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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0456f52a5aba090e3fce44ca6e21a59434e04914 | [
"rest_utils.validate_inputs({'blueprint_id': blueprint_id})\nvisibility = rest_utils.get_visibility_parameter(optional=True, is_argument=True, valid_values=VisibilityState.STATES)\nreturn UploadedBlueprintsManager().receive_uploaded_data(data_id=blueprint_id, visibility=visibility)",
"query_args = get_args_and_ve... | <|body_start_0|>
rest_utils.validate_inputs({'blueprint_id': blueprint_id})
visibility = rest_utils.get_visibility_parameter(optional=True, is_argument=True, valid_values=VisibilityState.STATES)
return UploadedBlueprintsManager().receive_uploaded_data(data_id=blueprint_id, visibility=visibility)... | BlueprintsId | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlueprintsId:
def put(self, blueprint_id, **kwargs):
"""Upload a blueprint (id specified)"""
<|body_0|>
def delete(self, blueprint_id, **kwargs):
"""Delete blueprint by id"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
rest_utils.validate_inputs({'... | stack_v2_sparse_classes_36k_train_012700 | 4,110 | permissive | [
{
"docstring": "Upload a blueprint (id specified)",
"name": "put",
"signature": "def put(self, blueprint_id, **kwargs)"
},
{
"docstring": "Delete blueprint by id",
"name": "delete",
"signature": "def delete(self, blueprint_id, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002298 | Implement the Python class `BlueprintsId` described below.
Class description:
Implement the BlueprintsId class.
Method signatures and docstrings:
- def put(self, blueprint_id, **kwargs): Upload a blueprint (id specified)
- def delete(self, blueprint_id, **kwargs): Delete blueprint by id | Implement the Python class `BlueprintsId` described below.
Class description:
Implement the BlueprintsId class.
Method signatures and docstrings:
- def put(self, blueprint_id, **kwargs): Upload a blueprint (id specified)
- def delete(self, blueprint_id, **kwargs): Delete blueprint by id
<|skeleton|>
class Blueprints... | 3e062e8dec16c89d2ab180d0b761cbf76d3f7ddc | <|skeleton|>
class BlueprintsId:
def put(self, blueprint_id, **kwargs):
"""Upload a blueprint (id specified)"""
<|body_0|>
def delete(self, blueprint_id, **kwargs):
"""Delete blueprint by id"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlueprintsId:
def put(self, blueprint_id, **kwargs):
"""Upload a blueprint (id specified)"""
rest_utils.validate_inputs({'blueprint_id': blueprint_id})
visibility = rest_utils.get_visibility_parameter(optional=True, is_argument=True, valid_values=VisibilityState.STATES)
return ... | the_stack_v2_python_sparse | rest-service/manager_rest/rest/resources_v3_1/blueprints.py | TS-at-WS/cloudify-manager | train | 0 | |
9601099aeb23c6effaa1c726a3cd6e6a0d2e52be | [
"if x < 0:\n return False\nif x < 10:\n return True\nl = []\nl.append(x % 10)\nx //= 10\nwhile x != 0:\n l.append(x % 10)\n x //= 10\nleft = 0\nright = len(l) - 1\nwhile left <= right:\n if l[left] != l[right]:\n return False\n left += 1\n right -= 1\nreturn True",
"if x < 0:\n retu... | <|body_start_0|>
if x < 0:
return False
if x < 10:
return True
l = []
l.append(x % 10)
x //= 10
while x != 0:
l.append(x % 10)
x //= 10
left = 0
right = len(l) - 1
while left <= right:
if ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def isPalindrome0(self, x):
""":type x: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x < 0:
return False
if x < 10:
... | stack_v2_sparse_classes_36k_train_012701 | 1,118 | no_license | [
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, x)"
},
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome0",
"signature": "def isPalindrome0(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014705 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def isPalindrome0(self, x): :type x: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def isPalindrome0(self, x): :type x: int :rtype: bool
<|skeleton|>
class Solution:
def isPalindrome(self, x):
... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def isPalindrome0(self, x):
""":type x: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
if x < 0:
return False
if x < 10:
return True
l = []
l.append(x % 10)
x //= 10
while x != 0:
l.append(x % 10)
x //= 10
left = 0
... | the_stack_v2_python_sparse | 9.回文数.py | yangyuxiang1996/leetcode | train | 0 | |
69d16ae20e4310f10b9ae804afebc7875377f2a9 | [
"logger.debug('Visiting %s', self.novel_url)\nsoup = self.get_soup(self.novel_url)\nself.novel_title = soup.select_one('.desc h5').text\nlogger.info('Novel title: %s', self.novel_title)\nself.novel_cover = self.absolute_url(soup.select_one('.about-author .row img')['src'])\nlogger.info('Novel cover: %s', self.novel... | <|body_start_0|>
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
self.novel_title = soup.select_one('.desc h5').text
logger.info('Novel title: %s', self.novel_title)
self.novel_cover = self.absolute_url(soup.select_one('.about-author .row img')['s... | MachineNovelTrans | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachineNovelTrans:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_0|>
def download_chapter_body(self, chapter):
"""Download body of a single chapter and return as clean html format."""
<|body_1|>
def format_text(self, text):
... | stack_v2_sparse_classes_36k_train_012702 | 2,664 | permissive | [
{
"docstring": "Get novel title, autor, cover etc",
"name": "read_novel_info",
"signature": "def read_novel_info(self)"
},
{
"docstring": "Download body of a single chapter and return as clean html format.",
"name": "download_chapter_body",
"signature": "def download_chapter_body(self, c... | 3 | stack_v2_sparse_classes_30k_train_000818 | Implement the Python class `MachineNovelTrans` described below.
Class description:
Implement the MachineNovelTrans class.
Method signatures and docstrings:
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_chapter_body(self, chapter): Download body of a single chapter and return as clean h... | Implement the Python class `MachineNovelTrans` described below.
Class description:
Implement the MachineNovelTrans class.
Method signatures and docstrings:
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_chapter_body(self, chapter): Download body of a single chapter and return as clean h... | 451e816ab03c8466be90f6f0b3eaa52d799140ce | <|skeleton|>
class MachineNovelTrans:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_0|>
def download_chapter_body(self, chapter):
"""Download body of a single chapter and return as clean html format."""
<|body_1|>
def format_text(self, text):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MachineNovelTrans:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
self.novel_title = soup.select_one('.desc h5').text
logger.info('Novel title: %s', self.novel_title)
... | the_stack_v2_python_sparse | lncrawl/sources/machinetrans.py | NNTin/lightnovel-crawler | train | 2 | |
1aaddf45d4a3ee8cfe7bdcd7366062735e914f2b | [
"path = app.config['USER_HOME_PATH']\nusers = [o for o in os.listdir(path) if os.path.isdir(path + '/' + o) and (not os.path.islink(path + '/' + o))]\nfor user in users:\n User(user)",
"home_path = app.config['USER_HOME_PATH']\ntemp_path = app.config['USER_TEMP_PATH']\nusers = [(o, False) for o in os.listdir(h... | <|body_start_0|>
path = app.config['USER_HOME_PATH']
users = [o for o in os.listdir(path) if os.path.isdir(path + '/' + o) and (not os.path.islink(path + '/' + o))]
for user in users:
User(user)
<|end_body_0|>
<|body_start_1|>
home_path = app.config['USER_HOME_PATH']
... | User service class | UserService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserService:
"""User service class"""
def find_users_in_home_path():
"""Create a new user for every user in home path"""
<|body_0|>
def sync_users():
"""Create a new index if a new filesystem is found and sync it. Delete the index if the filesystem has been remov... | stack_v2_sparse_classes_36k_train_012703 | 2,958 | permissive | [
{
"docstring": "Create a new user for every user in home path",
"name": "find_users_in_home_path",
"signature": "def find_users_in_home_path()"
},
{
"docstring": "Create a new index if a new filesystem is found and sync it. Delete the index if the filesystem has been removed.",
"name": "sync... | 2 | stack_v2_sparse_classes_30k_train_015017 | Implement the Python class `UserService` described below.
Class description:
User service class
Method signatures and docstrings:
- def find_users_in_home_path(): Create a new user for every user in home path
- def sync_users(): Create a new index if a new filesystem is found and sync it. Delete the index if the file... | Implement the Python class `UserService` described below.
Class description:
User service class
Method signatures and docstrings:
- def find_users_in_home_path(): Create a new user for every user in home path
- def sync_users(): Create a new index if a new filesystem is found and sync it. Delete the index if the file... | ed59a95071455abaf53dca5bb999364509fd9fcd | <|skeleton|>
class UserService:
"""User service class"""
def find_users_in_home_path():
"""Create a new user for every user in home path"""
<|body_0|>
def sync_users():
"""Create a new index if a new filesystem is found and sync it. Delete the index if the filesystem has been remov... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserService:
"""User service class"""
def find_users_in_home_path():
"""Create a new user for every user in home path"""
path = app.config['USER_HOME_PATH']
users = [o for o in os.listdir(path) if os.path.isdir(path + '/' + o) and (not os.path.islink(path + '/' + o))]
for ... | the_stack_v2_python_sparse | services/user_service.py | olavgg/py-sth | train | 0 |
269c9c5f8d21277d3660bbd9fd6d464a19b70b4c | [
"if self.request.method == 'GET':\n return [permissions.IsAuthenticated(), IsCasePatientOrDoctor(self.kwargs['case_id'])]\nif self.request.method == 'POST':\n return (permissions.IsAuthenticated(), IsFollowUpDoctor())\nreturn (permissions.IsAuthenticated(), IsFollowUpDoctor())",
"queryset = FollowUp.objects... | <|body_start_0|>
if self.request.method == 'GET':
return [permissions.IsAuthenticated(), IsCasePatientOrDoctor(self.kwargs['case_id'])]
if self.request.method == 'POST':
return (permissions.IsAuthenticated(), IsFollowUpDoctor())
return (permissions.IsAuthenticated(), IsFo... | Guidelines CRUD | FollowUpViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FollowUpViewSet:
"""Guidelines CRUD"""
def get_permissions(self):
"""Patients and doctors can view followup Doctors and Surgeons can create/update/delete followup"""
<|body_0|>
def get_queryset(self):
"""queryset returns only case's follow up type filter status f... | stack_v2_sparse_classes_36k_train_012704 | 15,503 | no_license | [
{
"docstring": "Patients and doctors can view followup Doctors and Surgeons can create/update/delete followup",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "queryset returns only case's follow up type filter status filter",
"name": "get_queryset",
... | 3 | stack_v2_sparse_classes_30k_train_019924 | Implement the Python class `FollowUpViewSet` described below.
Class description:
Guidelines CRUD
Method signatures and docstrings:
- def get_permissions(self): Patients and doctors can view followup Doctors and Surgeons can create/update/delete followup
- def get_queryset(self): queryset returns only case's follow up... | Implement the Python class `FollowUpViewSet` described below.
Class description:
Guidelines CRUD
Method signatures and docstrings:
- def get_permissions(self): Patients and doctors can view followup Doctors and Surgeons can create/update/delete followup
- def get_queryset(self): queryset returns only case's follow up... | 413664d4e77020c8fcb6bf95e31e3ff9908e2b60 | <|skeleton|>
class FollowUpViewSet:
"""Guidelines CRUD"""
def get_permissions(self):
"""Patients and doctors can view followup Doctors and Surgeons can create/update/delete followup"""
<|body_0|>
def get_queryset(self):
"""queryset returns only case's follow up type filter status f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FollowUpViewSet:
"""Guidelines CRUD"""
def get_permissions(self):
"""Patients and doctors can view followup Doctors and Surgeons can create/update/delete followup"""
if self.request.method == 'GET':
return [permissions.IsAuthenticated(), IsCasePatientOrDoctor(self.kwargs['case... | the_stack_v2_python_sparse | noccapp/views/case.py | otto-torino/nocc-server | train | 0 |
d4b2213318342a9176baf7a8f2e8b12dfcdaef31 | [
"self.cmp_name = cmp_name\nself.click_element(*self.workflow_manage_loc)\nself.scrollToElement('xpath', self.moveto_newSalesOrderMng_loc)\nself.click_element(*self.newSalesOrderMng_loc)\nself.setWaitTime(10)\nself.switchToOneFrameByXpath(self.salesOrderList_frame_loc)\nself.input_value(self.client_search_loc, cmp_n... | <|body_start_0|>
self.cmp_name = cmp_name
self.click_element(*self.workflow_manage_loc)
self.scrollToElement('xpath', self.moveto_newSalesOrderMng_loc)
self.click_element(*self.newSalesOrderMng_loc)
self.setWaitTime(10)
self.switchToOneFrameByXpath(self.salesOrderList_fra... | SalesBargainPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SalesBargainPage:
def CreateSalesBargainResult(self, cmp_name):
"""创建销售喜报"""
<|body_0|>
def inputSalesBarginDetail(self):
"""弹出窗，填写喜报详情"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.cmp_name = cmp_name
self.click_element(*self.workflo... | stack_v2_sparse_classes_36k_train_012705 | 3,444 | no_license | [
{
"docstring": "创建销售喜报",
"name": "CreateSalesBargainResult",
"signature": "def CreateSalesBargainResult(self, cmp_name)"
},
{
"docstring": "弹出窗，填写喜报详情",
"name": "inputSalesBarginDetail",
"signature": "def inputSalesBarginDetail(self)"
}
] | 2 | null | Implement the Python class `SalesBargainPage` described below.
Class description:
Implement the SalesBargainPage class.
Method signatures and docstrings:
- def CreateSalesBargainResult(self, cmp_name): 创建销售喜报
- def inputSalesBarginDetail(self): 弹出窗，填写喜报详情 | Implement the Python class `SalesBargainPage` described below.
Class description:
Implement the SalesBargainPage class.
Method signatures and docstrings:
- def CreateSalesBargainResult(self, cmp_name): 创建销售喜报
- def inputSalesBarginDetail(self): 弹出窗，填写喜报详情
<|skeleton|>
class SalesBargainPage:
def CreateSalesBarg... | a2ae1b26a90f321ea692b716bdeccdd9973331c5 | <|skeleton|>
class SalesBargainPage:
def CreateSalesBargainResult(self, cmp_name):
"""创建销售喜报"""
<|body_0|>
def inputSalesBarginDetail(self):
"""弹出窗，填写喜报详情"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SalesBargainPage:
def CreateSalesBargainResult(self, cmp_name):
"""创建销售喜报"""
self.cmp_name = cmp_name
self.click_element(*self.workflow_manage_loc)
self.scrollToElement('xpath', self.moveto_newSalesOrderMng_loc)
self.click_element(*self.newSalesOrderMng_loc)
sel... | the_stack_v2_python_sparse | test_case/page_obj/createSalesBragainResultPage.py | ykbfb/DFSS_Auto_Test_BDD | train | 0 | |
67495304b0a2d841043606f93e7787b974301a39 | [
"ctx.num_sync_devices = num_sync_devices\nctx.num_groups = num_groups\ninput_list = [torch.zeros_like(input) for k in range(du.get_local_size())]\ndist.all_gather(input_list, input, async_op=False, group=du._LOCAL_PROCESS_GROUP)\ninputs = torch.stack(input_list, dim=0)\nif num_groups > 1:\n rank = du.get_local_r... | <|body_start_0|>
ctx.num_sync_devices = num_sync_devices
ctx.num_groups = num_groups
input_list = [torch.zeros_like(input) for k in range(du.get_local_size())]
dist.all_gather(input_list, input, async_op=False, group=du._LOCAL_PROCESS_GROUP)
inputs = torch.stack(input_list, dim=0... | GroupGather performs all gather on each of the local process/ GPU groups. | GroupGather | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupGather:
"""GroupGather performs all gather on each of the local process/ GPU groups."""
def forward(ctx, input, num_sync_devices, num_groups):
"""Perform forwarding, gathering the stats across different process/ GPU group."""
<|body_0|>
def backward(ctx, grad_output... | stack_v2_sparse_classes_36k_train_012706 | 7,462 | permissive | [
{
"docstring": "Perform forwarding, gathering the stats across different process/ GPU group.",
"name": "forward",
"signature": "def forward(ctx, input, num_sync_devices, num_groups)"
},
{
"docstring": "Perform backwarding, gathering the gradients across different process/ GPU group.",
"name"... | 2 | stack_v2_sparse_classes_30k_train_015500 | Implement the Python class `GroupGather` described below.
Class description:
GroupGather performs all gather on each of the local process/ GPU groups.
Method signatures and docstrings:
- def forward(ctx, input, num_sync_devices, num_groups): Perform forwarding, gathering the stats across different process/ GPU group.... | Implement the Python class `GroupGather` described below.
Class description:
GroupGather performs all gather on each of the local process/ GPU groups.
Method signatures and docstrings:
- def forward(ctx, input, num_sync_devices, num_groups): Perform forwarding, gathering the stats across different process/ GPU group.... | 03279afc8d16509bf54cd9142304cd2d403f6e93 | <|skeleton|>
class GroupGather:
"""GroupGather performs all gather on each of the local process/ GPU groups."""
def forward(ctx, input, num_sync_devices, num_groups):
"""Perform forwarding, gathering the stats across different process/ GPU group."""
<|body_0|>
def backward(ctx, grad_output... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupGather:
"""GroupGather performs all gather on each of the local process/ GPU groups."""
def forward(ctx, input, num_sync_devices, num_groups):
"""Perform forwarding, gathering the stats across different process/ GPU group."""
ctx.num_sync_devices = num_sync_devices
ctx.num_gr... | the_stack_v2_python_sparse | models/SlowFast/slowfast/models/batchnorm_helper.py | artest08/LateTemporalModeling3DCNN | train | 171 |
50108bb4abdbde0a4433781c7ec232b9b8204af7 | [
"super(ConstraintSolver, self).__init__(constraint_list, dt)\nself.tolerance = tolerance\nself.maxit = maxit\nself.norm_order = norm_order",
"p = dstrip(self.beads.p[0]).copy()\nself.beads.p.hold()\nfor constr in self.constraint_list:\n dg = dstrip(constr.Dg)\n ic = constr.i3_unique\n b = np.dot(dg, p[ic... | <|body_start_0|>
super(ConstraintSolver, self).__init__(constraint_list, dt)
self.tolerance = tolerance
self.maxit = maxit
self.norm_order = norm_order
<|end_body_0|>
<|body_start_1|>
p = dstrip(self.beads.p[0]).copy()
self.beads.p.hold()
for constr in self.const... | An implementation of a constraint solver that uses M-RATTLE to impose constraints onto the momenta and a quasi-Newton method to impose constraints onto the positions. The constraint is applied sparsely, i.e. on each block of constraints separately. For implementation details of M-RATTLE see H. C. Andersen, J. Comput. P... | ConstraintSolver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConstraintSolver:
"""An implementation of a constraint solver that uses M-RATTLE to impose constraints onto the momenta and a quasi-Newton method to impose constraints onto the positions. The constraint is applied sparsely, i.e. on each block of constraints separately. For implementation details ... | stack_v2_sparse_classes_36k_train_012707 | 19,035 | no_license | [
{
"docstring": "Solver options include a tolerance for the projection on the manifold, maximum number of iterations for the projection, and the order of the norm to estimate the convergence",
"name": "__init__",
"signature": "def __init__(self, constraint_list, dt=1.0, tolerance=0.001, maxit=1000, norm_... | 3 | null | Implement the Python class `ConstraintSolver` described below.
Class description:
An implementation of a constraint solver that uses M-RATTLE to impose constraints onto the momenta and a quasi-Newton method to impose constraints onto the positions. The constraint is applied sparsely, i.e. on each block of constraints ... | Implement the Python class `ConstraintSolver` described below.
Class description:
An implementation of a constraint solver that uses M-RATTLE to impose constraints onto the momenta and a quasi-Newton method to impose constraints onto the positions. The constraint is applied sparsely, i.e. on each block of constraints ... | 57f255266d4668bafef0881d1e7cbf8a27270ddd | <|skeleton|>
class ConstraintSolver:
"""An implementation of a constraint solver that uses M-RATTLE to impose constraints onto the momenta and a quasi-Newton method to impose constraints onto the positions. The constraint is applied sparsely, i.e. on each block of constraints separately. For implementation details ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConstraintSolver:
"""An implementation of a constraint solver that uses M-RATTLE to impose constraints onto the momenta and a quasi-Newton method to impose constraints onto the positions. The constraint is applied sparsely, i.e. on each block of constraints separately. For implementation details of M-RATTLE s... | the_stack_v2_python_sparse | ipi/engine/motion/constrained_dynamics.py | i-pi/i-pi | train | 170 |
138f5d3aee531861b0bfc2126bb255b214f61d9e | [
"super(ReviewEntry, self).__init__(review.timestamp, collapsed)\nself.request = request\nself.review_request = review_request\nself.review = review\nself.issue_open_count = 0\nself.has_issues = False\nself.comments = {'diff_comments': [], 'screenshot_comments': [], 'file_attachment_comments': [], 'general_comments'... | <|body_start_0|>
super(ReviewEntry, self).__init__(review.timestamp, collapsed)
self.request = request
self.review_request = review_request
self.review = review
self.issue_open_count = 0
self.has_issues = False
self.comments = {'diff_comments': [], 'screenshot_com... | A review box. Attributes: review (reviewboard.reviews.models.Review): The review for this entry. issue_open_count (int): The count of open issues within this review. has_issues (bool): Whether there are any issues (open or not). comments (dict): A dictionary of comments. Each key in this represents a comment type, and ... | ReviewEntry | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReviewEntry:
"""A review box. Attributes: review (reviewboard.reviews.models.Review): The review for this entry. issue_open_count (int): The count of open issues within this review. has_issues (bool): Whether there are any issues (open or not). comments (dict): A dictionary of comments. Each key ... | stack_v2_sparse_classes_36k_train_012708 | 27,812 | permissive | [
{
"docstring": "Initialize the entry. Args: request (django.http.HttpRequest): The request object. review_request (reviewboard.reviews.models.ReviewRequest): The review request that the change is for. review (reviewboard.reviews.models.Review): The review. collapsed (bool): Whether the entry is collapsed by def... | 2 | null | Implement the Python class `ReviewEntry` described below.
Class description:
A review box. Attributes: review (reviewboard.reviews.models.Review): The review for this entry. issue_open_count (int): The count of open issues within this review. has_issues (bool): Whether there are any issues (open or not). comments (dic... | Implement the Python class `ReviewEntry` described below.
Class description:
A review box. Attributes: review (reviewboard.reviews.models.Review): The review for this entry. issue_open_count (int): The count of open issues within this review. has_issues (bool): Whether there are any issues (open or not). comments (dic... | 02e1ef3a4e9a8117977b053805234a713c31a699 | <|skeleton|>
class ReviewEntry:
"""A review box. Attributes: review (reviewboard.reviews.models.Review): The review for this entry. issue_open_count (int): The count of open issues within this review. has_issues (bool): Whether there are any issues (open or not). comments (dict): A dictionary of comments. Each key ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReviewEntry:
"""A review box. Attributes: review (reviewboard.reviews.models.Review): The review for this entry. issue_open_count (int): The count of open issues within this review. has_issues (bool): Whether there are any issues (open or not). comments (dict): A dictionary of comments. Each key in this repre... | the_stack_v2_python_sparse | reviewboard/reviews/detail.py | parthyz/reviewboard | train | 1 |
ff40622a9714ab371c06b30e36e211b300d090ea | [
"super(TrainableLayer, self).__init__(name=name)\nself.type_string = look_up_operations(type_string.lower(), SUPPORTED_OP)\nself.acti_func = acti_func\nself.conv_param = {'w_initializer': w_initializer, 'w_regularizer': w_regularizer, 'kernel_size': kernel_size, 'dilation': dilation, 'n_output_chns': n_output_chns}... | <|body_start_0|>
super(TrainableLayer, self).__init__(name=name)
self.type_string = look_up_operations(type_string.lower(), SUPPORTED_OP)
self.acti_func = acti_func
self.conv_param = {'w_initializer': w_initializer, 'w_regularizer': w_regularizer, 'kernel_size': kernel_size, 'dilation': ... | ResidualUnit | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResidualUnit:
def __init__(self, n_output_chns=1, kernel_size=3, dilation=1, acti_func='relu', w_initializer=None, w_regularizer=None, moving_decay=0.9, eps=1e-05, type_string='bn_acti_conv', name='res-downsample'):
"""Implementation of residual unit presented in: [1] He et al., Identity... | stack_v2_sparse_classes_36k_train_012709 | 4,424 | permissive | [
{
"docstring": "Implementation of residual unit presented in: [1] He et al., Identity mapping in deep residual networks, ECCV 2016 [2] He et al., Deep residual learning for image recognition, CVPR 2016 The possible types of connections are:: 'original': residual unit presented in [2] 'conv_bn_acti': ReLU before... | 2 | null | Implement the Python class `ResidualUnit` described below.
Class description:
Implement the ResidualUnit class.
Method signatures and docstrings:
- def __init__(self, n_output_chns=1, kernel_size=3, dilation=1, acti_func='relu', w_initializer=None, w_regularizer=None, moving_decay=0.9, eps=1e-05, type_string='bn_acti... | Implement the Python class `ResidualUnit` described below.
Class description:
Implement the ResidualUnit class.
Method signatures and docstrings:
- def __init__(self, n_output_chns=1, kernel_size=3, dilation=1, acti_func='relu', w_initializer=None, w_regularizer=None, moving_decay=0.9, eps=1e-05, type_string='bn_acti... | 84dd0f85c9a1ab8a72f4c55fcf073379acf5ae1b | <|skeleton|>
class ResidualUnit:
def __init__(self, n_output_chns=1, kernel_size=3, dilation=1, acti_func='relu', w_initializer=None, w_regularizer=None, moving_decay=0.9, eps=1e-05, type_string='bn_acti_conv', name='res-downsample'):
"""Implementation of residual unit presented in: [1] He et al., Identity... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResidualUnit:
def __init__(self, n_output_chns=1, kernel_size=3, dilation=1, acti_func='relu', w_initializer=None, w_regularizer=None, moving_decay=0.9, eps=1e-05, type_string='bn_acti_conv', name='res-downsample'):
"""Implementation of residual unit presented in: [1] He et al., Identity mapping in de... | the_stack_v2_python_sparse | niftynet/layer/residual_unit.py | 12SigmaTechnologies/NiftyNet-1 | train | 2 | |
392465fc0fd2ba78a674668137ea74c1f7921bd8 | [
"if not matrix:\n return 0\nres = 0\nheight = [0 for i in matrix[0]]\nfor i in matrix:\n for index, val in enumerate(i):\n height[index] = height[index] + 1 if val == '1' else 0\n res = max(res, self.largestRectangleArea(height))\nreturn res",
"stack = [0 for i in height]\ntop, max_area, index = (... | <|body_start_0|>
if not matrix:
return 0
res = 0
height = [0 for i in matrix[0]]
for i in matrix:
for index, val in enumerate(i):
height[index] = height[index] + 1 if val == '1' else 0
res = max(res, self.largestRectangleArea(height))
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maximalRectangle(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_0|>
def largestRectangleArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not matrix:
... | stack_v2_sparse_classes_36k_train_012710 | 1,403 | no_license | [
{
"docstring": ":type matrix: List[List[str]] :rtype: int",
"name": "maximalRectangle",
"signature": "def maximalRectangle(self, matrix)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "largestRectangleArea",
"signature": "def largestRectangleArea(self, height)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalRectangle(self, matrix): :type matrix: List[List[str]] :rtype: int
- def largestRectangleArea(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalRectangle(self, matrix): :type matrix: List[List[str]] :rtype: int
- def largestRectangleArea(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class So... | 22022f65bd894ca6c3546014b191dc2a33653ac3 | <|skeleton|>
class Solution:
def maximalRectangle(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_0|>
def largestRectangleArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maximalRectangle(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
if not matrix:
return 0
res = 0
height = [0 for i in matrix[0]]
for i in matrix:
for index, val in enumerate(i):
height[index] = height[... | the_stack_v2_python_sparse | Maximal Rectangle.py | txjzwzz/leetCodeJuly | train | 0 | |
e24f4bd82ef3a1275d28fb5af427dc9d27c225ce | [
"self.endline = '\\n'\nself.host = host\nself.port = port\nself.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nself.sock.connect((host, port))\nself.current_data = 0\nself.current_image = 0\nself.is_new_data = False",
"total_data = []\nwhile True:\n data = self.sock.recv(65536)\n data = data.deco... | <|body_start_0|>
self.endline = '\n'
self.host = host
self.port = port
self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.sock.connect((host, port))
self.current_data = 0
self.current_image = 0
self.is_new_data = False
<|end_body_0|>
<|bod... | Class which receives data from VideoCamera by built-in 'socket' interface, decodes it from json, utf-8 and base64 and makes it available for user | VideoCameraServer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoCameraServer:
"""Class which receives data from VideoCamera by built-in 'socket' interface, decodes it from json, utf-8 and base64 and makes it available for user"""
def __init__(self, host, port):
"""Initializes socket and opens data stream. :param host: address of a streaming ... | stack_v2_sparse_classes_36k_train_012711 | 6,070 | permissive | [
{
"docstring": "Initializes socket and opens data stream. :param host: address of a streaming socket :param port: port on which is the stream",
"name": "__init__",
"signature": "def __init__(self, host, port)"
},
{
"docstring": "This method is used to obtain only one object from socket. Sometime... | 6 | stack_v2_sparse_classes_30k_train_004461 | Implement the Python class `VideoCameraServer` described below.
Class description:
Class which receives data from VideoCamera by built-in 'socket' interface, decodes it from json, utf-8 and base64 and makes it available for user
Method signatures and docstrings:
- def __init__(self, host, port): Initializes socket an... | Implement the Python class `VideoCameraServer` described below.
Class description:
Class which receives data from VideoCamera by built-in 'socket' interface, decodes it from json, utf-8 and base64 and makes it available for user
Method signatures and docstrings:
- def __init__(self, host, port): Initializes socket an... | 7115f55799d9a81fdb214e20c4cdd8520dceb48e | <|skeleton|>
class VideoCameraServer:
"""Class which receives data from VideoCamera by built-in 'socket' interface, decodes it from json, utf-8 and base64 and makes it available for user"""
def __init__(self, host, port):
"""Initializes socket and opens data stream. :param host: address of a streaming ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VideoCameraServer:
"""Class which receives data from VideoCamera by built-in 'socket' interface, decodes it from json, utf-8 and base64 and makes it available for user"""
def __init__(self, host, port):
"""Initializes socket and opens data stream. :param host: address of a streaming socket :param... | the_stack_v2_python_sparse | MORSEProject/classes/video_camera_server.py | Kecz/MORSE-SLAM | train | 2 |
81f5465f85b4d9047c2b66e4a317d4832f0c294f | [
"errors = {}\nif user_input is not None:\n try:\n token = await validate_input(self.hass, user_input)\n await self.async_set_unique_id(user_input['username'])\n return self.async_create_entry(title=user_input['username'], data={'username': user_input['username'], 'token': token})\n except... | <|body_start_0|>
errors = {}
if user_input is not None:
try:
token = await validate_input(self.hass, user_input)
await self.async_set_unique_id(user_input['username'])
return self.async_create_entry(title=user_input['username'], data={'username... | Handle a config flow for Ring. | RingConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RingConfigFlow:
"""Handle a config flow for Ring."""
async def async_step_user(self, user_input=None):
"""Handle the initial step."""
