blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6b9711afb9dfe4c2623942eb01f67400b45a0864 | [
"username = self.cleaned_data.get('username')\nis_exist = models.UserInfo.objects.filter(username=username)\nif is_exist.exists():\n raise ValidationError('用户名已经存在')\nelse:\n return username",
"pwd = self.cleaned_data.get('password')\nre_pwd = self.cleaned_data.get('re_password')\nif pwd == re_pwd:\n ret... | <|body_start_0|>
username = self.cleaned_data.get('username')
is_exist = models.UserInfo.objects.filter(username=username)
if is_exist.exists():
raise ValidationError('用户名已经存在')
else:
return username
<|end_body_0|>
<|body_start_1|>
pwd = self.cleaned_data... | 用户注册校验 使用form组件 字段名称必须和数据库对应 re_password在数据库不存在，在存储数据前会删掉 RegexValidator forms中使用正则过滤 | RegisterForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterForm:
"""用户注册校验 使用form组件 字段名称必须和数据库对应 re_password在数据库不存在，在存储数据前会删掉 RegexValidator forms中使用正则过滤"""
def clean_username(self):
"""局部钩子 clean_username 对username字段进行校验 检测用户名唯一性 ValidationError 弹出异常 :return: 成功：用户名 失败：错误信息"""
<|body_0|>
def clean(self):
"""全局钩子... | stack_v2_sparse_classes_10k_train_006900 | 5,228 | no_license | [
{
"docstring": "局部钩子 clean_username 对username字段进行校验 检测用户名唯一性 ValidationError 弹出异常 :return: 成功：用户名 失败：错误信息",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "全局钩子 获取cleaned_data中的所有数据 检测两次输入的密码是否一致 :return: 成功: 返回cleaned_data 数据 失败：返回错误信息，并指定那个input返回错误信息",
... | 3 | stack_v2_sparse_classes_30k_train_003707 | Implement the Python class `RegisterForm` described below.
Class description:
用户注册校验 使用form组件 字段名称必须和数据库对应 re_password在数据库不存在，在存储数据前会删掉 RegexValidator forms中使用正则过滤
Method signatures and docstrings:
- def clean_username(self): 局部钩子 clean_username 对username字段进行校验 检测用户名唯一性 ValidationError 弹出异常 :return: 成功：用户名 失败：错误信息
- ... | Implement the Python class `RegisterForm` described below.
Class description:
用户注册校验 使用form组件 字段名称必须和数据库对应 re_password在数据库不存在，在存储数据前会删掉 RegexValidator forms中使用正则过滤
Method signatures and docstrings:
- def clean_username(self): 局部钩子 clean_username 对username字段进行校验 检测用户名唯一性 ValidationError 弹出异常 :return: 成功：用户名 失败：错误信息
- ... | d7fc68d3d23345df5bfb09d4a84686c8b49a5ad7 | <|skeleton|>
class RegisterForm:
"""用户注册校验 使用form组件 字段名称必须和数据库对应 re_password在数据库不存在，在存储数据前会删掉 RegexValidator forms中使用正则过滤"""
def clean_username(self):
"""局部钩子 clean_username 对username字段进行校验 检测用户名唯一性 ValidationError 弹出异常 :return: 成功：用户名 失败：错误信息"""
<|body_0|>
def clean(self):
"""全局钩子... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RegisterForm:
"""用户注册校验 使用form组件 字段名称必须和数据库对应 re_password在数据库不存在，在存储数据前会删掉 RegexValidator forms中使用正则过滤"""
def clean_username(self):
"""局部钩子 clean_username 对username字段进行校验 检测用户名唯一性 ValidationError 弹出异常 :return: 成功：用户名 失败：错误信息"""
username = self.cleaned_data.get('username')
is_exist... | the_stack_v2_python_sparse | day21/homework/CMS/fault_reporting/forms.py | 214031230/Python21 | train | 0 |
e318c2c5c922960ab49634f1943513ce804a2302 | [
"delay = DelayFilter()\noriginal = delay(0)\nnorm = NormFilter()\nshift = ShiftSWFilter(window_size=2, strict_windows=False, cs=False)\nmean = MeanSWFilter(window_size=25, cs=False)\nstd = StdSWFilter(window_size=25, strict_windows=True)\ndtr = DecisionTreeRegressorSWFilter(window_size=100, strict_windows=True, ove... | <|body_start_0|>
delay = DelayFilter()
original = delay(0)
norm = NormFilter()
shift = ShiftSWFilter(window_size=2, strict_windows=False, cs=False)
mean = MeanSWFilter(window_size=25, cs=False)
std = StdSWFilter(window_size=25, strict_windows=True)
dtr = DecisionT... | ... | DtrEventSelector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DtrEventSelector:
"""..."""
def seq_filters():
""":return:"""
<|body_0|>
def filter_events(self, event_seq, **kwargs):
"""Should be implemented :param event_seq:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
delay = DelayFilter()
origi... | stack_v2_sparse_classes_10k_train_006901 | 4,290 | permissive | [
{
"docstring": ":return:",
"name": "seq_filters",
"signature": "def seq_filters()"
},
{
"docstring": "Should be implemented :param event_seq:",
"name": "filter_events",
"signature": "def filter_events(self, event_seq, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005864 | Implement the Python class `DtrEventSelector` described below.
Class description:
...
Method signatures and docstrings:
- def seq_filters(): :return:
- def filter_events(self, event_seq, **kwargs): Should be implemented :param event_seq: | Implement the Python class `DtrEventSelector` described below.
Class description:
...
Method signatures and docstrings:
- def seq_filters(): :return:
- def filter_events(self, event_seq, **kwargs): Should be implemented :param event_seq:
<|skeleton|>
class DtrEventSelector:
"""..."""
def seq_filters():
... | 617ff45c9c3c96bbd9a975aef15f1b2697282b9c | <|skeleton|>
class DtrEventSelector:
"""..."""
def seq_filters():
""":return:"""
<|body_0|>
def filter_events(self, event_seq, **kwargs):
"""Should be implemented :param event_seq:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DtrEventSelector:
"""..."""
def seq_filters():
""":return:"""
delay = DelayFilter()
original = delay(0)
norm = NormFilter()
shift = ShiftSWFilter(window_size=2, strict_windows=False, cs=False)
mean = MeanSWFilter(window_size=25, cs=False)
std = StdS... | the_stack_v2_python_sparse | shot_detector/selectors/event/dtr_event_selector.py | w495/python-video-shot-detector | train | 20 |
b978db0826b73b580f4d19c86880a25ec10a8417 | [
"from pages.regions.accordion import Accordion\nfrom pages.regions.treeaccordionitem import LegacyTreeAccordionItem\nreturn Accordion(self.testsetup, LegacyTreeAccordionItem)",
"self.click_on_catalog_item('All Catalog Items')\nself.get_element(*self._configuration_button_locator).click()\nself.get_element(*self._... | <|body_start_0|>
from pages.regions.accordion import Accordion
from pages.regions.treeaccordionitem import LegacyTreeAccordionItem
return Accordion(self.testsetup, LegacyTreeAccordionItem)
<|end_body_0|>
<|body_start_1|>
self.click_on_catalog_item('All Catalog Items')
self.get_e... | Catalog Item page | CatalogItems | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CatalogItems:
"""Catalog Item page"""
def accordion(self):
"""accordion"""
<|body_0|>
def add_new_catalog_item(self):
"""click on Configuration and then Add new catalog item btn"""
<|body_1|>
def add_new_catalog_bundle(self):
"""Click on Conf... | stack_v2_sparse_classes_10k_train_006902 | 11,585 | no_license | [
{
"docstring": "accordion",
"name": "accordion",
"signature": "def accordion(self)"
},
{
"docstring": "click on Configuration and then Add new catalog item btn",
"name": "add_new_catalog_item",
"signature": "def add_new_catalog_item(self)"
},
{
"docstring": "Click on Configuratio... | 6 | null | Implement the Python class `CatalogItems` described below.
Class description:
Catalog Item page
Method signatures and docstrings:
- def accordion(self): accordion
- def add_new_catalog_item(self): click on Configuration and then Add new catalog item btn
- def add_new_catalog_bundle(self): Click on Configuration and t... | Implement the Python class `CatalogItems` described below.
Class description:
Catalog Item page
Method signatures and docstrings:
- def accordion(self): accordion
- def add_new_catalog_item(self): click on Configuration and then Add new catalog item btn
- def add_new_catalog_bundle(self): Click on Configuration and t... | 51bb86fda7d897e90444a6a0380a5aa2c61be6ff | <|skeleton|>
class CatalogItems:
"""Catalog Item page"""
def accordion(self):
"""accordion"""
<|body_0|>
def add_new_catalog_item(self):
"""click on Configuration and then Add new catalog item btn"""
<|body_1|>
def add_new_catalog_bundle(self):
"""Click on Conf... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CatalogItems:
"""Catalog Item page"""
def accordion(self):
"""accordion"""
from pages.regions.accordion import Accordion
from pages.regions.treeaccordionitem import LegacyTreeAccordionItem
return Accordion(self.testsetup, LegacyTreeAccordionItem)
def add_new_catalog_i... | the_stack_v2_python_sparse | pages/services_subpages/catalog_subpages/catalog_items.py | sshveta/cfme_tests | train | 0 |
b72592d05f7acb19c1a272189dd6789d3f4d890a | [
"try:\n with open(yaml_file_path, 'r') as f:\n self.doc = yaml.load(f)\nexcept Exception as ex:\n message = 'Exception: An exception occured: {}'.format(ex)\n raise Exception(message)",
"param_value = self.doc[appliance][param]\nif param_value == '':\n message = 'Value is not updated for the pa... | <|body_start_0|>
try:
with open(yaml_file_path, 'r') as f:
self.doc = yaml.load(f)
except Exception as ex:
message = 'Exception: An exception occured: {}'.format(ex)
raise Exception(message)
<|end_body_0|>
<|body_start_1|>
param_value = self.d... | GetYamlValue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetYamlValue:
def __init__(self, yaml_file_path=yaml_path):
""":param yaml_file_path: Path of yaml file, Default will the config.yaml file"""
<|body_0|>
def get_config(self, appliance, param):
"""This function gives the yaml value corresponding to the parameter sampl... | stack_v2_sparse_classes_10k_train_006903 | 1,425 | no_license | [
{
"docstring": ":param yaml_file_path: Path of yaml file, Default will the config.yaml file",
"name": "__init__",
"signature": "def __init__(self, yaml_file_path=yaml_path)"
},
{
"docstring": "This function gives the yaml value corresponding to the parameter sample Yaml file xstream_details: xtm... | 2 | null | Implement the Python class `GetYamlValue` described below.
Class description:
Implement the GetYamlValue class.
Method signatures and docstrings:
- def __init__(self, yaml_file_path=yaml_path): :param yaml_file_path: Path of yaml file, Default will the config.yaml file
- def get_config(self, appliance, param): This f... | Implement the Python class `GetYamlValue` described below.
Class description:
Implement the GetYamlValue class.
Method signatures and docstrings:
- def __init__(self, yaml_file_path=yaml_path): :param yaml_file_path: Path of yaml file, Default will the config.yaml file
- def get_config(self, appliance, param): This f... | 93dd6d14ae4b0856aa7c6f059904cc1f13800e5f | <|skeleton|>
class GetYamlValue:
def __init__(self, yaml_file_path=yaml_path):
""":param yaml_file_path: Path of yaml file, Default will the config.yaml file"""
<|body_0|>
def get_config(self, appliance, param):
"""This function gives the yaml value corresponding to the parameter sampl... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GetYamlValue:
def __init__(self, yaml_file_path=yaml_path):
""":param yaml_file_path: Path of yaml file, Default will the config.yaml file"""
try:
with open(yaml_file_path, 'r') as f:
self.doc = yaml.load(f)
except Exception as ex:
message = 'Exc... | the_stack_v2_python_sparse | automation_framework/utils/GetYamlValue.py | vijaymaddukuri/python_repo | 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_10k_train_006904 | 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 | null | 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_10k | 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 |
4e839ba3808743ba8c8785079521bbfa02a0e34f | [
"data = {}\nid = request.GET.get('id', None)\ndetailed_requirement_id = request.GET.get('detailed_requirement_id', None)\noffering_course_id = request.GET.get('offering_course_id', None)\nfield_of_study_id = request.GET.get('field_of_study_id', None)\nif id is not None:\n data['id'] = id\nif detailed_requirement... | <|body_start_0|>
data = {}
id = request.GET.get('id', None)
detailed_requirement_id = request.GET.get('detailed_requirement_id', None)
offering_course_id = request.GET.get('offering_course_id', None)
field_of_study_id = request.GET.get('field_of_study_id', None)
if id is ... | 支撑课程view | IndicatorFactors | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndicatorFactors:
"""支撑课程view"""
def get(self, request):
"""查询支撑课程"""
<|body_0|>
def put(self, request):
"""修改支撑课程"""
<|body_1|>
def post(self, request):
"""增加支撑课程"""
<|body_2|>
def delete(self, request):
"""删除支撑课程"""
... | stack_v2_sparse_classes_10k_train_006905 | 15,061 | permissive | [
{
"docstring": "查询支撑课程",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "修改支撑课程",
"name": "put",
"signature": "def put(self, request)"
},
{
"docstring": "增加支撑课程",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除支... | 4 | stack_v2_sparse_classes_30k_val_000257 | Implement the Python class `IndicatorFactors` described below.
Class description:
支撑课程view
Method signatures and docstrings:
- def get(self, request): 查询支撑课程
- def put(self, request): 修改支撑课程
- def post(self, request): 增加支撑课程
- def delete(self, request): 删除支撑课程 | Implement the Python class `IndicatorFactors` described below.
Class description:
支撑课程view
Method signatures and docstrings:
- def get(self, request): 查询支撑课程
- def put(self, request): 修改支撑课程
- def post(self, request): 增加支撑课程
- def delete(self, request): 删除支撑课程
<|skeleton|>
class IndicatorFactors:
"""支撑课程view"""
... | 7aaa1be773718de1beb3ce0080edca7c4114b7ad | <|skeleton|>
class IndicatorFactors:
"""支撑课程view"""
def get(self, request):
"""查询支撑课程"""
<|body_0|>
def put(self, request):
"""修改支撑课程"""
<|body_1|>
def post(self, request):
"""增加支撑课程"""
<|body_2|>
def delete(self, request):
"""删除支撑课程"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IndicatorFactors:
"""支撑课程view"""
def get(self, request):
"""查询支撑课程"""
data = {}
id = request.GET.get('id', None)
detailed_requirement_id = request.GET.get('detailed_requirement_id', None)
offering_course_id = request.GET.get('offering_course_id', None)
fiel... | the_stack_v2_python_sparse | plan/views.py | MIXISAMA/MIS-backend | train | 0 |
24946af70bd19f4df06148cc31a255e1e471b47b | [
"if not kwargs.get('obj_ids'):\n obj_model = facade.get_route_map_entry_by_search(self.search)\n objects = obj_model['query_set']\n only_main_property = False\nelse:\n ids = kwargs.get('obj_ids').split(';')\n objects = facade.get_route_map_entry_by_ids(ids)\n only_main_property = True\n obj_mod... | <|body_start_0|>
if not kwargs.get('obj_ids'):
obj_model = facade.get_route_map_entry_by_search(self.search)
objects = obj_model['query_set']
only_main_property = False
else:
ids = kwargs.get('obj_ids').split(';')
objects = facade.get_route_map... | RouteMapEntryDBView | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RouteMapEntryDBView:
def get(self, request, *args, **kwargs):
"""Returns a list of RouteMapEntries by ids ou dict."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Create new RouteMapEntry."""
<|body_1|>
def put(self, request, *args, **kwargs):... | stack_v2_sparse_classes_10k_train_006906 | 9,414 | permissive | [
{
"docstring": "Returns a list of RouteMapEntries by ids ou dict.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Create new RouteMapEntry.",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
},
{
"docstring": "Upda... | 4 | null | Implement the Python class `RouteMapEntryDBView` described below.
Class description:
Implement the RouteMapEntryDBView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Returns a list of RouteMapEntries by ids ou dict.
- def post(self, request, *args, **kwargs): Create new RouteMapEn... | Implement the Python class `RouteMapEntryDBView` described below.
Class description:
Implement the RouteMapEntryDBView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Returns a list of RouteMapEntries by ids ou dict.
- def post(self, request, *args, **kwargs): Create new RouteMapEn... | eb27e1d977a1c4bb1fee8fb51b8d8050c64696d9 | <|skeleton|>
class RouteMapEntryDBView:
def get(self, request, *args, **kwargs):
"""Returns a list of RouteMapEntries by ids ou dict."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Create new RouteMapEntry."""
<|body_1|>
def put(self, request, *args, **kwargs):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RouteMapEntryDBView:
def get(self, request, *args, **kwargs):
"""Returns a list of RouteMapEntries by ids ou dict."""
if not kwargs.get('obj_ids'):
obj_model = facade.get_route_map_entry_by_search(self.search)
objects = obj_model['query_set']
only_main_prope... | the_stack_v2_python_sparse | networkapi/api_route_map/v4/views.py | globocom/GloboNetworkAPI | train | 86 | |
6e2d01a30ec210e96623e2cda8d11110f6e1dc1f | [
"n = len(A)\nMX = [-float('inf') for _ in range(n + 1)]\nMI = [float('inf') for _ in range(n + 1)]\nfor i in range(n):\n MX[i + 1] = max(M[i], A[i])\nfor i in range(n - 1, -1, -1):\n MI[i] = min(MI[i + 1], A[i])\nfor l in range(1, n + 1):\n if MX[l] <= MI[l]:\n return l\nraise",
"MX = [0 for _ in ... | <|body_start_0|>
n = len(A)
MX = [-float('inf') for _ in range(n + 1)]
MI = [float('inf') for _ in range(n + 1)]
for i in range(n):
MX[i + 1] = max(M[i], A[i])
for i in range(n - 1, -1, -1):
MI[i] = min(MI[i + 1], A[i])
for l in range(1, n + 1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def partitionDisjoint(self, A: List[int]) -> int:
"""max(left) <= min(right) similar to 2 in terms of keyboard stroke count"""
<|body_0|>
def partitionDisjoint_2(self, A: List[int]) -> int:
"""max(left) <= min(right)"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_006907 | 1,705 | no_license | [
{
"docstring": "max(left) <= min(right) similar to 2 in terms of keyboard stroke count",
"name": "partitionDisjoint",
"signature": "def partitionDisjoint(self, A: List[int]) -> int"
},
{
"docstring": "max(left) <= min(right)",
"name": "partitionDisjoint_2",
"signature": "def partitionDis... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def partitionDisjoint(self, A: List[int]) -> int: max(left) <= min(right) similar to 2 in terms of keyboard stroke count
- def partitionDisjoint_2(self, A: List[int]) -> int: max... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def partitionDisjoint(self, A: List[int]) -> int: max(left) <= min(right) similar to 2 in terms of keyboard stroke count
- def partitionDisjoint_2(self, A: List[int]) -> int: max... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution:
def partitionDisjoint(self, A: List[int]) -> int:
"""max(left) <= min(right) similar to 2 in terms of keyboard stroke count"""
<|body_0|>
def partitionDisjoint_2(self, A: List[int]) -> int:
"""max(left) <= min(right)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def partitionDisjoint(self, A: List[int]) -> int:
"""max(left) <= min(right) similar to 2 in terms of keyboard stroke count"""
n = len(A)
MX = [-float('inf') for _ in range(n + 1)]
MI = [float('inf') for _ in range(n + 1)]
for i in range(n):
MX[i +... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/915 Partition Array into Disjoint Intervals.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
3911f7185aac3929ed43dc52ff80c3b894a367ee | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.win32LobAppFileSystemRule'.casefold():\n ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | A base complex type to store the detection or requirement rule data for a Win32 LOB app. | Win32LobAppRule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Win32LobAppRule:
"""A base complex type to store the detection or requirement rule data for a Win32 LOB app."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Win32LobAppRule:
"""Creates a new instance of the appropriate class based on discriminator valu... | stack_v2_sparse_classes_10k_train_006908 | 4,926 | 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: Win32LobAppRule",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_val... | 3 | null | Implement the Python class `Win32LobAppRule` described below.
Class description:
A base complex type to store the detection or requirement rule data for a Win32 LOB app.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Win32LobAppRule: Creates a new inst... | Implement the Python class `Win32LobAppRule` described below.
Class description:
A base complex type to store the detection or requirement rule data for a Win32 LOB app.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Win32LobAppRule: Creates a new inst... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Win32LobAppRule:
"""A base complex type to store the detection or requirement rule data for a Win32 LOB app."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Win32LobAppRule:
"""Creates a new instance of the appropriate class based on discriminator valu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Win32LobAppRule:
"""A base complex type to store the detection or requirement rule data for a Win32 LOB app."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Win32LobAppRule:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse... | the_stack_v2_python_sparse | msgraph/generated/models/win32_lob_app_rule.py | microsoftgraph/msgraph-sdk-python | train | 135 |
0bc268e0959ebd52db661aadc09388190f61175c | [
"super(Linker_complex, self).__init__()\nself.config = config\nself.encoder = encoder\nself.entity_embeddings_real = nn.Embedding(self.config.entity_size, self.config.embedding_dim)\nself.entity_embeddings_img = nn.Embedding(self.config.entity_size, self.config.embedding_dim)\nif self.config.priors:\n self.char_... | <|body_start_0|>
super(Linker_complex, self).__init__()
self.config = config
self.encoder = encoder
self.entity_embeddings_real = nn.Embedding(self.config.entity_size, self.config.embedding_dim)
self.entity_embeddings_img = nn.Embedding(self.config.entity_size, self.config.embedd... | Linker_complex | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linker_complex:
def __init__(self, config, encoder):
""":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions"""
<|body_0|>
def forward(self, entity_candidates, mention_representation, sentence, char_sc... | stack_v2_sparse_classes_10k_train_006909 | 42,719 | permissive | [
{
"docstring": ":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions",
"name": "__init__",
"signature": "def __init__(self, config, encoder)"
},
{
"docstring": ":return: unnormalized log probabilities (logits) of gold enti... | 2 | stack_v2_sparse_classes_30k_train_004588 | Implement the Python class `Linker_complex` described below.
Class description:
Implement the Linker_complex class.
Method signatures and docstrings:
- def __init__(self, config, encoder): :param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions
- ... | Implement the Python class `Linker_complex` described below.
Class description:
Implement the Linker_complex class.
Method signatures and docstrings:
- def __init__(self, config, encoder): :param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions
- ... | 6a7dcd7d3756327c61ef949e5b4f6af6e2849187 | <|skeleton|>
class Linker_complex:
def __init__(self, config, encoder):
""":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions"""
<|body_0|>
def forward(self, entity_candidates, mention_representation, sentence, char_sc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Linker_complex:
def __init__(self, config, encoder):
""":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions"""
super(Linker_complex, self).__init__()
self.config = config
self.encoder = encoder
s... | the_stack_v2_python_sparse | typenet/src/model.py | dhruvdcoder/dl-with-constraints | train | 0 | |
24da3e2f5f2a4d1053868c84264d30811ad91d2b | [
"url = 'projects/%s/tags/%s' % (project_id, tag)\nresp, body = self.put(url, '{}')\nself.expected_success(201, resp.status)\nreturn rest_client.ResponseBody(resp, body)",
"url = 'projects/%s/tags' % project_id\nresp, body = self.get(url)\nself.expected_success(200, resp.status)\nbody = json.loads(body)\nreturn re... | <|body_start_0|>
url = 'projects/%s/tags/%s' % (project_id, tag)
resp, body = self.put(url, '{}')
self.expected_success(201, resp.status)
return rest_client.ResponseBody(resp, body)
<|end_body_0|>
<|body_start_1|>
url = 'projects/%s/tags' % project_id
resp, body = self.g... | ProjectTagsClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectTagsClient:
def update_project_tag(self, project_id, tag):
"""Updates the specified tag and adds it to the project's list of tags."""
<|body_0|>
def list_project_tags(self, project_id):
"""List tags for a project."""
<|body_1|>
def update_all_proj... | stack_v2_sparse_classes_10k_train_006910 | 3,220 | permissive | [
{
"docstring": "Updates the specified tag and adds it to the project's list of tags.",
"name": "update_project_tag",
"signature": "def update_project_tag(self, project_id, tag)"
},
{
"docstring": "List tags for a project.",
"name": "list_project_tags",
"signature": "def list_project_tags... | 6 | null | Implement the Python class `ProjectTagsClient` described below.
Class description:
Implement the ProjectTagsClient class.
Method signatures and docstrings:
- def update_project_tag(self, project_id, tag): Updates the specified tag and adds it to the project's list of tags.
- def list_project_tags(self, project_id): L... | Implement the Python class `ProjectTagsClient` described below.
Class description:
Implement the ProjectTagsClient class.
Method signatures and docstrings:
- def update_project_tag(self, project_id, tag): Updates the specified tag and adds it to the project's list of tags.
- def list_project_tags(self, project_id): L... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class ProjectTagsClient:
def update_project_tag(self, project_id, tag):
"""Updates the specified tag and adds it to the project's list of tags."""
<|body_0|>
def list_project_tags(self, project_id):
"""List tags for a project."""
<|body_1|>
def update_all_proj... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProjectTagsClient:
def update_project_tag(self, project_id, tag):
"""Updates the specified tag and adds it to the project's list of tags."""
url = 'projects/%s/tags/%s' % (project_id, tag)
resp, body = self.put(url, '{}')
self.expected_success(201, resp.status)
return r... | the_stack_v2_python_sparse | tempest/lib/services/identity/v3/project_tags_client.py | openstack/tempest | train | 270 | |
f6797c753535093d995b1fea07443c77cb3058f7 | [
"if input_type == 'f':\n file = open(path, 'r')\nelif input_type == 's':\n file = path\nelse:\n raise exceptions.BadInputError(f'invalid input type {input_type}')\npdl = yaml.safe_load(file)\nself.type_checks = {'typedef': self.validate_typedef, 'component': self.validate_component, 'graph': self.validate_... | <|body_start_0|>
if input_type == 'f':
file = open(path, 'r')
elif input_type == 's':
file = path
else:
raise exceptions.BadInputError(f'invalid input type {input_type}')
pdl = yaml.safe_load(file)
self.type_checks = {'typedef': self.validate_t... | Represents a single PDL file. | File | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class File:
"""Represents a single PDL file."""
def __init__(self, path, input_type='f'):
"""Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that th... | stack_v2_sparse_classes_10k_train_006911 | 5,874 | permissive | [
{
"docstring": "Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that the file's contents use, - body: the body of PDL. Parameters ---------- path: string path should cont... | 6 | stack_v2_sparse_classes_30k_train_003722 | Implement the Python class `File` described below.
Class description:
Represents a single PDL file.
Method signatures and docstrings:
- def __init__(self, path, input_type='f'): Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's... | Implement the Python class `File` described below.
Class description:
Represents a single PDL file.
Method signatures and docstrings:
- def __init__(self, path, input_type='f'): Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's... | 345e7d47efdac04c2c5f70d55f83bd77acdbb511 | <|skeleton|>
class File:
"""Represents a single PDL file."""
def __init__(self, path, input_type='f'):
"""Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class File:
"""Represents a single PDL file."""
def __init__(self, path, input_type='f'):
"""Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that the file's cont... | the_stack_v2_python_sparse | topside/pdl/file.py | roguextech/Waterloo-Rocketry-topside | train | 0 |
c02dc20e9e0c84b1eec4e24f2729b26e0afd166f | [
"logging.Handler.__init__(self)\nself.oqueue = out_queue\nself.session = None",
"try:\n e_inf = record.exc_info\n if e_inf:\n dummy = self.format(record)\n record.exc_info = None\n dummy\n record.handle = self.session.handle if self.session is not None else None\n if self.session ... | <|body_start_0|>
logging.Handler.__init__(self)
self.oqueue = out_queue
self.session = None
<|end_body_0|>
<|body_start_1|>
try:
e_inf = record.exc_info
if e_inf:
dummy = self.format(record)
record.exc_info = None
d... | Log handler that sends the log up the 'event pipe'. This is a rather novel solution that seems overlooked in documentation or exisiting code, try it! | IPCLogHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IPCLogHandler:
"""Log handler that sends the log up the 'event pipe'. This is a rather novel solution that seems overlooked in documentation or exisiting code, try it!"""
def __init__(self, out_queue):
"""Constructor method, requires multiprocessing.Pipe"""
<|body_0|>
de... | stack_v2_sparse_classes_10k_train_006912 | 2,168 | no_license | [
{
"docstring": "Constructor method, requires multiprocessing.Pipe",
"name": "__init__",
"signature": "def __init__(self, out_queue)"
},
{
"docstring": "emit log record via IPC output queue",
"name": "emit",
"signature": "def emit(self, record)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001826 | Implement the Python class `IPCLogHandler` described below.
Class description:
Log handler that sends the log up the 'event pipe'. This is a rather novel solution that seems overlooked in documentation or exisiting code, try it!
Method signatures and docstrings:
- def __init__(self, out_queue): Constructor method, re... | Implement the Python class `IPCLogHandler` described below.
Class description:
Log handler that sends the log up the 'event pipe'. This is a rather novel solution that seems overlooked in documentation or exisiting code, try it!
