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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d302d4d888939057c62c35405668e750e665f10b | [
"if self.panel_url:\n return '{}&fullscreen'.format(self.panel_url.replace('dashboard-solo', 'dashboard'))\nreturn None",
"panel_url = self.panel_url.replace(urlparse.urljoin(self.grafana_instance.url, '/'), '')\nrendered_image_url = urlparse.urljoin('render/', panel_url)\nrendered_image_url = '{}&width={}&hei... | <|body_start_0|>
if self.panel_url:
return '{}&fullscreen'.format(self.panel_url.replace('dashboard-solo', 'dashboard'))
return None
<|end_body_0|>
<|body_start_1|>
panel_url = self.panel_url.replace(urlparse.urljoin(self.grafana_instance.url, '/'), '')
rendered_image_url = ... | Data about a Grafana panel. | GrafanaPanel | [
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GrafanaPanel:
"""Data about a Grafana panel."""
def modifiable_url(self):
"""Url with modifiable time range, dashboard link, etc"""
<|body_0|>
def get_rendered_image(self):
"""Get a .png image of this panel"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_006100 | 5,474 | permissive | [
{
"docstring": "Url with modifiable time range, dashboard link, etc",
"name": "modifiable_url",
"signature": "def modifiable_url(self)"
},
{
"docstring": "Get a .png image of this panel",
"name": "get_rendered_image",
"signature": "def get_rendered_image(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011705 | Implement the Python class `GrafanaPanel` described below.
Class description:
Data about a Grafana panel.
Method signatures and docstrings:
- def modifiable_url(self): Url with modifiable time range, dashboard link, etc
- def get_rendered_image(self): Get a .png image of this panel | Implement the Python class `GrafanaPanel` described below.
Class description:
Data about a Grafana panel.
Method signatures and docstrings:
- def modifiable_url(self): Url with modifiable time range, dashboard link, etc
- def get_rendered_image(self): Get a .png image of this panel
<|skeleton|>
class GrafanaPanel:
... | 61bf94af813b026d29288c6e3967d2225fdc4686 | <|skeleton|>
class GrafanaPanel:
"""Data about a Grafana panel."""
def modifiable_url(self):
"""Url with modifiable time range, dashboard link, etc"""
<|body_0|>
def get_rendered_image(self):
"""Get a .png image of this panel"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GrafanaPanel:
"""Data about a Grafana panel."""
def modifiable_url(self):
"""Url with modifiable time range, dashboard link, etc"""
if self.panel_url:
return '{}&fullscreen'.format(self.panel_url.replace('dashboard-solo', 'dashboard'))
return None
def get_rendered... | the_stack_v2_python_sparse | cabot/metricsapp/models/grafana.py | Affirm/cabot | train | 13 |
e8936994808e6f1a18a7dabbcf92d1570ab6efee | [
"super(ParameterizedStrategy, self).__init__(network)\nself.matrix = FeatureMatrix(network)\nself.bound = bound\nself.label = None\nself.covered_count = None\nself.objective_covered = None\nself.strategy = np.random.uniform(-self.bound, self.bound, size=FeatureMatrix.TOTAL_FEATURES)",
"scores = self.matrix.dot(se... | <|body_start_0|>
super(ParameterizedStrategy, self).__init__(network)
self.matrix = FeatureMatrix(network)
self.bound = bound
self.label = None
self.covered_count = None
self.objective_covered = None
self.strategy = np.random.uniform(-self.bound, self.bound, size=... | A strategy that uses a parameterized selection strategy. Parameterized neuron selection strategy is a strategy that parameterized neurons and scores with a selection vector. Please see the following paper for more details: Effective White-Box Testing for Deep Neural Networks with Adaptive Neuron-Selection Strategy http... | ParameterizedStrategy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParameterizedStrategy:
"""A strategy that uses a parameterized selection strategy. Parameterized neuron selection strategy is a strategy that parameterized neurons and scores with a selection vector. Please see the following paper for more details: Effective White-Box Testing for Deep Neural Netw... | stack_v2_sparse_classes_36k_train_006101 | 17,144 | permissive | [
{
"docstring": "Create a parameterized strategy, and initialize its variables. Args: network: A wrapped Keras model with `adapt.Network`. bound: A floating point number indicates the absolute value of minimum and maximum bounds. Example: >>> from adapt import Network >>> from adapt.strategy import Parameterized... | 4 | stack_v2_sparse_classes_30k_test_001158 | Implement the Python class `ParameterizedStrategy` described below.
Class description:
A strategy that uses a parameterized selection strategy. Parameterized neuron selection strategy is a strategy that parameterized neurons and scores with a selection vector. Please see the following paper for more details: Effective... | Implement the Python class `ParameterizedStrategy` described below.
Class description:
A strategy that uses a parameterized selection strategy. Parameterized neuron selection strategy is a strategy that parameterized neurons and scores with a selection vector. Please see the following paper for more details: Effective... | 0b801d2d2e828ac480d1097cb3bdd82b1e25c15b | <|skeleton|>
class ParameterizedStrategy:
"""A strategy that uses a parameterized selection strategy. Parameterized neuron selection strategy is a strategy that parameterized neurons and scores with a selection vector. Please see the following paper for more details: Effective White-Box Testing for Deep Neural Netw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParameterizedStrategy:
"""A strategy that uses a parameterized selection strategy. Parameterized neuron selection strategy is a strategy that parameterized neurons and scores with a selection vector. Please see the following paper for more details: Effective White-Box Testing for Deep Neural Networks with Ada... | the_stack_v2_python_sparse | code/deep/ReMoS/CV_adv/DNNtest/strategy/adapt.py | jindongwang/transferlearning | train | 12,773 |
d676b2e26dfe293749e8ee58a2232fdcd179f829 | [
"a = array([(1.0, 0), (0.5, sqrt(3.0) / 2)])\nsuper(Triangular_Lattice, self).__init__(a=a, catoms=catoms, name='triangular', N=N)\nc6vg = C6vGroup()\nself.usegroup(c6vg)",
"ks = super(Triangular_Lattice, self).kspace\nM0 = ks.b[1] / 2.0\nK0 = (ks.b[0] + 2 * ks.b[1]) / 3.0\nc6vg = C6vGroup()\nM = []\nK = []\nfor ... | <|body_start_0|>
a = array([(1.0, 0), (0.5, sqrt(3.0) / 2)])
super(Triangular_Lattice, self).__init__(a=a, catoms=catoms, name='triangular', N=N)
c6vg = C6vGroup()
self.usegroup(c6vg)
<|end_body_0|>
<|body_start_1|>
ks = super(Triangular_Lattice, self).kspace
M0 = ks.b[1... | Triangular Lattice, using C6v Group. Construct ---------------- Triangular_Lattice(N,catoms=[(0.,0.)]) | Triangular_Lattice | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Triangular_Lattice:
"""Triangular Lattice, using C6v Group. Construct ---------------- Triangular_Lattice(N,catoms=[(0.,0.)])"""
def __init__(self, N, catoms=[(0.0, 0.0)]):
"""Basic information of Triangular Lattice"""
<|body_0|>
def kspace(self):
"""Get the <KSp... | stack_v2_sparse_classes_36k_train_006102 | 5,854 | permissive | [
{
"docstring": "Basic information of Triangular Lattice",
"name": "__init__",
"signature": "def __init__(self, N, catoms=[(0.0, 0.0)])"
},
{
"docstring": "Get the <KSpace> instance.",
"name": "kspace",
"signature": "def kspace(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013354 | Implement the Python class `Triangular_Lattice` described below.
Class description:
Triangular Lattice, using C6v Group. Construct ---------------- Triangular_Lattice(N,catoms=[(0.,0.)])
Method signatures and docstrings:
- def __init__(self, N, catoms=[(0.0, 0.0)]): Basic information of Triangular Lattice
- def kspac... | Implement the Python class `Triangular_Lattice` described below.
Class description:
Triangular Lattice, using C6v Group. Construct ---------------- Triangular_Lattice(N,catoms=[(0.,0.)])
Method signatures and docstrings:
- def __init__(self, N, catoms=[(0.0, 0.0)]): Basic information of Triangular Lattice
- def kspac... | 88be712b2d17603f7a3c38836dabe8dbdee2aba3 | <|skeleton|>
class Triangular_Lattice:
"""Triangular Lattice, using C6v Group. Construct ---------------- Triangular_Lattice(N,catoms=[(0.,0.)])"""
def __init__(self, N, catoms=[(0.0, 0.0)]):
"""Basic information of Triangular Lattice"""
<|body_0|>
def kspace(self):
"""Get the <KSp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Triangular_Lattice:
"""Triangular Lattice, using C6v Group. Construct ---------------- Triangular_Lattice(N,catoms=[(0.,0.)])"""
def __init__(self, N, catoms=[(0.0, 0.0)]):
"""Basic information of Triangular Lattice"""
a = array([(1.0, 0), (0.5, sqrt(3.0) / 2)])
super(Triangular_L... | the_stack_v2_python_sparse | giggleliu/tba/lattice/latticelib.py | Lynn-015/NJU_DMRG | train | 2 |
0f8885626266ce0606f249d42c897092424da552 | [
"parser = argparse.ArgumentParser()\nparser.add_argument('--loglevel', dest='loglevel', nargs='?', type=int, default=default_loglevel, choices=ArgumentParser.CHOICES)\nreturn parser.parse_args()",
"parser = argparse.ArgumentParser()\nparser.add_argument('--house', dest='house')\nparser.add_argument('--loglevel', ... | <|body_start_0|>
parser = argparse.ArgumentParser()
parser.add_argument('--loglevel', dest='loglevel', nargs='?', type=int, default=default_loglevel, choices=ArgumentParser.CHOICES)
return parser.parse_args()
<|end_body_0|>
<|body_start_1|>
parser = argparse.ArgumentParser()
par... | ArgumentParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArgumentParser:
def logging_parser(default_loglevel=logging.DEBUG):
"""Gets a default argument parser including the house id and logging level :return:"""
<|body_0|>
def house_parser(default_loglevel=logging.DEBUG):
"""Gets a default argument parser including the hou... | stack_v2_sparse_classes_36k_train_006103 | 4,097 | permissive | [
{
"docstring": "Gets a default argument parser including the house id and logging level :return:",
"name": "logging_parser",
"signature": "def logging_parser(default_loglevel=logging.DEBUG)"
},
{
"docstring": "Gets a default argument parser including the house id and logging level :return:",
... | 5 | stack_v2_sparse_classes_30k_train_003321 | Implement the Python class `ArgumentParser` described below.
Class description:
Implement the ArgumentParser class.
Method signatures and docstrings:
- def logging_parser(default_loglevel=logging.DEBUG): Gets a default argument parser including the house id and logging level :return:
- def house_parser(default_loglev... | Implement the Python class `ArgumentParser` described below.
Class description:
Implement the ArgumentParser class.
Method signatures and docstrings:
- def logging_parser(default_loglevel=logging.DEBUG): Gets a default argument parser including the house id and logging level :return:
- def house_parser(default_loglev... | 981329bf85b5c1e8d8481efc40a90d5a676944df | <|skeleton|>
class ArgumentParser:
def logging_parser(default_loglevel=logging.DEBUG):
"""Gets a default argument parser including the house id and logging level :return:"""
<|body_0|>
def house_parser(default_loglevel=logging.DEBUG):
"""Gets a default argument parser including the hou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArgumentParser:
def logging_parser(default_loglevel=logging.DEBUG):
"""Gets a default argument parser including the house id and logging level :return:"""
parser = argparse.ArgumentParser()
parser.add_argument('--loglevel', dest='loglevel', nargs='?', type=int, default=default_loglevel... | the_stack_v2_python_sparse | sphere_plugins/sphere/utils/utils.py | IRC-SPHERE/SPHERE-HyperStream | train | 4 | |
570ea037b6f647fa98a805432505a45b2fd08f99 | [
"if root == None:\n return 'null'\nqueue = [root]\nres = ''\nindex = 0\nwhile index != len(queue):\n node = queue[index]\n if node != None:\n res += str(node.val)\n queue.append(node.left)\n queue.append(node.right)\n else:\n res += 'null'\n res += ','\n index += 1\nret... | <|body_start_0|>
if root == None:
return 'null'
queue = [root]
res = ''
index = 0
while index != len(queue):
node = queue[index]
if node != None:
res += str(node.val)
queue.append(node.left)
queue... | 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_006104 | 1,982 | 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:... | 2fda37371f1c5afcab80214580e8e5fd72b48a3b | <|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 == None:
return 'null'
queue = [root]
res = ''
index = 0
while index != len(queue):
node = queue[index]
if nod... | the_stack_v2_python_sparse | others/剑指 Offer/37/main.py | pauvrepetit/leetcode | train | 0 | |
fa6e62edb56a37cb380edc14e6d8c0cc11ac5fec | [
"if len(matrix):\n r, c = (len(matrix), len(matrix[0]))\n self.val = matrix\n for i in range(r):\n for j in range(1, c):\n self.val[i][j] += self.val[i][j - 1]\nelse:\n self.val = 0",
"ret_sum = 0\nif self.val == 0:\n return 0\nfor r in range(row1, row2 + 1):\n if col1 == 0:\n ... | <|body_start_0|>
if len(matrix):
r, c = (len(matrix), len(matrix[0]))
self.val = matrix
for i in range(r):
for j in range(1, c):
self.val[i][j] += self.val[i][j - 1]
else:
self.val = 0
<|end_body_0|>
<|body_start_1|>
... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_006105 | 1,027 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | null | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | 5222394470adf3522c11b11e59d05b0ddff09e20 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if len(matrix):
r, c = (len(matrix), len(matrix[0]))
self.val = matrix
for i in range(r):
for j in range(1, c):
self.val[i][j] += self.val[i][j - 1... | the_stack_v2_python_sparse | mycode/dynamic programming/Range Sum Query 2D - Immutable.py | guoguanglu/leetcode | train | 0 | |
41fb1c2d094a0c2c1c32909c6105440436191b5f | [
"def decode(s, i):\n \"\"\"Decode string s from position i.\n :param s: string to be decoded until ']' or end of the string.\n :param i: start position.\n :return: decoded string and the final position.\n \"\"\"\n ans, k = ('', '')\n while i < len(s):\n c ... | <|body_start_0|>
def decode(s, i):
"""Decode string s from position i.
:param s: string to be decoded until ']' or end of the string.
:param i: start position.
:return: decoded string and the final position.
"""
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def decodeString_v1(self, s: str) -> str:
"""Use recurssion. Similar to a DFS traversal."""
<|body_0|>
def decodeString_v2(self, s: str) -> str:
"""Use stack and loop. Note that using a stack is almost identical to using recurssion."""
<|body_1|>
<... | stack_v2_sparse_classes_36k_train_006106 | 3,069 | no_license | [
{
"docstring": "Use recurssion. Similar to a DFS traversal.",
"name": "decodeString_v1",
"signature": "def decodeString_v1(self, s: str) -> str"
},
{
"docstring": "Use stack and loop. Note that using a stack is almost identical to using recurssion.",
"name": "decodeString_v2",
"signature... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString_v1(self, s: str) -> str: Use recurssion. Similar to a DFS traversal.
- def decodeString_v2(self, s: str) -> str: Use stack and loop. Note that using a stack is a... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString_v1(self, s: str) -> str: Use recurssion. Similar to a DFS traversal.
- def decodeString_v2(self, s: str) -> str: Use stack and loop. Note that using a stack is a... | 97a2386f5e3adbd7138fd123810c3232bdf7f622 | <|skeleton|>
class Solution:
def decodeString_v1(self, s: str) -> str:
"""Use recurssion. Similar to a DFS traversal."""
<|body_0|>
def decodeString_v2(self, s: str) -> str:
"""Use stack and loop. Note that using a stack is almost identical to using recurssion."""
<|body_1|>
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def decodeString_v1(self, s: str) -> str:
"""Use recurssion. Similar to a DFS traversal."""
def decode(s, i):
"""Decode string s from position i.
:param s: string to be decoded until ']' or end of the string.
:param i: start positio... | the_stack_v2_python_sparse | python3/trees_and_graphs/decode_string.py | victorchu/algorithms | train | 0 | |
7f38b4005a156acd239974c2aa1ee31a3a3e6dc4 | [
"bot_messages = []\nbrian_bot = UserUtils.get_brian_bot()\nfor u1, u2 in [[user1, user2], [user2, user1]]:\n chat = ChatUtils.find_chat([brian_bot, u1])\n message = models.Message.objects.create(chat=chat, text=message_text.format(user1=u1.first_name, user2=u2.first_name), sender=brian_bot)\n bot_messages.... | <|body_start_0|>
bot_messages = []
brian_bot = UserUtils.get_brian_bot()
for u1, u2 in [[user1, user2], [user2, user1]]:
chat = ChatUtils.find_chat([brian_bot, u1])
message = models.Message.objects.create(chat=chat, text=message_text.format(user1=u1.first_name, user2=u2.f... | Utilities for chats. | ChatUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChatUtils:
"""Utilities for chats."""
def create_bot_chat_creation_messages(user1, user2, message_text):
"""Creates messages from Brian Bot to two users that a chat between them has been created. No push notifications are sent for these message. :param user1: A user. :param user2: A ... | stack_v2_sparse_classes_36k_train_006107 | 2,787 | permissive | [
{
"docstring": "Creates messages from Brian Bot to two users that a chat between them has been created. No push notifications are sent for these message. :param user1: A user. :param user2: A user. :param message_text: The bot message to notify users of the new match. Can contain placeholders {user1} and {user2... | 3 | stack_v2_sparse_classes_30k_train_021568 | Implement the Python class `ChatUtils` described below.
Class description:
Utilities for chats.
Method signatures and docstrings:
- def create_bot_chat_creation_messages(user1, user2, message_text): Creates messages from Brian Bot to two users that a chat between them has been created. No push notifications are sent ... | Implement the Python class `ChatUtils` described below.
Class description:
Utilities for chats.
Method signatures and docstrings:
- def create_bot_chat_creation_messages(user1, user2, message_text): Creates messages from Brian Bot to two users that a chat between them has been created. No push notifications are sent ... | 90ed2592f30afcb454111148a8121e1b9820e507 | <|skeleton|>
class ChatUtils:
"""Utilities for chats."""
def create_bot_chat_creation_messages(user1, user2, message_text):
"""Creates messages from Brian Bot to two users that a chat between them has been created. No push notifications are sent for these message. :param user1: A user. :param user2: A ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChatUtils:
"""Utilities for chats."""
def create_bot_chat_creation_messages(user1, user2, message_text):
"""Creates messages from Brian Bot to two users that a chat between them has been created. No push notifications are sent for these message. :param user1: A user. :param user2: A user. :param ... | the_stack_v2_python_sparse | friends/utilities/chat_utils.py | kairathmann/friends-backend | train | 0 |
9bb37a21fb0424dd3adda1339a0cead1e51e7ebd | [
"opt = input('choose game method:\\n' + ' 1) built-in puzzle\\n' + ' 2) rng puzzle\\n' + ' 3) user puzzle\\n')\nif opt == 1:\n puzzle = input('select puzzle (1-2):')\n if puzzle == 1:\n self.state = np.array([[0, 3, 0, 2, 9, 7, 0, 0, 4], [5, 0, 0, 0, 3, 0, 6, 2, 7], [0, 0, 0, 0, 6, 0, 0, 9, 0], [0, 0, ... | <|body_start_0|>
opt = input('choose game method:\n' + ' 1) built-in puzzle\n' + ' 2) rng puzzle\n' + ' 3) user puzzle\n')
if opt == 1:
puzzle = input('select puzzle (1-2):')
if puzzle == 1:
self.state = np.array([[0, 3, 0, 2, 9, 7, 0, 0, 4], [5, 0, 0, 0, 3, 0, 6,... | sudoku game state and solver class | Sudoku | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sudoku:
"""sudoku game state and solver class"""
def __init__(self):
"""initialize the board and vars"""
<|body_0|>
def solve(self):
"""solver loop that checks, steps, and prints"""
<|body_1|>
def checkboard(self):
"""iterate through board wr... | stack_v2_sparse_classes_36k_train_006108 | 4,686 | permissive | [
{
"docstring": "initialize the board and vars",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "solver loop that checks, steps, and prints",
"name": "solve",
"signature": "def solve(self)"
},
{
"docstring": "iterate through board writing potentials dict",... | 6 | stack_v2_sparse_classes_30k_train_010087 | Implement the Python class `Sudoku` described below.
Class description:
sudoku game state and solver class
Method signatures and docstrings:
- def __init__(self): initialize the board and vars
- def solve(self): solver loop that checks, steps, and prints
- def checkboard(self): iterate through board writing potential... | Implement the Python class `Sudoku` described below.
Class description:
sudoku game state and solver class
Method signatures and docstrings:
- def __init__(self): initialize the board and vars
- def solve(self): solver loop that checks, steps, and prints
- def checkboard(self): iterate through board writing potential... | 33aec6dc0bada8d9fe26a6df73d45eaf34e509c6 | <|skeleton|>
class Sudoku:
"""sudoku game state and solver class"""
def __init__(self):
"""initialize the board and vars"""
<|body_0|>
def solve(self):
"""solver loop that checks, steps, and prints"""
<|body_1|>
def checkboard(self):
"""iterate through board wr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sudoku:
"""sudoku game state and solver class"""
def __init__(self):
"""initialize the board and vars"""
opt = input('choose game method:\n' + ' 1) built-in puzzle\n' + ' 2) rng puzzle\n' + ' 3) user puzzle\n')
if opt == 1:
puzzle = input('select puzzle (1-2):')
... | the_stack_v2_python_sparse | python/dsbook/1.17-exercises/sudoku.py | jonjon33/sandbox | train | 0 |
ea8c39bc97a8e417a50e5e3755f7ac3f1c4180d4 | [
"self._logger = logging.getLogger('stone.compiler')\nself.api = api\nself.backend_module = backend_module\nself.backend_args = backend_args\nself.build_path = build_path\nif clean_build and os.path.exists(self.build_path):\n logging.info('Cleaning existing build directory %s...', self.build_path)\n shutil.rmt... | <|body_start_0|>
self._logger = logging.getLogger('stone.compiler')
self.api = api
self.backend_module = backend_module
self.backend_args = backend_args
self.build_path = build_path
if clean_build and os.path.exists(self.build_path):
logging.info('Cleaning exi... | Applies a collection of backends found in a single backend module to an API specification. | Compiler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Compiler:
"""Applies a collection of backends found in a single backend module to an API specification."""
def __init__(self, api, backend_module, backend_args, build_path, clean_build=False):
"""Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param back... | stack_v2_sparse_classes_36k_train_006109 | 4,380 | permissive | [
{
"docstring": "Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param backend_module: Python module that contains at least one top-level class definition that descends from a :class:`stone.backend.Backend`. :param list(str) backend_args: A list of command-line arguments to pass to ... | 5 | stack_v2_sparse_classes_30k_train_020954 | Implement the Python class `Compiler` described below.
Class description:
Applies a collection of backends found in a single backend module to an API specification.
Method signatures and docstrings:
- def __init__(self, api, backend_module, backend_args, build_path, clean_build=False): Creates a Compiler. :param ston... | Implement the Python class `Compiler` described below.
Class description:
Applies a collection of backends found in a single backend module to an API specification.
Method signatures and docstrings:
- def __init__(self, api, backend_module, backend_args, build_path, clean_build=False): Creates a Compiler. :param ston... | 0c9ceb748ac4dcdea5ff69c97704daccdcb7e60e | <|skeleton|>
class Compiler:
"""Applies a collection of backends found in a single backend module to an API specification."""
def __init__(self, api, backend_module, backend_args, build_path, clean_build=False):
"""Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param back... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Compiler:
"""Applies a collection of backends found in a single backend module to an API specification."""
def __init__(self, api, backend_module, backend_args, build_path, clean_build=False):
"""Creates a Compiler. :param stone.ir.Api api: A Stone description of the API. :param backend_module: P... | the_stack_v2_python_sparse | stone/compiler.py | dropbox/stone | train | 440 |
25fa50fb7404b71cb74cb8286b7222ed2f877697 | [
"len1, len2 = (len(nums1), len(nums2))\nres = [0] * k\nfor i in xrange(max(0, k - len2), min(k, len1) + 1):\n subarray1 = self.get_max_subarray(nums1, i)\n subarray2 = self.get_max_subarray(nums2, k - i)\n res = max(res, [max(subarray1, subarray2).pop(0) for _ in xrange(k)])\nreturn res",
"res = [0] * k\... | <|body_start_0|>
len1, len2 = (len(nums1), len(nums2))
res = [0] * k
for i in xrange(max(0, k - len2), min(k, len1) + 1):
subarray1 = self.get_max_subarray(nums1, i)
subarray2 = self.get_max_subarray(nums2, k - i)
res = max(res, [max(subarray1, subarray2).pop(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxNumber(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def get_max_subarray(self, nums, k):
"""A method to get the max subarray while preserve the related position in nums"""
... | stack_v2_sparse_classes_36k_train_006110 | 1,116 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]",
"name": "maxNumber",
"signature": "def maxNumber(self, nums1, nums2, k)"
},
{
"docstring": "A method to get the max subarray while preserve the related position in nums",
"name": "get_max_subarray"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxNumber(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]
- def get_max_subarray(self, nums, k): A method to get the max ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxNumber(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]
- def get_max_subarray(self, nums, k): A method to get the max ... | 580366c7de5f27a931930aeec5e08aa043aa1d54 | <|skeleton|>
class Solution:
def maxNumber(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def get_max_subarray(self, nums, k):
"""A method to get the max subarray while preserve the related position in nums"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxNumber(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]"""
len1, len2 = (len(nums1), len(nums2))
res = [0] * k
for i in xrange(max(0, k - len2), min(k, len1) + 1):
subarray1 = self.get_max_subar... | the_stack_v2_python_sparse | 321-Create-Maximum-Number/solution.py | z502185331/leetcode-python | train | 0 | |
578e53d4cb013ec851e991cbba692698cbeb54fc | [
"if not student.is_active:\n return False\nif semester.records_closing is not None and time > semester.records_closing:\n return False\nt0_record = None\ntry:\n t0_record = cls.objects.get(student=student, semester=semester)\nexcept cls.DoesNotExist:\n return False\nif time < t0_record.time:\n return... | <|body_start_0|>
if not student.is_active:
return False
if semester.records_closing is not None and time > semester.records_closing:
return False
t0_record = None
try:
t0_record = cls.objects.get(student=student, semester=semester)
except cls.D... | This model stores a T0 for a student. T0 is a time when they can enroll into each groups (except of those that are still closed). | T0Times | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class T0Times:
"""This model stores a T0 for a student. T0 is a time when they can enroll into each groups (except of those that are still closed)."""
def is_after_t0(cls, student: Student, semester: Semester, time: datetime) -> bool:
"""Checks whether the T0 for student has passed. The fu... | stack_v2_sparse_classes_36k_train_006111 | 12,426 | no_license | [
{
"docstring": "Checks whether the T0 for student has passed. The function will return False if student is inactive, his T0 is not in the database, the enrollment is closed in the semester or has not yet started.",
"name": "is_after_t0",
"signature": "def is_after_t0(cls, student: Student, semester: Sem... | 2 | stack_v2_sparse_classes_30k_train_001180 | Implement the Python class `T0Times` described below.
Class description:
This model stores a T0 for a student. T0 is a time when they can enroll into each groups (except of those that are still closed).
Method signatures and docstrings:
- def is_after_t0(cls, student: Student, semester: Semester, time: datetime) -> b... | Implement the Python class `T0Times` described below.
Class description:
This model stores a T0 for a student. T0 is a time when they can enroll into each groups (except of those that are still closed).
Method signatures and docstrings:
- def is_after_t0(cls, student: Student, semester: Semester, time: datetime) -> b... | 2299f5f57d67efb3ad8b661e9a22709d9eeec922 | <|skeleton|>
class T0Times:
"""This model stores a T0 for a student. T0 is a time when they can enroll into each groups (except of those that are still closed)."""
def is_after_t0(cls, student: Student, semester: Semester, time: datetime) -> bool:
"""Checks whether the T0 for student has passed. The fu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class T0Times:
"""This model stores a T0 for a student. T0 is a time when they can enroll into each groups (except of those that are still closed)."""
def is_after_t0(cls, student: Student, semester: Semester, time: datetime) -> bool:
"""Checks whether the T0 for student has passed. The function will r... | the_stack_v2_python_sparse | zapisy/apps/enrollment/records/models/opening_times.py | iiuni/projektzapisy | train | 34 |
d1d0fd8823504200abccdeeb501718200bfd4d00 | [
"super(RNNEncoder, self).__init__()\nself.batch = batch\nself.units = units\nself.embedding = tf.keras.layers.Embedding(vocab, embedding)\nself.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)",
"initializer = tf.keras.initializers.Zeros()\nhidden ... | <|body_start_0|>
super(RNNEncoder, self).__init__()
self.batch = batch
self.units = units
self.embedding = tf.keras.layers.Embedding(vocab, embedding)
self.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)
<|end_bod... | Rnn encoder class | RNNEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNEncoder:
"""Rnn encoder class"""
def __init__(self, vocab, embedding, units, batch):
"""Function that initializes variables"""
<|body_0|>
def initialize_hidden_state(self):
"""Function that initializes the hidden states for the RNN cell to a tensor of zeros"""... | stack_v2_sparse_classes_36k_train_006112 | 1,198 | no_license | [
{
"docstring": "Function that initializes variables",
"name": "__init__",
"signature": "def __init__(self, vocab, embedding, units, batch)"
},
{
"docstring": "Function that initializes the hidden states for the RNN cell to a tensor of zeros",
"name": "initialize_hidden_state",
"signature... | 3 | stack_v2_sparse_classes_30k_train_008809 | Implement the Python class `RNNEncoder` described below.
Class description:
Rnn encoder class
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Function that initializes variables
- def initialize_hidden_state(self): Function that initializes the hidden states for the RNN cell to... | Implement the Python class `RNNEncoder` described below.
Class description:
Rnn encoder class
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Function that initializes variables
- def initialize_hidden_state(self): Function that initializes the hidden states for the RNN cell to... | 9dbf8221d4eb22dbc2487cb55e84a801a38aa5c8 | <|skeleton|>
class RNNEncoder:
"""Rnn encoder class"""
def __init__(self, vocab, embedding, units, batch):
"""Function that initializes variables"""
<|body_0|>
def initialize_hidden_state(self):
"""Function that initializes the hidden states for the RNN cell to a tensor of zeros"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNEncoder:
"""Rnn encoder class"""
def __init__(self, vocab, embedding, units, batch):
"""Function that initializes variables"""
super(RNNEncoder, self).__init__()
self.batch = batch
self.units = units
self.embedding = tf.keras.layers.Embedding(vocab, embedding)
... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/0-rnn_encoder.py | yasmineholb/holbertonschool-machine_learning | train | 0 |
748114d06c300dc139966cfcba4747530920265c | [
"if '_xml_ns' in kwargs:\n self._xml_ns = kwargs['_xml_ns']\nif '_xml_ns_key' in kwargs:\n self._xml_ns_key = kwargs['_xml_ns_key']\nself.TypeID = TypeID\nself.CurrentIndex = CurrentIndex\nself.MatchCollections = MatchCollections\nsuper(MatchType, self).__init__(**kwargs)",
"if self.MatchCollections is None... | <|body_start_0|>
if '_xml_ns' in kwargs:
self._xml_ns = kwargs['_xml_ns']
if '_xml_ns_key' in kwargs:
self._xml_ns_key = kwargs['_xml_ns_key']
self.TypeID = TypeID
self.CurrentIndex = CurrentIndex
self.MatchCollections = MatchCollections
super(Matc... | The is an array element for match information. | MatchType | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatchType:
"""The is an array element for match information."""
def __init__(self, TypeID: str=None, CurrentIndex: Optional[int]=None, MatchCollections: Optional[List[MatchCollectionType]]=None, **kwargs):
"""Parameters ---------- TypeID : str CurrentIndex : None|int MatchCollections... | stack_v2_sparse_classes_36k_train_006113 | 8,888 | permissive | [
{
"docstring": "Parameters ---------- TypeID : str CurrentIndex : None|int MatchCollections : None|List[MatchCollectionType] kwargs",
"name": "__init__",
"signature": "def __init__(self, TypeID: str=None, CurrentIndex: Optional[int]=None, MatchCollections: Optional[List[MatchCollectionType]]=None, **kwa... | 2 | null | Implement the Python class `MatchType` described below.
