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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
abe36b79affb6c3b72833b3c03d964c92b7fe81a | [
"if not root:\n return []\nqueue = collections.deque([root])\nretval = ''\nwhile queue:\n curr = queue.popleft()\n if curr == 'null':\n retval += curr + ','\n continue\n else:\n retval += str(curr.val) + ','\n if curr.left:\n queue.append(curr.left)\n else:\n que... | <|body_start_0|>
if not root:
return []
queue = collections.deque([root])
retval = ''
while queue:
curr = queue.popleft()
if curr == 'null':
retval += curr + ','
continue
else:
retval += str(c... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode 0 1 2 3 4 5 6 "[1, 2, 3, null, null, 4, 5]" r r.... | stack_v2_sparse_classes_36k_train_006700 | 2,551 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode 0 1 2 3 4 5 6 \"[1, 2, 3, null, null, 4, 5]\" r r.l r.r r.l.l... | 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:... | bbfee57ae89d23cd4f4132fbb62d8931ea654a0e | <|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 0 1 2 3 4 5 6 "[1, 2, 3, null, null, 4, 5]" r r.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return []
queue = collections.deque([root])
retval = ''
while queue:
curr = queue.popleft()
if curr == 'null':
... | the_stack_v2_python_sparse | Algorithms/Leetcode/297 - Serialize and Deserialize Binary Tree.py | timpark0807/self-taught-swe | train | 1 | |
8f46a27f7c83bc18231870f1e29ea4b45f935519 | [
"db_api = DataBaseAPI(NotificationDB).session\nnote = NotificationDB()\nnote.sender = sender\nnote.receiver = receiver\nnote.msg_type = msg_type\nnote.message = message\nnote.read = 0\ndb_api.add(note)\ndb_api.commit()\ndb_api.close()\nqueue.put({'user_id': receiver, 'msg': message, 'msg_type': msg_type})\nlog.debu... | <|body_start_0|>
db_api = DataBaseAPI(NotificationDB).session
note = NotificationDB()
note.sender = sender
note.receiver = receiver
note.msg_type = msg_type
note.message = message
note.read = 0
db_api.add(note)
db_api.commit()
db_api.close(... | Implemented notification api | NotificationAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationAPI:
"""Implemented notification api"""
def send(sender, receiver, msg_type, message):
"""Add notification"""
<|body_0|>
def read(msg_id):
"""Read message"""
<|body_1|>
def get(get_by=None):
"""Get notification: all, by sender, by... | stack_v2_sparse_classes_36k_train_006701 | 1,653 | no_license | [
{
"docstring": "Add notification",
"name": "send",
"signature": "def send(sender, receiver, msg_type, message)"
},
{
"docstring": "Read message",
"name": "read",
"signature": "def read(msg_id)"
},
{
"docstring": "Get notification: all, by sender, by receiver get_by = ('sender/rec... | 3 | stack_v2_sparse_classes_30k_train_003092 | Implement the Python class `NotificationAPI` described below.
Class description:
Implemented notification api
Method signatures and docstrings:
- def send(sender, receiver, msg_type, message): Add notification
- def read(msg_id): Read message
- def get(get_by=None): Get notification: all, by sender, by receiver get_b... | Implement the Python class `NotificationAPI` described below.
Class description:
Implemented notification api
Method signatures and docstrings:
- def send(sender, receiver, msg_type, message): Add notification
- def read(msg_id): Read message
- def get(get_by=None): Get notification: all, by sender, by receiver get_b... | a14a5160e78c3d2ebf86a2eb91b13ae6f38ac32a | <|skeleton|>
class NotificationAPI:
"""Implemented notification api"""
def send(sender, receiver, msg_type, message):
"""Add notification"""
<|body_0|>
def read(msg_id):
"""Read message"""
<|body_1|>
def get(get_by=None):
"""Get notification: all, by sender, by... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotificationAPI:
"""Implemented notification api"""
def send(sender, receiver, msg_type, message):
"""Add notification"""
db_api = DataBaseAPI(NotificationDB).session
note = NotificationDB()
note.sender = sender
note.receiver = receiver
note.msg_type = msg_... | the_stack_v2_python_sparse | libs/user/notification_api.py | yacneyac/fportal | train | 0 |
ed3e8549fe20bd04c8c2de712e72c1acfd599457 | [
"super().__init__(energy=energy, direction=direction, particle_id=particle_id, name=name)\nself.x = x\nself.y = y\nself.prior_propagation_distance = prior_propagation_distance\nself.post_propagation_distance = post_propagation_distance\nself.propagation_step_size = propagation_step_size\nself.constant_de_dx = const... | <|body_start_0|>
super().__init__(energy=energy, direction=direction, particle_id=particle_id, name=name)
self.x = x
self.y = y
self.prior_propagation_distance = prior_propagation_distance
self.post_propagation_distance = post_propagation_distance
self.propagation_step_si... | This class implements a track-like particle. Energy depositions are distributed along the track in equal distances until the particle either has no more energy left or until it has propagated the specified distance. The track of the particle is defined by an anchor-point, the direction, and the propagation distance bef... | TrackParticle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrackParticle:
"""This class implements a track-like particle. Energy depositions are distributed along the track in equal distances until the particle either has no more energy left or until it has propagated the specified distance. The track of the particle is defined by an anchor-point, the di... | stack_v2_sparse_classes_36k_train_006702 | 6,812 | no_license | [
{
"docstring": "Initialize the track particle. Parameters ---------- energy : float The energy of the particle in arbitrary units. This must be greater equal zero. direction : float The direction of the particle in radians. The direction must be within [0, 2pi). x : float The x-coordinate of the track anchor-po... | 2 | stack_v2_sparse_classes_30k_test_001185 | Implement the Python class `TrackParticle` described below.
Class description:
This class implements a track-like particle. Energy depositions are distributed along the track in equal distances until the particle either has no more energy left or until it has propagated the specified distance. The track of the particl... | Implement the Python class `TrackParticle` described below.
Class description:
This class implements a track-like particle. Energy depositions are distributed along the track in equal distances until the particle either has no more energy left or until it has propagated the specified distance. The track of the particl... | 0d7442bd78f9899536a109e87a4c4639ade82a58 | <|skeleton|>
class TrackParticle:
"""This class implements a track-like particle. Energy depositions are distributed along the track in equal distances until the particle either has no more energy left or until it has propagated the specified distance. The track of the particle is defined by an anchor-point, the di... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrackParticle:
"""This class implements a track-like particle. Energy depositions are distributed along the track in equal distances until the particle either has no more energy left or until it has propagated the specified distance. The track of the particle is defined by an anchor-point, the direction, and ... | the_stack_v2_python_sparse | project_a5/simulation/particle/track.py | yungsalami/linuxtest | train | 0 |
2d6131dc1e935b2c4627483c654b7c7936f980cd | [
"self.cells = np.zeros(cells_shape)\nreal_width = cells_shape[0] - 2\nreal_height = cells_shape[1] - 2\nself.cells[1:-1, 1:-1] = np.random.randint(1, size=(real_width, real_height))\nself.timer = 0\nself.mask = np.ones(4)\nself.mask2 = np.ones(9)\nself.mask2[4] = 0",
"buf = np.zeros(self.cells.shape)\ncells = sel... | <|body_start_0|>
self.cells = np.zeros(cells_shape)
real_width = cells_shape[0] - 2
real_height = cells_shape[1] - 2
self.cells[1:-1, 1:-1] = np.random.randint(1, size=(real_width, real_height))
self.timer = 0
self.mask = np.ones(4)
self.mask2 = np.ones(9)
... | GameOfLife | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameOfLife:
def __init__(self, cells_shape):
"""Parameters ---------- cells_shape : 一个元组，表示画布的大小。 Examples -------- 建立一个高20，宽30的画布 game = GameOfLife((20, 30))"""
<|body_0|>
def update_state(self):
"""更新一次状态"""
<|body_1|>
def plot_state(self):
"""... | stack_v2_sparse_classes_36k_train_006703 | 4,173 | no_license | [
{
"docstring": "Parameters ---------- cells_shape : 一个元组，表示画布的大小。 Examples -------- 建立一个高20，宽30的画布 game = GameOfLife((20, 30))",
"name": "__init__",
"signature": "def __init__(self, cells_shape)"
},
{
"docstring": "更新一次状态",
"name": "update_state",
"signature": "def update_state(self)"
... | 4 | stack_v2_sparse_classes_30k_train_009254 | Implement the Python class `GameOfLife` described below.
Class description:
Implement the GameOfLife class.
Method signatures and docstrings:
- def __init__(self, cells_shape): Parameters ---------- cells_shape : 一个元组，表示画布的大小。 Examples -------- 建立一个高20，宽30的画布 game = GameOfLife((20, 30))
- def update_state(self): 更新一次... | Implement the Python class `GameOfLife` described below.
Class description:
Implement the GameOfLife class.
Method signatures and docstrings:
- def __init__(self, cells_shape): Parameters ---------- cells_shape : 一个元组，表示画布的大小。 Examples -------- 建立一个高20，宽30的画布 game = GameOfLife((20, 30))
- def update_state(self): 更新一次... | c7b1e4de3afda8eb64c0e48d0ec6a9ddd1eb15a0 | <|skeleton|>
class GameOfLife:
def __init__(self, cells_shape):
"""Parameters ---------- cells_shape : 一个元组，表示画布的大小。 Examples -------- 建立一个高20，宽30的画布 game = GameOfLife((20, 30))"""
<|body_0|>
def update_state(self):
"""更新一次状态"""
<|body_1|>
def plot_state(self):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameOfLife:
def __init__(self, cells_shape):
"""Parameters ---------- cells_shape : 一个元组，表示画布的大小。 Examples -------- 建立一个高20，宽30的画布 game = GameOfLife((20, 30))"""
self.cells = np.zeros(cells_shape)
real_width = cells_shape[0] - 2
real_height = cells_shape[1] - 2
self.cel... | the_stack_v2_python_sparse | day11.5/test.py | skyrookies/spider_learn | train | 1 | |
5e3c1767da85fc9a11cfda502c01d8108d32e1b2 | [
"self.nums = nums\nself.reset = lambda: nums\nprint(self.reset)",
"res = ListNode(0)\ntemp = self.head[:]\nwhile temp:\n ran = random.randrange(len(temp))\n res.append(temp[ran])\n temp.remove(temp[ran])\nreturn res"
] | <|body_start_0|>
self.nums = nums
self.reset = lambda: nums
print(self.reset)
<|end_body_0|>
<|body_start_1|>
res = ListNode(0)
temp = self.head[:]
while temp:
ran = random.randrange(len(temp))
res.append(temp[ran])
temp.remove(temp[ra... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
<|body_0|>
def getRandom(self):
""":rtype: List[int] randomly generate a number corre... | stack_v2_sparse_classes_36k_train_006704 | 1,098 | no_license | [
{
"docstring": "@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode",
"name": "__init__",
"signature": "def __init__(self, head)"
},
{
"docstring": ":rtype: List[int] randomly generate a number corresponding ... | 2 | stack_v2_sparse_classes_30k_train_010429 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): @param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode
- def getRan... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): @param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode
- def getRan... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
<|body_0|>
def getRandom(self):
""":rtype: List[int] randomly generate a number corre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
self.nums = nums
self.reset = lambda: nums
print(self.reset)
def getRandom(self):
"... | the_stack_v2_python_sparse | 382_linkedListShuffle.py | jennyChing/leetCode | train | 2 | |
b552b57e885cc03f71d154a606903e93c7d561f0 | [
"self.signatures = signature_dict\nself.ssgsea_kwds = ssgsea_kwds\nself.all_ids = reduce(lambda x, y: x.union(y), self.signatures.values(), set())",
"series_in = False\nif isinstance(sample_data, pd.Series):\n sample_data = pd.DataFrame(sample_data)\n series_in = True\nif sample_data.index.duplicated().any(... | <|body_start_0|>
self.signatures = signature_dict
self.ssgsea_kwds = ssgsea_kwds
self.all_ids = reduce(lambda x, y: x.union(y), self.signatures.values(), set())
<|end_body_0|>
<|body_start_1|>
series_in = False
if isinstance(sample_data, pd.Series):
sample_data = pd.... | Basic classifier that uses pre-defined signatures to score samples and assess classification. | ssGSEAClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ssGSEAClassifier:
"""Basic classifier that uses pre-defined signatures to score samples and assess classification."""
def __init__(self, signature_dict, **ssgsea_kwds):
""":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other ... | stack_v2_sparse_classes_36k_train_006705 | 3,530 | no_license | [
{
"docstring": ":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other row index :param ssgsea_kwds: Any additional kwargs are passed directly to the ssgsea algorithm.",
"name": "__init__",
"signature": "def __init__(self, signature_dict, **ssgsea... | 2 | stack_v2_sparse_classes_30k_train_015958 | Implement the Python class `ssGSEAClassifier` described below.
Class description:
Basic classifier that uses pre-defined signatures to score samples and assess classification.
Method signatures and docstrings:
- def __init__(self, signature_dict, **ssgsea_kwds): :param signature_dict: Dictionary. Keys are the class n... | Implement the Python class `ssGSEAClassifier` described below.
Class description:
Basic classifier that uses pre-defined signatures to score samples and assess classification.
Method signatures and docstrings:
- def __init__(self, signature_dict, **ssgsea_kwds): :param signature_dict: Dictionary. Keys are the class n... | 3cb6fa0e763ddc0a375fcd99a55eab5f9df26fe3 | <|skeleton|>
class ssGSEAClassifier:
"""Basic classifier that uses pre-defined signatures to score samples and assess classification."""
def __init__(self, signature_dict, **ssgsea_kwds):
""":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ssGSEAClassifier:
"""Basic classifier that uses pre-defined signatures to score samples and assess classification."""
def __init__(self, signature_dict, **ssgsea_kwds):
""":param signature_dict: Dictionary. Keys are the class name, values are iterables of genes / probes or any other row index :pa... | the_stack_v2_python_sparse | classification/signature.py | gaberosser/qmul-bioinf | train | 3 |
a46fd4c1c4ad085c0da0fbb28fbfbd97e7652ad4 | [
"found = False\nseedlist = self.get_Value()\nfor iseed in seedlist:\n found = iseed.startswith(name + ' ')\n if found:\n break\nreturn found",
"offset = jobproperties.RandomFlags.RandomSeedOffset.get_Value()\nnewseed = name + ' OFFSET ' + str(offset) + ' ' + str(seed1) + ' ' + str(seed2)\nlogRandomFl... | <|body_start_0|>
found = False
seedlist = self.get_Value()
for iseed in seedlist:
found = iseed.startswith(name + ' ')
if found:
break
return found
<|end_body_0|>
<|body_start_1|>
offset = jobproperties.RandomFlags.RandomSeedOffset.get_Val... | Random number stream seeds | RandomSeedList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomSeedList:
"""Random number stream seeds"""
def checkForExistingSeed(self, name):
"""Ensure that each stream is only initialized once"""
<|body_0|>
def addSeed(self, name, seed1, seed2):
"""Add seeds to internal seedlist. Seeds will be incremented by offset ... | stack_v2_sparse_classes_36k_train_006706 | 6,803 | no_license | [
{
"docstring": "Ensure that each stream is only initialized once",
"name": "checkForExistingSeed",
"signature": "def checkForExistingSeed(self, name)"
},
{
"docstring": "Add seeds to internal seedlist. Seeds will be incremented by offset values",
"name": "addSeed",
"signature": "def addS... | 5 | stack_v2_sparse_classes_30k_train_007144 | Implement the Python class `RandomSeedList` described below.
Class description:
Random number stream seeds
Method signatures and docstrings:
- def checkForExistingSeed(self, name): Ensure that each stream is only initialized once
- def addSeed(self, name, seed1, seed2): Add seeds to internal seedlist. Seeds will be i... | Implement the Python class `RandomSeedList` described below.
Class description:
Random number stream seeds
Method signatures and docstrings:
- def checkForExistingSeed(self, name): Ensure that each stream is only initialized once
- def addSeed(self, name, seed1, seed2): Add seeds to internal seedlist. Seeds will be i... | 22df23187ef85e9c3120122c8375ea0e7d8ea440 | <|skeleton|>
class RandomSeedList:
"""Random number stream seeds"""
def checkForExistingSeed(self, name):
"""Ensure that each stream is only initialized once"""
<|body_0|>
def addSeed(self, name, seed1, seed2):
"""Add seeds to internal seedlist. Seeds will be incremented by offset ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomSeedList:
"""Random number stream seeds"""
def checkForExistingSeed(self, name):
"""Ensure that each stream is only initialized once"""
found = False
seedlist = self.get_Value()
for iseed in seedlist:
found = iseed.startswith(name + ' ')
if fo... | the_stack_v2_python_sparse | athena/Control/RngComps/python/RandomFlags.py | rushioda/PIXELVALID_athena | train | 1 |
be9820eff1c4f8469af3a53d473ef9e2672c05bb | [
"if type(data) != np.ndarray or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nd, n = data.shape\nif n < 2:\n raise ValueError('data must contain multiple data points')\nX = data.T\nmean = np.mean(X, axis=0, keepdims=True)\ncov = np.matmul((X - mean).T, X - mean) / (n - 1)\nself.m... | <|body_start_0|>
if type(data) != np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
d, n = data.shape
if n < 2:
raise ValueError('data must contain multiple data points')
X = data.T
mean = np.mean(X, axis=0, keepdims=Tr... | MultiNormal class | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""MultiNormal class"""
def __init__(self, data):
"""Initializer"""
<|body_0|>
def pdf(self, x):
"""calculates the PDF at a data point. Args: x: (numpy.ndarray) containing the data point whose PDF should be calculated. Returns: (float) containing the... | stack_v2_sparse_classes_36k_train_006707 | 1,514 | no_license | [
{
"docstring": "Initializer",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "calculates the PDF at a data point. Args: x: (numpy.ndarray) containing the data point whose PDF should be calculated. Returns: (float) containing the value of the PDF.",
"name": "pdf... | 2 | null | Implement the Python class `MultiNormal` described below.
Class description:
MultiNormal class
Method signatures and docstrings:
- def __init__(self, data): Initializer
- def pdf(self, x): calculates the PDF at a data point. Args: x: (numpy.ndarray) containing the data point whose PDF should be calculated. Returns: (... | Implement the Python class `MultiNormal` described below.
Class description:
MultiNormal class
Method signatures and docstrings:
- def __init__(self, data): Initializer
- def pdf(self, x): calculates the PDF at a data point. Args: x: (numpy.ndarray) containing the data point whose PDF should be calculated. Returns: (... | 75274394adb52d740f6cd4000cc00bbde44b9b72 | <|skeleton|>
class MultiNormal:
"""MultiNormal class"""
def __init__(self, data):
"""Initializer"""
<|body_0|>
def pdf(self, x):
"""calculates the PDF at a data point. Args: x: (numpy.ndarray) containing the data point whose PDF should be calculated. Returns: (float) containing the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""MultiNormal class"""
def __init__(self, data):
"""Initializer"""
if type(data) != np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
d, n = data.shape
if n < 2:
raise ValueError('data must contain ... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | jdarangop/holbertonschool-machine_learning | train | 2 |
ec5c16e6b0505e1bbcec41c5e73e609eb7a11d24 | [
"self.constructeur = constructeur\nself.internes = internes\nself.l_externes = l_externes\nself.d_externes = d_externes",
"l_attributs = []\nfor attr in self.internes:\n if attr:\n l_attributs.append(getattr(objet, attr))\n else:\n l_attributs.append(objet)\nl_attributs.extend(self.l_externes)... | <|body_start_0|>
self.constructeur = constructeur
self.internes = internes
self.l_externes = l_externes
self.d_externes = d_externes
<|end_body_0|>
<|body_start_1|>
l_attributs = []
for attr in self.internes:
if attr:
l_attributs.append(getatt... | Définition d'une classe attribut. Elle prend en paramètre : - un constructeur - une liste de taille inconnue de paramètres à passer au constructeur de l'attribut Elle possède une méthode 'construire' qui retourne l'attribut construit. | Attribut | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Attribut:
"""Définition d'une classe attribut. Elle prend en paramètre : - un constructeur - une liste de taille inconnue de paramètres à passer au constructeur de l'attribut Elle possède une méthode 'construire' qui retourne l'attribut construit."""
def __init__(self, constructeur=None, int... | stack_v2_sparse_classes_36k_train_006708 | 3,048 | permissive | [
{
"docstring": "Constructeur d'un attribut",
"name": "__init__",
"signature": "def __init__(self, constructeur=None, internes=(), l_externes=(), d_externes={})"
},
{
"docstring": "On construit et retourne l'attribut. Les paramètres internes sont rattachés à 'objet' passé en paramètre. Par exempl... | 2 | stack_v2_sparse_classes_30k_val_000353 | Implement the Python class `Attribut` described below.
Class description:
Définition d'une classe attribut. Elle prend en paramètre : - un constructeur - une liste de taille inconnue de paramètres à passer au constructeur de l'attribut Elle possède une méthode 'construire' qui retourne l'attribut construit.
Method si... | Implement the Python class `Attribut` described below.
Class description:
Définition d'une classe attribut. Elle prend en paramètre : - un constructeur - une liste de taille inconnue de paramètres à passer au constructeur de l'attribut Elle possède une méthode 'construire' qui retourne l'attribut construit.
Method si... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class Attribut:
"""Définition d'une classe attribut. Elle prend en paramètre : - un constructeur - une liste de taille inconnue de paramètres à passer au constructeur de l'attribut Elle possède une méthode 'construire' qui retourne l'attribut construit."""
def __init__(self, constructeur=None, int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Attribut:
"""Définition d'une classe attribut. Elle prend en paramètre : - un constructeur - une liste de taille inconnue de paramètres à passer au constructeur de l'attribut Elle possède une méthode 'construire' qui retourne l'attribut construit."""
def __init__(self, constructeur=None, internes=(), l_e... | the_stack_v2_python_sparse | src/bases/objet/attribut.py | vincent-lg/tsunami | train | 5 |
ac833751a21f0b18f0ca50d8e1be0fa4233149ff | [
"self.logger = logging.getLogger(__name__)\nself.logger.addHandler(logging.NullHandler())\nself.root = BeautifulSoup(html, parser)",
"self.logger.debug('Shifting link tag values.')\na_tags = self.root.find_all('a')\nfor a_tag in a_tags:\n if a_tag.string is None:\n continue\n if 'href' not in a_tag.a... | <|body_start_0|>
self.logger = logging.getLogger(__name__)
self.logger.addHandler(logging.NullHandler())
self.root = BeautifulSoup(html, parser)
<|end_body_0|>
<|body_start_1|>
self.logger.debug('Shifting link tag values.')
a_tags = self.root.find_all('a')
for a_tag in a... | A class with tools to modify the HTML DOM via BeautifulSoup. Example: >>> html = open("sample.html").read() # string. >>> html = ModifyHTML(html, "html5lib") #BeautifulSoup object. >>> html.shift_links() >>> html.remove_images() >>> html.raw() # string version of the HTML with shifted links and no images. | ModifyHTML | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModifyHTML:
"""A class with tools to modify the HTML DOM via BeautifulSoup. Example: >>> html = open("sample.html").read() # string. >>> html = ModifyHTML(html, "html5lib") #BeautifulSoup object. >>> html.shift_links() >>> html.remove_images() >>> html.raw() # string version of the HTML with shif... | stack_v2_sparse_classes_36k_train_006709 | 6,227 | no_license | [
{
"docstring": "Sets instance attributes.",
"name": "__init__",
"signature": "def __init__(self, html, parser='html5lib')"
},
{
"docstring": "Appends each A tag's @href value to the tag's text value if the @href value starts with \"http\" or \"https\", i.e. \"<a href='bar'>foo</a>\" to \"<a href... | 4 | stack_v2_sparse_classes_30k_train_001545 | Implement the Python class `ModifyHTML` described below.
Class description:
A class with tools to modify the HTML DOM via BeautifulSoup. Example: >>> html = open("sample.html").read() # string. >>> html = ModifyHTML(html, "html5lib") #BeautifulSoup object. >>> html.shift_links() >>> html.remove_images() >>> html.raw()... | Implement the Python class `ModifyHTML` described below.
Class description:
A class with tools to modify the HTML DOM via BeautifulSoup. Example: >>> html = open("sample.html").read() # string. >>> html = ModifyHTML(html, "html5lib") #BeautifulSoup object. >>> html.shift_links() >>> html.remove_images() >>> html.raw()... | cbfb42e063e6d9436855ef7466c89e0f1c4d1ad3 | <|skeleton|>
class ModifyHTML:
"""A class with tools to modify the HTML DOM via BeautifulSoup. Example: >>> html = open("sample.html").read() # string. >>> html = ModifyHTML(html, "html5lib") #BeautifulSoup object. >>> html.shift_links() >>> html.remove_images() >>> html.raw() # string version of the HTML with shif... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModifyHTML:
"""A class with tools to modify the HTML DOM via BeautifulSoup. Example: >>> html = open("sample.html").read() # string. >>> html = ModifyHTML(html, "html5lib") #BeautifulSoup object. >>> html.shift_links() >>> html.remove_images() >>> html.raw() # string version of the HTML with shifted links and... | the_stack_v2_python_sparse | c4c/executables/b4 oct17/html_to_textOLD.py | sskenner/spydersPrj | train | 1 |
41770a091f9e1d5dad3af3007a5a0a58e5d07524 | [
"if k <= 0:\n return 0\nres = 0\nq = []\nodd_index = [-1]\ncount_odd = 0\nfor num_id, num in enumerate(nums):\n if num % 2:\n if count_odd == k:\n res += self.calc_sub_list(q, odd_index, num_id)\n count_odd -= 1\n q.append(num)\n odd_index.append(num_id)\n cou... | <|body_start_0|>
if k <= 0:
return 0
res = 0
q = []
odd_index = [-1]
count_odd = 0
for num_id, num in enumerate(nums):
if num % 2:
if count_odd == k:
res += self.calc_sub_list(q, odd_index, num_id)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numberOfSubarrays(self, nums: List[int], k: int) -> int:
"""思路： 举例 [2,2,2,1,2,2,1] k=1 1的index是3和6。 第一个1(满足k=1的条件)左边有四种可能(0-3个2, 3-(-1), -1相当于第0个奇数的索引,事实上不存在，3是第一个奇数1的索引)，右边有3中可能(0-2个2)因此，res=(3-(-1))*(6-3)=12 第二个1(满足k=1的条件)左边有三种可能(0-2个2)，右边有1中可能(0个2)因此，res=(6-3*(7-6)=3 所以总... | stack_v2_sparse_classes_36k_train_006710 | 2,847 | no_license | [
{
"docstring": "思路： 举例 [2,2,2,1,2,2,1] k=1 1的index是3和6。 第一个1(满足k=1的条件)左边有四种可能(0-3个2, 3-(-1), -1相当于第0个奇数的索引,事实上不存在，3是第一个奇数1的索引)，右边有3中可能(0-2个2)因此，res=(3-(-1))*(6-3)=12 第二个1(满足k=1的条件)左边有三种可能(0-2个2)，右边有1中可能(0个2)因此，res=(6-3*(7-6)=3 所以总共有12+3=15中可能",
"name": "numberOfSubarrays",
"signature": "def numberOfSuba... | 2 | stack_v2_sparse_classes_30k_train_009149 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numberOfSubarrays(self, nums: List[int], k: int) -> int: 思路： 举例 [2,2,2,1,2,2,1] k=1 1的index是3和6。 第一个1(满足k=1的条件)左边有四种可能(0-3个2, 3-(-1), -1相当于第0个奇数的索引,事实上不存在，3是第一个奇数1的索引)，右边有3中可... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numberOfSubarrays(self, nums: List[int], k: int) -> int: 思路： 举例 [2,2,2,1,2,2,1] k=1 1的index是3和6。 第一个1(满足k=1的条件)左边有四种可能(0-3个2, 3-(-1), -1相当于第0个奇数的索引,事实上不存在，3是第一个奇数1的索引)，右边有3中可... | 2f15563a6749ede4f244792314377db4d7c263ec | <|skeleton|>
class Solution:
def numberOfSubarrays(self, nums: List[int], k: int) -> int:
"""思路： 举例 [2,2,2,1,2,2,1] k=1 1的index是3和6。 第一个1(满足k=1的条件)左边有四种可能(0-3个2, 3-(-1), -1相当于第0个奇数的索引,事实上不存在，3是第一个奇数1的索引)，右边有3中可能(0-2个2)因此，res=(3-(-1))*(6-3)=12 第二个1(满足k=1的条件)左边有三种可能(0-2个2)，右边有1中可能(0个2)因此，res=(6-3*(7-6)=3 所以总... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numberOfSubarrays(self, nums: List[int], k: int) -> int:
"""思路： 举例 [2,2,2,1,2,2,1] k=1 1的index是3和6。 第一个1(满足k=1的条件)左边有四种可能(0-3个2, 3-(-1), -1相当于第0个奇数的索引,事实上不存在，3是第一个奇数1的索引)，右边有3中可能(0-2个2)因此，res=(3-(-1))*(6-3)=12 第二个1(满足k=1的条件)左边有三种可能(0-2个2)，右边有1中可能(0个2)因此，res=(6-3*(7-6)=3 所以总共有12+3=15中可能""... | the_stack_v2_python_sparse | array/1248. 统计「优美子数组」.py | Werifun/leetcode | train | 0 | |
23345d2ad3bec52df30ef073db3d4e0ebd9fb82b | [
"lab = Label(text=text, font_size=30, padding_x=5)\nlab.texture_update()\nreturn lab.texture_size",
"if self.talking:\n tsize = self.get_text_size(text)\n anim = Animation(text_colour=[1.0, 1.0, 1.0, 0.0], duration=0.2)\n anim += Animation(size=tsize, duration=0.5)\n anim.bind(on_complete=lambda x, y:... | <|body_start_0|>
lab = Label(text=text, font_size=30, padding_x=5)
lab.texture_update()
return lab.texture_size
<|end_body_0|>
<|body_start_1|>
if self.talking:
tsize = self.get_text_size(text)
anim = Animation(text_colour=[1.0, 1.0, 1.0, 0.0], duration=0.2)
... | Class for each individual NPC. | NPC | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NPC:
"""Class for each individual NPC."""
def get_text_size(self, text):
"""Helper method, weighs the size of the text."""
<|body_0|>
def update_speech(self, text):
"""Used to change speech in dialogue."""
<|body_1|>
def _upd_speech(self, txt):
... | stack_v2_sparse_classes_36k_train_006711 | 13,499 | no_license | [
{
"docstring": "Helper method, weighs the size of the text.",
"name": "get_text_size",
"signature": "def get_text_size(self, text)"
},
{
"docstring": "Used to change speech in dialogue.",
"name": "update_speech",
"signature": "def update_speech(self, text)"
},
{
"docstring": "Pri... | 4 | null | Implement the Python class `NPC` described below.
Class description:
Class for each individual NPC.
Method signatures and docstrings:
- def get_text_size(self, text): Helper method, weighs the size of the text.
- def update_speech(self, text): Used to change speech in dialogue.
- def _upd_speech(self, txt): Private h... | Implement the Python class `NPC` described below.
Class description:
Class for each individual NPC.
Method signatures and docstrings:
- def get_text_size(self, text): Helper method, weighs the size of the text.
- def update_speech(self, text): Used to change speech in dialogue.
- def _upd_speech(self, txt): Private h... | 732853897ae0048909efba7b57ea456e6aaf9e10 | <|skeleton|>
class NPC:
"""Class for each individual NPC."""
def get_text_size(self, text):
"""Helper method, weighs the size of the text."""
<|body_0|>
def update_speech(self, text):
"""Used to change speech in dialogue."""