Method signatures and docstrings:
- def __init__(self, out_queue): Constructor method, re... | 7b03a35f12d2b7a10fa4709b09107935c6f14000 | <|skeleton|>
class IPCLogHandler:
"""Log handler that sends the log up the 'event pipe'. This is a rather novel solution that seems overlooked in documentation or exisiting code, try it!"""
def __init__(self, out_queue):
"""Constructor method, requires multiprocessing.Pipe"""
<|body_0|>
de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IPCLogHandler:
"""Log handler that sends the log up the 'event pipe'. This is a rather novel solution that seems overlooked in documentation or exisiting code, try it!"""
def __init__(self, out_queue):
"""Constructor method, requires multiprocessing.Pipe"""
logging.Handler.__init__(self)
... | the_stack_v2_python_sparse | bbs/ipc.py | jonny290/yos-x84 | train | 2 |
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_10k_train_006913 | 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 | null | 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_10k | 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 | |
c1fb96d281ff340126642b38e421cb45381803dd | [
"config = current_app.cea_config\ndashboards = cea.plots.read_dashboards(config, current_app.plot_cache)\nreturn dashboard_to_dict(dashboards[dashboard_index])",
"config = current_app.cea_config\ncea.plots.delete_dashboard(config, dashboard_index)\nreturn {'message': 'deleted dashboard'}",
"form = api.payload\n... | <|body_start_0|>
config = current_app.cea_config
dashboards = cea.plots.read_dashboards(config, current_app.plot_cache)
return dashboard_to_dict(dashboards[dashboard_index])
<|end_body_0|>
<|body_start_1|>
config = current_app.cea_config
cea.plots.delete_dashboard(config, dashbo... | Dashboard | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dashboard:
def get(self, dashboard_index):
"""Get Dashboard"""
<|body_0|>
def delete(self, dashboard_index):
"""Delete Dashboard"""
<|body_1|>
def patch(self, dashboard_index):
"""Update Dashboard properties"""
<|body_2|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_006914 | 9,106 | permissive | [
{
"docstring": "Get Dashboard",
"name": "get",
"signature": "def get(self, dashboard_index)"
},
{
"docstring": "Delete Dashboard",
"name": "delete",
"signature": "def delete(self, dashboard_index)"
},
{
"docstring": "Update Dashboard properties",
"name": "patch",
"signatu... | 3 | null | Implement the Python class `Dashboard` described below.
Class description:
Implement the Dashboard class.
Method signatures and docstrings:
- def get(self, dashboard_index): Get Dashboard
- def delete(self, dashboard_index): Delete Dashboard
- def patch(self, dashboard_index): Update Dashboard properties | Implement the Python class `Dashboard` described below.
Class description:
Implement the Dashboard class.
Method signatures and docstrings:
- def get(self, dashboard_index): Get Dashboard
- def delete(self, dashboard_index): Delete Dashboard
- def patch(self, dashboard_index): Update Dashboard properties
<|skeleton|... | b84bcefdfdfc2bc0e009b5284b74391a957995ac | <|skeleton|>
class Dashboard:
def get(self, dashboard_index):
"""Get Dashboard"""
<|body_0|>
def delete(self, dashboard_index):
"""Delete Dashboard"""
<|body_1|>
def patch(self, dashboard_index):
"""Update Dashboard properties"""
<|body_2|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Dashboard:
def get(self, dashboard_index):
"""Get Dashboard"""
config = current_app.cea_config
dashboards = cea.plots.read_dashboards(config, current_app.plot_cache)
return dashboard_to_dict(dashboards[dashboard_index])
def delete(self, dashboard_index):
"""Delete ... | the_stack_v2_python_sparse | cea/interfaces/dashboard/api/dashboard.py | architecture-building-systems/CityEnergyAnalyst | train | 166 | |
ca813c490d8b9b04f642140945bdb8fe6c8f1aeb | [
"content_type = ContentType.objects.get_for_model(instance.__class__)\nqueryset = super(RateManager, self).filter(content_type=content_type, object_id=instance.id)\nreturn queryset",
"try:\n my_avg = self.filter_by_model(instance).aggregate(Avg('rating'))\nexcept ZeroDivisionError:\n logging.error(error_han... | <|body_start_0|>
content_type = ContentType.objects.get_for_model(instance.__class__)
queryset = super(RateManager, self).filter(content_type=content_type, object_id=instance.id)
return queryset
<|end_body_0|>
<|body_start_1|>
try:
my_avg = self.filter_by_model(instance).agg... | RateManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RateManager:
def filter_by_model(self, instance):
"""filter kardane content bar assasse model"""
<|body_0|>
def avg_rate(self, instance, avg=0):
"""emtiaz dehi be post bar assasse rate entekhab shude (az 1 ta 5) taghsim bar tedad e user haey ke be in post emtiaz dada... | stack_v2_sparse_classes_10k_train_006915 | 2,877 | permissive | [
{
"docstring": "filter kardane content bar assasse model",
"name": "filter_by_model",
"signature": "def filter_by_model(self, instance)"
},
{
"docstring": "emtiaz dehi be post bar assasse rate entekhab shude (az 1 ta 5) taghsim bar tedad e user haey ke be in post emtiaz dadan",
"name": "avg_... | 2 | stack_v2_sparse_classes_30k_train_006760 | Implement the Python class `RateManager` described below.
Class description:
Implement the RateManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): filter kardane content bar assasse model
- def avg_rate(self, instance, avg=0): emtiaz dehi be post bar assasse rate entekhab shude (az... | Implement the Python class `RateManager` described below.
Class description:
Implement the RateManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): filter kardane content bar assasse model
- def avg_rate(self, instance, avg=0): emtiaz dehi be post bar assasse rate entekhab shude (az... | aef47922fdd6488550881ed9d42bf30a0d33a32a | <|skeleton|>
class RateManager:
def filter_by_model(self, instance):
"""filter kardane content bar assasse model"""
<|body_0|>
def avg_rate(self, instance, avg=0):
"""emtiaz dehi be post bar assasse rate entekhab shude (az 1 ta 5) taghsim bar tedad e user haey ke be in post emtiaz dada... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RateManager:
def filter_by_model(self, instance):
"""filter kardane content bar assasse model"""
content_type = ContentType.objects.get_for_model(instance.__class__)
queryset = super(RateManager, self).filter(content_type=content_type, object_id=instance.id)
return queryset
... | the_stack_v2_python_sparse | src/rates/models.py | m3h-D/Myinfoblog | train | 0 | |
6fadbdb7d59da050da98b6ebfaa1449f04b33e5f | [
"result = {'result': 'NG', 'error': ''}\ndata_json = request.get_json(force=True)\nflag, error = CtrlUserGroup().update_manager_group(data_json)\nif flag:\n result['result'] = 'OK'\nelse:\n result['error'] = error\nreturn result",
"result = {'result': 'NG', 'error': ''}\nflag, error = CtrlUserGroup().delete... | <|body_start_0|>
result = {'result': 'NG', 'error': ''}
data_json = request.get_json(force=True)
flag, error = CtrlUserGroup().update_manager_group(data_json)
if flag:
result['result'] = 'OK'
else:
result['error'] = error
return result
<|end_body_0... | 项目体制组的删除与更新 | ApiManagerGroup | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApiManagerGroup:
"""项目体制组的删除与更新"""
def post(self):
"""更新"""
<|body_0|>
def delete(self, proj_id, group_id, commit_user):
"""删除"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = {'result': 'NG', 'error': ''}
data_json = request.get... | stack_v2_sparse_classes_10k_train_006916 | 3,031 | no_license | [
{
"docstring": "更新",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "删除",
"name": "delete",
"signature": "def delete(self, proj_id, group_id, commit_user)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002976 | Implement the Python class `ApiManagerGroup` described below.
Class description:
项目体制组的删除与更新
Method signatures and docstrings:
- def post(self): 更新
- def delete(self, proj_id, group_id, commit_user): 删除 | Implement the Python class `ApiManagerGroup` described below.
Class description:
项目体制组的删除与更新
Method signatures and docstrings:
- def post(self): 更新
- def delete(self, proj_id, group_id, commit_user): 删除
<|skeleton|>
class ApiManagerGroup:
"""项目体制组的删除与更新"""
def post(self):
"""更新"""
<|body_0|>... | 64b31e7bdfcb8a4c95f0a8a607f0bcff576cec11 | <|skeleton|>
class ApiManagerGroup:
"""项目体制组的删除与更新"""
def post(self):
"""更新"""
<|body_0|>
def delete(self, proj_id, group_id, commit_user):
"""删除"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ApiManagerGroup:
"""项目体制组的删除与更新"""
def post(self):
"""更新"""
result = {'result': 'NG', 'error': ''}
data_json = request.get_json(force=True)
flag, error = CtrlUserGroup().update_manager_group(data_json)
if flag:
result['result'] = 'OK'
else:
... | the_stack_v2_python_sparse | koala/koala_server/app/api_1_0/api_user_group.py | lsn1183/web_project | train | 0 |
6d5ed1d2eb359dbfbee3cac333e9e97acd6e0ad6 | [
"self.height = max(availheight, self.CODEBARHEIGHT)\nself.border = border\nif len(subtype) != 1 or subtype not in ascii_uppercase + string_digits:\n raise ValueError(\"Invalid subtype '%s'\" % subtype)\nif not number and len(prefix) > 6 or not prefix.isalnum():\n raise ValueError(\"Invalid prefix '%s'\" % pre... | <|body_start_0|>
self.height = max(availheight, self.CODEBARHEIGHT)
self.border = border
if len(subtype) != 1 or subtype not in ascii_uppercase + string_digits:
raise ValueError("Invalid subtype '%s'" % subtype)
if not number and len(prefix) > 6 or not prefix.isalnum():
... | Base class for LTO labels. Specification taken from "IBM LTO Ultrium Cartridge Label Specification, Revision 3" available on May 14th 2008 from : http://www-1.ibm.com/support/docview.wss?rs=543&context=STCVQ6R&q1=ssg1*&uid=ssg1S7000429&loc=en_US&cs=utf-8&lang=en+en | BaseLTOLabel | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseLTOLabel:
"""Base class for LTO labels. Specification taken from "IBM LTO Ultrium Cartridge Label Specification, Revision 3" available on May 14th 2008 from : http://www-1.ibm.com/support/docview.wss?rs=543&context=STCVQ6R&q1=ssg1*&uid=ssg1S7000429&loc=en_US&cs=utf-8&lang=en+en"""
def __... | stack_v2_sparse_classes_10k_train_006917 | 7,377 | permissive | [
{
"docstring": "Initializes an LTO label. prefix : Up to six characters from [A-Z][0-9]. Defaults to \"\". number : Label's number or None. Defaults to None. subtype : LTO subtype string , e.g. \"1\" for LTO1. Defaults to \"1\". border : None, or the width of the label's border. Defaults to None. checksum : Boo... | 2 | stack_v2_sparse_classes_30k_train_002792 | Implement the Python class `BaseLTOLabel` described below.
Class description:
Base class for LTO labels. Specification taken from "IBM LTO Ultrium Cartridge Label Specification, Revision 3" available on May 14th 2008 from : http://www-1.ibm.com/support/docview.wss?rs=543&context=STCVQ6R&q1=ssg1*&uid=ssg1S7000429&loc=e... | Implement the Python class `BaseLTOLabel` described below.
Class description:
Base class for LTO labels. Specification taken from "IBM LTO Ultrium Cartridge Label Specification, Revision 3" available on May 14th 2008 from : http://www-1.ibm.com/support/docview.wss?rs=543&context=STCVQ6R&q1=ssg1*&uid=ssg1S7000429&loc=e... | c28aa50e2d6d3451b47e114094a86c03c87d4c50 | <|skeleton|>
class BaseLTOLabel:
"""Base class for LTO labels. Specification taken from "IBM LTO Ultrium Cartridge Label Specification, Revision 3" available on May 14th 2008 from : http://www-1.ibm.com/support/docview.wss?rs=543&context=STCVQ6R&q1=ssg1*&uid=ssg1S7000429&loc=en_US&cs=utf-8&lang=en+en"""
def __... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseLTOLabel:
"""Base class for LTO labels. Specification taken from "IBM LTO Ultrium Cartridge Label Specification, Revision 3" available on May 14th 2008 from : http://www-1.ibm.com/support/docview.wss?rs=543&context=STCVQ6R&q1=ssg1*&uid=ssg1S7000429&loc=en_US&cs=utf-8&lang=en+en"""
def __init__(self, ... | the_stack_v2_python_sparse | src/reportlab/graphics/barcode/lto.py | MrBitBucket/reportlab-mirror | train | 64 |
6fdcc72bc044065bd13d29e7e9e577c10cb1da1a | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Fido2KeyRestrictions()",
"from .fido2_restriction_enforcement_type import Fido2RestrictionEnforcementType\nfrom .fido2_restriction_enforcement_type import Fido2RestrictionEnforcementType\nfields: Dict[str, Callable[[Any], None]] = {'aa... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Fido2KeyRestrictions()
<|end_body_0|>
<|body_start_1|>
from .fido2_restriction_enforcement_type import Fido2RestrictionEnforcementType
from .fido2_restriction_enforcement_type import Fid... | Fido2KeyRestrictions | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fido2KeyRestrictions:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Fido2KeyRestrictions:
"""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 ... | stack_v2_sparse_classes_10k_train_006918 | 3,446 | 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: Fido2KeyRestrictions",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminato... | 3 | null | Implement the Python class `Fido2KeyRestrictions` described below.
Class description:
Implement the Fido2KeyRestrictions class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Fido2KeyRestrictions: Creates a new instance of the appropriate class based o... | Implement the Python class `Fido2KeyRestrictions` described below.
Class description:
Implement the Fido2KeyRestrictions class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Fido2KeyRestrictions: Creates a new instance of the appropriate class based o... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Fido2KeyRestrictions:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Fido2KeyRestrictions:
"""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 ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Fido2KeyRestrictions:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Fido2KeyRestrictions:
"""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... | the_stack_v2_python_sparse | msgraph/generated/models/fido2_key_restrictions.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
7c7aadf180f5945e5395d110ad6c651d698b224c | [
"if user is None:\n user = ctx.author\nwith utils.Embed(use_random_colour=True) as embed:\n embed.set_image(url=user.avatar_url)\nawait ctx.send(embed=embed)",
"data = {'channel_name': ctx.channel.name, 'category_name': ctx.channel.category.name, 'guild_name': ctx.guild.name, 'guild_icon_url': str(ctx.guild... | <|body_start_0|>
if user is None:
user = ctx.author
with utils.Embed(use_random_colour=True) as embed:
embed.set_image(url=user.avatar_url)
await ctx.send(embed=embed)
<|end_body_0|>
<|body_start_1|>
data = {'channel_name': ctx.channel.name, 'category_name': ctx.... | UserInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserInfo:
async def avatar(self, ctx: utils.Context, user: discord.User=None):
"""Shows you the avatar of a given user"""
<|body_0|>
async def createlog(self, ctx: utils.Context, amount: int=100):
"""Create a log of chat"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_10k_train_006919 | 2,686 | no_license | [
{
"docstring": "Shows you the avatar of a given user",
"name": "avatar",
"signature": "async def avatar(self, ctx: utils.Context, user: discord.User=None)"
},
{
"docstring": "Create a log of chat",
"name": "createlog",
"signature": "async def createlog(self, ctx: utils.Context, amount: i... | 2 | stack_v2_sparse_classes_30k_train_005500 | Implement the Python class `UserInfo` described below.
Class description:
Implement the UserInfo class.
Method signatures and docstrings:
- async def avatar(self, ctx: utils.Context, user: discord.User=None): Shows you the avatar of a given user
- async def createlog(self, ctx: utils.Context, amount: int=100): Create... | Implement the Python class `UserInfo` described below.
Class description:
Implement the UserInfo class.
Method signatures and docstrings:
- async def avatar(self, ctx: utils.Context, user: discord.User=None): Shows you the avatar of a given user
- async def createlog(self, ctx: utils.Context, amount: int=100): Create... | 454a21afb33db5acc06e939caec8e545d762142e | <|skeleton|>
class UserInfo:
async def avatar(self, ctx: utils.Context, user: discord.User=None):
"""Shows you the avatar of a given user"""
<|body_0|>
async def createlog(self, ctx: utils.Context, amount: int=100):
"""Create a log of chat"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserInfo:
async def avatar(self, ctx: utils.Context, user: discord.User=None):
"""Shows you the avatar of a given user"""
if user is None:
user = ctx.author
with utils.Embed(use_random_colour=True) as embed:
embed.set_image(url=user.avatar_url)
await ctx... | the_stack_v2_python_sparse | cogs/user_info.py | fadedmax/Apple.Py | train | 0 | |
f9e05cc1bbfbe611d3785949ff87568079704d9a | [
"self.hass = hass\nself.loaded: dict[str, set[str]] = {}\nself.cache: dict[str, dict[str, dict[str, Any]]] = {}",
"components_to_load = components - self.loaded.setdefault(language, set())\nif components_to_load:\n await self._async_load(language, components_to_load)\ncached = self.cache.get(language, {})\nret... | <|body_start_0|>
self.hass = hass
self.loaded: dict[str, set[str]] = {}
self.cache: dict[str, dict[str, dict[str, Any]]] = {}
<|end_body_0|>
<|body_start_1|>
components_to_load = components - self.loaded.setdefault(language, set())
if components_to_load:
await self._... | Cache for flattened translations. | _TranslationCache | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _TranslationCache:
"""Cache for flattened translations."""
def __init__(self, hass: HomeAssistant) -> None:
"""Initialize the cache."""
<|body_0|>
async def async_fetch(self, language: str, category: str, components: set[str]) -> list[dict[str, dict[str, Any]]]:
... | stack_v2_sparse_classes_10k_train_006920 | 10,520 | permissive | [
{
"docstring": "Initialize the cache.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant) -> None"
},
{
"docstring": "Load resources into the cache.",
"name": "async_fetch",
"signature": "async def async_fetch(self, language: str, category: str, components: set[st... | 4 | null | Implement the Python class `_TranslationCache` described below.
Class description:
Cache for flattened translations.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant) -> None: Initialize the cache.
- async def async_fetch(self, language: str, category: str, components: set[str]) -> list[dict... | Implement the Python class `_TranslationCache` described below.
Class description:
Cache for flattened translations.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant) -> None: Initialize the cache.
- async def async_fetch(self, language: str, category: str, components: set[str]) -> list[dict... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class _TranslationCache:
"""Cache for flattened translations."""
def __init__(self, hass: HomeAssistant) -> None:
"""Initialize the cache."""
<|body_0|>
async def async_fetch(self, language: str, category: str, components: set[str]) -> list[dict[str, dict[str, Any]]]:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _TranslationCache:
"""Cache for flattened translations."""
def __init__(self, hass: HomeAssistant) -> None:
"""Initialize the cache."""
self.hass = hass
self.loaded: dict[str, set[str]] = {}
self.cache: dict[str, dict[str, dict[str, Any]]] = {}
async def async_fetch(s... | the_stack_v2_python_sparse | homeassistant/helpers/translation.py | home-assistant/core | train | 35,501 |
3ce597e3152c1182e3141e2370e04f1e61f2f2ad | [
"super(SelfAttention, self).__init__(options, is_training)\nif not isinstance(options, graph_network_pb2.SelfAttention):\n raise ValueError('Options has to be an SelfAttention proto.')\nself.add_bi_directional_edges = options.add_bi_directional_edges\nself.add_self_loop_edges = options.add_self_loop_edges",
"n... | <|body_start_0|>
super(SelfAttention, self).__init__(options, is_training)
if not isinstance(options, graph_network_pb2.SelfAttention):
raise ValueError('Options has to be an SelfAttention proto.')
self.add_bi_directional_edges = options.add_bi_directional_edges
self.add_self... | Self attention model using a RNN cell. | SelfAttention | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
"""Self attention model using a RNN cell."""
def __init__(self, options, is_training=False):
"""Initializes the graph network. Args: options: proto to store the configs. is_training: if True, build the training graph."""
<|body_0|>
def _build_graph(self, g... | stack_v2_sparse_classes_10k_train_006921 | 18,418 | permissive | [
{
"docstring": "Initializes the graph network. Args: options: proto to store the configs. is_training: if True, build the training graph.",
"name": "__init__",
"signature": "def __init__(self, options, is_training=False)"
},
{
"docstring": "Builds graph network. Args: graphs_tuple: A GraphTuple ... | 2 | stack_v2_sparse_classes_30k_train_001694 | Implement the Python class `SelfAttention` described below.
Class description:
Self attention model using a RNN cell.
Method signatures and docstrings:
- def __init__(self, options, is_training=False): Initializes the graph network. Args: options: proto to store the configs. is_training: if True, build the training g... | Implement the Python class `SelfAttention` described below.
Class description:
Self attention model using a RNN cell.
Method signatures and docstrings:
- def __init__(self, options, is_training=False): Initializes the graph network. Args: options: proto to store the configs. is_training: if True, build the training g... | 4d20dadffe7584ac2c7f26419960512380b8d06e | <|skeleton|>
class SelfAttention:
"""Self attention model using a RNN cell."""
def __init__(self, options, is_training=False):
"""Initializes the graph network. Args: options: proto to store the configs. is_training: if True, build the training graph."""
<|body_0|>
def _build_graph(self, g... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SelfAttention:
"""Self attention model using a RNN cell."""
def __init__(self, options, is_training=False):
"""Initializes the graph network. Args: options: proto to store the configs. is_training: if True, build the training graph."""
super(SelfAttention, self).__init__(options, is_train... | the_stack_v2_python_sparse | modeling/modules/graph_networks.py | yekeren/WSSGG | train | 40 |
e9ee9f9afcb5ec4266e57963e3065a2b9d2cf24e | [
"self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')\nself.n_win = hyper_parameters['model'].get('n_win', 3)\nsuper().__init__(hyper_parameters)",
"super().create_model(hyper_parameters)\nembedding = self.word_embedding.output\n\ndef win_mean(x):\n res_list = []\n for i in range(self.len_... | <|body_start_0|>
self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')
self.n_win = hyper_parameters['model'].get('n_win', 3)
super().__init__(hyper_parameters)
<|end_body_0|>
<|body_start_1|>
super().create_model(hyper_parameters)
embedding = self.word_embeddin... | SWEMGraph | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_10k_train_006922 | 2,341 | permissive | [
{
"docstring": "初始化 :param hyper_parameters: json，超参",
"name": "__init__",
"signature": "def __init__(self, hyper_parameters)"
},
{
"docstring": "构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl",
"name": "create_model",
"signature": "def create_mod... | 2 | stack_v2_sparse_classes_30k_train_004606 | Implement the Python class `SWEMGraph` described below.
Class description:
Implement the SWEMGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper parameters of ... | Implement the Python class `SWEMGraph` described below.
Class description:
Implement the SWEMGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper parameters of ... | 640e3f44f90d9d8046546f7e1a93a29ebe5c8d30 | <|skeleton|>
class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')
self.n_win = hyper_parameters['model'].get('n_win', 3)
super().__init__(hyper_parameters)
def create_model(sel... | the_stack_v2_python_sparse | keras_textclassification/m15_SWEM/graph.py | wzjames/Keras-TextClassification | train | 1 | |
835296b8bf555f955db865bc87f64328015dced8 | [
"super(TransformerEncoderLayer, self).__init__()\nself.layer_norm = nn.LayerNorm(size, eps=1e-06)\nself.src_src_att = MultiHeadedAttention(num_heads, size, dropout=dropout)\nself.feed_forward = PositionwiseFeedForward(input_size=size, ff_size=ff_size, dropout=dropout)\nself.dropout = nn.Dropout(dropout)\nself.size ... | <|body_start_0|>
super(TransformerEncoderLayer, self).__init__()
self.layer_norm = nn.LayerNorm(size, eps=1e-06)
self.src_src_att = MultiHeadedAttention(num_heads, size, dropout=dropout)
self.feed_forward = PositionwiseFeedForward(input_size=size, ff_size=ff_size, dropout=dropout)
... | One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer. | TransformerEncoderLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerEncoderLayer:
"""One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer."""
def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1):
"""A single Transformer layer. :param size: :param ff_size: :p... | stack_v2_sparse_classes_10k_train_006923 | 6,117 | no_license | [
{
"docstring": "A single Transformer layer. :param size: :param ff_size: :param num_heads: :param dropout:",
"name": "__init__",
"signature": "def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1)"
},
{
"docstring": "Forward pass for a single transformer encoder l... | 2 | stack_v2_sparse_classes_30k_train_004164 | Implement the Python class `TransformerEncoderLayer` described below.
Class description:
One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer.
Method signatures and docstrings:
- def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1): A ... | Implement the Python class `TransformerEncoderLayer` described below.
Class description:
One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer.
Method signatures and docstrings:
- def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1): A ... | e213665be8d3820fa2fc0aa9afe9949fd2e3d488 | <|skeleton|>
class TransformerEncoderLayer:
"""One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer."""
def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1):
"""A single Transformer layer. :param size: :param ff_size: :p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TransformerEncoderLayer:
"""One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer."""
def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1):
"""A single Transformer layer. :param size: :param ff_size: :param num_head... | the_stack_v2_python_sparse | modules/transformer_layers.py | zqp111/transformer_ar | train | 1 |
ef8495f4415279d10c485d25a04cdbe32618085a | [
"if threshold is None:\n threshold = self._threshold\nif self._classifier is not None:\n top_matches = min(top_matches, self._matcher_tup.length - 1)\n dists, inds = self._classifier.search(np.array(emb).astype('float32'), k=top_matches)\n dists = np.squeeze(dists).tolist()\n inds = np.squeeze(inds).... | <|body_start_0|>
if threshold is None:
threshold = self._threshold
if self._classifier is not None:
top_matches = min(top_matches, self._matcher_tup.length - 1)
dists, inds = self._classifier.search(np.array(emb).astype('float32'), k=top_matches)
dists = n... | Classify face id using Faiss | FaissMatcher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaissMatcher:
"""Classify face id using Faiss"""
def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True):
"""See superclass doc"""
<|body_0|>
def fit(self, embs, labels):
"""Fit current matc... | stack_v2_sparse_classes_10k_train_006924 | 16,051 | no_license | [
{
"docstring": "See superclass doc",
"name": "match",
"signature": "def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True)"
},
{
"docstring": "Fit current matcher to new embs and labels :param embs: list of embs :param lab... | 3 | stack_v2_sparse_classes_30k_train_002495 | Implement the Python class `FaissMatcher` described below.
Class description:
Classify face id using Faiss
Method signatures and docstrings:
- def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True): See superclass doc
- def fit(self, embs, labe... | Implement the Python class `FaissMatcher` described below.
Class description:
Classify face id using Faiss
Method signatures and docstrings:
- def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True): See superclass doc
- def fit(self, embs, labe... | 0f97af4e110b0e8de8d1b9f18fcd3f69c69b54cc | <|skeleton|>
class FaissMatcher:
"""Classify face id using Faiss"""
def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True):
"""See superclass doc"""
<|body_0|>
def fit(self, embs, labels):
"""Fit current matc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FaissMatcher:
"""Classify face id using Faiss"""
def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True):
"""See superclass doc"""
if threshold is None:
threshold = self._threshold
if self._classi... | the_stack_v2_python_sparse | src/matcher.py | duongle98/Face-Rec | train | 1 |
1a24651b2c711492f6dd3e6a6596b57059001220 | [
"self.leads, self.times, count = ([], times, {})\nlead = -1\nfor p, t in zip(persons, times):\n count[p] = count.get(p, 0) + 1\n if count.get(lead, 0) <= count[p]:\n lead = p\n self.leads.append(lead)",
"l, r = (0, len(self.times) - 1)\nwhile l <= r:\n mid = (l + r) // 2\n if self.times[mid]... | <|body_start_0|>
self.leads, self.times, count = ([], times, {})
lead = -1
for p, t in zip(persons, times):
count[p] = count.get(p, 0) + 1
if count.get(lead, 0) <= count[p]:
lead = p
self.leads.append(lead)
<|end_body_0|>
<|body_start_1|>
... | TopVotedCandidate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.leads, self.times, count = ([], ... | stack_v2_sparse_classes_10k_train_006925 | 1,680 | no_license | [
{
"docstring": ":type persons: List[int] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, persons, times)"
},
{
"docstring": ":type t: int :rtype: int",
"name": "q",
"signature": "def q(self, t)"
}
] | 2 | null | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int | Implement the Python class `TopVotedCandidate` described below.
Class description:
Implement the TopVotedCandidate class.
Method signatures and docstrings:
- def __init__(self, persons, times): :type persons: List[int] :type times: List[int]
- def q(self, t): :type t: int :rtype: int
<|skeleton|>
class TopVotedCandi... | 035ef08434fa1ca781a6fb2f9eed3538b7d20c02 | <|skeleton|>
class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
<|body_0|>
def q(self, t):
""":type t: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TopVotedCandidate:
def __init__(self, persons, times):
""":type persons: List[int] :type times: List[int]"""
self.leads, self.times, count = ([], times, {})
lead = -1
for p, t in zip(persons, times):
count[p] = count.get(p, 0) + 1
if count.get(lead, 0) <... | the_stack_v2_python_sparse | leetcode_python/Binary_Search/online-election.py | yennanliu/CS_basics | train | 64 | |
feb813fbd495df89816e1555c0653a3a62f6879c | [
"userBag = hallitem.itemSystem.loadUserAssets(self.userId).getUserBag()\nitemPermanent = userBag.getItemByKindId(config.PERMANENT_MONTH_CARD_KINDID)\nitem = userBag.getItemByKindId(config.MONTH_CARD_KINDID)\ngiftList = []\nfor giftId in self.giftListConf:\n giftConf = config.getGiftConf(self.clientId, giftId)\n ... | <|body_start_0|>
userBag = hallitem.itemSystem.loadUserAssets(self.userId).getUserBag()
itemPermanent = userBag.getItemByKindId(config.PERMANENT_MONTH_CARD_KINDID)
item = userBag.getItemByKindId(config.MONTH_CARD_KINDID)
giftList = []
for giftId in self.giftListConf:
... | 月卡礼包 | MonthCardGift | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MonthCardGift:
"""月卡礼包"""
def getCurrentGiftConf(self):
"""获取当前可显示礼包的配置"""
<|body_0|>
def getGiftInfo(self):
"""获取礼包信息"""
<|body_1|>
def addGiftData(self, giftId):
"""使礼包变为可领取状态并添加礼包数据"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_10k_train_006926 | 26,749 | no_license | [
{
"docstring": "获取当前可显示礼包的配置",
"name": "getCurrentGiftConf",
"signature": "def getCurrentGiftConf(self)"
},
{
"docstring": "获取礼包信息",
"name": "getGiftInfo",
"signature": "def getGiftInfo(self)"
},
{
"docstring": "使礼包变为可领取状态并添加礼包数据",
"name": "addGiftData",
"signature": "def... | 3 | stack_v2_sparse_classes_30k_train_005071 | Implement the Python class `MonthCardGift` described below.