Class description:
The is an array element for match information.
Method signatures and docstrings:
- def __init__(self, TypeID: str=None, CurrentIndex: Optional[int]=None, MatchCollections: Optional[List[MatchCollectionType]]=None, **kwargs): Parameters -------... | Implement the Python class `MatchType` described below.
Class description:
The is an array element for match information.
Method signatures and docstrings:
- def __init__(self, TypeID: str=None, CurrentIndex: Optional[int]=None, MatchCollections: Optional[List[MatchCollectionType]]=None, **kwargs): Parameters -------... | de1b1886f161a83b6c89aadc7a2c7cfc4892ef81 | <|skeleton|>
class MatchType:
"""The is an array element for match information."""
def __init__(self, TypeID: str=None, CurrentIndex: Optional[int]=None, MatchCollections: Optional[List[MatchCollectionType]]=None, **kwargs):
"""Parameters ---------- TypeID : str CurrentIndex : None|int MatchCollections... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MatchType:
"""The is an array element for match information."""
def __init__(self, TypeID: str=None, CurrentIndex: Optional[int]=None, MatchCollections: Optional[List[MatchCollectionType]]=None, **kwargs):
"""Parameters ---------- TypeID : str CurrentIndex : None|int MatchCollections : None|List[... | the_stack_v2_python_sparse | sarpy/io/complex/sicd_elements/MatchInfo.py | ngageoint/sarpy | train | 192 |
e50e6e8c278bdb72bc43d3d9bba64d3f204d78e9 | [
"super(TestAdmin2, cls).setUpClass()\ncls.pagelogin = PageLogin(cls.browserclass.get_driver())\ncls.pageindex = PageIndex(cls.browserclass.get_driver())",
"self.log.info('--------- Start Login ---------')\nself.browserclass.get_driver().get(self.loginurl)\ncaptvalue = self.pagelogin.getcaptcha(self.loginurl, self... | <|body_start_0|>
super(TestAdmin2, cls).setUpClass()
cls.pagelogin = PageLogin(cls.browserclass.get_driver())
cls.pageindex = PageIndex(cls.browserclass.get_driver())
<|end_body_0|>
<|body_start_1|>
self.log.info('--------- Start Login ---------')
self.browserclass.get_driver().... | TestAdmin2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAdmin2:
def setUpClass(cls):
"""测试类中所有测试方法执行前执行的方法"""
<|body_0|>
def test_a_weblogin(self):
"""登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:"""
<|body_1|>
def test_b_pagecheck(self, menu1, menu2, menu3, check_a):
"""数据驱动，左侧菜单点击及页面显示check 三个参数依次是 ... | stack_v2_sparse_classes_36k_train_006114 | 3,534 | no_license | [
{
"docstring": "测试类中所有测试方法执行前执行的方法",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:",
"name": "test_a_weblogin",
"signature": "def test_a_weblogin(self)"
},
{
"docstring": "数据驱动，左侧菜单点击及页面显示check 三个参数依次是 一级菜单 二... | 3 | null | Implement the Python class `TestAdmin2` described below.
Class description:
Implement the TestAdmin2 class.
Method signatures and docstrings:
- def setUpClass(cls): 测试类中所有测试方法执行前执行的方法
- def test_a_weblogin(self): 登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:
- def test_b_pagecheck(self, menu1, menu2, menu3, check_a): 数据驱... | Implement the Python class `TestAdmin2` described below.
Class description:
Implement the TestAdmin2 class.
Method signatures and docstrings:
- def setUpClass(cls): 测试类中所有测试方法执行前执行的方法
- def test_a_weblogin(self): 登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:
- def test_b_pagecheck(self, menu1, menu2, menu3, check_a): 数据驱... | 08b98e08b76ed2a4984efb7f543ed63eabe30757 | <|skeleton|>
class TestAdmin2:
def setUpClass(cls):
"""测试类中所有测试方法执行前执行的方法"""
<|body_0|>
def test_a_weblogin(self):
"""登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:"""
<|body_1|>
def test_b_pagecheck(self, menu1, menu2, menu3, check_a):
"""数据驱动，左侧菜单点击及页面显示check 三个参数依次是 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAdmin2:
def setUpClass(cls):
"""测试类中所有测试方法执行前执行的方法"""
super(TestAdmin2, cls).setUpClass()
cls.pagelogin = PageLogin(cls.browserclass.get_driver())
cls.pageindex = PageIndex(cls.browserclass.get_driver())
def test_a_weblogin(self):
"""登录测试，并为后面的菜单页面check测试，提供登录后... | the_stack_v2_python_sparse | Sys_Carloan/TestClass/TestAdmin2.py | duozi/webUITestLight | train | 0 | |
6ddfafd7856fda302593489726e8f1f46fb6ee67 | [
"user = self.login()\nif not user or not user.is_active:\n raise ValidationError('Sorry that was an invalid login. Please try again.')\nreturn self.cleaned_data",
"username = self.cleaned_data.get('username')\npassword = self.cleaned_data.get('password')\nuser = authenticate(username=username, password=passwor... | <|body_start_0|>
user = self.login()
if not user or not user.is_active:
raise ValidationError('Sorry that was an invalid login. Please try again.')
return self.cleaned_data
<|end_body_0|>
<|body_start_1|>
username = self.cleaned_data.get('username')
password = self.c... | Manage logins to the app. | LoginForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginForm:
"""Manage logins to the app."""
def clean(self):
"""Make sure the login worked. :return: dict, the cleaned_data."""
<|body_0|>
def login(self):
"""Authenticate the user for logging in. :return: User, the authenticated user."""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_006115 | 3,096 | permissive | [
{
"docstring": "Make sure the login worked. :return: dict, the cleaned_data.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Authenticate the user for logging in. :return: User, the authenticated user.",
"name": "login",
"signature": "def login(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001506 | Implement the Python class `LoginForm` described below.
Class description:
Manage logins to the app.
Method signatures and docstrings:
- def clean(self): Make sure the login worked. :return: dict, the cleaned_data.
- def login(self): Authenticate the user for logging in. :return: User, the authenticated user. | Implement the Python class `LoginForm` described below.
Class description:
Manage logins to the app.
Method signatures and docstrings:
- def clean(self): Make sure the login worked. :return: dict, the cleaned_data.
- def login(self): Authenticate the user for logging in. :return: User, the authenticated user.
<|skel... | 7e2c1f147cc10bccaac8ddaf15c7d8287527e2c1 | <|skeleton|>
class LoginForm:
"""Manage logins to the app."""
def clean(self):
"""Make sure the login worked. :return: dict, the cleaned_data."""
<|body_0|>
def login(self):
"""Authenticate the user for logging in. :return: User, the authenticated user."""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginForm:
"""Manage logins to the app."""
def clean(self):
"""Make sure the login worked. :return: dict, the cleaned_data."""
user = self.login()
if not user or not user.is_active:
raise ValidationError('Sorry that was an invalid login. Please try again.')
ret... | the_stack_v2_python_sparse | loader/forms.py | lnlfp/lnlfp | train | 2 |
4f3320ad73bcc1cd6d6795b273cc99eebcebb0b2 | [
"self.head = None\nself.tail = None\nself.length = 0",
"if index < 0 or index >= self.length:\n return -1\nresult = self.head\nfor i in range(index):\n result = result.next\nreturn result.val",
"if self.head is None:\n self.head = self.ListNode(val, None, None)\n self.tail = self.head\nelse:\n te... | <|body_start_0|>
self.head = None
self.tail = None
self.length = 0
<|end_body_0|>
<|body_start_1|>
if index < 0 or index >= self.length:
return -1
result = self.head
for i in range(index):
result = result.next
return result.val
<|end_body_... | MyLinkedList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1."""
<|body_1|>
def addAtHead(self, val:... | stack_v2_sparse_classes_36k_train_006116 | 3,577 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get the value of the index-th node in the linked list. If the index is invalid, return -1.",
"name": "get",
"signature": "def get(self, index: int) -> int"
},... | 6 | stack_v2_sparse_classes_30k_train_013086 | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If the index is invali... | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If the index is invali... | a0ab59ba0a1a11a06b7086aa8f791293ec9c7139 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1."""
<|body_1|>
def addAtHead(self, val:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
self.head = None
self.tail = None
self.length = 0
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1."""
... | the_stack_v2_python_sparse | leetCodePython2020/707.design-linked-list.py | HOZH/leetCode | train | 2 | |
cebd2e800c23b454505d335c8e1406011aeaea8e | [
"self.map = {}\nfor sentence, time in zip(sentences, times):\n self.map[sentence] = time",
"if c == '#':\n self.map[self.cur_sent] = self.map.get(self.cur_sent, 0) + 1\n self.cur_sent = ''\n return []\nresults = []\nself.cur_sent += c\nfor key in self.map:\n if key.startswith(self.cur_sent):\n ... | <|body_start_0|>
self.map = {}
for sentence, time in zip(sentences, times):
self.map[sentence] = time
<|end_body_0|>
<|body_start_1|>
if c == '#':
self.map[self.cur_sent] = self.map.get(self.cur_sent, 0) + 1
self.cur_sent = ''
return []
re... | AutocompleteSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.map = {}
... | stack_v2_sparse_classes_36k_train_006117 | 1,199 | no_license | [
{
"docstring": ":type sentences: List[str] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, sentences, times)"
},
{
"docstring": ":type c: str :rtype: List[str]",
"name": "input",
"signature": "def input(self, c)"
}
] | 2 | null | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str] | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str]
<|skeleton|>
cla... | c08fdd1556b6dbbdda8ad6210aa0eaa97074ae3b | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
self.map = {}
for sentence, time in zip(sentences, times):
self.map[sentence] = time
def input(self, c):
""":type c: str :rtype: List[str]"""
... | the_stack_v2_python_sparse | python/review/str_auto_complete_ht.py | sumitkrm/lang-1 | train | 0 | |
d2e7d46f5cdeb69140574ed57b1b244ac413e1a3 | [
"nums_map = dict()\nfor num in nums:\n nums_map[num] = True\nmiss_num = 1\nwhile miss_num in nums_map:\n miss_num += 1\nreturn miss_num",
"nums_len = len(nums)\nfor i in range(nums_len):\n while nums[i] != i + 1 and 0 < nums[i] <= nums_len and (nums[nums[i] - 1] != nums[i]):\n nums[nums[i] - 1], n... | <|body_start_0|>
nums_map = dict()
for num in nums:
nums_map[num] = True
miss_num = 1
while miss_num in nums_map:
miss_num += 1
return miss_num
<|end_body_0|>
<|body_start_1|>
nums_len = len(nums)
for i in range(nums_len):
whil... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nums_map = dict()
f... | stack_v2_sparse_classes_36k_train_006118 | 799 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "firstMissingPositive",
"signature": "def firstMissingPositive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "firstMissingPositive",
"signature": "def firstMissingPositive(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 firstMissingPositive(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 firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 052bd7915257679877dbe55b60ed1abb7528eaa2 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def firstMissingPositive(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"""
nums_map = dict()
for num in nums:
nums_map[num] = True
miss_num = 1
while miss_num in nums_map:
miss_num += 1
return miss_num
def firstMissingPo... | the_stack_v2_python_sparse | python_solution/Array/41_FirstMissingPositive.py | Dimen61/leetcode | train | 4 | |
df0bfdd6f9c355d9108f078218804a9b15d25f2a | [
"query_builder = Configuration.BASE_URI\nquery_builder += '/ws/scatterplot'\nquery_builder = APIHelper.append_url_with_query_parameters(query_builder, {'q': options.get('q', None), 'x': options.get('x', None), 'y': options.get('y', None), 'fq': options.get('fq', None), 'height': options.get('height', None), 'pointc... | <|body_start_0|>
query_builder = Configuration.BASE_URI
query_builder += '/ws/scatterplot'
query_builder = APIHelper.append_url_with_query_parameters(query_builder, {'q': options.get('q', None), 'x': options.get('x', None), 'y': options.get('y', None), 'fq': options.get('fq', None), 'height': op... | A Controller to access Endpoints in the AtlasOfLivingAustraliaOccurrencesLib API. | ScatterplotController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScatterplotController:
"""A Controller to access Endpoints in the AtlasOfLivingAustraliaOccurrencesLib API."""
def get_scatterplot_image(self, options=dict()):
"""Does a GET request to /ws/scatterplot. Return an image for occurrences and two environmental layers as a scatterplot. Arg... | stack_v2_sparse_classes_36k_train_006119 | 9,072 | no_license | [
{
"docstring": "Does a GET request to /ws/scatterplot. Return an image for occurrences and two environmental layers as a scatterplot. Args: options (dict, optional): Key-value pairs for any of the parameters to this API Endpoint. All parameters to the endpoint are supplied through the dictionary with their name... | 2 | stack_v2_sparse_classes_30k_train_014069 | Implement the Python class `ScatterplotController` described below.
Class description:
A Controller to access Endpoints in the AtlasOfLivingAustraliaOccurrencesLib API.
Method signatures and docstrings:
- def get_scatterplot_image(self, options=dict()): Does a GET request to /ws/scatterplot. Return an image for occur... | Implement the Python class `ScatterplotController` described below.
Class description:
A Controller to access Endpoints in the AtlasOfLivingAustraliaOccurrencesLib API.
Method signatures and docstrings:
- def get_scatterplot_image(self, options=dict()): Does a GET request to /ws/scatterplot. Return an image for occur... | a9f803ea42bef4eb3720d5dd92a53dc98e8f2678 | <|skeleton|>
class ScatterplotController:
"""A Controller to access Endpoints in the AtlasOfLivingAustraliaOccurrencesLib API."""
def get_scatterplot_image(self, options=dict()):
"""Does a GET request to /ws/scatterplot. Return an image for occurrences and two environmental layers as a scatterplot. Arg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScatterplotController:
"""A Controller to access Endpoints in the AtlasOfLivingAustraliaOccurrencesLib API."""
def get_scatterplot_image(self, options=dict()):
"""Does a GET request to /ws/scatterplot. Return an image for occurrences and two environmental layers as a scatterplot. Args: options (d... | the_stack_v2_python_sparse | AtlasOfLivingAustraliaOccurrencesLib/Controllers/ScatterplotController.py | chm052/naturehack | train | 2 |
70437f949a1b790fe0dc879fd379d9dcb00d5444 | [
"self.config = config\nself.add_entities = add_entities\nself.oauth = oauth",
"hass = request.app['hass']\ndata = request.query\nresponse_message = 'Fitbit has been successfully authorized!\\n You can close this window now!'\nresult = None\nif data.get('code') is not None:\n redirect_uri = f'{get_url(ha... | <|body_start_0|>
self.config = config
self.add_entities = add_entities
self.oauth = oauth
<|end_body_0|>
<|body_start_1|>
hass = request.app['hass']
data = request.query
response_message = 'Fitbit has been successfully authorized!\n You can close this window now!'... | Handle OAuth finish callback requests. | FitbitAuthCallbackView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FitbitAuthCallbackView:
"""Handle OAuth finish callback requests."""
def __init__(self, config, add_entities, oauth):
"""Initialize the OAuth callback view."""
<|body_0|>
def get(self, request):
"""Finish OAuth callback request."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_006120 | 19,565 | permissive | [
{
"docstring": "Initialize the OAuth callback view.",
"name": "__init__",
"signature": "def __init__(self, config, add_entities, oauth)"
},
{
"docstring": "Finish OAuth callback request.",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011242 | Implement the Python class `FitbitAuthCallbackView` described below.
Class description:
Handle OAuth finish callback requests.
Method signatures and docstrings:
- def __init__(self, config, add_entities, oauth): Initialize the OAuth callback view.
- def get(self, request): Finish OAuth callback request. | Implement the Python class `FitbitAuthCallbackView` described below.
Class description:
Handle OAuth finish callback requests.
Method signatures and docstrings:
- def __init__(self, config, add_entities, oauth): Initialize the OAuth callback view.
- def get(self, request): Finish OAuth callback request.
<|skeleton|>... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class FitbitAuthCallbackView:
"""Handle OAuth finish callback requests."""
def __init__(self, config, add_entities, oauth):
"""Initialize the OAuth callback view."""
<|body_0|>
def get(self, request):
"""Finish OAuth callback request."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FitbitAuthCallbackView:
"""Handle OAuth finish callback requests."""
def __init__(self, config, add_entities, oauth):
"""Initialize the OAuth callback view."""
self.config = config
self.add_entities = add_entities
self.oauth = oauth
def get(self, request):
"""... | the_stack_v2_python_sparse | homeassistant/components/fitbit/sensor.py | tchellomello/home-assistant | train | 8 |
82b2d8c031da6bb5e3cba80238a398ec3704c79c | [
"self.default_recipients = config[CONF_DEFAULT_RECIPIENTS]\nself.sender = config[CONF_SENDER]\nself.client = Client(config[CONF_SERVICE_PLAN_ID], config[CONF_API_KEY])",
"targets = kwargs.get(ATTR_TARGET, self.default_recipients)\ndata = kwargs.get(ATTR_DATA) or {}\nclx_args = {ATTR_MESSAGE: message, ATTR_SENDER:... | <|body_start_0|>
self.default_recipients = config[CONF_DEFAULT_RECIPIENTS]
self.sender = config[CONF_SENDER]
self.client = Client(config[CONF_SERVICE_PLAN_ID], config[CONF_API_KEY])
<|end_body_0|>
<|body_start_1|>
targets = kwargs.get(ATTR_TARGET, self.default_recipients)
data =... | Send Notifications to Sinch SMS recipients. | SinchNotificationService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SinchNotificationService:
"""Send Notifications to Sinch SMS recipients."""
def __init__(self, config):
"""Initialize the service."""
<|body_0|>
def send_message(self, message='', **kwargs):
"""Send a message to a user."""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_006121 | 3,370 | permissive | [
{
"docstring": "Initialize the service.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Send a message to a user.",
"name": "send_message",
"signature": "def send_message(self, message='', **kwargs)"
}
] | 2 | null | Implement the Python class `SinchNotificationService` described below.
Class description:
Send Notifications to Sinch SMS recipients.
Method signatures and docstrings:
- def __init__(self, config): Initialize the service.
- def send_message(self, message='', **kwargs): Send a message to a user. | Implement the Python class `SinchNotificationService` described below.
Class description:
Send Notifications to Sinch SMS recipients.
Method signatures and docstrings:
- def __init__(self, config): Initialize the service.
- def send_message(self, message='', **kwargs): Send a message to a user.
<|skeleton|>
class Si... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SinchNotificationService:
"""Send Notifications to Sinch SMS recipients."""
def __init__(self, config):
"""Initialize the service."""
<|body_0|>
def send_message(self, message='', **kwargs):
"""Send a message to a user."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SinchNotificationService:
"""Send Notifications to Sinch SMS recipients."""
def __init__(self, config):
"""Initialize the service."""
self.default_recipients = config[CONF_DEFAULT_RECIPIENTS]
self.sender = config[CONF_SENDER]
self.client = Client(config[CONF_SERVICE_PLAN_I... | the_stack_v2_python_sparse | homeassistant/components/sinch/notify.py | home-assistant/core | train | 35,501 |
af01f5fd79cc664a79cbc881d9b21e07ff36c642 | [
"self.access_key_id = access_key_id\nself.auth_method = auth_method\nself.ca_certificate = ca_certificate\nself.cmk_alias = cmk_alias\nself.cmk_arn = cmk_arn\nself.cmk_key_id = cmk_key_id\nself.iam_role_arn = iam_role_arn\nself.region = region\nself.secret_access_key = secret_access_key\nself.verify_s_s_l = verify_... | <|body_start_0|>
self.access_key_id = access_key_id
self.auth_method = auth_method
self.ca_certificate = ca_certificate
self.cmk_alias = cmk_alias
self.cmk_arn = cmk_arn
self.cmk_key_id = cmk_key_id
self.iam_role_arn = iam_role_arn
self.region = region
... | Implementation of the 'AwsKmsConfiguration' model. TODO: type description here. Attributes: access_key_id (string): Access key id needed to access the cloud account. When update cluster config, should encrypte accessKeyId with cluster ID. auth_method (AuthMethodEnum): Specifies the authentication method to be used for ... | AwsKmsConfiguration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AwsKmsConfiguration:
"""Implementation of the 'AwsKmsConfiguration' model. TODO: type description here. Attributes: access_key_id (string): Access key id needed to access the cloud account. When update cluster config, should encrypte accessKeyId with cluster ID. auth_method (AuthMethodEnum): Spec... | stack_v2_sparse_classes_36k_train_006122 | 4,533 | permissive | [
{
"docstring": "Constructor for the AwsKmsConfiguration class",
"name": "__init__",
"signature": "def __init__(self, access_key_id=None, auth_method=None, ca_certificate=None, cmk_alias=None, cmk_arn=None, cmk_key_id=None, iam_role_arn=None, region=None, secret_access_key=None, verify_s_s_l=None)"
},
... | 2 | stack_v2_sparse_classes_30k_train_009278 | Implement the Python class `AwsKmsConfiguration` described below.
Class description:
Implementation of the 'AwsKmsConfiguration' model. TODO: type description here. Attributes: access_key_id (string): Access key id needed to access the cloud account. When update cluster config, should encrypte accessKeyId with cluster... | Implement the Python class `AwsKmsConfiguration` described below.
Class description:
Implementation of the 'AwsKmsConfiguration' model. TODO: type description here. Attributes: access_key_id (string): Access key id needed to access the cloud account. When update cluster config, should encrypte accessKeyId with cluster... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class AwsKmsConfiguration:
"""Implementation of the 'AwsKmsConfiguration' model. TODO: type description here. Attributes: access_key_id (string): Access key id needed to access the cloud account. When update cluster config, should encrypte accessKeyId with cluster ID. auth_method (AuthMethodEnum): Spec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AwsKmsConfiguration:
"""Implementation of the 'AwsKmsConfiguration' model. TODO: type description here. Attributes: access_key_id (string): Access key id needed to access the cloud account. When update cluster config, should encrypte accessKeyId with cluster ID. auth_method (AuthMethodEnum): Specifies the aut... | the_stack_v2_python_sparse | cohesity_management_sdk/models/aws_kms_configuration.py | cohesity/management-sdk-python | train | 24 |
1ac0ef75dbb36aaf0434179755d81ac04d5e078e | [
"password1 = self.cleaned_data.get('password1')\npassword2 = self.cleaned_data.get('password2')\nif password1 and password2:\n if password1 != password2:\n raise forms.ValidationError(\"Passwords are n't the same\")\nelse:\n raise forms.ValidationError(\"Passwords can't be empty\")\nreturn password2",
... | <|body_start_0|>
password1 = self.cleaned_data.get('password1')
password2 = self.cleaned_data.get('password2')
if password1 and password2:
if password1 != password2:
raise forms.ValidationError("Passwords are n't the same")
else:
raise forms.Valida... | A form for registering new users with all required field | UserCreationForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCreationForm:
"""A form for registering new users with all required field"""
def clean_password2(self):
"""Check to ensure passwords are the same"""
<|body_0|>
def save(self, commit=True):
"""Save password in hashed form"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_006123 | 2,376 | no_license | [
{
"docstring": "Check to ensure passwords are the same",
"name": "clean_password2",
"signature": "def clean_password2(self)"
},
{
"docstring": "Save password in hashed form",
"name": "save",
"signature": "def save(self, commit=True)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016724 | Implement the Python class `UserCreationForm` described below.
Class description:
A form for registering new users with all required field
Method signatures and docstrings:
- def clean_password2(self): Check to ensure passwords are the same
- def save(self, commit=True): Save password in hashed form | Implement the Python class `UserCreationForm` described below.
Class description:
A form for registering new users with all required field
Method signatures and docstrings:
- def clean_password2(self): Check to ensure passwords are the same
- def save(self, commit=True): Save password in hashed form
<|skeleton|>
cla... | dbee8cab22d83e8b5d29c5172b5c3b1cdd729610 | <|skeleton|>
class UserCreationForm:
"""A form for registering new users with all required field"""
def clean_password2(self):
"""Check to ensure passwords are the same"""
<|body_0|>
def save(self, commit=True):
"""Save password in hashed form"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserCreationForm:
"""A form for registering new users with all required field"""
def clean_password2(self):
"""Check to ensure passwords are the same"""
password1 = self.cleaned_data.get('password1')
password2 = self.cleaned_data.get('password2')
if password1 and password2... | the_stack_v2_python_sparse | webproject/src/accounts/forms.py | Ajitesh27/SuperMarket-Management-System | train | 19 |
44989cde7ffa5b0aa8582c90078a959c3082d95f | [
"super().__init__()\nself.center_form_priors = build_priors(image_size=image_size, **priors_cfg)\nself.corner_form_priors = center_to_corner_form(self.center_form_priors)\nself.center_variance = center_variance\nself.size_variance = size_variance\nself.iou_threshold = iou_threshold",
"if type(gt_boxes) is numpy.n... | <|body_start_0|>
super().__init__()
self.center_form_priors = build_priors(image_size=image_size, **priors_cfg)
self.corner_form_priors = center_to_corner_form(self.center_form_priors)
self.center_variance = center_variance
self.size_variance = size_variance
self.iou_thre... | description | SSDAnnotationTransform | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSDAnnotationTransform:
"""description"""
def __init__(self, *, image_size: Any, priors_cfg: NOD, center_variance: Any, size_variance: Any, iou_threshold: Any):
""":param image_size: :type image_size: :param priors_cfg: :type priors_cfg: :param center_variance: :type center_variance:... | stack_v2_sparse_classes_36k_train_006124 | 3,743 | permissive | [
{
"docstring": ":param image_size: :type image_size: :param priors_cfg: :type priors_cfg: :param center_variance: :type center_variance: :param size_variance: :type size_variance: :param iou_threshold: :type iou_threshold:",
"name": "__init__",
"signature": "def __init__(self, *, image_size: Any, priors... | 2 | null | Implement the Python class `SSDAnnotationTransform` described below.
Class description:
description
Method signatures and docstrings:
- def __init__(self, *, image_size: Any, priors_cfg: NOD, center_variance: Any, size_variance: Any, iou_threshold: Any): :param image_size: :type image_size: :param priors_cfg: :type p... | Implement the Python class `SSDAnnotationTransform` described below.
Class description:
description
Method signatures and docstrings:
- def __init__(self, *, image_size: Any, priors_cfg: NOD, center_variance: Any, size_variance: Any, iou_threshold: Any): :param image_size: :type image_size: :param priors_cfg: :type p... | 06839b08d8e8f274c02a6bcd31bf1b32d3dc04e4 | <|skeleton|>
class SSDAnnotationTransform:
"""description"""
def __init__(self, *, image_size: Any, priors_cfg: NOD, center_variance: Any, size_variance: Any, iou_threshold: Any):
""":param image_size: :type image_size: :param priors_cfg: :type priors_cfg: :param center_variance: :type center_variance:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SSDAnnotationTransform:
"""description"""
def __init__(self, *, image_size: Any, priors_cfg: NOD, center_variance: Any, size_variance: Any, iou_threshold: Any):
""":param image_size: :type image_size: :param priors_cfg: :type priors_cfg: :param center_variance: :type center_variance: :param size_... | the_stack_v2_python_sparse | neodroidvision/detection/single_stage/ssd/bounding_boxes/ssd_transforms.py | aivclab/vision | train | 1 |
fbc7491a9b48d5a2eebd844a31cc626c2b7abc42 | [
"fulltext = db.session.query(Fulltext).get(id)\nif not fulltext:\n return not_found_error('<Fulltext(id={})> not found'.format(id))\nif g.current_user.is_admin is False and fulltext.review.users.filter_by(id=g.current_user.id).one_or_none() is None:\n return forbidden_error('{} forbidden to get this fulltext'... | <|body_start_0|>
fulltext = db.session.query(Fulltext).get(id)
if not fulltext:
return not_found_error('<Fulltext(id={})> not found'.format(id))
if g.current_user.is_admin is False and fulltext.review.users.filter_by(id=g.current_user.id).one_or_none() is None:
return for... | FulltextResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FulltextResource:
def get(self, id, fields):
"""get record for a single fulltext by id"""
<|body_0|>
def delete(self, id, test):
"""delete record for a single fulltext by id"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
fulltext = db.session.query... | stack_v2_sparse_classes_36k_train_006125 | 3,581 | no_license | [
{
"docstring": "get record for a single fulltext by id",
"name": "get",
"signature": "def get(self, id, fields)"
},
{
"docstring": "delete record for a single fulltext by id",
"name": "delete",
"signature": "def delete(self, id, test)"
}
] | 2 | null | Implement the Python class `FulltextResource` described below.
Class description:
Implement the FulltextResource class.
Method signatures and docstrings:
- def get(self, id, fields): get record for a single fulltext by id
- def delete(self, id, test): delete record for a single fulltext by id | Implement the Python class `FulltextResource` described below.
Class description:
Implement the FulltextResource class.
Method signatures and docstrings:
- def get(self, id, fields): get record for a single fulltext by id
- def delete(self, id, test): delete record for a single fulltext by id
<|skeleton|>
class Full... | 37936769dd7c4de05e44508eeb5eaf7b8cdf1c14 | <|skeleton|>
class FulltextResource:
def get(self, id, fields):
"""get record for a single fulltext by id"""
<|body_0|>
def delete(self, id, test):
"""delete record for a single fulltext by id"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FulltextResource:
def get(self, id, fields):
"""get record for a single fulltext by id"""
fulltext = db.session.query(Fulltext).get(id)
if not fulltext:
return not_found_error('<Fulltext(id={})> not found'.format(id))
if g.current_user.is_admin is False and fulltext... | the_stack_v2_python_sparse | colandr/api/resources/fulltexts.py | datakind/permanent-colandr-back | train | 13 | |
c592dde74f81df459ca629172241f383b399ac34 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Provides text analysis operations such as sentiment analysis and entity recognition. | LanguageServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LanguageServiceServicer:
"""Provides text analysis operations such as sentiment analysis and entity recognition."""
def AnalyzeSentiment(self, request, context):
"""Analyzes the sentiment of the provided text."""
<|body_0|>
def AnalyzeEntities(self, request, context):
... | stack_v2_sparse_classes_36k_train_006126 | 8,150 | permissive | [
{
"docstring": "Analyzes the sentiment of the provided text.",
"name": "AnalyzeSentiment",
"signature": "def AnalyzeSentiment(self, request, context)"
},
{
"docstring": "Finds named entities (currently proper names and common nouns) in the text along with entity types, salience, mentions for eac... | 6 | stack_v2_sparse_classes_30k_train_012255 | Implement the Python class `LanguageServiceServicer` described below.
Class description:
Provides text analysis operations such as sentiment analysis and entity recognition.
Method signatures and docstrings:
- def AnalyzeSentiment(self, request, context): Analyzes the sentiment of the provided text.
- def AnalyzeEnti... | Implement the Python class `LanguageServiceServicer` described below.
Class description:
Provides text analysis operations such as sentiment analysis and entity recognition.