<|body_0|>
async def async_step_2fa(self, user_input=None):
"""Handle 2fa step."""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_012712 | 2,684 | permissive | [
{
"docstring": "Handle the initial step.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input=None)"
},
{
"docstring": "Handle 2fa step.",
"name": "async_step_2fa",
"signature": "async def async_step_2fa(self, user_input=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019599 | Implement the Python class `RingConfigFlow` described below.
Class description:
Handle a config flow for Ring.
Method signatures and docstrings:
- async def async_step_user(self, user_input=None): Handle the initial step.
- async def async_step_2fa(self, user_input=None): Handle 2fa step. | Implement the Python class `RingConfigFlow` described below.
Class description:
Handle a config flow for Ring.
Method signatures and docstrings:
- async def async_step_user(self, user_input=None): Handle the initial step.
- async def async_step_2fa(self, user_input=None): Handle 2fa step.
<|skeleton|>
class RingConf... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class RingConfigFlow:
"""Handle a config flow for Ring."""
async def async_step_user(self, user_input=None):
"""Handle the initial step."""
<|body_0|>
async def async_step_2fa(self, user_input=None):
"""Handle 2fa step."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RingConfigFlow:
"""Handle a config flow for Ring."""
async def async_step_user(self, user_input=None):
"""Handle the initial step."""
errors = {}
if user_input is not None:
try:
token = await validate_input(self.hass, user_input)
await s... | the_stack_v2_python_sparse | homeassistant/components/ring/config_flow.py | home-assistant/core | train | 35,501 |
0fd910805b1fdac61da121ec6c095cdb95888651 | [
"ret = 0\nmn = float('inf')\nfor p in prices:\n ret = max(ret, p - mn)\n mn = min(mn, p)\nreturn ret",
"ret = 0\nmn = float('inf')\nfor p in prices:\n ret = max(ret, p - mn)\n mn = min(mn, p)\nreturn ret"
] | <|body_start_0|>
ret = 0
mn = float('inf')
for p in prices:
ret = max(ret, p - mn)
mn = min(mn, p)
return ret
<|end_body_0|>
<|body_start_1|>
ret = 0
mn = float('inf')
for p in prices:
ret = max(ret, p - mn)
mn = mi... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""Feb 17, 2022 16:10"""
<|body_0|>
def maxProfit(self, prices: List[int]) -> int:
"""Apr 02, 2023 00:28"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = 0
mn = float('inf')
... | stack_v2_sparse_classes_36k_train_012713 | 1,719 | no_license | [
{
"docstring": "Feb 17, 2022 16:10",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int]) -> int"
},
{
"docstring": "Apr 02, 2023 00:28",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int]) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: Feb 17, 2022 16:10
- def maxProfit(self, prices: List[int]) -> int: Apr 02, 2023 00:28 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: Feb 17, 2022 16:10
- def maxProfit(self, prices: List[int]) -> int: Apr 02, 2023 00:28
<|skeleton|>
class Solution:
def maxPr... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""Feb 17, 2022 16:10"""
<|body_0|>
def maxProfit(self, prices: List[int]) -> int:
"""Apr 02, 2023 00:28"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""Feb 17, 2022 16:10"""
ret = 0
mn = float('inf')
for p in prices:
ret = max(ret, p - mn)
mn = min(mn, p)
return ret
def maxProfit(self, prices: List[int]) -> int:
"""Apr 02, ... | the_stack_v2_python_sparse | leetcode/solved/121_Best_Time_to_Buy_and_Sell_Stock/solution.py | sungminoh/algorithms | train | 0 | |
a39055eae0cb80d7eed2d27804184f21b7c42011 | [
"i = 0\nfor num in nums:\n if i < 2 or num > nums[i - 2]:\n nums[i] = num\n i += 1\nreturn i",
"i = 0\nfor n in nums:\n if i < k or n > nums[i - k]:\n nums[i] = n\n i += 1\nreturn i"
] | <|body_start_0|>
i = 0
for num in nums:
if i < 2 or num > nums[i - 2]:
nums[i] = num
i += 1
return i
<|end_body_0|>
<|body_start_1|>
i = 0
for n in nums:
if i < k or n > nums[i - k]:
nums[i] = n
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates2(self, nums, k):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i = 0
for num in nums:
... | stack_v2_sparse_classes_36k_train_012714 | 1,176 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicates",
"signature": "def removeDuplicates(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicates2",
"signature": "def removeDuplicates2(self, nums, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicates(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates2(self, nums, k): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicates(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates2(self, nums, k): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
d... | 89142297559af20cf990a8e40975811b4be36955 | <|skeleton|>
class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates2(self, nums, k):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
i = 0
for num in nums:
if i < 2 or num > nums[i - 2]:
nums[i] = num
i += 1
return i
def removeDuplicates2(self, nums, k):
""":type nums: ... | the_stack_v2_python_sparse | ReferenceSolution/80.remove-duplicates-from-sorted-array-ii.143163442.ac.py | DarkAlexWang/leetcode | train | 3 | |
a0777a7f04a6eceb6258f7cb8b1c1d4cd078e27e | [
"m = len(nums)\nfor i in range(m - 1, -1, -1):\n for j in range(i):\n if nums[j] > nums[j + 1]:\n nums[j], nums[j + 1] = (nums[j + 1], nums[j])",
"m = len(nums)\nfor i in range(m - 1, -1, -1):\n is_sorted = True\n for j in range(i):\n if nums[j] > nums[j + 1]:\n nums[j... | <|body_start_0|>
m = len(nums)
for i in range(m - 1, -1, -1):
for j in range(i):
if nums[j] > nums[j + 1]:
nums[j], nums[j + 1] = (nums[j + 1], nums[j])
<|end_body_0|>
<|body_start_1|>
m = len(nums)
for i in range(m - 1, -1, -1):
... | 冒泡排序 | Bubble_sort | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bubble_sort:
"""冒泡排序"""
def sort(self, nums):
"""标准版冒泡排序 :type nums: List[int] 要排序的数组"""
<|body_0|>
def sort_optimize(self, nums):
"""优化版冒泡排序 :type nums: List[int] 要排序的数组"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m = len(nums)
for ... | stack_v2_sparse_classes_36k_train_012715 | 815 | no_license | [
{
"docstring": "标准版冒泡排序 :type nums: List[int] 要排序的数组",
"name": "sort",
"signature": "def sort(self, nums)"
},
{
"docstring": "优化版冒泡排序 :type nums: List[int] 要排序的数组",
"name": "sort_optimize",
"signature": "def sort_optimize(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017948 | Implement the Python class `Bubble_sort` described below.
Class description:
冒泡排序
Method signatures and docstrings:
- def sort(self, nums): 标准版冒泡排序 :type nums: List[int] 要排序的数组
- def sort_optimize(self, nums): 优化版冒泡排序 :type nums: List[int] 要排序的数组 | Implement the Python class `Bubble_sort` described below.
Class description:
冒泡排序
Method signatures and docstrings:
- def sort(self, nums): 标准版冒泡排序 :type nums: List[int] 要排序的数组
- def sort_optimize(self, nums): 优化版冒泡排序 :type nums: List[int] 要排序的数组
<|skeleton|>
class Bubble_sort:
"""冒泡排序"""
def sort(self, num... | 0b3bc77cbfe0e45e62c3c8f244e9e3d2421e6121 | <|skeleton|>
class Bubble_sort:
"""冒泡排序"""
def sort(self, nums):
"""标准版冒泡排序 :type nums: List[int] 要排序的数组"""
<|body_0|>
def sort_optimize(self, nums):
"""优化版冒泡排序 :type nums: List[int] 要排序的数组"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bubble_sort:
"""冒泡排序"""
def sort(self, nums):
"""标准版冒泡排序 :type nums: List[int] 要排序的数组"""
m = len(nums)
for i in range(m - 1, -1, -1):
for j in range(i):
if nums[j] > nums[j + 1]:
nums[j], nums[j + 1] = (nums[j + 1], nums[j])
def... | the_stack_v2_python_sparse | sort/bubble_sort.py | lailianqi/LeetCodeByPython | train | 0 |
7abe1af354a1bfafcfd00b03325031dba680c060 | [
"if len(strs) == 0:\n return ''\nminstrlenghth = 10 ** 9\nfor s in strs:\n if len(s) < minstrlenghth:\n minstrlenghth = len(s)\nprint(minstrlenghth)\nfor i in range(minstrlenghth):\n temp = strs[0][i]\n for j in range(1, len(strs)):\n if strs[j][i] != temp:\n return strs[0][:i]\... | <|body_start_0|>
if len(strs) == 0:
return ''
minstrlenghth = 10 ** 9
for s in strs:
if len(s) < minstrlenghth:
minstrlenghth = len(s)
print(minstrlenghth)
for i in range(minstrlenghth):
temp = strs[0][i]
for j in ra... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestCommonPrefix1(self, strs: List[str]) -> str:
"""我这里做纵向扫描，也就是从前向后遍历所有字符串的每一列， 比较相同列行的字符是否相同，如果相同则继续对下一列的字符进行比较 如果不相同则当前列不再属于公共前缀，当前列之前的部分为最长公共前缀 复杂度分析： 时间复杂度：O(nm) 其中m为字符串数组的长度，n为列表长度（即字符串的数量） 最坏的情况下，字符串数组中每个字符串的每个字符都要被比较一次 空间复杂度：O(1)"""
<|body_0|>
def lo... | stack_v2_sparse_classes_36k_train_012716 | 1,993 | no_license | [
{
"docstring": "我这里做纵向扫描，也就是从前向后遍历所有字符串的每一列， 比较相同列行的字符是否相同，如果相同则继续对下一列的字符进行比较 如果不相同则当前列不再属于公共前缀，当前列之前的部分为最长公共前缀 复杂度分析： 时间复杂度：O(nm) 其中m为字符串数组的长度，n为列表长度（即字符串的数量） 最坏的情况下，字符串数组中每个字符串的每个字符都要被比较一次 空间复杂度：O(1)",
"name": "longestCommonPrefix1",
"signature": "def longestCommonPrefix1(self, strs: List[str]) -> str... | 2 | stack_v2_sparse_classes_30k_train_000385 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix1(self, strs: List[str]) -> str: 我这里做纵向扫描，也就是从前向后遍历所有字符串的每一列， 比较相同列行的字符是否相同，如果相同则继续对下一列的字符进行比较 如果不相同则当前列不再属于公共前缀，当前列之前的部分为最长公共前缀 复杂度分析： 时间复杂度：O(nm) 其中m为字符串... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix1(self, strs: List[str]) -> str: 我这里做纵向扫描，也就是从前向后遍历所有字符串的每一列， 比较相同列行的字符是否相同，如果相同则继续对下一列的字符进行比较 如果不相同则当前列不再属于公共前缀，当前列之前的部分为最长公共前缀 复杂度分析： 时间复杂度：O(nm) 其中m为字符串... | 51943e2c2c4ec70c7c1d5b53c9fdf0a719428d7a | <|skeleton|>
class Solution:
def longestCommonPrefix1(self, strs: List[str]) -> str:
"""我这里做纵向扫描，也就是从前向后遍历所有字符串的每一列， 比较相同列行的字符是否相同，如果相同则继续对下一列的字符进行比较 如果不相同则当前列不再属于公共前缀，当前列之前的部分为最长公共前缀 复杂度分析： 时间复杂度：O(nm) 其中m为字符串数组的长度，n为列表长度（即字符串的数量） 最坏的情况下，字符串数组中每个字符串的每个字符都要被比较一次 空间复杂度：O(1)"""
<|body_0|>
def lo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestCommonPrefix1(self, strs: List[str]) -> str:
"""我这里做纵向扫描，也就是从前向后遍历所有字符串的每一列， 比较相同列行的字符是否相同，如果相同则继续对下一列的字符进行比较 如果不相同则当前列不再属于公共前缀，当前列之前的部分为最长公共前缀 复杂度分析： 时间复杂度：O(nm) 其中m为字符串数组的长度，n为列表长度（即字符串的数量） 最坏的情况下，字符串数组中每个字符串的每个字符都要被比较一次 空间复杂度：O(1)"""
if len(strs) == 0:
retur... | the_stack_v2_python_sparse | LeetCode_practice/0014_LongestCommonPrefix.py | LeBron-Jian/BasicAlgorithmPractice | train | 13 | |
88b815a2ff66d997118f4af7319f091518db86ec | [
"collection = lnlink.CollectedNames(['slashdot', 'freshmeat'])\nresult = collection.bind_with_LNQS('http://taoriver.net/tmp/gmail.txt', 'http://services.taoriver.net:9090/')\nassert len(result) == 0, 'still some unresolved names'\nbound = collection.bound\nassert bound['slashdot'] == 'http://www.slashdot.org/'\nass... | <|body_start_0|>
collection = lnlink.CollectedNames(['slashdot', 'freshmeat'])
result = collection.bind_with_LNQS('http://taoriver.net/tmp/gmail.txt', 'http://services.taoriver.net:9090/')
assert len(result) == 0, 'still some unresolved names'
bound = collection.bound
assert boun... | Test that we can remotely look up names. test1 -- test resolving within one namespace test_namespace_hopping -- test lookups transcending one namespace | RemoteLookupTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteLookupTest:
"""Test that we can remotely look up names. test1 -- test resolving within one namespace test_namespace_hopping -- test lookups transcending one namespace"""
def test1(self):
"""Make sure bind_with_LNQS resolves names in one namespace. If there's an error, it may be... | stack_v2_sparse_classes_36k_train_012717 | 3,716 | no_license | [
{
"docstring": "Make sure bind_with_LNQS resolves names in one namespace. If there's an error, it may be that it actually can't resolve slashdot or freshmeat- you'll have to check it independently, should this fail.",
"name": "test1",
"signature": "def test1(self)"
},
{
"docstring": "Make sure b... | 2 | null | Implement the Python class `RemoteLookupTest` described below.
Class description:
Test that we can remotely look up names. test1 -- test resolving within one namespace test_namespace_hopping -- test lookups transcending one namespace
Method signatures and docstrings:
- def test1(self): Make sure bind_with_LNQS resolv... | Implement the Python class `RemoteLookupTest` described below.
Class description:
Test that we can remotely look up names. test1 -- test resolving within one namespace test_namespace_hopping -- test lookups transcending one namespace
Method signatures and docstrings:
- def test1(self): Make sure bind_with_LNQS resolv... | da65d948b346d3f455e79168a8753b2b16d8fc5f | <|skeleton|>
class RemoteLookupTest:
"""Test that we can remotely look up names. test1 -- test resolving within one namespace test_namespace_hopping -- test lookups transcending one namespace"""
def test1(self):
"""Make sure bind_with_LNQS resolves names in one namespace. If there's an error, it may be... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RemoteLookupTest:
"""Test that we can remotely look up names. test1 -- test resolving within one namespace test_namespace_hopping -- test lookups transcending one namespace"""
def test1(self):
"""Make sure bind_with_LNQS resolves names in one namespace. If there's an error, it may be that it actu... | the_stack_v2_python_sparse | pre2007/lnlink/test.py | BackupTheBerlios/onebigsoup-svn | train | 0 |
b944d90d4784de8c2f92b8ac1bae26e5718db186 | [
"super(fcEncoderNet, self).__init__()\ndense = []\nfor i in range(num_layers):\n input_dim = np.product(in_dim) if i == 0 else hidden_dim\n dense.extend([nn.Linear(input_dim, hidden_dim), nn.Tanh()])\nself.dense = nn.Sequential(*dense)\nself.reshape_ = hidden_dim\nself.fc11 = nn.Linear(self.reshape_, latent_d... | <|body_start_0|>
super(fcEncoderNet, self).__init__()
dense = []
for i in range(num_layers):
input_dim = np.product(in_dim) if i == 0 else hidden_dim
dense.extend([nn.Linear(input_dim, hidden_dim), nn.Tanh()])
self.dense = nn.Sequential(*dense)
self.reshap... | Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by default) num_layers: number of NN layers... | fcEncoderNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class fcEncoderNet:
"""Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by ... | stack_v2_sparse_classes_36k_train_012718 | 28,462 | permissive | [
{
"docstring": "Initializes network parameters",
"name": "__init__",
"signature": "def __init__(self, in_dim: Tuple[int], latent_dim: int=2, num_layers: int=2, hidden_dim: int=32, **kwargs: bool) -> None"
},
{
"docstring": "Forward pass",
"name": "forward",
"signature": "def forward(self... | 2 | stack_v2_sparse_classes_30k_train_001134 | Implement the Python class `fcEncoderNet` described below.
Class description:
Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent ... | Implement the Python class `fcEncoderNet` described below.
Class description:
Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent ... | 6d187296074143d017ca8fc60302364cd946b180 | <|skeleton|>
class fcEncoderNet:
"""Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class fcEncoderNet:
"""Encoder/inference network (for variational autoencoder) Args: in_dim: Input dimensions. For images, it is (height, width) or (height, width, channels). For spectra, it is (length,) latent_dim: number of latent dimensions (the first 3 latent dimensions are angle & translations by default) num_... | the_stack_v2_python_sparse | atomai/nets/ed.py | pycroscopy/atomai | train | 157 |
99694fdcbf0b5db966cd16ee4d3768a6f816561d | [
"TestCommand.finalize_options(self)\nself.test_args = []\nself.test_suite = True",
"import pytest\nerrcode = pytest.main(self.test_args)\nsys.exit(errcode)"
] | <|body_start_0|>
TestCommand.finalize_options(self)
self.test_args = []
self.test_suite = True
<|end_body_0|>
<|body_start_1|>
import pytest
errcode = pytest.main(self.test_args)
sys.exit(errcode)
<|end_body_1|>
| PyTest | PyTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyTest:
"""PyTest"""
def finalize_options(self):
"""finalize_options"""
<|body_0|>
def run_tests(self):
"""run_tests"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
TestCommand.finalize_options(self)
self.test_args = []
self.test... | stack_v2_sparse_classes_36k_train_012719 | 1,582 | permissive | [
{
"docstring": "finalize_options",
"name": "finalize_options",
"signature": "def finalize_options(self)"
},
{
"docstring": "run_tests",
"name": "run_tests",
"signature": "def run_tests(self)"
}
] | 2 | null | Implement the Python class `PyTest` described below.
Class description:
PyTest
Method signatures and docstrings:
- def finalize_options(self): finalize_options
- def run_tests(self): run_tests | Implement the Python class `PyTest` described below.
Class description:
PyTest
Method signatures and docstrings:
- def finalize_options(self): finalize_options
- def run_tests(self): run_tests
<|skeleton|>
class PyTest:
"""PyTest"""
def finalize_options(self):
"""finalize_options"""
<|body_0... | 56c52702cec4370f551785508d284e5cbe1a744a | <|skeleton|>
class PyTest:
"""PyTest"""
def finalize_options(self):
"""finalize_options"""
<|body_0|>
def run_tests(self):
"""run_tests"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyTest:
"""PyTest"""
def finalize_options(self):
"""finalize_options"""
TestCommand.finalize_options(self)
self.test_args = []
self.test_suite = True
def run_tests(self):
"""run_tests"""
import pytest
errcode = pytest.main(self.test_args)
... | the_stack_v2_python_sparse | setup.py | nutanix/calm-dsl | train | 41 |
473e183c39784c3ac836b2fac5488650bb56e1c6 | [
"self.set_sys()\nself.fig = fig\nfrom wigner_normalize import WignerNormalize, WignerSymLogNorm\nimg_params = dict(extent=[self.hybrid_sys.X.min(), self.hybrid_sys.X.max(), self.hybrid_sys.P.min(), self.hybrid_sys.P.max()], origin='lower', cmap='seismic', norm=WignerSymLogNorm(linthresh=1e-07, vmin=-0.01, vmax=0.1)... | <|body_start_0|>
self.set_sys()
self.fig = fig
from wigner_normalize import WignerNormalize, WignerSymLogNorm
img_params = dict(extent=[self.hybrid_sys.X.min(), self.hybrid_sys.X.max(), self.hybrid_sys.P.min(), self.hybrid_sys.P.max()], origin='lower', cmap='seismic', norm=WignerSymLogNo... | Class to visualize the phase space dynamics in phase space. | VisualizeHybrid | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VisualizeHybrid:
"""Class to visualize the phase space dynamics in phase space."""
def __init__(self, fig):
"""Initialize all propagators and frame :param fig: matplotlib figure object"""
<|body_0|>
def set_sys(self):
"""Initialize quantum propagator :param self:... | stack_v2_sparse_classes_36k_train_012720 | 7,316 | no_license | [
{
"docstring": "Initialize all propagators and frame :param fig: matplotlib figure object",
"name": "__init__",
"signature": "def __init__(self, fig)"
},
{
"docstring": "Initialize quantum propagator :param self: :return:",
"name": "set_sys",
"signature": "def set_sys(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_001983 | Implement the Python class `VisualizeHybrid` described below.
Class description:
Class to visualize the phase space dynamics in phase space.
Method signatures and docstrings:
- def __init__(self, fig): Initialize all propagators and frame :param fig: matplotlib figure object
- def set_sys(self): Initialize quantum pr... | Implement the Python class `VisualizeHybrid` described below.
Class description:
Class to visualize the phase space dynamics in phase space.
Method signatures and docstrings:
- def __init__(self, fig): Initialize all propagators and frame :param fig: matplotlib figure object
- def set_sys(self): Initialize quantum pr... | c247a8dc47d38435191f14bc4d71fa64ad98e008 | <|skeleton|>
class VisualizeHybrid:
"""Class to visualize the phase space dynamics in phase space."""
def __init__(self, fig):
"""Initialize all propagators and frame :param fig: matplotlib figure object"""
<|body_0|>
def set_sys(self):
"""Initialize quantum propagator :param self:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VisualizeHybrid:
"""Class to visualize the phase space dynamics in phase space."""
def __init__(self, fig):
"""Initialize all propagators and frame :param fig: matplotlib figure object"""
self.set_sys()
self.fig = fig
from wigner_normalize import WignerNormalize, WignerSym... | the_stack_v2_python_sparse | hybrid_vs_pauli.py | gharib85/QCHybrid | train | 0 |
b4ecaf76d184aa68e3b715f653dbb78741c8ef69 | [
"article = get_object_or_404(Article, slug=self.kwargs['slug'])\ndata = request.data\nserializer = self.serializer_class(data=data)\nif serializer.is_valid():\n serializer.save(author=self.request.user, article=article)\n return Response(serializer.data, status=status.HTTP_201_CREATED)\nreturn Response(serial... | <|body_start_0|>
article = get_object_or_404(Article, slug=self.kwargs['slug'])
data = request.data
serializer = self.serializer_class(data=data)
if serializer.is_valid():
serializer.save(author=self.request.user, article=article)
return Response(serializer.data, ... | A user can comment on an article | ArticleCommentAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArticleCommentAPIView:
"""A user can comment on an article"""
def post(self, request, slug=None):
"""Comment on an article in the application"""
<|body_0|>
def get(self, request, slug=None):
"""Get all the comments of an article"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_012721 | 8,748 | permissive | [
{
"docstring": "Comment on an article in the application",
"name": "post",
"signature": "def post(self, request, slug=None)"
},
{
"docstring": "Get all the comments of an article",
"name": "get",
"signature": "def get(self, request, slug=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018542 | Implement the Python class `ArticleCommentAPIView` described below.
Class description:
A user can comment on an article
Method signatures and docstrings:
- def post(self, request, slug=None): Comment on an article in the application
- def get(self, request, slug=None): Get all the comments of an article | Implement the Python class `ArticleCommentAPIView` described below.
Class description:
A user can comment on an article
Method signatures and docstrings:
- def post(self, request, slug=None): Comment on an article in the application
- def get(self, request, slug=None): Get all the comments of an article
<|skeleton|>... | e8438b78b88c52d108520429d0b67cd3d13e0824 | <|skeleton|>
class ArticleCommentAPIView:
"""A user can comment on an article"""
def post(self, request, slug=None):
"""Comment on an article in the application"""
<|body_0|>
def get(self, request, slug=None):
"""Get all the comments of an article"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArticleCommentAPIView:
"""A user can comment on an article"""
def post(self, request, slug=None):
"""Comment on an article in the application"""
article = get_object_or_404(Article, slug=self.kwargs['slug'])
data = request.data
serializer = self.serializer_class(data=data)... | the_stack_v2_python_sparse | authors/apps/comments/views.py | andela/ah-sealteam | train | 1 |
283fd0a2f315f7fa00eada46979467e6cb7631c6 | [
"super().__init__(NAME)\nself.num_images = num_images\nself.time_interval_min = time_interval_min\nself.scaling_image = preprocessing.min_max_scaling_images()\nself.scaling_ghi = preprocessing.min_max_scaling_ghi()\nif encoder is None:\n self.encoder = autoencoder.Encoder()\n self.encoder.load(autoencoder.BES... | <|body_start_0|>
super().__init__(NAME)
self.num_images = num_images
self.time_interval_min = time_interval_min
self.scaling_image = preprocessing.min_max_scaling_images()
self.scaling_ghi = preprocessing.min_max_scaling_ghi()
if encoder is None:
self.encoder ... | Create GRU Model based on the embeddings created with the encoder. | GRU | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRU:
"""Create GRU Model based on the embeddings created with the encoder."""
def __init__(self, encoder=None, num_images=6, time_interval_min=30, dropout=0.2):
"""Initialize the architecture."""
<|body_0|>
def call(self, data: Tuple[tf.Tensor, tf.Tensor], training=False... | stack_v2_sparse_classes_36k_train_012722 | 3,350 | no_license | [
{
"docstring": "Initialize the architecture.",
"name": "__init__",
"signature": "def __init__(self, encoder=None, num_images=6, time_interval_min=30, dropout=0.2)"
},
{
"docstring": "Performs the forward pass in the neural network. Can use a different pass with the optional training boolean if s... | 4 | stack_v2_sparse_classes_30k_train_013906 | Implement the Python class `GRU` described below.
Class description:
Create GRU Model based on the embeddings created with the encoder.
Method signatures and docstrings:
- def __init__(self, encoder=None, num_images=6, time_interval_min=30, dropout=0.2): Initialize the architecture.
- def call(self, data: Tuple[tf.Te... | Implement the Python class `GRU` described below.
Class description:
Create GRU Model based on the embeddings created with the encoder.
Method signatures and docstrings:
- def __init__(self, encoder=None, num_images=6, time_interval_min=30, dropout=0.2): Initialize the architecture.
- def call(self, data: Tuple[tf.Te... | b20d809bff84bb508190be8540a815fb9b8b3f8b | <|skeleton|>
class GRU:
"""Create GRU Model based on the embeddings created with the encoder."""
def __init__(self, encoder=None, num_images=6, time_interval_min=30, dropout=0.2):
"""Initialize the architecture."""
<|body_0|>
def call(self, data: Tuple[tf.Tensor, tf.Tensor], training=False... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GRU:
"""Create GRU Model based on the embeddings created with the encoder."""
def __init__(self, encoder=None, num_images=6, time_interval_min=30, dropout=0.2):
"""Initialize the architecture."""
super().__init__(NAME)
self.num_images = num_images
self.time_interval_min = ... | the_stack_v2_python_sparse | src/model/gru.py | nathanielsimard/Solar-Irradiance-Prediction | train | 0 |
e1587896c664c3c35624d3aada1bcd1059a5410d | [
"params = publication_star_uid_parser.parse_args()\nres, status_code = star_publication(params, publication_id)\nreturn (res, status_code)",
"params = publication_star_uid_parser.parse_args()\nres, status_code = unstar_publication(params, publication_id)\nreturn (res, status_code)",
"params = publication_star_p... | <|body_start_0|>
params = publication_star_uid_parser.parse_args()
res, status_code = star_publication(params, publication_id)
return (res, status_code)
<|end_body_0|>
<|body_start_1|>
params = publication_star_uid_parser.parse_args()
res, status_code = unstar_publication(params... | PublicationStarResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublicationStarResource:
def post(self, publication_id):
"""Star a publication."""
<|body_0|>
def delete(self, publication_id):
"""Unstar a publication."""
<|body_1|>
def get(self, publication_id):
"""Get a starring."""
<|body_2|>
<|end_... | stack_v2_sparse_classes_36k_train_012723 | 5,345 | no_license | [
{
"docstring": "Star a publication.",
"name": "post",
"signature": "def post(self, publication_id)"
},
{
"docstring": "Unstar a publication.",
"name": "delete",
"signature": "def delete(self, publication_id)"
},
{
"docstring": "Get a starring.",
"name": "get",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_002371 | Implement the Python class `PublicationStarResource` described below.
Class description:
Implement the PublicationStarResource class.
Method signatures and docstrings:
- def post(self, publication_id): Star a publication.
- def delete(self, publication_id): Unstar a publication.
- def get(self, publication_id): Get a... | Implement the Python class `PublicationStarResource` described below.
Class description:
Implement the PublicationStarResource class.
Method signatures and docstrings:
- def post(self, publication_id): Star a publication.
- def delete(self, publication_id): Unstar a publication.
- def get(self, publication_id): Get a... | 30fff71d9cf58dbc9b38bd1cf999a03c51347dfd | <|skeleton|>
class PublicationStarResource:
def post(self, publication_id):
"""Star a publication."""
<|body_0|>
def delete(self, publication_id):
"""Unstar a publication."""
<|body_1|>
def get(self, publication_id):
"""Get a starring."""
<|body_2|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PublicationStarResource:
def post(self, publication_id):
"""Star a publication."""
params = publication_star_uid_parser.parse_args()
res, status_code = star_publication(params, publication_id)
return (res, status_code)
def delete(self, publication_id):
"""Unstar a ... | the_stack_v2_python_sparse | bookbnb_middleware/api/endpoints/publications.py | 7552-2020C2-grupo5/middleware | train | 0 | |
616f8c3a999eda66c7159802e13db85d9d7faf41 | [
"try:\n return self.request.user.roster\nexcept AttributeError:\n return None",
"context = super(FlashbackAddPostView, self).get_context_data(**kwargs)\nflashback = self.get_object()\nuser = self.request.user\ntry:\n user_is_staff = bool(user.is_staff or user.check_permstring('builders'))\n timeline =... | <|body_start_0|>
try:
return self.request.user.roster
except AttributeError:
return None
<|end_body_0|>
<|body_start_1|>
context = super(FlashbackAddPostView, self).get_context_data(**kwargs)
flashback = self.get_object()
user = self.request.user
... | View for an individual flashback or adding a post to it | FlashbackAddPostView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlashbackAddPostView:
"""View for an individual flashback or adding a post to it"""
def poster(self):
"""RosterEntry of user who will be making post"""
<|body_0|>
def get_context_data(self, **kwargs):
"""Gets context for template, ensures we have permissions"""
... | stack_v2_sparse_classes_36k_train_012724 | 34,840 | permissive | [
{
"docstring": "RosterEntry of user who will be making post",
"name": "poster",
"signature": "def poster(self)"
},
{
"docstring": "Gets context for template, ensures we have permissions",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_012995 | Implement the Python class `FlashbackAddPostView` described below.