Class description:
月卡礼包
Method signatures and docstrings:
- def getCurrentGiftConf(self): 获取当前可显示礼包的配置
- def getGiftInfo(self): 获取礼包信息
- def addGiftData(self, giftId): 使礼包变为可领取状态并添加礼包数据 | Implement the Python class `MonthCardGift` described below.
Class description:
月卡礼包
Method signatures and docstrings:
- def getCurrentGiftConf(self): 获取当前可显示礼包的配置
- def getGiftInfo(self): 获取礼包信息
- def addGiftData(self, giftId): 使礼包变为可领取状态并添加礼包数据
<|skeleton|>
class MonthCardGift:
"""月卡礼包"""
def getCurrentGif... | fa1591863985a418fd361eb6dac36d1301bc1231 | <|skeleton|>
class MonthCardGift:
"""月卡礼包"""
def getCurrentGiftConf(self):
"""获取当前可显示礼包的配置"""
<|body_0|>
def getGiftInfo(self):
"""获取礼包信息"""
<|body_1|>
def addGiftData(self, giftId):
"""使礼包变为可领取状态并添加礼包数据"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MonthCardGift:
"""月卡礼包"""
def getCurrentGiftConf(self):
"""获取当前可显示礼包的配置"""
userBag = hallitem.itemSystem.loadUserAssets(self.userId).getUserBag()
itemPermanent = userBag.getItemByKindId(config.PERMANENT_MONTH_CARD_KINDID)
item = userBag.getItemByKindId(config.MONTH_CARD_KI... | the_stack_v2_python_sparse | learn_tu_you/wx_superboss/trunk/hall37-newfish/src/newfish/entity/gift/gift_system.py | isoundy000/learn_python | train | 0 |
f076b38a31c15a6ce54a7ff1c79162ccfe17464d | [
"x_values = []\ny_values = []\nfor i, row in enumerate(grid):\n for j, val in enumerate(row):\n if val == 1:\n x_values.append(i)\n y_values.append(j)\nx_values.sort()\ny_values.sort()\nif x_values:\n return self.get_min_dist(x_values) + self.get_min_dist(y_values)\nelse:\n ret... | <|body_start_0|>
x_values = []
y_values = []
for i, row in enumerate(grid):
for j, val in enumerate(row):
if val == 1:
x_values.append(i)
y_values.append(j)
x_values.sort()
y_values.sort()
if x_values:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minTotalDistance(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def get_min_dist(self, arr):
"""https://en.wikipedia.org/wiki/Median_absolute_deviation."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
x_values = ... | stack_v2_sparse_classes_10k_train_006927 | 1,717 | no_license | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minTotalDistance",
"signature": "def minTotalDistance(self, grid)"
},
{
"docstring": "https://en.wikipedia.org/wiki/Median_absolute_deviation.",
"name": "get_min_dist",
"signature": "def get_min_dist(self, arr)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minTotalDistance(self, grid): :type grid: List[List[int]] :rtype: int
- def get_min_dist(self, arr): https://en.wikipedia.org/wiki/Median_absolute_deviation. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minTotalDistance(self, grid): :type grid: List[List[int]] :rtype: int
- def get_min_dist(self, arr): https://en.wikipedia.org/wiki/Median_absolute_deviation.
<|skeleton|>
cl... | 33c623f226981942780751554f0593f2c71cf458 | <|skeleton|>
class Solution:
def minTotalDistance(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def get_min_dist(self, arr):
"""https://en.wikipedia.org/wiki/Median_absolute_deviation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def minTotalDistance(self, grid):
""":type grid: List[List[int]] :rtype: int"""
x_values = []
y_values = []
for i, row in enumerate(grid):
for j, val in enumerate(row):
if val == 1:
x_values.append(i)
... | the_stack_v2_python_sparse | math/leetcode_Best_Meeting_Point.py | monkeylyf/interviewjam | train | 59 | |
f71fb29799963828121804cc9c7f55e535a96040 | [
"for i in range(1, len(nums)):\n nums[i] += nums[i - 1]\nself.nums = nums",
"if i == 0:\n return self.nums[j]\nreturn self.nums[j] - self.nums[i - 1]"
] | <|body_start_0|>
for i in range(1, len(nums)):
nums[i] += nums[i - 1]
self.nums = nums
<|end_body_0|>
<|body_start_1|>
if i == 0:
return self.nums[j]
return self.nums[j] - self.nums[i - 1]
<|end_body_1|>
| NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for i in range(1, len(nums)):
nums[i] += nums[i... | stack_v2_sparse_classes_10k_train_006928 | 1,602 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type j: int :rtype: int",
"name": "sumRange",
"signature": "def sumRange(self, i, j)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000192 | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def sumRange(self, i, j): :type i: int :type j: int :rtype: int | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def sumRange(self, i, j): :type i: int :type j: int :rtype: int
<|skeleton|>
class NumArray:
def __init__(self, nums):
... | c53264340a71305dd6c715b4408b5dec408ef2cc | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
for i in range(1, len(nums)):
nums[i] += nums[i - 1]
self.nums = nums
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
if i == 0:
return self.nums[j]
... | the_stack_v2_python_sparse | range-sum-query-immutable.py | seattlegirl/leetcode | train | 0 | |
e7a4d250251990927c740af6e38f019b72b7430e | [
"if self.doctype:\n yield '<!doctype html{}>'.format(self.doctypes[self.doctype])\nyield from super().header()\nyield '<html>'\nreturn",
"if isinstance(document, str):\n yield document\n return\nif isinstance(document, Exception):\n yield str(document)\n return\nyield from super().body(document=doc... | <|body_start_0|>
if self.doctype:
yield '<!doctype html{}>'.format(self.doctypes[self.doctype])
yield from super().header()
yield '<html>'
return
<|end_body_0|>
<|body_start_1|>
if isinstance(document, str):
yield document
return
if is... | Support for HTML | HTML | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTML:
"""Support for HTML"""
def header(self):
"""Layout the {document} using my stationery for the header"""
<|body_0|>
def body(self, document=(), **kwds):
"""The body of the document"""
<|body_1|>
def footer(self):
"""Layout the {document}... | stack_v2_sparse_classes_10k_train_006929 | 2,137 | permissive | [
{
"docstring": "Layout the {document} using my stationery for the header",
"name": "header",
"signature": "def header(self)"
},
{
"docstring": "The body of the document",
"name": "body",
"signature": "def body(self, document=(), **kwds)"
},
{
"docstring": "Layout the {document} u... | 3 | null | Implement the Python class `HTML` described below.
Class description:
Support for HTML
Method signatures and docstrings:
- def header(self): Layout the {document} using my stationery for the header
- def body(self, document=(), **kwds): The body of the document
- def footer(self): Layout the {document} using my stati... | Implement the Python class `HTML` described below.
Class description:
Support for HTML
Method signatures and docstrings:
- def header(self): Layout the {document} using my stationery for the header
- def body(self, document=(), **kwds): The body of the document
- def footer(self): Layout the {document} using my stati... | d741c44ffb3e9e1f726bf492202ac8738bb4aa1c | <|skeleton|>
class HTML:
"""Support for HTML"""
def header(self):
"""Layout the {document} using my stationery for the header"""
<|body_0|>
def body(self, document=(), **kwds):
"""The body of the document"""
<|body_1|>
def footer(self):
"""Layout the {document}... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HTML:
"""Support for HTML"""
def header(self):
"""Layout the {document} using my stationery for the header"""
if self.doctype:
yield '<!doctype html{}>'.format(self.doctypes[self.doctype])
yield from super().header()
yield '<html>'
return
def body(... | the_stack_v2_python_sparse | packages/pyre/weaver/HTML.py | pyre/pyre | train | 27 |
40bf947af3f03c23acc7fc10efb7893380ce96a9 | [
"owner_id = request.manager.id\nexsign = app_models.exSign.objects(owner_id=owner_id)\nif exsign.count() > 0:\n exsign = exsign[0]\n is_create_new_data = False\n project_id = 'new_app:exsign:%s' % exsign.related_page_id\nelse:\n exsign = None\n is_create_new_data = True\n project_id = 'new_app:exs... | <|body_start_0|>
owner_id = request.manager.id
exsign = app_models.exSign.objects(owner_id=owner_id)
if exsign.count() > 0:
exsign = exsign[0]
is_create_new_data = False
project_id = 'new_app:exsign:%s' % exsign.related_page_id
else:
exsign... | exSign | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class exSign:
def get(request):
"""响应GET"""
<|body_0|>
def api_put(request):
"""响应PUT"""
<|body_1|>
def api_post(request):
"""响应POST"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
owner_id = request.manager.id
exsign = app_mo... | stack_v2_sparse_classes_10k_train_006930 | 3,317 | no_license | [
{
"docstring": "响应GET",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "响应PUT",
"name": "api_put",
"signature": "def api_put(request)"
},
{
"docstring": "响应POST",
"name": "api_post",
"signature": "def api_post(request)"
}
] | 3 | null | Implement the Python class `exSign` described below.
Class description:
Implement the exSign class.
Method signatures and docstrings:
- def get(request): 响应GET
- def api_put(request): 响应PUT
- def api_post(request): 响应POST | Implement the Python class `exSign` described below.
Class description:
Implement the exSign class.
Method signatures and docstrings:
- def get(request): 响应GET
- def api_put(request): 响应PUT
- def api_post(request): 响应POST
<|skeleton|>
class exSign:
def get(request):
"""响应GET"""
<|body_0|>
d... | 8b2f7befe92841bcc35e0e60cac5958ef3f3af54 | <|skeleton|>
class exSign:
def get(request):
"""响应GET"""
<|body_0|>
def api_put(request):
"""响应PUT"""
<|body_1|>
def api_post(request):
"""响应POST"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class exSign:
def get(request):
"""响应GET"""
owner_id = request.manager.id
exsign = app_models.exSign.objects(owner_id=owner_id)
if exsign.count() > 0:
exsign = exsign[0]
is_create_new_data = False
project_id = 'new_app:exsign:%s' % exsign.related_p... | the_stack_v2_python_sparse | weapp/apps/customerized_apps/exsign/exsign.py | chengdg/weizoom | train | 1 | |
e88f654ea304df2031b12a019ec4815fc6c65348 | [
"super(GreedyPCTRAgent, self).__init__(action_space)\nself._choice_model = choice_model\nself._belief_state = belief_state",
"del reward\ndoc_obs = observation['doc']\nself._choice_model.score_documents(self._belief_state, doc_obs.values())\nslate = self.findBestDocuments(self._choice_model.scores)\nlogging.debug... | <|body_start_0|>
super(GreedyPCTRAgent, self).__init__(action_space)
self._choice_model = choice_model
self._belief_state = belief_state
<|end_body_0|>
<|body_start_1|>
del reward
doc_obs = observation['doc']
self._choice_model.score_documents(self._belief_state, doc_obs... | An agent that recommends slates with the highest pCTR items. This agent assumes knowledge of the true underlying choice model. Note that this implicitly means it receives observations of the true user and document states. This agent myopically creates slates with items that have the highest probability of being clicked... | GreedyPCTRAgent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GreedyPCTRAgent:
"""An agent that recommends slates with the highest pCTR items. This agent assumes knowledge of the true underlying choice model. Note that this implicitly means it receives observations of the true user and document states. This agent myopically creates slates with items that ha... | stack_v2_sparse_classes_10k_train_006931 | 3,737 | permissive | [
{
"docstring": "Initializes a new greedy pCTR agent. Args: action_space: A gym.spaces object that specifies the format of actions belief_state: An instantiation of AbstractUserState assumed by the agent choice_model: An instantiation of AbstractChoiceModel assumed by the agent Default to a multinomial logit cho... | 3 | stack_v2_sparse_classes_30k_train_000001 | Implement the Python class `GreedyPCTRAgent` described below.
Class description:
An agent that recommends slates with the highest pCTR items. This agent assumes knowledge of the true underlying choice model. Note that this implicitly means it receives observations of the true user and document states. This agent myopi... | Implement the Python class `GreedyPCTRAgent` described below.
Class description:
An agent that recommends slates with the highest pCTR items. This agent assumes knowledge of the true underlying choice model. Note that this implicitly means it receives observations of the true user and document states. This agent myopi... | 63fcacb177a029196abe57910bde88f737d5cca0 | <|skeleton|>
class GreedyPCTRAgent:
"""An agent that recommends slates with the highest pCTR items. This agent assumes knowledge of the true underlying choice model. Note that this implicitly means it receives observations of the true user and document states. This agent myopically creates slates with items that ha... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GreedyPCTRAgent:
"""An agent that recommends slates with the highest pCTR items. This agent assumes knowledge of the true underlying choice model. Note that this implicitly means it receives observations of the true user and document states. This agent myopically creates slates with items that have the highes... | the_stack_v2_python_sparse | recsim/agents/greedy_pctr_agent.py | kittipatv/recsim-no-tf | train | 1 |
912b6eb073c8bb0b49a0df46e7999a3f8716df9f | [
"eps_space = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nd_space = [100, 1000, 10000]\nfor eps in eps_space:\n for d in d_space:\n gamma, _ = privunit.find_best_gamma(d, eps)\n self.assertLessEqual(0, gamma)\n self.assertLessEqual(gamma, 1)\n if gamma <= np.sqrt(np.pi / (2 * (d - 1))) * (np.exp(... | <|body_start_0|>
eps_space = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
d_space = [100, 1000, 10000]
for eps in eps_space:
for d in d_space:
gamma, _ = privunit.find_best_gamma(d, eps)
self.assertLessEqual(0, gamma)
self.assertLessEqual(gamma, 1)
... | PrivunitTest | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrivunitTest:
def test_gamma_is_in_range(self):
"""Test whether gamma adheres to (16a) or (16b) in the original paper."""
<|body_0|>
def test_c2_is_less_equal_c1(self):
"""Tests if c2 is less than or equal to c1."""
<|body_1|>
def test_m_is_less_equal_on... | stack_v2_sparse_classes_10k_train_006932 | 3,348 | permissive | [
{
"docstring": "Test whether gamma adheres to (16a) or (16b) in the original paper.",
"name": "test_gamma_is_in_range",
"signature": "def test_gamma_is_in_range(self)"
},
{
"docstring": "Tests if c2 is less than or equal to c1.",
"name": "test_c2_is_less_equal_c1",
"signature": "def test... | 4 | null | Implement the Python class `PrivunitTest` described below.
Class description:
Implement the PrivunitTest class.
Method signatures and docstrings:
- def test_gamma_is_in_range(self): Test whether gamma adheres to (16a) or (16b) in the original paper.
- def test_c2_is_less_equal_c1(self): Tests if c2 is less than or eq... | Implement the Python class `PrivunitTest` described below.
Class description:
Implement the PrivunitTest class.
Method signatures and docstrings:
- def test_gamma_is_in_range(self): Test whether gamma adheres to (16a) or (16b) in the original paper.
- def test_c2_is_less_equal_c1(self): Tests if c2 is less than or eq... | 329e60fa56b87f691303638ceb9dfa1fc5083953 | <|skeleton|>
class PrivunitTest:
def test_gamma_is_in_range(self):
"""Test whether gamma adheres to (16a) or (16b) in the original paper."""
<|body_0|>
def test_c2_is_less_equal_c1(self):
"""Tests if c2 is less than or equal to c1."""
<|body_1|>
def test_m_is_less_equal_on... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrivunitTest:
def test_gamma_is_in_range(self):
"""Test whether gamma adheres to (16a) or (16b) in the original paper."""
eps_space = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
d_space = [100, 1000, 10000]
for eps in eps_space:
for d in d_space:
gamma, _ = priv... | the_stack_v2_python_sparse | rcc_dp/mean_estimation/privunit_test.py | google-research/federated | train | 595 | |
0f2090733ed508c29f786b2b06ca5d9aeb6f63e6 | [
"self.server, self.clients = (NfsServer(server), [NfsClient(server, client) for client in clients])\nself.directory_to_share = directory_to_share\nself.directory_to_mount = directory_to_mount",
"self.server.share(self.directory_to_share, privileges=privileges)\nfor client in self.clients:\n client.mount(self.d... | <|body_start_0|>
self.server, self.clients = (NfsServer(server), [NfsClient(server, client) for client in clients])
self.directory_to_share = directory_to_share
self.directory_to_mount = directory_to_mount
<|end_body_0|>
<|body_start_1|>
self.server.share(self.directory_to_share, privil... | NfsConnection | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NfsConnection:
def __init__(self, server, clients, directory_to_share, directory_to_mount):
"""Shares a folder across multiple clients using NFS. Shares `directory_to_share` on `server` across `clients` mounting the shared folder at `directory_to_mount`."""
<|body_0|>
def sh... | stack_v2_sparse_classes_10k_train_006933 | 4,906 | permissive | [
{
"docstring": "Shares a folder across multiple clients using NFS. Shares `directory_to_share` on `server` across `clients` mounting the shared folder at `directory_to_mount`.",
"name": "__init__",
"signature": "def __init__(self, server, clients, directory_to_share, directory_to_mount)"
},
{
"d... | 4 | null | Implement the Python class `NfsConnection` described below.
Class description:
Implement the NfsConnection class.
Method signatures and docstrings:
- def __init__(self, server, clients, directory_to_share, directory_to_mount): Shares a folder across multiple clients using NFS. Shares `directory_to_share` on `server` ... | Implement the Python class `NfsConnection` described below.
Class description:
Implement the NfsConnection class.
Method signatures and docstrings:
- def __init__(self, server, clients, directory_to_share, directory_to_mount): Shares a folder across multiple clients using NFS. Shares `directory_to_share` on `server` ... | 4882e593be50cecbebb2e6bf7b95dcce82324ea1 | <|skeleton|>
class NfsConnection:
def __init__(self, server, clients, directory_to_share, directory_to_mount):
"""Shares a folder across multiple clients using NFS. Shares `directory_to_share` on `server` across `clients` mounting the shared folder at `directory_to_mount`."""
<|body_0|>
def sh... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NfsConnection:
def __init__(self, server, clients, directory_to_share, directory_to_mount):
"""Shares a folder across multiple clients using NFS. Shares `directory_to_share` on `server` across `clients` mounting the shared folder at `directory_to_mount`."""
self.server, self.clients = (NfsServ... | the_stack_v2_python_sparse | lib/nfs.py | couchbaselabs/TAF | train | 16 | |
1b78c7d9d8a926db4786577ea8ebd650eecd1d3c | [
"super(LandmarkGeneratorHeatmap, self).__init__(dim, output_size, landmark_indizes, landmark_flip_pairs, data_format, pre_transformation, post_transformation)\nself.output_size_np = list(reversed(self.output_size))\nself.sigma = sigma\nself.scale_factor = scale_factor\nself.normalize_center = normalize_center",
"... | <|body_start_0|>
super(LandmarkGeneratorHeatmap, self).__init__(dim, output_size, landmark_indizes, landmark_flip_pairs, data_format, pre_transformation, post_transformation)
self.output_size_np = list(reversed(self.output_size))
self.sigma = sigma
self.scale_factor = scale_factor
... | Generates images of Gaussian heatmaps | LandmarkGeneratorHeatmap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LandmarkGeneratorHeatmap:
"""Generates images of Gaussian heatmaps"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformation=None):
"""Init... | stack_v2_sparse_classes_10k_train_006934 | 16,690 | no_license | [
{
"docstring": "Initializer :param output_size: output image size :param sigma: Gaussian sigma :param scale_factor: heatmap scale factor, each value of the Gaussian will be multiplied with this value :param normalize_center: if True, the value on the center is set to scale_factor otherwise, the default gaussian... | 2 | stack_v2_sparse_classes_30k_train_000293 | Implement the Python class `LandmarkGeneratorHeatmap` described below.
Class description:
Generates images of Gaussian heatmaps
Method signatures and docstrings:
- def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first',... | Implement the Python class `LandmarkGeneratorHeatmap` described below.
Class description:
Generates images of Gaussian heatmaps
Method signatures and docstrings:
- def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first',... | ef6cee91264ba1fe6b40d9823a07647b95bcc2c4 | <|skeleton|>
class LandmarkGeneratorHeatmap:
"""Generates images of Gaussian heatmaps"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformation=None):
"""Init... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LandmarkGeneratorHeatmap:
"""Generates images of Gaussian heatmaps"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformation=None):
"""Initializer :para... | the_stack_v2_python_sparse | generators/landmark_generator.py | XiaoweiXu/MedicalDataAugmentationTool | train | 1 |
59a00023644ee296d04b160e1830cad931a7ff6d | [
"self.env.revert_snapshot('deploy_ha_elasticsearch_kibana')\ntarget_node = {'slave-03': ['controller']}\nself.helpers.remove_nodes_from_cluster(target_node)\nself.check_plugin_online()\nself.helpers.run_ostf(should_fail=1)\nself.helpers.add_nodes_to_cluster(target_node)\nself.check_plugin_online()\nself.helpers.run... | <|body_start_0|>
self.env.revert_snapshot('deploy_ha_elasticsearch_kibana')
target_node = {'slave-03': ['controller']}
self.helpers.remove_nodes_from_cluster(target_node)
self.check_plugin_online()
self.helpers.run_ostf(should_fail=1)
self.helpers.add_nodes_to_cluster(tar... | Class for system tests for Elasticsearch-Kibana plugin. | TestNodesElasticsearchPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestNodesElasticsearchPlugin:
"""Class for system tests for Elasticsearch-Kibana plugin."""
def add_remove_controller_elasticsearch_kibana(self):
"""Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. R... | stack_v2_sparse_classes_10k_train_006935 | 7,162 | no_license | [
{
"docstring": "Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. Remove one controller node and redeploy the cluster 3. Check that Elasticsearch/Kibana are running 4. Run OSTF 5. Add one controller node (return previous state) ... | 5 | stack_v2_sparse_classes_30k_train_003377 | Implement the Python class `TestNodesElasticsearchPlugin` described below.
Class description:
Class for system tests for Elasticsearch-Kibana plugin.
Method signatures and docstrings:
- def add_remove_controller_elasticsearch_kibana(self): Verify that the number of controllers can scale up and down Scenario: 1. Rever... | Implement the Python class `TestNodesElasticsearchPlugin` described below.
Class description:
Class for system tests for Elasticsearch-Kibana plugin.
Method signatures and docstrings:
- def add_remove_controller_elasticsearch_kibana(self): Verify that the number of controllers can scale up and down Scenario: 1. Rever... | 179249df2d206eeabb3955c9dc8cb78cac3c36c6 | <|skeleton|>
class TestNodesElasticsearchPlugin:
"""Class for system tests for Elasticsearch-Kibana plugin."""
def add_remove_controller_elasticsearch_kibana(self):
"""Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. R... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestNodesElasticsearchPlugin:
"""Class for system tests for Elasticsearch-Kibana plugin."""
def add_remove_controller_elasticsearch_kibana(self):
"""Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. Remove one con... | the_stack_v2_python_sparse | stacklight_tests/elasticsearch_kibana/test_system.py | rkhozinov/stacklight-integration-tests | train | 1 |
942eb998d26bbb8b953c19ed6b3837aae7ed7fce | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | A service account is a special type of Google account that belongs to your application or a virtual machine (VM), instead of to an individual end user. Your application assumes the identity of the service account to call Google APIs, so that the users aren't directly involved. Service account credentials are used to te... | IAMCredentialsServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IAMCredentialsServicer:
"""A service account is a special type of Google account that belongs to your application or a virtual machine (VM), instead of to an individual end user. Your application assumes the identity of the service account to call Google APIs, so that the users aren't directly in... | stack_v2_sparse_classes_10k_train_006936 | 5,869 | permissive | [
{
"docstring": "Generates an OAuth 2.0 access token for a service account.",
"name": "GenerateAccessToken",
"signature": "def GenerateAccessToken(self, request, context)"
},
{
"docstring": "Generates an OpenID Connect ID token for a service account.",
"name": "GenerateIdToken",
"signatur... | 4 | stack_v2_sparse_classes_30k_train_007214 | Implement the Python class `IAMCredentialsServicer` described below.
Class description:
A service account is a special type of Google account that belongs to your application or a virtual machine (VM), instead of to an individual end user. Your application assumes the identity of the service account to call Google API... | Implement the Python class `IAMCredentialsServicer` described below.
Class description:
A service account is a special type of Google account that belongs to your application or a virtual machine (VM), instead of to an individual end user. Your application assumes the identity of the service account to call Google API... | d897d56bce03d1fda98b79afb08264e51d46c421 | <|skeleton|>
class IAMCredentialsServicer:
"""A service account is a special type of Google account that belongs to your application or a virtual machine (VM), instead of to an individual end user. Your application assumes the identity of the service account to call Google APIs, so that the users aren't directly in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IAMCredentialsServicer:
"""A service account is a special type of Google account that belongs to your application or a virtual machine (VM), instead of to an individual end user. Your application assumes the identity of the service account to call Google APIs, so that the users aren't directly involved. Servi... | the_stack_v2_python_sparse | iam/google/cloud/iam_credentials_v1/proto/iamcredentials_pb2_grpc.py | tswast/google-cloud-python | train | 1 |
b5a11abdbed5c40b1a3a49a3d4794ca10c94c4fd | [
"if not is_exe(exe_path):\n msg = '{0} is not an executable'.format(exe_path)\n raise NotExecutableError(msg)\nself._exe_path = exe_path",
"assert lreads != rreads\nself.__build_cmd(lreads, rreads, threads, outdir, prefix)\nif dry_run:\n return self._cmd\npipe = subprocess.run(self._cmd, shell=True, stdo... | <|body_start_0|>
if not is_exe(exe_path):
msg = '{0} is not an executable'.format(exe_path)
raise NotExecutableError(msg)
self._exe_path = exe_path
<|end_body_0|>
<|body_start_1|>
assert lreads != rreads
self.__build_cmd(lreads, rreads, threads, outdir, prefix)
... | Class for working with PEAR | Pear | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pear:
"""Class for working with PEAR"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False):
"""Run PEAR to merge passed read files - lreads - forward reads -... | stack_v2_sparse_classes_10k_train_006937 | 3,102 | permissive | [
{
"docstring": "Instantiate with location of executable",
"name": "__init__",
"signature": "def __init__(self, exe_path)"
},
{
"docstring": "Run PEAR to merge passed read files - lreads - forward reads - rreads - reverse reads - threads - number of threads for pear to use - outdir - output direc... | 3 | stack_v2_sparse_classes_30k_train_000840 | Implement the Python class `Pear` described below.
Class description:
Class for working with PEAR
Method signatures and docstrings:
- def __init__(self, exe_path): Instantiate with location of executable
- def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False): Run PEAR to merge passed read files - lre... | Implement the Python class `Pear` described below.
Class description:
Class for working with PEAR
Method signatures and docstrings:
- def __init__(self, exe_path): Instantiate with location of executable
- def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False): Run PEAR to merge passed read files - lre... | a3c64198aad3709a5c4d969f48ae0af11fdc25db | <|skeleton|>
class Pear:
"""Class for working with PEAR"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, lreads, rreads, threads, outdir, prefix, dry_run=False):
"""Run PEAR to merge passed read files - lreads - forward reads -... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Pear:
"""Class for working with PEAR"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
if not is_exe(exe_path):
msg = '{0} is not an executable'.format(exe_path)
raise NotExecutableError(msg)
self._exe_path = exe_path
def r... | the_stack_v2_python_sparse | metapy/pycits/pear.py | peterthorpe5/public_scripts | train | 35 |
ef0d35f80da8d9ee84f69a6605a7c3240511ecbb | [
"urls = response.css('ul li a::attr(\"href\")')\nprint('urls', urls)\nfor url in urls.re('/pickup/\\\\d+$'):\n yield response.follow(url, self.parse_topics)",
"item = Headline()\nitem['title'] = response.css('title::text').get()\nitem['body'] = response.css('article p.sc-inlrYM').xpath('string()').get()\nyield... | <|body_start_0|>
urls = response.css('ul li a::attr("href")')
print('urls', urls)
for url in urls.re('/pickup/\\d+$'):
yield response.follow(url, self.parse_topics)
<|end_body_0|>
<|body_start_1|>
item = Headline()
item['title'] = response.css('title::text').get()
... | NewsSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewsSpider:
def parse(self, response):
"""トップページのトピックス一覧からここのトピックスへのリンクを抜き出して表示する Args: response ([type]): [description]"""
<|body_0|>
def parse_topics(self, response):
"""トピックスのページからタイトルと本文を抜き出す Args: response ([type]): [description]"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_10k_train_006938 | 1,225 | no_license | [
{
"docstring": "トップページのトピックス一覧からここのトピックスへのリンクを抜き出して表示する Args: response ([type]): [description]",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "トピックスのページからタイトルと本文を抜き出す Args: response ([type]): [description]",
"name": "parse_topics",
"signature": "def parse_t... | 2 | stack_v2_sparse_classes_30k_train_000145 | Implement the Python class `NewsSpider` described below.
Class description:
Implement the NewsSpider class.
Method signatures and docstrings:
- def parse(self, response): トップページのトピックス一覧からここのトピックスへのリンクを抜き出して表示する Args: response ([type]): [description]
- def parse_topics(self, response): トピックスのページからタイトルと本文を抜き出す Args: re... | Implement the Python class `NewsSpider` described below.
Class description:
Implement the NewsSpider class.