Method signatures and docstrings:
- def AnalyzeSentiment(self, request, context): Analyzes the sentiment of the provided text.
- def AnalyzeEnti... | 253e419666f5dacf4566135faf5d451600020374 | <|skeleton|>
class LanguageServiceServicer:
"""Provides text analysis operations such as sentiment analysis and entity recognition."""
def AnalyzeSentiment(self, request, context):
"""Analyzes the sentiment of the provided text."""
<|body_0|>
def AnalyzeEntities(self, request, context):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LanguageServiceServicer:
"""Provides text analysis operations such as sentiment analysis and entity recognition."""
def AnalyzeSentiment(self, request, context):
"""Analyzes the sentiment of the provided text."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details(... | the_stack_v2_python_sparse | venv/lib/python3.7/site-packages/google/cloud/language_v1beta2/proto/language_service_pb2_grpc.py | nicholasadamou/stockmine | train | 2 |
3848ea739e8c653a33d2c9e2bac4a13ae6ea9551 | [
"response = requests.post(url=url, data=data, cookies=cookie, headers=header, verify=False)\nif get_cookie != None:\n cookie_value_jar = response.cookies\n cookie_value = requests.utils.dict_from_cookiejar(cookie_value_jar)\n write_cookie(cookie_value, get_cookie['is_cookie'])\nres = response.text\nreturn ... | <|body_start_0|>
response = requests.post(url=url, data=data, cookies=cookie, headers=header, verify=False)
if get_cookie != None:
cookie_value_jar = response.cookies
cookie_value = requests.utils.dict_from_cookiejar(cookie_value_jar)
write_cookie(cookie_value, get_co... | BaseRequest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseRequest:
def send_post(self, url, data, cookie=None, get_cookie=None, header=None):
"""发送post请求"""
<|body_0|>
def send_get(self, url, data, cookie=None, get_cookie=None, header=None):
"""发送get请求"""
<|body_1|>
def run_main(self, method, url, data, coo... | stack_v2_sparse_classes_36k_train_006127 | 2,202 | no_license | [
{
"docstring": "发送post请求",
"name": "send_post",
"signature": "def send_post(self, url, data, cookie=None, get_cookie=None, header=None)"
},
{
"docstring": "发送get请求",
"name": "send_get",
"signature": "def send_get(self, url, data, cookie=None, get_cookie=None, header=None)"
},
{
"... | 3 | stack_v2_sparse_classes_30k_train_004700 | Implement the Python class `BaseRequest` described below.
Class description:
Implement the BaseRequest class.
Method signatures and docstrings:
- def send_post(self, url, data, cookie=None, get_cookie=None, header=None): 发送post请求
- def send_get(self, url, data, cookie=None, get_cookie=None, header=None): 发送get请求
- de... | Implement the Python class `BaseRequest` described below.
Class description:
Implement the BaseRequest class.
Method signatures and docstrings:
- def send_post(self, url, data, cookie=None, get_cookie=None, header=None): 发送post请求
- def send_get(self, url, data, cookie=None, get_cookie=None, header=None): 发送get请求
- de... | 40f39930bb0856cb337cd44d2219da5f3f5db68a | <|skeleton|>
class BaseRequest:
def send_post(self, url, data, cookie=None, get_cookie=None, header=None):
"""发送post请求"""
<|body_0|>
def send_get(self, url, data, cookie=None, get_cookie=None, header=None):
"""发送get请求"""
<|body_1|>
def run_main(self, method, url, data, coo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseRequest:
def send_post(self, url, data, cookie=None, get_cookie=None, header=None):
"""发送post请求"""
response = requests.post(url=url, data=data, cookies=cookie, headers=header, verify=False)
if get_cookie != None:
cookie_value_jar = response.cookies
cookie_va... | the_stack_v2_python_sparse | Base/base_request.py | caiguoqiang/Imooc | train | 0 | |
58f5c77553c1294baaeb9911fb1119fdba89704a | [
"self.c = capacity\nself.cc = 0\nself.h = {}\nself.m = []",
"if key in self.h:\n self.m.remove(key)\n self.m.append(key)\n return self.h[key]\nelse:\n return -1",
"if self.cc < self.c:\n self.cc += 1\n self.h.update({key: value})\n self.m.append(key)\nelse:\n self.h.update({key: value})\... | <|body_start_0|>
self.c = capacity
self.cc = 0
self.h = {}
self.m = []
<|end_body_0|>
<|body_start_1|>
if key in self.h:
self.m.remove(key)
self.m.append(key)
return self.h[key]
else:
return -1
<|end_body_1|>
<|body_start_... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_006128 | 833 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_017729 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
<|sk... | 418172cee1bf48bb2aed3b84fe8b4defd9ef4fdf | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.c = capacity
self.cc = 0
self.h = {}
self.m = []
def get(self, key):
""":type key: int :rtype: int"""
if key in self.h:
self.m.remove(key)
self.m.append(k... | the_stack_v2_python_sparse | LRU Cache.py | TianyaoHua/LeetCodeSolutions | train | 0 | |
a6d618bdd10cf1ef7f19c2134eaacb8f966b9442 | [
"assert len(set(ms)) == 1\nVp = [list(eigen_basis(m)) for m in ms]\nVb = [q.subs(x, s) for q in eigen_basis(n)]\nQ = [mu.subs(x, s) for mu in eigen_basis(r)]\nCoupledProblem.__init__(self, Vp, Vb, Q, beam)\nself.params = params",
"if isinstance(self.beam, LineBeam):\n dim = max(self.n, self.r)\n Bb = eigen_... | <|body_start_0|>
assert len(set(ms)) == 1
Vp = [list(eigen_basis(m)) for m in ms]
Vb = [q.subs(x, s) for q in eigen_basis(n)]
Q = [mu.subs(x, s) for mu in eigen_basis(r)]
CoupledProblem.__init__(self, Vp, Vb, Q, beam)
self.params = params
<|end_body_0|>
<|body_start_1|>
... | Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis | CoupledEigen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoupledEigen:
"""Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis"""
def __init__(self, ms, n, r, beam, params):
"""Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q."""
<|body_0|>
def Bb_matrix(self):
... | stack_v2_sparse_classes_36k_train_006129 | 2,158 | no_license | [
{
"docstring": "Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q.",
"name": "__init__",
"signature": "def __init__(self, ms, n, r, beam, params)"
},
{
"docstring": "Matrix of the constraint on the beam",
"name": "Bb_matrix",
"signature": "def Bb_matrix(self)"
},
... | 3 | stack_v2_sparse_classes_30k_train_014753 | Implement the Python class `CoupledEigen` described below.
Class description:
Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis
Method signatures and docstrings:
- def __init__(self, ms, n, r, beam, params): Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q... | Implement the Python class `CoupledEigen` described below.
Class description:
Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis
Method signatures and docstrings:
- def __init__(self, ms, n, r, beam, params): Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q... | 2fb3686804e836d4031fbf231a36a0f9ac8a3012 | <|skeleton|>
class CoupledEigen:
"""Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis"""
def __init__(self, ms, n, r, beam, params):
"""Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q."""
<|body_0|>
def Bb_matrix(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoupledEigen:
"""Parent for coupled problems with spaces Vp, Vb, Q are spanned by functions from eigenbasis"""
def __init__(self, ms, n, r, beam, params):
"""Solver with ms[i] functions for i-th comp of Vp, n for Vb and r for Q."""
assert len(set(ms)) == 1
Vp = [list(eigen_basis(m... | the_stack_v2_python_sparse | kent-report/py/coupled_eigen.py | MiroK/cutFEM-beam | train | 0 |
87582888ab2665183465f46d5938441f413f5cca | [
"self.idxs = idxs\nself.logmin = float(logmin)\nself.logmax = float(logmax)\nself.logparam = logparam\nnamestr = 'logunidraw'\nfor ii in idxs:\n namestr += '_{}'.format(ii)\nself.__name__ = namestr",
"q = x.copy()\nlqxy = 0\nfor ii in self.idxs:\n if self.logparam:\n q[ii] = np.random.uniform(self.lo... | <|body_start_0|>
self.idxs = idxs
self.logmin = float(logmin)
self.logmax = float(logmax)
self.logparam = logparam
namestr = 'logunidraw'
for ii in idxs:
namestr += '_{}'.format(ii)
self.__name__ = namestr
<|end_body_0|>
<|body_start_1|>
q = x... | object for custom log-uniform draws | LogUniDraw | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogUniDraw:
"""object for custom log-uniform draws"""
def __init__(self, idxs, logmin, logmax, logparam=True):
""":param idx: index of parameter to use for jump"""
<|body_0|>
def __call__(self, x, iter, beta):
"""proposal from log-uniform distribution"""
... | stack_v2_sparse_classes_36k_train_006130 | 8,178 | permissive | [
{
"docstring": ":param idx: index of parameter to use for jump",
"name": "__init__",
"signature": "def __init__(self, idxs, logmin, logmax, logparam=True)"
},
{
"docstring": "proposal from log-uniform distribution",
"name": "__call__",
"signature": "def __call__(self, x, iter, beta)"
}... | 2 | stack_v2_sparse_classes_30k_val_000750 | Implement the Python class `LogUniDraw` described below.
Class description:
object for custom log-uniform draws
Method signatures and docstrings:
- def __init__(self, idxs, logmin, logmax, logparam=True): :param idx: index of parameter to use for jump
- def __call__(self, x, iter, beta): proposal from log-uniform dis... | Implement the Python class `LogUniDraw` described below.
Class description:
object for custom log-uniform draws
Method signatures and docstrings:
- def __init__(self, idxs, logmin, logmax, logparam=True): :param idx: index of parameter to use for jump
- def __call__(self, x, iter, beta): proposal from log-uniform dis... | 8d98ea04ea71fa404275f0a0a4fd67c94d37b159 | <|skeleton|>
class LogUniDraw:
"""object for custom log-uniform draws"""
def __init__(self, idxs, logmin, logmax, logparam=True):
""":param idx: index of parameter to use for jump"""
<|body_0|>
def __call__(self, x, iter, beta):
"""proposal from log-uniform distribution"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogUniDraw:
"""object for custom log-uniform draws"""
def __init__(self, idxs, logmin, logmax, logparam=True):
""":param idx: index of parameter to use for jump"""
self.idxs = idxs
self.logmin = float(logmin)
self.logmax = float(logmax)
self.logparam = logparam
... | the_stack_v2_python_sparse | utils/sample_helpers.py | paulthebaker/nano11_bwm | train | 3 |
ef10982b6e273e7456dff909c70456075cd34d19 | [
"logs.log_info('You are using the vgK channel: Kv1p1 ')\nself.time_unit = 1000.0\nself.vrev = -65\nself.m = 1.0 / (1 + np.exp((V - -30.5) / -11.3943))\nself.h = 1.0 / (1 + np.exp((V - -30.0) / 27.3943))\nself._mpower = 1\nself._hpower = 2",
"self._mInf = 1.0 / (1 + np.exp((V - -30.5) / -11.3943))\nself._mTau = 30... | <|body_start_0|>
logs.log_info('You are using the vgK channel: Kv1p1 ')
self.time_unit = 1000.0
self.vrev = -65
self.m = 1.0 / (1 + np.exp((V - -30.5) / -11.3943))
self.h = 1.0 / (1 + np.exp((V - -30.0) / 27.3943))
self._mpower = 1
self._hpower = 2
<|end_body_0|>
... | Kv1.1 model from Christie et al, cloned from rat brain, studied in xenopus. Kv1.1 are low-voltage activated (LVA) channels, expressed primarily in the central nervous system, and which open with small depolarizations at or below resting potential Reference: Christie MJ. et al. Expression of a cloned rat brain potassium... | Kv1p1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Kv1p1:
"""Kv1.1 model from Christie et al, cloned from rat brain, studied in xenopus. Kv1.1 are low-voltage activated (LVA) channels, expressed primarily in the central nervous system, and which open with small depolarizations at or below resting potential Reference: Christie MJ. et al. Expressio... | stack_v2_sparse_classes_36k_train_006131 | 24,227 | no_license | [
{
"docstring": "Run initialization calculation for m and h gates of the channel at starting Vmem value.",
"name": "_init_state",
"signature": "def _init_state(self, V)"
},
{
"docstring": "Update the state of m and h gates of the channel given their present value and present simulation Vmem.",
... | 2 | null | Implement the Python class `Kv1p1` described below.
Class description:
Kv1.1 model from Christie et al, cloned from rat brain, studied in xenopus. Kv1.1 are low-voltage activated (LVA) channels, expressed primarily in the central nervous system, and which open with small depolarizations at or below resting potential R... | Implement the Python class `Kv1p1` described below.
Class description:
Kv1.1 model from Christie et al, cloned from rat brain, studied in xenopus. Kv1.1 are low-voltage activated (LVA) channels, expressed primarily in the central nervous system, and which open with small depolarizations at or below resting potential R... | dd03ff5e3df3ef48d887a6566a6286fcd168880b | <|skeleton|>
class Kv1p1:
"""Kv1.1 model from Christie et al, cloned from rat brain, studied in xenopus. Kv1.1 are low-voltage activated (LVA) channels, expressed primarily in the central nervous system, and which open with small depolarizations at or below resting potential Reference: Christie MJ. et al. Expressio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Kv1p1:
"""Kv1.1 model from Christie et al, cloned from rat brain, studied in xenopus. Kv1.1 are low-voltage activated (LVA) channels, expressed primarily in the central nervous system, and which open with small depolarizations at or below resting potential Reference: Christie MJ. et al. Expression of a cloned... | the_stack_v2_python_sparse | betse/science/channels/vg_k.py | R-Stefano/betse-ml | train | 0 |
c11272ce6271903bba6c7ec0e3d90bb09cb6c505 | [
"self.user = user\nself.password = password\nif host:\n self.host = host",
"if not from_addr:\n from_addr = self.user\ndata = 'From: %s\\nTo: %s\\nSubject: %s\\n\\n%s' % (from_addr, to_addrs, subject, message)\ntry:\n server = smtplib.SMTP(self.host)\n server.ehlo()\n server.starttls()\n server.... | <|body_start_0|>
self.user = user
self.password = password
if host:
self.host = host
<|end_body_0|>
<|body_start_1|>
if not from_addr:
from_addr = self.user
data = 'From: %s\nTo: %s\nSubject: %s\n\n%s' % (from_addr, to_addrs, subject, message)
try... | Send email through Gmail. use: Gmailer(user, password[, host]) use: send(to_addrs, subject, message[, from_addrs]) | Gmailer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Gmailer:
"""Send email through Gmail. use: Gmailer(user, password[, host]) use: send(to_addrs, subject, message[, from_addrs])"""
def __init__(self, user, password, host=None):
"""Set Google username and passsword. use: Gmailer(user, password[, host])"""
<|body_0|>
def s... | stack_v2_sparse_classes_36k_train_006132 | 1,781 | no_license | [
{
"docstring": "Set Google username and passsword. use: Gmailer(user, password[, host])",
"name": "__init__",
"signature": "def __init__(self, user, password, host=None)"
},
{
"docstring": "Set username and passsword use: send(to_addrs, subject, message[, from_addrs])",
"name": "send",
"... | 2 | stack_v2_sparse_classes_30k_train_012308 | Implement the Python class `Gmailer` described below.
Class description:
Send email through Gmail. use: Gmailer(user, password[, host]) use: send(to_addrs, subject, message[, from_addrs])
Method signatures and docstrings:
- def __init__(self, user, password, host=None): Set Google username and passsword. use: Gmailer... | Implement the Python class `Gmailer` described below.
Class description:
Send email through Gmail. use: Gmailer(user, password[, host]) use: send(to_addrs, subject, message[, from_addrs])
Method signatures and docstrings:
- def __init__(self, user, password, host=None): Set Google username and passsword. use: Gmailer... | b02b9025add538a927538122558778c505a6c37b | <|skeleton|>
class Gmailer:
"""Send email through Gmail. use: Gmailer(user, password[, host]) use: send(to_addrs, subject, message[, from_addrs])"""
def __init__(self, user, password, host=None):
"""Set Google username and passsword. use: Gmailer(user, password[, host])"""
<|body_0|>
def s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Gmailer:
"""Send email through Gmail. use: Gmailer(user, password[, host]) use: send(to_addrs, subject, message[, from_addrs])"""
def __init__(self, user, password, host=None):
"""Set Google username and passsword. use: Gmailer(user, password[, host])"""
self.user = user
self.pass... | the_stack_v2_python_sparse | libs/gmailer.py | yezooz/24goals | train | 0 |
5d705cfb3d080c018b0b3fa01284b2454494da47 | [
"self._term_doc_matrix = term_doc_matrix\nself._term_doc_matrix_factory = term_doc_matrix_factory\nassert term_doc_matrix_factory._nlp is None\nassert term_doc_matrix_factory.category_text_iter is None\nself._category = category\nself._clf = None\nself._proba = None",
"self._clf = PassiveAggressiveClassifier(n_it... | <|body_start_0|>
self._term_doc_matrix = term_doc_matrix
self._term_doc_matrix_factory = term_doc_matrix_factory
assert term_doc_matrix_factory._nlp is None
assert term_doc_matrix_factory.category_text_iter is None
self._category = category
self._clf = None
self._... | DeployedClassifierFactory | [
"MIT",
"CC-BY-NC-SA-4.0",
"LicenseRef-scancode-proprietary-license",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeployedClassifierFactory:
def __init__(self, term_doc_matrix, term_doc_matrix_factory, category, nlp=None):
"""This is a class that enables one to train and save a classification model. Parameters ---------- term_doc_matrix : TermDocMatrix term_doc_matrix_factory : TermDocMatrixFactory ... | stack_v2_sparse_classes_36k_train_006133 | 2,832 | permissive | [
{
"docstring": "This is a class that enables one to train and save a classification model. Parameters ---------- term_doc_matrix : TermDocMatrix term_doc_matrix_factory : TermDocMatrixFactory category : str Category name nlp : spacy parser",
"name": "__init__",
"signature": "def __init__(self, term_doc_... | 3 | stack_v2_sparse_classes_30k_train_006399 | Implement the Python class `DeployedClassifierFactory` described below.
Class description:
Implement the DeployedClassifierFactory class.
Method signatures and docstrings:
- def __init__(self, term_doc_matrix, term_doc_matrix_factory, category, nlp=None): This is a class that enables one to train and save a classific... | Implement the Python class `DeployedClassifierFactory` described below.
Class description:
Implement the DeployedClassifierFactory class.
Method signatures and docstrings:
- def __init__(self, term_doc_matrix, term_doc_matrix_factory, category, nlp=None): This is a class that enables one to train and save a classific... | b41e3a875faf6dd886e49e524345202432db1b21 | <|skeleton|>
class DeployedClassifierFactory:
def __init__(self, term_doc_matrix, term_doc_matrix_factory, category, nlp=None):
"""This is a class that enables one to train and save a classification model. Parameters ---------- term_doc_matrix : TermDocMatrix term_doc_matrix_factory : TermDocMatrixFactory ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeployedClassifierFactory:
def __init__(self, term_doc_matrix, term_doc_matrix_factory, category, nlp=None):
"""This is a class that enables one to train and save a classification model. Parameters ---------- term_doc_matrix : TermDocMatrix term_doc_matrix_factory : TermDocMatrixFactory category : str... | the_stack_v2_python_sparse | scattertext/DeployedClassifier.py | JasonKessler/scattertext | train | 2,187 | |
e1054b304d7557ebad7fbfe99f4e76880defd500 | [
"self.host = database_config['host']\nif user is None:\n self.user = database_config['user']\nelse:\n self.user = user\nif password is None:\n self.password = database_config['password']\nelse:\n self.password = password\nself.database_name = database_config['database']\nif 'port' in database_config:\n ... | <|body_start_0|>
self.host = database_config['host']
if user is None:
self.user = database_config['user']
else:
self.user = user
if password is None:
self.password = database_config['password']
else:
self.password = password
... | Class to hold info on some connection. | DatabaseConnector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseConnector:
"""Class to hold info on some connection."""
def __init__(self, database_config, user=None, password=None):
"""Class to easily connect and disconnect some database. :param database_config: The config section for the database."""
<|body_0|>
def connect(... | stack_v2_sparse_classes_36k_train_006134 | 1,483 | no_license | [
{
"docstring": "Class to easily connect and disconnect some database. :param database_config: The config section for the database.",
"name": "__init__",
"signature": "def __init__(self, database_config, user=None, password=None)"
},
{
"docstring": "Connect to some database. :return: The database... | 2 | stack_v2_sparse_classes_30k_train_016690 | Implement the Python class `DatabaseConnector` described below.
Class description:
Class to hold info on some connection.
Method signatures and docstrings:
- def __init__(self, database_config, user=None, password=None): Class to easily connect and disconnect some database. :param database_config: The config section ... | Implement the Python class `DatabaseConnector` described below.
Class description:
Class to hold info on some connection.
Method signatures and docstrings:
- def __init__(self, database_config, user=None, password=None): Class to easily connect and disconnect some database. :param database_config: The config section ... | e10166847bd112fcd4fb7044e1478515104017e4 | <|skeleton|>
class DatabaseConnector:
"""Class to hold info on some connection."""
def __init__(self, database_config, user=None, password=None):
"""Class to easily connect and disconnect some database. :param database_config: The config section for the database."""
<|body_0|>
def connect(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatabaseConnector:
"""Class to hold info on some connection."""
def __init__(self, database_config, user=None, password=None):
"""Class to easily connect and disconnect some database. :param database_config: The config section for the database."""
self.host = database_config['host']
... | the_stack_v2_python_sparse | scripts/database/connect_database.py | Tubbz-alt/harmony | train | 0 |
5492778001410c75eb48373e4ad53175a0d7e4d6 | [
"if root == None:\n return 0\nelse:\n return 1 + self.caculate(root.left) + self.caculate(root.right)",
"if root == None:\n return 0\nleft_size = self.caculate(root.left)\nif k == left_size + 1:\n return root.val\nelif k < left_size + 1:\n return self.kthSmallest(root.left, k)\nelif k > left_size +... | <|body_start_0|>
if root == None:
return 0
else:
return 1 + self.caculate(root.left) + self.caculate(root.right)
<|end_body_0|>
<|body_start_1|>
if root == None:
return 0
left_size = self.caculate(root.left)
if k == left_size + 1:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def caculate(self, root):
"""caculate the tree's sons"""
<|body_0|>
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root == None:
return 0
... | stack_v2_sparse_classes_36k_train_006135 | 1,422 | no_license | [
{
"docstring": "caculate the tree's sons",
"name": "caculate",
"signature": "def caculate(self, root)"
},
{
"docstring": ":type root: TreeNode :type k: int :rtype: int",
"name": "kthSmallest",
"signature": "def kthSmallest(self, root, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def caculate(self, root): caculate the tree's sons
- def kthSmallest(self, root, k): :type root: TreeNode :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def caculate(self, root): caculate the tree's sons
- def kthSmallest(self, root, k): :type root: TreeNode :type k: int :rtype: int
<|skeleton|>
class Solution:
def caculate... | 2447f760f08fb3879c5f03d8650e30ff74115d3d | <|skeleton|>
class Solution:
def caculate(self, root):
"""caculate the tree's sons"""
<|body_0|>
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def caculate(self, root):
"""caculate the tree's sons"""
if root == None:
return 0
else:
return 1 + self.caculate(root.left) + self.caculate(root.right)
def kthSmallest(self, root, k):
""":type root: TreeNode :type k: int :rtype: int"""
... | the_stack_v2_python_sparse | 6.21/230.二叉搜素树中第K小的元素.py | pythonnewbird/LeetCodeSolution | train | 4 | |
31244b9a94674da0a9adb370d85d19452aade290 | [
"self.phoneDictSts = {}\nself.availableNums = []\nfor i in range(maxNumbers):\n self.phoneDictSts[i] = True\n heapq.heappush(self.availableNums, i)",
"if len(self.availableNums) > 0:\n num = heapq.heappop(self.availableNums)\n self.phoneDictSts[num] = False\n return num\nelse:\n return -1",
"i... | <|body_start_0|>
self.phoneDictSts = {}
self.availableNums = []
for i in range(maxNumbers):
self.phoneDictSts[i] = True
heapq.heappush(self.availableNums, i)
<|end_body_0|>
<|body_start_1|>
if len(self.availableNums) > 0:
num = heapq.heappop(self.avai... | PhoneDirectory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhoneDirectory:
def __init__(self, maxNumbers):
"""Initialize your data structure here @param maxNumbers - The maximum numbers that can be stored in the phone directory. :type maxNumbers: int"""
<|body_0|>
def get(self):
"""Provide a number which is not assigned to a... | stack_v2_sparse_classes_36k_train_006136 | 1,577 | permissive | [
{
"docstring": "Initialize your data structure here @param maxNumbers - The maximum numbers that can be stored in the phone directory. :type maxNumbers: int",
"name": "__init__",
"signature": "def __init__(self, maxNumbers)"
},
{
"docstring": "Provide a number which is not assigned to anyone. @r... | 4 | null | Implement the Python class `PhoneDirectory` described below.
Class description:
Implement the PhoneDirectory class.
Method signatures and docstrings:
- def __init__(self, maxNumbers): Initialize your data structure here @param maxNumbers - The maximum numbers that can be stored in the phone directory. :type maxNumber... | Implement the Python class `PhoneDirectory` described below.
Class description:
Implement the PhoneDirectory class.
Method signatures and docstrings:
- def __init__(self, maxNumbers): Initialize your data structure here @param maxNumbers - The maximum numbers that can be stored in the phone directory. :type maxNumber... | 20ae1a048eddbc9a32c819cf61258e2b57572f05 | <|skeleton|>
class PhoneDirectory:
def __init__(self, maxNumbers):
"""Initialize your data structure here @param maxNumbers - The maximum numbers that can be stored in the phone directory. :type maxNumbers: int"""
<|body_0|>
def get(self):
"""Provide a number which is not assigned to a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhoneDirectory:
def __init__(self, maxNumbers):
"""Initialize your data structure here @param maxNumbers - The maximum numbers that can be stored in the phone directory. :type maxNumbers: int"""
self.phoneDictSts = {}
self.availableNums = []
for i in range(maxNumbers):
... | the_stack_v2_python_sparse | leetcode.com/python/379_Design_Phone_Directory.py | partho-maple/coding-interview-gym | train | 862 | |
cfdef5a5b01241a659c4476355383b228f0e5934 | [
"try:\n tags = TagService.get_tags()\nexcept AppException:\n raise\nexcept Exception:\n raise AppException(exception_message.get('FETCH_TAG_EXCEPTION'))\nreturn (Response(True, tags).__dict__, 200)",
"try:\n input_data = api.payload\n TagService.create_tag(input_data)\nexcept AppException:\n rai... | <|body_start_0|>
try:
tags = TagService.get_tags()
except AppException:
raise
except Exception:
raise AppException(exception_message.get('FETCH_TAG_EXCEPTION'))
return (Response(True, tags).__dict__, 200)
<|end_body_0|>
<|body_start_1|>
try:
... | TagController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagController:
def get(self):
"""Fetches all tags :return:"""
<|body_0|>
def post(self):
"""Api for creating new tag for machine :return:"""
<|body_1|>
def delete(self):
"""Delete tag"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006137 | 1,657 | no_license | [
{
"docstring": "Fetches all tags :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Api for creating new tag for machine :return:",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Delete tag",
"name": "delete",
"signature": "def del... | 3 | stack_v2_sparse_classes_30k_train_003470 | Implement the Python class `TagController` described below.
Class description:
Implement the TagController class.
Method signatures and docstrings:
- def get(self): Fetches all tags :return:
- def post(self): Api for creating new tag for machine :return:
- def delete(self): Delete tag | Implement the Python class `TagController` described below.
Class description:
Implement the TagController class.
Method signatures and docstrings:
- def get(self): Fetches all tags :return:
- def post(self): Api for creating new tag for machine :return:
- def delete(self): Delete tag
<|skeleton|>
class TagControlle... | a4a452a02a1f1882c9e3f862854746d2fc7f54b6 | <|skeleton|>
class TagController:
def get(self):
"""Fetches all tags :return:"""
<|body_0|>
def post(self):
"""Api for creating new tag for machine :return:"""
<|body_1|>
def delete(self):
"""Delete tag"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TagController:
def get(self):
"""Fetches all tags :return:"""
try:
tags = TagService.get_tags()
except AppException:
raise
except Exception:
raise AppException(exception_message.get('FETCH_TAG_EXCEPTION'))
return (Response(True, tags)... | the_stack_v2_python_sparse | controllers/tag_controller.py | himani07/ManageCloud | train | 0 | |
46aec80a6e221972ea9647708cf556e76502de7a | [
"prev, current = (None, head)\nwhile current:\n temp = current.next\n current.next = prev\n prev = current\n current = temp\nreturn prev",
"def reverse(prev, current):\n if not current:\n return prev\n temp = current.next\n current.next = prev\n return reverse(current, temp)\nreturn... | <|body_start_0|>
prev, current = (None, head)
while current:
temp = current.next
current.next = prev
prev = current
current = temp
return prev
<|end_body_0|>
<|body_start_1|>
def reverse(prev, current):
if not current:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""Iterative approach Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def reverseListRecursive(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""Recursive approach Tim... | stack_v2_sparse_classes_36k_train_006138 | 1,202 | permissive | [
{
"docstring": "Iterative approach Time complexity: O(n) Space complexity: O(1)",
"name": "reverseList",
"signature": "def reverseList(self, head: Optional[ListNode]) -> Optional[ListNode]"
},
{
"docstring": "Recursive approach Time complexity: O(n) Space complexity: O(n)",
"name": "reverseL... | 2 | stack_v2_sparse_classes_30k_train_005026 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head: Optional[ListNode]) -> Optional[ListNode]: Iterative approach Time complexity: O(n) Space complexity: O(1)
- def reverseListRecursive(self, head: Opti... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head: Optional[ListNode]) -> Optional[ListNode]: Iterative approach Time complexity: O(n) Space complexity: O(1)
- def reverseListRecursive(self, head: Opti... | 32b0878f63e5edd19a1fbe13bfa4c518a4261e23 | <|skeleton|>
class Solution:
def reverseList(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""Iterative approach Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def reverseListRecursive(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""Recursive approach Tim... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head: Optional[ListNode]) -> Optional[ListNode]:
"""Iterative approach Time complexity: O(n) Space complexity: O(1)"""
prev, current = (None, head)
while current:
temp = current.next
current.next = prev
prev = current
... | the_stack_v2_python_sparse | leetcode/Linked Lists/206. Reverse Linked List.py | danielfsousa/algorithms-solutions | train | 2 | |
a2c7ccf2ad4b09dc8612eb5296653f0761c3e88e | [
"fields = super().get_fields()\nfields['current_user_permissions'] = CurrentUserPermissionsSerializer(read_only=True)\nreturn fields",
"data = super().to_representation(instance)\nif 'fields' not in self.request.query_params or 'current_user_permissions' in self.request.query_params['fields']:\n data['current_... | <|body_start_0|>
fields = super().get_fields()
fields['current_user_permissions'] = CurrentUserPermissionsSerializer(read_only=True)
return fields
<|end_body_0|>
<|body_start_1|>
data = super().to_representation(instance)
if 'fields' not in self.request.query_params or 'current_... | Augment serializer class. | SerializerWithPermissions | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SerializerWithPermissions:
"""Augment serializer class."""
def get_fields(serializer_self):
"""Return serializer's fields."""
<|body_0|>
def to_representation(serializer_self, instance: models.Model):
"""Object serializer."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_006139 | 5,053 | permissive | [
{
"docstring": "Return serializer's fields.",
"name": "get_fields",
"signature": "def get_fields(serializer_self)"
},
{
"docstring": "Object serializer.",
"name": "to_representation",
"signature": "def to_representation(serializer_self, instance: models.Model)"
}
] | 2 | null | Implement the Python class `SerializerWithPermissions` described below.
