blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
60e58ae2f11593b81982ec718ac87184974f3d9c | [
"try:\n payload = jwt.decode(data['token'], settings.SECRET_KEY, algorithms=['HS256'])\nexcept ExpiredSignatureError:\n raise serializers.ValidationError('The token has expired.')\nexcept JWTError:\n raise serializers.ValidationError('Error validating token. Ensure is the right token.')\nself.context['payl... | <|body_start_0|>
try:
payload = jwt.decode(data['token'], settings.SECRET_KEY, algorithms=['HS256'])
except ExpiredSignatureError:
raise serializers.ValidationError('The token has expired.')
except JWTError:
raise serializers.ValidationError('Error validating ... | Account verification Serializer that allows to know which user has a verificated account and which doesn't | AccountVerificationSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountVerificationSerializer:
"""Account verification Serializer that allows to know which user has a verificated account and which doesn't"""
def validate(self, data):
"""Validate method for the token"""
<|body_0|>
def save(self, **kwargs):
"""Update the user's... | stack_v2_sparse_classes_10k_train_006400 | 6,022 | no_license | [
{
"docstring": "Validate method for the token",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "Update the user's verification status",
"name": "save",
"signature": "def save(self, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001248 | Implement the Python class `AccountVerificationSerializer` described below.
Class description:
Account verification Serializer that allows to know which user has a verificated account and which doesn't
Method signatures and docstrings:
- def validate(self, data): Validate method for the token
- def save(self, **kwarg... | Implement the Python class `AccountVerificationSerializer` described below.
Class description:
Account verification Serializer that allows to know which user has a verificated account and which doesn't
Method signatures and docstrings:
- def validate(self, data): Validate method for the token
- def save(self, **kwarg... | bd037be8a814dce554e709d851c6a96e6a41ea78 | <|skeleton|>
class AccountVerificationSerializer:
"""Account verification Serializer that allows to know which user has a verificated account and which doesn't"""
def validate(self, data):
"""Validate method for the token"""
<|body_0|>
def save(self, **kwargs):
"""Update the user's... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AccountVerificationSerializer:
"""Account verification Serializer that allows to know which user has a verificated account and which doesn't"""
def validate(self, data):
"""Validate method for the token"""
try:
payload = jwt.decode(data['token'], settings.SECRET_KEY, algorithm... | the_stack_v2_python_sparse | users/serializers/users.py | jpcano1/tShoes | train | 0 |
ace94eee74d1e597d12c17a09cb675d6899aee62 | [
"self.n = len(nums)\nself.tree = nums + nums\nfor i in range(self.n - 1, 0, -1):\n self.tree[i] = self.tree[2 * i] + self.tree[2 * i + 1]",
"tree = self.tree\ni += self.n\ntree[i] = val\nwhile i > 0:\n left = right = i\n if i % 2 == 1:\n left -= 1\n else:\n right += 1\n tree[i / 2] = ... | <|body_start_0|>
self.n = len(nums)
self.tree = nums + nums
for i in range(self.n - 1, 0, -1):
self.tree[i] = self.tree[2 * i] + self.tree[2 * i + 1]
<|end_body_0|>
<|body_start_1|>
tree = self.tree
i += self.n
tree[i] = val
while i > 0:
l... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: int"""
<|body_1|>
def sumRange(self, i, j):
"""sum of elements nums[i... | stack_v2_sparse_classes_10k_train_006401 | 1,416 | no_license | [
{
"docstring": "initialize your data structure here. :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type val: int :rtype: int",
"name": "update",
"signature": "def update(self, i, val)"
},
{
"docstring": "sum o... | 3 | null | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: int
- def sumRange(self, i, j... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): initialize your data structure here. :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: int
- def sumRange(self, i, j... | 036a29d681cc91f2317d454e04530d7375d55478 | <|skeleton|>
class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: int"""
<|body_1|>
def sumRange(self, i, j):
"""sum of elements nums[i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
"""initialize your data structure here. :type nums: List[int]"""
self.n = len(nums)
self.tree = nums + nums
for i in range(self.n - 1, 0, -1):
self.tree[i] = self.tree[2 * i] + self.tree[2 * i + 1]
def update(self, i, val):
... | the_stack_v2_python_sparse | leetcode/range_sum_query_mutable_v1.py | myliu/python-algorithm | train | 0 | |
039c6622f853c67c0b637c34f4ff07e853015901 | [
"try:\n with open(primary_config_file, 'r') as f:\n self.primary_config = json.load(f)\nexcept Exception as e:\n raise Exception('Error reading primary config file: {}. Run reset.py script to reinitialize configs'.format(primary_config_file))\ntry:\n with open(secondary_config_file, 'r') as f:\n ... | <|body_start_0|>
try:
with open(primary_config_file, 'r') as f:
self.primary_config = json.load(f)
except Exception as e:
raise Exception('Error reading primary config file: {}. Run reset.py script to reinitialize configs'.format(primary_config_file))
try:... | Reads the config files and supports requested values from the user Methods: get_config_value: returns the value of the config key override_with_command_line_args: overrides the config values with command line arguments | ConfigReader | [
"Apache-2.0",
"BSD-3-Clause",
"MIT",
"WTFPL",
"GPL-2.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigReader:
"""Reads the config files and supports requested values from the user Methods: get_config_value: returns the value of the config key override_with_command_line_args: overrides the config values with command line arguments"""
def __init__(self, primary_config_file, secondary_con... | stack_v2_sparse_classes_10k_train_006402 | 3,982 | permissive | [
{
"docstring": "Constructor :param primary_config_file: str , path to primary config file :param secondary_config_file: str , path to secondary config file",
"name": "__init__",
"signature": "def __init__(self, primary_config_file, secondary_config_file)"
},
{
"docstring": "Overrides the config ... | 3 | null | Implement the Python class `ConfigReader` described below.
Class description:
Reads the config files and supports requested values from the user Methods: get_config_value: returns the value of the config key override_with_command_line_args: overrides the config values with command line arguments
Method signatures and... | Implement the Python class `ConfigReader` described below.
Class description:
Reads the config files and supports requested values from the user Methods: get_config_value: returns the value of the config key override_with_command_line_args: overrides the config values with command line arguments
Method signatures and... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class ConfigReader:
"""Reads the config files and supports requested values from the user Methods: get_config_value: returns the value of the config key override_with_command_line_args: overrides the config values with command line arguments"""
def __init__(self, primary_config_file, secondary_con... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ConfigReader:
"""Reads the config files and supports requested values from the user Methods: get_config_value: returns the value of the config key override_with_command_line_args: overrides the config values with command line arguments"""
def __init__(self, primary_config_file, secondary_config_file):
... | the_stack_v2_python_sparse | govern/data-security/ranger/ranger-tools/src/main/python/ranger_performance_tool/ranger_perf_utils/config_utils.py | alldatacenter/alldata | train | 774 |
fd94796047c557b42d455180121d18b4c96ee72f | [
"from scoop.content.models.content import Content\nuuid = self.value\nstyle = self.kwargs.get('style', 'link')\ncontents = Content.objects.visible().filter(uuid=uuid)\ncontent = contents[0] if contents.exists() else None\nreturn {'content': content, 'style': style}",
"base = super(ContentInline, self).get_templat... | <|body_start_0|>
from scoop.content.models.content import Content
uuid = self.value
style = self.kwargs.get('style', 'link')
contents = Content.objects.visible().filter(uuid=uuid)
content = contents[0] if contents.exists() else None
return {'content': content, 'style': st... | Inline d'insertion de contenus Format : {{content uuid [style=stylename]}} Exemple : {{content identifier style="link"}} | ContentInline | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContentInline:
"""Inline d'insertion de contenus Format : {{content uuid [style=stylename]}} Exemple : {{content identifier style="link"}}"""
def get_context(self):
"""Renvoyer un contexte pour le rendu de l'inline"""
<|body_0|>
def get_template_name(self):
"""Re... | stack_v2_sparse_classes_10k_train_006403 | 6,816 | no_license | [
{
"docstring": "Renvoyer un contexte pour le rendu de l'inline",
"name": "get_context",
"signature": "def get_context(self)"
},
{
"docstring": "Renvoyer le chemin du template",
"name": "get_template_name",
"signature": "def get_template_name(self)"
}
] | 2 | null | Implement the Python class `ContentInline` described below.
Class description:
Inline d'insertion de contenus Format : {{content uuid [style=stylename]}} Exemple : {{content identifier style="link"}}
Method signatures and docstrings:
- def get_context(self): Renvoyer un contexte pour le rendu de l'inline
- def get_te... | Implement the Python class `ContentInline` described below.
Class description:
Inline d'insertion de contenus Format : {{content uuid [style=stylename]}} Exemple : {{content identifier style="link"}}
Method signatures and docstrings:
- def get_context(self): Renvoyer un contexte pour le rendu de l'inline
- def get_te... | 8cef6f6e89c1990e2b25f83e54e0c3481d83b6d7 | <|skeleton|>
class ContentInline:
"""Inline d'insertion de contenus Format : {{content uuid [style=stylename]}} Exemple : {{content identifier style="link"}}"""
def get_context(self):
"""Renvoyer un contexte pour le rendu de l'inline"""
<|body_0|>
def get_template_name(self):
"""Re... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ContentInline:
"""Inline d'insertion de contenus Format : {{content uuid [style=stylename]}} Exemple : {{content identifier style="link"}}"""
def get_context(self):
"""Renvoyer un contexte pour le rendu de l'inline"""
from scoop.content.models.content import Content
uuid = self.va... | the_stack_v2_python_sparse | scoop/content/util/inlines.py | artscoop/scoop | train | 0 |
3fbad9abe1ddc3fdf17c50ca1ca108b45440e426 | [
"Q = self.coll.Qmat if Q is None else Q\nQI = np.zeros_like(Q) if QI is None else QI\nQE = np.zeros_like(Q) if QE is None else QE\nL = self.level\nme = []\nfor m in range(1, self.coll.num_nodes + 1):\n me.append(L.dt * ((Q - QI)[m, 1] * L.f[1].impl + (Q - QE)[m, 1] * L.f[1].expl))\n for j in range(2, self.col... | <|body_start_0|>
Q = self.coll.Qmat if Q is None else Q
QI = np.zeros_like(Q) if QI is None else QI
QE = np.zeros_like(Q) if QE is None else QE
L = self.level
me = []
for m in range(1, self.coll.num_nodes + 1):
me.append(L.dt * ((Q - QI)[m, 1] * L.f[1].impl + ... | Duplicate of `imex_1st_order` sweeper which is slightly more efficient at the cost of code readability. | imex_1st_order_efficient | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class imex_1st_order_efficient:
"""Duplicate of `imex_1st_order` sweeper which is slightly more efficient at the cost of code readability."""
def integrate(self, Q=None, QI=None, QE=None):
"""Integrates the right-hand side (here impl + expl) Args: Q (numpy.ndarray): Full quadrature rule QI... | stack_v2_sparse_classes_10k_train_006404 | 7,777 | permissive | [
{
"docstring": "Integrates the right-hand side (here impl + expl) Args: Q (numpy.ndarray): Full quadrature rule QI (numpy.ndarray): Implicit preconditioner QE (numpy.ndarray): Explicit preconditioner Returns: list of dtype_u: containing the integral as values",
"name": "integrate",
"signature": "def int... | 2 | null | Implement the Python class `imex_1st_order_efficient` described below.
Class description:
Duplicate of `imex_1st_order` sweeper which is slightly more efficient at the cost of code readability.
Method signatures and docstrings:
- def integrate(self, Q=None, QI=None, QE=None): Integrates the right-hand side (here impl... | Implement the Python class `imex_1st_order_efficient` described below.
Class description:
Duplicate of `imex_1st_order` sweeper which is slightly more efficient at the cost of code readability.
Method signatures and docstrings:
- def integrate(self, Q=None, QI=None, QE=None): Integrates the right-hand side (here impl... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class imex_1st_order_efficient:
"""Duplicate of `imex_1st_order` sweeper which is slightly more efficient at the cost of code readability."""
def integrate(self, Q=None, QI=None, QE=None):
"""Integrates the right-hand side (here impl + expl) Args: Q (numpy.ndarray): Full quadrature rule QI... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class imex_1st_order_efficient:
"""Duplicate of `imex_1st_order` sweeper which is slightly more efficient at the cost of code readability."""
def integrate(self, Q=None, QI=None, QE=None):
"""Integrates the right-hand side (here impl + expl) Args: Q (numpy.ndarray): Full quadrature rule QI (numpy.ndarr... | the_stack_v2_python_sparse | pySDC/projects/Resilience/sweepers.py | Parallel-in-Time/pySDC | train | 30 |
5f31c53665618560ad7de4dd2c2c9bf591afe89f | [
"if not root:\n return []\nqueue = deque([(0, root)])\nret = []\nwhile queue:\n l, n = queue.popleft()\n if l < len(ret):\n ret[l].append(n.val)\n else:\n ret.append([n.val])\n if n.children:\n for c in n.children:\n queue.append((l + 1, c))\nreturn ret",
"if not roo... | <|body_start_0|>
if not root:
return []
queue = deque([(0, root)])
ret = []
while queue:
l, n = queue.popleft()
if l < len(ret):
ret[l].append(n.val)
else:
ret.append([n.val])
if n.children:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root: 'Node') -> List[List[int]]:
"""04/28/2020 23:57"""
<|body_0|>
def levelOrder(self, root: 'Node') -> List[List[int]]:
"""08/23/2021 15:04"""
<|body_1|>
def levelOrder(self, root: 'Node') -> List[List[int]]:
"""... | stack_v2_sparse_classes_10k_train_006405 | 4,519 | no_license | [
{
"docstring": "04/28/2020 23:57",
"name": "levelOrder",
"signature": "def levelOrder(self, root: 'Node') -> List[List[int]]"
},
{
"docstring": "08/23/2021 15:04",
"name": "levelOrder",
"signature": "def levelOrder(self, root: 'Node') -> List[List[int]]"
},
{
"docstring": "09/18/... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: 'Node') -> List[List[int]]: 04/28/2020 23:57
- def levelOrder(self, root: 'Node') -> List[List[int]]: 08/23/2021 15:04
- def levelOrder(self, root: 'No... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: 'Node') -> List[List[int]]: 04/28/2020 23:57
- def levelOrder(self, root: 'Node') -> List[List[int]]: 08/23/2021 15:04
- def levelOrder(self, root: 'No... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def levelOrder(self, root: 'Node') -> List[List[int]]:
"""04/28/2020 23:57"""
<|body_0|>
def levelOrder(self, root: 'Node') -> List[List[int]]:
"""08/23/2021 15:04"""
<|body_1|>
def levelOrder(self, root: 'Node') -> List[List[int]]:
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root: 'Node') -> List[List[int]]:
"""04/28/2020 23:57"""
if not root:
return []
queue = deque([(0, root)])
ret = []
while queue:
l, n = queue.popleft()
if l < len(ret):
ret[l].append(n.va... | the_stack_v2_python_sparse | leetcode/solved/764_N-ary_Tree_Level_Order_Traversal/solution.py | sungminoh/algorithms | train | 0 | |
fa83e0fddf69bd0119cf9f296cd1f4783cbea9b4 | [
"self.backup_type = backup_type\nself.copy_partially_successful_run = copy_partially_successful_run\nself.granularity_bucket = granularity_bucket\nself.id = id\nself.retention_policy = retention_policy",
"if dictionary is None:\n return None\nbackup_type = dictionary.get('backupType')\ncopy_partially_successfu... | <|body_start_0|>
self.backup_type = backup_type
self.copy_partially_successful_run = copy_partially_successful_run
self.granularity_bucket = granularity_bucket
self.id = id
self.retention_policy = retention_policy
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
... | Implementation of the 'ExtendedRetentionPolicyProto' model. Message that specifies additional retention policies to apply to backup snapshots. Attributes: backup_type (int): The backup type to which this extended retention applies to. If this is not set, the extended retention will be applicable to all non-log backup t... | ExtendedRetentionPolicyProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtendedRetentionPolicyProto:
"""Implementation of the 'ExtendedRetentionPolicyProto' model. Message that specifies additional retention policies to apply to backup snapshots. Attributes: backup_type (int): The backup type to which this extended retention applies to. If this is not set, the exten... | stack_v2_sparse_classes_10k_train_006406 | 4,004 | permissive | [
{
"docstring": "Constructor for the ExtendedRetentionPolicyProto class",
"name": "__init__",
"signature": "def __init__(self, backup_type=None, copy_partially_successful_run=None, granularity_bucket=None, id=None, retention_policy=None)"
},
{
"docstring": "Creates an instance of this model from ... | 2 | stack_v2_sparse_classes_30k_train_002689 | Implement the Python class `ExtendedRetentionPolicyProto` described below.
Class description:
Implementation of the 'ExtendedRetentionPolicyProto' model. Message that specifies additional retention policies to apply to backup snapshots. Attributes: backup_type (int): The backup type to which this extended retention ap... | Implement the Python class `ExtendedRetentionPolicyProto` described below.
Class description:
Implementation of the 'ExtendedRetentionPolicyProto' model. Message that specifies additional retention policies to apply to backup snapshots. Attributes: backup_type (int): The backup type to which this extended retention ap... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ExtendedRetentionPolicyProto:
"""Implementation of the 'ExtendedRetentionPolicyProto' model. Message that specifies additional retention policies to apply to backup snapshots. Attributes: backup_type (int): The backup type to which this extended retention applies to. If this is not set, the exten... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExtendedRetentionPolicyProto:
"""Implementation of the 'ExtendedRetentionPolicyProto' model. Message that specifies additional retention policies to apply to backup snapshots. Attributes: backup_type (int): The backup type to which this extended retention applies to. If this is not set, the extended retention... | the_stack_v2_python_sparse | cohesity_management_sdk/models/extended_retention_policy_proto.py | cohesity/management-sdk-python | train | 24 |
9f266255e1c50b648cfa6d78fe24d41fda4cd497 | [
"delta_lat = size / 1000.0 / _EARTH_RADIUS_IN_KM * (180.0 / math.pi)\ndelta_lng = delta_lat / math.cos(math.pi * lat / 180.0)\nself._horizontal_stroke = _Polyline([lat, lat], [lng - delta_lng, lng + delta_lng], precision, **kwargs)\nself._vertical_stroke = _Polyline([lat - delta_lat, lat + delta_lat], [lng, lng], p... | <|body_start_0|>
delta_lat = size / 1000.0 / _EARTH_RADIUS_IN_KM * (180.0 / math.pi)
delta_lng = delta_lat / math.cos(math.pi * lat / 180.0)
self._horizontal_stroke = _Polyline([lat, lat], [lng - delta_lng, lng + delta_lng], precision, **kwargs)
self._vertical_stroke = _Polyline([lat - d... | _Plus | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Plus:
def __init__(self, lat, lng, size, precision, **kwargs):
"""Args: lat (float): Latitude of the center of the '+'. lng (float): Longitude of the center of the '+'. size (int): Size of the '+', in meters. precision (int): Number of digits after the decimal to round to for lat/lng va... | stack_v2_sparse_classes_10k_train_006407 | 1,509 | permissive | [
{
"docstring": "Args: lat (float): Latitude of the center of the '+'. lng (float): Longitude of the center of the '+'. size (int): Size of the '+', in meters. precision (int): Number of digits after the decimal to round to for lat/lng values. Optional: Args: color (str): Color of the '+'. Can be hex ('#00FFFF')... | 2 | stack_v2_sparse_classes_30k_train_003691 | Implement the Python class `_Plus` described below.
Class description:
Implement the _Plus class.
Method signatures and docstrings:
- def __init__(self, lat, lng, size, precision, **kwargs): Args: lat (float): Latitude of the center of the '+'. lng (float): Longitude of the center of the '+'. size (int): Size of the ... | Implement the Python class `_Plus` described below.
Class description:
Implement the _Plus class.
Method signatures and docstrings:
- def __init__(self, lat, lng, size, precision, **kwargs): Args: lat (float): Latitude of the center of the '+'. lng (float): Longitude of the center of the '+'. size (int): Size of the ... | 8654a5a370b5ec309e1282c457eaf375c3dcb4bb | <|skeleton|>
class _Plus:
def __init__(self, lat, lng, size, precision, **kwargs):
"""Args: lat (float): Latitude of the center of the '+'. lng (float): Longitude of the center of the '+'. size (int): Size of the '+', in meters. precision (int): Number of digits after the decimal to round to for lat/lng va... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _Plus:
def __init__(self, lat, lng, size, precision, **kwargs):
"""Args: lat (float): Latitude of the center of the '+'. lng (float): Longitude of the center of the '+'. size (int): Size of the '+', in meters. precision (int): Number of digits after the decimal to round to for lat/lng values. Optional... | the_stack_v2_python_sparse | gmplot/drawables/symbols/plus.py | fishke22/gmplot | train | 0 | |
d22cc28a5835a2111c7646ab5cf33c708abc3e5f | [
"if not root:\n return False\nif not root.left and (not root.right):\n return root.val == targetSum\nleft = self.hasPathSum(root.left, targetSum - root.val)\nright = self.hasPathSum(root.right, targetSum - root.val)\nreturn left or right",
"if not root:\n return False\n\ndef traverse(root, count):\n i... | <|body_start_0|>
if not root:
return False
if not root.left and (not root.right):
return root.val == targetSum
left = self.hasPathSum(root.left, targetSum - root.val)
right = self.hasPathSum(root.right, targetSum - root.val)
return left or right
<|end_body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasPathSum1(self, root, targetSum):
""":type root: TreeNode :type targetSum: int :rtype: bool 递归，如果需要搜索整颗二叉树，那么递归函数就不要返回值， 如果要搜索其中一条符合条件的路径，递归函数就需要返回值， 因为遇到符合条件的路径了就要及时返回。"""
<|body_0|>
def hasPathSum(self, root, targetSum):
""":type root: TreeNode :typ... | stack_v2_sparse_classes_10k_train_006408 | 2,781 | no_license | [
{
"docstring": ":type root: TreeNode :type targetSum: int :rtype: bool 递归，如果需要搜索整颗二叉树，那么递归函数就不要返回值， 如果要搜索其中一条符合条件的路径，递归函数就需要返回值， 因为遇到符合条件的路径了就要及时返回。",
"name": "hasPathSum1",
"signature": "def hasPathSum1(self, root, targetSum)"
},
{
"docstring": ":type root: TreeNode :type targetSum: int :rtype:... | 3 | stack_v2_sparse_classes_30k_train_003980 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum1(self, root, targetSum): :type root: TreeNode :type targetSum: int :rtype: bool 递归，如果需要搜索整颗二叉树，那么递归函数就不要返回值， 如果要搜索其中一条符合条件的路径，递归函数就需要返回值， 因为遇到符合条件的路径了就要及时返回。
- def... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum1(self, root, targetSum): :type root: TreeNode :type targetSum: int :rtype: bool 递归，如果需要搜索整颗二叉树，那么递归函数就不要返回值， 如果要搜索其中一条符合条件的路径，递归函数就需要返回值， 因为遇到符合条件的路径了就要及时返回。
- def... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def hasPathSum1(self, root, targetSum):
""":type root: TreeNode :type targetSum: int :rtype: bool 递归，如果需要搜索整颗二叉树，那么递归函数就不要返回值， 如果要搜索其中一条符合条件的路径，递归函数就需要返回值， 因为遇到符合条件的路径了就要及时返回。"""
<|body_0|>
def hasPathSum(self, root, targetSum):
""":type root: TreeNode :typ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def hasPathSum1(self, root, targetSum):
""":type root: TreeNode :type targetSum: int :rtype: bool 递归，如果需要搜索整颗二叉树，那么递归函数就不要返回值， 如果要搜索其中一条符合条件的路径，递归函数就需要返回值， 因为遇到符合条件的路径了就要及时返回。"""
if not root:
return False
if not root.left and (not root.right):
return r... | the_stack_v2_python_sparse | 112.路径总和.py | yangyuxiang1996/leetcode | train | 0 | |
964108a024c9f534d58c8b027b971aaefeb440bd | [
"self.head = head\nself.count = 0\nwhile head:\n self.count += 1\n head = head.next",
"randnode = random.randint(0, self.count - 1)\nnode = self.head\nfor _ in range(randnode):\n node = node.next\nreturn node.val"
] | <|body_start_0|>
self.head = head
self.count = 0
while head:
self.count += 1
head = head.next
<|end_body_0|>
<|body_start_1|>
randnode = random.randint(0, self.count - 1)
node = self.head
for _ in range(randnode):
node = node.next
... | 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):
"""Returns a random node's value. :rtype: int"""
... | stack_v2_sparse_classes_10k_train_006409 | 1,294 | 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": "Returns a random node's value. :rtype: int",
"name": "g... | 2 | stack_v2_sparse_classes_30k_val_000033 | 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... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|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):
"""Returns a random node's value. :rtype: int"""
... | stack_v2_sparse_classes_10k | 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.head = head
self.count = 0
while head:
self.count += 1
head = head.... | the_stack_v2_python_sparse | python_1_to_1000/382_Linked_List_Random_Node.py | jakehoare/leetcode | train | 58 | |
f0493c348d3af52f361513921d87bf8c06bc4055 | [
"if s == s[::-1]:\n return s\nLen = 1\nstart = 0\nfor i in range(1, len(s)):\n p1, p2 = (i - Len, i + 1)\n if p1 >= 1:\n temp = s[p1 - 1:p2]\n if temp == temp[::-1]:\n start = p1 - 1\n Len += 2\n continue\n if p1 >= 0:\n temp = s[p1:p2]\n if t... | <|body_start_0|>
if s == s[::-1]:
return s
Len = 1
start = 0
for i in range(1, len(s)):
p1, p2 = (i - Len, i + 1)
if p1 >= 1:
temp = s[p1 - 1:p2]
if temp == temp[::-1]:
start = p1 - 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome_mysecond_fromcenter(self, s):
""":type s: str :rtype: str"""
<|body_1|>
def longestPalindrome_myfirst(self, s):
""":type s: str :rtype: str"... | stack_v2_sparse_classes_10k_train_006410 | 2,919 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome_mysecond_fromcenter",
"signature": "def longestPalindrome_mysecond_fromcenter(self, s)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_006679 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def longestPalindrome_mysecond_fromcenter(self, s): :type s: str :rtype: str
- def longestPalindrome_myfirst(self, s): ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def longestPalindrome_mysecond_fromcenter(self, s): :type s: str :rtype: str
- def longestPalindrome_myfirst(self, s): ... | f0d9070fa292ca36971a465a805faddb12025482 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome_mysecond_fromcenter(self, s):
""":type s: str :rtype: str"""
<|body_1|>
def longestPalindrome_myfirst(self, s):
""":type s: str :rtype: str"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
if s == s[::-1]:
return s
Len = 1
start = 0
for i in range(1, len(s)):
p1, p2 = (i - Len, i + 1)
if p1 >= 1:
temp = s[p1 - 1:p2]
... | the_stack_v2_python_sparse | 5.LongestPalindromicSubstring.py | JerryRoc/leetcode | train | 0 | |
6727d0823ebc4b00846bc7eb6387aac3611391a9 | [
"if name is None:\n return jsonify(responses.missing_parameters)\nsensor = Sensor.objects(name=name).first()\nif sensor is None:\n return jsonify(responses.invalid_uuid)\ntags_owned = [{'name': tag.name, 'value': tag.value} for tag in sensor.tags]\nmetadata = Sensor._get_collection().find({'name': name}, {'me... | <|body_start_0|>
if name is None:
return jsonify(responses.missing_parameters)
sensor = Sensor.objects(name=name).first()
if sensor is None:
return jsonify(responses.invalid_uuid)
tags_owned = [{'name': tag.name, 'value': tag.value} for tag in sensor.tags]
... | SensorService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensorService:
def get(self, name):
"""Retrieve sensor details based on uuid specified Args as data: name : <name of sensor> Returns (JSON): { 'building': <name of building in which sensor is present>, 'name' : <sensor uuid>, 'tags' : tags_owned, 'metadata' : metadata, 'source_identifier... | stack_v2_sparse_classes_10k_train_006411 | 3,642 | permissive | [
{
"docstring": "Retrieve sensor details based on uuid specified Args as data: name : <name of sensor> Returns (JSON): { 'building': <name of building in which sensor is present>, 'name' : <sensor uuid>, 'tags' : tags_owned, 'metadata' : metadata, 'source_identifier' : str(sensor.source_identifier), 'source_name... | 2 | stack_v2_sparse_classes_30k_train_000571 | Implement the Python class `SensorService` described below.
Class description:
Implement the SensorService class.
Method signatures and docstrings:
- def get(self, name): Retrieve sensor details based on uuid specified Args as data: name : <name of sensor> Returns (JSON): { 'building': <name of building in which sens... | Implement the Python class `SensorService` described below.
Class description:
Implement the SensorService class.
Method signatures and docstrings:
- def get(self, name): Retrieve sensor details based on uuid specified Args as data: name : <name of sensor> Returns (JSON): { 'building': <name of building in which sens... | 53ba7519c56d46af1e32a77aab5cf1c5cd8143fc | <|skeleton|>
class SensorService:
def get(self, name):
"""Retrieve sensor details based on uuid specified Args as data: name : <name of sensor> Returns (JSON): { 'building': <name of building in which sensor is present>, 'name' : <sensor uuid>, 'tags' : tags_owned, 'metadata' : metadata, 'source_identifier... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SensorService:
def get(self, name):
"""Retrieve sensor details based on uuid specified Args as data: name : <name of sensor> Returns (JSON): { 'building': <name of building in which sensor is present>, 'name' : <sensor uuid>, 'tags' : tags_owned, 'metadata' : metadata, 'source_identifier' : str(sensor... | the_stack_v2_python_sparse | BuildingDepot-v3.2.8/buildingdepot/CentralService/app/rest_api/sensors/sensor.py | Entromorgan/GIoTTo | train | 0 | |
4ade24baff66daa44ecfc0010d597d1df486f7c3 | [
"response = super().to_representation(instance)\nif hasattr(response, 'user'):\n response['user'] = {'id': instance.user.id}\nif hasattr(response, 'listing'):\n response['listing'] = {'id': instance.listing.id}\nreturn response",
"request = self.context.get('request')\ndata['user'] = request.user\nif data['... | <|body_start_0|>
response = super().to_representation(instance)
if hasattr(response, 'user'):
response['user'] = {'id': instance.user.id}
if hasattr(response, 'listing'):
response['listing'] = {'id': instance.listing.id}
return response
<|end_body_0|>
<|body_star... | Serializer to create galleries | GallerySerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GallerySerializer:
"""Serializer to create galleries"""
def to_representation(self, instance):
"""Return only the id of the user or listing for the gallery and not the entire object."""
<|body_0|>
def validate(self, data):
"""Validate creation of gallery. - Check... | stack_v2_sparse_classes_10k_train_006412 | 2,374 | no_license | [
{
"docstring": "Return only the id of the user or listing for the gallery and not the entire object.",
"name": "to_representation",
"signature": "def to_representation(self, instance)"
},
{
"docstring": "Validate creation of gallery. - Check if user exists or has listing to make gallery - Check ... | 2 | stack_v2_sparse_classes_30k_train_005075 | Implement the Python class `GallerySerializer` described below.
Class description:
Serializer to create galleries
Method signatures and docstrings:
- def to_representation(self, instance): Return only the id of the user or listing for the gallery and not the entire object.
- def validate(self, data): Validate creatio... | Implement the Python class `GallerySerializer` described below.