Method signatures and docstrings:
- def parse(self, response): トップページのトピックス一覧からここのトピックスへのリンクを抜き出して表示する Args: response ([type]): [description]
- def parse_topics(self, response): トピックスのページからタイトルと本文を抜き出す Args: re... | f65681a6a1e478d0ac051d3bea8e7a354d2245d3 | <|skeleton|>
class NewsSpider:
def parse(self, response):
"""トップページのトピックス一覧からここのトピックスへのリンクを抜き出して表示する Args: response ([type]): [description]"""
<|body_0|>
def parse_topics(self, response):
"""トピックスのページからタイトルと本文を抜き出す Args: response ([type]): [description]"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NewsSpider:
def parse(self, response):
"""トップページのトピックス一覧からここのトピックスへのリンクを抜き出して表示する Args: response ([type]): [description]"""
urls = response.css('ul li a::attr("href")')
print('urls', urls)
for url in urls.re('/pickup/\\d+$'):
yield response.follow(url, self.parse_to... | the_stack_v2_python_sparse | chapter6/myproject/myproject/spiders/news.py | OtsukaTomoaki/PythonCrawlingScraping | train | 0 | |
9e228db3324cd172bbea850b528bb89d8db00247 | [
"self.val = int(x)\nself.next = next\nself.random = random",
"res, node = ([], self)\nwhile node:\n rand = node.random.val if node.random else None\n res.append([node.val, rand])\n node = node.next\nreturn res"
] | <|body_start_0|>
self.val = int(x)
self.next = next
self.random = random
<|end_body_0|>
<|body_start_1|>
res, node = ([], self)
while node:
rand = node.random.val if node.random else None
res.append([node.val, rand])
node = node.next
r... | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None):
"""Provided by LeetCode."""
<|body_0|>
def _path(self):
"""Used for testing. Returns the path of the linked list. Each element is the node's value, and the value of it's random node."""
... | stack_v2_sparse_classes_10k_train_006939 | 1,851 | no_license | [
{
"docstring": "Provided by LeetCode.",
"name": "__init__",
"signature": "def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None)"
},
{
"docstring": "Used for testing. Returns the path of the linked list. Each element is the node's value, and the value of it's random node.",
"name... | 2 | null | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None): Provided by LeetCode.
- def _path(self): Used for testing. Returns the path of the linked list. Each element is the no... | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None): Provided by LeetCode.
- def _path(self): Used for testing. Returns the path of the linked list. Each element is the no... | c6d600bc74afd14e00d4f0ffed40696192b229c3 | <|skeleton|>
class Node:
def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None):
"""Provided by LeetCode."""
<|body_0|>
def _path(self):
"""Used for testing. Returns the path of the linked list. Each element is the node's value, and the value of it's random node."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Node:
def __init__(self, x: int, next: 'Node'=None, random: 'Node'=None):
"""Provided by LeetCode."""
self.val = int(x)
self.next = next
self.random = random
def _path(self):
"""Used for testing. Returns the path of the linked list. Each element is the node's value... | the_stack_v2_python_sparse | python/Monthly/Feb2021/listrandompointerdeepcopy.py | Hilldrupca/LeetCode | train | 0 | |
f9e7fead436b149db2096f71f4c710d2a1a0881a | [
"comp = lambda x, y: 0 if x == y else -1 if x < y else 1\nself.sa = mysort([document[i:] for i in range(len(document))], comp)\npass",
"out = []\nfor x in range(0, len(self.sa)):\n sub = self.sa[x]\n if searchstr == sub[0:len(searchstr)]:\n out.append(x)\n return out\npass",
"for x in self.s... | <|body_start_0|>
comp = lambda x, y: 0 if x == y else -1 if x < y else 1
self.sa = mysort([document[i:] for i in range(len(document))], comp)
pass
<|end_body_0|>
<|body_start_1|>
out = []
for x in range(0, len(self.sa)):
sub = self.sa[x]
if searchstr == s... | SuffixArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuffixArray:
def __init__(self, document: str):
"""Creates a suffix array for document (a string)."""
<|body_0|>
def positions(self, searchstr: str):
"""Returns all the positions of searchstr in the documented indexed by the suffix array."""
<|body_1|>
d... | stack_v2_sparse_classes_10k_train_006940 | 8,672 | no_license | [
{
"docstring": "Creates a suffix array for document (a string).",
"name": "__init__",
"signature": "def __init__(self, document: str)"
},
{
"docstring": "Returns all the positions of searchstr in the documented indexed by the suffix array.",
"name": "positions",
"signature": "def positio... | 3 | stack_v2_sparse_classes_30k_train_006104 | Implement the Python class `SuffixArray` described below.
Class description:
Implement the SuffixArray class.
Method signatures and docstrings:
- def __init__(self, document: str): Creates a suffix array for document (a string).
- def positions(self, searchstr: str): Returns all the positions of searchstr in the docu... | Implement the Python class `SuffixArray` described below.
Class description:
Implement the SuffixArray class.
Method signatures and docstrings:
- def __init__(self, document: str): Creates a suffix array for document (a string).
- def positions(self, searchstr: str): Returns all the positions of searchstr in the docu... | b4edf759b2916ab44f08741a6f19b103a9070203 | <|skeleton|>
class SuffixArray:
def __init__(self, document: str):
"""Creates a suffix array for document (a string)."""
<|body_0|>
def positions(self, searchstr: str):
"""Returns all the positions of searchstr in the documented indexed by the suffix array."""
<|body_1|>
d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SuffixArray:
def __init__(self, document: str):
"""Creates a suffix array for document (a string)."""
comp = lambda x, y: 0 if x == y else -1 if x < y else 1
self.sa = mysort([document[i:] for i in range(len(document))], comp)
pass
def positions(self, searchstr: str):
... | the_stack_v2_python_sparse | lab03/lab03.py | saronson/cs331-s21-jmallett2 | train | 2 | |
3568cd4d8e40eee95f0a9716ba528f99e476e69f | [
"super(CoordinateInfo, self).__init__()\nself.name = name\nself.generic_level = False\nself.generic_lev_coords = {}\nself.axis = ''\n'Axis'\nself.value = ''\n'Coordinate value'\nself.standard_name = ''\n'Standard name'\nself.long_name = ''\n'Long name'\nself.out_name = ''\n'\\n Out name\\n\\n This is ... | <|body_start_0|>
super(CoordinateInfo, self).__init__()
self.name = name
self.generic_level = False
self.generic_lev_coords = {}
self.axis = ''
'Axis'
self.value = ''
'Coordinate value'
self.standard_name = ''
'Standard name'
self.l... | Class to read and store coordinate information. | CoordinateInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordinateInfo:
"""Class to read and store coordinate information."""
def __init__(self, name):
"""Class to read and store coordinate information. Parameters ---------- name: str coordinate's name"""
<|body_0|>
def read_json(self, json_data):
"""Read coordinate i... | stack_v2_sparse_classes_10k_train_006941 | 34,873 | permissive | [
{
"docstring": "Class to read and store coordinate information. Parameters ---------- name: str coordinate's name",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Read coordinate information from json. Non-present options will be set to empty Parameters ----------... | 2 | null | Implement the Python class `CoordinateInfo` described below.
Class description:
Class to read and store coordinate information.
Method signatures and docstrings:
- def __init__(self, name): Class to read and store coordinate information. Parameters ---------- name: str coordinate's name
- def read_json(self, json_dat... | Implement the Python class `CoordinateInfo` described below.
Class description:
Class to read and store coordinate information.
Method signatures and docstrings:
- def __init__(self, name): Class to read and store coordinate information. Parameters ---------- name: str coordinate's name
- def read_json(self, json_dat... | d5187438fea2928644cb53ecb26c6adb1e4cc947 | <|skeleton|>
class CoordinateInfo:
"""Class to read and store coordinate information."""
def __init__(self, name):
"""Class to read and store coordinate information. Parameters ---------- name: str coordinate's name"""
<|body_0|>
def read_json(self, json_data):
"""Read coordinate i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CoordinateInfo:
"""Class to read and store coordinate information."""
def __init__(self, name):
"""Class to read and store coordinate information. Parameters ---------- name: str coordinate's name"""
super(CoordinateInfo, self).__init__()
self.name = name
self.generic_leve... | the_stack_v2_python_sparse | esmvalcore/cmor/table.py | ESMValGroup/ESMValCore | train | 41 |
90d43a7b693fbf55f060706e1fdba5436b054ebe | [
"if context is None:\n context = {}\ndata = self.read(cr, uid, ids, context=context)[0]\nobj_account_move = self.pool.get('account.move')\nwf_service = netsvc.LocalService('workflow')\ndomain = [('state', '=', 'closed'), ('date', '>=', data['date_from']), ('date', '<=', data['date_to'])]\nif data['period_id']:\n... | <|body_start_0|>
if context is None:
context = {}
data = self.read(cr, uid, ids, context=context)[0]
obj_account_move = self.pool.get('account.move')
wf_service = netsvc.LocalService('workflow')
domain = [('state', '=', 'closed'), ('date', '>=', data['date_from']), ('... | This model to close moves in special period | account_close_period | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account_close_period:
"""This model to close moves in special period"""
def get_moves(self, cr, uid, ids, context=None):
"""Get All moves belong not in draft, posted or reversed state @return: dictionary of values"""
<|body_0|>
def close_period(self, cr, uid, ids, contex... | stack_v2_sparse_classes_10k_train_006942 | 3,896 | no_license | [
{
"docstring": "Get All moves belong not in draft, posted or reversed state @return: dictionary of values",
"name": "get_moves",
"signature": "def get_moves(self, cr, uid, ids, context=None)"
},
{
"docstring": "Validate all accounts belong in consolidation account or not @return: dictionary of v... | 2 | null | Implement the Python class `account_close_period` described below.
Class description:
This model to close moves in special period
Method signatures and docstrings:
- def get_moves(self, cr, uid, ids, context=None): Get All moves belong not in draft, posted or reversed state @return: dictionary of values
- def close_p... | Implement the Python class `account_close_period` described below.
Class description:
This model to close moves in special period
Method signatures and docstrings:
- def get_moves(self, cr, uid, ids, context=None): Get All moves belong not in draft, posted or reversed state @return: dictionary of values
- def close_p... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class account_close_period:
"""This model to close moves in special period"""
def get_moves(self, cr, uid, ids, context=None):
"""Get All moves belong not in draft, posted or reversed state @return: dictionary of values"""
<|body_0|>
def close_period(self, cr, uid, ids, contex... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class account_close_period:
"""This model to close moves in special period"""
def get_moves(self, cr, uid, ids, context=None):
"""Get All moves belong not in draft, posted or reversed state @return: dictionary of values"""
if context is None:
context = {}
data = self.read(cr... | the_stack_v2_python_sparse | v_7/Dongola/ntc/account_ntc/wizard/account_close_period.py | musabahmed/baba | train | 0 |
b8af26faeb4444367f05b43d3ffe9fba193942e1 | [
"obj = context.object\nif obj is None:\n return False\nreturn all([bool(obj), obj.type == 'MESH', obj.mode == 'EDIT'])",
"scene = context.scene\npg = scene.pdt_pg\nobj = bpy.context.view_layer.objects.active\nif obj is None:\n self.report({'ERROR'}, PDT_ERR_NO_ACT_OBJ)\n return {'FINISHED'}\nif obj.mode ... | <|body_start_0|>
obj = context.object
if obj is None:
return False
return all([bool(obj), obj.type == 'MESH', obj.mode == 'EDIT'])
<|end_body_0|>
<|body_start_1|>
scene = context.scene
pg = scene.pdt_pg
obj = bpy.context.view_layer.objects.active
if o... | Rotate Selected Vertices about Pivot Point in View Plane | PDT_OT_ViewPlaneRotate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PDT_OT_ViewPlaneRotate:
"""Rotate Selected Vertices about Pivot Point in View Plane"""
def poll(cls, context):
"""Check Object Status. Args: context: Blender bpy.context instance. Returns: Nothing."""
<|body_0|>
def execute(self, context):
"""Rotate Selected Vert... | stack_v2_sparse_classes_10k_train_006943 | 13,734 | permissive | [
{
"docstring": "Check Object Status. Args: context: Blender bpy.context instance. Returns: Nothing.",
"name": "poll",
"signature": "def poll(cls, context)"
},
{
"docstring": "Rotate Selected Vertices about Pivot Point. Note: Rotates any selected vertices about the Pivot Point in View Oriented co... | 2 | null | Implement the Python class `PDT_OT_ViewPlaneRotate` described below.
Class description:
Rotate Selected Vertices about Pivot Point in View Plane
Method signatures and docstrings:
- def poll(cls, context): Check Object Status. Args: context: Blender bpy.context instance. Returns: Nothing.
- def execute(self, context):... | Implement the Python class `PDT_OT_ViewPlaneRotate` described below.
Class description:
Rotate Selected Vertices about Pivot Point in View Plane
Method signatures and docstrings:
- def poll(cls, context): Check Object Status. Args: context: Blender bpy.context instance. Returns: Nothing.
- def execute(self, context):... | 4d5c304878c1e0018d97c1b07bcaa3981632265a | <|skeleton|>
class PDT_OT_ViewPlaneRotate:
"""Rotate Selected Vertices about Pivot Point in View Plane"""
def poll(cls, context):
"""Check Object Status. Args: context: Blender bpy.context instance. Returns: Nothing."""
<|body_0|>
def execute(self, context):
"""Rotate Selected Vert... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PDT_OT_ViewPlaneRotate:
"""Rotate Selected Vertices about Pivot Point in View Plane"""
def poll(cls, context):
"""Check Object Status. Args: context: Blender bpy.context instance. Returns: Nothing."""
obj = context.object
if obj is None:
return False
return all... | the_stack_v2_python_sparse | src/bpy/3.6/scripts/addons/precision_drawing_tools/pdt_pivot_point.py | RnoB/3DVisualSwarm | train | 0 |
58f08e42e09cfd43ed70b3b55c7b0c876f8f68e7 | [
"format_date = lambda d: d.date().strftime('%d.%m.%Y')\ndate_from, date_till = get_datetime_from_till(7)\nsubject = cls.get_full_subject('Подборка материалов %s-%s' % (format_date(date_from), format_date(date_till)))\ncontext = {'date_from': date_from.timestamp(), 'date_till': date_till.timestamp()}\ncls(subject, c... | <|body_start_0|>
format_date = lambda d: d.date().strftime('%d.%m.%Y')
date_from, date_till = get_datetime_from_till(7)
subject = cls.get_full_subject('Подборка материалов %s-%s' % (format_date(date_from), format_date(date_till)))
context = {'date_from': date_from.timestamp(), 'date_till... | Класс реализующий рассылку с подборкой новых материалов сайта (сводку). | PythonzEmailDigest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PythonzEmailDigest:
"""Класс реализующий рассылку с подборкой новых материалов сайта (сводку)."""
def create(cls):
"""Создаёт депеши для рассылки еженедельной сводки. Реальная компиляция сводки происходит в compile(). :return:"""
<|body_0|>
def get_realms_data(cls, date_... | stack_v2_sparse_classes_10k_train_006944 | 16,316 | no_license | [
{
"docstring": "Создаёт депеши для рассылки еженедельной сводки. Реальная компиляция сводки происходит в compile(). :return:",
"name": "create",
"signature": "def create(cls)"
},
{
"docstring": "Возвращает данные о материалах за указанный период. :param date date_from: Дата начала периода :param... | 5 | stack_v2_sparse_classes_30k_train_003662 | Implement the Python class `PythonzEmailDigest` described below.
Class description:
Класс реализующий рассылку с подборкой новых материалов сайта (сводку).
Method signatures and docstrings:
- def create(cls): Создаёт депеши для рассылки еженедельной сводки. Реальная компиляция сводки происходит в compile(). :return:
... | Implement the Python class `PythonzEmailDigest` described below.
Class description:
Класс реализующий рассылку с подборкой новых материалов сайта (сводку).
Method signatures and docstrings:
- def create(cls): Создаёт депеши для рассылки еженедельной сводки. Реальная компиляция сводки происходит в compile(). :return:
... | 8d5d41755f33b7850af677ba0a2f26cba823daf9 | <|skeleton|>
class PythonzEmailDigest:
"""Класс реализующий рассылку с подборкой новых материалов сайта (сводку)."""
def create(cls):
"""Создаёт депеши для рассылки еженедельной сводки. Реальная компиляция сводки происходит в compile(). :return:"""
<|body_0|>
def get_realms_data(cls, date_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PythonzEmailDigest:
"""Класс реализующий рассылку с подборкой новых материалов сайта (сводку)."""
def create(cls):
"""Создаёт депеши для рассылки еженедельной сводки. Реальная компиляция сводки происходит в compile(). :return:"""
format_date = lambda d: d.date().strftime('%d.%m.%Y')
... | the_stack_v2_python_sparse | apps/sitemessages.py | GraceAredel/pythonz | train | 1 |
aae9886c497007d76f76c70320050dbe0dabddec | [
"size = len(candidates)\nif size <= 0:\n return []\ncandidates.sort()\npath = []\nres = []\nself._find_path(target, path, res, candidates, 0, size)\nreturn res",
"if target == 0:\n res.append(path.copy())\nelse:\n for i in range(begin, size):\n left_num = target - candidates[i]\n if left_nu... | <|body_start_0|>
size = len(candidates)
if size <= 0:
return []
candidates.sort()
path = []
res = []
self._find_path(target, path, res, candidates, 0, size)
return res
<|end_body_0|>
<|body_start_1|>
if target == 0:
res.append(path... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；"""
<|body_0|>
def _find_path(self, target, path, res, candidates, begin, size):
"""沿着路径往下走"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_10k_train_006945 | 2,269 | no_license | [
{
"docstring": "回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；",
"name": "combinationSum",
"signature": "def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]"
},
{
"docstring": "沿着路径往下走",
"name": "_find_path",
"signature": "def _find_path(self, target, path... | 2 | stack_v2_sparse_classes_30k_train_004083 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]: 回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；
- def _find_path(self, target, path, res, cand... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]: 回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；
- def _find_path(self, target, path, res, cand... | 13e9f74be18949875b271a742b1dfe87485ff3a2 | <|skeleton|>
class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；"""
<|body_0|>
def _find_path(self, target, path, res, candidates, begin, size):
"""沿着路径往下走"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；"""
size = len(candidates)
if size <= 0:
return []
candidates.sort()
path = []
res = []
self._find... | the_stack_v2_python_sparse | 39_Combination_Sum.py | Joker-Jerome/leetcode | train | 1 | |
29cc16fb0d99d057a0938bdae89ef34b38679c34 | [
"self.file = file\nself.bills = {'5': [], '10': [], '20': [], '50': [], '100': []}\nif len(self.file) != 0:\n with open(self.file, 'r') as f:\n text = f.read().splitlines()\n for line in text:\n if line.split(' ')[1] == '5':\n self.bills['5'].append(line.split(' ')[0])\n ... | <|body_start_0|>
self.file = file
self.bills = {'5': [], '10': [], '20': [], '50': [], '100': []}
if len(self.file) != 0:
with open(self.file, 'r') as f:
text = f.read().splitlines()
for line in text:
if line.split(' ')[1] == '5':
... | WatchList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WatchList:
def __init__(self, file=''):
"""This method takes in a filename and initializes a dictionary by the name of bills which contains serial numbers of all the denominations contained as keys.It also checks if the lists in the keys of bills are sorted and uses regex module to check... | stack_v2_sparse_classes_10k_train_006946 | 4,514 | no_license | [
{
"docstring": "This method takes in a filename and initializes a dictionary by the name of bills which contains serial numbers of all the denominations contained as keys.It also checks if the lists in the keys of bills are sorted and uses regex module to check for valid serial numbers.",
"name": "__init__"... | 6 | stack_v2_sparse_classes_30k_train_007275 | Implement the Python class `WatchList` described below.
Class description:
Implement the WatchList class.
Method signatures and docstrings:
- def __init__(self, file=''): This method takes in a filename and initializes a dictionary by the name of bills which contains serial numbers of all the denominations contained ... | Implement the Python class `WatchList` described below.
Class description:
Implement the WatchList class.
Method signatures and docstrings:
- def __init__(self, file=''): This method takes in a filename and initializes a dictionary by the name of bills which contains serial numbers of all the denominations contained ... | e773e87668af057c8adb1e012aa5d81f42c70f2a | <|skeleton|>
class WatchList:
def __init__(self, file=''):
"""This method takes in a filename and initializes a dictionary by the name of bills which contains serial numbers of all the denominations contained as keys.It also checks if the lists in the keys of bills are sorted and uses regex module to check... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WatchList:
def __init__(self, file=''):
"""This method takes in a filename and initializes a dictionary by the name of bills which contains serial numbers of all the denominations contained as keys.It also checks if the lists in the keys of bills are sorted and uses regex module to check for valid ser... | the_stack_v2_python_sparse | HW/HW1/hw1.py | SiddhantBhardwaj2018/ISTA-350 | train | 0 | |
14ffef7b8d46d353529df670c2c4fa0c97c348bb | [
"seo = SiteSeo.objects.get(choices='Password Reset')\ntemplate_name = 'registration/password_reset_form.html'\nreset_form = PasswordResetForm()\ncontext = {'reset_form': reset_form, 'seo': seo}\nreturn render(request, template_name, context)",
"template_name = 'registration/password_reset_form.html'\nseo = SiteSe... | <|body_start_0|>
seo = SiteSeo.objects.get(choices='Password Reset')
template_name = 'registration/password_reset_form.html'
reset_form = PasswordResetForm()
context = {'reset_form': reset_form, 'seo': seo}
return render(request, template_name, context)
<|end_body_0|>
<|body_sta... | PasswordResetView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordResetView:
def get(self, request):
"""get method to display the password reset form"""
<|body_0|>
def post(self, request):
"""post method to receive the email id entered by the customer, create token,id to send the password reset link to entered email"""
... | stack_v2_sparse_classes_10k_train_006947 | 36,770 | permissive | [
{
"docstring": "get method to display the password reset form",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "post method to receive the email id entered by the customer, create token,id to send the password reset link to entered email",
"name": "post",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_003670 | Implement the Python class `PasswordResetView` described below.
Class description:
Implement the PasswordResetView class.
Method signatures and docstrings:
- def get(self, request): get method to display the password reset form
- def post(self, request): post method to receive the email id entered by the customer, cr... | Implement the Python class `PasswordResetView` described below.
Class description:
Implement the PasswordResetView class.
Method signatures and docstrings:
- def get(self, request): get method to display the password reset form
- def post(self, request): post method to receive the email id entered by the customer, cr... | ab828ca95571c6dffef2b2392522e6a4160a2304 | <|skeleton|>
class PasswordResetView:
def get(self, request):
"""get method to display the password reset form"""
<|body_0|>
def post(self, request):
"""post method to receive the email id entered by the customer, create token,id to send the password reset link to entered email"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PasswordResetView:
def get(self, request):
"""get method to display the password reset form"""
seo = SiteSeo.objects.get(choices='Password Reset')
template_name = 'registration/password_reset_form.html'
reset_form = PasswordResetForm()
context = {'reset_form': reset_for... | the_stack_v2_python_sparse | login/views.py | Quanscendence/braynai | train | 0 | |
623b601cc60ddc8c53f32b4acb616684179ef870 | [
"del observation\ndel a\nreturn -1",
"del reward\ndel observation\ndel a\nreturn -1"
] | <|body_start_0|>
del observation
del a
return -1
<|end_body_0|>
<|body_start_1|>
del reward
del observation
del a
return -1
<|end_body_1|>
| A MockExploration class that always returns -1. | MockExploration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MockExploration:
"""A MockExploration class that always returns -1."""
def begin_episode(self, observation: np.ndarray, a: int) -> int:
"""Returns the same action passed by the agent."""
<|body_0|>
def step(self, reward: float, observation: np.ndarray, a: int) -> int:
... | stack_v2_sparse_classes_10k_train_006948 | 11,665 | permissive | [
{
"docstring": "Returns the same action passed by the agent.",
"name": "begin_episode",
"signature": "def begin_episode(self, observation: np.ndarray, a: int) -> int"
},
{
"docstring": "Returns the same action passed by the agent.",
"name": "step",
"signature": "def step(self, reward: fl... | 2 | stack_v2_sparse_classes_30k_train_004694 | Implement the Python class `MockExploration` described below.
Class description:
A MockExploration class that always returns -1.
Method signatures and docstrings:
- def begin_episode(self, observation: np.ndarray, a: int) -> int: Returns the same action passed by the agent.
- def step(self, reward: float, observation... | Implement the Python class `MockExploration` described below.
Class description:
A MockExploration class that always returns -1.
Method signatures and docstrings:
- def begin_episode(self, observation: np.ndarray, a: int) -> int: Returns the same action passed by the agent.
- def step(self, reward: float, observation... | 72082feccf404e5bf946e513e4f6c0ae8fb279ad | <|skeleton|>
class MockExploration:
"""A MockExploration class that always returns -1."""
def begin_episode(self, observation: np.ndarray, a: int) -> int:
"""Returns the same action passed by the agent."""
<|body_0|>
def step(self, reward: float, observation: np.ndarray, a: int) -> int:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MockExploration:
"""A MockExploration class that always returns -1."""
def begin_episode(self, observation: np.ndarray, a: int) -> int:
"""Returns the same action passed by the agent."""
del observation
del a
return -1
def step(self, reward: float, observation: np.nda... | the_stack_v2_python_sparse | balloon_learning_environment/agents/quantile_agent_test.py | google/balloon-learning-environment | train | 108 |
05e30fb880eb841c828cbd062efdc755935388cd | [
"caller = self.caller\nif hasattr(self.caller.location, 'get_detail'):\n detail = self.caller.location.get_detail(self.args, looker=self.caller)\n if detail:\n caller.location.msg_contents(f'$You() $conj(look) closely at {self.args}.\\n', from_obj=caller, exclude=caller)\n caller.msg(detail)\n ... | <|body_start_0|>
caller = self.caller
if hasattr(self.caller.location, 'get_detail'):
detail = self.caller.location.get_detail(self.args, looker=self.caller)
if detail:
caller.location.msg_contents(f'$You() $conj(look) closely at {self.args}.\n', from_obj=caller, ... | look Usage: look look <obj> look <room detail> look *<account> Observes your location, details at your location or objects in your vicinity. | CmdExtendedRoomLook | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CmdExtendedRoomLook:
"""look Usage: look look <obj> look <room detail> look *<account> Observes your location, details at your location or objects in your vicinity."""
def look_detail(self):
"""Look for detail on room."""
<|body_0|>
def func(self):
"""Handle the ... | stack_v2_sparse_classes_10k_train_006949 | 34,295 | permissive | [
{
"docstring": "Look for detail on room.",
"name": "look_detail",
"signature": "def look_detail(self)"
},
{
"docstring": "Handle the looking.",
"name": "func",
"signature": "def func(self)"
}
] | 2 | null | Implement the Python class `CmdExtendedRoomLook` described below.
Class description:
look Usage: look look <obj> look <room detail> look *<account> Observes your location, details at your location or objects in your vicinity.
Method signatures and docstrings:
- def look_detail(self): Look for detail on room.
- def fu... | Implement the Python class `CmdExtendedRoomLook` described below.
Class description:
look Usage: look look <obj> look <room detail> look *<account> Observes your location, details at your location or objects in your vicinity.
Method signatures and docstrings:
- def look_detail(self): Look for detail on room.
- def fu... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class CmdExtendedRoomLook:
"""look Usage: look look <obj> look <room detail> look *<account> Observes your location, details at your location or objects in your vicinity."""
def look_detail(self):
"""Look for detail on room."""
<|body_0|>
def func(self):
"""Handle the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CmdExtendedRoomLook:
"""look Usage: look look <obj> look <room detail> look *<account> Observes your location, details at your location or objects in your vicinity."""
def look_detail(self):
"""Look for detail on room."""
caller = self.caller
if hasattr(self.caller.location, 'get_... | the_stack_v2_python_sparse | evennia/contrib/grid/extended_room/extended_room.py | evennia/evennia | train | 1,781 |
3a8b2cf6d3f36cfe05234b8088f2db3fb8254e99 | [
"self._logger = logger\nself._no_run = False\nif not is_exe(exe_path):\n self._logger.error('No trim_quality script available (exiting)')\n sys.exit(1)\nself._exe_path = exe_path\nself.format = 'fastq'",
"self.__build_cmd(infname, outdir)\nmsg = ['Running...', '\\t%s' % self._cmd]\nfor m in msg:\n self._... | <|body_start_0|>
self._logger = logger
self._no_run = False
if not is_exe(exe_path):
self._logger.error('No trim_quality script available (exiting)')
sys.exit(1)
self._exe_path = exe_path
self.format = 'fastq'
<|end_body_0|>
<|body_start_1|>
self.... | Class for working with trim_quality | Trim_Quality | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trim_Quality:
"""Class for working with trim_quality"""
def __init__(self, exe_path, logger):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, infname, outdir):
"""Run trim_quality on the passed file"""
<|body_1|>
def __build_cm... | stack_v2_sparse_classes_10k_train_006950 | 3,597 | permissive | [
{
"docstring": "Instantiate with location of executable",
"name": "__init__",
"signature": "def __init__(self, exe_path, logger)"
},
{
"docstring": "Run trim_quality on the passed file",
"name": "run",
"signature": "def run(self, infname, outdir)"
},
{
"docstring": "Build a comma... | 3 | stack_v2_sparse_classes_30k_train_003638 | Implement the Python class `Trim_Quality` described below.
Class description:
Class for working with trim_quality
Method signatures and docstrings:
- def __init__(self, exe_path, logger): Instantiate with location of executable
- def run(self, infname, outdir): Run trim_quality on the passed file
- def __build_cmd(se... | Implement the Python class `Trim_Quality` described below.
