blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c1523587f90bc9a42b5173aea128d555c4bb7912 | [
"super().__init__(**kwargs)\nself.magnitude = magnitude\nself.n_transforms = n_transforms\nself._max_magnitude = 10.0\nself._max_x_shift = 0.1\nself._max_y_shift = 0.2\nself._max_angle = 30\nself._max_contrast = 1\nself._max_brightness = 1",
"level = self.magnitude / self._max_magnitude\nangle = self.randomly_neg... | <|body_start_0|>
super().__init__(**kwargs)
self.magnitude = magnitude
self.n_transforms = n_transforms
self._max_magnitude = 10.0
self._max_x_shift = 0.1
self._max_y_shift = 0.2
self._max_angle = 30
self._max_contrast = 1
self._max_brightness = 1
... | Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are brightness adjustment and contrast adjustment. | RandAugmentSlice | [
"MIT",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandAugmentSlice:
"""Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are bri... | stack_v2_sparse_classes_36k_train_018200 | 19,979 | permissive | [
{
"docstring": ":param magnitude: magnitude to apply to the transformations as defined in the RandAugment paper. 1 means a weak transform, 10 is the strongest transform. :param n_transforms: number of transformation to sample for each image.",
"name": "__init__",
"signature": "def __init__(self, magnitu... | 3 | stack_v2_sparse_classes_30k_train_017238 | Implement the Python class `RandAugmentSlice` described below.
Class description:
Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additi... | Implement the Python class `RandAugmentSlice` described below.
Class description:
Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additi... | 12b496093097ef48d5ac8880985c04918d7f76fe | <|skeleton|>
class RandAugmentSlice:
"""Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are bri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandAugmentSlice:
"""Implements the RandAugment procedure on a restricted set of transformations. https://arxiv.org/abs/1909.13719 Possible transformations for segmentations maps are: rotation, horizontal and vertical shift, horizontal flip, identity. Additional transformations for images are brightness adjus... | the_stack_v2_python_sparse | InnerEye/ML/utils/augmentation.py | MaxCodeXTC/InnerEye-DeepLearning | train | 1 |
fb4d0df9511817eb85430d4f2962c51ca0883d8c | [
"if root is None:\n return '{}'\nqueue = [root]\nindex = 0\nwhile index < len(queue):\n if queue[index] is not None:\n queue.append(queue[index].left)\n queue.append(queue[index].right)\n index += 1\nwhile queue[-1] is None:\n queue.pop()\nreturn '{%s}' % ','.join((str(node.val) if node is... | <|body_start_0|>
if root is None:
return '{}'
queue = [root]
index = 0
while index < len(queue):
if queue[index] is not None:
queue.append(queue[index].left)
queue.append(queue[index].right)
index += 1
while queu... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_018201 | 5,059 | 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 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: 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:... | 01ee75be4ec9bbb080f170cb747f3fc443eb4d55 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root is None:
return '{}'
queue = [root]
index = 0
while index < len(queue):
if queue[index] is not None:
queue.append(... | the_stack_v2_python_sparse | python3/297_Serialize_and_Deserialize_Binary_Tree.py | ytatus94/Leetcode | train | 0 | |
b3e87975a505a0082bf88f5c44bd6a39ca71666a | [
"super(SentinelClient, self).__init__(server, params, backend)\nself._client_write = None\nself._client_read = None\nself._connection_string = server",
"try:\n connection_params = constring.split('/')\n master_name = connection_params[0]\n servers = [host_port.split(':') for host_port in connection_param... | <|body_start_0|>
super(SentinelClient, self).__init__(server, params, backend)
self._client_write = None
self._client_read = None
self._connection_string = server
<|end_body_0|>
<|body_start_1|>
try:
connection_params = constring.split('/')
master_name = ... | Sentinel client object extending django-redis DefaultClient | SentinelClient | [
"MIT",
"LGPL-2.1-or-later",
"LGPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentinelClient:
"""Sentinel client object extending django-redis DefaultClient"""
def __init__(self, server, params, backend):
"""Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway."""... | stack_v2_sparse_classes_36k_train_018202 | 5,721 | permissive | [
{
"docstring": "Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway.",
"name": "__init__",
"signature": "def __init__(self, server, params, backend)"
},
{
"docstring": "Parse connection string in f... | 5 | stack_v2_sparse_classes_30k_train_008759 | Implement the Python class `SentinelClient` described below.
Class description:
Sentinel client object extending django-redis DefaultClient
Method signatures and docstrings:
- def __init__(self, server, params, backend): Slightly different logic than connection to multiple Redis servers. Reserve only one write and re... | Implement the Python class `SentinelClient` described below.
Class description:
Sentinel client object extending django-redis DefaultClient
Method signatures and docstrings:
- def __init__(self, server, params, backend): Slightly different logic than connection to multiple Redis servers. Reserve only one write and re... | 2d708bd0d869d391456e0fb8d644af3b9f031acf | <|skeleton|>
class SentinelClient:
"""Sentinel client object extending django-redis DefaultClient"""
def __init__(self, server, params, backend):
"""Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SentinelClient:
"""Sentinel client object extending django-redis DefaultClient"""
def __init__(self, server, params, backend):
"""Slightly different logic than connection to multiple Redis servers. Reserve only one write and read descriptors, as they will be closed on exit anyway."""
supe... | the_stack_v2_python_sparse | itsm/component/data/sentinel.py | TencentBlueKing/bk-itsm | train | 100 |
124c97729075dc788d84f7b3a36dfd1a0820525b | [
"from pygtt import PyGTT\nself._pygtt = PyGTT()\nself._stop = stop\nself._bus_name = bus_name\nself.bus_list = {}\nself.state_bus = {}",
"self.bus_list = self._pygtt.get_by_stop(self._stop)\nself.bus_list.sort(key=get_datetime)\nif self._bus_name is not None:\n self.state_bus = self.get_bus_by_name()\n retu... | <|body_start_0|>
from pygtt import PyGTT
self._pygtt = PyGTT()
self._stop = stop
self._bus_name = bus_name
self.bus_list = {}
self.state_bus = {}
<|end_body_0|>
<|body_start_1|>
self.bus_list = self._pygtt.get_by_stop(self._stop)
self.bus_list.sort(key=ge... | Inteface to PyGTT. | GttData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GttData:
"""Inteface to PyGTT."""
def __init__(self, stop, bus_name):
"""Initialize the GttData class."""
<|body_0|>
def get_data(self):
"""Get the data from the api."""
<|body_1|>
def get_bus_by_name(self):
"""Get the bus by name."""
... | stack_v2_sparse_classes_36k_train_018203 | 3,266 | permissive | [
{
"docstring": "Initialize the GttData class.",
"name": "__init__",
"signature": "def __init__(self, stop, bus_name)"
},
{
"docstring": "Get the data from the api.",
"name": "get_data",
"signature": "def get_data(self)"
},
{
"docstring": "Get the bus by name.",
"name": "get_b... | 3 | stack_v2_sparse_classes_30k_train_003523 | Implement the Python class `GttData` described below.
Class description:
Inteface to PyGTT.
Method signatures and docstrings:
- def __init__(self, stop, bus_name): Initialize the GttData class.
- def get_data(self): Get the data from the api.
- def get_bus_by_name(self): Get the bus by name. | Implement the Python class `GttData` described below.
Class description:
Inteface to PyGTT.
Method signatures and docstrings:
- def __init__(self, stop, bus_name): Initialize the GttData class.
- def get_data(self): Get the data from the api.
- def get_bus_by_name(self): Get the bus by name.
<|skeleton|>
class GttDa... | 534eee0796950f3f6aade978316418a194a6b2a1 | <|skeleton|>
class GttData:
"""Inteface to PyGTT."""
def __init__(self, stop, bus_name):
"""Initialize the GttData class."""
<|body_0|>
def get_data(self):
"""Get the data from the api."""
<|body_1|>
def get_bus_by_name(self):
"""Get the bus by name."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GttData:
"""Inteface to PyGTT."""
def __init__(self, stop, bus_name):
"""Initialize the GttData class."""
from pygtt import PyGTT
self._pygtt = PyGTT()
self._stop = stop
self._bus_name = bus_name
self.bus_list = {}
self.state_bus = {}
def get_d... | the_stack_v2_python_sparse | homeassistant/custom_components/gtt/sensor.py | eliseomartelli/HomeAutomation-Config | train | 32 |
751351080ebaf462be12548e5e6e16c2fedd7fd5 | [
"n = len(nums)\ni = 0\nwhile i < len(nums):\n if nums[i] == 'a':\n i += 1\n continue\n if nums[i] <= 0:\n nums[i] = 0\n elif nums[i] > n:\n nums[i] = 0\n else:\n if i < n and i < nums[i] - 1:\n nums.append(nums[nums[i] - 1])\n nums[nums[i] - 1] = 'a'\... | <|body_start_0|>
n = len(nums)
i = 0
while i < len(nums):
if nums[i] == 'a':
i += 1
continue
if nums[i] <= 0:
nums[i] = 0
elif nums[i] > n:
nums[i] = 0
else:
if i < n a... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def firstMissingPositive0(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
i = ... | stack_v2_sparse_classes_36k_train_018204 | 1,502 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "firstMissingPositive",
"signature": "def firstMissingPositive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "firstMissingPositive0",
"signature": "def firstMissingPositive0(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def firstMissingPositive0(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def firstMissingPositive0(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def firstMissingPositive0(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
i = 0
while i < len(nums):
if nums[i] == 'a':
i += 1
continue
if nums[i] <= 0:
nums[i] = 0
e... | the_stack_v2_python_sparse | PythonCode/src/0041_First_Missing_Positive.py | oneyuan/CodeforFun | train | 0 | |
1fafc3060125454ea4b577b9191e82e70c1d2f6d | [
"super().__init__(coordinator, description)\nenpower_data = self.data.enpower\nassert enpower_data is not None\nself._attr_unique_id = f'{enpower_data.serial_number}_{description.key}'\nself._attr_device_info = DeviceInfo(identifiers={(DOMAIN, enpower_data.serial_number)}, manufacturer='Enphase', model='Enpower', n... | <|body_start_0|>
super().__init__(coordinator, description)
enpower_data = self.data.enpower
assert enpower_data is not None
self._attr_unique_id = f'{enpower_data.serial_number}_{description.key}'
self._attr_device_info = DeviceInfo(identifiers={(DOMAIN, enpower_data.serial_numb... | Envoy Enpower sensor entity. | EnvoyEnpowerEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvoyEnpowerEntity:
"""Envoy Enpower sensor entity."""
def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnpowerSensorEntityDescription) -> None:
"""Initialize Enpower entity."""
<|body_0|>
def native_value(self) -> datetime.datetime | int | flo... | stack_v2_sparse_classes_36k_train_018205 | 19,764 | permissive | [
{
"docstring": "Initialize Enpower entity.",
"name": "__init__",
"signature": "def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnpowerSensorEntityDescription) -> None"
},
{
"docstring": "Return the state of the power sensors.",
"name": "native_value",
"signatu... | 2 | null | Implement the Python class `EnvoyEnpowerEntity` described below.
Class description:
Envoy Enpower sensor entity.
Method signatures and docstrings:
- def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnpowerSensorEntityDescription) -> None: Initialize Enpower entity.
- def native_value(self) ... | Implement the Python class `EnvoyEnpowerEntity` described below.
Class description:
Envoy Enpower sensor entity.
Method signatures and docstrings:
- def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnpowerSensorEntityDescription) -> None: Initialize Enpower entity.
- def native_value(self) ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class EnvoyEnpowerEntity:
"""Envoy Enpower sensor entity."""
def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnpowerSensorEntityDescription) -> None:
"""Initialize Enpower entity."""
<|body_0|>
def native_value(self) -> datetime.datetime | int | flo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnvoyEnpowerEntity:
"""Envoy Enpower sensor entity."""
def __init__(self, coordinator: EnphaseUpdateCoordinator, description: EnvoyEnpowerSensorEntityDescription) -> None:
"""Initialize Enpower entity."""
super().__init__(coordinator, description)
enpower_data = self.data.enpower
... | the_stack_v2_python_sparse | homeassistant/components/enphase_envoy/sensor.py | home-assistant/core | train | 35,501 |
252f2daf493396c4a54a3091e5bd71e8b993aae1 | [
"res = len(nums)\nfor i in range(len(nums)):\n res ^= i\n res ^= nums[i]\nreturn res",
"nums.sort()\nfor i in range(len(nums)):\n if i != nums[i]:\n return i\nreturn nums[-1] + 1"
] | <|body_start_0|>
res = len(nums)
for i in range(len(nums)):
res ^= i
res ^= nums[i]
return res
<|end_body_0|>
<|body_start_1|>
nums.sort()
for i in range(len(nums)):
if i != nums[i]:
return i
return nums[-1] + 1
<|end_b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
"""' 使用异或 0 ^ 4 = 4 4 ^ 4 = 0 不用求和，直接使用异或运算^进行 抵消，剩下的数字就是缺失的了。 :type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumber2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_018206 | 1,082 | no_license | [
{
"docstring": "' 使用异或 0 ^ 4 = 4 4 ^ 4 = 0 不用求和，直接使用异或运算^进行 抵消，剩下的数字就是缺失的了。 :type nums: List[int] :rtype: int",
"name": "missingNumber",
"signature": "def missingNumber(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "missingNumber2",
"signature": "def missing... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): ' 使用异或 0 ^ 4 = 4 4 ^ 4 = 0 不用求和，直接使用异或运算^进行 抵消，剩下的数字就是缺失的了。 :type nums: List[int] :rtype: int
- def missingNumber2(self, nums): :type nums: List[in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): ' 使用异或 0 ^ 4 = 4 4 ^ 4 = 0 不用求和，直接使用异或运算^进行 抵消，剩下的数字就是缺失的了。 :type nums: List[int] :rtype: int
- def missingNumber2(self, nums): :type nums: List[in... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
"""' 使用异或 0 ^ 4 = 4 4 ^ 4 = 0 不用求和，直接使用异或运算^进行 抵消，剩下的数字就是缺失的了。 :type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumber2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def missingNumber(self, nums):
"""' 使用异或 0 ^ 4 = 4 4 ^ 4 = 0 不用求和，直接使用异或运算^进行 抵消，剩下的数字就是缺失的了。 :type nums: List[int] :rtype: int"""
res = len(nums)
for i in range(len(nums)):
res ^= i
res ^= nums[i]
return res
def missingNumber2(self, nums)... | the_stack_v2_python_sparse | 268_缺失数字.py | lovehhf/LeetCode | train | 0 | |
5e8b9932734bec2eac26839189e7c997956ec95b | [
"if self.request.version == 'v6':\n return ScaleFileSerializerV6\nelif self.request.version == 'v7':\n return ScaleFileSerializerV6",
"if request.version == 'v6':\n return self._list_v6(request)\nelif request.version == 'v7':\n return self._list_v6(request)\nraise Http404()",
"countries = rest_util.... | <|body_start_0|>
if self.request.version == 'v6':
return ScaleFileSerializerV6
elif self.request.version == 'v7':
return ScaleFileSerializerV6
<|end_body_0|>
<|body_start_1|>
if request.version == 'v6':
return self._list_v6(request)
elif request.versi... | This view is the endpoint for retrieving source/product files | FilesView | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilesView:
"""This view is the endpoint for retrieving source/product files"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API"""
<|body_0|>
def list(self, request):
"""Retrieves the batches and... | stack_v2_sparse_classes_36k_train_018207 | 19,677 | permissive | [
{
"docstring": "Returns the appropriate serializer based off the requests version of the REST API",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Retrieves the batches and returns them in JSON form :param request: the HTTP GET request :type requ... | 3 | stack_v2_sparse_classes_30k_train_020351 | Implement the Python class `FilesView` described below.
Class description:
This view is the endpoint for retrieving source/product files
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API
- def list(self, request): Retr... | Implement the Python class `FilesView` described below.
Class description:
This view is the endpoint for retrieving source/product files
Method signatures and docstrings:
- def get_serializer_class(self): Returns the appropriate serializer based off the requests version of the REST API
- def list(self, request): Retr... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class FilesView:
"""This view is the endpoint for retrieving source/product files"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API"""
<|body_0|>
def list(self, request):
"""Retrieves the batches and... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FilesView:
"""This view is the endpoint for retrieving source/product files"""
def get_serializer_class(self):
"""Returns the appropriate serializer based off the requests version of the REST API"""
if self.request.version == 'v6':
return ScaleFileSerializerV6
elif sel... | the_stack_v2_python_sparse | scale/storage/views.py | kfconsultant/scale | train | 0 |
038e7f4f40bb48ce32ddb6d50eb19eb13c0cea8a | [
"def nodes(node: TreeNode):\n if node is not None:\n yield str(node.val)\n yield from nodes(node.left)\n yield from nodes(node.right)\nreturn ' '.join(nodes(root))",
"def restore(lo: int, hi: int) -> Union[TreeNode, None]:\n if items and lo < items[0] < hi:\n num = items.popleft(... | <|body_start_0|>
def nodes(node: TreeNode):
if node is not None:
yield str(node.val)
yield from nodes(node.left)
yield from nodes(node.right)
return ' '.join(nodes(root))
<|end_body_0|>
<|body_start_1|>
def restore(lo: int, hi: int) ->... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Time/Space: O(n)"""
<|body_0|>
def deserialize(self, data: str) -> Union[TreeNode, None]:
"""Time/Space: O(n)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def nodes(node: TreeNode):
... | stack_v2_sparse_classes_36k_train_018208 | 1,014 | no_license | [
{
"docstring": "Time/Space: O(n)",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Time/Space: O(n)",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> Union[TreeNode, None]"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Time/Space: O(n)
- def deserialize(self, data: str) -> Union[TreeNode, None]: Time/Space: O(n) | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Time/Space: O(n)
- def deserialize(self, data: str) -> Union[TreeNode, None]: Time/Space: O(n)
<|skeleton|>
class Codec:
def serialize... | 359f3b78da90c41c7e42e5c9e13d49b4fc67fe41 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Time/Space: O(n)"""
<|body_0|>
def deserialize(self, data: str) -> Union[TreeNode, None]:
"""Time/Space: O(n)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Time/Space: O(n)"""
def nodes(node: TreeNode):
if node is not None:
yield str(node.val)
yield from nodes(node.left)
yield from nodes(node.right)
return ' '.join(nodes(root)... | the_stack_v2_python_sparse | problems/449. Serialize and Deserialize BST/1 - Preorder + Queue.py | Vasilic-Maxim/LeetCode-Problems | train | 0 | |
1a2ad286bc144f2698ad28212d23b4531edb2d69 | [
"if not head:\n return head\nodd, even, even_head = (head, head.next, head.next)\nwhile even and even.next:\n odd.next = even.next\n odd = odd.next\n even.next = odd.next\n even = even.next\nodd.next = even_head\nreturn head",
"if not head or not head.next:\n return head\neven_head = head.next\n... | <|body_start_0|>
if not head:
return head
odd, even, even_head = (head, head.next, head.next)
while even and even.next:
odd.next = even.next
odd = odd.next
even.next = odd.next
even = even.next
odd.next = even_head
retur... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def oddEvenList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def oddEvenList_v0(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not head:
return he... | stack_v2_sparse_classes_36k_train_018209 | 4,099 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "oddEvenList",
"signature": "def oddEvenList(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "oddEvenList_v0",
"signature": "def oddEvenList_v0(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001294 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def oddEvenList(self, head): :type head: ListNode :rtype: ListNode
- def oddEvenList_v0(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def oddEvenList(self, head): :type head: ListNode :rtype: ListNode
- def oddEvenList_v0(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def ... | b5e09f24e8e96454dc99e20281e853fb9fcc85ed | <|skeleton|>
class Solution:
def oddEvenList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def oddEvenList_v0(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def oddEvenList(self, head):
""":type head: ListNode :rtype: ListNode"""
if not head:
return head
odd, even, even_head = (head, head.next, head.next)
while even and even.next:
odd.next = even.next
odd = odd.next
even.nex... | the_stack_v2_python_sparse | python/328_Odd_Even_Linked_List.py | Moby5/myleetcode | train | 2 | |
bdeccc9fef18eb5aad5d0bf1f75585064b1d3013 | [
"from pyramid.testing import DummySecurityPolicy\npolicy = DummySecurityPolicy(userid, groupids, permissive, remember_result, forget_result)\nself.registry.registerUtility(policy, IAuthorizationPolicy)\nself.registry.registerUtility(policy, IAuthenticationPolicy)\nreturn policy",
"class DummyTraverserFactory:\n\n... | <|body_start_0|>
from pyramid.testing import DummySecurityPolicy
policy = DummySecurityPolicy(userid, groupids, permissive, remember_result, forget_result)
self.registry.registerUtility(policy, IAuthorizationPolicy)
self.registry.registerUtility(policy, IAuthenticationPolicy)
ret... | TestingConfiguratorMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestingConfiguratorMixin:
def testing_securitypolicy(self, userid=None, groupids=(), permissive=True, remember_result=None, forget_result=None):
"""Unit/integration testing helper: Registers a pair of faux :app:`Pyramid` security policies: a :term:`authentication policy` and a :term:`aut... | stack_v2_sparse_classes_36k_train_018210 | 7,302 | permissive | [
{
"docstring": "Unit/integration testing helper: Registers a pair of faux :app:`Pyramid` security policies: a :term:`authentication policy` and a :term:`authorization policy`. The behavior of the registered :term:`authorization policy` depends on the ``permissive`` argument. If ``permissive`` is true, a permiss... | 4 | stack_v2_sparse_classes_30k_train_002698 | Implement the Python class `TestingConfiguratorMixin` described below.
Class description:
Implement the TestingConfiguratorMixin class.
Method signatures and docstrings:
- def testing_securitypolicy(self, userid=None, groupids=(), permissive=True, remember_result=None, forget_result=None): Unit/integration testing he... | Implement the Python class `TestingConfiguratorMixin` described below.
Class description:
Implement the TestingConfiguratorMixin class.
Method signatures and docstrings:
- def testing_securitypolicy(self, userid=None, groupids=(), permissive=True, remember_result=None, forget_result=None): Unit/integration testing he... | 8d08bb85fcbc28800c2c9b35f370d8cc0813dac9 | <|skeleton|>
class TestingConfiguratorMixin:
def testing_securitypolicy(self, userid=None, groupids=(), permissive=True, remember_result=None, forget_result=None):
"""Unit/integration testing helper: Registers a pair of faux :app:`Pyramid` security policies: a :term:`authentication policy` and a :term:`aut... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestingConfiguratorMixin:
def testing_securitypolicy(self, userid=None, groupids=(), permissive=True, remember_result=None, forget_result=None):
"""Unit/integration testing helper: Registers a pair of faux :app:`Pyramid` security policies: a :term:`authentication policy` and a :term:`authorization pol... | the_stack_v2_python_sparse | venv/Lib/site-packages/pyramid/config/testing.py | supermax03/Port-Scanner-as-a-Service-2 | train | 0 | |
f4993869f710f3dba6a7d9316f24bbad6bedacad | [
"if len(password) < 9:\n return False\nreturn True",
"pattern = '\\\\d'\nif not re.search(pattern, password):\n return False\nreturn True",
"pattern = '\\\\w'\nif not re.search(pattern, password):\n return False\nreturn True",
"pattern = '\\\\W'\nif not re.search(pattern, password):\n return False... | <|body_start_0|>
if len(password) < 9:
return False
return True
<|end_body_0|>
<|body_start_1|>
pattern = '\\d'
if not re.search(pattern, password):
return False
return True
<|end_body_1|>
<|body_start_2|>
pattern = '\\w'
if not re.search... | 密码复杂度检查 | CheckPass | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckPass:
"""密码复杂度检查"""
def check_length(password):
"""长度"""
<|body_0|>
def check_number_exists(password):
"""数字"""
<|body_1|>
def check_letter_exists(password):
"""大小写字母"""
<|body_2|>
def check_special_exists(password):
... | stack_v2_sparse_classes_36k_train_018211 | 1,276 | no_license | [
{
"docstring": "长度",
"name": "check_length",
"signature": "def check_length(password)"
},
{
"docstring": "数字",
"name": "check_number_exists",
"signature": "def check_number_exists(password)"
},
{
"docstring": "大小写字母",
"name": "check_letter_exists",
"signature": "def check... | 4 | null | Implement the Python class `CheckPass` described below.
Class description:
密码复杂度检查
Method signatures and docstrings:
- def check_length(password): 长度
- def check_number_exists(password): 数字
- def check_letter_exists(password): 大小写字母
- def check_special_exists(password): 特殊字符 | Implement the Python class `CheckPass` described below.
Class description:
密码复杂度检查
Method signatures and docstrings:
- def check_length(password): 长度
- def check_number_exists(password): 数字
- def check_letter_exists(password): 大小写字母
- def check_special_exists(password): 特殊字符
<|skeleton|>
class CheckPass:
"""密码复杂... | 04bb7f387633ba8af81148dc73a95c2a6d56a8d1 | <|skeleton|>
class CheckPass:
"""密码复杂度检查"""
def check_length(password):
"""长度"""
<|body_0|>
def check_number_exists(password):
"""数字"""
<|body_1|>
def check_letter_exists(password):
"""大小写字母"""
<|body_2|>
def check_special_exists(password):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckPass:
"""密码复杂度检查"""
def check_length(password):
"""长度"""
if len(password) < 9:
return False
return True
def check_number_exists(password):
"""数字"""
pattern = '\\d'
if not re.search(pattern, password):
return False
r... | the_stack_v2_python_sparse | app/utils/check_pass.py | Rabbit-st/rabbit | train | 0 |
078792af45859978f5e44b8afac3bbd92d69794d | [
"payload_proto = training_job_response_payload_pb2.TrainingJobResponsePayload()\npayload_proto.ParseFromString(self.request.body)\nsignature = payload_proto.signature\nvm_id = payload_proto.vm_id\nreturn classifier_domain.OppiaMLAuthInfo(payload_proto.job_result.SerializeToString(), vm_id, signature)",
"payload_p... | <|body_start_0|>
payload_proto = training_job_response_payload_pb2.TrainingJobResponsePayload()
payload_proto.ParseFromString(self.request.body)
signature = payload_proto.signature
vm_id = payload_proto.vm_id
return classifier_domain.OppiaMLAuthInfo(payload_proto.job_result.Seria... | This handler stores the result of the training job in datastore and updates the status of the job. | TrainedClassifierHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainedClassifierHandler:
"""This handler stores the result of the training job in datastore and updates the status of the job."""
def extract_request_message_vm_id_and_signature(self) -> classifier_domain.OppiaMLAuthInfo:
"""Returns message, vm_id and signature retrieved from incomi... | stack_v2_sparse_classes_36k_train_018212 | 11,389 | permissive | [
{
"docstring": "Returns message, vm_id and signature retrieved from incoming request. Returns: OppiaMLAuthInfo. Message at index 0, vm_id at index 1 and signature at index 2.",
"name": "extract_request_message_vm_id_and_signature",
"signature": "def extract_request_message_vm_id_and_signature(self) -> c... | 3 | null | Implement the Python class `TrainedClassifierHandler` described below.
Class description:
This handler stores the result of the training job in datastore and updates the status of the job.
Method signatures and docstrings:
- def extract_request_message_vm_id_and_signature(self) -> classifier_domain.OppiaMLAuthInfo: R... | Implement the Python class `TrainedClassifierHandler` described below.
Class description:
This handler stores the result of the training job in datastore and updates the status of the job.
Method signatures and docstrings:
- def extract_request_message_vm_id_and_signature(self) -> classifier_domain.OppiaMLAuthInfo: R... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class TrainedClassifierHandler:
"""This handler stores the result of the training job in datastore and updates the status of the job."""
def extract_request_message_vm_id_and_signature(self) -> classifier_domain.OppiaMLAuthInfo:
"""Returns message, vm_id and signature retrieved from incomi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainedClassifierHandler:
"""This handler stores the result of the training job in datastore and updates the status of the job."""
def extract_request_message_vm_id_and_signature(self) -> classifier_domain.OppiaMLAuthInfo:
"""Returns message, vm_id and signature retrieved from incoming request. R... | the_stack_v2_python_sparse | core/controllers/classifier.py | oppia/oppia | train | 6,172 |
d4da298294246ba9fb6f097affa8460719beaff6 | [
"super(SceneNode, self).__init__()\nself.name = name\nself.transform = Transform()\nself.world_transform = WorldTransform(self.transform)\ndispatcher.connect(self._on_parent_changed, TreeNode.on_parent_changed, self)",
"if old_parent != None:\n old_parent.world_transform.remove_child(self.world_transform)\nif ... | <|body_start_0|>
super(SceneNode, self).__init__()
self.name = name
self.transform = Transform()
self.world_transform = WorldTransform(self.transform)
dispatcher.connect(self._on_parent_changed, TreeNode.on_parent_changed, self)
<|end_body_0|>
<|body_start_1|>
if old_par... | Base class for Scene Graph objects. | SceneNode | [
"BSD-2-Clause-Views",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SceneNode:
"""Base class for Scene Graph objects."""
def __init__(self, name):
"""Creates a SceneNode object with the specified name."""
<|body_0|>
def _on_parent_changed(self, old_parent, new_parent):
"""Event handler for TreeNode's parent events. Manages the ad... | stack_v2_sparse_classes_36k_train_018213 | 1,670 | permissive | [
{
"docstring": "Creates a SceneNode object with the specified name.",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Event handler for TreeNode's parent events. Manages the addition and removal of our world transform from our parent.",
"name": "_on_parent_chan... | 2 | stack_v2_sparse_classes_30k_train_018352 | Implement the Python class `SceneNode` described below.
Class description:
Base class for Scene Graph objects.
Method signatures and docstrings:
- def __init__(self, name): Creates a SceneNode object with the specified name.
- def _on_parent_changed(self, old_parent, new_parent): Event handler for TreeNode's parent e... | Implement the Python class `SceneNode` described below.
Class description:
Base class for Scene Graph objects.
Method signatures and docstrings:
- def __init__(self, name): Creates a SceneNode object with the specified name.
