve the target. If so, increase the... | stack_v2_sparse_classes_36k_train_025686 | 3,257 | no_license | [
{
"docstring": ":type root: TreeNode :type sum: int :rtype: int",
"name": "pathSum",
"signature": "def pathSum(self, root, sum)"
},
{
"docstring": "recursively iterate all nodes and check if previous sum plus current node can achieve the target. If so, increase the count. Then we need to recursi... | 2 | null | Implement the Python class `Solution2` described below.
Class description:
Implement the Solution2 class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def helper(self, node, partial, target): recursively iterate all nodes and check if previous sum... | Implement the Python class `Solution2` described below.
Class description:
Implement the Solution2 class.
Method signatures and docstrings:
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def helper(self, node, partial, target): recursively iterate all nodes and check if previous sum... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution2:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def helper(self, node, partial, target):
"""recursively iterate all nodes and check if previous sum plus current node can achieve the target. If so, increase the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution2:
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
self.count = 0
self.helper(root, 0, sum)
return self.count
def helper(self, node, partial, target):
"""recursively iterate all nodes and check if previous sum plus curren... | the_stack_v2_python_sparse | code437PathSumIII.py | cybelewang/leetcode-python | train | 0 | |
61986e13f0c5d64a20c28c8de5c6fadd24e62153 | [
"recommend_type = kwargs.get('type')\nplaceholder = '{}_placeholder'.format(recommend_type)\nlimit = kwargs.get('limit')\nnow = local_now().strftime('%Y%m%d%H%M%S')\nwords = RecommendWord.objects.filter(is_display=True)\nplaceholder = words.filter(recommend_type=placeholder, start_date__lt=now, end_date__gt=now).va... | <|body_start_0|>
recommend_type = kwargs.get('type')
placeholder = '{}_placeholder'.format(recommend_type)
limit = kwargs.get('limit')
now = local_now().strftime('%Y%m%d%H%M%S')
words = RecommendWord.objects.filter(is_display=True)
placeholder = words.filter(recommend_typ... | RecommendService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecommendService:
def get_recommend_words(self, **kwargs):
"""추천 검색어"""
<|body_0|>
def get_recommend_words_by_dynamodb(self, **kwargs):
"""추천 검색어 ( dynamoDB )"""
<|body_1|>
def get_recommend_products(self):
"""이달의 추천 신제품 목록"""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_025687 | 2,711 | no_license | [
{
"docstring": "추천 검색어",
"name": "get_recommend_words",
"signature": "def get_recommend_words(self, **kwargs)"
},
{
"docstring": "추천 검색어 ( dynamoDB )",
"name": "get_recommend_words_by_dynamodb",
"signature": "def get_recommend_words_by_dynamodb(self, **kwargs)"
},
{
"docstring": ... | 3 | null | Implement the Python class `RecommendService` described below.
Class description:
Implement the RecommendService class.
Method signatures and docstrings:
- def get_recommend_words(self, **kwargs): 추천 검색어
- def get_recommend_words_by_dynamodb(self, **kwargs): 추천 검색어 ( dynamoDB )
- def get_recommend_products(self): 이달의... | Implement the Python class `RecommendService` described below.
Class description:
Implement the RecommendService class.