Class description:
Serializer to create galleries
Method signatures and docstrings:
- def to_representation(self, instance): Return only the id of the user or listing for the gallery and not the entire object.
- def validate(self, data): Validate creatio... | 1f2c8c232372de6a40089c8b867ce1798d2296c7 | <|skeleton|>
class GallerySerializer:
"""Serializer to create galleries"""
def to_representation(self, instance):
"""Return only the id of the user or listing for the gallery and not the entire object."""
<|body_0|>
def validate(self, data):
"""Validate creation of gallery. - Check... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GallerySerializer:
"""Serializer to create galleries"""
def to_representation(self, instance):
"""Return only the id of the user or listing for the gallery and not the entire object."""
response = super().to_representation(instance)
if hasattr(response, 'user'):
respon... | the_stack_v2_python_sparse | core/roommates_api/serializers/gallery_serializers.py | harmanT23/yournextroommates | train | 1 |
c9b35349b6916ecf5981f3cd0c7548abb28ba931 | [
"l = len(s)\nstep = 1\ncur = s[0:step]\nwhile step < l:\n if l % step == 0:\n i = 1\n while i < l // step:\n if s[step * i:step * i + step] != cur:\n break\n i += 1\n if i == l // step:\n return True\n step += 1\n cur = s[0:step]\nreturn ... | <|body_start_0|>
l = len(s)
step = 1
cur = s[0:step]
while step < l:
if l % step == 0:
i = 1
while i < l // step:
if s[step * i:step * i + step] != cur:
break
i += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def repeatedSubstringPattern(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def repeatedSubstringPattern(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l = len(s)
step = 1
cur =... | stack_v2_sparse_classes_10k_train_006413 | 716 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "repeatedSubstringPattern",
"signature": "def repeatedSubstringPattern(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "repeatedSubstringPattern",
"signature": "def repeatedSubstringPattern(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def repeatedSubstringPattern(self, s): :type s: str :rtype: bool
- def repeatedSubstringPattern(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 repeatedSubstringPattern(self, s): :type s: str :rtype: bool
- def repeatedSubstringPattern(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def repeate... | 7c5e5fe76cee542f67cd7dd3a389470b02597548 | <|skeleton|>
class Solution:
def repeatedSubstringPattern(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def repeatedSubstringPattern(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def repeatedSubstringPattern(self, s):
""":type s: str :rtype: bool"""
l = len(s)
step = 1
cur = s[0:step]
while step < l:
if l % step == 0:
i = 1
while i < l // step:
if s[step * i:step * i + ste... | the_stack_v2_python_sparse | 459. Repeated Substring Pattern.py | Mschikay/leetcode | train | 0 | |
9689eeca03569387815b68344597f6e1c00654f0 | [
"super(AlphaBeta, self).__init__()\nself.portfolioReturn = portfolioReturn\nself.benchmarkReturn = benchmarkReturn\nself.riskfreeRate = riskfreeRate",
"alphas = []\nbetas = []\nfor i in range(len(self.portfolioReturn)):\n if i == 0:\n alpha = np.nan\n beta = np.nan\n else:\n n = i + 1\n... | <|body_start_0|>
super(AlphaBeta, self).__init__()
self.portfolioReturn = portfolioReturn
self.benchmarkReturn = benchmarkReturn
self.riskfreeRate = riskfreeRate
<|end_body_0|>
<|body_start_1|>
alphas = []
betas = []
for i in range(len(self.portfolioReturn)):
... | Alpha-beta of the given profit returns to the risk free rate. | AlphaBeta | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlphaBeta:
"""Alpha-beta of the given profit returns to the risk free rate."""
def __init__(self, portfolioReturn, benchmarkReturn, riskfreeRate):
"""Initialize the AlphaBeta calculator with the portfolio data and a benchmark one. Parameters ---------- portfolioReturn : pandas.Series... | stack_v2_sparse_classes_10k_train_006414 | 10,010 | permissive | [
{
"docstring": "Initialize the AlphaBeta calculator with the portfolio data and a benchmark one. Parameters ---------- portfolioReturn : pandas.Series annual returns indexed by trading date as strings in the format %Y%m%d; benchmarkReturn : pandas.Series benchmark return indexed by trading date as strings in th... | 2 | stack_v2_sparse_classes_30k_train_000819 | Implement the Python class `AlphaBeta` described below.
Class description:
Alpha-beta of the given profit returns to the risk free rate.
Method signatures and docstrings:
- def __init__(self, portfolioReturn, benchmarkReturn, riskfreeRate): Initialize the AlphaBeta calculator with the portfolio data and a benchmark o... | Implement the Python class `AlphaBeta` described below.
Class description:
Alpha-beta of the given profit returns to the risk free rate.
Method signatures and docstrings:
- def __init__(self, portfolioReturn, benchmarkReturn, riskfreeRate): Initialize the AlphaBeta calculator with the portfolio data and a benchmark o... | 139d604177da3855503643e0fcfa87711ba7e588 | <|skeleton|>
class AlphaBeta:
"""Alpha-beta of the given profit returns to the risk free rate."""
def __init__(self, portfolioReturn, benchmarkReturn, riskfreeRate):
"""Initialize the AlphaBeta calculator with the portfolio data and a benchmark one. Parameters ---------- portfolioReturn : pandas.Series... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AlphaBeta:
"""Alpha-beta of the given profit returns to the risk free rate."""
def __init__(self, portfolioReturn, benchmarkReturn, riskfreeRate):
"""Initialize the AlphaBeta calculator with the portfolio data and a benchmark one. Parameters ---------- portfolioReturn : pandas.Series annual retur... | the_stack_v2_python_sparse | analytics/riskMeasurement/riskMetric.py | WinQuant/arsenal | train | 0 |
23509248321e8b3b939dba7d92e4b3f406c684ac | [
"sqlalchemy_uri = self.get_uri()\nsqlite_uri = sqlalchemy_uri.replace('sqlite:///', 'file:')\nconn = sqlite3.connect(sqlite_uri, uri=True)\nreturn conn",
"conn_id = getattr(self, self.conn_name_attr)\nairflow_conn = self.get_connection(conn_id)\nif airflow_conn.conn_type is None:\n airflow_conn.conn_type = sel... | <|body_start_0|>
sqlalchemy_uri = self.get_uri()
sqlite_uri = sqlalchemy_uri.replace('sqlite:///', 'file:')
conn = sqlite3.connect(sqlite_uri, uri=True)
return conn
<|end_body_0|>
<|body_start_1|>
conn_id = getattr(self, self.conn_name_attr)
airflow_conn = self.get_conne... | Interact with SQLite. | SqliteHook | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqliteHook:
"""Interact with SQLite."""
def get_conn(self) -> sqlite3.dbapi2.Connection:
"""Returns a sqlite connection object."""
<|body_0|>
def get_uri(self) -> str:
"""Override DbApiHook get_uri method for get_sqlalchemy_engine()."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_10k_train_006415 | 2,402 | permissive | [
{
"docstring": "Returns a sqlite connection object.",
"name": "get_conn",
"signature": "def get_conn(self) -> sqlite3.dbapi2.Connection"
},
{
"docstring": "Override DbApiHook get_uri method for get_sqlalchemy_engine().",
"name": "get_uri",
"signature": "def get_uri(self) -> str"
}
] | 2 | null | Implement the Python class `SqliteHook` described below.
Class description:
Interact with SQLite.
Method signatures and docstrings:
- def get_conn(self) -> sqlite3.dbapi2.Connection: Returns a sqlite connection object.
- def get_uri(self) -> str: Override DbApiHook get_uri method for get_sqlalchemy_engine(). | Implement the Python class `SqliteHook` described below.
Class description:
Interact with SQLite.
Method signatures and docstrings:
- def get_conn(self) -> sqlite3.dbapi2.Connection: Returns a sqlite connection object.
- def get_uri(self) -> str: Override DbApiHook get_uri method for get_sqlalchemy_engine().
<|skele... | 1b122c15030e99cef9d4ff26d3781a7a9d6949bc | <|skeleton|>
class SqliteHook:
"""Interact with SQLite."""
def get_conn(self) -> sqlite3.dbapi2.Connection:
"""Returns a sqlite connection object."""
<|body_0|>
def get_uri(self) -> str:
"""Override DbApiHook get_uri method for get_sqlalchemy_engine()."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SqliteHook:
"""Interact with SQLite."""
def get_conn(self) -> sqlite3.dbapi2.Connection:
"""Returns a sqlite connection object."""
sqlalchemy_uri = self.get_uri()
sqlite_uri = sqlalchemy_uri.replace('sqlite:///', 'file:')
conn = sqlite3.connect(sqlite_uri, uri=True)
... | the_stack_v2_python_sparse | airflow/providers/sqlite/hooks/sqlite.py | apache/airflow | train | 22,756 |
60dfebbf7e17ad808dc88026523469f4eca9367f | [
"try:\n\n def generate(vo):\n for exception in list_exceptions(vo=vo):\n yield (dumps(exception, cls=APIEncoder) + '\\n')\n return try_stream(generate(vo=request.environ.get('vo')))\nexcept LifetimeExceptionNotFound as error:\n return generate_http_error_flask(404, error)",
"parameters ... | <|body_start_0|>
try:
def generate(vo):
for exception in list_exceptions(vo=vo):
yield (dumps(exception, cls=APIEncoder) + '\n')
return try_stream(generate(vo=request.environ.get('vo')))
except LifetimeExceptionNotFound as error:
r... | REST APIs for Lifetime Model exception. | LifetimeException | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LifetimeException:
"""REST APIs for Lifetime Model exception."""
def get(self):
"""--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception pe... | stack_v2_sparse_classes_10k_train_006416 | 12,043 | permissive | [
{
"docstring": "--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception per line. type: array items: description: A lifetime exception type: object properties: id: descr... | 2 | null | Implement the Python class `LifetimeException` described below.
Class description:
REST APIs for Lifetime Model exception.
Method signatures and docstrings:
- def get(self): --- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: applica... | Implement the Python class `LifetimeException` described below.
Class description:
REST APIs for Lifetime Model exception.
Method signatures and docstrings:
- def get(self): --- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: applica... | 7f0d229ac0b3bc7dec12c6e158bea2b82d414a3b | <|skeleton|>
class LifetimeException:
"""REST APIs for Lifetime Model exception."""
def get(self):
"""--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception pe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LifetimeException:
"""REST APIs for Lifetime Model exception."""
def get(self):
"""--- summary: List Exceptions description: Retrieves all exceptions. tags: - Lifetime Exceptions responses: 200: description: OK content: application/x-json-stream: schema: description: One exception per line. type:... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/lifetime_exceptions.py | rucio/rucio | train | 232 |
86900507eb1c7bbb75bb1acb8836d304c1f4e76e | [
"if self.key not in data:\n _logger.debug(f'Could not find {self.key} key.')\n data[self.key] = self.get_hash(circuit)\n return True\nnew_hash = self.get_hash(circuit)\nif data[self.key] == new_hash:\n _logger.debug('Hashes match; no change detected.')\n return False\ndata[self.key] = new_hash\n_logg... | <|body_start_0|>
if self.key not in data:
_logger.debug(f'Could not find {self.key} key.')
data[self.key] = self.get_hash(circuit)
return True
new_hash = self.get_hash(circuit)
if data[self.key] == new_hash:
_logger.debug('Hashes match; no change d... | The ChangePredicate class. The ChangePredicate returns true if the circuit has changed since the last call. On the first call, the predicate returns true. | ChangePredicate | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChangePredicate:
"""The ChangePredicate class. The ChangePredicate returns true if the circuit has changed since the last call. On the first call, the predicate returns true."""
def get_truth_value(self, circuit: Circuit, data: PassData) -> bool:
"""Call this predicate, see :class:`P... | stack_v2_sparse_classes_10k_train_006417 | 1,984 | permissive | [
{
"docstring": "Call this predicate, see :class:`PassPredicate` for more info.",
"name": "get_truth_value",
"signature": "def get_truth_value(self, circuit: Circuit, data: PassData) -> bool"
},
{
"docstring": "Retreive hash associated with `circuit`.",
"name": "get_hash",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_005499 | Implement the Python class `ChangePredicate` described below.
Class description:
The ChangePredicate class. The ChangePredicate returns true if the circuit has changed since the last call. On the first call, the predicate returns true.
Method signatures and docstrings:
- def get_truth_value(self, circuit: Circuit, da... | Implement the Python class `ChangePredicate` described below.
Class description:
The ChangePredicate class. The ChangePredicate returns true if the circuit has changed since the last call. On the first call, the predicate returns true.
Method signatures and docstrings:
- def get_truth_value(self, circuit: Circuit, da... | c89112d15072e8ffffb68cf1757b184e2aeb3dc8 | <|skeleton|>
class ChangePredicate:
"""The ChangePredicate class. The ChangePredicate returns true if the circuit has changed since the last call. On the first call, the predicate returns true."""
def get_truth_value(self, circuit: Circuit, data: PassData) -> bool:
"""Call this predicate, see :class:`P... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ChangePredicate:
"""The ChangePredicate class. The ChangePredicate returns true if the circuit has changed since the last call. On the first call, the predicate returns true."""
def get_truth_value(self, circuit: Circuit, data: PassData) -> bool:
"""Call this predicate, see :class:`PassPredicate`... | the_stack_v2_python_sparse | bqskit/passes/control/predicates/change.py | BQSKit/bqskit | train | 54 |
adee28b65fc41db2414026f42a549c2495195562 | [
"self.res = []\nself.getPaths(root, '')\nreturn self.res",
"if root == None:\n return\nif path == '':\n path = path + str(root.val)\nelse:\n path = path + '->' + str(root.val)\nif root.left == None and root.right == None:\n self.res.append(path)\nelse:\n self.getPaths(root.left, path)\n self.get... | <|body_start_0|>
self.res = []
self.getPaths(root, '')
return self.res
<|end_body_0|>
<|body_start_1|>
if root == None:
return
if path == '':
path = path + str(root.val)
else:
path = path + '->' + str(root.val)
if root.left == ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def binaryTreePaths(self, root):
""":type root: TreeNode :rtype: List[str]"""
<|body_0|>
def getPaths(self, root, path):
""":type root: TreeNode :rtype: None"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.res = []
self.getPat... | stack_v2_sparse_classes_10k_train_006418 | 1,625 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[str]",
"name": "binaryTreePaths",
"signature": "def binaryTreePaths(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: None",
"name": "getPaths",
"signature": "def getPaths(self, root, path)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001050 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binaryTreePaths(self, root): :type root: TreeNode :rtype: List[str]
- def getPaths(self, root, path): :type root: TreeNode :rtype: None | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binaryTreePaths(self, root): :type root: TreeNode :rtype: List[str]
- def getPaths(self, root, path): :type root: TreeNode :rtype: None
<|skeleton|>
class Solution:
def... | 8cda0518440488992d7e2c70cb8555ec7b34083f | <|skeleton|>
class Solution:
def binaryTreePaths(self, root):
""":type root: TreeNode :rtype: List[str]"""
<|body_0|>
def getPaths(self, root, path):
""":type root: TreeNode :rtype: None"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def binaryTreePaths(self, root):
""":type root: TreeNode :rtype: List[str]"""
self.res = []
self.getPaths(root, '')
return self.res
def getPaths(self, root, path):
""":type root: TreeNode :rtype: None"""
if root == None:
return
... | the_stack_v2_python_sparse | 257/main.py | szhongren/leetcode | train | 0 | |
bee3d4f0aea87a8bf7d2551f4a0f57068b3b36dc | [
"fast, slow = (head, head)\nwhile fast and fast.next:\n fast, slow = (fast.next.next, slow.next)\n if fast is slow:\n fast = head\n while fast is not slow:\n fast, slow = (fast.next, slow.next)\n return fast\nreturn None",
"if len(data) == 0 or data is None:\n return None\... | <|body_start_0|>
fast, slow = (head, head)
while fast and fast.next:
fast, slow = (fast.next.next, slow.next)
if fast is slow:
fast = head
while fast is not slow:
fast, slow = (fast.next, slow.next)
return fast
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def createList(self, data):
""":param data: a list :return: a head node to a linked list"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
fast, slow = (head... | stack_v2_sparse_classes_10k_train_006419 | 1,748 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "detectCycle",
"signature": "def detectCycle(self, head)"
},
{
"docstring": ":param data: a list :return: a head node to a linked list",
"name": "createList",
"signature": "def createList(self, data)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detectCycle(self, head): :type head: ListNode :rtype: ListNode
- def createList(self, data): :param data: a list :return: a head node to a linked list | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detectCycle(self, head): :type head: ListNode :rtype: ListNode
- def createList(self, data): :param data: a list :return: a head node to a linked list
<|skeleton|>
class Sol... | a5b02044ef39154b6a8d32eb57682f447e1632ba | <|skeleton|>
class Solution:
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def createList(self, data):
""":param data: a list :return: a head node to a linked list"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
fast, slow = (head, head)
while fast and fast.next:
fast, slow = (fast.next.next, slow.next)
if fast is slow:
fast = head
while fast is not slow:
... | the_stack_v2_python_sparse | algo/list/linked_list_cycle_II.py | xys234/coding-problems | train | 0 | |
5b0500661a868e1922a93a3abd6f634c0d08e8ec | [
"self.name = name\nself.num = num\nself.course = course\nself.classes = classes\nself.teacher = teacher\nself.student = student",
"ret = MyPickle.load(settings.schoolinfo)\nfor i in ret.values():\n if self.name == i.name:\n Public.print('%s已经存在！' % self.name, 'error')\n return 0\nself.num = len(r... | <|body_start_0|>
self.name = name
self.num = num
self.course = course
self.classes = classes
self.teacher = teacher
self.student = student
<|end_body_0|>
<|body_start_1|>
ret = MyPickle.load(settings.schoolinfo)
for i in ret.values():
if self.... | School | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class School:
def __init__(self, name, num=0, classes={}, course={}, teacher={}, student={}):
""":param name: 学校名称 :param num: 学校的ID :param classes: 学校包含的所有班级 :param course: 学校包含的所有课程 :param teacher: 学校包含的所有老师 :param student: 包含学校的所有学生"""
<|body_0|>
def create(self):
"""创建... | stack_v2_sparse_classes_10k_train_006420 | 3,775 | no_license | [
{
"docstring": ":param name: 学校名称 :param num: 学校的ID :param classes: 学校包含的所有班级 :param course: 学校包含的所有课程 :param teacher: 学校包含的所有老师 :param student: 包含学校的所有学生",
"name": "__init__",
"signature": "def __init__(self, name, num=0, classes={}, course={}, teacher={}, student={})"
},
{
"docstring": "创建学校 :... | 2 | stack_v2_sparse_classes_30k_train_006963 | Implement the Python class `School` described below.
Class description:
Implement the School class.
Method signatures and docstrings:
- def __init__(self, name, num=0, classes={}, course={}, teacher={}, student={}): :param name: 学校名称 :param num: 学校的ID :param classes: 学校包含的所有班级 :param course: 学校包含的所有课程 :param teacher:... | Implement the Python class `School` described below.
Class description:
Implement the School class.
Method signatures and docstrings:
- def __init__(self, name, num=0, classes={}, course={}, teacher={}, student={}): :param name: 学校名称 :param num: 学校的ID :param classes: 学校包含的所有班级 :param course: 学校包含的所有课程 :param teacher:... | d7fc68d3d23345df5bfb09d4a84686c8b49a5ad7 | <|skeleton|>
class School:
def __init__(self, name, num=0, classes={}, course={}, teacher={}, student={}):
""":param name: 学校名称 :param num: 学校的ID :param classes: 学校包含的所有班级 :param course: 学校包含的所有课程 :param teacher: 学校包含的所有老师 :param student: 包含学校的所有学生"""
<|body_0|>
def create(self):
"""创建... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class School:
def __init__(self, name, num=0, classes={}, course={}, teacher={}, student={}):
""":param name: 学校名称 :param num: 学校的ID :param classes: 学校包含的所有班级 :param course: 学校包含的所有课程 :param teacher: 学校包含的所有老师 :param student: 包含学校的所有学生"""
self.name = name
self.num = num
self.course =... | the_stack_v2_python_sparse | Homework/day07/core/school.py | 214031230/Python21 | train | 0 | |
b3b5a46342b86652deb5a903b9cf477dcc9c5fd6 | [
"self.enable_fips_mode = enable_fips_mode\nself.enable_hardware_encryption = enable_hardware_encryption\nself.enable_software_encryption = enable_software_encryption\nself.rotation_period = rotation_period",
"if dictionary is None:\n return None\nenable_fips_mode = dictionary.get('enableFipsMode')\nenable_hard... | <|body_start_0|>
self.enable_fips_mode = enable_fips_mode
self.enable_hardware_encryption = enable_hardware_encryption
self.enable_software_encryption = enable_software_encryption
self.rotation_period = rotation_period
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
... | Implementation of the 'EncryptionConfiguration' model. Specifies the parameters the user wants to use when configuring encryption for the new Cluster. Attributes: enable_fips_mode (bool): Specifies whether or not to enable FIPS mode. EnableSoftwareEncryption must be set to true in order to enable FIPS. enable_hardware_... | EncryptionConfiguration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncryptionConfiguration:
"""Implementation of the 'EncryptionConfiguration' model. Specifies the parameters the user wants to use when configuring encryption for the new Cluster. Attributes: enable_fips_mode (bool): Specifies whether or not to enable FIPS mode. EnableSoftwareEncryption must be se... | stack_v2_sparse_classes_10k_train_006421 | 3,088 | permissive | [
{
"docstring": "Constructor for the EncryptionConfiguration class",
"name": "__init__",
"signature": "def __init__(self, enable_fips_mode=None, enable_hardware_encryption=None, enable_software_encryption=None, rotation_period=None)"
},
{
"docstring": "Creates an instance of this model from a dic... | 2 | null | Implement the Python class `EncryptionConfiguration` described below.
Class description:
Implementation of the 'EncryptionConfiguration' model. Specifies the parameters the user wants to use when configuring encryption for the new Cluster. Attributes: enable_fips_mode (bool): Specifies whether or not to enable FIPS mo... | Implement the Python class `EncryptionConfiguration` described below.
Class description:
Implementation of the 'EncryptionConfiguration' model. Specifies the parameters the user wants to use when configuring encryption for the new Cluster. Attributes: enable_fips_mode (bool): Specifies whether or not to enable FIPS mo... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class EncryptionConfiguration:
"""Implementation of the 'EncryptionConfiguration' model. Specifies the parameters the user wants to use when configuring encryption for the new Cluster. Attributes: enable_fips_mode (bool): Specifies whether or not to enable FIPS mode. EnableSoftwareEncryption must be se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncryptionConfiguration:
"""Implementation of the 'EncryptionConfiguration' model. Specifies the parameters the user wants to use when configuring encryption for the new Cluster. Attributes: enable_fips_mode (bool): Specifies whether or not to enable FIPS mode. EnableSoftwareEncryption must be set to true in ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/encryption_configuration.py | cohesity/management-sdk-python | train | 24 |
ad14551af5a156ae4c87b25bdcb75383ea771922 | [
"digits_len = len(digits)\nif not self.increment_digit(digits, digits_len - 1, 1):\n return digits\nfor i in range(digits_len - 2, -1, -1):\n if not self.increment_digit(digits, i, 1):\n break\nreturn digits",
"new_digit = digits[i] + carry\ndigits[i] = new_digit % 10\ncarry = new_digit // 10\nif i =... | <|body_start_0|>
digits_len = len(digits)
if not self.increment_digit(digits, digits_len - 1, 1):
return digits
for i in range(digits_len - 2, -1, -1):
if not self.increment_digit(digits, i, 1):
break
return digits
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def plusOne(self, digits: List[int]) -> List[int]:
"""(Solution, list of int) -> list of int Return a list of digits representing a number that is one higher than the number represented by digits. >>> soln = Solution() >>> soln.plusOne([1, 2, 3]) [1, 2, 4] >>> soln.plusOne([4, ... | stack_v2_sparse_classes_10k_train_006422 | 2,409 | no_license | [
{
"docstring": "(Solution, list of int) -> list of int Return a list of digits representing a number that is one higher than the number represented by digits. >>> soln = Solution() >>> soln.plusOne([1, 2, 3]) [1, 2, 4] >>> soln.plusOne([4, 3, 2, 1]) [4, 3, 2, 2] >>> soln.plusOne([9]) [1, 0]",
"name": "plusO... | 2 | stack_v2_sparse_classes_30k_train_004756 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits: List[int]) -> List[int]: (Solution, list of int) -> list of int Return a list of digits representing a number that is one higher than the number represe... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits: List[int]) -> List[int]: (Solution, list of int) -> list of int Return a list of digits representing a number that is one higher than the number represe... | 6812253b90bdd5a35c6bfba8eac54da9be26d56c | <|skeleton|>
class Solution:
def plusOne(self, digits: List[int]) -> List[int]:
"""(Solution, list of int) -> list of int Return a list of digits representing a number that is one higher than the number represented by digits. >>> soln = Solution() >>> soln.plusOne([1, 2, 3]) [1, 2, 4] >>> soln.plusOne([4, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def plusOne(self, digits: List[int]) -> List[int]:
"""(Solution, list of int) -> list of int Return a list of digits representing a number that is one higher than the number represented by digits. >>> soln = Solution() >>> soln.plusOne([1, 2, 3]) [1, 2, 4] >>> soln.plusOne([4, 3, 2, 1]) [4, ... | the_stack_v2_python_sparse | python3/plusOne.py | yichuanma95/leetcode-solns | train | 2 | |
813362b8df0c6241ec1d8bcdce7750e4b2355363 | [
"def inorder(root):\n if not root:\n return\n inorder(root.left)\n ans.append(root.val)\n inorder(root.right)\nans = []\ninorder(root)\nreturn ans",
"def preorder(root):\n if not root:\n return\n ans.append(root)\n preorder(root.left)\n preorder(root.right)\nans = []\npreorde... | <|body_start_0|>
def inorder(root):
if not root:
return
inorder(root.left)
ans.append(root.val)
inorder(root.right)
ans = []
inorder(root)
return ans
<|end_body_0|>
<|body_start_1|>
def preorder(root):
i... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def inorderTraversal(self, root):
"""采用递归方法实现 中序遍历 :param root: TreeNode :return: List[int]"""
<|body_0|>
def preorderTraversal(self, root):
"""采用递归方法实现 先序遍历 :param root: TreeNode :return: List[int]"""
<|body_1|>
def postorderTraversal(self, r... | stack_v2_sparse_classes_10k_train_006423 | 1,981 | no_license | [
{
"docstring": "采用递归方法实现 中序遍历 :param root: TreeNode :return: List[int]",
"name": "inorderTraversal",
"signature": "def inorderTraversal(self, root)"
},
{
"docstring": "采用递归方法实现 先序遍历 :param root: TreeNode :return: List[int]",
"name": "preorderTraversal",
"signature": "def preorderTraversa... | 3 | stack_v2_sparse_classes_30k_train_005944 | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def inorderTraversal(self, root): 采用递归方法实现 中序遍历 :param root: TreeNode :return: List[int]
- def preorderTraversal(self, root): 采用递归方法实现 先序遍历 :param root: TreeNode :return: List[... | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def inorderTraversal(self, root): 采用递归方法实现 中序遍历 :param root: TreeNode :return: List[int]
- def preorderTraversal(self, root): 采用递归方法实现 先序遍历 :param root: TreeNode :return: List[... | e03b8a324e816fee9c8440552de825be07132170 | <|skeleton|>
class Solution1:
def inorderTraversal(self, root):
"""采用递归方法实现 中序遍历 :param root: TreeNode :return: List[int]"""
<|body_0|>
def preorderTraversal(self, root):
"""采用递归方法实现 先序遍历 :param root: TreeNode :return: List[int]"""
<|body_1|>
def postorderTraversal(self, r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution1:
def inorderTraversal(self, root):
"""采用递归方法实现 中序遍历 :param root: TreeNode :return: List[int]"""
def inorder(root):
if not root:
return
inorder(root.left)
ans.append(root.val)
inorder(root.right)
ans = []
... | the_stack_v2_python_sparse | Leetcode0094.py | ThompsonHe/LeetCode-Python | train | 0 | |
1982d1f1f14c08951ebd42990e0e5de9894822bc | [
"self.logger = logging.getLogger(__name__)\nself.logger.setLevel(logging.DEBUG)\nself.X = X\nself.Y = Y\nself.is_stochastic = is_stochastic\nif is_stochastic:\n self.logger.debug('Running Stochastic Perceptron...')\nself.step_size = step_size\nself.max_steps = max_steps\nself.reg_constant = reg_constant\nself.w ... | <|body_start_0|>
self.logger = logging.getLogger(__name__)
self.logger.setLevel(logging.DEBUG)
self.X = X
self.Y = Y
self.is_stochastic = is_stochastic
if is_stochastic:
self.logger.debug('Running Stochastic Perceptron...')
self.step_size = step_size
... | The Perceptron classifier, intended to be run on a dataset of two classes that are linearly separable. | Perceptron | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Perceptron:
"""The Perceptron classifier, intended to be run on a dataset of two classes that are linearly separable."""
def __init__(self, X, Y, is_stochastic, step_size, max_steps, reg_constant=0):
"""Initializes the Perceptron classifier. X and Y is the training data over which to... | stack_v2_sparse_classes_10k_train_006424 | 4,229 | permissive | [
{
"docstring": "Initializes the Perceptron classifier. X and Y is the training data over which to learn the hyperplane If is_stochastic is True then the perceptron gradient steps will be stochastic not batch. step_size is the learning rate to be used. max_steps is the maximum number of iterations to use before ... | 4 | stack_v2_sparse_classes_30k_train_001617 | Implement the Python class `Perceptron` described below.
Class description:
The Perceptron classifier, intended to be run on a dataset of two classes that are linearly separable.
Method signatures and docstrings:
- def __init__(self, X, Y, is_stochastic, step_size, max_steps, reg_constant=0): Initializes the Perceptr... | Implement the Python class `Perceptron` described below.
Class description:
The Perceptron classifier, intended to be run on a dataset of two classes that are linearly separable.
Method signatures and docstrings:
- def __init__(self, X, Y, is_stochastic, step_size, max_steps, reg_constant=0): Initializes the Perceptr... | 5d5a372f315cbd3cf8a3b2e865a8724f7cf4cc2b | <|skeleton|>
class Perceptron:
"""The Perceptron classifier, intended to be run on a dataset of two classes that are linearly separable."""
def __init__(self, X, Y, is_stochastic, step_size, max_steps, reg_constant=0):
"""Initializes the Perceptron classifier. X and Y is the training data over which to... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Perceptron:
"""The Perceptron classifier, intended to be run on a dataset of two classes that are linearly separable."""
def __init__(self, X, Y, is_stochastic, step_size, max_steps, reg_constant=0):
"""Initializes the Perceptron classifier. X and Y is the training data over which to learn the hy... | the_stack_v2_python_sparse | ml_lib/perceptron.py | enerve/ml | train | 0 |
17fcdfb0e94493d58fab386764d7a0dd2a58df65 | [
"super().__init__(data)\ncoloring = config.get_option_from_section(consts.DisplayOptions.FLAMEGRAPH.value, 'coloring')\nself.display_options = self.DisplayOptions(coloring)\nself.svg_temp_file = str(file.TempFileName())",
"stacks_temp_file = str(file.TempFileName())\ncounts = collections.Counter()\nstack_data = s... | <|body_start_0|>
super().__init__(data)
coloring = config.get_option_from_section(consts.DisplayOptions.FLAMEGRAPH.value, 'coloring')
self.display_options = self.DisplayOptions(coloring)
self.svg_temp_file = str(file.TempFileName())
<|end_body_0|>
<|body_start_1|>
stacks_temp_fi... | The class representing flamegraphs. | Flamegraph | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Flamegraph:
"""The class representing flamegraphs."""
def __init__(self, data):
"""Initialise the flamegraph. :param data: A `data_io.StackData` object that encapsulated the collected data we want to display as a flamegraph"""
<|body_0|>
def _make(self):
"""Uses ... | stack_v2_sparse_classes_10k_train_006425 | 3,399 | permissive | [
{
"docstring": "Initialise the flamegraph. :param data: A `data_io.StackData` object that encapsulated the collected data we want to display as a flamegraph",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Uses Brendan Gregg's flamegraph tool to convert data to fl... | 3 | stack_v2_sparse_classes_30k_val_000220 | Implement the Python class `Flamegraph` described below.