Class description:
View for an individual flashback or adding a post to it
Method signatures and docstrings:
- def poster(self): RosterEntry of user who will be making post
- def get_context_data(self, **kwargs): Gets context for template, ensures we ... | Implement the Python class `FlashbackAddPostView` described below.
Class description:
View for an individual flashback or adding a post to it
Method signatures and docstrings:
- def poster(self): RosterEntry of user who will be making post
- def get_context_data(self, **kwargs): Gets context for template, ensures we ... | 363a1f14fd1a640580a4bf4486a1afe776757557 | <|skeleton|>
class FlashbackAddPostView:
"""View for an individual flashback or adding a post to it"""
def poster(self):
"""RosterEntry of user who will be making post"""
<|body_0|>
def get_context_data(self, **kwargs):
"""Gets context for template, ensures we have permissions"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlashbackAddPostView:
"""View for an individual flashback or adding a post to it"""
def poster(self):
"""RosterEntry of user who will be making post"""
try:
return self.request.user.roster
except AttributeError:
return None
def get_context_data(self, *... | the_stack_v2_python_sparse | web/character/views.py | Arx-Game/arxcode | train | 52 |
3089a101c3cf3522e5e7043fbfa59efc4b80a792 | [
"self.__width = width\nself.__height = height\nself.__score = 0\nself.__food = deque(food)\nself.__snake = deque([(0, 0)])\nself.__direction = {'U': (-1, 0), 'L': (0, -1), 'R': (0, 1), 'D': (1, 0)}",
"def valid(x, y):\n return 0 <= x < self.__height and 0 <= y < self.__width and ((x, y) not in self.__snake)\nd... | <|body_start_0|>
self.__width = width
self.__height = height
self.__score = 0
self.__food = deque(food)
self.__snake = deque([(0, 0)])
self.__direction = {'U': (-1, 0), 'L': (0, -1), 'R': (0, 1), 'D': (1, 0)}
<|end_body_0|>
<|body_start_1|>
def valid(x, y):
... | SnakeGame | [
"Apache-2.0"
] | 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_012725 | 8,150 | permissive | [
{
"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 | stack_v2_sparse_classes_30k_train_003820 | 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... | 0ba027d9b8bc7c80bc89ce2da3543ce7a49a403c | <|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 | cs15211/DesignSnakeGame.py | JulyKikuAkita/PythonPrac | train | 1 | |
a639412340c7c976da22e0ae2f1cb875ddf94df8 | [
"r = Round.query.get(round_id)\nif r is not None:\n return {'splits': r.split_options__html(), 'competitions': [c.dancing_class.name for c in r.competition.sorted_qualifications()]}\nabort(404, 'Unknown round_id')",
"r = Round.query.get(round_id)\nif r is not None:\n r.split_qualification(api.payload['split... | <|body_start_0|>
r = Round.query.get(round_id)
if r is not None:
return {'splits': r.split_options__html(), 'competitions': [c.dancing_class.name for c in r.competition.sorted_qualifications()]}
abort(404, 'Unknown round_id')
<|end_body_0|>
<|body_start_1|>
r = Round.query.g... | RoundAPIProgressCouplesSplit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoundAPIProgressCouplesSplit:
def get(self, round_id):
"""Get the possible split options for a qualification round"""
<|body_0|>
def post(self, round_id):
"""Split the qualification round"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
r = Round.que... | stack_v2_sparse_classes_36k_train_012726 | 25,303 | no_license | [
{
"docstring": "Get the possible split options for a qualification round",
"name": "get",
"signature": "def get(self, round_id)"
},
{
"docstring": "Split the qualification round",
"name": "post",
"signature": "def post(self, round_id)"
}
] | 2 | null | Implement the Python class `RoundAPIProgressCouplesSplit` described below.
Class description:
Implement the RoundAPIProgressCouplesSplit class.
Method signatures and docstrings:
- def get(self, round_id): Get the possible split options for a qualification round
- def post(self, round_id): Split the qualification roun... | Implement the Python class `RoundAPIProgressCouplesSplit` described below.
Class description:
Implement the RoundAPIProgressCouplesSplit class.
Method signatures and docstrings:
- def get(self, round_id): Get the possible split options for a qualification round
- def post(self, round_id): Split the qualification roun... | 079b109fd13683a31d1d632faa5ab72cf0e78ddf | <|skeleton|>
class RoundAPIProgressCouplesSplit:
def get(self, round_id):
"""Get the possible split options for a qualification round"""
<|body_0|>
def post(self, round_id):
"""Split the qualification round"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoundAPIProgressCouplesSplit:
def get(self, round_id):
"""Get the possible split options for a qualification round"""
r = Round.query.get(round_id)
if r is not None:
return {'splits': r.split_options__html(), 'competitions': [c.dancing_class.name for c in r.competition.sort... | the_stack_v2_python_sparse | backend/apis/round/apis.py | AlenAlic/DANCE | train | 0 | |
8cccad9fe52080596f6d8036dec16b0f06e7fd1b | [
"graph = [[] for _ in xrange(numCourses)]\nvisit = [0 for _ in xrange(numCourses)]\nfor x, y in prerequisites:\n graph[x].append(y)\n\ndef dfs(i):\n if visit[i] == -1:\n return False\n if visit[i] == 1:\n return True\n visit[i] = -1\n for j in graph[i]:\n if not dfs(j):\n ... | <|body_start_0|>
graph = [[] for _ in xrange(numCourses)]
visit = [0 for _ in xrange(numCourses)]
for x, y in prerequisites:
graph[x].append(y)
def dfs(i):
if visit[i] == -1:
return False
if visit[i] == 1:
return True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canFinish(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool"""
<|body_0|>
def canFinish_2(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: ... | stack_v2_sparse_classes_36k_train_012727 | 3,440 | no_license | [
{
"docstring": ":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool",
"name": "canFinish",
"signature": "def canFinish(self, numCourses, prerequisites)"
},
{
"docstring": ":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool",
"name": "canFinish_2",
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canFinish(self, numCourses, prerequisites): :type numCourses: int :type prerequisites: List[List[int]] :rtype: bool
- def canFinish_2(self, numCourses, prerequisites): :type ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canFinish(self, numCourses, prerequisites): :type numCourses: int :type prerequisites: List[List[int]] :rtype: bool
- def canFinish_2(self, numCourses, prerequisites): :type ... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def canFinish(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool"""
<|body_0|>
def canFinish_2(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canFinish(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: bool"""
graph = [[] for _ in xrange(numCourses)]
visit = [0 for _ in xrange(numCourses)]
for x, y in prerequisites:
graph[x].append(y)
... | the_stack_v2_python_sparse | medium/dfsbfs/test_207_Course_Schedule.py | wuxu1019/leetcode_sophia | train | 1 | |
48c27873ddd652db728fe3b279a7f8d145ec456e | [
"if parity == 1:\n gamma = (1.0 / mu_t - 1.0 / mu_r) * 0.5\n kappa = 1 - gamma - 1.0 / mu_r\nelif parity == -1:\n gamma = (1.0 / mu_t + 1.0 / mu_r) * 0.5\n kappa = 1 - gamma + 1.0 / mu_r\nelse:\n raise ValueError('%f is not a valid value for the parity of the macromodel. Choose either +1 or -1.' % pa... | <|body_start_0|>
if parity == 1:
gamma = (1.0 / mu_t - 1.0 / mu_r) * 0.5
kappa = 1 - gamma - 1.0 / mu_r
elif parity == -1:
gamma = (1.0 / mu_t + 1.0 / mu_r) * 0.5
kappa = 1 - gamma + 1.0 / mu_r
else:
raise ValueError('%f is not a valid ... | this class implements the macromodel potential of `Diego et al. <https://www.aanda.org/articles/aa/pdf/2019/07/aa35490-19.pdf>`_ Convergence and shear are computed according to `Diego2018 <arXiv:1706.10281v2>`_ | ConstMag | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConstMag:
"""this class implements the macromodel potential of `Diego et al. <https://www.aanda.org/articles/aa/pdf/2019/07/aa35490-19.pdf>`_ Convergence and shear are computed according to `Diego2018 <arXiv:1706.10281v2>`_"""
def function(self, x, y, mu_r, mu_t, parity, phi_G, center_x=0, c... | stack_v2_sparse_classes_36k_train_012728 | 4,987 | permissive | [
{
"docstring": ":param x: x-coord (in angles) :param y: y-coord (in angles) :param mu_r: radial magnification :param mu_t: tangential magnification :param parity: parity side of the macromodel. Either +1 (positive parity) or -1 (negative parity) :param phi_G: shear orientation angle (relative to the x-axis) :re... | 3 | stack_v2_sparse_classes_30k_train_010435 | Implement the Python class `ConstMag` described below.
Class description:
this class implements the macromodel potential of `Diego et al. <https://www.aanda.org/articles/aa/pdf/2019/07/aa35490-19.pdf>`_ Convergence and shear are computed according to `Diego2018 <arXiv:1706.10281v2>`_
Method signatures and docstrings:... | Implement the Python class `ConstMag` described below.
Class description:
this class implements the macromodel potential of `Diego et al. <https://www.aanda.org/articles/aa/pdf/2019/07/aa35490-19.pdf>`_ Convergence and shear are computed according to `Diego2018 <arXiv:1706.10281v2>`_
Method signatures and docstrings:... | 73c9645f26f6983fe7961104075ebe8bf7a4b54c | <|skeleton|>
class ConstMag:
"""this class implements the macromodel potential of `Diego et al. <https://www.aanda.org/articles/aa/pdf/2019/07/aa35490-19.pdf>`_ Convergence and shear are computed according to `Diego2018 <arXiv:1706.10281v2>`_"""
def function(self, x, y, mu_r, mu_t, parity, phi_G, center_x=0, c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConstMag:
"""this class implements the macromodel potential of `Diego et al. <https://www.aanda.org/articles/aa/pdf/2019/07/aa35490-19.pdf>`_ Convergence and shear are computed according to `Diego2018 <arXiv:1706.10281v2>`_"""
def function(self, x, y, mu_r, mu_t, parity, phi_G, center_x=0, center_y=0):
... | the_stack_v2_python_sparse | lenstronomy/LensModel/Profiles/const_mag.py | lenstronomy/lenstronomy | train | 41 |
39b17239a3a3658044307180c9ddcefa60dca73d | [
"self.__phone_number = phone_number\nself.__password_hash = password_hash\nself.__connection = connection\nself.__first_name = first_name\nself.__middle_name = middle_name\nself.__last_name = last_name\nself.__dob = dob",
"try:\n cursor = self.__connection.cursor()\n cursor.execute('insert into neutron_buye... | <|body_start_0|>
self.__phone_number = phone_number
self.__password_hash = password_hash
self.__connection = connection
self.__first_name = first_name
self.__middle_name = middle_name
self.__last_name = last_name
self.__dob = dob
<|end_body_0|>
<|body_start_1|>
... | This class is used to create a new buyer account | BuyerSignUp | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuyerSignUp:
"""This class is used to create a new buyer account"""
def __init__(self, phone_number, password_hash, first_name, middle_name, last_name, dob, connection):
"""Constructor to initialize the instance variables. :param phone_number: The phone number of the buyer :param pas... | stack_v2_sparse_classes_36k_train_012729 | 2,462 | no_license | [
{
"docstring": "Constructor to initialize the instance variables. :param phone_number: The phone number of the buyer :param password_hash: The sha512 hash of the password of the buyer :param first_name: First Name of the buyer :param last_name: Last Name of the buyer :param middle_name: Middle Name of the buyer... | 2 | stack_v2_sparse_classes_30k_train_009473 | Implement the Python class `BuyerSignUp` described below.
Class description:
This class is used to create a new buyer account
Method signatures and docstrings:
- def __init__(self, phone_number, password_hash, first_name, middle_name, last_name, dob, connection): Constructor to initialize the instance variables. :par... | Implement the Python class `BuyerSignUp` described below.
Class description:
This class is used to create a new buyer account
Method signatures and docstrings:
- def __init__(self, phone_number, password_hash, first_name, middle_name, last_name, dob, connection): Constructor to initialize the instance variables. :par... | c3b067492b9ffa885323f457a6e101ced8dcef06 | <|skeleton|>
class BuyerSignUp:
"""This class is used to create a new buyer account"""
def __init__(self, phone_number, password_hash, first_name, middle_name, last_name, dob, connection):
"""Constructor to initialize the instance variables. :param phone_number: The phone number of the buyer :param pas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BuyerSignUp:
"""This class is used to create a new buyer account"""
def __init__(self, phone_number, password_hash, first_name, middle_name, last_name, dob, connection):
"""Constructor to initialize the instance variables. :param phone_number: The phone number of the buyer :param password_hash: T... | the_stack_v2_python_sparse | Neutron/buyer/sign_up.py | VISWESWARAN1998/Neutron | train | 6 |
53749f648fa8110d9eb59f99dab9e8e9ff3ad060 | [
"self.platform_id = platform_id\nself.name = name\nself.status = status\nself.source = source\nself.source_id = source_id\nself.file_avatar_thumb = self.find_avatar(platform_id, 'thumb')\nself.file_avatar = self.find_avatar(platform_id)\nif owner:\n self.file_avatar_thumb = self.find_avatar('me', 'thumb')\n f... | <|body_start_0|>
self.platform_id = platform_id
self.name = name
self.status = status
self.source = source
self.source_id = source_id
self.file_avatar_thumb = self.find_avatar(platform_id, 'thumb')
self.file_avatar = self.find_avatar(platform_id)
if owner:... | Contact object to store contact information | Contact | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Contact:
"""Contact object to store contact information"""
def __init__(self, platform_id, name=None, status=None, source=None, source_id=None, owner=None):
"""Create a new Contact object. :param platform_id: WhatsApp-ID :param name=None: name of contact :param status=None: user stat... | stack_v2_sparse_classes_36k_train_012730 | 46,698 | permissive | [
{
"docstring": "Create a new Contact object. :param platform_id: WhatsApp-ID :param name=None: name of contact :param status=None: user status :param source=None: source of data (database, etc.) :param source_id=None: source id of data (id of entry in database)",
"name": "__init__",
"signature": "def __... | 2 | stack_v2_sparse_classes_30k_train_017886 | Implement the Python class `Contact` described below.
Class description:
Contact object to store contact information
Method signatures and docstrings:
- def __init__(self, platform_id, name=None, status=None, source=None, source_id=None, owner=None): Create a new Contact object. :param platform_id: WhatsApp-ID :param... | Implement the Python class `Contact` described below.
Class description:
Contact object to store contact information
Method signatures and docstrings:
- def __init__(self, platform_id, name=None, status=None, source=None, source_id=None, owner=None): Create a new Contact object. :param platform_id: WhatsApp-ID :param... | 5ba553fd0eb4c1d80842074a553119486f005822 | <|skeleton|>
class Contact:
"""Contact object to store contact information"""
def __init__(self, platform_id, name=None, status=None, source=None, source_id=None, owner=None):
"""Create a new Contact object. :param platform_id: WhatsApp-ID :param name=None: name of contact :param status=None: user stat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Contact:
"""Contact object to store contact information"""
def __init__(self, platform_id, name=None, status=None, source=None, source_id=None, owner=None):
"""Create a new Contact object. :param platform_id: WhatsApp-ID :param name=None: name of contact :param status=None: user status :param sou... | the_stack_v2_python_sparse | MobileRevelator/python/whatsapp.py | bkerler/MR | train | 140 |
35c779ca407e7070ae7c6a3d4c93b4016be0b8f0 | [
"if not root:\n return None\nq = deque([root])\narr = []\nwhile q:\n node = q.popleft()\n if not node:\n arr.append('None')\n continue\n arr.append(str(node.val))\n q.extend([node.left, node.right])\nreturn ' '.join(arr)",
"if not data:\n return None\nnodes = deque(data.split(' '))... | <|body_start_0|>
if not root:
return None
q = deque([root])
arr = []
while q:
node = q.popleft()
if not node:
arr.append('None')
continue
arr.append(str(node.val))
q.extend([node.left, node.right]... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_012731 | 2,857 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_011011 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | fbaae4bdbb2017ee43b0d1a3f23137a75f7ea2c1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return None
q = deque([root])
arr = []
while q:
node = q.popleft()
if not node:
arr.append('None'... | the_stack_v2_python_sparse | serialise_deserialise_binary_tree.py | Milan-Chicago/ds-guide | train | 0 | |
42e73af0a8a0595994a59e3400f84348ec0959e1 | [
"try:\n vaccination = models.Vaccination.create_from_json(data=request.data, patient_profile=request.user.patient_profile)\nexcept custom_exceptions.DataNotProvided as e:\n return response.Response(data=e.get_response_format(), status=status.HTTP_400_BAD_REQUEST)\nserialized_vaccination = serializers.Vaccinat... | <|body_start_0|>
try:
vaccination = models.Vaccination.create_from_json(data=request.data, patient_profile=request.user.patient_profile)
except custom_exceptions.DataNotProvided as e:
return response.Response(data=e.get_response_format(), status=status.HTTP_400_BAD_REQUEST)
... | Endpoints for Vaccination objects. | VaccinationsEndpoint | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VaccinationsEndpoint:
"""Endpoints for Vaccination objects."""
def post(self, request: Request) -> response.Response:
"""Adds a new vaccination for the user."""
<|body_0|>
def put(self, request: Request) -> response.Response:
"""Updates an existing vaccination.""... | stack_v2_sparse_classes_36k_train_012732 | 14,860 | no_license | [
{
"docstring": "Adds a new vaccination for the user.",
"name": "post",
"signature": "def post(self, request: Request) -> response.Response"
},
{
"docstring": "Updates an existing vaccination.",
"name": "put",
"signature": "def put(self, request: Request) -> response.Response"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_014760 | Implement the Python class `VaccinationsEndpoint` described below.
Class description:
Endpoints for Vaccination objects.
Method signatures and docstrings:
- def post(self, request: Request) -> response.Response: Adds a new vaccination for the user.
- def put(self, request: Request) -> response.Response: Updates an ex... | Implement the Python class `VaccinationsEndpoint` described below.
Class description:
Endpoints for Vaccination objects.
Method signatures and docstrings:
- def post(self, request: Request) -> response.Response: Adds a new vaccination for the user.
- def put(self, request: Request) -> response.Response: Updates an ex... | b6d757895132b9b3c8c6682c11efadf993d5905b | <|skeleton|>
class VaccinationsEndpoint:
"""Endpoints for Vaccination objects."""
def post(self, request: Request) -> response.Response:
"""Adds a new vaccination for the user."""
<|body_0|>
def put(self, request: Request) -> response.Response:
"""Updates an existing vaccination.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VaccinationsEndpoint:
"""Endpoints for Vaccination objects."""
def post(self, request: Request) -> response.Response:
"""Adds a new vaccination for the user."""
try:
vaccination = models.Vaccination.create_from_json(data=request.data, patient_profile=request.user.patient_profi... | the_stack_v2_python_sparse | main/model_api.py | kalolad1/cosmos | train | 0 |
7888c2b1eb20ff56234bb05f494a8abc41294b8a | [
"search = ['أ', 'إ', 'آ', 'ة', '_', '-', '/', '.', '،', ' و ', ' يا ', '\"', 'ـ', \"'\", 'ى', '\\\\', '\\n', '\\t', '"', '?', '؟', '!', ':', '(', ')', '\\x02']\nreplace = ['ا', 'ا', 'ا', 'ه', ' ', ' ', '', '', '', ' و', ' يا', '', '', '', 'ي', '', ' ', ' ', ' ', ' ? ', ' ؟ ', ' ! ', '', '', '', '']\np_tashkeel... | <|body_start_0|>
search = ['أ', 'إ', 'آ', 'ة', '_', '-', '/', '.', '،', ' و ', ' يا ', '"', 'ـ', "'", 'ى', '\\', '\n', '\t', '"', '?', '؟', '!', ':', '(', ')', '\x02']
replace = ['ا', 'ا', 'ا', 'ه', ' ', ' ', '', '', '', ' و', ' يا', '', '', '', 'ي', '', ' ', ' ', ' ', ' ? ', ' ؟ ', ' ! ', '', '', ... | Procces the data and embed them using AraVec OR ELMo | Embedding | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Embedding:
"""Procces the data and embed them using AraVec OR ELMo"""
def clean_str(text: str) -> str:
"""Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_012733 | 5,959 | no_license | [
{
"docstring": "Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book",
"name": "clean_str",
"signature": "def clean_str(text: str) -> str"
},
{
"docstring": "Embed each word in the book into a Vector in... | 3 | stack_v2_sparse_classes_30k_train_000505 | Implement the Python class `Embedding` described below.
Class description:
Procces the data and embed them using AraVec OR ELMo
Method signatures and docstrings:
- def clean_str(text: str) -> str: Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns s... | Implement the Python class `Embedding` described below.
Class description:
Procces the data and embed them using AraVec OR ELMo
Method signatures and docstrings:
- def clean_str(text: str) -> str: Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns s... | c7349dd0501e9a0d47a8f1024762ee15b225c6e0 | <|skeleton|>
class Embedding:
"""Procces the data and embed them using AraVec OR ELMo"""
def clean_str(text: str) -> str:
"""Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Embedding:
"""Procces the data and embed them using AraVec OR ELMo"""
def clean_str(text: str) -> str:
"""Removing any additional characters found in the TEXT, Based on AraVec. :parameter text in str format as a book :returns str as a preprocessed book"""
search = ['أ', 'إ', 'آ', 'ة', '_'... | the_stack_v2_python_sparse | Algs/Embedding.py | saleems11/Final_Project_B | train | 0 |
a7565767aba273b63778460edc7e99085fe1bbd6 | [
"self.x = int(x)\nself.y = int(y)\nself.p = int(p)\nself.ip_address = ip_address",
"if self.p > 0:\n return self.p\nelse:\n return TYPICAL_PHYSICAL_VIRTUAL_MAP[0 - self.p]",
"result = CORE_RANGE.fullmatch(core_string)\nif result is not None:\n return range(int(result.group(1)), int(result.group(2)) + 1... | <|body_start_0|>
self.x = int(x)
self.y = int(y)
self.p = int(p)
self.ip_address = ip_address
<|end_body_0|>
<|body_start_1|>
if self.p > 0:
return self.p
else:
return TYPICAL_PHYSICAL_VIRTUAL_MAP[0 - self.p]
<|end_body_1|>
<|body_start_2|>
... | Represents a core to be ignored when building a machine. | IgnoreCore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IgnoreCore:
"""Represents a core to be ignored when building a machine."""
def __init__(self, x, y, p, ip_address=None):
""":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a... | stack_v2_sparse_classes_36k_train_012734 | 5,810 | permissive | [
{
"docstring": ":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a core if > 0, or the physical core if <= 0 (actual value will be negated) :type p: int or str :param ip_address: Optional IP address whi... | 5 | stack_v2_sparse_classes_30k_train_003086 | Implement the Python class `IgnoreCore` described below.
Class description:
Represents a core to be ignored when building a machine.
Method signatures and docstrings:
- def __init__(self, x, y, p, ip_address=None): :param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to igno... | Implement the Python class `IgnoreCore` described below.
Class description:
Represents a core to be ignored when building a machine.
Method signatures and docstrings:
- def __init__(self, x, y, p, ip_address=None): :param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to igno... | 7ec4276879249d53ed8153a62b0b344c5f0b99e3 | <|skeleton|>
class IgnoreCore:
"""Represents a core to be ignored when building a machine."""
def __init__(self, x, y, p, ip_address=None):
""":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IgnoreCore:
"""Represents a core to be ignored when building a machine."""
def __init__(self, x, y, p, ip_address=None):
""":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a core if > 0,... | the_stack_v2_python_sparse | spinn_machine/ignores/ignore_core.py | SpiNNakerManchester/SpiNNMachine | train | 6 |
49919c2323266cadcc59c59e708a976a5f266ba7 | [
"flags.AddParentFlagsToParser(parser)\nparser.add_argument('--location', metavar='LOCATION', required=True, help='Location')\nparser.add_argument('--insight-type', metavar='INSIGHT_TYPE', required=True, help='Insight type to list insights for. Supported insight-types can be found here: https://cloud.google.com/reco... | <|body_start_0|>
flags.AddParentFlagsToParser(parser)
parser.add_argument('--location', metavar='LOCATION', required=True, help='Location')
parser.add_argument('--insight-type', metavar='INSIGHT_TYPE', required=True, help='Insight type to list insights for. Supported insight-types can be found h... | List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are supported: project, billing_account, folder a... | ListOriginal | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListOriginal:
"""List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are suppo... | stack_v2_sparse_classes_36k_train_012735 | 6,196 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Run 'gcloud recommender insight... | 2 | stack_v2_sparse_classes_30k_train_012744 | Implement the Python class `ListOriginal` described below.
Class description:
List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the... | Implement the Python class `ListOriginal` described below.
Class description:
List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class ListOriginal:
"""List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are suppo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListOriginal:
"""List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are supported: project... | the_stack_v2_python_sparse | lib/surface/recommender/insights/list.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
458a9c1bcfbad838e32131bc43236e48ecb6fd87 | [
"with patch('goldstone.core.utils.exception_handler') as exception_handler:\n exception_handler.return_value = \"it's handled\"\n result = custom_exception_handler(None, None)\n self.assertTrue(exception_handler.called)\n self.assertEqual(result, \"it's handled\")",
"with patch('goldstone.core.utils.e... | <|body_start_0|>
with patch('goldstone.core.utils.exception_handler') as exception_handler:
exception_handler.return_value = "it's handled"
result = custom_exception_handler(None, None)
self.assertTrue(exception_handler.called)
self.assertEqual(result, "it's handl... | Tests for DRF custom exception handling. | CustomExceptionHandlerTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomExceptionHandlerTests:
"""Tests for DRF custom exception handling."""
def test_drf_handled_exception(self):
"""Test that we pass DRF recognized exceptions through unmodified"""
<|body_0|>
def test_502_error_exceptions(self):
"""Test ES connection exception ... | stack_v2_sparse_classes_36k_train_012736 | 22,971 | permissive | [
{
"docstring": "Test that we pass DRF recognized exceptions through unmodified",
"name": "test_drf_handled_exception",
"signature": "def test_drf_handled_exception(self)"
},
{
"docstring": "Test ES connection exception is handled",
"name": "test_502_error_exceptions",
"signature": "def t... | 4 | stack_v2_sparse_classes_30k_train_016697 | Implement the Python class `CustomExceptionHandlerTests` described below.
Class description:
Tests for DRF custom exception handling.
Method signatures and docstrings:
- def test_drf_handled_exception(self): Test that we pass DRF recognized exceptions through unmodified
- def test_502_error_exceptions(self): Test ES ... | Implement the Python class `CustomExceptionHandlerTests` described below.
Class description:
Tests for DRF custom exception handling.
Method signatures and docstrings:
- def test_drf_handled_exception(self): Test that we pass DRF recognized exceptions through unmodified
- def test_502_error_exceptions(self): Test ES ... | 73d334a9f0df7c044c06989977a9a22dd2ff9b7a | <|skeleton|>
class CustomExceptionHandlerTests:
"""Tests for DRF custom exception handling."""
def test_drf_handled_exception(self):
"""Test that we pass DRF recognized exceptions through unmodified"""
<|body_0|>
def test_502_error_exceptions(self):
"""Test ES connection exception ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomExceptionHandlerTests:
"""Tests for DRF custom exception handling."""
def test_drf_handled_exception(self):
"""Test that we pass DRF recognized exceptions through unmodified"""
with patch('goldstone.core.utils.exception_handler') as exception_handler:
exception_handler.r... | the_stack_v2_python_sparse | goldstone/core/tests.py | bhuvan-rk/goldstone-server | train | 0 |
4e9b8c123a2225ecf7660fbd919f985063439c33 | [
"page = page\nper_page = 8\nrecommendations = Recommendation.query.order_by(Recommendation.created_at.desc()).paginate(page, per_page, error_out=False)\nresponse = {'items': recommendations_schema.dump(recommendations.items), 'has_next': recommendations.has_next, 'has_prev': recommendations.has_prev, 'next_num': re... | <|body_start_0|>
page = page
per_page = 8
recommendations = Recommendation.query.order_by(Recommendation.created_at.desc()).paginate(page, per_page, error_out=False)
response = {'items': recommendations_schema.dump(recommendations.items), 'has_next': recommendations.has_next, 'has_prev':... | Recommendations | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Recommendations:
def get(self, page):
"""List Recommendations"""
<|body_0|>
def post(self):
"""Add new Recommendation"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
page = page
per_page = 8
recommendations = Recommendation.query.ord... | stack_v2_sparse_classes_36k_train_012737 | 7,370 | no_license | [
{
"docstring": "List Recommendations",
"name": "get",
"signature": "def get(self, page)"
},
{
"docstring": "Add new Recommendation",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020142 | Implement the Python class `Recommendations` described below.
Class description:
Implement the Recommendations class.
Method signatures and docstrings:
- def get(self, page): List Recommendations
- def post(self): Add new Recommendation | Implement the Python class `Recommendations` described below.
Class description:
Implement the Recommendations class.
Method signatures and docstrings:
- def get(self, page): List Recommendations
- def post(self): Add new Recommendation
<|skeleton|>
class Recommendations:
def get(self, page):
"""List Re... | ae78fff9888b0f68d9403d7f65cba086dabb3802 | <|skeleton|>
class Recommendations:
def get(self, page):
"""List Recommendations"""
<|body_0|>
def post(self):
"""Add new Recommendation"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Recommendations:
def get(self, page):
"""List Recommendations"""
page = page
per_page = 8
recommendations = Recommendation.query.order_by(Recommendation.created_at.desc()).paginate(page, per_page, error_out=False)
response = {'items': recommendations_schema.dump(recomme... | the_stack_v2_python_sparse | api/v1/recommendations.py | mythril-io/flask-api | train | 0 | |
7bc476d9def287da9ea035bb6aba2aa17d8691f3 | [
"Frame.__init__(self, master)\nself.pack()\nself.createWidgets()",
"main_frame = Frame(self)\nLabel(main_frame, text='Please input a county').pack()\nself.text_in = Entry(main_frame)\nself.text_in.insert('end', 'Kent')\nself.text_in.pack()\nself.btn_go = Button(main_frame, text='GO!', command=self.handler)\nself.... | <|body_start_0|>
Frame.__init__(self, master)
self.pack()
self.createWidgets()
<|end_body_0|>
<|body_start_1|>
main_frame = Frame(self)
Label(main_frame, text='Please input a county').pack()
self.text_in = Entry(main_frame)
self.text_in.insert('end', 'Kent')
... | Application main window class. | Application | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handler(self):
... | stack_v2_sparse_classes_36k_train_012738 | 1,927 | permissive | [
{
"docstring": "Main frame initialization (mostly delegated)",
"name": "__init__",
"signature": "def __init__(self, master=None)"
},
{
"docstring": "Add all the widgets to the main frame.",
"name": "createWidgets",
"signature": "def createWidgets(self)"
},
{
"docstring": "Runs a ... | 3 | stack_v2_sparse_classes_30k_train_012615 | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createWidgets(self): Add all the widgets to the main frame.