Method signatures and docstrings:
- def get_recommend_words(self, **kwargs): 추천 검색어
- def get_recommend_words_by_dynamodb(self, **kwargs): 추천 검색어 ( dynamoDB )
- def get_recommend_products(self): 이달의... | 0edc046f57a1c171c10be5dfa4b4e26f440847be | <|skeleton|>
class RecommendService:
def get_recommend_words(self, **kwargs):
"""추천 검색어"""
<|body_0|>
def get_recommend_words_by_dynamodb(self, **kwargs):
"""추천 검색어 ( dynamoDB )"""
<|body_1|>
def get_recommend_products(self):
"""이달의 추천 신제품 목록"""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecommendService:
def get_recommend_words(self, **kwargs):
"""추천 검색어"""
recommend_type = kwargs.get('type')
placeholder = '{}_placeholder'.format(recommend_type)
limit = kwargs.get('limit')
now = local_now().strftime('%Y%m%d%H%M%S')
words = RecommendWord.objects... | the_stack_v2_python_sparse | services/recommends.py | jmp7786/coins | train | 0 | |
7ac1f61cc5da06e0a138292f693c05e36b60b3bc | [
"if p.val > q.val:\n p, q = (q, p)\nwhile root:\n if root.val < p.val:\n root = root.right\n elif root.val > q.val:\n root = root.left\n else:\n break\nreturn root",
"if root.val < p.val and root.val < q.val:\n return self.lowestCommonAncestor_2(root.right, p, q)\nif root.val >... | <|body_start_0|>
if p.val > q.val:
p, q = (q, p)
while root:
if root.val < p.val:
root = root.right
elif root.val > q.val:
root = root.left
else:
break
return root
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lowestCommonAncestor_1(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""时间复杂度 O(N)： 其中 N 为二叉树节点数；每循环一轮排除一层，二叉搜索树的层数最小为 logN （满二叉树）， 最大为 N （退化为链表）。 空间复杂度 O(1)： 使用常数大小的额外空间。 :param root: :param p: :param q: :return:"""
<|body_0|>
def lowest... | stack_v2_sparse_classes_36k_train_025688 | 2,864 | no_license | [
{
"docstring": "时间复杂度 O(N)： 其中 N 为二叉树节点数；每循环一轮排除一层，二叉搜索树的层数最小为 logN （满二叉树）， 最大为 N （退化为链表）。 空间复杂度 O(1)： 使用常数大小的额外空间。 :param root: :param p: :param q: :return:",
"name": "lowestCommonAncestor_1",
"signature": "def lowestCommonAncestor_1(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode'"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor_1(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode': 时间复杂度 O(N)： 其中 N 为二叉树节点数；每循环一轮排除一层，二叉搜索树的层数最小为 logN （满二叉树）， 最大为 N （退化为链表）。 空间复杂度 O... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor_1(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode': 时间复杂度 O(N)： 其中 N 为二叉树节点数；每循环一轮排除一层，二叉搜索树的层数最小为 logN （满二叉树）， 最大为 N （退化为链表）。 空间复杂度 O... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def lowestCommonAncestor_1(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""时间复杂度 O(N)： 其中 N 为二叉树节点数；每循环一轮排除一层，二叉搜索树的层数最小为 logN （满二叉树）， 最大为 N （退化为链表）。 空间复杂度 O(1)： 使用常数大小的额外空间。 :param root: :param p: :param q: :return:"""
<|body_0|>
def lowest... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lowestCommonAncestor_1(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""时间复杂度 O(N)： 其中 N 为二叉树节点数；每循环一轮排除一层，二叉搜索树的层数最小为 logN （满二叉树）， 最大为 N （退化为链表）。 空间复杂度 O(1)： 使用常数大小的额外空间。 :param root: :param p: :param q: :return:"""
if p.val > q.val:
p, q = (q,... | the_stack_v2_python_sparse | 剑指 Offer（第 2 版）/lowestCommonAncestor_I.py | MaoningGuan/LeetCode | train | 3 | |
6b313cea77fe58bdf916cabd52fde3fd25a585e0 | [
"new_instance = self.create(header=header, definition=definition)\nvalue, _ = DataElementValue.objects.from_dicom_parser(data_element)\nnew_instance._values.set(value)\nreturn new_instance",
"definition, _ = DataElementDefinition.objects.from_dicom_parser(data_element)\ntry:\n return self.get(header=header, de... | <|body_start_0|>
new_instance = self.create(header=header, definition=definition)
value, _ = DataElementValue.objects.from_dicom_parser(data_element)
new_instance._values.set(value)
return new_instance
<|end_body_0|>
<|body_start_1|>
definition, _ = DataElementDefinition.objects... | Custom :class:`~django.db.models.Manager` for the :class:`~django_dicom.models.data_element.DataElement` model. | DataElementManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataElementManager:
"""Custom :class:`~django.db.models.Manager` for the :class:`~django_dicom.models.data_element.DataElement` model."""
def create_from_dicom_parser(self, header, definition, data_element: DicomDataElement):
"""Creates a new instance under *header* using the provide... | stack_v2_sparse_classes_36k_train_025689 | 3,104 | permissive | [
{
"docstring": "Creates a new instance under *header* using the provided *definition* and *data_element*. Parameters ---------- header : :class:`~django_dicom.models.header.Header` The header instance with which the created data element should be associated. definition : :class:`~django_dicom.models.data_elemen... | 2 | null | Implement the Python class `DataElementManager` described below.
Class description:
Custom :class:`~django.db.models.Manager` for the :class:`~django_dicom.models.data_element.DataElement` model.