<|body_1|>
def _upd_speech(self, txt):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NPC:
"""Class for each individual NPC."""
def get_text_size(self, text):
"""Helper method, weighs the size of the text."""
lab = Label(text=text, font_size=30, padding_x=5)
lab.texture_update()
return lab.texture_size
def update_speech(self, text):
"""Used to ... | the_stack_v2_python_sparse | Games/Story-RPG/Original/entities.py | Exodus111/Projects | train | 1 |
6926353fdae3345fd9c58cba4e88b821d6076eee | [
"def dfs(root):\n if not root:\n res.append('None')\n return\n res.append(str(root.val))\n dfs(root.left)\n dfs(root.right)\nres = []\ndfs(root)\nreturn ','.join(res)",
"def recursiveDeserialize(stringList):\n if stringList[0] == 'None':\n stringList.pop(0)\n return None... | <|body_start_0|>
def dfs(root):
if not root:
res.append('None')
return
res.append(str(root.val))
dfs(root.left)
dfs(root.right)
res = []
dfs(root)
return ','.join(res)
<|end_body_0|>
<|body_start_1|>
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: 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_006712 | 2,513 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_018133 | 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:... | d4d138716db9bfa236c87c25ae582a76a14faa28 | <|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"""
def dfs(root):
if not root:
res.append('None')
return
res.append(str(root.val))
dfs(root.left)
dfs(root.ri... | the_stack_v2_python_sparse | SerializeAndDeserializeBinaryTree.py | aaronfox/LeetCode-Work | train | 0 | |
ba055b1214ab013bece7d277b8c7ae461caac1e1 | [
"Node.__init__(self)\nself.dim = dim\nif init:\n self.value = np.mat(np.random.normal(0, 0.001, (self.dim, 1)))\nself.trainable = trainable",
"assert isinstance(value, np.matrix) and value.shape == (self.dim, 1)\nself.reset_value()\nself.value = value"
] | <|body_start_0|>
Node.__init__(self)
self.dim = dim
if init:
self.value = np.mat(np.random.normal(0, 0.001, (self.dim, 1)))
self.trainable = trainable
<|end_body_0|>
<|body_start_1|>
assert isinstance(value, np.matrix) and value.shape == (self.dim, 1)
self.re... | 变（向）量节点 | Variable | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Variable:
"""变（向）量节点"""
def __init__(self, dim, init=False, trainable=True):
"""变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识"""
<|body_0|>
def set_value(self, value):
"""为变量赋值"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Node.__init__(self)
se... | stack_v2_sparse_classes_36k_train_006713 | 6,904 | permissive | [
{
"docstring": "变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识",
"name": "__init__",
"signature": "def __init__(self, dim, init=False, trainable=True)"
},
{
"docstring": "为变量赋值",
"name": "set_value",
"signature": "def set_value(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006925 | Implement the Python class `Variable` described below.
Class description:
变（向）量节点
Method signatures and docstrings:
- def __init__(self, dim, init=False, trainable=True): 变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识
- def set_value(self, value): 为变量赋值 | Implement the Python class `Variable` described below.
Class description:
变（向）量节点
Method signatures and docstrings:
- def __init__(self, dim, init=False, trainable=True): 变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识
- def set_value(self, value): 为变量赋值
<|skeleton|>
class Variable:
"""变（向）量节点"""
def __init__(self, dim... | b4a9ddcc2820fd0e3c9bbd81c26a8fa35f348c23 | <|skeleton|>
class Variable:
"""变（向）量节点"""
def __init__(self, dim, init=False, trainable=True):
"""变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识"""
<|body_0|>
def set_value(self, value):
"""为变量赋值"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Variable:
"""变（向）量节点"""
def __init__(self, dim, init=False, trainable=True):
"""变量节点没有父节点，构造函数接受变量的维数，以及变量是否参与训练的标识"""
Node.__init__(self)
self.dim = dim
if init:
self.value = np.mat(np.random.normal(0, 0.001, (self.dim, 1)))
self.trainable = trainable
... | the_stack_v2_python_sparse | lang/programming/python/深入理解神经网络：从逻辑回归到CNN/neural_network-neural_network_code-master/neural_network_code/第 8 章 计算图/node.py | dlxj/doc | train | 10 |
275fa2c7e5d4e146c26456ec9769dc22ac47e764 | [
"n = len(arr)\nbest_i = 0\ndist = sum([abs(arr[i] - x) for i in range(k)])\nfor i in range(1, n - k + 1):\n new_dist = dist - abs(arr[i - 1] - x) + abs(arr[i + (k - 1)] - x)\n if new_dist < dist:\n dist = new_dist\n best_i = i\nreturn arr[best_i:best_i + k]",
"n = len(arr)\nl, r = (0, n)\nwhil... | <|body_start_0|>
n = len(arr)
best_i = 0
dist = sum([abs(arr[i] - x) for i in range(k)])
for i in range(1, n - k + 1):
new_dist = dist - abs(arr[i - 1] - x) + abs(arr[i + (k - 1)] - x)
if new_dist < dist:
dist = new_dist
best_i = i
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]:
"""Sliding Window, Time: O(n), Space: O(k) for returns"""
<|body_0|>
def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]:
"""Binary Search, Time: O(logn+k), S... | stack_v2_sparse_classes_36k_train_006714 | 1,595 | no_license | [
{
"docstring": "Sliding Window, Time: O(n), Space: O(k) for returns",
"name": "findClosestElements",
"signature": "def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]"
},
{
"docstring": "Binary Search, Time: O(logn+k), Space: O(k) for returns",
"name": "findClosestElem... | 2 | stack_v2_sparse_classes_30k_train_005792 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]: Sliding Window, Time: O(n), Space: O(k) for returns
- def findClosestElements(self, arr: List[int], k:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]: Sliding Window, Time: O(n), Space: O(k) for returns
- def findClosestElements(self, arr: List[int], k:... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]:
"""Sliding Window, Time: O(n), Space: O(k) for returns"""
<|body_0|>
def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]:
"""Binary Search, Time: O(logn+k), S... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findClosestElements(self, arr: List[int], k: int, x: int) -> List[int]:
"""Sliding Window, Time: O(n), Space: O(k) for returns"""
n = len(arr)
best_i = 0
dist = sum([abs(arr[i] - x) for i in range(k)])
for i in range(1, n - k + 1):
new_dist = d... | the_stack_v2_python_sparse | python/658-Find K Closest Elements.py | cwza/leetcode | train | 0 | |
884d63824f61ffe9bdb65c8b283659498eb9699b | [
"previous = None\ncurrent = head\nwhile current:\n next = current.next\n current.setNext(previous)\n previous = current\n current = next\nhead = current\nreturn previous",
"if head == None or head.getNext() == None:\n return head\nelse:\n new_head = self.reverseListRecursive(head.getNext())\n ... | <|body_start_0|>
previous = None
current = head
while current:
next = current.next
current.setNext(previous)
previous = current
current = next
head = current
return previous
<|end_body_0|>
<|body_start_1|>
if head == None o... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseListIteratively(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseListRecursive(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
def reverseListStack(self, head):
""":type head:... | stack_v2_sparse_classes_36k_train_006715 | 1,941 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseListIteratively",
"signature": "def reverseListIteratively(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseListRecursive",
"signature": "def reverseListRecursive(self, head)"
... | 3 | stack_v2_sparse_classes_30k_train_021463 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseListIteratively(self, head): :type head: ListNode :rtype: ListNode
- def reverseListRecursive(self, head): :type head: ListNode :rtype: ListNode
- def reverseListStack... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseListIteratively(self, head): :type head: ListNode :rtype: ListNode
- def reverseListRecursive(self, head): :type head: ListNode :rtype: ListNode
- def reverseListStack... | 52d71a93de7f002ac887a82c947e1e32a3e7255f | <|skeleton|>
class Solution:
def reverseListIteratively(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseListRecursive(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
def reverseListStack(self, head):
""":type head:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseListIteratively(self, head):
""":type head: ListNode :rtype: ListNode"""
previous = None
current = head
while current:
next = current.next
current.setNext(previous)
previous = current
current = next
he... | the_stack_v2_python_sparse | reverse-linked-list/solution.py | code-in-public/leetcode | train | 3 | |
90200695d97e7dad68b0b3a641b4fb01cc34eee1 | [
"self.E1 = E1\nself.E2 = E2\nself.G12 = G12\nself.nu12 = nu12\nself.rho = rho\nself.name = name",
"f = open(fname)\nskipLines(f, 3)\nmaterials = []\nfor line in f:\n array = line.split()\n mat = cls(float(array[1]), float(array[2]), float(array[3]), float(array[4]), float(array[5]), array[6])\n materials... | <|body_start_0|>
self.E1 = E1
self.E2 = E2
self.G12 = G12
self.nu12 = nu12
self.rho = rho
self.name = name
<|end_body_0|>
<|body_start_1|>
f = open(fname)
skipLines(f, 3)
materials = []
for line in f:
array = line.split()
... | Represents a homogeneous orthotropic material in a plane stress state. | Orthotropic2DMaterial | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Orthotropic2DMaterial:
"""Represents a homogeneous orthotropic material in a plane stress state."""
def __init__(self, E1, E2, G12, nu12, rho, name=''):
"""a struct-like object. all inputs are also fields. The object also has an identification number *.mat_idx so unique materials can... | stack_v2_sparse_classes_36k_train_006716 | 46,713 | permissive | [
{
"docstring": "a struct-like object. all inputs are also fields. The object also has an identification number *.mat_idx so unique materials can be identified. Parameters ---------- E1 : float (N/m^2) Young's modulus in first principal direction E2 : float (N/m^2) Young's modulus in second principal direction G... | 2 | null | Implement the Python class `Orthotropic2DMaterial` described below.
Class description:
Represents a homogeneous orthotropic material in a plane stress state.
Method signatures and docstrings:
- def __init__(self, E1, E2, G12, nu12, rho, name=''): a struct-like object. all inputs are also fields. The object also has a... | Implement the Python class `Orthotropic2DMaterial` described below.
Class description:
Represents a homogeneous orthotropic material in a plane stress state.
Method signatures and docstrings:
- def __init__(self, E1, E2, G12, nu12, rho, name=''): a struct-like object. all inputs are also fields. The object also has a... | d7270ebe1c554293a9d36730d67ab555c071cb17 | <|skeleton|>
class Orthotropic2DMaterial:
"""Represents a homogeneous orthotropic material in a plane stress state."""
def __init__(self, E1, E2, G12, nu12, rho, name=''):
"""a struct-like object. all inputs are also fields. The object also has an identification number *.mat_idx so unique materials can... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Orthotropic2DMaterial:
"""Represents a homogeneous orthotropic material in a plane stress state."""
def __init__(self, E1, E2, G12, nu12, rho, name=''):
"""a struct-like object. all inputs are also fields. The object also has an identification number *.mat_idx so unique materials can be identifie... | the_stack_v2_python_sparse | wisdem/rotorse/precomp.py | WISDEM/WISDEM | train | 120 |
28e24b31e0271fe24559f6fdfff255d20ff1d1e8 | [
"try:\n if not data['project_id'] or not data['case_id'] or (not data['id']) or (not data['host_id']):\n return JsonResponse(code=code.CODE_PARAMETER_ERROR)\nexcept KeyError:\n return JsonResponse(code=code.CODE_PARAMETER_ERROR)",
"data = JSONParser().parse(request)\nproject = get_availability_projec... | <|body_start_0|>
try:
if not data['project_id'] or not data['case_id'] or (not data['id']) or (not data['host_id']):
return JsonResponse(code=code.CODE_PARAMETER_ERROR)
except KeyError:
return JsonResponse(code=code.CODE_PARAMETER_ERROR)
<|end_body_0|>
<|body_sta... | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
def parameter_check(self, data):
"""校验参数 :param data: :return:"""
<|body_0|>
def post(self, request):
"""执行 :param request: :return:0"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
if not data['project_id'] or not data['case_... | stack_v2_sparse_classes_36k_train_006717 | 11,514 | no_license | [
{
"docstring": "校验参数 :param data: :return:",
"name": "parameter_check",
"signature": "def parameter_check(self, data)"
},
{
"docstring": "执行 :param request: :return:0",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005290 | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def parameter_check(self, data): 校验参数 :param data: :return:
- def post(self, request): 执行 :param request: :return:0 | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def parameter_check(self, data): 校验参数 :param data: :return:
- def post(self, request): 执行 :param request: :return:0
<|skeleton|>
class Test:
def parameter_check(self, data):
... | 85a3804c10c6966eecf89deb7a6baccd2a03b875 | <|skeleton|>
class Test:
def parameter_check(self, data):
"""校验参数 :param data: :return:"""
<|body_0|>
def post(self, request):
"""执行 :param request: :return:0"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test:
def parameter_check(self, data):
"""校验参数 :param data: :return:"""
try:
if not data['project_id'] or not data['case_id'] or (not data['id']) or (not data['host_id']):
return JsonResponse(code=code.CODE_PARAMETER_ERROR)
except KeyError:
retur... | the_stack_v2_python_sparse | api_test/views/test_case.py | AqiComing/Aqi_Automations_API | train | 0 | |
fd568b75de80c290f602f228a76c009882ea4e9d | [
"g.sort()\ns.sort()\ncount = 0\ni, j = (0, 0)\nm, n = (len(g), len(s))\nwhile i < m and j < n:\n if s[j] >= g[i]:\n i += 1\n j += 1\n count += 1\n else:\n j += 1\nreturn count",
"g.sort()\ns.sort()\nans = 0\nwhile g and s:\n if s[0] >= g[0]:\n ans += 1\n g.pop(0)... | <|body_start_0|>
g.sort()
s.sort()
count = 0
i, j = (0, 0)
m, n = (len(g), len(s))
while i < m and j < n:
if s[j] >= g[i]:
i += 1
j += 1
count += 1
else:
j += 1
return count
<|... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findContentChildren(self, g, s):
""":type g: List[int] :type s: List[int] :rtype: int"""
<|body_0|>
def findContentChildren2(self, g, s):
""":type g: List[int] :type s: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006718 | 1,187 | no_license | [
{
"docstring": ":type g: List[int] :type s: List[int] :rtype: int",
"name": "findContentChildren",
"signature": "def findContentChildren(self, g, s)"
},
{
"docstring": ":type g: List[int] :type s: List[int] :rtype: int",
"name": "findContentChildren2",
"signature": "def findContentChildr... | 2 | stack_v2_sparse_classes_30k_train_007891 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findContentChildren(self, g, s): :type g: List[int] :type s: List[int] :rtype: int
- def findContentChildren2(self, g, s): :type g: List[int] :type s: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findContentChildren(self, g, s): :type g: List[int] :type s: List[int] :rtype: int
- def findContentChildren2(self, g, s): :type g: List[int] :type s: List[int] :rtype: int
... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def findContentChildren(self, g, s):
""":type g: List[int] :type s: List[int] :rtype: int"""
<|body_0|>
def findContentChildren2(self, g, s):
""":type g: List[int] :type s: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findContentChildren(self, g, s):
""":type g: List[int] :type s: List[int] :rtype: int"""
g.sort()
s.sort()
count = 0
i, j = (0, 0)
m, n = (len(g), len(s))
while i < m and j < n:
if s[j] >= g[i]:
i += 1
... | the_stack_v2_python_sparse | 455. Assign Cookies/cookie.py | Macielyoung/LeetCode | train | 1 | |
075f1e254770ec0a618e4773a9cbf8b3a096061f | [
"dp = [1] * (n + 1)\nfor i in range(2, n + 1):\n for j in range(1, i // 2 + 1):\n dp[i] = max(dp[i], max(i - j, dp[i - j]) * j)\nreturn dp[-1]",
"res = 1\n\ndef dfs(remain, count, presum):\n nonlocal res\n if remain == 0:\n if count > 1:\n res = max(res, presum)\n return\n... | <|body_start_0|>
dp = [1] * (n + 1)
for i in range(2, n + 1):
for j in range(1, i // 2 + 1):
dp[i] = max(dp[i], max(i - j, dp[i - j]) * j)
return dp[-1]
<|end_body_0|>
<|body_start_1|>
res = 1
def dfs(remain, count, presum):
nonlocal res
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def integerBreak1(self, n: int) -> int:
"""思路：动态规划法 1. i:当前n的大小； 2. j:最后一段划分的长度 3. 当划分了最后一段后，前面的有两种情况： 1）i-j:表示没有分段 2）dp[i-j]:表示有分段"""
<|body_0|>
def integerBreak2(self, n: int) -> int:
"""思路：dfs超时"""
<|body_1|>
def integerBreak3(self, n: int) ... | stack_v2_sparse_classes_36k_train_006719 | 2,843 | no_license | [
{
"docstring": "思路：动态规划法 1. i:当前n的大小； 2. j:最后一段划分的长度 3. 当划分了最后一段后，前面的有两种情况： 1）i-j:表示没有分段 2）dp[i-j]:表示有分段",
"name": "integerBreak1",
"signature": "def integerBreak1(self, n: int) -> int"
},
{
"docstring": "思路：dfs超时",
"name": "integerBreak2",
"signature": "def integerBreak2(self, n: int) -... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerBreak1(self, n: int) -> int: 思路：动态规划法 1. i:当前n的大小； 2. j:最后一段划分的长度 3. 当划分了最后一段后，前面的有两种情况： 1）i-j:表示没有分段 2）dp[i-j]:表示有分段
- def integerBreak2(self, n: int) -> int: 思路：dfs超... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerBreak1(self, n: int) -> int: 思路：动态规划法 1. i:当前n的大小； 2. j:最后一段划分的长度 3. 当划分了最后一段后，前面的有两种情况： 1）i-j:表示没有分段 2）dp[i-j]:表示有分段
- def integerBreak2(self, n: int) -> int: 思路：dfs超... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def integerBreak1(self, n: int) -> int:
"""思路：动态规划法 1. i:当前n的大小； 2. j:最后一段划分的长度 3. 当划分了最后一段后，前面的有两种情况： 1）i-j:表示没有分段 2）dp[i-j]:表示有分段"""
<|body_0|>
def integerBreak2(self, n: int) -> int:
"""思路：dfs超时"""
<|body_1|>
def integerBreak3(self, n: int) ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def integerBreak1(self, n: int) -> int:
"""思路：动态规划法 1. i:当前n的大小； 2. j:最后一段划分的长度 3. 当划分了最后一段后，前面的有两种情况： 1）i-j:表示没有分段 2）dp[i-j]:表示有分段"""
dp = [1] * (n + 1)
for i in range(2, n + 1):
for j in range(1, i // 2 + 1):
dp[i] = max(dp[i], max(i - j, dp[i - ... | the_stack_v2_python_sparse | LeetCode/动态规划法(dp)/343. 整数拆分.py | yiming1012/MyLeetCode | train | 2 | |
7678c0146afcfe24fad1401d4474d098fa05d29c | [
"super(SourceTraitSearchForm, self).__init__(*args, **kwargs)\nself.helper = FormHelper(self)\nself.helper.form_method = 'get'\nself.helper.form_class = 'form-horizontal'\nself.helper.label_class = 'col-sm-2'\nself.helper.field_class = 'col-sm-10'\nself.helper.layout = Layout(Row(Div(name_checkbox_layout, 'descript... | <|body_start_0|>
super(SourceTraitSearchForm, self).__init__(*args, **kwargs)
self.helper = FormHelper(self)
self.helper.form_method = 'get'
self.helper.form_class = 'form-horizontal'
self.helper.label_class = 'col-sm-2'
self.helper.field_class = 'col-sm-10'
self.... | Form to handle django-watson searches for SourceTrait objects. This form class is a Subclass of crispy_forms.Form. Crispy forms is a Django app that improves upon the built in Django Form object. | SourceTraitSearchForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceTraitSearchForm:
"""Form to handle django-watson searches for SourceTrait objects. This form class is a Subclass of crispy_forms.Form. Crispy forms is a Django app that improves upon the built in Django Form object."""
def __init__(self, *args, **kwargs):
"""Initialize form wit... | stack_v2_sparse_classes_36k_train_006720 | 19,577 | permissive | [
{
"docstring": "Initialize form with formatting and submit button.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Perform additional multi-field cleaning to make sure that either description or name is entered.",
"name": "clean",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_010750 | Implement the Python class `SourceTraitSearchForm` described below.
Class description:
Form to handle django-watson searches for SourceTrait objects. This form class is a Subclass of crispy_forms.Form. Crispy forms is a Django app that improves upon the built in Django Form object.
Method signatures and docstrings:
-... | Implement the Python class `SourceTraitSearchForm` described below.
Class description:
Form to handle django-watson searches for SourceTrait objects. This form class is a Subclass of crispy_forms.Form. Crispy forms is a Django app that improves upon the built in Django Form object.
Method signatures and docstrings:
-... | 89ae277f5ba1357580d78c3527f26200686308a6 | <|skeleton|>
class SourceTraitSearchForm:
"""Form to handle django-watson searches for SourceTrait objects. This form class is a Subclass of crispy_forms.Form. Crispy forms is a Django app that improves upon the built in Django Form object."""
def __init__(self, *args, **kwargs):
"""Initialize form wit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SourceTraitSearchForm:
"""Form to handle django-watson searches for SourceTrait objects. This form class is a Subclass of crispy_forms.Form. Crispy forms is a Django app that improves upon the built in Django Form object."""
def __init__(self, *args, **kwargs):
"""Initialize form with formatting ... | the_stack_v2_python_sparse | trait_browser/forms.py | UW-GAC/pie | train | 0 |
5885f66e6d7e56f733deb43afa3733a8d645136c | [
"k = 2 * np.pi / wave.wavelength\nunwrapped_phase_lbl = f'[{np.min(wave.get_unwrapped_phase(aperture=aperture, z=z)[0]):.2f}, {np.max(wave.get_unwrapped_phase(aperture=aperture, z=z)[0]):.2f}] rad; [{np.min(wave.get_unwrapped_phase(aperture=aperture, z=z)[0]) * 1000000.0 / k:.1f}, {np.max(wave.get_unwrapped_phase(a... | <|body_start_0|>
k = 2 * np.pi / wave.wavelength
unwrapped_phase_lbl = f'[{np.min(wave.get_unwrapped_phase(aperture=aperture, z=z)[0]):.2f}, {np.max(wave.get_unwrapped_phase(aperture=aperture, z=z)[0]):.2f}] rad; [{np.min(wave.get_unwrapped_phase(aperture=aperture, z=z)[0]) * 1000000.0 / k:.1f}, {np.max... | Построение графиков распространения волны в пространстве | WavePlotter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WavePlotter:
"""Построение графиков распространения волны в пространстве"""
def save_phase(wave: Wave, aperture: Aperture, z: float, saver: Saver, save_npy: bool=False):
"""Сохраняет график для фазы :return:"""
<|body_0|>
def save_intensity(wave: Wave, z: float, saver: S... | stack_v2_sparse_classes_36k_train_006721 | 3,997 | no_license | [
{
"docstring": "Сохраняет график для фазы :return:",
"name": "save_phase",
"signature": "def save_phase(wave: Wave, aperture: Aperture, z: float, saver: Saver, save_npy: bool=False)"
},
{
"docstring": "Сохраняет график для интенсивности :return:",
"name": "save_intensity",
"signature": "... | 4 | stack_v2_sparse_classes_30k_train_006136 | Implement the Python class `WavePlotter` described below.
Class description:
Построение графиков распространения волны в пространстве
Method signatures and docstrings:
- def save_phase(wave: Wave, aperture: Aperture, z: float, saver: Saver, save_npy: bool=False): Сохраняет график для фазы :return:
- def save_intensit... | Implement the Python class `WavePlotter` described below.
Class description:
Построение графиков распространения волны в пространстве
Method signatures and docstrings:
- def save_phase(wave: Wave, aperture: Aperture, z: float, saver: Saver, save_npy: bool=False): Сохраняет график для фазы :return:
- def save_intensit... | 102ff08f22d9f82d74884d5c31a6b91b804d26f4 | <|skeleton|>
class WavePlotter:
"""Построение графиков распространения волны в пространстве"""
def save_phase(wave: Wave, aperture: Aperture, z: float, saver: Saver, save_npy: bool=False):
"""Сохраняет график для фазы :return:"""
<|body_0|>
def save_intensity(wave: Wave, z: float, saver: S... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WavePlotter:
"""Построение графиков распространения волны в пространстве"""
def save_phase(wave: Wave, aperture: Aperture, z: float, saver: Saver, save_npy: bool=False):
"""Сохраняет график для фазы :return:"""
k = 2 * np.pi / wave.wavelength
unwrapped_phase_lbl = f'[{np.min(wave.... | the_stack_v2_python_sparse | src/propagation/presenter/interface/wave_plotter.py | megamott/Phase-problem-modeling | train | 2 |
9827027d6011841b373dcc555e813f9804a058c9 | [
"self.dict = dict()\nself.chars = []\nfor i in range(ord('a'), ord('z') + 1):\n self.chars.append(chr(i))",
"for word in dict:\n for charIndex in range(0, len(word)):\n for w in self.chars:\n if w != word[charIndex]:\n newStr = word[0:charIndex] + w + word[charIndex + 1:len(... | <|body_start_0|>
self.dict = dict()
self.chars = []
for i in range(ord('a'), ord('z') + 1):
self.chars.append(chr(i))
<|end_body_0|>
<|body_start_1|>
for word in dict:
for charIndex in range(0, len(word)):
for w in self.chars:
... | MagicDictionary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MagicDictionary:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def buildDict(self, dict):
"""Build a dictionary through a list of words :type dict: List[str] :rtype: None"""
<|body_1|>
def search(self, word):
"""Return... | stack_v2_sparse_classes_36k_train_006722 | 1,381 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Build a dictionary through a list of words :type dict: List[str] :rtype: None",
"name": "buildDict",
"signature": "def buildDict(self, dict)"
},
{
"docs... | 3 | stack_v2_sparse_classes_30k_train_002849 | Implement the Python class `MagicDictionary` described below.
Class description:
Implement the MagicDictionary class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def buildDict(self, dict): Build a dictionary through a list of words :type dict: List[str] :rtype: None
... | Implement the Python class `MagicDictionary` described below.
Class description:
Implement the MagicDictionary class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def buildDict(self, dict): Build a dictionary through a list of words :type dict: List[str] :rtype: None
... | 56c9bfde870e2d682539e5bf223e0f32e411e610 | <|skeleton|>
class MagicDictionary:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def buildDict(self, dict):
"""Build a dictionary through a list of words :type dict: List[str] :rtype: None"""
<|body_1|>
def search(self, word):
"""Return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MagicDictionary:
def __init__(self):
"""Initialize your data structure here."""
self.dict = dict()
self.chars = []
for i in range(ord('a'), ord('z') + 1):
self.chars.append(chr(i))
def buildDict(self, dict):
"""Build a dictionary through a list of words... | the_stack_v2_python_sparse | Tree/Implement Magic Dictionary.py | lulukdog/leetcode-Python | train | 3 | |
60b332c50a941ae0f7c4f6e8da27b7c4e836e455 | [
"param = {'account': self.phone, 'address': '办公地址', 'annexList': [{'name': '1', 'url': '1.txt'}, {'name': '2', 'url': '2.png'}], 'businessLicense': random.randint(1000000, 9999999), 'certificateList': [{'name': '1', 'url': '1.txt'}, {'name': '2', 'url': '2.png'}], 'constructorCount': 100, 'email': 'string@163.com',... | <|body_start_0|>
param = {'account': self.phone, 'address': '办公地址', 'annexList': [{'name': '1', 'url': '1.txt'}, {'name': '2', 'url': '2.png'}], 'businessLicense': random.randint(1000000, 9999999), 'certificateList': [{'name': '1', 'url': '1.txt'}, {'name': '2', 'url': '2.png'}], 'constructorCount': 100, 'email... | TestGovernConstruction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGovernConstruction:
def test_001_add_construction_business(self):
"""【政府端--适老化】：添加施工单位"""
<|body_0|>
def test_002_get_construction_business_list(self):
"""【政府端--适老化】：分页查询施工单位列表"""
<|body_1|>
def test_003_edit_construction_business(self):
"""【... | stack_v2_sparse_classes_36k_train_006723 | 5,711 | no_license | [
{
"docstring": "【政府端--适老化】：添加施工单位",
"name": "test_001_add_construction_business",
"signature": "def test_001_add_construction_business(self)"
},
{
"docstring": "【政府端--适老化】：分页查询施工单位列表",
"name": "test_002_get_construction_business_list",
"signature": "def test_002_get_construction_business... | 6 | stack_v2_sparse_classes_30k_train_017752 | Implement the Python class `TestGovernConstruction` described below.
Class description:
Implement the TestGovernConstruction class.
Method signatures and docstrings:
- def test_001_add_construction_business(self): 【政府端--适老化】：添加施工单位
- def test_002_get_construction_business_list(self): 【政府端--适老化】：分页查询施工单位列表
- def test_... | Implement the Python class `TestGovernConstruction` described below.
Class description:
Implement the TestGovernConstruction class.
Method signatures and docstrings:
- def test_001_add_construction_business(self): 【政府端--适老化】：添加施工单位
- def test_002_get_construction_business_list(self): 【政府端--适老化】：分页查询施工单位列表
- def test_... | 024bb8f0e8be7d19abfb14b405ef79bd85cc6b7b | <|skeleton|>
class TestGovernConstruction:
def test_001_add_construction_business(self):
"""【政府端--适老化】：添加施工单位"""
<|body_0|>
def test_002_get_construction_business_list(self):
"""【政府端--适老化】：分页查询施工单位列表"""
<|body_1|>
def test_003_edit_construction_business(self):
"""【... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestGovernConstruction:
def test_001_add_construction_business(self):
"""【政府端--适老化】：添加施工单位"""
param = {'account': self.phone, 'address': '办公地址', 'annexList': [{'name': '1', 'url': '1.txt'}, {'name': '2', 'url': '2.png'}], 'businessLicense': random.randint(1000000, 9999999), 'certificateList': ... | the_stack_v2_python_sparse | test_case/test_house/test_govern_construction.py | cjuan123/auto_api | train | 0 | |
749fb019c39d3c8c3c474528a1eb7f585e7109af | [
"self.session = session\nself.tornado_cassandra = TornadoCassandra(self.session)\nself.project = project\nself.txid = txid\nself.op_id = uuid.uuid4()\nself.read_op_id = None\nself.applied = False",
"if self.applied:\n raise gen.Return(True)\nget_status = '\\n SELECT applied, op_id FROM batch_status\\n ... | <|body_start_0|>
self.session = session
self.tornado_cassandra = TornadoCassandra(self.session)
self.project = project
self.txid = txid
self.op_id = uuid.uuid4()
self.read_op_id = None
self.applied = False
<|end_body_0|>
<|body_start_1|>
if self.applied:
... | LargeBatch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LargeBatch:
def __init__(self, session, project, txid):
"""Create a new LargeBatch object. Args: session: A cassandra-driver session. project: A string specifying a project ID. txid: An integer specifying a transaction ID."""
<|body_0|>
def is_applied(self, retries=5):
... | stack_v2_sparse_classes_36k_train_006724 | 13,309 | permissive | [
{
"docstring": "Create a new LargeBatch object. Args: session: A cassandra-driver session. project: A string specifying a project ID. txid: An integer specifying a transaction ID.",
"name": "__init__",
"signature": "def __init__(self, session, project, txid)"
},
{
"docstring": "Fetch the status ... | 5 | null | Implement the Python class `LargeBatch` described below.
Class description:
Implement the LargeBatch class.
Method signatures and docstrings:
- def __init__(self, session, project, txid): Create a new LargeBatch object. Args: session: A cassandra-driver session. project: A string specifying a project ID. txid: An int... | Implement the Python class `LargeBatch` described below.
Class description:
Implement the LargeBatch class.
Method signatures and docstrings:
- def __init__(self, session, project, txid): Create a new LargeBatch object. Args: session: A cassandra-driver session. project: A string specifying a project ID. txid: An int... | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | <|skeleton|>
class LargeBatch:
def __init__(self, session, project, txid):
"""Create a new LargeBatch object. Args: session: A cassandra-driver session. project: A string specifying a project ID. txid: An integer specifying a transaction ID."""