- def _on_parent_changed(self, old_parent, new_parent): Event handler for TreeNode's parent e... | 929d50e2bd8b24f079e6c43d6a54b2ff8e572d5f | <|skeleton|>
class SceneNode:
"""Base class for Scene Graph objects."""
def __init__(self, name):
"""Creates a SceneNode object with the specified name."""
<|body_0|>
def _on_parent_changed(self, old_parent, new_parent):
"""Event handler for TreeNode's parent events. Manages the ad... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SceneNode:
"""Base class for Scene Graph objects."""
def __init__(self, name):
"""Creates a SceneNode object with the specified name."""
super(SceneNode, self).__init__()
self.name = name
self.transform = Transform()
self.world_transform = WorldTransform(self.trans... | the_stack_v2_python_sparse | pygly/scene_node.py | adamlwgriffiths/PyGLy | train | 28 |
8b734006b474033bb71c3699c1f1c9bbc21479db | [
"yMax = 0\nyMin = 0\nif len(logList) == 0:\n logger.debug('Log list length is zero cannot set log depth range')\n return (yMin, yMax)\nelif len(logList[0].z_measure_data) == 0:\n logger.debug('Log depth data length is zero cannot set log depth range')\n return (yMin, yMax)\nyMax = logList[0].z_measure_d... | <|body_start_0|>
yMax = 0
yMin = 0
if len(logList) == 0:
logger.debug('Log list length is zero cannot set log depth range')
return (yMin, yMax)
elif len(logList[0].z_measure_data) == 0:
logger.debug('Log depth data length is zero cannot set log depth r... | Logic layer wrapper for LogBase | Log | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Log:
"""Logic layer wrapper for LogBase"""
def getDepthRange(self, logList):
"""finds max and min depth values for all log data supplied returns all logs depth min, max"""
<|body_0|>
def findLogWithLargestDepthRange(self, logList):
"""returns longest (log with la... | stack_v2_sparse_classes_36k_train_018214 | 2,464 | permissive | [
{
"docstring": "finds max and min depth values for all log data supplied returns all logs depth min, max",
"name": "getDepthRange",
"signature": "def getDepthRange(self, logList)"
},
{
"docstring": "returns longest (log with largest depth min, max difference) relies on z_measure_max and z_measur... | 3 | null | Implement the Python class `Log` described below.
Class description:
Logic layer wrapper for LogBase
Method signatures and docstrings:
- def getDepthRange(self, logList): finds max and min depth values for all log data supplied returns all logs depth min, max
- def findLogWithLargestDepthRange(self, logList): returns... | Implement the Python class `Log` described below.
Class description:
Logic layer wrapper for LogBase
Method signatures and docstrings:
- def getDepthRange(self, logList): finds max and min depth values for all log data supplied returns all logs depth min, max
- def findLogWithLargestDepthRange(self, logList): returns... | 20fba1b1fd1a42add223d9e8af2d267665bec493 | <|skeleton|>
class Log:
"""Logic layer wrapper for LogBase"""
def getDepthRange(self, logList):
"""finds max and min depth values for all log data supplied returns all logs depth min, max"""
<|body_0|>
def findLogWithLargestDepthRange(self, logList):
"""returns longest (log with la... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Log:
"""Logic layer wrapper for LogBase"""
def getDepthRange(self, logList):
"""finds max and min depth values for all log data supplied returns all logs depth min, max"""
yMax = 0
yMin = 0
if len(logList) == 0:
logger.debug('Log list length is zero cannot set ... | the_stack_v2_python_sparse | db/core/log/log.py | ABV-Hub/qreservoir | train | 0 |
9997f09387522570e5cfb1369655a98206fcf4bb | [
"self.product_code = product_code\nself.description = description\nself.market_price = market_price\nself.rental_price = rental_price",
"output_dict = {}\noutput_dict['productCode'] = self.product_code\noutput_dict['description'] = self.description\noutput_dict['marketPrice'] = self.market_price\noutput_dict['ren... | <|body_start_0|>
self.product_code = product_code
self.description = description
self.market_price = market_price
self.rental_price = rental_price
<|end_body_0|>
<|body_start_1|>
output_dict = {}
output_dict['productCode'] = self.product_code
output_dict['descrip... | inventory base class | Inventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inventory:
"""inventory base class"""
def __init__(self, product_code, description, market_price, rental_price):
"""initializing"""
<|body_0|>
def return_as_dictionary(self):
"""returns a dictionary"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_018215 | 772 | no_license | [
{
"docstring": "initializing",
"name": "__init__",
"signature": "def __init__(self, product_code, description, market_price, rental_price)"
},
{
"docstring": "returns a dictionary",
"name": "return_as_dictionary",
"signature": "def return_as_dictionary(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005413 | Implement the Python class `Inventory` described below.
Class description:
inventory base class
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price): initializing
- def return_as_dictionary(self): returns a dictionary | Implement the Python class `Inventory` described below.
Class description:
inventory base class
Method signatures and docstrings:
- def __init__(self, product_code, description, market_price, rental_price): initializing
- def return_as_dictionary(self): returns a dictionary
<|skeleton|>
class Inventory:
"""inven... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class Inventory:
"""inventory base class"""
def __init__(self, product_code, description, market_price, rental_price):
"""initializing"""
<|body_0|>
def return_as_dictionary(self):
"""returns a dictionary"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Inventory:
"""inventory base class"""
def __init__(self, product_code, description, market_price, rental_price):
"""initializing"""
self.product_code = product_code
self.description = description
self.market_price = market_price
self.rental_price = rental_price
... | the_stack_v2_python_sparse | students/humberto_gonzalez/lesson01/inventory_management/inventory_class.py | JavaRod/SP_Python220B_2019 | train | 1 |
341d8807eb407681ac4a7202b209f63a5642d24b | [
"super().__init__()\nself.msg_function_edge = nn.Sequential(nn.Linear(edge_size, node_size), ShiftedSoftplus(), nn.Linear(node_size, node_size))\nself.msg_function_node = nn.Sequential(nn.Linear(node_size, node_size), ShiftedSoftplus(), nn.Linear(node_size, node_size))",
"gates = self.msg_function_edge(edge_state... | <|body_start_0|>
super().__init__()
self.msg_function_edge = nn.Sequential(nn.Linear(edge_size, node_size), ShiftedSoftplus(), nn.Linear(node_size, node_size))
self.msg_function_node = nn.Sequential(nn.Linear(node_size, node_size), ShiftedSoftplus(), nn.Linear(node_size, node_size))
<|end_body_0... | Message function | SchnetMessageFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchnetMessageFunction:
"""Message function"""
def __init__(self, node_size, edge_size):
"""Args: node_size (int): Size of node state edge_size (int): Size of edge state"""
<|body_0|>
def forward(self, node_state, edge_state):
"""Args: node_state (tensor): State o... | stack_v2_sparse_classes_36k_train_018216 | 7,647 | no_license | [
{
"docstring": "Args: node_size (int): Size of node state edge_size (int): Size of edge state",
"name": "__init__",
"signature": "def __init__(self, node_size, edge_size)"
},
{
"docstring": "Args: node_state (tensor): State of each sender node (num_edges, node_size) edge_state (tensor): Edge sta... | 2 | stack_v2_sparse_classes_30k_train_001324 | Implement the Python class `SchnetMessageFunction` described below.
Class description:
Message function
Method signatures and docstrings:
- def __init__(self, node_size, edge_size): Args: node_size (int): Size of node state edge_size (int): Size of edge state
- def forward(self, node_state, edge_state): Args: node_st... | Implement the Python class `SchnetMessageFunction` described below.
Class description:
Message function
Method signatures and docstrings:
- def __init__(self, node_size, edge_size): Args: node_size (int): Size of node state edge_size (int): Size of edge state
- def forward(self, node_state, edge_state): Args: node_st... | 117b1898d389b4b1727f0531c1f7eb827384f5c8 | <|skeleton|>
class SchnetMessageFunction:
"""Message function"""
def __init__(self, node_size, edge_size):
"""Args: node_size (int): Size of node state edge_size (int): Size of edge state"""
<|body_0|>
def forward(self, node_state, edge_state):
"""Args: node_state (tensor): State o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SchnetMessageFunction:
"""Message function"""
def __init__(self, node_size, edge_size):
"""Args: node_size (int): Size of node state edge_size (int): Size of edge state"""
super().__init__()
self.msg_function_edge = nn.Sequential(nn.Linear(edge_size, node_size), ShiftedSoftplus(),... | the_stack_v2_python_sparse | models/layer.py | bhastrup/RL-on-energy-surfaces | train | 0 |
8a2649388439d558532beb9fe1dfa919978382e9 | [
"if key is None or item is None:\n return\nself.cache_data[key] = item",
"if key is None or key not in self.cache_data:\n return None\nvalue = self.cache_data.get(key)\nreturn value"
] | <|body_start_0|>
if key is None or item is None:
return
self.cache_data[key] = item
<|end_body_0|>
<|body_start_1|>
if key is None or key not in self.cache_data:
return None
value = self.cache_data.get(key)
return value
<|end_body_1|>
| class basiccache child class to basecaching | BasicCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicCache:
"""class basiccache child class to basecaching"""
def put(self, key, item):
"""Add an item in the cache"""
<|body_0|>
def get(self, key):
"""Get an item by key"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if key is None or item is... | stack_v2_sparse_classes_36k_train_018217 | 586 | no_license | [
{
"docstring": "Add an item in the cache",
"name": "put",
"signature": "def put(self, key, item)"
},
{
"docstring": "Get an item by key",
"name": "get",
"signature": "def get(self, key)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002867 | Implement the Python class `BasicCache` described below.
Class description:
class basiccache child class to basecaching
Method signatures and docstrings:
- def put(self, key, item): Add an item in the cache
- def get(self, key): Get an item by key | Implement the Python class `BasicCache` described below.
Class description:
class basiccache child class to basecaching
Method signatures and docstrings:
- def put(self, key, item): Add an item in the cache
- def get(self, key): Get an item by key
<|skeleton|>
class BasicCache:
"""class basiccache child class to... | c0182a227da7a47fd641b3d9e085243b36b626db | <|skeleton|>
class BasicCache:
"""class basiccache child class to basecaching"""
def put(self, key, item):
"""Add an item in the cache"""
<|body_0|>
def get(self, key):
"""Get an item by key"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicCache:
"""class basiccache child class to basecaching"""
def put(self, key, item):
"""Add an item in the cache"""
if key is None or item is None:
return
self.cache_data[key] = item
def get(self, key):
"""Get an item by key"""
if key is None or... | the_stack_v2_python_sparse | 0x03-caching/0-basic_cache.py | Jilroge7/holbertonschool-web_back_end | train | 0 |
2fe5e1aa02b31005092dcd43d6f3fb2d697408d6 | [
"self.base_image = pygame.image.load(image)\nself.images = []\nself.duration = duration\nself.last_change = time()\nself.selected_image = 0\nsprite_w = self.base_image.get_width() / w\nsprite_h = self.base_image.get_height() / h\nself.final_size = final_size\nself.invisible_color = invisible_color\nif final_size is... | <|body_start_0|>
self.base_image = pygame.image.load(image)
self.images = []
self.duration = duration
self.last_change = time()
self.selected_image = 0
sprite_w = self.base_image.get_width() / w
sprite_h = self.base_image.get_height() / h
self.final_size =... | SpriteSheet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h... | stack_v2_sparse_classes_36k_train_018218 | 2,468 | no_license | [
{
"docstring": "This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h: the height of each frame in the sheet :param duration: the number of seconds to stay on each frame :param final_size: the final size to scale the imag... | 3 | stack_v2_sparse_classes_30k_train_021651 | Implement the Python class `SpriteSheet` described below.
Class description:
Implement the SpriteSheet class.
Method signatures and docstrings:
- def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)): This class is for creating spritesheets :par... | Implement the Python class `SpriteSheet` described below.
Class description:
Implement the SpriteSheet class.
Method signatures and docstrings:
- def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)): This class is for creating spritesheets :par... | e9e68cf3ba4f9f12e66eae81893ca9dcc534835c | <|skeleton|>
class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h: the height o... | the_stack_v2_python_sparse | Objects/SpriteSheet.py | john-palazzolo/PyGE | train | 0 | |
c969c9c9b90dfe4a487a32c12d317b2b663469aa | [
"res = []\n\ndef preOrder(root):\n if root:\n res.append(str(root.val))\n preOrder(root.left)\n preOrder(root.right)\npreOrder(root)\nreturn ' '.join(res)",
"vals = collections.deque((val for val in data.split()))\n\ndef build(minVal, maxVal):\n if vals and minVal < vals[0] < maxVal:\n ... | <|body_start_0|>
res = []
def preOrder(root):
if root:
res.append(str(root.val))
preOrder(root.left)
preOrder(root.right)
preOrder(root)
return ' '.join(res)
<|end_body_0|>
<|body_start_1|>
vals = collections.deque((va... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
... | stack_v2_sparse_classes_36k_train_018219 | 3,330 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_012018 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 3fe8c2298a52a15fadec0693e00445d875c4b6ea | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
res = []
def preOrder(root):
if root:
res.append(str(root.val))
preOrder(root.left)
preOrder(root.right)
preOrder(root)
... | the_stack_v2_python_sparse | Serialize and Deserialize BST.py | huiyi999/leetcode_python | train | 0 | |
f863c52b39e2dc0c857874b6af24dc600c89f412 | [
"filters = [('uuid', None, 'str')]\nparams = external_common.parse_arguments(filters, kwargs)\nif not params.uuid:\n raise MissingOrBadArgumentError(\"Mandatory parameter 'uuid' is missing or empty\")\nsql = '\\n /* socorro.external.postgresql.priorityjobs.Priorityjobs.get */\\n SELECT uuid... | <|body_start_0|>
filters = [('uuid', None, 'str')]
params = external_common.parse_arguments(filters, kwargs)
if not params.uuid:
raise MissingOrBadArgumentError("Mandatory parameter 'uuid' is missing or empty")
sql = '\n /* socorro.external.postgresql.priorityjobs.... | Implement the /priorityjobs service with PostgreSQL. | Priorityjobs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Priorityjobs:
"""Implement the /priorityjobs service with PostgreSQL."""
def get(self, **kwargs):
"""Return a job in the priority queue."""
<|body_0|>
def create(self, **kwargs):
"""Add a new job to the priority queue if not already in that queue."""
<|bo... | stack_v2_sparse_classes_36k_train_018220 | 3,475 | no_license | [
{
"docstring": "Return a job in the priority queue.",
"name": "get",
"signature": "def get(self, **kwargs)"
},
{
"docstring": "Add a new job to the priority queue if not already in that queue.",
"name": "create",
"signature": "def create(self, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020174 | Implement the Python class `Priorityjobs` described below.
Class description:
Implement the /priorityjobs service with PostgreSQL.
Method signatures and docstrings:
- def get(self, **kwargs): Return a job in the priority queue.
- def create(self, **kwargs): Add a new job to the priority queue if not already in that q... | Implement the Python class `Priorityjobs` described below.
Class description:
Implement the /priorityjobs service with PostgreSQL.
Method signatures and docstrings:
- def get(self, **kwargs): Return a job in the priority queue.
- def create(self, **kwargs): Add a new job to the priority queue if not already in that q... | aafd7ed25b3601653584337b4af29254d98b3ade | <|skeleton|>
class Priorityjobs:
"""Implement the /priorityjobs service with PostgreSQL."""
def get(self, **kwargs):
"""Return a job in the priority queue."""
<|body_0|>
def create(self, **kwargs):
"""Add a new job to the priority queue if not already in that queue."""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Priorityjobs:
"""Implement the /priorityjobs service with PostgreSQL."""
def get(self, **kwargs):
"""Return a job in the priority queue."""
filters = [('uuid', None, 'str')]
params = external_common.parse_arguments(filters, kwargs)
if not params.uuid:
raise Mis... | the_stack_v2_python_sparse | socorro/external/postgresql/priorityjobs.py | mpressman/socorro | train | 0 |
f6fc44385200a173674cfb15cbc87bf8dfe7e5cb | [
"columns = []\ncolumns = DownloadAlliesTest.fields_helper(User, columns)\ncolumns = DownloadAlliesTest.fields_helper(Ally, columns)\ncolumns = DownloadAlliesTest.fields_helper(StudentCategories, columns)\nallies = Ally.objects.all()\ndata = []\nfor user in allies:\n categories = StudentCategories.objects.filter(... | <|body_start_0|>
columns = []
columns = DownloadAlliesTest.fields_helper(User, columns)
columns = DownloadAlliesTest.fields_helper(Ally, columns)
columns = DownloadAlliesTest.fields_helper(StudentCategories, columns)
allies = Ally.objects.all()
data = []
for user ... | Unit tests for upload feature | UploadFileTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadFileTest:
"""Unit tests for upload feature"""
def make_frame():
"""helper function for upload file test"""
<|body_0|>
def setUp(self):
"""Set up the test"""
<|body_1|>
def test_post_not_staff(self):
"""upload file: testing files that ha... | stack_v2_sparse_classes_36k_train_018221 | 44,760 | no_license | [
{
"docstring": "helper function for upload file test",
"name": "make_frame",
"signature": "def make_frame()"
},
{
"docstring": "Set up the test",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "upload file: testing files that has inappropriate input",
"name... | 5 | stack_v2_sparse_classes_30k_train_004373 | Implement the Python class `UploadFileTest` described below.
Class description:
Unit tests for upload feature
Method signatures and docstrings:
- def make_frame(): helper function for upload file test
- def setUp(self): Set up the test
- def test_post_not_staff(self): upload file: testing files that has inappropriate... | Implement the Python class `UploadFileTest` described below.
Class description:
Unit tests for upload feature
Method signatures and docstrings:
- def make_frame(): helper function for upload file test
- def setUp(self): Set up the test
- def test_post_not_staff(self): upload file: testing files that has inappropriate... | cafd691a7bb5e78e03d93a7c8f46ae3a69f1a01e | <|skeleton|>
class UploadFileTest:
"""Unit tests for upload feature"""
def make_frame():
"""helper function for upload file test"""
<|body_0|>
def setUp(self):
"""Set up the test"""
<|body_1|>
def test_post_not_staff(self):
"""upload file: testing files that ha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UploadFileTest:
"""Unit tests for upload feature"""
def make_frame():
"""helper function for upload file test"""
columns = []
columns = DownloadAlliesTest.fields_helper(User, columns)
columns = DownloadAlliesTest.fields_helper(Ally, columns)
columns = DownloadAllie... | the_stack_v2_python_sparse | sap/tests_v3.py | zshanahmed/SAP | train | 2 |
9a43b92e4bb5334fd39f8c837b1e679c197cb7c5 | [
"logging.info('*** 登录功能 - 正常登录用例：登录成功 ***')\ninit_driver['lp'].login(LD.correct_data['account'], LD.correct_data['password'])\ntime.sleep(0.5)\nassert init_driver['driver'].current_url == LD.correct_data['check_url']",
"logging.info('*** 登陆功能 - 异常用例 - 用户名不能为空/密码不能为空 ***')\ninit_driver['lp'].login(case['account'],... | <|body_start_0|>
logging.info('*** 登录功能 - 正常登录用例：登录成功 ***')
init_driver['lp'].login(LD.correct_data['account'], LD.correct_data['password'])
time.sleep(0.5)
assert init_driver['driver'].current_url == LD.correct_data['check_url']
<|end_body_0|>
<|body_start_1|>
logging.info('***... | TestLogin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLogin:
def test_login_success(self, init_driver):
"""正常场景 -- 登录成功 :param init_driver: 使用前置后置的返回值 :return:"""
<|body_0|>
def test_login_failed(self, case, init_driver):
"""异常用例 - 用户名不能为空/密码不能为空 :param case: 数据驱动，使用 LD.wrong_data 传递的参数 :param init_driver: 使用前置后置的返回... | stack_v2_sparse_classes_36k_train_018222 | 2,650 | no_license | [
{
"docstring": "正常场景 -- 登录成功 :param init_driver: 使用前置后置的返回值 :return:",
"name": "test_login_success",
"signature": "def test_login_success(self, init_driver)"
},
{
"docstring": "异常用例 - 用户名不能为空/密码不能为空 :param case: 数据驱动，使用 LD.wrong_data 传递的参数 :param init_driver: 使用前置后置的返回值 :return:",
"name": "t... | 2 | null | Implement the Python class `TestLogin` described below.
Class description:
Implement the TestLogin class.
Method signatures and docstrings:
- def test_login_success(self, init_driver): 正常场景 -- 登录成功 :param init_driver: 使用前置后置的返回值 :return:
- def test_login_failed(self, case, init_driver): 异常用例 - 用户名不能为空/密码不能为空 :param c... | Implement the Python class `TestLogin` described below.
Class description:
Implement the TestLogin class.
Method signatures and docstrings:
- def test_login_success(self, init_driver): 正常场景 -- 登录成功 :param init_driver: 使用前置后置的返回值 :return:
- def test_login_failed(self, case, init_driver): 异常用例 - 用户名不能为空/密码不能为空 :param c... | cfadd3132c2c7c518c784589e0dab6510a662a6c | <|skeleton|>
class TestLogin:
def test_login_success(self, init_driver):
"""正常场景 -- 登录成功 :param init_driver: 使用前置后置的返回值 :return:"""
<|body_0|>
def test_login_failed(self, case, init_driver):
"""异常用例 - 用户名不能为空/密码不能为空 :param case: 数据驱动，使用 LD.wrong_data 传递的参数 :param init_driver: 使用前置后置的返回... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestLogin:
def test_login_success(self, init_driver):
"""正常场景 -- 登录成功 :param init_driver: 使用前置后置的返回值 :return:"""
logging.info('*** 登录功能 - 正常登录用例：登录成功 ***')
init_driver['lp'].login(LD.correct_data['account'], LD.correct_data['password'])
time.sleep(0.5)
assert init_drive... | the_stack_v2_python_sparse | lemon/Python_ketangpai/test_cases/test_login.py | songyongzhuang/PythonCode_office | train | 0 | |
30320a9cfbeb7999bf7cebd6f29d244942537849 | [
"self._threshold = threshold\nself._partner_defections = 0\nself._ready_to_interact = False\nself._cooperate_resource_index = 0\nself._defect_resource_index = 1\nself._column_player_is_focal = True",
"interaction_inventories = observation['INTERACTION_INVENTORIES']\nrow_inventory = interaction_inventories[0]\ncol... | <|body_start_0|>
self._threshold = threshold
self._partner_defections = 0
self._ready_to_interact = False
self._cooperate_resource_index = 0
self._defect_resource_index = 1
self._column_player_is_focal = True
<|end_body_0|>
<|body_start_1|>
interaction_inventorie... | Puppeteer function for a GRIM strategy in two resource *_in_the_matrix. | GrimTwoResourceInTheMatrix | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GrimTwoResourceInTheMatrix:
"""Puppeteer function for a GRIM strategy in two resource *_in_the_matrix."""
def __init__(self, threshold: int) -> None:
"""Initializes the puppeteer. Args: threshold: number of defections after which it will switch behavior."""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_018223 | 7,109 | permissive | [
{
"docstring": "Initializes the puppeteer. Args: threshold: number of defections after which it will switch behavior.",
"name": "__init__",
"signature": "def __init__(self, threshold: int) -> None"
},
{
"docstring": "Returns the focal and partner inventories from the latest interaction.",
"n... | 4 | stack_v2_sparse_classes_30k_train_005818 | Implement the Python class `GrimTwoResourceInTheMatrix` described below.
Class description:
Puppeteer function for a GRIM strategy in two resource *_in_the_matrix.
Method signatures and docstrings:
- def __init__(self, threshold: int) -> None: Initializes the puppeteer. Args: threshold: number of defections after whi... | Implement the Python class `GrimTwoResourceInTheMatrix` described below.
Class description:
Puppeteer function for a GRIM strategy in two resource *_in_the_matrix.
Method signatures and docstrings:
- def __init__(self, threshold: int) -> None: Initializes the puppeteer. Args: threshold: number of defections after whi... | e42b916b32771f7af5ad4eccbdf4ded410735299 | <|skeleton|>
class GrimTwoResourceInTheMatrix:
"""Puppeteer function for a GRIM strategy in two resource *_in_the_matrix."""
def __init__(self, threshold: int) -> None:
"""Initializes the puppeteer. Args: threshold: number of defections after which it will switch behavior."""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GrimTwoResourceInTheMatrix:
"""Puppeteer function for a GRIM strategy in two resource *_in_the_matrix."""
def __init__(self, threshold: int) -> None:
"""Initializes the puppeteer. Args: threshold: number of defections after which it will switch behavior."""
self._threshold = threshold
... | the_stack_v2_python_sparse | meltingpot/python/utils/bots/puppeteer_functions.py | classicvalues/meltingpot | train | 0 |
624cda2a86d315ead7c117e1cf9798ac677a0311 | [
"if len(s) == 0:\n return 0\nStact = [-1]\nmaxLens = 0\nfor i, ch in enumerate(s):\n if ch == '(':\n Stact.append(i)\n else:\n Stact.pop()\n if len(Stact) == 0:\n Stact.append(i)\n else:\n maxLens = max(maxLens, i - Stact[-1])\nreturn maxLens",
"left, rig... | <|body_start_0|>
if len(s) == 0:
return 0
Stact = [-1]
maxLens = 0
for i, ch in enumerate(s):
if ch == '(':
Stact.append(i)
else:
Stact.pop()
if len(Stact) == 0:
Stact.append(i)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestValidParentheses(self, s: str) -> int:
"""使用堆栈，堆栈存下标 :param s: :return:"""
<|body_0|>
def longestValidParentheses2(self, s: str) -> int:
"""两遍遍历 :param s: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(s) == 0:
... | stack_v2_sparse_classes_36k_train_018224 | 1,896 | no_license | [
{
"docstring": "使用堆栈，堆栈存下标 :param s: :return:",
"name": "longestValidParentheses",
"signature": "def longestValidParentheses(self, s: str) -> int"
},
{
"docstring": "两遍遍历 :param s: :return:",
"name": "longestValidParentheses2",
"signature": "def longestValidParentheses2(self, s: str) -> ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses(self, s: str) -> int: 使用堆栈，堆栈存下标 :param s: :return:
- def longestValidParentheses2(self, s: str) -> int: 两遍遍历 :param s: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses(self, s: str) -> int: 使用堆栈，堆栈存下标 :param s: :return:
- def longestValidParentheses2(self, s: str) -> int: 两遍遍历 :param s: :return:
<|skeleton|>
class S... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class Solution:
def longestValidParentheses(self, s: str) -> int:
"""使用堆栈，堆栈存下标 :param s: :return:"""
<|body_0|>
def longestValidParentheses2(self, s: str) -> int:
"""两遍遍历 :param s: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestValidParentheses(self, s: str) -> int:
"""使用堆栈，堆栈存下标 :param s: :return:"""
if len(s) == 0:
return 0
Stact = [-1]
maxLens = 0
for i, ch in enumerate(s):
if ch == '(':
Stact.append(i)
else:
... | the_stack_v2_python_sparse | 华为题库/最长有效括号.py | 2226171237/Algorithmpractice | train | 0 | |
639a624c10f5b44ed90385709220e66cbb3ba471 | [
"self.__threads = threads\nself.__count = 0\nself.__main = _thread.allocate_lock()\nself.__exit = _thread.allocate_lock()\nself.__exit.acquire()",
"self.__main.acquire()\nself.__count += 1\nif self.__count < self.__threads:\n self.__main.release()\nelse:\n self.__exit.release()\nself.__exit.acquire()\nself.... | <|body_start_0|>
self.__threads = threads
self.__count = 0
self.__main = _thread.allocate_lock()
self.__exit = _thread.allocate_lock()
self.__exit.acquire()
<|end_body_0|>
<|body_start_1|>
self.__main.acquire()
self.__count += 1
if self.__count < self.__t... | Sync(threads) -> Sync | Sync | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sync:
"""Sync(threads) -> Sync"""
def __init__(self, threads):
"""Initialize the Sync object."""
<|body_0|>
def sync(self):
"""Automatically syncronize calling threads."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.__threads = threads
... | stack_v2_sparse_classes_36k_train_018225 | 1,230 | no_license | [
{
"docstring": "Initialize the Sync object.",
"name": "__init__",
"signature": "def __init__(self, threads)"
},
{
"docstring": "Automatically syncronize calling threads.",
"name": "sync",
"signature": "def sync(self)"
}
] | 2 | null | Implement the Python class `Sync` described below.
Class description:
Sync(threads) -> Sync
Method signatures and docstrings:
- def __init__(self, threads): Initialize the Sync object.
- def sync(self): Automatically syncronize calling threads. | Implement the Python class `Sync` described below.
Class description:
Sync(threads) -> Sync
Method signatures and docstrings:
- def __init__(self, threads): Initialize the Sync object.
- def sync(self): Automatically syncronize calling threads.
<|skeleton|>
class Sync:
"""Sync(threads) -> Sync"""
def __init... | 45837fc39f99b5f7f69919ed2f6732e6b7bec936 | <|skeleton|>
class Sync:
"""Sync(threads) -> Sync"""
def __init__(self, threads):
"""Initialize the Sync object."""
<|body_0|>
def sync(self):
"""Automatically syncronize calling threads."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sync:
"""Sync(threads) -> Sync"""
def __init__(self, threads):
"""Initialize the Sync object."""
self.__threads = threads
self.__count = 0
self.__main = _thread.allocate_lock()
self.__exit = _thread.allocate_lock()
self.__exit.acquire()
def sync(self):... | the_stack_v2_python_sparse | Python 2.X/ZERO/Experiments/Client-Server Demo/Working Example/prog/sync.py | jacobbridges/my-chaos | train | 0 |
e13723b025110410024b86c27a0ddea9d70e377e | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn MembersAddedEventMessageDetail()",
"from .event_message_detail import EventMessageDetail\nfrom .identity_set import IdentitySet\nfrom .teamwork_user_identity import TeamworkUserIdentity\nfrom .event_message_detail import EventMessageDe... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return MembersAddedEventMessageDetail()
<|end_body_0|>
<|body_start_1|>
from .event_message_detail import EventMessageDetail
from .identity_set import IdentitySet
from .teamwork_user_id... | MembersAddedEventMessageDetail | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MembersAddedEventMessageDetail:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MembersAddedEventMessageDetail:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator v... | stack_v2_sparse_classes_36k_train_018226 | 3,235 | 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: MembersAddedEventMessageDetail",
"name": "create_from_discriminator_value",
"signature": "def create_from_di... | 3 | null | Implement the Python class `MembersAddedEventMessageDetail` described below.