Method signatures and docstrings:
- def create_from_dicom_parser(self, header, definition, data_element: DicomDataElement)... | Implement the Python class `DataElementManager` described below.
Class description:
Custom :class:`~django.db.models.Manager` for the :class:`~django_dicom.models.data_element.DataElement` model.
Method signatures and docstrings:
- def create_from_dicom_parser(self, header, definition, data_element: DicomDataElement)... | cd49a08b1f0efbbb8e05b20ec03d0afc3789cf6f | <|skeleton|>
class DataElementManager:
"""Custom :class:`~django.db.models.Manager` for the :class:`~django_dicom.models.data_element.DataElement` model."""
def create_from_dicom_parser(self, header, definition, data_element: DicomDataElement):
"""Creates a new instance under *header* using the provide... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataElementManager:
"""Custom :class:`~django.db.models.Manager` for the :class:`~django_dicom.models.data_element.DataElement` model."""
def create_from_dicom_parser(self, header, definition, data_element: DicomDataElement):
"""Creates a new instance under *header* using the provided *definition... | the_stack_v2_python_sparse | django_dicom/models/managers/data_element.py | ZviBaratz/django_dicom | train | 8 |
bdf1d1dd1115bdf04fd513be501d8103764d2717 | [
"if destination.is_dirty():\n raise OSError(f'Repo `{destination.working_tree_dir}` is dirty')\nself.source = source\nself.destination = destination\nself.commits_in_order = GetCommitsInOrder(source, head_ref=head_ref)\nself.files_of_interest = files_of_interest\nif not self.commits_in_order:\n raise OSError(... | <|body_start_0|>
if destination.is_dirty():
raise OSError(f'Repo `{destination.working_tree_dir}` is dirty')
self.source = source
self.destination = destination
self.commits_in_order = GetCommitsInOrder(source, head_ref=head_ref)
self.files_of_interest = files_of_inte... | A progressable thread for exporting a subset of a repo's commits. | SubtreeExporter | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubtreeExporter:
"""A progressable thread for exporting a subset of a repo's commits."""
def __init__(self, source: git.Repo, destination: git.Repo, files_of_interest: Set[str], head_ref: str='HEAD'):
"""Constructor. Args: source: The source repository to export from. destination: Th... | stack_v2_sparse_classes_36k_train_025690 | 6,824 | permissive | [
{
"docstring": "Constructor. Args: source: The source repository to export from. destination: The destination repository to export to. files_of_interest: The relpaths of the files to export. head_ref: The commit to export up to.",
"name": "__init__",
"signature": "def __init__(self, source: git.Repo, de... | 2 | stack_v2_sparse_classes_30k_train_005282 | Implement the Python class `SubtreeExporter` described below.
Class description:
A progressable thread for exporting a subset of a repo's commits.
Method signatures and docstrings:
- def __init__(self, source: git.Repo, destination: git.Repo, files_of_interest: Set[str], head_ref: str='HEAD'): Constructor. Args: sour... | Implement the Python class `SubtreeExporter` described below.
Class description:
A progressable thread for exporting a subset of a repo's commits.
Method signatures and docstrings:
- def __init__(self, source: git.Repo, destination: git.Repo, files_of_interest: Set[str], head_ref: str='HEAD'): Constructor. Args: sour... | 913d67f4f454cedc61220a210113bbf0460bb4d5 | <|skeleton|>
class SubtreeExporter:
"""A progressable thread for exporting a subset of a repo's commits."""
def __init__(self, source: git.Repo, destination: git.Repo, files_of_interest: Set[str], head_ref: str='HEAD'):
"""Constructor. Args: source: The source repository to export from. destination: Th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubtreeExporter:
"""A progressable thread for exporting a subset of a repo's commits."""