- def handler(self): Runs a db... | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createWidgets(self): Add all the widgets to the main frame.
- def handler(self): Runs a db... | a9d0dc2eb16ebc4d2fd451c3a3e6f96e37c87675 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handler(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
Frame.__init__(self, master)
self.pack()
self.createWidgets()
def createWidgets(self):
"""Add all the widgets to the main fram... | the_stack_v2_python_sparse | dkr-py310/docker-student-portal-310/course_files/begin_advanced/solution_python2_chapter07_logging_gui.py | pbarton666/virtual_classroom | train | 0 |
78b760f76448912785e3aecb3cf2f3780ee1ada1 | [
"if minfo is None:\n minfo = {}\nsuper(ShutdownMessage, self).__init__(minfo)\nself.NodeList = minfo.get('NodeList', [])\nself.IsSystemMessage = True\nself.IsForward = True\nself.IsReliable = False",
"result = super(ShutdownMessage, self).dump()\nresult['NodeList'] = self.NodeList\nreturn result"
] | <|body_start_0|>
if minfo is None:
minfo = {}
super(ShutdownMessage, self).__init__(minfo)
self.NodeList = minfo.get('NodeList', [])
self.IsSystemMessage = True
self.IsForward = True
self.IsReliable = False
<|end_body_0|>
<|body_start_1|>
result = sup... | Shutdown messages are sent to a peer node to initiate shutdown. Attributes: ShutdownMessage.MessageType (str): The class name of the message. NodeList (list): The list of nodes to shutdown. IsSystemMessage (bool): Whether or not this is a system message. System messages have special delivery priority rules. IsForward (... | ShutdownMessage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShutdownMessage:
"""Shutdown messages are sent to a peer node to initiate shutdown. Attributes: ShutdownMessage.MessageType (str): The class name of the message. NodeList (list): The list of nodes to shutdown. IsSystemMessage (bool): Whether or not this is a system message. System messages have s... | stack_v2_sparse_classes_36k_train_012739 | 4,179 | permissive | [
{
"docstring": "Constructor for the ShutdownMessage class. Args: minfo (dict): Dictionary of values for message fields.",
"name": "__init__",
"signature": "def __init__(self, minfo=None)"
},
{
"docstring": "Dumps a dict containing object attributes. Returns: dict: A mapping of object attribute n... | 2 | stack_v2_sparse_classes_30k_train_010321 | Implement the Python class `ShutdownMessage` described below.
Class description:
Shutdown messages are sent to a peer node to initiate shutdown. Attributes: ShutdownMessage.MessageType (str): The class name of the message. NodeList (list): The list of nodes to shutdown. IsSystemMessage (bool): Whether or not this is a... | Implement the Python class `ShutdownMessage` described below.
Class description:
Shutdown messages are sent to a peer node to initiate shutdown. Attributes: ShutdownMessage.MessageType (str): The class name of the message. NodeList (list): The list of nodes to shutdown. IsSystemMessage (bool): Whether or not this is a... | 8f4ca1aab54ef420a0db10c8ca822ec8686cd423 | <|skeleton|>
class ShutdownMessage:
"""Shutdown messages are sent to a peer node to initiate shutdown. Attributes: ShutdownMessage.MessageType (str): The class name of the message. NodeList (list): The list of nodes to shutdown. IsSystemMessage (bool): Whether or not this is a system message. System messages have s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShutdownMessage:
"""Shutdown messages are sent to a peer node to initiate shutdown. Attributes: ShutdownMessage.MessageType (str): The class name of the message. NodeList (list): The list of nodes to shutdown. IsSystemMessage (bool): Whether or not this is a system message. System messages have special delive... | the_stack_v2_python_sparse | validator/gossip/messages/shutdown_message.py | aludvik/sawtooth-core | train | 0 |
015dcf019daa518cea756c0b30993eb52246411b | [
"if len(prices) < 2:\n return 0\ndp = [[[0 for _ in range(2)] for _ in range(k + 1)] for _ in range(len(prices))]\nfor i in range(1, k + 1):\n dp[0][i][0] = 0\n dp[0][i][1] = -prices[0]\nfor i in range(1, len(prices)):\n for j in range(1, k + 1):\n dp[i][j][0] = max(dp[i - 1][j][0], dp[i - 1][j][... | <|body_start_0|>
if len(prices) < 2:
return 0
dp = [[[0 for _ in range(2)] for _ in range(k + 1)] for _ in range(len(prices))]
for i in range(1, k + 1):
dp[0][i][0] = 0
dp[0][i][1] = -prices[0]
for i in range(1, len(prices)):
for j in range... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, k: int, prices: List[int]) -> int:
"""动态规划 方程为 dp[i][k][j] 0 <= i < len(prices) 表示天数 dp[i][k][0] 表示当前天未持股，有以下两种情况: 1. 昨天未持股今天也未持股 2. 昨天持股，今天卖出 dp[i][k][0] = max(dp[i - 1][k][0], dp[i - 1][k][1] + prices[i]) dp[i][k][1] 表示当前天持股，有以下两种情况: 1. 昨天持股，今天也持股 2. 昨天未持股... | stack_v2_sparse_classes_36k_train_012740 | 2,774 | no_license | [
{
"docstring": "动态规划 方程为 dp[i][k][j] 0 <= i < len(prices) 表示天数 dp[i][k][0] 表示当前天未持股，有以下两种情况: 1. 昨天未持股今天也未持股 2. 昨天持股，今天卖出 dp[i][k][0] = max(dp[i - 1][k][0], dp[i - 1][k][1] + prices[i]) dp[i][k][1] 表示当前天持股，有以下两种情况: 1. 昨天持股，今天也持股 2. 昨天未持股，今天买入 dp[i][k][1] = max(dp[i - 1][k][1], dp[i - 1][k - 1][0] - prices[i]) :p... | 2 | stack_v2_sparse_classes_30k_train_001502 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, k: int, prices: List[int]) -> int: 动态规划 方程为 dp[i][k][j] 0 <= i < len(prices) 表示天数 dp[i][k][0] 表示当前天未持股，有以下两种情况: 1. 昨天未持股今天也未持股 2. 昨天持股，今天卖出 dp[i][k][0] = max(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, k: int, prices: List[int]) -> int: 动态规划 方程为 dp[i][k][j] 0 <= i < len(prices) 表示天数 dp[i][k][0] 表示当前天未持股，有以下两种情况: 1. 昨天未持股今天也未持股 2. 昨天持股，今天卖出 dp[i][k][0] = max(... | 9acba92695c06406f12f997a720bfe1deb9464a8 | <|skeleton|>
class Solution:
def maxProfit(self, k: int, prices: List[int]) -> int:
"""动态规划 方程为 dp[i][k][j] 0 <= i < len(prices) 表示天数 dp[i][k][0] 表示当前天未持股，有以下两种情况: 1. 昨天未持股今天也未持股 2. 昨天持股，今天卖出 dp[i][k][0] = max(dp[i - 1][k][0], dp[i - 1][k][1] + prices[i]) dp[i][k][1] 表示当前天持股，有以下两种情况: 1. 昨天持股，今天也持股 2. 昨天未持股... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, k: int, prices: List[int]) -> int:
"""动态规划 方程为 dp[i][k][j] 0 <= i < len(prices) 表示天数 dp[i][k][0] 表示当前天未持股，有以下两种情况: 1. 昨天未持股今天也未持股 2. 昨天持股，今天卖出 dp[i][k][0] = max(dp[i - 1][k][0], dp[i - 1][k][1] + prices[i]) dp[i][k][1] 表示当前天持股，有以下两种情况: 1. 昨天持股，今天也持股 2. 昨天未持股，今天买入 dp[i][k]... | the_stack_v2_python_sparse | datastructure/dp_exercise/MaxProfit5.py | yinhuax/leet_code | train | 0 | |
75455841030bdbb9160abe2cfd88a463c92783b3 | [
"ret = [1] * len(nums)\naccum = 1\nfor i, n in enumerate(nums):\n ret[i] *= accum\n accum *= n\naccum = 1\nfor i, n in enumerate(nums[-1::-1]):\n ret[len(nums) - 1 - i] *= accum\n accum *= n\nreturn ret",
"if not nums:\n return []\nprefix = [1]\nfor i in range(len(nums)):\n prefix.append(prefix[... | <|body_start_0|>
ret = [1] * len(nums)
accum = 1
for i, n in enumerate(nums):
ret[i] *= accum
accum *= n
accum = 1
for i, n in enumerate(nums[-1::-1]):
ret[len(nums) - 1 - i] *= accum
accum *= n
return ret
<|end_body_0|>
<|... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""08/25/2019 19:56"""
<|body_0|>
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""12/03/2021 20:57"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = [1] * len(num... | stack_v2_sparse_classes_36k_train_012741 | 2,089 | no_license | [
{
"docstring": "08/25/2019 19:56",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums: List[int]) -> List[int]"
},
{
"docstring": "12/03/2021 20:57",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums: List[int]) -> List[int]"
}
] | 2 | stack_v2_sparse_classes_30k_train_009873 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums: List[int]) -> List[int]: 08/25/2019 19:56
- def productExceptSelf(self, nums: List[int]) -> List[int]: 12/03/2021 20:57 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums: List[int]) -> List[int]: 08/25/2019 19:56
- def productExceptSelf(self, nums: List[int]) -> List[int]: 12/03/2021 20:57
<|skeleton|>
class Solu... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""08/25/2019 19:56"""
<|body_0|>
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""12/03/2021 20:57"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""08/25/2019 19:56"""
ret = [1] * len(nums)
accum = 1
for i, n in enumerate(nums):
ret[i] *= accum
accum *= n
accum = 1
for i, n in enumerate(nums[-1::-1]):
... | the_stack_v2_python_sparse | leetcode/solved/238_Product_of_Array_Except_Self/solution.py | sungminoh/algorithms | train | 0 | |
db0e904737fdef2468c5bd5147e13e427330e691 | [
"if n < 0:\n return 0\nif n == 0:\n return 1\nsum = 0\nsum += self.climbStairsRecur(n - 1)\nsum += self.climbStairsRecur(n - 2)\nreturn sum",
"memo = [0] * (n + 1)\nmemo[0] = 1\nmemo[1] = 1\nfor i in range(2, n + 1):\n j = 1\n while j <= 2 and j <= i:\n memo[i] += memo[i - j]\n j += 1\nr... | <|body_start_0|>
if n < 0:
return 0
if n == 0:
return 1
sum = 0
sum += self.climbStairsRecur(n - 1)
sum += self.climbStairsRecur(n - 2)
return sum
<|end_body_0|>
<|body_start_1|>
memo = [0] * (n + 1)
memo[0] = 1
memo[1] = 1... | Stairs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Stairs:
def climbStairsRecur(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n < 0:
return 0
if n == 0:
retu... | stack_v2_sparse_classes_36k_train_012742 | 618 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairsRecur",
"signature": "def climbStairsRecur(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
}
] | 2 | null | Implement the Python class `Stairs` described below.
Class description:
Implement the Stairs class.
Method signatures and docstrings:
- def climbStairsRecur(self, n): :type n: int :rtype: int
- def climbStairs(self, n): :type n: int :rtype: int | Implement the Python class `Stairs` described below.
Class description:
Implement the Stairs class.
Method signatures and docstrings:
- def climbStairsRecur(self, n): :type n: int :rtype: int
- def climbStairs(self, n): :type n: int :rtype: int
<|skeleton|>
class Stairs:
def climbStairsRecur(self, n):
"... | e7f486114df17918e49d6452c7047c9d90e8aef2 | <|skeleton|>
class Stairs:
def climbStairsRecur(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Stairs:
def climbStairsRecur(self, n):
""":type n: int :rtype: int"""
if n < 0:
return 0
if n == 0:
return 1
sum = 0
sum += self.climbStairsRecur(n - 1)
sum += self.climbStairsRecur(n - 2)
return sum
def climbStairs(self, n):... | the_stack_v2_python_sparse | tranquil-beach/dp/stairs.py | yokolet/tranquil-beach-python | train | 0 | |
c481ad15d87ebb2a2781147cc29366163b036161 | [
"self.absdatadir = os.path.abspath(datadir)\nvalid_datadir(self.absdatadir)\ntemp = create_unique_file(self.absdatadir)\nos.remove(temp)\nself.hostname = socket.gethostname()\nself.sequence_number = 0\nself.last_process_most_recent = most_recent_unique_file(self.absdatadir)\nif self.last_process_most_recent:\n s... | <|body_start_0|>
self.absdatadir = os.path.abspath(datadir)
valid_datadir(self.absdatadir)
temp = create_unique_file(self.absdatadir)
os.remove(temp)
self.hostname = socket.gethostname()
self.sequence_number = 0
self.last_process_most_recent = most_recent_unique_f... | BoardData holds state required to write records to a simple database. Records are stored one at a time and stored in individual files in a data directory. Records consist of any Python data structure that can be represented with JSON. The records are stored in a header structure which provides meta-information. Files i... | BoardData | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoardData:
"""BoardData holds state required to write records to a simple database. Records are stored one at a time and stored in individual files in a data directory. Records consist of any Python data structure that can be represented with JSON. The records are stored in a header structure whi... | stack_v2_sparse_classes_36k_train_012743 | 19,539 | permissive | [
{
"docstring": "Initialize the BoardData instance using datadir as the directory to store data.",
"name": "__init__",
"signature": "def __init__(self, datadir)"
},
{
"docstring": "Stores payload conforming to schema.",
"name": "Store",
"signature": "def Store(self, payload, schema)"
}
... | 2 | stack_v2_sparse_classes_30k_train_013483 | Implement the Python class `BoardData` described below.
Class description:
BoardData holds state required to write records to a simple database. Records are stored one at a time and stored in individual files in a data directory. Records consist of any Python data structure that can be represented with JSON. The recor... | Implement the Python class `BoardData` described below.
Class description:
BoardData holds state required to write records to a simple database. Records are stored one at a time and stored in individual files in a data directory. Records consist of any Python data structure that can be represented with JSON. The recor... | 9617691ac997f12085b688c3ecc6746e8510976d | <|skeleton|>
class BoardData:
"""BoardData holds state required to write records to a simple database. Records are stored one at a time and stored in individual files in a data directory. Records consist of any Python data structure that can be represented with JSON. The records are stored in a header structure whi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BoardData:
"""BoardData holds state required to write records to a simple database. Records are stored one at a time and stored in individual files in a data directory. Records consist of any Python data structure that can be represented with JSON. The records are stored in a header structure which provides m... | the_stack_v2_python_sparse | hf/boardlib/boardlib.py | Thireus/hashfast-tools | train | 0 |
81f363368eb9da41b4414fd7151288444367e500 | [
"def dfs(i):\n if visited[i]:\n return 0\n visited[i] = True\n count = 1\n for j in range(len(M[i])):\n if M[i][j] == 1 and i != j:\n count += dfs(j)\n return count\ncount = 0\nvisited = [False] * len(M)\nfor i in range(len(M)):\n if dfs(i) > 0:\n count += 1\nreturn... | <|body_start_0|>
def dfs(i):
if visited[i]:
return 0
visited[i] = True
count = 1
for j in range(len(M[i])):
if M[i][j] == 1 and i != j:
count += dfs(j)
return count
count = 0
visited =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findCircleNum(self, M):
""":type M: List[List[int]] :rtype: int"""
<|body_0|>
def findCircleNum_unionfind(self, M):
""":type M: List[List[int]] :rtype: int"""
<|body_1|>
def findCircleNum_wrong(self, M):
""":type M: List[List[int]] ... | stack_v2_sparse_classes_36k_train_012744 | 24,866 | no_license | [
{
"docstring": ":type M: List[List[int]] :rtype: int",
"name": "findCircleNum",
"signature": "def findCircleNum(self, M)"
},
{
"docstring": ":type M: List[List[int]] :rtype: int",
"name": "findCircleNum_unionfind",
"signature": "def findCircleNum_unionfind(self, M)"
},
{
"docstri... | 4 | stack_v2_sparse_classes_30k_train_005058 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findCircleNum(self, M): :type M: List[List[int]] :rtype: int
- def findCircleNum_unionfind(self, M): :type M: List[List[int]] :rtype: int
- def findCircleNum_wrong(self, M): ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findCircleNum(self, M): :type M: List[List[int]] :rtype: int
- def findCircleNum_unionfind(self, M): :type M: List[List[int]] :rtype: int
- def findCircleNum_wrong(self, M): ... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def findCircleNum(self, M):
""":type M: List[List[int]] :rtype: int"""
<|body_0|>
def findCircleNum_unionfind(self, M):
""":type M: List[List[int]] :rtype: int"""
<|body_1|>
def findCircleNum_wrong(self, M):
""":type M: List[List[int]] ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findCircleNum(self, M):
""":type M: List[List[int]] :rtype: int"""
def dfs(i):
if visited[i]:
return 0
visited[i] = True
count = 1
for j in range(len(M[i])):
if M[i][j] == 1 and i != j:
... | the_stack_v2_python_sparse | src/lt_547.py | oxhead/CodingYourWay | train | 0 | |
1e4aa5f9f632274a0d6750c981aaaa07fc9a2930 | [
"if not nums:\n return 0\nmemo = [0] * (len(nums) + 1)\nmemo[1] = nums[0]\nfor i in range(1, len(nums)):\n memo[i + 1] = max(memo[i], memo[i - 1] + nums[i])\nreturn memo[-1]",
"prevMax = 0\ncurrMax = 0\nfor i in nums:\n temp = currMax\n currMax = max(prevMax + i, currMax)\n prevMax = temp\nreturn c... | <|body_start_0|>
if not nums:
return 0
memo = [0] * (len(nums) + 1)
memo[1] = nums[0]
for i in range(1, len(nums)):
memo[i + 1] = max(memo[i], memo[i - 1] + nums[i])
return memo[-1]
<|end_body_0|>
<|body_start_1|>
prevMax = 0
currMax = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return 0
memo = [0] * (len(... | stack_v2_sparse_classes_36k_train_012745 | 808 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob",
"signature": "def rob(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob2",
"signature": "def rob2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): :type nums: List[int] :rtype: int
- def rob2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): :type nums: List[int] :rtype: int
- def rob2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def rob(self, nums):
"... | 28219fbc5e2e96f59e9d2b9d1da18f05187898c8 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
memo = [0] * (len(nums) + 1)
memo[1] = nums[0]
for i in range(1, len(nums)):
memo[i + 1] = max(memo[i], memo[i - 1] + nums[i])
return memo[-1]
... | the_stack_v2_python_sparse | 2019/go/198-house-robber.py | the-potato-man/lc | train | 0 | |
663058f58bcb7d19c05c3ee2b5f758bf6c919e72 | [
"super(_SoilWateringPollWorker, self).__init__(scheduler, record_queue, mqtt_client, soil_moisture_sensor)\nself._drain_sensor = drain_sensor\nself._pump_manager = pump_manager",
"time.sleep(SOIL_WATERING_POLL_DELAY)\nsoil_moisture = self._sensor.soil_moisture()\nwater_present = self._drain_sensor.water_present()... | <|body_start_0|>
super(_SoilWateringPollWorker, self).__init__(scheduler, record_queue, mqtt_client, soil_moisture_sensor)
self._drain_sensor = drain_sensor
self._pump_manager = pump_manager
<|end_body_0|>
<|body_start_1|>
time.sleep(SOIL_WATERING_POLL_DELAY)
soil_moisture = sel... | Polls for and records watering event data. Polls soil moisture sensor and oversees a water pump based to add water when the moisture drops too low. Records both soil moisture and watering events. | _SoilWateringPollWorker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _SoilWateringPollWorker:
"""Polls for and records watering event data. Polls soil moisture sensor and oversees a water pump based to add water when the moisture drops too low. Records both soil moisture and watering events."""
def __init__(self, scheduler, record_queue, mqtt_client, soil_moi... | stack_v2_sparse_classes_36k_train_012746 | 12,545 | permissive | [
{
"docstring": "Creates a new SoilWateringPoller object. Args: scheduler: Poll time scheduler. record_queue: Queue on which to place soil moisture records and watering event records for storage. soil_moisture_sensor: An interface for reading the soil moisture level. drain_sensor: An interface for reading the dr... | 2 | stack_v2_sparse_classes_30k_train_011440 | Implement the Python class `_SoilWateringPollWorker` described below.
Class description:
Polls for and records watering event data. Polls soil moisture sensor and oversees a water pump based to add water when the moisture drops too low. Records both soil moisture and watering events.
Method signatures and docstrings:... | Implement the Python class `_SoilWateringPollWorker` described below.
Class description:
Polls for and records watering event data. Polls soil moisture sensor and oversees a water pump based to add water when the moisture drops too low. Records both soil moisture and watering events.
Method signatures and docstrings:... | 3cfb27b3fc08692fe7d190f9c4b3cf82eb262edc | <|skeleton|>
class _SoilWateringPollWorker:
"""Polls for and records watering event data. Polls soil moisture sensor and oversees a water pump based to add water when the moisture drops too low. Records both soil moisture and watering events."""
def __init__(self, scheduler, record_queue, mqtt_client, soil_moi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _SoilWateringPollWorker:
"""Polls for and records watering event data. Polls soil moisture sensor and oversees a water pump based to add water when the moisture drops too low. Records both soil moisture and watering events."""
def __init__(self, scheduler, record_queue, mqtt_client, soil_moisture_sensor,... | the_stack_v2_python_sparse | greenpithumb/poller.py | masterhui/GreenPiThumb | train | 0 |
dcad7b62a01dbd960e6b9c3695f7816dd4e8aebe | [
"if self.request.version == 'v6':\n return QueueStatusSerializerV6\nelif self.request.version == 'v7':\n return QueueStatusSerializerV6",
"queue_statuses = Queue.objects.get_queue_status()\npage = self.paginate_queryset(queue_statuses)\nserializer = self.get_serializer(page, many=True)\nreturn self.get_pagi... | <|body_start_0|>
if self.request.version == 'v6':
return QueueStatusSerializerV6
elif self.request.version == 'v7':
return QueueStatusSerializerV6
<|end_body_0|>
<|body_start_1|>
queue_statuses = Queue.objects.get_queue_status()
page = self.paginate_queryset(queu... | This view is the endpoint for retrieving the queue status. | QueueStatusView | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueueStatusView:
"""This view is the endpoint for retrieving the queue status."""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def list(self, request):
"""Retrieves the current... | stack_v2_sparse_classes_36k_train_012747 | 2,758 | permissive | [
{
"docstring": "Returns the appropriate serializer based off the requests version of the REST API.",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Retrieves the current status of the queue and returns it in JSON form :param request: the HTTP GET... | 2 | null | Implement the Python class `QueueStatusView` described below.
Class description:
This view is the endpoint for retrieving the queue status.
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def list(self, request): ... | Implement the Python class `QueueStatusView` described below.
Class description:
This view is the endpoint for retrieving the queue status.
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API.
- def list(self, request): ... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class QueueStatusView:
"""This view is the endpoint for retrieving the queue status."""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
<|body_0|>
def list(self, request):
"""Retrieves the current... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueueStatusView:
"""This view is the endpoint for retrieving the queue status."""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API."""
if self.request.version == 'v6':
return QueueStatusSerializerV6
el... | the_stack_v2_python_sparse | scale/queue/views.py | kfconsultant/scale | train | 0 |
7366fb7bb893ff649f7d292e9a5a7b51cec0985d | [
"self.structures = proteins\nself.reference_ligand = reference_ligand\nself.ligand_radius = ligand_radius\nself.ensemble_name = ensemble_name",
"binding_sites = []\nfor i, s in enumerate(self.structures):\n s.detect_ligand_bonds()\n sbinding_site = Protein.BindingSiteFromMolecule(s, self.reference_ligand)\n... | <|body_start_0|>
self.structures = proteins
self.reference_ligand = reference_ligand
self.ligand_radius = ligand_radius
self.ensemble_name = ensemble_name
<|end_body_0|>
<|body_start_1|>
binding_sites = []
for i, s in enumerate(self.structures):
s.detect_liga... | Experimental class. Please do not use. Given a list of protein structures for the same target, will output an estimate of the quality of structures and ligands within the ensemble. | EnsembleQC | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnsembleQC:
"""Experimental class. Please do not use. Given a list of protein structures for the same target, will output an estimate of the quality of structures and ligands within the ensemble."""
def __init__(self, proteins, reference_ligand, ligand_radius=6.0, ensemble_name=None):
... | stack_v2_sparse_classes_36k_train_012748 | 22,715 | permissive | [
{
"docstring": ":param proteins: list of ccdc.protein.Protein objects :param reference_ligand: ccdc.molecule.Molecule: a bound ligand (with appropriate 3D coordinates) to be used to define the binding site of interest :param ligand_radius: the radius around the bound ligand used to define binding site residues.... | 5 | stack_v2_sparse_classes_30k_train_011222 | Implement the Python class `EnsembleQC` described below.
Class description:
Experimental class. Please do not use. Given a list of protein structures for the same target, will output an estimate of the quality of structures and ligands within the ensemble.
Method signatures and docstrings:
- def __init__(self, protei... | Implement the Python class `EnsembleQC` described below.
Class description:
Experimental class. Please do not use. Given a list of protein structures for the same target, will output an estimate of the quality of structures and ligands within the ensemble.
Method signatures and docstrings:
- def __init__(self, protei... | a6dbd7f650d28a867594ca48597f7e1b3a131168 | <|skeleton|>
class EnsembleQC:
"""Experimental class. Please do not use. Given a list of protein structures for the same target, will output an estimate of the quality of structures and ligands within the ensemble."""
def __init__(self, proteins, reference_ligand, ligand_radius=6.0, ensemble_name=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnsembleQC:
"""Experimental class. Please do not use. Given a list of protein structures for the same target, will output an estimate of the quality of structures and ligands within the ensemble."""
def __init__(self, proteins, reference_ligand, ligand_radius=6.0, ensemble_name=None):
""":param p... | the_stack_v2_python_sparse | hotspots/hs_ensembles.py | shiyx409/hotspots | train | 0 |
b92683a12163d0187bfaff6a88eadd8b02cecf3a | [
"if fs is None:\n self.ObjectType = 0\n self.Element = 0\n self.OffsetToValue = vtOffset\nelse:\n self.PopulateFromFileStream(fs, vtOffset)\nerrorMessage = 'Reserved2 not fully supported'\nif STRICT is True:\n raise Exception(errorMessage)",
"if fs is None:\n raise Exception('Invalid File stream... | <|body_start_0|>
if fs is None:
self.ObjectType = 0
self.Element = 0
self.OffsetToValue = vtOffset
else:
self.PopulateFromFileStream(fs, vtOffset)
errorMessage = 'Reserved2 not fully supported'
if STRICT is True:
raise Exception... | Class for managing Reserved2 structures. For testing non-firmware, legacy policies Implementation can do basic parsing of rules but not values For test purposes only | Reserved2 | [
"BSD-2-Clause-Patent"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reserved2:
"""Class for managing Reserved2 structures. For testing non-firmware, legacy policies Implementation can do basic parsing of rules but not values For test purposes only"""
def __init__(self, fs: BinaryIO=None, vtOffset: int=0):
"""Initializes the Reserved2 structure. Args:... | stack_v2_sparse_classes_36k_train_012749 | 33,094 | permissive | [
{
"docstring": "Initializes the Reserved2 structure. Args: fs (:obj:`BinaryIO`, optional): initialize with a filestream vtOffset (:obj:`int`, optional): used if populating from a filestream",
"name": "__init__",
"signature": "def __init__(self, fs: BinaryIO=None, vtOffset: int=0)"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_train_010337 | Implement the Python class `Reserved2` described below.
Class description:
Class for managing Reserved2 structures. For testing non-firmware, legacy policies Implementation can do basic parsing of rules but not values For test purposes only
Method signatures and docstrings:
- def __init__(self, fs: BinaryIO=None, vtO... | Implement the Python class `Reserved2` described below.
Class description:
Class for managing Reserved2 structures. For testing non-firmware, legacy policies Implementation can do basic parsing of rules but not values For test purposes only
Method signatures and docstrings:
- def __init__(self, fs: BinaryIO=None, vtO... | 78295929b37af62a8cfc4c28eab72ed0c468f350 | <|skeleton|>
class Reserved2:
"""Class for managing Reserved2 structures. For testing non-firmware, legacy policies Implementation can do basic parsing of rules but not values For test purposes only"""
def __init__(self, fs: BinaryIO=None, vtOffset: int=0):
"""Initializes the Reserved2 structure. Args:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Reserved2:
"""Class for managing Reserved2 structures. For testing non-firmware, legacy policies Implementation can do basic parsing of rules but not values For test purposes only"""
def __init__(self, fs: BinaryIO=None, vtOffset: int=0):
"""Initializes the Reserved2 structure. Args: fs (:obj:`Bi... | the_stack_v2_python_sparse | edk2toollib/windows/policy/firmware_policy.py | tianocore/edk2-pytool-library | train | 47 |
00aebdf3dfd86c7ea7580ca6118a1db55fb135ab | [
"self.A, self.w, self.p, self.c = 4 * [-1.0]\nself._func = lambda t, A, w, p, c: A * np.sin(w * t + p) + c\nself._fit_func = lambda t: self.A * np.sin(self.w * t + self.p) + self.c\nself.random_state = random_state\nself.opt_initial_guess = opt_initial_guess\nself._fitted = False",
"if self.opt_initial_guess:\n ... | <|body_start_0|>
self.A, self.w, self.p, self.c = 4 * [-1.0]
self._func = lambda t, A, w, p, c: A * np.sin(w * t + p) + c
self._fit_func = lambda t: self.A * np.sin(self.w * t + self.p) + self.c
self.random_state = random_state
self.opt_initial_guess = opt_initial_guess
s... | Sine forecasting model. The sine model is in the form by y(t) = A * sin(w * t + p) + c, where `A`, `w`, `p` and `c` are parameters to be optimized from the fitted data. | TSSine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TSSine:
"""Sine forecasting model. The sine model is in the form by y(t) = A * sin(w * t + p) + c, where `A`, `w`, `p` and `c` are parameters to be optimized from the fitted data."""
def __init__(self, random_state: t.Optional[int]=None, opt_initial_guess: bool=True):
"""Init the sin... | stack_v2_sparse_classes_36k_train_012750 | 12,299 | permissive | [
{
"docstring": "Init the sine forecasting model. Parameters ---------- random_state : int, optional Random seed, to keep the optimization process deterministic. opt_initial_guess : bool, optional (default=True) If True, make an informed choice of the initial parameters before the optimization process.",
"na... | 4 | stack_v2_sparse_classes_30k_train_003407 | Implement the Python class `TSSine` described below.