Class description:
Class for working with trim_quality
Method signatures and docstrings:
- def __init__(self, exe_path, logger): Instantiate with location of executable
- def run(self, infname, outdir): Run trim_quality on the passed file
- def __build_cmd(se... | a3c64198aad3709a5c4d969f48ae0af11fdc25db | <|skeleton|>
class Trim_Quality:
"""Class for working with trim_quality"""
def __init__(self, exe_path, logger):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, infname, outdir):
"""Run trim_quality on the passed file"""
<|body_1|>
def __build_cm... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Trim_Quality:
"""Class for working with trim_quality"""
def __init__(self, exe_path, logger):
"""Instantiate with location of executable"""
self._logger = logger
self._no_run = False
if not is_exe(exe_path):
self._logger.error('No trim_quality script available ... | the_stack_v2_python_sparse | metapy/pycits/seq_crumbs.py | peterthorpe5/public_scripts | train | 35 |
a9ae7db40d5dfe0db8a5b380b155cd97b0f46df2 | [
"n = len(nums)\ncounter = Counter(nums)\nfreq = SortedList(counter.values())\nfor i in range(n - 1, -1, -1):\n if len(freq) <= 1:\n return i + 1\n if freq[0] == 1 and freq[1] == freq[-1]:\n return i + 1\n if freq[0] == freq[-2] and freq[-1] == freq[-2] + 1:\n return i + 1\n num = nu... | <|body_start_0|>
n = len(nums)
counter = Counter(nums)
freq = SortedList(counter.values())
for i in range(n - 1, -1, -1):
if len(freq) <= 1:
return i + 1
if freq[0] == 1 and freq[1] == freq[-1]:
return i + 1
if freq[0] =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxEqualFreq(self, nums: List[int]) -> int:
"""有序集合维护有序的频率 during iteration 1. decrement the biggest count or 2. decrement the smallest count 移除最多或者最少的"""
<|body_0|>
def maxEqualFreq2(self, nums: List[int]) -> int:
"""分三种情况讨论 1. 最大出现次数 maxFreq == 1 随意删除... | stack_v2_sparse_classes_10k_train_006951 | 3,113 | no_license | [
{
"docstring": "有序集合维护有序的频率 during iteration 1. decrement the biggest count or 2. decrement the smallest count 移除最多或者最少的",
"name": "maxEqualFreq",
"signature": "def maxEqualFreq(self, nums: List[int]) -> int"
},
{
"docstring": "分三种情况讨论 1. 最大出现次数 maxFreq == 1 随意删除一个元素 2. 所有数出现次数都是 maxFreq 或者 maxF... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEqualFreq(self, nums: List[int]) -> int: 有序集合维护有序的频率 during iteration 1. decrement the biggest count or 2. decrement the smallest count 移除最多或者最少的
- def maxEqualFreq2(self,... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEqualFreq(self, nums: List[int]) -> int: 有序集合维护有序的频率 during iteration 1. decrement the biggest count or 2. decrement the smallest count 移除最多或者最少的
- def maxEqualFreq2(self,... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def maxEqualFreq(self, nums: List[int]) -> int:
"""有序集合维护有序的频率 during iteration 1. decrement the biggest count or 2. decrement the smallest count 移除最多或者最少的"""
<|body_0|>
def maxEqualFreq2(self, nums: List[int]) -> int:
"""分三种情况讨论 1. 最大出现次数 maxFreq == 1 随意删除... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxEqualFreq(self, nums: List[int]) -> int:
"""有序集合维护有序的频率 during iteration 1. decrement the biggest count or 2. decrement the smallest count 移除最多或者最少的"""
n = len(nums)
counter = Counter(nums)
freq = SortedList(counter.values())
for i in range(n - 1, -1, -... | the_stack_v2_python_sparse | 5_map/经典题/哈希表统计/1224. 最大相等频率-有序集合维护有序的频率.py | 981377660LMT/algorithm-study | train | 225 | |
cd2d54970da531e6bb5eaf99d1cbaed325663bf1 | [
"self.SetStartDate(2004, 1, 1)\nself.SetEndDate(2015, 1, 1)\nself.SetCash(100000)\nself.AddEquity('SPY', Resolution.Daily)\nself.__macd = self.MACD('SPY', 12, 26, 9, MovingAverageType.Exponential, Resolution.Daily)\nself.__previous = datetime.min\nself.PlotIndicator('MACD', True, self.__macd, self.__macd.Signal)\ns... | <|body_start_0|>
self.SetStartDate(2004, 1, 1)
self.SetEndDate(2015, 1, 1)
self.SetCash(100000)
self.AddEquity('SPY', Resolution.Daily)
self.__macd = self.MACD('SPY', 12, 26, 9, MovingAverageType.Exponential, Resolution.Daily)
self.__previous = datetime.min
self.P... | MACDTrendAlgorithm | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MACDTrendAlgorithm:
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
<|body_0|>
def OnData(self, data):
"""OnData event is the primary entry point for... | stack_v2_sparse_classes_10k_train_006952 | 2,822 | permissive | [
{
"docstring": "Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.",
"name": "Initialize",
"signature": "def Initialize(self)"
},
{
"docstring": "OnData event is the primary entry point for your algorithm. Eac... | 2 | null | Implement the Python class `MACDTrendAlgorithm` described below.
Class description:
Implement the MACDTrendAlgorithm class.
Method signatures and docstrings:
- def Initialize(self): Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized... | Implement the Python class `MACDTrendAlgorithm` described below.
Class description:
Implement the MACDTrendAlgorithm class.
Method signatures and docstrings:
- def Initialize(self): Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized... | b33dd3bc140e14b883f39ecf848a793cf7292277 | <|skeleton|>
class MACDTrendAlgorithm:
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
<|body_0|>
def OnData(self, data):
"""OnData event is the primary entry point for... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MACDTrendAlgorithm:
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
self.SetStartDate(2004, 1, 1)
self.SetEndDate(2015, 1, 1)
self.SetCash(100000)
self.... | the_stack_v2_python_sparse | Algorithm.Python/MACDTrendAlgorithm.py | Capnode/Algoloop | train | 87 | |
0f375f0f5bc5ff81b28b2302bee2d5b5a5954aac | [
"stack, curr = ([], root)\nres = []\nwhile stack or curr:\n if curr:\n res.append(str(curr.val))\n stack.append(curr)\n curr = curr.left\n else:\n res.append('None')\n curr = stack.pop()\n curr = curr.right\nprint(res)\nreturn ' '.join(res)",
"if not data:\n retu... | <|body_start_0|>
stack, curr = ([], root)
res = []
while stack or curr:
if curr:
res.append(str(curr.val))
stack.append(curr)
curr = curr.left
else:
res.append('None')
curr = stack.pop()
... | 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_10k_train_006953 | 4,842 | 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_001925 | 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:... | 63120dbaabd7c3c19633ebe952bcee4cf826b0e0 | <|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_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
stack, curr = ([], root)
res = []
while stack or curr:
if curr:
res.append(str(curr.val))
stack.append(curr)
c... | the_stack_v2_python_sparse | 297. Serialize and Deserialize Binary Tree _ tee.py | CaizhiXu/LeetCode-Python-Solutions | train | 0 | |
31f5a45e28ccb77adff1f5f3761e9297a121f0cd | [
"if not root:\n return -1\nret = 1 + max((self.findLeavesHelper(child, results) for child in (root.left, root.right)))\nif ret >= len(results):\n results.append([])\nresults[ret].append(root.val)\nreturn ret",
"ret = []\nself.findLeavesHelper(root, ret)\nreturn ret"
] | <|body_start_0|>
if not root:
return -1
ret = 1 + max((self.findLeavesHelper(child, results) for child in (root.left, root.right)))
if ret >= len(results):
results.append([])
results[ret].append(root.val)
return ret
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findLeavesHelper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
<|body_0|>
def findLeaves(self, root: TreeNode) -> List[List[int]]:
""":type root: TreeNode :rtype: List[List[int]]"""
... | stack_v2_sparse_classes_10k_train_006954 | 2,449 | no_license | [
{
"docstring": "push root and all descendants to results return the distance from root to farthest leaf",
"name": "findLeavesHelper",
"signature": "def findLeavesHelper(self, root, results)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "findLeaves",
"signatur... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLeavesHelper(self, root, results): push root and all descendants to results return the distance from root to farthest leaf
- def findLeaves(self, root: TreeNode) -> List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLeavesHelper(self, root, results): push root and all descendants to results return the distance from root to farthest leaf
- def findLeaves(self, root: TreeNode) -> List[... | f2621cd76822a922c49b60f32931f26cce1c571d | <|skeleton|>
class Solution:
def findLeavesHelper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
<|body_0|>
def findLeaves(self, root: TreeNode) -> List[List[int]]:
""":type root: TreeNode :rtype: List[List[int]]"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findLeavesHelper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
if not root:
return -1
ret = 1 + max((self.findLeavesHelper(child, results) for child in (root.left, root.right)))
if r... | the_stack_v2_python_sparse | Tree_and_BST/021_leetcode_P_366_FindLeavesOfBinaryTree/Solution.py | Keshav1506/competitive_programming | train | 0 | |
555ff7e75e6a06ccfb454c2367fd443e236d6063 | [
"super(PostProcessor, self).__init__()\nself.score_thresh = score_thresh\nself.nms = nms\nself.detections_per_img = detections_per_img\nif box_coder is None:\n box_coder = BoxCoder(weights=(10.0, 10.0, 5.0, 5.0))\nself.box_coder = box_coder\nself.cls_agnostic_bbox_reg = cls_agnostic_bbox_reg\nself.is_repeat = is... | <|body_start_0|>
super(PostProcessor, self).__init__()
self.score_thresh = score_thresh
self.nms = nms
self.detections_per_img = detections_per_img
if box_coder is None:
box_coder = BoxCoder(weights=(10.0, 10.0, 5.0, 5.0))
self.box_coder = box_coder
se... | From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results | PostProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostProcessor:
"""From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results"""
def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=None, cls_agnostic_bbox_reg=False, is_repeat... | stack_v2_sparse_classes_10k_train_006955 | 7,503 | permissive | [
{
"docstring": "Arguments: score_thresh (float) nms (float) detections_per_img (int) box_coder (BoxCoder)",
"name": "__init__",
"signature": "def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=None, cls_agnostic_bbox_reg=False, is_repeat=False)"
},
{
"docstring": "A... | 6 | stack_v2_sparse_classes_30k_train_003303 | Implement the Python class `PostProcessor` described below.
Class description:
From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results
Method signatures and docstrings:
- def __init__(self, score_thresh=0.05, nms=0.5, detections... | Implement the Python class `PostProcessor` described below.
Class description:
From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results
Method signatures and docstrings:
- def __init__(self, score_thresh=0.05, nms=0.5, detections... | a0c9ed8850abe740eedf8bfc6e1577cc0aa3fc7b | <|skeleton|>
class PostProcessor:
"""From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results"""
def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=None, cls_agnostic_bbox_reg=False, is_repeat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PostProcessor:
"""From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results"""
def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=None, cls_agnostic_bbox_reg=False, is_repeat=False):
... | the_stack_v2_python_sparse | rcnn/modeling/cascade_rcnn/inference.py | rs9899/Parsing-R-CNN | train | 0 |
d7de809cb6ec6c52b1835df62a2df121ee02c79e | [
"author = g.user\nnote = NoteModel.query.get(note_id)\nif not note:\n abort(404, error=f'Note with id={note_id} not found')\nif note.author != author:\n abort(403, error=f'Access denied to note with id={note_id}')\nreturn (note, 200)",
"author = g.user\nnote = NoteModel.query.get(note_id)\nif not note:\n ... | <|body_start_0|>
author = g.user
note = NoteModel.query.get(note_id)
if not note:
abort(404, error=f'Note with id={note_id} not found')
if note.author != author:
abort(403, error=f'Access denied to note with id={note_id}')
return (note, 200)
<|end_body_0|>... | NoteResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NoteResource:
def get(self, note_id):
"""Возвращает заметку пользователя. Требуется аутентификация. :param note_id: id заметки :return: замтку"""
<|body_0|>
def put(self, note_id, **kwargs):
"""Меняет заметку пользователя. Требуется аутентификация. :param note_id: id... | stack_v2_sparse_classes_10k_train_006956 | 11,305 | no_license | [
{
"docstring": "Возвращает заметку пользователя. Требуется аутентификация. :param note_id: id заметки :return: замтку",
"name": "get",
"signature": "def get(self, note_id)"
},
{
"docstring": "Меняет заметку пользователя. Требуется аутентификация. :param note_id: id заметки :param kwargs: парамет... | 3 | stack_v2_sparse_classes_30k_train_003101 | Implement the Python class `NoteResource` described below.
Class description:
Implement the NoteResource class.
Method signatures and docstrings:
- def get(self, note_id): Возвращает заметку пользователя. Требуется аутентификация. :param note_id: id заметки :return: замтку
- def put(self, note_id, **kwargs): Меняет з... | Implement the Python class `NoteResource` described below.
Class description:
Implement the NoteResource class.
Method signatures and docstrings:
- def get(self, note_id): Возвращает заметку пользователя. Требуется аутентификация. :param note_id: id заметки :return: замтку
- def put(self, note_id, **kwargs): Меняет з... | adb9a3f4524ab76e8ba656344e2ed452e87b577c | <|skeleton|>
class NoteResource:
def get(self, note_id):
"""Возвращает заметку пользователя. Требуется аутентификация. :param note_id: id заметки :return: замтку"""
<|body_0|>
def put(self, note_id, **kwargs):
"""Меняет заметку пользователя. Требуется аутентификация. :param note_id: id... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NoteResource:
def get(self, note_id):
"""Возвращает заметку пользователя. Требуется аутентификация. :param note_id: id заметки :return: замтку"""
author = g.user
note = NoteModel.query.get(note_id)
if not note:
abort(404, error=f'Note with id={note_id} not found')
... | the_stack_v2_python_sparse | api/resources/note.py | UshakovAleksandr/Blog | train | 1 | |
b105420447c6bebd1494e6b8cf1bcb9c0a81624a | [
"if k >= len(cardPoints):\n return sum(cardPoints)\nleft = [0] + list(itertools.accumulate(cardPoints))\nright = [0] + list(itertools.accumulate(reversed(cardPoints)))\nreturn max((left[i] + right[k - i] for i in range(k + 1)))",
"n = len(cardPoints) - 1\n\n@lru_cache(None)\ndef rec(i, j):\n if i + (n - j) ... | <|body_start_0|>
if k >= len(cardPoints):
return sum(cardPoints)
left = [0] + list(itertools.accumulate(cardPoints))
right = [0] + list(itertools.accumulate(reversed(cardPoints)))
return max((left[i] + right[k - i] for i in range(k + 1)))
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxScore(self, cardPoints: List[int], k: int) -> int:
"""05/27/2021 15:20 DP Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def maxScore(self, cardPoints: List[int], k: int) -> int:
"""TLE"""
<|body_1|>
def maxScore(self, cardPo... | stack_v2_sparse_classes_10k_train_006957 | 3,048 | no_license | [
{
"docstring": "05/27/2021 15:20 DP Time complexity: O(n) Space complexity: O(n)",
"name": "maxScore",
"signature": "def maxScore(self, cardPoints: List[int], k: int) -> int"
},
{
"docstring": "TLE",
"name": "maxScore",
"signature": "def maxScore(self, cardPoints: List[int], k: int) -> i... | 3 | stack_v2_sparse_classes_30k_train_006975 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxScore(self, cardPoints: List[int], k: int) -> int: 05/27/2021 15:20 DP Time complexity: O(n) Space complexity: O(n)
- def maxScore(self, cardPoints: List[int], k: int) -> ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxScore(self, cardPoints: List[int], k: int) -> int: 05/27/2021 15:20 DP Time complexity: O(n) Space complexity: O(n)
- def maxScore(self, cardPoints: List[int], k: int) -> ... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def maxScore(self, cardPoints: List[int], k: int) -> int:
"""05/27/2021 15:20 DP Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def maxScore(self, cardPoints: List[int], k: int) -> int:
"""TLE"""
<|body_1|>
def maxScore(self, cardPo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxScore(self, cardPoints: List[int], k: int) -> int:
"""05/27/2021 15:20 DP Time complexity: O(n) Space complexity: O(n)"""
if k >= len(cardPoints):
return sum(cardPoints)
left = [0] + list(itertools.accumulate(cardPoints))
right = [0] + list(itertool... | the_stack_v2_python_sparse | leetcode/solved/1538_Maximum_Points_You_Can_Obtain_from_Cards/solution.py | sungminoh/algorithms | train | 0 | |
9efc50638e516b542eddacc588fcc642faf7b0cd | [
"self.url = url\nheaders = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.75 Safari/537.36 Maxthon/5.1.3.2000'}\nr = requests.get(url=self.url, headers=headers)\nif r.status_code == 200:\n self.text = r.text\nelse:\n self.text = None",
"if self.te... | <|body_start_0|>
self.url = url
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.75 Safari/537.36 Maxthon/5.1.3.2000'}
r = requests.get(url=self.url, headers=headers)
if r.status_code == 200:
self.text = r.t... | Extract_link | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Extract_link:
def __init__(self, url):
"""初始化时访问url并将response的内容存储起来"""
<|body_0|>
def extract_link(self):
"""从页面中分析出链接"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.url = url
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW... | stack_v2_sparse_classes_10k_train_006958 | 1,794 | no_license | [
{
"docstring": "初始化时访问url并将response的内容存储起来",
"name": "__init__",
"signature": "def __init__(self, url)"
},
{
"docstring": "从页面中分析出链接",
"name": "extract_link",
"signature": "def extract_link(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004509 | Implement the Python class `Extract_link` described below.
Class description:
Implement the Extract_link class.
Method signatures and docstrings:
- def __init__(self, url): 初始化时访问url并将response的内容存储起来
- def extract_link(self): 从页面中分析出链接 | Implement the Python class `Extract_link` described below.
Class description:
Implement the Extract_link class.
Method signatures and docstrings:
- def __init__(self, url): 初始化时访问url并将response的内容存储起来
- def extract_link(self): 从页面中分析出链接
<|skeleton|>
class Extract_link:
def __init__(self, url):
"""初始化时访问u... | 355c7251dda058deefc80f3bffbf6c541d92ad41 | <|skeleton|>
class Extract_link:
def __init__(self, url):
"""初始化时访问url并将response的内容存储起来"""
<|body_0|>
def extract_link(self):
"""从页面中分析出链接"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Extract_link:
def __init__(self, url):
"""初始化时访问url并将response的内容存储起来"""
self.url = url
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.75 Safari/537.36 Maxthon/5.1.3.2000'}
r = requests.get(url=self.url, head... | the_stack_v2_python_sparse | module4-04threads/spider.py | echolvan/homework | train | 0 | |
b94c9c7d7c2f42509bd2d6aaa8a39c14b9b05835 | [
"stack = []\ncurstring = ''\ncurnum = 0\nfor c in s:\n if c == '[':\n stack.append(curstring)\n stack.append(curnum)\n curnum = 0\n curstring = ''\n elif c == ']':\n num = stack.pop()\n prevstring = stack.pop()\n curstring = prevstring + num * curstring\n el... | <|body_start_0|>
stack = []
curstring = ''
curnum = 0
for c in s:
if c == '[':
stack.append(curstring)
stack.append(curnum)
curnum = 0
curstring = ''
elif c == ']':
num = stack.pop()
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def decodeString(self, s):
"""Stack time O(S+|s|) space O(S) 本题难点在于括号内嵌套括号，需要从内向外生成与拼接字符串，这与栈的先入后出特性对应。 算法流程： 构建辅助栈 stack， 遍历字符串 s 中每个字符 c； 当 c 为数字时，将数字字符转化为数字 multi，用于后续倍数计算； 当 c 为字母时，在 res 尾部添加 c； 当 c 为 [ 时，将当前 multi 和 res 入栈，并分别置空置 000： 记录此 [ 前的临时结果 res 至栈，用于发现对应 ] 后的拼接操作； 记... | stack_v2_sparse_classes_10k_train_006959 | 3,130 | no_license | [
{
"docstring": "Stack time O(S+|s|) space O(S) 本题难点在于括号内嵌套括号，需要从内向外生成与拼接字符串，这与栈的先入后出特性对应。 算法流程： 构建辅助栈 stack， 遍历字符串 s 中每个字符 c； 当 c 为数字时，将数字字符转化为数字 multi，用于后续倍数计算； 当 c 为字母时，在 res 尾部添加 c； 当 c 为 [ 时，将当前 multi 和 res 入栈，并分别置空置 000： 记录此 [ 前的临时结果 res 至栈，用于发现对应 ] 后的拼接操作； 记录此 [ 前的倍数 multi 至栈，用于发现对应 ] 后，获取 multi × [...] 字... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString(self, s): Stack time O(S+|s|) space O(S) 本题难点在于括号内嵌套括号，需要从内向外生成与拼接字符串，这与栈的先入后出特性对应。 算法流程： 构建辅助栈 stack， 遍历字符串 s 中每个字符 c； 当 c 为数字时，将数字字符转化为数字 multi，用于后续倍数计算； 当 c 为... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString(self, s): Stack time O(S+|s|) space O(S) 本题难点在于括号内嵌套括号，需要从内向外生成与拼接字符串，这与栈的先入后出特性对应。 算法流程： 构建辅助栈 stack， 遍历字符串 s 中每个字符 c； 当 c 为数字时，将数字字符转化为数字 multi，用于后续倍数计算； 当 c 为... | 85f71621c54f6b0029f3a2746f022f89dd7419d9 | <|skeleton|>
class Solution:
def decodeString(self, s):
"""Stack time O(S+|s|) space O(S) 本题难点在于括号内嵌套括号，需要从内向外生成与拼接字符串，这与栈的先入后出特性对应。 算法流程： 构建辅助栈 stack， 遍历字符串 s 中每个字符 c； 当 c 为数字时，将数字字符转化为数字 multi，用于后续倍数计算； 当 c 为字母时，在 res 尾部添加 c； 当 c 为 [ 时，将当前 multi 和 res 入栈，并分别置空置 000： 记录此 [ 前的临时结果 res 至栈，用于发现对应 ] 后的拼接操作； 记... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def decodeString(self, s):
"""Stack time O(S+|s|) space O(S) 本题难点在于括号内嵌套括号，需要从内向外生成与拼接字符串，这与栈的先入后出特性对应。 算法流程： 构建辅助栈 stack， 遍历字符串 s 中每个字符 c； 当 c 为数字时，将数字字符转化为数字 multi，用于后续倍数计算； 当 c 为字母时，在 res 尾部添加 c； 当 c 为 [ 时，将当前 multi 和 res 入栈，并分别置空置 000： 记录此 [ 前的临时结果 res 至栈，用于发现对应 ] 后的拼接操作； 记录此 [ 前的倍数 mult... | the_stack_v2_python_sparse | LeetCode/Stack/394_decode_string.py | XyK0907/for_work | train | 0 | |
ed2e07a76bfac34836053d5b79eaf2386e0fe269 | [
"if output_image_topic is not None:\n self.image_publisher = rospy.Publisher(output_image_topic, ROS_Image, queue_size=10)\nelse:\n self.image_publisher = None\nrospy.Subscriber(input_image_topic, ROS_Image, self.callback)\nself.bridge = ROSBridge()\nself.ID = 0\nself.parser = argparse.ArgumentParser()\nself.... | <|body_start_0|>
if output_image_topic is not None:
self.image_publisher = rospy.Publisher(output_image_topic, ROS_Image, queue_size=10)
else:
self.image_publisher = None
rospy.Subscriber(input_image_topic, ROS_Image, self.callback)
self.bridge = ROSBridge()
... | Synthetic_Data_Generation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Synthetic_Data_Generation:
def __init__(self, input_image_topic='/usb_cam/image_raw', output_image_topic='/opendr/synthetic_facial_images', device='cuda'):
"""Creates a ROS Node for SyntheticDataGeneration :param input_image_topic: Topic from which we are reading the input image :type in... | stack_v2_sparse_classes_10k_train_006960 | 5,315 | permissive | [
{
"docstring": "Creates a ROS Node for SyntheticDataGeneration :param input_image_topic: Topic from which we are reading the input image :type input_image_topic: str :param output_image_topic: Topic to which we are publishing the synthetic facial image (if None, we are not publishing any image) :type output_ima... | 3 | stack_v2_sparse_classes_30k_train_004152 | Implement the Python class `Synthetic_Data_Generation` described below.
Class description:
Implement the Synthetic_Data_Generation class.
Method signatures and docstrings:
- def __init__(self, input_image_topic='/usb_cam/image_raw', output_image_topic='/opendr/synthetic_facial_images', device='cuda'): Creates a ROS N... | Implement the Python class `Synthetic_Data_Generation` described below.
Class description:
Implement the Synthetic_Data_Generation class.
Method signatures and docstrings:
- def __init__(self, input_image_topic='/usb_cam/image_raw', output_image_topic='/opendr/synthetic_facial_images', device='cuda'): Creates a ROS N... | b3d6ce670cdf63469fc5766630eb295d67b3d788 | <|skeleton|>
class Synthetic_Data_Generation:
def __init__(self, input_image_topic='/usb_cam/image_raw', output_image_topic='/opendr/synthetic_facial_images', device='cuda'):
"""Creates a ROS Node for SyntheticDataGeneration :param input_image_topic: Topic from which we are reading the input image :type in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Synthetic_Data_Generation:
def __init__(self, input_image_topic='/usb_cam/image_raw', output_image_topic='/opendr/synthetic_facial_images', device='cuda'):
"""Creates a ROS Node for SyntheticDataGeneration :param input_image_topic: Topic from which we are reading the input image :type input_image_topi... | the_stack_v2_python_sparse | projects/opendr_ws/src/opendr_data_generation/scripts/synthetic_facial_generation_node.py | opendr-eu/opendr | train | 535 | |
6b0a3c65d424a58eca674bfeb5e503dda88075f4 | [
"with self.assertRaise(ValueError) as error:\n Yearly_Income('a', 2001)\nself.assertTrue('Invalid type for data passed into this class' in str(error.exception))",
"with self.assertRaise(ValueError) as error:\n Yearly_Income(data, 'a')\nself.assertTrue('Improper type for year passed into this class' in str(e... | <|body_start_0|>
with self.assertRaise(ValueError) as error:
Yearly_Income('a', 2001)
self.assertTrue('Invalid type for data passed into this class' in str(error.exception))
<|end_body_0|>
<|body_start_1|>
with self.assertRaise(ValueError) as error:
Yearly_Income(data, '... | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
def income_test1(self):
"""This function tests to see that the proper Error is raised when something besides a dataframe is passed for data into the class"""
<|body_0|>
def income_test2(self):
"""This function tests to see that the proper Error is raised when s... | stack_v2_sparse_classes_10k_train_006961 | 1,630 | no_license | [
{
"docstring": "This function tests to see that the proper Error is raised when something besides a dataframe is passed for data into the class",
"name": "income_test1",
"signature": "def income_test1(self)"
},
{
"docstring": "This function tests to see that the proper Error is raised when somet... | 3 | stack_v2_sparse_classes_30k_train_000412 | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def income_test1(self): This function tests to see that the proper Error is raised when something besides a dataframe is passed for data into the class
- def income_test2(self): This fun... | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def income_test1(self): This function tests to see that the proper Error is raised when something besides a dataframe is passed for data into the class
- def income_test2(self): This fun... | f5bb1e51de4f84ab3dd62d3073aee4f56534afa1 | <|skeleton|>
class Test:
def income_test1(self):
"""This function tests to see that the proper Error is raised when something besides a dataframe is passed for data into the class"""
<|body_0|>
def income_test2(self):
"""This function tests to see that the proper Error is raised when s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test:
def income_test1(self):
"""This function tests to see that the proper Error is raised when something besides a dataframe is passed for data into the class"""
with self.assertRaise(ValueError) as error:
Yearly_Income('a', 2001)
self.assertTrue('Invalid type for data pa... | the_stack_v2_python_sparse | sar516/tests.py | ds-ga-1007/assignment9 | train | 2 | |
6e37b1348c1be40e545799b6bc4e433b804de5af | [
"self.__author__ = 'GodSaveTheDoge'\nself.selector = '#mw-content-text li , p'\nself.url = 'https://{}.wikipedia.org/wiki/{}'\nself.apiurl = 'https://en.wikipedia.org/w/api.php?action=query&titles={}&format=json'",
"if '-1' in requests.get(self.apiurl.format(page)).json()['query']['pages']:\n return False\nret... | <|body_start_0|>
self.__author__ = 'GodSaveTheDoge'
self.selector = '#mw-content-text li , p'
self.url = 'https://{}.wikipedia.org/wiki/{}'
self.apiurl = 'https://en.wikipedia.org/w/api.php?action=query&titles={}&format=json'
<|end_body_0|>
<|body_start_1|>
if '-1' in requests.g... | Wikipedia | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Wikipedia:
def __init__(self) -> None:
"""You can use this class to look up a page on wikipedia"""
<|body_0|>
def exists(self, page: str) -> bool:
"""Check if a page exists :param page: url of the page :return:"""
<|body_1|>
def getpage(self, page: str, ... | stack_v2_sparse_classes_10k_train_006962 | 1,240 | no_license | [
{
"docstring": "You can use this class to look up a page on wikipedia",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Check if a page exists :param page: url of the page :return:",
"name": "exists",
"signature": "def exists(self, page: str) -> bool"
}... | 3 | stack_v2_sparse_classes_30k_train_002278 | Implement the Python class `Wikipedia` described below.
Class description:
Implement the Wikipedia class.
Method signatures and docstrings:
- def __init__(self) -> None: You can use this class to look up a page on wikipedia
- def exists(self, page: str) -> bool: Check if a page exists :param page: url of the page :re... | Implement the Python class `Wikipedia` described below.
Class description:
Implement the Wikipedia class.