def __init__(self, source: git.Repo, destination: git.Repo, files_of_interest: Set[str], head_ref: str='HEAD'):
"""Constructor. Args: source: The source repository to export from. destination: The destination... | the_stack_v2_python_sparse | tools/git/export_subtree.py | ChrisCummins/labm8 | train | 3 |
3341f212189aefb222f15433ae144571fa6b52c7 | [
"if not root:\n return None\nhead, tail = self.get_linked_list(root)\nhead.left = tail\ntail.right = head\nreturn head",
"if not node.left and (not node.right):\n return (node, node)\nlhead, ltail = self.get_linked_list(node.left) if node.left else (node, None)\nrhead, rtail = self.get_linked_list(node.righ... | <|body_start_0|>
if not root:
return None
head, tail = self.get_linked_list(root)
head.left = tail
tail.right = head
return head
<|end_body_0|>
<|body_start_1|>
if not node.left and (not node.right):
return (node, node)
lhead, ltail = self... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def treeToDoublyList(self, root):
""":type root: Node :rtype: Node"""
<|body_0|>
def get_linked_list(self, node):
"""Helper function to turn subtree starting at node into linked list. Returns (head, tail) of the linked list."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_025691 | 2,611 | no_license | [
{
"docstring": ":type root: Node :rtype: Node",
"name": "treeToDoublyList",
"signature": "def treeToDoublyList(self, root)"
},
{
"docstring": "Helper function to turn subtree starting at node into linked list. Returns (head, tail) of the linked list.",
"name": "get_linked_list",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_021385 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def treeToDoublyList(self, root): :type root: Node :rtype: Node
- def get_linked_list(self, node): Helper function to turn subtree starting at node into linked list. Returns (hea... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def treeToDoublyList(self, root): :type root: Node :rtype: Node
- def get_linked_list(self, node): Helper function to turn subtree starting at node into linked list. Returns (hea... | eb3fc22450b362703c3322d9e975d191eb324ffc | <|skeleton|>
class Solution:
def treeToDoublyList(self, root):
""":type root: Node :rtype: Node"""
<|body_0|>
def get_linked_list(self, node):
"""Helper function to turn subtree starting at node into linked list. Returns (head, tail) of the linked list."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def treeToDoublyList(self, root):
""":type root: Node :rtype: Node"""
if not root:
return None
head, tail = self.get_linked_list(root)
head.left = tail
tail.right = head
return head
def get_linked_list(self, node):
"""Helper fu... | the_stack_v2_python_sparse | 2-14/426-Convert-Binary-Search-Tree-to-Sorted-DLL.py | whalejasmine/leetcode_python_summary | train | 0 | |
1c64ed9b5b9863a52944e5abddea62a9e264b8ce | [
"self.negword = 'moins '\nself.pointword = 'virgule'\nself.exclude_title = ['et', 'virgule', 'moins']\nself.mid_numwords = [(1000, 'mille'), (100, 'cent'), (80, 'quatre-vingts'), (60, 'soixante'), (50, 'cinquante'), (40, 'quarante'), (30, 'trente')]\nself.low_numwords = ['vingt', 'dix-neuf', 'dix-huit', 'dix-sept',... | <|body_start_0|>
self.negword = 'moins '
self.pointword = 'virgule'
self.exclude_title = ['et', 'virgule', 'moins']
self.mid_numwords = [(1000, 'mille'), (100, 'cent'), (80, 'quatre-vingts'), (60, 'soixante'), (50, 'cinquante'), (40, 'quarante'), (30, 'trente')]
self.low_numwords... | NumWord FR | NumWordFR | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumWordFR:
"""NumWord FR"""
def _setup(self):
"""Setup"""
<|body_0|>
def _merge(self, curr, next):
"""Merge"""
<|body_1|>
def ordinal(self, value):
"""Convert to ordinal"""
<|body_2|>
def ordinal_number(self, value):
"""C... | stack_v2_sparse_classes_36k_train_025692 | 3,430 | permissive | [
{
"docstring": "Setup",
"name": "_setup",
"signature": "def _setup(self)"
},
{
"docstring": "Merge",
"name": "_merge",
"signature": "def _merge(self, curr, next)"
},
{
"docstring": "Convert to ordinal",
"name": "ordinal",
"signature": "def ordinal(self, value)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_006757 | Implement the Python class `NumWordFR` described below.
Class description:
NumWord FR
Method signatures and docstrings:
- def _setup(self): Setup
- def _merge(self, curr, next): Merge
- def ordinal(self, value): Convert to ordinal
- def ordinal_number(self, value): Convert to ordinal number
- def currency(self, val, ... | Implement the Python class `NumWordFR` described below.