Class description:
The class representing flamegraphs.
Method signatures and docstrings:
- def __init__(self, data): Initialise the flamegraph. :param data: A `data_io.StackData` object that encapsulated the collected data we want to display as a flamegraph
- d... | Implement the Python class `Flamegraph` described below.
Class description:
The class representing flamegraphs.
Method signatures and docstrings:
- def __init__(self, data): Initialise the flamegraph. :param data: A `data_io.StackData` object that encapsulated the collected data we want to display as a flamegraph
- d... | d36c3203cefdd4690ba2ecf076e5e9fca05cbc80 | <|skeleton|>
class Flamegraph:
"""The class representing flamegraphs."""
def __init__(self, data):
"""Initialise the flamegraph. :param data: A `data_io.StackData` object that encapsulated the collected data we want to display as a flamegraph"""
<|body_0|>
def _make(self):
"""Uses ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Flamegraph:
"""The class representing flamegraphs."""
def __init__(self, data):
"""Initialise the flamegraph. :param data: A `data_io.StackData` object that encapsulated the collected data we want to display as a flamegraph"""
super().__init__(data)
coloring = config.get_option_fr... | the_stack_v2_python_sparse | marple/display/interface/flamegraph.py | ensoft/marple | train | 7 |
a2027fc35fac278eedc0d6b16539ecf32c5ecaa2 | [
"super(DNN, self).__init__()\nself._dropout = dropout\nself.hidden_layers = [None for _ in range(10)]\nfor i in range(10):\n self.hidden_layers[i] = tf.keras.layers.Dense(100, activation='relu', use_bias=True, trainable=trainable, name='dense_{}'.format(i), kernel_initializer='he_normal')\nself.linear = tf.keras... | <|body_start_0|>
super(DNN, self).__init__()
self._dropout = dropout
self.hidden_layers = [None for _ in range(10)]
for i in range(10):
self.hidden_layers[i] = tf.keras.layers.Dense(100, activation='relu', use_bias=True, trainable=trainable, name='dense_{}'.format(i), kernel_... | Deep Neural Network with 10 hidden layers. Attributes: hidden_layers: A list of 10 tf.keras.layers.Dense layers with ReLU. linear: Fully-connected layer. | DNN | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DNN:
"""Deep Neural Network with 10 hidden layers. Attributes: hidden_layers: A list of 10 tf.keras.layers.Dense layers with ReLU. linear: Fully-connected layer."""
def __init__(self, trainable=True, dropout=0.15):
"""Creates the DNN layers. Args: trainable: Whether the DNN parameter... | stack_v2_sparse_classes_10k_train_006426 | 10,796 | permissive | [
{
"docstring": "Creates the DNN layers. Args: trainable: Whether the DNN parameters are trainable or not. dropout: Coefficient for dropout regularization.",
"name": "__init__",
"signature": "def __init__(self, trainable=True, dropout=0.15)"
},
{
"docstring": "Creates the output tensor given an i... | 2 | null | Implement the Python class `DNN` described below.
Class description:
Deep Neural Network with 10 hidden layers. Attributes: hidden_layers: A list of 10 tf.keras.layers.Dense layers with ReLU. linear: Fully-connected layer.
Method signatures and docstrings:
- def __init__(self, trainable=True, dropout=0.15): Creates t... | Implement the Python class `DNN` described below.
Class description:
Deep Neural Network with 10 hidden layers. Attributes: hidden_layers: A list of 10 tf.keras.layers.Dense layers with ReLU. linear: Fully-connected layer.
Method signatures and docstrings:
- def __init__(self, trainable=True, dropout=0.15): Creates t... | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | <|skeleton|>
class DNN:
"""Deep Neural Network with 10 hidden layers. Attributes: hidden_layers: A list of 10 tf.keras.layers.Dense layers with ReLU. linear: Fully-connected layer."""
def __init__(self, trainable=True, dropout=0.15):
"""Creates the DNN layers. Args: trainable: Whether the DNN parameter... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DNN:
"""Deep Neural Network with 10 hidden layers. Attributes: hidden_layers: A list of 10 tf.keras.layers.Dense layers with ReLU. linear: Fully-connected layer."""
def __init__(self, trainable=True, dropout=0.15):
"""Creates the DNN layers. Args: trainable: Whether the DNN parameters are trainab... | the_stack_v2_python_sparse | neural_additive_models/models.py | Ayoob7/google-research | train | 2 |
bec1a20f5d61760917005ff69c85a57821f7b375 | [
"cnt = 0\nfor i in range(len(flowerbed)):\n if flowerbed[i] == 0 and (i == 0 or flowerbed[i - 1] == 0) and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):\n flowerbed[i] = 1\n cnt += 1\nreturn cnt >= n",
"cnt = 0\nfor i in range(len(flowerbed)):\n if flowerbed[i] == 0 and (i == 0 or flower... | <|body_start_0|>
cnt = 0
for i in range(len(flowerbed)):
if flowerbed[i] == 0 and (i == 0 or flowerbed[i - 1] == 0) and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):
flowerbed[i] = 1
cnt += 1
return cnt >= n
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_0|>
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_1|>
def canPlaceFlowers(se... | stack_v2_sparse_classes_10k_train_006427 | 1,373 | no_license | [
{
"docstring": ":type flowerbed: List[int] :type n: int :rtype: bool",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(self, flowerbed, n)"
},
{
"docstring": ":type flowerbed: List[int] :type n: int :rtype: bool",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(... | 3 | stack_v2_sparse_classes_30k_train_000551 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :rtype: bool
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :rtype: bool
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_0|>
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_1|>
def canPlaceFlowers(se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
cnt = 0
for i in range(len(flowerbed)):
if flowerbed[i] == 0 and (i == 0 or flowerbed[i - 1] == 0) and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):
... | the_stack_v2_python_sparse | 0605_Can_Place_Flowers.py | bingli8802/leetcode | train | 0 | |
a0bfb0aec0a5a0db1b795389abf7866bdb28db3a | [
"self.enable_deepcopy = enable_deepcopy\nself.init_val = init_val\nself.root = TrieNode(self.init_val, self.enable_deepcopy)",
"i, n = (0, len(string))\nnode = self.root\nwhile i < n:\n if string[i] not in node.next:\n node.next[string[i]] = TrieNode(self.init_val, self.enable_deepcopy)\n if insert_o... | <|body_start_0|>
self.enable_deepcopy = enable_deepcopy
self.init_val = init_val
self.root = TrieNode(self.init_val, self.enable_deepcopy)
<|end_body_0|>
<|body_start_1|>
i, n = (0, len(string))
node = self.root
while i < n:
if string[i] not in node.next:
... | Class of Trie, which is a kind of search tree—an ordered tree data structure used to store a dynamic set or associative array where the keys are usually strings. (See: https://en.wikipedia.org/wiki/Trie) | Trie | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trie:
"""Class of Trie, which is a kind of search tree—an ordered tree data structure used to store a dynamic set or associative array where the keys are usually strings. (See: https://en.wikipedia.org/wiki/Trie)"""
def __init__(self, init_val=None, enable_deepcopy=False):
"""Init a ... | stack_v2_sparse_classes_10k_train_006428 | 3,546 | no_license | [
{
"docstring": "Init a Trie using specific initial value. :param init_val: Initial value of each Trie node. :param enable_deepcopy: Whether using the deepcopy to initialize the value of Trie node. This option is useful to avoiding initialize all nodes with a same reference when using list/dict as initial value.... | 3 | stack_v2_sparse_classes_30k_val_000219 | Implement the Python class `Trie` described below.
Class description:
Class of Trie, which is a kind of search tree—an ordered tree data structure used to store a dynamic set or associative array where the keys are usually strings. (See: https://en.wikipedia.org/wiki/Trie)
Method signatures and docstrings:
- def __in... | Implement the Python class `Trie` described below.
Class description:
Class of Trie, which is a kind of search tree—an ordered tree data structure used to store a dynamic set or associative array where the keys are usually strings. (See: https://en.wikipedia.org/wiki/Trie)
Method signatures and docstrings:
- def __in... | 72d172ea25777980a49439042dbc39448fcad73d | <|skeleton|>
class Trie:
"""Class of Trie, which is a kind of search tree—an ordered tree data structure used to store a dynamic set or associative array where the keys are usually strings. (See: https://en.wikipedia.org/wiki/Trie)"""
def __init__(self, init_val=None, enable_deepcopy=False):
"""Init a ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Trie:
"""Class of Trie, which is a kind of search tree—an ordered tree data structure used to store a dynamic set or associative array where the keys are usually strings. (See: https://en.wikipedia.org/wiki/Trie)"""
def __init__(self, init_val=None, enable_deepcopy=False):
"""Init a Trie using sp... | the_stack_v2_python_sparse | src/data_structure/trie.py | stupidchen/leetcode | train | 7 |
eea60ad92b847edb5f9854240c2da5fa07d695cd | [
"string = ''\nstack = [root]\nwhile stack:\n node = stack.pop(0)\n if node is None:\n string += 'null,'\n continue\n else:\n string += f'{node.val},'\n stack.extend([node.left, node.right])\nreturn f'[{string[:-1]}]'",
"nodes = data.strip('[').strip(']').split(',')\nheader = nodes... | <|body_start_0|>
string = ''
stack = [root]
while stack:
node = stack.pop(0)
if node is None:
string += 'null,'
continue
else:
string += f'{node.val},'
stack.extend([node.left, node.right])
re... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_006429 | 1,676 | 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_002381 | 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:... | b47280681276ec7001efa3d0dbb9c354ca5c6abc | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
string = ''
stack = [root]
while stack:
node = stack.pop(0)
if node is None:
string += 'null,'
continue
... | the_stack_v2_python_sparse | 算法训练营/07-递归/297/广度优先遍历.py | youguanxinqing/RoadOfDSA | train | 0 | |
7d2fce56982c6d54a4ede5b681be380be64e8019 | [
"self.proof_type = proof_type\nself.proof_purpose = proof_purpose\nself.created = created\nself.domain = domain\nself.challenge = challenge\nself.credential_status = credential_status",
"if isinstance(o, LDProofVCDetailOptions):\n return self.proof_type == o.proof_type and self.proof_purpose == o.proof_purpose... | <|body_start_0|>
self.proof_type = proof_type
self.proof_purpose = proof_purpose
self.created = created
self.domain = domain
self.challenge = challenge
self.credential_status = credential_status
<|end_body_0|>
<|body_start_1|>
if isinstance(o, LDProofVCDetailOpti... | Linked Data Proof verifiable credential options model. | LDProofVCDetailOptions | [
"LicenseRef-scancode-dco-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LDProofVCDetailOptions:
"""Linked Data Proof verifiable credential options model."""
def __init__(self, proof_type: Optional[str]=None, proof_purpose: Optional[str]=None, created: Optional[str]=None, domain: Optional[str]=None, challenge: Optional[str]=None, credential_status: Optional[dict]... | stack_v2_sparse_classes_10k_train_006430 | 4,481 | permissive | [
{
"docstring": "Initialize the LDProofVCDetailOptions instance.",
"name": "__init__",
"signature": "def __init__(self, proof_type: Optional[str]=None, proof_purpose: Optional[str]=None, created: Optional[str]=None, domain: Optional[str]=None, challenge: Optional[str]=None, credential_status: Optional[di... | 2 | null | Implement the Python class `LDProofVCDetailOptions` described below.
Class description:
Linked Data Proof verifiable credential options model.
Method signatures and docstrings:
- def __init__(self, proof_type: Optional[str]=None, proof_purpose: Optional[str]=None, created: Optional[str]=None, domain: Optional[str]=No... | Implement the Python class `LDProofVCDetailOptions` described below.
Class description:
Linked Data Proof verifiable credential options model.
Method signatures and docstrings:
- def __init__(self, proof_type: Optional[str]=None, proof_purpose: Optional[str]=None, created: Optional[str]=None, domain: Optional[str]=No... | 39cac36d8937ce84a9307ce100aaefb8bc05ec04 | <|skeleton|>
class LDProofVCDetailOptions:
"""Linked Data Proof verifiable credential options model."""
def __init__(self, proof_type: Optional[str]=None, proof_purpose: Optional[str]=None, created: Optional[str]=None, domain: Optional[str]=None, challenge: Optional[str]=None, credential_status: Optional[dict]... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LDProofVCDetailOptions:
"""Linked Data Proof verifiable credential options model."""
def __init__(self, proof_type: Optional[str]=None, proof_purpose: Optional[str]=None, created: Optional[str]=None, domain: Optional[str]=None, challenge: Optional[str]=None, credential_status: Optional[dict]=None) -> Non... | the_stack_v2_python_sparse | aries_cloudagent/protocols/issue_credential/v2_0/formats/ld_proof/models/cred_detail_options.py | hyperledger/aries-cloudagent-python | train | 370 |
a2ade2c6ca67f1449d567d17b0258d2879668864 | [
"try:\n self.account = Account.actives.get(pk=account_id)\nexcept Account.DoesNotExist:\n raise AccountNotExistError('Account ID %s does not exist or not active' % account_id)\nelse:\n storage = Storage(GoogleCredentials, 'account', self.account, 'credentials')\n self.credentials = storage.get()\n if... | <|body_start_0|>
try:
self.account = Account.actives.get(pk=account_id)
except Account.DoesNotExist:
raise AccountNotExistError('Account ID %s does not exist or not active' % account_id)
else:
storage = Storage(GoogleCredentials, 'account', self.account, 'cred... | Call Google Data APIs using pre-existing google credentials. Use /api/self/google-connect to get and save credentials. Sample usage: Get all Google contacts of account with id=3 g = GDataClient(account_id=3) response = g.get_json_response('get', 'https://www.google.com/m8/feeds/contacts/default/full', {'max-results': 1... | GDataClient | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GDataClient:
"""Call Google Data APIs using pre-existing google credentials. Use /api/self/google-connect to get and save credentials. Sample usage: Get all Google contacts of account with id=3 g = GDataClient(account_id=3) response = g.get_json_response('get', 'https://www.google.com/m8/feeds/co... | stack_v2_sparse_classes_10k_train_006431 | 2,708 | no_license | [
{
"docstring": "Create GDataClient connecting to an account_id. This account must have google credentials.",
"name": "__init__",
"signature": "def __init__(self, account_id)"
},
{
"docstring": "Returns access_token. Refresh if access_token has already expired.",
"name": "get_access_token",
... | 3 | stack_v2_sparse_classes_30k_test_000023 | Implement the Python class `GDataClient` described below.
Class description:
Call Google Data APIs using pre-existing google credentials. Use /api/self/google-connect to get and save credentials. Sample usage: Get all Google contacts of account with id=3 g = GDataClient(account_id=3) response = g.get_json_response('ge... | Implement the Python class `GDataClient` described below.
Class description:
Call Google Data APIs using pre-existing google credentials. Use /api/self/google-connect to get and save credentials. Sample usage: Get all Google contacts of account with id=3 g = GDataClient(account_id=3) response = g.get_json_response('ge... | 0d5912eb2800eeb095df9aec19045e3916ba0d13 | <|skeleton|>
class GDataClient:
"""Call Google Data APIs using pre-existing google credentials. Use /api/self/google-connect to get and save credentials. Sample usage: Get all Google contacts of account with id=3 g = GDataClient(account_id=3) response = g.get_json_response('get', 'https://www.google.com/m8/feeds/co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GDataClient:
"""Call Google Data APIs using pre-existing google credentials. Use /api/self/google-connect to get and save credentials. Sample usage: Get all Google contacts of account with id=3 g = GDataClient(account_id=3) response = g.get_json_response('get', 'https://www.google.com/m8/feeds/contacts/defaul... | the_stack_v2_python_sparse | core/shared/google_data_api.py | eventure-interactive/eventure_django | train | 0 |
3b2d844358edfa8f87ccbb40f7f3b7a178157d99 | [
"a = 'AGC'\nb = 'AC'\ncomputedMatrix = [[0 for i in range(len(b) + 1)] for j in range(len(a) + 1)]\nfor i in range(1, len(a) + 1):\n computedMatrix[i][0] = computedMatrix[i - 1][0] + pah().weightFunctionDifference('', a[i - 1])\nfor i in range(1, len(b) + 1):\n computedMatrix[0][i] = computedMatrix[0][i - 1] ... | <|body_start_0|>
a = 'AGC'
b = 'AC'
computedMatrix = [[0 for i in range(len(b) + 1)] for j in range(len(a) + 1)]
for i in range(1, len(a) + 1):
computedMatrix[i][0] = computedMatrix[i - 1][0] + pah().weightFunctionDifference('', a[i - 1])
for i in range(1, len(b) + 1)... | Class to test the correctness of the computation for the class NeedlemanWunsch. | NeedlemanWunschTestClass | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeedlemanWunschTestClass:
"""Class to test the correctness of the computation for the class NeedlemanWunsch."""
def test_computeMatrix(self):
"""Test of the computation of the matrix."""
<|body_0|>
def test_traceback(self):
"""Test of the traceback computation.""... | stack_v2_sparse_classes_10k_train_006432 | 2,597 | no_license | [
{
"docstring": "Test of the computation of the matrix.",
"name": "test_computeMatrix",
"signature": "def test_computeMatrix(self)"
},
{
"docstring": "Test of the traceback computation.",
"name": "test_traceback",
"signature": "def test_traceback(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005281 | Implement the Python class `NeedlemanWunschTestClass` described below.
Class description:
Class to test the correctness of the computation for the class NeedlemanWunsch.
Method signatures and docstrings:
- def test_computeMatrix(self): Test of the computation of the matrix.
- def test_traceback(self): Test of the tra... | Implement the Python class `NeedlemanWunschTestClass` described below.
Class description:
Class to test the correctness of the computation for the class NeedlemanWunsch.
Method signatures and docstrings:
- def test_computeMatrix(self): Test of the computation of the matrix.
- def test_traceback(self): Test of the tra... | 20d8df6172906337f81583dabb841d66b8f31857 | <|skeleton|>
class NeedlemanWunschTestClass:
"""Class to test the correctness of the computation for the class NeedlemanWunsch."""
def test_computeMatrix(self):
"""Test of the computation of the matrix."""
<|body_0|>
def test_traceback(self):
"""Test of the traceback computation.""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NeedlemanWunschTestClass:
"""Class to test the correctness of the computation for the class NeedlemanWunsch."""
def test_computeMatrix(self):
"""Test of the computation of the matrix."""
a = 'AGC'
b = 'AC'
computedMatrix = [[0 for i in range(len(b) + 1)] for j in range(len... | the_stack_v2_python_sparse | new_algs/Sequence+algorithms/Needleman-Wunsch+algorithm/needlemanWunschTest.py | coolsnake/JupyterNotebook | train | 0 |
d2e255737b5c37972a519266509de2d4291e2ac5 | [
"i = 0\nwhile i < len(arr):\n if len(arr[i:]) < m * k:\n return False\n j = 1\n while j < k:\n if arr[i:i + m] != arr[i + m * j:i + m * (j + 1)]:\n i += 1\n break\n elif arr[i:i + m] == arr[i + m * j:i + m * (j + 1)]:\n j += 1\n if j == k:\n r... | <|body_start_0|>
i = 0
while i < len(arr):
if len(arr[i:]) < m * k:
return False
j = 1
while j < k:
if arr[i:i + m] != arr[i + m * j:i + m * (j + 1)]:
i += 1
break
elif arr[i:i + m... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def containsPattern(self, arr, m, k):
""":type arr: List[int] :type m: int :type k: int :rtype: bool"""
<|body_0|>
def containsPattern(self, arr, m, k):
""":type arr: List[int] :type m: int :type k: int :rtype: bool"""
<|body_1|>
def containsPa... | stack_v2_sparse_classes_10k_train_006433 | 1,339 | no_license | [
{
"docstring": ":type arr: List[int] :type m: int :type k: int :rtype: bool",
"name": "containsPattern",
"signature": "def containsPattern(self, arr, m, k)"
},
{
"docstring": ":type arr: List[int] :type m: int :type k: int :rtype: bool",
"name": "containsPattern",
"signature": "def conta... | 3 | stack_v2_sparse_classes_30k_train_003778 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsPattern(self, arr, m, k): :type arr: List[int] :type m: int :type k: int :rtype: bool
- def containsPattern(self, arr, m, k): :type arr: List[int] :type m: int :type ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsPattern(self, arr, m, k): :type arr: List[int] :type m: int :type k: int :rtype: bool
- def containsPattern(self, arr, m, k): :type arr: List[int] :type m: int :type ... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def containsPattern(self, arr, m, k):
""":type arr: List[int] :type m: int :type k: int :rtype: bool"""
<|body_0|>
def containsPattern(self, arr, m, k):
""":type arr: List[int] :type m: int :type k: int :rtype: bool"""
<|body_1|>
def containsPa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def containsPattern(self, arr, m, k):
""":type arr: List[int] :type m: int :type k: int :rtype: bool"""
i = 0
while i < len(arr):
if len(arr[i:]) < m * k:
return False
j = 1
while j < k:
if arr[i:i + m] != ar... | the_stack_v2_python_sparse | 1566_Detect_Pattern_of_Length_M_Repeated_K_or_More.py | bingli8802/leetcode | train | 0 | |
9e9a5cbfdd434932d9742249705770a7d795518d | [
"if six.PY2:\n buf = io.BytesIO()\n try:\n json.dump(self.document, buf, cls=ProvJSONEncoder, **kwargs)\n buf.seek(0, 0)\n if isinstance(stream, io.TextIOBase):\n stream.write(buf.read().decode('utf-8'))\n else:\n stream.write(buf.read())\n finally:\n ... | <|body_start_0|>
if six.PY2:
buf = io.BytesIO()
try:
json.dump(self.document, buf, cls=ProvJSONEncoder, **kwargs)
buf.seek(0, 0)
if isinstance(stream, io.TextIOBase):
stream.write(buf.read().decode('utf-8'))
... | PROV-JSON serializer for :class:`~prov.model.ProvDocument` | ProvJSONSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProvJSONSerializer:
"""PROV-JSON serializer for :class:`~prov.model.ProvDocument`"""
def serialize(self, stream, **kwargs):
"""Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the out... | stack_v2_sparse_classes_10k_train_006434 | 13,588 | permissive | [
{
"docstring": "Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the output.",
"name": "serialize",
"signature": "def serialize(self, stream, **kwargs)"
},
{
"docstring": "Deserialize from the `P... | 2 | null | Implement the Python class `ProvJSONSerializer` described below.
Class description:
PROV-JSON serializer for :class:`~prov.model.ProvDocument`
Method signatures and docstrings:
- def serialize(self, stream, **kwargs): Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.... | Implement the Python class `ProvJSONSerializer` described below.
Class description:
PROV-JSON serializer for :class:`~prov.model.ProvDocument`
Method signatures and docstrings:
- def serialize(self, stream, **kwargs): Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.... | 3c3acc55de8ba741e673063378e6cbaf10b64c7a | <|skeleton|>
class ProvJSONSerializer:
"""PROV-JSON serializer for :class:`~prov.model.ProvDocument`"""
def serialize(self, stream, **kwargs):
"""Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the out... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProvJSONSerializer:
"""PROV-JSON serializer for :class:`~prov.model.ProvDocument`"""
def serialize(self, stream, **kwargs):
"""Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the output."""
... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/prov/serializers/provjson.py | Raniac/NEURO-LEARN | train | 9 |
a1536957cbf57af9f9ffc12f1fbdfb42c4bc4414 | [
"self.session = session\nself.starting_op_names = starting_op_names\nself.layer_output = LayerOutput(session=session, starting_op_names=starting_op_names, output_op_names=output_op_names, dir_path=dir_path)\naxis_layout = 'NHWC' if tf.keras.backend.image_data_format() == 'channels_last' else 'NCHW'\nself.save_input... | <|body_start_0|>
self.session = session
self.starting_op_names = starting_op_names
self.layer_output = LayerOutput(session=session, starting_op_names=starting_op_names, output_op_names=output_op_names, dir_path=dir_path)
axis_layout = 'NHWC' if tf.keras.backend.image_data_format() == 'ch... | Implementation to capture and save outputs of intermediate layers of a model (fp32/quantsim) | LayerOutputUtil | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerOutputUtil:
"""Implementation to capture and save outputs of intermediate layers of a model (fp32/quantsim)"""
def __init__(self, session: tf.compat.v1.Session, starting_op_names: List[str], output_op_names: List[str], dir_path: str):
"""Constructor for LayerOutputUtil. :param s... | stack_v2_sparse_classes_10k_train_006435 | 8,075 | permissive | [
{
"docstring": "Constructor for LayerOutputUtil. :param session: Session containing the model whose layer-outputs are needed. :param starting_op_names: List of starting op names of the model. :param output_op_names: List of output op names of the model. :param dir_path: Directory wherein layer-outputs will be s... | 2 | stack_v2_sparse_classes_30k_train_006152 | Implement the Python class `LayerOutputUtil` described below.
Class description:
Implementation to capture and save outputs of intermediate layers of a model (fp32/quantsim)
Method signatures and docstrings:
- def __init__(self, session: tf.compat.v1.Session, starting_op_names: List[str], output_op_names: List[str], ... | Implement the Python class `LayerOutputUtil` described below.
Class description:
Implementation to capture and save outputs of intermediate layers of a model (fp32/quantsim)
Method signatures and docstrings:
- def __init__(self, session: tf.compat.v1.Session, starting_op_names: List[str], output_op_names: List[str], ... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class LayerOutputUtil:
"""Implementation to capture and save outputs of intermediate layers of a model (fp32/quantsim)"""
def __init__(self, session: tf.compat.v1.Session, starting_op_names: List[str], output_op_names: List[str], dir_path: str):
"""Constructor for LayerOutputUtil. :param s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LayerOutputUtil:
"""Implementation to capture and save outputs of intermediate layers of a model (fp32/quantsim)"""
def __init__(self, session: tf.compat.v1.Session, starting_op_names: List[str], output_op_names: List[str], dir_path: str):
"""Constructor for LayerOutputUtil. :param session: Sessi... | the_stack_v2_python_sparse | TrainingExtensions/tensorflow/src/python/aimet_tensorflow/layer_output_utils.py | quic/aimet | train | 1,676 |
a30dc668ed4919bd8a22cc3bec519de812a774a5 | [
"print('Inside __init__()')\nself.arg1 = arg1\nself.arg2 = arg2\nself.arg3 = arg3",
"print('Inside __call__()')\n\ndef wrapped_f(*args):\n print('Inside wrapped_f()')\n print('Decorator arguments:', self.arg1, self.arg2, self.arg3)\n f(*args)\n print('After f(*args)')\nreturn wrapped_f"
] | <|body_start_0|>
print('Inside __init__()')
self.arg1 = arg1
self.arg2 = arg2
self.arg3 = arg3
<|end_body_0|>
<|body_start_1|>
print('Inside __call__()')
def wrapped_f(*args):
print('Inside wrapped_f()')
print('Decorator arguments:', self.arg1, s... | DecoratorWithArguments | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoratorWithArguments:
def __init__(self, arg1, arg2, arg3):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
<|body_0|>
def __call__(self, f):
"""If there are decorator arguments, __call__() is only called once,... | stack_v2_sparse_classes_10k_train_006436 | 2,861 | no_license | [
{
"docstring": "If there are decorator arguments, the function to be decorated is not passed to the constructor!",
"name": "__init__",
"signature": "def __init__(self, arg1, arg2, arg3)"
},
{
"docstring": "If there are decorator arguments, __call__() is only called once, as part of the decoratio... | 2 | stack_v2_sparse_classes_30k_train_000445 | Implement the Python class `DecoratorWithArguments` described below.
Class description:
Implement the DecoratorWithArguments class.
Method signatures and docstrings:
- def __init__(self, arg1, arg2, arg3): If there are decorator arguments, the function to be decorated is not passed to the constructor!
- def __call__(... | Implement the Python class `DecoratorWithArguments` described below.
Class description:
Implement the DecoratorWithArguments class.
Method signatures and docstrings:
- def __init__(self, arg1, arg2, arg3): If there are decorator arguments, the function to be decorated is not passed to the constructor!
- def __call__(... | d0b821a48a05f0ec28db73351b6e7a07b435b4a5 | <|skeleton|>
class DecoratorWithArguments:
def __init__(self, arg1, arg2, arg3):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
<|body_0|>
def __call__(self, f):
"""If there are decorator arguments, __call__() is only called once,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DecoratorWithArguments:
def __init__(self, arg1, arg2, arg3):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
print('Inside __init__()')
self.arg1 = arg1
self.arg2 = arg2
self.arg3 = arg3
def __call__(self, f):... | the_stack_v2_python_sparse | src/main/python/lang/decorator_example.py | solma/com.sma | train | 4 | |
8f42eb8d9d3d6c628d52930e874ac5f67242d578 | [
"db = DatabaseConnection()\nconn = db.getconnection()\ntry:\n with conn.cursor() as cursor:\n sql = \"SELECT A.user_pref, AST.assertion_type, A.parameters FROM assertions A LEFT JOIN assertions_types AST ON A.assertion_type = AST.id WHERE A.user_pref = '\" + user_pref + \"' ORDER BY A.assertion_type\"\n ... | <|body_start_0|>
db = DatabaseConnection()
conn = db.getconnection()
try:
with conn.cursor() as cursor:
sql = "SELECT A.user_pref, AST.assertion_type, A.parameters FROM assertions A LEFT JOIN assertions_types AST ON A.assertion_type = AST.id WHERE A.user_pref = '" + u... | AssertionModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssertionModel:
def getAssertionByUserPreference(self, user_pref):
""":param user_pref: :returns the assertions by user preference:"""
<|body_0|>
def getLikedPagesAndEvents(self):
""":returns list of LikedPagesAndEvents object:"""
<|body_1|>
def getAsser... | stack_v2_sparse_classes_10k_train_006437 | 4,087 | no_license | [
{
"docstring": ":param user_pref: :returns the assertions by user preference:",
"name": "getAssertionByUserPreference",
"signature": "def getAssertionByUserPreference(self, user_pref)"
},
{
"docstring": ":returns list of LikedPagesAndEvents object:",
"name": "getLikedPagesAndEvents",
"si... | 4 | stack_v2_sparse_classes_30k_train_004647 | Implement the Python class `AssertionModel` described below.
Class description:
Implement the AssertionModel class.
Method signatures and docstrings:
- def getAssertionByUserPreference(self, user_pref): :param user_pref: :returns the assertions by user preference:
- def getLikedPagesAndEvents(self): :returns list of ... | Implement the Python class `AssertionModel` described below.
Class description:
Implement the AssertionModel class.