Method signatures and docstrings:
- def __init__(self) -> None: You can use this class to look up a page on wikipedia
- def exists(self, page: str) -> bool: Check if a page exists :param page: url of the page :re... | cc0db796c5516b36e82ef6f70c5649902366df62 | <|skeleton|>
class Wikipedia:
def __init__(self) -> None:
"""You can use this class to look up a page on wikipedia"""
<|body_0|>
def exists(self, page: str) -> bool:
"""Check if a page exists :param page: url of the page :return:"""
<|body_1|>
def getpage(self, page: str, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Wikipedia:
def __init__(self) -> None:
"""You can use this class to look up a page on wikipedia"""
self.__author__ = 'GodSaveTheDoge'
self.selector = '#mw-content-text li , p'
self.url = 'https://{}.wikipedia.org/wiki/{}'
self.apiurl = 'https://en.wikipedia.org/w/api.ph... | the_stack_v2_python_sparse | methods/Wiki.py | ankit-sinha-18/MultiUserbot | train | 0 | |
f463be88b853bbd18d79428e0b26cc2b489eba14 | [
"self.k = k\nself.arr = nums\nself.arr.sort()\nwhile len(self.arr) > self.k:\n self.arr.pop(0)",
"self.arr.append(val)\nself.arr.sort()\nif len(self.arr) > self.k:\n self.arr.pop(0)\nreturn self.arr[0]"
] | <|body_start_0|>
self.k = k
self.arr = nums
self.arr.sort()
while len(self.arr) > self.k:
self.arr.pop(0)
<|end_body_0|>
<|body_start_1|>
self.arr.append(val)
self.arr.sort()
if len(self.arr) > self.k:
self.arr.pop(0)
return self.a... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
self.arr = nums
self.arr.sort()... | stack_v2_sparse_classes_10k_train_006963 | 630 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002710 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 920b65db80031fad45d495431eda8d3fb4ef06e5 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
self.arr = nums
self.arr.sort()
while len(self.arr) > self.k:
self.arr.pop(0)
def add(self, val):
""":type val: int :rtype: int"""
self.arr.appe... | the_stack_v2_python_sparse | easy/ex703.py | ziyuan-shen/leetcode_algorithm_python_solution | train | 2 | |
34214125728ef5378fc0039be119a79c54feb478 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn PrintTaskDefinition()",
"from .app_identity import AppIdentity\nfrom .entity import Entity\nfrom .print_task import PrintTask\nfrom .app_identity import AppIdentity\nfrom .entity import Entity\nfrom .print_task import PrintTask\nfields... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return PrintTaskDefinition()
<|end_body_0|>
<|body_start_1|>
from .app_identity import AppIdentity
from .entity import Entity
from .print_task import PrintTask
from .app_identit... | PrintTaskDefinition | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrintTaskDefinition:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintTaskDefinition:
"""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 ob... | stack_v2_sparse_classes_10k_train_006964 | 2,858 | 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: PrintTaskDefinition",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | stack_v2_sparse_classes_30k_train_001973 | Implement the Python class `PrintTaskDefinition` described below.
Class description:
Implement the PrintTaskDefinition class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintTaskDefinition: Creates a new instance of the appropriate class based on d... | Implement the Python class `PrintTaskDefinition` described below.
Class description:
Implement the PrintTaskDefinition class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintTaskDefinition: Creates a new instance of the appropriate class based on d... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class PrintTaskDefinition:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintTaskDefinition:
"""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 ob... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrintTaskDefinition:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PrintTaskDefinition:
"""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: ... | the_stack_v2_python_sparse | msgraph/generated/models/print_task_definition.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
90bb4f0e13c4dfbad464e855fa6ce8530677ba8b | [
"if not -2 ** 31 < x < 2 ** 31 - 1:\n return 0\nif x < 0:\n y = int(str(-x)[::-1]) * -1\nelse:\n y = int(str(x)[::-1])\nif not -2 ** 31 < y < 2 ** 31 - 1:\n return 0\nreturn y",
"x = str(x)\nif '-' not in str(x):\n y = int(str(x)[::-1])\nelse:\n x = [v for v in x if v != '-']\n x = ''.join(x)... | <|body_start_0|>
if not -2 ** 31 < x < 2 ** 31 - 1:
return 0
if x < 0:
y = int(str(-x)[::-1]) * -1
else:
y = int(str(x)[::-1])
if not -2 ** 31 < y < 2 ** 31 - 1:
return 0
return y
<|end_body_0|>
<|body_start_1|>
x = str(x)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse_str(self, x):
""":type x: int :rtype: int"""
<|body_1|>
def reverse_math(self, x):
""":type x: int :rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_10k_train_006965 | 1,905 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "reverse",
"signature": "def reverse(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse_str",
"signature": "def reverse_str(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse_math",... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def reverse_str(self, x): :type x: int :rtype: int
- def reverse_math(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def reverse_str(self, x): :type x: int :rtype: int
- def reverse_math(self, x): :type x: int :rtype: int
<|skeleton|>
class Solu... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse_str(self, x):
""":type x: int :rtype: int"""
<|body_1|>
def reverse_math(self, x):
""":type x: int :rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
if not -2 ** 31 < x < 2 ** 31 - 1:
return 0
if x < 0:
y = int(str(-x)[::-1]) * -1
else:
y = int(str(x)[::-1])
if not -2 ** 31 < y < 2 ** 31 - 1:
return 0
... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00007.Reverse Integer.py | roger6blog/LeetCode | train | 0 | |
ea97491740fdb756629ae14602b1db028a3c93fa | [
"leoTkinterDialog.__init__(self, title, resizeable)\nself.createTopFrame()\nself.top.bind('<Key>', self.onKey)\nif message:\n self.createMessageFrame(message)\nbuttons = ({'text': 'Yes', 'command': self.yesButton, 'default': True}, {'text': 'No', 'command': self.noButton})\nself.createButtons(buttons)",
"ch = ... | <|body_start_0|>
leoTkinterDialog.__init__(self, title, resizeable)
self.createTopFrame()
self.top.bind('<Key>', self.onKey)
if message:
self.createMessageFrame(message)
buttons = ({'text': 'Yes', 'command': self.yesButton, 'default': True}, {'text': 'No', 'command': ... | A class that creates a Tkinter dialog with two buttons: Yes and No. | tkinterAskYesNo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class tkinterAskYesNo:
"""A class that creates a Tkinter dialog with two buttons: Yes and No."""
def __init__(self, title, message=None, resizeable=False):
"""Create a dialog having yes and no buttons."""
<|body_0|>
def onKey(self, event):
"""Handle keystroke events in... | stack_v2_sparse_classes_10k_train_006966 | 25,997 | no_license | [
{
"docstring": "Create a dialog having yes and no buttons.",
"name": "__init__",
"signature": "def __init__(self, title, message=None, resizeable=False)"
},
{
"docstring": "Handle keystroke events in dialogs having yes and no buttons.",
"name": "onKey",
"signature": "def onKey(self, even... | 2 | stack_v2_sparse_classes_30k_val_000224 | Implement the Python class `tkinterAskYesNo` described below.
Class description:
A class that creates a Tkinter dialog with two buttons: Yes and No.
Method signatures and docstrings:
- def __init__(self, title, message=None, resizeable=False): Create a dialog having yes and no buttons.
- def onKey(self, event): Handl... | Implement the Python class `tkinterAskYesNo` described below.
Class description:
A class that creates a Tkinter dialog with two buttons: Yes and No.
Method signatures and docstrings:
- def __init__(self, title, message=None, resizeable=False): Create a dialog having yes and no buttons.
- def onKey(self, event): Handl... | 28c22721e1bc313c120a8a6c288893bc566a5c67 | <|skeleton|>
class tkinterAskYesNo:
"""A class that creates a Tkinter dialog with two buttons: Yes and No."""
def __init__(self, title, message=None, resizeable=False):
"""Create a dialog having yes and no buttons."""
<|body_0|>
def onKey(self, event):
"""Handle keystroke events in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class tkinterAskYesNo:
"""A class that creates a Tkinter dialog with two buttons: Yes and No."""
def __init__(self, title, message=None, resizeable=False):
"""Create a dialog having yes and no buttons."""
leoTkinterDialog.__init__(self, title, resizeable)
self.createTopFrame()
s... | the_stack_v2_python_sparse | Projects/jyleo/src/leoTkinterDialog.py | leo-editor/leo-editor-contrib | train | 6 |
d2d592d3ecb224608f13f4e89ae27264652d4913 | [
"count = 0\nflag = 1\nwhile flag <= n:\n if n & flag:\n count += 1\n flag = flag << 1\n print(flag)\nprint(count)\nreturn count",
"count = 0\nwhile n:\n count += 1\n n = n - 1 & n\nreturn count"
] | <|body_start_0|>
count = 0
flag = 1
while flag <= n:
if n & flag:
count += 1
flag = flag << 1
print(flag)
print(count)
return count
<|end_body_0|>
<|body_start_1|>
count = 0
while n:
count += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hammingWeight(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def hammingWeight2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
count = 0
flag = 1
while flag <= n:
... | stack_v2_sparse_classes_10k_train_006967 | 606 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "hammingWeight",
"signature": "def hammingWeight(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "hammingWeight2",
"signature": "def hammingWeight2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006155 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hammingWeight(self, n): :type n: int :rtype: int
- def hammingWeight2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hammingWeight(self, n): :type n: int :rtype: int
- def hammingWeight2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def hammingWeight(self, n):
... | 38eec6f07fdc16658372490cd8c68dcb3d88a77f | <|skeleton|>
class Solution:
def hammingWeight(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def hammingWeight2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def hammingWeight(self, n):
""":type n: int :rtype: int"""
count = 0
flag = 1
while flag <= n:
if n & flag:
count += 1
flag = flag << 1
print(flag)
print(count)
return count
def hammingWeight2(se... | the_stack_v2_python_sparse | offer/15.py | gebijiaxiaowang/leetcode | train | 0 | |
9a24c9335ef51e078bb970aa7705783607e06e86 | [
"Editeur.__init__(self, pere, objet, attribut)\nself.ajouter_option('n', self.opt_creer_etat)\nself.ajouter_option('d', self.opt_supprimer_etat)",
"prototype = self.objet\nmsg = '| |tit|' + 'Edition des états de {}'.format(prototype).ljust(76)\nmsg += '|ff||\\n' + self.opts.separateur + '\\n'\nmsg += 'Options :\\... | <|body_start_0|>
Editeur.__init__(self, pere, objet, attribut)
self.ajouter_option('n', self.opt_creer_etat)
self.ajouter_option('d', self.opt_supprimer_etat)
<|end_body_0|>
<|body_start_1|>
prototype = self.objet
msg = '| |tit|' + 'Edition des états de {}'.format(prototype).lju... | Contexte-éditeur d'édition des états. | EdtEtats | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdtEtats:
"""Contexte-éditeur d'édition des états."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def accueil(self):
"""Message d'accueil du contexte"""
<|body_1|>
def opt_creer_etat(self, arguments... | stack_v2_sparse_classes_10k_train_006968 | 4,367 | permissive | [
{
"docstring": "Constructeur de l'éditeur",
"name": "__init__",
"signature": "def __init__(self, pere, objet=None, attribut=None)"
},
{
"docstring": "Message d'accueil du contexte",
"name": "accueil",
"signature": "def accueil(self)"
},
{
"docstring": "Crée un nouvel état. Syntax... | 5 | null | Implement the Python class `EdtEtats` described below.
Class description:
Contexte-éditeur d'édition des états.
Method signatures and docstrings:
- def __init__(self, pere, objet=None, attribut=None): Constructeur de l'éditeur
- def accueil(self): Message d'accueil du contexte
- def opt_creer_etat(self, arguments): C... | Implement the Python class `EdtEtats` described below.
Class description:
Contexte-éditeur d'édition des états.
Method signatures and docstrings:
- def __init__(self, pere, objet=None, attribut=None): Constructeur de l'éditeur
- def accueil(self): Message d'accueil du contexte
- def opt_creer_etat(self, arguments): C... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class EdtEtats:
"""Contexte-éditeur d'édition des états."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def accueil(self):
"""Message d'accueil du contexte"""
<|body_1|>
def opt_creer_etat(self, arguments... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EdtEtats:
"""Contexte-éditeur d'édition des états."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur"""
Editeur.__init__(self, pere, objet, attribut)
self.ajouter_option('n', self.opt_creer_etat)
self.ajouter_option('d', self.opt_supprime... | the_stack_v2_python_sparse | src/primaires/salle/editeurs/sbedit/edt_etats.py | vincent-lg/tsunami | train | 5 |
6944c738e108175e6c7a35cda0a120ffcf5e1c54 | [
"self.attr_flags = attr_flags\nself.dest_value = dest_value\nself.ldap_name = ldap_name\nself.same_value = same_value\nself.source_value = source_value\nself.status = status",
"if dictionary is None:\n return None\nattr_flags = dictionary.get('attrFlags')\ndest_value = cohesity_management_sdk.models.compare_ad... | <|body_start_0|>
self.attr_flags = attr_flags
self.dest_value = dest_value
self.ldap_name = ldap_name
self.same_value = same_value
self.source_value = source_value
self.status = status
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None... | Implementation of the 'CompareADObjectsResult_ADAttribute' model. TODO: type description here. Attributes: attr_flags (int): Object result flags of type ADAttributeFlags. dest_value (CompareADObjectsResult_ADAttributeValue): Destination attribute value if dest value exists (!ADAttributeFlags.kNotFound) and is different... | CompareADObjectsResult_ADAttribute | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompareADObjectsResult_ADAttribute:
"""Implementation of the 'CompareADObjectsResult_ADAttribute' model. TODO: type description here. Attributes: attr_flags (int): Object result flags of type ADAttributeFlags. dest_value (CompareADObjectsResult_ADAttributeValue): Destination attribute value if de... | stack_v2_sparse_classes_10k_train_006969 | 3,784 | permissive | [
{
"docstring": "Constructor for the CompareADObjectsResult_ADAttribute class",
"name": "__init__",
"signature": "def __init__(self, attr_flags=None, dest_value=None, ldap_name=None, same_value=None, source_value=None, status=None)"
},
{
"docstring": "Creates an instance of this model from a dict... | 2 | null | Implement the Python class `CompareADObjectsResult_ADAttribute` described below.
Class description:
Implementation of the 'CompareADObjectsResult_ADAttribute' model. TODO: type description here. Attributes: attr_flags (int): Object result flags of type ADAttributeFlags. dest_value (CompareADObjectsResult_ADAttributeVa... | Implement the Python class `CompareADObjectsResult_ADAttribute` described below.
Class description:
Implementation of the 'CompareADObjectsResult_ADAttribute' model. TODO: type description here. Attributes: attr_flags (int): Object result flags of type ADAttributeFlags. dest_value (CompareADObjectsResult_ADAttributeVa... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CompareADObjectsResult_ADAttribute:
"""Implementation of the 'CompareADObjectsResult_ADAttribute' model. TODO: type description here. Attributes: attr_flags (int): Object result flags of type ADAttributeFlags. dest_value (CompareADObjectsResult_ADAttributeValue): Destination attribute value if de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CompareADObjectsResult_ADAttribute:
"""Implementation of the 'CompareADObjectsResult_ADAttribute' model. TODO: type description here. Attributes: attr_flags (int): Object result flags of type ADAttributeFlags. dest_value (CompareADObjectsResult_ADAttributeValue): Destination attribute value if dest value exis... | the_stack_v2_python_sparse | cohesity_management_sdk/models/compare_ad_objects_result_ad_attribute.py | cohesity/management-sdk-python | train | 24 |
7d9810ea4d21b6a6becb8acb1572f7495b048e6b | [
"self.m = collections.defaultdict(list)\nfor i, word in enumerate(words):\n self.m[word].append(i)",
"idx1, idx2 = (self.m[word1], self.m[word2])\nres = float('inf')\ni = j = 0\nwhile i < len(idx1) and j < len(idx2):\n res = min(res, abs(idx1[i] - idx2[j]))\n if idx1[i] < idx2[j]:\n i += 1\n el... | <|body_start_0|>
self.m = collections.defaultdict(list)
for i, word in enumerate(words):
self.m[word].append(i)
<|end_body_0|>
<|body_start_1|>
idx1, idx2 = (self.m[word1], self.m[word2])
res = float('inf')
i = j = 0
while i < len(idx1) and j < len(idx2):
... | WordDistance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.m = collections.defaultdict(list... | stack_v2_sparse_classes_10k_train_006970 | 785 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortest(self, word1, word2)"
}
] | 2 | null | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int
<|skeleton|>
class WordDistance:
... | 5b14b6f42baf59b04cbcc8e115df4272029b64c8 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
self.m = collections.defaultdict(list)
for i, word in enumerate(words):
self.m[word].append(i)
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
id... | the_stack_v2_python_sparse | LeetCode/0244.Shortest-Word-Distance-Ii/Shortest-Word-Distance-Ii.py | htingwang/HandsOnAlgoDS | train | 12 | |
a7c6de54e0b4448064476e07c284c9ace13e00fd | [
"cnt = [0] * 2\nleft, right = (0, 0)\nres = 0\nwhile right < len(nums):\n cnt[nums[right]] += 1\n if nums[right] == 0:\n while cnt[0] > k:\n cnt[nums[left]] -= 1\n left += 1\n if cnt[0] <= k:\n while right + 1 < len(nums) and nums[right + 1] == 1:\n right += 1... | <|body_start_0|>
cnt = [0] * 2
left, right = (0, 0)
res = 0
while right < len(nums):
cnt[nums[right]] += 1
if nums[right] == 0:
while cnt[0] > k:
cnt[nums[left]] -= 1
left += 1
if cnt[0] <= k:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestOnes(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def longestOnes2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cnt = [0] * ... | stack_v2_sparse_classes_10k_train_006971 | 1,278 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "longestOnes",
"signature": "def longestOnes(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "longestOnes2",
"signature": "def longestOnes2(self, nums, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003844 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestOnes(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def longestOnes2(self, nums, k): :type nums: List[int] :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestOnes(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def longestOnes2(self, nums, k): :type nums: List[int] :type k: int :rtype: int
<|skeleton|>
cla... | a32a1add8720de35e0ddc0c51efe781fb04c9d4a | <|skeleton|>
class Solution:
def longestOnes(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def longestOnes2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestOnes(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
cnt = [0] * 2
left, right = (0, 0)
res = 0
while right < len(nums):
cnt[nums[right]] += 1
if nums[right] == 0:
while cnt[0] > k:
... | the_stack_v2_python_sparse | 双指针/leetcode_1004_Max_Consecutive_Ones_III.py | cleverer123/Algorithm | train | 0 | |
cfe39d4fe3842f1c1a8a268abb61be7c34dda5be | [
"self._multFE = ',' in self._how\nif self._multFE:\n self._sepFE = self._how.split(', ')\nelse:\n self._sepFE = self._how\nif self._multFE:\n self._boolCombFE = ['x' in FE for FE in self._sepFE]\nelse:\n self._boolCombFE = 'x' in self._sepFE\nreturn self",
"if not self._multFE:\n if self._boolCombF... | <|body_start_0|>
self._multFE = ',' in self._how
if self._multFE:
self._sepFE = self._how.split(', ')
else:
self._sepFE = self._how
if self._multFE:
self._boolCombFE = ['x' in FE for FE in self._sepFE]
else:
self._boolCombFE = 'x' i... | Transformation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformation:
def inventorizeFE(self):
"""Function to determine how to transform"""
<|body_0|>
def FEColumns(self):
"""Creates the correct FE columns. If there are any combinations of FE the method creates a new column"""
<|body_1|>
def dataTransformat... | stack_v2_sparse_classes_10k_train_006972 | 35,310 | no_license | [
{
"docstring": "Function to determine how to transform",
"name": "inventorizeFE",
"signature": "def inventorizeFE(self)"
},
{
"docstring": "Creates the correct FE columns. If there are any combinations of FE the method creates a new column",
"name": "FEColumns",
"signature": "def FEColum... | 4 | stack_v2_sparse_classes_30k_train_006953 | Implement the Python class `Transformation` described below.
Class description:
Implement the Transformation class.
Method signatures and docstrings:
- def inventorizeFE(self): Function to determine how to transform
- def FEColumns(self): Creates the correct FE columns. If there are any combinations of FE the method ... | Implement the Python class `Transformation` described below.
Class description:
Implement the Transformation class.
Method signatures and docstrings:
- def inventorizeFE(self): Function to determine how to transform
- def FEColumns(self): Creates the correct FE columns. If there are any combinations of FE the method ... | fd00afeae5ea691ca060c1e2b4fa9683a5c1f039 | <|skeleton|>
class Transformation:
def inventorizeFE(self):
"""Function to determine how to transform"""
<|body_0|>
def FEColumns(self):
"""Creates the correct FE columns. If there are any combinations of FE the method creates a new column"""
<|body_1|>
def dataTransformat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Transformation:
def inventorizeFE(self):
"""Function to determine how to transform"""
self._multFE = ',' in self._how
if self._multFE:
self._sepFE = self._how.split(', ')
else:
self._sepFE = self._how
if self._multFE:
self._boolCombFE... | the_stack_v2_python_sparse | Help_functions/MD_panel_estimation.py | MARQyie/PhD_project2_distance | train | 0 | |
1c1a8fca50b5a7993cf3d4e86a1b0939eb83e4c2 | [
"from apysc import EventType\nfrom apysc import MouseEvent\nfrom apysc.event.handler import append_handler_expression\nfrom apysc.event.handler import get_handler_name\nfrom apysc.type.variable_name_interface import VariableNameInterface\nself_instance: VariableNameInterface = self._validate_self_is_variable_name_i... | <|body_start_0|>
from apysc import EventType
from apysc import MouseEvent
from apysc.event.handler import append_handler_expression
from apysc.event.handler import get_handler_name
from apysc.type.variable_name_interface import VariableNameInterface
self_instance: Variabl... | MouseOutInterface | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MouseOutInterface:
def mouseout(self, handler: Handler, options: Optional[Dict[str, Any]]=None) -> str:
"""Add mouse out event listener setting. Parameters ---------- handler : Handler Callable that called when mouse is outed on this instance. options : dict or None, default None Optiona... | stack_v2_sparse_classes_10k_train_006973 | 3,029 | permissive | [
{
"docstring": "Add mouse out event listener setting. Parameters ---------- handler : Handler Callable that called when mouse is outed on this instance. options : dict or None, default None Optional arguments dictionary to be passed to handler. Returns ------- name : str Handler's name.",
"name": "mouseout"... | 4 | stack_v2_sparse_classes_30k_train_004141 | Implement the Python class `MouseOutInterface` described below.
Class description:
Implement the MouseOutInterface class.
Method signatures and docstrings:
- def mouseout(self, handler: Handler, options: Optional[Dict[str, Any]]=None) -> str: Add mouse out event listener setting. Parameters ---------- handler : Handl... | Implement the Python class `MouseOutInterface` described below.
Class description:
Implement the MouseOutInterface class.
Method signatures and docstrings:
- def mouseout(self, handler: Handler, options: Optional[Dict[str, Any]]=None) -> str: Add mouse out event listener setting. Parameters ---------- handler : Handl... | 5c6a4674e2e9684cb2cb1325dc9b070879d4d355 | <|skeleton|>
class MouseOutInterface:
def mouseout(self, handler: Handler, options: Optional[Dict[str, Any]]=None) -> str:
"""Add mouse out event listener setting. Parameters ---------- handler : Handler Callable that called when mouse is outed on this instance. options : dict or None, default None Optiona... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MouseOutInterface:
def mouseout(self, handler: Handler, options: Optional[Dict[str, Any]]=None) -> str:
"""Add mouse out event listener setting. Parameters ---------- handler : Handler Callable that called when mouse is outed on this instance. options : dict or None, default None Optional arguments di... | the_stack_v2_python_sparse | apysc/event/mouse_out_interface.py | TrendingTechnology/apysc | train | 0 | |
3d317fbd1b08326fd870ca9d738ca97b660df64d | [
"self.text = ''\nself.keywords = None\nself.seg = Segmentation(stop_words_file=stop_words_file, allow_speech_tags=allow_speech_tags, delimiters=delimiters)\nself.sentences = None\nself.words_no_filter = None\nself.words_no_stop_words = None\nself.words_all_filters = None",
"self.text = text\nself.word_index = {}\... | <|body_start_0|>
self.text = ''
self.keywords = None
self.seg = Segmentation(stop_words_file=stop_words_file, allow_speech_tags=allow_speech_tags, delimiters=delimiters)
self.sentences = None
self.words_no_filter = None
self.words_no_stop_words = None
self.words_a... | TextRankKeyword | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextRankKeyword:
def __init__(self, stop_words_file='./stopwords.txt', allow_speech_tags=util.allow_speech_tags, delimiters=util.sentence_delimiters):
"""Keyword arguments: stop_words_file -- str，指定停止词文件路径（一行一个停止词），若为其他类型，则使用默认停止词文件 delimiters -- 默认值是`?!;？！。；… `，用来将文本拆分为句子。 Object Var: w... | stack_v2_sparse_classes_10k_train_006974 | 8,424 | no_license | [
{
"docstring": "Keyword arguments: stop_words_file -- str，指定停止词文件路径（一行一个停止词），若为其他类型，则使用默认停止词文件 delimiters -- 默认值是`?!;？！。；… `，用来将文本拆分为句子。 Object Var: words_no_filter -- 对sentences中每个句子分词而得到的两级列表。 words_no_stop_words -- 去掉words_no_filter中的停止词而得到的两级列表。 words_all_filters -- 保留words_no_stop_words中指定词性的单词而得到的两级列表。",
... | 4 | stack_v2_sparse_classes_30k_train_001285 | Implement the Python class `TextRankKeyword` described below.
Class description:
Implement the TextRankKeyword class.
Method signatures and docstrings:
- def __init__(self, stop_words_file='./stopwords.txt', allow_speech_tags=util.allow_speech_tags, delimiters=util.sentence_delimiters): Keyword arguments: stop_words_... | Implement the Python class `TextRankKeyword` described below.
Class description:
Implement the TextRankKeyword class.
Method signatures and docstrings:
- def __init__(self, stop_words_file='./stopwords.txt', allow_speech_tags=util.allow_speech_tags, delimiters=util.sentence_delimiters): Keyword arguments: stop_words_... | 7f7c4e56a8a66618feeb245b5394c0fc7d4f529a | <|skeleton|>
class TextRankKeyword:
def __init__(self, stop_words_file='./stopwords.txt', allow_speech_tags=util.allow_speech_tags, delimiters=util.sentence_delimiters):
"""Keyword arguments: stop_words_file -- str，指定停止词文件路径（一行一个停止词），若为其他类型，则使用默认停止词文件 delimiters -- 默认值是`?!;？！。；… `，用来将文本拆分为句子。 Object Var: w... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextRankKeyword:
def __init__(self, stop_words_file='./stopwords.txt', allow_speech_tags=util.allow_speech_tags, delimiters=util.sentence_delimiters):
"""Keyword arguments: stop_words_file -- str，指定停止词文件路径（一行一个停止词），若为其他类型，则使用默认停止词文件 delimiters -- 默认值是`?!;？！。；… `，用来将文本拆分为句子。 Object Var: words_no_filter... | the_stack_v2_python_sparse | KwordExtr/TextRank/TextRankKeyword.py | primingrx/NLP | train | 0 | |
cdc19af05f58fcb427e17f867790974aecb5254a | [
"if remote.ssh:\n return Connection(remote.ssh)\nelif remote.http:\n hostName = urlparse(remote.http).hostname\n username = None\n password = None\n if hostName in httpCredentials:\n username = httpCredentials[hostName].username\n password = httpCredentials[hostName].password\n retur... | <|body_start_0|>
if remote.ssh:
return Connection(remote.ssh)
elif remote.http:
hostName = urlparse(remote.http).hostname
username = None
password = None
if hostName in httpCredentials:
username = httpCredentials[hostName].usern... | Collection of drepo utility functions | Utils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Utils:
"""Collection of drepo utility functions"""
def createQueryConnection(remote, httpCredentials):
"""Create a query connection (HTTP or SSH) based on what's available in the given remote @param remote Remote @param httpCredentials A map of HTTP credentials"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_006975 | 3,013 | permissive | [
{
"docstring": "Create a query connection (HTTP or SSH) based on what's available in the given remote @param remote Remote @param httpCredentials A map of HTTP credentials",
"name": "createQueryConnection",
"signature": "def createQueryConnection(remote, httpCredentials)"
},
{
"docstring": "Inje... | 2 | stack_v2_sparse_classes_30k_train_005270 | Implement the Python class `Utils` described below.
Class description:
Collection of drepo utility functions
Method signatures and docstrings:
- def createQueryConnection(remote, httpCredentials): Create a query connection (HTTP or SSH) based on what's available in the given remote @param remote Remote @param httpCre... | Implement the Python class `Utils` described below.
Class description:
Collection of drepo utility functions
Method signatures and docstrings:
- def createQueryConnection(remote, httpCredentials): Create a query connection (HTTP or SSH) based on what's available in the given remote @param remote Remote @param httpCre... | 58a035a08a7c58035c25f992c1b8aa33cc997cd2 | <|skeleton|>
class Utils:
"""Collection of drepo utility functions"""
def createQueryConnection(remote, httpCredentials):
"""Create a query connection (HTTP or SSH) based on what's available in the given remote @param remote Remote @param httpCredentials A map of HTTP credentials"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Utils:
"""Collection of drepo utility functions"""
def createQueryConnection(remote, httpCredentials):
"""Create a query connection (HTTP or SSH) based on what's available in the given remote @param remote Remote @param httpCredentials A map of HTTP credentials"""
if remote.ssh:
... | the_stack_v2_python_sparse | du/drepo/Utils.py | spiricn/DevUtils | train | 1 |
2c8107e7a8d8da7babf3458be79656bf6ddf9cf4 | [
"super(SelfAttention, self).__init__()\nself.units = units\nself.W = tf.keras.layers.Dense(units)\nself.U = tf.keras.layers.Dense(units)\nself.V = tf.keras.layers.Dense(1)",
"prev = tf.expand_dims(s_prev, axis=1)\nscore = self.V(tf.nn.tanh(self.W(prev) + self.U(hidden_states)))\nweights = tf.nn.softmax(score, axi... | <|body_start_0|>
super(SelfAttention, self).__init__()
self.units = units
self.W = tf.keras.layers.Dense(units)
self.U = tf.keras.layers.Dense(units)
self.V = tf.keras.layers.Dense(1)
<|end_body_0|>
<|body_start_1|>
prev = tf.expand_dims(s_prev, axis=1)
score = s... | class SelfAttention | SelfAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""Class constructor"""
<|body_0|>
def call(self, s_prev, hidden_states):
"""call function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(SelfAttention, self).__init__()
... | stack_v2_sparse_classes_10k_train_006976 | 754 | no_license | [
{
"docstring": "Class constructor",
"name": "__init__",
"signature": "def __init__(self, units)"
},
{
"docstring": "call function",
"name": "call",
"signature": "def call(self, s_prev, hidden_states)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000095 | Implement the Python class `SelfAttention` described below.