Class description:
NumWord FR
Method signatures and docstrings:
- def _setup(self): Setup
- def _merge(self, curr, next): Merge
- def ordinal(self, value): Convert to ordinal
- def ordinal_number(self, value): Convert to ordinal number
- def currency(self, val, ... | bdf0d633663d289a6cb9ed10c1529afb086d410f | <|skeleton|>
class NumWordFR:
"""NumWord FR"""
def _setup(self):
"""Setup"""
<|body_0|>
def _merge(self, curr, next):
"""Merge"""
<|body_1|>
def ordinal(self, value):
"""Convert to ordinal"""
<|body_2|>
def ordinal_number(self, value):
"""C... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumWordFR:
"""NumWord FR"""
def _setup(self):
"""Setup"""
self.negword = 'moins '
self.pointword = 'virgule'
self.exclude_title = ['et', 'virgule', 'moins']
self.mid_numwords = [(1000, 'mille'), (100, 'cent'), (80, 'quatre-vingts'), (60, 'soixante'), (50, 'cinquant... | the_stack_v2_python_sparse | venv/lib/python3.7/site-packages/numword/numword_fr.py | Spam-Slayers/Newsify | train | 0 |
e19a4c76ea0dd20b861f67b3f9a3cafe5dbe0d4e | [
"start = end = 0\nans = 0\nwhile start < len(A):\n end = start\n while end + 1 < len(A) and A[end] < A[end + 1]:\n end += 1\n if end + 1 < len(A) and A[end] > A[end + 1]:\n while end + 1 < N and A[end] > A[end + 1]:\n end += 1\n ans = max(ans, end - start + 1)\n start = m... | <|body_start_0|>
start = end = 0
ans = 0
while start < len(A):
end = start
while end + 1 < len(A) and A[end] < A[end + 1]:
end += 1
if end + 1 < len(A) and A[end] > A[end + 1]:
while end + 1 < N and A[end] > A[end + 1]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestMountain(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def longestMountain_two_pass(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
start = end = 0
ans = 0
... | stack_v2_sparse_classes_36k_train_025693 | 1,838 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "longestMountain",
"signature": "def longestMountain(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: int",
"name": "longestMountain_two_pass",
"signature": "def longestMountain_two_pass(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestMountain(self, A): :type A: List[int] :rtype: int
- def longestMountain_two_pass(self, A): :type A: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestMountain(self, A): :type A: List[int] :rtype: int
- def longestMountain_two_pass(self, A): :type A: List[int] :rtype: int
<|skeleton|>
class Solution:
def longes... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def longestMountain(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def longestMountain_two_pass(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestMountain(self, A):
""":type A: List[int] :rtype: int"""
start = end = 0
ans = 0
while start < len(A):
end = start
while end + 1 < len(A) and A[end] < A[end + 1]:
end += 1
if end + 1 < len(A) and A[end] > A... | the_stack_v2_python_sparse | medium/twopointer/test_845_Longest_Mountain_in_Array.py | wuxu1019/leetcode_sophia | train | 1 | |
483be93f8565deca77f31e4507bc0f156594ca94 | [
"Parametre.__init__(self, 'email', 'email')\nself.tronquer = True\nself.schema = '<etat>'\nself.aide_courte = \"active / désactive l'envoi d'e-mails\"\nself.aide_longue = \"Cette commande permet d'activer ou désactiver l'envoi d'e-mails à ce compte en cas de réception d'un UmdMail. Si cette option est active, un e-... | <|body_start_0|>
Parametre.__init__(self, 'email', 'email')
self.tronquer = True
self.schema = '<etat>'
self.aide_courte = "active / désactive l'envoi d'e-mails"
self.aide_longue = "Cette commande permet d'activer ou désactiver l'envoi d'e-mails à ce compte en cas de réception d'... | Commande 'options email'. | PrmEmail | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmEmail:
"""Commande 'options email'."""
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._... | stack_v2_sparse_classes_36k_train_025694 | 3,177 | 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 | stack_v2_sparse_classes_30k_train_004221 | Implement the Python class `PrmEmail` described below.
Class description:
Commande 'options email'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre.
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre. | Implement the Python class `PrmEmail` described below.
Class description:
Commande 'options email'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre.
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre.
<|skeleton|>
class PrmEmail:
"""Commande 'options e... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmEmail:
"""Commande 'options email'."""
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 PrmEmail:
"""Commande 'options email'."""
def __init__(self):
"""Constructeur du paramètre."""