Class description:
Implement the MembersAddedEventMessageDetail class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MembersAddedEventMessageDetail: Creates a new instance of... | Implement the Python class `MembersAddedEventMessageDetail` described below.
Class description:
Implement the MembersAddedEventMessageDetail class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MembersAddedEventMessageDetail: Creates a new instance of... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class MembersAddedEventMessageDetail:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MembersAddedEventMessageDetail:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MembersAddedEventMessageDetail:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MembersAddedEventMessageDetail:
"""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 creat... | the_stack_v2_python_sparse | msgraph/generated/models/members_added_event_message_detail.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
9d014f4ae52e42e9dcb2ad26031379c8d2bd7d44 | [
"super(ConvNetFeatureExtractor, self).__init__()\nself.feature_layer = feature_layer\nself.pretrained_params = pretrained_params\nself.pretrained_meta = pretrained_meta\nself.center_only = center_only\nself.convnet = DecafNet(self.pretrained_params, self.pretrained_meta)",
"img = self.convnet.oversample(img, cent... | <|body_start_0|>
super(ConvNetFeatureExtractor, self).__init__()
self.feature_layer = feature_layer
self.pretrained_params = pretrained_params
self.pretrained_meta = pretrained_meta
self.center_only = center_only
self.convnet = DecafNet(self.pretrained_params, self.pretra... | ConvNetFeatureExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvNetFeatureExtractor:
def __init__(self, feature_layer='fc7_cudanet_out', pretrained_params='imagenet.decafnet.epoch90', pretrained_meta='imagenet.decafnet.meta', center_only=True):
""":param feature_layer: The ConvNet layer that's used for feature extraction. Defaults to `fc7_cudanet... | stack_v2_sparse_classes_36k_train_018227 | 3,051 | no_license | [
{
"docstring": ":param feature_layer: The ConvNet layer that's used for feature extraction. Defaults to `fc7_cudanet_out`. A description of all available layers for the ImageNet-1k-pretrained ConvNet is found in the DeCAF wiki. They are: - `pool5_cudanet_out` - `fc6_cudanet_out` - `fc6_neuron_cudanet_out` - `fc... | 2 | stack_v2_sparse_classes_30k_train_004977 | Implement the Python class `ConvNetFeatureExtractor` described below.
Class description:
Implement the ConvNetFeatureExtractor class.
Method signatures and docstrings:
- def __init__(self, feature_layer='fc7_cudanet_out', pretrained_params='imagenet.decafnet.epoch90', pretrained_meta='imagenet.decafnet.meta', center_... | Implement the Python class `ConvNetFeatureExtractor` described below.
Class description:
Implement the ConvNetFeatureExtractor class.
Method signatures and docstrings:
- def __init__(self, feature_layer='fc7_cudanet_out', pretrained_params='imagenet.decafnet.epoch90', pretrained_meta='imagenet.decafnet.meta', center_... | 6fc9c749194f8a348f773aa989183ab9c751b008 | <|skeleton|>
class ConvNetFeatureExtractor:
def __init__(self, feature_layer='fc7_cudanet_out', pretrained_params='imagenet.decafnet.epoch90', pretrained_meta='imagenet.decafnet.meta', center_only=True):
""":param feature_layer: The ConvNet layer that's used for feature extraction. Defaults to `fc7_cudanet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvNetFeatureExtractor:
def __init__(self, feature_layer='fc7_cudanet_out', pretrained_params='imagenet.decafnet.epoch90', pretrained_meta='imagenet.decafnet.meta', center_only=True):
""":param feature_layer: The ConvNet layer that's used for feature extraction. Defaults to `fc7_cudanet_out`. A descr... | the_stack_v2_python_sparse | src/feature_extractors/conv_net_feature_extractor.py | ktisha/object_class_recognition | train | 0 | |
a19770a27e469c5c481825c3e653fcffe2b28bab | [
"def traverse(node, cur_sum):\n if not node:\n return\n if not node.left and (not node.right):\n if cur_sum - node.val == 0:\n self.bool = True\n return\n if node.left:\n traverse(node.left, cur_sum - node.val)\n if node.right:\n traverse(node.right, cur_sum... | <|body_start_0|>
def traverse(node, cur_sum):
if not node:
return
if not node.left and (not node.right):
if cur_sum - node.val == 0:
self.bool = True
return
if node.left:
traverse(node.left, c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasPathSum(self, root: TreeNode, targetSum: int) -> bool:
"""Purpose: Returns a boolean indicating whether a binary tree has a root-to-leaf path such that all values along the path add to `targetSum`."""
<|body_0|>
def pathSumII(self, root, targetSum):
... | stack_v2_sparse_classes_36k_train_018228 | 3,110 | no_license | [
{
"docstring": "Purpose: Returns a boolean indicating whether a binary tree has a root-to-leaf path such that all values along the path add to `targetSum`.",
"name": "hasPathSum",
"signature": "def hasPathSum(self, root: TreeNode, targetSum: int) -> bool"
},
{
"docstring": "Purpose: Returns a li... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum(self, root: TreeNode, targetSum: int) -> bool: Purpose: Returns a boolean indicating whether a binary tree has a root-to-leaf path such that all values along the p... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum(self, root: TreeNode, targetSum: int) -> bool: Purpose: Returns a boolean indicating whether a binary tree has a root-to-leaf path such that all values along the p... | 95a86cbbca28d0c0f6d72d28a2f1cb5a86327934 | <|skeleton|>
class Solution:
def hasPathSum(self, root: TreeNode, targetSum: int) -> bool:
"""Purpose: Returns a boolean indicating whether a binary tree has a root-to-leaf path such that all values along the path add to `targetSum`."""
<|body_0|>
def pathSumII(self, root, targetSum):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hasPathSum(self, root: TreeNode, targetSum: int) -> bool:
"""Purpose: Returns a boolean indicating whether a binary tree has a root-to-leaf path such that all values along the path add to `targetSum`."""
def traverse(node, cur_sum):
if not node:
return... | the_stack_v2_python_sparse | pathSumMethods.py | tashakim/puzzles_python | train | 8 | |
205a72bd295953f65bf374c61a3efa7c02c839ec | [
"super().__init__()\nself.dim = dim\nself.dim_out = dim_out\nself.norm1 = norm_layer(dim)\nkernel_skip = [s + 1 if s > 1 else s for s in stride_q]\nstride_skip = stride_q\npadding_skip = [int(skip // 2) for skip in kernel_skip]\nself.attn = MultiScaleAttention(dim, num_heads=num_heads, qkv_bias=qkv_bias, dropout_ra... | <|body_start_0|>
super().__init__()
self.dim = dim
self.dim_out = dim_out
self.norm1 = norm_layer(dim)
kernel_skip = [s + 1 if s > 1 else s for s in stride_q]
stride_skip = stride_q
padding_skip = [int(skip // 2) for skip in kernel_skip]
self.attn = MultiS... | Implementation of a multiscale vision transformer block. Each block contains a multiscale attention layer and a Mlp layer. :: Input |-------------------+ ↓ | Norm | ↓ | MultiScaleAttention Pool ↓ | DropPath | ↓ | Summation ←-------------+ | |-------------------+ ↓ | Norm | ↓ | Mlp Proj ↓ | DropPath | ↓ | Summation ←---... | MultiScaleBlock | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiScaleBlock:
"""Implementation of a multiscale vision transformer block. Each block contains a multiscale attention layer and a Mlp layer. :: Input |-------------------+ ↓ | Norm | ↓ | MultiScaleAttention Pool ↓ | DropPath | ↓ | Summation ←-------------+ | |-------------------+ ↓ | Norm | ↓ |... | stack_v2_sparse_classes_36k_train_018229 | 21,342 | permissive | [
{
"docstring": "Args: dim (int): Input feature dimension. dim_out (int): Output feature dimension. num_heads (int): Number of heads in the attention layer. mlp_ratio (float): Mlp ratio which controls the feature dimension in the hidden layer of the Mlp block. qkv_bias (bool): If set to False, the qkv layer will... | 2 | stack_v2_sparse_classes_30k_train_016143 | Implement the Python class `MultiScaleBlock` described below.
Class description:
Implementation of a multiscale vision transformer block. Each block contains a multiscale attention layer and a Mlp layer. :: Input |-------------------+ ↓ | Norm | ↓ | MultiScaleAttention Pool ↓ | DropPath | ↓ | Summation ←-------------+... | Implement the Python class `MultiScaleBlock` described below.
Class description:
Implementation of a multiscale vision transformer block. Each block contains a multiscale attention layer and a Mlp layer. :: Input |-------------------+ ↓ | Norm | ↓ | MultiScaleAttention Pool ↓ | DropPath | ↓ | Summation ←-------------+... | 16f2abf2f8aa174915316007622bbb260215dee8 | <|skeleton|>
class MultiScaleBlock:
"""Implementation of a multiscale vision transformer block. Each block contains a multiscale attention layer and a Mlp layer. :: Input |-------------------+ ↓ | Norm | ↓ | MultiScaleAttention Pool ↓ | DropPath | ↓ | Summation ←-------------+ | |-------------------+ ↓ | Norm | ↓ |... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiScaleBlock:
"""Implementation of a multiscale vision transformer block. Each block contains a multiscale attention layer and a Mlp layer. :: Input |-------------------+ ↓ | Norm | ↓ | MultiScaleAttention Pool ↓ | DropPath | ↓ | Summation ←-------------+ | |-------------------+ ↓ | Norm | ↓ | Mlp Proj ↓ |... | the_stack_v2_python_sparse | pytorchvideo/layers/attention.py | xchani/pytorchvideo | train | 0 |
5831972a5794dcf8aa9e0e00aea64dc737110f5c | [
"full_path = self._DISCOVERY_API_PATH_PREFIX + path\nheaders = {'Content-type': 'application/json'}\nconnection = httplib.HTTPSConnection(self._DISCOVERY_PROXY_HOST)\ntry:\n connection.request('POST', full_path, body, headers)\n response = connection.getresponse()\n response_body = response.read()\n if ... | <|body_start_0|>
full_path = self._DISCOVERY_API_PATH_PREFIX + path
headers = {'Content-type': 'application/json'}
connection = httplib.HTTPSConnection(self._DISCOVERY_PROXY_HOST)
try:
connection.request('POST', full_path, body, headers)
response = connection.getr... | Proxies discovery service requests to a known cloud endpoint. | DiscoveryApiProxy | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiscoveryApiProxy:
"""Proxies discovery service requests to a known cloud endpoint."""
def _dispatch_request(self, path, body):
"""Proxies GET request to discovery service API. Args: path: A string containing the URL path relative to discovery service. body: A string containing the H... | stack_v2_sparse_classes_36k_train_018230 | 3,900 | permissive | [
{
"docstring": "Proxies GET request to discovery service API. Args: path: A string containing the URL path relative to discovery service. body: A string containing the HTTP POST request body. Returns: HTTP response body or None if it failed.",
"name": "_dispatch_request",
"signature": "def _dispatch_req... | 4 | null | Implement the Python class `DiscoveryApiProxy` described below.
Class description:
Proxies discovery service requests to a known cloud endpoint.
Method signatures and docstrings:
- def _dispatch_request(self, path, body): Proxies GET request to discovery service API. Args: path: A string containing the URL path relat... | Implement the Python class `DiscoveryApiProxy` described below.
Class description:
Proxies discovery service requests to a known cloud endpoint.
Method signatures and docstrings:
- def _dispatch_request(self, path, body): Proxies GET request to discovery service API. Args: path: A string containing the URL path relat... | 53102de187a48ac2cfc241fef54dcbc29c453a8e | <|skeleton|>
class DiscoveryApiProxy:
"""Proxies discovery service requests to a known cloud endpoint."""
def _dispatch_request(self, path, body):
"""Proxies GET request to discovery service API. Args: path: A string containing the URL path relative to discovery service. body: A string containing the H... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiscoveryApiProxy:
"""Proxies discovery service requests to a known cloud endpoint."""
def _dispatch_request(self, path, body):
"""Proxies GET request to discovery service API. Args: path: A string containing the URL path relative to discovery service. body: A string containing the HTTP POST requ... | the_stack_v2_python_sparse | third_party/google-endpoints/endpoints/discovery_api_proxy.py | catapult-project/catapult | train | 2,032 |
8676856f96acc37f8505db7309cc431a5ab3b4b1 | [
"df = pd.read_csv(csv_file, index_col=0)\ndf['ratio'] = df['count'].div(df['count'].shift(1)) - 1\ndf = df.dropna(subset=['ratio'])[['yearpd', 'ratio']]\nprint(df)",
"df_armed = pd.read_csv(csv_shootings_armed, usecols=['race_name', 'armed', 'count'])\ndf_unarmed = pd.read_csv(csv_shootings_unarmed, usecols=['rac... | <|body_start_0|>
df = pd.read_csv(csv_file, index_col=0)
df['ratio'] = df['count'].div(df['count'].shift(1)) - 1
df = df.dropna(subset=['ratio'])[['yearpd', 'ratio']]
print(df)
<|end_body_0|>
<|body_start_1|>
df_armed = pd.read_csv(csv_shootings_armed, usecols=['race_name', 'arm... | MetricEvaluator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricEvaluator:
def m1(self, csv_file):
"""Computes the rate of increase for crime by year input: crimes_trend.csv"""
<|body_0|>
def m2(self, csv_shootings_armed, csv_shootings_unarmed):
"""Computes and compare the ratio of armed/not armed blacks dead with whites in... | stack_v2_sparse_classes_36k_train_018231 | 5,126 | no_license | [
{
"docstring": "Computes the rate of increase for crime by year input: crimes_trend.csv",
"name": "m1",
"signature": "def m1(self, csv_file)"
},
{
"docstring": "Computes and compare the ratio of armed/not armed blacks dead with whites input: armed.csv, unarmed.csv",
"name": "m2",
"signat... | 5 | stack_v2_sparse_classes_30k_train_020335 | Implement the Python class `MetricEvaluator` described below.
Class description:
Implement the MetricEvaluator class.
Method signatures and docstrings:
- def m1(self, csv_file): Computes the rate of increase for crime by year input: crimes_trend.csv
- def m2(self, csv_shootings_armed, csv_shootings_unarmed): Computes... | Implement the Python class `MetricEvaluator` described below.
Class description:
Implement the MetricEvaluator class.
Method signatures and docstrings:
- def m1(self, csv_file): Computes the rate of increase for crime by year input: crimes_trend.csv
- def m2(self, csv_shootings_armed, csv_shootings_unarmed): Computes... | 0f957f56e7df5beffdc6554375def95456841e87 | <|skeleton|>
class MetricEvaluator:
def m1(self, csv_file):
"""Computes the rate of increase for crime by year input: crimes_trend.csv"""
<|body_0|>
def m2(self, csv_shootings_armed, csv_shootings_unarmed):
"""Computes and compare the ratio of armed/not armed blacks dead with whites in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetricEvaluator:
def m1(self, csv_file):
"""Computes the rate of increase for crime by year input: crimes_trend.csv"""
df = pd.read_csv(csv_file, index_col=0)
df['ratio'] = df['count'].div(df['count'].shift(1)) - 1
df = df.dropna(subset=['ratio'])[['yearpd', 'ratio']]
p... | the_stack_v2_python_sparse | metrics.py | domk11/BigDataProjectCrimes | train | 0 | |
9fcf56722eb12d308e917e9dc1fd65371bb3ecfd | [
"self.account_id = account_id\nself.conference_id = conference_id\nself.name = name\nself.recording_id = recording_id\nself.duration = duration\nself.channels = channels\nself.start_time = APIHelper.RFC3339DateTime(start_time) if start_time else None\nself.end_time = APIHelper.RFC3339DateTime(end_time) if end_time ... | <|body_start_0|>
self.account_id = account_id
self.conference_id = conference_id
self.name = name
self.recording_id = recording_id
self.duration = duration
self.channels = channels
self.start_time = APIHelper.RFC3339DateTime(start_time) if start_time else None
... | Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id (string): TODO: type description here. duration (strin... | ConferenceRecordingMetadata | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConferenceRecordingMetadata:
"""Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id... | stack_v2_sparse_classes_36k_train_018232 | 4,419 | permissive | [
{
"docstring": "Constructor for the ConferenceRecordingMetadata class",
"name": "__init__",
"signature": "def __init__(self, account_id=None, conference_id=None, name=None, recording_id=None, duration=None, channels=None, start_time=None, end_time=None, file_format=None, status=None, media_url=None)"
... | 2 | stack_v2_sparse_classes_30k_train_004916 | Implement the Python class `ConferenceRecordingMetadata` described below.
Class description:
Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TO... | Implement the Python class `ConferenceRecordingMetadata` described below.
Class description:
Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TO... | 447df3cc8cb7acaf3361d842630c432a9c31ce6e | <|skeleton|>
class ConferenceRecordingMetadata:
"""Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConferenceRecordingMetadata:
"""Implementation of the 'ConferenceRecordingMetadata' model. TODO: type model description here. Attributes: account_id (string): TODO: type description here. conference_id (string): TODO: type description here. name (string): TODO: type description here. recording_id (string): TO... | the_stack_v2_python_sparse | bandwidth/voice/models/conference_recording_metadata.py | Bandwidth/python-sdk | train | 10 |
2c7ce517e2e7c10e7e1df4569b9ae5020580c498 | [
"factor_collection = DB_CONN[factor]\nfactor_cursor = factor_collection.find({'code': code, 'date': {'$gte': begin_date, '$lte': end_date}}, sort=[('date', ASCENDING)])\nfactor_df = DataFrame([{'date': x['date'], factor: x[factor], 'code': x['code']} for x in factor_cursor])\nreturn factor_df",
"factor_collection... | <|body_start_0|>
factor_collection = DB_CONN[factor]
factor_cursor = factor_collection.find({'code': code, 'date': {'$gte': begin_date, '$lte': end_date}}, sort=[('date', ASCENDING)])
factor_df = DataFrame([{'date': x['date'], factor: x[factor], 'code': x['code']} for x in factor_cursor])
... | FactorModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FactorModule:
def get_single_stock_factors(self, code, factor, begin_date, end_date):
"""获取某只股票的某个因子在一段时间内的值 :param code: 股票代码 :param factor: 因子名称 :param begin_date: 开始日期 :param end_date: 结束日期 :return: DataFrame(columns=['code',factor, 'date'])"""
<|body_0|>
def get_single_d... | stack_v2_sparse_classes_36k_train_018233 | 1,605 | no_license | [
{
"docstring": "获取某只股票的某个因子在一段时间内的值 :param code: 股票代码 :param factor: 因子名称 :param begin_date: 开始日期 :param end_date: 结束日期 :return: DataFrame(columns=['code',factor, 'date'])",
"name": "get_single_stock_factors",
"signature": "def get_single_stock_factors(self, code, factor, begin_date, end_date)"
},
{... | 2 | stack_v2_sparse_classes_30k_train_000278 | Implement the Python class `FactorModule` described below.
Class description:
Implement the FactorModule class.
Method signatures and docstrings:
- def get_single_stock_factors(self, code, factor, begin_date, end_date): 获取某只股票的某个因子在一段时间内的值 :param code: 股票代码 :param factor: 因子名称 :param begin_date: 开始日期 :param end_date:... | Implement the Python class `FactorModule` described below.
Class description:
Implement the FactorModule class.
Method signatures and docstrings:
- def get_single_stock_factors(self, code, factor, begin_date, end_date): 获取某只股票的某个因子在一段时间内的值 :param code: 股票代码 :param factor: 因子名称 :param begin_date: 开始日期 :param end_date:... | d93a55fda84052068ccd5c483f67eec6ffbec3f4 | <|skeleton|>
class FactorModule:
def get_single_stock_factors(self, code, factor, begin_date, end_date):
"""获取某只股票的某个因子在一段时间内的值 :param code: 股票代码 :param factor: 因子名称 :param begin_date: 开始日期 :param end_date: 结束日期 :return: DataFrame(columns=['code',factor, 'date'])"""
<|body_0|>
def get_single_d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FactorModule:
def get_single_stock_factors(self, code, factor, begin_date, end_date):
"""获取某只股票的某个因子在一段时间内的值 :param code: 股票代码 :param factor: 因子名称 :param begin_date: 开始日期 :param end_date: 结束日期 :return: DataFrame(columns=['code',factor, 'date'])"""
factor_collection = DB_CONN[factor]
fa... | the_stack_v2_python_sparse | xiaoxiang/06.第六课：交易决策子系统的实现—信号计算、仓位管理、风险管理/第6课代码/factor/factor_module.py | webclinic017/quantBigA | train | 0 | |
2c5b3255f2bc9fa3d96f5af3b5885f817ee45e34 | [
"if minimum >= maximum:\n raise Error(\"Can't normalize to empty range: \" + f'[{(self.minimum, self.maximum)}]')\nself.minimum = tf.constant(minimum, dtype=tf.float32)\nself.maximum = tf.constant(maximum, dtype=tf.float32)\nsuper().__init__()",
"length = self.maximum - self.minimum\nrange_too_large = tf.math.... | <|body_start_0|>
if minimum >= maximum:
raise Error("Can't normalize to empty range: " + f'[{(self.minimum, self.maximum)}]')
self.minimum = tf.constant(minimum, dtype=tf.float32)
self.maximum = tf.constant(maximum, dtype=tf.float32)
super().__init__()
<|end_body_0|>
<|body_... | Normalize a number in a given range to the range -1, 1. | NormalizeRange | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NormalizeRange:
"""Normalize a number in a given range to the range -1, 1."""
def __init__(self, minimum: float, maximum: float):
"""Create a NormalizeRange layer with the indicated range. Args: minimum: A float scalar representing the lower bound on the range. maximum: A float scala... | stack_v2_sparse_classes_36k_train_018234 | 14,886 | permissive | [
{
"docstring": "Create a NormalizeRange layer with the indicated range. Args: minimum: A float scalar representing the lower bound on the range. maximum: A float scalar representing the upper bound on the range. Raises: Error: If an empty range is specified.",
"name": "__init__",
"signature": "def __ini... | 2 | stack_v2_sparse_classes_30k_train_002697 | Implement the Python class `NormalizeRange` described below.
Class description:
Normalize a number in a given range to the range -1, 1.
Method signatures and docstrings:
- def __init__(self, minimum: float, maximum: float): Create a NormalizeRange layer with the indicated range. Args: minimum: A float scalar represen... | Implement the Python class `NormalizeRange` described below.
Class description:
Normalize a number in a given range to the range -1, 1.
Method signatures and docstrings:
- def __init__(self, minimum: float, maximum: float): Create a NormalizeRange layer with the indicated range. Args: minimum: A float scalar represen... | 26ab377a6853463b2efce40970e54d44b91e79ca | <|skeleton|>
class NormalizeRange:
"""Normalize a number in a given range to the range -1, 1."""
def __init__(self, minimum: float, maximum: float):
"""Create a NormalizeRange layer with the indicated range. Args: minimum: A float scalar representing the lower bound on the range. maximum: A float scala... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NormalizeRange:
"""Normalize a number in a given range to the range -1, 1."""
def __init__(self, minimum: float, maximum: float):
"""Create a NormalizeRange layer with the indicated range. Args: minimum: A float scalar representing the lower bound on the range. maximum: A float scalar representin... | the_stack_v2_python_sparse | service/learner/brains/layers.py | stewartmiles/falken | train | 1 |
c891ea6c60d4b38eeb7717a4f9bb87c812324201 | [
"c = 1\nself.weight = weight\nself.age = age\nself.color = color\nc = 1",
"c = 1\nres = super().__new__(cls)\nc = 1\nreturn res"
] | <|body_start_0|>
c = 1
self.weight = weight
self.age = age
self.color = color
c = 1
<|end_body_0|>
<|body_start_1|>
c = 1
res = super().__new__(cls)
c = 1
return res
<|end_body_1|>
| Matryoshka | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Matryoshka:
def __init__(self, weight, age, color):
"""Раскрашивает нашу болванку"""
<|body_0|>
def __new__(cls, *args, **kwargs):
"""Изготавливает пустую болванку"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
c = 1
self.weight = weight
... | stack_v2_sparse_classes_36k_train_018235 | 8,031 | no_license | [
{
"docstring": "Раскрашивает нашу болванку",
"name": "__init__",
"signature": "def __init__(self, weight, age, color)"
},
{
"docstring": "Изготавливает пустую болванку",
"name": "__new__",
"signature": "def __new__(cls, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002690 | Implement the Python class `Matryoshka` described below.
Class description:
Implement the Matryoshka class.
Method signatures and docstrings:
- def __init__(self, weight, age, color): Раскрашивает нашу болванку
- def __new__(cls, *args, **kwargs): Изготавливает пустую болванку | Implement the Python class `Matryoshka` described below.
Class description:
Implement the Matryoshka class.
Method signatures and docstrings:
- def __init__(self, weight, age, color): Раскрашивает нашу болванку
- def __new__(cls, *args, **kwargs): Изготавливает пустую болванку
<|skeleton|>
class Matryoshka:
def... | b3c1bc09a35d706d84a6ae67a484c7ae359cede8 | <|skeleton|>
class Matryoshka:
def __init__(self, weight, age, color):
"""Раскрашивает нашу болванку"""
<|body_0|>
def __new__(cls, *args, **kwargs):
"""Изготавливает пустую болванку"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Matryoshka:
def __init__(self, weight, age, color):
"""Раскрашивает нашу болванку"""
c = 1
self.weight = weight
self.age = age
self.color = color
c = 1
def __new__(cls, *args, **kwargs):
"""Изготавливает пустую болванку"""
c = 1
res ... | the_stack_v2_python_sparse | dasha_folder/lesson_17.py | Totoro2205/for_my_shiny_students | train | 0 | |
6e61fc1cae406dabd9bba67eaa6a53f1565e2b51 | [
"if amount == 0:\n return 1\nif not coins:\n return 0\nif amount < coins[0]:\n return 0\nglobal c\nc = 0\ncoins.sort()\n\ndef helper(i, count):\n global c\n if count == amount:\n c += 1\n return\n for j in range(i, len(coins)):\n if count + coins[j] > amount:\n brea... | <|body_start_0|>
if amount == 0:
return 1
if not coins:
return 0
if amount < coins[0]:
return 0
global c
c = 0
coins.sort()
def helper(i, count):
global c
if count == amount:
c += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def change(self, amount, coins):
"""回溯法,使用模板，排序解决重复使用问题 超出时间限制 :type amount: int :type coins: List[int] :rtype: int"""
<|body_0|>
def change2(self, amount, coins):
"""动态规划，完全背包问题 :param amount: :param coins: :return:"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_018236 | 2,253 | no_license | [
{
"docstring": "回溯法,使用模板，排序解决重复使用问题 超出时间限制 :type amount: int :type coins: List[int] :rtype: int",
"name": "change",
"signature": "def change(self, amount, coins)"
},
{
"docstring": "动态规划，完全背包问题 :param amount: :param coins: :return:",
"name": "change2",
"signature": "def change2(self, amo... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): 回溯法,使用模板，排序解决重复使用问题 超出时间限制 :type amount: int :type coins: List[int] :rtype: int
- def change2(self, amount, coins): 动态规划，完全背包问题 :param amount: :p... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): 回溯法,使用模板，排序解决重复使用问题 超出时间限制 :type amount: int :type coins: List[int] :rtype: int
- def change2(self, amount, coins): 动态规划，完全背包问题 :param amount: :p... | 95dddb78bccd169d9d219a473627361fe739ab5e | <|skeleton|>
class Solution:
def change(self, amount, coins):
"""回溯法,使用模板，排序解决重复使用问题 超出时间限制 :type amount: int :type coins: List[int] :rtype: int"""
<|body_0|>
def change2(self, amount, coins):
"""动态规划，完全背包问题 :param amount: :param coins: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def change(self, amount, coins):
"""回溯法,使用模板，排序解决重复使用问题 超出时间限制 :type amount: int :type coins: List[int] :rtype: int"""
if amount == 0:
return 1
if not coins:
return 0
if amount < coins[0]:
return 0
global c
c = 0
... | the_stack_v2_python_sparse | DrasticPlan/coinChange2.py | Philex5/codingPractice | train | 0 | |
e4791412da0cc3439476c78f0b8df7db19e05957 | [
"if self.instance.status != FinancialAidStatus.PENDING_DOCS:\n raise ValidationError('Cannot indicate documents sent for an application that is not pending documents')\nreturn data",
"self.instance.status = FinancialAidStatus.DOCS_SENT\nself.instance.date_documents_sent = self.validated_data['date_documents_se... | <|body_start_0|>
if self.instance.status != FinancialAidStatus.PENDING_DOCS:
raise ValidationError('Cannot indicate documents sent for an application that is not pending documents')
return data
<|end_body_0|>
<|body_start_1|>
self.instance.status = FinancialAidStatus.DOCS_SENT
... | Serializer for indicating financial documents have been sent | FinancialAidSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FinancialAidSerializer:
"""Serializer for indicating financial documents have been sent"""
def validate(self, data):
"""Validate method for this serializer"""
<|body_0|>
def save(self):
"""Save method for this serializer"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_018237 | 6,670 | no_license | [
{
"docstring": "Validate method for this serializer",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "Save method for this serializer",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002715 | Implement the Python class `FinancialAidSerializer` described below.
Class description:
Serializer for indicating financial documents have been sent
Method signatures and docstrings:
- def validate(self, data): Validate method for this serializer
- def save(self): Save method for this serializer | Implement the Python class `FinancialAidSerializer` described below.
