blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
de657f6e41f4b3a2951491b151a73910da459499 | [
"lo, hi = (max(nums), sum(nums))\nwhile lo < hi:\n mid = lo + (hi - lo) // 2\n cnt = 0\n curr = 0\n for num in nums:\n if curr + num <= mid:\n curr += num\n else:\n cnt += 1\n curr = num\n if cnt >= m:\n lo = mid + 1\n else:\n hi = mid\n... | <|body_start_0|>
lo, hi = (max(nums), sum(nums))
while lo < hi:
mid = lo + (hi - lo) // 2
cnt = 0
curr = 0
for num in nums:
if curr + num <= mid:
curr += num
else:
cnt += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def splitArray1(self, nums: List[int], m: int) -> int:
"""binary search"""
<|body_0|>
def splitArray2(self, nums: List[int], m: int) -> int:
"""dynamic programming: define dp[i][j] as minimum largest subarray sum for splitting nums[0..j] in i parts time: O(... | stack_v2_sparse_classes_36k_train_012300 | 2,009 | no_license | [
{
"docstring": "binary search",
"name": "splitArray1",
"signature": "def splitArray1(self, nums: List[int], m: int) -> int"
},
{
"docstring": "dynamic programming: define dp[i][j] as minimum largest subarray sum for splitting nums[0..j] in i parts time: O(MN^2) space: O(MN)",
"name": "splitA... | 2 | stack_v2_sparse_classes_30k_train_006065 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitArray1(self, nums: List[int], m: int) -> int: binary search
- def splitArray2(self, nums: List[int], m: int) -> int: dynamic programming: define dp[i][j] as minimum larg... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitArray1(self, nums: List[int], m: int) -> int: binary search
- def splitArray2(self, nums: List[int], m: int) -> int: dynamic programming: define dp[i][j] as minimum larg... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def splitArray1(self, nums: List[int], m: int) -> int:
"""binary search"""
<|body_0|>
def splitArray2(self, nums: List[int], m: int) -> int:
"""dynamic programming: define dp[i][j] as minimum largest subarray sum for splitting nums[0..j] in i parts time: O(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def splitArray1(self, nums: List[int], m: int) -> int:
"""binary search"""
lo, hi = (max(nums), sum(nums))
while lo < hi:
mid = lo + (hi - lo) // 2
cnt = 0
curr = 0
for num in nums:
if curr + num <= mid:
... | the_stack_v2_python_sparse | Leetcode 0410. Split Array Largest Sum.py | Chaoran-sjsu/leetcode | train | 0 | |
ba3a5f1c9813e9546e496c36725bcad3ed6aa44c | [
"self.cycletime = datetime(2017, 1, 10, 6)\ncube_uk_det = set_up_variable_cube(np.full((4, 4), 273.15, dtype=np.float32), time=self.cycletime, frt=datetime(2017, 1, 10, 3))\ntime_points = [1484038800, 1484046000, 1484053200]\ncube_uk_det = add_coordinate(cube_uk_det, time_points, 'time', dtype=np.int64, coord_units... | <|body_start_0|>
self.cycletime = datetime(2017, 1, 10, 6)
cube_uk_det = set_up_variable_cube(np.full((4, 4), 273.15, dtype=np.float32), time=self.cycletime, frt=datetime(2017, 1, 10, 3))
time_points = [1484038800, 1484046000, 1484053200]
cube_uk_det = add_coordinate(cube_uk_det, time_po... | Test the unify_cycletime function. | Test_unify_cycletime | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_unify_cycletime:
"""Test the unify_cycletime function."""
def setUp(self):
"""Set up a UK deterministic cube for testing."""
<|body_0|>
def test_cubelist_input(self):
"""Test when supplying a cubelist as input containing cubes representing UK deterministic a... | stack_v2_sparse_classes_36k_train_012301 | 20,564 | permissive | [
{
"docstring": "Set up a UK deterministic cube for testing.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test when supplying a cubelist as input containing cubes representing UK deterministic and UK ensemble model configuration and unifying the forecast_reference_time, so... | 4 | null | Implement the Python class `Test_unify_cycletime` described below.
Class description:
Test the unify_cycletime function.
Method signatures and docstrings:
- def setUp(self): Set up a UK deterministic cube for testing.
- def test_cubelist_input(self): Test when supplying a cubelist as input containing cubes representi... | Implement the Python class `Test_unify_cycletime` described below.
Class description:
Test the unify_cycletime function.
Method signatures and docstrings:
- def setUp(self): Set up a UK deterministic cube for testing.
- def test_cubelist_input(self): Test when supplying a cubelist as input containing cubes representi... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_unify_cycletime:
"""Test the unify_cycletime function."""
def setUp(self):
"""Set up a UK deterministic cube for testing."""
<|body_0|>
def test_cubelist_input(self):
"""Test when supplying a cubelist as input containing cubes representing UK deterministic a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_unify_cycletime:
"""Test the unify_cycletime function."""
def setUp(self):
"""Set up a UK deterministic cube for testing."""