Parametre.__init__(self, 'email', 'email')
self.tronquer = True
self.schema = '<etat>'
self.aide_courte = "active / désactive l'envoi d'e-mails"
self.aide_longue ... | the_stack_v2_python_sparse | src/primaires/joueur/commandes/options/email.py | vincent-lg/tsunami | train | 5 |
60e3f8764853e5156982855ae193d1cdba1ed48f | [
"super(Instance, self).__init__(resource_id=instance_id, resource_type=resource.ResourceType.INSTANCE, name=kwargs.get('name'), display_name=kwargs.get('name'), parent=parent, locations=kwargs.get('locations'))\nif parent and parent.type != 'project':\n raise TypeError('Unexpected parent type: got {}, want proje... | <|body_start_0|>
super(Instance, self).__init__(resource_id=instance_id, resource_type=resource.ResourceType.INSTANCE, name=kwargs.get('name'), display_name=kwargs.get('name'), parent=parent, locations=kwargs.get('locations'))
if parent and parent.type != 'project':
raise TypeError('Unexpect... | Represents Instance resource. | Instance | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Instance:
"""Represents Instance resource."""
def __init__(self, instance_id, parent=None, **kwargs):
"""Instance resource. Args: instance_id (str): id of the instance. parent (Resource): Parent resource of this instance. Should be a project. **kwargs (dict): The object's attributes.... | stack_v2_sparse_classes_36k_train_025695 | 10,814 | permissive | [
{
"docstring": "Instance resource. Args: instance_id (str): id of the instance. parent (Resource): Parent resource of this instance. Should be a project. **kwargs (dict): The object's attributes. Raises: TypeError: If unexpected parent type.",
"name": "__init__",
"signature": "def __init__(self, instanc... | 6 | stack_v2_sparse_classes_30k_train_001282 | Implement the Python class `Instance` described below.
Class description:
Represents Instance resource.
Method signatures and docstrings:
- def __init__(self, instance_id, parent=None, **kwargs): Instance resource. Args: instance_id (str): id of the instance. parent (Resource): Parent resource of this instance. Shoul... | Implement the Python class `Instance` described below.
Class description:
Represents Instance resource.
Method signatures and docstrings:
- def __init__(self, instance_id, parent=None, **kwargs): Instance resource. Args: instance_id (str): id of the instance. parent (Resource): Parent resource of this instance. Shoul... | d4421afa50a17ed47cbebe942044ebab3720e0f5 | <|skeleton|>
class Instance:
"""Represents Instance resource."""
def __init__(self, instance_id, parent=None, **kwargs):
"""Instance resource. Args: instance_id (str): id of the instance. parent (Resource): Parent resource of this instance. Should be a project. **kwargs (dict): The object's attributes.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Instance:
"""Represents Instance resource."""
def __init__(self, instance_id, parent=None, **kwargs):
"""Instance resource. Args: instance_id (str): id of the instance. parent (Resource): Parent resource of this instance. Should be a project. **kwargs (dict): The object's attributes. Raises: Type... | the_stack_v2_python_sparse | google/cloud/forseti/common/gcp_type/instance.py | kevensen/forseti-security | train | 1 |
7bc1783af65e3191d92d49d03a6a53ff5acd504c | [
"super().__init__()\nself.pre_ln_attn = nn.LayerNorm(n_hidden)\nself.pre_ln_ffn = nn.LayerNorm(n_hidden)\nself.attention = AttentionLayer(n_hidden, n_heads)\nself.ffn = FFNLayer(n_hidden)",
"residual = x\nattn = self.attention(self.pre_ln_attn(x))\nffn = self.ffn(self.pre_ln_ffn(x))\nreturn attn + ffn + residual"... | <|body_start_0|>
super().__init__()
self.pre_ln_attn = nn.LayerNorm(n_hidden)
self.pre_ln_ffn = nn.LayerNorm(n_hidden)
self.attention = AttentionLayer(n_hidden, n_heads)
self.ffn = FFNLayer(n_hidden)
<|end_body_0|>
<|body_start_1|>
residual = x
attn = self.attent... | ## Transformer Layer | TransformerLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerLayer:
"""## Transformer Layer"""
def __init__(self, n_hidden: int=6144, n_heads: int=64):
""":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*."""
<|body_0|>
def forward(self, x: torch.T... | stack_v2_sparse_classes_36k_train_025696 | 13,522 | no_license | [
{
"docstring": ":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*.",
"name": "__init__",
"signature": "def __init__(self, n_hidden: int=6144, n_heads: int=64)"
},
{
"docstring": ":param x: are the embeddings of shape `[batc... | 3 | stack_v2_sparse_classes_30k_train_004031 | Implement the Python class `TransformerLayer` described below.