Class description:
Serializer for indicating financial documents have been sent
Method signatures and docstrings:
- def validate(self, data): Validate method for this serializer
- def save(self): Save method for this serializer
<|skeleton|>
class F... | 3c166bc52dfe8d7aa04f922134f4f6deeff49eb6 | <|skeleton|>
class FinancialAidSerializer:
"""Serializer for indicating financial documents have been sent"""
def validate(self, data):
"""Validate method for this serializer"""
<|body_0|>
def save(self):
"""Save method for this serializer"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FinancialAidSerializer:
"""Serializer for indicating financial documents have been sent"""
def validate(self, data):
"""Validate method for this serializer"""
if self.instance.status != FinancialAidStatus.PENDING_DOCS:
raise ValidationError('Cannot indicate documents sent for ... | the_stack_v2_python_sparse | financialaid/serializers.py | avontd2868/micromasters | train | 0 |
e2f915cf1d9ac338204783620731e4efc1bf5f83 | [
"params = request.GET\ncomment_id = params.get('comment_id')\nif comment_id:\n try:\n return Comment.objects.get(pk=comment_id, is_removed=False, is_public=True)\n except Comment.DoesNotExist:\n return rc.NOT_HERE\ntid = params.get('tid')\nct = ContentType.objects.get_by_natural_key('kinger', 't... | <|body_start_0|>
params = request.GET
comment_id = params.get('comment_id')
if comment_id:
try:
return Comment.objects.get(pk=comment_id, is_removed=False, is_public=True)
except Comment.DoesNotExist:
return rc.NOT_HERE
tid = params... | Api for comments resource | CommentHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommentHandler:
"""Api for comments resource"""
def get(self, request):
"""获得某条瓦片的评论详细信息 ``GET`` `comments/show/ <http://192.168.1.222:8080/v1/comments/show>`_ :param tid: 瓦片 id. :param comment_id: 某条评论的 id"""
<|body_0|>
def post(self, request):
"""发布一条评论 ``POST`... | stack_v2_sparse_classes_36k_train_018238 | 5,451 | no_license | [
{
"docstring": "获得某条瓦片的评论详细信息 ``GET`` `comments/show/ <http://192.168.1.222:8080/v1/comments/show>`_ :param tid: 瓦片 id. :param comment_id: 某条评论的 id",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "发布一条评论 ``POST`` `comments/create/ <http://192.168.1.222:8080/v1/comments/c... | 3 | null | Implement the Python class `CommentHandler` described below.
Class description:
Api for comments resource
Method signatures and docstrings:
- def get(self, request): 获得某条瓦片的评论详细信息 ``GET`` `comments/show/ <http://192.168.1.222:8080/v1/comments/show>`_ :param tid: 瓦片 id. :param comment_id: 某条评论的 id
- def post(self, req... | Implement the Python class `CommentHandler` described below.
Class description:
Api for comments resource
Method signatures and docstrings:
- def get(self, request): 获得某条瓦片的评论详细信息 ``GET`` `comments/show/ <http://192.168.1.222:8080/v1/comments/show>`_ :param tid: 瓦片 id. :param comment_id: 某条评论的 id
- def post(self, req... | 1b1fbe4c66df731f63f10c57dee20cb0bb4edb4c | <|skeleton|>
class CommentHandler:
"""Api for comments resource"""
def get(self, request):
"""获得某条瓦片的评论详细信息 ``GET`` `comments/show/ <http://192.168.1.222:8080/v1/comments/show>`_ :param tid: 瓦片 id. :param comment_id: 某条评论的 id"""
<|body_0|>
def post(self, request):
"""发布一条评论 ``POST`... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommentHandler:
"""Api for comments resource"""
def get(self, request):
"""获得某条瓦片的评论详细信息 ``GET`` `comments/show/ <http://192.168.1.222:8080/v1/comments/show>`_ :param tid: 瓦片 id. :param comment_id: 某条评论的 id"""
params = request.GET
comment_id = params.get('comment_id')
if c... | the_stack_v2_python_sparse | apiv2/handlers/comment.py | nuannuanwu/weixiao | train | 1 |
a855b2d8d75c73709dfd91c3ac9d2e49ebe96ff3 | [
"if not nums:\n return []\nres, root = ([], [])\n\ndef backref(nums, res, root):\n if len(root) == len(nums):\n res.append(root[:])\n return\n for i in nums:\n if i in root:\n continue\n root.append(i)\n backref(nums, res, root)\n root.remove(i)\nbackref... | <|body_start_0|>
if not nums:
return []
res, root = ([], [])
def backref(nums, res, root):
if len(root) == len(nums):
res.append(root[:])
return
for i in nums:
if i in root:
continue
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def permute(self, nums: list) -> list:
"""针对没有重复元素的全排列"""
<|body_0|>
def permute_1(self, nums: list) -> list:
"""和上面的思路基本一致"""
<|body_1|>
def permute_2(self, nums: list) -> list:
"""针对有重复元素的全排列"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_018239 | 2,834 | no_license | [
{
"docstring": "针对没有重复元素的全排列",
"name": "permute",
"signature": "def permute(self, nums: list) -> list"
},
{
"docstring": "和上面的思路基本一致",
"name": "permute_1",
"signature": "def permute_1(self, nums: list) -> list"
},
{
"docstring": "针对有重复元素的全排列",
"name": "permute_2",
"signat... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums: list) -> list: 针对没有重复元素的全排列
- def permute_1(self, nums: list) -> list: 和上面的思路基本一致
- def permute_2(self, nums: list) -> list: 针对有重复元素的全排列 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums: list) -> list: 针对没有重复元素的全排列
- def permute_1(self, nums: list) -> list: 和上面的思路基本一致
- def permute_2(self, nums: list) -> list: 针对有重复元素的全排列
<|skeleton|>
cla... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def permute(self, nums: list) -> list:
"""针对没有重复元素的全排列"""
<|body_0|>
def permute_1(self, nums: list) -> list:
"""和上面的思路基本一致"""
<|body_1|>
def permute_2(self, nums: list) -> list:
"""针对有重复元素的全排列"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def permute(self, nums: list) -> list:
"""针对没有重复元素的全排列"""
if not nums:
return []
res, root = ([], [])
def backref(nums, res, root):
if len(root) == len(nums):
res.append(root[:])
return
for i in nums... | the_stack_v2_python_sparse | algorithm/leetcode/backtracking/01-全排列.py | lxconfig/UbuntuCode_bak | train | 0 | |
dfcf93c63081b448b7919b041633701edd045b27 | [
"base_url = 'https://stores.joann.com/{}'\nfor state in STATES:\n state_url = base_url.format(state)\n request = scrapy.Request(state_url, callback=self.parse_state, headers=HEADERS)\n request.meta['state'] = state\n yield request",
"state_url = 'stores.joann.com/{}*'.format(response.meta['state'])\ne... | <|body_start_0|>
base_url = 'https://stores.joann.com/{}'
for state in STATES:
state_url = base_url.format(state)
request = scrapy.Request(state_url, callback=self.parse_state, headers=HEADERS)
request.meta['state'] = state
yield request
<|end_body_0|>
<|... | JoAnnFabricsSpider | [
"MIT",
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JoAnnFabricsSpider:
def start_requests(self):
"""Yields a scrapy.Request object for each state in the USA"""
<|body_0|>
def parse_state(self, response):
"""Yields a scrapy.Request object for each city with a store in the state"""
<|body_1|>
def parse_cit... | stack_v2_sparse_classes_36k_train_018240 | 3,220 | permissive | [
{
"docstring": "Yields a scrapy.Request object for each state in the USA",
"name": "start_requests",
"signature": "def start_requests(self)"
},
{
"docstring": "Yields a scrapy.Request object for each city with a store in the state",
"name": "parse_state",
"signature": "def parse_state(se... | 5 | null | Implement the Python class `JoAnnFabricsSpider` described below.
Class description:
Implement the JoAnnFabricsSpider class.
Method signatures and docstrings:
- def start_requests(self): Yields a scrapy.Request object for each state in the USA
- def parse_state(self, response): Yields a scrapy.Request object for each ... | Implement the Python class `JoAnnFabricsSpider` described below.
Class description:
Implement the JoAnnFabricsSpider class.
Method signatures and docstrings:
- def start_requests(self): Yields a scrapy.Request object for each state in the USA
- def parse_state(self, response): Yields a scrapy.Request object for each ... | ac4d4783572d55c0799fe6aeb5f6c0e72fad55fb | <|skeleton|>
class JoAnnFabricsSpider:
def start_requests(self):
"""Yields a scrapy.Request object for each state in the USA"""
<|body_0|>
def parse_state(self, response):
"""Yields a scrapy.Request object for each city with a store in the state"""
<|body_1|>
def parse_cit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JoAnnFabricsSpider:
def start_requests(self):
"""Yields a scrapy.Request object for each state in the USA"""
base_url = 'https://stores.joann.com/{}'
for state in STATES:
state_url = base_url.format(state)
request = scrapy.Request(state_url, callback=self.parse_... | the_stack_v2_python_sparse | locations/spiders/joann_fabrics.py | thomas536/alltheplaces | train | 0 | |
d7b106f05df134d2fa2d3bfd997385fdd56236ec | [
"requestor = Requestor(local_api_key=api_key)\nurl = cls.class_url()\nwrapped_params = {cls.snakecase_name(): params}\nresponse, api_key = requestor.request(method=RequestMethod.POST, url=url, params=wrapped_params)\nreturn convert_to_easypost_object(response=response, api_key=api_key)",
"if not easypost_id:\n ... | <|body_start_0|>
requestor = Requestor(local_api_key=api_key)
url = cls.class_url()
wrapped_params = {cls.snakecase_name(): params}
response, api_key = requestor.request(method=RequestMethod.POST, url=url, params=wrapped_params)
return convert_to_easypost_object(response=response... | User | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
def create(cls, api_key: Optional[str]=None, **params) -> 'User':
"""Create a child user."""
<|body_0|>
def retrieve(cls, easypost_id: Optional[str]=None, api_key: Optional[str]=None, **params) -> 'User':
"""Retrieve a user."""
<|body_1|>
def retri... | stack_v2_sparse_classes_36k_train_018241 | 3,246 | permissive | [
{
"docstring": "Create a child user.",
"name": "create",
"signature": "def create(cls, api_key: Optional[str]=None, **params) -> 'User'"
},
{
"docstring": "Retrieve a user.",
"name": "retrieve",
"signature": "def retrieve(cls, easypost_id: Optional[str]=None, api_key: Optional[str]=None,... | 6 | stack_v2_sparse_classes_30k_train_011013 | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def create(cls, api_key: Optional[str]=None, **params) -> 'User': Create a child user.
- def retrieve(cls, easypost_id: Optional[str]=None, api_key: Optional[str]=None, **params) -> 'Use... | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def create(cls, api_key: Optional[str]=None, **params) -> 'User': Create a child user.
- def retrieve(cls, easypost_id: Optional[str]=None, api_key: Optional[str]=None, **params) -> 'Use... | c8f7a3f2472ae5fea13a5b596b4618bd55f3be0c | <|skeleton|>
class User:
def create(cls, api_key: Optional[str]=None, **params) -> 'User':
"""Create a child user."""
<|body_0|>
def retrieve(cls, easypost_id: Optional[str]=None, api_key: Optional[str]=None, **params) -> 'User':
"""Retrieve a user."""
<|body_1|>
def retri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class User:
def create(cls, api_key: Optional[str]=None, **params) -> 'User':
"""Create a child user."""
requestor = Requestor(local_api_key=api_key)
url = cls.class_url()
wrapped_params = {cls.snakecase_name(): params}
response, api_key = requestor.request(method=RequestMeth... | the_stack_v2_python_sparse | easypost/user.py | dsanders11/easypost-python | train | 0 | |
518c717cd995a97c9decd1e4cf08f2e9e8c9ad81 | [
"super(AutoEncoderEnvironmentModel, self).__init__()\nself.encoder = encoder\nself.decoder = decoder\nself.observation_shape = observation_shape\nself.num_actions = num_actions\nself.reward_size = reward_size\nself.use_cuda = use_cuda\nself.reward_fc = nn.Linear(self.encoder.get_feature_shape(), self.reward_size)\n... | <|body_start_0|>
super(AutoEncoderEnvironmentModel, self).__init__()
self.encoder = encoder
self.decoder = decoder
self.observation_shape = observation_shape
self.num_actions = num_actions
self.reward_size = reward_size
self.use_cuda = use_cuda
self.reward... | AutoEncoderEnvironmentModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoEncoderEnvironmentModel:
def __init__(self, encoder, decoder, observation_shape, num_actions, reward_size, use_cuda=False):
""":param encoder: :param decoder: :param observation_shape: shape depth x height x width. :param num_actions: number of actions that are available in the envir... | stack_v2_sparse_classes_36k_train_018242 | 2,222 | permissive | [
{
"docstring": ":param encoder: :param decoder: :param observation_shape: shape depth x height x width. :param num_actions: number of actions that are available in the environment. :param reward_size: number of dimensions of the reward vector. Eventhough OpenAI Gym Interface always provides scalar reward functi... | 2 | stack_v2_sparse_classes_30k_train_005403 | Implement the Python class `AutoEncoderEnvironmentModel` described below.
Class description:
Implement the AutoEncoderEnvironmentModel class.
Method signatures and docstrings:
- def __init__(self, encoder, decoder, observation_shape, num_actions, reward_size, use_cuda=False): :param encoder: :param decoder: :param ob... | Implement the Python class `AutoEncoderEnvironmentModel` described below.
Class description:
Implement the AutoEncoderEnvironmentModel class.
Method signatures and docstrings:
- def __init__(self, encoder, decoder, observation_shape, num_actions, reward_size, use_cuda=False): :param encoder: :param decoder: :param ob... | 825c7dacf955a3e2f6c658c0ecb879a0ca036c1a | <|skeleton|>
class AutoEncoderEnvironmentModel:
def __init__(self, encoder, decoder, observation_shape, num_actions, reward_size, use_cuda=False):
""":param encoder: :param decoder: :param observation_shape: shape depth x height x width. :param num_actions: number of actions that are available in the envir... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutoEncoderEnvironmentModel:
def __init__(self, encoder, decoder, observation_shape, num_actions, reward_size, use_cuda=False):
""":param encoder: :param decoder: :param observation_shape: shape depth x height x width. :param num_actions: number of actions that are available in the environment. :param... | the_stack_v2_python_sparse | regym/rl_algorithms/algorithms/I2A/autoencoder_environment_model.py | Near32/Regym | train | 4 | |
3d4e524d94a9dca353e995268487e3bb6a147be5 | [
"compound_list = []\ncompound_entry = info_dict.get('Compounds')\nif compound_entry:\n for family_annotation in compound_entry.split(','):\n compounds = family_annotation.split(':')[-1].split('|')\n for compound in compounds:\n splitted_compound = compound.split('>')\n compoun... | <|body_start_0|>
compound_list = []
compound_entry = info_dict.get('Compounds')
if compound_entry:
for family_annotation in compound_entry.split(','):
compounds = family_annotation.split(':')[-1].split('|')
for compound in compounds:
... | Mixin class to store methods that deals with parsing annotations | AnnotationExtras | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnnotationExtras:
"""Mixin class to store methods that deals with parsing annotations"""
def _add_compounds(self, variant_obj, info_dict):
"""Check if there are any compounds and add them to the variant The compounds that are added should be sorted on rank score"""
<|body_0|>... | stack_v2_sparse_classes_36k_train_018243 | 3,385 | permissive | [
{
"docstring": "Check if there are any compounds and add them to the variant The compounds that are added should be sorted on rank score",
"name": "_add_compounds",
"signature": "def _add_compounds(self, variant_obj, info_dict)"
},
{
"docstring": "Add the cadd score to the variant Args: variant_... | 4 | stack_v2_sparse_classes_30k_train_018890 | Implement the Python class `AnnotationExtras` described below.
Class description:
Mixin class to store methods that deals with parsing annotations
Method signatures and docstrings:
- def _add_compounds(self, variant_obj, info_dict): Check if there are any compounds and add them to the variant The compounds that are a... | Implement the Python class `AnnotationExtras` described below.
Class description:
Mixin class to store methods that deals with parsing annotations
Method signatures and docstrings:
- def _add_compounds(self, variant_obj, info_dict): Check if there are any compounds and add them to the variant The compounds that are a... | 9476f05b416d3a5135d25492cb31411fdf831c58 | <|skeleton|>
class AnnotationExtras:
"""Mixin class to store methods that deals with parsing annotations"""
def _add_compounds(self, variant_obj, info_dict):
"""Check if there are any compounds and add them to the variant The compounds that are added should be sorted on rank score"""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AnnotationExtras:
"""Mixin class to store methods that deals with parsing annotations"""
def _add_compounds(self, variant_obj, info_dict):
"""Check if there are any compounds and add them to the variant The compounds that are added should be sorted on rank score"""
compound_list = []
... | the_stack_v2_python_sparse | puzzle/plugins/vcf/mixins/variant_extras/annotations.py | haoziyeung/puzzle | train | 0 |
c5f5490146234380dcb74910bddcb9bbdd8399c6 | [
"s = math.factorial(n)\nl = 0\nfor i in reversed(str(s)):\n if i == '0':\n l += 1\n else:\n return l\nreturn l",
"if n == 0:\n return 0\nreturn n / 5 + self.trailingZeroes(n - 1) if n % 5 == 0 else self.trailingZeroes(n - 1)",
"if n == 0:\n return 0\nreturn n / 5 + self.trailingZeroes(... | <|body_start_0|>
s = math.factorial(n)
l = 0
for i in reversed(str(s)):
if i == '0':
l += 1
else:
return l
return l
<|end_body_0|>
<|body_start_1|>
if n == 0:
return 0
return n / 5 + self.trailingZeroes(... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _trailingZeroes(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def __trailingZeroes(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def trailingZeroes(self, n):
""":type n: int :rtype: int"""
<|body_2|>
def ___... | stack_v2_sparse_classes_36k_train_018244 | 1,964 | permissive | [
{
"docstring": ":type n: int :rtype: int",
"name": "_trailingZeroes",
"signature": "def _trailingZeroes(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "__trailingZeroes",
"signature": "def __trailingZeroes(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
... | 4 | stack_v2_sparse_classes_30k_train_020011 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _trailingZeroes(self, n): :type n: int :rtype: int
- def __trailingZeroes(self, n): :type n: int :rtype: int
- def trailingZeroes(self, n): :type n: int :rtype: int
- def ___... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _trailingZeroes(self, n): :type n: int :rtype: int
- def __trailingZeroes(self, n): :type n: int :rtype: int
- def trailingZeroes(self, n): :type n: int :rtype: int
- def ___... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _trailingZeroes(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def __trailingZeroes(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def trailingZeroes(self, n):
""":type n: int :rtype: int"""
<|body_2|>
def ___... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _trailingZeroes(self, n):
""":type n: int :rtype: int"""
s = math.factorial(n)
l = 0
for i in reversed(str(s)):
if i == '0':
l += 1
else:
return l
return l
def __trailingZeroes(self, n):
... | the_stack_v2_python_sparse | 172.factorial-trailing-zeroes.py | windard/leeeeee | train | 0 | |
5861cc01c4a420be5f5f333481614ec63a6891f1 | [
"if len(directory_path) > 0:\n if not os.path.isdir(directory_path):\n raise Exception('Path {} for '.format(directory_path) + 'StructDict construction was not a directory.')\n self.update(read(directory_path, file_format=file_format))",
"if type(struct) == dict:\n for key, value in struct.items()... | <|body_start_0|>
if len(directory_path) > 0:
if not os.path.isdir(directory_path):
raise Exception('Path {} for '.format(directory_path) + 'StructDict construction was not a directory.')
self.update(read(directory_path, file_format=file_format))
<|end_body_0|>
<|body_sta... | Specifies the behavior of a StructDict which is abbreviated as struct_dict throughout the code base. The StructDict behaves exactly the same as a Python dictionary where each key is the struct_id and each value is a Structure. | StructDict | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StructDict:
"""Specifies the behavior of a StructDict which is abbreviated as struct_dict throughout the code base. The StructDict behaves exactly the same as a Python dictionary where each key is the struct_id and each value is a Structure."""
def __init__(self, directory_path='', file_form... | stack_v2_sparse_classes_36k_train_018245 | 8,467 | permissive | [
{
"docstring": "Creates StructDict for the optional input directory path.",
"name": "__init__",
"signature": "def __init__(self, directory_path='', file_format='')"
},
{
"docstring": "Behaves as a wrapper to append",
"name": "update",
"signature": "def update(self, struct)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_007704 | Implement the Python class `StructDict` described below.
Class description:
Specifies the behavior of a StructDict which is abbreviated as struct_dict throughout the code base. The StructDict behaves exactly the same as a Python dictionary where each key is the struct_id and each value is a Structure.
Method signatur... | Implement the Python class `StructDict` described below.
Class description:
Specifies the behavior of a StructDict which is abbreviated as struct_dict throughout the code base. The StructDict behaves exactly the same as a Python dictionary where each key is the struct_id and each value is a Structure.
Method signatur... | 142d6f6b4f852b23aa8cfdae1593db207363e30e | <|skeleton|>
class StructDict:
"""Specifies the behavior of a StructDict which is abbreviated as struct_dict throughout the code base. The StructDict behaves exactly the same as a Python dictionary where each key is the struct_id and each value is a Structure."""
def __init__(self, directory_path='', file_form... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StructDict:
"""Specifies the behavior of a StructDict which is abbreviated as struct_dict throughout the code base. The StructDict behaves exactly the same as a Python dictionary where each key is the struct_id and each value is a Structure."""
def __init__(self, directory_path='', file_format=''):
... | the_stack_v2_python_sparse | mcse/core/struct_dict.py | manny405/mcse | train | 6 |
2c56abeb2396749edb0ac6a156b985fc6cf2b939 | [
"form_opts = self.request.GET.copy()\ntry:\n del form_opts['page']\nexcept KeyError:\n pass\nself.form = self.form_class(form_opts or self.form_class.defaults)\nif self.form.is_valid():\n search_opts = self.form.cleaned_data\n if search_opts['content_type'] != 'all':\n if search_opts['content_typ... | <|body_start_0|>
form_opts = self.request.GET.copy()
try:
del form_opts['page']
except KeyError:
pass
self.form = self.form_class(form_opts or self.form_class.defaults)
if self.form.is_valid():
search_opts = self.form.cleaned_data
i... | SearchView | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchView:
def get(self, *args, **kwargs):
"""Process form for :class:`SearchView`."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Retrieve Solr queries for :class:`SearchView` context."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
form_o... | stack_v2_sparse_classes_36k_train_018246 | 37,410 | permissive | [
{
"docstring": "Process form for :class:`SearchView`.",
"name": "get",
"signature": "def get(self, *args, **kwargs)"
},
{
"docstring": "Retrieve Solr queries for :class:`SearchView` context.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019580 | Implement the Python class `SearchView` described below.
Class description:
Implement the SearchView class.
Method signatures and docstrings:
- def get(self, *args, **kwargs): Process form for :class:`SearchView`.
- def get_context_data(self, **kwargs): Retrieve Solr queries for :class:`SearchView` context. | Implement the Python class `SearchView` described below.
Class description:
Implement the SearchView class.
Method signatures and docstrings:
- def get(self, *args, **kwargs): Process form for :class:`SearchView`.
- def get_context_data(self, **kwargs): Retrieve Solr queries for :class:`SearchView` context.
<|skelet... | 6371bb1266d7751af59aeaa3426ef7ac02a1fe17 | <|skeleton|>
class SearchView:
def get(self, *args, **kwargs):
"""Process form for :class:`SearchView`."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Retrieve Solr queries for :class:`SearchView` context."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchView:
def get(self, *args, **kwargs):
"""Process form for :class:`SearchView`."""
form_opts = self.request.GET.copy()
try:
del form_opts['page']
except KeyError:
pass
self.form = self.form_class(form_opts or self.form_class.defaults)
... | the_stack_v2_python_sparse | derrida/books/views.py | Princeton-CDH/derrida-django | train | 13 | |
85068b845fc62bc3ca6b9307072225de0f5d380f | [
"self.w = width\nself.h = height\nself.food = deque(food)\nself.body = deque([(0, 0)])\nself.dirs = {'U': (-1, 0), 'L': (0, -1), 'R': (0, 1), 'D': (1, 0)}\nself.eat = 0",
"x, y = self.body[0]\ndx, dy = self.dirs[direction]\nx += dx\ny += dy\nfx, fy = self.food[0] if self.food else (-1, -1)\nif x == fx and y == fy... | <|body_start_0|>
self.w = width
self.h = height
self.food = deque(food)
self.body = deque([(0, 0)])
self.dirs = {'U': (-1, 0), 'L': (0, -1), 'R': (0, 1), 'D': (1, 0)}
self.eat = 0
<|end_body_0|>
<|body_start_1|>
x, y = self.body[0]
dx, dy = self.dirs[dire... | SnakeGame | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k_train_018247 | 2,043 | permissive | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | 353 Design Snake Game.py | Aminaba123/LeetCode | train | 1 | |
3f2fc192072a292440709ab2683b38c607d4c722 | [
"assert fanouts, 'fanouts must be specified'\nconfig = dict(fanouts=fanouts)\nconfig.update(kwargs)\nsuper().__init__(config=config)\nself.fanouts = fanouts\nself.fanouts_list = get_fanouts_list(fanouts)\nself.fanouts_dim = sum(self.fanouts_list)\nself.fanouts_indices = get_fanouts_indices(fanouts)\nself.sort_indic... | <|body_start_0|>
assert fanouts, 'fanouts must be specified'
config = dict(fanouts=fanouts)
config.update(kwargs)
super().__init__(config=config)
self.fanouts = fanouts
self.fanouts_list = get_fanouts_list(fanouts)
self.fanouts_dim = sum(self.fanouts_list)
... | \\brief transform multi hops to relation graph \\details a relation graph is a dict: \\code{.py} dict( relation_indices=tensor, relation_weight=tensor, target_indices=tensor, ) \\endcode relation_indices is a [2,E] int tensor, E is number of edges,\\n indices of relation/edge of graph relation_weight is a [E,1] float t... | RelationTransform | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelationTransform:
"""\\brief transform multi hops to relation graph \\details a relation graph is a dict: \\code{.py} dict( relation_indices=tensor, relation_weight=tensor, target_indices=tensor, ) \\endcode relation_indices is a [2,E] int tensor, E is number of edges,\\n indices of relation/edg... | stack_v2_sparse_classes_36k_train_018248 | 4,420 | permissive | [
{
"docstring": "\\\\param fanouts number of multi hop \\\\param sort_indices sort relation indices",
"name": "__init__",
"signature": "def __init__(self, fanouts: list, sort_indices: bool=False, **kwargs)"
},
{
"docstring": "\\\\param inputs list or tuple or \\\\n dict(indices=tensor, edge_weigh... | 2 | null | Implement the Python class `RelationTransform` described below.
Class description:
\\brief transform multi hops to relation graph \\details a relation graph is a dict: \\code{.py} dict( relation_indices=tensor, relation_weight=tensor, target_indices=tensor, ) \\endcode relation_indices is a [2,E] int tensor, E is numb... | Implement the Python class `RelationTransform` described below.
Class description:
\\brief transform multi hops to relation graph \\details a relation graph is a dict: \\code{.py} dict( relation_indices=tensor, relation_weight=tensor, target_indices=tensor, ) \\endcode relation_indices is a [2,E] int tensor, E is numb... | 48099ec3f0331196c6812208ceb080ba618a588b | <|skeleton|>
class RelationTransform:
"""\\brief transform multi hops to relation graph \\details a relation graph is a dict: \\code{.py} dict( relation_indices=tensor, relation_weight=tensor, target_indices=tensor, ) \\endcode relation_indices is a [2,E] int tensor, E is number of edges,\\n indices of relation/edg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelationTransform:
"""\\brief transform multi hops to relation graph \\details a relation graph is a dict: \\code{.py} dict( relation_indices=tensor, relation_weight=tensor, target_indices=tensor, ) \\endcode relation_indices is a [2,E] int tensor, E is number of edges,\\n indices of relation/edge of graph re... | the_stack_v2_python_sparse | galileo/framework/pytorch/python/transforms/relation.py | 2012fang1/galileo | train | 0 |
76b7d00085e4188bb4ae21443fea4e2d3d10f90a | [
"try:\n page = abs(int(self.get_argument('page', '1')))\n step = abs(int(self.get_argument('step', '20')))\n start = (page - 1) * step\nexcept (ValueError, KeyError):\n return await self.finish({'code': response_code.ParameterError})\nasync with aiomysql.create_pool(host='192.168.80.128', port=3306, use... | <|body_start_0|>
try:
page = abs(int(self.get_argument('page', '1')))
step = abs(int(self.get_argument('step', '20')))
start = (page - 1) * step
except (ValueError, KeyError):
return await self.finish({'code': response_code.ParameterError})
async w... | 技战法管理器 | TacticsManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TacticsManager:
"""技战法管理器"""
async def get(self) -> None:
"""根据字典type值获取相关字典数据，动态资源 :param manager_id: :return:"""
<|body_0|>
async def post(self) -> None:
"""添加技战法处理 :return:"""
<|body_1|>
async def put(self) -> None:
"""修改技战法 :param manager... | stack_v2_sparse_classes_36k_train_018249 | 19,675 | no_license | [
{
"docstring": "根据字典type值获取相关字典数据，动态资源 :param manager_id: :return:",
"name": "get",
"signature": "async def get(self) -> None"
},
{
"docstring": "添加技战法处理 :return:",
"name": "post",
"signature": "async def post(self) -> None"
},
{
"docstring": "修改技战法 :param manager_id: :return:",
... | 3 | stack_v2_sparse_classes_30k_train_018426 | Implement the Python class `TacticsManager` described below.
Class description:
技战法管理器
Method signatures and docstrings:
- async def get(self) -> None: 根据字典type值获取相关字典数据，动态资源 :param manager_id: :return:
- async def post(self) -> None: 添加技战法处理 :return:
- async def put(self) -> None: 修改技战法 :param manager_id: :return: | Implement the Python class `TacticsManager` described below.