Class description:
Augment serializer class.
Method signatures and docstrings:
- def get_fields(serializer_self): Return serializer's fields.
- def to_representation(serializer_self, instance: models.Model): Object serializer. | Implement the Python class `SerializerWithPermissions` described below.
Class description:
Augment serializer class.
Method signatures and docstrings:
- def get_fields(serializer_self): Return serializer's fields.
- def to_representation(serializer_self, instance: models.Model): Object serializer.
<|skeleton|>
class... | 25c0c45235ef37beb45c1af4c917fbbae6282016 | <|skeleton|>
class SerializerWithPermissions:
"""Augment serializer class."""
def get_fields(serializer_self):
"""Return serializer's fields."""
<|body_0|>
def to_representation(serializer_self, instance: models.Model):
"""Object serializer."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SerializerWithPermissions:
"""Augment serializer class."""
def get_fields(serializer_self):
"""Return serializer's fields."""
fields = super().get_fields()
fields['current_user_permissions'] = CurrentUserPermissionsSerializer(read_only=True)
return fields
def to_repre... | the_stack_v2_python_sparse | resolwe/permissions/mixins.py | genialis/resolwe | train | 35 |
741c6773ee9da987a6884ccf683917d9f868c4c8 | [
"kwargs = super(NewbobRelative, cls).load_initial_kwargs_from_config(config)\nkwargs.update({'relativeErrorThreshold': config.float('newbob_relative_error_threshold', -0.01), 'learningRateDecayFactor': config.float('newbob_learning_rate_decay', 0.5)})\nreturn kwargs",
"super(NewbobRelative, self).__init__(**kwarg... | <|body_start_0|>
kwargs = super(NewbobRelative, cls).load_initial_kwargs_from_config(config)
kwargs.update({'relativeErrorThreshold': config.float('newbob_relative_error_threshold', -0.01), 'learningRateDecayFactor': config.float('newbob_learning_rate_decay', 0.5)})
return kwargs
<|end_body_0|>
... | NewbobRelative | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewbobRelative:
def load_initial_kwargs_from_config(cls, config):
""":type config: Config.Config :rtype: dict[str]"""
<|body_0|>
def __init__(self, relativeErrorThreshold, learningRateDecayFactor, **kwargs):
""":param float defaultLearningRate: learning rate for epoc... | stack_v2_sparse_classes_36k_train_006140 | 19,323 | no_license | [
{
"docstring": ":type config: Config.Config :rtype: dict[str]",
"name": "load_initial_kwargs_from_config",
"signature": "def load_initial_kwargs_from_config(cls, config)"
},
{
"docstring": ":param float defaultLearningRate: learning rate for epoch 1+2 :type relativeErrorThreshold: float :type le... | 3 | stack_v2_sparse_classes_30k_train_014807 | Implement the Python class `NewbobRelative` described below.
Class description:
Implement the NewbobRelative class.
Method signatures and docstrings:
- def load_initial_kwargs_from_config(cls, config): :type config: Config.Config :rtype: dict[str]
- def __init__(self, relativeErrorThreshold, learningRateDecayFactor, ... | Implement the Python class `NewbobRelative` described below.
Class description:
Implement the NewbobRelative class.
Method signatures and docstrings:
- def load_initial_kwargs_from_config(cls, config): :type config: Config.Config :rtype: dict[str]
- def __init__(self, relativeErrorThreshold, learningRateDecayFactor, ... | d494b3041069d377d6a7a9c296a14334f2fa5acc | <|skeleton|>
class NewbobRelative:
def load_initial_kwargs_from_config(cls, config):
""":type config: Config.Config :rtype: dict[str]"""
<|body_0|>
def __init__(self, relativeErrorThreshold, learningRateDecayFactor, **kwargs):
""":param float defaultLearningRate: learning rate for epoc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewbobRelative:
def load_initial_kwargs_from_config(cls, config):
""":type config: Config.Config :rtype: dict[str]"""
kwargs = super(NewbobRelative, cls).load_initial_kwargs_from_config(config)
kwargs.update({'relativeErrorThreshold': config.float('newbob_relative_error_threshold', -0.... | the_stack_v2_python_sparse | python/rwth-i6_returnn/returnn-master/LearningRateControl.py | LiuFang816/SALSTM_py_data | train | 10 | |
e80916f52ec9e55e0abc080368b1e8b1a91b5c8d | [
"redis = Redis.get_instance(1)\nuser_as_json = redis.get('doula:user:%s' % username)\nif user_as_json:\n return json.loads(user_as_json)\nelse:\n return None",
"if not 'email' in user:\n user['email'] = 'no-reply@surveymonkey.com'\nif not 'settings' in user:\n user['settings'] = {}\nif not 'notify_me'... | <|body_start_0|>
redis = Redis.get_instance(1)
user_as_json = redis.get('doula:user:%s' % username)
if user_as_json:
return json.loads(user_as_json)
else:
return None
<|end_body_0|>
<|body_start_1|>
if not 'email' in user:
user['email'] = 'no-... | The user represents a user that has logged into Doula via GitHub Example user object: user = { 'username': '', 'oauth_token': '', 'avatar_url': '', 'email': '', 'settings': { 'notify_me': 'failed', 'subscribed_to': ['my_jobs'] } } | User | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
"""The user represents a user that has logged into Doula via GitHub Example user object: user = { 'username': '', 'oauth_token': '', 'avatar_url': '', 'email': '', 'settings': { 'notify_me': 'failed', 'subscribed_to': ['my_jobs'] } }"""
def find(username):
"""Find the user in t... | stack_v2_sparse_classes_36k_train_006141 | 2,506 | permissive | [
{
"docstring": "Find the user in the redis db by username Users are stored in redis with the key: 'doula:user:[username]'",
"name": "find",
"signature": "def find(username)"
},
{
"docstring": "Save the user object to redis and make sure the user has all right key values",
"name": "save",
... | 4 | stack_v2_sparse_classes_30k_val_000360 | Implement the Python class `User` described below.
Class description:
The user represents a user that has logged into Doula via GitHub Example user object: user = { 'username': '', 'oauth_token': '', 'avatar_url': '', 'email': '', 'settings': { 'notify_me': 'failed', 'subscribed_to': ['my_jobs'] } }
Method signatures... | Implement the Python class `User` described below.
Class description:
The user represents a user that has logged into Doula via GitHub Example user object: user = { 'username': '', 'oauth_token': '', 'avatar_url': '', 'email': '', 'settings': { 'notify_me': 'failed', 'subscribed_to': ['my_jobs'] } }
Method signatures... | 239a8c522c9d3488920581f802f7a1ef1f5f6355 | <|skeleton|>
class User:
"""The user represents a user that has logged into Doula via GitHub Example user object: user = { 'username': '', 'oauth_token': '', 'avatar_url': '', 'email': '', 'settings': { 'notify_me': 'failed', 'subscribed_to': ['my_jobs'] } }"""
def find(username):
"""Find the user in t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class User:
"""The user represents a user that has logged into Doula via GitHub Example user object: user = { 'username': '', 'oauth_token': '', 'avatar_url': '', 'email': '', 'settings': { 'notify_me': 'failed', 'subscribed_to': ['my_jobs'] } }"""
def find(username):
"""Find the user in the redis db b... | the_stack_v2_python_sparse | doula/models/user.py | msabramo/Doula | train | 0 |
71b4ba13e85dad5800089b4efe0d300d5185f144 | [
"names = set()\nconnections = list()\nwith open(filename, 'r') as myfile:\n for line in myfile.readlines():\n con = line.strip().split(',')\n connections.append(con)\n names.add(con[0])\n names.add(con[1])\nself.names = sorted(list(names))\nn = len(self.names)\nself.n = n\nA = np.zero... | <|body_start_0|>
names = set()
connections = list()
with open(filename, 'r') as myfile:
for line in myfile.readlines():
con = line.strip().split(',')
connections.append(con)
names.add(con[0])
names.add(con[1])
se... | Predict links between nodes of a network. | LinkPredictor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkPredictor:
"""Predict links between nodes of a network."""
def __init__(self, filename='social_network.csv'):
"""Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data."""
<|body_0|>... | stack_v2_sparse_classes_36k_train_006142 | 6,778 | no_license | [
{
"docstring": "Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data.",
"name": "__init__",
"signature": "def __init__(self, filename='social_network.csv')"
},
{
"docstring": "Predict the next link, eithe... | 3 | stack_v2_sparse_classes_30k_train_007697 | Implement the Python class `LinkPredictor` described below.
Class description:
Predict links between nodes of a network.
Method signatures and docstrings:
- def __init__(self, filename='social_network.csv'): Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The na... | Implement the Python class `LinkPredictor` described below.
Class description:
Predict links between nodes of a network.
Method signatures and docstrings:
- def __init__(self, filename='social_network.csv'): Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The na... | 6e969de3a8337b0bd9bb4ba7abac722ab5c065ab | <|skeleton|>
class LinkPredictor:
"""Predict links between nodes of a network."""
def __init__(self, filename='social_network.csv'):
"""Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data."""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkPredictor:
"""Predict links between nodes of a network."""
def __init__(self, filename='social_network.csv'):
"""Create the effective resistance matrix by constructing an adjacency matrix. Parameters: filename (str): The name of a file containing graph data."""
names = set()
c... | the_stack_v2_python_sparse | Class/ACME_Volume_1-Python/DrazinInverse/drazin.py | scj1420/Class-Projects-Research | train | 0 |
d66b1f5f73f2e1f15c574871c2971068441dda0c | [
"self.params = params\nself.dev_mode = dev_mode\nself.result_list = []",
"result = scale_result(result, scaler)\nif self.dev_mode:\n self.result_list.append(result)\nelse:\n self._send_request(result)",
"response = requests.post(self.params['aggregationServiceUrl'], json={'update': result})\nif response.s... | <|body_start_0|>
self.params = params
self.dev_mode = dev_mode
self.result_list = []
<|end_body_0|>
<|body_start_1|>
result = scale_result(result, scaler)
if self.dev_mode:
self.result_list.append(result)
else:
self._send_request(result)
<|end_bod... | Process results. Args: params (dict): Dictionary of parameters. dev_mode (bool): Specify if dev_mode is on. | ResultProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResultProcessor:
"""Process results. Args: params (dict): Dictionary of parameters. dev_mode (bool): Specify if dev_mode is on."""
def __init__(self, params, dev_mode):
"""Initialize result processor."""
<|body_0|>
def __call__(self, result, scaler=1):
"""Process... | stack_v2_sparse_classes_36k_train_006143 | 13,445 | permissive | [
{
"docstring": "Initialize result processor.",
"name": "__init__",
"signature": "def __init__(self, params, dev_mode)"
},
{
"docstring": "Process the result. If dev_mode is set to true, it appends the result to a list. Else it send the post request to `aggregationServiceUrl`. Args: result (dict)... | 4 | stack_v2_sparse_classes_30k_train_001360 | Implement the Python class `ResultProcessor` described below.
Class description:
Process results. Args: params (dict): Dictionary of parameters. dev_mode (bool): Specify if dev_mode is on.
Method signatures and docstrings:
- def __init__(self, params, dev_mode): Initialize result processor.
- def __call__(self, resul... | Implement the Python class `ResultProcessor` described below.
Class description:
Process results. Args: params (dict): Dictionary of parameters. dev_mode (bool): Specify if dev_mode is on.
Method signatures and docstrings:
- def __init__(self, params, dev_mode): Initialize result processor.
- def __call__(self, resul... | d575747f2e45672b88f2545ff79c9ae771e483a6 | <|skeleton|>
class ResultProcessor:
"""Process results. Args: params (dict): Dictionary of parameters. dev_mode (bool): Specify if dev_mode is on."""
def __init__(self, params, dev_mode):
"""Initialize result processor."""
<|body_0|>
def __call__(self, result, scaler=1):
"""Process... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResultProcessor:
"""Process results. Args: params (dict): Dictionary of parameters. dev_mode (bool): Specify if dev_mode is on."""
def __init__(self, params, dev_mode):
"""Initialize result processor."""
self.params = params
self.dev_mode = dev_mode
self.result_list = []
... | the_stack_v2_python_sparse | opalalgorithms/utils/algorithmrunner.py | OPAL-Project/opalalgorithms | train | 10 |
391d8181f8fd64850043c1ecea4eb1ad70f0f661 | [
"super().__init__()\nself.conv = nn.Sequential(nn.Conv2D(1, odim, 3, 2), nn.ReLU(), nn.Conv2D(odim, odim, 3, 2), nn.ReLU())\nself.out = nn.Sequential(nn.Linear(odim * (((idim - 1) // 2 - 1) // 2), odim), pos_enc if pos_enc is not None else PositionalEncoding(odim, dropout_rate))",
"x = x.unsqueeze(1)\nx = self.co... | <|body_start_0|>
super().__init__()
self.conv = nn.Sequential(nn.Conv2D(1, odim, 3, 2), nn.ReLU(), nn.Conv2D(odim, odim, 3, 2), nn.ReLU())
self.out = nn.Sequential(nn.Linear(odim * (((idim - 1) // 2 - 1) // 2), odim), pos_enc if pos_enc is not None else PositionalEncoding(odim, dropout_rate))
<|... | Convolutional 2D subsampling (to 1/4 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (nn.Layer): Custom position encoding layer. | Conv2dSubsampling | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv2dSubsampling:
"""Convolutional 2D subsampling (to 1/4 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (nn.Layer): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
... | stack_v2_sparse_classes_36k_train_006144 | 2,748 | permissive | [
{
"docstring": "Construct an Conv2dSubsampling object.",
"name": "__init__",
"signature": "def __init__(self, idim, odim, dropout_rate, pos_enc=None)"
},
{
"docstring": "Subsample x. Args: x (Tensor): Input tensor (#batch, time, idim). x_mask (Tensor): Input mask (#batch, 1, time). Returns: Tens... | 3 | null | Implement the Python class `Conv2dSubsampling` described below.
Class description:
Convolutional 2D subsampling (to 1/4 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (nn.Layer): Custom position encoding layer.
Method signatures and docstrings:
- ... | Implement the Python class `Conv2dSubsampling` described below.
Class description:
Convolutional 2D subsampling (to 1/4 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (nn.Layer): Custom position encoding layer.
Method signatures and docstrings:
- ... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class Conv2dSubsampling:
"""Convolutional 2D subsampling (to 1/4 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (nn.Layer): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Conv2dSubsampling:
"""Convolutional 2D subsampling (to 1/4 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (nn.Layer): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
"""Construct ... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/transformer/subsampling.py | anniyanvr/DeepSpeech-1 | train | 0 |
ec6c2326762d753e3b2b903ec46089302904aee2 | [
"if self._short_id is None:\n if hasattr(self, 'eadid') and self.eadid.value:\n eadid = self.eadid.value\n else:\n eadid = None\n self._short_id = shortform_id(self.id, eadid)\nreturn self._short_id",
"if self._title is None:\n if hasattr(self, 'did') and hasattr(self.did, 'unittitle'):\... | <|body_start_0|>
if self._short_id is None:
if hasattr(self, 'eadid') and self.eadid.value:
eadid = self.eadid.value
else:
eadid = None
self._short_id = shortform_id(self.id, eadid)
return self._short_id
<|end_body_0|>
<|body_start_1|>... | Top-level (c01) series. Customized version of :class:`eulcore.xmlmap.eadmap.Component` | Series | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Series:
"""Top-level (c01) series. Customized version of :class:`eulcore.xmlmap.eadmap.Component`"""
def short_id(self):
"""Short-form id (without eadid prefix) for use in external urls."""
<|body_0|>
def title(self):
"""Title of series without the date."""
... | stack_v2_sparse_classes_36k_train_006145 | 4,050 | no_license | [
{
"docstring": "Short-form id (without eadid prefix) for use in external urls.",
"name": "short_id",
"signature": "def short_id(self)"
},
{
"docstring": "Title of series without the date.",
"name": "title",
"signature": "def title(self)"
}
] | 2 | null | Implement the Python class `Series` described below.
Class description:
Top-level (c01) series. Customized version of :class:`eulcore.xmlmap.eadmap.Component`
Method signatures and docstrings:
- def short_id(self): Short-form id (without eadid prefix) for use in external urls.
- def title(self): Title of series witho... | Implement the Python class `Series` described below.
Class description:
Top-level (c01) series. Customized version of :class:`eulcore.xmlmap.eadmap.Component`
Method signatures and docstrings:
- def short_id(self): Short-form id (without eadid prefix) for use in external urls.
- def title(self): Title of series witho... | 579d926794fc5662312e3f009c4b1a0d589867c9 | <|skeleton|>
class Series:
"""Top-level (c01) series. Customized version of :class:`eulcore.xmlmap.eadmap.Component`"""
def short_id(self):
"""Short-form id (without eadid prefix) for use in external urls."""
<|body_0|>
def title(self):
"""Title of series without the date."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Series:
"""Top-level (c01) series. Customized version of :class:`eulcore.xmlmap.eadmap.Component`"""
def short_id(self):
"""Short-form id (without eadid prefix) for use in external urls."""
if self._short_id is None:
if hasattr(self, 'eadid') and self.eadid.value:
... | the_stack_v2_python_sparse | keep/common/eadmap.py | emory-libraries/TheKeep | train | 0 |
e6b851c4f7dbe161c3358a7fe87b576d481f02e6 | [
"if root is None:\n return 0\nqueue = [root]\ndepth = 0\nwhile queue != []:\n depth += 1\n for i in range(len(queue)):\n if queue[0].left is not None:\n queue.append(queue[0].left)\n if queue[0].right is not None:\n queue.append(queue[0].right)\n queue.pop(0)\nret... | <|body_start_0|>
if root is None:
return 0
queue = [root]
depth = 0
while queue != []:
depth += 1
for i in range(len(queue)):
if queue[0].left is not None:
queue.append(queue[0].left)
if queue[0].righ... | DFS | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""DFS"""
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
return 0
... | stack_v2_sparse_classes_36k_train_006146 | 2,157 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
DFS
Method signatures and docstrings:
- def maxDepth(self, root): :type root: TreeNode :rtype: int
- def maxDepth(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
DFS
Method signatures and docstrings:
- def maxDepth(self, root): :type root: TreeNode :rtype: int
- def maxDepth(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
"""DFS"""
def maxDepth(self, root):
"... | e41a86e9d4615079247ef3ef9a35537f4b40d338 | <|skeleton|>
class Solution:
"""DFS"""
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""DFS"""
def maxDepth(self, root):
""":type root: TreeNode :rtype: int"""
if root is None:
return 0
queue = [root]
depth = 0
while queue != []:
depth += 1
for i in range(len(queue)):
if queue[0].left is... | the_stack_v2_python_sparse | Algorithms/二叉树的最大深度.py | pppineapple/LeetCode | train | 0 |
484ab52a9b288846d4ff055d7a46687ac2ba512d | [
"super(NormalizeImage, self).__init__()\nself.mean = mean\nself.std = std\nself.is_scale = is_scale\nself.is_channel_first = is_channel_first\nif not (isinstance(self.mean, list) and isinstance(self.std, list) and isinstance(self.is_scale, bool)):\n raise TypeError('{}: input type is invalid.'.format(self))\nfro... | <|body_start_0|>
super(NormalizeImage, self).__init__()
self.mean = mean
self.std = std
self.is_scale = is_scale
self.is_channel_first = is_channel_first
if not (isinstance(self.mean, list) and isinstance(self.std, list) and isinstance(self.is_scale, bool)):
r... | NormalizeImage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NormalizeImage:
def __init__(self, mean=[0.485, 0.456, 0.406], std=[1, 1, 1], is_scale=True, is_channel_first=True):
"""Args: mean (list): the pixel mean std (list): the pixel variance"""
<|body_0|>
def __call__(self, sample, context=None):
"""Normalize the image. Op... | stack_v2_sparse_classes_36k_train_006147 | 39,037 | permissive | [
{
"docstring": "Args: mean (list): the pixel mean std (list): the pixel variance",
"name": "__init__",
"signature": "def __init__(self, mean=[0.485, 0.456, 0.406], std=[1, 1, 1], is_scale=True, is_channel_first=True)"
},
{
"docstring": "Normalize the image. Operators: 1.(optional) Scale the imag... | 2 | stack_v2_sparse_classes_30k_train_009342 | Implement the Python class `NormalizeImage` described below.
Class description:
Implement the NormalizeImage class.
Method signatures and docstrings:
- def __init__(self, mean=[0.485, 0.456, 0.406], std=[1, 1, 1], is_scale=True, is_channel_first=True): Args: mean (list): the pixel mean std (list): the pixel variance
... | Implement the Python class `NormalizeImage` described below.
Class description:
Implement the NormalizeImage class.
Method signatures and docstrings:
- def __init__(self, mean=[0.485, 0.456, 0.406], std=[1, 1, 1], is_scale=True, is_channel_first=True): Args: mean (list): the pixel mean std (list): the pixel variance
... | 420527996b6da60ca401717a734329f126ed0680 | <|skeleton|>
class NormalizeImage:
def __init__(self, mean=[0.485, 0.456, 0.406], std=[1, 1, 1], is_scale=True, is_channel_first=True):
"""Args: mean (list): the pixel mean std (list): the pixel variance"""
<|body_0|>
def __call__(self, sample, context=None):
"""Normalize the image. Op... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NormalizeImage:
def __init__(self, mean=[0.485, 0.456, 0.406], std=[1, 1, 1], is_scale=True, is_channel_first=True):
"""Args: mean (list): the pixel mean std (list): the pixel variance"""
super(NormalizeImage, self).__init__()
self.mean = mean
self.std = std
self.is_sca... | the_stack_v2_python_sparse | PaddleCV/PaddleDetection/ppdet/data/transform/operators.py | chenbjin/models | train | 3 | |
4733cceed5f5e562b2c330358c115c8da883b44e | [
"similarities = sequences.new_zeros((cluster_centers_count, cluster_centers_count), dtype=torch.float)\noccurred_seqs = sequence_occurrences > 0\nif not occurred_seqs.any():\n return similarities\nsequences = sequences[occurred_seqs]\nsequence_occurrences = sequence_occurrences[occurred_seqs]\nsimilarities_flat ... | <|body_start_0|>
similarities = sequences.new_zeros((cluster_centers_count, cluster_centers_count), dtype=torch.float)
occurred_seqs = sequence_occurrences > 0
if not occurred_seqs.any():
return similarities
sequences = sequences[occurred_seqs]
sequence_occurrences = ... | ClusterUtils | [
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClusterUtils:
def compute_similarities(cluster_centers_count: int, sequences: torch.Tensor, sequence_occurrences: torch.Tensor) -> torch.Tensor:
"""Compute cluster centers similarities. Args: cluster_centers_count: number of cluster centers sequences: tensor[sequences_count, sequence_len... | stack_v2_sparse_classes_36k_train_006148 | 38,858 | permissive | [
{
"docstring": "Compute cluster centers similarities. Args: cluster_centers_count: number of cluster centers sequences: tensor[sequences_count, sequence_length] = cluster_center_id sequence_occurrences: tensor[sequences_count] = number_of_occurrences Returns: tensor[cluster_centers_count, cluster_centers_count]... | 2 | stack_v2_sparse_classes_30k_train_007723 | Implement the Python class `ClusterUtils` described below.
Class description:
Implement the ClusterUtils class.
Method signatures and docstrings:
- def compute_similarities(cluster_centers_count: int, sequences: torch.Tensor, sequence_occurrences: torch.Tensor) -> torch.Tensor: Compute cluster centers similarities. A... | Implement the Python class `ClusterUtils` described below.
Class description:
Implement the ClusterUtils class.
Method signatures and docstrings:
- def compute_similarities(cluster_centers_count: int, sequences: torch.Tensor, sequence_occurrences: torch.Tensor) -> torch.Tensor: Compute cluster centers similarities. A... | 81d72b82ec96948c26d292d709f18c9c77a17ba4 | <|skeleton|>
class ClusterUtils:
def compute_similarities(cluster_centers_count: int, sequences: torch.Tensor, sequence_occurrences: torch.Tensor) -> torch.Tensor:
"""Compute cluster centers similarities. Args: cluster_centers_count: number of cluster centers sequences: tensor[sequences_count, sequence_len... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClusterUtils:
def compute_similarities(cluster_centers_count: int, sequences: torch.Tensor, sequence_occurrences: torch.Tensor) -> torch.Tensor:
"""Compute cluster centers similarities. Args: cluster_centers_count: number of cluster centers sequences: tensor[sequences_count, sequence_length] = cluster... | the_stack_v2_python_sparse | torchsim/gui/observers/cluster_observer.py | andreofner/torchsim | train | 0 | |
603691d1509b668cf8a5ea530b286ac41029f5cc | [
"timeout: float = kwargs.get('timeout', 2.0)\nresponse = self._session.head(self._path(f'/'), allow_redirects=True, timeout=timeout)\nreturn bool(response.status_code == status.OK)",
"r = self._session.head(self._path(f'/pdf/{identifier}'), allow_redirects=True)\nif r.status_code == status.OK:\n return True\ni... | <|body_start_0|>
timeout: float = kwargs.get('timeout', 2.0)
response = self._session.head(self._path(f'/'), allow_redirects=True, timeout=timeout)
return bool(response.status_code == status.OK)
<|end_body_0|>
<|body_start_1|>
r = self._session.head(self._path(f'/pdf/{identifier}'), all... | Provides an interface to get PDFs. | CanonicalPDF | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CanonicalPDF:
"""Provides an interface to get PDFs."""
def is_available(self, **kwargs: Any) -> bool:
"""Determine whether canonical PDFs are available."""
<|body_0|>
def exists(self, identifier: str) -> bool:
"""Determine whether or not a target URL is available... | stack_v2_sparse_classes_36k_train_006149 | 3,680 | permissive | [
{
"docstring": "Determine whether canonical PDFs are available.",
"name": "is_available",
"signature": "def is_available(self, **kwargs: Any) -> bool"
},
{
"docstring": "Determine whether or not a target URL is available (HEAD request). Parameters ---------- identifier : str arXiv identifier for... | 3 | stack_v2_sparse_classes_30k_train_011547 | Implement the Python class `CanonicalPDF` described below.
Class description:
Provides an interface to get PDFs.
Method signatures and docstrings:
- def is_available(self, **kwargs: Any) -> bool: Determine whether canonical PDFs are available.
- def exists(self, identifier: str) -> bool: Determine whether or not a ta... | Implement the Python class `CanonicalPDF` described below.
Class description:
Provides an interface to get PDFs.
Method signatures and docstrings:
- def is_available(self, **kwargs: Any) -> bool: Determine whether canonical PDFs are available.
- def exists(self, identifier: str) -> bool: Determine whether or not a ta... | 36008457022cde245d78b3ad91e0a95aa21bc420 | <|skeleton|>
class CanonicalPDF:
"""Provides an interface to get PDFs."""
def is_available(self, **kwargs: Any) -> bool:
"""Determine whether canonical PDFs are available."""
<|body_0|>
def exists(self, identifier: str) -> bool:
"""Determine whether or not a target URL is available... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CanonicalPDF:
"""Provides an interface to get PDFs."""
def is_available(self, **kwargs: Any) -> bool:
"""Determine whether canonical PDFs are available."""
timeout: float = kwargs.get('timeout', 2.0)
response = self._session.head(self._path(f'/'), allow_redirects=True, timeout=tim... | the_stack_v2_python_sparse | fulltext/services/legacy/legacy.py | arXiv/arxiv-fulltext | train | 38 |
a9dd14cf8b725888fd2afb51028023c7476bd15d | [
"self.device_path = device_path\nself.guid = guid\nself.is_boot_volume = is_boot_volume\nself.is_extended_attributes_supported = is_extended_attributes_supported\nself.is_protected = is_protected\nself.is_shared_volume = is_shared_volume\nself.label = label\nself.logical_size_bytes = logical_size_bytes\nself.mount_... | <|body_start_0|>
self.device_path = device_path
self.guid = guid
self.is_boot_volume = is_boot_volume
self.is_extended_attributes_supported = is_extended_attributes_supported
self.is_protected = is_protected
self.is_shared_volume = is_shared_volume
self.label = la... | Implementation of the 'PhysicalVolume' model. Specifies volume information about a Physical Protection Source. Attributes: device_path (string): Specifies the path to the device that hosts the volume locally. guid (string): Specifies an id for the Physical Volume. is_boot_volume (bool): Specifies whether the volume is ... | PhysicalVolume | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhysicalVolume:
"""Implementation of the 'PhysicalVolume' model. Specifies volume information about a Physical Protection Source. Attributes: device_path (string): Specifies the path to the device that hosts the volume locally. guid (string): Specifies an id for the Physical Volume. is_boot_volum... | stack_v2_sparse_classes_36k_train_006150 | 5,033 | permissive | [
{
"docstring": "Constructor for the PhysicalVolume class",
"name": "__init__",
"signature": "def __init__(self, device_path=None, guid=None, is_boot_volume=None, is_extended_attributes_supported=None, is_protected=None, is_shared_volume=None, label=None, logical_size_bytes=None, mount_points=None, mount... | 2 | null | Implement the Python class `PhysicalVolume` described below.
Class description:
Implementation of the 'PhysicalVolume' model. Specifies volume information about a Physical Protection Source. Attributes: device_path (string): Specifies the path to the device that hosts the volume locally. guid (string): Specifies an id... | Implement the Python class `PhysicalVolume` described below.
Class description:
Implementation of the 'PhysicalVolume' model. Specifies volume information about a Physical Protection Source. Attributes: device_path (string): Specifies the path to the device that hosts the volume locally. guid (string): Specifies an id... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PhysicalVolume:
"""Implementation of the 'PhysicalVolume' model. Specifies volume information about a Physical Protection Source. Attributes: device_path (string): Specifies the path to the device that hosts the volume locally. guid (string): Specifies an id for the Physical Volume. is_boot_volum... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhysicalVolume:
"""Implementation of the 'PhysicalVolume' model. Specifies volume information about a Physical Protection Source. Attributes: device_path (string): Specifies the path to the device that hosts the volume locally. guid (string): Specifies an id for the Physical Volume. is_boot_volume (bool): Spe... | the_stack_v2_python_sparse | cohesity_management_sdk/models/physical_volume.py | cohesity/management-sdk-python | train | 24 |
b097669829826d57218b56d17b47a55831c33581 | [
"self.derivatives = derivatives\nfor param_str in params:\n if not hasattr(self, param_str):\n setattr(self, param_str, self._make_param_function(param_str))\nsuper().__init__(params=params)",
"def param_function(ext, module, g_inp, g_out, bpQuantities):\n \"\"\"Calculates gradient with the help of d... | <|body_start_0|>
self.derivatives = derivatives
for param_str in params:
if not hasattr(self, param_str):
setattr(self, param_str, self._make_param_function(param_str))
super().__init__(params=params)
<|end_body_0|>
<|body_start_1|>
def param_function(ext, mo... | Calculates the gradient. Passes the calls for the parameters to the derivatives class. Implements functions with method names from params. If child class wants to overwrite these methods - for example to support an additional external module - it can do so using the interface for parameter "param1":: param1(ext, module... | GradBaseModule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradBaseModule:
"""Calculates the gradient. Passes the calls for the parameters to the derivatives class. Implements functions with method names from params. If child class wants to overwrite these methods - for example to support an additional external module - it can do so using the interface f... | stack_v2_sparse_classes_36k_train_006151 | 2,424 | permissive | [
{
"docstring": "Initializes all methods. If the param method has already been defined, it is left unchanged. Args: derivatives(backpack.core.derivatives.basederivatives.BaseParameterDerivatives): # noqa: B950 Derivatives object assigned to self.derivatives. params (list[str]): list of strings with parameter nam... | 2 | null | Implement the Python class `GradBaseModule` described below.