Method signatures and docstrings:
- def getAssertionByUserPreference(self, user_pref): :param user_pref: :returns the assertions by user preference:
- def getLikedPagesAndEvents(self): :returns list of ... | 44a7dc53f33cb342b087d3c62149437eb655a3c7 | <|skeleton|>
class AssertionModel:
def getAssertionByUserPreference(self, user_pref):
""":param user_pref: :returns the assertions by user preference:"""
<|body_0|>
def getLikedPagesAndEvents(self):
""":returns list of LikedPagesAndEvents object:"""
<|body_1|>
def getAsser... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AssertionModel:
def getAssertionByUserPreference(self, user_pref):
""":param user_pref: :returns the assertions by user preference:"""
db = DatabaseConnection()
conn = db.getconnection()
try:
with conn.cursor() as cursor:
sql = "SELECT A.user_pref, A... | the_stack_v2_python_sparse | StoryGenerator/storygenappv2/storygen/models/AssertionModel.py | hbrosas/Persona-Based-Life-Story-Generation | train | 0 | |
274249474a90cf743e2ab9414cac17c62aa4f169 | [
"assert dataset, 'Groundtruth should not be empty.'\nassert isinstance(dataset, dict), 'annotation file format {} not supported'.format(type(dataset))\nself.anns, self.cats, self.imgs = (dict(), dict(), dict())\nself.dataset = copy.deepcopy(dataset)\nself.createIndex()",
"res = MaskCOCO()\nres.dataset['images'] =... | <|body_start_0|>
assert dataset, 'Groundtruth should not be empty.'
assert isinstance(dataset, dict), 'annotation file format {} not supported'.format(type(dataset))
self.anns, self.cats, self.imgs = (dict(), dict(), dict())
self.dataset = copy.deepcopy(dataset)
self.createIndex(... | COCO object for mask evaluation. | MaskCOCO | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaskCOCO:
"""COCO object for mask evaluation."""
def reset(self, dataset):
"""Reset the dataset and groundtruth data index in this object. Args: dataset: dict of groundtruth data. It should has similar structure as the COCO groundtruth JSON file. Must contains three keys: {'images', ... | stack_v2_sparse_classes_10k_train_006438 | 14,113 | permissive | [
{
"docstring": "Reset the dataset and groundtruth data index in this object. Args: dataset: dict of groundtruth data. It should has similar structure as the COCO groundtruth JSON file. Must contains three keys: {'images', 'annotations', 'categories'}. 'images': list of image information dictionary. Required key... | 3 | stack_v2_sparse_classes_30k_train_005496 | Implement the Python class `MaskCOCO` described below.
Class description:
COCO object for mask evaluation.
Method signatures and docstrings:
- def reset(self, dataset): Reset the dataset and groundtruth data index in this object. Args: dataset: dict of groundtruth data. It should has similar structure as the COCO gro... | Implement the Python class `MaskCOCO` described below.
Class description:
COCO object for mask evaluation.
Method signatures and docstrings:
- def reset(self, dataset): Reset the dataset and groundtruth data index in this object. Args: dataset: dict of groundtruth data. It should has similar structure as the COCO gro... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class MaskCOCO:
"""COCO object for mask evaluation."""
def reset(self, dataset):
"""Reset the dataset and groundtruth data index in this object. Args: dataset: dict of groundtruth data. It should has similar structure as the COCO groundtruth JSON file. Must contains three keys: {'images', ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MaskCOCO:
"""COCO object for mask evaluation."""
def reset(self, dataset):
"""Reset the dataset and groundtruth data index in this object. Args: dataset: dict of groundtruth data. It should has similar structure as the COCO groundtruth JSON file. Must contains three keys: {'images', 'annotations'... | the_stack_v2_python_sparse | TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/utils/coco_metric.py | NVIDIA/DeepLearningExamples | train | 11,838 |
b0dde38ca32d9cb6f940d0cfac13eaf2cb04d2c7 | [
"n = len(A)\nif n < 3 or A[0] >= A[1] or A[n - 2] <= A[n - 1]:\n return False\ni = 1\nwhile i < n:\n if A[i - 1] < A[i]:\n i += 1\n else:\n break\nif i == n or A[i - 1] == A[i]:\n return False\nwhile i < n:\n if A[i - 1] > A[i]:\n i += 1\n else:\n return False\nreturn i... | <|body_start_0|>
n = len(A)
if n < 3 or A[0] >= A[1] or A[n - 2] <= A[n - 1]:
return False
i = 1
while i < n:
if A[i - 1] < A[i]:
i += 1
else:
break
if i == n or A[i - 1] == A[i]:
return False
... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def validMountainArray(self, A: List[int]) -> bool:
"""Runtime: 236 ms, faster than 79.18% of Python3 online submissions for Valid Mountain Array. Memory Usage: 15.2 MB, less than 5.26% of Python3 online submissions for Valid Mountain Array."""
<|body_0|>
def valid... | stack_v2_sparse_classes_10k_train_006439 | 1,841 | permissive | [
{
"docstring": "Runtime: 236 ms, faster than 79.18% of Python3 online submissions for Valid Mountain Array. Memory Usage: 15.2 MB, less than 5.26% of Python3 online submissions for Valid Mountain Array.",
"name": "validMountainArray",
"signature": "def validMountainArray(self, A: List[int]) -> bool"
}... | 2 | stack_v2_sparse_classes_30k_train_001485 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validMountainArray(self, A: List[int]) -> bool: Runtime: 236 ms, faster than 79.18% of Python3 online submissions for Valid Mountain Array. Memory Usage: 15.2 MB, less than 5... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validMountainArray(self, A: List[int]) -> bool: Runtime: 236 ms, faster than 79.18% of Python3 online submissions for Valid Mountain Array. Memory Usage: 15.2 MB, less than 5... | 9d7759bea1f44673c2de4f25a94b27368928a59f | <|skeleton|>
class Solution:
def validMountainArray(self, A: List[int]) -> bool:
"""Runtime: 236 ms, faster than 79.18% of Python3 online submissions for Valid Mountain Array. Memory Usage: 15.2 MB, less than 5.26% of Python3 online submissions for Valid Mountain Array."""
<|body_0|>
def valid... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def validMountainArray(self, A: List[int]) -> bool:
"""Runtime: 236 ms, faster than 79.18% of Python3 online submissions for Valid Mountain Array. Memory Usage: 15.2 MB, less than 5.26% of Python3 online submissions for Valid Mountain Array."""
n = len(A)
if n < 3 or A[0] >= ... | the_stack_v2_python_sparse | leetcode/google/tagged/mountain_array.py | pagsamo/google-tech-dev-guide | train | 0 | |
c66b999b7b85c6b60b29e358a5db643988fde3b4 | [
"n = len(init_val)\nself.segfunc = segfunc\nself.ide_ele = ide_ele\nself.num = 1 << (n - 1).bit_length()\nself.tree = [ide_ele] * 2 * self.num\nfor i in range(n):\n self.tree[self.num + i] = init_val[i]\nfor i in range(self.num - 1, 0, -1):\n self.tree[i] = self.segfunc(self.tree[2 * i], self.tree[2 * i + 1])... | <|body_start_0|>
n = len(init_val)
self.segfunc = segfunc
self.ide_ele = ide_ele
self.num = 1 << (n - 1).bit_length()
self.tree = [ide_ele] * 2 * self.num
for i in range(n):
self.tree[self.num + i] = init_val[i]
for i in range(self.num - 1, 0, -1):
... | init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN) | SegTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegTree:
"""init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)"""
def __init__(self, init_val, segfunc, ide_ele):
"""init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
... | stack_v2_sparse_classes_10k_train_006440 | 2,441 | no_license | [
{
"docstring": "init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)",
"name": "__init__",
"signature": "def __init__(self, init_val, segfunc, ide_ele)"
},
{
"docstring": "k番目の値をxに更新 k: index(0-index) x: update value",
"name": "update",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_000938 | Implement the Python class `SegTree` described below.
Class description:
init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)
Method signatures and docstrings:
- def __init__(self, init_val, segfunc, ide_ele): init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_el... | Implement the Python class `SegTree` described below.
Class description:
init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)
Method signatures and docstrings:
- def __init__(self, init_val, segfunc, ide_ele): init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_el... | 2526e72de9eb19d1e1c634dbd577816bfe39bc10 | <|skeleton|>
class SegTree:
"""init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)"""
def __init__(self, init_val, segfunc, ide_ele):
"""init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SegTree:
"""init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)"""
def __init__(self, init_val, segfunc, ide_ele):
"""init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
n = l... | the_stack_v2_python_sparse | ABC/ACLBC/ACLBC_D.py | happa64/AtCoder_Beginner_Contest | train | 0 |
87a7e039e27f4b1b3d22c985e9a3f9461d2728ec | [
"user = self\nuser_employee = self.env['hr.employee'].search_read([('user_id', '=', user.id)], fields=['id'])\nresult = []\nif user_employee:\n employee_ref = user_employee[0]['id']\n result.append(str(employee_ref))\n my_subordinates = self.env['hr.employee'].search_read(['|', ('coach_id', '=', employee_r... | <|body_start_0|>
user = self
user_employee = self.env['hr.employee'].search_read([('user_id', '=', user.id)], fields=['id'])
result = []
if user_employee:
employee_ref = user_employee[0]['id']
result.append(str(employee_ref))
my_subordinates = self.env... | ResUsers | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResUsers:
def get_my_subordinate_employees(self):
"""Return employee's subordinates - list of employees for which user is a Manager Or Coach"""
<|body_0|>
def get_my_subordinate_employees_list(self):
"""Return employee's subordinates - list of employees for which use... | stack_v2_sparse_classes_10k_train_006441 | 1,903 | no_license | [
{
"docstring": "Return employee's subordinates - list of employees for which user is a Manager Or Coach",
"name": "get_my_subordinate_employees",
"signature": "def get_my_subordinate_employees(self)"
},
{
"docstring": "Return employee's subordinates - list of employees for which user is a Manage... | 2 | null | Implement the Python class `ResUsers` described below.
Class description:
Implement the ResUsers class.
Method signatures and docstrings:
- def get_my_subordinate_employees(self): Return employee's subordinates - list of employees for which user is a Manager Or Coach
- def get_my_subordinate_employees_list(self): Ret... | Implement the Python class `ResUsers` described below.
Class description:
Implement the ResUsers class.
Method signatures and docstrings:
- def get_my_subordinate_employees(self): Return employee's subordinates - list of employees for which user is a Manager Or Coach
- def get_my_subordinate_employees_list(self): Ret... | 4fe19ca76523cf274a3a85c8bcad653100ff556f | <|skeleton|>
class ResUsers:
def get_my_subordinate_employees(self):
"""Return employee's subordinates - list of employees for which user is a Manager Or Coach"""
<|body_0|>
def get_my_subordinate_employees_list(self):
"""Return employee's subordinates - list of employees for which use... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResUsers:
def get_my_subordinate_employees(self):
"""Return employee's subordinates - list of employees for which user is a Manager Or Coach"""
user = self
user_employee = self.env['hr.employee'].search_read([('user_id', '=', user.id)], fields=['id'])
result = []
if use... | the_stack_v2_python_sparse | odoo app/ksa_hr_vacation/models/res_users.py | ahmed-amine-ellouze/personal | train | 0 | |
1b3538cb8b6ddc9180fb62f925ab213932bb6415 | [
"self.minBit = minBit\nself.nBits = nBits\nself.desc = desc",
"reg_shift = regVal / 2 ** self.minBit\nreg_mod = reg_shift % 2 ** self.nBits\nreturn reg_mod"
] | <|body_start_0|>
self.minBit = minBit
self.nBits = nBits
self.desc = desc
<|end_body_0|>
<|body_start_1|>
reg_shift = regVal / 2 ** self.minBit
reg_mod = reg_shift % 2 ** self.nBits
return reg_mod
<|end_body_1|>
| Describe meaning of a register bit-set | RegisterFieldInfo | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterFieldInfo:
"""Describe meaning of a register bit-set"""
def __init__(self, minBit, nBits, desc):
"""fieldName - name of bitfield withing register minBit - LSB of field (numbered from 0) nBits - size of bit-field desc - txt description"""
<|body_0|>
def extractVal... | stack_v2_sparse_classes_10k_train_006442 | 9,121 | permissive | [
{
"docstring": "fieldName - name of bitfield withing register minBit - LSB of field (numbered from 0) nBits - size of bit-field desc - txt description",
"name": "__init__",
"signature": "def __init__(self, minBit, nBits, desc)"
},
{
"docstring": "Extract register field value (as integer) from fu... | 2 | stack_v2_sparse_classes_30k_train_007173 | Implement the Python class `RegisterFieldInfo` described below.
Class description:
Describe meaning of a register bit-set
Method signatures and docstrings:
- def __init__(self, minBit, nBits, desc): fieldName - name of bitfield withing register minBit - LSB of field (numbered from 0) nBits - size of bit-field desc - ... | Implement the Python class `RegisterFieldInfo` described below.
Class description:
Describe meaning of a register bit-set
Method signatures and docstrings:
- def __init__(self, minBit, nBits, desc): fieldName - name of bitfield withing register minBit - LSB of field (numbered from 0) nBits - size of bit-field desc - ... | 3b824540d8173a24be12316a3821304e4ea20a1f | <|skeleton|>
class RegisterFieldInfo:
"""Describe meaning of a register bit-set"""
def __init__(self, minBit, nBits, desc):
"""fieldName - name of bitfield withing register minBit - LSB of field (numbered from 0) nBits - size of bit-field desc - txt description"""
<|body_0|>
def extractVal... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RegisterFieldInfo:
"""Describe meaning of a register bit-set"""
def __init__(self, minBit, nBits, desc):
"""fieldName - name of bitfield withing register minBit - LSB of field (numbered from 0) nBits - size of bit-field desc - txt description"""
self.minBit = minBit
self.nBits = n... | the_stack_v2_python_sparse | python/LATCRootData.py | fermi-lat/configData | train | 0 |
ae9a8f0bb32df5471b28635dd3f324a8914f0761 | [
"KratosMultiphysics.Process.__init__(self)\ndefault_settings = KratosMultiphysics.Parameters('\\n {\\n \"help\" : \"This process replaces the properties in a given instant\",\\n \"model_part_name\" : \"\",\\n \"materials_filename\" ... | <|body_start_0|>
KratosMultiphysics.Process.__init__(self)
default_settings = KratosMultiphysics.Parameters('\n {\n "help" : "This process replaces the properties in a given instant",\n "model_part_name" : "",\n "materials_filena... | This process replaces the properties in a given instant Only the member variables listed below should be accessed directly. Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings. | ReplacePropertiesProcess | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReplacePropertiesProcess:
"""This process replaces the properties in a given instant Only the member variables listed below should be accessed directly. Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings."""
... | stack_v2_sparse_classes_10k_train_006443 | 3,806 | permissive | [
{
"docstring": "The default constructor of the class Keyword arguments: self -- It signifies an instance of a class. Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings.",
"name": "__init__",
"signature": "def __init__(self, Model, settings)"
}... | 2 | null | Implement the Python class `ReplacePropertiesProcess` described below.
Class description:
This process replaces the properties in a given instant Only the member variables listed below should be accessed directly. Public member variables: Model -- the container of the different model parts. settings -- Kratos paramete... | Implement the Python class `ReplacePropertiesProcess` described below.
Class description:
This process replaces the properties in a given instant Only the member variables listed below should be accessed directly. Public member variables: Model -- the container of the different model parts. settings -- Kratos paramete... | 366949ec4e3651702edc6ac3061d2988f10dd271 | <|skeleton|>
class ReplacePropertiesProcess:
"""This process replaces the properties in a given instant Only the member variables listed below should be accessed directly. Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ReplacePropertiesProcess:
"""This process replaces the properties in a given instant Only the member variables listed below should be accessed directly. Public member variables: Model -- the container of the different model parts. settings -- Kratos parameters containing solver settings."""
def __init__(... | the_stack_v2_python_sparse | applications/ContactStructuralMechanicsApplication/python_scripts/replace_properties_process.py | KratosMultiphysics/Kratos | train | 994 |
c81679de5cc003b92c404006a988f2623b6537f6 | [
"def bisearch_l() -> int:\n i = -1\n l, r = (0, len(nums) - 1)\n while l <= r:\n m = (l + r) // 2\n if nums[m] >= target:\n r = m - 1\n else:\n l = m + 1\n if nums[m] == target:\n i = m\n return i\n\ndef bisearch_r() -> int:\n i = -1\n l... | <|body_start_0|>
def bisearch_l() -> int:
i = -1
l, r = (0, len(nums) - 1)
while l <= r:
m = (l + r) // 2
if nums[m] >= target:
r = m - 1
else:
l = m + 1
if nums[m] == targ... | Solution | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchRange4(self, nums: List[int], target: int) -> List[int]:
"""bisect.bisect_left() and bisect.bisect_right(), O(log n) Runtime: 68ms"""
<|body_0|>
def searchRange1(self, nums: List[int], target: int) -> List[int]:
"""Binary search: O(log n), the wor... | stack_v2_sparse_classes_10k_train_006444 | 4,074 | permissive | [
{
"docstring": "bisect.bisect_left() and bisect.bisect_right(), O(log n) Runtime: 68ms",
"name": "searchRange4",
"signature": "def searchRange4(self, nums: List[int], target: int) -> List[int]"
},
{
"docstring": "Binary search: O(log n), the worst case n + log n Runtime: 72ms",
"name": "sear... | 4 | stack_v2_sparse_classes_30k_train_001808 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchRange4(self, nums: List[int], target: int) -> List[int]: bisect.bisect_left() and bisect.bisect_right(), O(log n) Runtime: 68ms
- def searchRange1(self, nums: List[int]... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchRange4(self, nums: List[int], target: int) -> List[int]: bisect.bisect_left() and bisect.bisect_right(), O(log n) Runtime: 68ms
- def searchRange1(self, nums: List[int]... | 49a0b03c55d8a702785888d473ef96539265ce9c | <|skeleton|>
class Solution:
def searchRange4(self, nums: List[int], target: int) -> List[int]:
"""bisect.bisect_left() and bisect.bisect_right(), O(log n) Runtime: 68ms"""
<|body_0|>
def searchRange1(self, nums: List[int], target: int) -> List[int]:
"""Binary search: O(log n), the wor... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def searchRange4(self, nums: List[int], target: int) -> List[int]:
"""bisect.bisect_left() and bisect.bisect_right(), O(log n) Runtime: 68ms"""
def bisearch_l() -> int:
i = -1
l, r = (0, len(nums) - 1)
while l <= r:
m = (l + r) // 2... | the_stack_v2_python_sparse | leetcode/0034_find_first_and_last_position_of_element_in_sorted_array.py | chaosWsF/Python-Practice | train | 1 | |
29fb92fea72b57ffec209da8be14747c69eede46 | [
"self.hhsearch_pdb70_runner = HHSearch(binary_path=hhsearch_binary_path, databases=[pdb70_database_path])\nself.template_featurizer = template_featurizer\nself.result_path = result_path\nself.use_env = use_env",
"with open(input_fasta_path) as f:\n input_fasta_str = f.read()\ninput_seqs, input_descs = parse_fa... | <|body_start_0|>
self.hhsearch_pdb70_runner = HHSearch(binary_path=hhsearch_binary_path, databases=[pdb70_database_path])
self.template_featurizer = template_featurizer
self.result_path = result_path
self.use_env = use_env
<|end_body_0|>
<|body_start_1|>
with open(input_fasta_pa... | Runs the alignment tools and assembles the input features. | DataPipeline | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataPipeline:
"""Runs the alignment tools and assembles the input features."""
def __init__(self, hhsearch_binary_path: str, pdb70_database_path: str, template_featurizer: TemplateHitFeaturizer, result_path, use_env=False):
"""Constructs a feature dict for a given FASTA file."""
... | stack_v2_sparse_classes_10k_train_006445 | 8,009 | permissive | [
{
"docstring": "Constructs a feature dict for a given FASTA file.",
"name": "__init__",
"signature": "def __init__(self, hhsearch_binary_path: str, pdb70_database_path: str, template_featurizer: TemplateHitFeaturizer, result_path, use_env=False)"
},
{
"docstring": "Runs alignment tools on the in... | 2 | stack_v2_sparse_classes_30k_train_001507 | Implement the Python class `DataPipeline` described below.
Class description:
Runs the alignment tools and assembles the input features.
Method signatures and docstrings:
- def __init__(self, hhsearch_binary_path: str, pdb70_database_path: str, template_featurizer: TemplateHitFeaturizer, result_path, use_env=False): ... | Implement the Python class `DataPipeline` described below.
Class description:
Runs the alignment tools and assembles the input features.
Method signatures and docstrings:
- def __init__(self, hhsearch_binary_path: str, pdb70_database_path: str, template_featurizer: TemplateHitFeaturizer, result_path, use_env=False): ... | c72ce898482419117550ad16d93b38298f4306a1 | <|skeleton|>
class DataPipeline:
"""Runs the alignment tools and assembles the input features."""
def __init__(self, hhsearch_binary_path: str, pdb70_database_path: str, template_featurizer: TemplateHitFeaturizer, result_path, use_env=False):
"""Constructs a feature dict for a given FASTA file."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataPipeline:
"""Runs the alignment tools and assembles the input features."""
def __init__(self, hhsearch_binary_path: str, pdb70_database_path: str, template_featurizer: TemplateHitFeaturizer, result_path, use_env=False):
"""Constructs a feature dict for a given FASTA file."""
self.hhse... | the_stack_v2_python_sparse | reproduce/AlphaFold2-Chinese/data/tools/data_process.py | mindspore-ai/community | train | 193 |
0bc268e0959ebd52db661aadc09388190f61175c | [
"super(Linker_separate, self).__init__()\nself.config = config\nself.encoder = encoder\nself.entity_embeddings = nn.Embedding(self.config.entity_size, self.config.embedding_dim)\nself.entity_embeddings_struct = nn.Embedding(self.config.entity_size, self.config.embedding_dim)\nif self.config.priors:\n self.char_f... | <|body_start_0|>
super(Linker_separate, self).__init__()
self.config = config
self.encoder = encoder
self.entity_embeddings = nn.Embedding(self.config.entity_size, self.config.embedding_dim)
self.entity_embeddings_struct = nn.Embedding(self.config.entity_size, self.config.embeddi... | Linker_separate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linker_separate:
def __init__(self, config, encoder):
""":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions"""
<|body_0|>
def forward(self, entity_candidates, mention_representation, sentence, char_s... | stack_v2_sparse_classes_10k_train_006446 | 42,719 | permissive | [
{
"docstring": ":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions",
"name": "__init__",
"signature": "def __init__(self, config, encoder)"
},
{
"docstring": ":return: unnormalized log probabilities (logits) of gold enti... | 2 | stack_v2_sparse_classes_30k_train_007094 | Implement the Python class `Linker_separate` described below.
Class description:
Implement the Linker_separate class.
Method signatures and docstrings:
- def __init__(self, config, encoder): :param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions
... | Implement the Python class `Linker_separate` described below.
Class description:
Implement the Linker_separate class.
Method signatures and docstrings:
- def __init__(self, config, encoder): :param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions
... | 6a7dcd7d3756327c61ef949e5b4f6af6e2849187 | <|skeleton|>
class Linker_separate:
def __init__(self, config, encoder):
""":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions"""
<|body_0|>
def forward(self, entity_candidates, mention_representation, sentence, char_s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Linker_separate:
def __init__(self, config, encoder):
""":param config: A config object that specifies the hyperparameters of the model :param encoder: A Encoder for encoding mentions"""
super(Linker_separate, self).__init__()
self.config = config
self.encoder = encoder
... | the_stack_v2_python_sparse | typenet/src/model.py | dhruvdcoder/dl-with-constraints | train | 0 | |
bd487e09af6d18f93bf1d59df677765294db5a40 | [
"pm_config = pm.PaddleMobileConfig()\npm_config.precision = pm.PaddleMobileConfig.Precision.FP32\npm_config.device = pm.PaddleMobileConfig.Device.kFPGA\nif model_dir:\n pm_config.model_dir = model_dir\nelse:\n pm_config.prog_file = model_flie\n pm_config.param_file = param_file\npm_config.thread_num = thre... | <|body_start_0|>
pm_config = pm.PaddleMobileConfig()
pm_config.precision = pm.PaddleMobileConfig.Precision.FP32
pm_config.device = pm.PaddleMobileConfig.Device.kFPGA
if model_dir:
pm_config.model_dir = model_dir
else:
pm_config.prog_file = model_flie
... | pm_model | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class pm_model:
def load_model(self, model_flie, param_file, thread_num, model_dir):
"""加载PaddleMobile模型 参数：模型文件、模型参数文件、线程数、模型目录 返回：模型预测器"""
<|body_0|>
def data_feed(self, data_shape):
"""初始化PaddleMobile模型输入数据张量 参数：数据形状 返回：数据张量"""
<|body_1|>
def predict(self, ... | stack_v2_sparse_classes_10k_train_006447 | 3,563 | permissive | [
{
"docstring": "加载PaddleMobile模型 参数：模型文件、模型参数文件、线程数、模型目录 返回：模型预测器",
"name": "load_model",
"signature": "def load_model(self, model_flie, param_file, thread_num, model_dir)"
},
{
"docstring": "初始化PaddleMobile模型输入数据张量 参数：数据形状 返回：数据张量",
"name": "data_feed",
"signature": "def data_feed(self,... | 3 | null | Implement the Python class `pm_model` described below.
Class description:
Implement the pm_model class.
Method signatures and docstrings:
- def load_model(self, model_flie, param_file, thread_num, model_dir): 加载PaddleMobile模型 参数：模型文件、模型参数文件、线程数、模型目录 返回：模型预测器
- def data_feed(self, data_shape): 初始化PaddleMobile模型输入数据张量 ... | Implement the Python class `pm_model` described below.
Class description:
Implement the pm_model class.
Method signatures and docstrings:
- def load_model(self, model_flie, param_file, thread_num, model_dir): 加载PaddleMobile模型 参数：模型文件、模型参数文件、线程数、模型目录 返回：模型预测器
- def data_feed(self, data_shape): 初始化PaddleMobile模型输入数据张量 ... | afbd0e081763c53833617a4892d03043e644d641 | <|skeleton|>
class pm_model:
def load_model(self, model_flie, param_file, thread_num, model_dir):
"""加载PaddleMobile模型 参数：模型文件、模型参数文件、线程数、模型目录 返回：模型预测器"""
<|body_0|>
def data_feed(self, data_shape):
"""初始化PaddleMobile模型输入数据张量 参数：数据形状 返回：数据张量"""
<|body_1|>
def predict(self, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class pm_model:
def load_model(self, model_flie, param_file, thread_num, model_dir):
"""加载PaddleMobile模型 参数：模型文件、模型参数文件、线程数、模型目录 返回：模型预测器"""
pm_config = pm.PaddleMobileConfig()
pm_config.precision = pm.PaddleMobileConfig.Precision.FP32
pm_config.device = pm.PaddleMobileConfig.Device.... | the_stack_v2_python_sparse | mastercar/eblite_smart_car-master/model.py | wpy-111/python | train | 1 | |
7f6a83b13e41852bfb6bf635e66d82ab2997389e | [
"super(MultiBandUpdateManager, self).__init__(kwargs_model, kwargs_constraints, kwargs_likelihood, kwargs_params)\nkwargs_lens_fixed_init, _, _, _, _, _ = self.fixed_kwargs\nself._kwargs_lens_fixed_init = copy.deepcopy(kwargs_lens_fixed_init)\nself._index_lens_model_list = kwargs_model.get('index_lens_model_list', ... | <|body_start_0|>
super(MultiBandUpdateManager, self).__init__(kwargs_model, kwargs_constraints, kwargs_likelihood, kwargs_params)
kwargs_lens_fixed_init, _, _, _, _, _ = self.fixed_kwargs
self._kwargs_lens_fixed_init = copy.deepcopy(kwargs_lens_fixed_init)
self._index_lens_model_list = k... | specific Manager to deal with multiple images with disjoint lens model parameterization. The class inherits the UpdateManager() class and adds functionalities to hold and relieve fixed all lens model parameters of a specific frame/image for more convenient use of the FittingSequence. | MultiBandUpdateManager | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiBandUpdateManager:
"""specific Manager to deal with multiple images with disjoint lens model parameterization. The class inherits the UpdateManager() class and adds functionalities to hold and relieve fixed all lens model parameters of a specific frame/image for more convenient use of the Fi... | stack_v2_sparse_classes_10k_train_006448 | 4,390 | permissive | [
{
"docstring": ":param kwargs_model: keyword arguments to describe all model components used in class_creator.create_class_instances() :param kwargs_constraints: keyword arguments of the Param() class to handle parameter constraints during the sampling (except upper and lower limits and sampling input mean and ... | 4 | null | Implement the Python class `MultiBandUpdateManager` described below.
Class description:
specific Manager to deal with multiple images with disjoint lens model parameterization. The class inherits the UpdateManager() class and adds functionalities to hold and relieve fixed all lens model parameters of a specific frame/... | Implement the Python class `MultiBandUpdateManager` described below.
Class description:
specific Manager to deal with multiple images with disjoint lens model parameterization. The class inherits the UpdateManager() class and adds functionalities to hold and relieve fixed all lens model parameters of a specific frame/... | 73c9645f26f6983fe7961104075ebe8bf7a4b54c | <|skeleton|>
class MultiBandUpdateManager:
"""specific Manager to deal with multiple images with disjoint lens model parameterization. The class inherits the UpdateManager() class and adds functionalities to hold and relieve fixed all lens model parameters of a specific frame/image for more convenient use of the Fi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiBandUpdateManager:
"""specific Manager to deal with multiple images with disjoint lens model parameterization. The class inherits the UpdateManager() class and adds functionalities to hold and relieve fixed all lens model parameters of a specific frame/image for more convenient use of the FittingSequence... | the_stack_v2_python_sparse | lenstronomy/Workflow/multi_band_manager.py | lenstronomy/lenstronomy | train | 41 |
4e589f8922519877ee6234a81b63ea36292a13a8 | [
"super().__init__()\nself.recursion_degree = recursion_degree\nself._sk = SolovayKitaevDecomposition(basic_approximations)",
"for node in dag.op_nodes():\n if not node.op.num_qubits == 1:\n continue\n check_input = not isinstance(node.op, Gate)\n if not hasattr(node.op, 'to_matrix'):\n rais... | <|body_start_0|>
super().__init__()
self.recursion_degree = recursion_degree
self._sk = SolovayKitaevDecomposition(basic_approximations)
<|end_body_0|>
<|body_start_1|>
for node in dag.op_nodes():
if not node.op.num_qubits == 1:
continue
check_inp... | Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math:`SU(2)`. This is an important result, si... | SolovayKitaev | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SolovayKitaev:
"""Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math... | stack_v2_sparse_classes_10k_train_006449 | 10,726 | permissive | [
{
"docstring": "Args: recursion_degree: The recursion depth for the Solovay-Kitaev algorithm. A larger recursion depth increases the accuracy and length of the decomposition. basic_approximations: The basic approximations for the finding the best discrete decomposition at the root of the recursion. If a string,... | 2 | stack_v2_sparse_classes_30k_test_000402 | Implement the Python class `SolovayKitaev` described below.
Class description:
Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if th... | Implement the Python class `SolovayKitaev` described below.