Class description:
## Transformer Layer
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144, n_heads: int=64): :param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*... | Implement the Python class `TransformerLayer` described below.
Class description:
## Transformer Layer
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144, n_heads: int=64): :param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class TransformerLayer:
"""## Transformer Layer"""
def __init__(self, n_hidden: int=6144, n_heads: int=64):
""":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*."""
<|body_0|>
def forward(self, x: torch.T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformerLayer:
"""## Transformer Layer"""
def __init__(self, n_hidden: int=6144, n_heads: int=64):
""":param n_hidden: is the embedding size :param n_heads: is the number of heads *Out implementation doesn't include dropout*."""
super().__init__()
self.pre_ln_attn = nn.LayerNor... | the_stack_v2_python_sparse | generated/test_labmlai_neox.py | jansel/pytorch-jit-paritybench | train | 35 |
904a70e65d34af2744309ad0fb649a5f7c54ce73 | [
"if not root:\n return None\nrootNode = TreeNode(root.val)\nif len(root.children) > 0:\n firstChild = root.children[0]\n rootNode.left = self.encode(firstChild)\ncurr = rootNode.left\nfor i in range(1, len(root.children)):\n curr.right = self.encode(root.children[i])\n curr = curr.right\nreturn rootN... | <|body_start_0|>
if not root:
return None
rootNode = TreeNode(root.val)
if len(root.children) > 0:
firstChild = root.children[0]
rootNode.left = self.encode(firstChild)
curr = rootNode.left
for i in range(1, len(root.children)):
cur... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
<|body_0|>
def decode(self, data):
"""Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_025697 | 3,222 | no_license | [
{
"docstring": "Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode",
"name": "encode",
"signature": "def encode(self, root)"
},
{
"docstring": "Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node",
"name": "decode",
"signature": "def decode... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, root): Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode
- def decode(self, data): Decodes your binary tree to an n-ary tree. :type data: TreeN... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, root): Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode
- def decode(self, data): Decodes your binary tree to an n-ary tree. :type data: TreeN... | 44765a7d89423b7ec2c159f70b1a6f6e446523c2 | <|skeleton|>
class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
<|body_0|>
def decode(self, data):
"""Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
if not root:
return None
rootNode = TreeNode(root.val)
if len(root.children) > 0:
firstChild = root.children[0]
rootNode.left = sel... | the_stack_v2_python_sparse | python/_0001_0500/0431_encode-n-ary-tree-to-binary-tree.py | Wang-Yann/LeetCodeMe | train | 0 | |
0996e31f12ab51a6a7af4eaf175549f278da21b8 | [
"result = do(self, platform)\nlogging.info('GET charge result: %s' % result)\nself.write(result)",
"result = do(self, platform)\nlogging.info('POST charge result: %s' % result)\nself.write(result)"
] | <|body_start_0|>
result = do(self, platform)
logging.info('GET charge result: %s' % result)
self.write(result)
<|end_body_0|>
<|body_start_1|>
result = do(self, platform)
logging.info('POST charge result: %s' % result)
self.write(result)
<|end_body_1|>
| Notification | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Notification:
def get(self, platform):
"""1.易接SDK支付: alliance.xtzj.luckyfuturetech.com/notification/EZ?app=1234567890ABCDEF&cbi=CBI123456&ct=1376578903&fee=100&pt=1376577801&ssid=123456&st=1&tcd=137657AVDEDFS&uid=1234&ver=1&sign=xxxxxxxxxxx"""
<|body_0|>
def post(self, platf... | stack_v2_sparse_classes_36k_train_025698 | 1,263 | no_license | [
{
"docstring": "1.易接SDK支付: alliance.xtzj.luckyfuturetech.com/notification/EZ?app=1234567890ABCDEF&cbi=CBI123456&ct=1376578903&fee=100&pt=1376577801&ssid=123456&st=1&tcd=137657AVDEDFS&uid=1234&ver=1&sign=xxxxxxxxxxx",
"name": "get",
"signature": "def get(self, platform)"
},
{
"docstring": "1.XY S... | 2 | stack_v2_sparse_classes_30k_train_014654 | Implement the Python class `Notification` described below.
Class description:
Implement the Notification class.
Method signatures and docstrings:
- def get(self, platform): 1.易接SDK支付: alliance.xtzj.luckyfuturetech.com/notification/EZ?app=1234567890ABCDEF&cbi=CBI123456&ct=1376578903&fee=100&pt=1376577801&ssid=123456&s... | Implement the Python class `Notification` described below.