Class description:
Sine forecasting model. The sine model is in the form by y(t) = A * sin(w * t + p) + c, where `A`, `w`, `p` and `c` are parameters to be optimized from the fitted data.
Method signatures and docstrings:
- def __init__(self, random_state: t.Option... | Implement the Python class `TSSine` described below.
Class description:
Sine forecasting model. The sine model is in the form by y(t) = A * sin(w * t + p) + c, where `A`, `w`, `p` and `c` are parameters to be optimized from the fitted data.
Method signatures and docstrings:
- def __init__(self, random_state: t.Option... | 61cc1f63fa055c7466151cfefa7baff8df1702b7 | <|skeleton|>
class TSSine:
"""Sine forecasting model. The sine model is in the form by y(t) = A * sin(w * t + p) + c, where `A`, `w`, `p` and `c` are parameters to be optimized from the fitted data."""
def __init__(self, random_state: t.Optional[int]=None, opt_initial_guess: bool=True):
"""Init the sin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TSSine:
"""Sine forecasting model. The sine model is in the form by y(t) = A * sin(w * t + p) + c, where `A`, `w`, `p` and `c` are parameters to be optimized from the fitted data."""
def __init__(self, random_state: t.Optional[int]=None, opt_initial_guess: bool=True):
"""Init the sine forecasting... | the_stack_v2_python_sparse | tspymfe/_models.py | FelSiq/ts-pymfe | train | 9 |
461a3e101962bf0a72ae45eb440c488237e1b07e | [
"if not matrix:\n self.matrix = []\n return\nn = len(matrix)\nm = len(matrix[0])\nfor i in range(n):\n for j in range(m):\n if i == 0 and j == 0:\n continue\n elif i == 0:\n matrix[i][j] += matrix[i][j - 1]\n elif j == 0:\n matrix[i][j] += matrix[i - 1]... | <|body_start_0|>
if not matrix:
self.matrix = []
return
n = len(matrix)
m = len(matrix[0])
for i in range(n):
for j in range(m):
if i == 0 and j == 0:
continue
elif i == 0:
matrix[... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_36k_train_012751 | 1,688 | no_license | [
{
"docstring": "initialize your data structure here. :type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": "sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :type row2: int :type col2: int :rtyp... | 2 | stack_v2_sparse_classes_30k_train_016349 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | b6328e726c8d986d6b85e2d41c7e678e29dc1153 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
if not matrix:
self.matrix = []
return
n = len(matrix)
m = len(matrix[0])
for i in range(n):
for j in range(m):
... | the_stack_v2_python_sparse | Range Sum Query 2D - Immutable.py | dragonlee8/leetcode | train | 0 | |
79855f7a675baf76e5c312e40149a428df882736 | [
"self.multi_stage_restore_options = multi_stage_restore_options\nself.sync_size_bytes = sync_size_bytes\nself.sync_time_usecs = sync_time_usecs",
"if dictionary is None:\n return None\nmulti_stage_restore_options = cohesity_management_sdk.models.update_restore_task_options.UpdateRestoreTaskOptions.from_diction... | <|body_start_0|>
self.multi_stage_restore_options = multi_stage_restore_options
self.sync_size_bytes = sync_size_bytes
self.sync_time_usecs = sync_time_usecs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
multi_stage_restore_options = cohesity_man... | Implementation of the 'MultiStageRestoreTaskStateProto' model. TODO: type description here. Attributes: multi_stage_restore_options (UpdateRestoreTaskOptions): Captures the options(parameters) corresponding to the multi-stage restore task. sync_size_bytes (long|int): Captures the size of the data being synced to the ta... | MultiStageRestoreTaskStateProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiStageRestoreTaskStateProto:
"""Implementation of the 'MultiStageRestoreTaskStateProto' model. TODO: type description here. Attributes: multi_stage_restore_options (UpdateRestoreTaskOptions): Captures the options(parameters) corresponding to the multi-stage restore task. sync_size_bytes (long... | stack_v2_sparse_classes_36k_train_012752 | 2,858 | permissive | [
{
"docstring": "Constructor for the MultiStageRestoreTaskStateProto class",
"name": "__init__",
"signature": "def __init__(self, multi_stage_restore_options=None, sync_size_bytes=None, sync_time_usecs=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary ... | 2 | null | Implement the Python class `MultiStageRestoreTaskStateProto` described below.
Class description:
Implementation of the 'MultiStageRestoreTaskStateProto' model. TODO: type description here. Attributes: multi_stage_restore_options (UpdateRestoreTaskOptions): Captures the options(parameters) corresponding to the multi-st... | Implement the Python class `MultiStageRestoreTaskStateProto` described below.
Class description:
Implementation of the 'MultiStageRestoreTaskStateProto' model. TODO: type description here. Attributes: multi_stage_restore_options (UpdateRestoreTaskOptions): Captures the options(parameters) corresponding to the multi-st... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class MultiStageRestoreTaskStateProto:
"""Implementation of the 'MultiStageRestoreTaskStateProto' model. TODO: type description here. Attributes: multi_stage_restore_options (UpdateRestoreTaskOptions): Captures the options(parameters) corresponding to the multi-stage restore task. sync_size_bytes (long... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiStageRestoreTaskStateProto:
"""Implementation of the 'MultiStageRestoreTaskStateProto' model. TODO: type description here. Attributes: multi_stage_restore_options (UpdateRestoreTaskOptions): Captures the options(parameters) corresponding to the multi-stage restore task. sync_size_bytes (long|int): Captur... | the_stack_v2_python_sparse | cohesity_management_sdk/models/multi_stage_restore_task_state_proto.py | cohesity/management-sdk-python | train | 24 |
aac6252addba670c62f15a789416785e19be7ce9 | [
"super(MeshUnpooling, self).__init__()\nself.cached = cached\nself.matrix = matrix\nself.face = face",
"if self.matrix is None or not self.cached:\n self.face, self.matrix = subdivide(x.pos, x.face)[1:]\n self.matrix.requires_grad = False\nx.pos = torch.matmul(self.matrix, x.pos)\nx.norm = torch.matmul(self... | <|body_start_0|>
super(MeshUnpooling, self).__init__()
self.cached = cached
self.matrix = matrix
self.face = face
<|end_body_0|>
<|body_start_1|>
if self.matrix is None or not self.cached:
self.face, self.matrix = subdivide(x.pos, x.face)[1:]
self.matrix.... | A class representing a mesh unpooling layer. Attributes ---------- cached : bool if True caches the pooling data, otherwise computes it at every input matrix : Tensor the pooling matrix face : LongTensor the topology tensor Methods ------- forward(x, *args) unpools the input data | MeshUnpooling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MeshUnpooling:
"""A class representing a mesh unpooling layer. Attributes ---------- cached : bool if True caches the pooling data, otherwise computes it at every input matrix : Tensor the pooling matrix face : LongTensor the topology tensor Methods ------- forward(x, *args) unpools the input dat... | stack_v2_sparse_classes_36k_train_012753 | 1,789 | permissive | [
{
"docstring": "Parameters ---------- matrix : Tensor (optional) the unpool matrix (default is None) face : LongTensor (optional) the topology tensor (default is None) cached : bool (optional) if True caches the unpooling data, otherwise computes it at every input (default is True)",
"name": "__init__",
... | 2 | null | Implement the Python class `MeshUnpooling` described below.
Class description:
A class representing a mesh unpooling layer. Attributes ---------- cached : bool if True caches the pooling data, otherwise computes it at every input matrix : Tensor the pooling matrix face : LongTensor the topology tensor Methods ------- ... | Implement the Python class `MeshUnpooling` described below.
Class description:
A class representing a mesh unpooling layer. Attributes ---------- cached : bool if True caches the pooling data, otherwise computes it at every input matrix : Tensor the pooling matrix face : LongTensor the topology tensor Methods ------- ... | 2615b66dd4addfd5c03d9d91a24c7da414294308 | <|skeleton|>
class MeshUnpooling:
"""A class representing a mesh unpooling layer. Attributes ---------- cached : bool if True caches the pooling data, otherwise computes it at every input matrix : Tensor the pooling matrix face : LongTensor the topology tensor Methods ------- forward(x, *args) unpools the input dat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MeshUnpooling:
"""A class representing a mesh unpooling layer. Attributes ---------- cached : bool if True caches the pooling data, otherwise computes it at every input matrix : Tensor the pooling matrix face : LongTensor the topology tensor Methods ------- forward(x, *args) unpools the input data"""
def... | the_stack_v2_python_sparse | ACME/layer/MeshUnpooling.py | mauriziokovacic/ACME | train | 3 |
f8ae240497f8b672335581c378632cd63f513426 | [
"allnode = []\nself.findAllNode(root, allnode)\nerror1 = allnode[0]\nfor i in range(len(allnode) - 1):\n if allnode[i].val > allnode[i + 1].val:\n error1 = allnode[i]\n break\nerror2 = allnode[len(allnode) - 1]\nfor i in range(len(allnode) - 1, 0, -1):\n if allnode[i].val < allnode[i - 1].val:\n... | <|body_start_0|>
allnode = []
self.findAllNode(root, allnode)
error1 = allnode[0]
for i in range(len(allnode) - 1):
if allnode[i].val > allnode[i + 1].val:
error1 = allnode[i]
break
error2 = allnode[len(allnode) - 1]
for i in ra... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def recoverTree(self, root):
""":type root: TreeNode :rtype: void Do not return anything, modify root in-place instead."""
<|body_0|>
def findAllNode(self, root, res):
"""找错误点 :param root: :param res: :return:"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_012754 | 1,513 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: void Do not return anything, modify root in-place instead.",
"name": "recoverTree",
"signature": "def recoverTree(self, root)"
},
{
"docstring": "找错误点 :param root: :param res: :return:",
"name": "findAllNode",
"signature": "def findAllNode(sel... | 2 | stack_v2_sparse_classes_30k_train_016645 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def recoverTree(self, root): :type root: TreeNode :rtype: void Do not return anything, modify root in-place instead.
- def findAllNode(self, root, res): 找错误点 :param root: :param ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def recoverTree(self, root): :type root: TreeNode :rtype: void Do not return anything, modify root in-place instead.
- def findAllNode(self, root, res): 找错误点 :param root: :param ... | beabfd31379f44ffd767fc676912db5022495b53 | <|skeleton|>
class Solution:
def recoverTree(self, root):
""":type root: TreeNode :rtype: void Do not return anything, modify root in-place instead."""
<|body_0|>
def findAllNode(self, root, res):
"""找错误点 :param root: :param res: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def recoverTree(self, root):
""":type root: TreeNode :rtype: void Do not return anything, modify root in-place instead."""
allnode = []
self.findAllNode(root, allnode)
error1 = allnode[0]
for i in range(len(allnode) - 1):
if allnode[i].val > allnod... | the_stack_v2_python_sparse | leetCode/tree/099recoverTree.py | fatezy/Algorithm | train | 1 | |
236a368e7134bd6b4bbe643076ef60f205b6ac36 | [
"self.instance = instance\nsuper(AbstractModelInstanceUpdateForm, self).__init__(*args, instance=instance, **kwargs)\nself._set_save_fields(*args)\nsave_fields_dict = dict(zip(self.save_fields, [True] * len(self.save_fields)))\nif args or kwargs:\n for name, field in self.fields.items():\n if name not in ... | <|body_start_0|>
self.instance = instance
super(AbstractModelInstanceUpdateForm, self).__init__(*args, instance=instance, **kwargs)
self._set_save_fields(*args)
save_fields_dict = dict(zip(self.save_fields, [True] * len(self.save_fields)))
if args or kwargs:
for name,... | An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-update mechanism is useful for API endpoints that only updat... | AbstractModelInstanceUpdateForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractModelInstanceUpdateForm:
"""An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-u... | stack_v2_sparse_classes_36k_train_012755 | 3,013 | permissive | [
{
"docstring": "Overrides forms.ModelForm.__init__() Unlike forms.ModelForm, instance is required",
"name": "__init__",
"signature": "def __init__(self, instance, *args, **kwargs)"
},
{
"docstring": "Determine the subset of fields that we want to save Called by self.__init__()",
"name": "_se... | 3 | stack_v2_sparse_classes_30k_train_008924 | Implement the Python class `AbstractModelInstanceUpdateForm` described below.
Class description:
An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only lim... | Implement the Python class `AbstractModelInstanceUpdateForm` described below.
Class description:
An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only lim... | fcb39285be552629a09aa3bee03d08da4016809b | <|skeleton|>
class AbstractModelInstanceUpdateForm:
"""An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbstractModelInstanceUpdateForm:
"""An abstract class for manipulating Model instances Since this is an abstract class, it is meant to be extended Features: All fields that aren't passed in request.POST or request.FILES are optional (required=False) Only limited fields are saved This is limited-update mechani... | the_stack_v2_python_sparse | forms/classes.py | davidvtran/django-htk | train | 0 |
512f7c1dc3816cce5fab4b977b2ca1a6cefde202 | [
"_ = language\nlanguage = 'th'\ntry:\n from thai_segmenter import tokenize as thai_tokenize\n self._thai_tokenize = thai_tokenize\nexcept ImportError:\n raise ImportError('Please install Thai tokenizer with: pip install thai-segmenter')\nself._thai_tokenize('')\nsuper(ThaiTokenizer, self).__init__(language... | <|body_start_0|>
_ = language
language = 'th'
try:
from thai_segmenter import tokenize as thai_tokenize
self._thai_tokenize = thai_tokenize
except ImportError:
raise ImportError('Please install Thai tokenizer with: pip install thai-segmenter')
... | ThaiTokenizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThaiTokenizer:
def __init__(self, language='th', glossaries=None):
"""Initializes."""
<|body_0|>
def tokenize(self, text, return_str=False):
"""Tokenize a text."""
<|body_1|>
def detokenize(self, words, return_str=True):
"""Recovers the result of... | stack_v2_sparse_classes_36k_train_012756 | 1,913 | permissive | [
{
"docstring": "Initializes.",
"name": "__init__",
"signature": "def __init__(self, language='th', glossaries=None)"
},
{
"docstring": "Tokenize a text.",
"name": "tokenize",
"signature": "def tokenize(self, text, return_str=False)"
},
{
"docstring": "Recovers the result of `toke... | 3 | null | Implement the Python class `ThaiTokenizer` described below.
Class description:
Implement the ThaiTokenizer class.
Method signatures and docstrings:
- def __init__(self, language='th', glossaries=None): Initializes.
- def tokenize(self, text, return_str=False): Tokenize a text.
- def detokenize(self, words, return_str... | Implement the Python class `ThaiTokenizer` described below.
Class description:
Implement the ThaiTokenizer class.
Method signatures and docstrings:
- def __init__(self, language='th', glossaries=None): Initializes.
- def tokenize(self, text, return_str=False): Tokenize a text.
- def detokenize(self, words, return_str... | 06613a99305f02312a0e64ee3c3c50e7b00dcf0e | <|skeleton|>
class ThaiTokenizer:
def __init__(self, language='th', glossaries=None):
"""Initializes."""
<|body_0|>
def tokenize(self, text, return_str=False):
"""Tokenize a text."""
<|body_1|>
def detokenize(self, words, return_str=True):
"""Recovers the result of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThaiTokenizer:
def __init__(self, language='th', glossaries=None):
"""Initializes."""
_ = language
language = 'th'
try:
from thai_segmenter import tokenize as thai_tokenize
self._thai_tokenize = thai_tokenize
except ImportError:
raise... | the_stack_v2_python_sparse | neurst/neurst/data/text/thai_tokenizer.py | ohlionel/Prune-Tune | train | 12 | |
7e603bc83e2f4a647876b23b6d570edec12ec6f4 | [
"self.model = model\nself.file_manager = file_manager\nself.signatures = signatures\nself.options = options",
"export_dir = self.file_manager.next_name()\ntf.saved_model.save(self.model, export_dir, self.signatures, self.options)\nself.file_manager.clean_up()"
] | <|body_start_0|>
self.model = model
self.file_manager = file_manager
self.signatures = signatures
self.options = options
<|end_body_0|>
<|body_start_1|>
export_dir = self.file_manager.next_name()
tf.saved_model.save(self.model, export_dir, self.signatures, self.options)
... | Action that exports the given model as a SavedModel. | ExportSavedModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExportSavedModel:
"""Action that exports the given model as a SavedModel."""
def __init__(self, model: tf.Module, file_manager: ExportFileManager, signatures, options: Optional[tf.saved_model.SaveOptions]=None):
"""Initializes the instance. Args: model: The model to export. file_mana... | stack_v2_sparse_classes_36k_train_012757 | 5,540 | permissive | [
{
"docstring": "Initializes the instance. Args: model: The model to export. file_manager: An instance of `ExportFileManager` (or a subclass), that provides file naming and cleanup functionality. signatures: The signatures to forward to `tf.saved_model.save()`. options: Optional options to forward to `tf.saved_m... | 2 | stack_v2_sparse_classes_30k_train_014786 | Implement the Python class `ExportSavedModel` described below.
Class description:
Action that exports the given model as a SavedModel.
Method signatures and docstrings:
- def __init__(self, model: tf.Module, file_manager: ExportFileManager, signatures, options: Optional[tf.saved_model.SaveOptions]=None): Initializes ... | Implement the Python class `ExportSavedModel` described below.
Class description:
Action that exports the given model as a SavedModel.
Method signatures and docstrings:
- def __init__(self, model: tf.Module, file_manager: ExportFileManager, signatures, options: Optional[tf.saved_model.SaveOptions]=None): Initializes ... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class ExportSavedModel:
"""Action that exports the given model as a SavedModel."""
def __init__(self, model: tf.Module, file_manager: ExportFileManager, signatures, options: Optional[tf.saved_model.SaveOptions]=None):
"""Initializes the instance. Args: model: The model to export. file_mana... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExportSavedModel:
"""Action that exports the given model as a SavedModel."""
def __init__(self, model: tf.Module, file_manager: ExportFileManager, signatures, options: Optional[tf.saved_model.SaveOptions]=None):
"""Initializes the instance. Args: model: The model to export. file_manager: An insta... | the_stack_v2_python_sparse | orbit/actions/export_saved_model.py | jianzhnie/models | train | 2 |
2e18b9c369764b6268f7adadde215a45fcc4ab1a | [
"close_time = deserialize_timestamp_from_date(date=csv_row['transactTime'], formatstr=timestamp_format, location='Bitmex Wallet History Import')\nrealised_pnl = AssetAmount(satoshis_to_btc(deserialize_asset_amount(csv_row['amount'])))\nfee = deserialize_fee(csv_row['fee']) if csv_row['fee'] != 'null' else Fee(ZERO)... | <|body_start_0|>
close_time = deserialize_timestamp_from_date(date=csv_row['transactTime'], formatstr=timestamp_format, location='Bitmex Wallet History Import')
realised_pnl = AssetAmount(satoshis_to_btc(deserialize_asset_amount(csv_row['amount'])))
fee = deserialize_fee(csv_row['fee']) if csv_r... | BitMEXImporter | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BitMEXImporter:
def _consume_realised_pnl(csv_row: dict[str, Any], timestamp_format: str='%m/%d/%Y, %H:%M:%S %p') -> MarginPosition:
"""Use entries resulting from Realised PnL to generate a MarginPosition object. May raise: - KeyError - DeserializationError"""
<|body_0|>
def... | stack_v2_sparse_classes_36k_train_012758 | 5,939 | permissive | [
{
"docstring": "Use entries resulting from Realised PnL to generate a MarginPosition object. May raise: - KeyError - DeserializationError",
"name": "_consume_realised_pnl",
"signature": "def _consume_realised_pnl(csv_row: dict[str, Any], timestamp_format: str='%m/%d/%Y, %H:%M:%S %p') -> MarginPosition"
... | 3 | null | Implement the Python class `BitMEXImporter` described below.
Class description:
Implement the BitMEXImporter class.
Method signatures and docstrings:
- def _consume_realised_pnl(csv_row: dict[str, Any], timestamp_format: str='%m/%d/%Y, %H:%M:%S %p') -> MarginPosition: Use entries resulting from Realised PnL to genera... | Implement the Python class `BitMEXImporter` described below.
Class description:
Implement the BitMEXImporter class.
Method signatures and docstrings:
- def _consume_realised_pnl(csv_row: dict[str, Any], timestamp_format: str='%m/%d/%Y, %H:%M:%S %p') -> MarginPosition: Use entries resulting from Realised PnL to genera... | 496948458b89afc41458f19d1cba0e971ab67c8b | <|skeleton|>
class BitMEXImporter:
def _consume_realised_pnl(csv_row: dict[str, Any], timestamp_format: str='%m/%d/%Y, %H:%M:%S %p') -> MarginPosition:
"""Use entries resulting from Realised PnL to generate a MarginPosition object. May raise: - KeyError - DeserializationError"""
<|body_0|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BitMEXImporter:
def _consume_realised_pnl(csv_row: dict[str, Any], timestamp_format: str='%m/%d/%Y, %H:%M:%S %p') -> MarginPosition:
"""Use entries resulting from Realised PnL to generate a MarginPosition object. May raise: - KeyError - DeserializationError"""
close_time = deserialize_timestam... | the_stack_v2_python_sparse | rotkehlchen/data_import/importers/bitmex.py | LefterisJP/rotkehlchen | train | 0 | |
00463ef5bf7a318bfe7bcf4ddaf69cb8dac74afb | [
"if SuperUserPermission().can():\n registry_size = get_registry_size()\n if registry_size is not None:\n return {'size_bytes': registry_size.size_bytes, 'last_ran': registry_size.completed_ms, 'queued': registry_size.queued, 'running': registry_size.running}\n else:\n return {'size_bytes': 0,... | <|body_start_0|>
if SuperUserPermission().can():
registry_size = get_registry_size()
if registry_size is not None:
return {'size_bytes': registry_size.size_bytes, 'last_ran': registry_size.completed_ms, 'queued': registry_size.queued, 'running': registry_size.running}
... | Resource for the current registry size. | SuperUserRegistrySize | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperUserRegistrySize:
"""Resource for the current registry size."""
def get(self):
"""Returns size of the registry"""
<|body_0|>
def post(self):
"""Queues registry size calculation"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if SuperUserPer... | stack_v2_sparse_classes_36k_train_012759 | 40,556 | permissive | [
{
"docstring": "Returns size of the registry",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Queues registry size calculation",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `SuperUserRegistrySize` described below.
Class description:
Resource for the current registry size.
Method signatures and docstrings:
- def get(self): Returns size of the registry
- def post(self): Queues registry size calculation | Implement the Python class `SuperUserRegistrySize` described below.
Class description:
Resource for the current registry size.
Method signatures and docstrings:
- def get(self): Returns size of the registry
- def post(self): Queues registry size calculation
<|skeleton|>
class SuperUserRegistrySize:
"""Resource f... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class SuperUserRegistrySize:
"""Resource for the current registry size."""
def get(self):
"""Returns size of the registry"""
<|body_0|>
def post(self):
"""Queues registry size calculation"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SuperUserRegistrySize:
"""Resource for the current registry size."""
def get(self):
"""Returns size of the registry"""
if SuperUserPermission().can():
registry_size = get_registry_size()
if registry_size is not None:
return {'size_bytes': registry_s... | the_stack_v2_python_sparse | endpoints/api/superuser.py | quay/quay | train | 2,363 |
91397f7ddc1e148835a57ddbc130e7cb8464f66f | [
"self.instance = instance\nself.schema = None\nif self.instance:\n self.schema = SurveySchema(self.instance.survey)",
"for name, field in self.fields.items():\n yield (field.verbose_name, getattr(self.instance, name))\nif self.schema:\n for field in self.schema:\n field_id = field.getFieldName()\n... | <|body_start_0|>
self.instance = instance
self.schema = None
if self.instance:
self.schema = SurveySchema(self.instance.survey)
<|end_body_0|>
<|body_start_1|>
for name, field in self.fields.items():
yield (field.verbose_name, getattr(self.instance, name))
... | A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model. | SurveyRecordReadOnlyTemplate | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SurveyRecordReadOnlyTemplate:
"""A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model."""
def __init__(self, instance=Non... | stack_v2_sparse_classes_36k_train_012760 | 6,916 | permissive | [
{
"docstring": "Constructor to initialize the model instance. The readonly template will be rendered for the data in this model instance.",
"name": "__init__",
"signature": "def __init__(self, instance=None)"
},
{
"docstring": "Iterator yielding groups of record instance's properties to be rende... | 3 | stack_v2_sparse_classes_30k_train_008690 | Implement the Python class `SurveyRecordReadOnlyTemplate` described below.
Class description:
A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model.
... | Implement the Python class `SurveyRecordReadOnlyTemplate` described below.
Class description:
A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model.
... | 6bbd1674c99fe285596e46e738856a82afe036af | <|skeleton|>
class SurveyRecordReadOnlyTemplate:
"""A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model."""
def __init__(self, instance=Non... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SurveyRecordReadOnlyTemplate:
"""A base class that constructs the readonly template for given survey record. This uses the same notion that is used to build the model based readonly templates but the schema read from the survey schema rather than the model."""
def __init__(self, instance=None):
"... | the_stack_v2_python_sparse | app/soc/views/readonly_template.py | adviti/melange | train | 0 |
873eda56637a7f687a7dc874145ec3d7dfe8c609 | [
"if self.asignacion_id:\n self.asignacion_id.state = 'descartado'\n self.asignacion_id.fechahora_ar = datetime.now()\nself.asignacion_id = False\nself.asignadoa_id = False\nself.asignadoi_id = False\nself.asignadoa_id = False",
"if self.asignadoa_id:\n if self.asignadoa_id.id != self.env.user.id:\n ... | <|body_start_0|>
if self.asignacion_id:
self.asignacion_id.state = 'descartado'
self.asignacion_id.fechahora_ar = datetime.now()
self.asignacion_id = False
self.asignadoa_id = False
self.asignadoi_id = False
self.asignadoa_id = False
<|end_body_0|>
<|body... | TrafitecContrarecibo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrafitecContrarecibo:
def action_asignar_quitar(self):
"""Quita la asignacion incondicionalmente."""
<|body_0|>
def action_asignar_asignar(self):
"""Asignación."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self.asignacion_id:
self.... | stack_v2_sparse_classes_36k_train_012761 | 2,037 | no_license | [
{
"docstring": "Quita la asignacion incondicionalmente.",
"name": "action_asignar_quitar",
"signature": "def action_asignar_quitar(self)"
},
{
"docstring": "Asignación.",
"name": "action_asignar_asignar",
"signature": "def action_asignar_asignar(self)"
}
] | 2 | null | Implement the Python class `TrafitecContrarecibo` described below.
Class description:
Implement the TrafitecContrarecibo class.
Method signatures and docstrings:
- def action_asignar_quitar(self): Quita la asignacion incondicionalmente.
- def action_asignar_asignar(self): Asignación. | Implement the Python class `TrafitecContrarecibo` described below.
Class description:
Implement the TrafitecContrarecibo class.
Method signatures and docstrings:
- def action_asignar_quitar(self): Quita la asignacion incondicionalmente.
- def action_asignar_asignar(self): Asignación.
<|skeleton|>
class TrafitecContr... | cd226c4519157ffeab2f85a3a9ccff5e1d8143b0 | <|skeleton|>
class TrafitecContrarecibo:
def action_asignar_quitar(self):
"""Quita la asignacion incondicionalmente."""
<|body_0|>
def action_asignar_asignar(self):
"""Asignación."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrafitecContrarecibo:
def action_asignar_quitar(self):
"""Quita la asignacion incondicionalmente."""
if self.asignacion_id:
self.asignacion_id.state = 'descartado'
self.asignacion_id.fechahora_ar = datetime.now()
self.asignacion_id = False
self.asignadoa... | the_stack_v2_python_sparse | sli_documentos/models/trafitec_contrarecibo.py | RLJO/SLI | train | 0 | |
31ba6dbd9b5fc8f2c579e3ed5b955384fefbc457 | [
"if not t:\n return [None]\nreturn [t.val] + self.preorderTraversal(t.left) + self.preorderTraversal(t.right)",
"list_s, list_t = (self.preorderTraversal(s), self.preorderTraversal(t))\nlen_s, len_t = (len(list_s), len(list_t))\nfor i in range(0, len_s - len_t + 1):\n if list_s[i:i + len_t] == list_t:\n ... | <|body_start_0|>
if not t:
return [None]
return [t.val] + self.preorderTraversal(t.left) + self.preorderTraversal(t.right)
<|end_body_0|>
<|body_start_1|>
list_s, list_t = (self.preorderTraversal(s), self.preorderTraversal(t))
len_s, len_t = (len(list_s), len(list_t))
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, t):
"""return a flat list of the binary tree including None"""
<|body_0|>
def isSubtree(self, s: TreeNode, t: TreeNode) -> bool:
"""check if preorderTraversal(t) is a sublist of preorderTraversal(s)"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_012762 | 2,483 | permissive | [
{
"docstring": "return a flat list of the binary tree including None",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, t)"
},
{
"docstring": "check if preorderTraversal(t) is a sublist of preorderTraversal(s)",
"name": "isSubtree",
"signature": "def isSubtree(self,... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, t): return a flat list of the binary tree including None
- def isSubtree(self, s: TreeNode, t: TreeNode) -> bool: check if preorderTraversal(t) is a s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, t): return a flat list of the binary tree including None
- def isSubtree(self, s: TreeNode, t: TreeNode) -> bool: check if preorderTraversal(t) is a s... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution:
def preorderTraversal(self, t):
"""return a flat list of the binary tree including None"""
<|body_0|>
def isSubtree(self, s: TreeNode, t: TreeNode) -> bool:
"""check if preorderTraversal(t) is a sublist of preorderTraversal(s)"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preorderTraversal(self, t):
"""return a flat list of the binary tree including None"""
if not t:
return [None]
return [t.val] + self.preorderTraversal(t.left) + self.preorderTraversal(t.right)
def isSubtree(self, s: TreeNode, t: TreeNode) -> bool:
... | the_stack_v2_python_sparse | LeetCode/LC572_subtree_of_another_tree.py | jxie0755/Learning_Python | train | 0 | |
cbfd4e0a26c7ee55e146a5ad1631b7c3a5e34d7c | [
"writer = metadata_writer.MetadataWriter(model_buffer)\nwriter.add_general_info(_MODEL_NAME, _MODEL_DESCRIPTION)\nwriter.add_regex_text_input(regex_tokenizer)\nwriter.add_classification_output(labels)\nreturn cls(writer)",
"writer = metadata_writer.MetadataWriter(model_buffer)\nwriter.add_general_info(_MODEL_NAME... | <|body_start_0|>
writer = metadata_writer.MetadataWriter(model_buffer)
writer.add_general_info(_MODEL_NAME, _MODEL_DESCRIPTION)
writer.add_regex_text_input(regex_tokenizer)
writer.add_classification_output(labels)
return cls(writer)
<|end_body_0|>
<|body_start_1|>
writer... | MetadataWriter to write the metadata into the text classifier. | MetadataWriter | [
"Apache-2.0",
"dtoa"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetadataWriter:
"""MetadataWriter to write the metadata into the text classifier."""
def create_for_regex_model(cls, model_buffer: bytearray, regex_tokenizer: metadata_writer.RegexTokenizer, labels: metadata_writer.Labels) -> 'MetadataWriter':
"""Creates MetadataWriter for TFLite mod... | stack_v2_sparse_classes_36k_train_012763 | 5,558 | permissive | [
{
"docstring": "Creates MetadataWriter for TFLite model with regex tokentizer. The parameters required in this method are mandatory when using MediaPipe Tasks. Note that only the output TFLite is used for deployment. The output JSON content is used to interpret the metadata content. Args: model_buffer: A valid ... | 2 | null | Implement the Python class `MetadataWriter` described below.