Class description:
Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if th... | 0b51250e219ca303654fc28a318c21366584ccd3 | <|skeleton|>
class SolovayKitaev:
"""Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SolovayKitaev:
"""Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math:`SU(2)`. Thi... | the_stack_v2_python_sparse | qiskit/transpiler/passes/synthesis/solovay_kitaev_synthesis.py | 1ucian0/qiskit-terra | train | 6 |
e59c138015eb4cb1bd22d60604ba1e0588687204 | [
"self.root = Node()\nself.m = max(map(len, words))\nself.initials = set([word[0] for word in words])\nl = []\nfor word in words:\n l += list(word)\nself.letters = set(l)\nself.trie = Trie()\nself.stream = ''",
"if letter not in self.letters:\n self.stream = ''\n return False\nif len(self.stream) == 0 and... | <|body_start_0|>
self.root = Node()
self.m = max(map(len, words))
self.initials = set([word[0] for word in words])
l = []
for word in words:
l += list(word)
self.letters = set(l)
self.trie = Trie()
self.stream = ''
<|end_body_0|>
<|body_start_... | StreamChecker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def query(self, letter):
""":type letter: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.root = Node()
self.m = max(map(len, words))
... | stack_v2_sparse_classes_10k_train_006450 | 2,195 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type letter: str :rtype: bool",
"name": "query",
"signature": "def query(self, letter)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003380 | Implement the Python class `StreamChecker` described below.
Class description:
Implement the StreamChecker class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def query(self, letter): :type letter: str :rtype: bool | Implement the Python class `StreamChecker` described below.
Class description:
Implement the StreamChecker class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def query(self, letter): :type letter: str :rtype: bool
<|skeleton|>
class StreamChecker:
def __init__(self, w... | 0c3ae35908cb6aa73c0962376facbdd750854f48 | <|skeleton|>
class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def query(self, letter):
""":type letter: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
self.root = Node()
self.m = max(map(len, words))
self.initials = set([word[0] for word in words])
l = []
for word in words:
l += list(word)
self.letters = set(l)
s... | the_stack_v2_python_sparse | theory/data_structures/trie/stream_of_characters.py | tHeMaskedMan981/coding_practice | train | 0 | |
c25d7dafdeaf49c5244ff060abf91e3f73419a66 | [
"if not data.get('project_id'):\n data['project_id'] = uuid.uuid4().hex\nreturn data",
"try:\n git_url = GitURL.parse(data['git_url'])\nexcept UnicodeError as e:\n raise ValidationError('`git_url` contains unsupported characters') from e\nexcept errors.InvalidGitURL as e:\n raise ValidationError('Inva... | <|body_start_0|>
if not data.get('project_id'):
data['project_id'] = uuid.uuid4().hex
return data
<|end_body_0|>
<|body_start_1|>
try:
git_url = GitURL.parse(data['git_url'])
except UnicodeError as e:
raise ValidationError('`git_url` contains unsuppor... | Context schema for project clone. | ProjectCloneContext | [
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectCloneContext:
"""Context schema for project clone."""
def set_missing_id(self, data, **kwargs):
"""Set project_id when missing."""
<|body_0|>
def set_owner_name(self, data, **kwargs):
"""Set owner and name fields."""
<|body_1|>
def format_url(... | stack_v2_sparse_classes_10k_train_006451 | 14,192 | permissive | [
{
"docstring": "Set project_id when missing.",
"name": "set_missing_id",
"signature": "def set_missing_id(self, data, **kwargs)"
},
{
"docstring": "Set owner and name fields.",
"name": "set_owner_name",
"signature": "def set_owner_name(self, data, **kwargs)"
},
{
"docstring": "Fo... | 4 | null | Implement the Python class `ProjectCloneContext` described below.
Class description:
Context schema for project clone.
Method signatures and docstrings:
- def set_missing_id(self, data, **kwargs): Set project_id when missing.
- def set_owner_name(self, data, **kwargs): Set owner and name fields.
- def format_url(self... | Implement the Python class `ProjectCloneContext` described below.
Class description:
Context schema for project clone.
Method signatures and docstrings:
- def set_missing_id(self, data, **kwargs): Set project_id when missing.
- def set_owner_name(self, data, **kwargs): Set owner and name fields.
- def format_url(self... | e0ff587f507d049eeeb873e8488ba8bb10ac1a15 | <|skeleton|>
class ProjectCloneContext:
"""Context schema for project clone."""
def set_missing_id(self, data, **kwargs):
"""Set project_id when missing."""
<|body_0|>
def set_owner_name(self, data, **kwargs):
"""Set owner and name fields."""
<|body_1|>
def format_url(... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProjectCloneContext:
"""Context schema for project clone."""
def set_missing_id(self, data, **kwargs):
"""Set project_id when missing."""
if not data.get('project_id'):
data['project_id'] = uuid.uuid4().hex
return data
def set_owner_name(self, data, **kwargs):
... | the_stack_v2_python_sparse | renku/ui/service/serializers/cache.py | SwissDataScienceCenter/renku-python | train | 30 |
00a16404f30a7f2e6baa4e684ec4435e5ae5287a | [
"self.corpora = self.process_corpora(corporaList, stopwords_f)\nprint('loading pre-trained w2v model...')\ntic = time.time()\nif pretrained_w2v:\n self.w2v_model = pretrained_w2v\nelif w2v_f.endswith('.bin'):\n self.w2v_model = gensim.models.KeyedVectors.load_word2vec_format(w2v_f, binary=True)\nelse:\n se... | <|body_start_0|>
self.corpora = self.process_corpora(corporaList, stopwords_f)
print('loading pre-trained w2v model...')
tic = time.time()
if pretrained_w2v:
self.w2v_model = pretrained_w2v
elif w2v_f.endswith('.bin'):
self.w2v_model = gensim.models.KeyedV... | W2VModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class W2VModel:
def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None):
"""实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [["There", "is", "a", "cat"], ["There", "is", "a", "dog"],... | stack_v2_sparse_classes_10k_train_006452 | 8,398 | no_license | [
{
"docstring": "实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [[\"There\", \"is\", \"a\", \"cat\"], [\"There\", \"is\", \"a\", \"dog\"], [\"There\", \"is\", \"a\", \"wolf\"]] w2v_f: str, 预训练的词向量文件路径 stopwords_f: str, 停用词文件 pretrained_w2v: ge... | 6 | stack_v2_sparse_classes_30k_val_000266 | Implement the Python class `W2VModel` described below.
Class description:
Implement the W2VModel class.
Method signatures and docstrings:
- def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None): 实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个... | Implement the Python class `W2VModel` described below.
Class description:
Implement the W2VModel class.
Method signatures and docstrings:
- def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None): 实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个... | c2a20a430de197d06dca5ada96160388730a5db5 | <|skeleton|>
class W2VModel:
def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None):
"""实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [["There", "is", "a", "cat"], ["There", "is", "a", "dog"],... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class W2VModel:
def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None):
"""实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [["There", "is", "a", "cat"], ["There", "is", "a", "dog"], ["There", "is... | the_stack_v2_python_sparse | Models/Word2Vec/API/Word2VecModel.py | JaMesLiMers/Image_Retrieval_Framework_FYP | train | 2 | |
f6718c95d2fc137a47c3d02148bd1e571c72797f | [
"assert 0 < smoothing < 1, 'Smoothing factor should be in (0.0, 1.0)'\nassert reduction in {'batchmean', 'none', 'sum'}\nsuper().__init__()\nself.smoothing = smoothing\nself.ignore_index = ignore_index\nself.reduction = reduction",
"target = target.view(-1, 1)\nsmoothed_target = torch.zeros(input.shape, requires_... | <|body_start_0|>
assert 0 < smoothing < 1, 'Smoothing factor should be in (0.0, 1.0)'
assert reduction in {'batchmean', 'none', 'sum'}
super().__init__()
self.smoothing = smoothing
self.ignore_index = ignore_index
self.reduction = reduction
<|end_body_0|>
<|body_start_1|... | Computes cross entropy loss with uniformly smoothed targets. | SmoothedCrossEntropyLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmoothedCrossEntropyLoss:
"""Computes cross entropy loss with uniformly smoothed targets."""
def __init__(self, smoothing: float=0.1, ignore_index: int=-1, reduction: str='batchmean'):
"""Cross entropy loss with uniformly smoothed targets. :param float smoothing: Label smoothing fact... | stack_v2_sparse_classes_10k_train_006453 | 4,120 | permissive | [
{
"docstring": "Cross entropy loss with uniformly smoothed targets. :param float smoothing: Label smoothing factor, between 0 and 1 (exclusive; default is 0.1) :param int ignore_index: Index to be ignored. (PAD_ID by default) :param str reduction: Style of reduction to be done. One of 'batchmean'(default), 'non... | 2 | stack_v2_sparse_classes_30k_train_005946 | Implement the Python class `SmoothedCrossEntropyLoss` described below.
Class description:
Computes cross entropy loss with uniformly smoothed targets.
Method signatures and docstrings:
- def __init__(self, smoothing: float=0.1, ignore_index: int=-1, reduction: str='batchmean'): Cross entropy loss with uniformly smoot... | Implement the Python class `SmoothedCrossEntropyLoss` described below.
Class description:
Computes cross entropy loss with uniformly smoothed targets.
Method signatures and docstrings:
- def __init__(self, smoothing: float=0.1, ignore_index: int=-1, reduction: str='batchmean'): Cross entropy loss with uniformly smoot... | be5595fc5f40f7d281f9318ff26095c0d15ed5da | <|skeleton|>
class SmoothedCrossEntropyLoss:
"""Computes cross entropy loss with uniformly smoothed targets."""
def __init__(self, smoothing: float=0.1, ignore_index: int=-1, reduction: str='batchmean'):
"""Cross entropy loss with uniformly smoothed targets. :param float smoothing: Label smoothing fact... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SmoothedCrossEntropyLoss:
"""Computes cross entropy loss with uniformly smoothed targets."""
def __init__(self, smoothing: float=0.1, ignore_index: int=-1, reduction: str='batchmean'):
"""Cross entropy loss with uniformly smoothed targets. :param float smoothing: Label smoothing factor, between 0... | the_stack_v2_python_sparse | mwptoolkit/loss/smoothed_cross_entropy_loss.py | TalhaAbid/MWPToolkit | train | 0 |
e58cd79f1d25175c204ec9244c29c2bf0ebdf6da | [
"self.index = index\nself.source_name = source_name\nself.file_extension = file_extension\nself.sourcetype = sourcetype\nself.host = host",
"fields_str = None\nfor field_name, field_value in fields_dict.items():\n if fields_str is None:\n fields_str = ''\n elif fields_str is not None:\n fields... | <|body_start_0|>
self.index = index
self.source_name = source_name
self.file_extension = file_extension
self.sourcetype = sourcetype
self.host = host
<|end_body_0|>
<|body_start_1|>
fields_str = None
for field_name, field_value in fields_dict.items():
... | The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly). | StashNewWriter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StashNewWriter:
"""The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly)."""
def __init__(self, index, source_name, file_extension='.stash_new', sourcetype=None, host=None):
"""Constructor... | stack_v2_sparse_classes_10k_train_006454 | 13,683 | permissive | [
{
"docstring": "Constructor for the stash writer,=. Arguments: index -- the index to send the events to source_name -- the search that is being used to generate the results file_extension -- the extension of the stash file (usually .stash_new) sourcetype -- the sourcetype to use for the event host -- the host t... | 5 | stack_v2_sparse_classes_30k_train_006549 | Implement the Python class `StashNewWriter` described below.
Class description:
The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly).
Method signatures and docstrings:
- def __init__(self, index, source_name, file_extensi... | Implement the Python class `StashNewWriter` described below.
Class description:
The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly).
Method signatures and docstrings:
- def __init__(self, index, source_name, file_extensi... | 9c1027f1b1a58d30973256412fb72a6fe6bf029c | <|skeleton|>
class StashNewWriter:
"""The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly)."""
def __init__(self, index, source_name, file_extension='.stash_new', sourcetype=None, host=None):
"""Constructor... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StashNewWriter:
"""The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly)."""
def __init__(self, index, source_name, file_extension='.stash_new', sourcetype=None, host=None):
"""Constructor for the stas... | the_stack_v2_python_sparse | src/bin/network_tools_app/event_writer.py | LukeMurphey/splunk-network-tools | train | 6 |
db29e9509c6f77cb897cc65e58127c3799636518 | [
"self.key = key\nif isinstance(val, list):\n nested_debug_strs = [self.StringRep(v) for v in val]\n self.val = '[%s]' % ', '.join(nested_debug_strs)\nelse:\n self.val = self.StringRep(val)",
"try:\n return val.DebugString()\nexcept Exception:\n try:\n return str(val.__dict__)\n except Exc... | <|body_start_0|>
self.key = key
if isinstance(val, list):
nested_debug_strs = [self.StringRep(v) for v in val]
self.val = '[%s]' % ', '.join(nested_debug_strs)
else:
self.val = self.StringRep(val)
<|end_body_0|>
<|body_start_1|>
try:
retur... | Wrapper class to generate on-screen debugging output. | _ContextDebugItem | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ContextDebugItem:
"""Wrapper class to generate on-screen debugging output."""
def __init__(self, key, val):
"""Store the key and generate a string for the value."""
<|body_0|>
def StringRep(self, val):
"""Make a useful string representation of the given value.""... | stack_v2_sparse_classes_10k_train_006455 | 36,471 | permissive | [
{
"docstring": "Store the key and generate a string for the value.",
"name": "__init__",
"signature": "def __init__(self, key, val)"
},
{
"docstring": "Make a useful string representation of the given value.",
"name": "StringRep",
"signature": "def StringRep(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006130 | Implement the Python class `_ContextDebugItem` described below.
Class description:
Wrapper class to generate on-screen debugging output.
Method signatures and docstrings:
- def __init__(self, key, val): Store the key and generate a string for the value.
- def StringRep(self, val): Make a useful string representation ... | Implement the Python class `_ContextDebugItem` described below.
Class description:
Wrapper class to generate on-screen debugging output.
Method signatures and docstrings:
- def __init__(self, key, val): Store the key and generate a string for the value.
- def StringRep(self, val): Make a useful string representation ... | b5d4783f99461438ca9e6a477535617fadab6ba3 | <|skeleton|>
class _ContextDebugItem:
"""Wrapper class to generate on-screen debugging output."""
def __init__(self, key, val):
"""Store the key and generate a string for the value."""
<|body_0|>
def StringRep(self, val):
"""Make a useful string representation of the given value.""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _ContextDebugItem:
"""Wrapper class to generate on-screen debugging output."""
def __init__(self, key, val):
"""Store the key and generate a string for the value."""
self.key = key
if isinstance(val, list):
nested_debug_strs = [self.StringRep(v) for v in val]
... | the_stack_v2_python_sparse | appengine/monorail/framework/servlet.py | xinghun61/infra | train | 2 |
92baa7a659351e7b65a740d822cbfd51ae1a6e03 | [
"object = get_object_or_404(CallRegister, pk=id)\nform = CallRegisterForm(instance=object)\ncontext = {'object': object, 'form': form}\nreturn render(request, self.template_name, context)",
"form = CallRegisterForm(request.POST or None)\nif form.is_valid():\n object = get_object_or_404(CallRegister, pk=id)\n ... | <|body_start_0|>
object = get_object_or_404(CallRegister, pk=id)
form = CallRegisterForm(instance=object)
context = {'object': object, 'form': form}
return render(request, self.template_name, context)
<|end_body_0|>
<|body_start_1|>
form = CallRegisterForm(request.POST or None)
... | CallEditView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CallEditView:
def get(self, request, id):
"""Returns single call data from db, appointment_date is passed into form to display as form only."""
<|body_0|>
def post(self, request, id):
"""Overrides all existing details of specific call, similar to call register."""
... | stack_v2_sparse_classes_10k_train_006456 | 8,699 | no_license | [
{
"docstring": "Returns single call data from db, appointment_date is passed into form to display as form only.",
"name": "get",
"signature": "def get(self, request, id)"
},
{
"docstring": "Overrides all existing details of specific call, similar to call register.",
"name": "post",
"sign... | 2 | stack_v2_sparse_classes_30k_train_001720 | Implement the Python class `CallEditView` described below.
Class description:
Implement the CallEditView class.
Method signatures and docstrings:
- def get(self, request, id): Returns single call data from db, appointment_date is passed into form to display as form only.
- def post(self, request, id): Overrides all e... | Implement the Python class `CallEditView` described below.
Class description:
Implement the CallEditView class.
Method signatures and docstrings:
- def get(self, request, id): Returns single call data from db, appointment_date is passed into form to display as form only.
- def post(self, request, id): Overrides all e... | bdd7c5ca9f00ce33be31609e5be9c2ccfcd8743a | <|skeleton|>
class CallEditView:
def get(self, request, id):
"""Returns single call data from db, appointment_date is passed into form to display as form only."""
<|body_0|>
def post(self, request, id):
"""Overrides all existing details of specific call, similar to call register."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CallEditView:
def get(self, request, id):
"""Returns single call data from db, appointment_date is passed into form to display as form only."""
object = get_object_or_404(CallRegister, pk=id)
form = CallRegisterForm(instance=object)
context = {'object': object, 'form': form}
... | the_stack_v2_python_sparse | calls/views.py | mrmaheshrajput/htscrm | train | 0 | |
a6169279466f3ef82482f9c3a52e0e3b6f28f523 | [
"cg_model = self.DATA.CG_MODEL.strip()\nscp_array = numpy.array([float(self.DATA.CG_SCECN_X), float(self.DATA.CG_SCECN_Y), float(self.DATA.CG_SCECN_Z)], dtype='float64')\nif cg_model == 'ECEF':\n return scp_array\nelif cg_model == 'WGS84':\n return geodetic_to_ecf(scp_array)\nelse:\n raise ValueError('Got ... | <|body_start_0|>
cg_model = self.DATA.CG_MODEL.strip()
scp_array = numpy.array([float(self.DATA.CG_SCECN_X), float(self.DATA.CG_SCECN_Y), float(self.DATA.CG_SCECN_Z)], dtype='float64')
if cg_model == 'ECEF':
return scp_array
elif cg_model == 'WGS84':
return geodet... | CMETAA | [
"LicenseRef-scancode-free-unknown",
"MIT",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CMETAA:
def get_scp(self):
"""Gets the SCP location in ECF coordinates. Returns ------- numpy.ndarray"""
<|body_0|>
def get_arp(self):
"""Gets the Aperture Position, at SCP Time, in ECF coordinates. Returns ------- numpy.ndarray"""
<|body_1|>
def get_ima... | stack_v2_sparse_classes_10k_train_006457 | 11,683 | permissive | [
{
"docstring": "Gets the SCP location in ECF coordinates. Returns ------- numpy.ndarray",
"name": "get_scp",
"signature": "def get_scp(self)"
},
{
"docstring": "Gets the Aperture Position, at SCP Time, in ECF coordinates. Returns ------- numpy.ndarray",
"name": "get_arp",
"signature": "d... | 3 | null | Implement the Python class `CMETAA` described below.
Class description:
Implement the CMETAA class.
Method signatures and docstrings:
- def get_scp(self): Gets the SCP location in ECF coordinates. Returns ------- numpy.ndarray
- def get_arp(self): Gets the Aperture Position, at SCP Time, in ECF coordinates. Returns -... | Implement the Python class `CMETAA` described below.
Class description:
Implement the CMETAA class.
Method signatures and docstrings:
- def get_scp(self): Gets the SCP location in ECF coordinates. Returns ------- numpy.ndarray
- def get_arp(self): Gets the Aperture Position, at SCP Time, in ECF coordinates. Returns -... | de1b1886f161a83b6c89aadc7a2c7cfc4892ef81 | <|skeleton|>
class CMETAA:
def get_scp(self):
"""Gets the SCP location in ECF coordinates. Returns ------- numpy.ndarray"""
<|body_0|>
def get_arp(self):
"""Gets the Aperture Position, at SCP Time, in ECF coordinates. Returns ------- numpy.ndarray"""
<|body_1|>
def get_ima... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CMETAA:
def get_scp(self):
"""Gets the SCP location in ECF coordinates. Returns ------- numpy.ndarray"""
cg_model = self.DATA.CG_MODEL.strip()
scp_array = numpy.array([float(self.DATA.CG_SCECN_X), float(self.DATA.CG_SCECN_Y), float(self.DATA.CG_SCECN_Z)], dtype='float64')
if cg... | the_stack_v2_python_sparse | sarpy/io/general/nitf_elements/tres/unclass/CMETAA.py | ngageoint/sarpy | train | 192 | |
3c0c88dcecaaef0791230f216f06b9a984ba389b | [
"PlottingComponent.__init__(self, config)\nDecompositionComponent.__init__(self)\nself.frame = None\nself.bulge = None\nself.disk = None\nself.model = None",
"self.setup()\nself.load_images()\nself.plot()",
"log.info('Loading the IRAC 3.6 micron image ...')\npath = fs.join(self.truncation_path, 'IRAC I1.fits')\... | <|body_start_0|>
PlottingComponent.__init__(self, config)
DecompositionComponent.__init__(self)
self.frame = None
self.bulge = None
self.disk = None
self.model = None
<|end_body_0|>
<|body_start_1|>
self.setup()
self.load_images()
self.plot()
<|en... | This class... | DecompositionPlotter | [
"MIT",
"GPL-1.0-or-later",
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-philippe-de-muyter"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecompositionPlotter:
"""This class..."""
def __init__(self, config=None):
"""The constructor ... :param config: :return:"""
<|body_0|>
def run(self, features=None):
"""This function ... :return:"""
<|body_1|>
def load_images(self):
"""This f... | stack_v2_sparse_classes_10k_train_006458 | 4,395 | permissive | [
{
"docstring": "The constructor ... :param config: :return:",
"name": "__init__",
"signature": "def __init__(self, config=None)"
},
{
"docstring": "This function ... :return:",
"name": "run",
"signature": "def run(self, features=None)"
},
{
"docstring": "This function ... :return... | 4 | null | Implement the Python class `DecompositionPlotter` described below.
Class description:
This class...
Method signatures and docstrings:
- def __init__(self, config=None): The constructor ... :param config: :return:
- def run(self, features=None): This function ... :return:
- def load_images(self): This function ... :re... | Implement the Python class `DecompositionPlotter` described below.
Class description:
This class...
Method signatures and docstrings:
- def __init__(self, config=None): The constructor ... :param config: :return:
- def run(self, features=None): This function ... :return:
- def load_images(self): This function ... :re... | 62b2339beb2eb956565e1605d44d92f934361ad7 | <|skeleton|>
class DecompositionPlotter:
"""This class..."""
def __init__(self, config=None):
"""The constructor ... :param config: :return:"""
<|body_0|>
def run(self, features=None):
"""This function ... :return:"""
<|body_1|>
def load_images(self):
"""This f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DecompositionPlotter:
"""This class..."""
def __init__(self, config=None):
"""The constructor ... :param config: :return:"""
PlottingComponent.__init__(self, config)
DecompositionComponent.__init__(self)
self.frame = None
self.bulge = None
self.disk = None
... | the_stack_v2_python_sparse | CAAPR/CAAPR_AstroMagic/PTS/pts/modeling/plotting/decomposition.py | Stargrazer82301/CAAPR | train | 8 |
3f4b8f24136aa531101e5c0643163f534ba1ee94 | [
"seg_logits = self(inputs)\nvalid_label_mask = get_valid_label_mask_per_batch(img_metas, self.num_classes)\nlosses = self.losses(seg_logits, gt_semantic_seg, train_cfg, valid_label_mask=valid_label_mask, pixel_weights=pixel_weights)\nif return_logits:\n logits = self.forward_output if self.forward_output is not ... | <|body_start_0|>
seg_logits = self(inputs)
valid_label_mask = get_valid_label_mask_per_batch(img_metas, self.num_classes)
losses = self.losses(seg_logits, gt_semantic_seg, train_cfg, valid_label_mask=valid_label_mask, pixel_weights=pixel_weights)
if return_logits:
logits = se... | PixelWeightsMixin2 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PixelWeightsMixin2:
def forward_train(self, inputs, img_metas, gt_semantic_seg, train_cfg, pixel_weights=None, return_logits=False):
"""Forward function for training. Args: inputs (list[Tensor]): List of multi-level img features. img_metas (list[dict]): List of image info dict where each... | stack_v2_sparse_classes_10k_train_006459 | 7,209 | permissive | [
{
"docstring": "Forward function for training. Args: inputs (list[Tensor]): List of multi-level img features. img_metas (list[dict]): List of image info dict where each dict has: 'img_shape', 'scale_factor', 'flip', and may also contain 'filename', 'ori_shape', 'pad_shape', 'img_norm_cfg', and 'ignored_labels'.... | 2 | stack_v2_sparse_classes_30k_train_004485 | Implement the Python class `PixelWeightsMixin2` described below.
Class description:
Implement the PixelWeightsMixin2 class.
Method signatures and docstrings:
- def forward_train(self, inputs, img_metas, gt_semantic_seg, train_cfg, pixel_weights=None, return_logits=False): Forward function for training. Args: inputs (... | Implement the Python class `PixelWeightsMixin2` described below.
Class description:
Implement the PixelWeightsMixin2 class.
Method signatures and docstrings:
- def forward_train(self, inputs, img_metas, gt_semantic_seg, train_cfg, pixel_weights=None, return_logits=False): Forward function for training. Args: inputs (... | 6116639caeff100b06a6c10a96c7e7f5951f20c7 | <|skeleton|>
class PixelWeightsMixin2:
def forward_train(self, inputs, img_metas, gt_semantic_seg, train_cfg, pixel_weights=None, return_logits=False):
"""Forward function for training. Args: inputs (list[Tensor]): List of multi-level img features. img_metas (list[dict]): List of image info dict where each... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PixelWeightsMixin2:
def forward_train(self, inputs, img_metas, gt_semantic_seg, train_cfg, pixel_weights=None, return_logits=False):
"""Forward function for training. Args: inputs (list[Tensor]): List of multi-level img features. img_metas (list[dict]): List of image info dict where each dict has: 'im... | the_stack_v2_python_sparse | otx/mpa/modules/models/heads/pixel_weights_mixin.py | GalyaZalesskaya/openvino_training_extensions | train | 0 | |
8e95d308ef5d686aa068a1050d4965350314c80b | [
"json_dict = json.loads(request.body.decode())\nreceiver = json_dict.get('receiver')\nprovince_id = json_dict.get('province_id')\ncity_id = json_dict.get('city_id')\ndistrict_id = json_dict.get('district_id')\nplace = json_dict.get('place')\nmobile = json_dict.get('mobile')\ntel = json_dict.get('tel')\nemail = json... | <|body_start_0|>
json_dict = json.loads(request.body.decode())
receiver = json_dict.get('receiver')
province_id = json_dict.get('province_id')
city_id = json_dict.get('city_id')
district_id = json_dict.get('district_id')
place = json_dict.get('place')
mobile = jso... | 修改和删除地址 | UpdateDestroyAddressView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除地址"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
json_dict = json.loads(request.body.decode())
... | stack_v2_sparse_classes_10k_train_006460 | 29,582 | permissive | [
{
"docstring": "修改地址",
"name": "put",
"signature": "def put(self, request, address_id)"
},
{
"docstring": "删除地址",
"name": "delete",
"signature": "def delete(self, request, address_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004400 | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
修改和删除地址
Method signatures and docstrings:
- def put(self, request, address_id): 修改地址
- def delete(self, request, address_id): 删除地址 | Implement the Python class `UpdateDestroyAddressView` described below.
Class description:
修改和删除地址
Method signatures and docstrings:
- def put(self, request, address_id): 修改地址
- def delete(self, request, address_id): 删除地址
<|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, addre... | 5b3ca1fba8205c2c0a2b91d951f812f1c30e12ae | <|skeleton|>
class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
<|body_0|>
def delete(self, request, address_id):
"""删除地址"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateDestroyAddressView:
"""修改和删除地址"""
def put(self, request, address_id):
"""修改地址"""
json_dict = json.loads(request.body.decode())
receiver = json_dict.get('receiver')
province_id = json_dict.get('province_id')
city_id = json_dict.get('city_id')
district_... | the_stack_v2_python_sparse | meiduo1/apps/user/views.py | woobrain/nginx-uwsgi-web | train | 0 |
271f1b18ec797c25f684df51ed466dbfd051ab2e | [
"self.connector_group_id = connector_group_id\nself.entity_id = entity_id\nself.network_realm_id = network_realm_id",
"if dictionary is None:\n return None\nconnector_group_id = dictionary.get('connectorGroupId')\nentity_id = dictionary.get('entityId')\nnetwork_realm_id = dictionary.get('networkRealmId')\nretu... | <|body_start_0|>
self.connector_group_id = connector_group_id
self.entity_id = entity_id
self.network_realm_id = network_realm_id
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
connector_group_id = dictionary.get('connectorGroupId')
entity... | Implementation of the 'NetworkRealmInfo' model. Contains mapping of network realms with adapter specific entities. This will be populated by IRIS for create/update source requests so that we can persist the mapping in the corresponding entity hierarchy. Attributes: connector_group_id (long|int): 'network_realm_id' main... | NetworkRealmInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkRealmInfo:
"""Implementation of the 'NetworkRealmInfo' model. Contains mapping of network realms with adapter specific entities. This will be populated by IRIS for create/update source requests so that we can persist the mapping in the corresponding entity hierarchy. Attributes: connector_... | stack_v2_sparse_classes_10k_train_006461 | 2,452 | permissive | [
{
"docstring": "Constructor for the NetworkRealmInfo class",
"name": "__init__",
"signature": "def __init__(self, connector_group_id=None, entity_id=None, network_realm_id=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary re... | 2 | null | Implement the Python class `NetworkRealmInfo` described below.
Class description:
Implementation of the 'NetworkRealmInfo' model. Contains mapping of network realms with adapter specific entities. This will be populated by IRIS for create/update source requests so that we can persist the mapping in the corresponding e... | Implement the Python class `NetworkRealmInfo` described below.
Class description:
Implementation of the 'NetworkRealmInfo' model. Contains mapping of network realms with adapter specific entities. This will be populated by IRIS for create/update source requests so that we can persist the mapping in the corresponding e... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class NetworkRealmInfo:
"""Implementation of the 'NetworkRealmInfo' model. Contains mapping of network realms with adapter specific entities. This will be populated by IRIS for create/update source requests so that we can persist the mapping in the corresponding entity hierarchy. Attributes: connector_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NetworkRealmInfo:
"""Implementation of the 'NetworkRealmInfo' model. Contains mapping of network realms with adapter specific entities. This will be populated by IRIS for create/update source requests so that we can persist the mapping in the corresponding entity hierarchy. Attributes: connector_group_id (lon... | the_stack_v2_python_sparse | cohesity_management_sdk/models/network_realm_info.py | cohesity/management-sdk-python | train | 24 |
9fc1955b3e73b4629b0fa0d89440aa8dd053f8bb | [
"super(BiAffineAttention, self).__init__()\nself.encoder_size = encoder_size\nself.decoder_size = decoder_size\nself.num_labels = num_labels\nself.hidden_size = hidden_size\nself.e_mlp = nn.Sequential(nn.Linear(encoder_size, hidden_size), nn.ReLU())\nself.d_mlp = nn.Sequential(nn.Linear(decoder_size, hidden_size), ... | <|body_start_0|>
super(BiAffineAttention, self).__init__()
self.encoder_size = encoder_size
self.decoder_size = decoder_size
self.num_labels = num_labels
self.hidden_size = hidden_size
self.e_mlp = nn.Sequential(nn.Linear(encoder_size, hidden_size), nn.ReLU())
sel... | BiAffineAttention | [
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiAffineAttention:
def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE):
"""num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。"""
<|body_0|>
def forward(self, e_outputs,... | stack_v2_sparse_classes_10k_train_006462 | 3,328 | permissive | [
{
"docstring": "num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。",
"name": "__init__",
"signature": "def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE)"
},
{
"docstring": ":param e_outpu... | 2 | stack_v2_sparse_classes_30k_train_004887 | Implement the Python class `BiAffineAttention` described below.