Class description:
Implement the Notification class.
Method signatures and docstrings:
- def get(self, platform): 1.易接SDK支付: alliance.xtzj.luckyfuturetech.com/notification/EZ?app=1234567890ABCDEF&cbi=CBI123456&ct=1376578903&fee=100&pt=1376577801&ssid=123456&s... | 4f430d5631b1118ad251bdaf8384bc0dbdaf07b9 | <|skeleton|>
class Notification:
def get(self, platform):
"""1.易接SDK支付: alliance.xtzj.luckyfuturetech.com/notification/EZ?app=1234567890ABCDEF&cbi=CBI123456&ct=1376578903&fee=100&pt=1376577801&ssid=123456&st=1&tcd=137657AVDEDFS&uid=1234&ver=1&sign=xxxxxxxxxxx"""
<|body_0|>
def post(self, platf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Notification:
def get(self, platform):
"""1.易接SDK支付: alliance.xtzj.luckyfuturetech.com/notification/EZ?app=1234567890ABCDEF&cbi=CBI123456&ct=1376578903&fee=100&pt=1376577801&ssid=123456&st=1&tcd=137657AVDEDFS&uid=1234&ver=1&sign=xxxxxxxxxxx"""
result = do(self, platform)
logging.info('... | the_stack_v2_python_sparse | server/apps/handlers/charge.py | wade333777/cocos-js-tips | train | 0 | |
f6defbd42a86546d088088fc7ebc7498d386340b | [
"results = []\nall_meals = Meal.list_all_meals()\ntry:\n menu = Menu.find_by_id(menu_id)\n if not menu:\n raise MealError.NotFound('Menu does not exist yet! Create one?')\n if all_meals:\n for meal in all_meals:\n obj = Response.define_meal(meal)\n results.append(obj)\n ... | <|body_start_0|>
results = []
all_meals = Meal.list_all_meals()
try:
menu = Menu.find_by_id(menu_id)
if not menu:
raise MealError.NotFound('Menu does not exist yet! Create one?')
if all_meals:
for meal in all_meals:
... | Contains GET and POST methods | MealsView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MealsView:
"""Contains GET and POST methods"""
def get(self, menu_id):
"""Endpoint for fetching all meals."""
<|body_0|>
def post(self, menu_id, user_id):
"""Endpoint for adding a new meal."""
<|body_1|>
def delete(self, menu_id, user_id):
""... | stack_v2_sparse_classes_36k_train_025699 | 6,144 | no_license | [
{
"docstring": "Endpoint for fetching all meals.",
"name": "get",
"signature": "def get(self, menu_id)"
},
{
"docstring": "Endpoint for adding a new meal.",
"name": "post",
"signature": "def post(self, menu_id, user_id)"
},
{
"docstring": "Endpoint for deleting all meals.",
"... | 3 | stack_v2_sparse_classes_30k_train_018177 | Implement the Python class `MealsView` described below.
Class description:
Contains GET and POST methods
Method signatures and docstrings:
- def get(self, menu_id): Endpoint for fetching all meals.
- def post(self, menu_id, user_id): Endpoint for adding a new meal.
- def delete(self, menu_id, user_id): Endpoint for d... | Implement the Python class `MealsView` described below.
Class description:
Contains GET and POST methods
Method signatures and docstrings:
- def get(self, menu_id): Endpoint for fetching all meals.
- def post(self, menu_id, user_id): Endpoint for adding a new meal.
- def delete(self, menu_id, user_id): Endpoint for d... | b98a0fbaa7b881e7f39152cc4f7846cfac3e8029 | <|skeleton|>
class MealsView:
"""Contains GET and POST methods"""
def get(self, menu_id):
"""Endpoint for fetching all meals."""
<|body_0|>
def post(self, menu_id, user_id):
"""Endpoint for adding a new meal."""
<|body_1|>
def delete(self, menu_id, user_id):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MealsView:
"""Contains GET and POST methods"""
def get(self, menu_id):
"""Endpoint for fetching all meals."""
results = []
all_meals = Meal.list_all_meals()
try:
menu = Menu.find_by_id(menu_id)
if not menu:
raise MealError.NotFound('... | the_stack_v2_python_sparse | app/api/v2/views/meal.py | mashafrancis/fast-food-fast-api | train | 0 |
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