Class description:
class SelfAttention
Method signatures and docstrings:
- def __init__(self, units): Class constructor
- def call(self, s_prev, hidden_states): call function | Implement the Python class `SelfAttention` described below.
Class description:
class SelfAttention
Method signatures and docstrings:
- def __init__(self, units): Class constructor
- def call(self, s_prev, hidden_states): call function
<|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(... | a49eb348ff994f35b0efbbd5ac3ac8ae8ccb57d2 | <|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""Class constructor"""
<|body_0|>
def call(self, s_prev, hidden_states):
"""call function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""Class constructor"""
super(SelfAttention, self).__init__()
self.units = units
self.W = tf.keras.layers.Dense(units)
self.U = tf.keras.layers.Dense(units)
self.V = tf.keras.layers.Dense(1... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/1-self_attention.py | salmenz/holbertonschool-machine_learning | train | 4 |
72e365b959c1cd6aec2927d4b10361517de9c055 | [
"self.middle = middle\nself.timeout = timeout\nself.locations = locations",
"to_do = plan['visit']\nfor loc in to_do:\n position = self.locations[loc]\n arrived = self.middle.do({'go_to': position, 'timeout': self.timeout})\n self.display(1, 'Arrived at', loc, arrived)"
] | <|body_start_0|>
self.middle = middle
self.timeout = timeout
self.locations = locations
<|end_body_0|>
<|body_start_1|>
to_do = plan['visit']
for loc in to_do:
position = self.locations[loc]
arrived = self.middle.do({'go_to': position, 'timeout': self.tim... | Rob_top_layer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rob_top_layer:
def __init__(self, middle, timeout=200, locations={'mail': (-5, 10), 'o103': (50, 10), 'o109': (100, 10), 'storage': (101, 51)}):
"""middle is the middle layer timeout is the number of steps the middle layer goes before giving up locations is a loc:pos dictionary where loc... | stack_v2_sparse_classes_10k_train_006977 | 3,349 | no_license | [
{
"docstring": "middle is the middle layer timeout is the number of steps the middle layer goes before giving up locations is a loc:pos dictionary where loc is a named location, and pos is an (x,y) position.",
"name": "__init__",
"signature": "def __init__(self, middle, timeout=200, locations={'mail': (... | 2 | stack_v2_sparse_classes_30k_train_000447 | Implement the Python class `Rob_top_layer` described below.
Class description:
Implement the Rob_top_layer class.
Method signatures and docstrings:
- def __init__(self, middle, timeout=200, locations={'mail': (-5, 10), 'o103': (50, 10), 'o109': (100, 10), 'storage': (101, 51)}): middle is the middle layer timeout is ... | Implement the Python class `Rob_top_layer` described below.
Class description:
Implement the Rob_top_layer class.
Method signatures and docstrings:
- def __init__(self, middle, timeout=200, locations={'mail': (-5, 10), 'o103': (50, 10), 'o109': (100, 10), 'storage': (101, 51)}): middle is the middle layer timeout is ... | 479d6120b75ac0ff602f032474cad440cadd9f31 | <|skeleton|>
class Rob_top_layer:
def __init__(self, middle, timeout=200, locations={'mail': (-5, 10), 'o103': (50, 10), 'o109': (100, 10), 'storage': (101, 51)}):
"""middle is the middle layer timeout is the number of steps the middle layer goes before giving up locations is a loc:pos dictionary where loc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Rob_top_layer:
def __init__(self, middle, timeout=200, locations={'mail': (-5, 10), 'o103': (50, 10), 'o109': (100, 10), 'storage': (101, 51)}):
"""middle is the middle layer timeout is the number of steps the middle layer goes before giving up locations is a loc:pos dictionary where loc is a named lo... | the_stack_v2_python_sparse | ass1/aipython/agentTop.py | fckphil/COMP9814 | train | 5 | |
83569443e35a57b8a489b7b74e4b49760d2ae5da | [
"self.x = input\nself.y = label\nself.sigmoid_layers = []\nself.rbm_layers = []\nself.n_layers = len(hidden_layer_size)\nif rng == None:\n rng = np.random.RandomState(111)\nassert self.n_layers > 0\nfor i in range(self.n_layers):\n if i == 0:\n input_size = n_ins\n else:\n input_size = hidden... | <|body_start_0|>
self.x = input
self.y = label
self.sigmoid_layers = []
self.rbm_layers = []
self.n_layers = len(hidden_layer_size)
if rng == None:
rng = np.random.RandomState(111)
assert self.n_layers > 0
for i in range(self.n_layers):
... | 深度置信网络 几个问题：为什么引入sigmoid层（隐层），这是一个MLP和RBMs共存的网络，我们在训练RBMs的同时得到的更新参数值是与MLP共享的，即我们 其实是采用无监督预训练层层的RBM得到的参数，其实的得到的就是MLP的参数，然后最后再接一个Logstic层，用于做监督学习的，然 后再利用的finetune的方式微调一下参数。 | DBN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBN:
"""深度置信网络 几个问题：为什么引入sigmoid层（隐层），这是一个MLP和RBMs共存的网络，我们在训练RBMs的同时得到的更新参数值是与MLP共享的，即我们 其实是采用无监督预训练层层的RBM得到的参数，其实的得到的就是MLP的参数，然后最后再接一个Logstic层，用于做监督学习的，然 后再利用的finetune的方式微调一下参数。"""
def __init__(self, input=None, label=None, n_ins=2, hidden_layer_size=[3, 3], n_out=2, rng=None):
""":... | stack_v2_sparse_classes_10k_train_006978 | 5,851 | no_license | [
{
"docstring": ":param input: 输入数据的属性 :param label: 输入数据的标签 :param n_ins: 输入层， 数据属性的数量 :param hidden_layer_size: :param n_out: 输出层，总共要输出几个标签 :param rng: 随机数发生器",
"name": "__init__",
"signature": "def __init__(self, input=None, label=None, n_ins=2, hidden_layer_size=[3, 3], n_out=2, rng=None)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_005020 | Implement the Python class `DBN` described below.
Class description:
深度置信网络 几个问题：为什么引入sigmoid层（隐层），这是一个MLP和RBMs共存的网络，我们在训练RBMs的同时得到的更新参数值是与MLP共享的，即我们 其实是采用无监督预训练层层的RBM得到的参数，其实的得到的就是MLP的参数，然后最后再接一个Logstic层，用于做监督学习的，然 后再利用的finetune的方式微调一下参数。
Method signatures and docstrings:
- def __init__(self, input=None, label=None,... | Implement the Python class `DBN` described below.
Class description:
深度置信网络 几个问题：为什么引入sigmoid层（隐层），这是一个MLP和RBMs共存的网络，我们在训练RBMs的同时得到的更新参数值是与MLP共享的，即我们 其实是采用无监督预训练层层的RBM得到的参数，其实的得到的就是MLP的参数，然后最后再接一个Logstic层，用于做监督学习的，然 后再利用的finetune的方式微调一下参数。
Method signatures and docstrings:
- def __init__(self, input=None, label=None,... | 8fda025b7fea0fd4ad9e9fafd4736f75ec452b2f | <|skeleton|>
class DBN:
"""深度置信网络 几个问题：为什么引入sigmoid层（隐层），这是一个MLP和RBMs共存的网络，我们在训练RBMs的同时得到的更新参数值是与MLP共享的，即我们 其实是采用无监督预训练层层的RBM得到的参数，其实的得到的就是MLP的参数，然后最后再接一个Logstic层，用于做监督学习的，然 后再利用的finetune的方式微调一下参数。"""
def __init__(self, input=None, label=None, n_ins=2, hidden_layer_size=[3, 3], n_out=2, rng=None):
""":... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DBN:
"""深度置信网络 几个问题：为什么引入sigmoid层（隐层），这是一个MLP和RBMs共存的网络，我们在训练RBMs的同时得到的更新参数值是与MLP共享的，即我们 其实是采用无监督预训练层层的RBM得到的参数，其实的得到的就是MLP的参数，然后最后再接一个Logstic层，用于做监督学习的，然 后再利用的finetune的方式微调一下参数。"""
def __init__(self, input=None, label=None, n_ins=2, hidden_layer_size=[3, 3], n_out=2, rng=None):
""":param input: ... | the_stack_v2_python_sparse | Deep_learning/Simplify_model/DBN.py | chunchunya/machine_learning_algorithms | train | 0 |
358b9fc7008e0fd736df204b022c6b2b48ccf631 | [
"self.dict = collections.defaultdict(set)\nfor word in dictionary:\n if word:\n self.dict[word[0] + str(len(word) - 2) + word[-1]].add(word)",
"if not word:\n return True\nkey = word[0] + str(len(word) - 2) + word[-1]\nif word in self.dict[key]:\n return len(self.dict[key]) == 1\nelse:\n return... | <|body_start_0|>
self.dict = collections.defaultdict(set)
for word in dictionary:
if word:
self.dict[word[0] + str(len(word) - 2) + word[-1]].add(word)
<|end_body_0|>
<|body_start_1|>
if not word:
return True
key = word[0] + str(len(word) - 2) + w... | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.dict = collections.defaultdict(set)
fo... | stack_v2_sparse_classes_10k_train_006979 | 751 | no_license | [
{
"docstring": ":type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": ":type word: str :rtype: bool",
"name": "isUnique",
"signature": "def isUnique(self, word)"
}
] | 2 | null | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool
<|skeleton|>
class ValidWordAbbr:
def __init_... | 5b14b6f42baf59b04cbcc8e115df4272029b64c8 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
self.dict = collections.defaultdict(set)
for word in dictionary:
if word:
self.dict[word[0] + str(len(word) - 2) + word[-1]].add(word)
def isUnique(self, word):
"""... | the_stack_v2_python_sparse | LeetCode/0288.Unique-Word-Abbreviation/Unique-Word-Abbreviation.py | htingwang/HandsOnAlgoDS | train | 12 | |
38ec1daf7d822c2cb3aa3b3a717ced0153c80ce1 | [
"webapp_user = args['webapp_user']\nship_info_id = (int(args['ship_id']),)\nnew_ship_info = {'ship_name': args['ship_name'], 'ship_address': args['ship_address'], 'ship_tel': args['ship_tel'], 'area': args['area']}\narea = args['area']\nif False in map(lambda x: x.isdigit(), area.split('_')):\n webapp_user_id = ... | <|body_start_0|>
webapp_user = args['webapp_user']
ship_info_id = (int(args['ship_id']),)
new_ship_info = {'ship_name': args['ship_name'], 'ship_address': args['ship_address'], 'ship_tel': args['ship_tel'], 'area': args['area']}
area = args['area']
if False in map(lambda x: x.isd... | 收货地址 | AShipInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AShipInfo:
"""收货地址"""
def post(args):
"""@brief 修改收货地址 @param ship_id @param ship_name @param ship_address @param ship_tel @param area @return {result:True}"""
<|body_0|>
def put(args):
"""新建收货地址 @param ship_name @param ship_address @param ship_tel @param area @r... | stack_v2_sparse_classes_10k_train_006980 | 2,372 | no_license | [
{
"docstring": "@brief 修改收货地址 @param ship_id @param ship_name @param ship_address @param ship_tel @param area @return {result:True}",
"name": "post",
"signature": "def post(args)"
},
{
"docstring": "新建收货地址 @param ship_name @param ship_address @param ship_tel @param area @return {'ship_info_id': ... | 3 | null | Implement the Python class `AShipInfo` described below.
Class description:
收货地址
Method signatures and docstrings:
- def post(args): @brief 修改收货地址 @param ship_id @param ship_name @param ship_address @param ship_tel @param area @return {result:True}
- def put(args): 新建收货地址 @param ship_name @param ship_address @param sh... | Implement the Python class `AShipInfo` described below.
Class description:
收货地址
Method signatures and docstrings:
- def post(args): @brief 修改收货地址 @param ship_id @param ship_name @param ship_address @param ship_tel @param area @return {result:True}
- def put(args): 新建收货地址 @param ship_name @param ship_address @param sh... | 15621db1a64ffe199619924b75a5b5c5e6416bed | <|skeleton|>
class AShipInfo:
"""收货地址"""
def post(args):
"""@brief 修改收货地址 @param ship_id @param ship_name @param ship_address @param ship_tel @param area @return {result:True}"""
<|body_0|>
def put(args):
"""新建收货地址 @param ship_name @param ship_address @param ship_tel @param area @r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AShipInfo:
"""收货地址"""
def post(args):
"""@brief 修改收货地址 @param ship_id @param ship_name @param ship_address @param ship_tel @param area @return {result:True}"""
webapp_user = args['webapp_user']
ship_info_id = (int(args['ship_id']),)
new_ship_info = {'ship_name': args['ship... | the_stack_v2_python_sparse | api/mall/a_ship_info.py | nuaays/apiserver | train | 0 |
5e1e307d01d7f127a87b51c22cdc3118de1aa0f9 | [
"res = []\n\ndef helper(root):\n if not root:\n return\n if root:\n helper(root.left)\n res.append(root.data)\n helper(root.right)\nhelper(root)\nreturn res",
"res = []\nstack = []\np = root\nwhile p or stack:\n while p:\n stack.append(p)\n p = stack.pop()\n res.a... | <|body_start_0|>
res = []
def helper(root):
if not root:
return
if root:
helper(root.left)
res.append(root.data)
helper(root.right)
helper(root)
return res
<|end_body_0|>
<|body_start_1|>
re... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def inorderTraversal(self, root: TreeNode) -> List[int]:
"""递归 时间复杂度为 O(n) 空间复杂度为 O(n) 递归可以解决问题，但是考虑到效率，我们通常不推荐使用递归 :param root: :return:"""
<|body_0|>
def inorderTraversal2(self, root: TreeNode) -> List[int]:
"""迭代 通过栈 时间复杂度为 O(n) 空间复杂度为 O(n) 但是栈有个问题，虽然栈提高... | stack_v2_sparse_classes_10k_train_006981 | 3,517 | no_license | [
{
"docstring": "递归 时间复杂度为 O(n) 空间复杂度为 O(n) 递归可以解决问题，但是考虑到效率，我们通常不推荐使用递归 :param root: :return:",
"name": "inorderTraversal",
"signature": "def inorderTraversal(self, root: TreeNode) -> List[int]"
},
{
"docstring": "迭代 通过栈 时间复杂度为 O(n) 空间复杂度为 O(n) 但是栈有个问题，虽然栈提高了效率，但是嵌套循环非常烧脑，不易理解，容易造成一看就懂 一写就废的情况，而... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal(self, root: TreeNode) -> List[int]: 递归 时间复杂度为 O(n) 空间复杂度为 O(n) 递归可以解决问题，但是考虑到效率，我们通常不推荐使用递归 :param root: :return:
- def inorderTraversal2(self, root: TreeNod... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal(self, root: TreeNode) -> List[int]: 递归 时间复杂度为 O(n) 空间复杂度为 O(n) 递归可以解决问题，但是考虑到效率，我们通常不推荐使用递归 :param root: :return:
- def inorderTraversal2(self, root: TreeNod... | 51943e2c2c4ec70c7c1d5b53c9fdf0a719428d7a | <|skeleton|>
class Solution:
def inorderTraversal(self, root: TreeNode) -> List[int]:
"""递归 时间复杂度为 O(n) 空间复杂度为 O(n) 递归可以解决问题，但是考虑到效率，我们通常不推荐使用递归 :param root: :return:"""
<|body_0|>
def inorderTraversal2(self, root: TreeNode) -> List[int]:
"""迭代 通过栈 时间复杂度为 O(n) 空间复杂度为 O(n) 但是栈有个问题，虽然栈提高... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def inorderTraversal(self, root: TreeNode) -> List[int]:
"""递归 时间复杂度为 O(n) 空间复杂度为 O(n) 递归可以解决问题，但是考虑到效率，我们通常不推荐使用递归 :param root: :return:"""
res = []
def helper(root):
if not root:
return
if root:
helper(root.left)
... | the_stack_v2_python_sparse | LeetCode_practice/BinaryTree/0094_BinaryTreeInorderTraversal.py | LeBron-Jian/BasicAlgorithmPractice | train | 13 | |
9997586f3652df7b0bfbb50b4708e5fecc8345fb | [
"input_json = request.data\noutput_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'Payload'], [request.data['AvailabilityDetails'], request.data['AuthenticationDetails'], None]))\nif 'APIParams' not in input_json or 'user_ip' not in input_json['APIParams']:\n user_ip_var = None\nelse:\n user... | <|body_start_0|>
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'Payload'], [request.data['AvailabilityDetails'], request.data['AuthenticationDetails'], None]))
if 'APIParams' not in input_json or 'user_ip' not in input_json['APIParams']:
... | This covers the API for fetching all support centre tickets raised by the user | GetUserGeosAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetUserGeosAPI:
"""This covers the API for fetching all support centre tickets raised by the user"""
def post(self, request):
"""Post Function to fetching common questions based on ticket type."""
<|body_0|>
def get_user_geos_json(self, request):
"""this function... | stack_v2_sparse_classes_10k_train_006982 | 4,683 | no_license | [
{
"docstring": "Post Function to fetching common questions based on ticket type.",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "this function calls third party API to get user's country from ip_address in case user_ip is provided in the input. If user_ip is not provi... | 2 | stack_v2_sparse_classes_30k_test_000366 | Implement the Python class `GetUserGeosAPI` described below.
Class description:
This covers the API for fetching all support centre tickets raised by the user
Method signatures and docstrings:
- def post(self, request): Post Function to fetching common questions based on ticket type.
- def get_user_geos_json(self, re... | Implement the Python class `GetUserGeosAPI` described below.
Class description:
This covers the API for fetching all support centre tickets raised by the user
Method signatures and docstrings:
- def post(self, request): Post Function to fetching common questions based on ticket type.
- def get_user_geos_json(self, re... | 36eb9931f330e64902354c6fc471be2adf4b7049 | <|skeleton|>
class GetUserGeosAPI:
"""This covers the API for fetching all support centre tickets raised by the user"""
def post(self, request):
"""Post Function to fetching common questions based on ticket type."""
<|body_0|>
def get_user_geos_json(self, request):
"""this function... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GetUserGeosAPI:
"""This covers the API for fetching all support centre tickets raised by the user"""
def post(self, request):
"""Post Function to fetching common questions based on ticket type."""
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'Authentica... | the_stack_v2_python_sparse | Generic/common/location/api/get_user_geos/views_get_user_geos.py | archiemb303/common_backend_django | train | 0 |
d178d30106276ed713d76afe79af8f3802451c1e | [
"self.pump = Pump('127.0.0.1', 8000)\nself.sensor = Sensor('127.1.1.3', 9000)\nself.decider = Decider(100, 0.05)\nself.controller = Controller(self.sensor, self.pump, self.decider)",
"self.sensor.measure = MagicMock(return_value=110)\nself.pump.get_state = MagicMock(return_value='PUMP_OFF')\nself.controller.tick ... | <|body_start_0|>
self.pump = Pump('127.0.0.1', 8000)
self.sensor = Sensor('127.1.1.3', 9000)
self.decider = Decider(100, 0.05)
self.controller = Controller(self.sensor, self.pump, self.decider)
<|end_body_0|>
<|body_start_1|>
self.sensor.measure = MagicMock(return_value=110)
... | Unit tests for the Controller class | ControllerTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ControllerTests:
"""Unit tests for the Controller class"""
def setUp(self):
"""setup :return:"""
<|body_0|>
def test_tick(self):
"""test tick of Controller class :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.pump = Pump('127.0.0.... | stack_v2_sparse_classes_10k_train_006983 | 3,198 | no_license | [
{
"docstring": "setup :return:",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "test tick of Controller class :return:",
"name": "test_tick",
"signature": "def test_tick(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003152 | Implement the Python class `ControllerTests` described below.
Class description:
Unit tests for the Controller class
Method signatures and docstrings:
- def setUp(self): setup :return:
- def test_tick(self): test tick of Controller class :return: | Implement the Python class `ControllerTests` described below.
Class description:
Unit tests for the Controller class
Method signatures and docstrings:
- def setUp(self): setup :return:
- def test_tick(self): test tick of Controller class :return:
<|skeleton|>
class ControllerTests:
"""Unit tests for the Controll... | 263685ca90110609bfd05d621516727f8cd0028f | <|skeleton|>
class ControllerTests:
"""Unit tests for the Controller class"""
def setUp(self):
"""setup :return:"""
<|body_0|>
def test_tick(self):
"""test tick of Controller class :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ControllerTests:
"""Unit tests for the Controller class"""
def setUp(self):
"""setup :return:"""
self.pump = Pump('127.0.0.1', 8000)
self.sensor = Sensor('127.1.1.3', 9000)
self.decider = Decider(100, 0.05)
self.controller = Controller(self.sensor, self.pump, self.... | the_stack_v2_python_sparse | students/marc_charbo/assignment_6/assign_6/waterregulation/test.py | aurel1212/Sp2018-Online | train | 0 |
b95d712a4835f82033d7abd63d28646b75595633 | [
"i, j = (0, len(nums) - 1)\nwhile i <= j:\n mid = (i + j) // 2\n if nums[mid] == target:\n return mid\n elif nums[mid] > target:\n j = mid - 1\n else:\n i = mid + 1\nreturn i",
"n = len(nums)\nif nums[n - 1] < target:\n return n\nelif nums[0] > target:\n return 0\nleft, righ... | <|body_start_0|>
i, j = (0, len(nums) - 1)
while i <= j:
mid = (i + j) // 2
if nums[mid] == target:
return mid
elif nums[mid] > target:
j = mid - 1
else:
i = mid + 1
return i
<|end_body_0|>
<|body_st... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
"""二分查找"""
<|body_0|>
def searchInsert2(self, nums: List[int], target: int) -> int:
"""官方答案，返回第一个大于等于 target 的下标"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i, j = (0, len(nu... | stack_v2_sparse_classes_10k_train_006984 | 2,482 | no_license | [
{
"docstring": "二分查找",
"name": "searchInsert",
"signature": "def searchInsert(self, nums: List[int], target: int) -> int"
},
{
"docstring": "官方答案，返回第一个大于等于 target 的下标",
"name": "searchInsert2",
"signature": "def searchInsert2(self, nums: List[int], target: int) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_005254 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums: List[int], target: int) -> int: 二分查找
- def searchInsert2(self, nums: List[int], target: int) -> int: 官方答案，返回第一个大于等于 target 的下标 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums: List[int], target: int) -> int: 二分查找
- def searchInsert2(self, nums: List[int], target: int) -> int: 官方答案，返回第一个大于等于 target 的下标
<|skeleton|>
class So... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
"""二分查找"""
<|body_0|>
def searchInsert2(self, nums: List[int], target: int) -> int:
"""官方答案，返回第一个大于等于 target 的下标"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
"""二分查找"""
i, j = (0, len(nums) - 1)
while i <= j:
mid = (i + j) // 2
if nums[mid] == target:
return mid
elif nums[mid] > target:
j = mid - 1
... | the_stack_v2_python_sparse | 35.搜索插入位置/solution.py | QtTao/daily_leetcode | train | 0 | |
3b08750108e602ee1a2738e031c57d1854f32304 | [
"import collections\ndicts = collections.defaultdict(set)\nfor allow in allowed:\n dicts[allow[0:2]].add(allow[-1])\n\ndef dfs(s, c):\n if len(s) == 1 and s + c in dicts:\n return True\n for i in dicts[s[-1] + c]:\n for j in dicts[s]:\n dicts[s + c].add(j + i)\n for i in dicts[s... | <|body_start_0|>
import collections
dicts = collections.defaultdict(set)
for allow in allowed:
dicts[allow[0:2]].add(allow[-1])
def dfs(s, c):
if len(s) == 1 and s + c in dicts:
return True
for i in dicts[s[-1] + c]:
fo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
<|body_0|>
def pyramidTransition_1(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool 85ms worry ans"""
<|bod... | stack_v2_sparse_classes_10k_train_006985 | 4,317 | no_license | [
{
"docstring": ":type bottom: str :type allowed: List[str] :rtype: bool",
"name": "pyramidTransition",
"signature": "def pyramidTransition(self, bottom, allowed)"
},
{
"docstring": ":type bottom: str :type allowed: List[str] :rtype: bool 85ms worry ans",
"name": "pyramidTransition_1",
"s... | 2 | stack_v2_sparse_classes_30k_train_005540 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pyramidTransition(self, bottom, allowed): :type bottom: str :type allowed: List[str] :rtype: bool
- def pyramidTransition_1(self, bottom, allowed): :type bottom: str :type al... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pyramidTransition(self, bottom, allowed): :type bottom: str :type allowed: List[str] :rtype: bool
- def pyramidTransition_1(self, bottom, allowed): :type bottom: str :type al... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
<|body_0|>
def pyramidTransition_1(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool 85ms worry ans"""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
import collections
dicts = collections.defaultdict(set)
for allow in allowed:
dicts[allow[0:2]].add(allow[-1])
def dfs(s, c):
i... | the_stack_v2_python_sparse | PyramidTransitionMatrix_MID_757.py | 953250587/leetcode-python | train | 2 | |
7b0d8b5cfafb5b2dc39eb2872c0b1b30e3dd1b9d | [
"user = mixer.blend(User, email='newuser@gmail.com', phone='12345678', password='test_password_1')\nuser.set_password('test_password_1')\nuser.save()\nrequest_data_cases = [{'grant_type': 'password', 'login': user.email, 'password': 'test_password_1'}, {'grant_type': 'password', 'login': user.phone, 'password': 'te... | <|body_start_0|>
user = mixer.blend(User, email='newuser@gmail.com', phone='12345678', password='test_password_1')
user.set_password('test_password_1')
user.save()
request_data_cases = [{'grant_type': 'password', 'login': user.email, 'password': 'test_password_1'}, {'grant_type': 'passwo... | TestCustomLoginView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCustomLoginView:
def test_post_with_email_and_phone(self):
"""Test: login by user with email / phone"""
<|body_0|>
def test_post_with_wallet_erc20(self):
"""Test: login by user with wallet ERC-20"""
<|body_1|>
def test_post_with_refresh_token(self):
... | stack_v2_sparse_classes_10k_train_006986 | 6,349 | permissive | [
{
"docstring": "Test: login by user with email / phone",
"name": "test_post_with_email_and_phone",
"signature": "def test_post_with_email_and_phone(self)"
},
{
"docstring": "Test: login by user with wallet ERC-20",
"name": "test_post_with_wallet_erc20",
"signature": "def test_post_with_w... | 6 | stack_v2_sparse_classes_30k_train_005437 | Implement the Python class `TestCustomLoginView` described below.
Class description:
Implement the TestCustomLoginView class.
Method signatures and docstrings:
- def test_post_with_email_and_phone(self): Test: login by user with email / phone
- def test_post_with_wallet_erc20(self): Test: login by user with wallet ER... | Implement the Python class `TestCustomLoginView` described below.
Class description:
Implement the TestCustomLoginView class.
Method signatures and docstrings:
- def test_post_with_email_and_phone(self): Test: login by user with email / phone
- def test_post_with_wallet_erc20(self): Test: login by user with wallet ER... | f8930ff1c009ad18e522ab29680b4bcd50a6020e | <|skeleton|>
class TestCustomLoginView:
def test_post_with_email_and_phone(self):
"""Test: login by user with email / phone"""
<|body_0|>
def test_post_with_wallet_erc20(self):
"""Test: login by user with wallet ERC-20"""
<|body_1|>
def test_post_with_refresh_token(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestCustomLoginView:
def test_post_with_email_and_phone(self):
"""Test: login by user with email / phone"""
user = mixer.blend(User, email='newuser@gmail.com', phone='12345678', password='test_password_1')
user.set_password('test_password_1')
user.save()
request_data_ca... | the_stack_v2_python_sparse | src/auth/tests.py | evis-market/web-interface-backend | train | 2 | |
90ca908e6aa8c2b879eae8b7a43f7c67a125af19 | [
"super().initialize()\nself._remote_buttons_ambient_light = self.args.get('remote_buttons_ambient_light', {})\nfor remote_button_ambient_light in self._remote_buttons_ambient_light:\n self.listen_state(self.__on_ambient_light_button_pressed, remote_button_ambient_light)",
"if new == 'on':\n self.log('FIRE C... | <|body_start_0|>
super().initialize()
self._remote_buttons_ambient_light = self.args.get('remote_buttons_ambient_light', {})
for remote_button_ambient_light in self._remote_buttons_ambient_light:
self.listen_state(self.__on_ambient_light_button_pressed, remote_button_ambient_light)
<... | LightManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LightManager:
def initialize(self) -> None:
"""Initialize."""
<|body_0|>
def __on_ambient_light_button_pressed(self, entity: Union[str, dict], attribute: str, old: dict, new: dict, kwargs: dict) -> None:
"""called when ambient remote that button pressed on controlls"... | stack_v2_sparse_classes_10k_train_006987 | 1,380 | no_license | [
{
"docstring": "Initialize.",
"name": "initialize",
"signature": "def initialize(self) -> None"
},
{
"docstring": "called when ambient remote that button pressed on controlls",
"name": "__on_ambient_light_button_pressed",
"signature": "def __on_ambient_light_button_pressed(self, entity: ... | 2 | stack_v2_sparse_classes_30k_train_002832 | Implement the Python class `LightManager` described below.
Class description:
Implement the LightManager class.
Method signatures and docstrings:
- def initialize(self) -> None: Initialize.
- def __on_ambient_light_button_pressed(self, entity: Union[str, dict], attribute: str, old: dict, new: dict, kwargs: dict) -> N... | Implement the Python class `LightManager` described below.