Class description:
Implement the BiAffineAttention class.
Method signatures and docstrings:
- def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE): num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择... | Implement the Python class `BiAffineAttention` described below.
Class description:
Implement the BiAffineAttention class.
Method signatures and docstrings:
- def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE): num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择... | fd71b353c59bcb82ec2cd0bebf943040756faa63 | <|skeleton|>
class BiAffineAttention:
def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE):
"""num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。"""
<|body_0|>
def forward(self, e_outputs,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BiAffineAttention:
def __init__(self, encoder_size, decoder_size, num_labels=1, hidden_size=HIDDEN_SIZE):
"""num_labels 代表当前节点到各个节点之间做的 bi_affine attention 分配给各个节点的向量维度， 因为子句分割是分割点选择任务，所以每个分割点的维度设置为1即可，一组标量的 soft_max 概率即 为边界标签的选择结果。"""
super(BiAffineAttention, self).__init__()
self.enc... | the_stack_v2_python_sparse | CDTB_Seg/model/ENC_DEC_GCN/biaffine_attn.py | NLP-Discourse-SoochowU/segmenter2020 | train | 0 | |
57b9a03d623010d22f1b49278971f4561f2ea44e | [
"lLatitude = self.cleaned_data['latitude']\nif lLatitude:\n lValue = lLatitude.strip()\n if lValue:\n lRegEx = re.compile(CO_ORD_REGEX)\n if lRegEx.match(lValue) == None:\n raise forms.ValidationError(\"Please enter the location in decimal notation, for example 53.768761 If it ends w... | <|body_start_0|>
lLatitude = self.cleaned_data['latitude']
if lLatitude:
lValue = lLatitude.strip()
if lValue:
lRegEx = re.compile(CO_ORD_REGEX)
if lRegEx.match(lValue) == None:
raise forms.ValidationError("Please enter the loca... | Form for entering a new venue | EditVenueForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditVenueForm:
"""Form for entering a new venue"""
def clean_latitude(self):
"""Validate latitude is in correct format"""
<|body_0|>
def clean_longitude(self):
"""Validation longitude is in correct format"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_006463 | 1,542 | no_license | [
{
"docstring": "Validate latitude is in correct format",
"name": "clean_latitude",
"signature": "def clean_latitude(self)"
},
{
"docstring": "Validation longitude is in correct format",
"name": "clean_longitude",
"signature": "def clean_longitude(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000313 | Implement the Python class `EditVenueForm` described below.
Class description:
Form for entering a new venue
Method signatures and docstrings:
- def clean_latitude(self): Validate latitude is in correct format
- def clean_longitude(self): Validation longitude is in correct format | Implement the Python class `EditVenueForm` described below.
Class description:
Form for entering a new venue
Method signatures and docstrings:
- def clean_latitude(self): Validate latitude is in correct format
- def clean_longitude(self): Validation longitude is in correct format
<|skeleton|>
class EditVenueForm:
... | 05c9d3a53c491cc255e7a351de87273df31a0303 | <|skeleton|>
class EditVenueForm:
"""Form for entering a new venue"""
def clean_latitude(self):
"""Validate latitude is in correct format"""
<|body_0|>
def clean_longitude(self):
"""Validation longitude is in correct format"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EditVenueForm:
"""Form for entering a new venue"""
def clean_latitude(self):
"""Validate latitude is in correct format"""
lLatitude = self.cleaned_data['latitude']
if lLatitude:
lValue = lLatitude.strip()
if lValue:
lRegEx = re.compile(CO_OR... | the_stack_v2_python_sparse | web/site/venues/forms.py | BrassBandResults/bbr4 | train | 5 |
6f5bf1475447565543f34822df10f7e59262fcd2 | [
"super(Worker, self).__init__()\nself.func = func\nself.args = args\nself.kwargs = kwargs",
"try:\n result = self.func(*self.args, **self.kwargs)\n self.result.emit(result)\nexcept:\n import sys\n self.error.emit(sys.exc_info())"
] | <|body_start_0|>
super(Worker, self).__init__()
self.func = func
self.args = args
self.kwargs = kwargs
<|end_body_0|>
<|body_start_1|>
try:
result = self.func(*self.args, **self.kwargs)
self.result.emit(result)
except:
import sys
... | Worker | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Worker:
def __init__(self, func, *args, **kwargs):
"""Execute a function call on a different QThread :param func: The function object to call :param args: arguments to pass to the function :param kwargs: kwargs to pass to the function"""
<|body_0|>
def run(self):
"""... | stack_v2_sparse_classes_10k_train_006464 | 1,096 | permissive | [
{
"docstring": "Execute a function call on a different QThread :param func: The function object to call :param args: arguments to pass to the function :param kwargs: kwargs to pass to the function",
"name": "__init__",
"signature": "def __init__(self, func, *args, **kwargs)"
},
{
"docstring": "I... | 2 | stack_v2_sparse_classes_30k_train_000041 | Implement the Python class `Worker` described below.
Class description:
Implement the Worker class.
Method signatures and docstrings:
- def __init__(self, func, *args, **kwargs): Execute a function call on a different QThread :param func: The function object to call :param args: arguments to pass to the function :par... | Implement the Python class `Worker` described below.
Class description:
Implement the Worker class.
Method signatures and docstrings:
- def __init__(self, func, *args, **kwargs): Execute a function call on a different QThread :param func: The function object to call :param args: arguments to pass to the function :par... | 4aa8c64a6f65629207e40df9963232473a24c9f6 | <|skeleton|>
class Worker:
def __init__(self, func, *args, **kwargs):
"""Execute a function call on a different QThread :param func: The function object to call :param args: arguments to pass to the function :param kwargs: kwargs to pass to the function"""
<|body_0|>
def run(self):
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Worker:
def __init__(self, func, *args, **kwargs):
"""Execute a function call on a different QThread :param func: The function object to call :param args: arguments to pass to the function :param kwargs: kwargs to pass to the function"""
super(Worker, self).__init__()
self.func = func
... | the_stack_v2_python_sparse | glue/utils/qt/threading.py | astrofrog/glue | train | 3 | |
9f88d859633b506dc00d9689f06b08a9846b075d | [
"self.author = Author.objects.create(name='Test Name', email='testemail@email.com', address='Test address', bio='Test bio')\nself.publisher = publisher = Publisher.objects.create(name='Test Name', address='Test address', email='testemail@email.com', publisher_url='http://testpublisherurl.com')\nself.book = Book.obj... | <|body_start_0|>
self.author = Author.objects.create(name='Test Name', email='testemail@email.com', address='Test address', bio='Test bio')
self.publisher = publisher = Publisher.objects.create(name='Test Name', address='Test address', email='testemail@email.com', publisher_url='http://testpublisherurl.... | Test casees for the Book model | BookTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookTestCase:
"""Test casees for the Book model"""
def setUp(self):
"""Set up data to be used in test cases"""
<|body_0|>
def test_model_fields_with_correct_values(self):
"""Test the model fields with correct values."""
<|body_1|>
def test_model_fiel... | stack_v2_sparse_classes_10k_train_006465 | 12,307 | permissive | [
{
"docstring": "Set up data to be used in test cases",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test the model fields with correct values.",
"name": "test_model_fields_with_correct_values",
"signature": "def test_model_fields_with_correct_values(self)"
},
{
... | 6 | stack_v2_sparse_classes_30k_train_000342 | Implement the Python class `BookTestCase` described below.
Class description:
Test casees for the Book model
Method signatures and docstrings:
- def setUp(self): Set up data to be used in test cases
- def test_model_fields_with_correct_values(self): Test the model fields with correct values.
- def test_model_fields_w... | Implement the Python class `BookTestCase` described below.
Class description:
Test casees for the Book model
Method signatures and docstrings:
- def setUp(self): Set up data to be used in test cases
- def test_model_fields_with_correct_values(self): Test the model fields with correct values.
- def test_model_fields_w... | a364e9997c1c91b09f5db8a004deb4df305fa8cf | <|skeleton|>
class BookTestCase:
"""Test casees for the Book model"""
def setUp(self):
"""Set up data to be used in test cases"""
<|body_0|>
def test_model_fields_with_correct_values(self):
"""Test the model fields with correct values."""
<|body_1|>
def test_model_fiel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BookTestCase:
"""Test casees for the Book model"""
def setUp(self):
"""Set up data to be used in test cases"""
self.author = Author.objects.create(name='Test Name', email='testemail@email.com', address='Test address', bio='Test bio')
self.publisher = publisher = Publisher.objects.... | the_stack_v2_python_sparse | libStash/books/tests.py | Dev-Rem/libStash | train | 0 |
407a5cc2239767789366aac65dc362cc9f6001bf | [
"self.current_usage_gib = current_usage_gib\nself.feature_name = feature_name\nself.num_vm = num_vm",
"if dictionary is None:\n return None\ncurrent_usage_gib = dictionary.get('currentUsageGiB')\nfeature_name = dictionary.get('featureName')\nnum_vm = dictionary.get('numVm')\nreturn cls(current_usage_gib, featu... | <|body_start_0|>
self.current_usage_gib = current_usage_gib
self.feature_name = feature_name
self.num_vm = num_vm
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
current_usage_gib = dictionary.get('currentUsageGiB')
feature_name = dictionar... | Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned. | FeatureUsage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, fea... | stack_v2_sparse_classes_10k_train_006466 | 1,804 | permissive | [
{
"docstring": "Constructor for the FeatureUsage class",
"name": "__init__",
"signature": "def __init__(self, current_usage_gib=None, feature_name=None, num_vm=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation... | 2 | null | Implement the Python class `FeatureUsage` described below.
Class description:
Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned.
Method signatu... | Implement the Python class `FeatureUsage` described below.
Class description:
Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned.
Method signatu... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, fea... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, feature_name=Non... | the_stack_v2_python_sparse | cohesity_management_sdk/models/feature_usage.py | cohesity/management-sdk-python | train | 24 |
b7344d986efccd29dea4086d92f2298c174e1360 | [
"_1 = ListNode(3)\n_2 = ListNode(2)\n_3 = ListNode(0)\n_4 = ListNode(-4)\n_1.next = _2\n_2.next = _3\n_3.next = _4\n_4.next = _2\ns = Solution()\nself.assertTrue(s.hasCycle(_1))",
"l = [-21, 10, 17, 8, 4, 26, 5, 35, 33, -7, -16, 27, -12, 6, 29, -12, 5, 9, 20, 14, 14, 2, 13, -24, 21, 23, -21, 5]\nn = len(l)\nhead ... | <|body_start_0|>
_1 = ListNode(3)
_2 = ListNode(2)
_3 = ListNode(0)
_4 = ListNode(-4)
_1.next = _2
_2.next = _3
_3.next = _4
_4.next = _2
s = Solution()
self.assertTrue(s.hasCycle(_1))
<|end_body_0|>
<|body_start_1|>
l = [-21, 10, ... | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
def test1(self):
"""head = [3,2,0,-4], pos = 1 为了表示给定链表中的环，我们使用整数 pos 来表示链表尾连接到链表中的位置（索引从 0 开始） 如果 pos 是 -1，则在该链表中没有环"""
<|body_0|>
def test2(self):
"""[-21,10,17,8,4,26,5,35,33,-7,-16,27,-12,6,29,-12,5,9,20,14,14,2,13,-24,21,23,-21,5] -1"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_006467 | 1,711 | no_license | [
{
"docstring": "head = [3,2,0,-4], pos = 1 为了表示给定链表中的环，我们使用整数 pos 来表示链表尾连接到链表中的位置（索引从 0 开始） 如果 pos 是 -1，则在该链表中没有环",
"name": "test1",
"signature": "def test1(self)"
},
{
"docstring": "[-21,10,17,8,4,26,5,35,33,-7,-16,27,-12,6,29,-12,5,9,20,14,14,2,13,-24,21,23,-21,5] -1",
"name": "test2",
... | 2 | stack_v2_sparse_classes_30k_train_001158 | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def test1(self): head = [3,2,0,-4], pos = 1 为了表示给定链表中的环，我们使用整数 pos 来表示链表尾连接到链表中的位置（索引从 0 开始） 如果 pos 是 -1，则在该链表中没有环
- def test2(self): [-21,10,17,8,4,26,5,35,33,-7,-16,27,-12,6,29,-12,5,9... | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def test1(self): head = [3,2,0,-4], pos = 1 为了表示给定链表中的环，我们使用整数 pos 来表示链表尾连接到链表中的位置（索引从 0 开始） 如果 pos 是 -1，则在该链表中没有环
- def test2(self): [-21,10,17,8,4,26,5,35,33,-7,-16,27,-12,6,29,-12,5,9... | 248b620791611001ebb471dcf8284437264b2f20 | <|skeleton|>
class Test:
def test1(self):
"""head = [3,2,0,-4], pos = 1 为了表示给定链表中的环，我们使用整数 pos 来表示链表尾连接到链表中的位置（索引从 0 开始） 如果 pos 是 -1，则在该链表中没有环"""
<|body_0|>
def test2(self):
"""[-21,10,17,8,4,26,5,35,33,-7,-16,27,-12,6,29,-12,5,9,20,14,14,2,13,-24,21,23,-21,5] -1"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test:
def test1(self):
"""head = [3,2,0,-4], pos = 1 为了表示给定链表中的环，我们使用整数 pos 来表示链表尾连接到链表中的位置（索引从 0 开始） 如果 pos 是 -1，则在该链表中没有环"""
_1 = ListNode(3)
_2 = ListNode(2)
_3 = ListNode(0)
_4 = ListNode(-4)
_1.next = _2
_2.next = _3
_3.next = _4
_4.... | the_stack_v2_python_sparse | 141_linked_list_cycle/_2.py | chxj1992/leetcode-exercise | train | 0 | |
892cbc07a1524f47caaf9eddeb1e1485bb79c915 | [
"data = form.cleaned_data\nself.success_url = reverse('tokens', kwargs={'level': int(data['level']), 'semester': int(data['semester']), 'course': int(data['course'].id)})\nreturn super().form_valid(form)",
"context = super().get_context_data(**kwargs)\ncontext['title_text'] = 'Choose Course To View The Tokens'\nc... | <|body_start_0|>
data = form.cleaned_data
self.success_url = reverse('tokens', kwargs={'level': int(data['level']), 'semester': int(data['semester']), 'course': int(data['course'].id)})
return super().form_valid(form)
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(**... | View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid. | ShowTokensView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShowTokensView:
"""View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|body_0|>
def get_c... | stack_v2_sparse_classes_10k_train_006468 | 29,759 | no_license | [
{
"docstring": "Compute the success URL and call super.form_valid()",
"name": "form_valid",
"signature": "def form_valid(self, form)"
},
{
"docstring": "Return the data used in the templates rendering.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
... | 2 | stack_v2_sparse_classes_30k_train_004547 | Implement the Python class `ShowTokensView` described below.
Class description:
View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the success URL and cal... | Implement the Python class `ShowTokensView` described below.
Class description:
View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the success URL and cal... | 06bc577d01d3dbf6c425e03dcb903977a38e377c | <|skeleton|>
class ShowTokensView:
"""View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|body_0|>
def get_c... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ShowTokensView:
"""View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
data = form.cleaned_data
self.... | the_stack_v2_python_sparse | cbt/views.py | Festusali/CBTest | train | 6 |
2042473ac58e6837d57ab386b9a24b3cc0020c86 | [
"self.reporting_enabled = reporting_enabled\nself.collector_ip = collector_ip\nself.collector_port = collector_port",
"if dictionary is None:\n return None\nreporting_enabled = dictionary.get('reportingEnabled')\ncollector_ip = dictionary.get('collectorIp')\ncollector_port = dictionary.get('collectorPort')\nre... | <|body_start_0|>
self.reporting_enabled = reporting_enabled
self.collector_ip = collector_ip
self.collector_port = collector_port
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
reporting_enabled = dictionary.get('reportingEnabled')
collect... | Implementation of the 'updateNetworkNetflowSettings' model. TODO: type model description here. Attributes: reporting_enabled (bool): Boolean indicating whether NetFlow traffic reporting is enabled (true) or disabled (false). collector_ip (string): The IPv4 address of the NetFlow collector. collector_port (int): The por... | UpdateNetworkNetflowSettingsModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkNetflowSettingsModel:
"""Implementation of the 'updateNetworkNetflowSettings' model. TODO: type model description here. Attributes: reporting_enabled (bool): Boolean indicating whether NetFlow traffic reporting is enabled (true) or disabled (false). collector_ip (string): The IPv4 ad... | stack_v2_sparse_classes_10k_train_006469 | 2,229 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkNetflowSettingsModel class",
"name": "__init__",
"signature": "def __init__(self, reporting_enabled=None, collector_ip=None, collector_port=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary)... | 2 | null | Implement the Python class `UpdateNetworkNetflowSettingsModel` described below.
Class description:
Implementation of the 'updateNetworkNetflowSettings' model. TODO: type model description here. Attributes: reporting_enabled (bool): Boolean indicating whether NetFlow traffic reporting is enabled (true) or disabled (fal... | Implement the Python class `UpdateNetworkNetflowSettingsModel` described below.
Class description:
Implementation of the 'updateNetworkNetflowSettings' model. TODO: type model description here. Attributes: reporting_enabled (bool): Boolean indicating whether NetFlow traffic reporting is enabled (true) or disabled (fal... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkNetflowSettingsModel:
"""Implementation of the 'updateNetworkNetflowSettings' model. TODO: type model description here. Attributes: reporting_enabled (bool): Boolean indicating whether NetFlow traffic reporting is enabled (true) or disabled (false). collector_ip (string): The IPv4 ad... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateNetworkNetflowSettingsModel:
"""Implementation of the 'updateNetworkNetflowSettings' model. TODO: type model description here. Attributes: reporting_enabled (bool): Boolean indicating whether NetFlow traffic reporting is enabled (true) or disabled (false). collector_ip (string): The IPv4 address of the ... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_netflow_settings_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
f13f51ae6ca9e5819d9a91a07a4e207f260340ec | [
"question_text = json_dict['question']\ntable_rows = json_dict['table'].split('\\n')\ninstance = self._dataset_reader.text_to_instance(question_text, table_rows)\nreturn instance",
"instance = self._json_to_instance(inputs)\nindex_to_rule = [production_rule_field.rule for production_rule_field in instance.fields[... | <|body_start_0|>
question_text = json_dict['question']
table_rows = json_dict['table'].split('\n')
instance = self._dataset_reader.text_to_instance(question_text, table_rows)
return instance
<|end_body_0|>
<|body_start_1|>
instance = self._json_to_instance(inputs)
index_... | Wrapper for the :class:`~allennlp.models.encoder_decoders.wikitables_semantic_parser.WikiTablesSemanticParser` model. | WikiTablesParserPredictor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WikiTablesParserPredictor:
"""Wrapper for the :class:`~allennlp.models.encoder_decoders.wikitables_semantic_parser.WikiTablesSemanticParser` model."""
def _json_to_instance(self, json_dict: JsonDict) -> Instance:
"""Expects JSON that looks like ``{"question": "...", "table": "..."}``... | stack_v2_sparse_classes_10k_train_006470 | 3,591 | permissive | [
{
"docstring": "Expects JSON that looks like ``{\"question\": \"...\", \"table\": \"...\"}``.",
"name": "_json_to_instance",
"signature": "def _json_to_instance(self, json_dict: JsonDict) -> Instance"
},
{
"docstring": "We need to override this because of the interactive beam search aspects.",
... | 2 | stack_v2_sparse_classes_30k_train_000091 | Implement the Python class `WikiTablesParserPredictor` described below.
Class description:
Wrapper for the :class:`~allennlp.models.encoder_decoders.wikitables_semantic_parser.WikiTablesSemanticParser` model.
Method signatures and docstrings:
- def _json_to_instance(self, json_dict: JsonDict) -> Instance: Expects JSO... | Implement the Python class `WikiTablesParserPredictor` described below.
Class description:
Wrapper for the :class:`~allennlp.models.encoder_decoders.wikitables_semantic_parser.WikiTablesSemanticParser` model.
Method signatures and docstrings:
- def _json_to_instance(self, json_dict: JsonDict) -> Instance: Expects JSO... | c863900e3e1fe7be540b9a0632a7a032491fc3ab | <|skeleton|>
class WikiTablesParserPredictor:
"""Wrapper for the :class:`~allennlp.models.encoder_decoders.wikitables_semantic_parser.WikiTablesSemanticParser` model."""
def _json_to_instance(self, json_dict: JsonDict) -> Instance:
"""Expects JSON that looks like ``{"question": "...", "table": "..."}``... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WikiTablesParserPredictor:
"""Wrapper for the :class:`~allennlp.models.encoder_decoders.wikitables_semantic_parser.WikiTablesSemanticParser` model."""
def _json_to_instance(self, json_dict: JsonDict) -> Instance:
"""Expects JSON that looks like ``{"question": "...", "table": "..."}``."""
... | the_stack_v2_python_sparse | allennlp/predictors/wikitables_parser.py | Whu-wxy/allennlp | train | 6 |
ed0e0fd89f5f7d5a3b77397969eae0978e64e2ea | [
"self.pf = kwargs.copy()\nself.grid = grid\nif type(self.pf['source_type']) is not list:\n self.pf['source_type'] = [self.pf['source_type']]\nself.Ns = len(self.pf['source_type'])\nself.all_sources = self.src = self.initialize_sources()",
"sources = []\nfor i in range(self.Ns):\n sf = self.pf.copy()\n if... | <|body_start_0|>
self.pf = kwargs.copy()
self.grid = grid
if type(self.pf['source_type']) is not list:
self.pf['source_type'] = [self.pf['source_type']]
self.Ns = len(self.pf['source_type'])
self.all_sources = self.src = self.initialize_sources()
<|end_body_0|>
<|bod... | Class for stitching together several radiation sources. | Composite | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Composite:
"""Class for stitching together several radiation sources."""
def __init__(self, grid=None, **kwargs):
"""Initialize composite radiation source object. Parameters ---------- grid : ares.static.Grid.Grid instance"""
<|body_0|>
def initialize_sources(self):
... | stack_v2_sparse_classes_10k_train_006471 | 2,207 | permissive | [
{
"docstring": "Initialize composite radiation source object. Parameters ---------- grid : ares.static.Grid.Grid instance",
"name": "__init__",
"signature": "def __init__(self, grid=None, **kwargs)"
},
{
"docstring": "Construct list of RadiationSource class instances.",
"name": "initialize_s... | 2 | null | Implement the Python class `Composite` described below.
Class description:
Class for stitching together several radiation sources.
Method signatures and docstrings:
- def __init__(self, grid=None, **kwargs): Initialize composite radiation source object. Parameters ---------- grid : ares.static.Grid.Grid instance
- de... | Implement the Python class `Composite` described below.
Class description:
Class for stitching together several radiation sources.
Method signatures and docstrings:
- def __init__(self, grid=None, **kwargs): Initialize composite radiation source object. Parameters ---------- grid : ares.static.Grid.Grid instance
- de... | f323300b56ae61fab56eda1e5179cfc991eaa74f | <|skeleton|>
class Composite:
"""Class for stitching together several radiation sources."""
def __init__(self, grid=None, **kwargs):
"""Initialize composite radiation source object. Parameters ---------- grid : ares.static.Grid.Grid instance"""
<|body_0|>
def initialize_sources(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Composite:
"""Class for stitching together several radiation sources."""
def __init__(self, grid=None, **kwargs):
"""Initialize composite radiation source object. Parameters ---------- grid : ares.static.Grid.Grid instance"""
self.pf = kwargs.copy()
self.grid = grid
if typ... | the_stack_v2_python_sparse | ares/sources/Composite.py | mirochaj/ares | train | 16 |
2f8dfa2dbce137eb9548ccb02aa6a1acf5836866 | [
"self.left_top_point = ShapePoint(start_end_points[0])\nself.right_top_point = ShapePoint(start_end_points[1])\nself.bins = bins\nself.count = count\nstep = abs((self.right_top_point[0] - self.left_top_point[0]) / count)\nx_start_point = self.left_top_point[0]\nx_end_point = x_start_point + step\ny_point = self.lef... | <|body_start_0|>
self.left_top_point = ShapePoint(start_end_points[0])
self.right_top_point = ShapePoint(start_end_points[1])
self.bins = bins
self.count = count
step = abs((self.right_top_point[0] - self.left_top_point[0]) / count)
x_start_point = self.left_top_point[0]
... | Funnels | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Funnels:
def __init__(self, start_end_points: Tuple[tuple, tuple], funnel: Funnel, count: int, bins: Union[int, float], annot: bool=False, *args, **kwargs):
"""Object-constructor for the funnels. Inside init, you could pass all needed variables that will be passed to the Funnel init as w... | stack_v2_sparse_classes_10k_train_006472 | 3,894 | no_license | [
{
"docstring": "Object-constructor for the funnels. Inside init, you could pass all needed variables that will be passed to the Funnel init as well. Args: start_end_points (Tuple[tuple, tuple]): Left top and right top points. ((x1,y1), (x2,y2)). funnel (Funnel): Class for the funnel building. Must be inherited ... | 2 | stack_v2_sparse_classes_30k_train_005307 | Implement the Python class `Funnels` described below.
Class description:
Implement the Funnels class.
Method signatures and docstrings:
- def __init__(self, start_end_points: Tuple[tuple, tuple], funnel: Funnel, count: int, bins: Union[int, float], annot: bool=False, *args, **kwargs): Object-constructor for the funne... | Implement the Python class `Funnels` described below.
Class description:
Implement the Funnels class.
Method signatures and docstrings:
- def __init__(self, start_end_points: Tuple[tuple, tuple], funnel: Funnel, count: int, bins: Union[int, float], annot: bool=False, *args, **kwargs): Object-constructor for the funne... | 290bf56ef888283a0225939ed8b1f87445e506d0 | <|skeleton|>
class Funnels:
def __init__(self, start_end_points: Tuple[tuple, tuple], funnel: Funnel, count: int, bins: Union[int, float], annot: bool=False, *args, **kwargs):
"""Object-constructor for the funnels. Inside init, you could pass all needed variables that will be passed to the Funnel init as w... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Funnels:
def __init__(self, start_end_points: Tuple[tuple, tuple], funnel: Funnel, count: int, bins: Union[int, float], annot: bool=False, *args, **kwargs):
"""Object-constructor for the funnels. Inside init, you could pass all needed variables that will be passed to the Funnel init as well. Args: sta... | the_stack_v2_python_sparse | classes/funnels.py | mohovkm/habr_manim | train | 0 | |
f275cb47faca3b046385f94c356da4ad879ec7ac | [
"self.main_window = QtGui.QWidget()\nself.gui = Ui_StopwatchGui()\nself.gui.setupUi(self.main_window)\nself.gui.start_stop_button.clicked.connect(self.start_stop)\nself.stop_event = Event()\nself.stop_event.set()\nself.main_window.show()",
"if self.stop_event.is_set():\n self.stop_event.clear()\n self.timer... | <|body_start_0|>
self.main_window = QtGui.QWidget()
self.gui = Ui_StopwatchGui()
self.gui.setupUi(self.main_window)
self.gui.start_stop_button.clicked.connect(self.start_stop)
self.stop_event = Event()
self.stop_event.set()
self.main_window.show()
<|end_body_0|>
... | Application class to instantiate and control a StopwatchGui. | StopwatchApp | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
<|body_0|>
def start_stop(self):
"""Start the stopwatch if it is not running; stop it if it is running."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_006473 | 2,727 | no_license | [
{
"docstring": "Initialize and show the gui.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Start the stopwatch if it is not running; stop it if it is running.",
"name": "start_stop",
"signature": "def start_stop(self)"
},
{
"docstring": "Runs a stopwa... | 3 | stack_v2_sparse_classes_30k_test_000123 | Implement the Python class `StopwatchApp` described below.
Class description:
Application class to instantiate and control a StopwatchGui.
Method signatures and docstrings:
- def __init__(self): Initialize and show the gui.
- def start_stop(self): Start the stopwatch if it is not running; stop it if it is running.
- ... | Implement the Python class `StopwatchApp` described below.
Class description:
Application class to instantiate and control a StopwatchGui.
Method signatures and docstrings:
- def __init__(self): Initialize and show the gui.
- def start_stop(self): Start the stopwatch if it is not running; stop it if it is running.
- ... | e1ad9c8f3e09aec3ee72821bd8374c957f047589 | <|skeleton|>
class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
<|body_0|>
def start_stop(self):
"""Start the stopwatch if it is not running; stop it if it is running."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
self.main_window = QtGui.QWidget()
self.gui = Ui_StopwatchGui()
self.gui.setupUi(self.main_window)
self.gui.start_stop_button.cli... | the_stack_v2_python_sparse | DailyLabs/Lsn35/StopwatchApp.py | NathanRuprecht/CS210_IntroToProgramming | train | 0 |
760d5168f4a32fc286485913717ee250692e0ba4 | [
"log = ResultLog.ResultLog()\ntry:\n br = webdriver.Firefox()\nexcept:\n log.info('浏览器初始化失败了')\nbr.get('http://www.xebest.com:8000')\nreturn br",
"log = ResultLog.ResultLog()\ntry:\n br = webdriver.Firefox()\nexcept:\n log.info('浏览器初始化失败了')\nbr.get('https://user.xebest.com:8443/loginAction!init.action... | <|body_start_0|>
log = ResultLog.ResultLog()
try:
br = webdriver.Firefox()
except:
log.info('浏览器初始化失败了')
br.get('http://www.xebest.com:8000')
return br
<|end_body_0|>
<|body_start_1|>
log = ResultLog.ResultLog()
try:
br = webdr... | Browser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Browser:
def init_browser(self):
"""该函数主要是初始化浏览器对象并返回一个webdriver对象"""
<|body_0|>
def init_browserByCustomerCenter(self):
"""该函数主要是初始化浏览器对象并返回一个webdriver对象"""
<|body_1|>
def init_browserByRegister(self):
"""该函数主要是初始化浏览器对象并返回一个webdriver对象"""
... | stack_v2_sparse_classes_10k_train_006474 | 1,205 | no_license | [
{
"docstring": "该函数主要是初始化浏览器对象并返回一个webdriver对象",
"name": "init_browser",
"signature": "def init_browser(self)"
},
{
"docstring": "该函数主要是初始化浏览器对象并返回一个webdriver对象",
"name": "init_browserByCustomerCenter",
"signature": "def init_browserByCustomerCenter(self)"
},
{
"docstring": "该函数主... | 3 | stack_v2_sparse_classes_30k_train_005548 | Implement the Python class `Browser` described below.
Class description:
Implement the Browser class.
Method signatures and docstrings:
- def init_browser(self): 该函数主要是初始化浏览器对象并返回一个webdriver对象
- def init_browserByCustomerCenter(self): 该函数主要是初始化浏览器对象并返回一个webdriver对象
- def init_browserByRegister(self): 该函数主要是初始化浏览器对象并返... | Implement the Python class `Browser` described below.
Class description:
Implement the Browser class.