Class description:
技战法管理器
Method signatures and docstrings:
- async def get(self) -> None: 根据字典type值获取相关字典数据，动态资源 :param manager_id: :return:
- async def post(self) -> None: 添加技战法处理 :return:
- async def put(self) -> None: 修改技战法 :param manager_id: :return:
... | e2fc98c7262cc06f7687530d23a626f250dabb58 | <|skeleton|>
class TacticsManager:
"""技战法管理器"""
async def get(self) -> None:
"""根据字典type值获取相关字典数据，动态资源 :param manager_id: :return:"""
<|body_0|>
async def post(self) -> None:
"""添加技战法处理 :return:"""
<|body_1|>
async def put(self) -> None:
"""修改技战法 :param manager... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TacticsManager:
"""技战法管理器"""
async def get(self) -> None:
"""根据字典type值获取相关字典数据，动态资源 :param manager_id: :return:"""
try:
page = abs(int(self.get_argument('page', '1')))
step = abs(int(self.get_argument('step', '20')))
start = (page - 1) * step
ex... | the_stack_v2_python_sparse | tornado_test/filehandler.py | yanghusf/Code | train | 0 |
aefc90c00da4d0b3e669e90055fa5a8d70b530cf | [
"if not host or (not host.ips and (not host.name)):\n raise ValueError('Invalid host')\nif host.name:\n osh = ObjectStateHolder(self.CIT)\n osh.setStringAttribute('name', host.name)\nelse:\n osh = self.build_complete_host(str(host.ips[0]))\nif host.fqdns:\n osh.setStringAttribute('primary_dns_name', ... | <|body_start_0|>
if not host or (not host.ips and (not host.name)):
raise ValueError('Invalid host')
if host.name:
osh = ObjectStateHolder(self.CIT)
osh.setStringAttribute('name', host.name)
else:
osh = self.build_complete_host(str(host.ips[0]))
... | Builder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Builder:
def build_host(self, host):
"""@types: host_base_parser.HostDescriptor -> ObjectStateHolder"""
<|body_0|>
def build_complete_host(self, key):
"""Build generic host @types: str -> ObjectSateHolder @raise ValueError: Host key is not specified"""
<|body... | stack_v2_sparse_classes_36k_train_018250 | 2,763 | no_license | [
{
"docstring": "@types: host_base_parser.HostDescriptor -> ObjectStateHolder",
"name": "build_host",
"signature": "def build_host(self, host)"
},
{
"docstring": "Build generic host @types: str -> ObjectSateHolder @raise ValueError: Host key is not specified",
"name": "build_complete_host",
... | 2 | stack_v2_sparse_classes_30k_train_016117 | Implement the Python class `Builder` described below.
Class description:
Implement the Builder class.
Method signatures and docstrings:
- def build_host(self, host): @types: host_base_parser.HostDescriptor -> ObjectStateHolder
- def build_complete_host(self, key): Build generic host @types: str -> ObjectSateHolder @r... | Implement the Python class `Builder` described below.
Class description:
Implement the Builder class.
Method signatures and docstrings:
- def build_host(self, host): @types: host_base_parser.HostDescriptor -> ObjectStateHolder
- def build_complete_host(self, key): Build generic host @types: str -> ObjectSateHolder @r... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class Builder:
def build_host(self, host):
"""@types: host_base_parser.HostDescriptor -> ObjectStateHolder"""
<|body_0|>
def build_complete_host(self, key):
"""Build generic host @types: str -> ObjectSateHolder @raise ValueError: Host key is not specified"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Builder:
def build_host(self, host):
"""@types: host_base_parser.HostDescriptor -> ObjectStateHolder"""
if not host or (not host.ips and (not host.name)):
raise ValueError('Invalid host')
if host.name:
osh = ObjectStateHolder(self.CIT)
osh.setStringA... | the_stack_v2_python_sparse | reference/ucmdb/discovery/host_topology.py | madmonkyang/cda-record | train | 0 | |
1ed96fb4456af7633fd2d8ffa6fc40bc6059bf08 | [
"assert _dir is None or _dir == '', 'Cannot use _dir with TextDataReader.'\nif isinstance(sequences, str):\n sequences = DataReaderBase._read_file(sequences)\nfor i, seq in enumerate(sequences):\n if isinstance(seq, six.binary_type):\n seq = seq.decode('utf-8')\n yield {side: seq, 'indices': i}",
... | <|body_start_0|>
assert _dir is None or _dir == '', 'Cannot use _dir with TextDataReader.'
if isinstance(sequences, str):
sequences = DataReaderBase._read_file(sequences)
for i, seq in enumerate(sequences):
if isinstance(seq, six.binary_type):
seq = seq.de... | NewsDataReader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewsDataReader:
def read(self, sequences, side, _dir=None):
"""Read text data from disk. Read from both src and tgt files. Args: sequences (str or Iterable[str]): path to text file or iterable of the actual text data. side (str): Prefix used in return dict. Usually ``"src"`` or ``"tgt"``... | stack_v2_sparse_classes_36k_train_018251 | 47,907 | permissive | [
{
"docstring": "Read text data from disk. Read from both src and tgt files. Args: sequences (str or Iterable[str]): path to text file or iterable of the actual text data. side (str): Prefix used in return dict. Usually ``\"src\"`` or ``\"tgt\"``. _dir (NoneType): Leave as ``None``. This parameter exists to conf... | 2 | null | Implement the Python class `NewsDataReader` described below.
Class description:
Implement the NewsDataReader class.
Method signatures and docstrings:
- def read(self, sequences, side, _dir=None): Read text data from disk. Read from both src and tgt files. Args: sequences (str or Iterable[str]): path to text file or i... | Implement the Python class `NewsDataReader` described below.
Class description:
Implement the NewsDataReader class.
Method signatures and docstrings:
- def read(self, sequences, side, _dir=None): Read text data from disk. Read from both src and tgt files. Args: sequences (str or Iterable[str]): path to text file or i... | d16bf09e21521a6854ff3c7fe6eb271412914960 | <|skeleton|>
class NewsDataReader:
def read(self, sequences, side, _dir=None):
"""Read text data from disk. Read from both src and tgt files. Args: sequences (str or Iterable[str]): path to text file or iterable of the actual text data. side (str): Prefix used in return dict. Usually ``"src"`` or ``"tgt"``... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewsDataReader:
def read(self, sequences, side, _dir=None):
"""Read text data from disk. Read from both src and tgt files. Args: sequences (str or Iterable[str]): path to text file or iterable of the actual text data. side (str): Prefix used in return dict. Usually ``"src"`` or ``"tgt"``. _dir (NoneTy... | the_stack_v2_python_sparse | onmt/inputters/news_dataset.py | memray/OpenNMT-kpg-release | train | 222 | |
5326ae2b783ce1a52c3f1cdf37f112f3f971a2c8 | [
"decorator_name = ''.join(('@', MPMDMPI.__name__.lower()))\nself.decorator_name = decorator_name\nself.args = args\nself.kwargs = kwargs\nself.scope = CONTEXT.in_pycompss()\nself.core_element = None\nself.core_element_configured = False\nself.task_type = 'mpmd_mpi'\nself.processes = 0\nif self.scope:\n if __debu... | <|body_start_0|>
decorator_name = ''.join(('@', MPMDMPI.__name__.lower()))
self.decorator_name = decorator_name
self.args = args
self.kwargs = kwargs
self.scope = CONTEXT.in_pycompss()
self.core_element = None
self.core_element_configured = False
self.task... | MPMDMPI decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on mpmd_mpi task creation. | MPMDMPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MPMDMPI:
"""MPMDMPI decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on mpmd_mpi task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorator. self =... | stack_v2_sparse_classes_36k_train_018252 | 8,390 | permissive | [
{
"docstring": "Store arguments passed to the decorator. self = itself. args = not used. kwargs = dictionary with the given mpi parameters. :param args: Arguments :param kwargs: Keyword arguments",
"name": "__init__",
"signature": "def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None"
}... | 5 | null | Implement the Python class `MPMDMPI` described below.
Class description:
MPMDMPI decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on mpmd_mpi task creation.
Method signatures and docstrings:
- def __init__(self, *args: typing.Any, **kwargs: typing.Any)... | Implement the Python class `MPMDMPI` described below.
Class description:
MPMDMPI decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on mpmd_mpi task creation.
Method signatures and docstrings:
- def __init__(self, *args: typing.Any, **kwargs: typing.Any)... | 5f7a31436d0e6f5acbeb66fa36ab8aad18dc4092 | <|skeleton|>
class MPMDMPI:
"""MPMDMPI decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on mpmd_mpi task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorator. self =... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MPMDMPI:
"""MPMDMPI decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on mpmd_mpi task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorator. self = itself. args... | the_stack_v2_python_sparse | compss/programming_model/bindings/python/src/pycompss/api/mpmd_mpi.py | bsc-wdc/compss | train | 39 |
2ef6b2cd95bb6fd892032e027489765f92510afb | [
"self.pctls = pctls\npctls_v = np.percentile(X, pctls, axis=1)\nself.X_sc = X / np.diff(pctls_v, n=1, axis=0).squeeze()[:, None]",
"pctls_v = np.percentile(Y, self.pctls, axis=lam_axis)\na = np.diff(pctls_v, n=1, axis=0).squeeze()\nY_sc = Y / a[None, ...]\nreturn (Y_sc, a)"
] | <|body_start_0|>
self.pctls = pctls
pctls_v = np.percentile(X, pctls, axis=1)
self.X_sc = X / np.diff(pctls_v, n=1, axis=0).squeeze()[:, None]
<|end_body_0|>
<|body_start_1|>
pctls_v = np.percentile(Y, self.pctls, axis=lam_axis)
a = np.diff(pctls_v, n=1, axis=0).squeeze()
... | scale spectra to unit dispersion | SpecScaler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecScaler:
"""scale spectra to unit dispersion"""
def __init__(self, X, pctls=(16.0, 84.0)):
"""params: - X (nspec, nl): array of spectra"""
<|body_0|>
def __call__(self, Y, lam_axis=0, map_axis=(1, 2)):
"""apply the same scaling as is fit"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_018253 | 18,611 | permissive | [
{
"docstring": "params: - X (nspec, nl): array of spectra",
"name": "__init__",
"signature": "def __init__(self, X, pctls=(16.0, 84.0))"
},
{
"docstring": "apply the same scaling as is fit",
"name": "__call__",
"signature": "def __call__(self, Y, lam_axis=0, map_axis=(1, 2))"
}
] | 2 | stack_v2_sparse_classes_30k_train_019489 | Implement the Python class `SpecScaler` described below.
Class description:
scale spectra to unit dispersion
Method signatures and docstrings:
- def __init__(self, X, pctls=(16.0, 84.0)): params: - X (nspec, nl): array of spectra
- def __call__(self, Y, lam_axis=0, map_axis=(1, 2)): apply the same scaling as is fit | Implement the Python class `SpecScaler` described below.
Class description:
scale spectra to unit dispersion
Method signatures and docstrings:
- def __init__(self, X, pctls=(16.0, 84.0)): params: - X (nspec, nl): array of spectra
- def __call__(self, Y, lam_axis=0, map_axis=(1, 2)): apply the same scaling as is fit
... | 6d7f3e8e4d3d637432d1bac6ed17a837c0ca9c75 | <|skeleton|>
class SpecScaler:
"""scale spectra to unit dispersion"""
def __init__(self, X, pctls=(16.0, 84.0)):
"""params: - X (nspec, nl): array of spectra"""
<|body_0|>
def __call__(self, Y, lam_axis=0, map_axis=(1, 2)):
"""apply the same scaling as is fit"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpecScaler:
"""scale spectra to unit dispersion"""
def __init__(self, X, pctls=(16.0, 84.0)):
"""params: - X (nspec, nl): array of spectra"""
self.pctls = pctls
pctls_v = np.percentile(X, pctls, axis=1)
self.X_sc = X / np.diff(pctls_v, n=1, axis=0).squeeze()[:, None]
... | the_stack_v2_python_sparse | utils.py | CSwigg/stellarmass_pca | train | 0 |
0eb89f9958d583727ed838f03b7d621dacf19dca | [
"super(StageToRedshiftOperator, self).__init__(*args, **kwargs)\nself.arn = arn\nself.aws_credentials_id = aws_credentials_id\nself.conn_id = conn_id\nself.execution_date = kwargs.get('execution_date')\nself.jsonformat = jsonformat\nself.s3_bucket = s3_bucket\nself.s3_key = s3_key\nself.region = region\nself.table ... | <|body_start_0|>
super(StageToRedshiftOperator, self).__init__(*args, **kwargs)
self.arn = arn
self.aws_credentials_id = aws_credentials_id
self.conn_id = conn_id
self.execution_date = kwargs.get('execution_date')
self.jsonformat = jsonformat
self.s3_bucket = s3_b... | Copy Data from S3 onto Redshift Props: - arn, path, conn_id, region, table: see __init__ docstring - qf_truncate: SQL to TRUNCATE the table. Qf means Query Formatted. - qf_copy: SQL to COPY FROM. | StageToRedshiftOperator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StageToRedshiftOperator:
"""Copy Data from S3 onto Redshift Props: - arn, path, conn_id, region, table: see __init__ docstring - qf_truncate: SQL to TRUNCATE the table. Qf means Query Formatted. - qf_copy: SQL to COPY FROM."""
def __init__(self, arn='', aws_credentials_id='', conn_id='', reg... | stack_v2_sparse_classes_36k_train_018254 | 3,004 | no_license | [
{
"docstring": "Args: arn (str): name of ARN role assumed by the Redshift cluster aws_credentials_id (str): AWS credentials in Airflow s3_bucket (str): path to file(s) s3_key (str): path to file(s) conn_id (str): Redshift connection ID in Airflow region (str): AWS region table (str): Redshift table name **kwarg... | 2 | stack_v2_sparse_classes_30k_train_003874 | Implement the Python class `StageToRedshiftOperator` described below.
Class description:
Copy Data from S3 onto Redshift Props: - arn, path, conn_id, region, table: see __init__ docstring - qf_truncate: SQL to TRUNCATE the table. Qf means Query Formatted. - qf_copy: SQL to COPY FROM.
Method signatures and docstrings:... | Implement the Python class `StageToRedshiftOperator` described below.
Class description:
Copy Data from S3 onto Redshift Props: - arn, path, conn_id, region, table: see __init__ docstring - qf_truncate: SQL to TRUNCATE the table. Qf means Query Formatted. - qf_copy: SQL to COPY FROM.
Method signatures and docstrings:... | ec7f881b6e11d7e3294176128290fdd1ad684fc0 | <|skeleton|>
class StageToRedshiftOperator:
"""Copy Data from S3 onto Redshift Props: - arn, path, conn_id, region, table: see __init__ docstring - qf_truncate: SQL to TRUNCATE the table. Qf means Query Formatted. - qf_copy: SQL to COPY FROM."""
def __init__(self, arn='', aws_credentials_id='', conn_id='', reg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StageToRedshiftOperator:
"""Copy Data from S3 onto Redshift Props: - arn, path, conn_id, region, table: see __init__ docstring - qf_truncate: SQL to TRUNCATE the table. Qf means Query Formatted. - qf_copy: SQL to COPY FROM."""
def __init__(self, arn='', aws_credentials_id='', conn_id='', region='', s3_bu... | the_stack_v2_python_sparse | p5_pipeline_airflow/airflowcode/plugins/operators/stage_redshift.py | ogierpaul/Udacity-Data-Engineer-NanoDegree | train | 1 |
225b166357d764d1c3a79970e8e0ca90c2adca4d | [
"from django.conf.urls import url\n\ndef wrap(view):\n\n def wrapper(*args, **kwargs):\n return self.admin_site.admin_view(view)(*args, **kwargs)\n return update_wrapper(wrapper, view)\ninfo = (self.model._meta.app_label, self.model._meta.model_name)\nreturn [url('^import-data/$', wrap(self.import_data... | <|body_start_0|>
from django.conf.urls import url
def wrap(view):
def wrapper(*args, **kwargs):
return self.admin_site.admin_view(view)(*args, **kwargs)
return update_wrapper(wrapper, view)
info = (self.model._meta.app_label, self.model._meta.model_name)... | AttendeeAdmin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttendeeAdmin:
def get_urls(self):
"""Override to add URL to import data."""
<|body_0|>
def import_data(self, request):
"""Admin view to import data from Ticketea."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from django.conf.urls import url
... | stack_v2_sparse_classes_36k_train_018255 | 2,595 | permissive | [
{
"docstring": "Override to add URL to import data.",
"name": "get_urls",
"signature": "def get_urls(self)"
},
{
"docstring": "Admin view to import data from Ticketea.",
"name": "import_data",
"signature": "def import_data(self, request)"
}
] | 2 | null | Implement the Python class `AttendeeAdmin` described below.
Class description:
Implement the AttendeeAdmin class.
Method signatures and docstrings:
- def get_urls(self): Override to add URL to import data.
- def import_data(self, request): Admin view to import data from Ticketea. | Implement the Python class `AttendeeAdmin` described below.
Class description:
Implement the AttendeeAdmin class.
Method signatures and docstrings:
- def get_urls(self): Override to add URL to import data.
- def import_data(self, request): Admin view to import data from Ticketea.
<|skeleton|>
class AttendeeAdmin:
... | 618deb55168f7b93f9569b0813f6fa26274b45ee | <|skeleton|>
class AttendeeAdmin:
def get_urls(self):
"""Override to add URL to import data."""
<|body_0|>
def import_data(self, request):
"""Admin view to import data from Ticketea."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttendeeAdmin:
def get_urls(self):
"""Override to add URL to import data."""
from django.conf.urls import url
def wrap(view):
def wrapper(*args, **kwargs):
return self.admin_site.admin_view(view)(*args, **kwargs)
return update_wrapper(wrapper, ... | the_stack_v2_python_sparse | pycones/attendees/admin.py | python-spain/PyConES-2016 | train | 4 | |
4695784a3f157e9a6d3e17212f1f079d42b282fc | [
"assert isinstance(response, scrapy.http.response.html.HtmlResponse)\nBOARDS = ['Shore Catch Reports NESA', 'Lure Fishing NESA', 'Lure Catch Reports NESA', 'Boat Catch Reports NESA', 'Boat Fishing NESA']\nURLS = ['https://www.nesa.co.uk/forums/shore-catch-reports/', 'https://www.nesa.co.uk/forums/lure-fishing/', 'h... | <|body_start_0|>
assert isinstance(response, scrapy.http.response.html.HtmlResponse)
BOARDS = ['Shore Catch Reports NESA', 'Lure Fishing NESA', 'Lure Catch Reports NESA', 'Boat Catch Reports NESA', 'Boat Fishing NESA']
URLS = ['https://www.nesa.co.uk/forums/shore-catch-reports/', 'https://www.ne... | scrape reports from angling addicts forum | NESASpiderShoreExtraAfloat | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NESASpiderShoreExtraAfloat:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board"""
<|body_0|>
def crawl_board_threads(self, response):
"""crawl"""
<|body_1|>
def parse_thread(self, response... | stack_v2_sparse_classes_36k_train_018256 | 13,051 | no_license | [
{
"docstring": "generate links to pages in a board",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "crawl",
"name": "crawl_board_threads",
"signature": "def crawl_board_threads(self, response)"
},
{
"docstring": "open a report thread and parse first ... | 3 | null | Implement the Python class `NESASpiderShoreExtraAfloat` described below.
Class description:
scrape reports from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): generate links to pages in a board
- def crawl_board_threads(self, response): crawl
- def parse_thread(self, response): o... | Implement the Python class `NESASpiderShoreExtraAfloat` described below.
Class description:
scrape reports from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): generate links to pages in a board
- def crawl_board_threads(self, response): crawl
- def parse_thread(self, response): o... | 9123aa6baf538b662143b9098d963d55165e8409 | <|skeleton|>
class NESASpiderShoreExtraAfloat:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board"""
<|body_0|>
def crawl_board_threads(self, response):
"""crawl"""
<|body_1|>
def parse_thread(self, response... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NESASpiderShoreExtraAfloat:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board"""
assert isinstance(response, scrapy.http.response.html.HtmlResponse)
BOARDS = ['Shore Catch Reports NESA', 'Lure Fishing NESA', 'Lure Catc... | the_stack_v2_python_sparse | imgscrape/spiders/nesa.py | gmonkman/python | train | 0 |
4d872759fa35674d42f80d59a1bc7c236f5f1ad4 | [
"while True:\n try:\n args = qin.get_nowait()\n except Empty:\n return\n qout.put(func(args))",
"if nworkers < 1:\n raise ValueError(f'Invalid number of workers: {nworkers}')\nqin = Queue()\nfor arg in args:\n qin.put(arg)\nqout = Queue()\nprocesses = []\nfor _ in range(nworkers):\n ... | <|body_start_0|>
while True:
try:
args = qin.get_nowait()
except Empty:
return
qout.put(func(args))
<|end_body_0|>
<|body_start_1|>
if nworkers < 1:
raise ValueError(f'Invalid number of workers: {nworkers}')
qin = Q... | ParallerRunner | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParallerRunner:
def _sub_func(qin, qout, func):
"""Single worker called by `run()`."""
<|body_0|>
def run(nworkers, func, args):
"""Run a given function in parallel and return the list of their return values. Parameters ---------- nworkers : int The number of workers... | stack_v2_sparse_classes_36k_train_018257 | 8,239 | permissive | [
{
"docstring": "Single worker called by `run()`.",
"name": "_sub_func",
"signature": "def _sub_func(qin, qout, func)"
},
{
"docstring": "Run a given function in parallel and return the list of their return values. Parameters ---------- nworkers : int The number of workers to spawn. func : lambda... | 2 | stack_v2_sparse_classes_30k_train_001002 | Implement the Python class `ParallerRunner` described below.
Class description:
Implement the ParallerRunner class.
Method signatures and docstrings:
- def _sub_func(qin, qout, func): Single worker called by `run()`.
- def run(nworkers, func, args): Run a given function in parallel and return the list of their return... | Implement the Python class `ParallerRunner` described below.
Class description:
Implement the ParallerRunner class.
Method signatures and docstrings:
- def _sub_func(qin, qout, func): Single worker called by `run()`.
- def run(nworkers, func, args): Run a given function in parallel and return the list of their return... | b8a10b69add71760bd1036e54e67eb191dacc039 | <|skeleton|>
class ParallerRunner:
def _sub_func(qin, qout, func):
"""Single worker called by `run()`."""
<|body_0|>
def run(nworkers, func, args):
"""Run a given function in parallel and return the list of their return values. Parameters ---------- nworkers : int The number of workers... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParallerRunner:
def _sub_func(qin, qout, func):
"""Single worker called by `run()`."""
while True:
try:
args = qin.get_nowait()
except Empty:
return
qout.put(func(args))
def run(nworkers, func, args):
"""Run a giv... | the_stack_v2_python_sparse | uiiit/utils.py | liwen96/netsquid | train | 0 | |
23787fc865f134b31e77ffccdee6a860b99ba01e | [
"if not root:\n return ''\nleft = self.serialize(root.left)\nright = self.serialize(root.right)\nserialized = str(root.val) + 'R' + '[' + left + ']' + right\nreturn serialized",
"if not data:\n return None\nleft_index = data.index('R')\nroot = TreeNode(int(data[:left_index]))\nlr = data[left_index + 1:]\nl,... | <|body_start_0|>
if not root:
return ''
left = self.serialize(root.left)
right = self.serialize(root.right)
serialized = str(root.val) + 'R' + '[' + left + ']' + right
return serialized
<|end_body_0|>
<|body_start_1|>
if not data:
return None
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_36k_train_018258 | 1,453 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 00bf9a8164008aa17507b1c87ce72a3374bcb7b9 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if not root:
return ''
left = self.serialize(root.left)
right = self.serialize(root.right)
serialized = str(root.val) + 'R' + '[' + left + ']' + right
return ... | the_stack_v2_python_sparse | solutions/449.serialize-and-deserialize-bst.py | quixoteji/Leetcode | train | 1 | |
ac2b9a4348543ce1c9ad4a3cefd2fe31343db183 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ConditionalAccessApplications()",
"from .conditional_access_filter import ConditionalAccessFilter\nfrom .conditional_access_filter import ConditionalAccessFilter\nfields: Dict[str, Callable[[Any], None]] = {'applicationFilter': lambda ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ConditionalAccessApplications()
<|end_body_0|>
<|body_start_1|>
from .conditional_access_filter import ConditionalAccessFilter
from .conditional_access_filter import ConditionalAccessFil... | ConditionalAccessApplications | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConditionalAccessApplications:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessApplications:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k_train_018259 | 4,721 | 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: ConditionalAccessApplications",
"name": "create_from_discriminator_value",
"signature": "def create_from_dis... | 3 | stack_v2_sparse_classes_30k_train_013573 | Implement the Python class `ConditionalAccessApplications` described below.
Class description:
Implement the ConditionalAccessApplications class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessApplications: Creates a new instance of th... | Implement the Python class `ConditionalAccessApplications` described below.
Class description:
Implement the ConditionalAccessApplications class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessApplications: Creates a new instance of th... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ConditionalAccessApplications:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessApplications:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConditionalAccessApplications:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessApplications:
"""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_python_sparse | msgraph/generated/models/conditional_access_applications.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
1d6fbb9df7bc76945733639373fec09b99b04d5b | [
"dp = [[0.0] * (r + 1) for r in range(query_row + 1)]\ndp[0][0] = poured\nfor r in range(query_row):\n for c in range(r + 1):\n exceeds = (dp[r][c] - 1.0) / 2.0\n if exceeds > 0:\n dp[r + 1][c] += exceeds\n dp[r + 1][c + 1] += exceeds\nreturn min(1.0, dp[query_row][query_glass... | <|body_start_0|>
dp = [[0.0] * (r + 1) for r in range(query_row + 1)]
dp[0][0] = poured
for r in range(query_row):
for c in range(r + 1):
exceeds = (dp[r][c] - 1.0) / 2.0
if exceeds > 0:
dp[r + 1][c] += exceeds
d... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def champagneTower(self, poured: int, query_row: int, query_glass: int) -> float:
"""Calculate the total champagne flow through each glass. For example, if poured 10 cups, the only glass on the first row has 9 cups flowed through; then the two glasses on the second row has 3.5 ... | stack_v2_sparse_classes_36k_train_018260 | 1,508 | no_license | [
{
"docstring": "Calculate the total champagne flow through each glass. For example, if poured 10 cups, the only glass on the first row has 9 cups flowed through; then the two glasses on the second row has 3.5 cups flowed through each.",
"name": "champagneTower",
"signature": "def champagneTower(self, po... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def champagneTower(self, poured: int, query_row: int, query_glass: int) -> float: Calculate the total champagne flow through each glass. For example, if poured 10 cups, the only ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def champagneTower(self, poured: int, query_row: int, query_glass: int) -> float: Calculate the total champagne flow through each glass. For example, if poured 10 cups, the only ... | edb870f83f0c4568cce0cacec04ee70cf6b545bf | <|skeleton|>
class Solution:
def champagneTower(self, poured: int, query_row: int, query_glass: int) -> float:
"""Calculate the total champagne flow through each glass. For example, if poured 10 cups, the only glass on the first row has 9 cups flowed through; then the two glasses on the second row has 3.5 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def champagneTower(self, poured: int, query_row: int, query_glass: int) -> float:
"""Calculate the total champagne flow through each glass. For example, if poured 10 cups, the only glass on the first row has 9 cups flowed through; then the two glasses on the second row has 3.5 cups flowed th... | the_stack_v2_python_sparse | 2020/champagne_tower.py | eronekogin/leetcode | train | 0 | |
246197011a78ce13d7dfa7841fa8450d9d60d67c | [
"super().__init__()\nself.memory_dim = memory_dim\nself.variational_dropout = variational_dropout\nself.dropout = dropout\nself.read_dropout = nn.Dropout(self.dropout)\nself.mem_proj = xavier_uniform_linear(self.memory_dim, self.memory_dim)\nself.kb_proj = xavier_uniform_linear(self.memory_dim, self.memory_dim)\nse... | <|body_start_0|>
super().__init__()
self.memory_dim = memory_dim
self.variational_dropout = variational_dropout
self.dropout = dropout
self.read_dropout = nn.Dropout(self.dropout)
self.mem_proj = xavier_uniform_linear(self.memory_dim, self.memory_dim)
self.kb_proj... | A MAC recurrent cell read unit. | ReadUnit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadUnit:
"""A MAC recurrent cell read unit."""
def __init__(self, memory_dim: int=512, variational_dropout: bool=True, dropout: float=0.15):
"""Initialise the read unit."""
<|body_0|>
def forward(self, memories: Sequence[torch.Tensor], know: torch.Tensor, controls: Sequ... | stack_v2_sparse_classes_36k_train_018261 | 2,897 | no_license | [
{
"docstring": "Initialise the read unit.",
"name": "__init__",
"signature": "def __init__(self, memory_dim: int=512, variational_dropout: bool=True, dropout: float=0.15)"
},
{
"docstring": "Propagate data through the model.",
"name": "forward",
"signature": "def forward(self, memories: ... | 2 | stack_v2_sparse_classes_30k_train_014161 | Implement the Python class `ReadUnit` described below.
Class description:
A MAC recurrent cell read unit.
Method signatures and docstrings:
- def __init__(self, memory_dim: int=512, variational_dropout: bool=True, dropout: float=0.15): Initialise the read unit.
- def forward(self, memories: Sequence[torch.Tensor], kn... | Implement the Python class `ReadUnit` described below.
Class description:
A MAC recurrent cell read unit.
Method signatures and docstrings:
- def __init__(self, memory_dim: int=512, variational_dropout: bool=True, dropout: float=0.15): Initialise the read unit.
- def forward(self, memories: Sequence[torch.Tensor], kn... | 78c479f8d0b3209ece9f9ccbbf63810802293f61 | <|skeleton|>
class ReadUnit:
"""A MAC recurrent cell read unit."""
def __init__(self, memory_dim: int=512, variational_dropout: bool=True, dropout: float=0.15):
"""Initialise the read unit."""