<|body_0|>
def is_applied(self, retries=5):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LargeBatch:
def __init__(self, session, project, txid):
"""Create a new LargeBatch object. Args: session: A cassandra-driver session. project: A string specifying a project ID. txid: An integer specifying a transaction ID."""
self.session = session
self.tornado_cassandra = TornadoCassa... | the_stack_v2_python_sparse | AppDB/appscale/datastore/cassandra_env/large_batch.py | obino/appscale | train | 1 | |
bb8d606dd6fab92e7a643bd2ffe8a380187e108f | [
"super(AdaptiveSoftmaxEmbedding, self).__init__(name=name)\nself._hidden_size = dim\nself._vocab_size = vocab_size\nself._cutoffs = [0] + list(cutoffs) + [self._vocab_size]\nself._tail_shrink_factor = tail_shrink_factor\nself._hierarchical = hierarchical\nself._dtype = dtype\nself._embeddings = []\nself._projection... | <|body_start_0|>
super(AdaptiveSoftmaxEmbedding, self).__init__(name=name)
self._hidden_size = dim
self._vocab_size = vocab_size
self._cutoffs = [0] + list(cutoffs) + [self._vocab_size]
self._tail_shrink_factor = tail_shrink_factor
self._hierarchical = hierarchical
... | Adaptive inputs and softmax (https://arxiv.org/abs/1809.10853). | AdaptiveSoftmaxEmbedding | [
"Apache-2.0",
"CC-BY-SA-4.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaptiveSoftmaxEmbedding:
"""Adaptive inputs and softmax (https://arxiv.org/abs/1809.10853)."""
def __init__(self, dim: int, vocab_size: int, cutoffs: List[int], tail_shrink_factor: int=4, hierarchical: bool=True, init_std: float=0.02, init_proj_std: float=0.01, dtype: jnp.dtype=jnp.float32,... | stack_v2_sparse_classes_36k_train_006725 | 14,391 | permissive | [
{
"docstring": "Initialize a AdaptiveSoftmaxEmbedding. Args: dim: dimensionality of the hidden space. vocab_size: the size of the vocabulary. cutoffs: the cutoff indices of the vocabulary used for the adaptive softmax embedding. tail_shrink_factor: how many times to shrink the hidden dimensionality for low-freq... | 5 | null | Implement the Python class `AdaptiveSoftmaxEmbedding` described below.
Class description:
Adaptive inputs and softmax (https://arxiv.org/abs/1809.10853).
Method signatures and docstrings:
- def __init__(self, dim: int, vocab_size: int, cutoffs: List[int], tail_shrink_factor: int=4, hierarchical: bool=True, init_std: ... | Implement the Python class `AdaptiveSoftmaxEmbedding` described below.
Class description:
Adaptive inputs and softmax (https://arxiv.org/abs/1809.10853).
Method signatures and docstrings:
- def __init__(self, dim: int, vocab_size: int, cutoffs: List[int], tail_shrink_factor: int=4, hierarchical: bool=True, init_std: ... | a6ef8053380d6aa19aaae14b93f013ae9762d057 | <|skeleton|>
class AdaptiveSoftmaxEmbedding:
"""Adaptive inputs and softmax (https://arxiv.org/abs/1809.10853)."""
def __init__(self, dim: int, vocab_size: int, cutoffs: List[int], tail_shrink_factor: int=4, hierarchical: bool=True, init_std: float=0.02, init_proj_std: float=0.01, dtype: jnp.dtype=jnp.float32,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdaptiveSoftmaxEmbedding:
"""Adaptive inputs and softmax (https://arxiv.org/abs/1809.10853)."""
def __init__(self, dim: int, vocab_size: int, cutoffs: List[int], tail_shrink_factor: int=4, hierarchical: bool=True, init_std: float=0.02, init_proj_std: float=0.01, dtype: jnp.dtype=jnp.float32, name: Option... | the_stack_v2_python_sparse | wikigraphs/wikigraphs/model/embedding.py | sethuramanio/deepmind-research | train | 1 |
230e85628c62cd1b6f2bbad827fab61227c72304 | [
"args = self.get_args.parse_args()\nnum_rows = args.get('rows') or 100\nquery = g.db.query(MachineGroup)\nif args['name']:\n query = query.filter(MachineGroup.name == args['name'])\nquery = query.order_by(-MachineGroup.machinegroup_id)\nquery = query.limit(num_rows)\nrows = query.all()\nret = []\nfor row in rows... | <|body_start_0|>
args = self.get_args.parse_args()
num_rows = args.get('rows') or 100
query = g.db.query(MachineGroup)
if args['name']:
query = query.filter(MachineGroup.name == args['name'])
query = query.order_by(-MachineGroup.machinegroup_id)
query = query.... | MachineGroupsAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachineGroupsAPI:
def get(self):
"""Get a list of machine groups"""
<|body_0|>
def post(self):
"""Create machine group"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = self.get_args.parse_args()
num_rows = args.get('rows') or 100
... | stack_v2_sparse_classes_36k_train_006726 | 4,880 | permissive | [
{
"docstring": "Get a list of machine groups",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create machine group",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `MachineGroupsAPI` described below.
Class description:
Implement the MachineGroupsAPI class.
Method signatures and docstrings:
- def get(self): Get a list of machine groups
- def post(self): Create machine group | Implement the Python class `MachineGroupsAPI` described below.
Class description:
Implement the MachineGroupsAPI class.
Method signatures and docstrings:
- def get(self): Get a list of machine groups
- def post(self): Create machine group
<|skeleton|>
class MachineGroupsAPI:
def get(self):
"""Get a list... | 9825cb22b26b577b715f2ce95453363bf90ecc7e | <|skeleton|>
class MachineGroupsAPI:
def get(self):
"""Get a list of machine groups"""
<|body_0|>
def post(self):
"""Create machine group"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MachineGroupsAPI:
def get(self):
"""Get a list of machine groups"""
args = self.get_args.parse_args()
num_rows = args.get('rows') or 100
query = g.db.query(MachineGroup)
if args['name']:
query = query.filter(MachineGroup.name == args['name'])
query =... | the_stack_v2_python_sparse | driftbase/api/machinegroups.py | dgnorth/drift-base | train | 1 | |
10ce31fab78c771bafd534c5ccd69276ac026eb1 | [
"contribution = self.get_contribution(request.user, project_id, contribution_id)\nfile = self.get_file(contribution, file_id)\nreturn self.get_single_and_respond(request, file)",
"contribution = self.get_contribution(request.user, project_id, contribution_id)\nfile = self.get_file(contribution, file_id)\nreturn s... | <|body_start_0|>
contribution = self.get_contribution(request.user, project_id, contribution_id)
file = self.get_file(contribution, file_id)
return self.get_single_and_respond(request, file)
<|end_body_0|>
<|body_start_1|>
contribution = self.get_contribution(request.user, project_id, c... | Public API for a single media. | SingleMediaAPIView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleMediaAPIView:
"""Public API for a single media."""
def get(self, request, project_id, contribution_id, file_id):
"""Handle GET request. Return a single media file. Parameters ---------- request : rest_framework.request.Request Object representing the request. project_id : int I... | stack_v2_sparse_classes_36k_train_006727 | 9,811 | permissive | [
{
"docstring": "Handle GET request. Return a single media file. Parameters ---------- request : rest_framework.request.Request Object representing the request. project_id : int Identifies the project in the database. contribution_id : int Identifies the contribution in the database. file_id : int Identifies the... | 2 | null | Implement the Python class `SingleMediaAPIView` described below.
Class description:
Public API for a single media.
Method signatures and docstrings:
- def get(self, request, project_id, contribution_id, file_id): Handle GET request. Return a single media file. Parameters ---------- request : rest_framework.request.Re... | Implement the Python class `SingleMediaAPIView` described below.
Class description:
Public API for a single media.
Method signatures and docstrings:
- def get(self, request, project_id, contribution_id, file_id): Handle GET request. Return a single media file. Parameters ---------- request : rest_framework.request.Re... | 16d31b5207de9f699fc01054baad1fe65ad1c3ca | <|skeleton|>
class SingleMediaAPIView:
"""Public API for a single media."""
def get(self, request, project_id, contribution_id, file_id):
"""Handle GET request. Return a single media file. Parameters ---------- request : rest_framework.request.Request Object representing the request. project_id : int I... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SingleMediaAPIView:
"""Public API for a single media."""
def get(self, request, project_id, contribution_id, file_id):
"""Handle GET request. Return a single media file. Parameters ---------- request : rest_framework.request.Request Object representing the request. project_id : int Identifies the... | the_stack_v2_python_sparse | geokey/contributions/views/media.py | NeolithEra/geokey | train | 0 |
65b9d7822e4a288223cd61732077935de9c06c02 | [
"widget = widget\nsummary = get_widget_r(self, 'summary')\nif self.mode == 'svg':\n summary.set_text(_('Image « <b><u>%s</u></b> »\\nstored in <b>%s</b> ') % (self.book.get_page('svg_name').get_imagename(), self.book.get_page('svg_kind').get_target()))\nsummary.set_justify(gtk.JUSTIFY_CENTER)\nsummary.set_use_ma... | <|body_start_0|>
widget = widget
summary = get_widget_r(self, 'summary')
if self.mode == 'svg':
summary.set_text(_('Image « <b><u>%s</u></b> »\nstored in <b>%s</b> ') % (self.book.get_page('svg_name').get_imagename(), self.book.get_page('svg_kind').get_target()))
summary.set_... | Page used to display a summary of what will be done | PageSummary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PageSummary:
"""Page used to display a summary of what will be done"""
def _cb_show(self, widget=None, data=None):
"""refresh summary when shown"""
<|body_0|>
def launch_backup(self, widget=None, data=None):
"""called when the user starts a backup"""
<|bo... | stack_v2_sparse_classes_36k_train_006728 | 41,782 | no_license | [
{
"docstring": "refresh summary when shown",
"name": "_cb_show",
"signature": "def _cb_show(self, widget=None, data=None)"
},
{
"docstring": "called when the user starts a backup",
"name": "launch_backup",
"signature": "def launch_backup(self, widget=None, data=None)"
},
{
"docst... | 4 | stack_v2_sparse_classes_30k_train_011797 | Implement the Python class `PageSummary` described below.
Class description:
Page used to display a summary of what will be done
Method signatures and docstrings:
- def _cb_show(self, widget=None, data=None): refresh summary when shown
- def launch_backup(self, widget=None, data=None): called when the user starts a b... | Implement the Python class `PageSummary` described below.
Class description:
Page used to display a summary of what will be done
Method signatures and docstrings:
- def _cb_show(self, widget=None, data=None): refresh summary when shown
- def launch_backup(self, widget=None, data=None): called when the user starts a b... | 53c26e3c03c5054fb9d5730cf98716442a07464a | <|skeleton|>
class PageSummary:
"""Page used to display a summary of what will be done"""
def _cb_show(self, widget=None, data=None):
"""refresh summary when shown"""
<|body_0|>
def launch_backup(self, widget=None, data=None):
"""called when the user starts a backup"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PageSummary:
"""Page used to display a summary of what will be done"""
def _cb_show(self, widget=None, data=None):
"""refresh summary when shown"""
widget = widget
summary = get_widget_r(self, 'summary')
if self.mode == 'svg':
summary.set_text(_('Image « <b><u>... | the_stack_v2_python_sparse | beam_pages.py | mandriva-management-console/beam | train | 0 |
adbf410bd5c87415c82ffabead0805a0846f1089 | [
"d = set()\nfor i in nums:\n if i in d:\n return True\n else:\n d.add(i)\nreturn False",
"if len(nums) == 0:\n return False\nnums.sort()\nfor i in range(0, len(nums) - 1):\n if nums[i] == nums[i + 1]:\n return True\nreturn False"
] | <|body_start_0|>
d = set()
for i in nums:
if i in d:
return True
else:
d.add(i)
return False
<|end_body_0|>
<|body_start_1|>
if len(nums) == 0:
return False
nums.sort()
for i in range(0, len(nums) - 1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def containsDuplicate(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def containsDuplicate2(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
d = set()
for i in num... | stack_v2_sparse_classes_36k_train_006729 | 1,137 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "containsDuplicate",
"signature": "def containsDuplicate(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "containsDuplicate2",
"signature": "def containsDuplicate2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016970 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsDuplicate(self, nums): :type nums: List[int] :rtype: bool
- def containsDuplicate2(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsDuplicate(self, nums): :type nums: List[int] :rtype: bool
- def containsDuplicate2(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
... | 813235789ce422a3bab198317aafc46fbc61625e | <|skeleton|>
class Solution:
def containsDuplicate(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def containsDuplicate2(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def containsDuplicate(self, nums):
""":type nums: List[int] :rtype: bool"""
d = set()
for i in nums:
if i in d:
return True
else:
d.add(i)
return False
def containsDuplicate2(self, nums):
""":type nu... | the_stack_v2_python_sparse | 2.SET/e217_contains_duplicate/solution.py | kimmyoo/python_leetcode | train | 1 | |
a7671d493884bd184cdb4d8959f22f244fe2d152 | [
"bracket_map = {'(': ')', '{': '}', '[': ']'}\nstack = []\nfor c in s:\n if c in bracket_map:\n stack.append(bracket_map[c])\n elif c in bracket_map.values():\n if stack:\n test = stack.pop()\n if test != c:\n return False\n else:\n return F... | <|body_start_0|>
bracket_map = {'(': ')', '{': '}', '[': ']'}
stack = []
for c in s:
if c in bracket_map:
stack.append(bracket_map[c])
elif c in bracket_map.values():
if stack:
test = stack.pop()
if t... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValid1(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
bracket_map = {'(': ')', '{': '}', '[': ']'}
stack = []
fo... | stack_v2_sparse_classes_36k_train_006730 | 1,061 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isValid1",
"signature": "def isValid1(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "isValid",
"signature": "def isValid(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid1(self, s): :type s: str :rtype: bool
- def isValid(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid1(self, s): :type s: str :rtype: bool
- def isValid(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def isValid1(self, s):
""":type s: s... | 4a1747b6497305f3821612d9c358a6795b1690da | <|skeleton|>
class Solution:
def isValid1(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValid1(self, s):
""":type s: str :rtype: bool"""
bracket_map = {'(': ')', '{': '}', '[': ']'}
stack = []
for c in s:
if c in bracket_map:
stack.append(bracket_map[c])
elif c in bracket_map.values():
if stac... | the_stack_v2_python_sparse | Stack/q020_valid_parenthese.py | sevenhe716/LeetCode | train | 0 | |
65d1da10ab57a2cac7ac1ca0f94dbdd9c31e3e9b | [
"resource_args.AddCopyBackupResourceArgs(parser)\ngroup_parser = parser.add_argument_group(mutex=True, required=True)\ngroup_parser.add_argument('--expiration-date', help='Expiration time of the backup, must be at least 6 hours and at most 366 days from the time when the source backup is created. See `$ gcloud topi... | <|body_start_0|>
resource_args.AddCopyBackupResourceArgs(parser)
group_parser = parser.add_argument_group(mutex=True, required=True)
group_parser.add_argument('--expiration-date', help='Expiration time of the backup, must be at least 6 hours and at most 366 days from the time when the source bac... | Copies a backup of a Cloud Spanner database. | Copy | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Copy:
"""Copies a backup of a Cloud Spanner database."""
def Args(parser):
"""Register flags for this command."""
<|body_0|>
def Run(self, args):
"""This is what gets called when the user runs this command."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_006731 | 3,919 | permissive | [
{
"docstring": "Register flags for this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "This is what gets called when the user runs this command.",
"name": "Run",
"signature": "def Run(self, args)"
}
] | 2 | null | Implement the Python class `Copy` described below.
Class description:
Copies a backup of a Cloud Spanner database.
Method signatures and docstrings:
- def Args(parser): Register flags for this command.
- def Run(self, args): This is what gets called when the user runs this command. | Implement the Python class `Copy` described below.
Class description:
Copies a backup of a Cloud Spanner database.
Method signatures and docstrings:
- def Args(parser): Register flags for this command.
- def Run(self, args): This is what gets called when the user runs this command.
<|skeleton|>
class Copy:
"""Co... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class Copy:
"""Copies a backup of a Cloud Spanner database."""
def Args(parser):
"""Register flags for this command."""
<|body_0|>
def Run(self, args):
"""This is what gets called when the user runs this command."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Copy:
"""Copies a backup of a Cloud Spanner database."""
def Args(parser):
"""Register flags for this command."""
resource_args.AddCopyBackupResourceArgs(parser)
group_parser = parser.add_argument_group(mutex=True, required=True)
group_parser.add_argument('--expiration-dat... | the_stack_v2_python_sparse | lib/surface/spanner/backups/copy.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
dfb3cb00901145667477975d43c55445d752eda1 | [
"behavior.Behavior.__init__(self, nodename, ctrlrID)\nself._uses_wp_control = True\nself._last_wp_id = 0\nself.wp_msg = LLA()\nself._wpPublisher = rospy.Publisher('autopilot/payload_waypoint', LLA, tcp_nodelay=True, latch=True, queue_size=1)",
"if wp.alt >= enums.MIN_REL_ALT and wp.alt <= enums.MAX_REL_ALT and (a... | <|body_start_0|>
behavior.Behavior.__init__(self, nodename, ctrlrID)
self._uses_wp_control = True
self._last_wp_id = 0
self.wp_msg = LLA()
self._wpPublisher = rospy.Publisher('autopilot/payload_waypoint', LLA, tcp_nodelay=True, latch=True, queue_size=1)
<|end_body_0|>
<|body_sta... | Abstract class for wrapping a control-order-issuing ACS ROS object Control is implemented through the generation of waypoint commands. Instantiated objects will provide a waypoint publisher that publishes computed waypoints to the appropriate topic. Class member variables: _wpPublisher: publisher object for publishing ... | WaypointBehavior | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WaypointBehavior:
"""Abstract class for wrapping a control-order-issuing ACS ROS object Control is implemented through the generation of waypoint commands. Instantiated objects will provide a waypoint publisher that publishes computed waypoints to the appropriate topic. Class member variables: _w... | stack_v2_sparse_classes_36k_train_006732 | 4,100 | no_license | [
{
"docstring": "Class initializer sets up the publisher for the waypoint topic @param nodename: name of the node that the object is contained in @param ctrlrID: identifier (int) for this particular behavior",
"name": "__init__",
"signature": "def __init__(self, nodename, ctrlrID)"
},
{
"docstrin... | 2 | stack_v2_sparse_classes_30k_val_000420 | Implement the Python class `WaypointBehavior` described below.
Class description:
Abstract class for wrapping a control-order-issuing ACS ROS object Control is implemented through the generation of waypoint commands. Instantiated objects will provide a waypoint publisher that publishes computed waypoints to the approp... | Implement the Python class `WaypointBehavior` described below.
Class description:
Abstract class for wrapping a control-order-issuing ACS ROS object Control is implemented through the generation of waypoint commands. Instantiated objects will provide a waypoint publisher that publishes computed waypoints to the approp... | ec2b5c43abed51a37c17bde0c000c2dfbfcbb9b1 | <|skeleton|>
class WaypointBehavior:
"""Abstract class for wrapping a control-order-issuing ACS ROS object Control is implemented through the generation of waypoint commands. Instantiated objects will provide a waypoint publisher that publishes computed waypoints to the appropriate topic. Class member variables: _w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WaypointBehavior:
"""Abstract class for wrapping a control-order-issuing ACS ROS object Control is implemented through the generation of waypoint commands. Instantiated objects will provide a waypoint publisher that publishes computed waypoints to the appropriate topic. Class member variables: _wpPublisher: p... | the_stack_v2_python_sparse | ap_lib/src/ap_lib/waypoint_behavior.py | jaymonty/autonomy-payload | train | 0 |
b4cc6bcb27a43d153bc09ea98392be10defb41b1 | [
"cluster = self.get_object_or_404(objects.Cluster, cluster_id)\nself.check_net_provider(cluster)\nreturn self.serializer.serialize_for_cluster(cluster)",
"data = jsonutils.loads(web.data())\nif data.get('networks'):\n data['networks'] = [n for n in data['networks'] if n.get('name') != 'fuelweb_admin']\ncluster... | <|body_start_0|>
cluster = self.get_object_or_404(objects.Cluster, cluster_id)
self.check_net_provider(cluster)
return self.serializer.serialize_for_cluster(cluster)
<|end_body_0|>
<|body_start_1|>
data = jsonutils.loads(web.data())
if data.get('networks'):
data['net... | Network configuration handler | NovaNetworkConfigurationHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NovaNetworkConfigurationHandler:
"""Network configuration handler"""
def GET(self, cluster_id):
""":returns: JSONized network configuration for cluster. :http: * 200 (OK) * 404 (cluster not found in db)"""
<|body_0|>
def PUT(self, cluster_id):
""":returns: JSONiz... | stack_v2_sparse_classes_36k_train_006733 | 8,763 | permissive | [
{
"docstring": ":returns: JSONized network configuration for cluster. :http: * 200 (OK) * 404 (cluster not found in db)",
"name": "GET",
"signature": "def GET(self, cluster_id)"
},
{
"docstring": ":returns: JSONized Task object. :http: * 200 (task successfully executed) * 202 (network checking t... | 2 | null | Implement the Python class `NovaNetworkConfigurationHandler` described below.
Class description:
Network configuration handler
Method signatures and docstrings:
- def GET(self, cluster_id): :returns: JSONized network configuration for cluster. :http: * 200 (OK) * 404 (cluster not found in db)
- def PUT(self, cluster_... | Implement the Python class `NovaNetworkConfigurationHandler` described below.
Class description:
Network configuration handler
Method signatures and docstrings:
- def GET(self, cluster_id): :returns: JSONized network configuration for cluster. :http: * 200 (OK) * 404 (cluster not found in db)
- def PUT(self, cluster_... | 976baf842242a5f97c95bdc3e20328fa0558bf69 | <|skeleton|>
class NovaNetworkConfigurationHandler:
"""Network configuration handler"""
def GET(self, cluster_id):
""":returns: JSONized network configuration for cluster. :http: * 200 (OK) * 404 (cluster not found in db)"""
<|body_0|>
def PUT(self, cluster_id):
""":returns: JSONiz... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NovaNetworkConfigurationHandler:
"""Network configuration handler"""
def GET(self, cluster_id):
""":returns: JSONized network configuration for cluster. :http: * 200 (OK) * 404 (cluster not found in db)"""
cluster = self.get_object_or_404(objects.Cluster, cluster_id)
self.check_ne... | the_stack_v2_python_sparse | nailgun/nailgun/api/v1/handlers/network_configuration.py | nebril/fuel-web | train | 1 |
e2bfccc5e25a7ea591fb31c4019eb4a45a244a94 | [
"xff = request.META.get('HTTP_X_FORWARDED_FOR')\nremote_addr = request.META.get('REMOTE_ADDR')\nnum_proxies = api_settings.NUM_PROXIES\nif num_proxies is not None:\n if num_proxies == 0 or xff is None:\n return remote_addr\n addrs = xff.split(',')\n client_addr = addrs[-min(num_proxies, len(addrs))]... | <|body_start_0|>
xff = request.META.get('HTTP_X_FORWARDED_FOR')
remote_addr = request.META.get('REMOTE_ADDR')
num_proxies = api_settings.NUM_PROXIES
if num_proxies is not None:
if num_proxies == 0 or xff is None:
return remote_addr
addrs = xff.spli... | TestThrottle | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestThrottle:
def get_ident(self, request):
"""根据用户IP和代理IP，当做请求者的唯一IP Identify the machine making the request by parsing HTTP_X_FORWARDED_FOR if present and number of proxies is > 0. If not use all of HTTP_X_FORWARDED_FOR if it is available, if not use REMOTE_ADDR."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_006734 | 3,502 | permissive | [
{
"docstring": "根据用户IP和代理IP，当做请求者的唯一IP Identify the machine making the request by parsing HTTP_X_FORWARDED_FOR if present and number of proxies is > 0. If not use all of HTTP_X_FORWARDED_FOR if it is available, if not use REMOTE_ADDR.",
"name": "get_ident",
"signature": "def get_ident(self, request)"
... | 3 | stack_v2_sparse_classes_30k_train_018407 | Implement the Python class `TestThrottle` described below.
Class description:
Implement the TestThrottle class.
Method signatures and docstrings:
- def get_ident(self, request): 根据用户IP和代理IP，当做请求者的唯一IP Identify the machine making the request by parsing HTTP_X_FORWARDED_FOR if present and number of proxies is > 0. If n... | Implement the Python class `TestThrottle` described below.
Class description:
Implement the TestThrottle class.
Method signatures and docstrings:
- def get_ident(self, request): 根据用户IP和代理IP，当做请求者的唯一IP Identify the machine making the request by parsing HTTP_X_FORWARDED_FOR if present and number of proxies is > 0. If n... | 58d7060ce255092c3ec9908dfa1810bd7a665365 | <|skeleton|>
class TestThrottle:
def get_ident(self, request):
"""根据用户IP和代理IP，当做请求者的唯一IP Identify the machine making the request by parsing HTTP_X_FORWARDED_FOR if present and number of proxies is > 0. If not use all of HTTP_X_FORWARDED_FOR if it is available, if not use REMOTE_ADDR."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestThrottle:
def get_ident(self, request):
"""根据用户IP和代理IP，当做请求者的唯一IP Identify the machine making the request by parsing HTTP_X_FORWARDED_FOR if present and number of proxies is > 0. If not use all of HTTP_X_FORWARDED_FOR if it is available, if not use REMOTE_ADDR."""
xff = request.META.get('H... | the_stack_v2_python_sparse | day08/views.py | jiawenquan/django_restful_demo | train | 0 | |
ac37e5b443e7c473a0176322bc7df017a0c61f54 | [
"attr_map = {'node_uuid': 'uuid', 'bfd_admin_down_count': 'admin_down_count', 'bfd_init_count': 'init_count', 'bfd_up_count': 'up_count', 'bfd_down_count': 'down_count'}\nclient_class_obj = listtransportnodestatus.ListTransportNodeStatus(connection_object=client_obj.connection)\nstatus_schema_object = client_class_... | <|body_start_0|>
attr_map = {'node_uuid': 'uuid', 'bfd_admin_down_count': 'admin_down_count', 'bfd_init_count': 'init_count', 'bfd_up_count': 'up_count', 'bfd_down_count': 'down_count'}
client_class_obj = listtransportnodestatus.ListTransportNodeStatus(connection_object=client_obj.connection)
st... | NSX70AggregationImpl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NSX70AggregationImpl:
def get_aggregation_transportnode_status(cls, client_obj, **kwargs):
"""Get status summary of all transport nodes under MP. @type client_object: ManagerAPIClient @param client_object: Client object @rtype: dict @return: Dict having status details of all TNs. Endpoin... | stack_v2_sparse_classes_36k_train_006735 | 4,454 | no_license | [
{
"docstring": "Get status summary of all transport nodes under MP. @type client_object: ManagerAPIClient @param client_object: Client object @rtype: dict @return: Dict having status details of all TNs. Endpoint: /aggregations/transport-node-status",
"name": "get_aggregation_transportnode_status",
"sign... | 3 | stack_v2_sparse_classes_30k_train_018908 | Implement the Python class `NSX70AggregationImpl` described below.
Class description:
Implement the NSX70AggregationImpl class.
Method signatures and docstrings:
- def get_aggregation_transportnode_status(cls, client_obj, **kwargs): Get status summary of all transport nodes under MP. @type client_object: ManagerAPICl... | Implement the Python class `NSX70AggregationImpl` described below.
Class description:
Implement the NSX70AggregationImpl class.
Method signatures and docstrings:
- def get_aggregation_transportnode_status(cls, client_obj, **kwargs): Get status summary of all transport nodes under MP. @type client_object: ManagerAPICl... | 5b55817c050b637e2747084290f6206d2e622938 | <|skeleton|>
class NSX70AggregationImpl:
def get_aggregation_transportnode_status(cls, client_obj, **kwargs):
"""Get status summary of all transport nodes under MP. @type client_object: ManagerAPIClient @param client_object: Client object @rtype: dict @return: Dict having status details of all TNs. Endpoin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NSX70AggregationImpl:
def get_aggregation_transportnode_status(cls, client_obj, **kwargs):
"""Get status summary of all transport nodes under MP. @type client_object: ManagerAPIClient @param client_object: Client object @rtype: dict @return: Dict having status details of all TNs. Endpoint: /aggregatio... | the_stack_v2_python_sparse | SystemTesting/pylib/vmware/nsx/manager/api/nsx70_aggregation_impl.py | Cloudxtreme/MyProject | train | 0 | |
96906b7e79f9a7476ce3c1c31d06ae5bf3c7c8df | [
"self.val = None\nself.next = None\nself.prev = None\nself.head = None\nself.tail = None",
"walker = self.head\nfor i in range(index):\n if walker == None:\n break\n walker = walker.next\nif walker != None:\n return walker.val\nreturn -1",
"newNode = MyLinkedList()\nnewNode.val = val\nif self.he... | <|body_start_0|>
self.val = None
self.next = None
self.prev = None
self.head = None
self.tail = None
<|end_body_0|>
<|body_start_1|>
walker = self.head
for i in range(index):
if walker == None:
break
walker = walker.next
... | MyLinkedList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index):
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1. :type index: int :rtype: int"""
<|body_1|>
def add... | stack_v2_sparse_classes_36k_train_006736 | 6,076 | permissive | [
{
"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. :type index: int :rtype: int",
"name": "get",
"signature": "def get(s... | 6 | stack_v2_sparse_classes_30k_train_001027 | 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): Get the value of the index-th node in the linked list. If the index is invalid, return -1... | 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): Get the value of the index-th node in the linked list. If the index is invalid, return -1... | d137df53fa2489821b3c17ac22f24d9a1ae86304 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index):
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1. :type index: int :rtype: int"""
<|body_1|>
def add... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
self.val = None
self.next = None
self.prev = None
self.head = None
self.tail = None
def get(self, index):
"""Get the value of the index-th node in the linked list. If the i... | the_stack_v2_python_sparse | easy/design-linked-list.py | trilliwon/LeetCode | train | 0 | |
7c73a735ebdbb9b2aef63f29ac9a3cf74eb5aec8 | [
"X = df[col]\ny = df[target_col]\nestimator = SVR(kernel='linear')\nselector = RFE(estimator, n_features_to_select=len(col), step=1)\nselector = selector.fit(X, y)\ndf = pd.DataFrame(selector.transform(X), columns=col)\ndf[target_col] = y\nreturn df",
"X = df[col]\ny = df[target_col]\nestimator = SVR(kernel='line... | <|body_start_0|>
X = df[col]
y = df[target_col]
estimator = SVR(kernel='linear')
selector = RFE(estimator, n_features_to_select=len(col), step=1)
selector = selector.fit(X, y)
df = pd.DataFrame(selector.transform(X), columns=col)
df[target_col] = y
return ... | SelectFeatures | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectFeatures:
def rfe(df, col, target_col):
"""递归特征消除的目标（RFE） 针对那些特征含有权重的预测模型，RFE通过递归的方式， 不断减少特征集的规模来选择需要的特征。"""
<|body_0|>
def rfecv(df, col, target_col):
"""带交叉验证带递归特征消除的目标（RFE）"""
<|body_1|>
def select_fdr(df, target_col):
"""FDR错误发现率-P值校正学习... | stack_v2_sparse_classes_36k_train_006737 | 41,790 | no_license | [
{
"docstring": "递归特征消除的目标（RFE） 针对那些特征含有权重的预测模型，RFE通过递归的方式， 不断减少特征集的规模来选择需要的特征。",
"name": "rfe",
"signature": "def rfe(df, col, target_col)"
},
{
"docstring": "带交叉验证带递归特征消除的目标（RFE）",
"name": "rfecv",
"signature": "def rfecv(df, col, target_col)"
},
{
"docstring": "FDR错误发现率-P值校正学习 ... | 5 | stack_v2_sparse_classes_30k_train_014800 | Implement the Python class `SelectFeatures` described below.