Method signatures and docstrings:
- def init_browser(self): 该函数主要是初始化浏览器对象并返回一个webdriver对象
- def init_browserByCustomerCenter(self): 该函数主要是初始化浏览器对象并返回一个webdriver对象
- def init_browserByRegister(self): 该函数主要是初始化浏览器对象并返... | 4dd065806f20bfdec885fa2b40f2c22e5a8d4f15 | <|skeleton|>
class Browser:
def init_browser(self):
"""该函数主要是初始化浏览器对象并返回一个webdriver对象"""
<|body_0|>
def init_browserByCustomerCenter(self):
"""该函数主要是初始化浏览器对象并返回一个webdriver对象"""
<|body_1|>
def init_browserByRegister(self):
"""该函数主要是初始化浏览器对象并返回一个webdriver对象"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Browser:
def init_browser(self):
"""该函数主要是初始化浏览器对象并返回一个webdriver对象"""
log = ResultLog.ResultLog()
try:
br = webdriver.Firefox()
except:
log.info('浏览器初始化失败了')
br.get('http://www.xebest.com:8000')
return br
def init_browserByCustomerCe... | the_stack_v2_python_sparse | Action/Browser.py | Hardworking-tester/HuaYing | train | 0 | |
fda012309a0db17998c7739733f7afee064c0767 | [
"updated = 0\nnow = datetime.datetime.now()\nfor t in queryset:\n t.last_run = now - datetime.timedelta(seconds=t.run_every)\n t.save()\n updated += 1\nif updated == 1:\n message = '1 task has been rescheduled'\nelse:\n message = '%d tasks have been rescheduled' % updated\nself.message_user(request, ... | <|body_start_0|>
updated = 0
now = datetime.datetime.now()
for t in queryset:
t.last_run = now - datetime.timedelta(seconds=t.run_every)
t.save()
updated += 1
if updated == 1:
message = '1 task has been rescheduled'
else:
... | Schedule admin | ScheduleAdmin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScheduleAdmin:
"""Schedule admin"""
def run_now(self, request, queryset):
"""Reschedule selected tasks"""
<|body_0|>
def save_model(self, request, obj, form, change):
"""Handle timeout"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
updated = 0
... | stack_v2_sparse_classes_10k_train_006475 | 2,711 | permissive | [
{
"docstring": "Reschedule selected tasks",
"name": "run_now",
"signature": "def run_now(self, request, queryset)"
},
{
"docstring": "Handle timeout",
"name": "save_model",
"signature": "def save_model(self, request, obj, form, change)"
}
] | 2 | null | Implement the Python class `ScheduleAdmin` described below.
Class description:
Schedule admin
Method signatures and docstrings:
- def run_now(self, request, queryset): Reschedule selected tasks
- def save_model(self, request, obj, form, change): Handle timeout | Implement the Python class `ScheduleAdmin` described below.
Class description:
Schedule admin
Method signatures and docstrings:
- def run_now(self, request, queryset): Reschedule selected tasks
- def save_model(self, request, obj, form, change): Handle timeout
<|skeleton|>
class ScheduleAdmin:
"""Schedule admin"... | d43c14f02266b5a4e1fca2db3296cef612d63374 | <|skeleton|>
class ScheduleAdmin:
"""Schedule admin"""
def run_now(self, request, queryset):
"""Reschedule selected tasks"""
<|body_0|>
def save_model(self, request, obj, form, change):
"""Handle timeout"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScheduleAdmin:
"""Schedule admin"""
def run_now(self, request, queryset):
"""Reschedule selected tasks"""
updated = 0
now = datetime.datetime.now()
for t in queryset:
t.last_run = now - datetime.timedelta(seconds=t.run_every)
t.save()
up... | the_stack_v2_python_sparse | services/web/apps/main/schedule/views.py | fantmas2/noc | train | 0 |
887cc014f6ea3f57abd3d0350894f93c11a21a13 | [
"args = self.args\nif args and (not args[0] in [\"'\", ',', ':']):\n args = ' %s' % args.strip()\nself.args = args",
"if not self.args:\n msg = 'What do you want to do?'\n self.caller.msg(msg)\nelse:\n msg = f'{self.caller.name}{self.args}'\n self.caller.location.msg_contents(text=(msg, {'type': 'p... | <|body_start_0|>
args = self.args
if args and (not args[0] in ["'", ',', ':']):
args = ' %s' % args.strip()
self.args = args
<|end_body_0|>
<|body_start_1|>
if not self.args:
msg = 'What do you want to do?'
self.caller.msg(msg)
else:
... | strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name. | CmdPose | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CmdPose:
"""strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name."""
def parse(self):
""... | stack_v2_sparse_classes_10k_train_006476 | 22,494 | permissive | [
{
"docstring": "Custom parse the cases where the emote starts with some special letter, such as 's, at which we don't want to separate the caller's name and the emote with a space.",
"name": "parse",
"signature": "def parse(self)"
},
{
"docstring": "Hook function",
"name": "func",
"signa... | 2 | null | Implement the Python class `CmdPose` described below.
Class description:
strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your na... | Implement the Python class `CmdPose` described below.
Class description:
strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your na... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class CmdPose:
"""strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name."""
def parse(self):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CmdPose:
"""strike a pose Usage: pose <pose text> pose's <pose text> Example: pose is standing by the wall, smiling. -> others will see: Tom is standing by the wall, smiling. Describe an action being taken. The pose text will automatically begin with your name."""
def parse(self):
"""Custom parse... | the_stack_v2_python_sparse | evennia/commands/default/general.py | evennia/evennia | train | 1,781 |
6fc43cc5de2f4eb3942f4a340d9281a9dffb19cf | [
"levels = []\nif not root:\n return levels\n\ndef helper(node, level):\n if len(levels) == level:\n levels.append([])\n levels[level].append(node.val)\n if node.left:\n helper(node.left, level + 1)\n if node.right:\n helper(node.right, level + 1)\nhelper(root, 0)\nreturn levels[:... | <|body_start_0|>
levels = []
if not root:
return levels
def helper(node, level):
if len(levels) == level:
levels.append([])
levels[level].append(node.val)
if node.left:
helper(node.left, level + 1)
if no... | Tree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tree:
def traversal_(self, root: 'TreeNode') -> List[int]:
"""Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def traversal(self, root: 'TreeNode') -> List[int]:
"""Approach: Iterative/ BFS Time Complexity: O(N) Sp... | stack_v2_sparse_classes_10k_train_006477 | 1,516 | no_license | [
{
"docstring": "Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:",
"name": "traversal_",
"signature": "def traversal_(self, root: 'TreeNode') -> List[int]"
},
{
"docstring": "Approach: Iterative/ BFS Time Complexity: O(N) Space Complexity: O(N) :param root: ... | 2 | null | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def traversal_(self, root: 'TreeNode') -> List[int]: Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def traversal(self, root: 'TreeNode') -> Lis... | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def traversal_(self, root: 'TreeNode') -> List[int]: Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def traversal(self, root: 'TreeNode') -> Lis... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Tree:
def traversal_(self, root: 'TreeNode') -> List[int]:
"""Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def traversal(self, root: 'TreeNode') -> List[int]:
"""Approach: Iterative/ BFS Time Complexity: O(N) Sp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Tree:
def traversal_(self, root: 'TreeNode') -> List[int]:
"""Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
levels = []
if not root:
return levels
def helper(node, level):
if len(levels) == level:
... | the_stack_v2_python_sparse | revisited_2021/tree/bst_level_order_traversal.py | Shiv2157k/leet_code | train | 1 | |
de87a8bccdaaf69f6bc607b4bfd5a44026af09af | [
"self.region = region\nself.proxy_config = Config()\nif proxy != 'NONE':\n self.proxy_config = Config(proxies={'https': proxy})",
"try:\n return boto3.client(service, region_name=self.region, config=self.proxy_config)\nexcept ClientError as e:\n fail('AWS %s service failed with exception: %s' % (service,... | <|body_start_0|>
self.region = region
self.proxy_config = Config()
if proxy != 'NONE':
self.proxy_config = Config(proxies={'https': proxy})
<|end_body_0|>
<|body_start_1|>
try:
return boto3.client(service, region_name=self.region, config=self.proxy_config)
... | Boto3 configuration object. | Boto3ClientFactory | [
"Python-2.0",
"GPL-1.0-or-later",
"MPL-2.0",
"MIT",
"LicenseRef-scancode-python-cwi",
"BSD-3-Clause",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"MIT-0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Boto3ClientFactory:
"""Boto3 configuration object."""
def __init__(self, region, proxy='NONE'):
"""Initialize the object."""
<|body_0|>
def get_client(self, service):
"""Initialize the boto3 client for a given service. :param service: boto3 service. :return: the ... | stack_v2_sparse_classes_10k_train_006478 | 14,826 | permissive | [
{
"docstring": "Initialize the object.",
"name": "__init__",
"signature": "def __init__(self, region, proxy='NONE')"
},
{
"docstring": "Initialize the boto3 client for a given service. :param service: boto3 service. :return: the boto3 client",
"name": "get_client",
"signature": "def get_... | 2 | stack_v2_sparse_classes_30k_train_002416 | Implement the Python class `Boto3ClientFactory` described below.
Class description:
Boto3 configuration object.
Method signatures and docstrings:
- def __init__(self, region, proxy='NONE'): Initialize the object.
- def get_client(self, service): Initialize the boto3 client for a given service. :param service: boto3 s... | Implement the Python class `Boto3ClientFactory` described below.
Class description:
Boto3 configuration object.
Method signatures and docstrings:
- def __init__(self, region, proxy='NONE'): Initialize the object.
- def get_client(self, service): Initialize the boto3 client for a given service. :param service: boto3 s... | a213978a09ea7fc80855bf55c539861ea95259f9 | <|skeleton|>
class Boto3ClientFactory:
"""Boto3 configuration object."""
def __init__(self, region, proxy='NONE'):
"""Initialize the object."""
<|body_0|>
def get_client(self, service):
"""Initialize the boto3 client for a given service. :param service: boto3 service. :return: the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Boto3ClientFactory:
"""Boto3 configuration object."""
def __init__(self, region, proxy='NONE'):
"""Initialize the object."""
self.region = region
self.proxy_config = Config()
if proxy != 'NONE':
self.proxy_config = Config(proxies={'https': proxy})
def get_... | the_stack_v2_python_sparse | awsbatch-cli/src/awsbatch/common.py | aws/aws-parallelcluster | train | 520 |
ec77e5f2083daba0c58efe8a6e8f2644aeabb214 | [
"super().__init__(name)\nself.__name__ = name\nself.gen = gen",
"rval = []\nfor tup, param in zip(tups, params):\n if not isinstance(tup, AbstractTuple):\n raise MyiaTypeError(f'Expected AbstractTuple, not {tup}')\n rval.append([g.apply(P.tuple_getitem, param, i) for i, elem in enumerate(tup.elements... | <|body_start_0|>
super().__init__(name)
self.__name__ = name
self.gen = gen
<|end_body_0|>
<|body_start_1|>
rval = []
for tup, param in zip(tups, params):
if not isinstance(tup, AbstractTuple):
raise MyiaTypeError(f'Expected AbstractTuple, not {tup}')... | Parametrizable MetaGraph to combine or extract tuples. | TupleReorganizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TupleReorganizer:
"""Parametrizable MetaGraph to combine or extract tuples."""
def __init__(self, name, gen):
"""Initialize a TupleReorganizer."""
<|body_0|>
def map_tuples(self, g, params, tups):
"""Map each element of each tuple to a getitem on the parameter.""... | stack_v2_sparse_classes_10k_train_006479 | 2,705 | permissive | [
{
"docstring": "Initialize a TupleReorganizer.",
"name": "__init__",
"signature": "def __init__(self, name, gen)"
},
{
"docstring": "Map each element of each tuple to a getitem on the parameter.",
"name": "map_tuples",
"signature": "def map_tuples(self, g, params, tups)"
},
{
"do... | 3 | null | Implement the Python class `TupleReorganizer` described below.
Class description:
Parametrizable MetaGraph to combine or extract tuples.
Method signatures and docstrings:
- def __init__(self, name, gen): Initialize a TupleReorganizer.
- def map_tuples(self, g, params, tups): Map each element of each tuple to a getite... | Implement the Python class `TupleReorganizer` described below.
Class description:
Parametrizable MetaGraph to combine or extract tuples.
Method signatures and docstrings:
- def __init__(self, name, gen): Initialize a TupleReorganizer.
- def map_tuples(self, g, params, tups): Map each element of each tuple to a getite... | d7b12c15453079e1a2c4fdae611c5f741574363d | <|skeleton|>
class TupleReorganizer:
"""Parametrizable MetaGraph to combine or extract tuples."""
def __init__(self, name, gen):
"""Initialize a TupleReorganizer."""
<|body_0|>
def map_tuples(self, g, params, tups):
"""Map each element of each tuple to a getitem on the parameter.""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TupleReorganizer:
"""Parametrizable MetaGraph to combine or extract tuples."""
def __init__(self, name, gen):
"""Initialize a TupleReorganizer."""
super().__init__(name)
self.__name__ = name
self.gen = gen
def map_tuples(self, g, params, tups):
"""Map each ele... | the_stack_v2_python_sparse | myia/operations/ops_tuple.py | breuleux/myia | train | 1 |
bac021f94f2e11735c86c690c60800a8c16a2fd2 | [
"queue = self.messages.Queue(name=queue_ref.RelativeName(), retryConfig=retry_config, rateLimits=rate_limits, appEngineRoutingOverride=app_engine_routing_override)\nrequest = self.messages.CloudtasksProjectsLocationsQueuesCreateRequest(parent=parent_ref.RelativeName(), queue=queue)\nreturn self.queues_service.Creat... | <|body_start_0|>
queue = self.messages.Queue(name=queue_ref.RelativeName(), retryConfig=retry_config, rateLimits=rate_limits, appEngineRoutingOverride=app_engine_routing_override)
request = self.messages.CloudtasksProjectsLocationsQueuesCreateRequest(parent=parent_ref.RelativeName(), queue=queue)
... | Client for queues service in the Cloud Tasks API. | Queues | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Queues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_routing_override=None):
"""Prepares and sends a Create request for creating a queue."""
<|body_0|>
def Patch(self, queu... | stack_v2_sparse_classes_10k_train_006480 | 9,305 | permissive | [
{
"docstring": "Prepares and sends a Create request for creating a queue.",
"name": "Create",
"signature": "def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_routing_override=None)"
},
{
"docstring": "Prepares and sends a Patch request for modifying a queue.... | 2 | null | Implement the Python class `Queues` described below.
Class description:
Client for queues service in the Cloud Tasks API.
Method signatures and docstrings:
- def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_routing_override=None): Prepares and sends a Create request for creating... | Implement the Python class `Queues` described below.
Class description:
Client for queues service in the Cloud Tasks API.
Method signatures and docstrings:
- def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_routing_override=None): Prepares and sends a Create request for creating... | 85bb264e273568b5a0408f733b403c56373e2508 | <|skeleton|>
class Queues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_routing_override=None):
"""Prepares and sends a Create request for creating a queue."""
<|body_0|>
def Patch(self, queu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Queues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_routing_override=None):
"""Prepares and sends a Create request for creating a queue."""
queue = self.messages.Queue(name=queue_ref.Relati... | the_stack_v2_python_sparse | google-cloud-sdk/lib/googlecloudsdk/api_lib/tasks/queues.py | bopopescu/socialliteapp | train | 0 |
97c6a9ba97285ce1e460158b94b8e7f4e21c6d02 | [
"self.logger = logger\nself.options = options\nif options.checkpoint_file is not None:\n local_ckpt_file = os.path.join(options.checkpoint_dir, options.checkpoint_file)\n if not os.path.exists(local_ckpt_file):\n raise ValueError('Checkpoint file [{}] does not exist!'.format(options.checkpoint_file))\n... | <|body_start_0|>
self.logger = logger
self.options = options
if options.checkpoint_file is not None:
local_ckpt_file = os.path.join(options.checkpoint_dir, options.checkpoint_file)
if not os.path.exists(local_ckpt_file):
raise ValueError('Checkpoint file [... | Class that handles saving and loading checkpoints during training. | CheckpointSaver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckpointSaver:
"""Class that handles saving and loading checkpoints during training."""
def __init__(self, logger: Logger, options: EasyDict, training: str):
"""Initialization function. :param logger :param options"""
<|body_0|>
def check_end_epoch(self, fn: str) -> bo... | stack_v2_sparse_classes_10k_train_006481 | 5,171 | permissive | [
{
"docstring": "Initialization function. :param logger :param options",
"name": "__init__",
"signature": "def __init__(self, logger: Logger, options: EasyDict, training: str)"
},
{
"docstring": "Check if the checkpoint file is the end of one epoch. :param fn: :return:",
"name": "check_end_ep... | 5 | stack_v2_sparse_classes_30k_train_006117 | Implement the Python class `CheckpointSaver` described below.
Class description:
Class that handles saving and loading checkpoints during training.
Method signatures and docstrings:
- def __init__(self, logger: Logger, options: EasyDict, training: str): Initialization function. :param logger :param options
- def chec... | Implement the Python class `CheckpointSaver` described below.
Class description:
Class that handles saving and loading checkpoints during training.
Method signatures and docstrings:
- def __init__(self, logger: Logger, options: EasyDict, training: str): Initialization function. :param logger :param options
- def chec... | ca88df568a6f2143dcb85d22c005fce4562a7523 | <|skeleton|>
class CheckpointSaver:
"""Class that handles saving and loading checkpoints during training."""
def __init__(self, logger: Logger, options: EasyDict, training: str):
"""Initialization function. :param logger :param options"""
<|body_0|>
def check_end_epoch(self, fn: str) -> bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CheckpointSaver:
"""Class that handles saving and loading checkpoints during training."""
def __init__(self, logger: Logger, options: EasyDict, training: str):
"""Initialization function. :param logger :param options"""
self.logger = logger
self.options = options
if option... | the_stack_v2_python_sparse | PointNetBaseline/code/functions/saver.py | zshyang/FieldConvolution | train | 1 |
6a04d4d9f38017243fa2cef2220b0823b713c29f | [
"super(DataViewerWriter, self).__init__(cmd_tlm_data, deployment_name, cosmos_directory)\nself.repeated_names = {}\nself.destination = cosmos_directory + '/config/targets/' + deployment_name.upper() + '/tools/data_viewer/'",
"event_list = []\nfor evr in self.cmd_tlm_data[2]:\n n = evr.get_evr_name()\n if n ... | <|body_start_0|>
super(DataViewerWriter, self).__init__(cmd_tlm_data, deployment_name, cosmos_directory)
self.repeated_names = {}
self.destination = cosmos_directory + '/config/targets/' + deployment_name.upper() + '/tools/data_viewer/'
<|end_body_0|>
<|body_start_1|>
event_list = []
... | This class generates the data viewer definition file in cosmos_directory/config/targets/deployment_name.upper()/tools/data_viewer/ | DataViewerWriter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataViewerWriter:
"""This class generates the data viewer definition file in cosmos_directory/config/targets/deployment_name.upper()/tools/data_viewer/"""
def __init__(self, cmd_tlm_data, deployment_name, cosmos_directory):
"""@param cmd_tlm_data: Tuple containing lists channels [0],... | stack_v2_sparse_classes_10k_train_006482 | 2,935 | permissive | [
{
"docstring": "@param cmd_tlm_data: Tuple containing lists channels [0], commands [1], and events [2] @param deployment_name: name of the COSMOS target @param cosmos_directory: Directory of COSMOS",
"name": "__init__",
"signature": "def __init__(self, cmd_tlm_data, deployment_name, cosmos_directory)"
... | 2 | stack_v2_sparse_classes_30k_test_000197 | Implement the Python class `DataViewerWriter` described below.
Class description:
This class generates the data viewer definition file in cosmos_directory/config/targets/deployment_name.upper()/tools/data_viewer/
Method signatures and docstrings:
- def __init__(self, cmd_tlm_data, deployment_name, cosmos_directory): ... | Implement the Python class `DataViewerWriter` described below.
Class description:
This class generates the data viewer definition file in cosmos_directory/config/targets/deployment_name.upper()/tools/data_viewer/
Method signatures and docstrings:
- def __init__(self, cmd_tlm_data, deployment_name, cosmos_directory): ... | d19cade2140231b4e0879b2f6ab4a62b25792dea | <|skeleton|>
class DataViewerWriter:
"""This class generates the data viewer definition file in cosmos_directory/config/targets/deployment_name.upper()/tools/data_viewer/"""
def __init__(self, cmd_tlm_data, deployment_name, cosmos_directory):
"""@param cmd_tlm_data: Tuple containing lists channels [0],... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataViewerWriter:
"""This class generates the data viewer definition file in cosmos_directory/config/targets/deployment_name.upper()/tools/data_viewer/"""
def __init__(self, cmd_tlm_data, deployment_name, cosmos_directory):
"""@param cmd_tlm_data: Tuple containing lists channels [0], commands [1]... | the_stack_v2_python_sparse | Autocoders/Python/src/fprime_ac/utils/cosmos/writers/DataViewerWriter.py | nodcah/fprime | train | 0 |
8c5d3028a982f74a580479b0a66eaf298f1600fd | [
"self.capacity = capacity\nself.queue = DLL()\nself.mapping = {}",
"if key not in self.mapping:\n return -1\nnode = self.mapping[key]\nself.queue.update(node)\nreturn node.val",
"if key in self.mapping:\n node = self.mapping[key]\n node.val = value\n self.queue.update(node)\n return\nnode = Node(... | <|body_start_0|>
self.capacity = capacity
self.queue = DLL()
self.mapping = {}
<|end_body_0|>
<|body_start_1|>
if key not in self.mapping:
return -1
node = self.mapping[key]
self.queue.update(node)
return node.val
<|end_body_1|>
<|body_start_2|>
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_006483 | 2,822 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: nothing",
"name": "set",
"sig... | 3 | stack_v2_sparse_classes_30k_train_006633 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing
<|skeleton|>
cla... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.queue = DLL()
self.mapping = {}
def get(self, key):
""":rtype: int"""
if key not in self.mapping:
return -1
node = self.mapping[key]
... | the_stack_v2_python_sparse | python_1_to_1000/146_LRU_Cache.py | jakehoare/leetcode | train | 58 | |
c8c853392ee573013a8b6c0d0da6c010fde2b69b | [
"if 'git_uri' not in self.user_params:\n raise ValueError(f'{self.__class__.__name__} instance has no source (no git_uri in user params)')\nreturn source.GitSource(provider='git', uri=self.user_params['git_uri'], provider_params={'git_commit': self.user_params.get('git_ref'), 'git_commit_depth': self.user_params... | <|body_start_0|>
if 'git_uri' not in self.user_params:
raise ValueError(f'{self.__class__.__name__} instance has no source (no git_uri in user params)')
return source.GitSource(provider='git', uri=self.user_params['git_uri'], provider_params={'git_commit': self.user_params.get('git_ref'), 'g... | Task parameters (coming from CLI arguments). | TaskParams | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskParams:
"""Task parameters (coming from CLI arguments)."""
def source(self) -> source.Source:
"""Source for the input files the task will operate on (e.g. a git repo)."""
<|body_0|>
def from_cli_args(cls, args: dict):
"""Create a TaskParams instance from CLI ... | stack_v2_sparse_classes_10k_train_006484 | 4,580 | permissive | [
{
"docstring": "Source for the input files the task will operate on (e.g. a git repo).",
"name": "source",
"signature": "def source(self) -> source.Source"
},
{
"docstring": "Create a TaskParams instance from CLI arguments.",
"name": "from_cli_args",
"signature": "def from_cli_args(cls, ... | 2 | stack_v2_sparse_classes_30k_train_004370 | Implement the Python class `TaskParams` described below.
Class description:
Task parameters (coming from CLI arguments).
Method signatures and docstrings:
- def source(self) -> source.Source: Source for the input files the task will operate on (e.g. a git repo).
- def from_cli_args(cls, args: dict): Create a TaskPara... | Implement the Python class `TaskParams` described below.
Class description:
Task parameters (coming from CLI arguments).
Method signatures and docstrings:
- def source(self) -> source.Source: Source for the input files the task will operate on (e.g. a git repo).
- def from_cli_args(cls, args: dict): Create a TaskPara... | 0ed6e07d848db7090332a18ef8ace3585dd314ac | <|skeleton|>
class TaskParams:
"""Task parameters (coming from CLI arguments)."""
def source(self) -> source.Source:
"""Source for the input files the task will operate on (e.g. a git repo)."""
<|body_0|>
def from_cli_args(cls, args: dict):
"""Create a TaskParams instance from CLI ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TaskParams:
"""Task parameters (coming from CLI arguments)."""
def source(self) -> source.Source:
"""Source for the input files the task will operate on (e.g. a git repo)."""
if 'git_uri' not in self.user_params:
raise ValueError(f'{self.__class__.__name__} instance has no sou... | the_stack_v2_python_sparse | atomic_reactor/tasks/common.py | fr34k8/atomic-reactor | train | 1 |
29a1184fa0a47b1bf31e810232f41e76866cfb1d | [
"if not root:\n return 0\nreturn self.subroutine(root, 0)",
"if not node:\n return depth\nreturn max(self.subroutine(node.left, depth + 1), self.subroutine(node.right, depth + 1))"
] | <|body_start_0|>
if not root:
return 0
return self.subroutine(root, 0)
<|end_body_0|>
<|body_start_1|>
if not node:
return depth
return max(self.subroutine(node.left, depth + 1), self.subroutine(node.right, depth + 1))
<|end_body_1|>
| Leet104 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Leet104:
def max_depth(self, root):
"""Finds the max depth of a binary tree. Args: root -- TreeNode Returns: The max depth of a binary tree."""
<|body_0|>
def subroutine(self, node, depth):
"""Find the max depth of two subtrees of a node. Args: node -- TreeNode max_d... | stack_v2_sparse_classes_10k_train_006485 | 1,033 | no_license | [
{
"docstring": "Finds the max depth of a binary tree. Args: root -- TreeNode Returns: The max depth of a binary tree.",
"name": "max_depth",
"signature": "def max_depth(self, root)"
},
{
"docstring": "Find the max depth of two subtrees of a node. Args: node -- TreeNode max_depth -- keeps track o... | 2 | stack_v2_sparse_classes_30k_train_001280 | Implement the Python class `Leet104` described below.
Class description:
Implement the Leet104 class.
Method signatures and docstrings:
- def max_depth(self, root): Finds the max depth of a binary tree. Args: root -- TreeNode Returns: The max depth of a binary tree.
- def subroutine(self, node, depth): Find the max d... | Implement the Python class `Leet104` described below.
Class description:
Implement the Leet104 class.
Method signatures and docstrings:
- def max_depth(self, root): Finds the max depth of a binary tree. Args: root -- TreeNode Returns: The max depth of a binary tree.
- def subroutine(self, node, depth): Find the max d... | b0cfcfa1eff0101cf8e0e3fb9db55fb83f566f6f | <|skeleton|>
class Leet104:
def max_depth(self, root):
"""Finds the max depth of a binary tree. Args: root -- TreeNode Returns: The max depth of a binary tree."""
<|body_0|>
def subroutine(self, node, depth):
"""Find the max depth of two subtrees of a node. Args: node -- TreeNode max_d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Leet104:
def max_depth(self, root):
"""Finds the max depth of a binary tree. Args: root -- TreeNode Returns: The max depth of a binary tree."""
if not root:
return 0
return self.subroutine(root, 0)
def subroutine(self, node, depth):
"""Find the max depth of two... | the_stack_v2_python_sparse | archive/algorithms-leetcode/leet104.py | riehseun/software-engineering | train | 0 | |
61929cb9652b6dedc88baeb58838ac8b580e44ae | [
"for order in self.browse(cr, uid, ids, context=context):\n if order.ttype == 'other':\n if order.stock_journal_id.need_visit:\n return True\n for line in order.order_line:\n if line.product_id.need_visit:\n return True\nreturn super(exchange_order, self).has_ca... | <|body_start_0|>
for order in self.browse(cr, uid, ids, context=context):
if order.ttype == 'other':
if order.stock_journal_id.need_visit:
return True
for line in order.order_line:
if line.product_id.need_visit:
... | exchange_order | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class exchange_order:
def has_category_manager(self, cr, uid, ids, context=None):
"""Condition Workflow function. @return: boolean"""
<|body_0|>
def action_approve_order(self, cr, uid, ids, context=None):
"""Workflow function Changes order state to approve. @return: True""... | stack_v2_sparse_classes_10k_train_006486 | 6,031 | no_license | [
{
"docstring": "Condition Workflow function. @return: boolean",
"name": "has_category_manager",
"signature": "def has_category_manager(self, cr, uid, ids, context=None)"
},
{
"docstring": "Workflow function Changes order state to approve. @return: True",
"name": "action_approve_order",
"... | 3 | null | Implement the Python class `exchange_order` described below.
Class description:
Implement the exchange_order class.
Method signatures and docstrings:
- def has_category_manager(self, cr, uid, ids, context=None): Condition Workflow function. @return: boolean
- def action_approve_order(self, cr, uid, ids, context=None)... | Implement the Python class `exchange_order` described below.
Class description:
Implement the exchange_order class.
Method signatures and docstrings:
- def has_category_manager(self, cr, uid, ids, context=None): Condition Workflow function. @return: boolean
- def action_approve_order(self, cr, uid, ids, context=None)... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class exchange_order:
def has_category_manager(self, cr, uid, ids, context=None):
"""Condition Workflow function. @return: boolean"""
<|body_0|>
def action_approve_order(self, cr, uid, ids, context=None):
"""Workflow function Changes order state to approve. @return: True""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class exchange_order:
def has_category_manager(self, cr, uid, ids, context=None):
"""Condition Workflow function. @return: boolean"""
for order in self.browse(cr, uid, ids, context=context):
if order.ttype == 'other':
if order.stock_journal_id.need_visit:
... | the_stack_v2_python_sparse | v_7/GDS/shamil_v3/stock_exchange_NISS/stock_exchange.py | musabahmed/baba | train | 0 | |
916bccd256044d2f40648b401b3dd8f97c296758 | [
"self.client_ip = client_ip\nself.node_ip = node_ip\nself.server_ip = server_ip\nself.view_id = view_id\nself.view_name = view_name",
"if dictionary is None:\n return None\nclient_ip = dictionary.get('clientIp')\nnode_ip = dictionary.get('nodeIp')\nserver_ip = dictionary.get('serverIp')\nview_id = dictionary.g... | <|body_start_0|>
self.client_ip = client_ip
self.node_ip = node_ip
self.server_ip = server_ip
self.view_id = view_id
self.view_name = view_name
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
client_ip = dictionary.get('clientIp')
... | Implementation of the 'NfsConnection' model. TODO: type description here. Attributes: client_ip (string): Specifies the Client IP address of the connection. node_ip (string): Specifies a Node IP address where the connection request is received. server_ip (string): Specifies the Server IP address of the connection. This... | NfsConnection | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NfsConnection:
"""Implementation of the 'NfsConnection' model. TODO: type description here. Attributes: client_ip (string): Specifies the Client IP address of the connection. node_ip (string): Specifies a Node IP address where the connection request is received. server_ip (string): Specifies the ... | stack_v2_sparse_classes_10k_train_006487 | 2,341 | permissive | [
{
"docstring": "Constructor for the NfsConnection class",
"name": "__init__",
"signature": "def __init__(self, client_ip=None, node_ip=None, server_ip=None, view_id=None, view_name=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dict... | 2 | stack_v2_sparse_classes_30k_train_000252 | Implement the Python class `NfsConnection` described below.
Class description:
Implementation of the 'NfsConnection' model. TODO: type description here. Attributes: client_ip (string): Specifies the Client IP address of the connection. node_ip (string): Specifies a Node IP address where the connection request is recei... | Implement the Python class `NfsConnection` described below.