<|body_0|>
def forward(self, memories: Sequence[torch.Tensor], know: torch.Tensor, controls: Sequ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadUnit:
"""A MAC recurrent cell read unit."""
def __init__(self, memory_dim: int=512, variational_dropout: bool=True, dropout: float=0.15):
"""Initialise the read unit."""
super().__init__()
self.memory_dim = memory_dim
self.variational_dropout = variational_dropout
... | the_stack_v2_python_sparse | gat_vqa/modules/reasoning/mac/read.py | alexmirrington/gat-vqa | train | 4 |
70fca5eea5a5bc74e7556970c89b284e1dc6341a | [
"client = queries.QuizClientMissMatch.getInstance()\nclient.setUp(1, 2)\nself.assertEqual(client, False)",
"client = queries.QuizClientMissMatch.getInstance()\nclient.setUp(1, 1)\nself.assertEqual(client, False)"
] | <|body_start_0|>
client = queries.QuizClientMissMatch.getInstance()
client.setUp(1, 2)
self.assertEqual(client, False)
<|end_body_0|>
<|body_start_1|>
client = queries.QuizClientMissMatch.getInstance()
client.setUp(1, 1)
self.assertEqual(client, False)
<|end_body_1|>
| QuizClientMissMatchTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuizClientMissMatchTest:
def session_vaild_missmatch(self):
"""Check if there's a missmatch"""
<|body_0|>
def session_vaild_match(self):
"""Check if there's a match"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
client = queries.QuizClientMissMatch... | stack_v2_sparse_classes_36k_train_018262 | 15,976 | no_license | [
{
"docstring": "Check if there's a missmatch",
"name": "session_vaild_missmatch",
"signature": "def session_vaild_missmatch(self)"
},
{
"docstring": "Check if there's a match",
"name": "session_vaild_match",
"signature": "def session_vaild_match(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013301 | Implement the Python class `QuizClientMissMatchTest` described below.
Class description:
Implement the QuizClientMissMatchTest class.
Method signatures and docstrings:
- def session_vaild_missmatch(self): Check if there's a missmatch
- def session_vaild_match(self): Check if there's a match | Implement the Python class `QuizClientMissMatchTest` described below.
Class description:
Implement the QuizClientMissMatchTest class.
Method signatures and docstrings:
- def session_vaild_missmatch(self): Check if there's a missmatch
- def session_vaild_match(self): Check if there's a match
<|skeleton|>
class QuizCl... | 58081fd46749e9ca5dea1597f479025c872bccfe | <|skeleton|>
class QuizClientMissMatchTest:
def session_vaild_missmatch(self):
"""Check if there's a missmatch"""
<|body_0|>
def session_vaild_match(self):
"""Check if there's a match"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuizClientMissMatchTest:
def session_vaild_missmatch(self):
"""Check if there's a missmatch"""
client = queries.QuizClientMissMatch.getInstance()
client.setUp(1, 2)
self.assertEqual(client, False)
def session_vaild_match(self):
"""Check if there's a match"""
... | the_stack_v2_python_sparse | triviaQuiz/tests.py | Bradenm1/Django-quiz | train | 0 | |
b7429a64befe2c04c0844c1f4cbdc429a345aa5f | [
"if treeNode is None:\n return\nprint(treeNode.data.data)\nself.middleOrderTraversalRecursion(treeNode.leftChild)\nself.middleOrderTraversalRecursion(treeNode.rightChild)",
"stack = []\nresult = []\nwhile treeNode or stack:\n if treeNode:\n result.append(treeNode.data.data)\n stack.append(tree... | <|body_start_0|>
if treeNode is None:
return
print(treeNode.data.data)
self.middleOrderTraversalRecursion(treeNode.leftChild)
self.middleOrderTraversalRecursion(treeNode.rightChild)
<|end_body_0|>
<|body_start_1|>
stack = []
result = []
while treeNode... | MiddleOrderTraversal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MiddleOrderTraversal:
def middleOrderTraversalRecursion(self, treeNode):
"""先序遍历的递归实现 :param treeNode: :return:"""
<|body_0|>
def middleOrderTraversalNotRecursion(self, treeNode):
"""先序遍历的非递归实现 :param treeNode: :return:"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_018263 | 2,289 | no_license | [
{
"docstring": "先序遍历的递归实现 :param treeNode: :return:",
"name": "middleOrderTraversalRecursion",
"signature": "def middleOrderTraversalRecursion(self, treeNode)"
},
{
"docstring": "先序遍历的非递归实现 :param treeNode: :return:",
"name": "middleOrderTraversalNotRecursion",
"signature": "def middleOr... | 2 | stack_v2_sparse_classes_30k_train_014274 | Implement the Python class `MiddleOrderTraversal` described below.
Class description:
Implement the MiddleOrderTraversal class.
Method signatures and docstrings:
- def middleOrderTraversalRecursion(self, treeNode): 先序遍历的递归实现 :param treeNode: :return:
- def middleOrderTraversalNotRecursion(self, treeNode): 先序遍历的非递归实现 ... | Implement the Python class `MiddleOrderTraversal` described below.
Class description:
Implement the MiddleOrderTraversal class.
Method signatures and docstrings:
- def middleOrderTraversalRecursion(self, treeNode): 先序遍历的递归实现 :param treeNode: :return:
- def middleOrderTraversalNotRecursion(self, treeNode): 先序遍历的非递归实现 ... | cded97a52c422f98b55f2b3527a054d23541d5a4 | <|skeleton|>
class MiddleOrderTraversal:
def middleOrderTraversalRecursion(self, treeNode):
"""先序遍历的递归实现 :param treeNode: :return:"""
<|body_0|>
def middleOrderTraversalNotRecursion(self, treeNode):
"""先序遍历的非递归实现 :param treeNode: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MiddleOrderTraversal:
def middleOrderTraversalRecursion(self, treeNode):
"""先序遍历的递归实现 :param treeNode: :return:"""
if treeNode is None:
return
print(treeNode.data.data)
self.middleOrderTraversalRecursion(treeNode.leftChild)
self.middleOrderTraversalRecursion... | the_stack_v2_python_sparse | chapter5/先序遍历.py | AnJian2020/Leetcode | train | 1 | |
f8b3ea6bdf77ce81af3b9f50b07a3bce034c65fb | [
"line = line.split()\nself.nevery = int(line[1])\nself.x_store = np.zeros((nsteps / self.nevery, natoms))\nself.y_store = np.zeros((nsteps / self.nevery, natoms))\nself.scprod = np.zeros((nsteps / self.nevery, natoms))\nself.counter = 0\nreturn",
"if step % self.nevery != 0:\n return\ncos = np.cos(phi)\nsin = ... | <|body_start_0|>
line = line.split()
self.nevery = int(line[1])
self.x_store = np.zeros((nsteps / self.nevery, natoms))
self.y_store = np.zeros((nsteps / self.nevery, natoms))
self.scprod = np.zeros((nsteps / self.nevery, natoms))
self.counter = 0
return
<|end_bod... | OrientVel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrientVel:
def __init__(self, nsteps, natoms, line):
"""initialize: allocate density array"""
<|body_0|>
def compute(self, step, x, y, vx, vy, phi, natoms, plot='False'):
"""compute a density distribution and a histogram of the density distribution"""
<|body_... | stack_v2_sparse_classes_36k_train_018264 | 1,754 | no_license | [
{
"docstring": "initialize: allocate density array",
"name": "__init__",
"signature": "def __init__(self, nsteps, natoms, line)"
},
{
"docstring": "compute a density distribution and a histogram of the density distribution",
"name": "compute",
"signature": "def compute(self, step, x, y, ... | 2 | stack_v2_sparse_classes_30k_train_001864 | Implement the Python class `OrientVel` described below.
Class description:
Implement the OrientVel class.
Method signatures and docstrings:
- def __init__(self, nsteps, natoms, line): initialize: allocate density array
- def compute(self, step, x, y, vx, vy, phi, natoms, plot='False'): compute a density distribution ... | Implement the Python class `OrientVel` described below.
Class description:
Implement the OrientVel class.
Method signatures and docstrings:
- def __init__(self, nsteps, natoms, line): initialize: allocate density array
- def compute(self, step, x, y, vx, vy, phi, natoms, plot='False'): compute a density distribution ... | 7d2659bee85c955c680eda019cbff6e2b93ecff2 | <|skeleton|>
class OrientVel:
def __init__(self, nsteps, natoms, line):
"""initialize: allocate density array"""
<|body_0|>
def compute(self, step, x, y, vx, vy, phi, natoms, plot='False'):
"""compute a density distribution and a histogram of the density distribution"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrientVel:
def __init__(self, nsteps, natoms, line):
"""initialize: allocate density array"""
line = line.split()
self.nevery = int(line[1])
self.x_store = np.zeros((nsteps / self.nevery, natoms))
self.y_store = np.zeros((nsteps / self.nevery, natoms))
self.scpr... | the_stack_v2_python_sparse | analyse_collective/orientvel.py | melampyge/CollectiveFilament | train | 0 | |
b59300fadfcbb5ea24be202f588d2ebdd165a0d1 | [
"super(SentimentRNN, self).__init__()\nself.output_size = output_size\nself.n_layers = n_layers\nself.hidden_dim = hidden_dim\nself.embedding = nn.Embedding(vocab_size, embedding_dim)\nself.lstm = nn.LSTM(embedding_dim, hidden_dim, n_layers, dropout=drop_prob, batch_first=True)\nself.dropout = nn.Dropout(0.3)\nself... | <|body_start_0|>
super(SentimentRNN, self).__init__()
self.output_size = output_size
self.n_layers = n_layers
self.hidden_dim = hidden_dim
self.embedding = nn.Embedding(vocab_size, embedding_dim)
self.lstm = nn.LSTM(embedding_dim, hidden_dim, n_layers, dropout=drop_prob, ... | The RNN models that will be used to perform Sentiment analysis. | SentimentRNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentimentRNN:
"""The RNN models that will be used to perform Sentiment analysis."""
def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5):
"""Initialize the models by setting up the layers."""
<|body_0|>
def forward(self, x, hidd... | stack_v2_sparse_classes_36k_train_018265 | 3,087 | no_license | [
{
"docstring": "Initialize the models by setting up the layers.",
"name": "__init__",
"signature": "def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5)"
},
{
"docstring": "Perform a forward pass of our models on some input and hidden state.",
"name... | 3 | stack_v2_sparse_classes_30k_train_021000 | Implement the Python class `SentimentRNN` described below.
Class description:
The RNN models that will be used to perform Sentiment analysis.
Method signatures and docstrings:
- def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5): Initialize the models by setting up the lay... | Implement the Python class `SentimentRNN` described below.
Class description:
The RNN models that will be used to perform Sentiment analysis.
Method signatures and docstrings:
- def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5): Initialize the models by setting up the lay... | aa9d9a6e99abc5b2fbee8a724e02a65232d2eb60 | <|skeleton|>
class SentimentRNN:
"""The RNN models that will be used to perform Sentiment analysis."""
def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5):
"""Initialize the models by setting up the layers."""
<|body_0|>
def forward(self, x, hidd... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SentimentRNN:
"""The RNN models that will be used to perform Sentiment analysis."""
def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5):
"""Initialize the models by setting up the layers."""
super(SentimentRNN, self).__init__()
self.outp... | the_stack_v2_python_sparse | sentiment_analysis/model.py | ilyarudyak/tv_script_gen | train | 1 |
506d7a651b513b3474ac3b5cc718e0a9e9331929 | [
"length = 0\nhead_0 = head\nwhile head_0 is not None:\n head_0 = head_0.next\n length += 1\nidx_n = length - n\nif idx_n == 0:\n head = head.next\n return head\nhead_0, cur, idx = (head, head_0, 0)\nwhile idx < idx_n:\n cur, head_0 = (head_0, head_0.next)\n idx += 1\nif head_0 is None:\n cur.ne... | <|body_start_0|>
length = 0
head_0 = head
while head_0 is not None:
head_0 = head_0.next
length += 1
idx_n = length - n
if idx_n == 0:
head = head.next
return head
head_0, cur, idx = (head, head_0, 0)
while idx < idx... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeNthFromEnd1(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_018266 | 1,857 | no_license | [
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEnd1",
"signature": "def removeNthFromEnd1(self, head, n)"
},
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEnd",
"signature": "def removeNthFromEnd(sel... | 2 | stack_v2_sparse_classes_30k_train_018796 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd1(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd1(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode... | 96e847591aa6ea7ea285dbcfc1c9bcfc32026de5 | <|skeleton|>
class Solution:
def removeNthFromEnd1(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeNthFromEnd1(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
length = 0
head_0 = head
while head_0 is not None:
head_0 = head_0.next
length += 1
idx_n = length - n
if idx_n == 0:
hea... | the_stack_v2_python_sparse | LinkList/L19_remove-nth-node-from-end-of-list.py | lihujun101/LeetCode | train | 0 | |
0540fb9754f4cc101eae2e36c02e365448f6c1c1 | [
"result = []\nqe = Queue.Queue(maxsize=0)\nqe.put(root)\nwhile not qe.empty():\n node = qe.get()\n if not node:\n result.append('None')\n else:\n result.append(str(node.val))\n qe.put(node.left)\n qe.put(node.right)\nreturn ','.join(result)",
"qe = Queue.Queue(maxsize=0)\nspli... | <|body_start_0|>
result = []
qe = Queue.Queue(maxsize=0)
qe.put(root)
while not qe.empty():
node = qe.get()
if not node:
result.append('None')
else:
result.append(str(node.val))
qe.put(node.left)
... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_018267 | 1,567 | permissive | [
{
"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 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: 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:... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
result = []
qe = Queue.Queue(maxsize=0)
qe.put(root)
while not qe.empty():
node = qe.get()
if not node:
result.append('Non... | the_stack_v2_python_sparse | LCOF/31-40/37/37.py | xuychen/Leetcode | train | 0 | |
81531b11ebb37d9ccf312feb7be24d91b1dcd327 | [
"super(ResidualRecurrentEncoder, self).__init__()\nself.batch_first = batch_first\nself.rnn_layers = nn.ModuleList()\nself.rnn_layers.append(EmuBidirLSTM(hidden_size, hidden_size, num_layers=1, bias=bias, batch_first=batch_first, bidirectional=True))\nself.rnn_layers.append(nn.LSTM(2 * hidden_size, hidden_size, num... | <|body_start_0|>
super(ResidualRecurrentEncoder, self).__init__()
self.batch_first = batch_first
self.rnn_layers = nn.ModuleList()
self.rnn_layers.append(EmuBidirLSTM(hidden_size, hidden_size, num_layers=1, bias=bias, batch_first=batch_first, bidirectional=True))
self.rnn_layers.... | Encoder with Embedding, LSTM layers, residual connections and optional dropout. The first LSTM layer is bidirectional and uses variable sequence length API, the remaining (num_layers-1) layers are unidirectional. Residual connections are enabled after third LSTM layer, dropout is applied between LSTM layers. | ResidualRecurrentEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResidualRecurrentEncoder:
"""Encoder with Embedding, LSTM layers, residual connections and optional dropout. The first LSTM layer is bidirectional and uses variable sequence length API, the remaining (num_layers-1) layers are unidirectional. Residual connections are enabled after third LSTM layer... | stack_v2_sparse_classes_36k_train_018268 | 6,026 | permissive | [
{
"docstring": "Constructor for the ResidualRecurrentEncoder. :param vocab_size: size of vocabulary :param hidden_size: hidden size for LSTM layers :param num_layers: number of LSTM layers, 1st layer is bidirectional :param bias: enables bias in LSTM layers :param dropout: probability of dropout (between LSTM l... | 2 | null | Implement the Python class `ResidualRecurrentEncoder` described below.
Class description:
Encoder with Embedding, LSTM layers, residual connections and optional dropout. The first LSTM layer is bidirectional and uses variable sequence length API, the remaining (num_layers-1) layers are unidirectional. Residual connect... | Implement the Python class `ResidualRecurrentEncoder` described below.
Class description:
Encoder with Embedding, LSTM layers, residual connections and optional dropout. The first LSTM layer is bidirectional and uses variable sequence length API, the remaining (num_layers-1) layers are unidirectional. Residual connect... | 7db6a1c3e64996d5b319faec6ca38cb31bfea1c4 | <|skeleton|>
class ResidualRecurrentEncoder:
"""Encoder with Embedding, LSTM layers, residual connections and optional dropout. The first LSTM layer is bidirectional and uses variable sequence length API, the remaining (num_layers-1) layers are unidirectional. Residual connections are enabled after third LSTM layer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResidualRecurrentEncoder:
"""Encoder with Embedding, LSTM layers, residual connections and optional dropout. The first LSTM layer is bidirectional and uses variable sequence length API, the remaining (num_layers-1) layers are unidirectional. Residual connections are enabled after third LSTM layer, dropout is ... | the_stack_v2_python_sparse | runtime/translation/seq2seq/models/encoder.py | msr-fiddle/pipedream | train | 356 |
df031083da352c5a0ffd4fc93cd0e764c1fdef00 | [
"startup_program = paddle.static.Program()\ntrain_program = paddle.static.Program()\nwith paddle.static.program_guard(train_program, startup_program):\n input_word = paddle.static.data(name='input_word', shape=[None, 1], dtype='int64')\n param_attr = paddle.ParamAttr(name='emb', initializer=paddle.nn.initiali... | <|body_start_0|>
startup_program = paddle.static.Program()
train_program = paddle.static.Program()
with paddle.static.program_guard(train_program, startup_program):
input_word = paddle.static.data(name='input_word', shape=[None, 1], dtype='int64')
param_attr = paddle.Para... | test paddleslim.quant.quant_embedding | TestQuantEmbedding | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestQuantEmbedding:
"""test paddleslim.quant.quant_embedding"""
def test_quant_embedding(self):
"""paddleslim.quant.quant_embedding(program, place, config=None, scope=None) :return:"""
<|body_0|>
def test_quant_embedding1(self):
"""paddleslim.quant.quant_embeddin... | stack_v2_sparse_classes_36k_train_018269 | 4,417 | no_license | [
{
"docstring": "paddleslim.quant.quant_embedding(program, place, config=None, scope=None) :return:",
"name": "test_quant_embedding",
"signature": "def test_quant_embedding(self)"
},
{
"docstring": "paddleslim.quant.quant_embedding(program, place, config=None, scope=None) :return:",
"name": "... | 3 | null | Implement the Python class `TestQuantEmbedding` described below.
Class description:
test paddleslim.quant.quant_embedding
Method signatures and docstrings:
- def test_quant_embedding(self): paddleslim.quant.quant_embedding(program, place, config=None, scope=None) :return:
- def test_quant_embedding1(self): paddleslim... | Implement the Python class `TestQuantEmbedding` described below.
Class description:
test paddleslim.quant.quant_embedding
Method signatures and docstrings:
- def test_quant_embedding(self): paddleslim.quant.quant_embedding(program, place, config=None, scope=None) :return:
- def test_quant_embedding1(self): paddleslim... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class TestQuantEmbedding:
"""test paddleslim.quant.quant_embedding"""
def test_quant_embedding(self):
"""paddleslim.quant.quant_embedding(program, place, config=None, scope=None) :return:"""
<|body_0|>
def test_quant_embedding1(self):
"""paddleslim.quant.quant_embeddin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestQuantEmbedding:
"""test paddleslim.quant.quant_embedding"""
def test_quant_embedding(self):
"""paddleslim.quant.quant_embedding(program, place, config=None, scope=None) :return:"""
startup_program = paddle.static.Program()
train_program = paddle.static.Program()
with p... | the_stack_v2_python_sparse | models/PaddleSlim/CI/Slim_CI_all_case/p1_api_case_static/test_api_quant_embedding.py | PaddlePaddle/PaddleTest | train | 42 |
fed57dc3bb8cc0043c1505cca7ff05c86473b362 | [
"super().__init__()\nself.inventory = None\nself.supplier_inventory = None\nself.indicators = None\nif inventory is not None and supplier_inventory is not None:\n self.build(inventory, supplier_inventory)",
"print(f'Building QUBO')\nself.inventory = inventory\nself.supplier_inventory = supplier_inventory\nself... | <|body_start_0|>
super().__init__()
self.inventory = None
self.supplier_inventory = None
self.indicators = None
if inventory is not None and supplier_inventory is not None:
self.build(inventory, supplier_inventory)
<|end_body_0|>
<|body_start_1|>
print(f'Buil... | SupplierQubo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SupplierQubo:
def __init__(self, inventory: list[int or str] or None, supplier_inventory: list[set[int or str]] or None) -> None:
"""Initializes the SupplierQubo inventory (list): List of items we want for our inventory supplier_inventory (list of sets): List for each supplier their inve... | stack_v2_sparse_classes_36k_train_018270 | 4,576 | permissive | [
{
"docstring": "Initializes the SupplierQubo inventory (list): List of items we want for our inventory supplier_inventory (list of sets): List for each supplier their inventory",
"name": "__init__",
"signature": "def __init__(self, inventory: list[int or str] or None, supplier_inventory: list[set[int or... | 4 | stack_v2_sparse_classes_30k_train_002658 | Implement the Python class `SupplierQubo` described below.
Class description:
Implement the SupplierQubo class.
Method signatures and docstrings:
- def __init__(self, inventory: list[int or str] or None, supplier_inventory: list[set[int or str]] or None) -> None: Initializes the SupplierQubo inventory (list): List of... | Implement the Python class `SupplierQubo` described below.
Class description:
Implement the SupplierQubo class.
Method signatures and docstrings:
- def __init__(self, inventory: list[int or str] or None, supplier_inventory: list[set[int or str]] or None) -> None: Initializes the SupplierQubo inventory (list): List of... | de3a36e292683485682f0f7b12aabcf8f548bab7 | <|skeleton|>
class SupplierQubo:
def __init__(self, inventory: list[int or str] or None, supplier_inventory: list[set[int or str]] or None) -> None:
"""Initializes the SupplierQubo inventory (list): List of items we want for our inventory supplier_inventory (list of sets): List for each supplier their inve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SupplierQubo:
def __init__(self, inventory: list[int or str] or None, supplier_inventory: list[set[int or str]] or None) -> None:
"""Initializes the SupplierQubo inventory (list): List of items we want for our inventory supplier_inventory (list of sets): List for each supplier their inventory"""
... | the_stack_v2_python_sparse | ZebraKet/models/SupplierQubo.py | olegxtend/Hackathon2021 | train | 0 | |
b5d588c6f95481853b9d658933d0ec48620f8d7e | [
"super().__init__()\nself.t_last_solution = 0\nself.num_restarts = 0",
"super().post_step(step, level_number)\nself.t_last_solution = step.levels[0].time + step.levels[0].dt\nself.num_restarts = step.status.get('restarts_in_a_row', 0)",
"super().post_run(step, level_number)\nself._hooks__num_restarts = self.num... | <|body_start_0|>
super().__init__()
self.t_last_solution = 0
self.num_restarts = 0
<|end_body_0|>
<|body_start_1|>
super().post_step(step, level_number)
self.t_last_solution = step.levels[0].time + step.levels[0].dt
self.num_restarts = step.status.get('restarts_in_a_row'... | Compute the global error once after the run is finished. Because of some timing issues, we cannot inherit from the `LogError` class here. The issue is that the convergence controllers can change the step size after the final iteration but before the `post_run` functions of the hooks are called, which results in a misma... | LogGlobalErrorPostRun | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogGlobalErrorPostRun:
"""Compute the global error once after the run is finished. Because of some timing issues, we cannot inherit from the `LogError` class here. The issue is that the convergence controllers can change the step size after the final iteration but before the `post_run` functions ... | stack_v2_sparse_classes_36k_train_018271 | 7,407 | permissive | [
{
"docstring": "Add an attribute for when the last solution was added.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Store the time at which the solution is stored. This is required because between the `post_step` hook where the solution is stored and the `post_run` ... | 3 | null | Implement the Python class `LogGlobalErrorPostRun` described below.
Class description:
Compute the global error once after the run is finished. Because of some timing issues, we cannot inherit from the `LogError` class here. The issue is that the convergence controllers can change the step size after the final iterati... | Implement the Python class `LogGlobalErrorPostRun` described below.
Class description:
Compute the global error once after the run is finished. Because of some timing issues, we cannot inherit from the `LogError` class here. The issue is that the convergence controllers can change the step size after the final iterati... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class LogGlobalErrorPostRun:
"""Compute the global error once after the run is finished. Because of some timing issues, we cannot inherit from the `LogError` class here. The issue is that the convergence controllers can change the step size after the final iteration but before the `post_run` functions ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogGlobalErrorPostRun:
"""Compute the global error once after the run is finished. Because of some timing issues, we cannot inherit from the `LogError` class here. The issue is that the convergence controllers can change the step size after the final iteration but before the `post_run` functions of the hooks ... | the_stack_v2_python_sparse | pySDC/implementations/hooks/log_errors.py | Parallel-in-Time/pySDC | train | 30 |
105672e66eb8bee3a5cfb49e473e97e855b6ed28 | [
"task_qs = Task.objects.select_related('manager').prefetch_related('agent_list').filter(id=pk)\nif len(task_qs) < 1:\n return Response({'detail': 'Task not found!'}, status=400)\ntask = task_qs[0]\nself.check_object_permissions(request, task)\ntask_data = get_task_details(task)\nreturn Response(task_data, status... | <|body_start_0|>
task_qs = Task.objects.select_related('manager').prefetch_related('agent_list').filter(id=pk)
if len(task_qs) < 1:
return Response({'detail': 'Task not found!'}, status=400)
task = task_qs[0]
self.check_object_permissions(request, task)
task_data = ge... | TaskViewSetAgent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskViewSetAgent:
def retrieve(self, request, pk, format=None):
"""Sample response: --- { 'id': 11, 'title': 'Title', 'point': {'lat': 23.780926, 'lng': 90.422858}, 'status': 0, 'start': datetime, 'deadline': datetime, "images": ['url1..', 'url2..'], 'task_type': 'Doctors visit', 'agent_... | stack_v2_sparse_classes_36k_train_018272 | 22,163 | no_license | [
{
"docstring": "Sample response: --- { 'id': 11, 'title': 'Title', 'point': {'lat': 23.780926, 'lng': 90.422858}, 'status': 0, 'start': datetime, 'deadline': datetime, \"images\": ['url1..', 'url2..'], 'task_type': 'Doctors visit', 'agent_list': [50, 51], 'manager': 'name', 'custom_fields': [], 'address': 'addr... | 4 | null | Implement the Python class `TaskViewSetAgent` described below.
Class description:
Implement the TaskViewSetAgent class.
Method signatures and docstrings:
- def retrieve(self, request, pk, format=None): Sample response: --- { 'id': 11, 'title': 'Title', 'point': {'lat': 23.780926, 'lng': 90.422858}, 'status': 0, 'star... | Implement the Python class `TaskViewSetAgent` described below.
Class description:
Implement the TaskViewSetAgent class.
Method signatures and docstrings:
- def retrieve(self, request, pk, format=None): Sample response: --- { 'id': 11, 'title': 'Title', 'point': {'lat': 23.780926, 'lng': 90.422858}, 'status': 0, 'star... | 11be165f85cda0ffe7a237d011de562d3dc64135 | <|skeleton|>
class TaskViewSetAgent:
def retrieve(self, request, pk, format=None):
"""Sample response: --- { 'id': 11, 'title': 'Title', 'point': {'lat': 23.780926, 'lng': 90.422858}, 'status': 0, 'start': datetime, 'deadline': datetime, "images": ['url1..', 'url2..'], 'task_type': 'Doctors visit', 'agent_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskViewSetAgent:
def retrieve(self, request, pk, format=None):
"""Sample response: --- { 'id': 11, 'title': 'Title', 'point': {'lat': 23.780926, 'lng': 90.422858}, 'status': 0, 'start': datetime, 'deadline': datetime, "images": ['url1..', 'url2..'], 'task_type': 'Doctors visit', 'agent_list': [50, 51... | the_stack_v2_python_sparse | apps/task/views.py | ash018/FFTracker | train | 0 | |
1c6315bf1ee497701ab03a0319aa9cf1024b13f0 | [
"url = '/dashboard/bulkpricing/'\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
"url = '/dashboard/bulkpricing/'\nself.client.login(username=self.adminUN, password='pass')\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(re... | <|body_start_0|>
url = '/dashboard/bulkpricing/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
url = '/dashboard/bulkpricing/'
self.client.login(username=self.adminUN, password='pass')
... | DashboardBulkpricingTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DashboardBulkpricingTestCase:
def test_not_logged_in(self):
"""Test that the dashboard bulkpricing view will redirect whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the dashboard bulkpricing view will load whilst logged in as admin."... | stack_v2_sparse_classes_36k_train_018273 | 26,818 | permissive | [
{
"docstring": "Test that the dashboard bulkpricing view will redirect whilst not logged in.",
"name": "test_not_logged_in",
"signature": "def test_not_logged_in(self)"
},
{
"docstring": "Test that the dashboard bulkpricing view will load whilst logged in as admin.",
"name": "test_logged_in_... | 3 | null | Implement the Python class `DashboardBulkpricingTestCase` described below.
Class description:
Implement the DashboardBulkpricingTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the dashboard bulkpricing view will redirect whilst not logged in.
- def test_logged_in_admin(self... | Implement the Python class `DashboardBulkpricingTestCase` described below.
Class description:
Implement the DashboardBulkpricingTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the dashboard bulkpricing view will redirect whilst not logged in.