Class description:
Implement the SelectFeatures class.
Method signatures and docstrings:
- def rfe(df, col, target_col): 递归特征消除的目标（RFE） 针对那些特征含有权重的预测模型，RFE通过递归的方式， 不断减少特征集的规模来选择需要的特征。
- def rfecv(df, col, target_col): 带交叉验证带递归特征消除的目标（RFE）
- def select_fdr(d... | Implement the Python class `SelectFeatures` described below.
Class description:
Implement the SelectFeatures class.
Method signatures and docstrings:
- def rfe(df, col, target_col): 递归特征消除的目标（RFE） 针对那些特征含有权重的预测模型，RFE通过递归的方式， 不断减少特征集的规模来选择需要的特征。
- def rfecv(df, col, target_col): 带交叉验证带递归特征消除的目标（RFE）
- def select_fdr(d... | 12f7ac9c7d9ba0f32a5feb35777760e929af900a | <|skeleton|>
class SelectFeatures:
def rfe(df, col, target_col):
"""递归特征消除的目标（RFE） 针对那些特征含有权重的预测模型，RFE通过递归的方式， 不断减少特征集的规模来选择需要的特征。"""
<|body_0|>
def rfecv(df, col, target_col):
"""带交叉验证带递归特征消除的目标（RFE）"""
<|body_1|>
def select_fdr(df, target_col):
"""FDR错误发现率-P值校正学习... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelectFeatures:
def rfe(df, col, target_col):
"""递归特征消除的目标（RFE） 针对那些特征含有权重的预测模型，RFE通过递归的方式， 不断减少特征集的规模来选择需要的特征。"""
X = df[col]
y = df[target_col]
estimator = SVR(kernel='linear')
selector = RFE(estimator, n_features_to_select=len(col), step=1)
selector = selecto... | the_stack_v2_python_sparse | Tools/FeatureEngineering/FeatureEnginering.py | nexusme/data_process_tools | train | 2 | |
3cb877ac1c346cf7ad85b1103d2c75f7af15cbb1 | [
"updateConstant('general__discountsEnabled', True)\ntest_combo, test_component = self.create_discount(active=False)\ns = self.create_series(pricingTier=self.defaultPricing)\nresponse = self.register_to_check_discount(s, s.getBasePrice())\ninvoice = response.context_data.get('invoice')\nself.assertEqual(response.red... | <|body_start_0|>
updateConstant('general__discountsEnabled', True)
test_combo, test_component = self.create_discount(active=False)
s = self.create_series(pricingTier=self.defaultPricing)
response = self.register_to_check_discount(s, s.getBasePrice())
invoice = response.context_da... | DiscountsConditionsTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiscountsConditionsTest:
def test_inactive_discount(self):
"""Make a discount inactive and make sure that it doesn't work"""
<|body_0|>
def test_expired_discount(self):
"""Create an expired discount and make sure that it doesn't work."""
<|body_1|>
def t... | stack_v2_sparse_classes_36k_train_006738 | 20,249 | permissive | [
{
"docstring": "Make a discount inactive and make sure that it doesn't work",
"name": "test_inactive_discount",
"signature": "def test_inactive_discount(self)"
},
{
"docstring": "Create an expired discount and make sure that it doesn't work.",
"name": "test_expired_discount",
"signature"... | 5 | null | Implement the Python class `DiscountsConditionsTest` described below.
Class description:
Implement the DiscountsConditionsTest class.
Method signatures and docstrings:
- def test_inactive_discount(self): Make a discount inactive and make sure that it doesn't work
- def test_expired_discount(self): Create an expired d... | Implement the Python class `DiscountsConditionsTest` described below.
Class description:
Implement the DiscountsConditionsTest class.
Method signatures and docstrings:
- def test_inactive_discount(self): Make a discount inactive and make sure that it doesn't work
- def test_expired_discount(self): Create an expired d... | 19db3e83e76ea2002ee841989410d12d1e601023 | <|skeleton|>
class DiscountsConditionsTest:
def test_inactive_discount(self):
"""Make a discount inactive and make sure that it doesn't work"""
<|body_0|>
def test_expired_discount(self):
"""Create an expired discount and make sure that it doesn't work."""
<|body_1|>
def t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiscountsConditionsTest:
def test_inactive_discount(self):
"""Make a discount inactive and make sure that it doesn't work"""
updateConstant('general__discountsEnabled', True)
test_combo, test_component = self.create_discount(active=False)
s = self.create_series(pricingTier=self... | the_stack_v2_python_sparse | danceschool/discounts/tests.py | django-danceschool/django-danceschool | train | 40 | |
b84e3cb91074d6b171e31e95bd1f8dbf7cc7d14a | [
"low, high = (0, len(nums) - 1)\nwhile low <= high:\n mid = low + (high - low) // 2\n if nums[mid] == target:\n return mid\n elif nums[mid] > target:\n high = mid - 1\n else:\n low = mid + 1\nreturn len(nums)",
"low, high = (0, len(nums) - 1)\nwhile low <= high:\n mid = low + (... | <|body_start_0|>
low, high = (0, len(nums) - 1)
while low <= high:
mid = low + (high - low) // 2
if nums[mid] == target:
return mid
elif nums[mid] > target:
high = mid - 1
else:
low = mid + 1
return l... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def binary_search(self, nums, target):
""":param nums: :param target: :return:返回数组中target的下标，如果不存在target ,则返回数组长度"""
<|body_0|>
def upper_bound(self, nums, target):
""":param nums: 升序的数组 :param target: :return: 数组nums中比target大的第一个数字的下标,如果不存在，则返回数组长度"""
... | stack_v2_sparse_classes_36k_train_006739 | 2,827 | no_license | [
{
"docstring": ":param nums: :param target: :return:返回数组中target的下标，如果不存在target ,则返回数组长度",
"name": "binary_search",
"signature": "def binary_search(self, nums, target)"
},
{
"docstring": ":param nums: 升序的数组 :param target: :return: 数组nums中比target大的第一个数字的下标,如果不存在，则返回数组长度",
"name": "upper_bound"... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binary_search(self, nums, target): :param nums: :param target: :return:返回数组中target的下标，如果不存在target ,则返回数组长度
- def upper_bound(self, nums, target): :param nums: 升序的数组 :param ta... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binary_search(self, nums, target): :param nums: :param target: :return:返回数组中target的下标，如果不存在target ,则返回数组长度
- def upper_bound(self, nums, target): :param nums: 升序的数组 :param ta... | 0e093db4990f56d883f124e4c5a4b7317825049b | <|skeleton|>
class Solution:
def binary_search(self, nums, target):
""":param nums: :param target: :return:返回数组中target的下标，如果不存在target ,则返回数组长度"""
<|body_0|>
def upper_bound(self, nums, target):
""":param nums: 升序的数组 :param target: :return: 数组nums中比target大的第一个数字的下标,如果不存在，则返回数组长度"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def binary_search(self, nums, target):
""":param nums: :param target: :return:返回数组中target的下标，如果不存在target ,则返回数组长度"""
low, high = (0, len(nums) - 1)
while low <= high:
mid = low + (high - low) // 2
if nums[mid] == target:
return mid
... | the_stack_v2_python_sparse | 1分钟写算法/upper_bound.py | pororodl/LeetCode | train | 0 | |
dddad10ba1560958f88eaa0f63d30767297d9cf9 | [
"s = sessionmanage(self.driver)\ns.open_sessionmanage()\nself.assertEqual(s.verify(), True)\ns.modify_obj()\nself.assertEqual(s.sub_tagname(), '会话管理-修改')\ns.name_clear()\ns.session_modify(Data.roomname, 'Update')\ns.modify_save()\nself.assertEqual(s.success(), True)\nfunction.screenshot(self.driver, 'session_modify... | <|body_start_0|>
s = sessionmanage(self.driver)
s.open_sessionmanage()
self.assertEqual(s.verify(), True)
s.modify_obj()
self.assertEqual(s.sub_tagname(), '会话管理-修改')
s.name_clear()
s.session_modify(Data.roomname, 'Update')
s.modify_save()
self.asse... | Test047_Sission_Modify_P1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test047_Sission_Modify_P1:
def test_session_modify_name(self):
"""修改会话名称"""
<|body_0|>
def test_session_modify_keyword(self):
"""修改关键词"""
<|body_1|>
def test_back(self):
"""修改并返回"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_36k_train_006740 | 1,685 | no_license | [
{
"docstring": "修改会话名称",
"name": "test_session_modify_name",
"signature": "def test_session_modify_name(self)"
},
{
"docstring": "修改关键词",
"name": "test_session_modify_keyword",
"signature": "def test_session_modify_keyword(self)"
},
{
"docstring": "修改并返回",
"name": "test_back"... | 3 | null | Implement the Python class `Test047_Sission_Modify_P1` described below.
Class description:
Implement the Test047_Sission_Modify_P1 class.
Method signatures and docstrings:
- def test_session_modify_name(self): 修改会话名称
- def test_session_modify_keyword(self): 修改关键词
- def test_back(self): 修改并返回 | Implement the Python class `Test047_Sission_Modify_P1` described below.
Class description:
Implement the Test047_Sission_Modify_P1 class.
Method signatures and docstrings:
- def test_session_modify_name(self): 修改会话名称
- def test_session_modify_keyword(self): 修改关键词
- def test_back(self): 修改并返回
<|skeleton|>
class Test0... | 6f42c25249fc642cecc270578a180820988d45b5 | <|skeleton|>
class Test047_Sission_Modify_P1:
def test_session_modify_name(self):
"""修改会话名称"""
<|body_0|>
def test_session_modify_keyword(self):
"""修改关键词"""
<|body_1|>
def test_back(self):
"""修改并返回"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test047_Sission_Modify_P1:
def test_session_modify_name(self):
"""修改会话名称"""
s = sessionmanage(self.driver)
s.open_sessionmanage()
self.assertEqual(s.verify(), True)
s.modify_obj()
self.assertEqual(s.sub_tagname(), '会话管理-修改')
s.name_clear()
s.sess... | the_stack_v2_python_sparse | GlxssLive_web/TestCase/Manage_Session/Test047_session_modify_P1.py | rrmiracle/GlxssLive | train | 0 | |
df5d2e0541397e5c8c6863ced056aa9a5711873f | [
"query = self.session.query(VOpenposition.timecreate, VOpenposition.timeupdate, VOpenposition.position, VOpenposition.login, VOpenposition.symbol, VOpenposition.action, VOpenposition.volume, VOpenposition.priceopen, VOpenposition.pricesl, VOpenposition.pricetp, VOpenposition.pricecurrent, VOpenposition.storage, VOp... | <|body_start_0|>
query = self.session.query(VOpenposition.timecreate, VOpenposition.timeupdate, VOpenposition.position, VOpenposition.login, VOpenposition.symbol, VOpenposition.action, VOpenposition.volume, VOpenposition.priceopen, VOpenposition.pricesl, VOpenposition.pricetp, VOpenposition.pricecurrent, VOpenp... | v_openposition视图操作 | VOpenpositionDao | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VOpenpositionDao:
"""v_openposition视图操作"""
def search_by_uid(self, uid, start, end, mtlogin, page=None):
"""已知用户id，根据时间段，查询飘单记录 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和"""
<|body_0|>
def searchsum_by_uid(self, uid, start, end, mtlogin):
... | stack_v2_sparse_classes_36k_train_006741 | 26,694 | permissive | [
{
"docstring": "已知用户id，根据时间段，查询飘单记录 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和",
"name": "search_by_uid",
"signature": "def search_by_uid(self, uid, start, end, mtlogin, page=None)"
},
{
"docstring": "已知用户id，根据时间段，查询总和 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 ... | 2 | stack_v2_sparse_classes_30k_train_007449 | Implement the Python class `VOpenpositionDao` described below.
Class description:
v_openposition视图操作
Method signatures and docstrings:
- def search_by_uid(self, uid, start, end, mtlogin, page=None): 已知用户id，根据时间段，查询飘单记录 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和
- def searchsum_by_uid(self, uid... | Implement the Python class `VOpenpositionDao` described below.
Class description:
v_openposition视图操作
Method signatures and docstrings:
- def search_by_uid(self, uid, start, end, mtlogin, page=None): 已知用户id，根据时间段，查询飘单记录 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和
- def searchsum_by_uid(self, uid... | 1fadeecf31f1d25e258dc5d70c47a785f7b33961 | <|skeleton|>
class VOpenpositionDao:
"""v_openposition视图操作"""
def search_by_uid(self, uid, start, end, mtlogin, page=None):
"""已知用户id，根据时间段，查询飘单记录 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和"""
<|body_0|>
def searchsum_by_uid(self, uid, start, end, mtlogin):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VOpenpositionDao:
"""v_openposition视图操作"""
def search_by_uid(self, uid, start, end, mtlogin, page=None):
"""已知用户id，根据时间段，查询飘单记录 :param uid: 用户id :param start: 开始时间 :param end: 结束时间 :return: 各项总和"""
query = self.session.query(VOpenposition.timecreate, VOpenposition.timeupdate, VOpenpositio... | the_stack_v2_python_sparse | xwcrm/model/views.py | MSUNorg/XWCRM | train | 0 |
d3d39ef733a4b03992e0b1fed1edd813ab3e305e | [
"self.cast: Type[T] = cast\nself.delimiter = delimiter\nself.strip = strip\nself.post_process = post_process",
"if isinstance(value, (tuple, list)):\n value = ''.join((str(v) + self.delimiter for v in value))[:-1]\n\ndef transform(s):\n return self.cast(s.strip(self.strip))\nsplitter = shlex(value, posix=Tr... | <|body_start_0|>
self.cast: Type[T] = cast
self.delimiter = delimiter
self.strip = strip
self.post_process = post_process
<|end_body_0|>
<|body_start_1|>
if isinstance(value, (tuple, list)):
value = ''.join((str(v) + self.delimiter for v in value))[:-1]
def ... | Produces a csv parser that return a list of transformed elements. From python-decouple. | Csv | [
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Csv:
"""Produces a csv parser that return a list of transformed elements. From python-decouple."""
def __init__(self, cast: Type[T]=str, delimiter=',', strip=string.whitespace, post_process=list):
"""Parameters: cast -- callable that transforms the item just before it's added to the ... | stack_v2_sparse_classes_36k_train_006742 | 7,619 | permissive | [
{
"docstring": "Parameters: cast -- callable that transforms the item just before it's added to the list. delimiter -- string of delimiters chars passed to shlex. strip -- string of non-relevant characters to be passed to str.strip after the split. post_process -- callable to post process all casted values. Def... | 2 | stack_v2_sparse_classes_30k_test_000528 | Implement the Python class `Csv` described below.
Class description:
Produces a csv parser that return a list of transformed elements. From python-decouple.
Method signatures and docstrings:
- def __init__(self, cast: Type[T]=str, delimiter=',', strip=string.whitespace, post_process=list): Parameters: cast -- callabl... | Implement the Python class `Csv` described below.
Class description:
Produces a csv parser that return a list of transformed elements. From python-decouple.
Method signatures and docstrings:
- def __init__(self, cast: Type[T]=str, delimiter=',', strip=string.whitespace, post_process=list): Parameters: cast -- callabl... | ab7ac9ceeaf4ea06dfbbd1280be4430d4ac6d684 | <|skeleton|>
class Csv:
"""Produces a csv parser that return a list of transformed elements. From python-decouple."""
def __init__(self, cast: Type[T]=str, delimiter=',', strip=string.whitespace, post_process=list):
"""Parameters: cast -- callable that transforms the item just before it's added to the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Csv:
"""Produces a csv parser that return a list of transformed elements. From python-decouple."""
def __init__(self, cast: Type[T]=str, delimiter=',', strip=string.whitespace, post_process=list):
"""Parameters: cast -- callable that transforms the item just before it's added to the list. delimit... | the_stack_v2_python_sparse | DeepFilterNet/df/config.py | oucxlw/DeepFilterNet | train | 1 |
72f8ba893736985521e157cf42d768137923168e | [
"super(DFTXC, self).__init__()\nself.xcstr = xcstr\nself.nnmodel = nnmodel",
"hybridxc = HybridXC(self.xcstr, self.nnmodel, aweight0=0.0)\noutput = []\nfor entry in inputs:\n evl = XCNNSCF(hybridxc, entry)\n qcs = []\n for system in entry.get_systems():\n qcs.append(evl.run(system))\n if entry.... | <|body_start_0|>
super(DFTXC, self).__init__()
self.xcstr = xcstr
self.nnmodel = nnmodel
<|end_body_0|>
<|body_start_1|>
hybridxc = HybridXC(self.xcstr, self.nnmodel, aweight0=0.0)
output = []
for entry in inputs:
evl = XCNNSCF(hybridxc, entry)
qc... | This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_type = 'ie' >>> true_val= '0.5341... | DFTXC | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DFTXC:
"""This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_... | stack_v2_sparse_classes_36k_train_006743 | 9,553 | permissive | [
{
"docstring": "Parameters ---------- xcstr: str The choice of xc to use. Some of the commonly used ones are: lda_x, lda_c_pw, lda_c_ow, lda_c_pz, lda_xc_lp_a, lda_xc_lp_b. nnmodel: torch.nn.Module the PyTorch model implementing the calculation Notes ----- It is not necessary to use the default method(_construc... | 2 | null | Implement the Python class `DFTXC` described below.
Class description:
This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepch... | Implement the Python class `DFTXC` described below.
Class description:
This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepch... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class DFTXC:
"""This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DFTXC:
"""This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_type = 'ie' >... | the_stack_v2_python_sparse | deepchem/models/dft/dftxc.py | deepchem/deepchem | train | 4,876 |
977363adde53c3c5f9d31f7ae2b9b18a3360c2a3 | [
"super().__init__(self.PROBLEM_NAME)\nself.number_vertices = number_vertices\nself.input_graph = input_graph",
"print('Solving {} problem ...'.format(self.PROBLEM_NAME))\nvisited_list = [False] * self.number_vertices\nsort_list = []\nfor vertex in range(self.number_vertices):\n if not visited_list[vertex]:\n ... | <|body_start_0|>
super().__init__(self.PROBLEM_NAME)
self.number_vertices = number_vertices
self.input_graph = input_graph
<|end_body_0|>
<|body_start_1|>
print('Solving {} problem ...'.format(self.PROBLEM_NAME))
visited_list = [False] * self.number_vertices
sort_list = ... | TopologicalSortingDAG | TopologicalSortingDAG | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopologicalSortingDAG:
"""TopologicalSortingDAG"""
def __init__(self, number_vertices, input_graph):
"""Topological Sorting of DAG Args: number_vertices: Number of vertices in the graph input_graph: Graph for which to find the minimum spanning tree Returns: None Raises: None"""
... | stack_v2_sparse_classes_36k_train_006744 | 2,682 | no_license | [
{
"docstring": "Topological Sorting of DAG Args: number_vertices: Number of vertices in the graph input_graph: Graph for which to find the minimum spanning tree Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, number_vertices, input_graph)"
},
{
"docstring": "Sol... | 3 | null | Implement the Python class `TopologicalSortingDAG` described below.
Class description:
TopologicalSortingDAG
Method signatures and docstrings:
- def __init__(self, number_vertices, input_graph): Topological Sorting of DAG Args: number_vertices: Number of vertices in the graph input_graph: Graph for which to find the ... | Implement the Python class `TopologicalSortingDAG` described below.
Class description:
TopologicalSortingDAG
Method signatures and docstrings:
- def __init__(self, number_vertices, input_graph): Topological Sorting of DAG Args: number_vertices: Number of vertices in the graph input_graph: Graph for which to find the ... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class TopologicalSortingDAG:
"""TopologicalSortingDAG"""
def __init__(self, number_vertices, input_graph):
"""Topological Sorting of DAG Args: number_vertices: Number of vertices in the graph input_graph: Graph for which to find the minimum spanning tree Returns: None Raises: None"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TopologicalSortingDAG:
"""TopologicalSortingDAG"""
def __init__(self, number_vertices, input_graph):
"""Topological Sorting of DAG Args: number_vertices: Number of vertices in the graph input_graph: Graph for which to find the minimum spanning tree Returns: None Raises: None"""
super().__... | the_stack_v2_python_sparse | python/problems/graphs/topological_sorting_dag.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
0c1c3a2b7e96d421262dda670c35ec747d20f73a | [
"ctx.save_for_backward(dim, kappa)\nkappa_copy = kappa.clone()\nm = sp.ive(dim, kappa_copy)\nx = torch.tensor(m).to(device)\nreturn x.clone()",
"dim, kappa = ctx.saved_tensors\ngrad_input = grad_output.clone()\ngrad = grad_input * (bessel_ive(dim - 1, kappa) - bessel_ive(dim, kappa) * (dim + kappa) / kappa)\nretu... | <|body_start_0|>
ctx.save_for_backward(dim, kappa)
kappa_copy = kappa.clone()
m = sp.ive(dim, kappa_copy)
x = torch.tensor(m).to(device)
return x.clone()
<|end_body_0|>
<|body_start_1|>
dim, kappa = ctx.saved_tensors
grad_input = grad_output.clone()
grad ... | We can implement our own custom autograd Functions by subclassing torch.autograd.Function and implementing the forward and backward passes which operate on Tensors. | BesselIve | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BesselIve:
"""We can implement our own custom autograd Functions by subclassing torch.autograd.Function and implementing the forward and backward passes which operate on Tensors."""
def forward(ctx, dim, kappa):
"""In the forward pass we receive a Tensor containing the input and retu... | stack_v2_sparse_classes_36k_train_006745 | 10,798 | permissive | [
{
"docstring": "In the forward pass we receive a Tensor containing the input and return a Tensor containing the output. ctx is a context object that can be used to stash information for backward computation. You can cache arbitrary objects for use in the backward pass using the ctx.save_for_backward method.",
... | 2 | stack_v2_sparse_classes_30k_test_000985 | Implement the Python class `BesselIve` described below.
Class description:
We can implement our own custom autograd Functions by subclassing torch.autograd.Function and implementing the forward and backward passes which operate on Tensors.
Method signatures and docstrings:
- def forward(ctx, dim, kappa): In the forwa... | Implement the Python class `BesselIve` described below.
Class description:
We can implement our own custom autograd Functions by subclassing torch.autograd.Function and implementing the forward and backward passes which operate on Tensors.
Method signatures and docstrings:
- def forward(ctx, dim, kappa): In the forwa... | 95a39fa9f7a0659e432475e8dfb9a46e305d53b7 | <|skeleton|>
class BesselIve:
"""We can implement our own custom autograd Functions by subclassing torch.autograd.Function and implementing the forward and backward passes which operate on Tensors."""
def forward(ctx, dim, kappa):
"""In the forward pass we receive a Tensor containing the input and retu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BesselIve:
"""We can implement our own custom autograd Functions by subclassing torch.autograd.Function and implementing the forward and backward passes which operate on Tensors."""
def forward(ctx, dim, kappa):
"""In the forward pass we receive a Tensor containing the input and return a Tensor c... | the_stack_v2_python_sparse | NVLL/distribution/vmf_hypvae.py | jennhu/vmf_vae_nlp | train | 0 |
2b240565e8d891fd45f3853f3c87af73248f7457 | [
"self.factory = RequestFactory()\nself.temp_dir = tempfile.mkdtemp()\nsuper(ViewTestCase, self).setUp()",
"setattr(request, 'session', 'session')\nmessages = FallbackStorage(request)\nsetattr(request, '_messages', messages)",
"\"\"\"Annotate a request object with a session\"\"\"\nmiddleware = SessionMiddleware(... | <|body_start_0|>
self.factory = RequestFactory()
self.temp_dir = tempfile.mkdtemp()
super(ViewTestCase, self).setUp()
<|end_body_0|>
<|body_start_1|>
setattr(request, 'session', 'session')
messages = FallbackStorage(request)
setattr(request, '_messages', messages)
<|end_... | Test basic view functionality. | ViewTestCase | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewTestCase:
"""Test basic view functionality."""
def setUp(self):
"""Create request factory and set temp_dir for testing."""
<|body_0|>
def set_request_message_attributes(request):
"""Set session and _messages attributies on request."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_006746 | 40,377 | permissive | [
{
"docstring": "Create request factory and set temp_dir for testing.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Set session and _messages attributies on request.",
"name": "set_request_message_attributes",
"signature": "def set_request_message_attributes(request... | 3 | null | Implement the Python class `ViewTestCase` described below.
Class description:
Test basic view functionality.
Method signatures and docstrings:
- def setUp(self): Create request factory and set temp_dir for testing.
- def set_request_message_attributes(request): Set session and _messages attributies on request.
- def ... | Implement the Python class `ViewTestCase` described below.
Class description:
Test basic view functionality.
Method signatures and docstrings:
- def setUp(self): Create request factory and set temp_dir for testing.
- def set_request_message_attributes(request): Set session and _messages attributies on request.
- def ... | 69855813052243c702c9b0108d2eac3f4f1a768f | <|skeleton|>
class ViewTestCase:
"""Test basic view functionality."""
def setUp(self):
"""Create request factory and set temp_dir for testing."""
<|body_0|>
def set_request_message_attributes(request):
"""Set session and _messages attributies on request."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViewTestCase:
"""Test basic view functionality."""
def setUp(self):
"""Create request factory and set temp_dir for testing."""
self.factory = RequestFactory()
self.temp_dir = tempfile.mkdtemp()
super(ViewTestCase, self).setUp()
def set_request_message_attributes(reque... | the_stack_v2_python_sparse | hs_core/testing.py | hydroshare/hydroshare | train | 207 |
99f6281c1a3a20480785de966d0f780fea322734 | [
"nums.sort()\nmin_dist, max_dist = (nums[-1] - nums[0], nums[-1] - nums[0])\nfor i in xrange(1, len(nums)):\n min_dist = min(min_dist, nums[i] - nums[i - 1])\nleft, right = (min_dist, max_dist)\nwhile left < right:\n mid = left + (right - left >> 1)\n if self.countPairs(nums, mid) < k:\n left = mid ... | <|body_start_0|>
nums.sort()
min_dist, max_dist = (nums[-1] - nums[0], nums[-1] - nums[0])
for i in xrange(1, len(nums)):
min_dist = min(min_dist, nums[i] - nums[i - 1])
left, right = (min_dist, max_dist)
while left < right:
mid = left + (right - left >> 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def countPairs(self, nums, dist):
"""number of pairs whose distance is no more than dist"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006747 | 1,663 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "smallestDistancePair",
"signature": "def smallestDistancePair(self, nums, k)"
},
{
"docstring": "number of pairs whose distance is no more than dist",
"name": "countPairs",
"signature": "def countPairs(self, nums, ... | 2 | stack_v2_sparse_classes_30k_train_021370 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def countPairs(self, nums, dist): number of pairs whose distance is no more than dist | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def countPairs(self, nums, dist): number of pairs whose distance is no more than dist
<... | ee79d3437cf47b26a4bca0ec798dc54d7b623453 | <|skeleton|>
class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def countPairs(self, nums, dist):
"""number of pairs whose distance is no more than dist"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
nums.sort()
min_dist, max_dist = (nums[-1] - nums[0], nums[-1] - nums[0])
for i in xrange(1, len(nums)):
min_dist = min(min_dist, nums[i] - nums[i - 1])
l... | the_stack_v2_python_sparse | Algorithm/Python/719. Find K-th Smallest Pair Distance.py | WuLC/LeetCode | train | 29 | |
97a67f51b8049bd5793ae85fd916ac49c770a3ae | [
"super(PGCRAirMarkets, self).__init__()\nself.location = FileUtilities.PathToForwardSlash(os.path.dirname(os.path.abspath(__file__)))\nself.awsParams = ''",
"jobParams = dict(self.job)\njobParams['s3Filename'] = 's3://' + self.job['bucketName'] + '/' + self.job['s3SrcDirectory'] + '/' + srcFileParameter['s3Filena... | <|body_start_0|>
super(PGCRAirMarkets, self).__init__()
self.location = FileUtilities.PathToForwardSlash(os.path.dirname(os.path.abspath(__file__)))
self.awsParams = ''
<|end_body_0|>
<|body_start_1|>
jobParams = dict(self.job)
jobParams['s3Filename'] = 's3://' + self.job['bucke... | Code to process the PGCR Air Markets data | PGCRAirMarkets | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PGCRAirMarkets:
"""Code to process the PGCR Air Markets data"""
def __init__(self):
"""Initial settings"""
<|body_0|>
def ProcessS3File(self, srcFileParameter):
"""For each file we need to process, provide the data loader the s3 key and destination table name"""
... | stack_v2_sparse_classes_36k_train_006748 | 2,489 | no_license | [
{
"docstring": "Initial settings",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "For each file we need to process, provide the data loader the s3 key and destination table name",
"name": "ProcessS3File",
"signature": "def ProcessS3File(self, srcFileParameter)"
... | 3 | stack_v2_sparse_classes_30k_train_014065 | Implement the Python class `PGCRAirMarkets` described below.
Class description:
Code to process the PGCR Air Markets data
Method signatures and docstrings:
- def __init__(self): Initial settings
- def ProcessS3File(self, srcFileParameter): For each file we need to process, provide the data loader the s3 key and desti... | Implement the Python class `PGCRAirMarkets` described below.
Class description:
Code to process the PGCR Air Markets data
Method signatures and docstrings:
- def __init__(self): Initial settings
- def ProcessS3File(self, srcFileParameter): For each file we need to process, provide the data loader the s3 key and desti... | 9ff48f61cfd4e0c5994ad3dabab3987255cea953 | <|skeleton|>
class PGCRAirMarkets:
"""Code to process the PGCR Air Markets data"""
def __init__(self):
"""Initial settings"""
<|body_0|>
def ProcessS3File(self, srcFileParameter):
"""For each file we need to process, provide the data loader the s3 key and destination table name"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PGCRAirMarkets:
"""Code to process the PGCR Air Markets data"""
def __init__(self):
"""Initial settings"""
super(PGCRAirMarkets, self).__init__()
self.location = FileUtilities.PathToForwardSlash(os.path.dirname(os.path.abspath(__file__)))
self.awsParams = ''
def Proce... | the_stack_v2_python_sparse | EAA_Dataloader/src/Applications/PGCRAirMarketsIteration2/PGCRAirMarkets.py | eulertech/backup | train | 0 |
1ec29dface10807c10c46bc6d740497d0eef06aa | [
"airbyte_level = self.level_mapping.get(record.levelno, 'INFO')\nif airbyte_level == 'DEBUG':\n extras = self.extract_extra_args_from_record(record)\n debug_dict = {'type': 'DEBUG', 'message': record.getMessage(), 'data': extras}\n return filter_secrets(json.dumps(debug_dict))\nelse:\n message = super()... | <|body_start_0|>
airbyte_level = self.level_mapping.get(record.levelno, 'INFO')
if airbyte_level == 'DEBUG':
extras = self.extract_extra_args_from_record(record)
debug_dict = {'type': 'DEBUG', 'message': record.getMessage(), 'data': extras}
return filter_secrets(json.... | Output log records using AirbyteMessage | AirbyteLogFormatter | [
"MIT",
"Elastic-2.0",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AirbyteLogFormatter:
"""Output log records using AirbyteMessage"""
def format(self, record: logging.LogRecord) -> str:
"""Return a JSON representation of the log message"""
<|body_0|>
def extract_extra_args_from_record(record: logging.LogRecord):
"""The python lo... | stack_v2_sparse_classes_36k_train_006749 | 3,985 | permissive | [
{
"docstring": "Return a JSON representation of the log message",
"name": "format",
"signature": "def format(self, record: logging.LogRecord) -> str"
},
{
"docstring": "The python logger conflates default args with extra args. We use an empty log record and set operations to isolate fields passe... | 2 | null | Implement the Python class `AirbyteLogFormatter` described below.