Class description:
MetadataWriter to write the metadata into the text classifier.
Method signatures and docstrings:
- def create_for_regex_model(cls, model_buffer: bytearray, regex_tokenizer: metadata_writer.RegexTokenizer, labels: metadata_writer.Labels) -... | Implement the Python class `MetadataWriter` described below.
Class description:
MetadataWriter to write the metadata into the text classifier.
Method signatures and docstrings:
- def create_for_regex_model(cls, model_buffer: bytearray, regex_tokenizer: metadata_writer.RegexTokenizer, labels: metadata_writer.Labels) -... | 007824594bf1d07c7c1467df03a43886f8a4b3ad | <|skeleton|>
class MetadataWriter:
"""MetadataWriter to write the metadata into the text classifier."""
def create_for_regex_model(cls, model_buffer: bytearray, regex_tokenizer: metadata_writer.RegexTokenizer, labels: metadata_writer.Labels) -> 'MetadataWriter':
"""Creates MetadataWriter for TFLite mod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetadataWriter:
"""MetadataWriter to write the metadata into the text classifier."""
def create_for_regex_model(cls, model_buffer: bytearray, regex_tokenizer: metadata_writer.RegexTokenizer, labels: metadata_writer.Labels) -> 'MetadataWriter':
"""Creates MetadataWriter for TFLite model with regex... | the_stack_v2_python_sparse | mediapipe/tasks/python/metadata/metadata_writers/text_classifier.py | google/mediapipe | train | 23,940 |
ad65870af378c1a9402e1bf010eb13d8abf34a44 | [
"self.kwargs = kwargs.copy()\nself.mass_bins = [[9.7, 10.1], [10.1, 10.5], [10.5, 10.9], [10.9, 11.3]]\nself.ssfr_range = [-13.0, -7.0]\nself.ssfr_nbin = 40\nself.ssfr_dist = None\nself.ssfr_bin_edges = None\nself.ssfr_bin_mid = None",
"if len(mass) != len(ssfr):\n raise ValueError\nself.ssfr_dist = []\nself.s... | <|body_start_0|>
self.kwargs = kwargs.copy()
self.mass_bins = [[9.7, 10.1], [10.1, 10.5], [10.5, 10.9], [10.9, 11.3]]
self.ssfr_range = [-13.0, -7.0]
self.ssfr_nbin = 40
self.ssfr_dist = None
self.ssfr_bin_edges = None
self.ssfr_bin_mid = None
<|end_body_0|>
<|bo... | Ssfr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ssfr:
def __init__(self, **kwargs):
"""Class object that describes the sSFR distribution of a galaxy population"""
<|body_0|>
def Calculate(self, mass, ssfr):
"""Calculate the SSFR distribution for the four hardcoded mass bins from the mass and ssfr values"""
... | stack_v2_sparse_classes_36k_train_012764 | 15,116 | no_license | [
{
"docstring": "Class object that describes the sSFR distribution of a galaxy population",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Calculate the SSFR distribution for the four hardcoded mass bins from the mass and ssfr values",
"name": "Calculate",
... | 2 | null | Implement the Python class `Ssfr` described below.
Class description:
Implement the Ssfr class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Class object that describes the sSFR distribution of a galaxy population
- def Calculate(self, mass, ssfr): Calculate the SSFR distribution for the four har... | Implement the Python class `Ssfr` described below.
Class description:
Implement the Ssfr class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Class object that describes the sSFR distribution of a galaxy population
- def Calculate(self, mass, ssfr): Calculate the SSFR distribution for the four har... | 0afc55f7c4b2e8a76ec8ee69b4d0e3f4742a3f93 | <|skeleton|>
class Ssfr:
def __init__(self, **kwargs):
"""Class object that describes the sSFR distribution of a galaxy population"""
<|body_0|>
def Calculate(self, mass, ssfr):
"""Calculate the SSFR distribution for the four hardcoded mass bins from the mass and ssfr values"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ssfr:
def __init__(self, **kwargs):
"""Class object that describes the sSFR distribution of a galaxy population"""
self.kwargs = kwargs.copy()
self.mass_bins = [[9.7, 10.1], [10.1, 10.5], [10.5, 10.9], [10.9, 11.3]]
self.ssfr_range = [-13.0, -7.0]
self.ssfr_nbin = 40
... | the_stack_v2_python_sparse | CenQue/gal_prop.py | changhoonhahn/central_quenching | train | 0 | |
176c0080fda8414ca1ca820cddbc5d7f1ed8950c | [
"super(GeonamesTestCase, self).setUp()\nself._admin = self.model('user').createUser('admin', 'password', 'admin', 'user', 'admin@example.com', admin=True)\nself._user = self.model('user').createUser('minervauser', 'password', 'minerva', 'user', 'minervauser@example.com')",
"params = {'parentType': 'user', 'parent... | <|body_start_0|>
super(GeonamesTestCase, self).setUp()
self._admin = self.model('user').createUser('admin', 'password', 'admin', 'user', 'admin@example.com', admin=True)
self._user = self.model('user').createUser('minervauser', 'password', 'minerva', 'user', 'minervauser@example.com')
<|end_body... | Tests of the minerva geonames API endpoints. | GeonamesTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeonamesTestCase:
"""Tests of the minerva geonames API endpoints."""
def setUp(self):
"""Set up the test case with a user."""
<|body_0|>
def test_geocode(self):
"""Test importing the geonames database and geocoding."""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_012765 | 4,048 | no_license | [
{
"docstring": "Set up the test case with a user.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test importing the geonames database and geocoding.",
"name": "test_geocode",
"signature": "def test_geocode(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000463 | Implement the Python class `GeonamesTestCase` described below.
Class description:
Tests of the minerva geonames API endpoints.
Method signatures and docstrings:
- def setUp(self): Set up the test case with a user.
- def test_geocode(self): Test importing the geonames database and geocoding. | Implement the Python class `GeonamesTestCase` described below.
Class description:
Tests of the minerva geonames API endpoints.
Method signatures and docstrings:
- def setUp(self): Set up the test case with a user.
- def test_geocode(self): Test importing the geonames database and geocoding.
<|skeleton|>
class Geonam... | 878d3aa26781439914871a54bbb27412a7a4719e | <|skeleton|>
class GeonamesTestCase:
"""Tests of the minerva geonames API endpoints."""
def setUp(self):
"""Set up the test case with a user."""
<|body_0|>
def test_geocode(self):
"""Test importing the geonames database and geocoding."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeonamesTestCase:
"""Tests of the minerva geonames API endpoints."""
def setUp(self):
"""Set up the test case with a user."""
super(GeonamesTestCase, self).setUp()
self._admin = self.model('user').createUser('admin', 'password', 'admin', 'user', 'admin@example.com', admin=True)
... | the_stack_v2_python_sparse | plugin_tests/geonames_test.py | justincampbell/minerva | train | 0 |
a5948168972f42dccf896a7f81528cbd5a4f3ae9 | [
"self.gov = request.args.get('gov', '')\nself.dep = request.args.get('govtype', '')\nself.relation = request.args.get('dep', '')\nself.govtype = request.args.get('deptype', 'word')\nself.deptype = request.args.get('relation', 'word')\ntry:\n self.phrases = json.loads(str(request.args['phrases']))\n self.metad... | <|body_start_0|>
self.gov = request.args.get('gov', '')
self.dep = request.args.get('govtype', '')
self.relation = request.args.get('dep', '')
self.govtype = request.args.get('deptype', 'word')
self.deptype = request.args.get('relation', 'word')
try:
self.phra... | Return adjectives, nouns, and verbs with high TF-IDF scores that tend to occur within 10 sentences of the given word. The expected url arguments are documented below. Keyword Arguments: phrases (str): govtype (str): dep (str): deptype (str): relation (str): phrases (JSON): Required. metadata (JSON): Required. searches ... | GetAssociatedWords | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetAssociatedWords:
"""Return adjectives, nouns, and verbs with high TF-IDF scores that tend to occur within 10 sentences of the given word. The expected url arguments are documented below. Keyword Arguments: phrases (str): govtype (str): dep (str): deptype (str): relation (str): phrases (JSON): ... | stack_v2_sparse_classes_36k_train_012766 | 3,365 | no_license | [
{
"docstring": "Initialize variables necessary for the GetAssociatedUsers view.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create a JSON response to the request.",
"name": "dispatch_request",
"signature": "def dispatch_request(self)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_018986 | Implement the Python class `GetAssociatedWords` described below.
Class description:
Return adjectives, nouns, and verbs with high TF-IDF scores that tend to occur within 10 sentences of the given word. The expected url arguments are documented below. Keyword Arguments: phrases (str): govtype (str): dep (str): deptype ... | Implement the Python class `GetAssociatedWords` described below.
Class description:
Return adjectives, nouns, and verbs with high TF-IDF scores that tend to occur within 10 sentences of the given word. The expected url arguments are documented below. Keyword Arguments: phrases (str): govtype (str): dep (str): deptype ... | 93b90e6a8592a26c6efa09ea5f5aa4fab044f9d7 | <|skeleton|>
class GetAssociatedWords:
"""Return adjectives, nouns, and verbs with high TF-IDF scores that tend to occur within 10 sentences of the given word. The expected url arguments are documented below. Keyword Arguments: phrases (str): govtype (str): dep (str): deptype (str): relation (str): phrases (JSON): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetAssociatedWords:
"""Return adjectives, nouns, and verbs with high TF-IDF scores that tend to occur within 10 sentences of the given word. The expected url arguments are documented below. Keyword Arguments: phrases (str): govtype (str): dep (str): deptype (str): relation (str): phrases (JSON): Required. met... | the_stack_v2_python_sparse | app/wordseer/views/getassociatedwords.py | xiaobaozi34/wordseer | train | 0 |
d7bd925d86bc94029018158283007d12061bbb81 | [
"if max_iter < 0:\n raise ValueError('Argument, max_iter must be positive')\nif min_change < 0:\n raise ValueError('Arguement: min_change must be positive')\nself._max_iter = max_iter\nself._min_change = min_change\nsuper().__init__()",
"if gradients is None:\n raise TypeError('Argument: gradients must b... | <|body_start_0|>
if max_iter < 0:
raise ValueError('Argument, max_iter must be positive')
if min_change < 0:
raise ValueError('Arguement: min_change must be positive')
self._max_iter = max_iter
self._min_change = min_change
super().__init__()
<|end_body_0|... | FrankWolfeSolver class. Inherits from the COPSolver class. FrankWolfeSolver is used to calculate the numerical solutions for the QCOP for 2 or more gradients Attributes: max_iter: max number of iterations for the algorithm min_change: minimum change stopping criterion. The algorithms stop when the difference between it... | FrankWolfeSolver | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrankWolfeSolver:
"""FrankWolfeSolver class. Inherits from the COPSolver class. FrankWolfeSolver is used to calculate the numerical solutions for the QCOP for 2 or more gradients Attributes: max_iter: max number of iterations for the algorithm min_change: minimum change stopping criterion. The al... | stack_v2_sparse_classes_36k_train_012767 | 4,848 | permissive | [
{
"docstring": "Inits FrankWolfeSolver with hyperparameters values Args: max_iter: maximum number of iterations. Must be <= 1. default value is 100. min_change: minimum change stopping criterion. Must be < 0 default value is 1e-3",
"name": "__init__",
"signature": "def __init__(self, max_iter=100, min_c... | 3 | stack_v2_sparse_classes_30k_val_000528 | Implement the Python class `FrankWolfeSolver` described below.
Class description:
FrankWolfeSolver class. Inherits from the COPSolver class. FrankWolfeSolver is used to calculate the numerical solutions for the QCOP for 2 or more gradients Attributes: max_iter: max number of iterations for the algorithm min_change: mi... | Implement the Python class `FrankWolfeSolver` described below.
Class description:
FrankWolfeSolver class. Inherits from the COPSolver class. FrankWolfeSolver is used to calculate the numerical solutions for the QCOP for 2 or more gradients Attributes: max_iter: max number of iterations for the algorithm min_change: mi... | 26d6a08c8c7e7d33ad60d7e6896b0ffeede41bc1 | <|skeleton|>
class FrankWolfeSolver:
"""FrankWolfeSolver class. Inherits from the COPSolver class. FrankWolfeSolver is used to calculate the numerical solutions for the QCOP for 2 or more gradients Attributes: max_iter: max number of iterations for the algorithm min_change: minimum change stopping criterion. The al... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FrankWolfeSolver:
"""FrankWolfeSolver class. Inherits from the COPSolver class. FrankWolfeSolver is used to calculate the numerical solutions for the QCOP for 2 or more gradients Attributes: max_iter: max number of iterations for the algorithm min_change: minimum change stopping criterion. The algorithms stop... | the_stack_v2_python_sparse | copsolver/frank_wolfe_solver.py | swisscom/ai-research-mamo-framework | train | 30 |
887cc014f6ea3f57abd3d0350894f93c11a21a13 | [
"args = self.args\nif args and (not args[0] in [\"'\", ',', ':']):\n args = ' %s' % args.strip()\nself.args = args",
"if not self.args:\n msg = 'What do you want to do?'\n self.caller.msg(msg)\nelse:\n msg = f'{self.caller.name}{self.args}'\n self.caller.location.msg_contents(text=(msg, {'type': 'p... | <|body_start_0|>
args = self.args
if args and (not args[0] in ["'", ',', ':']):
args = ' %s' % args.strip()
self.args = args
<|end_body_0|>
<|body_start_1|>
if not self.args:
msg = 'What do you want to do?'
self.caller.msg(msg)
else:
... | strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name. | CmdPose | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CmdPose:
"""strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name."""
def parse(self):
""... | stack_v2_sparse_classes_36k_train_012768 | 22,494 | permissive | [
{
"docstring": "Custom parse the cases where the emote starts with some special letter, such as 's, at which we don't want to separate the caller's name and the emote with a space.",
"name": "parse",
"signature": "def parse(self)"
},
{
"docstring": "Hook function",
"name": "func",
"signa... | 2 | stack_v2_sparse_classes_30k_train_006379 | Implement the Python class `CmdPose` described below.
Class description:
strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your na... | Implement the Python class `CmdPose` described below.
Class description:
strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your na... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class CmdPose:
"""strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name."""
def parse(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CmdPose:
"""strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name."""
def parse(self):
"""Custom parse... | the_stack_v2_python_sparse | evennia/commands/default/general.py | evennia/evennia | train | 1,781 |
a071ae6dc0156217830ddfd3789d3b86e824d90e | [
"engine = MainEngine()\nqubits = engine.allocate_qureg(3)\nH | qubits[0]\nengine.flush()\nprint(engine.backend.cheat())\nX | qubits[2]\nengine.flush()\nprint(engine.backend.cheat())\nCNOT | (qubits[0], qubits[1])\nengine.flush()\nprint(engine.backend.cheat())",
"drawer = CircuitDrawer()\nengine = MainEngine(drawe... | <|body_start_0|>
engine = MainEngine()
qubits = engine.allocate_qureg(3)
H | qubits[0]
engine.flush()
print(engine.backend.cheat())
X | qubits[2]
engine.flush()
print(engine.backend.cheat())
CNOT | (qubits[0], qubits[1])
engine.flush()
... | This class contains demonstrations of ProjectQ's debugging and diagnostic features. | DebuggingFeatures | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DebuggingFeatures:
"""This class contains demonstrations of ProjectQ's debugging and diagnostic features."""
def test_step_by_step_circuit_inspection(self):
"""This function demonstrates how to use ProjectQ to print the state vector of every step (moment) in a circuit. It also shows ... | stack_v2_sparse_classes_36k_train_012769 | 3,023 | permissive | [
{
"docstring": "This function demonstrates how to use ProjectQ to print the state vector of every step (moment) in a circuit. It also shows how to get the state vector at each step, and how to print it in ket notation.",
"name": "test_step_by_step_circuit_inspection",
"signature": "def test_step_by_step... | 3 | stack_v2_sparse_classes_30k_train_012810 | Implement the Python class `DebuggingFeatures` described below.
Class description:
This class contains demonstrations of ProjectQ's debugging and diagnostic features.
Method signatures and docstrings:
- def test_step_by_step_circuit_inspection(self): This function demonstrates how to use ProjectQ to print the state v... | Implement the Python class `DebuggingFeatures` described below.
Class description:
This class contains demonstrations of ProjectQ's debugging and diagnostic features.
Method signatures and docstrings:
- def test_step_by_step_circuit_inspection(self): This function demonstrates how to use ProjectQ to print the state v... | 941488f8f8a81a4b7d7fe28414ce14fa478a692a | <|skeleton|>
class DebuggingFeatures:
"""This class contains demonstrations of ProjectQ's debugging and diagnostic features."""
def test_step_by_step_circuit_inspection(self):
"""This function demonstrates how to use ProjectQ to print the state vector of every step (moment) in a circuit. It also shows ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DebuggingFeatures:
"""This class contains demonstrations of ProjectQ's debugging and diagnostic features."""
def test_step_by_step_circuit_inspection(self):
"""This function demonstrates how to use ProjectQ to print the state vector of every step (moment) in a circuit. It also shows how to get th... | the_stack_v2_python_sparse | ProjectQ/ProjectQDebugging/debugging_features.py | taibah/qsfe | train | 0 |
baf3d85d06ee3df698f558f1b5390abe8bedec11 | [
"super(RelaxListType, self).__init__()\nself.list_name = 'relax_list'\nself.list_desc = 'relax list container'\nself.element_name = 'relax_list_element'\nself.element_desc = 'relax container'\nself.blacklist = []",
"xml_to_object(super_node, self, file_version=file_version, blacklist=self.blacklist)\nnodes = supe... | <|body_start_0|>
super(RelaxListType, self).__init__()
self.list_name = 'relax_list'
self.list_desc = 'relax list container'
self.element_name = 'relax_list_element'
self.element_desc = 'relax container'
self.blacklist = []
<|end_body_0|>
<|body_start_1|>
xml_to_... | An empty list type container. | RelaxListType | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelaxListType:
"""An empty list type container."""
def __init__(self):
"""Initialise some class variables."""
<|body_0|>
def from_xml(self, super_node, file_version=1):
"""Recreate the data structure from the XML node. @param super_node: The XML nodes. @type supe... | stack_v2_sparse_classes_36k_train_012770 | 10,046 | no_license | [
{
"docstring": "Initialise some class variables.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Recreate the data structure from the XML node. @param super_node: The XML nodes. @type super_node: xml.dom.minicompat.Element instance @keyword file_version: The relax XML ... | 3 | stack_v2_sparse_classes_30k_train_018819 | Implement the Python class `RelaxListType` described below.
Class description:
An empty list type container.
Method signatures and docstrings:
- def __init__(self): Initialise some class variables.
- def from_xml(self, super_node, file_version=1): Recreate the data structure from the XML node. @param super_node: The ... | Implement the Python class `RelaxListType` described below.
Class description:
An empty list type container.
Method signatures and docstrings:
- def __init__(self): Initialise some class variables.
- def from_xml(self, super_node, file_version=1): Recreate the data structure from the XML node. @param super_node: The ... | c317326ddeacd1a1c608128769676899daeae531 | <|skeleton|>
class RelaxListType:
"""An empty list type container."""
def __init__(self):
"""Initialise some class variables."""
<|body_0|>
def from_xml(self, super_node, file_version=1):
"""Recreate the data structure from the XML node. @param super_node: The XML nodes. @type supe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelaxListType:
"""An empty list type container."""
def __init__(self):
"""Initialise some class variables."""
super(RelaxListType, self).__init__()
self.list_name = 'relax_list'
self.list_desc = 'relax list container'
self.element_name = 'relax_list_element'
... | the_stack_v2_python_sparse | data_store/data_classes.py | jlec/relax | train | 4 |
10f3f42991c5e58b5eea8c5cf0f3e204f6230789 | [
"list_controls = self._device.CallOutput(['amixer', '-c%d' % int(card), 'controls'])\nre_control = re.compile(self._CONTROL_RE_STR % name)\nnumid = 0\nfor ctl in list_controls.splitlines():\n m = re_control.match(ctl)\n if m:\n numid = int(m.group(1))\n break\nelse:\n logging.info(\"Unable to... | <|body_start_0|>
list_controls = self._device.CallOutput(['amixer', '-c%d' % int(card), 'controls'])
re_control = re.compile(self._CONTROL_RE_STR % name)
numid = 0
for ctl in list_controls.splitlines():
m = re_control.match(ctl)
if m:
numid = int(m... | Mixer controller for alsa. | AlsaMixerController | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlsaMixerController:
"""Mixer controller for alsa."""
def GetMixerControls(self, name, card='0'):
"""See BaseMixerController.GetMixerControls"""
<|body_0|>
def SetMixerControls(self, mixer_settings, card='0', store=True):
"""See BaseMixerController.SetMixerContro... | stack_v2_sparse_classes_36k_train_012771 | 9,957 | permissive | [
{
"docstring": "See BaseMixerController.GetMixerControls",
"name": "GetMixerControls",
"signature": "def GetMixerControls(self, name, card='0')"
},
{
"docstring": "See BaseMixerController.SetMixerControls",
"name": "SetMixerControls",
"signature": "def SetMixerControls(self, mixer_settin... | 3 | null | Implement the Python class `AlsaMixerController` described below.
Class description:
Mixer controller for alsa.
Method signatures and docstrings:
- def GetMixerControls(self, name, card='0'): See BaseMixerController.GetMixerControls
- def SetMixerControls(self, mixer_settings, card='0', store=True): See BaseMixerCont... | Implement the Python class `AlsaMixerController` described below.
Class description:
Mixer controller for alsa.
Method signatures and docstrings:
- def GetMixerControls(self, name, card='0'): See BaseMixerController.GetMixerControls
- def SetMixerControls(self, mixer_settings, card='0', store=True): See BaseMixerCont... | a1b0fccd68987d8cd9c89710adc3c04b868347ec | <|skeleton|>
class AlsaMixerController:
"""Mixer controller for alsa."""
def GetMixerControls(self, name, card='0'):
"""See BaseMixerController.GetMixerControls"""
<|body_0|>
def SetMixerControls(self, mixer_settings, card='0', store=True):
"""See BaseMixerController.SetMixerContro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlsaMixerController:
"""Mixer controller for alsa."""
def GetMixerControls(self, name, card='0'):
"""See BaseMixerController.GetMixerControls"""
list_controls = self._device.CallOutput(['amixer', '-c%d' % int(card), 'controls'])
re_control = re.compile(self._CONTROL_RE_STR % name)... | the_stack_v2_python_sparse | py/device/audio/alsa.py | bridder/factory | train | 0 |
46a57b7429bfa95fed9b004173c0cc7b34df941c | [
"n = len(searchString)\nmin_window_size = sys.maxsize\nmin_window = ''\nfor left in range(0, n):\n for right in range(left, n):\n window_snippet = searchString[left:right + 1]\n window_contains_all = self.contains_all(window_snippet, t)\n if window_contains_all and len(window_snippet) < min_... | <|body_start_0|>
n = len(searchString)
min_window_size = sys.maxsize
min_window = ''
for left in range(0, n):
for right in range(left, n):
window_snippet = searchString[left:right + 1]
window_contains_all = self.contains_all(window_snippet, t)
... | BruteForceSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BruteForceSolution:
def minWindow(self, searchString, t):
"""Interface ---- :type searchString: str :type t: str :rtype: str Approach ---- 1. Plant the left pointer and scan the window 2. Find all substrings that contain all of the target 3. Take the smallest Complexity ---- M = target s... | stack_v2_sparse_classes_36k_train_012772 | 6,464 | no_license | [
{
"docstring": "Interface ---- :type searchString: str :type t: str :rtype: str Approach ---- 1. Plant the left pointer and scan the window 2. Find all substrings that contain all of the target 3. Take the smallest Complexity ---- M = target string N = length of query string Time : O(N^2) Space : O(1)",
"na... | 2 | stack_v2_sparse_classes_30k_train_015982 | Implement the Python class `BruteForceSolution` described below.
Class description:
Implement the BruteForceSolution class.
Method signatures and docstrings:
- def minWindow(self, searchString, t): Interface ---- :type searchString: str :type t: str :rtype: str Approach ---- 1. Plant the left pointer and scan the win... | Implement the Python class `BruteForceSolution` described below.
Class description:
Implement the BruteForceSolution class.
Method signatures and docstrings:
- def minWindow(self, searchString, t): Interface ---- :type searchString: str :type t: str :rtype: str Approach ---- 1. Plant the left pointer and scan the win... | c0d49423885832b616ae3c7cd58e8f24c17cfd4d | <|skeleton|>
class BruteForceSolution:
def minWindow(self, searchString, t):
"""Interface ---- :type searchString: str :type t: str :rtype: str Approach ---- 1. Plant the left pointer and scan the window 2. Find all substrings that contain all of the target 3. Take the smallest Complexity ---- M = target s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BruteForceSolution:
def minWindow(self, searchString, t):
"""Interface ---- :type searchString: str :type t: str :rtype: str Approach ---- 1. Plant the left pointer and scan the window 2. Find all substrings that contain all of the target 3. Take the smallest Complexity ---- M = target string N = leng... | the_stack_v2_python_sparse | Hashtables/minimumWindowSubstring.py | miaviles/Data-Structures-Algorithms-Python | train | 0 | |
069f365118e68e3ed1d3fadc30529f41e5028933 | [
"\"\"\"\n review a short tutorial video: \n heap and priority queue https://www.youtube.com/watch?v=hj9lOSJCy-U\n this problem can be solved by priority queue\n since priority queues normal are implemented by heap tree.\n the insertion and removal of heap tree is O(logn)\n ... | <|body_start_0|>
"""
review a short tutorial video:
heap and priority queue https://www.youtube.com/watch?v=hj9lOSJCy-U
this problem can be solved by priority queue
since priority queues normal are implemented by heap tree.
the ins... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeKLists_heap_priority_queue(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_0|>
def mergeKLists(self, lists):
"""divide and conquer method the time complexity is O(nklogk), space complexity is O(1) k*n + k/2*2n + k/4*4n + ...... | stack_v2_sparse_classes_36k_train_012773 | 3,053 | no_license | [
{
"docstring": ":type lists: List[ListNode] :rtype: ListNode",
"name": "mergeKLists_heap_priority_queue",
"signature": "def mergeKLists_heap_priority_queue(self, lists)"
},
{
"docstring": "divide and conquer method the time complexity is O(nklogk), space complexity is O(1) k*n + k/2*2n + k/4*4n ... | 3 | stack_v2_sparse_classes_30k_test_000819 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKLists_heap_priority_queue(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def mergeKLists(self, lists): divide and conquer method the time complexity is O(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKLists_heap_priority_queue(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def mergeKLists(self, lists): divide and conquer method the time complexity is O(... | 5532195d25a32474aeb13b5564f26a8d2b0759db | <|skeleton|>
class Solution:
def mergeKLists_heap_priority_queue(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_0|>
def mergeKLists(self, lists):
"""divide and conquer method the time complexity is O(nklogk), space complexity is O(1) k*n + k/2*2n + k/4*4n + ...... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeKLists_heap_priority_queue(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
"""
review a short tutorial video:
heap and priority queue https://www.youtube.com/watch?v=hj9lOSJCy-U
this problem can be solved by p... | the_stack_v2_python_sparse | leetcode/23_merge_k_sorted_lists/solution.py | stenliao/coding_practice | train | 0 | |
6083020295890c697cfa3823c5109d759eb49eb4 | [
"if type(data) is not np.ndarray:\n raise TypeError('data must be a 2D numpy.ndarray')\nif len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nn = data.shape[1]\nif n < 2:\n raise ValueError('data must contain multiple data points')\nself.mean = data.mean(axis=1, keepdims=True)\nsel... | <|body_start_0|>
if type(data) is not np.ndarray:
raise TypeError('data must be a 2D numpy.ndarray')
if len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
n = data.shape[1]
if n < 2:
raise ValueError('data must contain multiple da... | MultiNormal Class | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""MultiNormal Class"""
def __init__(self, data):
"""Multinormal Class"""
<|body_0|>
def pdf(self, x):
"""Multinormal Class"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if type(data) is not np.ndarray:
raise TypeError... | stack_v2_sparse_classes_36k_train_012774 | 1,330 | no_license | [
{
"docstring": "Multinormal Class",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Multinormal Class",
"name": "pdf",
"signature": "def pdf(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015401 | Implement the Python class `MultiNormal` described below.
Class description:
MultiNormal Class
Method signatures and docstrings:
- def __init__(self, data): Multinormal Class
- def pdf(self, x): Multinormal Class | Implement the Python class `MultiNormal` described below.
Class description:
MultiNormal Class
Method signatures and docstrings:
- def __init__(self, data): Multinormal Class
- def pdf(self, x): Multinormal Class
<|skeleton|>
class MultiNormal:
"""MultiNormal Class"""
def __init__(self, data):
"""Mu... | 8761eb876046ad3c0c3f85d98dbdca4007d93cd1 | <|skeleton|>
class MultiNormal:
"""MultiNormal Class"""
def __init__(self, data):
"""Multinormal Class"""
<|body_0|>
def pdf(self, x):
"""Multinormal Class"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""MultiNormal Class"""
def __init__(self, data):
"""Multinormal Class"""
if type(data) is not np.ndarray:
raise TypeError('data must be a 2D numpy.ndarray')
if len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
n ... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | oran2527/holbertonschool-machine_learning | train | 0 |
bfddf40cb678c98d2b73767b34afb4259402e163 | [
"user = request.user\nnotifications = Notification.objects.all()\ndata = {}\nfor notification in notifications:\n if user in notification.notified.all():\n serializer = self.serializer_class(notification, context={'request': request})\n data[notification.id] = serializer.data\nreturn Response(data,... | <|body_start_0|>
user = request.user
notifications = Notification.objects.all()
data = {}
for notification in notifications:
if user in notification.notified.all():
serializer = self.serializer_class(notification, context={'request': request})
... | get: | NotificationAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationAPIView:
"""get:"""
def get(self, request):
"""Retrieve all notifications from the database for a specific user. :returns notifications: a json data for the notifications"""
<|body_0|>
def put(self, request):
"""Mark all notifications as read."""