Class description:
Calculates the gradient. Passes the calls for the parameters to the derivatives class. Implements functions with method names from params. If child class wants to overwrite these methods - for example to support an additional external modu... | Implement the Python class `GradBaseModule` described below.
Class description:
Calculates the gradient. Passes the calls for the parameters to the derivatives class. Implements functions with method names from params. If child class wants to overwrite these methods - for example to support an additional external modu... | 1ebfb4055be72ed9e0f9d101d78806bd4119645e | <|skeleton|>
class GradBaseModule:
"""Calculates the gradient. Passes the calls for the parameters to the derivatives class. Implements functions with method names from params. If child class wants to overwrite these methods - for example to support an additional external module - it can do so using the interface f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GradBaseModule:
"""Calculates the gradient. Passes the calls for the parameters to the derivatives class. Implements functions with method names from params. If child class wants to overwrite these methods - for example to support an additional external module - it can do so using the interface for parameter ... | the_stack_v2_python_sparse | backpack/extensions/firstorder/gradient/base.py | f-dangel/backpack | train | 505 |
3547327a987b356285be5ebc56c271bfa6fff12b | [
"Stream.Stream_Energy.__init__(self, initScript)\nself.CreatePort(SIG, SIG_PORT)\nself.GetPort(SIG_PORT).SetSignalType(ENERGY_VAR)",
"sigPort = self.GetPort(SIG_PORT)\ninPort = self.GetPort(IN_PORT)\noutPort = self.GetPort(OUT_PORT)\nsigValue = sigPort.GetValue()\nif sigValue == None:\n sigValue = inPort.GetVa... | <|body_start_0|>
Stream.Stream_Energy.__init__(self, initScript)
self.CreatePort(SIG, SIG_PORT)
self.GetPort(SIG_PORT).SetSignalType(ENERGY_VAR)
<|end_body_0|>
<|body_start_1|>
sigPort = self.GetPort(SIG_PORT)
inPort = self.GetPort(IN_PORT)
outPort = self.GetPort(OUT_POR... | Class for the sensor. Inherits from Stream_Energy provides a signal port for reporting a energy value, but can also use that signal to 'calculate' the energy | EnergySensor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnergySensor:
"""Class for the sensor. Inherits from Stream_Energy provides a signal port for reporting a energy value, but can also use that signal to 'calculate' the energy"""
def __init__(self, initScript=None):
"""Init the sensor Init Info: varType = GENERIC_VAR"""
<|body... | stack_v2_sparse_classes_36k_train_006152 | 3,056 | no_license | [
{
"docstring": "Init the sensor Init Info: varType = GENERIC_VAR",
"name": "__init__",
"signature": "def __init__(self, initScript=None)"
},
{
"docstring": "Solve",
"name": "Solve",
"signature": "def Solve(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000189 | Implement the Python class `EnergySensor` described below.
Class description:
Class for the sensor. Inherits from Stream_Energy provides a signal port for reporting a energy value, but can also use that signal to 'calculate' the energy
Method signatures and docstrings:
- def __init__(self, initScript=None): Init the ... | Implement the Python class `EnergySensor` described below.
Class description:
Class for the sensor. Inherits from Stream_Energy provides a signal port for reporting a energy value, but can also use that signal to 'calculate' the energy
Method signatures and docstrings:
- def __init__(self, initScript=None): Init the ... | 8fb4c90180dc96be66f7ca05a30e59a8735fc072 | <|skeleton|>
class EnergySensor:
"""Class for the sensor. Inherits from Stream_Energy provides a signal port for reporting a energy value, but can also use that signal to 'calculate' the energy"""
def __init__(self, initScript=None):
"""Init the sensor Init Info: varType = GENERIC_VAR"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnergySensor:
"""Class for the sensor. Inherits from Stream_Energy provides a signal port for reporting a energy value, but can also use that signal to 'calculate' the energy"""
def __init__(self, initScript=None):
"""Init the sensor Init Info: varType = GENERIC_VAR"""
Stream.Stream_Energ... | the_stack_v2_python_sparse | sim/unitop/Sensor.py | psy007/NNPC-CHEMICAL-SIM- | train | 1 |
afcfa1cbc68632c2acc0fafe0c1427319653fd69 | [
"passports = parse(filename)\nvalid_passports = [passport for passport in passports if is_valid_passport1(passport)]\nreturn len(valid_passports)",
"passports = parse(filename)\nvalid_passports = [passport for passport in passports if is_valid_passport2(passport)]\nreturn len(valid_passports)"
] | <|body_start_0|>
passports = parse(filename)
valid_passports = [passport for passport in passports if is_valid_passport1(passport)]
return len(valid_passports)
<|end_body_0|>
<|body_start_1|>
passports = parse(filename)
valid_passports = [passport for passport in passports if is... | AoC 2020 Day 04 | Day04 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Day04:
"""AoC 2020 Day 04"""
def part1(filename: str) -> int:
"""Given a filename, solve 2020 day 04 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2020 day 04 part 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006153 | 2,461 | no_license | [
{
"docstring": "Given a filename, solve 2020 day 04 part 1",
"name": "part1",
"signature": "def part1(filename: str) -> int"
},
{
"docstring": "Given a filename, solve 2020 day 04 part 2",
"name": "part2",
"signature": "def part2(filename: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_002005 | Implement the Python class `Day04` described below.
Class description:
AoC 2020 Day 04
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2020 day 04 part 1
- def part2(filename: str) -> int: Given a filename, solve 2020 day 04 part 2 | Implement the Python class `Day04` described below.
Class description:
AoC 2020 Day 04
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2020 day 04 part 1
- def part2(filename: str) -> int: Given a filename, solve 2020 day 04 part 2
<|skeleton|>
class Day04:
"""AoC 202... | e89db235837d2d05848210a18c9c2a4456085570 | <|skeleton|>
class Day04:
"""AoC 2020 Day 04"""
def part1(filename: str) -> int:
"""Given a filename, solve 2020 day 04 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2020 day 04 part 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Day04:
"""AoC 2020 Day 04"""
def part1(filename: str) -> int:
"""Given a filename, solve 2020 day 04 part 1"""
passports = parse(filename)
valid_passports = [passport for passport in passports if is_valid_passport1(passport)]
return len(valid_passports)
def part2(file... | the_stack_v2_python_sparse | 2020/python2020/aoc/day04.py | mreishus/aoc | train | 16 |
bdf3e276085636e30406ca017a1167ca99be5cdc | [
"super().__init__()\nself.input_channels = input_channels\nself.output_channels = output_channels\nself.data_layout = data_layout\nGraphConv.global_count += 1\nself.name = name if name else 'Graph_{}'.format(GraphConv.global_count)\nvalue = math.sqrt(6 / (input_channels + output_channels))\nself.mat_weights = lbann... | <|body_start_0|>
super().__init__()
self.input_channels = input_channels
self.output_channels = output_channels
self.data_layout = data_layout
GraphConv.global_count += 1
self.name = name if name else 'Graph_{}'.format(GraphConv.global_count)
value = math.sqrt(6 /... | Graph Conv layer. See: https://arxiv.org/abs/1609.02907 | GraphConv | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphConv:
"""Graph Conv layer. See: https://arxiv.org/abs/1609.02907"""
def __init__(self, input_channels, output_channels, bias=True, activation=lbann.Relu, name=None, data_layout='data_parallel'):
"""Initialize Graph layer Args: input_channels (int): The size of the input node fea... | stack_v2_sparse_classes_36k_train_006154 | 5,326 | permissive | [
{
"docstring": "Initialize Graph layer Args: input_channels (int): The size of the input node features output_channels (int): The output size of the node features bias (bool): Whether to apply biases after MatMul name (str): Default name of the layer is GCN_{number} data_layout (str): Data layout activation (ty... | 2 | stack_v2_sparse_classes_30k_train_000239 | Implement the Python class `GraphConv` described below.
Class description:
Graph Conv layer. See: https://arxiv.org/abs/1609.02907
Method signatures and docstrings:
- def __init__(self, input_channels, output_channels, bias=True, activation=lbann.Relu, name=None, data_layout='data_parallel'): Initialize Graph layer A... | Implement the Python class `GraphConv` described below.
Class description:
Graph Conv layer. See: https://arxiv.org/abs/1609.02907
Method signatures and docstrings:
- def __init__(self, input_channels, output_channels, bias=True, activation=lbann.Relu, name=None, data_layout='data_parallel'): Initialize Graph layer A... | 57116ecc030c0d17bc941f81131c1a335bc2c4ad | <|skeleton|>
class GraphConv:
"""Graph Conv layer. See: https://arxiv.org/abs/1609.02907"""
def __init__(self, input_channels, output_channels, bias=True, activation=lbann.Relu, name=None, data_layout='data_parallel'):
"""Initialize Graph layer Args: input_channels (int): The size of the input node fea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GraphConv:
"""Graph Conv layer. See: https://arxiv.org/abs/1609.02907"""
def __init__(self, input_channels, output_channels, bias=True, activation=lbann.Relu, name=None, data_layout='data_parallel'):
"""Initialize Graph layer Args: input_channels (int): The size of the input node features output_... | the_stack_v2_python_sparse | python/lbann/modules/graph/sparse/GraphConv.py | oyamay/lbann | train | 0 |
555c8a6f8091c7e47c2c87f6762c78fae3129f34 | [
"super().__init__()\nself.up_conv = nn.ConvTranspose2d(in_channels, out_channels // 2, kernel_size=2, stride=2)\nself.bn1 = nn.BatchNorm2d(out_channels // 2)\nself.dropout = nn.Dropout2d(dropout_prob) if dropout_prob > 0.0 else None\nself.dropout2 = nn.Dropout2d(0.5)\nself.act_function1 = act(inplace=True)\nself.ac... | <|body_start_0|>
super().__init__()
self.up_conv = nn.ConvTranspose2d(in_channels, out_channels // 2, kernel_size=2, stride=2)
self.bn1 = nn.BatchNorm2d(out_channels // 2)
self.dropout = nn.Dropout2d(dropout_prob) if dropout_prob > 0.0 else None
self.dropout2 = nn.Dropout2d(0.5)
... | Up Transition Block. | UpTransition | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpTransition:
"""Up Transition Block."""
def __init__(self, in_channels: int, out_channels: int, convs: int, act: nn.Module=nn.ELU, dropout_prob: float=0.0):
"""Parameters ---------- in_channels : int Number of input channels. out_channels : int Number of output channels. convs : int... | stack_v2_sparse_classes_36k_train_006155 | 8,968 | permissive | [
{
"docstring": "Parameters ---------- in_channels : int Number of input channels. out_channels : int Number of output channels. convs : int Number of LUConv layers. act : nn.Module Activation function. dropout_prob : float Dropout probability.",
"name": "__init__",
"signature": "def __init__(self, in_ch... | 2 | stack_v2_sparse_classes_30k_train_020303 | Implement the Python class `UpTransition` described below.
Class description:
Up Transition Block.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, convs: int, act: nn.Module=nn.ELU, dropout_prob: float=0.0): Parameters ---------- in_channels : int Number of input channels. ... | Implement the Python class `UpTransition` described below.
Class description:
Up Transition Block.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, convs: int, act: nn.Module=nn.ELU, dropout_prob: float=0.0): Parameters ---------- in_channels : int Number of input channels. ... | 6d15dd55ca5ed6fc9fbfd31d8488ee7bab453066 | <|skeleton|>
class UpTransition:
"""Up Transition Block."""
def __init__(self, in_channels: int, out_channels: int, convs: int, act: nn.Module=nn.ELU, dropout_prob: float=0.0):
"""Parameters ---------- in_channels : int Number of input channels. out_channels : int Number of output channels. convs : int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpTransition:
"""Up Transition Block."""
def __init__(self, in_channels: int, out_channels: int, convs: int, act: nn.Module=nn.ELU, dropout_prob: float=0.0):
"""Parameters ---------- in_channels : int Number of input channels. out_channels : int Number of output channels. convs : int Number of LU... | the_stack_v2_python_sparse | mridc/collections/segmentation/models/vnet_base/vnet_block.py | wdika/mridc | train | 40 |
505999933a931ff59a7e1dfa82ecd7e3396a79d7 | [
"super(RelativisticAdvLoss, self).__init__()\nself.mode = mode\nself.device = device\nself.BCEloss = nn.BCEWithLogitsLoss().to(device)",
"mean_fake = torch.mean(fake_dis, dim=0, keepdim=True)\nmean_real = torch.mean(real_dis, dim=0, keepdim=True)\nD_real = real_dis - mean_fake\nD_fake = fake_dis - mean_real\nzero... | <|body_start_0|>
super(RelativisticAdvLoss, self).__init__()
self.mode = mode
self.device = device
self.BCEloss = nn.BCEWithLogitsLoss().to(device)
<|end_body_0|>
<|body_start_1|>
mean_fake = torch.mean(fake_dis, dim=0, keepdim=True)
mean_real = torch.mean(real_dis, dim=... | RelativisticAdvLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelativisticAdvLoss:
def __init__(self, mode, device):
""":param mode: mode to compute adversarial loss: bce or l1 :param device: device"""
<|body_0|>
def forward(self, fake_dis, real_dis, model):
""":param fake_dis: predicted image from generator output :param real_... | stack_v2_sparse_classes_36k_train_006156 | 7,116 | no_license | [
{
"docstring": ":param mode: mode to compute adversarial loss: bce or l1 :param device: device",
"name": "__init__",
"signature": "def __init__(self, mode, device)"
},
{
"docstring": ":param fake_dis: predicted image from generator output :param real_dis: real image :param model: generator or di... | 2 | stack_v2_sparse_classes_30k_train_011480 | Implement the Python class `RelativisticAdvLoss` described below.
Class description:
Implement the RelativisticAdvLoss class.
Method signatures and docstrings:
- def __init__(self, mode, device): :param mode: mode to compute adversarial loss: bce or l1 :param device: device
- def forward(self, fake_dis, real_dis, mod... | Implement the Python class `RelativisticAdvLoss` described below.
Class description:
Implement the RelativisticAdvLoss class.
Method signatures and docstrings:
- def __init__(self, mode, device): :param mode: mode to compute adversarial loss: bce or l1 :param device: device
- def forward(self, fake_dis, real_dis, mod... | eb9325edb73208ea992eda4be2a92119be867d10 | <|skeleton|>
class RelativisticAdvLoss:
def __init__(self, mode, device):
""":param mode: mode to compute adversarial loss: bce or l1 :param device: device"""
<|body_0|>
def forward(self, fake_dis, real_dis, model):
""":param fake_dis: predicted image from generator output :param real_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelativisticAdvLoss:
def __init__(self, mode, device):
""":param mode: mode to compute adversarial loss: bce or l1 :param device: device"""
super(RelativisticAdvLoss, self).__init__()
self.mode = mode
self.device = device
self.BCEloss = nn.BCEWithLogitsLoss().to(device)... | the_stack_v2_python_sparse | base_model/base_losses/base_losses.py | Oorgien/Scene-Inpainting | train | 1 | |
2305f2f0d959554ce14adc6c6bf39e80efc65800 | [
"if not root:\n return 0\nif not root.left and (not root.right):\n return 1\nif not root.left:\n return 1 + self.minDepthRecursive(root.right)\nif not root.right:\n return 1 + self.minDepthRecursive(root.left)\nreturn 1 + min(self.minDepthRecursive(root.left), self.minDepthRecursive(root.right))",
"if... | <|body_start_0|>
if not root:
return 0
if not root.left and (not root.right):
return 1
if not root.left:
return 1 + self.minDepthRecursive(root.right)
if not root.right:
return 1 + self.minDepthRecursive(root.left)
return 1 + min(se... | MinimumDepthOfBinaryTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinimumDepthOfBinaryTree:
def minDepthRecursive(self, root: TreeNode) -> int:
"""Recursive solution. Check all cases below, this is different from max depth of binary tree question 1. Base case: Leaf node. Return 1, because height of node is 1 2. Left subtree is null (right subtree is no... | stack_v2_sparse_classes_36k_train_006157 | 6,761 | no_license | [
{
"docstring": "Recursive solution. Check all cases below, this is different from max depth of binary tree question 1. Base case: Leaf node. Return 1, because height of node is 1 2. Left subtree is null (right subtree is non-null) 3. Right subtree is null (left subtree is non-null) 4. Left and Right subtree are... | 2 | null | Implement the Python class `MinimumDepthOfBinaryTree` described below.
Class description:
Implement the MinimumDepthOfBinaryTree class.
Method signatures and docstrings:
- def minDepthRecursive(self, root: TreeNode) -> int: Recursive solution. Check all cases below, this is different from max depth of binary tree que... | Implement the Python class `MinimumDepthOfBinaryTree` described below.
Class description:
Implement the MinimumDepthOfBinaryTree class.
Method signatures and docstrings:
- def minDepthRecursive(self, root: TreeNode) -> int: Recursive solution. Check all cases below, this is different from max depth of binary tree que... | 33184f22ac6346f8734d4fcb98f4b52cf157931e | <|skeleton|>
class MinimumDepthOfBinaryTree:
def minDepthRecursive(self, root: TreeNode) -> int:
"""Recursive solution. Check all cases below, this is different from max depth of binary tree question 1. Base case: Leaf node. Return 1, because height of node is 1 2. Left subtree is null (right subtree is no... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MinimumDepthOfBinaryTree:
def minDepthRecursive(self, root: TreeNode) -> int:
"""Recursive solution. Check all cases below, this is different from max depth of binary tree question 1. Base case: Leaf node. Return 1, because height of node is 1 2. Left subtree is null (right subtree is non-null) 3. Rig... | the_stack_v2_python_sparse | DataStructures/TreesGraphs/MinimumDepthOfBinaryTree/MinimumDepthOfBinaryTree.py | cagriozcaglar/ProgrammingExamples | train | 0 | |
3f590307c4e50d1541efba93db3325a8e347bd33 | [
"self.instance_keypair = self.os_conn.create_key(key_name='instancekey')\nzone = self.os_conn.nova.availability_zones.find(zoneName='nova')\nhost = zone.hosts.keys()[0]\nself.setup_rules_for_default_sec_group()\nnet, subnet = self.create_internal_network_with_subnet()\nself.os_conn.create_server(name='server01', av... | <|body_start_0|>
self.instance_keypair = self.os_conn.create_key(key_name='instancekey')
zone = self.os_conn.nova.availability_zones.find(zoneName='nova')
host = zone.hosts.keys()[0]
self.setup_rules_for_default_sec_group()
net, subnet = self.create_internal_network_with_subnet()... | Check restarts of openvswitch-agents. | TestOVSRestartTwoVmsOnSingleCompute | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOVSRestartTwoVmsOnSingleCompute:
"""Check restarts of openvswitch-agents."""
def _prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create networks net01: net01__subnet, 192.168.1.0/24 3. Launch vm1 and vm2 in net01 network... | stack_v2_sparse_classes_36k_train_006158 | 41,546 | no_license | [
{
"docstring": "Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create networks net01: net01__subnet, 192.168.1.0/24 3. Launch vm1 and vm2 in net01 network on a single compute compute 4. Go to vm1 console and send pings to vm2",
"name": "_prepare_openstack",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_020602 | Implement the Python class `TestOVSRestartTwoVmsOnSingleCompute` described below.
Class description:
Check restarts of openvswitch-agents.
Method signatures and docstrings:
- def _prepare_openstack(self): Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create networks net01: net01__subn... | Implement the Python class `TestOVSRestartTwoVmsOnSingleCompute` described below.
Class description:
Check restarts of openvswitch-agents.
Method signatures and docstrings:
- def _prepare_openstack(self): Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create networks net01: net01__subn... | 8aced2855b78b5f123195d188c80e27b43888a2e | <|skeleton|>
class TestOVSRestartTwoVmsOnSingleCompute:
"""Check restarts of openvswitch-agents."""
def _prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create networks net01: net01__subnet, 192.168.1.0/24 3. Launch vm1 and vm2 in net01 network... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestOVSRestartTwoVmsOnSingleCompute:
"""Check restarts of openvswitch-agents."""
def _prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create networks net01: net01__subnet, 192.168.1.0/24 3. Launch vm1 and vm2 in net01 network on a single ... | the_stack_v2_python_sparse | mos_tests/neutron/python_tests/test_ovs_restart.py | Mirantis/mos-integration-tests | train | 16 |
011bc5956b1e9ec88ee3aa2f277415a06ff1e2ad | [
"user = User.objects.get(email=email)\nsalt = sha1(str(random.random())).hexdigest()[:5]\nkey = sha1(salt + user.username).hexdigest()\nResetPassword.objects.create(user=user, activation_key=key)\nurl = '{}{}'.format('tandlr://', key)\nurl_web = '{}{}/{}'.format(settings.FRONTEND_RECOVERY_PASSWORD_URL, key, user.em... | <|body_start_0|>
user = User.objects.get(email=email)
salt = sha1(str(random.random())).hexdigest()[:5]
key = sha1(salt + user.username).hexdigest()
ResetPassword.objects.create(user=user, activation_key=key)
url = '{}{}'.format('tandlr://', key)
url_web = '{}{}/{}'.forma... | ActivationKeysManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActivationKeysManager:
def reset_user_password(self, email, request=None):
"""Custom reset password"""
<|body_0|>
def activation_user(self, user, request=None):
"""Custom activation user"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = User.ob... | stack_v2_sparse_classes_36k_train_006159 | 5,482 | permissive | [
{
"docstring": "Custom reset password",
"name": "reset_user_password",
"signature": "def reset_user_password(self, email, request=None)"
},
{
"docstring": "Custom activation user",
"name": "activation_user",
"signature": "def activation_user(self, user, request=None)"
}
] | 2 | null | Implement the Python class `ActivationKeysManager` described below.
Class description:
Implement the ActivationKeysManager class.
Method signatures and docstrings:
- def reset_user_password(self, email, request=None): Custom reset password
- def activation_user(self, user, request=None): Custom activation user | Implement the Python class `ActivationKeysManager` described below.
Class description:
Implement the ActivationKeysManager class.
Method signatures and docstrings:
- def reset_user_password(self, email, request=None): Custom reset password
- def activation_user(self, user, request=None): Custom activation user
<|ske... | 7349ce18f56658d67daedf5e1abb352b5c15a029 | <|skeleton|>
class ActivationKeysManager:
def reset_user_password(self, email, request=None):
"""Custom reset password"""
<|body_0|>
def activation_user(self, user, request=None):
"""Custom activation user"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActivationKeysManager:
def reset_user_password(self, email, request=None):
"""Custom reset password"""
user = User.objects.get(email=email)
salt = sha1(str(random.random())).hexdigest()[:5]
key = sha1(salt + user.username).hexdigest()
ResetPassword.objects.create(user=u... | the_stack_v2_python_sparse | src/tandlr/registration/models.py | shrmoud/schoolapp | train | 0 | |
df859ad61ad861d19bf9e8343c4ecc8ea4d1f5b8 | [
"if endWord not in wordList:\n return 0\nqueue = deque([(beginWord, 1)])\nvisted = set([beginWord])\nchars = [chr(ord('a') + i) for i in range(26)]\nwhile queue:\n word, step = queue.popleft()\n if word == endWord:\n return step\n for i in range(len(word)):\n for c in chars:\n n... | <|body_start_0|>
if endWord not in wordList:
return 0
queue = deque([(beginWord, 1)])
visted = set([beginWord])
chars = [chr(ord('a') + i) for i in range(26)]
while queue:
word, step = queue.popleft()
if word == endWord:
return ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def ladderLength(self, beginWord, endWord, wordList):
""":type beginWord: str :type endWord: str :type wordList: List[str] :rtype: int Time Limit Exceeded"""
<|body_0|>
def ladderLength1(self, beginWord, endWord, wordList):
""":type beginWord: str :type end... | stack_v2_sparse_classes_36k_train_006160 | 2,378 | no_license | [
{
"docstring": ":type beginWord: str :type endWord: str :type wordList: List[str] :rtype: int Time Limit Exceeded",
"name": "ladderLength",
"signature": "def ladderLength(self, beginWord, endWord, wordList)"
},
{
"docstring": ":type beginWord: str :type endWord: str :type wordList: List[str] :rt... | 2 | stack_v2_sparse_classes_30k_train_007609 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def ladderLength(self, beginWord, endWord, wordList): :type beginWord: str :type endWord: str :type wordList: List[str] :rtype: int Time Limit Exceeded
- def ladderLength1(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def ladderLength(self, beginWord, endWord, wordList): :type beginWord: str :type endWord: str :type wordList: List[str] :rtype: int Time Limit Exceeded
- def ladderLength1(self, ... | bad06f681d8d3f2b841cb3c8a969198b8643f864 | <|skeleton|>
class Solution:
def ladderLength(self, beginWord, endWord, wordList):
""":type beginWord: str :type endWord: str :type wordList: List[str] :rtype: int Time Limit Exceeded"""
<|body_0|>
def ladderLength1(self, beginWord, endWord, wordList):
""":type beginWord: str :type end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def ladderLength(self, beginWord, endWord, wordList):
""":type beginWord: str :type endWord: str :type wordList: List[str] :rtype: int Time Limit Exceeded"""
if endWord not in wordList:
return 0
queue = deque([(beginWord, 1)])
visted = set([beginWord])
... | the_stack_v2_python_sparse | 127_word_ladder.py | subicWang/leetcode_aotang | train | 0 | |
da1d1184ef77c3d4f4f8389cdd4213f0d1aaac29 | [
"self.num_points = num_points\nself.x_values = [0]\nself.y_values = [0]",
"while len(self.x_values) < self.num_points:\n x_step = self.get_step()\n y_step = self.get_step()\n if x_step == 0 and y_step == 0:\n continue\n next_x = self.x_values[-1] + x_step\n next_y = self.y_values[-1] + y_ste... | <|body_start_0|>
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
<|end_body_0|>
<|body_start_1|>
while len(self.x_values) < self.num_points:
x_step = self.get_step()
y_step = self.get_step()
if x_step == 0 and y_step == 0:
... | 一个生产随机漫步数据的类 | RandomWalk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
"""计算随机漫步包含的所有点"""
<|body_1|>
def get_step(self):
"""获取每次漫步的距离和方向"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006161 | 1,452 | no_license | [
{
"docstring": "初始化随机漫步的属性",
"name": "__init__",
"signature": "def __init__(self, num_points=5000)"
},
{
"docstring": "计算随机漫步包含的所有点",
"name": "fill_walk",
"signature": "def fill_walk(self)"
},
{
"docstring": "获取每次漫步的距离和方向",
"name": "get_step",
"signature": "def get_step(s... | 3 | null | Implement the Python class `RandomWalk` described below.
Class description:
一个生产随机漫步数据的类
Method signatures and docstrings:
- def __init__(self, num_points=5000): 初始化随机漫步的属性
- def fill_walk(self): 计算随机漫步包含的所有点
- def get_step(self): 获取每次漫步的距离和方向 | Implement the Python class `RandomWalk` described below.
Class description:
一个生产随机漫步数据的类
Method signatures and docstrings:
- def __init__(self, num_points=5000): 初始化随机漫步的属性
- def fill_walk(self): 计算随机漫步包含的所有点
- def get_step(self): 获取每次漫步的距离和方向
<|skeleton|>
class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(s... | 6f91fe5e7cbedcdf4b8f7baa7641fd615b4d6141 | <|skeleton|>
class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
<|body_0|>
def fill_walk(self):
"""计算随机漫步包含的所有点"""
<|body_1|>
def get_step(self):
"""获取每次漫步的距离和方向"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomWalk:
"""一个生产随机漫步数据的类"""
def __init__(self, num_points=5000):
"""初始化随机漫步的属性"""
self.num_points = num_points
self.x_values = [0]
self.y_values = [0]
def fill_walk(self):
"""计算随机漫步包含的所有点"""
while len(self.x_values) < self.num_points:
x_... | the_stack_v2_python_sparse | demos/data-analysis/data_visual_by_generate/random_walk.py | romanticair/python | train | 0 |
e117251e912cd0899dcc123843678db4a2e92211 | [
"self.control = control = myEditorAreaWidget(self, parent)\nself._filter = EditorAreaDropFilter(self)\nself.control.installEventFilter(self._filter)\nif sys.platform == 'darwin':\n next_seq = 'Ctrl+}'\n prev_seq = 'Ctrl+{'\nelse:\n next_seq = 'Ctrl+PgDown'\n prev_seq = 'Ctrl+PgUp'\nshortcut = QtGui.QSho... | <|body_start_0|>
self.control = control = myEditorAreaWidget(self, parent)
self._filter = EditorAreaDropFilter(self)
self.control.installEventFilter(self._filter)
if sys.platform == 'darwin':
next_seq = 'Ctrl+}'
prev_seq = 'Ctrl+{'
else:
next_s... | myAdvancedEditorAreaPane | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class myAdvancedEditorAreaPane:
def create(self, parent):
"""Create and set the toolkit-specific control that represents the pane."""
<|body_0|>
def remove_editor(self, editor):
"""Removes an editor from the pane."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006162 | 7,390 | permissive | [
{
"docstring": "Create and set the toolkit-specific control that represents the pane.",
"name": "create",
"signature": "def create(self, parent)"
},
{
"docstring": "Removes an editor from the pane.",
"name": "remove_editor",
"signature": "def remove_editor(self, editor)"
}
] | 2 | null | Implement the Python class `myAdvancedEditorAreaPane` described below.
Class description:
Implement the myAdvancedEditorAreaPane class.
Method signatures and docstrings:
- def create(self, parent): Create and set the toolkit-specific control that represents the pane.
- def remove_editor(self, editor): Removes an edit... | Implement the Python class `myAdvancedEditorAreaPane` described below.
Class description:
Implement the myAdvancedEditorAreaPane class.
Method signatures and docstrings:
- def create(self, parent): Create and set the toolkit-specific control that represents the pane.
- def remove_editor(self, editor): Removes an edit... | 8cfc8085393ace2aee6b98d36bfd6fba0bcb41c6 | <|skeleton|>
class myAdvancedEditorAreaPane:
def create(self, parent):
"""Create and set the toolkit-specific control that represents the pane."""
<|body_0|>
def remove_editor(self, editor):
"""Removes an editor from the pane."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class myAdvancedEditorAreaPane:
def create(self, parent):
"""Create and set the toolkit-specific control that represents the pane."""
self.control = control = myEditorAreaWidget(self, parent)
self._filter = EditorAreaDropFilter(self)
self.control.installEventFilter(self._filter)
... | the_stack_v2_python_sparse | pychron/envisage/tasks/advanced_editor_area_pane.py | NMGRL/pychron | train | 38 | |
a4733ce990067ef7eab4073f308d66952e132018 | [
"super(mod_xes, self).__init__(address=address, **kwds)\nself.pickle_dirname = cspad_tbx.getOptString(pickle_dirname)\nself.pickle_basename = cspad_tbx.getOptString(pickle_basename)\nself.roi = cspad_tbx.getOptROI(roi)",
"super(mod_xes, self).event(evt, env)\nif evt.get('skip_event'):\n return\nif self.roi is ... | <|body_start_0|>
super(mod_xes, self).__init__(address=address, **kwds)
self.pickle_dirname = cspad_tbx.getOptString(pickle_dirname)
self.pickle_basename = cspad_tbx.getOptString(pickle_basename)
self.roi = cspad_tbx.getOptROI(roi)
<|end_body_0|>
<|body_start_1|>
super(mod_xes, ... | Class for generating first- and second-order statistics within the pyana framework XXX Maybe this module should be renamed to mod_stat12, mod_sstat or some such? | mod_xes | [
"BSD-3-Clause",
"BSD-3-Clause-LBNL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mod_xes:
"""Class for generating first- and second-order statistics within the pyana framework XXX Maybe this module should be renamed to mod_stat12, mod_sstat or some such?"""
def __init__(self, address, pickle_dirname='.', pickle_basename='', roi=None, **kwds):
"""The mod_average c... | stack_v2_sparse_classes_36k_train_006163 | 4,349 | permissive | [
{
"docstring": "The mod_average class constructor stores the parameters passed from the pyana configuration file in instance variables. All parameters, except @p address are optional, and hence need not be defined in pyana.cfg. @param address Full data source address of the DAQ device @param pickle_dirname Dire... | 3 | null | Implement the Python class `mod_xes` described below.