Class description:
Output log records using AirbyteMessage
Method signatures and docstrings:
- def format(self, record: logging.LogRecord) -> str: Return a JSON representation of the log message
- def extract_extra_args_from_record(record: logging.LogR... | Implement the Python class `AirbyteLogFormatter` described below.
Class description:
Output log records using AirbyteMessage
Method signatures and docstrings:
- def format(self, record: logging.LogRecord) -> str: Return a JSON representation of the log message
- def extract_extra_args_from_record(record: logging.LogR... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class AirbyteLogFormatter:
"""Output log records using AirbyteMessage"""
def format(self, record: logging.LogRecord) -> str:
"""Return a JSON representation of the log message"""
<|body_0|>
def extract_extra_args_from_record(record: logging.LogRecord):
"""The python lo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AirbyteLogFormatter:
"""Output log records using AirbyteMessage"""
def format(self, record: logging.LogRecord) -> str:
"""Return a JSON representation of the log message"""
airbyte_level = self.level_mapping.get(record.levelno, 'INFO')
if airbyte_level == 'DEBUG':
extr... | the_stack_v2_python_sparse | dts/airbyte/airbyte-cdk/python/airbyte_cdk/logger.py | alldatacenter/alldata | train | 774 |
9981baaff44d2c5a4e994bc9866d61eb52f65c6d | [
"ret = 0\nsums = defaultdict(int)\nsums[0] += 1\nacc = 0\nfor n in nums:\n acc += n\n for s in sums:\n if (acc - s) % k == 0:\n ret += sums[s]\n sums[acc] += 1\nreturn ret",
"ret = 0\ncnt = [0] * k\ncnt[0] = 1\nacc = 0\nfor n in nums:\n acc += n\n ret += cnt[acc % k]\n cnt[acc ... | <|body_start_0|>
ret = 0
sums = defaultdict(int)
sums[0] += 1
acc = 0
for n in nums:
acc += n
for s in sums:
if (acc - s) % k == 0:
ret += sums[s]
sums[acc] += 1
return ret
<|end_body_0|>
<|body_star... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subarraysDivByK(self, nums: List[int], k: int) -> int:
"""Mar 05, 2023 22:16 TLE"""
<|body_0|>
def subarraysDivByK(self, nums: List[int], k: int) -> int:
"""Mar 05, 2023 22:20"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = 0
... | stack_v2_sparse_classes_36k_train_006750 | 1,821 | no_license | [
{
"docstring": "Mar 05, 2023 22:16 TLE",
"name": "subarraysDivByK",
"signature": "def subarraysDivByK(self, nums: List[int], k: int) -> int"
},
{
"docstring": "Mar 05, 2023 22:20",
"name": "subarraysDivByK",
"signature": "def subarraysDivByK(self, nums: List[int], k: int) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_010213 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subarraysDivByK(self, nums: List[int], k: int) -> int: Mar 05, 2023 22:16 TLE
- def subarraysDivByK(self, nums: List[int], k: int) -> int: Mar 05, 2023 22:20 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subarraysDivByK(self, nums: List[int], k: int) -> int: Mar 05, 2023 22:16 TLE
- def subarraysDivByK(self, nums: List[int], k: int) -> int: Mar 05, 2023 22:20
<|skeleton|>
cl... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def subarraysDivByK(self, nums: List[int], k: int) -> int:
"""Mar 05, 2023 22:16 TLE"""
<|body_0|>
def subarraysDivByK(self, nums: List[int], k: int) -> int:
"""Mar 05, 2023 22:20"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def subarraysDivByK(self, nums: List[int], k: int) -> int:
"""Mar 05, 2023 22:16 TLE"""
ret = 0
sums = defaultdict(int)
sums[0] += 1
acc = 0
for n in nums:
acc += n
for s in sums:
if (acc - s) % k == 0:
... | the_stack_v2_python_sparse | leetcode/solved/1016_Subarray_Sums_Divisible_by_K/solution.py | sungminoh/algorithms | train | 0 | |
fb42951a51294cfff88ca441eb07fc9529dc8ddd | [
"self.msg_id = msg_id\nif failure_info is not None:\n ex_class = failure_info[0]\n ex = failure_info[1]\n tb = traceback.format_exception(*failure_info)\n if issubclass(ex_class, RemoteExceptionMixin):\n failure_data = {'c': ex.clazz, 'm': ex.module, 's': ex.message, 't': tb}\n else:\n ... | <|body_start_0|>
self.msg_id = msg_id
if failure_info is not None:
ex_class = failure_info[0]
ex = failure_info[1]
tb = traceback.format_exception(*failure_info)
if issubclass(ex_class, RemoteExceptionMixin):
failure_data = {'c': ex.clazz, ... | PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response | RpcReplyPikaOutgoingMessage | [
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RpcReplyPikaOutgoingMessage:
"""PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response"""
def __init__(self, pika_engine, msg_id, reply=None, failure_info=None, content_type=None):
"""Initialize with reply info... | stack_v2_sparse_classes_36k_train_006751 | 24,684 | permissive | [
{
"docstring": "Initialize with reply information for sending :param pika_engine: PikaEngine, shared object with configuration and shared driver functionality :param msg_id: String, msg_id of RPC request, which waits for reply :param reply: Dictionary, reply. In case of exception should be None :param failure_i... | 2 | stack_v2_sparse_classes_30k_train_013581 | Implement the Python class `RpcReplyPikaOutgoingMessage` described below.
Class description:
PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response
Method signatures and docstrings:
- def __init__(self, pika_engine, msg_id, reply=None, failure_... | Implement the Python class `RpcReplyPikaOutgoingMessage` described below.
Class description:
PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response
Method signatures and docstrings:
- def __init__(self, pika_engine, msg_id, reply=None, failure_... | c01951b33e278de9e769c2d0609c0be61d2cb26b | <|skeleton|>
class RpcReplyPikaOutgoingMessage:
"""PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response"""
def __init__(self, pika_engine, msg_id, reply=None, failure_info=None, content_type=None):
"""Initialize with reply info... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RpcReplyPikaOutgoingMessage:
"""PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response"""
def __init__(self, pika_engine, msg_id, reply=None, failure_info=None, content_type=None):
"""Initialize with reply information for s... | the_stack_v2_python_sparse | filesystems/vnx_rootfs_lxc_ubuntu64-16.04-v025-openstack-compute/rootfs/usr/lib/python2.7/dist-packages/oslo_messaging/_drivers/pika_driver/pika_message.py | juancarlosdiaztorres/Ansible-OpenStack | train | 0 |
fb74be051b57cfe2206202bab3c3312998d7714c | [
"super().__init__()\nself.upsampler = dnnlib.util.construct_class_by_name(**upsampler_kwargs)\nself.z_dim = self.upsampler.z_dim\nself.c_dim = self.upsampler.c_dim\nself.img_channels = self.upsampler.img_channels\nself.img_resolution = self.upsampler.img_resolution\nself.layout_model_path = layout_model_path\nwith ... | <|body_start_0|>
super().__init__()
self.upsampler = dnnlib.util.construct_class_by_name(**upsampler_kwargs)
self.z_dim = self.upsampler.z_dim
self.c_dim = self.upsampler.c_dim
self.img_channels = self.upsampler.img_channels
self.img_resolution = self.upsampler.img_resolu... | Terrain wraps upsampler and layout model. | ModelTerrain | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelTerrain:
"""Terrain wraps upsampler and layout model."""
def __init__(self, layout_model_path, **upsampler_kwargs):
"""Initialize wrapper for upsampler refinement module. Args: layout_model_path: str containing the path to layout model **upsampler_kwargs: dictionary of inputs to... | stack_v2_sparse_classes_36k_train_006752 | 7,503 | permissive | [
{
"docstring": "Initialize wrapper for upsampler refinement module. Args: layout_model_path: str containing the path to layout model **upsampler_kwargs: dictionary of inputs to initialize upsampler",
"name": "__init__",
"signature": "def __init__(self, layout_model_path, **upsampler_kwargs)"
},
{
... | 5 | stack_v2_sparse_classes_30k_test_000858 | Implement the Python class `ModelTerrain` described below.
Class description:
Terrain wraps upsampler and layout model.
Method signatures and docstrings:
- def __init__(self, layout_model_path, **upsampler_kwargs): Initialize wrapper for upsampler refinement module. Args: layout_model_path: str containing the path to... | Implement the Python class `ModelTerrain` described below.
Class description:
Terrain wraps upsampler and layout model.
Method signatures and docstrings:
- def __init__(self, layout_model_path, **upsampler_kwargs): Initialize wrapper for upsampler refinement module. Args: layout_model_path: str containing the path to... | c1ae273841592fce4c993bf35cdd0a6424e73da4 | <|skeleton|>
class ModelTerrain:
"""Terrain wraps upsampler and layout model."""
def __init__(self, layout_model_path, **upsampler_kwargs):
"""Initialize wrapper for upsampler refinement module. Args: layout_model_path: str containing the path to layout model **upsampler_kwargs: dictionary of inputs to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelTerrain:
"""Terrain wraps upsampler and layout model."""
def __init__(self, layout_model_path, **upsampler_kwargs):
"""Initialize wrapper for upsampler refinement module. Args: layout_model_path: str containing the path to layout model **upsampler_kwargs: dictionary of inputs to initialize u... | the_stack_v2_python_sparse | persistent-nature/models/layout/model_terrain.py | ishine/google-research | train | 0 |
21c04defb8f361da7720357494063b243f68f190 | [
"super().__init__()\nimport sklearn\nimport sklearn.multiclass\nself.model = sklearn.multiclass.OneVsRestClassifier",
"specs = super().getInputSpecification()\nspecs.description = 'The \\\\xmlNode{OneVsRestClassifier} (\\\\textit{One-vs-the-rest (OvR) multiclass strategy})\\n Also known as ... | <|body_start_0|>
super().__init__()
import sklearn
import sklearn.multiclass
self.model = sklearn.multiclass.OneVsRestClassifier
<|end_body_0|>
<|body_start_1|>
specs = super().getInputSpecification()
specs.description = 'The \\xmlNode{OneVsRestClassifier} (\\textit{One-... | One-vs-the-rest (OvR) multiclass strategy classifer | OneVsRestClassifier | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OneVsRestClassifier:
"""One-vs-the-rest (OvR) multiclass strategy classifer"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get... | stack_v2_sparse_classes_36k_train_006753 | 5,730 | permissive | [
{
"docstring": "Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for... | 4 | stack_v2_sparse_classes_30k_test_000942 | Implement the Python class `OneVsRestClassifier` described below.
Class description:
One-vs-the-rest (OvR) multiclass strategy classifer
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecificatio... | Implement the Python class `OneVsRestClassifier` described below.
Class description:
One-vs-the-rest (OvR) multiclass strategy classifer
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecificatio... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class OneVsRestClassifier:
"""One-vs-the-rest (OvR) multiclass strategy classifer"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OneVsRestClassifier:
"""One-vs-the-rest (OvR) multiclass strategy classifer"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
super().__init__()
import sklearn
import sklearn.multiclass
s... | the_stack_v2_python_sparse | ravenframework/SupervisedLearning/ScikitLearn/MultiClass/OneVsRestClassifier.py | idaholab/raven | train | 201 |
e289205113301f5ec8e762154fa23b908b845812 | [
"if serializer_class is None:\n if 'context' in kwargs.keys():\n kwargs.pop('context')\n return self.get_serializer(queryset, *args, **kwargs)\nreturn serializer_class(queryset, *args, context=self.get_serializer_context(), **kwargs)",
"if user_pk is None:\n queryset = self.get_queryset().filter(u... | <|body_start_0|>
if serializer_class is None:
if 'context' in kwargs.keys():
kwargs.pop('context')
return self.get_serializer(queryset, *args, **kwargs)
return serializer_class(queryset, *args, context=self.get_serializer_context(), **kwargs)
<|end_body_0|>
<|bod... | /users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin | UserNestedListMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserNestedListMixin:
"""/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin"""
def _serialize(self, serializer_class, queryset, *args, **kwargs):
"""Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位... | stack_v2_sparse_classes_36k_train_006754 | 5,541 | no_license | [
{
"docstring": "Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位置引数 :param kwargs: Serializerをインスタンス化する際のオプション引数 :return: インスタンス化されたSerializer",
"name": "_serialize",
"signature": "def _serialize(self, serializer_class... | 2 | stack_v2_sparse_classes_30k_train_000479 | Implement the Python class `UserNestedListMixin` described below.
Class description:
/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin
Method signatures and docstrings:
- def _serialize(self, serializer_class, queryset, *args, **kwargs): Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用... | Implement the Python class `UserNestedListMixin` described below.
Class description:
/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin
Method signatures and docstrings:
- def _serialize(self, serializer_class, queryset, *args, **kwargs): Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用... | 6f9487dcfc13c706d312be6586159c7d3a25c6aa | <|skeleton|>
class UserNestedListMixin:
"""/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin"""
def _serialize(self, serializer_class, queryset, *args, **kwargs):
"""Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserNestedListMixin:
"""/users/<user_pk>/favs/ のようなネストされた要素に対してリストを返す時のmixin"""
def _serialize(self, serializer_class, queryset, *args, **kwargs):
"""Serializerの指定があればそれで返す．無ければself.get_serializerする． :param serializer_class: 使用するSerializerクラスを指定する :param args: Serializerをインスタンス化する際の位置引数 :param kw... | the_stack_v2_python_sparse | src/plan/mixins.py | jphacks/KB_1809_2 | train | 3 |
777f59068da91a2689ace0b31b53a77b956cd0ca | [
"password1 = self.cleaned_data.get('password1')\npassword2 = self.cleaned_data.get('password2')\nif password1 and password2 and (password1 != password2):\n raise forms.ValidationError('Passwords do not match')\nreturn password2",
"user = super(UserCreationForm, self).save(commit=False)\nuser.set_password(self.... | <|body_start_0|>
password1 = self.cleaned_data.get('password1')
password2 = self.cleaned_data.get('password2')
if password1 and password2 and (password1 != password2):
raise forms.ValidationError('Passwords do not match')
return password2
<|end_body_0|>
<|body_start_1|>
... | A form for creating new users with a password confirmation field. | UserCreationForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCreationForm:
"""A form for creating new users with a password confirmation field."""
def clean_password(self):
"""Checks that both of the passwords match :return: String - Password or Boolean False otherwise"""
<|body_0|>
def save(self, commit=True):
"""Save... | stack_v2_sparse_classes_36k_train_006755 | 4,010 | no_license | [
{
"docstring": "Checks that both of the passwords match :return: String - Password or Boolean False otherwise",
"name": "clean_password",
"signature": "def clean_password(self)"
},
{
"docstring": "Save data, mostly the password, in a hashed form :param commit: Whether or not to commit the change... | 2 | stack_v2_sparse_classes_30k_train_007689 | Implement the Python class `UserCreationForm` described below.
Class description:
A form for creating new users with a password confirmation field.
Method signatures and docstrings:
- def clean_password(self): Checks that both of the passwords match :return: String - Password or Boolean False otherwise
- def save(sel... | Implement the Python class `UserCreationForm` described below.
Class description:
A form for creating new users with a password confirmation field.
Method signatures and docstrings:
- def clean_password(self): Checks that both of the passwords match :return: String - Password or Boolean False otherwise
- def save(sel... | 167a39307fe3d978d3eee4b3fcd53c27143f5924 | <|skeleton|>
class UserCreationForm:
"""A form for creating new users with a password confirmation field."""
def clean_password(self):
"""Checks that both of the passwords match :return: String - Password or Boolean False otherwise"""
<|body_0|>
def save(self, commit=True):
"""Save... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserCreationForm:
"""A form for creating new users with a password confirmation field."""
def clean_password(self):
"""Checks that both of the passwords match :return: String - Password or Boolean False otherwise"""
password1 = self.cleaned_data.get('password1')
password2 = self.c... | the_stack_v2_python_sparse | summit/libs/auth/admin.py | NAU-CCL/cpcesu-summit | train | 0 |
32f9d59b11d0474392c4eb5ce7ed8fa09a6c5f32 | [
"super().__init__(event, arg_string)\nself.bot = SlackHandler()\nself.ka = KarmaAssistant()",
"how_many = 5\nif self.arg_string:\n try:\n how_many = int(self.arg_string)\n except ValueError:\n self.bot.make_post(self.event, '{} is not a valid number.'.format(self.arg_string))\n return\n... | <|body_start_0|>
super().__init__(event, arg_string)
self.bot = SlackHandler()
self.ka = KarmaAssistant()
<|end_body_0|>
<|body_start_1|>
how_many = 5
if self.arg_string:
try:
how_many = int(self.arg_string)
except ValueError:
... | Post highest-karma karma entries. | KarmaTopPlugin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KarmaTopPlugin:
"""Post highest-karma karma entries."""
def __init__(self, event, arg_string):
"""Config."""
<|body_0|>
def run(self):
"""Run the plugin."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__(event, arg_string)
... | stack_v2_sparse_classes_36k_train_006756 | 11,809 | permissive | [
{
"docstring": "Config.",
"name": "__init__",
"signature": "def __init__(self, event, arg_string)"
},
{
"docstring": "Run the plugin.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011902 | Implement the Python class `KarmaTopPlugin` described below.
Class description:
Post highest-karma karma entries.
Method signatures and docstrings:
- def __init__(self, event, arg_string): Config.
- def run(self): Run the plugin. | Implement the Python class `KarmaTopPlugin` described below.
Class description:
Post highest-karma karma entries.
Method signatures and docstrings:
- def __init__(self, event, arg_string): Config.
- def run(self): Run the plugin.
<|skeleton|>
class KarmaTopPlugin:
"""Post highest-karma karma entries."""
def... | 715c14d3a06d8a7a8771572371b67cc87c7e17fb | <|skeleton|>
class KarmaTopPlugin:
"""Post highest-karma karma entries."""
def __init__(self, event, arg_string):
"""Config."""
<|body_0|>
def run(self):
"""Run the plugin."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KarmaTopPlugin:
"""Post highest-karma karma entries."""
def __init__(self, event, arg_string):
"""Config."""
super().__init__(event, arg_string)
self.bot = SlackHandler()
self.ka = KarmaAssistant()
def run(self):
"""Run the plugin."""
how_many = 5
... | the_stack_v2_python_sparse | src/dungeonbot/plugins/karma.py | DungeonBot/dungeonbot | train | 0 |
298242012aea52f7a1f4a9543ce2ba4fe0c34ea6 | [
"logging.info('Select/click the ' + self.name)\ncheckbox = self.x_driver.find_element(self.x_elem_id[0], self.x_elem_id[1])\nif wait:\n time.sleep(wait_time)\ncheckbox.click()",
"logging.info('Determine if the ' + self.name + ' is checked.')\ncheckbox = self.x_driver.find_element(self.x_elem_id[0], self.x_elem... | <|body_start_0|>
logging.info('Select/click the ' + self.name)
checkbox = self.x_driver.find_element(self.x_elem_id[0], self.x_elem_id[1])
if wait:
time.sleep(wait_time)
checkbox.click()
<|end_body_0|>
<|body_start_1|>
logging.info('Determine if the ' + self.name + '... | Common class for checkbox elements/widgets | CheckBox | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckBox:
"""Common class for checkbox elements/widgets"""
def select(self, wait=True, wait_time=config.wait_time):
"""Select the checkbox :param wait: True - Wait before performing action False - Do not wait before performing action :param wait_time: Time to wait before performing a... | stack_v2_sparse_classes_36k_train_006757 | 1,509 | no_license | [
{
"docstring": "Select the checkbox :param wait: True - Wait before performing action False - Do not wait before performing action :param wait_time: Time to wait before performing action. :return: None",
"name": "select",
"signature": "def select(self, wait=True, wait_time=config.wait_time)"
},
{
... | 2 | stack_v2_sparse_classes_30k_test_000989 | Implement the Python class `CheckBox` described below.
Class description:
Common class for checkbox elements/widgets
Method signatures and docstrings:
- def select(self, wait=True, wait_time=config.wait_time): Select the checkbox :param wait: True - Wait before performing action False - Do not wait before performing ... | Implement the Python class `CheckBox` described below.
Class description:
Common class for checkbox elements/widgets
Method signatures and docstrings:
- def select(self, wait=True, wait_time=config.wait_time): Select the checkbox :param wait: True - Wait before performing action False - Do not wait before performing ... | c7ae5cd1c14defdbff57c2ed5e4a447c7799c495 | <|skeleton|>
class CheckBox:
"""Common class for checkbox elements/widgets"""
def select(self, wait=True, wait_time=config.wait_time):
"""Select the checkbox :param wait: True - Wait before performing action False - Do not wait before performing action :param wait_time: Time to wait before performing a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckBox:
"""Common class for checkbox elements/widgets"""
def select(self, wait=True, wait_time=config.wait_time):
"""Select the checkbox :param wait: True - Wait before performing action False - Do not wait before performing action :param wait_time: Time to wait before performing action. :retur... | the_stack_v2_python_sparse | support/common_controls/__checkbox.py | chrisaroy/proj_selenium_python_dev | train | 0 |
9db7c40c3e23c144188df31219c4201cd1f83fec | [
"form_pk = self.kwargs.get('pk')\nif self.action == 'list' and form_pk is None:\n return OSMSiteMapSerializer\nreturn super().get_serializer_class()",
"form_pk = self.kwargs.get('pk')\nif form_pk:\n queryset = queryset.filter(pk=form_pk)\nreturn super().filter_queryset(queryset)",
"obj = super().get_objec... | <|body_start_0|>
form_pk = self.kwargs.get('pk')
if self.action == 'list' and form_pk is None:
return OSMSiteMapSerializer
return super().get_serializer_class()
<|end_body_0|>
<|body_start_1|>
form_pk = self.kwargs.get('pk')
if form_pk:
queryset = queryse... | This endpoint provides public access to OSM submitted data in OSM format. No authentication is required. Where: * `pk` - the form unique identifier * `dataid` - submission data unique identifier * `owner` - username of the owner(user/organization) of the data point ## GET JSON List of data end points Lists the data end... | OsmViewSet | [
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OsmViewSet:
"""This endpoint provides public access to OSM submitted data in OSM format. No authentication is required. Where: * `pk` - the form unique identifier * `dataid` - submission data unique identifier * `owner` - username of the owner(user/organization) of the data point ## GET JSON List... | stack_v2_sparse_classes_36k_train_006758 | 6,952 | permissive | [
{
"docstring": "Returns the OSMSiteMapSerializer class when list API is invoked.",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self)"
},
{
"docstring": "Filters the queryset using the ``pk`` when used.",
"name": "filter_queryset",
"signature": "def filter_query... | 5 | stack_v2_sparse_classes_30k_train_005469 | Implement the Python class `OsmViewSet` described below.
Class description:
This endpoint provides public access to OSM submitted data in OSM format. No authentication is required. Where: * `pk` - the form unique identifier * `dataid` - submission data unique identifier * `owner` - username of the owner(user/organizat... | Implement the Python class `OsmViewSet` described below.
Class description:
This endpoint provides public access to OSM submitted data in OSM format. No authentication is required. Where: * `pk` - the form unique identifier * `dataid` - submission data unique identifier * `owner` - username of the owner(user/organizat... | e5bdec91cb47179172b515bbcb91701262ff3377 | <|skeleton|>
class OsmViewSet:
"""This endpoint provides public access to OSM submitted data in OSM format. No authentication is required. Where: * `pk` - the form unique identifier * `dataid` - submission data unique identifier * `owner` - username of the owner(user/organization) of the data point ## GET JSON List... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OsmViewSet:
"""This endpoint provides public access to OSM submitted data in OSM format. No authentication is required. Where: * `pk` - the form unique identifier * `dataid` - submission data unique identifier * `owner` - username of the owner(user/organization) of the data point ## GET JSON List of data end ... | the_stack_v2_python_sparse | onadata/apps/api/viewsets/osm_viewset.py | onaio/onadata | train | 177 |
48647e0b097b5b723e16913789939961587f3db7 | [
"super().__init__(*args, category=CATEGORY_ALARM_SYSTEM)\nstate = self.hass.states.get(self.entity_id)\nself._alarm_code = self.config.get(ATTR_CODE)\nsupported_states = state.attributes.get(ATTR_SUPPORTED_FEATURES, SUPPORT_ALARM_ARM_HOME | SUPPORT_ALARM_ARM_AWAY | SUPPORT_ALARM_ARM_NIGHT | SUPPORT_ALARM_TRIGGER)\n... | <|body_start_0|>
super().__init__(*args, category=CATEGORY_ALARM_SYSTEM)
state = self.hass.states.get(self.entity_id)
self._alarm_code = self.config.get(ATTR_CODE)
supported_states = state.attributes.get(ATTR_SUPPORTED_FEATURES, SUPPORT_ALARM_ARM_HOME | SUPPORT_ALARM_ARM_AWAY | SUPPORT_A... | Generate an SecuritySystem accessory for an alarm control panel. | SecuritySystem | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecuritySystem:
"""Generate an SecuritySystem accessory for an alarm control panel."""
def __init__(self, *args):
"""Initialize a SecuritySystem accessory object."""
<|body_0|>
def set_security_state(self, value):
"""Move security state to value if call came from... | stack_v2_sparse_classes_36k_train_006759 | 6,081 | permissive | [
{
"docstring": "Initialize a SecuritySystem accessory object.",
"name": "__init__",
"signature": "def __init__(self, *args)"
},
{
"docstring": "Move security state to value if call came from HomeKit.",
"name": "set_security_state",
"signature": "def set_security_state(self, value)"
},
... | 3 | stack_v2_sparse_classes_30k_train_002240 | Implement the Python class `SecuritySystem` described below.
Class description:
Generate an SecuritySystem accessory for an alarm control panel.
Method signatures and docstrings:
- def __init__(self, *args): Initialize a SecuritySystem accessory object.
- def set_security_state(self, value): Move security state to va... | Implement the Python class `SecuritySystem` described below.
Class description:
Generate an SecuritySystem accessory for an alarm control panel.
Method signatures and docstrings:
- def __init__(self, *args): Initialize a SecuritySystem accessory object.
- def set_security_state(self, value): Move security state to va... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class SecuritySystem:
"""Generate an SecuritySystem accessory for an alarm control panel."""
def __init__(self, *args):
"""Initialize a SecuritySystem accessory object."""
<|body_0|>
def set_security_state(self, value):
"""Move security state to value if call came from... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecuritySystem:
"""Generate an SecuritySystem accessory for an alarm control panel."""
def __init__(self, *args):
"""Initialize a SecuritySystem accessory object."""
super().__init__(*args, category=CATEGORY_ALARM_SYSTEM)
state = self.hass.states.get(self.entity_id)
self._... | the_stack_v2_python_sparse | homeassistant/components/homekit/type_security_systems.py | BenWoodford/home-assistant | train | 11 |
38628210514547e37e6b3fe73a5a6c75ab68fd98 | [
"self.num_failed = num_failed\nself.num_objects = num_objects\nself.size_bytes = size_bytes",
"if dictionary is None:\n return None\nnum_failed = dictionary.get('numFailed')\nnum_objects = dictionary.get('numObjects')\nsize_bytes = dictionary.get('sizeBytes')\nreturn cls(num_failed, num_objects, size_bytes)"
] | <|body_start_0|>
self.num_failed = num_failed
self.num_objects = num_objects
self.size_bytes = size_bytes
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
num_failed = dictionary.get('numFailed')
num_objects = dictionary.get('numObjects')
... | Implementation of the 'ProtectionStats' model. Protection Statistics. Attributes: num_failed (int): Number of Failed Objects. num_objects (int): Number of Objects. size_bytes (long|int): Size in Bytes. | ProtectionStats | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectionStats:
"""Implementation of the 'ProtectionStats' model. Protection Statistics. Attributes: num_failed (int): Number of Failed Objects. num_objects (int): Number of Objects. size_bytes (long|int): Size in Bytes."""
def __init__(self, num_failed=None, num_objects=None, size_bytes=No... | stack_v2_sparse_classes_36k_train_006760 | 1,756 | permissive | [
{
"docstring": "Constructor for the ProtectionStats class",
"name": "__init__",
"signature": "def __init__(self, num_failed=None, num_objects=None, size_bytes=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation ... | 2 | stack_v2_sparse_classes_30k_test_000226 | Implement the Python class `ProtectionStats` described below.
Class description:
Implementation of the 'ProtectionStats' model. Protection Statistics. Attributes: num_failed (int): Number of Failed Objects. num_objects (int): Number of Objects. size_bytes (long|int): Size in Bytes.
Method signatures and docstrings:
-... | Implement the Python class `ProtectionStats` described below.
Class description:
Implementation of the 'ProtectionStats' model. Protection Statistics. Attributes: num_failed (int): Number of Failed Objects. num_objects (int): Number of Objects. size_bytes (long|int): Size in Bytes.
Method signatures and docstrings:
-... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ProtectionStats:
"""Implementation of the 'ProtectionStats' model. Protection Statistics. Attributes: num_failed (int): Number of Failed Objects. num_objects (int): Number of Objects. size_bytes (long|int): Size in Bytes."""
def __init__(self, num_failed=None, num_objects=None, size_bytes=No... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectionStats:
"""Implementation of the 'ProtectionStats' model. Protection Statistics. Attributes: num_failed (int): Number of Failed Objects. num_objects (int): Number of Objects. size_bytes (long|int): Size in Bytes."""
def __init__(self, num_failed=None, num_objects=None, size_bytes=None):
... | the_stack_v2_python_sparse | cohesity_management_sdk/models/protection_stats.py | cohesity/management-sdk-python | train | 24 |
e7c2346eb99219742a7d46c817bba1194fdc6313 | [
"dp = [[0] * len(l) for l in triangle]\ndp[0] = triangle[0]\nfor i in range(1, len(triangle)):\n for j in range(len(triangle[i])):\n l = dp[i - 1][j - 1] if j >= 1 else float('inf')\n m = dp[i - 1][j] if j < len(dp[i - 1]) else float('inf')\n ele = min(l, m)\n dp[i][j] = ele + triangl... | <|body_start_0|>
dp = [[0] * len(l) for l in triangle]
dp[0] = triangle[0]
for i in range(1, len(triangle)):
for j in range(len(triangle[i])):
l = dp[i - 1][j - 1] if j >= 1 else float('inf')
m = dp[i - 1][j] if j < len(dp[i - 1]) else float('inf')
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Dynamic Programming"""
<|body_0|>
def minimum_total(self, triangle):
"""Linear Space"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dp = [[0] * len(l) for l in triangle]
... | stack_v2_sparse_classes_36k_train_006761 | 1,014 | no_license | [
{
"docstring": "Dynamic Programming",
"name": "minimumTotal",
"signature": "def minimumTotal(self, triangle: List[List[int]]) -> int"
},
{
"docstring": "Linear Space",
"name": "minimum_total",
"signature": "def minimum_total(self, triangle)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: List[List[int]]) -> int: Dynamic Programming
- def minimum_total(self, triangle): Linear Space | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: List[List[int]]) -> int: Dynamic Programming
- def minimum_total(self, triangle): Linear Space
<|skeleton|>
class Solution:
def minimumTota... | 33252434f8d90b46fd2de07e257842331dcd81a8 | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Dynamic Programming"""
<|body_0|>
def minimum_total(self, triangle):
"""Linear Space"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Dynamic Programming"""
dp = [[0] * len(l) for l in triangle]
dp[0] = triangle[0]
for i in range(1, len(triangle)):
for j in range(len(triangle[i])):
l = dp[i - 1][j - 1] if j >= 1... | the_stack_v2_python_sparse | main/leetcode/120.py | dawnonme/Eureka | train | 0 | |
a184c10bc5a33f14401a45ca96bc88c0ee033b86 | [
"try:\n resp = Node().get_data_by_node_id(node_id)\n return masked_json_template(resp, 200)\nexcept:\n abort(400, 'Input unrecognizable.')",
"try:\n resp = Node().delete_data_by_node_id(node_id)\n return masked_json_template(resp, 200)\nexcept:\n abort(400, 'Input unrecognizable.')"