... | stack_v2_sparse_classes_36k_train_012775 | 7,717 | permissive | [
{
"docstring": "Retrieve all notifications from the database for a specific user. :returns notifications: a json data for the notifications",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Mark all notifications as read.",
"name": "put",
"signature": "def put(sel... | 2 | stack_v2_sparse_classes_30k_train_018792 | Implement the Python class `NotificationAPIView` described below.
Class description:
get:
Method signatures and docstrings:
- def get(self, request): Retrieve all notifications from the database for a specific user. :returns notifications: a json data for the notifications
- def put(self, request): Mark all notificat... | Implement the Python class `NotificationAPIView` described below.
Class description:
get:
Method signatures and docstrings:
- def get(self, request): Retrieve all notifications from the database for a specific user. :returns notifications: a json data for the notifications
- def put(self, request): Mark all notificat... | daf55ce4819f57cec8510c5726e86a0b1e78e3e1 | <|skeleton|>
class NotificationAPIView:
"""get:"""
def get(self, request):
"""Retrieve all notifications from the database for a specific user. :returns notifications: a json data for the notifications"""
<|body_0|>
def put(self, request):
"""Mark all notifications as read."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotificationAPIView:
"""get:"""
def get(self, request):
"""Retrieve all notifications from the database for a specific user. :returns notifications: a json data for the notifications"""
user = request.user
notifications = Notification.objects.all()
data = {}
for no... | the_stack_v2_python_sparse | authors/apps/notifications/views.py | andela/ah-magnificent6 | train | 0 |
5c65113d8fe3bf75317e6aaf727dbade145e3641 | [
"if not itvls:\n return []\nitvls.sort(key=lambda x: x.start)\nret = [itvls[0]]\nfor cur in itvls[1:]:\n pre = ret[-1]\n if cur.start <= pre.end:\n pre.end = max(pre.end, cur.end)\n else:\n ret.append(cur)\nreturn ret",
"if not itvls:\n return []\nret = [itvls[0]]\nfor interval in itv... | <|body_start_0|>
if not itvls:
return []
itvls.sort(key=lambda x: x.start)
ret = [itvls[0]]
for cur in itvls[1:]:
pre = ret[-1]
if cur.start <= pre.end:
pre.end = max(pre.end, cur.end)
else:
ret.append(cur)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def merge(self, itvls):
"""scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval"""
<|body_0|>
def merge_error(self, itvls):
"""scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval"""
... | stack_v2_sparse_classes_36k_train_012776 | 2,093 | permissive | [
{
"docstring": "scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval",
"name": "merge",
"signature": "def merge(self, itvls)"
},
{
"docstring": "scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval",
"name": "merge_error... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, itvls): scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval
- def merge_error(self, itvls): scanning. No algorithm math :para... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, itvls): scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval
- def merge_error(self, itvls): scanning. No algorithm math :para... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class Solution:
def merge(self, itvls):
"""scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval"""
<|body_0|>
def merge_error(self, itvls):
"""scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def merge(self, itvls):
"""scanning. No algorithm math :param itvls: a list of Interval :return: a list of Interval"""
if not itvls:
return []
itvls.sort(key=lambda x: x.start)
ret = [itvls[0]]
for cur in itvls[1:]:
pre = ret[-1]
... | the_stack_v2_python_sparse | 055 Merge Intervals.py | Aminaba123/LeetCode | train | 1 | |
d2bdf00c6ea36704e7032d866c502c3b02e5976d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AccessReviewStageSettings()",
"from .access_review_recommendation_insight_setting import AccessReviewRecommendationInsightSetting\nfrom .access_review_reviewer_scope import AccessReviewReviewerScope\nfrom .access_review_recommendation_... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AccessReviewStageSettings()
<|end_body_0|>
<|body_start_1|>
from .access_review_recommendation_insight_setting import AccessReviewRecommendationInsightSetting
from .access_review_reviewe... | AccessReviewStageSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccessReviewStageSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewStageSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and c... | stack_v2_sparse_classes_36k_train_012777 | 7,044 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AccessReviewStageSettings",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrim... | 3 | stack_v2_sparse_classes_30k_train_013119 | Implement the Python class `AccessReviewStageSettings` described below.
Class description:
Implement the AccessReviewStageSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewStageSettings: Creates a new instance of the appropriat... | Implement the Python class `AccessReviewStageSettings` described below.
Class description:
Implement the AccessReviewStageSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewStageSettings: Creates a new instance of the appropriat... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AccessReviewStageSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewStageSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccessReviewStageSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewStageSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the obje... | the_stack_v2_python_sparse | msgraph/generated/models/access_review_stage_settings.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
96334f3a232b0bb91b1f4dff25f965c29912bd96 | [
"if model_output_transform is None and transforms is None:\n model_output_transform = SameSize(resize_target=False, interpolation=self.DEFAULT_MASK_INTERPOLATION)\nif transforms is not None:\n transforms_wt_device: Compose = Compose([OnBothSides(ToDevice(device)), transforms])\nelse:\n transforms_wt_device... | <|body_start_0|>
if model_output_transform is None and transforms is None:
model_output_transform = SameSize(resize_target=False, interpolation=self.DEFAULT_MASK_INTERPOLATION)
if transforms is not None:
transforms_wt_device: Compose = Compose([OnBothSides(ToDevice(device)), tran... | Train test handle for concept localization models. Takes the concept data of the concept model's concept, and automatically converts it appropriately for the concept model (see :py:meth:`data_from_concept`). | ConceptDetection2DTrainTestHandle | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConceptDetection2DTrainTestHandle:
"""Train test handle for concept localization models. Takes the concept data of the concept model's concept, and automatically converts it appropriately for the concept model (see :py:meth:`data_from_concept`)."""
def __init__(self, concept_model: ConceptDe... | stack_v2_sparse_classes_36k_train_012778 | 27,601 | permissive | [
{
"docstring": "Init. For further parameter descriptions see ``__init__()`` of :py:class:`~hybrid_learning.concepts.models.base_handles.train_test_handle.TrainEvalHandle`. :param concept_model: the concept localization model to work on with concept. :param act_map_filepath_fns: dictionary of ``{split: func}`` w... | 3 | stack_v2_sparse_classes_30k_test_000962 | Implement the Python class `ConceptDetection2DTrainTestHandle` described below.
Class description:
Train test handle for concept localization models. Takes the concept data of the concept model's concept, and automatically converts it appropriately for the concept model (see :py:meth:`data_from_concept`).
Method sign... | Implement the Python class `ConceptDetection2DTrainTestHandle` described below.
Class description:
Train test handle for concept localization models. Takes the concept data of the concept model's concept, and automatically converts it appropriately for the concept model (see :py:meth:`data_from_concept`).
Method sign... | 37b9fc83d7b14902dfe92e0c45071c150bcf3779 | <|skeleton|>
class ConceptDetection2DTrainTestHandle:
"""Train test handle for concept localization models. Takes the concept data of the concept model's concept, and automatically converts it appropriately for the concept model (see :py:meth:`data_from_concept`)."""
def __init__(self, concept_model: ConceptDe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConceptDetection2DTrainTestHandle:
"""Train test handle for concept localization models. Takes the concept data of the concept model's concept, and automatically converts it appropriately for the concept model (see :py:meth:`data_from_concept`)."""
def __init__(self, concept_model: ConceptDetectionModel2... | the_stack_v2_python_sparse | hybrid_learning/concepts/models/concept_detection.py | JohnnyZhang917/hybrid_learning | train | 0 |
f071908d6b373e03e4f1505fda56c51775cae8b4 | [
"if root is None:\n return None\nif root.left is None and root.right is None:\n return [[root.val]]\nlevel_order = []\nlevel_limit = 0\ntmp_stack = [root]\ntmp_level = []\ncur_node = root\nwhile tmp_stack:\n level_limit = len(tmp_stack)\n while level_limit != 0:\n cur_node = tmp_stack.pop(0)\n ... | <|body_start_0|>
if root is None:
return None
if root.left is None and root.right is None:
return [[root.val]]
level_order = []
level_limit = 0
tmp_stack = [root]
tmp_level = []
cur_node = root
while tmp_stack:
level_lim... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrder1(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
... | stack_v2_sparse_classes_36k_train_012779 | 2,776 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrder",
"signature": "def levelOrder(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrder1",
"signature": "def levelOrder1(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrder1(self, root): :type root: TreeNode :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrder1(self, root): :type root: TreeNode :rtype: List[List[int]]
<|skeleton|>
class Solution:... | 233d12deca34f51c3bb0406831cc07f3b72b50cf | <|skeleton|>
class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrder1(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
if root is None:
return None
if root.left is None and root.right is None:
return [[root.val]]
level_order = []
level_limit = 0
tmp_stack = [root]
... | the_stack_v2_python_sparse | Python/Binary Tree Level Order Traversal/main.py | briansu2004/MyLeet | train | 1 | |
bd5da5c516f3a0003478b4d0713baf58782e5b5a | [
"current_user = g.user\nmeal = Meal.find_meal(meal_id, current_user)\nif not meal['status']:\n abort(http_status_code=400, message=meal['message'])\nmeal['meal'].delete_meal()\nreturn make_response(jsonify({'message': 'Meal deleted succesfully'}), 200)",
"parser = reqparse.RequestParser()\nparser.add_argument(... | <|body_start_0|>
current_user = g.user
meal = Meal.find_meal(meal_id, current_user)
if not meal['status']:
abort(http_status_code=400, message=meal['message'])
meal['meal'].delete_meal()
return make_response(jsonify({'message': 'Meal deleted succesfully'}), 200)
<|end... | mealone class | MealOne | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MealOne:
"""mealone class"""
def delete(meal_id):
"""Deletes a meal from the database if it exists token is required to get admin Id"""
<|body_0|>
def put(meal_id):
"""Allows admin to edit the meal details from the meals_list if it exists. token is required to ge... | stack_v2_sparse_classes_36k_train_012780 | 4,258 | no_license | [
{
"docstring": "Deletes a meal from the database if it exists token is required to get admin Id",
"name": "delete",
"signature": "def delete(meal_id)"
},
{
"docstring": "Allows admin to edit the meal details from the meals_list if it exists. token is required to get admin Id",
"name": "put",... | 3 | stack_v2_sparse_classes_30k_train_002702 | Implement the Python class `MealOne` described below.
Class description:
mealone class
Method signatures and docstrings:
- def delete(meal_id): Deletes a meal from the database if it exists token is required to get admin Id
- def put(meal_id): Allows admin to edit the meal details from the meals_list if it exists. to... | Implement the Python class `MealOne` described below.
Class description:
mealone class
Method signatures and docstrings:
- def delete(meal_id): Deletes a meal from the database if it exists token is required to get admin Id
- def put(meal_id): Allows admin to edit the meal details from the meals_list if it exists. to... | eef5f2802c94e428412e2f9814a5dac85575ed8e | <|skeleton|>
class MealOne:
"""mealone class"""
def delete(meal_id):
"""Deletes a meal from the database if it exists token is required to get admin Id"""
<|body_0|>
def put(meal_id):
"""Allows admin to edit the meal details from the meals_list if it exists. token is required to ge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MealOne:
"""mealone class"""
def delete(meal_id):
"""Deletes a meal from the database if it exists token is required to get admin Id"""
current_user = g.user
meal = Meal.find_meal(meal_id, current_user)
if not meal['status']:
abort(http_status_code=400, message... | the_stack_v2_python_sparse | api/views/meal_views.py | magicmarie/book_a_meal | train | 1 |
a58e738b54028b4973ded0540cf875ed30a7399d | [
"config = super(VarnishStatusCollector, self).get_default_config()\nconfig.update({'path': 'availability', 'bin': '/usr/bin/varnishtop'})\nreturn config",
"group_by_type = {'2xx': 0, '3xx': 0, '4xx': 0, '5xx': 0}\ntotal = 0\nlines = self.poll()\nfor line in lines:\n parts = line.split()\n if len(parts) == 3... | <|body_start_0|>
config = super(VarnishStatusCollector, self).get_default_config()
config.update({'path': 'availability', 'bin': '/usr/bin/varnishtop'})
return config
<|end_body_0|>
<|body_start_1|>
group_by_type = {'2xx': 0, '3xx': 0, '4xx': 0, '5xx': 0}
total = 0
lines... | VarnishStatusCollector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VarnishStatusCollector:
def get_default_config(self):
"""Returns the default collector settings"""
<|body_0|>
def collect(self):
"""Publishes stats to the configured path. e.g. /deployment-prep/hostname/availability/# with one # for each http status code"""
<... | stack_v2_sparse_classes_36k_train_012781 | 2,622 | no_license | [
{
"docstring": "Returns the default collector settings",
"name": "get_default_config",
"signature": "def get_default_config(self)"
},
{
"docstring": "Publishes stats to the configured path. e.g. /deployment-prep/hostname/availability/# with one # for each http status code",
"name": "collect"... | 3 | null | Implement the Python class `VarnishStatusCollector` described below.
Class description:
Implement the VarnishStatusCollector class.
Method signatures and docstrings:
- def get_default_config(self): Returns the default collector settings
- def collect(self): Publishes stats to the configured path. e.g. /deployment-pre... | Implement the Python class `VarnishStatusCollector` described below.
Class description:
Implement the VarnishStatusCollector class.
Method signatures and docstrings:
- def get_default_config(self): Returns the default collector settings
- def collect(self): Publishes stats to the configured path. e.g. /deployment-pre... | 75e0dd3698efa8e7cf95f6ef1348d16a299faa82 | <|skeleton|>
class VarnishStatusCollector:
def get_default_config(self):
"""Returns the default collector settings"""
<|body_0|>
def collect(self):
"""Publishes stats to the configured path. e.g. /deployment-prep/hostname/availability/# with one # for each http status code"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VarnishStatusCollector:
def get_default_config(self):
"""Returns the default collector settings"""
config = super(VarnishStatusCollector, self).get_default_config()
config.update({'path': 'availability', 'bin': '/usr/bin/varnishtop'})
return config
def collect(self):
... | the_stack_v2_python_sparse | modules/diamond/files/collector/varnishstatus.py | dkuspawono/puppet | train | 0 | |
cb8fccecfb6c6a499dd7ae3fb7d5eeb30333f589 | [
"if mec_controller.MecController.check_deployment(service_mec_server, extracted_service):\n mec_controller.MecController.deploy_service(service_mec_server, extracted_service)\nelse:\n mec_controller.MecController.deploy_service(service_mec_server, extracted_service)\n if not migration.service_migration(bas... | <|body_start_0|>
if mec_controller.MecController.check_deployment(service_mec_server, extracted_service):
mec_controller.MecController.deploy_service(service_mec_server, extracted_service)
else:
mec_controller.MecController.deploy_service(service_mec_server, extracted_service)
... | WorkloadController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkloadController:
def check_migration_demand(base_station_set: Dict[str, 'BaseStation'], mec_set: Dict[str, 'Mec'], hmds_set: Dict[str, 'VrHMD'], graph: 'Graph', service: 'VrService', extracted_service: 'VrService', service_mec_server: 'Mec', quota_copy: str, migration: 'Migration') -> None:
... | stack_v2_sparse_classes_36k_train_012782 | 5,608 | no_license | [
{
"docstring": "Checks whether a service fits on a mec server, otherwise, it checks the migration. If migration is not possible, it will revert the service to the previous service quota.",
"name": "check_migration_demand",
"signature": "def check_migration_demand(base_station_set: Dict[str, 'BaseStation... | 3 | null | Implement the Python class `WorkloadController` described below.
Class description:
Implement the WorkloadController class.
Method signatures and docstrings:
- def check_migration_demand(base_station_set: Dict[str, 'BaseStation'], mec_set: Dict[str, 'Mec'], hmds_set: Dict[str, 'VrHMD'], graph: 'Graph', service: 'VrSe... | Implement the Python class `WorkloadController` described below.
Class description:
Implement the WorkloadController class.
Method signatures and docstrings:
- def check_migration_demand(base_station_set: Dict[str, 'BaseStation'], mec_set: Dict[str, 'Mec'], hmds_set: Dict[str, 'VrHMD'], graph: 'Graph', service: 'VrSe... | e3e022a14058936619f1d79d11dbbb4f6f48d531 | <|skeleton|>
class WorkloadController:
def check_migration_demand(base_station_set: Dict[str, 'BaseStation'], mec_set: Dict[str, 'Mec'], hmds_set: Dict[str, 'VrHMD'], graph: 'Graph', service: 'VrService', extracted_service: 'VrService', service_mec_server: 'Mec', quota_copy: str, migration: 'Migration') -> None:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkloadController:
def check_migration_demand(base_station_set: Dict[str, 'BaseStation'], mec_set: Dict[str, 'Mec'], hmds_set: Dict[str, 'VrHMD'], graph: 'Graph', service: 'VrService', extracted_service: 'VrService', service_mec_server: 'Mec', quota_copy: str, migration: 'Migration') -> None:
"""Chec... | the_stack_v2_python_sparse | controllers/workload_controller.py | alissonpmedeiros/scg | train | 0 | |
521b86c34acf5b9486dd2c3ad8a7fc57cc2b664b | [
"if num_packs <= 0:\n raise ValueError('num_packs must be greater than zero.')\nself.num_packs = num_packs",
"self.grouped_grads_and_vars = grouped_grads_and_vars\nself.all_tower_shapes = []\nself.all_tower_sizes = []\ndevice_grad_packs = []\nfor tower_grads_and_vars in grouped_grads_and_vars:\n with ops.co... | <|body_start_0|>
if num_packs <= 0:
raise ValueError('num_packs must be greater than zero.')
self.num_packs = num_packs
<|end_body_0|>
<|body_start_1|>
self.grouped_grads_and_vars = grouped_grads_and_vars
self.all_tower_shapes = []
self.all_tower_sizes = []
d... | Concatenate and split tensors for reduction. | ConcatAndSplitPacker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConcatAndSplitPacker:
"""Concatenate and split tensors for reduction."""
def __init__(self, num_packs=1):
"""Initialize the ConcatAndSplitPacker object. Args: num_packs: specifies the number of split packs that will be formed. Raises: ValueError: if num_packs is not greater than 0.""... | stack_v2_sparse_classes_36k_train_012783 | 22,363 | permissive | [
{
"docstring": "Initialize the ConcatAndSplitPacker object. Args: num_packs: specifies the number of split packs that will be formed. Raises: ValueError: if num_packs is not greater than 0.",
"name": "__init__",
"signature": "def __init__(self, num_packs=1)"
},
{
"docstring": "Pack tensors.",
... | 3 | stack_v2_sparse_classes_30k_train_015022 | Implement the Python class `ConcatAndSplitPacker` described below.
Class description:
Concatenate and split tensors for reduction.
Method signatures and docstrings:
- def __init__(self, num_packs=1): Initialize the ConcatAndSplitPacker object. Args: num_packs: specifies the number of split packs that will be formed. ... | Implement the Python class `ConcatAndSplitPacker` described below.
Class description:
Concatenate and split tensors for reduction.
Method signatures and docstrings:
- def __init__(self, num_packs=1): Initialize the ConcatAndSplitPacker object. Args: num_packs: specifies the number of split packs that will be formed. ... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class ConcatAndSplitPacker:
"""Concatenate and split tensors for reduction."""
def __init__(self, num_packs=1):
"""Initialize the ConcatAndSplitPacker object. Args: num_packs: specifies the number of split packs that will be formed. Raises: ValueError: if num_packs is not greater than 0.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConcatAndSplitPacker:
"""Concatenate and split tensors for reduction."""
def __init__(self, num_packs=1):
"""Initialize the ConcatAndSplitPacker object. Args: num_packs: specifies the number of split packs that will be formed. Raises: ValueError: if num_packs is not greater than 0."""
if ... | the_stack_v2_python_sparse | Keras_tensorflow_nightly/source2.7/tensorflow/contrib/distribute/python/cross_tower_ops.py | ryfeus/lambda-packs | train | 1,283 |
119116554190346cc09b8a920d32915a28fc52f2 | [
"OutputPanelHandler.hide_panel()\noutput = ''\nworkspace_file = File.search('WORKSPACE', TreeSearchScope(path.dirname(view.file_name())))\nif not workspace_file:\n return None\ncmd = [path.join(PKG_FOLDER, 'external', 'bazel-compilation-database', 'generate.sh')]\noutput = Tools.run_command(cmd, cwd=workspace_fi... | <|body_start_0|>
OutputPanelHandler.hide_panel()
output = ''
workspace_file = File.search('WORKSPACE', TreeSearchScope(path.dirname(view.file_name())))
if not workspace_file:
return None
cmd = [path.join(PKG_FOLDER, 'external', 'bazel-compilation-database', 'generate.... | Collection of methods to generate a compilation database. | Bazel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bazel:
"""Collection of methods to generate a compilation database."""
def generate_compdb(view):
"""Generate the compilation database."""
<|body_0|>
def compdb_generated(future):
"""Generate a compilation database."""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_012784 | 1,614 | permissive | [
{
"docstring": "Generate the compilation database.",
"name": "generate_compdb",
"signature": "def generate_compdb(view)"
},
{
"docstring": "Generate a compilation database.",
"name": "compdb_generated",
"signature": "def compdb_generated(future)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017379 | Implement the Python class `Bazel` described below.
Class description:
Collection of methods to generate a compilation database.
Method signatures and docstrings:
- def generate_compdb(view): Generate the compilation database.
- def compdb_generated(future): Generate a compilation database. | Implement the Python class `Bazel` described below.
Class description:
Collection of methods to generate a compilation database.
Method signatures and docstrings:
- def generate_compdb(view): Generate the compilation database.
- def compdb_generated(future): Generate a compilation database.
<|skeleton|>
class Bazel:... | c2e8913052f4c9f11433f0a421fbbc4b78699fd6 | <|skeleton|>
class Bazel:
"""Collection of methods to generate a compilation database."""
def generate_compdb(view):
"""Generate the compilation database."""
<|body_0|>
def compdb_generated(future):
"""Generate a compilation database."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bazel:
"""Collection of methods to generate a compilation database."""
def generate_compdb(view):
"""Generate the compilation database."""
OutputPanelHandler.hide_panel()
output = ''
workspace_file = File.search('WORKSPACE', TreeSearchScope(path.dirname(view.file_name())))... | the_stack_v2_python_sparse | plugin/flags_sources/bazel.py | niosus/EasyClangComplete | train | 677 |
a83fa557f878fa922738032bdcdccbc0f8d7e364 | [
"if gr_pin not in [PMOD_GROVE_G1, PMOD_GROVE_G2, PMOD_GROVE_G3, PMOD_GROVE_G4]:\n raise ValueError('Group number can only be G1 - G4.')\nself.microblaze = Pmod(mb_info, PMOD_GROVE_EAR_HR_PROGRAM)\nself.microblaze.write_mailbox(0, gr_pin[0])\nself.microblaze.write_blocking_command(CONFIG_IOP_SWITCH)",
"beats, i... | <|body_start_0|>
if gr_pin not in [PMOD_GROVE_G1, PMOD_GROVE_G2, PMOD_GROVE_G3, PMOD_GROVE_G4]:
raise ValueError('Group number can only be G1 - G4.')
self.microblaze = Pmod(mb_info, PMOD_GROVE_EAR_HR_PROGRAM)
self.microblaze.write_mailbox(0, gr_pin[0])
self.microblaze.write_b... | This class controls the Grove ear clip heart rate sensor. Sensor model: MED03212P. Attributes ---------- microblaze : Pmod Microblaze processor instance used by this module. | Grove_EarHR | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Grove_EarHR:
"""This class controls the Grove ear clip heart rate sensor. Sensor model: MED03212P. Attributes ---------- microblaze : Pmod Microblaze processor instance used by this module."""
def __init__(self, mb_info, gr_pin):
"""Return a new instance of an Grove_EarHR object. Par... | stack_v2_sparse_classes_36k_train_012785 | 3,981 | permissive | [
{
"docstring": "Return a new instance of an Grove_EarHR object. Parameters ---------- mb_info : dict A dictionary storing Microblaze information, such as the IP name and the reset name. gr_pin: list A group of pins on pmod-grove adapter.",
"name": "__init__",
"signature": "def __init__(self, mb_info, gr... | 3 | stack_v2_sparse_classes_30k_val_000092 | Implement the Python class `Grove_EarHR` described below.
Class description:
This class controls the Grove ear clip heart rate sensor. Sensor model: MED03212P. Attributes ---------- microblaze : Pmod Microblaze processor instance used by this module.
Method signatures and docstrings:
- def __init__(self, mb_info, gr_... | Implement the Python class `Grove_EarHR` described below.
Class description:
This class controls the Grove ear clip heart rate sensor. Sensor model: MED03212P. Attributes ---------- microblaze : Pmod Microblaze processor instance used by this module.
Method signatures and docstrings:
- def __init__(self, mb_info, gr_... | 38e9fcee46f0839e83e123cf22af76b13671a574 | <|skeleton|>
class Grove_EarHR:
"""This class controls the Grove ear clip heart rate sensor. Sensor model: MED03212P. Attributes ---------- microblaze : Pmod Microblaze processor instance used by this module."""
def __init__(self, mb_info, gr_pin):
"""Return a new instance of an Grove_EarHR object. Par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Grove_EarHR:
"""This class controls the Grove ear clip heart rate sensor. Sensor model: MED03212P. Attributes ---------- microblaze : Pmod Microblaze processor instance used by this module."""
def __init__(self, mb_info, gr_pin):
"""Return a new instance of an Grove_EarHR object. Parameters -----... | the_stack_v2_python_sparse | pynq/lib/pmod/pmod_grove_ear_hr.py | yunqu/PYNQ | train | 8 |
dc88a450b52fcb40e235a7d2d8c0a9f1559b1732 | [
"try:\n job = Job.objects.get(identifier=context.identifier)\n job.status = Job.STARTED\n job.started = datetime.now(utc)\n job.save()\n context.logger.info('Job started after %.3gs waiting.', (job.started - job.created).total_seconds())\nexcept Job.DoesNotExist:\n context.logger.warning('Failed t... | <|body_start_0|>
try:
job = Job.objects.get(identifier=context.identifier)
job.status = Job.STARTED
job.started = datetime.now(utc)
job.save()
context.logger.info('Job started after %.3gs waiting.', (job.started - job.created).total_seconds())
... | Base asynchronous WPS process class. | AsyncProcessBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsyncProcessBase:
"""Base asynchronous WPS process class."""
def on_started(context, progress, message):
"""Callback executed when an asynchronous Job gets started."""
<|body_0|>
def on_succeeded(context, outputs):
"""Callback executed when an asynchronous Job fi... | stack_v2_sparse_classes_36k_train_012786 | 22,253 | no_license | [
{
"docstring": "Callback executed when an asynchronous Job gets started.",
"name": "on_started",
"signature": "def on_started(context, progress, message)"
},
{
"docstring": "Callback executed when an asynchronous Job finishes.",
"name": "on_succeeded",
"signature": "def on_succeeded(cont... | 5 | stack_v2_sparse_classes_30k_train_013122 | Implement the Python class `AsyncProcessBase` described below.
Class description:
Base asynchronous WPS process class.
Method signatures and docstrings:
- def on_started(context, progress, message): Callback executed when an asynchronous Job gets started.
- def on_succeeded(context, outputs): Callback executed when a... | Implement the Python class `AsyncProcessBase` described below.
Class description:
Base asynchronous WPS process class.
Method signatures and docstrings:
- def on_started(context, progress, message): Callback executed when an asynchronous Job gets started.
- def on_succeeded(context, outputs): Callback executed when a... | e75048c8607532d43e717d2a1d79a17fe9b0d1a1 | <|skeleton|>
class AsyncProcessBase:
"""Base asynchronous WPS process class."""
def on_started(context, progress, message):
"""Callback executed when an asynchronous Job gets started."""
<|body_0|>
def on_succeeded(context, outputs):
"""Callback executed when an asynchronous Job fi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsyncProcessBase:
"""Base asynchronous WPS process class."""
def on_started(context, progress, message):
"""Callback executed when an asynchronous Job gets started."""
try:
job = Job.objects.get(identifier=context.identifier)
job.status = Job.STARTED
jo... | the_stack_v2_python_sparse | aeolus/processes/util/base.py | ESA-VirES/Aeolus-Server | train | 2 |
68c8fb5e47ded6387ccdda8fbac0572394565315 | [
"if k == len(num):\n return '0'\nfor _ in range(k):\n i, j = (0, 0)\n while j + 1 < len(num) and num[j + 1] >= num[j]:\n j += 1\n if num[i] > num[j]:\n num = num[i + 1:]\n else:\n num = num[:j] + num[j + 1:]\nnum = num.lstrip('0')\nreturn '0' if not num else num",
"stk = []\ni ... | <|body_start_0|>
if k == len(num):
return '0'
for _ in range(k):
i, j = (0, 0)
while j + 1 < len(num) and num[j + 1] >= num[j]:
j += 1
if num[i] > num[j]:
num = num[i + 1:]
else:
num = num[:j] + n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_0|>
def removeKdigits_stk_way(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if k == len(num):... | stack_v2_sparse_classes_36k_train_012787 | 1,714 | no_license | [
{
"docstring": ":type num: str :type k: int :rtype: str",
"name": "removeKdigits",
"signature": "def removeKdigits(self, num, k)"
},
{
"docstring": ":type num: str :type k: int :rtype: str",
"name": "removeKdigits_stk_way",
"signature": "def removeKdigits_stk_way(self, num, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeKdigits(self, num, k): :type num: str :type k: int :rtype: str
- def removeKdigits_stk_way(self, num, k): :type num: str :type k: int :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeKdigits(self, num, k): :type num: str :type k: int :rtype: str
- def removeKdigits_stk_way(self, num, k): :type num: str :type k: int :rtype: str
<|skeleton|>
class So... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_0|>
def removeKdigits_stk_way(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
if k == len(num):
return '0'
for _ in range(k):
i, j = (0, 0)
while j + 1 < len(num) and num[j + 1] >= num[j]:
j += 1
if num[i] > num... | the_stack_v2_python_sparse | medium/heapstack/test_402_Remove_K_Digits.py | wuxu1019/leetcode_sophia | train | 1 | |
4a65127aa2c7e14766a2aafc7c85c90b26793c55 | [
"super(BehaviorAttackRanged, self).__init__(_move_cost)\nself.strength = _strength\nself.range = _range",
"zap_x, zap_y = _level_view.ent_coords(_target_eid)\nadv_x, adv_y = _user.get_coords()\nin_los = Z_ALGS.check_los(zap_x, zap_y, adv_x, adv_y, self.range + 1, _level_view.cell_is_transparent)\nin_rng = Z_ALGS.... | <|body_start_0|>
super(BehaviorAttackRanged, self).__init__(_move_cost)
self.strength = _strength
self.range = _range
<|end_body_0|>
<|body_start_1|>
zap_x, zap_y = _level_view.ent_coords(_target_eid)
adv_x, adv_y = _user.get_coords()
in_los = Z_ALGS.check_los(zap_x, zap... | BehaviorAttackRanged | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BehaviorAttackRanged:
def __init__(self, _move_cost=1, _strength=1, _range=5):
""":type _move_cost: int :type _strength: int :type _range: int"""
<|body_0|>
def _special_can_execute(self, _target_eid, _level_view, _user):
""":type _target_eid: int :type _level_view: ... | stack_v2_sparse_classes_36k_train_012788 | 1,805 | no_license | [
{
"docstring": ":type _move_cost: int :type _strength: int :type _range: int",
"name": "__init__",
"signature": "def __init__(self, _move_cost=1, _strength=1, _range=5)"
},
{
"docstring": ":type _target_eid: int :type _level_view: level.LevelView.LevelView :type _user: entity.actor.Adversary.Adv... | 3 | stack_v2_sparse_classes_30k_train_007436 | Implement the Python class `BehaviorAttackRanged` described below.