Class description:
Class for generating first- and second-order statistics within the pyana framework XXX Maybe this module should be renamed to mod_stat12, mod_sstat or some such?
Method signatures and docstrings:
- def __init__(self, address, pickle_dirname='.',... | Implement the Python class `mod_xes` described below.
Class description:
Class for generating first- and second-order statistics within the pyana framework XXX Maybe this module should be renamed to mod_stat12, mod_sstat or some such?
Method signatures and docstrings:
- def __init__(self, address, pickle_dirname='.',... | 77d66c719b5746f37af51ad593e2941ed6fbba17 | <|skeleton|>
class mod_xes:
"""Class for generating first- and second-order statistics within the pyana framework XXX Maybe this module should be renamed to mod_stat12, mod_sstat or some such?"""
def __init__(self, address, pickle_dirname='.', pickle_basename='', roi=None, **kwds):
"""The mod_average c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class mod_xes:
"""Class for generating first- and second-order statistics within the pyana framework XXX Maybe this module should be renamed to mod_stat12, mod_sstat or some such?"""
def __init__(self, address, pickle_dirname='.', pickle_basename='', roi=None, **kwds):
"""The mod_average class construc... | the_stack_v2_python_sparse | modules/cctbx_project/xfel/cxi/cspad_ana/mod_xes.py | jorgediazjr/dials-dev20191018 | train | 0 |
b2c8849b114ffbfe4722b43a1884203fb935c767 | [
"self._mask_num_classes = num_classes if use_category_for_mask else 1\nself._use_category_for_mask = use_category_for_mask\nself._num_downsample_channels = num_downsample_channels\nself._mask_crop_size = mask_crop_size\nself._num_convs = num_convs\nself._batch_norm_activation = batch_norm_activation",
"with tf.va... | <|body_start_0|>
self._mask_num_classes = num_classes if use_category_for_mask else 1
self._use_category_for_mask = use_category_for_mask
self._num_downsample_channels = num_downsample_channels
self._mask_crop_size = mask_crop_size
self._num_convs = num_convs
self._batch_... | ShapemaskCoarsemaskHead head. | ShapemaskCoarsemaskHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShapemaskCoarsemaskHead:
"""ShapemaskCoarsemaskHead head."""
def __init__(self, num_classes, num_downsample_channels, mask_crop_size, use_category_for_mask, num_convs, batch_norm_activation):
"""Initialize params to build ShapeMask coarse and fine prediction head. Args: num_classes: ... | stack_v2_sparse_classes_36k_train_006164 | 46,218 | permissive | [
{
"docstring": "Initialize params to build ShapeMask coarse and fine prediction head. Args: num_classes: `int` number of mask classification categories. num_downsample_channels: `int` number of filters at mask head. mask_crop_size: feature crop size. use_category_for_mask: use class information in mask branch. ... | 3 | null | Implement the Python class `ShapemaskCoarsemaskHead` described below.
Class description:
ShapemaskCoarsemaskHead head.
Method signatures and docstrings:
- def __init__(self, num_classes, num_downsample_channels, mask_crop_size, use_category_for_mask, num_convs, batch_norm_activation): Initialize params to build Shape... | Implement the Python class `ShapemaskCoarsemaskHead` described below.
Class description:
ShapemaskCoarsemaskHead head.
Method signatures and docstrings:
- def __init__(self, num_classes, num_downsample_channels, mask_crop_size, use_category_for_mask, num_convs, batch_norm_activation): Initialize params to build Shape... | 0f7adb97a93ec3e3485c261d030c507eb16b33e4 | <|skeleton|>
class ShapemaskCoarsemaskHead:
"""ShapemaskCoarsemaskHead head."""
def __init__(self, num_classes, num_downsample_channels, mask_crop_size, use_category_for_mask, num_convs, batch_norm_activation):
"""Initialize params to build ShapeMask coarse and fine prediction head. Args: num_classes: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShapemaskCoarsemaskHead:
"""ShapemaskCoarsemaskHead head."""
def __init__(self, num_classes, num_downsample_channels, mask_crop_size, use_category_for_mask, num_convs, batch_norm_activation):
"""Initialize params to build ShapeMask coarse and fine prediction head. Args: num_classes: `int` number ... | the_stack_v2_python_sparse | models/official/detection/modeling/architecture/heads.py | tensorflow/tpu | train | 5,627 |
c33383580f7ddf7a92122fc8650d60b05dfcbfd6 | [
"discrete_space, continuous_space = env.action_space.spaces\nassert isinstance(continuous_space, spaces.Box) or isinstance(continuous_space, spaces.Tuple), 'expected Box or Tuple for continuous action space, got {}'.format(type(continuous_space))\nsuper().__init__(env)\nself.low = np.zeros(continuous_space.shape, d... | <|body_start_0|>
discrete_space, continuous_space = env.action_space.spaces
assert isinstance(continuous_space, spaces.Box) or isinstance(continuous_space, spaces.Tuple), 'expected Box or Tuple for continuous action space, got {}'.format(type(continuous_space))
super().__init__(env)
self... | Rescales the continuous actions of a parameterized action space. | RescaleParameterizedAction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RescaleParameterizedAction:
"""Rescales the continuous actions of a parameterized action space."""
def __init__(self, env: Env, low: float, high: float):
"""Rescales the continuous actions of the parameterized action space to have the low and high given. Args: env: The environment wi... | stack_v2_sparse_classes_36k_train_006165 | 3,671 | permissive | [
{
"docstring": "Rescales the continuous actions of the parameterized action space to have the low and high given. Args: env: The environment with the action space to wrap. low: The infinum of the action space. hi gh: The suprenum of the action space.",
"name": "__init__",
"signature": "def __init__(self... | 3 | null | Implement the Python class `RescaleParameterizedAction` described below.
Class description:
Rescales the continuous actions of a parameterized action space.
Method signatures and docstrings:
- def __init__(self, env: Env, low: float, high: float): Rescales the continuous actions of the parameterized action space to h... | Implement the Python class `RescaleParameterizedAction` described below.
Class description:
Rescales the continuous actions of a parameterized action space.
Method signatures and docstrings:
- def __init__(self, env: Env, low: float, high: float): Rescales the continuous actions of the parameterized action space to h... | cde3be1c69bfd76fe4a78fa529e851d0a78318c7 | <|skeleton|>
class RescaleParameterizedAction:
"""Rescales the continuous actions of a parameterized action space."""
def __init__(self, env: Env, low: float, high: float):
"""Rescales the continuous actions of the parameterized action space to have the low and high given. Args: env: The environment wi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RescaleParameterizedAction:
"""Rescales the continuous actions of a parameterized action space."""
def __init__(self, env: Env, low: float, high: float):
"""Rescales the continuous actions of the parameterized action space to have the low and high given. Args: env: The environment with the action... | the_stack_v2_python_sparse | hlrl/core/envs/gym/wrappers/rescale_parameterized_action.py | Chainso/HLRL | train | 3 |
0b55c5d84ee26f11cc18460b2254ad0c99c82f28 | [
"self.request.errors.add('body', 'data', \"Can't update lot for tender stage2\")\nself.request.errors.status = 403\nreturn",
"self.request.errors.add('body', 'data', \"Can't create lot for tender stage2\")\nself.request.errors.status = 403\nreturn",
"self.request.errors.add('body', 'data', \"Can't delete lot fo... | <|body_start_0|>
self.request.errors.add('body', 'data', "Can't update lot for tender stage2")
self.request.errors.status = 403
return
<|end_body_0|>
<|body_start_1|>
self.request.errors.add('body', 'data', "Can't create lot for tender stage2")
self.request.errors.status = 403
... | TenderStage2EULotResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TenderStage2EULotResource:
def patch(self):
"""Update of lot"""
<|body_0|>
def collection_post(self):
"""Add a lot"""
<|body_1|>
def delete(self):
"""Lot deleting"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.request.erro... | stack_v2_sparse_classes_36k_train_006166 | 2,757 | permissive | [
{
"docstring": "Update of lot",
"name": "patch",
"signature": "def patch(self)"
},
{
"docstring": "Add a lot",
"name": "collection_post",
"signature": "def collection_post(self)"
},
{
"docstring": "Lot deleting",
"name": "delete",
"signature": "def delete(self)"
}
] | 3 | stack_v2_sparse_classes_30k_train_006203 | Implement the Python class `TenderStage2EULotResource` described below.
Class description:
Implement the TenderStage2EULotResource class.
Method signatures and docstrings:
- def patch(self): Update of lot
- def collection_post(self): Add a lot
- def delete(self): Lot deleting | Implement the Python class `TenderStage2EULotResource` described below.
Class description:
Implement the TenderStage2EULotResource class.
Method signatures and docstrings:
- def patch(self): Update of lot
- def collection_post(self): Add a lot
- def delete(self): Lot deleting
<|skeleton|>
class TenderStage2EULotReso... | fb955c110ceb40ca7b82b11280602145385a017f | <|skeleton|>
class TenderStage2EULotResource:
def patch(self):
"""Update of lot"""
<|body_0|>
def collection_post(self):
"""Add a lot"""
<|body_1|>
def delete(self):
"""Lot deleting"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TenderStage2EULotResource:
def patch(self):
"""Update of lot"""
self.request.errors.add('body', 'data', "Can't update lot for tender stage2")
self.request.errors.status = 403
return
def collection_post(self):
"""Add a lot"""
self.request.errors.add('body', ... | the_stack_v2_python_sparse | openprocurement/tender/competitivedialogue/views/stage2/lot.py | VDigitall/openprocurement.tender.competitivedialogue | train | 0 | |
f2e3089fd4f1179f25a16c39cadd49fb3d572b09 | [
"assert check_argument_types()\nsuper(StyleTokenLayer, self).__init__()\ngst_embs = paddle.randn(shape=[gst_tokens, gst_token_dim // gst_heads])\nself.gst_embs = paddle.create_parameter(shape=gst_embs.shape, dtype=str(gst_embs.numpy().dtype), default_initializer=paddle.nn.initializer.Assign(gst_embs))\nself.mha = M... | <|body_start_0|>
assert check_argument_types()
super(StyleTokenLayer, self).__init__()
gst_embs = paddle.randn(shape=[gst_tokens, gst_token_dim // gst_heads])
self.gst_embs = paddle.create_parameter(shape=gst_embs.shape, dtype=str(gst_embs.numpy().dtype), default_initializer=paddle.nn.in... | Style token layer module. This module is style token layer introduced in `Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`. .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`: https://arxiv.org/abs/1803.09017 Parameters ---... | StyleTokenLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StyleTokenLayer:
"""Style token layer module. This module is style token layer introduced in `Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`. .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`: http... | stack_v2_sparse_classes_36k_train_006167 | 10,798 | permissive | [
{
"docstring": "Initilize style token layer module.",
"name": "__init__",
"signature": "def __init__(self, ref_embed_dim: int=128, gst_tokens: int=10, gst_token_dim: int=256, gst_heads: int=4, dropout_rate: float=0.0)"
},
{
"docstring": "Calculate forward propagation. Parameters ---------- ref_e... | 2 | null | Implement the Python class `StyleTokenLayer` described below.
Class description:
Style token layer module. This module is style token layer introduced in `Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`. .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfe... | Implement the Python class `StyleTokenLayer` described below.
Class description:
Style token layer module. This module is style token layer introduced in `Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`. .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfe... | 8705a2a8405e3c63f2174d69880d2b5525a6c9fd | <|skeleton|>
class StyleTokenLayer:
"""Style token layer module. This module is style token layer introduced in `Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`. .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`: http... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StyleTokenLayer:
"""Style token layer module. This module is style token layer introduced in `Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`. .. _`Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis`: https://arxiv.org... | the_stack_v2_python_sparse | parakeet/modules/style_encoder.py | PaddlePaddle/Parakeet | train | 609 |
771d0a7fd546cd8ae30a47c296fc62c68c4566ea | [
"categories = Category.objects.all()\ncates = []\nnav_cates = []\nfor category in categories:\n if category.is_nav:\n nav_cates.append(category)\n else:\n cates.append(category)\nreturn {'nav_cates': nav_cates, 'cates': cates}",
"sidebars = SideBar.objects.filter(status=1)\nrecently_posts = Po... | <|body_start_0|>
categories = Category.objects.all()
cates = []
nav_cates = []
for category in categories:
if category.is_nav:
nav_cates.append(category)
else:
cates.append(category)
return {'nav_cates': nav_cates, 'cates': ... | CommonMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommonMixin:
def get_category_context(self):
"""分类 1、nav_cates = categoryies.filter(is_nav=True) 导航分类 2、cates = categories.filter(is_nav=False) 普通分类 3、Category.objects.all()返回一个queryset对象复制给categories"""
<|body_0|>
def get_context_data(self, **kwargs):
"""侧边栏"""
... | stack_v2_sparse_classes_36k_train_006168 | 5,314 | permissive | [
{
"docstring": "分类 1、nav_cates = categoryies.filter(is_nav=True) 导航分类 2、cates = categories.filter(is_nav=False) 普通分类 3、Category.objects.all()返回一个queryset对象复制给categories",
"name": "get_category_context",
"signature": "def get_category_context(self)"
},
{
"docstring": "侧边栏",
"name": "get_conte... | 2 | stack_v2_sparse_classes_30k_train_017908 | Implement the Python class `CommonMixin` described below.
Class description:
Implement the CommonMixin class.
Method signatures and docstrings:
- def get_category_context(self): 分类 1、nav_cates = categoryies.filter(is_nav=True) 导航分类 2、cates = categories.filter(is_nav=False) 普通分类 3、Category.objects.all()返回一个queryset对象复... | Implement the Python class `CommonMixin` described below.
Class description:
Implement the CommonMixin class.
Method signatures and docstrings:
- def get_category_context(self): 分类 1、nav_cates = categoryies.filter(is_nav=True) 导航分类 2、cates = categories.filter(is_nav=False) 普通分类 3、Category.objects.all()返回一个queryset对象复... | 52e74f18d37abc6e937d7cb5c752bc9dfd6ed662 | <|skeleton|>
class CommonMixin:
def get_category_context(self):
"""分类 1、nav_cates = categoryies.filter(is_nav=True) 导航分类 2、cates = categories.filter(is_nav=False) 普通分类 3、Category.objects.all()返回一个queryset对象复制给categories"""
<|body_0|>
def get_context_data(self, **kwargs):
"""侧边栏"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommonMixin:
def get_category_context(self):
"""分类 1、nav_cates = categoryies.filter(is_nav=True) 导航分类 2、cates = categories.filter(is_nav=False) 普通分类 3、Category.objects.all()返回一个queryset对象复制给categories"""
categories = Category.objects.all()
cates = []
nav_cates = []
for ... | the_stack_v2_python_sparse | Myblog/blog/views.py | Family-TreeSY/Myblog | train | 5 | |
2ccc503f8a9efd4aa08f95ef77e3b4988adb1420 | [
"comments = CommentsPhotos.query.order_by(asc(CommentsPhotos.PhotoID), asc(CommentsPhotos.Created)).all()\ncontents = jsonify({'comments': [{'commentID': comment.CommentID, 'photoID': comment.PhotoID, 'userID': comment.UserID, 'name': get_username(comment.UserID), 'comment': comment.Comment, 'createdAt': get_iso_fo... | <|body_start_0|>
comments = CommentsPhotos.query.order_by(asc(CommentsPhotos.PhotoID), asc(CommentsPhotos.Created)).all()
contents = jsonify({'comments': [{'commentID': comment.CommentID, 'photoID': comment.PhotoID, 'userID': comment.UserID, 'name': get_username(comment.UserID), 'comment': comment.Comme... | PhotoCommentsView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhotoCommentsView:
def index(self):
"""Return all comments for all photos."""
<|body_0|>
def get(self, photo_id):
"""Return the comments for a specific photo."""
<|body_1|>
def post(self):
"""Add a comment to a photo specified in the payload."""
... | stack_v2_sparse_classes_36k_train_006169 | 26,847 | permissive | [
{
"docstring": "Return all comments for all photos.",
"name": "index",
"signature": "def index(self)"
},
{
"docstring": "Return the comments for a specific photo.",
"name": "get",
"signature": "def get(self, photo_id)"
},
{
"docstring": "Add a comment to a photo specified in the ... | 5 | stack_v2_sparse_classes_30k_train_019069 | Implement the Python class `PhotoCommentsView` described below.
Class description:
Implement the PhotoCommentsView class.
Method signatures and docstrings:
- def index(self): Return all comments for all photos.
- def get(self, photo_id): Return the comments for a specific photo.
- def post(self): Add a comment to a p... | Implement the Python class `PhotoCommentsView` described below.
Class description:
Implement the PhotoCommentsView class.
Method signatures and docstrings:
- def index(self): Return all comments for all photos.
- def get(self, photo_id): Return the comments for a specific photo.
- def post(self): Add a comment to a p... | 62f8e8e904e379541193f0cbb91a8434b47f538f | <|skeleton|>
class PhotoCommentsView:
def index(self):
"""Return all comments for all photos."""
<|body_0|>
def get(self, photo_id):
"""Return the comments for a specific photo."""
<|body_1|>
def post(self):
"""Add a comment to a photo specified in the payload."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhotoCommentsView:
def index(self):
"""Return all comments for all photos."""
comments = CommentsPhotos.query.order_by(asc(CommentsPhotos.PhotoID), asc(CommentsPhotos.Created)).all()
contents = jsonify({'comments': [{'commentID': comment.CommentID, 'photoID': comment.PhotoID, 'userID':... | the_stack_v2_python_sparse | apps/comments/views.py | Torniojaws/vortech-backend | train | 0 | |
d2358f34e298d0542adfe7debf59b270859f0e2c | [
"pos = 1\ncur = k\ncount = k\nwhile pos < n:\n if k % 2 == 0:\n cur = cur // 2\n else:\n cur = cur // 2 + 1\n count += cur\n pos += 1\nreturn count",
"l = 1\nr = m\nmid = l + (r - l) // 2\nwhile l <= r:\n v = self.compute(n, mid)\n if v == m:\n return mid\n elif v > m:\n ... | <|body_start_0|>
pos = 1
cur = k
count = k
while pos < n:
if k % 2 == 0:
cur = cur // 2
else:
cur = cur // 2 + 1
count += cur
pos += 1
return count
<|end_body_0|>
<|body_start_1|>
l = 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def compute(self, n, k):
"""第一天吃k块, 至少需要多少块. :param k: :return:"""
<|body_0|>
def twosplit(self, n, m):
""":param n: 天数 :param m: 巧克力数量 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pos = 1
cur = k
count = k
... | stack_v2_sparse_classes_36k_train_006170 | 914 | no_license | [
{
"docstring": "第一天吃k块, 至少需要多少块. :param k: :return:",
"name": "compute",
"signature": "def compute(self, n, k)"
},
{
"docstring": ":param n: 天数 :param m: 巧克力数量 :return:",
"name": "twosplit",
"signature": "def twosplit(self, n, m)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015837 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compute(self, n, k): 第一天吃k块, 至少需要多少块. :param k: :return:
- def twosplit(self, n, m): :param n: 天数 :param m: 巧克力数量 :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compute(self, n, k): 第一天吃k块, 至少需要多少块. :param k: :return:
- def twosplit(self, n, m): :param n: 天数 :param m: 巧克力数量 :return:
<|skeleton|>
class Solution:
def compute(self... | 4e03eee4558800e6e23504840401bb0544fac752 | <|skeleton|>
class Solution:
def compute(self, n, k):
"""第一天吃k块, 至少需要多少块. :param k: :return:"""
<|body_0|>
def twosplit(self, n, m):
""":param n: 天数 :param m: 巧克力数量 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def compute(self, n, k):
"""第一天吃k块, 至少需要多少块. :param k: :return:"""
pos = 1
cur = k
count = k
while pos < n:
if k % 2 == 0:
cur = cur // 2
else:
cur = cur // 2 + 1
count += cur
pos ... | the_stack_v2_python_sparse | leetcode_ex/ex贪吃的小q.py | LNZ001/Analysis-of-algorithm-exercises | train | 0 | |
87d52fce0c5028d4b402759a700e64d54da1b79c | [
"self.gyx = 0\nself.gyy = 0\nself.gyz = 0\nself.acx = 0\nself.acy = 0\nself.acz = 0\nself.prs = 0\nself.temp = 0\nself.arduino = arduino",
"dicioDeDados = self.arduino.dicioDeDados\nif 'acx' in dicioDeDados:\n self.acx = dicioDeDados['acx']\nif 'acy' in dicioDeDados:\n self.acy = dicioDeDados['acy']\nif 'ac... | <|body_start_0|>
self.gyx = 0
self.gyy = 0
self.gyz = 0
self.acx = 0
self.acy = 0
self.acz = 0
self.prs = 0
self.temp = 0
self.arduino = arduino
<|end_body_0|>
<|body_start_1|>
dicioDeDados = self.arduino.dicioDeDados
if 'acx' in d... | Um objeto dessa classe deve ser criado quando quiser realizar a comunicação ou obter dados da MPU (Acelerômetro e Giroscópio). Para utilizar a classe, criamos o construtor colocando como parâmetros se queremos pegar os parâmetros. Depois, utilizamos a função atualiza() para fazer a aquisição pelo I2C. Por fim, acessa o... | IMU | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IMU:
"""Um objeto dessa classe deve ser criado quando quiser realizar a comunicação ou obter dados da MPU (Acelerômetro e Giroscópio). Para utilizar a classe, criamos o construtor colocando como parâmetros se queremos pegar os parâmetros. Depois, utilizamos a função atualiza() para fazer a aquisi... | stack_v2_sparse_classes_36k_train_006171 | 1,618 | permissive | [
{
"docstring": "Inicializa a classe com os parâmetros setados para adquirir e realiza configurações para aquisição do I2C.",
"name": "__init__",
"signature": "def __init__(self, arduino)"
},
{
"docstring": "Le valor analogico do ADC e transforma isso em pressão e velocidade. Todas as variaveis s... | 2 | stack_v2_sparse_classes_30k_train_007642 | Implement the Python class `IMU` described below.
Class description:
Um objeto dessa classe deve ser criado quando quiser realizar a comunicação ou obter dados da MPU (Acelerômetro e Giroscópio). Para utilizar a classe, criamos o construtor colocando como parâmetros se queremos pegar os parâmetros. Depois, utilizamos ... | Implement the Python class `IMU` described below.
Class description:
Um objeto dessa classe deve ser criado quando quiser realizar a comunicação ou obter dados da MPU (Acelerômetro e Giroscópio). Para utilizar a classe, criamos o construtor colocando como parâmetros se queremos pegar os parâmetros. Depois, utilizamos ... | 28162dab4b115232442a331dbdeacd13c0b1abc2 | <|skeleton|>
class IMU:
"""Um objeto dessa classe deve ser criado quando quiser realizar a comunicação ou obter dados da MPU (Acelerômetro e Giroscópio). Para utilizar a classe, criamos o construtor colocando como parâmetros se queremos pegar os parâmetros. Depois, utilizamos a função atualiza() para fazer a aquisi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IMU:
"""Um objeto dessa classe deve ser criado quando quiser realizar a comunicação ou obter dados da MPU (Acelerômetro e Giroscópio). Para utilizar a classe, criamos o construtor colocando como parâmetros se queremos pegar os parâmetros. Depois, utilizamos a função atualiza() para fazer a aquisição pelo I2C.... | the_stack_v2_python_sparse | code/libs/sensors/imu.py | solkan1201/Vivace | train | 0 |
d9b0202788216d0a3536f3d80b470c2da58c54d5 | [
"self.settings = tools.getSettingsObject()\nlastBackup = int(self.settings['System']['Backup']['lastBackup'])\nnow = int(tools.makeDateStamp())\nself.doBackup()\nprojConf = tools.getProjectSettingsObject()\nprojConf['System']['Backup']['lastBackup'] = now\nprojConf.write()\nself.settings['System']['Backup']['lastBa... | <|body_start_0|>
self.settings = tools.getSettingsObject()
lastBackup = int(self.settings['System']['Backup']['lastBackup'])
now = int(tools.makeDateStamp())
self.doBackup()
projConf = tools.getProjectSettingsObject()
projConf['System']['Backup']['lastBackup'] = now
... | BackupProject | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackupProject:
def main(self):
"""Here we will manage the backup process."""
<|body_0|>
def doBackup(self):
"""This is the main backup process."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.settings = tools.getSettingsObject()
lastBac... | stack_v2_sparse_classes_36k_train_006172 | 2,572 | no_license | [
{
"docstring": "Here we will manage the backup process.",
"name": "main",
"signature": "def main(self)"
},
{
"docstring": "This is the main backup process.",
"name": "doBackup",
"signature": "def doBackup(self)"
}
] | 2 | null | Implement the Python class `BackupProject` described below.
Class description:
Implement the BackupProject class.
Method signatures and docstrings:
- def main(self): Here we will manage the backup process.
- def doBackup(self): This is the main backup process. | Implement the Python class `BackupProject` described below.
Class description:
Implement the BackupProject class.
Method signatures and docstrings:
- def main(self): Here we will manage the backup process.
- def doBackup(self): This is the main backup process.
<|skeleton|>
class BackupProject:
def main(self):
... | 315e2e7544e2001404b8d7dbfdd1ffbee5e389f8 | <|skeleton|>
class BackupProject:
def main(self):
"""Here we will manage the backup process."""
<|body_0|>
def doBackup(self):
"""This is the main backup process."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BackupProject:
def main(self):
"""Here we will manage the backup process."""
self.settings = tools.getSettingsObject()
lastBackup = int(self.settings['System']['Backup']['lastBackup'])
now = int(tools.makeDateStamp())
self.doBackup()
projConf = tools.getProjectS... | the_stack_v2_python_sparse | bin/python/lib_system/backup_project.py | sillsdevarchive/ptxplus | train | 0 | |
17cac3f29858b7edb8053fab35a6f5e04545cc6f | [
"if verbose:\n print('SQL Database type %s verbose=%s' % (db_dict, verbose))\nsuper(SQLLastScanTable, self).__init__(db_dict, dbtype, verbose)\nself.connection = None",
"try:\n print('database characteristics')\n for key in self.db_dict:\n print('%s: %s' % (key, self.db_dict[key]))\nexcept ValueE... | <|body_start_0|>
if verbose:
print('SQL Database type %s verbose=%s' % (db_dict, verbose))
super(SQLLastScanTable, self).__init__(db_dict, dbtype, verbose)
self.connection = None
<|end_body_0|>
<|body_start_1|>
try:
print('database characteristics')
... | SQL table for Last scan | SQLLastScanTable | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SQLLastScanTable:
"""SQL table for Last scan"""
def __init__(self, db_dict, dbtype, verbose):
"""Pass through to SQL"""
<|body_0|>
def db_info(self):
"""Display the db info and Return info on the database used as a dictionary."""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_006173 | 6,482 | permissive | [
{
"docstring": "Pass through to SQL",
"name": "__init__",
"signature": "def __init__(self, db_dict, dbtype, verbose)"
},
{
"docstring": "Display the db info and Return info on the database used as a dictionary.",
"name": "db_info",
"signature": "def db_info(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017763 | Implement the Python class `SQLLastScanTable` described below.
Class description:
SQL table for Last scan
Method signatures and docstrings:
- def __init__(self, db_dict, dbtype, verbose): Pass through to SQL
- def db_info(self): Display the db info and Return info on the database used as a dictionary. | Implement the Python class `SQLLastScanTable` described below.
Class description:
SQL table for Last scan
Method signatures and docstrings:
- def __init__(self, db_dict, dbtype, verbose): Pass through to SQL
- def db_info(self): Display the db info and Return info on the database used as a dictionary.
<|skeleton|>
c... | 9c60b3489f02592bd9099b8719ca23ae43a9eaa5 | <|skeleton|>
class SQLLastScanTable:
"""SQL table for Last scan"""
def __init__(self, db_dict, dbtype, verbose):
"""Pass through to SQL"""
<|body_0|>
def db_info(self):
"""Display the db info and Return info on the database used as a dictionary."""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SQLLastScanTable:
"""SQL table for Last scan"""
def __init__(self, db_dict, dbtype, verbose):
"""Pass through to SQL"""
if verbose:
print('SQL Database type %s verbose=%s' % (db_dict, verbose))
super(SQLLastScanTable, self).__init__(db_dict, dbtype, verbose)
s... | the_stack_v2_python_sparse | smipyping/_lastscantable.py | KSchopmeyer/smipyping | train | 0 |
34045d5cf713f009d944664c24c7d912d94e9354 | [
"self.inputs = []\nself.outputs = []\nself.pos = pos\nself.new_w = None\nself.new_b = None\nself.extra_attr = None\nself.klayer = klayer\nif klayer is None:\n return\nself.name = prefix + klayer.name + postfix\nself.type = helper.getKerasLayerType(self.klayer)\nif hasattr(klayer, 'data_format'):\n if helper.d... | <|body_start_0|>
self.inputs = []
self.outputs = []
self.pos = pos
self.new_w = None
self.new_b = None
self.extra_attr = None
self.klayer = klayer
if klayer is None:
return
self.name = prefix + klayer.name + postfix
self.type = ... | Intermedia structure for model graph | TreeNode | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreeNode:
"""Intermedia structure for model graph"""
def __init__(self, klayer=None, prefix='', postfix='', pos=0):
"""Initialize a tree node object # Arguments: klayer: The layer defined in keras. prefix: The prefix inherited from the parent layer. No prefix by default. postfix: Usu... | stack_v2_sparse_classes_36k_train_006174 | 3,764 | permissive | [
{
"docstring": "Initialize a tree node object # Arguments: klayer: The layer defined in keras. prefix: The prefix inherited from the parent layer. No prefix by default. postfix: Usually the position name of the node for the shared layer. pos: The position of the current node among all duplicated shared layers."... | 6 | stack_v2_sparse_classes_30k_train_004984 | Implement the Python class `TreeNode` described below.
Class description:
Intermedia structure for model graph
Method signatures and docstrings:
- def __init__(self, klayer=None, prefix='', postfix='', pos=0): Initialize a tree node object # Arguments: klayer: The layer defined in keras. prefix: The prefix inherited ... | Implement the Python class `TreeNode` described below.