] | <|body_start_0|>
try:
resp = Node().get_data_by_node_id(node_id)
return masked_json_template(resp, 200)
except:
abort(400, 'Input unrecognizable.')
<|end_body_0|>
<|body_start_1|>
try:
resp = Node().delete_data_by_node_id(node_id)
retu... | NodeFindRoute | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeFindRoute:
def get(self, node_id):
"""Get Node data by Node ID"""
<|body_0|>
def delete(self, node_id):
"""Delete Node data by Node ID"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
resp = Node().get_data_by_node_id(node_id)
... | stack_v2_sparse_classes_36k_train_006762 | 4,218 | permissive | [
{
"docstring": "Get Node data by Node ID",
"name": "get",
"signature": "def get(self, node_id)"
},
{
"docstring": "Delete Node data by Node ID",
"name": "delete",
"signature": "def delete(self, node_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021255 | Implement the Python class `NodeFindRoute` described below.
Class description:
Implement the NodeFindRoute class.
Method signatures and docstrings:
- def get(self, node_id): Get Node data by Node ID
- def delete(self, node_id): Delete Node data by Node ID | Implement the Python class `NodeFindRoute` described below.
Class description:
Implement the NodeFindRoute class.
Method signatures and docstrings:
- def get(self, node_id): Get Node data by Node ID
- def delete(self, node_id): Delete Node data by Node ID
<|skeleton|>
class NodeFindRoute:
def get(self, node_id)... | 100fca0d2dd9b0b2ab2fa5974d8126af35ddcfd1 | <|skeleton|>
class NodeFindRoute:
def get(self, node_id):
"""Get Node data by Node ID"""
<|body_0|>
def delete(self, node_id):
"""Delete Node data by Node ID"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NodeFindRoute:
def get(self, node_id):
"""Get Node data by Node ID"""
try:
resp = Node().get_data_by_node_id(node_id)
return masked_json_template(resp, 200)
except:
abort(400, 'Input unrecognizable.')
def delete(self, node_id):
"""Delete... | the_stack_v2_python_sparse | app/controllers/api/node/node.py | ardihikaru/api-dashboard-5g-dive | train | 0 | |
92d21f23e8f986666ede4e10477e79a34ec5dd81 | [
"self.words = words\nself.temp_dict = {}\nfor i in range(len(words)):\n if words[i] not in self.temp_dict:\n self.temp_dict[words[i]] = [i]\n else:\n self.temp_dict[words[i]].append(i)",
"maxi = sys.maxint\nlist1 = self.temp_dict[word1]\nlist2 = self.temp_dict[word2]\nfor i in range(len(list1)... | <|body_start_0|>
self.words = words
self.temp_dict = {}
for i in range(len(words)):
if words[i] not in self.temp_dict:
self.temp_dict[words[i]] = [i]
else:
self.temp_dict[words[i]].append(i)
<|end_body_0|>
<|body_start_1|>
maxi = s... | WordDistance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.words = words
self.temp_... | stack_v2_sparse_classes_36k_train_006763 | 935 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortest(self, word1, word2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013132 | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int
<|skeleton|>
class WordDistance:
... | 2f53c4e16d244c83aad9b4d67a249f669b9da92a | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
self.words = words
self.temp_dict = {}
for i in range(len(words)):
if words[i] not in self.temp_dict:
self.temp_dict[words[i]] = [i]
else:
self.temp_dic... | the_stack_v2_python_sparse | prob244/shortest_word_distance2.py | sharath28/leetcode | train | 1 | |
397e735b5a62ed49e22c9d50970bc0f817a9cac2 | [
"self.data_feature = data_feature\nself.argmax_feature = argmax_feature\nself.argmin_feature = argmin_feature\nself.mask_data = mask_data",
"if self.mask_data:\n valid_data_mask = eopatch.mask['VALID_DATA']\nelse:\n valid_data_mask = eopatch.mask['IS_DATA']\nndvi = np.ma.array(eopatch.data[self.data_feature... | <|body_start_0|>
self.data_feature = data_feature
self.argmax_feature = argmax_feature
self.argmin_feature = argmin_feature
self.mask_data = mask_data
<|end_body_0|>
<|body_start_1|>
if self.mask_data:
valid_data_mask = eopatch.mask['VALID_DATA']
else:
... | Task to compute the argmax and argmin of the NDVI slope This task computes the slope of the NDVI feature using central differences. The NDVI feature can be masked using the `'VALID_DATA'` mask. Current implementation loops through every location of eopatch, and is therefore slow. The NDVI slope at date t is computed as... | AddMaxMinNDVISlopeIndicesTask | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddMaxMinNDVISlopeIndicesTask:
"""Task to compute the argmax and argmin of the NDVI slope This task computes the slope of the NDVI feature using central differences. The NDVI feature can be masked using the `'VALID_DATA'` mask. Current implementation loops through every location of eopatch, and i... | stack_v2_sparse_classes_36k_train_006764 | 10,624 | permissive | [
{
"docstring": "Task constructor :param data_feature: Name of data feature with NDVI values. Default is `'NDVI'` :param argmax_feature: Name of feature with computed argmax values of the NDVI slope :param argmin_feature: Name of feature with computed argmin values of the NDVI slope :param mask_data: Flag for ma... | 2 | stack_v2_sparse_classes_30k_train_019870 | Implement the Python class `AddMaxMinNDVISlopeIndicesTask` described below.
Class description:
Task to compute the argmax and argmin of the NDVI slope This task computes the slope of the NDVI feature using central differences. The NDVI feature can be masked using the `'VALID_DATA'` mask. Current implementation loops t... | Implement the Python class `AddMaxMinNDVISlopeIndicesTask` described below.
Class description:
Task to compute the argmax and argmin of the NDVI slope This task computes the slope of the NDVI feature using central differences. The NDVI feature can be masked using the `'VALID_DATA'` mask. Current implementation loops t... | a65899e4632b50c9c41a67e1f7698c09b929d840 | <|skeleton|>
class AddMaxMinNDVISlopeIndicesTask:
"""Task to compute the argmax and argmin of the NDVI slope This task computes the slope of the NDVI feature using central differences. The NDVI feature can be masked using the `'VALID_DATA'` mask. Current implementation loops through every location of eopatch, and i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddMaxMinNDVISlopeIndicesTask:
"""Task to compute the argmax and argmin of the NDVI slope This task computes the slope of the NDVI feature using central differences. The NDVI feature can be masked using the `'VALID_DATA'` mask. Current implementation loops through every location of eopatch, and is therefore s... | the_stack_v2_python_sparse | features/eolearn/features/temporal_features.py | sentinel-hub/eo-learn | train | 1,072 |
83c0a8247bca4eef0fd03dc5c97a2360a9fbdaab | [
"myHead = ListNode(0)\nmyHead.next = head\nfast, slow = (myHead, myHead)\nwhile fast and slow:\n fast = fast.next\n if fast == None:\n break\n fast = fast.next\n slow = slow.next\nreturn slow",
"if head == None:\n return head\np = head.next\nwhile p and p.next:\n tmp = p.next\n p.next ... | <|body_start_0|>
myHead = ListNode(0)
myHead.next = head
fast, slow = (myHead, myHead)
while fast and slow:
fast = fast.next
if fast == None:
break
fast = fast.next
slow = slow.next
return slow
<|end_body_0|>
<|body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMiddle(self, head):
"""找到中间节点"""
<|body_0|>
def myReverse(self, head):
"""head是头结点"""
<|body_1|>
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006765 | 1,227 | no_license | [
{
"docstring": "找到中间节点",
"name": "findMiddle",
"signature": "def findMiddle(self, head)"
},
{
"docstring": "head是头结点",
"name": "myReverse",
"signature": "def myReverse(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "isPalindrome",
"signature":... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMiddle(self, head): 找到中间节点
- def myReverse(self, head): head是头结点
- def isPalindrome(self, head): :type head: ListNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMiddle(self, head): 找到中间节点
- def myReverse(self, head): head是头结点
- def isPalindrome(self, head): :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:
def ... | 56e33dff3918e371f14d6f7ef03f8951056cc273 | <|skeleton|>
class Solution:
def findMiddle(self, head):
"""找到中间节点"""
<|body_0|>
def myReverse(self, head):
"""head是头结点"""
<|body_1|>
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMiddle(self, head):
"""找到中间节点"""
myHead = ListNode(0)
myHead.next = head
fast, slow = (myHead, myHead)
while fast and slow:
fast = fast.next
if fast == None:
break
fast = fast.next
slow = ... | the_stack_v2_python_sparse | accepted/Palindrome Linked List.py | hustlrr/leetcode | train | 4 | |
de550336b302414759beed9364981f8d19e27e0b | [
"ArgsUtils.addIfMissing('yLabel', 'Frequency', kwargs)\nsuper(Histogram, self).__init__(**kwargs)\nself.color = kwargs.get('color', 'b')\nself.binCount = kwargs.get('binCount', 100)\nself.data = kwargs.get('data', [])\nself.isLog = kwargs.get('isLog', False)",
"if not self.xLimits or not len(self.xLimits) == 2:\n... | <|body_start_0|>
ArgsUtils.addIfMissing('yLabel', 'Frequency', kwargs)
super(Histogram, self).__init__(**kwargs)
self.color = kwargs.get('color', 'b')
self.binCount = kwargs.get('binCount', 100)
self.data = kwargs.get('data', [])
self.isLog = kwargs.get('isLog', False)
<|... | A class for... | Histogram | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Histogram:
"""A class for..."""
def __init__(self, **kwargs):
"""Creates a new instance of Histogram."""
<|body_0|>
def shaveDataToXLimits(self):
"""shaveData doc..."""
<|body_1|>
def _plot(self):
"""_plot doc..."""
<|body_2|>
<|end_... | stack_v2_sparse_classes_36k_train_006766 | 2,345 | no_license | [
{
"docstring": "Creates a new instance of Histogram.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "shaveData doc...",
"name": "shaveDataToXLimits",
"signature": "def shaveDataToXLimits(self)"
},
{
"docstring": "_plot doc...",
"name": "_p... | 3 | stack_v2_sparse_classes_30k_train_021417 | Implement the Python class `Histogram` described below.
Class description:
A class for...
Method signatures and docstrings:
- def __init__(self, **kwargs): Creates a new instance of Histogram.
- def shaveDataToXLimits(self): shaveData doc...
- def _plot(self): _plot doc... | Implement the Python class `Histogram` described below.
Class description:
A class for...
Method signatures and docstrings:
- def __init__(self, **kwargs): Creates a new instance of Histogram.
- def shaveDataToXLimits(self): shaveData doc...
- def _plot(self): _plot doc...
<|skeleton|>
class Histogram:
"""A clas... | bcd0d80077c68cf4bb515d643e51f62dd6c4caaa | <|skeleton|>
class Histogram:
"""A class for..."""
def __init__(self, **kwargs):
"""Creates a new instance of Histogram."""
<|body_0|>
def shaveDataToXLimits(self):
"""shaveData doc..."""
<|body_1|>
def _plot(self):
"""_plot doc..."""
<|body_2|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Histogram:
"""A class for..."""
def __init__(self, **kwargs):
"""Creates a new instance of Histogram."""
ArgsUtils.addIfMissing('yLabel', 'Frequency', kwargs)
super(Histogram, self).__init__(**kwargs)
self.color = kwargs.get('color', 'b')
self.binCount = kwargs.get... | the_stack_v2_python_sparse | src/cadence/analysis/shared/plotting/Histogram.py | sernst/Cadence | train | 2 |
98cecb0e98adffa15e5dd566ed8507923ba97aeb | [
"self._encoder = encoder\nself._decoder = decoder\nself._rho = rho",
"posterior = self._encoder(input_data)\nsamples = self._encoder.sample(posterior, key)\nkls = jax.vmap(kl.kl_p_with_uniform_normal, [0])(posterior.mean, posterior.variance)\nrecons = self._decoder(samples)\ndata_fidelity = self._decoder.data_fid... | <|body_start_0|>
self._encoder = encoder
self._decoder = decoder
self._rho = rho
<|end_body_0|>
<|body_start_1|>
posterior = self._encoder(input_data)
samples = self._encoder.sample(posterior, key)
kls = jax.vmap(kl.kl_p_with_uniform_normal, [0])(posterior.mean, posterio... | VAE class. This class defines the ELBO used in training VAE models. It also adds function for forward passing data through VAE. | VAE | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VAE:
"""VAE class. This class defines the ELBO used in training VAE models. It also adds function for forward passing data through VAE."""
def __init__(self, encoder: encoders.EncoderBase, decoder: decoders.DecoderBase, rho: Optional[float]=None):
"""Class initializer. Args: encoder:... | stack_v2_sparse_classes_36k_train_006767 | 4,304 | permissive | [
{
"docstring": "Class initializer. Args: encoder: Encoder network architecture. decoder: Decoder network architecture. rho: Rho parameter used in AVAE training.",
"name": "__init__",
"signature": "def __init__(self, encoder: encoders.EncoderBase, decoder: decoders.DecoderBase, rho: Optional[float]=None)... | 4 | stack_v2_sparse_classes_30k_train_017170 | Implement the Python class `VAE` described below.
Class description:
VAE class. This class defines the ELBO used in training VAE models. It also adds function for forward passing data through VAE.
Method signatures and docstrings:
- def __init__(self, encoder: encoders.EncoderBase, decoder: decoders.DecoderBase, rho:... | Implement the Python class `VAE` described below.
Class description:
VAE class. This class defines the ELBO used in training VAE models. It also adds function for forward passing data through VAE.
Method signatures and docstrings:
- def __init__(self, encoder: encoders.EncoderBase, decoder: decoders.DecoderBase, rho:... | f5de0ede8430809180254ee957abf36ed62579ef | <|skeleton|>
class VAE:
"""VAE class. This class defines the ELBO used in training VAE models. It also adds function for forward passing data through VAE."""
def __init__(self, encoder: encoders.EncoderBase, decoder: decoders.DecoderBase, rho: Optional[float]=None):
"""Class initializer. Args: encoder:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VAE:
"""VAE class. This class defines the ELBO used in training VAE models. It also adds function for forward passing data through VAE."""
def __init__(self, encoder: encoders.EncoderBase, decoder: decoders.DecoderBase, rho: Optional[float]=None):
"""Class initializer. Args: encoder: Encoder netw... | the_stack_v2_python_sparse | avae/vae.py | vishalbelsare/deepmind-research | train | 0 |
0c4639094b8a36755da8e49221d6534073a69560 | [
"self.config = config\nself.name = name\nif len(rules_or_filters) == 0:\n raise ValueError('concept has one rule or filter at least', name)\nself.rules_or_filters = rules_or_filters\nself.concept_filters = concept_filters",
"results = Results()\nfor rule_or_filter in self.rules_or_filters:\n results.add(rul... | <|body_start_0|>
self.config = config
self.name = name
if len(rules_or_filters) == 0:
raise ValueError('concept has one rule or filter at least', name)
self.rules_or_filters = rules_or_filters
self.concept_filters = concept_filters
<|end_body_0|>
<|body_start_1|>
... | 概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ] | Concept | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Concept:
"""概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]"""
def __init__(self, config, name, rules_or_filters, conce... | stack_v2_sparse_classes_36k_train_006768 | 2,530 | no_license | [
{
"docstring": "初始化一个 Concept 对象 :param config: 包含配置信息的对象 :param name: 概念名称 :param rules_or_filters: 概念的匹配规则或规则过滤器, 规则与规则之间是 \"逻辑或\" 的操作, 即所有规则命中结果的集合 :param concept_filters: 概念过滤器, 用在所有的结果上进行过滤, 默认不存在",
"name": "__init__",
"signature": "def __init__(self, config, name, rules_or_filters, concept_filters... | 2 | stack_v2_sparse_classes_30k_train_013493 | Implement the Python class `Concept` described below.
Class description:
概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]
Method signatures and do... | Implement the Python class `Concept` described below.
Class description:
概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]
Method signatures and do... | 0d587707b0ecae5a321e8a394cc0cf96fcf58235 | <|skeleton|>
class Concept:
"""概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]"""
def __init__(self, config, name, rules_or_filters, conce... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Concept:
"""概念对象是规则的集合, 可以一定程度标定客观物理世界的一些通用规范. 例如, 我们规则中会大量使用到 "手机" 这个概念, 我们可以建立一个 "Phone" 的概念, 对应给它赋予一些规则来表征. concept_name = Phone rules = [ $kw("mobilephone"), $kw("phone"), $seq("mobile", "phone"), $ord(@d5, "my", "phone"), ... ]"""
def __init__(self, config, name, rules_or_filters, concept_filters=[]... | the_stack_v2_python_sparse | report_code/code/kme/concept/concept.py | Mi524/tools_copy | train | 0 |
e927e755cb0c0f1254686f1eb20a9446517bffe7 | [
"Muscle.__init__(self, params_, simulator)\nself.percent_slow_fiber = self.params['percent_slow_fiber'] if 'percent_slow_fiber' in self.params else 3.5\nself.f_05 = 0.36\nself.pcsa = 0.0 if 'pcsa' not in self.params else self.params['pcsa']\nself.l_ce = np.linalg.norm(self.app_point_1 - self.app_point_2)\nself.l_0 ... | <|body_start_0|>
Muscle.__init__(self, params_, simulator)
self.percent_slow_fiber = self.params['percent_slow_fiber'] if 'percent_slow_fiber' in self.params else 3.5
self.f_05 = 0.36
self.pcsa = 0.0 if 'pcsa' not in self.params else self.params['pcsa']
self.l_ce = np.linalg.norm... | BrownMuscle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrownMuscle:
def __init__(self, params_, simulator):
"""Class initialization. Mammalian Muscle Model for predicting force and energetics during physiological behavior Based on BROWN, CHENG and LOEB muscle models :param params_: Dictionary containing parameter for the muscle :param simula... | stack_v2_sparse_classes_36k_train_006769 | 4,770 | no_license | [
{
"docstring": "Class initialization. Mammalian Muscle Model for predicting force and energetics during physiological behavior Based on BROWN, CHENG and LOEB muscle models :param params_: Dictionary containing parameter for the muscle :param simulator: SimulatorUtils class to access utility functions",
"nam... | 5 | null | Implement the Python class `BrownMuscle` described below.
Class description:
Implement the BrownMuscle class.
Method signatures and docstrings:
- def __init__(self, params_, simulator): Class initialization. Mammalian Muscle Model for predicting force and energetics during physiological behavior Based on BROWN, CHENG... | Implement the Python class `BrownMuscle` described below.
Class description:
Implement the BrownMuscle class.
Method signatures and docstrings:
- def __init__(self, params_, simulator): Class initialization. Mammalian Muscle Model for predicting force and energetics during physiological behavior Based on BROWN, CHENG... | f4f212a7533a63d1148068bacf1cc13d3f64db49 | <|skeleton|>
class BrownMuscle:
def __init__(self, params_, simulator):
"""Class initialization. Mammalian Muscle Model for predicting force and energetics during physiological behavior Based on BROWN, CHENG and LOEB muscle models :param params_: Dictionary containing parameter for the muscle :param simula... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrownMuscle:
def __init__(self, params_, simulator):
"""Class initialization. Mammalian Muscle Model for predicting force and energetics during physiological behavior Based on BROWN, CHENG and LOEB muscle models :param params_: Dictionary containing parameter for the muscle :param simulator: Simulator... | the_stack_v2_python_sparse | src/musculoskeletals/muscles/brown.py | mahedjaved/mouse_locomotion | train | 0 | |
29075a4ee0a7d91237d1ab8e086703445c9d3509 | [
"should_exit = False\nwhile not should_exit:\n os.system('clear')\n RecoveryView.display_main_menu()\n user_input = RecoveryView.get_user_input('Choose an option: ')\n if user_input == '1':\n self.new_recovery_password_process()\n should_exit = True\n elif user_input == '2':\n sh... | <|body_start_0|>
should_exit = False
while not should_exit:
os.system('clear')
RecoveryView.display_main_menu()
user_input = RecoveryView.get_user_input('Choose an option: ')
if user_input == '1':
self.new_recovery_password_process()
... | RecoveryController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecoveryController:
def start(self):
"""Method starts RecoveryController loop :return: None"""
<|body_0|>
def new_recovery_password_process(self):
"""Method handles new password recovery process. :return: None"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_006770 | 2,012 | no_license | [
{
"docstring": "Method starts RecoveryController loop :return: None",
"name": "start",
"signature": "def start(self)"
},
{
"docstring": "Method handles new password recovery process. :return: None",
"name": "new_recovery_password_process",
"signature": "def new_recovery_password_process(... | 2 | stack_v2_sparse_classes_30k_train_020509 | Implement the Python class `RecoveryController` described below.
Class description:
Implement the RecoveryController class.
Method signatures and docstrings:
- def start(self): Method starts RecoveryController loop :return: None
- def new_recovery_password_process(self): Method handles new password recovery process. ... | Implement the Python class `RecoveryController` described below.
Class description:
Implement the RecoveryController class.
Method signatures and docstrings:
- def start(self): Method starts RecoveryController loop :return: None
- def new_recovery_password_process(self): Method handles new password recovery process. ... | fe152dc4a112f62572f2d7ccb74d293ea994ef9f | <|skeleton|>
class RecoveryController:
def start(self):
"""Method starts RecoveryController loop :return: None"""
<|body_0|>
def new_recovery_password_process(self):
"""Method handles new password recovery process. :return: None"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecoveryController:
def start(self):
"""Method starts RecoveryController loop :return: None"""
should_exit = False
while not should_exit:
os.system('clear')
RecoveryView.display_main_menu()
user_input = RecoveryView.get_user_input('Choose an option: ... | the_stack_v2_python_sparse | controllers/recovery_controller.py | KamilPchelka/CcMS-Aktywnosc | train | 0 | |
eec269b1d989d34ae5f80122a3d62ee2dd7fe227 | [
"v0 = Vertex()\nself.assertIsNot(v0, None)\nself.assertIsInstance(v0, Vertex)",
"v1 = Vertex([1, 2, 3])\nself.assertIsNot(v1, None)\nself.assertIsInstance(v1, Vertex)",
"t = Triangle()\nv = Vertex(t)\nself.assertIsInstance(v, Vertex)\nv_parents = v.parents()\nself.assertTrue(t in v_parents)"
] | <|body_start_0|>
v0 = Vertex()
self.assertIsNot(v0, None)
self.assertIsInstance(v0, Vertex)
<|end_body_0|>
<|body_start_1|>
v1 = Vertex([1, 2, 3])
self.assertIsNot(v1, None)
self.assertIsInstance(v1, Vertex)
<|end_body_1|>
<|body_start_2|>
t = Triangle()
... | Test Vertex class calls | TestConstructor_Vertex | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestConstructor_Vertex:
"""Test Vertex class calls"""
def test_none(self):
"""Calling Vertex class with no key (key = None)"""
<|body_0|>
def test_iterable_simple(self):
"""Calling Vertex class with key containing simple types"""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k_train_006771 | 11,224 | permissive | [
{
"docstring": "Calling Vertex class with no key (key = None)",
"name": "test_none",
"signature": "def test_none(self)"
},
{
"docstring": "Calling Vertex class with key containing simple types",
"name": "test_iterable_simple",
"signature": "def test_iterable_simple(self)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_020987 | Implement the Python class `TestConstructor_Vertex` described below.
Class description:
Test Vertex class calls
Method signatures and docstrings:
- def test_none(self): Calling Vertex class with no key (key = None)
- def test_iterable_simple(self): Calling Vertex class with key containing simple types
- def test_iter... | Implement the Python class `TestConstructor_Vertex` described below.
Class description:
Test Vertex class calls
Method signatures and docstrings:
- def test_none(self): Calling Vertex class with no key (key = None)
- def test_iterable_simple(self): Calling Vertex class with key containing simple types
- def test_iter... | f9b00a39bc16aea4abac60c0dd0aab2acac5adcf | <|skeleton|>
class TestConstructor_Vertex:
"""Test Vertex class calls"""
def test_none(self):
"""Calling Vertex class with no key (key = None)"""
<|body_0|>
def test_iterable_simple(self):
"""Calling Vertex class with key containing simple types"""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestConstructor_Vertex:
"""Test Vertex class calls"""
def test_none(self):
"""Calling Vertex class with no key (key = None)"""
v0 = Vertex()
self.assertIsNot(v0, None)
self.assertIsInstance(v0, Vertex)
def test_iterable_simple(self):
"""Calling Vertex class wi... | the_stack_v2_python_sparse | _BACKUPS_V4/v4_5/LightPicture_Test.py | nagame/LightPicture | train | 0 |
920f1e4b5a646ca7afb81ae72530b5918d9d973e | [
"self.__func = func\nself.__args = args\nself.__kwargs = kwargs\nself.__mutex = _thread.allocate_lock()\nself.__mutex.acquire()",
"try:\n self.__value = self.__func(*self.__args, **self.__kwargs)\n self.__error = False\nexcept:\n self.__value = sys.exc_info()[1]\n self.__error = True\nself.__mutex.rel... | <|body_start_0|>
self.__func = func
self.__args = args
self.__kwargs = kwargs
self.__mutex = _thread.allocate_lock()
self.__mutex.acquire()
<|end_body_0|>
<|body_start_1|>
try:
self.__value = self.__func(*self.__args, **self.__kwargs)
self.__error... | _Delegate(func, args, kwargs) -> _Delegate instance | _Delegate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Delegate:
"""_Delegate(func, args, kwargs) -> _Delegate instance"""
def __init__(self, func, args, kwargs):
"""Initializes instance from arguments and prepares to run."""
<|body_0|>
def __call__(self):
"""Executes code with arguments and allows value retrieval."... | stack_v2_sparse_classes_36k_train_006772 | 2,633 | permissive | [
{
"docstring": "Initializes instance from arguments and prepares to run.",
"name": "__init__",
"signature": "def __init__(self, func, args, kwargs)"
},
{
"docstring": "Executes code with arguments and allows value retrieval.",
"name": "__call__",
"signature": "def __call__(self)"
},
... | 3 | null | Implement the Python class `_Delegate` described below.
Class description:
_Delegate(func, args, kwargs) -> _Delegate instance
Method signatures and docstrings:
- def __init__(self, func, args, kwargs): Initializes instance from arguments and prepares to run.
- def __call__(self): Executes code with arguments and all... | Implement the Python class `_Delegate` described below.
Class description:
_Delegate(func, args, kwargs) -> _Delegate instance
Method signatures and docstrings:
- def __init__(self, func, args, kwargs): Initializes instance from arguments and prepares to run.
- def __call__(self): Executes code with arguments and all... | d097ca0ad6a6aee2180d32dce6a3322621f655fd | <|skeleton|>
class _Delegate:
"""_Delegate(func, args, kwargs) -> _Delegate instance"""
def __init__(self, func, args, kwargs):
"""Initializes instance from arguments and prepares to run."""
<|body_0|>
def __call__(self):
"""Executes code with arguments and allows value retrieval."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _Delegate:
"""_Delegate(func, args, kwargs) -> _Delegate instance"""
def __init__(self, func, args, kwargs):
"""Initializes instance from arguments and prepares to run."""
self.__func = func
self.__args = args
self.__kwargs = kwargs
self.__mutex = _thread.allocate_... | the_stack_v2_python_sparse | recipes/Python/578151_affinitypy/recipe-578151.py | betty29/code-1 | train | 0 |
dd28f16740bfda2e2604876bc1ecb820a9fe167b | [
"self.config = None\nself._com_ports_list = None\nself._default_com_port = None",
"errors = {}\nif self._com_ports_list is None:\n result = await self.hass.async_add_executor_job(scan_comports)\n self._com_ports_list, self._default_com_port = result\n if self._default_com_port is None:\n return se... | <|body_start_0|>
self.config = None
self._com_ports_list = None
self._default_com_port = None
<|end_body_0|>
<|body_start_1|>
errors = {}
if self._com_ports_list is None:
result = await self.hass.async_add_executor_job(scan_comports)
self._com_ports_list,... | Handle a config flow for Aurora ABB PowerOne. | AuroraABBConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuroraABBConfigFlow:
"""Handle a config flow for Aurora ABB PowerOne."""
def __init__(self):
"""Initialise the config flow."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle a flow initialised by the us... | stack_v2_sparse_classes_36k_train_006773 | 4,922 | permissive | [
{
"docstring": "Initialise the config flow.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Handle a flow initialised by the user.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult"
... | 2 | null | Implement the Python class `AuroraABBConfigFlow` described below.
Class description:
Handle a config flow for Aurora ABB PowerOne.
Method signatures and docstrings:
- def __init__(self): Initialise the config flow.
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle a flow ... | Implement the Python class `AuroraABBConfigFlow` described below.
Class description:
Handle a config flow for Aurora ABB PowerOne.
Method signatures and docstrings:
- def __init__(self): Initialise the config flow.
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle a flow ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AuroraABBConfigFlow:
"""Handle a config flow for Aurora ABB PowerOne."""
def __init__(self):
"""Initialise the config flow."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle a flow initialised by the us... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuroraABBConfigFlow:
"""Handle a config flow for Aurora ABB PowerOne."""
def __init__(self):
"""Initialise the config flow."""
self.config = None
self._com_ports_list = None
self._default_com_port = None
async def async_step_user(self, user_input: dict[str, Any] | Non... | the_stack_v2_python_sparse | homeassistant/components/aurora_abb_powerone/config_flow.py | home-assistant/core | train | 35,501 |
c0e1b08ce0019bd16c1f94cbde79331a1ef3a130 | [
"self.p = collections.defaultdict(list)\nfor i, w in enumerate(words):\n self.p[w].append(i)",
"l1, l2 = (self.p[word1], self.p[word2])\np1, p2 = (0, 0)\nd = sys.maxsize\nwhile p1 < len(l1) and p2 < len(l2):\n d = min(d, abs(l1[p1] - l2[p2]))\n if l1[p1] < l2[p2]:\n p1 += 1\n else:\n p2 ... | <|body_start_0|>
self.p = collections.defaultdict(list)
for i, w in enumerate(words):
self.p[w].append(i)
<|end_body_0|>
<|body_start_1|>
l1, l2 = (self.p[word1], self.p[word2])
p1, p2 = (0, 0)
d = sys.maxsize
while p1 < len(l1) and p2 < len(l2):
... | WordDistance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words: List[str]):
"""Running Time: O(n) where n is the length of words."""
<|body_0|>
def shortest(self, word1: str, word2: str) -> int:
"""Running Time: O(m) where m is the sum of appearance of word1 and word2 in the original words ... | stack_v2_sparse_classes_36k_train_006774 | 738 | permissive | [
{
"docstring": "Running Time: O(n) where n is the length of words.",
"name": "__init__",
"signature": "def __init__(self, words: List[str])"
},
{
"docstring": "Running Time: O(m) where m is the sum of appearance of word1 and word2 in the original words list.",
"name": "shortest",
"signat... | 2 | null | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words: List[str]): Running Time: O(n) where n is the length of words.
- def shortest(self, word1: str, word2: str) -> int: Running Time: O(m) where m i... | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words: List[str]): Running Time: O(n) where n is the length of words.
- def shortest(self, word1: str, word2: str) -> int: Running Time: O(m) where m i... | 4a508a982b125a3a90ea893ae70863df7c99cc70 | <|skeleton|>
class WordDistance:
def __init__(self, words: List[str]):
"""Running Time: O(n) where n is the length of words."""