Class description:
Implement the BehaviorAttackRanged class.
Method signatures and docstrings:
- def __init__(self, _move_cost=1, _strength=1, _range=5): :type _move_cost: int :type _strength: int :type _range: int
- def _special_can_execute(self, _ta... | Implement the Python class `BehaviorAttackRanged` described below.
Class description:
Implement the BehaviorAttackRanged class.
Method signatures and docstrings:
- def __init__(self, _move_cost=1, _strength=1, _range=5): :type _move_cost: int :type _strength: int :type _range: int
- def _special_can_execute(self, _ta... | 0342700b0edfeedd8e3a8c1fea9bd790d2b8a042 | <|skeleton|>
class BehaviorAttackRanged:
def __init__(self, _move_cost=1, _strength=1, _range=5):
""":type _move_cost: int :type _strength: int :type _range: int"""
<|body_0|>
def _special_can_execute(self, _target_eid, _level_view, _user):
""":type _target_eid: int :type _level_view: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BehaviorAttackRanged:
def __init__(self, _move_cost=1, _strength=1, _range=5):
""":type _move_cost: int :type _strength: int :type _range: int"""
super(BehaviorAttackRanged, self).__init__(_move_cost)
self.strength = _strength
self.range = _range
def _special_can_execute(s... | the_stack_v2_python_sparse | Python_Zappy/entity/actor/behaviors/BehaviorAttackRanged.py | MoyTW/Zappy | train | 0 | |
b84ab33b94ac6099b0dcc0f00f9916f379d65306 | [
"if type(data) is not np.ndarray or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nd, n = data.shape\nif n < 2:\n raise ValueError('data must contain multiple data points')\nself.mean = np.mean(data, axis=1, keepdims=True)\nself.n = n\nself.d = d\nself.data = data\nself.stdev = np... | <|body_start_0|>
if type(data) is not np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
d, n = data.shape
if n < 2:
raise ValueError('data must contain multiple data points')
self.mean = np.mean(data, axis=1, keepdims=True)
... | Represents multivariate normal distribution | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Represents multivariate normal distribution"""
def __init__(self, data):
"""data ndarray (d, n) n # data points, d # dims"""
<|body_0|>
def pdf(self, x):
"""calculates pdf at data point x ndarray (d, 1) data point to calculate pdf d # dims of mult... | stack_v2_sparse_classes_36k_train_012789 | 2,245 | no_license | [
{
"docstring": "data ndarray (d, n) n # data points, d # dims",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "calculates pdf at data point x ndarray (d, 1) data point to calculate pdf d # dims of multinomial instance Returns: value of pdf",
"name": "pdf",
... | 2 | null | Implement the Python class `MultiNormal` described below.
Class description:
Represents multivariate normal distribution
Method signatures and docstrings:
- def __init__(self, data): data ndarray (d, n) n # data points, d # dims
- def pdf(self, x): calculates pdf at data point x ndarray (d, 1) data point to calculate... | Implement the Python class `MultiNormal` described below.
Class description:
Represents multivariate normal distribution
Method signatures and docstrings:
- def __init__(self, data): data ndarray (d, n) n # data points, d # dims
- def pdf(self, x): calculates pdf at data point x ndarray (d, 1) data point to calculate... | 5114f884241b3406940b00450d8c71f55d5d6a70 | <|skeleton|>
class MultiNormal:
"""Represents multivariate normal distribution"""
def __init__(self, data):
"""data ndarray (d, n) n # data points, d # dims"""
<|body_0|>
def pdf(self, x):
"""calculates pdf at data point x ndarray (d, 1) data point to calculate pdf d # dims of mult... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""Represents multivariate normal distribution"""
def __init__(self, data):
"""data ndarray (d, n) n # data points, d # dims"""
if type(data) is not np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
d, n = data.shape
... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | icculp/holbertonschool-machine_learning | train | 0 |
df9c6379631b6ece15592df0ac426a797e1e9478 | [
"self.ai_settings = ai_settings\ntry:\n with open('high_score.txt') as f:\n high_score = f.read()\n self.high_score = int(high_score) if high_score else 0\nexcept FileNotFoundError:\n self.high_score = 0\nself.reset_stats()\nself.game_active = False",
"self.ships_left = self.ai_settings.ship_l... | <|body_start_0|>
self.ai_settings = ai_settings
try:
with open('high_score.txt') as f:
high_score = f.read()
self.high_score = int(high_score) if high_score else 0
except FileNotFoundError:
self.high_score = 0
self.reset_stats()
... | 跟踪游戏的统计信息 | GameStats | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, ai_settings):
"""初始化统计信息"""
<|body_0|>
def reset_stats(self):
"""初始化在游戏运行期间可能变化的统计信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.ai_settings = ai_settings
try:
with open(... | stack_v2_sparse_classes_36k_train_012790 | 670 | no_license | [
{
"docstring": "初始化统计信息",
"name": "__init__",
"signature": "def __init__(self, ai_settings)"
},
{
"docstring": "初始化在游戏运行期间可能变化的统计信息",
"name": "reset_stats",
"signature": "def reset_stats(self)"
}
] | 2 | null | Implement the Python class `GameStats` described below.
Class description:
跟踪游戏的统计信息
Method signatures and docstrings:
- def __init__(self, ai_settings): 初始化统计信息
- def reset_stats(self): 初始化在游戏运行期间可能变化的统计信息 | Implement the Python class `GameStats` described below.
Class description:
跟踪游戏的统计信息
Method signatures and docstrings:
- def __init__(self, ai_settings): 初始化统计信息
- def reset_stats(self): 初始化在游戏运行期间可能变化的统计信息
<|skeleton|>
class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, ai_settings):
"""初始化统计信息"""
... | 916a3269cb3946f33bc87b289c5f20f26c265436 | <|skeleton|>
class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, ai_settings):
"""初始化统计信息"""
<|body_0|>
def reset_stats(self):
"""初始化在游戏运行期间可能变化的统计信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameStats:
"""跟踪游戏的统计信息"""
def __init__(self, ai_settings):
"""初始化统计信息"""
self.ai_settings = ai_settings
try:
with open('high_score.txt') as f:
high_score = f.read()
self.high_score = int(high_score) if high_score else 0
except F... | the_stack_v2_python_sparse | Python编程从入门到实践/alien_invasion/game_stats.py | daedalaus/practice | train | 0 |
1702641cb99fbc8e9025526995d600323caa8558 | [
"if not args:\n args = ('',)\napps = self.catalog_apps(cherrypy.tree.apps, args[0] == 'all')\nif cherrypy.request.wants == 'org':\n checklist = (f'- [ ] {name}' for name, _, _ in apps)\n return '\\n'.join(checklist).encode()\nreturn cherrypy.engine.publish('jinja:render', 'apps/homepage/homepage.jinja.html... | <|body_start_0|>
if not args:
args = ('',)
apps = self.catalog_apps(cherrypy.tree.apps, args[0] == 'all')
if cherrypy.request.wants == 'org':
checklist = (f'- [ ] {name}' for name, _, _ in apps)
return '\n'.join(checklist).encode()
return cherrypy.engi... | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
def GET(self, *args: str, **_kwargs: str) -> bytes:
"""List all available applications. Apps can be excluded from this list by setting show_on_homepage to False."""
<|body_0|>
def catalog_apps(apps: Dict[str, cherrypy.Application], show_all: bool=True) -> List[Tu... | stack_v2_sparse_classes_36k_train_012791 | 2,402 | no_license | [
{
"docstring": "List all available applications. Apps can be excluded from this list by setting show_on_homepage to False.",
"name": "GET",
"signature": "def GET(self, *args: str, **_kwargs: str) -> bytes"
},
{
"docstring": "Extract app summaries from module docstrings.",
"name": "catalog_ap... | 2 | null | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def GET(self, *args: str, **_kwargs: str) -> bytes: List all available applications. Apps can be excluded from this list by setting show_on_homepage to False.
- def catalog_a... | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def GET(self, *args: str, **_kwargs: str) -> bytes: List all available applications. Apps can be excluded from this list by setting show_on_homepage to False.
- def catalog_a... | 7129415303b94d5d10b2c29ec432f0c7d41cc651 | <|skeleton|>
class Controller:
def GET(self, *args: str, **_kwargs: str) -> bytes:
"""List all available applications. Apps can be excluded from this list by setting show_on_homepage to False."""
<|body_0|>
def catalog_apps(apps: Dict[str, cherrypy.Application], show_all: bool=True) -> List[Tu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
def GET(self, *args: str, **_kwargs: str) -> bytes:
"""List all available applications. Apps can be excluded from this list by setting show_on_homepage to False."""
if not args:
args = ('',)
apps = self.catalog_apps(cherrypy.tree.apps, args[0] == 'all')
... | the_stack_v2_python_sparse | apps/homepage/main.py | lovett/medley | train | 6 | |
f96a5f183c0fc2c46190ada3e960a5908db37d6b | [
"name = 'rc_wiki.preprocessed'\ndescription = _RC_DESCRIPTION\nsuper(BigBirdTriviaQAConfig, self).__init__(name=name, description=description, version=tfds.core.Version('1.1.1'), **kwargs)\nself.unfiltered = False\nself.exclude_context = False",
"self.sentencepiece_model_path = sentencepiece_model_path\nself.sequ... | <|body_start_0|>
name = 'rc_wiki.preprocessed'
description = _RC_DESCRIPTION
super(BigBirdTriviaQAConfig, self).__init__(name=name, description=description, version=tfds.core.Version('1.1.1'), **kwargs)
self.unfiltered = False
self.exclude_context = False
<|end_body_0|>
<|body_s... | BuilderConfig for TriviaQA. | BigBirdTriviaQAConfig | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BigBirdTriviaQAConfig:
"""BuilderConfig for TriviaQA."""
def __init__(self, **kwargs):
"""BuilderConfig for TriviaQA. Args: **kwargs: keyword arguments forwarded to super."""
<|body_0|>
def configure(self, sentencepiece_model_path, sequence_length, stride, global_sequenc... | stack_v2_sparse_classes_36k_train_012792 | 16,324 | permissive | [
{
"docstring": "BuilderConfig for TriviaQA. Args: **kwargs: keyword arguments forwarded to super.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Configures additional user-specified arguments.",
"name": "configure",
"signature": "def configure(self, ... | 3 | stack_v2_sparse_classes_30k_train_007581 | Implement the Python class `BigBirdTriviaQAConfig` described below.
Class description:
BuilderConfig for TriviaQA.
Method signatures and docstrings:
- def __init__(self, **kwargs): BuilderConfig for TriviaQA. Args: **kwargs: keyword arguments forwarded to super.
- def configure(self, sentencepiece_model_path, sequenc... | Implement the Python class `BigBirdTriviaQAConfig` described below.
Class description:
BuilderConfig for TriviaQA.
Method signatures and docstrings:
- def __init__(self, **kwargs): BuilderConfig for TriviaQA. Args: **kwargs: keyword arguments forwarded to super.
- def configure(self, sentencepiece_model_path, sequenc... | 6fc53292b1d3ce3c0340ce724c2c11c77e663d27 | <|skeleton|>
class BigBirdTriviaQAConfig:
"""BuilderConfig for TriviaQA."""
def __init__(self, **kwargs):
"""BuilderConfig for TriviaQA. Args: **kwargs: keyword arguments forwarded to super."""
<|body_0|>
def configure(self, sentencepiece_model_path, sequence_length, stride, global_sequenc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BigBirdTriviaQAConfig:
"""BuilderConfig for TriviaQA."""
def __init__(self, **kwargs):
"""BuilderConfig for TriviaQA. Args: **kwargs: keyword arguments forwarded to super."""
name = 'rc_wiki.preprocessed'
description = _RC_DESCRIPTION
super(BigBirdTriviaQAConfig, self).__i... | the_stack_v2_python_sparse | models/official/nlp/projects/triviaqa/dataset.py | aboerzel/German_License_Plate_Recognition | train | 34 |
a47037dcdc96c63b2f885c7750f80f258c15760c | [
"self._data = data\nself._attr_name = name\nself._attr_native_value = None\nself._type = sensor_type\nself._attr_native_unit_of_measurement = sensor_unit\nself._attr_device_class = device_class\nself._attr_state_class = state_class",
"self._data.update()\nself._attr_native_value = self._data.get_value(self._type)... | <|body_start_0|>
self._data = data
self._attr_name = name
self._attr_native_value = None
self._type = sensor_type
self._attr_native_unit_of_measurement = sensor_unit
self._attr_device_class = device_class
self._attr_state_class = state_class
<|end_body_0|>
<|body... | Representation of a Sensor. | DanfossAir | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DanfossAir:
"""Representation of a Sensor."""
def __init__(self, data, name, sensor_unit, sensor_type, device_class, state_class):
"""Initialize the sensor."""
<|body_0|>
def update(self) -> None:
"""Update the new state of the sensor. This is done through the Da... | stack_v2_sparse_classes_36k_train_012793 | 3,911 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, data, name, sensor_unit, sensor_type, device_class, state_class)"
},
{
"docstring": "Update the new state of the sensor. This is done through the DanfossAir object that does the actual communication wit... | 2 | null | Implement the Python class `DanfossAir` described below.
Class description:
Representation of a Sensor.
Method signatures and docstrings:
- def __init__(self, data, name, sensor_unit, sensor_type, device_class, state_class): Initialize the sensor.
- def update(self) -> None: Update the new state of the sensor. This i... | Implement the Python class `DanfossAir` described below.
Class description:
Representation of a Sensor.
Method signatures and docstrings:
- def __init__(self, data, name, sensor_unit, sensor_type, device_class, state_class): Initialize the sensor.
- def update(self) -> None: Update the new state of the sensor. This i... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class DanfossAir:
"""Representation of a Sensor."""
def __init__(self, data, name, sensor_unit, sensor_type, device_class, state_class):
"""Initialize the sensor."""
<|body_0|>
def update(self) -> None:
"""Update the new state of the sensor. This is done through the Da... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DanfossAir:
"""Representation of a Sensor."""
def __init__(self, data, name, sensor_unit, sensor_type, device_class, state_class):
"""Initialize the sensor."""
self._data = data
self._attr_name = name
self._attr_native_value = None
self._type = sensor_type
... | the_stack_v2_python_sparse | homeassistant/components/danfoss_air/sensor.py | home-assistant/core | train | 35,501 |
963bb5e374f6f7d04809626b0bfa6e55f2daa0fc | [
"self.raidus = radius\nself.x = x_center\nself.y = y_center",
"r = self.raidus * math.sqrt(random.random())\ntheta = 2 * math.pi * random.random()\nreturn [self.x + r * math.cos(theta), self.y + r * math.sin(theta)]"
] | <|body_start_0|>
self.raidus = radius
self.x = x_center
self.y = y_center
<|end_body_0|>
<|body_start_1|>
r = self.raidus * math.sqrt(random.random())
theta = 2 * math.pi * random.random()
return [self.x + r * math.cos(theta), self.y + r * math.sin(theta)]
<|end_body_1|>... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.raidus = radi... | stack_v2_sparse_classes_36k_train_012794 | 2,360 | no_license | [
{
"docstring": ":type radius: float :type x_center: float :type y_center: float",
"name": "__init__",
"signature": "def __init__(self, radius, x_center, y_center)"
},
{
"docstring": ":rtype: List[float]",
"name": "randPoint",
"signature": "def randPoint(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float]
<|skeleton|>
class Sol... | 8595b04cf5a024c2cd8a97f750d890a818568401 | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
self.raidus = radius
self.x = x_center
self.y = y_center
def randPoint(self):
""":rtype: List[float]"""
r = self.raidus * math.sq... | the_stack_v2_python_sparse | python/478.generate-random-point-in-a-circle.py | tainenko/Leetcode2019 | train | 5 | |
e485d15ba9140bb22e30b9c72e18bd6fd5a8b19a | [
"super(LayerNorm, self).__init__()\nself.weight = self.set_parameters('gamma', ones(hidden_size))\nself.bias = self.set_parameters('beta', zeros(hidden_size))\nself.variance_epsilon = eps",
"u = x.mean(-1, keepdim=True)\ns = (x - u).pow(2).mean(-1, keepdim=True)\nx = (x - u) / sqrt(s + self.variance_epsilon)\nret... | <|body_start_0|>
super(LayerNorm, self).__init__()
self.weight = self.set_parameters('gamma', ones(hidden_size))
self.bias = self.set_parameters('beta', zeros(hidden_size))
self.variance_epsilon = eps
<|end_body_0|>
<|body_start_1|>
u = x.mean(-1, keepdim=True)
s = (x - ... | Layer Norm module. | LayerNorm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerNorm:
"""Layer Norm module."""
def __init__(self, hidden_size, eps=1e-12):
"""Construct a layernorm module in the TF style (epsilon inside the square root)."""
<|body_0|>
def call(self, x):
"""Call LayerNorm."""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_012795 | 25,894 | permissive | [
{
"docstring": "Construct a layernorm module in the TF style (epsilon inside the square root).",
"name": "__init__",
"signature": "def __init__(self, hidden_size, eps=1e-12)"
},
{
"docstring": "Call LayerNorm.",
"name": "call",
"signature": "def call(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007045 | Implement the Python class `LayerNorm` described below.
Class description:
Layer Norm module.
Method signatures and docstrings:
- def __init__(self, hidden_size, eps=1e-12): Construct a layernorm module in the TF style (epsilon inside the square root).
- def call(self, x): Call LayerNorm. | Implement the Python class `LayerNorm` described below.
Class description:
Layer Norm module.
Method signatures and docstrings:
- def __init__(self, hidden_size, eps=1e-12): Construct a layernorm module in the TF style (epsilon inside the square root).
- def call(self, x): Call LayerNorm.
<|skeleton|>
class LayerNor... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class LayerNorm:
"""Layer Norm module."""
def __init__(self, hidden_size, eps=1e-12):
"""Construct a layernorm module in the TF style (epsilon inside the square root)."""
<|body_0|>
def call(self, x):
"""Call LayerNorm."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayerNorm:
"""Layer Norm module."""
def __init__(self, hidden_size, eps=1e-12):
"""Construct a layernorm module in the TF style (epsilon inside the square root)."""
super(LayerNorm, self).__init__()
self.weight = self.set_parameters('gamma', ones(hidden_size))
self.bias = ... | the_stack_v2_python_sparse | zeus/modules/operators/functions/pytorch_fn.py | huawei-noah/xingtian | train | 308 |
e49fa94a3b9a59cf82ec296590b2156bf9e74624 | [
"self.username = ''\nself.password = ''\nself.baseUrl = 'http://{0}:{1}/'.format(hostname, port)",
"api = self.baseUrl + 'init'\ntry:\n return self._http_request(api, 'GET', timeout=30)\nexcept ServerUnavailableException:\n print('Dashboard is not available... bypassing.')\n return (False, None)",
"api... | <|body_start_0|>
self.username = ''
self.password = ''
self.baseUrl = 'http://{0}:{1}/'.format(hostname, port)
<|end_body_0|>
<|body_start_1|>
api = self.baseUrl + 'init'
try:
return self._http_request(api, 'GET', timeout=30)
except ServerUnavailableException... | Performance dashboard (cbkarma) REST API | CbKarmaClient | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CbKarmaClient:
"""Performance dashboard (cbkarma) REST API"""
def __init__(self, hostname, port='80'):
"""Create REST API client. Keyword arguments: hostname -- dashboard hostname/ip address port -- dashboard port"""
<|body_0|>
def init(self):
"""Get initial test... | stack_v2_sparse_classes_36k_train_012796 | 2,862 | permissive | [
{
"docstring": "Create REST API client. Keyword arguments: hostname -- dashboard hostname/ip address port -- dashboard port",
"name": "__init__",
"signature": "def __init__(self, hostname, port='80')"
},
{
"docstring": "Get initial test id (optional)",
"name": "init",
"signature": "def i... | 5 | stack_v2_sparse_classes_30k_train_011738 | Implement the Python class `CbKarmaClient` described below.
Class description:
Performance dashboard (cbkarma) REST API
Method signatures and docstrings:
- def __init__(self, hostname, port='80'): Create REST API client. Keyword arguments: hostname -- dashboard hostname/ip address port -- dashboard port
- def init(se... | Implement the Python class `CbKarmaClient` described below.
Class description:
Performance dashboard (cbkarma) REST API
Method signatures and docstrings:
- def __init__(self, hostname, port='80'): Create REST API client. Keyword arguments: hostname -- dashboard hostname/ip address port -- dashboard port
- def init(se... | 9d8220a0925327bddf0e10887e22b57c5d6adb37 | <|skeleton|>
class CbKarmaClient:
"""Performance dashboard (cbkarma) REST API"""
def __init__(self, hostname, port='80'):
"""Create REST API client. Keyword arguments: hostname -- dashboard hostname/ip address port -- dashboard port"""
<|body_0|>
def init(self):
"""Get initial test... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CbKarmaClient:
"""Performance dashboard (cbkarma) REST API"""
def __init__(self, hostname, port='80'):
"""Create REST API client. Keyword arguments: hostname -- dashboard hostname/ip address port -- dashboard port"""
self.username = ''
self.password = ''
self.baseUrl = 'ht... | the_stack_v2_python_sparse | lib/cbkarma/rest_client.py | couchbase/testrunner | train | 18 |
732e8bc2fa1a8d8fafffd9ec5afce24978bf6fe4 | [
"if numRows == 1 or numRows >= len(s):\n return s\ndelta = -1\nrow = 0\nres = [[] for i in range(numRows)]\nfor c in s:\n res[row].append(c)\n if row == 0 or row == numRows - 1:\n delta *= -1\n row += delta\nfor i in range(len(res)):\n res[i] = ''.join(res[i])\nreturn ''.join(res)",
"if numR... | <|body_start_0|>
if numRows == 1 or numRows >= len(s):
return s
delta = -1
row = 0
res = [[] for i in range(numRows)]
for c in s:
res[row].append(c)
if row == 0 or row == numRows - 1:
delta *= -1
row += delta
... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def convert(self, s: str, numRows: int) -> str:
"""Approach 1 : Time: O( n+k < n+n <2n ) = O(n) Space: O(n) :type s: str :type numRows: int :rtype: str"""
<|body_0|>
def convert2(self, s: str, numRows: int) -> str:
"""Approach 2 : if numRows=4 row 0 ==> 0 ... | stack_v2_sparse_classes_36k_train_012797 | 1,659 | no_license | [
{
"docstring": "Approach 1 : Time: O( n+k < n+n <2n ) = O(n) Space: O(n) :type s: str :type numRows: int :rtype: str",
"name": "convert",
"signature": "def convert(self, s: str, numRows: int) -> str"
},
{
"docstring": "Approach 2 : if numRows=4 row 0 ==> 0 6 12 ... 0 +6 +6 row 1 ==> 1 5 7 13 ...... | 2 | stack_v2_sparse_classes_30k_train_013720 | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def convert(self, s: str, numRows: int) -> str: Approach 1 : Time: O( n+k < n+n <2n ) = O(n) Space: O(n) :type s: str :type numRows: int :rtype: str
- def convert2(self, s: str... | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def convert(self, s: str, numRows: int) -> str: Approach 1 : Time: O( n+k < n+n <2n ) = O(n) Space: O(n) :type s: str :type numRows: int :rtype: str
- def convert2(self, s: str... | f1b466a5f2ffc9ff00a0d9895bda145eb3c7db54 | <|skeleton|>
class Solution1:
def convert(self, s: str, numRows: int) -> str:
"""Approach 1 : Time: O( n+k < n+n <2n ) = O(n) Space: O(n) :type s: str :type numRows: int :rtype: str"""
<|body_0|>
def convert2(self, s: str, numRows: int) -> str:
"""Approach 2 : if numRows=4 row 0 ==> 0 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution1:
def convert(self, s: str, numRows: int) -> str:
"""Approach 1 : Time: O( n+k < n+n <2n ) = O(n) Space: O(n) :type s: str :type numRows: int :rtype: str"""
if numRows == 1 or numRows >= len(s):
return s
delta = -1
row = 0
res = [[] for i in range(n... | the_stack_v2_python_sparse | LeetCode_exercises/ex0006_zigZag_conversion.py | msjithin/LeetCode_exercises | train | 0 | |
eac5417971633ce3a2982c832dd850dc619b8617 | [
"super().__init__(coordinator)\nself._attr_device_info = DeviceInfo(entry_type=DeviceEntryType.SERVICE, identifiers={(DOMAIN, f'{coordinator.latitude}-{coordinator.longitude}')}, manufacturer=MANUFACTURER, name=name, configuration_url=URL.format(latitude=coordinator.latitude, longitude=coordinator.longitude))\nself... | <|body_start_0|>
super().__init__(coordinator)
self._attr_device_info = DeviceInfo(entry_type=DeviceEntryType.SERVICE, identifiers={(DOMAIN, f'{coordinator.latitude}-{coordinator.longitude}')}, manufacturer=MANUFACTURER, name=name, configuration_url=URL.format(latitude=coordinator.latitude, longitude=co... | Define an Airly sensor. | AirlySensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AirlySensor:
"""Define an Airly sensor."""
def __init__(self, coordinator: AirlyDataUpdateCoordinator, name: str, description: AirlySensorEntityDescription) -> None:
"""Initialize."""
<|body_0|>
def _handle_coordinator_update(self) -> None:
"""Handle updated data... | stack_v2_sparse_classes_36k_train_012798 | 7,989 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, coordinator: AirlyDataUpdateCoordinator, name: str, description: AirlySensorEntityDescription) -> None"
},
{
"docstring": "Handle updated data from the coordinator.",
"name": "_handle_coordinator_update",
... | 2 | stack_v2_sparse_classes_30k_train_013912 | Implement the Python class `AirlySensor` described below.
Class description:
Define an Airly sensor.
Method signatures and docstrings:
- def __init__(self, coordinator: AirlyDataUpdateCoordinator, name: str, description: AirlySensorEntityDescription) -> None: Initialize.
- def _handle_coordinator_update(self) -> None... | Implement the Python class `AirlySensor` described below.
Class description:
Define an Airly sensor.
Method signatures and docstrings:
- def __init__(self, coordinator: AirlyDataUpdateCoordinator, name: str, description: AirlySensorEntityDescription) -> None: Initialize.
- def _handle_coordinator_update(self) -> None... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AirlySensor:
"""Define an Airly sensor."""
def __init__(self, coordinator: AirlyDataUpdateCoordinator, name: str, description: AirlySensorEntityDescription) -> None:
"""Initialize."""
<|body_0|>
def _handle_coordinator_update(self) -> None:
"""Handle updated data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AirlySensor:
"""Define an Airly sensor."""
def __init__(self, coordinator: AirlyDataUpdateCoordinator, name: str, description: AirlySensorEntityDescription) -> None:
"""Initialize."""
super().__init__(coordinator)
self._attr_device_info = DeviceInfo(entry_type=DeviceEntryType.SERV... | the_stack_v2_python_sparse | homeassistant/components/airly/sensor.py | home-assistant/core | train | 35,501 |
69dc2a79424eeff834d1ab01797bba91455f5304 | [
"super().__init__(parent)\nself.parent = parent\nself.setViewMode(QListView.ViewMode.IconMode)\nself.setTextElideMode(Qt.TextElideMode.ElideMiddle)\nself.setResizeMode(QListView.ResizeMode.Adjust)\nself.setGridSize(QSize(110, 110))\nself.setLayoutMode(QListView.LayoutMode.Batched)\nself.setBatchSize(20)\nself.setSe... | <|body_start_0|>
super().__init__(parent)
self.parent = parent
self.setViewMode(QListView.ViewMode.IconMode)
self.setTextElideMode(Qt.TextElideMode.ElideMiddle)
self.setResizeMode(QListView.ResizeMode.Adjust)
self.setGridSize(QSize(110, 110))
self.setLayoutMode(QL... | ImageViewerListWidget | [
"GPL-3.0-only",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageViewerListWidget:
def __init__(self, parent):
"""Subclassed QListWidget that displays images"""
<|body_0|>
def contextMenuEvent(self, event):
"""A simple context menu for managing images."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().... | stack_v2_sparse_classes_36k_train_012799 | 1,542 | permissive | [
{
"docstring": "Subclassed QListWidget that displays images",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "A simple context menu for managing images.",
"name": "contextMenuEvent",
"signature": "def contextMenuEvent(self, event)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015644 | Implement the Python class `ImageViewerListWidget` described below.
Class description:
Implement the ImageViewerListWidget class.
Method signatures and docstrings:
- def __init__(self, parent): Subclassed QListWidget that displays images
- def contextMenuEvent(self, event): A simple context menu for managing images. | Implement the Python class `ImageViewerListWidget` described below.
Class description:
Implement the ImageViewerListWidget class.
Method signatures and docstrings:
- def __init__(self, parent): Subclassed QListWidget that displays images
- def contextMenuEvent(self, event): A simple context menu for managing images.
... | 6edbecdb422b10881216c310e70796c5cc3c9d04 | <|skeleton|>
class ImageViewerListWidget:
def __init__(self, parent):
"""Subclassed QListWidget that displays images"""
<|body_0|>
def contextMenuEvent(self, event):
"""A simple context menu for managing images."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageViewerListWidget:
def __init__(self, parent):
"""Subclassed QListWidget that displays images"""
super().__init__(parent)
self.parent = parent
self.setViewMode(QListView.ViewMode.IconMode)
self.setTextElideMode(Qt.TextElideMode.ElideMiddle)
self.setResizeMod... | the_stack_v2_python_sparse | Chapter02/ImageManager/image_manager/widgets/image_viewer.py | ralex1975/Building-Custom-UIs-with-PyQt | train | 1 |
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