Class description:
Intermedia structure for model graph
Method signatures and docstrings:
- def __init__(self, klayer=None, prefix='', postfix='', pos=0): Initialize a tree node object # Arguments: klayer: The layer defined in keras. prefix: The prefix inherited ... | 7ba4fe3fd9f606d39cf61b46080c3dc244dfe207 | <|skeleton|>
class TreeNode:
"""Intermedia structure for model graph"""
def __init__(self, klayer=None, prefix='', postfix='', pos=0):
"""Initialize a tree node object # Arguments: klayer: The layer defined in keras. prefix: The prefix inherited from the parent layer. No prefix by default. postfix: Usu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TreeNode:
"""Intermedia structure for model graph"""
def __init__(self, klayer=None, prefix='', postfix='', pos=0):
"""Initialize a tree node object # Arguments: klayer: The layer defined in keras. prefix: The prefix inherited from the parent layer. No prefix by default. postfix: Usually the posi... | the_stack_v2_python_sparse | keras-onnx/onnx_keras/tree_structure.py | WeiChe-Huang/ONNX_Convertor | train | 0 |
9c3a655c5779af63b5e3bd80a2eaf6e10eff0cd2 | [
"super(WorkflowsYamlConfigurationWriter, self).__init__()\nself.__filesystem = filesystem\nself.__tables_configuration = tables_configuration\nself.__logger = logger",
"common_data = {'table_base_location': 's3://${swampBucket}/<source>/<database>.<schema>/', 'db_connection_string': tables_information['db_connect... | <|body_start_0|>
super(WorkflowsYamlConfigurationWriter, self).__init__()
self.__filesystem = filesystem
self.__tables_configuration = tables_configuration
self.__logger = logger
<|end_body_0|>
<|body_start_1|>
common_data = {'table_base_location': 's3://${swampBucket}/<source>/... | Write the YAML configuration files needed to run the workflows | WorkflowsYamlConfigurationWriter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkflowsYamlConfigurationWriter:
"""Write the YAML configuration files needed to run the workflows"""
def __init__(self, filesystem, tables_configuration, logger):
"""Initialize the class :param filesystem: Filesystem :param tables_configuration: TablesConfiguration :param logger: L... | stack_v2_sparse_classes_36k_train_006175 | 4,261 | permissive | [
{
"docstring": "Initialize the class :param filesystem: Filesystem :param tables_configuration: TablesConfiguration :param logger: Logging",
"name": "__init__",
"signature": "def __init__(self, filesystem, tables_configuration, logger)"
},
{
"docstring": "Given tables and database connection inf... | 2 | null | Implement the Python class `WorkflowsYamlConfigurationWriter` described below.
Class description:
Write the YAML configuration files needed to run the workflows
Method signatures and docstrings:
- def __init__(self, filesystem, tables_configuration, logger): Initialize the class :param filesystem: Filesystem :param t... | Implement the Python class `WorkflowsYamlConfigurationWriter` described below.
Class description:
Write the YAML configuration files needed to run the workflows
Method signatures and docstrings:
- def __init__(self, filesystem, tables_configuration, logger): Initialize the class :param filesystem: Filesystem :param t... | d0e52277daff523eda63f5d3137b5a990413923d | <|skeleton|>
class WorkflowsYamlConfigurationWriter:
"""Write the YAML configuration files needed to run the workflows"""
def __init__(self, filesystem, tables_configuration, logger):
"""Initialize the class :param filesystem: Filesystem :param tables_configuration: TablesConfiguration :param logger: L... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkflowsYamlConfigurationWriter:
"""Write the YAML configuration files needed to run the workflows"""
def __init__(self, filesystem, tables_configuration, logger):
"""Initialize the class :param filesystem: Filesystem :param tables_configuration: TablesConfiguration :param logger: Logging"""
... | the_stack_v2_python_sparse | src/slippinj/filesystem/yaml_configuration.py | cupid4/slippin-jimmy | train | 0 |
29a8e30590090fdb239510371528bf28671d5b6c | [
"if not root:\n return []\norder = [[]]\nqueue = [(root, 0)]\nwhile queue:\n curr = queue[0]\n if len(order) < curr[1] + 1:\n order.append([])\n order[curr[1]].append(curr[0].val)\n del queue[0]\n if curr[0].left:\n queue.append((curr[0].left, curr[1] + 1))\n if curr[0].right:\n ... | <|body_start_0|>
if not root:
return []
order = [[]]
queue = [(root, 0)]
while queue:
curr = queue[0]
if len(order) < curr[1] + 1:
order.append([])
order[curr[1]].append(curr[0].val)
del queue[0]
if c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrderBottom(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_006176 | 2,510 | 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": "levelOrderBottom",
"signature": "def levelOrderBottom(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018822 | 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 levelOrderBottom(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 levelOrderBottom(self, root): :type root: TreeNode :rtype: List[List[int]]
<|skeleton|>
class Solu... | 0584b86642dff667f5bf6b7acfbbce86a41a55b6 | <|skeleton|>
class Solution:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrderBottom(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 []
order = [[]]
queue = [(root, 0)]
while queue:
curr = queue[0]
if len(order) < curr[1] + 1:
order.append([]... | the_stack_v2_python_sparse | python_solution/101_110/BinaryTreeLevelOrderTraversal.py | CescWang1991/LeetCode-Python | train | 1 | |
18304955acfc7cdcf25e313a437e1f6a78c305d3 | [
"if len(self.children) == 1 and self.children[0].qname() == (dav_namespace, 'all'):\n return True\n\ndef isAggregate(supportedPrivilege):\n sp = supportedPrivilege.childOfType(Privilege)\n if sp == self:\n\n def find(supportedPrivilege):\n if supportedPrivilege.childOfType(Privilege) == s... | <|body_start_0|>
if len(self.children) == 1 and self.children[0].qname() == (dav_namespace, 'all'):
return True
def isAggregate(supportedPrivilege):
sp = supportedPrivilege.childOfType(Privilege)
if sp == self:
def find(supportedPrivilege):
... | Identifies a privilege. (RFC 3744, sections 5.3 and 5.5.1) | Privilege | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Privilege:
"""Identifies a privilege. (RFC 3744, sections 5.3 and 5.5.1)"""
def isAggregateOf(self, subprivilege, supportedPrivileges):
"""Check whether this privilege is an aggregate of another. @param subprivilege: a L{Privilege} @param supportedPrivileges: a L{SupportedPrivilegeSe... | stack_v2_sparse_classes_36k_train_006177 | 26,487 | permissive | [
{
"docstring": "Check whether this privilege is an aggregate of another. @param subprivilege: a L{Privilege} @param supportedPrivileges: a L{SupportedPrivilegeSet} @return: C{True} is this privilege is an aggregate of C{subprivilege} according to C{supportedPrivileges}.",
"name": "isAggregateOf",
"signa... | 2 | stack_v2_sparse_classes_30k_train_015469 | Implement the Python class `Privilege` described below.
Class description:
Identifies a privilege. (RFC 3744, sections 5.3 and 5.5.1)
Method signatures and docstrings:
- def isAggregateOf(self, subprivilege, supportedPrivileges): Check whether this privilege is an aggregate of another. @param subprivilege: a L{Privil... | Implement the Python class `Privilege` described below.
Class description:
Identifies a privilege. (RFC 3744, sections 5.3 and 5.5.1)
Method signatures and docstrings:
- def isAggregateOf(self, subprivilege, supportedPrivileges): Check whether this privilege is an aggregate of another. @param subprivilege: a L{Privil... | cb2962f1f1927f1e52ea405094fa3e7e180f23cb | <|skeleton|>
class Privilege:
"""Identifies a privilege. (RFC 3744, sections 5.3 and 5.5.1)"""
def isAggregateOf(self, subprivilege, supportedPrivileges):
"""Check whether this privilege is an aggregate of another. @param subprivilege: a L{Privilege} @param supportedPrivileges: a L{SupportedPrivilegeSe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Privilege:
"""Identifies a privilege. (RFC 3744, sections 5.3 and 5.5.1)"""
def isAggregateOf(self, subprivilege, supportedPrivileges):
"""Check whether this privilege is an aggregate of another. @param subprivilege: a L{Privilege} @param supportedPrivileges: a L{SupportedPrivilegeSet} @return: C... | the_stack_v2_python_sparse | txdav/xml/rfc3744.py | ass-a2s/ccs-calendarserver | train | 2 |
3d2b488ec37bf23033803e9a30c8c872f48ab3e8 | [
"Sum = 0\nif n == 1 or n == 0:\n return 1\nif n % 2 == 0:\n for i in range(0, n // 2):\n Sum += 2 * self.numTrees(i) * self.numTrees(n - 1 - i)\n return Sum\nelse:\n for i in range(0, n // 2):\n Sum += 2 * self.numTrees(i) * self.numTrees(n - 1 - i)\n return Sum + self.numTrees(n // 2) ... | <|body_start_0|>
Sum = 0
if n == 1 or n == 0:
return 1
if n % 2 == 0:
for i in range(0, n // 2):
Sum += 2 * self.numTrees(i) * self.numTrees(n - 1 - i)
return Sum
else:
for i in range(0, n // 2):
Sum += 2 * s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numTrees2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Sum = 0
if n == 1 or n == 0:
return 1
if n % 2... | stack_v2_sparse_classes_36k_train_006178 | 1,102 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "numTrees",
"signature": "def numTrees(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "numTrees2",
"signature": "def numTrees2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004835 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numTrees(self, n): :type n: int :rtype: int
- def numTrees2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numTrees(self, n): :type n: int :rtype: int
- def numTrees2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def numTrees(self, n):
""":type n: i... | 6ed06f5d1b27b5d13e8a2f590d781053bccf3a12 | <|skeleton|>
class Solution:
def numTrees(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numTrees2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numTrees(self, n):
""":type n: int :rtype: int"""
Sum = 0
if n == 1 or n == 0:
return 1
if n % 2 == 0:
for i in range(0, n // 2):
Sum += 2 * self.numTrees(i) * self.numTrees(n - 1 - i)
return Sum
else:
... | the_stack_v2_python_sparse | Tree/Unique Binary Search Trees.py | lll109512/LeetCode | train | 0 | |
f16c84514defbbc1319eead11515ff60d318300d | [
"self.min_val = min_val\nself.max_val = max_val\nself.alpha = alpha\nself.beta = beta",
"if X.pixeltype != 'float':\n raise ValueError('image.pixeltype must be float ... use TypeCast transform or clone to float')\ninsuffix = X._libsuffix\ncast_fn = utils.get_lib_fn('sigmoidAntsImage%s' % insuffix)\ncasted_ptr ... | <|body_start_0|>
self.min_val = min_val
self.max_val = max_val
self.alpha = alpha
self.beta = beta
<|end_body_0|>
<|body_start_1|>
if X.pixeltype != 'float':
raise ValueError('image.pixeltype must be float ... use TypeCast transform or clone to float')
insuff... | Transform an image using a sigmoid function | SigmoidIntensity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SigmoidIntensity:
"""Transform an image using a sigmoid function"""
def __init__(self, min_val, max_val, alpha, beta):
"""Initialize a SigmoidIntensity transform Arguments --------- min_val : float minimum value max_val : float maximum value alpha : float alpha value for sigmoid beta... | stack_v2_sparse_classes_36k_train_006179 | 24,297 | permissive | [
{
"docstring": "Initialize a SigmoidIntensity transform Arguments --------- min_val : float minimum value max_val : float maximum value alpha : float alpha value for sigmoid beta : flaot beta value for sigmoid Example ------- >>> import ants >>> sigscaler = ants.contrib.SigmoidIntensity(0,1,1,1)",
"name": "... | 2 | null | Implement the Python class `SigmoidIntensity` described below.
Class description:
Transform an image using a sigmoid function
Method signatures and docstrings:
- def __init__(self, min_val, max_val, alpha, beta): Initialize a SigmoidIntensity transform Arguments --------- min_val : float minimum value max_val : float... | Implement the Python class `SigmoidIntensity` described below.
Class description:
Transform an image using a sigmoid function
Method signatures and docstrings:
- def __init__(self, min_val, max_val, alpha, beta): Initialize a SigmoidIntensity transform Arguments --------- min_val : float minimum value max_val : float... | 41f2dd3fcf72654f284dac1a9448033e963f0afb | <|skeleton|>
class SigmoidIntensity:
"""Transform an image using a sigmoid function"""
def __init__(self, min_val, max_val, alpha, beta):
"""Initialize a SigmoidIntensity transform Arguments --------- min_val : float minimum value max_val : float maximum value alpha : float alpha value for sigmoid beta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SigmoidIntensity:
"""Transform an image using a sigmoid function"""
def __init__(self, min_val, max_val, alpha, beta):
"""Initialize a SigmoidIntensity transform Arguments --------- min_val : float minimum value max_val : float maximum value alpha : float alpha value for sigmoid beta : flaot beta... | the_stack_v2_python_sparse | ants/contrib/sampling/transforms.py | ANTsX/ANTsPy | train | 483 |
f134a40446d6c1f8cd4e047c68d64a3af6a7bde6 | [
"i = low - 1\nchange = array[high]\nfor j in range(low, high):\n if array[j] <= change:\n i = i + 1\n array[i], array[j] = (array[j], array[i])\narray[i + 1], array[high] = (array[high], array[i + 1])\nreturn i + 1",
"if low < high:\n pi = self.splitter(array, low, high)\n self.quickSort(ar... | <|body_start_0|>
i = low - 1
change = array[high]
for j in range(low, high):
if array[j] <= change:
i = i + 1
array[i], array[j] = (array[j], array[i])
array[i + 1], array[high] = (array[high], array[i + 1])
return i + 1
<|end_body_0|>
... | QuickSort | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuickSort:
def splitter(array: list, low: int, high: int) -> int:
"""A function that splits an array Parameters low - starting boundary value high - starting boundary value array - entered list"""
<|body_0|>
def quickSort(self, array, low, high) -> None:
"""Main func... | stack_v2_sparse_classes_36k_train_006180 | 1,236 | no_license | [
{
"docstring": "A function that splits an array Parameters low - starting boundary value high - starting boundary value array - entered list",
"name": "splitter",
"signature": "def splitter(array: list, low: int, high: int) -> int"
},
{
"docstring": "Main function of sorting",
"name": "quick... | 2 | stack_v2_sparse_classes_30k_train_021011 | Implement the Python class `QuickSort` described below.
Class description:
Implement the QuickSort class.
Method signatures and docstrings:
- def splitter(array: list, low: int, high: int) -> int: A function that splits an array Parameters low - starting boundary value high - starting boundary value array - entered l... | Implement the Python class `QuickSort` described below.
Class description:
Implement the QuickSort class.
Method signatures and docstrings:
- def splitter(array: list, low: int, high: int) -> int: A function that splits an array Parameters low - starting boundary value high - starting boundary value array - entered l... | dad4ccf4e3d420dc7fa04656efc851088bb57eb7 | <|skeleton|>
class QuickSort:
def splitter(array: list, low: int, high: int) -> int:
"""A function that splits an array Parameters low - starting boundary value high - starting boundary value array - entered list"""
<|body_0|>
def quickSort(self, array, low, high) -> None:
"""Main func... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuickSort:
def splitter(array: list, low: int, high: int) -> int:
"""A function that splits an array Parameters low - starting boundary value high - starting boundary value array - entered list"""
i = low - 1
change = array[high]
for j in range(low, high):
if array[... | the_stack_v2_python_sparse | algorithms/algorithms_practice/quick_sort.py | lazorikv/python-education | train | 0 | |
97ee880dbda4007a4d29b15025b672cf45d9ebf9 | [
"self.archival_target = archival_target\nself.cloud_replication_target = cloud_replication_target\nself.days_to_keep = days_to_keep\nself.hold_for_legal_purpose = hold_for_legal_purpose\nself.replication_target = replication_target\nself.mtype = mtype",
"if dictionary is None:\n return None\narchival_target = ... | <|body_start_0|>
self.archival_target = archival_target
self.cloud_replication_target = cloud_replication_target
self.days_to_keep = days_to_keep
self.hold_for_legal_purpose = hold_for_legal_purpose
self.replication_target = replication_target
self.mtype = mtype
<|end_bod... | Implementation of the 'RunJobSnapshotTarget' model. Specifies settings for a Copy Task when a Protection is run. It gives the target location for the Snapshot and its retention. Attributes: archival_target (ArchivalExternalTarget): Specifies the Archival External Target for storing a copied Snapshot. If the type is not... | RunJobSnapshotTarget | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunJobSnapshotTarget:
"""Implementation of the 'RunJobSnapshotTarget' model. Specifies settings for a Copy Task when a Protection is run. It gives the target location for the Snapshot and its retention. Attributes: archival_target (ArchivalExternalTarget): Specifies the Archival External Target f... | stack_v2_sparse_classes_36k_train_006181 | 5,344 | permissive | [
{
"docstring": "Constructor for the RunJobSnapshotTarget class",
"name": "__init__",
"signature": "def __init__(self, archival_target=None, cloud_replication_target=None, days_to_keep=None, hold_for_legal_purpose=None, replication_target=None, mtype=None)"
},
{
"docstring": "Creates an instance ... | 2 | null | Implement the Python class `RunJobSnapshotTarget` described below.
Class description:
Implementation of the 'RunJobSnapshotTarget' model. Specifies settings for a Copy Task when a Protection is run. It gives the target location for the Snapshot and its retention. Attributes: archival_target (ArchivalExternalTarget): S... | Implement the Python class `RunJobSnapshotTarget` described below.
Class description:
Implementation of the 'RunJobSnapshotTarget' model. Specifies settings for a Copy Task when a Protection is run. It gives the target location for the Snapshot and its retention. Attributes: archival_target (ArchivalExternalTarget): S... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RunJobSnapshotTarget:
"""Implementation of the 'RunJobSnapshotTarget' model. Specifies settings for a Copy Task when a Protection is run. It gives the target location for the Snapshot and its retention. Attributes: archival_target (ArchivalExternalTarget): Specifies the Archival External Target f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunJobSnapshotTarget:
"""Implementation of the 'RunJobSnapshotTarget' model. Specifies settings for a Copy Task when a Protection is run. It gives the target location for the Snapshot and its retention. Attributes: archival_target (ArchivalExternalTarget): Specifies the Archival External Target for storing a ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/run_job_snapshot_target.py | cohesity/management-sdk-python | train | 24 |
ed23ecd66262e9a323d2d2943b8f08f6728d1b19 | [
"self.debug = debug\nself.model_file_path = model_file_path\ntry:\n self.model_grammar = nocomment(open(ModelParser.grammar_file, 'r').read())\nexcept OSError as e:\n raise ModelGrammarFileOpen(ModelParser.grammar_file)\ntry:\n self.model_text = nocomment(open(self.model_file_path, 'r').read())\nexcept OSE... | <|body_start_0|>
self.debug = debug
self.model_file_path = model_file_path
try:
self.model_grammar = nocomment(open(ModelParser.grammar_file, 'r').read())
except OSError as e:
raise ModelGrammarFileOpen(ModelParser.grammar_file)
try:
self.model... | Parses an Executable UML subsystem model input file using the arpeggio parser generator Attributes - grammar_file -- (class based) Name of the system file defining the Executable UML grammar - root_rule_name -- (class based) Name of the top level grammar element found in grammar file - debug -- debug flag (used to set ... | ModelParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelParser:
"""Parses an Executable UML subsystem model input file using the arpeggio parser generator Attributes - grammar_file -- (class based) Name of the system file defining the Executable UML grammar - root_rule_name -- (class based) Name of the top level grammar element found in grammar f... | stack_v2_sparse_classes_36k_train_006182 | 4,980 | permissive | [
{
"docstring": "Constructor :param model_file_path: Where to find the user supplied model input file :param debug: Debug flag",
"name": "__init__",
"signature": "def __init__(self, model_file_path, debug=True)"
},
{
"docstring": "Parse the model file and return the content :return: The abstract ... | 2 | stack_v2_sparse_classes_30k_train_019953 | Implement the Python class `ModelParser` described below.
Class description:
Parses an Executable UML subsystem model input file using the arpeggio parser generator Attributes - grammar_file -- (class based) Name of the system file defining the Executable UML grammar - root_rule_name -- (class based) Name of the top l... | Implement the Python class `ModelParser` described below.
Class description:
Parses an Executable UML subsystem model input file using the arpeggio parser generator Attributes - grammar_file -- (class based) Name of the system file defining the Executable UML grammar - root_rule_name -- (class based) Name of the top l... | 088e27cded9eca2cacba2c6168c03caf4b43ef72 | <|skeleton|>
class ModelParser:
"""Parses an Executable UML subsystem model input file using the arpeggio parser generator Attributes - grammar_file -- (class based) Name of the system file defining the Executable UML grammar - root_rule_name -- (class based) Name of the top level grammar element found in grammar f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelParser:
"""Parses an Executable UML subsystem model input file using the arpeggio parser generator Attributes - grammar_file -- (class based) Name of the system file defining the Executable UML grammar - root_rule_name -- (class based) Name of the top level grammar element found in grammar file - debug -... | the_stack_v2_python_sparse | flatland/input/model_parser.py | Laurelinex/flatland-model-diagram-editor | train | 0 |
152aff2507e410d3883eb54100d6d8551b621fb7 | [
"self.user = user\nself.client = client\nself.key = key\nself.secret = secret\nself.endpoint = endpoint\nself.cred_type = cred_type\nself.token_properties = token_properties",
"credentials_path = expanduser(expandvars(path))\nif not exists(credentials_path):\n raise HereCredentialsException('Unable to find cre... | <|body_start_0|>
self.user = user
self.client = client
self.key = key
self.secret = secret
self.endpoint = endpoint
self.cred_type = cred_type
self.token_properties = token_properties
<|end_body_0|>
<|body_start_1|>
credentials_path = expanduser(expandvar... | HereCredentials | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HereCredentials:
def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_properties: dict=None):
"""Instantiate the credentials object. :param user: the HERE user id :param client: the HE... | stack_v2_sparse_classes_36k_train_006183 | 2,705 | permissive | [
{
"docstring": "Instantiate the credentials object. :param user: the HERE user id :param client: the HERE client id :param key: the HERE access key id :param secret: there HERE access key secret :param endpoint: the URL of the HERE account service :param cred_type: the type of credentials eg: DEFAULT, TOKEN :to... | 2 | stack_v2_sparse_classes_30k_val_000990 | Implement the Python class `HereCredentials` described below.
Class description:
Implement the HereCredentials class.
Method signatures and docstrings:
- def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_propert... | Implement the Python class `HereCredentials` described below.
Class description:
Implement the HereCredentials class.
Method signatures and docstrings:
- def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_propert... | e45f6c578733b3adce5a32dba575884ff76274b3 | <|skeleton|>
class HereCredentials:
def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_properties: dict=None):
"""Instantiate the credentials object. :param user: the HERE user id :param client: the HE... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HereCredentials:
def __init__(self, user: str, client: str, key: str, secret: str, endpoint: str='https://account.api.here.com/oauth2/token', cred_type: str='DEFAULT', token_properties: dict=None):
"""Instantiate the credentials object. :param user: the HERE user id :param client: the HERE client id :... | the_stack_v2_python_sparse | XYZHubConnector/xyz_qgis/common/here_credentials.py | heremaps/xyz-qgis-plugin | train | 23 | |
7d7db67781d618d26200cfc1b908775614ba4f68 | [
"sl = []\n\ndef buildString(root, sl):\n if root == None:\n sl.append('X')\n else:\n sl.append(str(root.val))\n buildString(root.left, sl)\n buildString(root.right, sl)\nbuildString(root, sl)\nreturn ','.join(sl)",
"data = data.split(',')\n\ndef buildTree(data):\n val = data.p... | <|body_start_0|>
sl = []
def buildString(root, sl):
if root == None:
sl.append('X')
else:
sl.append(str(root.val))
buildString(root.left, sl)
buildString(root.right, sl)
buildString(root, sl)
return ... | 采用前序遍历. 序列化，即将二叉树转成字符串。因为二叉树中包含null节点。需要采用一个特殊字符标记，因为这里的二叉树的值都是数字，所以可以采用非数字作为标记，如采用X。每个节点间用,分割。然后就是按照前序遍历的方法，输入二叉树成字符串。 反序列化，即将刚才生成的字符串转换成二叉树。首先，将字符串按照,split成字符串数组的形式，该数组中每一个元素即为一个二叉树的节点。这里本来可以很简单的用一个全局变量记录，当前遍历的数组index，但是因为题目中要求采用stateless的方式，所以必须换种方式。可以采用list的方式，将已经遍历的节点删除，剩下的就是当该字符串不是X时，按照前序遍历的方式重建二叉树。 | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
"""采用前序遍历. 序列化，即将二叉树转成字符串。因为二叉树中包含null节点。需要采用一个特殊字符标记，因为这里的二叉树的值都是数字，所以可以采用非数字作为标记，如采用X。每个节点间用,分割。然后就是按照前序遍历的方法，输入二叉树成字符串。 反序列化，即将刚才生成的字符串转换成二叉树。首先，将字符串按照,split成字符串数组的形式，该数组中每一个元素即为一个二叉树的节点。这里本来可以很简单的用一个全局变量记录，当前遍历的数组index，但是因为题目中要求采用stateless的方式，所以必须换种方式。可以采用list的方式，将已经遍历的节点删除，剩下的就是当该字符串不... | stack_v2_sparse_classes_36k_train_006184 | 2,142 | 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:
采用前序遍历. 序列化，即将二叉树转成字符串。因为二叉树中包含null节点。需要采用一个特殊字符标记，因为这里的二叉树的值都是数字，所以可以采用非数字作为标记，如采用X。每个节点间用,分割。然后就是按照前序遍历的方法，输入二叉树成字符串。 反序列化，即将刚才生成的字符串转换成二叉树。首先，将字符串按照,split成字符串数组的形式，该数组中每一个元素即为一个二叉树的节点。这里本来可以很简单的用一个全局变量记录，当前遍历的数组index，但是因为题目中要求采用stateless的方式，所以必须... | Implement the Python class `Codec` described below.
Class description:
采用前序遍历. 序列化，即将二叉树转成字符串。因为二叉树中包含null节点。需要采用一个特殊字符标记，因为这里的二叉树的值都是数字，所以可以采用非数字作为标记，如采用X。每个节点间用,分割。然后就是按照前序遍历的方法，输入二叉树成字符串。 反序列化，即将刚才生成的字符串转换成二叉树。首先，将字符串按照,split成字符串数组的形式，该数组中每一个元素即为一个二叉树的节点。这里本来可以很简单的用一个全局变量记录，当前遍历的数组index，但是因为题目中要求采用stateless的方式，所以必须... | b49633ac8edc7bd96dec4b44f7e6acf504cda2a6 | <|skeleton|>
class Codec:
"""采用前序遍历. 序列化，即将二叉树转成字符串。因为二叉树中包含null节点。需要采用一个特殊字符标记，因为这里的二叉树的值都是数字，所以可以采用非数字作为标记，如采用X。每个节点间用,分割。然后就是按照前序遍历的方法，输入二叉树成字符串。 反序列化，即将刚才生成的字符串转换成二叉树。首先，将字符串按照,split成字符串数组的形式，该数组中每一个元素即为一个二叉树的节点。这里本来可以很简单的用一个全局变量记录，当前遍历的数组index，但是因为题目中要求采用stateless的方式，所以必须换种方式。可以采用list的方式，将已经遍历的节点删除，剩下的就是当该字符串不... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
"""采用前序遍历. 序列化，即将二叉树转成字符串。因为二叉树中包含null节点。需要采用一个特殊字符标记，因为这里的二叉树的值都是数字，所以可以采用非数字作为标记，如采用X。每个节点间用,分割。然后就是按照前序遍历的方法，输入二叉树成字符串。 反序列化，即将刚才生成的字符串转换成二叉树。首先，将字符串按照,split成字符串数组的形式，该数组中每一个元素即为一个二叉树的节点。这里本来可以很简单的用一个全局变量记录，当前遍历的数组index，但是因为题目中要求采用stateless的方式，所以必须换种方式。可以采用list的方式，将已经遍历的节点删除，剩下的就是当该字符串不是X时，按照前序遍历的方式... | the_stack_v2_python_sparse | 算法/Python/297. Serialize and Deserialize Binary Tree.py | honchen22/LeetCode | train | 1 |
160427c655ff89686c3af2e5697f70d41fa5728c | [
"self.data = _data\nself.cov = _cov\nself.z = _z\nself.prior = _prior\nself.LikeFunc = Likelihood(_data, _cov)",
"_mod = model(_theta, self.z)\nself.u = -self.LikeFunc.get_likelihood(_mod) - self.prior.get_log_pdf(_theta)\nreturn self.u",
"theta_grad = torch.tensor(_theta.clone(), requires_grad=True)\nval = sel... | <|body_start_0|>
self.data = _data
self.cov = _cov
self.z = _z
self.prior = _prior
self.LikeFunc = Likelihood(_data, _cov)
<|end_body_0|>
<|body_start_1|>
_mod = model(_theta, self.z)
self.u = -self.LikeFunc.get_likelihood(_mod) - self.prior.get_log_pdf(_theta)
... | Potential | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Potential:
def __init__(self, _data, _cov, _z, _prior):
"""Computes potential energy and its gradient. dat: array (ndata), data. _cov: array (1, ndata), data error z: array (ndata), redshift. prior: object, prior."""
<|body_0|>
def value(self, _theta):
"""Returns pot... | stack_v2_sparse_classes_36k_train_006185 | 16,303 | no_license | [
{
"docstring": "Computes potential energy and its gradient. dat: array (ndata), data. _cov: array (1, ndata), data error z: array (ndata), redshift. prior: object, prior.",
"name": "__init__",
"signature": "def __init__(self, _data, _cov, _z, _prior)"
},
{
"docstring": "Returns potential log val... | 3 | stack_v2_sparse_classes_30k_train_020911 | Implement the Python class `Potential` described below.
Class description:
Implement the Potential class.
Method signatures and docstrings:
- def __init__(self, _data, _cov, _z, _prior): Computes potential energy and its gradient. dat: array (ndata), data. _cov: array (1, ndata), data error z: array (ndata), redshift... | Implement the Python class `Potential` described below.
Class description:
Implement the Potential class.
Method signatures and docstrings:
- def __init__(self, _data, _cov, _z, _prior): Computes potential energy and its gradient. dat: array (ndata), data. _cov: array (1, ndata), data error z: array (ndata), redshift... | 8789f692d81c5435a5888b6b151ccf6187d5a064 | <|skeleton|>
class Potential:
def __init__(self, _data, _cov, _z, _prior):
"""Computes potential energy and its gradient. dat: array (ndata), data. _cov: array (1, ndata), data error z: array (ndata), redshift. prior: object, prior."""
<|body_0|>
def value(self, _theta):
"""Returns pot... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Potential:
def __init__(self, _data, _cov, _z, _prior):
"""Computes potential energy and its gradient. dat: array (ndata), data. _cov: array (1, ndata), data error z: array (ndata), redshift. prior: object, prior."""
self.data = _data
self.cov = _cov
self.z = _z
self.pr... | the_stack_v2_python_sparse | p18/toy.py | fluowhy/MCMC-methods | train | 1 | |
ca4ec8e5cda1856c6340492f7846df17eba81d29 | [
"def _9Tuple(a12=dflt, lat2=dflt, lon2=dflt, azi2=dflt, s12=dflt, m12=dflt, M12=dflt, M21=dflt, S12=dflt, **unused):\n return Direct9Tuple(a12, lat2, lon2, azi2, s12, m12, M12, M21, S12)\nreturn _9Tuple(**self)",
"def _12Tuple(lat1=dflt, lon1=dflt, azi1=dflt, lat2=dflt, lon2=dflt, azi2=dflt, s12=dflt, a12=dflt... | <|body_start_0|>
def _9Tuple(a12=dflt, lat2=dflt, lon2=dflt, azi2=dflt, s12=dflt, m12=dflt, M12=dflt, M21=dflt, S12=dflt, **unused):
return Direct9Tuple(a12, lat2, lon2, azi2, s12, m12, M12, M21, S12)
return _9Tuple(**self)
<|end_body_0|>
<|body_start_1|>
def _12Tuple(lat1=dflt, lon... | Basic C{dict} with both key I{and} attribute access to the C{dict} items. Results of all C{geodesic} methods are returned as a L{GDict} instance. | GDict | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GDict:
"""Basic C{dict} with both key I{and} attribute access to the C{dict} items. Results of all C{geodesic} methods are returned as a L{GDict} instance."""
def toDirect9Tuple(self, dflt=NAN):
"""Convert this L{GDict} result to a 9-tuple, like I{Karney}'s method C{geographiclib.geo... | stack_v2_sparse_classes_36k_train_006186 | 27,898 | permissive | [
{
"docstring": "Convert this L{GDict} result to a 9-tuple, like I{Karney}'s method C{geographiclib.geodesic.Geodesic._GenDirect}. @return: L{Direct9Tuple}C{(a12, lat2, lon2, azi2, s12, m12, M12, M21, S12)}",
"name": "toDirect9Tuple",
"signature": "def toDirect9Tuple(self, dflt=NAN)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_019952 | Implement the Python class `GDict` described below.