<|body_0|>
def shortest(self, word1: str, word2: str) -> int:
"""Running Time: O(m) where m is the sum of appearance of word1 and word2 in the original words ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words: List[str]):
"""Running Time: O(n) where n is the length of words."""
self.p = collections.defaultdict(list)
for i, w in enumerate(words):
self.p[w].append(i)
def shortest(self, word1: str, word2: str) -> int:
"""Running T... | the_stack_v2_python_sparse | solutions/244_shortest_word_distance_ii.py | YiqunPeng/leetcode_pro | train | 0 | |
dad213cb4430af087a0f19a090febe04be542649 | [
"self.Wh = np.random.randn(i + h, h)\nself.Wy = np.random.randn(h, o)\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"concat = np.concatenate((h_prev, x_t), axis=1)\nh_next = np.tanh(concat @ self.Wh + self.bh)\nsoft = h_next @ self.Wy + self.by\ny = np.exp(soft) / np.sum(np.exp(soft), axis=1, keepdims... | <|body_start_0|>
self.Wh = np.random.randn(i + h, h)
self.Wy = np.random.randn(h, o)
self.bh = np.zeros((1, h))
self.by = np.zeros((1, o))
<|end_body_0|>
<|body_start_1|>
concat = np.concatenate((h_prev, x_t), axis=1)
h_next = np.tanh(concat @ self.Wh + self.bh)
... | Represents a cell of a simple RNN | RNNCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNCell:
"""Represents a cell of a simple RNN"""
def __init__(self, i, h, o):
"""Class constructor"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Performs forward propagation for one time step. Returns: h_next, y"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_006775 | 1,066 | no_license | [
{
"docstring": "Class constructor",
"name": "__init__",
"signature": "def __init__(self, i, h, o)"
},
{
"docstring": "Performs forward propagation for one time step. Returns: h_next, y",
"name": "forward",
"signature": "def forward(self, h_prev, x_t)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001356 | Implement the Python class `RNNCell` described below.
Class description:
Represents a cell of a simple RNN
Method signatures and docstrings:
- def __init__(self, i, h, o): Class constructor
- def forward(self, h_prev, x_t): Performs forward propagation for one time step. Returns: h_next, y | Implement the Python class `RNNCell` described below.
Class description:
Represents a cell of a simple RNN
Method signatures and docstrings:
- def __init__(self, i, h, o): Class constructor
- def forward(self, h_prev, x_t): Performs forward propagation for one time step. Returns: h_next, y
<|skeleton|>
class RNNCell... | 161e33b23d398d7d01ad0d7740b78dda3f27e787 | <|skeleton|>
class RNNCell:
"""Represents a cell of a simple RNN"""
def __init__(self, i, h, o):
"""Class constructor"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Performs forward propagation for one time step. Returns: h_next, y"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNCell:
"""Represents a cell of a simple RNN"""
def __init__(self, i, h, o):
"""Class constructor"""
self.Wh = np.random.randn(i + h, h)
self.Wy = np.random.randn(h, o)
self.bh = np.zeros((1, h))
self.by = np.zeros((1, o))
def forward(self, h_prev, x_t):
... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/0-rnn_cell.py | felipeserna/holbertonschool-machine_learning | train | 0 |
8ce8a2ca00e9a3a64f0357fea66d4451de94b78a | [
"total, dir_infos = self.job_manager.get_job_list(offset=offset, limit=limit)\njob_infos = [self._dir_2_info(dir_info) for dir_info in dir_infos]\nreturn (total, job_infos)",
"job = self.job_manager.get_job(train_id)\nif job is None:\n raise TrainJobNotExistError(train_id)\nreturn self._job_2_meta(job)",
"in... | <|body_start_0|>
total, dir_infos = self.job_manager.get_job_list(offset=offset, limit=limit)
job_infos = [self._dir_2_info(dir_info) for dir_info in dir_infos]
return (total, job_infos)
<|end_body_0|>
<|body_start_1|>
job = self.job_manager.get_job(train_id)
if job is None:
... | Explain job list encapsulator. | ExplainJobEncap | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExplainJobEncap:
"""Explain job list encapsulator."""
def query_explain_jobs(self, offset, limit):
"""Query explain job list. Args: offset (int): Page offset. limit (int): Maximum number of items to be returned. Returns: tuple[int, list[Dict]], total number of jobs and job list."""
... | stack_v2_sparse_classes_36k_train_006776 | 3,607 | permissive | [
{
"docstring": "Query explain job list. Args: offset (int): Page offset. limit (int): Maximum number of items to be returned. Returns: tuple[int, list[Dict]], total number of jobs and job list.",
"name": "query_explain_jobs",
"signature": "def query_explain_jobs(self, offset, limit)"
},
{
"docst... | 5 | stack_v2_sparse_classes_30k_train_007669 | Implement the Python class `ExplainJobEncap` described below.
Class description:
Explain job list encapsulator.
Method signatures and docstrings:
- def query_explain_jobs(self, offset, limit): Query explain job list. Args: offset (int): Page offset. limit (int): Maximum number of items to be returned. Returns: tuple[... | Implement the Python class `ExplainJobEncap` described below.
Class description:
Explain job list encapsulator.
Method signatures and docstrings:
- def query_explain_jobs(self, offset, limit): Query explain job list. Args: offset (int): Page offset. limit (int): Maximum number of items to be returned. Returns: tuple[... | a774d893fb2f21dbc3edb5cd89f9e6eec274ebf1 | <|skeleton|>
class ExplainJobEncap:
"""Explain job list encapsulator."""
def query_explain_jobs(self, offset, limit):
"""Query explain job list. Args: offset (int): Page offset. limit (int): Maximum number of items to be returned. Returns: tuple[int, list[Dict]], total number of jobs and job list."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExplainJobEncap:
"""Explain job list encapsulator."""
def query_explain_jobs(self, offset, limit):
"""Query explain job list. Args: offset (int): Page offset. limit (int): Maximum number of items to be returned. Returns: tuple[int, list[Dict]], total number of jobs and job list."""
total,... | the_stack_v2_python_sparse | mindinsight/explainer/encapsulator/explain_job_encap.py | mindspore-ai/mindinsight | train | 224 |
62c0f0c1b2372e504e976537e9269c7f09445f23 | [
"res = []\nif not root:\n return res\n\ndef serialize_dfs(root):\n if not root:\n res.append('null')\n return\n res.append(root.val)\n serialize_dfs(root.left)\n serialize_dfs(root.right)\nserialize_dfs(root)\nreturn res",
"if not data:\n return []\nindex = [0]\n\ndef deserialize_d... | <|body_start_0|>
res = []
if not root:
return res
def serialize_dfs(root):
if not root:
res.append('null')
return
res.append(root.val)
serialize_dfs(root.left)
serialize_dfs(root.right)
serialize... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_006777 | 1,868 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | a8518964df9dd04d9d06ada1f6814897d6451edb | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = []
if not root:
return res
def serialize_dfs(root):
if not root:
res.append('null')
return
res.... | the_stack_v2_python_sparse | bianryTree/37_serialize_deserialize_tree_hard.py | nadong/leetcode | train | 0 | |
2cfc6c9190fb3f10d5e62af4f94e85e5a5a431b8 | [
"from agilo.scrum.workflow import rules\nfor member in dir(rules):\n if type(member) == type and issubclass(member, Component):\n member(self.env)",
"debug(self, 'Called validate_rules(%s)' % ticket)\nfor r in self.rules:\n r.validate(ticket)"
] | <|body_start_0|>
from agilo.scrum.workflow import rules
for member in dir(rules):
if type(member) == type and issubclass(member, Component):
member(self.env)
<|end_body_0|>
<|body_start_1|>
debug(self, 'Called validate_rules(%s)' % ticket)
for r in self.rules... | Used to check that all the business rules are met before completing an operation. The RuleEngine has different domains where the rules applies and can be called from the specific object when is saved | RuleEngine | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RuleEngine:
"""Used to check that all the business rules are met before completing an operation. The RuleEngine has different domains where the rules applies and can be called from the specific object when is saved"""
def __init__(self):
"""Make sure that all the rules are instantiat... | stack_v2_sparse_classes_36k_train_006778 | 2,197 | no_license | [
{
"docstring": "Make sure that all the rules are instantiated and registered",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Validates the give ticket against the registered rules. Every rule will be validated and has to take care of all the checks, return True or Fals... | 2 | null | Implement the Python class `RuleEngine` described below.
Class description:
Used to check that all the business rules are met before completing an operation. The RuleEngine has different domains where the rules applies and can be called from the specific object when is saved
Method signatures and docstrings:
- def __... | Implement the Python class `RuleEngine` described below.
Class description:
Used to check that all the business rules are met before completing an operation. The RuleEngine has different domains where the rules applies and can be called from the specific object when is saved
Method signatures and docstrings:
- def __... | 1059b76554363004887b2a60953957f413b80bb0 | <|skeleton|>
class RuleEngine:
"""Used to check that all the business rules are met before completing an operation. The RuleEngine has different domains where the rules applies and can be called from the specific object when is saved"""
def __init__(self):
"""Make sure that all the rules are instantiat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RuleEngine:
"""Used to check that all the business rules are met before completing an operation. The RuleEngine has different domains where the rules applies and can be called from the specific object when is saved"""
def __init__(self):
"""Make sure that all the rules are instantiated and regist... | the_stack_v2_python_sparse | agilo/scrum/workflow/api.py | djangsters/agilo | train | 0 |
93c2a19630fc4ac0443167238cd4246ab2a8b58b | [
"super(CredentialDialog, self).__init__()\nself.askpassword = askpassword\nself.initUI(context)",
"self.formlayout = QtWidgets.QFormLayout(self)\nself.username_le = QtWidgets.QLineEdit(self)\nself.username_le.returnPressed.connect(self.accept)\nif self.askpassword:\n self.formlayout.addRow('Användarnamn:', sel... | <|body_start_0|>
super(CredentialDialog, self).__init__()
self.askpassword = askpassword
self.initUI(context)
<|end_body_0|>
<|body_start_1|>
self.formlayout = QtWidgets.QFormLayout(self)
self.username_le = QtWidgets.QLineEdit(self)
self.username_le.returnPressed.connect... | Asks for credentials. | CredentialDialog | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CredentialDialog:
"""Asks for credentials."""
def __init__(self, context='', askpassword=True):
"""Creates a dialog that asks for username and optionally password."""
<|body_0|>
def initUI(self, context):
"""Creates the UI widgets. context -- String to set as win... | stack_v2_sparse_classes_36k_train_006779 | 15,052 | permissive | [
{
"docstring": "Creates a dialog that asks for username and optionally password.",
"name": "__init__",
"signature": "def __init__(self, context='', askpassword=True)"
},
{
"docstring": "Creates the UI widgets. context -- String to set as windowtitle.",
"name": "initUI",
"signature": "def... | 3 | stack_v2_sparse_classes_30k_train_014756 | Implement the Python class `CredentialDialog` described below.
Class description:
Asks for credentials.
Method signatures and docstrings:
- def __init__(self, context='', askpassword=True): Creates a dialog that asks for username and optionally password.
- def initUI(self, context): Creates the UI widgets. context --... | Implement the Python class `CredentialDialog` described below.
Class description:
Asks for credentials.
Method signatures and docstrings:
- def __init__(self, context='', askpassword=True): Creates a dialog that asks for username and optionally password.
- def initUI(self, context): Creates the UI widgets. context --... | b9aeca845d65d6de07b3dbef4dafccacc6a81cc4 | <|skeleton|>
class CredentialDialog:
"""Asks for credentials."""
def __init__(self, context='', askpassword=True):
"""Creates a dialog that asks for username and optionally password."""
<|body_0|>
def initUI(self, context):
"""Creates the UI widgets. context -- String to set as win... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CredentialDialog:
"""Asks for credentials."""
def __init__(self, context='', askpassword=True):
"""Creates a dialog that asks for username and optionally password."""
super(CredentialDialog, self).__init__()
self.askpassword = askpassword
self.initUI(context)
def init... | the_stack_v2_python_sparse | passwordsafe.py | Teknologforeningen/svaksvat | train | 0 |
46850c8332c1f12a8f83b9b691ffedd863f2c29d | [
"try:\n return self.load_cached_obj('native.coordinates')\nexcept:\n pass\nds = self.dataset\nbase_date = ds['time'].attributes['units']\nbase_date = self.date_url_re.search(base_date).group()\ntimes = ds['time'][:].astype('timedelta64[h]') + np.array(base_date, 'datetime64')\nlons = podpac.crange(ds['lon'][0... | <|body_start_0|>
try:
return self.load_cached_obj('native.coordinates')
except:
pass
ds = self.dataset
base_date = ds['time'].attributes['units']
base_date = self.date_url_re.search(base_date).group()
times = ds['time'][:].astype('timedelta64[h]') ... | Summary Attributes ---------- datakey : TYPE Description date_url_re : TYPE Description nan_vals : list Description product : TYPE Description | AirMOSS_Source | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AirMOSS_Source:
"""Summary Attributes ---------- datakey : TYPE Description date_url_re : TYPE Description nan_vals : list Description product : TYPE Description"""
def get_native_coordinates(self):
"""Summary Returns ------- TYPE Description"""
<|body_0|>
def get_data(s... | stack_v2_sparse_classes_36k_train_006780 | 5,736 | permissive | [
{
"docstring": "Summary Returns ------- TYPE Description",
"name": "get_native_coordinates",
"signature": "def get_native_coordinates(self)"
},
{
"docstring": "Summary Parameters ---------- coordinates : TYPE Description coordinates_index : TYPE Description Returns ------- TYPE Description",
... | 2 | stack_v2_sparse_classes_30k_train_003620 | Implement the Python class `AirMOSS_Source` described below.
Class description:
Summary Attributes ---------- datakey : TYPE Description date_url_re : TYPE Description nan_vals : list Description product : TYPE Description
Method signatures and docstrings:
- def get_native_coordinates(self): Summary Returns ------- T... | Implement the Python class `AirMOSS_Source` described below.
Class description:
Summary Attributes ---------- datakey : TYPE Description date_url_re : TYPE Description nan_vals : list Description product : TYPE Description
Method signatures and docstrings:
- def get_native_coordinates(self): Summary Returns ------- T... | 0a96a9b3726aee9bb6208244ae96ed685667e16c | <|skeleton|>
class AirMOSS_Source:
"""Summary Attributes ---------- datakey : TYPE Description date_url_re : TYPE Description nan_vals : list Description product : TYPE Description"""
def get_native_coordinates(self):
"""Summary Returns ------- TYPE Description"""
<|body_0|>
def get_data(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AirMOSS_Source:
"""Summary Attributes ---------- datakey : TYPE Description date_url_re : TYPE Description nan_vals : list Description product : TYPE Description"""
def get_native_coordinates(self):
"""Summary Returns ------- TYPE Description"""
try:
return self.load_cached_ob... | the_stack_v2_python_sparse | podpac/datalib/airmoss.py | ccuadrado/podpac | train | 0 |
38f3a4f431116540174ad959300bfcbb07efd330 | [
"self._source = source\nself._time_provider = time_provider\nself._storage_engine = storage_engine",
"if slack_task.archived:\n return\nasync with self._storage_engine.get_unit_of_work() as uow:\n slack_task_collection = await uow.slack_task_collection_repository.load_by_id(slack_task.slack_task_collection_... | <|body_start_0|>
self._source = source
self._time_provider = time_provider
self._storage_engine = storage_engine
<|end_body_0|>
<|body_start_1|>
if slack_task.archived:
return
async with self._storage_engine.get_unit_of_work() as uow:
slack_task_collectio... | Shared service for archiving a slack task. | SlackTaskArchiveService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlackTaskArchiveService:
"""Shared service for archiving a slack task."""
def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None:
"""Constructor."""
<|body_0|>
async def do_it(self, progress_reporter: ProgressRep... | stack_v2_sparse_classes_36k_train_006781 | 2,869 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None"
},
{
"docstring": "Execute the service's action.",
"name": "do_it",
"signature": "async def do_it(self, prog... | 2 | stack_v2_sparse_classes_30k_test_001160 | Implement the Python class `SlackTaskArchiveService` described below.
Class description:
Shared service for archiving a slack task.
Method signatures and docstrings:
- def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None: Constructor.
- async def do_it(self... | Implement the Python class `SlackTaskArchiveService` described below.
Class description:
Shared service for archiving a slack task.
Method signatures and docstrings:
- def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None: Constructor.
- async def do_it(self... | 911ecd560142a9b4e57498f2b090f9469a0718a1 | <|skeleton|>
class SlackTaskArchiveService:
"""Shared service for archiving a slack task."""
def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None:
"""Constructor."""
<|body_0|>
async def do_it(self, progress_reporter: ProgressRep... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SlackTaskArchiveService:
"""Shared service for archiving a slack task."""
def __init__(self, source: EventSource, time_provider: TimeProvider, storage_engine: DomainStorageEngine) -> None:
"""Constructor."""
self._source = source
self._time_provider = time_provider
self._s... | the_stack_v2_python_sparse | src/core/jupiter/core/domain/push_integrations/slack/service/archive_service.py | horia141/jupiter | train | 16 |
6f8b53ce430263f3a32bdc8fd6619c31e4562dea | [
"if cls.instance is None:\n cls.instance = super().__new__(cls)\nreturn cls.instance",
"self.host = host\nself.username = username\nself.password = password\nself.database = database\nself.port = port\nself.maxconn = maxconn\nself.pool = Queue(maxconn)\ntry:\n for x in range(maxconn):\n conn = pymysq... | <|body_start_0|>
if cls.instance is None:
cls.instance = super().__new__(cls)
return cls.instance
<|end_body_0|>
<|body_start_1|>
self.host = host
self.username = username
self.password = password
self.database = database
self.port = port
self... | 定义MySQL操作类 使用单例模式 构建链接池 | MySQL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySQL:
"""定义MySQL操作类 使用单例模式 构建链接池"""
def __new__(cls, *args, **kwargs):
"""对new方法进行重写，实现单例模式 :param args: :param kwargs:"""
<|body_0|>
def __init__(self, host, username, password, database, port, maxconn=5):
"""初始化数据库信息并创建数据库链接池"""
<|body_1|>
def de_... | stack_v2_sparse_classes_36k_train_006782 | 2,664 | no_license | [
{
"docstring": "对new方法进行重写，实现单例模式 :param args: :param kwargs:",
"name": "__new__",
"signature": "def __new__(cls, *args, **kwargs)"
},
{
"docstring": "初始化数据库信息并创建数据库链接池",
"name": "__init__",
"signature": "def __init__(self, host, username, password, database, port, maxconn=5)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_003479 | Implement the Python class `MySQL` described below.
Class description:
定义MySQL操作类 使用单例模式 构建链接池
Method signatures and docstrings:
- def __new__(cls, *args, **kwargs): 对new方法进行重写，实现单例模式 :param args: :param kwargs:
- def __init__(self, host, username, password, database, port, maxconn=5): 初始化数据库信息并创建数据库链接池
- def de_dupl... | Implement the Python class `MySQL` described below.
Class description:
定义MySQL操作类 使用单例模式 构建链接池
Method signatures and docstrings:
- def __new__(cls, *args, **kwargs): 对new方法进行重写，实现单例模式 :param args: :param kwargs:
- def __init__(self, host, username, password, database, port, maxconn=5): 初始化数据库信息并创建数据库链接池
- def de_dupl... | 6f138a7a4eaaa0892986be07232d68defeafaeb6 | <|skeleton|>
class MySQL:
"""定义MySQL操作类 使用单例模式 构建链接池"""
def __new__(cls, *args, **kwargs):
"""对new方法进行重写，实现单例模式 :param args: :param kwargs:"""
<|body_0|>
def __init__(self, host, username, password, database, port, maxconn=5):
"""初始化数据库信息并创建数据库链接池"""
<|body_1|>
def de_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MySQL:
"""定义MySQL操作类 使用单例模式 构建链接池"""
def __new__(cls, *args, **kwargs):
"""对new方法进行重写，实现单例模式 :param args: :param kwargs:"""
if cls.instance is None:
cls.instance = super().__new__(cls)
return cls.instance
def __init__(self, host, username, password, database, port... | the_stack_v2_python_sparse | DataBaseHandler/mysql_handle.py | zeze-ya/12306Train_Info_Spider | train | 1 |
b963a97531d82a23abf230fccbda536070e0f719 | [
"self.__class__.__name__ = 'Contingency' + measures.__class__.__name__\nfor k in dir(measures):\n if k.startswith('__'):\n continue\n v = getattr(measures, k)\n if not k.startswith('_'):\n v = self._make_contingency_fn(measures, v)\n setattr(self, k, v)",
"def res(*contingency):\n ret... | <|body_start_0|>
self.__class__.__name__ = 'Contingency' + measures.__class__.__name__
for k in dir(measures):
if k.startswith('__'):
continue
v = getattr(measures, k)
if not k.startswith('_'):
v = self._make_contingency_fn(measures, v)... | Wraps NgramAssocMeasures classes such that the arguments of association measures are contingency table values rather than marginals. | ContingencyMeasures | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"CC-BY-NC-ND-3.0",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContingencyMeasures:
"""Wraps NgramAssocMeasures classes such that the arguments of association measures are contingency table values rather than marginals."""
def __init__(self, measures):
"""Constructs a ContingencyMeasures given a NgramAssocMeasures class"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_006783 | 16,093 | permissive | [
{
"docstring": "Constructs a ContingencyMeasures given a NgramAssocMeasures class",
"name": "__init__",
"signature": "def __init__(self, measures)"
},
{
"docstring": "From an association measure function, produces a new function which accepts contingency table values as its arguments.",
"nam... | 2 | stack_v2_sparse_classes_30k_train_016527 | Implement the Python class `ContingencyMeasures` described below.
Class description:
Wraps NgramAssocMeasures classes such that the arguments of association measures are contingency table values rather than marginals.
Method signatures and docstrings:
- def __init__(self, measures): Constructs a ContingencyMeasures g... | Implement the Python class `ContingencyMeasures` described below.
Class description:
Wraps NgramAssocMeasures classes such that the arguments of association measures are contingency table values rather than marginals.
Method signatures and docstrings:
- def __init__(self, measures): Constructs a ContingencyMeasures g... | 582e6e35f0e6c984b44ec49dcb8846d9c011d0a8 | <|skeleton|>
class ContingencyMeasures:
"""Wraps NgramAssocMeasures classes such that the arguments of association measures are contingency table values rather than marginals."""
def __init__(self, measures):
"""Constructs a ContingencyMeasures given a NgramAssocMeasures class"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContingencyMeasures:
"""Wraps NgramAssocMeasures classes such that the arguments of association measures are contingency table values rather than marginals."""
def __init__(self, measures):
"""Constructs a ContingencyMeasures given a NgramAssocMeasures class"""
self.__class__.__name__ = '... | the_stack_v2_python_sparse | nltk/metrics/association.py | nltk/nltk | train | 11,860 |
adfd4be4369ecdcf001509ea48feebc1ffc3758d | [
"if data is None:\n if lambtha < 1:\n raise ValueError('lambtha must be a positive value')\n else:\n self.lambtha = float(lambtha)\nelif type(data) is not list:\n raise TypeError('data must be a list')\nelif len(data) < 2:\n raise ValueError('data must contain multiple values')\nelse:\n ... | <|body_start_0|>
if data is None:
if lambtha < 1:
raise ValueError('lambtha must be a positive value')
else:
self.lambtha = float(lambtha)
elif type(data) is not list:
raise TypeError('data must be a list')
elif len(data) < 2:
... | class that represents exponential distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pdf(self, x): calculates PDF for given time period def cdf(self, x): calculates CDF for given time per... | Exponential | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exponential:
"""class that represents exponential distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pdf(self, x): calculates PDF for given time period def cdf(self... | stack_v2_sparse_classes_36k_train_006784 | 2,503 | no_license | [
{
"docstring": "class constructor parameters: data [list]: data to be used to estimate the distibution lambtha [float]: the expected number of occurances on a given time Sets the instance attribute lambtha as a float If data is not given: Use the given lambtha or raise ValueError if lambtha is not positive valu... | 3 | stack_v2_sparse_classes_30k_train_012897 | Implement the Python class `Exponential` described below.
Class description:
class that represents exponential distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pdf(self, x): calculates... | Implement the Python class `Exponential` described below.
Class description:
class that represents exponential distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pdf(self, x): calculates... | 8834b201ca84937365e4dcc0fac978656cdf5293 | <|skeleton|>
class Exponential:
"""class that represents exponential distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pdf(self, x): calculates PDF for given time period def cdf(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exponential:
"""class that represents exponential distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pdf(self, x): calculates PDF for given time period def cdf(self, x): calcula... | the_stack_v2_python_sparse | math/0x03-probability/exponential.py | ejonakodra/holbertonschool-machine_learning-1 | train | 0 |
4aded413d52144df720fc507fc8cf8698e2df53b | [
"if value == 1:\n self._update_attribute(self.attributes_by_name['system_mode'].id, Thermostat.SystemMode.Heat)\n self._update_attribute(self.attributes_by_name['running_mode'].id, Thermostat.RunningMode.Heat)\n _LOGGER.debug('reported system_mode: heat')\nelse:\n self._update_attribute(self.attributes_... | <|body_start_0|>
if value == 1:
self._update_attribute(self.attributes_by_name['system_mode'].id, Thermostat.SystemMode.Heat)
self._update_attribute(self.attributes_by_name['running_mode'].id, Thermostat.RunningMode.Heat)
_LOGGER.debug('reported system_mode: heat')
el... | Thermostat cluster. | ThermostatCluster | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThermostatCluster:
"""Thermostat cluster."""
def system_mode_reported(self, value):
"""Handle reported system mode."""
<|body_0|>
def map_attribute(self, attribute, value):
"""Map standardized attribute value to dict of manufacturer values."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_006785 | 11,139 | permissive | [
{
"docstring": "Handle reported system mode.",
"name": "system_mode_reported",
"signature": "def system_mode_reported(self, value)"
},
{
"docstring": "Map standardized attribute value to dict of manufacturer values.",
"name": "map_attribute",
"signature": "def map_attribute(self, attribu... | 2 | null | Implement the Python class `ThermostatCluster` described below.
Class description:
Thermostat cluster.
Method signatures and docstrings:
- def system_mode_reported(self, value): Handle reported system mode.
- def map_attribute(self, attribute, value): Map standardized attribute value to dict of manufacturer values. | Implement the Python class `ThermostatCluster` described below.
Class description:
Thermostat cluster.
Method signatures and docstrings:
- def system_mode_reported(self, value): Handle reported system mode.
- def map_attribute(self, attribute, value): Map standardized attribute value to dict of manufacturer values.
... | 84d02be7abde55a6cee80fa155f0cbbc20347c40 | <|skeleton|>
class ThermostatCluster:
"""Thermostat cluster."""
def system_mode_reported(self, value):
"""Handle reported system mode."""
<|body_0|>
def map_attribute(self, attribute, value):
"""Map standardized attribute value to dict of manufacturer values."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThermostatCluster:
"""Thermostat cluster."""
def system_mode_reported(self, value):
"""Handle reported system mode."""
if value == 1:
self._update_attribute(self.attributes_by_name['system_mode'].id, Thermostat.SystemMode.Heat)
self._update_attribute(self.attribute... | the_stack_v2_python_sparse | zhaquirks/tuya/ts0601_trv_sas.py | Shulyaka/zha-device-handlers | train | 1 |
ebd07dd0a6d3076593de2edd4ad9dd9d0dc7d891 | [
"section = self.CONF_SECTION if section is None else section\nif section is None:\n raise AttributeError('A SpyderConfigurationAccessor must define a `CONF_SECTION` class attribute!')\nreturn CONF.get(section, option, default)",
"section = self.CONF_SECTION if section is None else section\nif section is None:\... | <|body_start_0|>
section = self.CONF_SECTION if section is None else section
if section is None:
raise AttributeError('A SpyderConfigurationAccessor must define a `CONF_SECTION` class attribute!')
return CONF.get(section, option, default)
<|end_body_0|>
<|body_start_1|>
sect... | Mixin used to access options stored in the Spyder configuration system. | SpyderConfigurationAccessor | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"LGPL-3.0-only",
"LicenseRef-scancode-free-unknown",
"LGPL-3.0-or-later",
"LicenseRef-scancode-proprietary-license",
"LGPL-2.1-or-later",
"CC-BY-2.5",
"CC-BY-4.0",
"MIT",
"LGPL-2.1-only",
"CC-BY-3.0",
"LicenseRef-scancode-unknown-license-reference",
"OF... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpyderConfigurationAccessor:
"""Mixin used to access options stored in the Spyder configuration system."""
def get_conf(self, option: ConfigurationKey, default: Union[NoDefault, BasicTypes]=NoDefault, section: Optional[str]=None):
"""Get an option from the Spyder configuration system... | stack_v2_sparse_classes_36k_train_006786 | 9,488 | permissive | [
{
"docstring": "Get an option from the Spyder configuration system. Parameters ---------- option: ConfigurationKey Name/Tuple path of the option to get its value from. default: Union[NoDefault, BasicTypes] Fallback value to return if the option is not found on the configuration system. section: str Section in t... | 4 | stack_v2_sparse_classes_30k_train_018762 | Implement the Python class `SpyderConfigurationAccessor` described below.
Class description:
Mixin used to access options stored in the Spyder configuration system.
Method signatures and docstrings:
- def get_conf(self, option: ConfigurationKey, default: Union[NoDefault, BasicTypes]=NoDefault, section: Optional[str]=... | Implement the Python class `SpyderConfigurationAccessor` described below.
Class description:
Mixin used to access options stored in the Spyder configuration system.
Method signatures and docstrings:
- def get_conf(self, option: ConfigurationKey, default: Union[NoDefault, BasicTypes]=NoDefault, section: Optional[str]=... | 0b4929cef420ba6c625566e52200e959f3566f33 | <|skeleton|>
class SpyderConfigurationAccessor:
"""Mixin used to access options stored in the Spyder configuration system."""
def get_conf(self, option: ConfigurationKey, default: Union[NoDefault, BasicTypes]=NoDefault, section: Optional[str]=None):
"""Get an option from the Spyder configuration system... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpyderConfigurationAccessor:
"""Mixin used to access options stored in the Spyder configuration system."""
def get_conf(self, option: ConfigurationKey, default: Union[NoDefault, BasicTypes]=NoDefault, section: Optional[str]=None):
"""Get an option from the Spyder configuration system. Parameters ... | the_stack_v2_python_sparse | spyder/api/config/mixins.py | juanis2112/spyder | train | 1 |
2fb0f1d98471f905ee90db70b97835795a8ddce9 | [
"cities_subscriptions = request.user.cities_subscriptions.filter(is_active=True)\ncontext = {'cities_subscriptions': cities_subscriptions}\nreturn render(request, self.template_name, context)",
"subscription_pk = request.POST.get('subscription_pk', '')\nnext = request.POST.get('next', '')\nif subscription_pk:\n ... | <|body_start_0|>
cities_subscriptions = request.user.cities_subscriptions.filter(is_active=True)
context = {'cities_subscriptions': cities_subscriptions}
return render(request, self.template_name, context)
<|end_body_0|>
<|body_start_1|>
subscription_pk = request.POST.get('subscription_... | Manage cities' subscriptions | CitiesManagementView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CitiesManagementView:
"""Manage cities' subscriptions"""
def get(self, request, *args, **kwargs):
"""GET request handler."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""POST request handler."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006787 | 5,471 | no_license | [
{
"docstring": "GET request handler.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "POST request handler.",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011861 | Implement the Python class `CitiesManagementView` described below.
Class description:
Manage cities' subscriptions
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): GET request handler.
- def post(self, request, *args, **kwargs): POST request handler. | Implement the Python class `CitiesManagementView` described below.
Class description:
Manage cities' subscriptions
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): GET request handler.
- def post(self, request, *args, **kwargs): POST request handler.