Class description:
Implement the LightManager class.
Method signatures and docstrings:
- def initialize(self) -> None: Initialize.
- def __on_ambient_light_button_pressed(self, entity: Union[str, dict], attribute: str, old: dict, new: dict, kwargs: dict) -> N... | 2c027d10e0e3aa86d97c83d1b9c3124cf980d160 | <|skeleton|>
class LightManager:
def initialize(self) -> None:
"""Initialize."""
<|body_0|>
def __on_ambient_light_button_pressed(self, entity: Union[str, dict], attribute: str, old: dict, new: dict, kwargs: dict) -> None:
"""called when ambient remote that button pressed on controlls"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LightManager:
def initialize(self) -> None:
"""Initialize."""
super().initialize()
self._remote_buttons_ambient_light = self.args.get('remote_buttons_ambient_light', {})
for remote_button_ambient_light in self._remote_buttons_ambient_light:
self.listen_state(self.__... | the_stack_v2_python_sparse | appdaemon/apps/lights/light_manager.py | forksbot/hassio | train | 0 | |
e9af86f6c1091cc9e7270711bba8db7bc0151066 | [
"msg = '\\n\\nRunning SMA strategy | SMA1 = %d & SMA2 = %d' % (SMA1, SMA2)\nmsg += '\\nfixed costs %.2f | ' % self.ftc\nmsg += 'proportional costs %.4f' % self.ptc\nprint(msg)\nprint('=' * 55)\nself.position = 0\nself.amount = self._amount\nself.data['SMA1'] = self.data['price'].rolling(SMA1).mean()\nself.data['SMA... | <|body_start_0|>
msg = '\n\nRunning SMA strategy | SMA1 = %d & SMA2 = %d' % (SMA1, SMA2)
msg += '\nfixed costs %.2f | ' % self.ftc
msg += 'proportional costs %.4f' % self.ptc
print(msg)
print('=' * 55)
self.position = 0
self.amount = self._amount
self.data... | BacktestLongOnly | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BacktestLongOnly:
def run_sma_strategy(self, SMA1, SMA2):
"""Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)"""
<|body_0|>
def run_momentum_strategy(self, momentum):
"""Backtesting a mome... | stack_v2_sparse_classes_10k_train_006988 | 4,494 | no_license | [
{
"docstring": "Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)",
"name": "run_sma_strategy",
"signature": "def run_sma_strategy(self, SMA1, SMA2)"
},
{
"docstring": "Backtesting a momentum-based strategy. Parameters... | 3 | stack_v2_sparse_classes_30k_train_003947 | Implement the Python class `BacktestLongOnly` described below.
Class description:
Implement the BacktestLongOnly class.
Method signatures and docstrings:
- def run_sma_strategy(self, SMA1, SMA2): Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in ... | Implement the Python class `BacktestLongOnly` described below.
Class description:
Implement the BacktestLongOnly class.
Method signatures and docstrings:
- def run_sma_strategy(self, SMA1, SMA2): Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in ... | bfc8baa153aec70caa8981b8e9215bb0be7f3163 | <|skeleton|>
class BacktestLongOnly:
def run_sma_strategy(self, SMA1, SMA2):
"""Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)"""
<|body_0|>
def run_momentum_strategy(self, momentum):
"""Backtesting a mome... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BacktestLongOnly:
def run_sma_strategy(self, SMA1, SMA2):
"""Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)"""
msg = '\n\nRunning SMA strategy | SMA1 = %d & SMA2 = %d' % (SMA1, SMA2)
msg += '\nfixed costs ... | the_stack_v2_python_sparse | code/pyquants/pyalgo/ch06/BacktestLongOnly.py | godknowspe/NoahsArk | train | 1 | |
f00fc9b4082a43d85cab5a599307a9f5c5ad5579 | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(username=username, email=self.normalize_email(email), phone=phone)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(username=username, email=email, phone=phone, password=passw... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(username=username, email=self.normalize_email(email), phone=phone)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
... | This class handles the creation of our users. We need to create this class and extend BaseUserManager because our model (CustomUser) has additional fields to Django's default User class. | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
"""This class handles the creation of our users. We need to create this class and extend BaseUserManager because our model (CustomUser) has additional fields to Django's default User class."""
def create_user(self, username, email, phone, password=None):
"""Create a Cu... | stack_v2_sparse_classes_10k_train_006989 | 22,769 | no_license | [
{
"docstring": "Create a CustomUser, which are the users on our site.",
"name": "create_user",
"signature": "def create_user(self, username, email, phone, password=None)"
},
{
"docstring": "Create a superuser, which is just a user object with special attributes.",
"name": "create_superuser",... | 2 | stack_v2_sparse_classes_30k_train_002036 | Implement the Python class `MyUserManager` described below.
Class description:
This class handles the creation of our users. We need to create this class and extend BaseUserManager because our model (CustomUser) has additional fields to Django's default User class.
Method signatures and docstrings:
- def create_user(... | Implement the Python class `MyUserManager` described below.
Class description:
This class handles the creation of our users. We need to create this class and extend BaseUserManager because our model (CustomUser) has additional fields to Django's default User class.
Method signatures and docstrings:
- def create_user(... | 31ef33b573b991f9425e4b1edc09dbbd044a69b0 | <|skeleton|>
class MyUserManager:
"""This class handles the creation of our users. We need to create this class and extend BaseUserManager because our model (CustomUser) has additional fields to Django's default User class."""
def create_user(self, username, email, phone, password=None):
"""Create a Cu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyUserManager:
"""This class handles the creation of our users. We need to create this class and extend BaseUserManager because our model (CustomUser) has additional fields to Django's default User class."""
def create_user(self, username, email, phone, password=None):
"""Create a CustomUser, whi... | the_stack_v2_python_sparse | ibet_apps/users/models.py | senclaymoreusa/ibet-django-backup | train | 0 |
2481c6e91a9ed020ba39e63a3921e3875236f751 | [
"count = 0\nfor i in range(1, len(nums)):\n if nums[i] < nums[i - 1]:\n count += 1\n if i + 1 < len(nums) and i - 2 >= 0:\n if nums[i + 1] < nums[i - 1] and nums[i - 2] > nums[i]:\n return False\n if count > 1:\n return False\nreturn True",
"cnt = 0\nfor i in r... | <|body_start_0|>
count = 0
for i in range(1, len(nums)):
if nums[i] < nums[i - 1]:
count += 1
if i + 1 < len(nums) and i - 2 >= 0:
if nums[i + 1] < nums[i - 1] and nums[i - 2] > nums[i]:
return False
if c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtyp... | stack_v2_sparse_classes_10k_train_006990 | 1,452 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "checkPossibility",
"signature": "def checkPossibility(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "checkPossibility",
"signature": "def checkPossibility(self, nums)"
},
{
"docstring": "... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums): :t... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
def checkPossibility(self, nums):
""":type nums: List[int] :rtyp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
count = 0
for i in range(1, len(nums)):
if nums[i] < nums[i - 1]:
count += 1
if i + 1 < len(nums) and i - 2 >= 0:
if nums[i + 1] < nums[i... | the_stack_v2_python_sparse | 0665_Non-decreasing_Array.py | bingli8802/leetcode | train | 0 | |
86032cf0a044b388109cde1acea1d15ff76b1105 | [
"m, n = (len(grid), len(grid[0]))\n\ndef bfs(grid, i, j, visited):\n Q = deque()\n Q.append((i, j))\n while len(Q):\n i1, j1 = Q.popleft()\n if grid[i1][j1] == 1:\n return abs(i1 - i) + abs(j1 - j)\n visited[i1][j1] = 1\n if 0 <= j1 - 1 < n and visited[i1][j1 - 1] == ... | <|body_start_0|>
m, n = (len(grid), len(grid[0]))
def bfs(grid, i, j, visited):
Q = deque()
Q.append((i, j))
while len(Q):
i1, j1 = Q.popleft()
if grid[i1][j1] == 1:
return abs(i1 - i) + abs(j1 - j)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDistance(self, grid) -> int:
"""BFS,超时 :param list[list[int]] grid: :return:"""
<|body_0|>
def maxDistance2(self, grid) -> int:
"""多源BFS，其实就是有一个超级原点，然后从该点进行BFS遍历，多源点是超级原点的邻接点。 :param grid: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_10k_train_006991 | 3,231 | no_license | [
{
"docstring": "BFS,超时 :param list[list[int]] grid: :return:",
"name": "maxDistance",
"signature": "def maxDistance(self, grid) -> int"
},
{
"docstring": "多源BFS，其实就是有一个超级原点，然后从该点进行BFS遍历，多源点是超级原点的邻接点。 :param grid: :return:",
"name": "maxDistance2",
"signature": "def maxDistance2(self, gri... | 2 | stack_v2_sparse_classes_30k_train_007162 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDistance(self, grid) -> int: BFS,超时 :param list[list[int]] grid: :return:
- def maxDistance2(self, grid) -> int: 多源BFS，其实就是有一个超级原点，然后从该点进行BFS遍历，多源点是超级原点的邻接点。 :param grid: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDistance(self, grid) -> int: BFS,超时 :param list[list[int]] grid: :return:
- def maxDistance2(self, grid) -> int: 多源BFS，其实就是有一个超级原点，然后从该点进行BFS遍历，多源点是超级原点的邻接点。 :param grid: ... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class Solution:
def maxDistance(self, grid) -> int:
"""BFS,超时 :param list[list[int]] grid: :return:"""
<|body_0|>
def maxDistance2(self, grid) -> int:
"""多源BFS，其实就是有一个超级原点，然后从该点进行BFS遍历，多源点是超级原点的邻接点。 :param grid: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxDistance(self, grid) -> int:
"""BFS,超时 :param list[list[int]] grid: :return:"""
m, n = (len(grid), len(grid[0]))
def bfs(grid, i, j, visited):
Q = deque()
Q.append((i, j))
while len(Q):
i1, j1 = Q.popleft()
... | the_stack_v2_python_sparse | 华为题库/地图分析.py | 2226171237/Algorithmpractice | train | 0 | |
3be18b63166b8b629f38f48d3f1ef200feb5b42e | [
"cmd = 'sudo yum --color=never -y install %s' % ' '.join(packages)\noutput_expects = ['\\\\[sudo\\\\] password for .*:', 'No package (.*) available.', 'file .* from install of .* conflicts with file from package (.*?)\\r\\n', 'Error: (.*?) conflicts with .*?\\r\\n', 'Processing Conflict: .* conflicts (.*?)\\r\\n', ... | <|body_start_0|>
cmd = 'sudo yum --color=never -y install %s' % ' '.join(packages)
output_expects = ['\\[sudo\\] password for .*:', 'No package (.*) available.', 'file .* from install of .* conflicts with file from package (.*?)\r\n', 'Error: (.*?) conflicts with .*?\r\n', 'Processing Conflict: .* confl... | RedhatPackagerMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RedhatPackagerMixin:
def _install(self, packages, time_out):
"""Attempts to install packages. Returns OK if the packages are installed or a result code if a recoverable-error occurred. Raises an exception if a non-recoverable error or timeout occurs."""
<|body_0|>
def _remov... | stack_v2_sparse_classes_10k_train_006992 | 16,357 | permissive | [
{
"docstring": "Attempts to install packages. Returns OK if the packages are installed or a result code if a recoverable-error occurred. Raises an exception if a non-recoverable error or timeout occurs.",
"name": "_install",
"signature": "def _install(self, packages, time_out)"
},
{
"docstring":... | 2 | null | Implement the Python class `RedhatPackagerMixin` described below.
Class description:
Implement the RedhatPackagerMixin class.
Method signatures and docstrings:
- def _install(self, packages, time_out): Attempts to install packages. Returns OK if the packages are installed or a result code if a recoverable-error occur... | Implement the Python class `RedhatPackagerMixin` described below.
Class description:
Implement the RedhatPackagerMixin class.
Method signatures and docstrings:
- def _install(self, packages, time_out): Attempts to install packages. Returns OK if the packages are installed or a result code if a recoverable-error occur... | 4288b8f78250cc3a1c93b019e2c3b4bf78df177c | <|skeleton|>
class RedhatPackagerMixin:
def _install(self, packages, time_out):
"""Attempts to install packages. Returns OK if the packages are installed or a result code if a recoverable-error occurred. Raises an exception if a non-recoverable error or timeout occurs."""
<|body_0|>
def _remov... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RedhatPackagerMixin:
def _install(self, packages, time_out):
"""Attempts to install packages. Returns OK if the packages are installed or a result code if a recoverable-error occurred. Raises an exception if a non-recoverable error or timeout occurs."""
cmd = 'sudo yum --color=never -y install... | the_stack_v2_python_sparse | trove/guestagent/pkg.py | openstack/trove | train | 258 | |
41e7948a5d4acfeffa0075528b818ee458353a07 | [
"self._nums = nums\nself.tree = [0 for _ in range(len(nums) + 1)]\nfor i in range(len(nums)):\n val = nums[i]\n i += 1\n while i < len(self.tree):\n self.tree[i] += val\n i += i & -i\nprint(self.tree)",
"val1 = self._nums[i]\nindex = i\ni = i + 1\nwhile i < len(self.tree):\n self.tree[i]... | <|body_start_0|>
self._nums = nums
self.tree = [0 for _ in range(len(nums) + 1)]
for i in range(len(nums)):
val = nums[i]
i += 1
while i < len(self.tree):
self.tree[i] += val
i += i & -i
print(self.tree)
<|end_body_0|>
... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_10k_train_006993 | 1,364 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type val: int :rtype: void",
"name": "update",
"signature": "def update(self, i, val)"
},
{
"docstring": ":type i: int :type j: int :rtype: int",
... | 3 | stack_v2_sparse_classes_30k_train_000780 | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): :type i: int :type j: int :rtype:... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): :type i: int :type j: int :rtype:... | a6d0e392134afe19d1aed2dfe7914b674e05ecc6 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
self._nums = nums
self.tree = [0 for _ in range(len(nums) + 1)]
for i in range(len(nums)):
val = nums[i]
i += 1
while i < len(self.tree):
self.tree[i] += val
... | the_stack_v2_python_sparse | 307RangeSumQuery.py | Ting007/leetcodePractice | train | 0 | |
c457a8dd7eb601c308c7b0bb507ff5e0ba0d1524 | [
"count = 1\narr = [0 for i in range(num_people)]\nwhile candies >= count:\n arr[(count - 1) % num_people] += count\n candies -= count\n count += 1\narr[(count - 1) % num_people] += candies\nreturn arr",
"count = 1\narr = [0 for i in range(num_people)]\nwhile candies > 0:\n '\\n min(count, c... | <|body_start_0|>
count = 1
arr = [0 for i in range(num_people)]
while candies >= count:
arr[(count - 1) % num_people] += count
candies -= count
count += 1
arr[(count - 1) % num_people] += candies
return arr
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def distributeCandies(self, candies: int, num_people: int) -> List[int]:
"""执行用时 :64 ms, 在所有 Python3 提交中击败了18.87%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了23.58%的用户 :param candies: :param num_people: :return:"""
<|body_0|>
def distributeCandies2(self, candies: int, num_... | stack_v2_sparse_classes_10k_train_006994 | 3,806 | no_license | [
{
"docstring": "执行用时 :64 ms, 在所有 Python3 提交中击败了18.87%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了23.58%的用户 :param candies: :param num_people: :return:",
"name": "distributeCandies",
"signature": "def distributeCandies(self, candies: int, num_people: int) -> List[int]"
},
{
"docstring": "执行用时 :52 ms, 在所... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def distributeCandies(self, candies: int, num_people: int) -> List[int]: 执行用时 :64 ms, 在所有 Python3 提交中击败了18.87%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了23.58%的用户 :param candies: :para... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def distributeCandies(self, candies: int, num_people: int) -> List[int]: 执行用时 :64 ms, 在所有 Python3 提交中击败了18.87%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了23.58%的用户 :param candies: :para... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def distributeCandies(self, candies: int, num_people: int) -> List[int]:
"""执行用时 :64 ms, 在所有 Python3 提交中击败了18.87%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了23.58%的用户 :param candies: :param num_people: :return:"""
<|body_0|>
def distributeCandies2(self, candies: int, num_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def distributeCandies(self, candies: int, num_people: int) -> List[int]:
"""执行用时 :64 ms, 在所有 Python3 提交中击败了18.87%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了23.58%的用户 :param candies: :param num_people: :return:"""
count = 1
arr = [0 for i in range(num_people)]
while candies ... | the_stack_v2_python_sparse | LeetCode/1103. Distribute Candies to People.py | yiming1012/MyLeetCode | train | 2 | |
c75186ad1a92476048421c4b15c6f9ad0292734f | [
"if not load_data:\n return\ndata_paths = ['app_data', '..app_data']\nadp = None\nfor data_path in data_paths:\n if os.path.exists(os.path.join(os.curdir, data_path)):\n adp = os.path.join(os.curdir, data_path)\nif not adp:\n _logger.error('app data path not found.')\n return\nfiles = glob(os.pat... | <|body_start_0|>
if not load_data:
return
data_paths = ['app_data', '..app_data']
adp = None
for data_path in data_paths:
if os.path.exists(os.path.join(os.curdir, data_path)):
adp = os.path.join(os.curdir, data_path)
if not adp:
... | base data generator object. | BaseGen | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseGen:
"""base data generator object."""
def __init__(self, load_data=True):
"""Initialize the QuestionnaireGen object. Try to re-use to save on loading files. :param load_data: load data from app_data directory"""
<|body_0|>
def update(self, resp):
"""Update t... | stack_v2_sparse_classes_10k_train_006995 | 2,060 | permissive | [
{
"docstring": "Initialize the QuestionnaireGen object. Try to re-use to save on loading files. :param load_data: load data from app_data directory",
"name": "__init__",
"signature": "def __init__(self, load_data=True)"
},
{
"docstring": "Update this object with response data :param resp: reques... | 2 | stack_v2_sparse_classes_30k_train_005739 | Implement the Python class `BaseGen` described below.
Class description:
base data generator object.
Method signatures and docstrings:
- def __init__(self, load_data=True): Initialize the QuestionnaireGen object. Try to re-use to save on loading files. :param load_data: load data from app_data directory
- def update(... | Implement the Python class `BaseGen` described below.
Class description:
base data generator object.
Method signatures and docstrings:
- def __init__(self, load_data=True): Initialize the QuestionnaireGen object. Try to re-use to save on loading files. :param load_data: load data from app_data directory
- def update(... | 461ae46aeda21d54de8a91aa5ef677676d5db541 | <|skeleton|>
class BaseGen:
"""base data generator object."""
def __init__(self, load_data=True):
"""Initialize the QuestionnaireGen object. Try to re-use to save on loading files. :param load_data: load data from app_data directory"""
<|body_0|>
def update(self, resp):
"""Update t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseGen:
"""base data generator object."""
def __init__(self, load_data=True):
"""Initialize the QuestionnaireGen object. Try to re-use to save on loading files. :param load_data: load data from app_data directory"""
if not load_data:
return
data_paths = ['app_data', '... | the_stack_v2_python_sparse | rdr_service/data_gen/generators/base_gen.py | all-of-us/raw-data-repository | train | 46 |
3e6a63db5f6e37635bbc84bf7ca5c8c630e9fc3e | [
"rt = self.rt\ninstances = self.instances\ngsi = rt['pcms']['gsi']\ngsi_state = rt['gsi_state']\ni8259_irq = gsi_state['i8259_irq']\nioapic_irq = gsi_state['ioapic_irq']\nfor i in range(24):\n gsi_addr = gsi[i].fetch_pointer()\n gsi_inst = instances[gsi_addr]\n self._MachineWatcher__notify_irq_split_create... | <|body_start_0|>
rt = self.rt
instances = self.instances
gsi = rt['pcms']['gsi']
gsi_state = rt['gsi_state']
i8259_irq = gsi_state['i8259_irq']
ioapic_irq = gsi_state['ioapic_irq']
for i in range(24):
gsi_addr = gsi[i].fetch_pointer()
gsi_i... | Support for non-standard IRQ creation of PC i440fx based machines (Global Signaling Interrupts). | PCMachineWatcher | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PCMachineWatcher:
"""Support for non-standard IRQ creation of PC i440fx based machines (Global Signaling Interrupts)."""
def on_pc_piix_gsi(self):
"""pc_piix.c:301 v2.12.0 1"""
<|body_0|>
def on_piix4_pm_gsi(self):
"""acpi/piix4.c:539 v5.1.0 acpi/piix4.c:578 v2.1... | stack_v2_sparse_classes_10k_train_006996 | 26,519 | permissive | [
{
"docstring": "pc_piix.c:301 v2.12.0 1",
"name": "on_pc_piix_gsi",
"signature": "def on_pc_piix_gsi(self)"
},
{
"docstring": "acpi/piix4.c:539 v5.1.0 acpi/piix4.c:578 v2.12.0",
"name": "on_piix4_pm_gsi",
"signature": "def on_piix4_pm_gsi(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005638 | Implement the Python class `PCMachineWatcher` described below.
Class description:
Support for non-standard IRQ creation of PC i440fx based machines (Global Signaling Interrupts).
Method signatures and docstrings:
- def on_pc_piix_gsi(self): pc_piix.c:301 v2.12.0 1
- def on_piix4_pm_gsi(self): acpi/piix4.c:539 v5.1.0 ... | Implement the Python class `PCMachineWatcher` described below.
Class description:
Support for non-standard IRQ creation of PC i440fx based machines (Global Signaling Interrupts).
Method signatures and docstrings:
- def on_pc_piix_gsi(self): pc_piix.c:301 v2.12.0 1
- def on_piix4_pm_gsi(self): acpi/piix4.c:539 v5.1.0 ... | 93e03c2b3f880f5c7c9f90e1ba5593dbf602bdb9 | <|skeleton|>
class PCMachineWatcher:
"""Support for non-standard IRQ creation of PC i440fx based machines (Global Signaling Interrupts)."""
def on_pc_piix_gsi(self):
"""pc_piix.c:301 v2.12.0 1"""
<|body_0|>
def on_piix4_pm_gsi(self):
"""acpi/piix4.c:539 v5.1.0 acpi/piix4.c:578 v2.1... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PCMachineWatcher:
"""Support for non-standard IRQ creation of PC i440fx based machines (Global Signaling Interrupts)."""
def on_pc_piix_gsi(self):
"""pc_piix.c:301 v2.12.0 1"""
rt = self.rt
instances = self.instances
gsi = rt['pcms']['gsi']
gsi_state = rt['gsi_stat... | the_stack_v2_python_sparse | qemu/qemu_watcher.py | ispras/qdt | train | 38 |
ff4986d247f8aee25bf3bbade1aa513a48303284 | [
"init_weights = 'glorot_uniform'\nsuper(RNNDecoder, self).__init__()\nself.embedding = tf.keras.layers.Embedding(output_dim=embedding, input_dim=vocab)\nself.gru = tf.keras.layers.GRU(units=units, recurrent_initializer=init_weights, return_sequences=True, return_state=True)\nself.F = tf.keras.layers.Dense(units=voc... | <|body_start_0|>
init_weights = 'glorot_uniform'
super(RNNDecoder, self).__init__()
self.embedding = tf.keras.layers.Embedding(output_dim=embedding, input_dim=vocab)
self.gru = tf.keras.layers.GRU(units=units, recurrent_initializer=init_weights, return_sequences=True, return_state=True)
... | class RNNEncoder Inherits from tensorflow.keras.layers.Layer to encode 4 ML translation Args: tf ([type]): [description] | RNNDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNDecoder:
"""class RNNEncoder Inherits from tensorflow.keras.layers.Layer to encode 4 ML translation Args: tf ([type]): [description]"""
def __init__(self, vocab, embedding, units, batch):
"""[Class constructor] Args: vocab ([int]): [size of the input vocabulary] embedding ([int]):... | stack_v2_sparse_classes_10k_train_006997 | 2,937 | no_license | [
{
"docstring": "[Class constructor] Args: vocab ([int]): [size of the input vocabulary] embedding ([int]): [dimensionality of the embedding vector] units ([int]): [number of hidden units in the RNN cell] batch ([int]): [batch size instance attributes] Attributes: batch Batch size units Number of hidden units in... | 2 | null | Implement the Python class `RNNDecoder` described below.
Class description:
class RNNEncoder Inherits from tensorflow.keras.layers.Layer to encode 4 ML translation Args: tf ([type]): [description]
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): [Class constructor] Args: vocab (... | Implement the Python class `RNNDecoder` described below.
Class description:
class RNNEncoder Inherits from tensorflow.keras.layers.Layer to encode 4 ML translation Args: tf ([type]): [description]
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): [Class constructor] Args: vocab (... | eb47cd4d12e2f0627bb5e5af28cc0802ff13d0d9 | <|skeleton|>
class RNNDecoder:
"""class RNNEncoder Inherits from tensorflow.keras.layers.Layer to encode 4 ML translation Args: tf ([type]): [description]"""
def __init__(self, vocab, embedding, units, batch):
"""[Class constructor] Args: vocab ([int]): [size of the input vocabulary] embedding ([int]):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RNNDecoder:
"""class RNNEncoder Inherits from tensorflow.keras.layers.Layer to encode 4 ML translation Args: tf ([type]): [description]"""
def __init__(self, vocab, embedding, units, batch):
"""[Class constructor] Args: vocab ([int]): [size of the input vocabulary] embedding ([int]): [dimensional... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/2-rnn_decoder.py | rodrigocruz13/holbertonschool-machine_learning | train | 4 |
546da4336aab8bb0e83a3be2303b77c6baa21bcd | [
"try:\n self.init_rotation = init_rotation\n super().__init__(task_list, qubits=qubits, sweep_points=sweep_points, nr_seqs=nr_seqs, cycles=cycles, init_rotation=init_rotation, **kw)\nexcept Exception as x:\n self.exception = x\n traceback.print_exc()",
"pulse_op_codes_list = []\ntl = [self.preprocesse... | <|body_start_0|>
try:
self.init_rotation = init_rotation
super().__init__(task_list, qubits=qubits, sweep_points=sweep_points, nr_seqs=nr_seqs, cycles=cycles, init_rotation=init_rotation, **kw)
except Exception as x:
self.exception = x
traceback.print_exc(... | Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel. | SingleQubitXEB | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleQubitXEB:
"""Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel."""
def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rotation=None, **kw):
"""Init of the SingleQubitXEB class. The e... | stack_v2_sparse_classes_10k_train_006998 | 38,263 | permissive | [
{
"docstring": "Init of the SingleQubitXEB class. The experiment consists of applying [[Ry - Rz(theta)] * nr_cycles for nr_cycles in cycles] nr_seqs times, with random values of theta each time. Args: nr_seqs (int): the number of times to apply a random iteration of a sequence consisting of nr_cycles cycles. If... | 2 | stack_v2_sparse_classes_30k_train_004252 | Implement the Python class `SingleQubitXEB` described below.
Class description:
Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel.
Method signatures and docstrings:
- def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rota... | Implement the Python class `SingleQubitXEB` described below.
Class description:
Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel.
Method signatures and docstrings:
- def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rota... | bc6733d774fe31a23f4c7e73e5eb0beed8d30e7d | <|skeleton|>
class SingleQubitXEB:
"""Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel."""
def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rotation=None, **kw):
"""Init of the SingleQubitXEB class. The e... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SingleQubitXEB:
"""Class for running the single qubit cross-entropy benchmarking experiment on several qubits in parallel."""
def __init__(self, task_list, sweep_points=None, qubits=None, nr_seqs=None, cycles=None, init_rotation=None, **kw):
"""Init of the SingleQubitXEB class. The experiment con... | the_stack_v2_python_sparse | pycqed/measurement/benchmarking/randomized_benchmarking.py | QudevETH/PycQED_py3 | train | 8 |
21e392a4eca73a9eac62e0fa3663b3b3b8a0b1eb | [
"super(PostProcessor, self).__init__()\nself.score_thresh = score_thresh\nself.nms = nms\nself.detections_per_img = detections_per_img\nself.box_coder = box_coder",
"assert len(boxes) == 1, 'Only single feature'\nboxes = boxes[0]\nclass_logits, box_regression = x\nclass_prob = F.softmax(class_logits, -1)\nimage_s... | <|body_start_0|>
super(PostProcessor, self).__init__()
self.score_thresh = score_thresh
self.nms = nms
self.detections_per_img = detections_per_img
self.box_coder = box_coder
<|end_body_0|>
<|body_start_1|>
assert len(boxes) == 1, 'Only single feature'
boxes = bo... | From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results | PostProcessor | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostProcessor:
"""From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results"""
def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=BoxCoder(weights=(10.0, 10.0, 5.0, 5.0))):
... | stack_v2_sparse_classes_10k_train_006999 | 8,271 | permissive | [
{
"docstring": "Arguments: score_thresh (float) nms (float) detections_per_img (int) box_coder (BoxCoder)",
"name": "__init__",
"signature": "def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=BoxCoder(weights=(10.0, 10.0, 5.0, 5.0)))"
},
{
"docstring": "Arguments: ... | 2 | stack_v2_sparse_classes_30k_train_002771 | Implement the Python class `PostProcessor` described below.
Class description:
From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results
Method signatures and docstrings:
- def __init__(self, score_thresh=0.05, nms=0.5, detections... | Implement the Python class `PostProcessor` described below.
Class description:
From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results
Method signatures and docstrings:
- def __init__(self, score_thresh=0.05, nms=0.5, detections... | 11c38436a158c453e3011f8684570f7a55c03330 | <|skeleton|>
class PostProcessor:
"""From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results"""
def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=BoxCoder(weights=(10.0, 10.0, 5.0, 5.0))):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PostProcessor:
"""From a set of classification scores, box regression and proposals, computes the post-processed boxes, and applies NMS to obtain the final results"""
def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=BoxCoder(weights=(10.0, 10.0, 5.0, 5.0))):
"""Arg... | the_stack_v2_python_sparse | v0.5.0/nvidia/submission/code/object_detection/pytorch/maskrcnn_benchmark/modeling/post_processors/fast_rcnn.py | myelintek/results | train | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.