- def test_logged_in_admin(self... | 37d2942efcbdaad072f7a06ac876a40e0f69f702 | <|skeleton|>
class DashboardBulkpricingTestCase:
def test_not_logged_in(self):
"""Test that the dashboard bulkpricing view will redirect whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the dashboard bulkpricing view will load whilst logged in as admin."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DashboardBulkpricingTestCase:
def test_not_logged_in(self):
"""Test that the dashboard bulkpricing view will redirect whilst not logged in."""
url = '/dashboard/bulkpricing/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)... | the_stack_v2_python_sparse | mooring/test_views.py | dbca-wa/moorings | train | 0 | |
32c1571a62386f6d4fb490056be5dc4bfd9763d7 | [
"super(PytorchGraphConverter, self).__init__(framework, base_path)\nprint('{} bmodel converter init'.format(model_name))\nself.model_name = model_name\nself.models_path = models_path\nself.shapes = shapes\nself.dyns = dyns\nself.outdirs = outdirs\nself.nets_name = nets_name\nself.target = target\nassert len(self.mo... | <|body_start_0|>
super(PytorchGraphConverter, self).__init__(framework, base_path)
print('{} bmodel converter init'.format(model_name))
self.model_name = model_name
self.models_path = models_path
self.shapes = shapes
self.dyns = dyns
self.outdirs = outdirs
... | pytorch graph bmodel converter | PytorchGraphConverter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PytorchGraphConverter:
"""pytorch graph bmodel converter"""
def __init__(self, model_name, base_path, models_path, shapes, dyns, outdirs, nets_name, framework, target):
"""Init pytorch graph bmodel converter"""
<|body_0|>
def converter(self):
"""convert pytorch g... | stack_v2_sparse_classes_36k_train_018274 | 15,723 | permissive | [
{
"docstring": "Init pytorch graph bmodel converter",
"name": "__init__",
"signature": "def __init__(self, model_name, base_path, models_path, shapes, dyns, outdirs, nets_name, framework, target)"
},
{
"docstring": "convert pytorch graph",
"name": "converter",
"signature": "def converter... | 2 | stack_v2_sparse_classes_30k_train_013102 | Implement the Python class `PytorchGraphConverter` described below.
Class description:
pytorch graph bmodel converter
Method signatures and docstrings:
- def __init__(self, model_name, base_path, models_path, shapes, dyns, outdirs, nets_name, framework, target): Init pytorch graph bmodel converter
- def converter(sel... | Implement the Python class `PytorchGraphConverter` described below.
Class description:
pytorch graph bmodel converter
Method signatures and docstrings:
- def __init__(self, model_name, base_path, models_path, shapes, dyns, outdirs, nets_name, framework, target): Init pytorch graph bmodel converter
- def converter(sel... | c9fa07851da663dda4953dba72e1d3937299a4ea | <|skeleton|>
class PytorchGraphConverter:
"""pytorch graph bmodel converter"""
def __init__(self, model_name, base_path, models_path, shapes, dyns, outdirs, nets_name, framework, target):
"""Init pytorch graph bmodel converter"""
<|body_0|>
def converter(self):
"""convert pytorch g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PytorchGraphConverter:
"""pytorch graph bmodel converter"""
def __init__(self, model_name, base_path, models_path, shapes, dyns, outdirs, nets_name, framework, target):
"""Init pytorch graph bmodel converter"""
super(PytorchGraphConverter, self).__init__(framework, base_path)
prin... | the_stack_v2_python_sparse | modules/utils/bmodel_converter.py | sophon-ai-algo/sophon-inference | train | 32 |
f7d10d41f7e0b2aae4cdde6a9a1c6e1eb4a94819 | [
"res = []\nlayer = [root]\nwhile any(layer):\n next_layer = []\n for node in layer:\n if node:\n next_layer.extend([node.left, node.right])\n res.append(str(node.val))\n else:\n res.append('#')\n layer = next_layer\nreturn ','.join(res)",
"if not data:\n ... | <|body_start_0|>
res = []
layer = [root]
while any(layer):
next_layer = []
for node in layer:
if node:
next_layer.extend([node.left, node.right])
res.append(str(node.val))
else:
re... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_018275 | 1,804 | 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 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: 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:... | 501c347004c140a82a95461e1dbcef6775b3d9da | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = []
layer = [root]
while any(layer):
next_layer = []
for node in layer:
if node:
next_layer.extend([node.... | the_stack_v2_python_sparse | 297-serialize_and_deserialize_binary_tree.py | dkrotx/leetcode | train | 0 | |
e49f8c0e1fbe2296d393d8acdee0d0edb15c41c1 | [
"l, r = (1, num)\nwhile l <= r:\n mid = (l + r) // 2\n square = mid * mid\n if square == num:\n return True\n elif square > num:\n r = mid - 1\n else:\n l = mid + 1\nreturn False",
"i = 1\nwhile num > 0:\n num -= i\n i += 2\nreturn num == 0"
] | <|body_start_0|>
l, r = (1, num)
while l <= r:
mid = (l + r) // 2
square = mid * mid
if square == num:
return True
elif square > num:
r = mid - 1
else:
l = mid + 1
return False
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPerfectSquare(self, num: int) -> bool:
"""1. 二分查找"""
<|body_0|>
def isPerfectSquare_2(self, num: int) -> bool:
"""2. 平方数一定可以写成 等差数列 之和：16=1+3+5+7"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l, r = (1, num)
while l <= r:
... | stack_v2_sparse_classes_36k_train_018276 | 1,278 | no_license | [
{
"docstring": "1. 二分查找",
"name": "isPerfectSquare",
"signature": "def isPerfectSquare(self, num: int) -> bool"
},
{
"docstring": "2. 平方数一定可以写成 等差数列 之和：16=1+3+5+7",
"name": "isPerfectSquare_2",
"signature": "def isPerfectSquare_2(self, num: int) -> bool"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPerfectSquare(self, num: int) -> bool: 1. 二分查找
- def isPerfectSquare_2(self, num: int) -> bool: 2. 平方数一定可以写成 等差数列 之和：16=1+3+5+7 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPerfectSquare(self, num: int) -> bool: 1. 二分查找
- def isPerfectSquare_2(self, num: int) -> bool: 2. 平方数一定可以写成 等差数列 之和：16=1+3+5+7
<|skeleton|>
class Solution:
def isPer... | 4732fb80710a08a715c3e7080c394f5298b8326d | <|skeleton|>
class Solution:
def isPerfectSquare(self, num: int) -> bool:
"""1. 二分查找"""
<|body_0|>
def isPerfectSquare_2(self, num: int) -> bool:
"""2. 平方数一定可以写成 等差数列 之和：16=1+3+5+7"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPerfectSquare(self, num: int) -> bool:
"""1. 二分查找"""
l, r = (1, num)
while l <= r:
mid = (l + r) // 2
square = mid * mid
if square == num:
return True
elif square > num:
r = mid - 1
... | the_stack_v2_python_sparse | .leetcode/367.有效的完全平方数.py | xiaoruijiang/algorithm | train | 0 | |
eb3cc5ca9a125393a703ed7178e464ac876ea14a | [
"if not root:\n return []\nres = [[root.val]]\nstruc = [[root]]\nlevel = 0\nwhile struc[level]:\n temp_res = []\n temp_struc = []\n for i in struc[level]:\n if i:\n temp_struc.extend([i.left, i.right])\n if i.left:\n temp_res.append(i.left.val)\n if... | <|body_start_0|>
if not root:
return []
res = [[root.val]]
struc = [[root]]
level = 0
while struc[level]:
temp_res = []
temp_struc = []
for i in struc[level]:
if i:
temp_struc.extend([i.left, i.ri... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrder2(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_36k_train_018277 | 1,837 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrder",
"signature": "def levelOrder(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrder2",
"signature": "def levelOrder2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016575 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrder2(self, root): :type root: TreeNode :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrder2(self, root): :type root: TreeNode :rtype: List[List[int]]
<|skeleton|>
class Solution:... | 391328c7c601b5c77ff250ad173600d4d1dd7f57 | <|skeleton|>
class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrder2(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
if not root:
return []
res = [[root.val]]
struc = [[root]]
level = 0
while struc[level]:
temp_res = []
temp_struc = []
for i ... | the_stack_v2_python_sparse | leetcode/algo/102. Binary Tree Level Order Traversal.py | wduncan21/Challenges | train | 0 | |
3a65c2e4a42a6902c9b1e98bfa023e4e0bde7002 | [
"allure.dynamic.title('Wolf at the beginning of the queue')\nallure.dynamic.severity(allure.severity_level.NORMAL)\nallure.dynamic.description_html('<h3>Codewars badge:</h3><img src=\"https://www.codewars.com/users/myFirstCode/badges/large\"><h3>Test Description:</h3><p></p>')\nlst = ['wolf', 'sheep', 'sheep', 'she... | <|body_start_0|>
allure.dynamic.title('Wolf at the beginning of the queue')
allure.dynamic.severity(allure.severity_level.NORMAL)
allure.dynamic.description_html('<h3>Codewars badge:</h3><img src="https://www.codewars.com/users/myFirstCode/badges/large"><h3>Test Description:</h3><p></p>')
... | Testing warn_the_sheep function | WarnTheSheepTestCase | [
"Unlicense",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WarnTheSheepTestCase:
"""Testing warn_the_sheep function"""
def test_warn_the_sheep_wolf_at_start(self):
"""If the wolf is the closest animal to you, return "Pls go away and stop eating my sheep". :return:"""
<|body_0|>
def test_warn_the_sheep_wolf_in_middle(self):
... | stack_v2_sparse_classes_36k_train_018278 | 4,284 | permissive | [
{
"docstring": "If the wolf is the closest animal to you, return \"Pls go away and stop eating my sheep\". :return:",
"name": "test_warn_the_sheep_wolf_at_start",
"signature": "def test_warn_the_sheep_wolf_at_start(self)"
},
{
"docstring": "If the wolf is the closest animal to you, return \"Pls ... | 3 | null | Implement the Python class `WarnTheSheepTestCase` described below.
Class description:
Testing warn_the_sheep function
Method signatures and docstrings:
- def test_warn_the_sheep_wolf_at_start(self): If the wolf is the closest animal to you, return "Pls go away and stop eating my sheep". :return:
- def test_warn_the_s... | Implement the Python class `WarnTheSheepTestCase` described below.
Class description:
Testing warn_the_sheep function
Method signatures and docstrings:
- def test_warn_the_sheep_wolf_at_start(self): If the wolf is the closest animal to you, return "Pls go away and stop eating my sheep". :return:
- def test_warn_the_s... | ba3ea81125b6082d867f0ae34c6c9be15e153966 | <|skeleton|>
class WarnTheSheepTestCase:
"""Testing warn_the_sheep function"""
def test_warn_the_sheep_wolf_at_start(self):
"""If the wolf is the closest animal to you, return "Pls go away and stop eating my sheep". :return:"""
<|body_0|>
def test_warn_the_sheep_wolf_in_middle(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WarnTheSheepTestCase:
"""Testing warn_the_sheep function"""
def test_warn_the_sheep_wolf_at_start(self):
"""If the wolf is the closest animal to you, return "Pls go away and stop eating my sheep". :return:"""
allure.dynamic.title('Wolf at the beginning of the queue')
allure.dynami... | the_stack_v2_python_sparse | kyu_8/wolf_in_sheep_clothing/test_wolf_in_sheep_clothing.py | qamine-test/codewars | train | 0 |
e51a01074b6f21dd3a86493642115b98d1975d7b | [
"if root is None:\n return 0\nmax_count = [1]\n\ndef DFS(node, count, parent_val):\n if parent_val + 1 == node.val:\n count += 1\n max_count[0] = max(max_count[0], count)\n else:\n count = 1\n if node.left:\n DFS(node.left, count, node.val)\n if node.right:\n DFS(no... | <|body_start_0|>
if root is None:
return 0
max_count = [1]
def DFS(node, count, parent_val):
if parent_val + 1 == node.val:
count += 1
max_count[0] = max(max_count[0], count)
else:
count = 1
if node.... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
retu... | stack_v2_sparse_classes_36k_train_018279 | 2,033 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "longestConsecutive",
"signature": "def longestConsecutive(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "longestConsecutive",
"signature": "def longestConsecutive(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, root): :type root: TreeNode :rtype: int
- def longestConsecutive(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, root): :type root: TreeNode :rtype: int
- def longestConsecutive(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def... | 8bb17099be02d997d554519be360ef4aa1c028e3 | <|skeleton|>
class Solution:
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestConsecutive(self, root):
""":type root: TreeNode :rtype: int"""
if root is None:
return 0
max_count = [1]
def DFS(node, count, parent_val):
if parent_val + 1 == node.val:
count += 1
max_count[0] = max... | the_stack_v2_python_sparse | Google/2. medium/298. Binary Tree Longest Consecutive Sequence.py | yemao616/summer18 | train | 0 | |
1fe89e0523c9160939709328d164a6fb22522b9e | [
"counter = 0\nwhile head:\n counter += 1\n head = head.next\nreturn counter",
"for i in range(size - 1):\n if not head:\n break\n head = head.next\nif not head:\n return None\nnext_start, head.next = (head.next, None)\nreturn next_start",
"curr = dummy_start\nwhile l1 and l2:\n if l1.va... | <|body_start_0|>
counter = 0
while head:
counter += 1
head = head.next
return counter
<|end_body_0|>
<|body_start_1|>
for i in range(size - 1):
if not head:
break
head = head.next
if not head:
return Non... | Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this way, we iteratively split the list in... | Solution2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
"""Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this ... | stack_v2_sparse_classes_36k_train_018280 | 4,593 | permissive | [
{
"docstring": "Count the length of the linked list",
"name": "get_size",
"signature": "def get_size(self, head: ListNode) -> int"
},
{
"docstring": "Given the head & size, return the start node of the next chunk",
"name": "split",
"signature": "def split(self, head: ListNode, size: int)... | 4 | stack_v2_sparse_classes_30k_train_005021 | Implement the Python class `Solution2` described below.
Class description:
Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is rep... | Implement the Python class `Solution2` described below.
Class description:
Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is rep... | 9f66d352c805fcdd9930aaa18c93d7546768287c | <|skeleton|>
class Solution2:
"""Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution2:
"""Algorithm: Bottom Up Merge Sort 1) Start with splitting the list into sublists of size 1. Each adjacent pair of sublists of size 1 is merged in sorted order. After the first iteration, we get the sorted lists of size 2. A similar process is repeated for a sublist of size 2. In this way, we itera... | the_stack_v2_python_sparse | medium/148_sort_list.py | niki4/leetcode_py3 | train | 0 |
6732325006f21a58628517b3b5fb88d4d2bf10fe | [
"self.dirname = Path(dirname).absolute()\nself.basename = basename\nif not self.dirname.is_dir():\n raise ValueError('dirname must be a directory')",
"all_filenames = self.dirname.glob('*')\nd = {}\nfor v in all_filenames:\n split_fn = v.name\n m = glob.re.search('^(\\\\w+)\\\\.%s\\\\.(\\\\d+)$' % typest... | <|body_start_0|>
self.dirname = Path(dirname).absolute()
self.basename = basename
if not self.dirname.is_dir():
raise ValueError('dirname must be a directory')
<|end_body_0|>
<|body_start_1|>
all_filenames = self.dirname.glob('*')
d = {}
for v in all_filename... | Simple class to interpret user's requests into KlustaKwik filenames | FilenameParser | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilenameParser:
"""Simple class to interpret user's requests into KlustaKwik filenames"""
def __init__(self, dirname, basename=None):
"""Initialize a new parser for a directory containing files dirname: directory containing files basename: basename in KlustaKwik format spec If basena... | stack_v2_sparse_classes_36k_train_018281 | 17,008 | permissive | [
{
"docstring": "Initialize a new parser for a directory containing files dirname: directory containing files basename: basename in KlustaKwik format spec If basename is left None, then files with any basename in the directory will be used. An error is raised if files with multiple basenames exist in the directo... | 2 | stack_v2_sparse_classes_30k_train_015215 | Implement the Python class `FilenameParser` described below.
Class description:
Simple class to interpret user's requests into KlustaKwik filenames
Method signatures and docstrings:
- def __init__(self, dirname, basename=None): Initialize a new parser for a directory containing files dirname: directory containing fil... | Implement the Python class `FilenameParser` described below.
Class description:
Simple class to interpret user's requests into KlustaKwik filenames
Method signatures and docstrings:
- def __init__(self, dirname, basename=None): Initialize a new parser for a directory containing files dirname: directory containing fil... | 354c8d9d5fbc4daad3547773d2f281f8c163d208 | <|skeleton|>
class FilenameParser:
"""Simple class to interpret user's requests into KlustaKwik filenames"""
def __init__(self, dirname, basename=None):
"""Initialize a new parser for a directory containing files dirname: directory containing files basename: basename in KlustaKwik format spec If basena... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FilenameParser:
"""Simple class to interpret user's requests into KlustaKwik filenames"""
def __init__(self, dirname, basename=None):
"""Initialize a new parser for a directory containing files dirname: directory containing files basename: basename in KlustaKwik format spec If basename is left No... | the_stack_v2_python_sparse | neo/io/klustakwikio.py | NeuralEnsemble/python-neo | train | 265 |
2a4ce08fa1df750db7bae3280b585a4edea41da7 | [
"_id = request.form.get('id', request.args.get('id', None))\nif _id is None:\n return ({'success': False, 'message': 'missing parameter: id'}, 400)\njob_spec = mozart_es.get_by_id(index=JOB_SPECS_INDEX, id=_id, ignore=404)\napp.logger.info(job_spec)\nif job_spec['found'] is False:\n app.logger.error('job_spec... | <|body_start_0|>
_id = request.form.get('id', request.args.get('id', None))
if _id is None:
return ({'success': False, 'message': 'missing parameter: id'}, 400)
job_spec = mozart_es.get_by_id(index=JOB_SPECS_INDEX, id=_id, ignore=404)
app.logger.info(job_spec)
if job_... | Rest APIs for all job_specs (GET, POST, DELETE) | JobSpecs | [
"LicenseRef-scancode-proprietary-license",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobSpecs:
"""Rest APIs for all job_specs (GET, POST, DELETE)"""
def get(self):
"""Gets a Job Type specification object for the given ID."""
<|body_0|>
def post(self):
"""Add a Job Type specification JSON object."""
<|body_1|>
def delete(self):
... | stack_v2_sparse_classes_36k_train_018282 | 13,931 | permissive | [
{
"docstring": "Gets a Job Type specification object for the given ID.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Add a Job Type specification JSON object.",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Remove Job Spec for the given ID",
... | 3 | stack_v2_sparse_classes_30k_test_000641 | Implement the Python class `JobSpecs` described below.
Class description:
Rest APIs for all job_specs (GET, POST, DELETE)
Method signatures and docstrings:
- def get(self): Gets a Job Type specification object for the given ID.
- def post(self): Add a Job Type specification JSON object.
- def delete(self): Remove Job... | Implement the Python class `JobSpecs` described below.
Class description:
Rest APIs for all job_specs (GET, POST, DELETE)
Method signatures and docstrings:
- def get(self): Gets a Job Type specification object for the given ID.
- def post(self): Add a Job Type specification JSON object.
- def delete(self): Remove Job... | c238340fafd96a9b92d92e544d0892a354c1ca32 | <|skeleton|>
class JobSpecs:
"""Rest APIs for all job_specs (GET, POST, DELETE)"""
def get(self):
"""Gets a Job Type specification object for the given ID."""
<|body_0|>
def post(self):
"""Add a Job Type specification JSON object."""
<|body_1|>
def delete(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobSpecs:
"""Rest APIs for all job_specs (GET, POST, DELETE)"""
def get(self):
"""Gets a Job Type specification object for the given ID."""
_id = request.form.get('id', request.args.get('id', None))
if _id is None:
return ({'success': False, 'message': 'missing paramet... | the_stack_v2_python_sparse | mozart/services/api_v02/specs.py | hysds/mozart | train | 1 |
a6489cd60d6902b6bbd014ce5508f25107fea124 | [
"res = super(AccountInvoiceLine, self).onchange_invoice_product_id(product_id, invoice)\nif isinstance(product_id, int):\n product_id = self.env['product.product'].browse(product_id)\nsuppinfo = False\nfiscal_position = invoice.fiscal_position_id\nif product_id:\n if product_id.purchase_ok and invoice.type in... | <|body_start_0|>
res = super(AccountInvoiceLine, self).onchange_invoice_product_id(product_id, invoice)
if isinstance(product_id, int):
product_id = self.env['product.product'].browse(product_id)
suppinfo = False
fiscal_position = invoice.fiscal_position_id
if product... | AccountInvoiceLine | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountInvoiceLine:
def onchange_invoice_product_id(self, product_id, invoice):
"""Récupération des infos du produit et du supplierinfo"""
<|body_0|>
def _onchange_sec_uom_qty(self):
"""Au changement de la qty, changement des autres qty"""
<|body_1|>
def... | stack_v2_sparse_classes_36k_train_018283 | 14,763 | no_license | [
{
"docstring": "Récupération des infos du produit et du supplierinfo",
"name": "onchange_invoice_product_id",
"signature": "def onchange_invoice_product_id(self, product_id, invoice)"
},
{
"docstring": "Au changement de la qty, changement des autres qty",
"name": "_onchange_sec_uom_qty",
... | 3 | null | Implement the Python class `AccountInvoiceLine` described below.
Class description:
Implement the AccountInvoiceLine class.
Method signatures and docstrings:
- def onchange_invoice_product_id(self, product_id, invoice): Récupération des infos du produit et du supplierinfo
- def _onchange_sec_uom_qty(self): Au changem... | Implement the Python class `AccountInvoiceLine` described below.
Class description:
Implement the AccountInvoiceLine class.
Method signatures and docstrings:
- def onchange_invoice_product_id(self, product_id, invoice): Récupération des infos du produit et du supplierinfo
- def _onchange_sec_uom_qty(self): Au changem... | eb394e1f79ba1995da2dcd81adfdd511c22caff9 | <|skeleton|>
class AccountInvoiceLine:
def onchange_invoice_product_id(self, product_id, invoice):
"""Récupération des infos du produit et du supplierinfo"""
<|body_0|>
def _onchange_sec_uom_qty(self):
"""Au changement de la qty, changement des autres qty"""
<|body_1|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountInvoiceLine:
def onchange_invoice_product_id(self, product_id, invoice):
"""Récupération des infos du produit et du supplierinfo"""
res = super(AccountInvoiceLine, self).onchange_invoice_product_id(product_id, invoice)
if isinstance(product_id, int):
product_id = sel... | the_stack_v2_python_sparse | OpenPROD/openprod-addons/purchase/account_invoice.py | kazacube-mziouadi/ceci | train | 0 | |
325fbf053795413e392bdfa484e193cfefd49874 | [
"self.prefix_sum_array = []\nprefix_sum = 0\nfor weight in w:\n prefix_sum += weight\n self.prefix_sum_array.append(prefix_sum)\nself.total_sum = prefix_sum",
"from bisect import bisect_left\nprefix_sum = self.total_sum * random.random()\nreturn bisect_left(self.prefix_sum_array, prefix_sum)"
] | <|body_start_0|>
self.prefix_sum_array = []
prefix_sum = 0
for weight in w:
prefix_sum += weight
self.prefix_sum_array.append(prefix_sum)
self.total_sum = prefix_sum
<|end_body_0|>
<|body_start_1|>
from bisect import bisect_left
prefix_sum = self.... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.prefix_sum_array = []
prefix_sum = 0
for weight in w:
prefix_su... | stack_v2_sparse_classes_36k_train_018284 | 648 | permissive | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007327 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | bf03743a3676ca9a8c107f92cf3858b6887d0308 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.prefix_sum_array = []
prefix_sum = 0
for weight in w:
prefix_sum += weight
self.prefix_sum_array.append(prefix_sum)
self.total_sum = prefix_sum
def pickIndex(self):
""":r... | the_stack_v2_python_sparse | python/528_random_pick_with_weight.py | liaison/LeetCode | train | 17 | |
46c1bf38178e10091bce874178c79c8292b3cf46 | [
"try:\n volume = int(redis.get('fm:player:volume'))\nexcept ValueError:\n volume = 100\nreturn http.OK({'volume': volume})",
"serializer = VolumeSerializer()\ntry:\n data = serializer.marshal(request.json)\nexcept MappingErrors as e:\n return http.UnprocessableEntity(errors=e.message)\nredis.publish(c... | <|body_start_0|>
try:
volume = int(redis.get('fm:player:volume'))
except ValueError:
volume = 100
return http.OK({'volume': volume})
<|end_body_0|>
<|body_start_1|>
serializer = VolumeSerializer()
try:
data = serializer.marshal(request.json)
... | Contorls Volume on the Physical player. | VolumeView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeView:
"""Contorls Volume on the Physical player."""
def get(self):
"""Retrieve the current volume level for the physical player."""
<|body_0|>
def post(self):
"""Change the volume level for the player."""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_018285 | 12,943 | no_license | [
{
"docstring": "Retrieve the current volume level for the physical player.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Change the volume level for the player.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019462 | Implement the Python class `VolumeView` described below.
Class description:
Contorls Volume on the Physical player.
Method signatures and docstrings:
- def get(self): Retrieve the current volume level for the physical player.
- def post(self): Change the volume level for the player. | Implement the Python class `VolumeView` described below.
Class description:
Contorls Volume on the Physical player.
Method signatures and docstrings:
- def get(self): Retrieve the current volume level for the physical player.
- def post(self): Change the volume level for the player.
<|skeleton|>
class VolumeView:
... | 817766c6d2e2660291b723274d345ce5eb40ab77 | <|skeleton|>
class VolumeView:
"""Contorls Volume on the Physical player."""
def get(self):
"""Retrieve the current volume level for the physical player."""
<|body_0|>
def post(self):
"""Change the volume level for the player."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VolumeView:
"""Contorls Volume on the Physical player."""
def get(self):
"""Retrieve the current volume level for the physical player."""
try:
volume = int(redis.get('fm:player:volume'))
except ValueError:
volume = 100
return http.OK({'volume': volu... | the_stack_v2_python_sparse | fm/views/player.py | thisissoon/FM-API | train | 3 |
6f97c9fe59b491b3f585e4695249f63f1543559a | [
"super().__init__(n_head, n_feat, dropout_rate)\nself.zero_triu = zero_triu\nself.linear_pos = nn.Linear(n_feat, n_feat, bias=False)\nself.pos_bias_u = nn.Parameter(torch.Tensor(self.h, self.d_k))\nself.pos_bias_v = nn.Parameter(torch.Tensor(self.h, self.d_k))\ntorch.nn.init.xavier_uniform_(self.pos_bias_u)\ntorch.... | <|body_start_0|>
super().__init__(n_head, n_feat, dropout_rate)
self.zero_triu = zero_triu
self.linear_pos = nn.Linear(n_feat, n_feat, bias=False)
self.pos_bias_u = nn.Parameter(torch.Tensor(self.h, self.d_k))
self.pos_bias_v = nn.Parameter(torch.Tensor(self.h, self.d_k))
... | Multi-Head Attention layer with relative position encoding (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of features. dropout_rate (float): Dropout rate. zero_triu (bool)... | RelPositionMultiHeadedAttention | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelPositionMultiHeadedAttention:
"""Multi-Head Attention layer with relative position encoding (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of fea... | stack_v2_sparse_classes_36k_train_018286 | 11,646 | permissive | [
{
"docstring": "Construct an RelPositionMultiHeadedAttention object.",
"name": "__init__",
"signature": "def __init__(self, n_head, n_feat, dropout_rate, zero_triu=False)"
},
{
"docstring": "Compute relative positional encoding. Args: x (torch.Tensor): Input tensor (batch, head, time1, 2*time1-1... | 3 | null | Implement the Python class `RelPositionMultiHeadedAttention` described below.
Class description:
Multi-Head Attention layer with relative position encoding (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of... | Implement the Python class `RelPositionMultiHeadedAttention` described below.
Class description:
Multi-Head Attention layer with relative position encoding (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class RelPositionMultiHeadedAttention:
"""Multi-Head Attention layer with relative position encoding (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of fea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelPositionMultiHeadedAttention:
"""Multi-Head Attention layer with relative position encoding (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. Paper: https://arxiv.org/abs/1901.02860 Args: n_head (int): The number of heads. n_feat (int): The number of features. dropou... | the_stack_v2_python_sparse | espnet/nets/pytorch_backend/transformer/attention.py | espnet/espnet | train | 7,242 |
6c2cc2009c99a7814846642daad27a99073c6cd0 | [
"super().save_model(request, obj, form, change)\nfrom celery_tasks.tasks import generate_static_index_html\ngenerate_static_index_html.delay()\ncache.delete('index_page_data')",
"super().save_model(request, obj)\nfrom celery_tasks.tasks import generate_static_index_html\ngenerate_static_index_html.delay()\ncache.... | <|body_start_0|>
super().save_model(request, obj, form, change)
from celery_tasks.tasks import generate_static_index_html
generate_static_index_html.delay()
cache.delete('index_page_data')
<|end_body_0|>
<|body_start_1|>
super().save_model(request, obj)
from celery_tasks... | BaseModelAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseModelAdmin:
def save_model(self, request, obj, form, change):
"""后台新增或更新表中的数据时调用这个方法"""
<|body_0|>
def delete_model(self, request, obj):
"""删除表中的数据时也使用"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().save_model(request, obj, form, change... | stack_v2_sparse_classes_36k_train_018287 | 1,872 | no_license | [
{
"docstring": "后台新增或更新表中的数据时调用这个方法",
"name": "save_model",
"signature": "def save_model(self, request, obj, form, change)"
},
{
"docstring": "删除表中的数据时也使用",
"name": "delete_model",
"signature": "def delete_model(self, request, obj)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003489 | Implement the Python class `BaseModelAdmin` described below.
Class description:
Implement the BaseModelAdmin class.
Method signatures and docstrings:
- def save_model(self, request, obj, form, change): 后台新增或更新表中的数据时调用这个方法
- def delete_model(self, request, obj): 删除表中的数据时也使用 | Implement the Python class `BaseModelAdmin` described below.
Class description:
Implement the BaseModelAdmin class.