<|skeleton|>
class CitiesManagementVie... | b0702a8f7f60de6db9de7f712108e68d66f07f61 | <|skeleton|>
class CitiesManagementView:
"""Manage cities' subscriptions"""
def get(self, request, *args, **kwargs):
"""GET request handler."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""POST request handler."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CitiesManagementView:
"""Manage cities' subscriptions"""
def get(self, request, *args, **kwargs):
"""GET request handler."""
cities_subscriptions = request.user.cities_subscriptions.filter(is_active=True)
context = {'cities_subscriptions': cities_subscriptions}
return rend... | the_stack_v2_python_sparse | getdeal/apps/profiles/views.py | PankeshGupta/getdeal | train | 0 |
099d098cfeef4209e750d9db6057d85f5358f72b | [
"parser.add_argument('user', metavar='USERNAME', help='User name for the owner of the sample.')\nparser.add_argument('sample_dir', metavar='SAMPLE_DIRECTORY', help='User name for the owner of the sample.')\nparser.add_argument('name', metavar='SAMPLE_NAME', help='Sample tag associated with sample.')\nparser.add_arg... | <|body_start_0|>
parser.add_argument('user', metavar='USERNAME', help='User name for the owner of the sample.')
parser.add_argument('sample_dir', metavar='SAMPLE_DIRECTORY', help='User name for the owner of the sample.')
parser.add_argument('name', metavar='SAMPLE_NAME', help='Sample tag associa... | Insert the results of sample analysis into the database. | Command | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
"""Insert the results of sample analysis into the database."""
def add_arguments(self, parser):
"""Command line arguements."""
<|body_0|>
def handle(self, *args, **opts):
"""Insert the results of sample analysis into the database."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_006788 | 4,597 | no_license | [
{
"docstring": "Command line arguements.",
"name": "add_arguments",
"signature": "def add_arguments(self, parser)"
},
{
"docstring": "Insert the results of sample analysis into the database.",
"name": "handle",
"signature": "def handle(self, *args, **opts)"
},
{
"docstring": "The... | 3 | stack_v2_sparse_classes_30k_train_008590 | Implement the Python class `Command` described below.
Class description:
Insert the results of sample analysis into the database.
Method signatures and docstrings:
- def add_arguments(self, parser): Command line arguements.
- def handle(self, *args, **opts): Insert the results of sample analysis into the database.
- ... | Implement the Python class `Command` described below.
Class description:
Insert the results of sample analysis into the database.
Method signatures and docstrings:
- def add_arguments(self, parser): Command line arguements.
- def handle(self, *args, **opts): Insert the results of sample analysis into the database.
- ... | 2c35ee47e131a74642e60fae6f1cc23561d8b1a6 | <|skeleton|>
class Command:
"""Insert the results of sample analysis into the database."""
def add_arguments(self, parser):
"""Command line arguements."""
<|body_0|>
def handle(self, *args, **opts):
"""Insert the results of sample analysis into the database."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Command:
"""Insert the results of sample analysis into the database."""
def add_arguments(self, parser):
"""Command line arguements."""
parser.add_argument('user', metavar='USERNAME', help='User name for the owner of the sample.')
parser.add_argument('sample_dir', metavar='SAMPLE_... | the_stack_v2_python_sparse | sample/management/commands/insert_analysis_results.py | staphopia/staphopia-web | train | 5 |
f63ca8fb02cb83cddd7128e4bba2463cc428e2b1 | [
"length = len(matrix)\nif length == 0:\n return []\nres = []\nt = []\ncur = matrix[0]\nfor i in range(length):\n for l in matrix:\n t = [l[i]] + t\n res.append(t)\n t = []\nmatrix = res",
"l = len(matrix)\nclcles = l // 2\npp = l - 1\nfor i in range(clcles):\n t = pp - i * 2\n for j in ra... | <|body_start_0|>
length = len(matrix)
if length == 0:
return []
res = []
t = []
cur = matrix[0]
for i in range(length):
for l in matrix:
t = [l[i]] + t
res.append(t)
t = []
matrix = res
<|end_body_0|>... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate1(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate2(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-... | stack_v2_sparse_classes_36k_train_006789 | 2,020 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
"name": "rotate1",
"signature": "def rotate1(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate1(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate2(self, matrix): :type matrix: List[List... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate1(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate2(self, matrix): :type matrix: List[List... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def rotate1(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate2(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate1(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
length = len(matrix)
if length == 0:
return []
res = []
t = []
cur = matrix[0]
for i in range(length... | the_stack_v2_python_sparse | py/leetcode/48.py | wfeng1991/learnpy | train | 0 | |
4e5125d6afee41d7e725caea9db5b258bbb7687e | [
"self.url = url\nself._content = None\nself.last_update = time.time()",
"reload_time = 10\nnow = time.time()\nif not self._content or now - self.last_update > reload_time:\n print('Retrieving New Page...')\n self._content = urlopen(self.url).read()\n self.last_update = time.time()\nelse:\n print(\"Has... | <|body_start_0|>
self.url = url
self._content = None
self.last_update = time.time()
<|end_body_0|>
<|body_start_1|>
reload_time = 10
now = time.time()
if not self._content or now - self.last_update > reload_time:
print('Retrieving New Page...')
se... | Cashin webpage | WebPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebPage:
"""Cashin webpage"""
def __init__(self, url):
"""Initializes web-page by url"""
<|body_0|>
def content(self):
"""Return content of web-page"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.url = url
self._content = None
... | stack_v2_sparse_classes_36k_train_006790 | 776 | no_license | [
{
"docstring": "Initializes web-page by url",
"name": "__init__",
"signature": "def __init__(self, url)"
},
{
"docstring": "Return content of web-page",
"name": "content",
"signature": "def content(self)"
}
] | 2 | null | Implement the Python class `WebPage` described below.
Class description:
Cashin webpage
Method signatures and docstrings:
- def __init__(self, url): Initializes web-page by url
- def content(self): Return content of web-page | Implement the Python class `WebPage` described below.
Class description:
Cashin webpage
Method signatures and docstrings:
- def __init__(self, url): Initializes web-page by url
- def content(self): Return content of web-page
<|skeleton|>
class WebPage:
"""Cashin webpage"""
def __init__(self, url):
"... | 1837d3234e5b4b5d46cd264bf4a0c4da75bfc3d2 | <|skeleton|>
class WebPage:
"""Cashin webpage"""
def __init__(self, url):
"""Initializes web-page by url"""
<|body_0|>
def content(self):
"""Return content of web-page"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WebPage:
"""Cashin webpage"""
def __init__(self, url):
"""Initializes web-page by url"""
self.url = url
self._content = None
self.last_update = time.time()
def content(self):
"""Return content of web-page"""
reload_time = 10
now = time.time()
... | the_stack_v2_python_sparse | lab07-cachingWebpage-scalingZipedImage/cache-webpage/cashe_webpage.py | 7ss8n/ProgrammingBasics2-Python | train | 0 |
6e486e6f1f0e0da64d4c7fc0d68b64758036dfd2 | [
"msg_info = dict()\nmsg_info['raw_message'] = line\nmatch = self._LINE_RE.search(line)\nif match:\n msg_info.update(match.groupdict())\n try:\n stamp = match.group('timestamp')\n msg_info['datetime'] = datetime.strptime(stamp[0:23] + stamp[24:26], self.time_format + ' %z')\n except:\n ... | <|body_start_0|>
msg_info = dict()
msg_info['raw_message'] = line
match = self._LINE_RE.search(line)
if match:
msg_info.update(match.groupdict())
try:
stamp = match.group('timestamp')
msg_info['datetime'] = datetime.strptime(stamp[0... | Reads the OSA dispatcher log. Based on the ``LogFileOutput`` class. .. note:: Please refer to its super-class :class:`insights.core.LogFileOutput` Works a bit like the XMLRPC log but the IP address always seems to be ``0.0.0.0`` and the module is always 'osad' - it's more like what produced the log. Sample log data:: 2... | OSADispatcherLog | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OSADispatcherLog:
"""Reads the OSA dispatcher log. Based on the ``LogFileOutput`` class. .. note:: Please refer to its super-class :class:`insights.core.LogFileOutput` Works a bit like the XMLRPC log but the IP address always seems to be ``0.0.0.0`` and the module is always 'osad' - it's more lik... | stack_v2_sparse_classes_36k_train_006791 | 4,166 | permissive | [
{
"docstring": "Parse a log line using the XMLRPC regular expression into a dict. All data will be in fields, and the raw log line is stored in 'raw_message'. This also attempts to convert the timestamp given into a datetime object; if it can't convert it, then you don't get a 'datetime' key in the line's dict.... | 2 | null | Implement the Python class `OSADispatcherLog` described below.
Class description:
Reads the OSA dispatcher log. Based on the ``LogFileOutput`` class. .. note:: Please refer to its super-class :class:`insights.core.LogFileOutput` Works a bit like the XMLRPC log but the IP address always seems to be ``0.0.0.0`` and the ... | Implement the Python class `OSADispatcherLog` described below.
Class description:
Reads the OSA dispatcher log. Based on the ``LogFileOutput`` class. .. note:: Please refer to its super-class :class:`insights.core.LogFileOutput` Works a bit like the XMLRPC log but the IP address always seems to be ``0.0.0.0`` and the ... | b0ea07fc3f4dd8801b505fe70e9b36e628152c4a | <|skeleton|>
class OSADispatcherLog:
"""Reads the OSA dispatcher log. Based on the ``LogFileOutput`` class. .. note:: Please refer to its super-class :class:`insights.core.LogFileOutput` Works a bit like the XMLRPC log but the IP address always seems to be ``0.0.0.0`` and the module is always 'osad' - it's more lik... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OSADispatcherLog:
"""Reads the OSA dispatcher log. Based on the ``LogFileOutput`` class. .. note:: Please refer to its super-class :class:`insights.core.LogFileOutput` Works a bit like the XMLRPC log but the IP address always seems to be ``0.0.0.0`` and the module is always 'osad' - it's more like what produc... | the_stack_v2_python_sparse | insights/parsers/osa_dispatcher_log.py | RedHatInsights/insights-core | train | 144 |
dbfa531f3ea253d4b9fe8cbf7b1da0c9e2bd7f93 | [
"known_pulsars = np.recfromcsv(KNOWNPSR_FILENM, delimiter=';', comments='#', usecols=(1, 2, 3, 4, 5))\nself.known_names = known_pulsars['name']\nself.known_ras = known_pulsars['rajd']\nself.known_decs = known_pulsars['decjd']\nself.known_dms = known_pulsars['dm']",
"dm = cand.info['dm']\nra = cand.info['raj_deg']... | <|body_start_0|>
known_pulsars = np.recfromcsv(KNOWNPSR_FILENM, delimiter=';', comments='#', usecols=(1, 2, 3, 4, 5))
self.known_names = known_pulsars['name']
self.known_ras = known_pulsars['rajd']
self.known_decs = known_pulsars['decjd']
self.known_dms = known_pulsars['dm']
<|en... | KnownPulsarRater | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KnownPulsarRater:
def _setup(self):
"""A setup method to be called when the Rater is initialised Inputs: None Outputs: None"""
<|body_0|>
def _compute_rating(self, cand):
"""Return a rating for the candidate. The rating value encodes how close the candidate's positio... | stack_v2_sparse_classes_36k_train_006792 | 2,809 | no_license | [
{
"docstring": "A setup method to be called when the Rater is initialised Inputs: None Outputs: None",
"name": "_setup",
"signature": "def _setup(self)"
},
{
"docstring": "Return a rating for the candidate. The rating value encodes how close the candidate's position and DM are to that of a known... | 2 | stack_v2_sparse_classes_30k_train_020080 | Implement the Python class `KnownPulsarRater` described below.
Class description:
Implement the KnownPulsarRater class.
Method signatures and docstrings:
- def _setup(self): A setup method to be called when the Rater is initialised Inputs: None Outputs: None
- def _compute_rating(self, cand): Return a rating for the ... | Implement the Python class `KnownPulsarRater` described below.
Class description:
Implement the KnownPulsarRater class.
Method signatures and docstrings:
- def _setup(self): A setup method to be called when the Rater is initialised Inputs: None Outputs: None
- def _compute_rating(self, cand): Return a rating for the ... | e81c4926fbe5e4da2e923b10747bf3b844715ced | <|skeleton|>
class KnownPulsarRater:
def _setup(self):
"""A setup method to be called when the Rater is initialised Inputs: None Outputs: None"""
<|body_0|>
def _compute_rating(self, cand):
"""Return a rating for the candidate. The rating value encodes how close the candidate's positio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KnownPulsarRater:
def _setup(self):
"""A setup method to be called when the Rater is initialised Inputs: None Outputs: None"""
known_pulsars = np.recfromcsv(KNOWNPSR_FILENM, delimiter=';', comments='#', usecols=(1, 2, 3, 4, 5))
self.known_names = known_pulsars['name']
self.know... | the_stack_v2_python_sparse | pipeline/lib/python/sp_raters/known_pulsar.py | ryanslynch/GBNCC-search | train | 2 | |
bbab6ed2284f420c0b1e85218b76b3b8863bd97d | [
"NonlinearProblem.__init__(self)\nself.bcs = bcs\nself.state = state\nu = state['u']\nV = u.function_space()\nv = TestFunction(V)\ndu = TrialFunction(V)\nself.residual = derivative(energy, u, v)\nself.jacobian = derivative(self.residual, u, du)",
"assemble(self.residual, tensor=b)\nfor bc in self.bcs:\n bc.app... | <|body_start_0|>
NonlinearProblem.__init__(self)
self.bcs = bcs
self.state = state
u = state['u']
V = u.function_space()
v = TestFunction(V)
du = TrialFunction(V)
self.residual = derivative(energy, u, v)
self.jacobian = derivative(self.residual, u,... | docstring for ElastcitityProblem | ElasticityProblem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElasticityProblem:
"""docstring for ElastcitityProblem"""
def __init__(self, energy, state, bcs):
"""Initialises the elasticity problem. Arguments: * energy * state * boundary conditions"""
<|body_0|>
def F(self, b, x):
"""Compute F at current point x. This funct... | stack_v2_sparse_classes_36k_train_006793 | 13,772 | permissive | [
{
"docstring": "Initialises the elasticity problem. Arguments: * energy * state * boundary conditions",
"name": "__init__",
"signature": "def __init__(self, energy, state, bcs)"
},
{
"docstring": "Compute F at current point x. This function is called at each interation of the solver.",
"name... | 3 | stack_v2_sparse_classes_30k_train_018950 | Implement the Python class `ElasticityProblem` described below.
Class description:
docstring for ElastcitityProblem
Method signatures and docstrings:
- def __init__(self, energy, state, bcs): Initialises the elasticity problem. Arguments: * energy * state * boundary conditions
- def F(self, b, x): Compute F at curren... | Implement the Python class `ElasticityProblem` described below.
Class description:
docstring for ElastcitityProblem
Method signatures and docstrings:
- def __init__(self, energy, state, bcs): Initialises the elasticity problem. Arguments: * energy * state * boundary conditions
- def F(self, b, x): Compute F at curren... | 9a82bf40742a9b16122b7a476ad8aec65fe22539 | <|skeleton|>
class ElasticityProblem:
"""docstring for ElastcitityProblem"""
def __init__(self, energy, state, bcs):
"""Initialises the elasticity problem. Arguments: * energy * state * boundary conditions"""
<|body_0|>
def F(self, b, x):
"""Compute F at current point x. This funct... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElasticityProblem:
"""docstring for ElastcitityProblem"""
def __init__(self, energy, state, bcs):
"""Initialises the elasticity problem. Arguments: * energy * state * boundary conditions"""
NonlinearProblem.__init__(self)
self.bcs = bcs
self.state = state
u = state... | the_stack_v2_python_sparse | src/solvers.py | kumiori/stability-bifurcation | train | 1 |
a764b0131e3533b74a24a52798018960a73cb851 | [
"RAMSTKDataModel.__init__(self, dao)\nself.dtm_site_options = SiteOptionsDataModel(site_dao)\nself.dtm_program_options = ProgramOptionsDataModel(dao)\nself.site_options = None\nself.program_options = None",
"_site = kwargs['site']\n_program = kwargs['program']\nif _site:\n self.site_options = self.dtm_site_opt... | <|body_start_0|>
RAMSTKDataModel.__init__(self, dao)
self.dtm_site_options = SiteOptionsDataModel(site_dao)
self.dtm_program_options = ProgramOptionsDataModel(dao)
self.site_options = None
self.program_options = None
<|end_body_0|>
<|body_start_1|>
_site = kwargs['site']... | Contains the attributes and methods of an Options data model. | OptionsDataModel | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptionsDataModel:
"""Contains the attributes and methods of an Options data model."""
def __init__(self, dao, site_dao):
"""Initialize an Options data model instance. :param dao: the data access object for communicating with the RAMSTK Program database. :type dao: :class:`ramstk.dao.... | stack_v2_sparse_classes_36k_train_006794 | 6,635 | permissive | [
{
"docstring": "Initialize an Options data model instance. :param dao: the data access object for communicating with the RAMSTK Program database. :type dao: :class:`ramstk.dao.DAO.DAO`",
"name": "__init__",
"signature": "def __init__(self, dao, site_dao)"
},
{
"docstring": "Retrieve Options from... | 3 | stack_v2_sparse_classes_30k_train_019430 | Implement the Python class `OptionsDataModel` described below.
Class description:
Contains the attributes and methods of an Options data model.
Method signatures and docstrings:
- def __init__(self, dao, site_dao): Initialize an Options data model instance. :param dao: the data access object for communicating with th... | Implement the Python class `OptionsDataModel` described below.
Class description:
Contains the attributes and methods of an Options data model.
Method signatures and docstrings:
- def __init__(self, dao, site_dao): Initialize an Options data model instance. :param dao: the data access object for communicating with th... | 488ffed8b842399ddcae93007de6c6f1dda23d05 | <|skeleton|>
class OptionsDataModel:
"""Contains the attributes and methods of an Options data model."""
def __init__(self, dao, site_dao):
"""Initialize an Options data model instance. :param dao: the data access object for communicating with the RAMSTK Program database. :type dao: :class:`ramstk.dao.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptionsDataModel:
"""Contains the attributes and methods of an Options data model."""
def __init__(self, dao, site_dao):
"""Initialize an Options data model instance. :param dao: the data access object for communicating with the RAMSTK Program database. :type dao: :class:`ramstk.dao.DAO.DAO`"""
... | the_stack_v2_python_sparse | src/ramstk/modules/options/Model.py | JmiXIII/ramstk | train | 0 |
a46c009c543e5be55ab11710f479c242db23127c | [
"def app_fn1(request):\n return str(request.params.get('foo'))\napp = makeapp({'': app_fn1})\nr = simulate_post(app, '/', {'foo': 'some data'})\nself.assertEqual(r.status, u'200 OK')\nself.assertEqual(dict(r.headers)[u'Content-Type'], u'text/plain')\nself.assertEqual(r.body, u\"['some data']\")",
"@wsgiwapi.js... | <|body_start_0|>
def app_fn1(request):
return str(request.params.get('foo'))
app = makeapp({'': app_fn1})
r = simulate_post(app, '/', {'foo': 'some data'})
self.assertEqual(r.status, u'200 OK')
self.assertEqual(dict(r.headers)[u'Content-Type'], u'text/plain')
... | Test validation support. | PostdataTest | [
"BSD-3-Clause",
"MIT",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostdataTest:
"""Test validation support."""
def test_default(self):
"""Test basic use of the default postdata handler."""
<|body_0|>
def test_json(self):
"""Test use of the default postdata handler with JSON body."""
<|body_1|>
def test_stream(self)... | stack_v2_sparse_classes_36k_train_006795 | 2,940 | permissive | [
{
"docstring": "Test basic use of the default postdata handler.",
"name": "test_default",
"signature": "def test_default(self)"
},
{
"docstring": "Test use of the default postdata handler with JSON body.",
"name": "test_json",
"signature": "def test_json(self)"
},
{
"docstring": ... | 3 | stack_v2_sparse_classes_30k_train_006983 | Implement the Python class `PostdataTest` described below.
Class description:
Test validation support.
Method signatures and docstrings:
- def test_default(self): Test basic use of the default postdata handler.
- def test_json(self): Test use of the default postdata handler with JSON body.
- def test_stream(self): Te... | Implement the Python class `PostdataTest` described below.
Class description:
Test validation support.
Method signatures and docstrings:
- def test_default(self): Test basic use of the default postdata handler.
- def test_json(self): Test use of the default postdata handler with JSON body.
- def test_stream(self): Te... | 040acfcc9fa724707a88e685dcd092e0606d05a3 | <|skeleton|>
class PostdataTest:
"""Test validation support."""
def test_default(self):
"""Test basic use of the default postdata handler."""
<|body_0|>
def test_json(self):
"""Test use of the default postdata handler with JSON body."""
<|body_1|>
def test_stream(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PostdataTest:
"""Test validation support."""
def test_default(self):
"""Test basic use of the default postdata handler."""
def app_fn1(request):
return str(request.params.get('foo'))
app = makeapp({'': app_fn1})
r = simulate_post(app, '/', {'foo': 'some data'})... | the_stack_v2_python_sparse | wsgiwapi/unittests/postdata.py | rboulton/wsgiwapi | train | 0 |
3f590307c4e50d1541efba93db3325a8e347bd33 | [
"self.instance_keypair = self.os_conn.create_key(key_name='instancekey')\nzone = self.os_conn.nova.availability_zones.find(zoneName='nova')\nvm_hosts = zone.hosts.keys()[:2]\nself.setup_rules_for_default_sec_group()\nrouter = self.os_conn.create_router(name='router01')\nfor i, hostname in enumerate(vm_hosts, 1):\n ... | <|body_start_0|>
self.instance_keypair = self.os_conn.create_key(key_name='instancekey')
zone = self.os_conn.nova.availability_zones.find(zoneName='nova')
vm_hosts = zone.hosts.keys()[:2]
self.setup_rules_for_default_sec_group()
router = self.os_conn.create_router(name='router01'... | Check restarts of openvswitch-agents. | TestOVSRestartTwoVms | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOVSRestartTwoVms:
"""Check restarts of openvswitch-agents."""
def _prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create router01, create networks net01: net01__subnet, 192.168.1.0/24, net02: net02__subnet, 192.168.2.0/2... | stack_v2_sparse_classes_36k_train_006796 | 41,546 | no_license | [
{
"docstring": "Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create router01, create networks net01: net01__subnet, 192.168.1.0/24, net02: net02__subnet, 192.168.2.0/24 and attach them to router01. 3. Launch vm1 in net01 network and vm2 in net02 network on different computes 4.... | 3 | stack_v2_sparse_classes_30k_train_020282 | Implement the Python class `TestOVSRestartTwoVms` 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 router01, create networks net01: net01__su... | Implement the Python class `TestOVSRestartTwoVms` 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 router01, create networks net01: net01__su... | 8aced2855b78b5f123195d188c80e27b43888a2e | <|skeleton|>
class TestOVSRestartTwoVms:
"""Check restarts of openvswitch-agents."""
def _prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create router01, create networks net01: net01__subnet, 192.168.1.0/24, net02: net02__subnet, 192.168.2.0/2... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestOVSRestartTwoVms:
"""Check restarts of openvswitch-agents."""
def _prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Update default security group 2. Create router01, create networks net01: net01__subnet, 192.168.1.0/24, net02: net02__subnet, 192.168.2.0/24 and attach ... | the_stack_v2_python_sparse | mos_tests/neutron/python_tests/test_ovs_restart.py | Mirantis/mos-integration-tests | train | 16 |
b92760b21a9131bf40847b2a8448974340dad85e | [
"tensors = arg\nif args:\n tensors = (arg,) + args\nelse:\n tensors = arg\nflattened_tensors = nest.flatten(tensors)\nflattened_values = []\nfor t in flattened_tensors:\n if isinstance(t, ops.Tensor):\n flattened_values.append(t)\n elif isinstance(t, sparse_tensor.SparseTensor):\n flattene... | <|body_start_0|>
tensors = arg
if args:
tensors = (arg,) + args
else:
tensors = arg
flattened_tensors = nest.flatten(tensors)
flattened_values = []
for t in flattened_tensors:
if isinstance(t, ops.Tensor):
flattened_valu... | Keys for different tensor kinds. | TensorKinds | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorKinds:
"""Keys for different tensor kinds."""
def normalize(cls, arg, *args):
"""Normalize structure into list of tensors."""
<|body_0|>
def denormalize(cls, structure, flatten_structure, tensors):
"""Denormalize structure from list of tensors."""
<... | stack_v2_sparse_classes_36k_train_006797 | 7,164 | permissive | [
{
"docstring": "Normalize structure into list of tensors.",
"name": "normalize",
"signature": "def normalize(cls, arg, *args)"
},
{
"docstring": "Denormalize structure from list of tensors.",
"name": "denormalize",
"signature": "def denormalize(cls, structure, flatten_structure, tensors)... | 2 | stack_v2_sparse_classes_30k_train_002829 | Implement the Python class `TensorKinds` described below.
Class description:
Keys for different tensor kinds.
Method signatures and docstrings:
- def normalize(cls, arg, *args): Normalize structure into list of tensors.
- def denormalize(cls, structure, flatten_structure, tensors): Denormalize structure from list of ... | Implement the Python class `TensorKinds` described below.
Class description:
Keys for different tensor kinds.
Method signatures and docstrings:
- def normalize(cls, arg, *args): Normalize structure into list of tensors.
- def denormalize(cls, structure, flatten_structure, tensors): Denormalize structure from list of ... | 4486ba138515a1dbdb6f7d542d7ad23a27476524 | <|skeleton|>
class TensorKinds:
"""Keys for different tensor kinds."""
def normalize(cls, arg, *args):
"""Normalize structure into list of tensors."""
<|body_0|>
def denormalize(cls, structure, flatten_structure, tensors):
"""Denormalize structure from list of tensors."""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TensorKinds:
"""Keys for different tensor kinds."""
def normalize(cls, arg, *args):
"""Normalize structure into list of tensors."""
tensors = arg
if args:
tensors = (arg,) + args
else:
tensors = arg
flattened_tensors = nest.flatten(tensors)
... | the_stack_v2_python_sparse | hybridbackend/tensorflow/framework/ops.py | DeepRec-AI/HybridBackend | train | 10 |
52918d175d5bb55d37edbc3a91a9ec1a61768dc1 | [
"if toggled and (not callable(toggled)):\n toggled = lambda value: None\nif toggled is not None:\n if section is None and option is not None:\n section = self.CONF_SECTION\ntoolbutton = create_toolbutton(self, text=text, shortcut=None, icon=icon, tip=tip, toggled=toggled, triggered=triggered, autoraise... | <|body_start_0|>
if toggled and (not callable(toggled)):
toggled = lambda value: None
if toggled is not None:
if section is None and option is not None:
section = self.CONF_SECTION
toolbutton = create_toolbutton(self, text=text, shortcut=None, icon=icon, t... | Provide methods to create, add and get toolbuttons. | SpyderToolButtonMixin | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"LGPL-3.0-only",
"LicenseRef-scancode-free-unknown",
"LGPL-3.0-or-later",
"LicenseRef-scancode-proprietary-license",
"LGPL-2.1-or-later",
"CC-BY-2.5",
"CC-BY-4.0",
"MIT",
"LGPL-2.1-only",
"CC-BY-3.0",
"LicenseRef-scancode-unknown-license-reference",
"OF... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpyderToolButtonMixin:
"""Provide methods to create, add and get toolbuttons."""
def create_toolbutton(self, name, text=None, icon=None, tip=None, toggled=None, triggered=None, autoraise=True, text_beside_icon=False, section=None, option=None):
"""Create a Spyder toolbutton."""
... | stack_v2_sparse_classes_36k_train_006798 | 20,997 | permissive | [
{
"docstring": "Create a Spyder toolbutton.",
"name": "create_toolbutton",
"signature": "def create_toolbutton(self, name, text=None, icon=None, tip=None, toggled=None, triggered=None, autoraise=True, text_beside_icon=False, section=None, option=None)"
},
{
"docstring": "Return toolbutton by nam... | 3 | stack_v2_sparse_classes_30k_train_020543 | Implement the Python class `SpyderToolButtonMixin` described below.
Class description:
Provide methods to create, add and get toolbuttons.
Method signatures and docstrings:
- def create_toolbutton(self, name, text=None, icon=None, tip=None, toggled=None, triggered=None, autoraise=True, text_beside_icon=False, section... | Implement the Python class `SpyderToolButtonMixin` described below.
Class description:
Provide methods to create, add and get toolbuttons.
Method signatures and docstrings:
- def create_toolbutton(self, name, text=None, icon=None, tip=None, toggled=None, triggered=None, autoraise=True, text_beside_icon=False, section... | 0b4929cef420ba6c625566e52200e959f3566f33 | <|skeleton|>
class SpyderToolButtonMixin:
"""Provide methods to create, add and get toolbuttons."""
def create_toolbutton(self, name, text=None, icon=None, tip=None, toggled=None, triggered=None, autoraise=True, text_beside_icon=False, section=None, option=None):
"""Create a Spyder toolbutton."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpyderToolButtonMixin:
"""Provide methods to create, add and get toolbuttons."""
def create_toolbutton(self, name, text=None, icon=None, tip=None, toggled=None, triggered=None, autoraise=True, text_beside_icon=False, section=None, option=None):
"""Create a Spyder toolbutton."""
if toggled... | the_stack_v2_python_sparse | spyder/api/widgets/mixins.py | juanis2112/spyder | train | 1 |
c4dfe1a8ae4eb825f7659bfcf00fe9cc734c6494 | [
"self.ps = PastaSauce()\nself.desired_capabilities['name'] = self.id()\nself.user = None",
"if not LOCAL_RUN:\n self.ps.update_job(job_id=str(self.user.driver.session_id), **self.ps.test_updates)\ntry:\n self.user.delete()\nexcept:\n pass",
"self.ps.test_updates['name'] = 't1.38.001' + inspect.currentf... | <|body_start_0|>
self.ps = PastaSauce()
self.desired_capabilities['name'] = self.id()
self.user = None
<|end_body_0|>
<|body_start_1|>
if not LOCAL_RUN:
self.ps.update_job(job_id=str(self.user.driver.session_id), **self.ps.test_updates)
try:
self.user.del... | T1.38 - Choose Course. | TestChooseCourse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestChooseCourse:
"""T1.38 - Choose Course."""
def setUp(self):
"""Pretest settings."""
<|body_0|>
def tearDown(self):
"""Test destructor."""
<|body_1|>
def test_student_select_a_course_8254(self):
"""Select a course. Steps: Click on a Tutor ... | stack_v2_sparse_classes_36k_train_006799 | 6,295 | no_license | [
{
"docstring": "Pretest settings.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test destructor.",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "Select a course. Steps: Click on a Tutor course name Expected Result: The user select... | 5 | stack_v2_sparse_classes_30k_train_019227 | Implement the Python class `TestChooseCourse` described below.
Class description:
T1.38 - Choose Course.
Method signatures and docstrings:
- def setUp(self): Pretest settings.
- def tearDown(self): Test destructor.
- def test_student_select_a_course_8254(self): Select a course. Steps: Click on a Tutor course name Exp... | Implement the Python class `TestChooseCourse` described below.
Class description:
T1.38 - Choose Course.
Method signatures and docstrings:
- def setUp(self): Pretest settings.
- def tearDown(self): Test destructor.
- def test_student_select_a_course_8254(self): Select a course. Steps: Click on a Tutor course name Exp... | 39751799858ac30df90760b8bb753d338e8edc46 | <|skeleton|>
class TestChooseCourse:
"""T1.38 - Choose Course."""
def setUp(self):
"""Pretest settings."""
<|body_0|>
def tearDown(self):
"""Test destructor."""
<|body_1|>
def test_student_select_a_course_8254(self):
"""Select a course. Steps: Click on a Tutor ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestChooseCourse:
"""T1.38 - Choose Course."""
def setUp(self):
"""Pretest settings."""
self.ps = PastaSauce()
self.desired_capabilities['name'] = self.id()
self.user = None
def tearDown(self):
"""Test destructor."""
if not LOCAL_RUN:
self.... | the_stack_v2_python_sparse | tutor/OldTests/test_t1_38_ChooseCourse.py | openstax/test-automation | train | 4 |
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