Class description:
Implementation of the 'NfsConnection' model. TODO: type description here. Attributes: client_ip (string): Specifies the Client IP address of the connection. node_ip (string): Specifies a Node IP address where the connection request is recei... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class NfsConnection:
"""Implementation of the 'NfsConnection' model. TODO: type description here. Attributes: client_ip (string): Specifies the Client IP address of the connection. node_ip (string): Specifies a Node IP address where the connection request is received. server_ip (string): Specifies the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NfsConnection:
"""Implementation of the 'NfsConnection' model. TODO: type description here. Attributes: client_ip (string): Specifies the Client IP address of the connection. node_ip (string): Specifies a Node IP address where the connection request is received. server_ip (string): Specifies the Server IP add... | the_stack_v2_python_sparse | cohesity_management_sdk/models/nfs_connection.py | cohesity/management-sdk-python | train | 24 |
6d5ed1d2eb359dbfbee3cac333e9e97acd6e0ad6 | [
"if 'colored' in kwargs:\n self.colored = kwargs['colored']\n del kwargs['colored']\nelse:\n self.colored = False\nkwargs['availheight'] = self.LABELHEIGHT - self.BLOCKHEIGHT\nBaseLTOLabel.__init__(self, *args, **kwargs)",
"BaseLTOLabel.drawOn(self, canvas, x, y)\ncanvas.saveState()\ncanvas.setLineWidth(... | <|body_start_0|>
if 'colored' in kwargs:
self.colored = kwargs['colored']
del kwargs['colored']
else:
self.colored = False
kwargs['availheight'] = self.LABELHEIGHT - self.BLOCKHEIGHT
BaseLTOLabel.__init__(self, *args, **kwargs)
<|end_body_0|>
<|body_s... | A class for LTO labels with rectangular blocks around the tape identifier. | VerticalLTOLabel | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VerticalLTOLabel:
"""A class for LTO labels with rectangular blocks around the tape identifier."""
def __init__(self, *args, **kwargs):
"""Initializes the label. colored : boolean to determine if blocks have to be colorized."""
<|body_0|>
def drawOn(self, canvas, x, y):
... | stack_v2_sparse_classes_10k_train_006488 | 7,377 | permissive | [
{
"docstring": "Initializes the label. colored : boolean to determine if blocks have to be colorized.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Draws some blocks around the identifier's characters.",
"name": "drawOn",
"signature": "def dr... | 2 | stack_v2_sparse_classes_30k_train_005412 | Implement the Python class `VerticalLTOLabel` described below.
Class description:
A class for LTO labels with rectangular blocks around the tape identifier.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initializes the label. colored : boolean to determine if blocks have to be colorized.
- ... | Implement the Python class `VerticalLTOLabel` described below.
Class description:
A class for LTO labels with rectangular blocks around the tape identifier.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initializes the label. colored : boolean to determine if blocks have to be colorized.
- ... | c28aa50e2d6d3451b47e114094a86c03c87d4c50 | <|skeleton|>
class VerticalLTOLabel:
"""A class for LTO labels with rectangular blocks around the tape identifier."""
def __init__(self, *args, **kwargs):
"""Initializes the label. colored : boolean to determine if blocks have to be colorized."""
<|body_0|>
def drawOn(self, canvas, x, y):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VerticalLTOLabel:
"""A class for LTO labels with rectangular blocks around the tape identifier."""
def __init__(self, *args, **kwargs):
"""Initializes the label. colored : boolean to determine if blocks have to be colorized."""
if 'colored' in kwargs:
self.colored = kwargs['co... | the_stack_v2_python_sparse | src/reportlab/graphics/barcode/lto.py | MrBitBucket/reportlab-mirror | train | 64 |
8cf82579b9009fbccb5335b99d74f667b681244d | [
"super(TextSubNet, self).__init__()\nif num_layers == 1:\n dropout = 0.0\nself.rnn = nn.LSTM(in_size, hidden_size, num_layers=num_layers, dropout=dropout, bidirectional=bidirectional, batch_first=True)\nself.dropout = nn.Dropout(dropout)\nself.linear_1 = nn.Linear(hidden_size, out_size)",
"_, final_states = se... | <|body_start_0|>
super(TextSubNet, self).__init__()
if num_layers == 1:
dropout = 0.0
self.rnn = nn.LSTM(in_size, hidden_size, num_layers=num_layers, dropout=dropout, bidirectional=bidirectional, batch_first=True)
self.dropout = nn.Dropout(dropout)
self.linear_1 = nn.... | The LSTM-based subnetwork that is used in TFN for text | TextSubNet | [
"GPL-1.0-or-later",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextSubNet:
"""The LSTM-based subnetwork that is used in TFN for text"""
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers ... | stack_v2_sparse_classes_10k_train_006489 | 3,873 | permissive | [
{
"docstring": "Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usage of bidirectional LSTM Output: (return value in forward) a tensor of shape (batch_size, out_size)",
"name": "__init__... | 2 | stack_v2_sparse_classes_30k_train_003236 | Implement the Python class `TextSubNet` described below.
Class description:
The LSTM-based subnetwork that is used in TFN for text
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False): Args: in_size: input dimension hidden_size: hidden ... | Implement the Python class `TextSubNet` described below.
Class description:
The LSTM-based subnetwork that is used in TFN for text
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False): Args: in_size: input dimension hidden_size: hidden ... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class TextSubNet:
"""The LSTM-based subnetwork that is used in TFN for text"""
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextSubNet:
"""The LSTM-based subnetwork that is used in TFN for text"""
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dro... | the_stack_v2_python_sparse | PyTorch/contrib/others/MMSA_ID2979_for_PyTorch/models/subNets/FeatureNets.py | Ascend/ModelZoo-PyTorch | train | 23 |
7ff20d2f3817695fbe07377b00deb27d0b3d0b72 | [
"super().__init__(serialName, debug)\nself.bytesStuffed = 0\nself.createCOM(serialName)\nself.run()",
"stop = False\nwhile not stop:\n print()\n self.getFile()\n self.checkBytes()\n self.buildHead()\n self.packet = self.head + self.fileBA + self.eop\n self.overhead = len(self.packet) / len(self.... | <|body_start_0|>
super().__init__(serialName, debug)
self.bytesStuffed = 0
self.createCOM(serialName)
self.run()
<|end_body_0|>
<|body_start_1|>
stop = False
while not stop:
print()
self.getFile()
self.checkBytes()
self.bui... | Client | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
def __init__(self, serialName, debug):
"""Executed when the object is created. Used to create all needed attributes."""
<|body_0|>
def run(self):
"""Runs all the logic needed to send a file and receive a response."""
<|body_1|>
def checkBytes(sel... | stack_v2_sparse_classes_10k_train_006490 | 12,431 | no_license | [
{
"docstring": "Executed when the object is created. Used to create all needed attributes.",
"name": "__init__",
"signature": "def __init__(self, serialName, debug)"
},
{
"docstring": "Runs all the logic needed to send a file and receive a response.",
"name": "run",
"signature": "def run... | 5 | stack_v2_sparse_classes_30k_train_006808 | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, serialName, debug): Executed when the object is created. Used to create all needed attributes.
- def run(self): Runs all the logic needed to send a file and receiv... | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, serialName, debug): Executed when the object is created. Used to create all needed attributes.
- def run(self): Runs all the logic needed to send a file and receiv... | e8c6ee9672ad33c568d97ec07c3faa6dbf9359ac | <|skeleton|>
class Client:
def __init__(self, serialName, debug):
"""Executed when the object is created. Used to create all needed attributes."""
<|body_0|>
def run(self):
"""Runs all the logic needed to send a file and receive a response."""
<|body_1|>
def checkBytes(sel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Client:
def __init__(self, serialName, debug):
"""Executed when the object is created. Used to create all needed attributes."""
super().__init__(serialName, debug)
self.bytesStuffed = 0
self.createCOM(serialName)
self.run()
def run(self):
"""Runs all the lo... | the_stack_v2_python_sparse | Projeto2/aplicacao.py | VFermat/CamadaFisica | train | 1 | |
619e841050b05e41f34952274311ffea92a5aebc | [
"freq = 0\nfor line in self.lines:\n freq += int(line)\nprint(f'Final freq: {freq}')",
"found = False\nfreq = 0\nfreqs_hit = {freq}\nwhile not found:\n for line in self.lines:\n freq += int(line)\n if freq in freqs_hit:\n found = True\n break\n freqs_hit.add(freq)\... | <|body_start_0|>
freq = 0
for line in self.lines:
freq += int(line)
print(f'Final freq: {freq}')
<|end_body_0|>
<|body_start_1|>
found = False
freq = 0
freqs_hit = {freq}
while not found:
for line in self.lines:
freq += int... | Day 1 challenges | Challenge | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Challenge:
"""Day 1 challenges"""
def challenge1(self):
"""Day 1 challenge 1"""
<|body_0|>
def challenge2(self):
"""Day 1 challenge 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
freq = 0
for line in self.lines:
freq += in... | stack_v2_sparse_classes_10k_train_006491 | 726 | permissive | [
{
"docstring": "Day 1 challenge 1",
"name": "challenge1",
"signature": "def challenge1(self)"
},
{
"docstring": "Day 1 challenge 2",
"name": "challenge2",
"signature": "def challenge2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007070 | Implement the Python class `Challenge` described below.
Class description:
Day 1 challenges
Method signatures and docstrings:
- def challenge1(self): Day 1 challenge 1
- def challenge2(self): Day 1 challenge 2 | Implement the Python class `Challenge` described below.
Class description:
Day 1 challenges
Method signatures and docstrings:
- def challenge1(self): Day 1 challenge 1
- def challenge2(self): Day 1 challenge 2
<|skeleton|>
class Challenge:
"""Day 1 challenges"""
def challenge1(self):
"""Day 1 challe... | 6671ef8c16a837f697bb3fb91004d1bd892814ba | <|skeleton|>
class Challenge:
"""Day 1 challenges"""
def challenge1(self):
"""Day 1 challenge 1"""
<|body_0|>
def challenge2(self):
"""Day 1 challenge 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Challenge:
"""Day 1 challenges"""
def challenge1(self):
"""Day 1 challenge 1"""
freq = 0
for line in self.lines:
freq += int(line)
print(f'Final freq: {freq}')
def challenge2(self):
"""Day 1 challenge 2"""
found = False
freq = 0
... | the_stack_v2_python_sparse | 2018/day1/challenge.py | ericgreveson/adventofcode | train | 0 |
0c7b1cfbf2e1d5472abbfe9ae038b643e0d875b3 | [
"cnt, stack = (0, [])\nfor c in s:\n if 0 == len(stack) or stack[-1] == c:\n stack.append(c)\n else:\n stack.pop()\n if 0 == len(stack):\n cnt += 1\nreturn cnt",
"lc, rc, cnt = (0, 0, 0)\nfor c in s:\n if c == 'L':\n lc += 1\n elif c == 'R':\n rc += 1\n if lc =... | <|body_start_0|>
cnt, stack = (0, [])
for c in s:
if 0 == len(stack) or stack[-1] == c:
stack.append(c)
else:
stack.pop()
if 0 == len(stack):
cnt += 1
return cnt
<|end_body_0|>
<|body_start_1|>
lc, rc, c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def balancedStringSplit0(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def balancedStringSplit(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cnt, stack = (0, [])
for c in s:
... | stack_v2_sparse_classes_10k_train_006492 | 1,184 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "balancedStringSplit0",
"signature": "def balancedStringSplit0(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "balancedStringSplit",
"signature": "def balancedStringSplit(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006269 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def balancedStringSplit0(self, s): :type s: str :rtype: int
- def balancedStringSplit(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def balancedStringSplit0(self, s): :type s: str :rtype: int
- def balancedStringSplit(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def balancedStringSpli... | 5376dd48b1cefb4faba9d2ef6a8a497b6b1d6c67 | <|skeleton|>
class Solution:
def balancedStringSplit0(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def balancedStringSplit(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def balancedStringSplit0(self, s):
""":type s: str :rtype: int"""
cnt, stack = (0, [])
for c in s:
if 0 == len(stack) or stack[-1] == c:
stack.append(c)
else:
stack.pop()
if 0 == len(stack):
c... | the_stack_v2_python_sparse | python/problem-stack-and-queue/split_a_string_in_balanced_strings.py | hyunjun/practice | train | 3 | |
495e39976d726bc69633ac7a16e49d0f827f46d3 | [
"pysam.Samfile.__init__(self, inputFname, openMode, **keywords)\nself.inputFname = inputFname\nself.openMode = openMode\n'\\n\\t\\tfrom pymodule import ProcessOptions\\n\\t\\tself.ad = ProcessOptions.process_function_arguments(keywords, self.option_default_dict, error_doc=self.__doc__, \\t\\t\\t\\t\\t\\t\\t\\t\\t\\... | <|body_start_0|>
pysam.Samfile.__init__(self, inputFname, openMode, **keywords)
self.inputFname = inputFname
self.openMode = openMode
'\n\t\tfrom pymodule import ProcessOptions\n\t\tself.ad = ProcessOptions.process_function_arguments(keywords, self.option_default_dict, error_doc=self.__d... | BamFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BamFile:
def __init__(self, inputFname, openMode, **keywords):
"""2011-7-11"""
<|body_0|>
def traverseBamByRead(self, processor=None):
"""2011-7-10 add samfile to param_obj 2011-2-8 a traverser used by other functions"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_10k_train_006493 | 4,113 | no_license | [
{
"docstring": "2011-7-11",
"name": "__init__",
"signature": "def __init__(self, inputFname, openMode, **keywords)"
},
{
"docstring": "2011-7-10 add samfile to param_obj 2011-2-8 a traverser used by other functions",
"name": "traverseBamByRead",
"signature": "def traverseBamByRead(self, ... | 2 | null | Implement the Python class `BamFile` described below.
Class description:
Implement the BamFile class.
Method signatures and docstrings:
- def __init__(self, inputFname, openMode, **keywords): 2011-7-11
- def traverseBamByRead(self, processor=None): 2011-7-10 add samfile to param_obj 2011-2-8 a traverser used by other... | Implement the Python class `BamFile` described below.
Class description:
Implement the BamFile class.
Method signatures and docstrings:
- def __init__(self, inputFname, openMode, **keywords): 2011-7-11
- def traverseBamByRead(self, processor=None): 2011-7-10 add samfile to param_obj 2011-2-8 a traverser used by other... | b9333b85daed71032a1cba766585d0be1986ffdb | <|skeleton|>
class BamFile:
def __init__(self, inputFname, openMode, **keywords):
"""2011-7-11"""
<|body_0|>
def traverseBamByRead(self, processor=None):
"""2011-7-10 add samfile to param_obj 2011-2-8 a traverser used by other functions"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BamFile:
def __init__(self, inputFname, openMode, **keywords):
"""2011-7-11"""
pysam.Samfile.__init__(self, inputFname, openMode, **keywords)
self.inputFname = inputFname
self.openMode = openMode
'\n\t\tfrom pymodule import ProcessOptions\n\t\tself.ad = ProcessOptions.p... | the_stack_v2_python_sparse | pymodule/yhio/BamFile.py | polyactis/gwasmodules | train | 0 | |
54c4f3520d5d633aec41806b924b17ff1faf61a8 | [
"QtWidgets.QDialog.__init__(self)\nself.resize(1000, 700)\nself.topicList = QtWidgets.QListWidget()\nself.topicList.setFixedWidth(200)\nself.topicList.addItem('General Use')\nself.topicList.addItem('File Menu')\nself.topicList.addItem('Operations')\nself.topicList.currentItemChanged.connect(self.displayHelp)\nself.... | <|body_start_0|>
QtWidgets.QDialog.__init__(self)
self.resize(1000, 700)
self.topicList = QtWidgets.QListWidget()
self.topicList.setFixedWidth(200)
self.topicList.addItem('General Use')
self.topicList.addItem('File Menu')
self.topicList.addItem('Operations')
... | A help wiki to teach the user about the program and how to use it. | HelpModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HelpModel:
"""A help wiki to teach the user about the program and how to use it."""
def __init__(self, parent=None):
"""Initializes the UI and sets the properties."""
<|body_0|>
def help(self, parent=None):
"""Present knowledge to the user"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_006494 | 29,548 | no_license | [
{
"docstring": "Initializes the UI and sets the properties.",
"name": "__init__",
"signature": "def __init__(self, parent=None)"
},
{
"docstring": "Present knowledge to the user",
"name": "help",
"signature": "def help(self, parent=None)"
},
{
"docstring": "Gets active selection ... | 3 | stack_v2_sparse_classes_30k_train_000708 | Implement the Python class `HelpModel` described below.
Class description:
A help wiki to teach the user about the program and how to use it.
Method signatures and docstrings:
- def __init__(self, parent=None): Initializes the UI and sets the properties.
- def help(self, parent=None): Present knowledge to the user
- ... | Implement the Python class `HelpModel` described below.
Class description:
A help wiki to teach the user about the program and how to use it.
Method signatures and docstrings:
- def __init__(self, parent=None): Initializes the UI and sets the properties.
- def help(self, parent=None): Present knowledge to the user
- ... | 1a3c5ad967472faf66236a311cc07a5128f5f911 | <|skeleton|>
class HelpModel:
"""A help wiki to teach the user about the program and how to use it."""
def __init__(self, parent=None):
"""Initializes the UI and sets the properties."""
<|body_0|>
def help(self, parent=None):
"""Present knowledge to the user"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HelpModel:
"""A help wiki to teach the user about the program and how to use it."""
def __init__(self, parent=None):
"""Initializes the UI and sets the properties."""
QtWidgets.QDialog.__init__(self)
self.resize(1000, 700)
self.topicList = QtWidgets.QListWidget()
s... | the_stack_v2_python_sparse | datatool/gui/Model.py | scottawalton/datatool | train | 0 |
f4236a16b7551e09fb381c3363817cce5168e813 | [
"item = MzituScrapyItem()\nmax_num = response.xpath(\"descendant::div[@class='main']/div[@class='content']/div[@class='pagenavi']/a[last()-1]/span/text()\").extract_first(default='N/A')\nitem['name'] = response.xpath(\"./*//div[@class='main']/div[1]/h2/text()\").extract_first(default='N/A')\nitem['url'] = response.... | <|body_start_0|>
item = MzituScrapyItem()
max_num = response.xpath("descendant::div[@class='main']/div[@class='content']/div[@class='pagenavi']/a[last()-1]/span/text()").extract_first(default='N/A')
item['name'] = response.xpath("./*//div[@class='main']/div[1]/h2/text()").extract_first(default='... | Spider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Spider:
def parse_item(self, response):
""":param response: 下载器返回的response :return:"""
<|body_0|>
def img_url(self, response):
"""取出图片URL 并添加进self.img_urls列表中 :param response: :param img_url 为每张图片的真实地址"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_006495 | 1,685 | permissive | [
{
"docstring": ":param response: 下载器返回的response :return:",
"name": "parse_item",
"signature": "def parse_item(self, response)"
},
{
"docstring": "取出图片URL 并添加进self.img_urls列表中 :param response: :param img_url 为每张图片的真实地址",
"name": "img_url",
"signature": "def img_url(self, response)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004968 | Implement the Python class `Spider` described below.
Class description:
Implement the Spider class.
Method signatures and docstrings:
- def parse_item(self, response): :param response: 下载器返回的response :return:
- def img_url(self, response): 取出图片URL 并添加进self.img_urls列表中 :param response: :param img_url 为每张图片的真实地址 | Implement the Python class `Spider` described below.
Class description:
Implement the Spider class.
Method signatures and docstrings:
- def parse_item(self, response): :param response: 下载器返回的response :return:
- def img_url(self, response): 取出图片URL 并添加进self.img_urls列表中 :param response: :param img_url 为每张图片的真实地址
<|ske... | 345e34fff7386d91acbb03a01fd4127c5dfed037 | <|skeleton|>
class Spider:
def parse_item(self, response):
""":param response: 下载器返回的response :return:"""
<|body_0|>
def img_url(self, response):
"""取出图片URL 并添加进self.img_urls列表中 :param response: :param img_url 为每张图片的真实地址"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Spider:
def parse_item(self, response):
""":param response: 下载器返回的response :return:"""
item = MzituScrapyItem()
max_num = response.xpath("descendant::div[@class='main']/div[@class='content']/div[@class='pagenavi']/a[last()-1]/span/text()").extract_first(default='N/A')
item['nam... | the_stack_v2_python_sparse | projects/scrapy_mzitu_webset/mzitu_scrapy/spiders/spider.py | ice-melt/python_code_manager | train | 0 | |
42bdf7c2c612f01d328701cac9604be820d4a039 | [
"super(MainApplication, self).__init__()\nself.ui = sff.SimilarFilesUIMainWindow()\nself.ui.setupUi(self)\nself.ui.search_button.clicked.connect(self.search_pressed)\nself.ui.tree.setHeaderLabels([''])",
"self.ui.tree.clear()\npath = self.ui.path_panel.displayText()\ntry:\n file_chains = similar_files_chains(p... | <|body_start_0|>
super(MainApplication, self).__init__()
self.ui = sff.SimilarFilesUIMainWindow()
self.ui.setupUi(self)
self.ui.search_button.clicked.connect(self.search_pressed)
self.ui.tree.setHeaderLabels([''])
<|end_body_0|>
<|body_start_1|>
self.ui.tree.clear()
... | Instances of this class will be similar files finder applications. | MainApplication | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainApplication:
"""Instances of this class will be similar files finder applications."""
def __init__(self):
"""Constructor of class MainApplication."""
<|body_0|>
def search_pressed(self):
"""This method is called when the button 'search' is pressed. It searche... | stack_v2_sparse_classes_10k_train_006496 | 2,033 | no_license | [
{
"docstring": "Constructor of class MainApplication.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "This method is called when the button 'search' is pressed. It searches for the similar files chains in the directory from the ui.path_panel and displays them in the ui... | 2 | stack_v2_sparse_classes_30k_train_002468 | Implement the Python class `MainApplication` described below.
Class description:
Instances of this class will be similar files finder applications.
Method signatures and docstrings:
- def __init__(self): Constructor of class MainApplication.
- def search_pressed(self): This method is called when the button 'search' i... | Implement the Python class `MainApplication` described below.
Class description:
Instances of this class will be similar files finder applications.
Method signatures and docstrings:
- def __init__(self): Constructor of class MainApplication.
- def search_pressed(self): This method is called when the button 'search' i... | 023307a9b7f7f8dbb1589e222e794e128f1f365b | <|skeleton|>
class MainApplication:
"""Instances of this class will be similar files finder applications."""
def __init__(self):
"""Constructor of class MainApplication."""
<|body_0|>
def search_pressed(self):
"""This method is called when the button 'search' is pressed. It searche... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MainApplication:
"""Instances of this class will be similar files finder applications."""
def __init__(self):
"""Constructor of class MainApplication."""
super(MainApplication, self).__init__()
self.ui = sff.SimilarFilesUIMainWindow()
self.ui.setupUi(self)
self.ui.... | the_stack_v2_python_sparse | supertool/src/supertool/sff_app.py | Goopard/Study-2 | train | 0 |
b691324c0b744ef61293ed58666d12ae927dc5d2 | [
"if not take_key_as_arg:\n self.missing_value_creator = lambda k: missing_value_creator()\nelse:\n self.missing_value_creator = missing_value_creator",
"value = self.missing_value_creator(k)\nself[k] = value\nreturn value"
] | <|body_start_0|>
if not take_key_as_arg:
self.missing_value_creator = lambda k: missing_value_creator()
else:
self.missing_value_creator = missing_value_creator
<|end_body_0|>
<|body_start_1|>
value = self.missing_value_creator(k)
self[k] = value
return v... | A dictionary where missing values are created by an __init__ time supplied function. | DictOf | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DictOf:
"""A dictionary where missing values are created by an __init__ time supplied function."""
def __init__(self, missing_value_creator, take_key_as_arg=False):
"""@arg missing_value_creator: Function to create missing values in the dictionary"""
<|body_0|>
def __mis... | stack_v2_sparse_classes_10k_train_006497 | 3,293 | permissive | [
{
"docstring": "@arg missing_value_creator: Function to create missing values in the dictionary",
"name": "__init__",
"signature": "def __init__(self, missing_value_creator, take_key_as_arg=False)"
},
{
"docstring": "Called when there is no value for a given key, k.",
"name": "__missing__",
... | 2 | stack_v2_sparse_classes_30k_train_005618 | Implement the Python class `DictOf` described below.
Class description:
A dictionary where missing values are created by an __init__ time supplied function.
Method signatures and docstrings:
- def __init__(self, missing_value_creator, take_key_as_arg=False): @arg missing_value_creator: Function to create missing valu... | Implement the Python class `DictOf` described below.
Class description:
A dictionary where missing values are created by an __init__ time supplied function.
Method signatures and docstrings:
- def __init__(self, missing_value_creator, take_key_as_arg=False): @arg missing_value_creator: Function to create missing valu... | 02db81f3e7c87c9497c527d3dc4ea5e3592a58cb | <|skeleton|>
class DictOf:
"""A dictionary where missing values are created by an __init__ time supplied function."""
def __init__(self, missing_value_creator, take_key_as_arg=False):
"""@arg missing_value_creator: Function to create missing values in the dictionary"""
<|body_0|>
def __mis... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DictOf:
"""A dictionary where missing values are created by an __init__ time supplied function."""
def __init__(self, missing_value_creator, take_key_as_arg=False):
"""@arg missing_value_creator: Function to create missing values in the dictionary"""
if not take_key_as_arg:
se... | the_stack_v2_python_sparse | python/cookbook/dicts.py | JohnReid/Cookbook | train | 1 |
139a67be94703b5979e587a828b8ce862535e6a2 | [
"if scipy.__version__ == '0.14.0':\n return self._fftconvolve_14(in1, in2, int2_fft, mode)\nelse:\n return self._fftconvolve_18(in1, in2, int2_fft, mode)",
"in1 = signaltools.asarray(in1)\nin2 = signaltools.asarray(in2)\nif in1.ndim == in2.ndim == 0:\n return in1 * in2\nelif not in1.ndim == in2.ndim:\n ... | <|body_start_0|>
if scipy.__version__ == '0.14.0':
return self._fftconvolve_14(in1, in2, int2_fft, mode)
else:
return self._fftconvolve_18(in1, in2, int2_fft, mode)
<|end_body_0|>
<|body_start_1|>
in1 = signaltools.asarray(in1)
in2 = signaltools.asarray(in2)
... | fft convolution routines optimized for different scipy versions | FFTConvolve | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FFTConvolve:
"""fft convolution routines optimized for different scipy versions"""
def fftconvolve(self, in1, in2, int2_fft, mode='same'):
""":param in1: :param in2: :param int2_fft: :param mode: :return:"""
<|body_0|>
def _fftconvolve_18(self, in1, in2, int2_fft, mode='... | stack_v2_sparse_classes_10k_train_006498 | 5,437 | permissive | [
{
"docstring": ":param in1: :param in2: :param int2_fft: :param mode: :return:",
"name": "fftconvolve",
"signature": "def fftconvolve(self, in1, in2, int2_fft, mode='same')"
},
{
"docstring": "scipy routine scipy.signal.fftconvolve with kernel already fourier transformed",
"name": "_fftconvo... | 6 | stack_v2_sparse_classes_30k_train_006446 | Implement the Python class `FFTConvolve` described below.
Class description:
fft convolution routines optimized for different scipy versions
Method signatures and docstrings:
- def fftconvolve(self, in1, in2, int2_fft, mode='same'): :param in1: :param in2: :param int2_fft: :param mode: :return:
- def _fftconvolve_18(... | Implement the Python class `FFTConvolve` described below.
Class description:
fft convolution routines optimized for different scipy versions
Method signatures and docstrings:
- def fftconvolve(self, in1, in2, int2_fft, mode='same'): :param in1: :param in2: :param int2_fft: :param mode: :return:
- def _fftconvolve_18(... | d2223705bc44d07575a5e93291375ab8e69ebfa8 | <|skeleton|>
class FFTConvolve:
"""fft convolution routines optimized for different scipy versions"""
def fftconvolve(self, in1, in2, int2_fft, mode='same'):
""":param in1: :param in2: :param int2_fft: :param mode: :return:"""
<|body_0|>
def _fftconvolve_18(self, in1, in2, int2_fft, mode='... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FFTConvolve:
"""fft convolution routines optimized for different scipy versions"""
def fftconvolve(self, in1, in2, int2_fft, mode='same'):
""":param in1: :param in2: :param int2_fft: :param mode: :return:"""
if scipy.__version__ == '0.14.0':
return self._fftconvolve_14(in1, in... | the_stack_v2_python_sparse | astrofunc/fft_convolve.py | sibirrer/astrofunc | train | 0 |
24c0eca60e4b90b60e8991bbd27f5d587f97dfc2 | [
"pc = DotDict()\nf2jd = copy.deepcopy(cannonical_json_dump)\npc.upload_file_minidump_flash2 = DotDict()\npc.upload_file_minidump_flash2.json_dump = f2jd\npc.upload_file_minidump_flash2.json_dump['threads'][0]['frames'][2]['function'] = 'NtAlpcSendWaitReceivePort'\nfake_processor = create_basic_fake_processor()\nrc ... | <|body_start_0|>
pc = DotDict()
f2jd = copy.deepcopy(cannonical_json_dump)
pc.upload_file_minidump_flash2 = DotDict()
pc.upload_file_minidump_flash2.json_dump = f2jd
pc.upload_file_minidump_flash2.json_dump['threads'][0]['frames'][2]['function'] = 'NtAlpcSendWaitReceivePort'
... | TestSendWaitReceivePort | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSendWaitReceivePort:
def test_action_case_1(self):
"""success - target found in top 5 frames of stack"""
<|body_0|>
def test_action_case_2(self):
"""failure - target not found in top 5 frames of stack"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_006499 | 27,276 | no_license | [
{
"docstring": "success - target found in top 5 frames of stack",
"name": "test_action_case_1",
"signature": "def test_action_case_1(self)"
},
{
"docstring": "failure - target not found in top 5 frames of stack",
"name": "test_action_case_2",
"signature": "def test_action_case_2(self)"
... | 2 | stack_v2_sparse_classes_30k_train_002374 | Implement the Python class `TestSendWaitReceivePort` described below.
Class description:
Implement the TestSendWaitReceivePort class.
Method signatures and docstrings:
- def test_action_case_1(self): success - target found in top 5 frames of stack
- def test_action_case_2(self): failure - target not found in top 5 fr... | Implement the Python class `TestSendWaitReceivePort` described below.
Class description:
Implement the TestSendWaitReceivePort class.
Method signatures and docstrings:
- def test_action_case_1(self): success - target found in top 5 frames of stack
- def test_action_case_2(self): failure - target not found in top 5 fr... | 9c9b7701d7ddf9f3cbba1a4d0aa65758e8b49528 | <|skeleton|>
class TestSendWaitReceivePort:
def test_action_case_1(self):
"""success - target found in top 5 frames of stack"""
<|body_0|>
def test_action_case_2(self):
"""failure - target not found in top 5 frames of stack"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSendWaitReceivePort:
def test_action_case_1(self):
"""success - target found in top 5 frames of stack"""
pc = DotDict()
f2jd = copy.deepcopy(cannonical_json_dump)
pc.upload_file_minidump_flash2 = DotDict()
pc.upload_file_minidump_flash2.json_dump = f2jd
pc.u... | the_stack_v2_python_sparse | socorro/unittest/processor/test_skunk_classifiers.py | v1ka5/socorro | train | 0 |
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