Method signatures and docstrings:
- def save_model(self, request, obj, form, change): 后台新增或更新表中的数据时调用这个方法
- def delete_model(self, request, obj): 删除表中的数据时也使用
<|skeleton|>
class BaseModelAdmin:
def... | 206909fa8ab76de4b2aa5cabc9d76e9977809d46 | <|skeleton|>
class BaseModelAdmin:
def save_model(self, request, obj, form, change):
"""后台新增或更新表中的数据时调用这个方法"""
<|body_0|>
def delete_model(self, request, obj):
"""删除表中的数据时也使用"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseModelAdmin:
def save_model(self, request, obj, form, change):
"""后台新增或更新表中的数据时调用这个方法"""
super().save_model(request, obj, form, change)
from celery_tasks.tasks import generate_static_index_html
generate_static_index_html.delay()
cache.delete('index_page_data')
d... | the_stack_v2_python_sparse | E-commerce/dailyfresh/apps/goods/admin.py | zxk1994/Project | train | 0 | |
66284f5d00c672fdd26fd53213b47ab1fb673281 | [
"if request.user.has_perm(CHANGE_TASK):\n task = Task.objects.get(pk=request.data['id_task'])\n team = Team.objects.get(pk=request.data['id_team'])\n task.teams.add(team)\n return Response(status=status.HTTP_201_CREATED)\nreturn Response(status=status.HTTP_401_UNAUTHORIZED)",
"if request.user.has_perm... | <|body_start_0|>
if request.user.has_perm(CHANGE_TASK):
task = Task.objects.get(pk=request.data['id_task'])
team = Team.objects.get(pk=request.data['id_team'])
task.teams.add(team)
return Response(status=status.HTTP_201_CREATED)
return Response(status=stat... | \\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the permissions, it will send HTTP 401. Both re... | AddTeamToTask | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddTeamToTask:
"""\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the pe... | stack_v2_sparse_classes_36k_train_018288 | 21,722 | permissive | [
{
"docstring": "Assign a team to a task.",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "Remove a team from a task.",
"name": "put",
"signature": "def put(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008442 | Implement the Python class `AddTeamToTask` described below.
Class description:
\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team fr... | Implement the Python class `AddTeamToTask` described below.
Class description:
\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team fr... | 56511ebac83a5dc1fb8768a98bc675e88530a447 | <|skeleton|>
class AddTeamToTask:
"""\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the pe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddTeamToTask:
"""\\n# Assign a team to a task. Parameters : request (HttpRequest) : the request coming from the front-end id (int) : the id of the task Return : response (Response) : the response. POST request : add team to task PUT request : remove team from task If the user doesn't have the permissions, it... | the_stack_v2_python_sparse | maintenancemanagement/views/views_task.py | Open-CMMS/openCMMS_backend | train | 4 |
694c38324e3bf23b4398aefe1d0871af5e873463 | [
"if stack:\n node = stack.pop()\n if node.right:\n node = node.right\n stack.append(node)\n while node.left:\n node = node.left\n stack.append(node)\n else:\n while stack and stack[-1].val < node.val:\n stack.pop()\n return stack[-1] if stack ... | <|body_start_0|>
if stack:
node = stack.pop()
if node.right:
node = node.right
stack.append(node)
while node.left:
node = node.left
stack.append(node)
else:
while stack and... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _nextGT(self, stack):
"""find node with smallest value > stack[-1].val."""
<|body_0|>
def inorderSuccessor(self, root: TreeNode, p: TreeNode) -> TreeNode:
"""Q0272, inorder predecessor and successor."""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_018289 | 921 | no_license | [
{
"docstring": "find node with smallest value > stack[-1].val.",
"name": "_nextGT",
"signature": "def _nextGT(self, stack)"
},
{
"docstring": "Q0272, inorder predecessor and successor.",
"name": "inorderSuccessor",
"signature": "def inorderSuccessor(self, root: TreeNode, p: TreeNode) -> ... | 2 | stack_v2_sparse_classes_30k_test_001065 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _nextGT(self, stack): find node with smallest value > stack[-1].val.
- def inorderSuccessor(self, root: TreeNode, p: TreeNode) -> TreeNode: Q0272, inorder predecessor and suc... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _nextGT(self, stack): find node with smallest value > stack[-1].val.
- def inorderSuccessor(self, root: TreeNode, p: TreeNode) -> TreeNode: Q0272, inorder predecessor and suc... | 6043134736452a6f4704b62857d0aed2e9571164 | <|skeleton|>
class Solution:
def _nextGT(self, stack):
"""find node with smallest value > stack[-1].val."""
<|body_0|>
def inorderSuccessor(self, root: TreeNode, p: TreeNode) -> TreeNode:
"""Q0272, inorder predecessor and successor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _nextGT(self, stack):
"""find node with smallest value > stack[-1].val."""
if stack:
node = stack.pop()
if node.right:
node = node.right
stack.append(node)
while node.left:
node = node.lef... | the_stack_v2_python_sparse | src/0200-0299/0285.inorder.successor.bst.py | gyang274/leetcode | train | 1 | |
a7a663ffedc2066df93d438dd8d6bc1ea365e704 | [
"if graph.is_directed():\n raise ValueError('the graph is directed')\nself.graph = graph\nself.hamiltonian_cycle = self.graph.__class__(self.graph.v())\nfor node in self.graph.iternodes():\n self.hamiltonian_cycle.add_node(node)\nself._uf = UnionFind()\nself._pq = PriorityQueue()",
"for node in self.graph.i... | <|body_start_0|>
if graph.is_directed():
raise ValueError('the graph is directed')
self.graph = graph
self.hamiltonian_cycle = self.graph.__class__(self.graph.v())
for node in self.graph.iternodes():
self.hamiltonian_cycle.add_node(node)
self._uf = UnionFi... | The sorted edge algorithm for TSP. Attributes ---------- graph : input weighted complete graph hamiltonian_cycle : cycle graph _uf : disjoint-set data structure, private _pq : priority queue, private | SortedEdgeTSPWithGraph | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SortedEdgeTSPWithGraph:
"""The sorted edge algorithm for TSP. Attributes ---------- graph : input weighted complete graph hamiltonian_cycle : cycle graph _uf : disjoint-set data structure, private _pq : priority queue, private"""
def __init__(self, graph):
"""The algorithm initializa... | stack_v2_sparse_classes_36k_train_018290 | 5,106 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self, source=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001680 | Implement the Python class `SortedEdgeTSPWithGraph` described below.
Class description:
The sorted edge algorithm for TSP. Attributes ---------- graph : input weighted complete graph hamiltonian_cycle : cycle graph _uf : disjoint-set data structure, private _pq : priority queue, private
Method signatures and docstrin... | Implement the Python class `SortedEdgeTSPWithGraph` described below.
Class description:
The sorted edge algorithm for TSP. Attributes ---------- graph : input weighted complete graph hamiltonian_cycle : cycle graph _uf : disjoint-set data structure, private _pq : priority queue, private
Method signatures and docstrin... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class SortedEdgeTSPWithGraph:
"""The sorted edge algorithm for TSP. Attributes ---------- graph : input weighted complete graph hamiltonian_cycle : cycle graph _uf : disjoint-set data structure, private _pq : priority queue, private"""
def __init__(self, graph):
"""The algorithm initializa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SortedEdgeTSPWithGraph:
"""The sorted edge algorithm for TSP. Attributes ---------- graph : input weighted complete graph hamiltonian_cycle : cycle graph _uf : disjoint-set data structure, private _pq : priority queue, private"""
def __init__(self, graph):
"""The algorithm initialization."""
... | the_stack_v2_python_sparse | graphtheory/hamiltonian/tspse.py | kgashok/graphs-dict | train | 0 |
7e36bd0a93c1562ad212bf7e819cba0634f51dbe | [
"self.root = root\nself.image = image\nself.filename = self.imagery[image]\nself.transforms = transforms\nif download:\n self.__download(api_key)\nself.files = self._load_files(os.path.join(root, self.dataset_id))",
"if os.path.exists(os.path.join(self.root, self.dataset_id, self.collections[0], 'collection.js... | <|body_start_0|>
self.root = root
self.image = image
self.filename = self.imagery[image]
self.transforms = transforms
if download:
self.__download(api_key)
self.files = self._load_files(os.path.join(root, self.dataset_id))
<|end_body_0|>
<|body_start_1|>
... | SpaceNet 6: Multi-Sensor All-Weather Mapping. `SpaceNet 6 <https://spacenet.ai/sn6-challenge/>`_ is a dataset of optical and SAR imagery over the city of Rotterdam. Collection features: +------------+---------------------+------------+-----------------------------+ | AOI | Area (km\\ :sup:`2`\\)| # Images | # Building ... | SpaceNet6 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpaceNet6:
"""SpaceNet 6: Multi-Sensor All-Weather Mapping. `SpaceNet 6 <https://spacenet.ai/sn6-challenge/>`_ is a dataset of optical and SAR imagery over the city of Rotterdam. Collection features: +------------+---------------------+------------+-----------------------------+ | AOI | Area (km\... | stack_v2_sparse_classes_36k_train_018291 | 45,367 | permissive | [
{
"docstring": "Initialize a new SpaceNet 6 Dataset instance. Args: root: root directory where dataset can be found image: image selection which must be in [\"PAN\", \"RGBNIR\", \"PS-RGB\", \"PS-RGBNIR\", \"SAR-Intensity\"] transforms: a function/transform that takes input sample and its target as entry and ret... | 2 | null | Implement the Python class `SpaceNet6` described below.
Class description:
SpaceNet 6: Multi-Sensor All-Weather Mapping. `SpaceNet 6 <https://spacenet.ai/sn6-challenge/>`_ is a dataset of optical and SAR imagery over the city of Rotterdam. Collection features: +------------+---------------------+------------+---------... | Implement the Python class `SpaceNet6` described below.
Class description:
SpaceNet 6: Multi-Sensor All-Weather Mapping. `SpaceNet 6 <https://spacenet.ai/sn6-challenge/>`_ is a dataset of optical and SAR imagery over the city of Rotterdam. Collection features: +------------+---------------------+------------+---------... | 29985861614b3b93f9ef5389469ebb98570de7dd | <|skeleton|>
class SpaceNet6:
"""SpaceNet 6: Multi-Sensor All-Weather Mapping. `SpaceNet 6 <https://spacenet.ai/sn6-challenge/>`_ is a dataset of optical and SAR imagery over the city of Rotterdam. Collection features: +------------+---------------------+------------+-----------------------------+ | AOI | Area (km\... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpaceNet6:
"""SpaceNet 6: Multi-Sensor All-Weather Mapping. `SpaceNet 6 <https://spacenet.ai/sn6-challenge/>`_ is a dataset of optical and SAR imagery over the city of Rotterdam. Collection features: +------------+---------------------+------------+-----------------------------+ | AOI | Area (km\\ :sup:`2`\\)... | the_stack_v2_python_sparse | torchgeo/datasets/spacenet.py | microsoft/torchgeo | train | 1,724 |
1f756a73bc382f0648c514246878dbf34c35700b | [
"queryset = Like.objects.filter(sender=user, receiver_content_type=6).order_by('-timestamp')\ntotal = len(queryset)\nreturn {'title': '喜欢', 'data': [], 'total': total, 'nextpage': 0, 'category': 'liking'}",
"queryset = Video.objects.filter(user=user).order_by('-upload_time')\ncount = len(queryset)\nlist = queryse... | <|body_start_0|>
queryset = Like.objects.filter(sender=user, receiver_content_type=6).order_by('-timestamp')
total = len(queryset)
return {'title': '喜欢', 'data': [], 'total': total, 'nextpage': 0, 'category': 'liking'}
<|end_body_0|>
<|body_start_1|>
queryset = Video.objects.filter(user... | UserHomeSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserHomeSerializer:
def get_liking(self, user):
"""请求用户喜欢的视频, 这里不返回视频数据，只返回视频数量 :param user: :return:"""
<|body_0|>
def get_videos(self, user):
"""请求用户发布的视频, 最多返回前20条 :param user: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
queryset = L... | stack_v2_sparse_classes_36k_train_018292 | 2,802 | permissive | [
{
"docstring": "请求用户喜欢的视频, 这里不返回视频数据，只返回视频数量 :param user: :return:",
"name": "get_liking",
"signature": "def get_liking(self, user)"
},
{
"docstring": "请求用户发布的视频, 最多返回前20条 :param user: :return:",
"name": "get_videos",
"signature": "def get_videos(self, user)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016347 | Implement the Python class `UserHomeSerializer` described below.
Class description:
Implement the UserHomeSerializer class.
Method signatures and docstrings:
- def get_liking(self, user): 请求用户喜欢的视频, 这里不返回视频数据，只返回视频数量 :param user: :return:
- def get_videos(self, user): 请求用户发布的视频, 最多返回前20条 :param user: :return: | Implement the Python class `UserHomeSerializer` described below.
Class description:
Implement the UserHomeSerializer class.
Method signatures and docstrings:
- def get_liking(self, user): 请求用户喜欢的视频, 这里不返回视频数据，只返回视频数量 :param user: :return:
- def get_videos(self, user): 请求用户发布的视频, 最多返回前20条 :param user: :return:
<|skel... | fb64440ec7f84f08cf9cd706bec374fa357d7936 | <|skeleton|>
class UserHomeSerializer:
def get_liking(self, user):
"""请求用户喜欢的视频, 这里不返回视频数据，只返回视频数量 :param user: :return:"""
<|body_0|>
def get_videos(self, user):
"""请求用户发布的视频, 最多返回前20条 :param user: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserHomeSerializer:
def get_liking(self, user):
"""请求用户喜欢的视频, 这里不返回视频数据，只返回视频数量 :param user: :return:"""
queryset = Like.objects.filter(sender=user, receiver_content_type=6).order_by('-timestamp')
total = len(queryset)
return {'title': '喜欢', 'data': [], 'total': total, 'nextpag... | the_stack_v2_python_sparse | apps/user_operation/serializers.py | tuxi/video-hub | train | 18 | |
13193787a4c772bd897f3c182ed349a5a7d8818a | [
"try:\n self._dao.execute('DELETE FROM Hobby WHERE id = %s AND scheme_id = %s;', (hobby_id, scheme_id))\n succ = self._dao.rowcount()\n self._dao.commit()\n return succ\nexcept Exception as e:\n self._log.exception('Could not delete the hobby')\n raise e",
"try:\n self._dao.execute('INSERT IN... | <|body_start_0|>
try:
self._dao.execute('DELETE FROM Hobby WHERE id = %s AND scheme_id = %s;', (hobby_id, scheme_id))
succ = self._dao.rowcount()
self._dao.commit()
return succ
except Exception as e:
self._log.exception('Could not delete the ho... | HobbyModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HobbyModel:
def delete_hobby(self, scheme_id, hobby_id):
"""Given the hobby_id will delete the hobby"""
<|body_0|>
def insert_hobby(self, scheme_id, hobby):
"""Will insert an entry for a hobby into the database"""
<|body_1|>
def select_hobby(self, scheme... | stack_v2_sparse_classes_36k_train_018293 | 1,612 | no_license | [
{
"docstring": "Given the hobby_id will delete the hobby",
"name": "delete_hobby",
"signature": "def delete_hobby(self, scheme_id, hobby_id)"
},
{
"docstring": "Will insert an entry for a hobby into the database",
"name": "insert_hobby",
"signature": "def insert_hobby(self, scheme_id, ho... | 4 | stack_v2_sparse_classes_30k_val_000147 | Implement the Python class `HobbyModel` described below.
Class description:
Implement the HobbyModel class.
Method signatures and docstrings:
- def delete_hobby(self, scheme_id, hobby_id): Given the hobby_id will delete the hobby
- def insert_hobby(self, scheme_id, hobby): Will insert an entry for a hobby into the da... | Implement the Python class `HobbyModel` described below.
Class description:
Implement the HobbyModel class.
Method signatures and docstrings:
- def delete_hobby(self, scheme_id, hobby_id): Given the hobby_id will delete the hobby
- def insert_hobby(self, scheme_id, hobby): Will insert an entry for a hobby into the da... | 649a3c1cdcc90443f9561dfa1262ae3b0e970729 | <|skeleton|>
class HobbyModel:
def delete_hobby(self, scheme_id, hobby_id):
"""Given the hobby_id will delete the hobby"""
<|body_0|>
def insert_hobby(self, scheme_id, hobby):
"""Will insert an entry for a hobby into the database"""
<|body_1|>
def select_hobby(self, scheme... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HobbyModel:
def delete_hobby(self, scheme_id, hobby_id):
"""Given the hobby_id will delete the hobby"""
try:
self._dao.execute('DELETE FROM Hobby WHERE id = %s AND scheme_id = %s;', (hobby_id, scheme_id))
succ = self._dao.rowcount()
self._dao.commit()
... | the_stack_v2_python_sparse | flaskr/models/hobbymdl.py | nickpezzotti1/BuddySchemeWebApp | train | 2 | |
fa6949e1b87fd23c469e0ab92f31e23fc0f6bf43 | [
"layer_db = LayerDatabase(model)\nuse_cuda = False\npruner = SpatialSvdPruner()\ncost_calculator = SpatialSvdCostCalculator()\ncomp_ratio_rounding_algo = RankRounder(params.multiplicity, cost_calculator)\nif params.mode == SpatialSvdParameters.Mode.auto:\n greedy_params = params.mode_params.greedy_params\n co... | <|body_start_0|>
layer_db = LayerDatabase(model)
use_cuda = False
pruner = SpatialSvdPruner()
cost_calculator = SpatialSvdCostCalculator()
comp_ratio_rounding_algo = RankRounder(params.multiplicity, cost_calculator)
if params.mode == SpatialSvdParameters.Mode.auto:
... | Factory to construct various aimet model compression classes based on a scheme | CompressionFactory | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompressionFactory:
"""Factory to construct various aimet model compression classes based on a scheme"""
def create_spatial_svd_algo(cls, model: tf.keras.Model, eval_callback: EvalFunction, eval_iterations: int, cost_metric: CostMetric, params: SpatialSvdParameters, bokeh_session: BokehServe... | stack_v2_sparse_classes_36k_train_018294 | 7,032 | permissive | [
{
"docstring": "Factory method to construct SpatialSvdCompressionAlgo :param model: Keras model to compress :param eval_callback: Evaluation callback for the model :param eval_iterations: Evaluation iterations :param cost_metric: Cost metric (mac or memory) :param params: Spatial SVD compression parameters :par... | 2 | stack_v2_sparse_classes_30k_train_016673 | Implement the Python class `CompressionFactory` described below.
Class description:
Factory to construct various aimet model compression classes based on a scheme
Method signatures and docstrings:
- def create_spatial_svd_algo(cls, model: tf.keras.Model, eval_callback: EvalFunction, eval_iterations: int, cost_metric:... | Implement the Python class `CompressionFactory` described below.
Class description:
Factory to construct various aimet model compression classes based on a scheme
Method signatures and docstrings:
- def create_spatial_svd_algo(cls, model: tf.keras.Model, eval_callback: EvalFunction, eval_iterations: int, cost_metric:... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class CompressionFactory:
"""Factory to construct various aimet model compression classes based on a scheme"""
def create_spatial_svd_algo(cls, model: tf.keras.Model, eval_callback: EvalFunction, eval_iterations: int, cost_metric: CostMetric, params: SpatialSvdParameters, bokeh_session: BokehServe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompressionFactory:
"""Factory to construct various aimet model compression classes based on a scheme"""
def create_spatial_svd_algo(cls, model: tf.keras.Model, eval_callback: EvalFunction, eval_iterations: int, cost_metric: CostMetric, params: SpatialSvdParameters, bokeh_session: BokehServerSession=None... | the_stack_v2_python_sparse | TrainingExtensions/tensorflow/src/python/aimet_tensorflow/keras/compression_factory.py | quic/aimet | train | 1,676 |
17148629a1a715097c551f0e78b2141c82ffdcd1 | [
"query = DuesPayment.query.filter_by(user_id=user.id)\nif not include_void:\n query = query.filter_by(void=False)\ndues_payments = query.all()\nif not include_exceptional:\n dues_payments = filter(lambda p: p.exception is None, dues_payments)\nif not include_invisible:\n dues_payments = filter(lambda p: p.... | <|body_start_0|>
query = DuesPayment.query.filter_by(user_id=user.id)
if not include_void:
query = query.filter_by(void=False)
dues_payments = query.all()
if not include_exceptional:
dues_payments = filter(lambda p: p.exception is None, dues_payments)
if n... | Provides high-level methods for managing member dues. | DuesService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DuesService:
"""Provides high-level methods for managing member dues."""
def get_dues_payments(self, user, include_void=False, include_exceptional=False, include_invisible=False):
"""Get all dues payments made by a user. :param user: the user to search for dues payments from :param i... | stack_v2_sparse_classes_36k_train_018295 | 3,876 | no_license | [
{
"docstring": "Get all dues payments made by a user. :param user: the user to search for dues payments from :param include_void: if True payments marked as void will be included in the results, if False they will not :param include_exceptional: if True payments with a non-None exceptional property will be incl... | 2 | stack_v2_sparse_classes_30k_train_010752 | Implement the Python class `DuesService` described below.
Class description:
Provides high-level methods for managing member dues.
Method signatures and docstrings:
- def get_dues_payments(self, user, include_void=False, include_exceptional=False, include_invisible=False): Get all dues payments made by a user. :param... | Implement the Python class `DuesService` described below.
Class description:
Provides high-level methods for managing member dues.
Method signatures and docstrings:
- def get_dues_payments(self, user, include_void=False, include_exceptional=False, include_invisible=False): Get all dues payments made by a user. :param... | 28cf2be6986045d68f12a647808b6c7a3446a50e | <|skeleton|>
class DuesService:
"""Provides high-level methods for managing member dues."""
def get_dues_payments(self, user, include_void=False, include_exceptional=False, include_invisible=False):
"""Get all dues payments made by a user. :param user: the user to search for dues payments from :param i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DuesService:
"""Provides high-level methods for managing member dues."""
def get_dues_payments(self, user, include_void=False, include_exceptional=False, include_invisible=False):
"""Get all dues payments made by a user. :param user: the user to search for dues payments from :param include_void: ... | the_stack_v2_python_sparse | dismember/dues.py | splatspace/dismember | train | 2 |
79d49aea9d87b6460e6df937a2e497fe637e2e91 | [
"if request.user.has_perm(CHANGE_TEAM):\n user = UserProfile.objects.get(pk=request.data['id_user'])\n team = Team.objects.get(pk=request.data['id_team'])\n team.user_set.add(user)\n logger.info('{user} ADDED {member} to {team}'.format(user=request.user, member=repr(user), team=repr(team)))\n return ... | <|body_start_0|>
if request.user.has_perm(CHANGE_TEAM):
user = UserProfile.objects.get(pk=request.data['id_user'])
team = Team.objects.get(pk=request.data['id_team'])
team.user_set.add(user)
logger.info('{user} ADDED {member} to {team}'.format(user=request.user, m... | # Add and remove users from team. Parameters : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. POST request : add a user to a team and send HTTP 201, must contain id_user (the id of the user to add, int) and id_team (the id of the team where the user will be ad... | AddUserToTeam | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddUserToTeam:
"""# Add and remove users from team. Parameters : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. POST request : add a user to a team and send HTTP 201, must contain id_user (the id of the user to add, int) and id_team (the... | stack_v2_sparse_classes_36k_train_018296 | 10,635 | permissive | [
{
"docstring": "Implement the POST method. ``` Parameters : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. POST request : add a user to a team and send HTTP 201, must contain id_user (the id of the user to add, int) and id_team (the id of the team wher... | 2 | stack_v2_sparse_classes_30k_train_008919 | Implement the Python class `AddUserToTeam` described below.
Class description:
# Add and remove users from team. Parameters : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. POST request : add a user to a team and send HTTP 201, must contain id_user (the id of... | Implement the Python class `AddUserToTeam` described below.
Class description:
# Add and remove users from team. Parameters : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. POST request : add a user to a team and send HTTP 201, must contain id_user (the id of... | 56511ebac83a5dc1fb8768a98bc675e88530a447 | <|skeleton|>
class AddUserToTeam:
"""# Add and remove users from team. Parameters : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. POST request : add a user to a team and send HTTP 201, must contain id_user (the id of the user to add, int) and id_team (the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddUserToTeam:
"""# Add and remove users from team. Parameters : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. POST request : add a user to a team and send HTTP 201, must contain id_user (the id of the user to add, int) and id_team (the id of the te... | the_stack_v2_python_sparse | usersmanagement/views/views_team.py | Open-CMMS/openCMMS_backend | train | 4 |
a9c58b23c11564becd9e282401af5923ff01a27b | [
"l = 0\nnode = head\nwhile node:\n node = node.next\n l += 1\n\ndef reverse(node):\n pre = None\n while node:\n pre, node.next, node = (node, pre, node.next)\n return pre\ni = l // 2\nnode = head\nwhile i > 0:\n node = node.next\n i -= 1\nnode = reverse(node)\nwhile node:\n if node.va... | <|body_start_0|>
l = 0
node = head
while node:
node = node.next
l += 1
def reverse(node):
pre = None
while node:
pre, node.next, node = (node, pre, node.next)
return pre
i = l // 2
node = head
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head: Optional[ListNode]) -> bool:
"""2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9"""
<|body_0|>
def isPalindrome2(self, hea... | stack_v2_sparse_classes_36k_train_018297 | 3,203 | permissive | [
{
"docstring": "2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head: Optional[ListNode]) -> bool"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_015839 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: Optional[ListNode]) -> bool: 2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: Optional[ListNode]) -> bool: 2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is ... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def isPalindrome(self, head: Optional[ListNode]) -> bool:
"""2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9"""
<|body_0|>
def isPalindrome2(self, hea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, head: Optional[ListNode]) -> bool:
"""2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9"""
l = 0
node = head
while node:
... | the_stack_v2_python_sparse | src/234-PalindromeLinkedList.py | Jiezhi/myleetcode | train | 1 | |
8bfeeabea7242fe99e897eb2f6d09239aacf8dd6 | [
"args = self.validate_input(args)\nvargs = vars(args)\nIS = vargs.pop('IS')\nGF = vargs.pop('gene_file')\nlogging.debug('Loading genes')\nscaff_2_gene_database, scaff2gene2sequence = parse_genes(GF, **vargs)\nGdbP = pd.concat([x for x in scaff_2_gene_database.values()])\nname2result = calculate_gene_metrics(IS, Gdb... | <|body_start_0|>
args = self.validate_input(args)
vargs = vars(args)
IS = vargs.pop('IS')
GF = vargs.pop('gene_file')
logging.debug('Loading genes')
scaff_2_gene_database, scaff2gene2sequence = parse_genes(GF, **vargs)
GdbP = pd.concat([x for x in scaff_2_gene_dat... | The command line access point to the program | Controller | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""The command line access point to the program"""
def main(self, args):
"""The main method when run on the command line"""
<|body_0|>
def validate_input(self, args):
"""Validate and mess with the arguments a bit"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_018298 | 31,954 | permissive | [
{
"docstring": "The main method when run on the command line",
"name": "main",
"signature": "def main(self, args)"
},
{
"docstring": "Validate and mess with the arguments a bit",
"name": "validate_input",
"signature": "def validate_input(self, args)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014217 | Implement the Python class `Controller` described below.
Class description:
The command line access point to the program
Method signatures and docstrings:
- def main(self, args): The main method when run on the command line
- def validate_input(self, args): Validate and mess with the arguments a bit | Implement the Python class `Controller` described below.
Class description:
The command line access point to the program
Method signatures and docstrings:
- def main(self, args): The main method when run on the command line
- def validate_input(self, args): Validate and mess with the arguments a bit
<|skeleton|>
cla... | 748ef37f1e3449e290f4b5eb574f6d0a3404daba | <|skeleton|>
class Controller:
"""The command line access point to the program"""
def main(self, args):
"""The main method when run on the command line"""
<|body_0|>
def validate_input(self, args):
"""Validate and mess with the arguments a bit"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
"""The command line access point to the program"""
def main(self, args):
"""The main method when run on the command line"""
args = self.validate_input(args)
vargs = vars(args)
IS = vargs.pop('IS')
GF = vargs.pop('gene_file')
logging.debug('Loadi... | the_stack_v2_python_sparse | inStrain/GeneProfile.py | MrOlm/inStrain | train | 103 |
b36de3369a3742eea67c70d68adb72794fc78a7f | [
"self._device = device\nself._attr_unique_id = device.serial_number\nself._attr_device_info = DeviceInfo(identifiers={(KALEIDESCAPE_DOMAIN, self._device.serial_number)}, name=f'{KALEIDESCAPE_NAME} {device.system.friendly_name}', model=self._device.system.type, manufacturer=KALEIDESCAPE_NAME, sw_version=f'{self._dev... | <|body_start_0|>
self._device = device
self._attr_unique_id = device.serial_number
self._attr_device_info = DeviceInfo(identifiers={(KALEIDESCAPE_DOMAIN, self._device.serial_number)}, name=f'{KALEIDESCAPE_NAME} {device.system.friendly_name}', model=self._device.system.type, manufacturer=KALEIDES... | Defines a base Kaleidescape entity. | KaleidescapeEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KaleidescapeEntity:
"""Defines a base Kaleidescape entity."""
def __init__(self, device: KaleidescapeDevice) -> None:
"""Initialize entity."""
<|body_0|>
async def async_added_to_hass(self) -> None:
"""Register update listener."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_018299 | 1,702 | permissive | [
{
"docstring": "Initialize entity.",
"name": "__init__",
"signature": "def __init__(self, device: KaleidescapeDevice) -> None"
},
{
"docstring": "Register update listener.",
"name": "async_added_to_hass",
"signature": "async def async_added_to_hass(self) -> None"
}
] | 2 | null | Implement the Python class `KaleidescapeEntity` described below.
Class description:
Defines a base Kaleidescape entity.
Method signatures and docstrings:
- def __init__(self, device: KaleidescapeDevice) -> None: Initialize entity.
- async def async_added_to_hass(self) -> None: Register update listener. | Implement the Python class `KaleidescapeEntity` described below.
Class description:
Defines a base Kaleidescape entity.
Method signatures and docstrings:
- def __init__(self, device: KaleidescapeDevice) -> None: Initialize entity.
- async def async_added_to_hass(self) -> None: Register update listener.
<|skeleton|>
... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class KaleidescapeEntity:
"""Defines a base Kaleidescape entity."""
def __init__(self, device: KaleidescapeDevice) -> None:
"""Initialize entity."""
<|body_0|>
async def async_added_to_hass(self) -> None:
"""Register update listener."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KaleidescapeEntity:
"""Defines a base Kaleidescape entity."""
def __init__(self, device: KaleidescapeDevice) -> None:
"""Initialize entity."""
self._device = device
self._attr_unique_id = device.serial_number
self._attr_device_info = DeviceInfo(identifiers={(KALEIDESCAPE_D... | the_stack_v2_python_sparse | homeassistant/components/kaleidescape/entity.py | home-assistant/core | train | 35,501 |
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