Class description:
Basic C{dict} with both key I{and} attribute access to the C{dict} items. Results of all C{geodesic} methods are returned as a L{GDict} instance.
Method signatures and docstrings:
- def toDirect9Tuple(self, dflt=NAN): Convert this L{GDict} result ... | Implement the Python class `GDict` described below.
Class description:
Basic C{dict} with both key I{and} attribute access to the C{dict} items. Results of all C{geodesic} methods are returned as a L{GDict} instance.
Method signatures and docstrings:
- def toDirect9Tuple(self, dflt=NAN): Convert this L{GDict} result ... | 3a7c03c42237102af0a9ab23b2d550020a601d98 | <|skeleton|>
class GDict:
"""Basic C{dict} with both key I{and} attribute access to the C{dict} items. Results of all C{geodesic} methods are returned as a L{GDict} instance."""
def toDirect9Tuple(self, dflt=NAN):
"""Convert this L{GDict} result to a 9-tuple, like I{Karney}'s method C{geographiclib.geo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GDict:
"""Basic C{dict} with both key I{and} attribute access to the C{dict} items. Results of all C{geodesic} methods are returned as a L{GDict} instance."""
def toDirect9Tuple(self, dflt=NAN):
"""Convert this L{GDict} result to a 9-tuple, like I{Karney}'s method C{geographiclib.geodesic.Geodesi... | the_stack_v2_python_sparse | pygeodesy/karney.py | ahaywardtvuk/PyGeodesy | train | 0 |
57e3fe0ecd2b8eb2c0d9f12488bd0ef6b3352a74 | [
"logging.info('======test_login1_normal=====')\nl = LoginView(self.driver)\nl.login_action('15013038819', 'yyy333')\nself.assertTrue(l.check_login_status('login_ok'), msg='login fail!')",
"logging.info('======test_login2_normal=====')\nl = LoginView(self.driver)\nl.login_action('15013038819', 'yyy331')\nself.asse... | <|body_start_0|>
logging.info('======test_login1_normal=====')
l = LoginView(self.driver)
l.login_action('15013038819', 'yyy333')
self.assertTrue(l.check_login_status('login_ok'), msg='login fail!')
<|end_body_0|>
<|body_start_1|>
logging.info('======test_login2_normal=====')
... | LoginTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginTest:
def test_login1_normal(self):
"""1.正确的手机号与密码"""
<|body_0|>
def test_login2_normal(self):
"""2.正确的手机号与错误密码"""
<|body_1|>
def test_login3_normal(self):
"""3.未注册的手机号码"""
<|body_2|>
def test_login4_normal(self):
"""4.正... | stack_v2_sparse_classes_36k_train_006187 | 2,390 | no_license | [
{
"docstring": "1.正确的手机号与密码",
"name": "test_login1_normal",
"signature": "def test_login1_normal(self)"
},
{
"docstring": "2.正确的手机号与错误密码",
"name": "test_login2_normal",
"signature": "def test_login2_normal(self)"
},
{
"docstring": "3.未注册的手机号码",
"name": "test_login3_normal",
... | 6 | null | Implement the Python class `LoginTest` described below.
Class description:
Implement the LoginTest class.
Method signatures and docstrings:
- def test_login1_normal(self): 1.正确的手机号与密码
- def test_login2_normal(self): 2.正确的手机号与错误密码
- def test_login3_normal(self): 3.未注册的手机号码
- def test_login4_normal(self): 4.正确邮箱与正确密码
-... | Implement the Python class `LoginTest` described below.
Class description:
Implement the LoginTest class.
Method signatures and docstrings:
- def test_login1_normal(self): 1.正确的手机号与密码
- def test_login2_normal(self): 2.正确的手机号与错误密码
- def test_login3_normal(self): 3.未注册的手机号码
- def test_login4_normal(self): 4.正确邮箱与正确密码
-... | 80539f8d3fc5ccb5c07aab2ad37a9c071bb4944d | <|skeleton|>
class LoginTest:
def test_login1_normal(self):
"""1.正确的手机号与密码"""
<|body_0|>
def test_login2_normal(self):
"""2.正确的手机号与错误密码"""
<|body_1|>
def test_login3_normal(self):
"""3.未注册的手机号码"""
<|body_2|>
def test_login4_normal(self):
"""4.正... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginTest:
def test_login1_normal(self):
"""1.正确的手机号与密码"""
logging.info('======test_login1_normal=====')
l = LoginView(self.driver)
l.login_action('15013038819', 'yyy333')
self.assertTrue(l.check_login_status('login_ok'), msg='login fail!')
def test_login2_normal(s... | the_stack_v2_python_sparse | WFX_App_Test/test_case/test_01_login.py | yangyuexiong/WFX_Test | train | 0 | |
9f60fff98431a4911dc8d793b750592448ae60f2 | [
"m = {}\nres = []\nfor i in nums1:\n m[i] = m.setdefault(i, 0) + 1\nfor i in nums2:\n if i in m and m[i] > 0:\n res.append(i)\n m[i] -= 1\nreturn res",
"nums1.sort()\nnums2.sort()\ni, j = (0, 0)\nres = []\nwhile i < len(nums1) and j < len(nums2):\n if nums1[i] == nums2[j]:\n res.appe... | <|body_start_0|>
m = {}
res = []
for i in nums1:
m[i] = m.setdefault(i, 0) + 1
for i in nums2:
if i in m and m[i] > 0:
res.append(i)
m[i] -= 1
return res
<|end_body_0|>
<|body_start_1|>
nums1.sort()
nums2.so... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersectSort(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_006188 | 2,765 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersect",
"signature": "def intersect(self, nums1, nums2)"
},
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersectSort",
"signature": "def intersec... | 2 | stack_v2_sparse_classes_30k_train_000214 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersectSort(self, nums1, nums2): :type nums1: List[int] :type nums2: Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersectSort(self, nums1, nums2): :type nums1: List[int] :type nums2: Li... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersectSort(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
m = {}
res = []
for i in nums1:
m[i] = m.setdefault(i, 0) + 1
for i in nums2:
if i in m and m[i] > 0:
res.append(i)... | the_stack_v2_python_sparse | I/IntersectionofTwoArraysII.py | bssrdf/pyleet | train | 2 | |
92da236757cbd5ab41c4147e912e813044e2de30 | [
"if not nums:\n return False\narr = [1] * len(nums)\np1 = p2 = 1\nfor i in range(len(nums)):\n arr[i] *= p1\n arr[~i] *= p2\n p1 *= nums[i]\n p2 *= nums[~i]\nreturn arr",
"if not nums:\n return False\np = 1\nn = len(nums)\noutput = []\nfor i in range(n):\n output.append(p)\n p = p * nums[i... | <|body_start_0|>
if not nums:
return False
arr = [1] * len(nums)
p1 = p2 = 1
for i in range(len(nums)):
arr[i] *= p1
arr[~i] *= p2
p1 *= nums[i]
p2 *= nums[~i]
return arr
<|end_body_0|>
<|body_start_1|>
if not n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""https://www.youtube.com/watch?v=tSRFtR3pv74 :param nums: :return:"""
<|body_0|>
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""Numbers [1 2 3 4 5] Pass 1: [- 1 12 123 1234] Pass 2:... | stack_v2_sparse_classes_36k_train_006189 | 958 | no_license | [
{
"docstring": "https://www.youtube.com/watch?v=tSRFtR3pv74 :param nums: :return:",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums: List[int]) -> List[int]"
},
{
"docstring": "Numbers [1 2 3 4 5] Pass 1: [- 1 12 123 1234] Pass 2: [2345 345 45 5 -]",
"name": "prod... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums: List[int]) -> List[int]: https://www.youtube.com/watch?v=tSRFtR3pv74 :param nums: :return:
- def productExceptSelf(self, nums: List[int]) -> Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums: List[int]) -> List[int]: https://www.youtube.com/watch?v=tSRFtR3pv74 :param nums: :return:
- def productExceptSelf(self, nums: List[int]) -> Lis... | e50dc0642f087f37ab3234390be3d8a0ed48fe62 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""https://www.youtube.com/watch?v=tSRFtR3pv74 :param nums: :return:"""
<|body_0|>
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""Numbers [1 2 3 4 5] Pass 1: [- 1 12 123 1234] Pass 2:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelf(self, nums: List[int]) -> List[int]:
"""https://www.youtube.com/watch?v=tSRFtR3pv74 :param nums: :return:"""
if not nums:
return False
arr = [1] * len(nums)
p1 = p2 = 1
for i in range(len(nums)):
arr[i] *= p1
... | the_stack_v2_python_sparse | Leetcode/238. Product of Array Except Self.py | brlala/Educative-Grokking-Coding-Exercise | train | 3 | |
1a614a75e3a793c22e184c4d00499e08ad9c89f8 | [
"self.summary = {}\nself.dictionary = set(dictionary)\nfor word in self.dictionary:\n if len(word) <= 2:\n self.summary[word] = self.summary.get(word, 0) + 1\n else:\n newWord = word[0] + str(len(word) - 2) + word[-1]\n self.summary[newWord] = self.summary.get(newWord, 0) + 1",
"if len(... | <|body_start_0|>
self.summary = {}
self.dictionary = set(dictionary)
for word in self.dictionary:
if len(word) <= 2:
self.summary[word] = self.summary.get(word, 0) + 1
else:
newWord = word[0] + str(len(word) - 2) + word[-1]
... | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.summary = {}
self.dictionary = set(dic... | stack_v2_sparse_classes_36k_train_006190 | 912 | no_license | [
{
"docstring": ":type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": ":type word: str :rtype: bool",
"name": "isUnique",
"signature": "def isUnique(self, word)"
}
] | 2 | null | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool
<|skeleton|>
class ValidWordAbbr:
def __init_... | 0e10a40921d9fa5ca8c53859e4b17bcb62ee899a | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
self.summary = {}
self.dictionary = set(dictionary)
for word in self.dictionary:
if len(word) <= 2:
self.summary[word] = self.summary.get(word, 0) + 1
else:
... | the_stack_v2_python_sparse | uniqueWordAbbreviation.py | peinanteng/leetcode | train | 0 | |
c39c395f30e35b9fa92d1dd9c556153e9b8ddf5c | [
"NamedObject.__init__(self, root, definitions)\npmd = Metadata()\npmd.wrappers = dict(element=repr, type=repr)\nself.__metadata__.__print__ = pmd\ntns = definitions.tns\nself.element = self.__getref('element', tns)\nself.type = self.__getref('type', tns)",
"s = self.root.get(a)\nif s is None:\n return s\nelse:... | <|body_start_0|>
NamedObject.__init__(self, root, definitions)
pmd = Metadata()
pmd.wrappers = dict(element=repr, type=repr)
self.__metadata__.__print__ = pmd
tns = definitions.tns
self.element = self.__getref('element', tns)
self.type = self.__getref('type', tns)... | Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str | Part | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Part:
"""Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str"... | stack_v2_sparse_classes_36k_train_006191 | 30,914 | permissive | [
{
"docstring": "@param root: An XML root element. @type root: L{Element} @param definitions: A definitions object. @type definitions: L{Definitions}",
"name": "__init__",
"signature": "def __init__(self, root, definitions)"
},
{
"docstring": "Get the qualified value of attribute named 'a'.",
... | 2 | stack_v2_sparse_classes_30k_train_002018 | Implement the Python class `Part` described below.
Class description:
Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted b... | Implement the Python class `Part` described below.
Class description:
Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted b... | 7d8843fcdfe179f018af2038f813795f7182b714 | <|skeleton|>
class Part:
"""Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Part:
"""Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str"""
def _... | the_stack_v2_python_sparse | suds/wsdl.py | CybernetiX-S3C/interactive-tutorials | train | 1 |
bd1b24f536bd75a33690848d4b8f6eee045cf609 | [
"self.context = context\nself.field = field\nself.widget = widget",
"html = self.widget.render().strip()\ntransforms = getToolByName(self.context, 'portal_transforms')\nstream = transforms.convertTo('text/plain', html, mimetype='text/html')\nreturn stream.getData().strip()"
] | <|body_start_0|>
self.context = context
self.field = field
self.widget = widget
<|end_body_0|>
<|body_start_1|>
html = self.widget.render().strip()
transforms = getToolByName(self.context, 'portal_transforms')
stream = transforms.convertTo('text/plain', html, mimetype='t... | Fallback field converter which uses the rendered widget in display mode for generating a indexable string. | DefaultDexterityTextIndexFieldConverter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefaultDexterityTextIndexFieldConverter:
"""Fallback field converter which uses the rendered widget in display mode for generating a indexable string."""
def __init__(self, context, field, widget):
"""Initialize field converter"""
<|body_0|>
def convert(self):
""... | stack_v2_sparse_classes_36k_train_006192 | 5,051 | no_license | [
{
"docstring": "Initialize field converter",
"name": "__init__",
"signature": "def __init__(self, context, field, widget)"
},
{
"docstring": "Convert the adapted field value to text/plain for indexing",
"name": "convert",
"signature": "def convert(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020981 | Implement the Python class `DefaultDexterityTextIndexFieldConverter` described below.
Class description:
Fallback field converter which uses the rendered widget in display mode for generating a indexable string.
Method signatures and docstrings:
- def __init__(self, context, field, widget): Initialize field converter... | Implement the Python class `DefaultDexterityTextIndexFieldConverter` described below.
Class description:
Fallback field converter which uses the rendered widget in display mode for generating a indexable string.
Method signatures and docstrings:
- def __init__(self, context, field, widget): Initialize field converter... | 51827ba0f63d8d342a360cd4b10213fd3a29557f | <|skeleton|>
class DefaultDexterityTextIndexFieldConverter:
"""Fallback field converter which uses the rendered widget in display mode for generating a indexable string."""
def __init__(self, context, field, widget):
"""Initialize field converter"""
<|body_0|>
def convert(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DefaultDexterityTextIndexFieldConverter:
"""Fallback field converter which uses the rendered widget in display mode for generating a indexable string."""
def __init__(self, context, field, widget):
"""Initialize field converter"""
self.context = context
self.field = field
... | the_stack_v2_python_sparse | plone/app/dexterity/textindexer/converters.py | plone/plone.app.dexterity | train | 12 |
89f55a19cbbbc135f23c8bb6ef2dd05c737a3f25 | [
"val = 0\ncal = [val]\nfor i in nums:\n val += i\n cal.append(val)\nself.cal = cal",
"try:\n return self.cal[j + 1] - self.cal[i]\nexcept IndexError:\n return 0"
] | <|body_start_0|>
val = 0
cal = [val]
for i in nums:
val += i
cal.append(val)
self.cal = cal
<|end_body_0|>
<|body_start_1|>
try:
return self.cal[j + 1] - self.cal[i]
except IndexError:
return 0
<|end_body_1|>
| NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
val = 0
cal = [val]
for i in nums:
... | stack_v2_sparse_classes_36k_train_006193 | 586 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type j: int :rtype: int",
"name": "sumRange",
"signature": "def sumRange(self, i, j)"
}
] | 2 | null | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def sumRange(self, i, j): :type i: int :type j: int :rtype: int | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def sumRange(self, i, j): :type i: int :type j: int :rtype: int
<|skeleton|>
class NumArray:
def __init__(self, nums):
... | d8ed762d1005975f0de4f07760c9671195621c88 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
val = 0
cal = [val]
for i in nums:
val += i
cal.append(val)
self.cal = cal
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
try:
... | the_stack_v2_python_sparse | range-sum-query-immutable/solution.py | uxlsl/leetcode_practice | train | 0 | |
c43098e360efe030c96e00170f5b328229875bdf | [
"self.username = username\nself.password = md5(password.encode('utf-8')).hexdigest()\nself.base_params = {'user': self.username, 'pass2': self.password, 'softid': '895210'}\nself.headers = {'Connection': 'Keep-Alive', 'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0)'}",
"params = {'c... | <|body_start_0|>
self.username = username
self.password = md5(password.encode('utf-8')).hexdigest()
self.base_params = {'user': self.username, 'pass2': self.password, 'softid': '895210'}
self.headers = {'Connection': 'Keep-Alive', 'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows... | GtClickShot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GtClickShot:
def __init__(self, username, password):
"""初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码"""
<|body_0|>
def PostPic(self, im, codetype):
"""发送图片至打码平台 args： im(Byte): 图片字节 codetype(str): 题目类型 参考 http://www.chaojiying.com/price.html r... | stack_v2_sparse_classes_36k_train_006194 | 26,194 | no_license | [
{
"docstring": "初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码",
"name": "__init__",
"signature": "def __init__(self, username, password)"
},
{
"docstring": "发送图片至打码平台 args： im(Byte): 图片字节 codetype(str): 题目类型 参考 http://www.chaojiying.com/price.html return(json):返回打码信息，包含坐标信... | 3 | null | Implement the Python class `GtClickShot` described below.
Class description:
Implement the GtClickShot class.
Method signatures and docstrings:
- def __init__(self, username, password): 初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码
- def PostPic(self, im, codetype): 发送图片至打码平台 args： im(Byte): 图片... | Implement the Python class `GtClickShot` described below.
Class description:
Implement the GtClickShot class.
Method signatures and docstrings:
- def __init__(self, username, password): 初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码
- def PostPic(self, im, codetype): 发送图片至打码平台 args： im(Byte): 图片... | dc9dbbb5bf5e3d29cd664219826ca334916b953f | <|skeleton|>
class GtClickShot:
def __init__(self, username, password):
"""初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码"""
<|body_0|>
def PostPic(self, im, codetype):
"""发送图片至打码平台 args： im(Byte): 图片字节 codetype(str): 题目类型 参考 http://www.chaojiying.com/price.html r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GtClickShot:
def __init__(self, username, password):
"""初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码"""
self.username = username
self.password = md5(password.encode('utf-8')).hexdigest()
self.base_params = {'user': self.username, 'pass2': self.password, ... | the_stack_v2_python_sparse | skill/crawler_gov.py | mj3428/python_for_practice | train | 1 | |
ef405907432352d1c603073d8e5a0f959d91d4c0 | [
"url = f'{cls.base_url}{cls.snapshot_urls[snapshot_type]}'\nresponse = requests.get(url)\nsnapshots = response.json()\nfor epoch, snapshot in snapshots.items():\n snapshot.update({'epoch': int(epoch)})\nreturn sorted(snapshots.values(), key=lambda i: i['epoch'])",
"url = f'{cls.base_url}{cls.epoch_rewards_link... | <|body_start_0|>
url = f'{cls.base_url}{cls.snapshot_urls[snapshot_type]}'
response = requests.get(url)
snapshots = response.json()
for epoch, snapshot in snapshots.items():
snapshot.update({'epoch': int(epoch)})
return sorted(snapshots.values(), key=lambda i: i['epoc... | Perp Off-chain storage for staking rewards, ... . | PerpOffChainStorage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PerpOffChainStorage:
"""Perp Off-chain storage for staking rewards, ... ."""
def get_epoch_snapshots(cls, snapshot_type: str) -> List[PerpSnapshot]:
"""Load epoch (weekly) immediate or vesting snapshots."""
<|body_0|>
def get_rewards(cls, epoch: int, hash_: str) -> Dict[... | stack_v2_sparse_classes_36k_train_006195 | 7,973 | permissive | [
{
"docstring": "Load epoch (weekly) immediate or vesting snapshots.",
"name": "get_epoch_snapshots",
"signature": "def get_epoch_snapshots(cls, snapshot_type: str) -> List[PerpSnapshot]"
},
{
"docstring": "Load perp rewards for whole epoch.",
"name": "get_rewards",
"signature": "def get_... | 2 | null | Implement the Python class `PerpOffChainStorage` described below.
Class description:
Perp Off-chain storage for staking rewards, ... .
Method signatures and docstrings:
- def get_epoch_snapshots(cls, snapshot_type: str) -> List[PerpSnapshot]: Load epoch (weekly) immediate or vesting snapshots.
- def get_rewards(cls, ... | Implement the Python class `PerpOffChainStorage` described below.
Class description:
Perp Off-chain storage for staking rewards, ... .
Method signatures and docstrings:
- def get_epoch_snapshots(cls, snapshot_type: str) -> List[PerpSnapshot]: Load epoch (weekly) immediate or vesting snapshots.
- def get_rewards(cls, ... | eaa9b81b826471fa1c7748c42162e46ad55183d4 | <|skeleton|>
class PerpOffChainStorage:
"""Perp Off-chain storage for staking rewards, ... ."""
def get_epoch_snapshots(cls, snapshot_type: str) -> List[PerpSnapshot]:
"""Load epoch (weekly) immediate or vesting snapshots."""
<|body_0|>
def get_rewards(cls, epoch: int, hash_: str) -> Dict[... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PerpOffChainStorage:
"""Perp Off-chain storage for staking rewards, ... ."""
def get_epoch_snapshots(cls, snapshot_type: str) -> List[PerpSnapshot]:
"""Load epoch (weekly) immediate or vesting snapshots."""
url = f'{cls.base_url}{cls.snapshot_urls[snapshot_type]}'
response = reque... | the_stack_v2_python_sparse | blockapi/v2/api/perpetual/perpetual.py | crypkit/blockapi | train | 22 |
14385afa20792ec779d1da6def124dde74e858c4 | [
"value = self._prepare_item(key, value)\nqs = self._get_queryset()\nfn = '.'.join([self.__field_name__, key])\nqs.update_one({'$set': {fn: value}})\nself._data[key] = value\nself.__log__.append(MapSet(key=key, value=value))\nif reload:\n self.reload()",
"qs = self._get_queryset()\nfn = '.'.join([self.__field_n... | <|body_start_0|>
value = self._prepare_item(key, value)
qs = self._get_queryset()
fn = '.'.join([self.__field_name__, key])
qs.update_one({'$set': {fn: value}})
self._data[key] = value
self.__log__.append(MapSet(key=key, value=value))
if reload:
self.r... | Map. | Map | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Map:
"""Map."""
def set(self, key, value, reload=True):
"""Set key directly in database. See `$set` in MongoDB's `set`."""
<|body_0|>
def unset(self, key, reload=True):
"""Unset key directly in database. See `$unset` in MongoDB's `unset`."""
<|body_1|>
<... | stack_v2_sparse_classes_36k_train_006196 | 5,850 | no_license | [
{
"docstring": "Set key directly in database. See `$set` in MongoDB's `set`.",
"name": "set",
"signature": "def set(self, key, value, reload=True)"
},
{
"docstring": "Unset key directly in database. See `$unset` in MongoDB's `unset`.",
"name": "unset",
"signature": "def unset(self, key, ... | 2 | stack_v2_sparse_classes_30k_train_006477 | Implement the Python class `Map` described below.
Class description:
Map.
Method signatures and docstrings:
- def set(self, key, value, reload=True): Set key directly in database. See `$set` in MongoDB's `set`.
- def unset(self, key, reload=True): Unset key directly in database. See `$unset` in MongoDB's `unset`. | Implement the Python class `Map` described below.
Class description:
Map.
Method signatures and docstrings:
- def set(self, key, value, reload=True): Set key directly in database. See `$set` in MongoDB's `set`.
- def unset(self, key, reload=True): Unset key directly in database. See `$unset` in MongoDB's `unset`.
<|... | b3b9f2fdd5987c718b9db600fd7881630bfef944 | <|skeleton|>
class Map:
"""Map."""
def set(self, key, value, reload=True):
"""Set key directly in database. See `$set` in MongoDB's `set`."""
<|body_0|>
def unset(self, key, reload=True):
"""Unset key directly in database. See `$unset` in MongoDB's `unset`."""
<|body_1|>
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Map:
"""Map."""
def set(self, key, value, reload=True):
"""Set key directly in database. See `$set` in MongoDB's `set`."""
value = self._prepare_item(key, value)
qs = self._get_queryset()
fn = '.'.join([self.__field_name__, key])
qs.update_one({'$set': {fn: value}}... | the_stack_v2_python_sparse | yadm/fields/map.py | habibutsu/yadm | train | 0 |
d0bc0d7027bf414c625d9d773737b6807f5441a0 | [
"if len(nums) == 1:\n return nums[0]\nres = self.getMaxSubArray(nums, len(nums) - 1)\nreturn max(res[0], res[1])",
"if i >= 2:\n res = self.getMaxSubArray(nums, i - 1)\n return (max(res[0], res[1]), nums[i] + max(res[1], 0))\nelse:\n return (nums[0], nums[1] + max(nums[0], 0))"
] | <|body_start_0|>
if len(nums) == 1:
return nums[0]
res = self.getMaxSubArray(nums, len(nums) - 1)
return max(res[0], res[1])
<|end_body_0|>
<|body_start_1|>
if i >= 2:
res = self.getMaxSubArray(nums, i - 1)
return (max(res[0], res[1]), nums[i] + max(r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def getMaxSubArray(self, nums, i):
""":rtype: tuple[int,int] [0]: max within [0,i] when not ending with nums[i] [1]: max within [0,i] when ending with nums[i]"""
<|body_... | stack_v2_sparse_classes_36k_train_006197 | 687 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":rtype: tuple[int,int] [0]: max within [0,i] when not ending with nums[i] [1]: max within [0,i] when ending with nums[i]",
"name": "getMaxSubArray",
"s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def getMaxSubArray(self, nums, i): :rtype: tuple[int,int] [0]: max within [0,i] when not ending with nums[i] [1]:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def getMaxSubArray(self, nums, i): :rtype: tuple[int,int] [0]: max within [0,i] when not ending with nums[i] [1]:... | f6019c6a04f6923e4ec3bb156c9ad80e6545c127 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def getMaxSubArray(self, nums, i):
""":rtype: tuple[int,int] [0]: max within [0,i] when not ending with nums[i] [1]: max within [0,i] when ending with nums[i]"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
if len(nums) == 1:
return nums[0]
res = self.getMaxSubArray(nums, len(nums) - 1)
return max(res[0], res[1])
def getMaxSubArray(self, nums, i):
""":rtype: tuple[int,int] [0]: ... | the_stack_v2_python_sparse | Algorithms/p053_Maximum_Subarray/p053_Maximum_Subarray_2.py | lbingbing/leetcode | train | 0 | |
7a843b8a94331af7a0d4a47c06e38b188d19659c | [
"super(Test200SmartSanityUi001, self).prepare()\nself.tmp = {'file': [], 'dir': []}\nself.logger.info('Preconditions:')\nself.logger.info('1. Open Micro/WIN;')",
"super(Test200SmartSanityUi001, self).process()\nself.logger.info('Step actions:')\nself.logger.info('Expected results:')\nself.logger.info('1. New a pr... | <|body_start_0|>
super(Test200SmartSanityUi001, self).prepare()
self.tmp = {'file': [], 'dir': []}
self.logger.info('Preconditions:')
self.logger.info('1. Open Micro/WIN;')
<|end_body_0|>
<|body_start_1|>
super(Test200SmartSanityUi001, self).process()
self.logger.info('S... | Project No.: test_200smart_sanity_ui_001 Preconditions: 1. Open Micro/WIN; Step actions: 1. New a project; 2. Save the project; 3. Open an existed project; 4. Save as the project; 5. Close the project; Expected results: 1. Create successful; 2. Save successful; 3. Open successful; 4. Save successful; 5. Close successfu... | Test200SmartSanityUi001 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test200SmartSanityUi001:
"""Project No.: test_200smart_sanity_ui_001 Preconditions: 1. Open Micro/WIN; Step actions: 1. New a project; 2. Save the project; 3. Open an existed project; 4. Save as the project; 5. Close the project; Expected results: 1. Create successful; 2. Save successful; 3. Open... | stack_v2_sparse_classes_36k_train_006198 | 3,454 | no_license | [
{
"docstring": "the preparation before executing the test steps Args: Example: Return: Author: Wang, Xing Yu IsInterface: False ChangeInfo: Wang, Xing Yu 2019-10-30 create",
"name": "prepare",
"signature": "def prepare(self)"
},
{
"docstring": "execute the test steps Args: Example: Return: Autho... | 3 | null | Implement the Python class `Test200SmartSanityUi001` described below.
Class description:
Project No.: test_200smart_sanity_ui_001 Preconditions: 1. Open Micro/WIN; Step actions: 1. New a project; 2. Save the project; 3. Open an existed project; 4. Save as the project; 5. Close the project; Expected results: 1. Create ... | Implement the Python class `Test200SmartSanityUi001` described below.
Class description:
Project No.: test_200smart_sanity_ui_001 Preconditions: 1. Open Micro/WIN; Step actions: 1. New a project; 2. Save the project; 3. Open an existed project; 4. Save as the project; 5. Close the project; Expected results: 1. Create ... | 2d3490393737b3e5f086cb6623369b988ffce67f | <|skeleton|>
class Test200SmartSanityUi001:
"""Project No.: test_200smart_sanity_ui_001 Preconditions: 1. Open Micro/WIN; Step actions: 1. New a project; 2. Save the project; 3. Open an existed project; 4. Save as the project; 5. Close the project; Expected results: 1. Create successful; 2. Save successful; 3. Open... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test200SmartSanityUi001:
"""Project No.: test_200smart_sanity_ui_001 Preconditions: 1. Open Micro/WIN; Step actions: 1. New a project; 2. Save the project; 3. Open an existed project; 4. Save as the project; 5. Close the project; Expected results: 1. Create successful; 2. Save successful; 3. Open successful; ... | the_stack_v2_python_sparse | test_case/no_piling/sanity_ui/base/ui/test_200smart_sanity_ui_001.py | Lewescaiyong/auto_test_framework | train | 1 |
f4e473994e46fb10d7249745bb3d6571b3bec214 | [
"ans = []\nnums = [1] + nums + [1]\nfor i in range(1, len(nums) - 1):\n ans.append(reduce(lambda x, y: x * y, nums[:i]) * reduce(lambda x, y: x * y, nums[i + 1:]))\nreturn ans",
"tmp_val = 1\ntmp = [0] * len(nums)\nfor i in range(len(nums)):\n tmp[i] = tmp_val\n tmp_val *= nums[i]\ntmp_val = 1\nfor i in ... | <|body_start_0|>
ans = []
nums = [1] + nums + [1]
for i in range(1, len(nums) - 1):
ans.append(reduce(lambda x, y: x * y, nums[:i]) * reduce(lambda x, y: x * y, nums[i + 1:]))
return ans
<|end_body_0|>
<|body_start_1|>
tmp_val = 1
tmp = [0] * len(nums)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelf1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ans = []
num... | stack_v2_sparse_classes_36k_train_006199 | 1,054 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf1",
"signature": "def productExceptSelf1(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf1(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf1(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
class Solut... | 2c47abbf020f44c97e7e439735e4b0d49f3b843f | <|skeleton|>
class Solution:
def productExceptSelf1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelf1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
ans = []
nums = [1] + nums + [1]
for i in range(1, len(nums) - 1):
ans.append(reduce(lambda x, y: x * y, nums[:i]) * reduce(lambda x, y: x * y, nums[i + 1:]))
return ... | the_stack_v2_python_sparse | LeetCode/LeetCode238product-of-array-except-self.py | weiguangjiayou/LeetCode | train | 0 |
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