self.cycletime = datetime(2017, 1, 10, 6)
cube_uk_det = set_up_variable_cube(np.full((4, 4), 273.15, dtype=np.float32), time=self.cycletime, frt=dateti... | the_stack_v2_python_sparse | improver_tests/metadata/test_forecast_times.py | metoppv/improver | train | 101 |
e59a8db10ff05797345353182cb7d141482091ec | [
"self.explanation_type = explanation_type\nself._internal_obj = internal_obj\nself.feature_names = feature_names\nself.feature_types = feature_types\nself.name = name\nself.selector = selector",
"if key is None:\n return self._internal_obj['overall']\nreturn None",
"from ..visual.plot import plot_performance... | <|body_start_0|>
self.explanation_type = explanation_type
self._internal_obj = internal_obj
self.feature_names = feature_names
self.feature_types = feature_types
self.name = name
self.selector = selector
<|end_body_0|>
<|body_start_1|>
if key is None:
... | Explanation object specific to ROC explainer. | ROCExplanation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ROCExplanation:
"""Explanation object specific to ROC explainer."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object... | stack_v2_sparse_classes_36k_train_012302 | 10,362 | permissive | [
{
"docstring": "Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object that backs the explanation. feature_names: List of feature names. feature_types: List of feature types. name: User-defined name of explanation. selector: A dataframe whose indices correspond to explan... | 3 | stack_v2_sparse_classes_30k_train_004554 | Implement the Python class `ROCExplanation` described below.
Class description:
Explanation object specific to ROC explainer.
Method signatures and docstrings:
- def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None): Initializes class. Args: explanation_t... | Implement the Python class `ROCExplanation` described below.
Class description:
Explanation object specific to ROC explainer.
Method signatures and docstrings:
- def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None): Initializes class. Args: explanation_t... | e6f38ea195aecbbd9d28c7183a83c65ada16e1ae | <|skeleton|>
class ROCExplanation:
"""Explanation object specific to ROC explainer."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ROCExplanation:
"""Explanation object specific to ROC explainer."""
def __init__(self, explanation_type, internal_obj, feature_names=None, feature_types=None, name=None, selector=None):
"""Initializes class. Args: explanation_type: Type of explanation. internal_obj: A jsonable object that backs t... | the_stack_v2_python_sparse | python/interpret-core/interpret/perf/_curve.py | interpretml/interpret | train | 3,731 |
db1d4a3da7a83ce12d74b4aaf8db23295dfee816 | [
"super(Attention, self).__init__()\nassert kernel_size % 2 == 1, \"Kernel size should be odd for 'same' conv.\"\npadding = (kernel_size - 1) // 2\nself.conv = nn.Conv1d(1, 1, kernel_size, padding=padding)\nself.log_t = log_t",
"pax = eh * dhx\npax = torch.sum(pax, dim=2)\nif ax is not None:\n ax = ax.unsqueeze... | <|body_start_0|>
super(Attention, self).__init__()
assert kernel_size % 2 == 1, "Kernel size should be odd for 'same' conv."
padding = (kernel_size - 1) // 2
self.conv = nn.Conv1d(1, 1, kernel_size, padding=padding)
self.log_t = log_t
<|end_body_0|>
<|body_start_1|>
pax ... | Attention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Attention:
def __init__(self, kernel_size=11, log_t=False):
"""Module which Performs a single attention step along the second axis of a given encoded input. The module uses both 'content' and 'location' based attention. The 'content' based attention is an inner product of the decoder hid... | stack_v2_sparse_classes_36k_train_012303 | 19,030 | no_license | [
{
"docstring": "Module which Performs a single attention step along the second axis of a given encoded input. The module uses both 'content' and 'location' based attention. The 'content' based attention is an inner product of the decoder hidden state with each time-step of the encoder state. The 'location' base... | 2 | stack_v2_sparse_classes_30k_train_002843 | Implement the Python class `Attention` described below.
Class description:
Implement the Attention class.
Method signatures and docstrings:
- def __init__(self, kernel_size=11, log_t=False): Module which Performs a single attention step along the second axis of a given encoded input. The module uses both 'content' an... | Implement the Python class `Attention` described below.
Class description:
Implement the Attention class.
Method signatures and docstrings:
- def __init__(self, kernel_size=11, log_t=False): Module which Performs a single attention step along the second axis of a given encoded input. The module uses both 'content' an... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Attention:
def __init__(self, kernel_size=11, log_t=False):
"""Module which Performs a single attention step along the second axis of a given encoded input. The module uses both 'content' and 'location' based attention. The 'content' based attention is an inner product of the decoder hid... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Attention:
def __init__(self, kernel_size=11, log_t=False):
"""Module which Performs a single attention step along the second axis of a given encoded input. The module uses both 'content' and 'location' based attention. The 'content' based attention is an inner product of the decoder hidden state with... | the_stack_v2_python_sparse | generated/test_awni_speech.py | jansel/pytorch-jit-paritybench | train | 35 | |
353a6ff0d796c054bc92a5c446de5b0439b6bfe8 | [
"if 'querystring_parts' not in context:\n context['querystring_parts'] = {}\nreturn deepcopy(context['querystring_parts'])",
"context = super(WithQueryStringViewMixin, self).get_context_data(**kwargs)\nqs = self.request.META.get('QUERY_STRING', '')\nqs_dict = parse_qs(qs)\nqs_parts = {}\nfor key, values in qs_... | <|body_start_0|>
if 'querystring_parts' not in context:
context['querystring_parts'] = {}
return deepcopy(context['querystring_parts'])
<|end_body_0|>
<|body_start_1|>
context = super(WithQueryStringViewMixin, self).get_context_data(**kwargs)
qs = self.request.META.get('QUER... | WithQueryStringViewMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WithQueryStringViewMixin:
def get_qs_parts(self, context):
"""Get the querystring parts from the context"""
<|body_0|>
def get_context_data(self, **kwargs):
"""By default, simply split the querystring in parts for use in other views, and put the parts and the whole q... | stack_v2_sparse_classes_36k_train_012304 | 15,489 | no_license | [
{
"docstring": "Get the querystring parts from the context",
"name": "get_qs_parts",
"signature": "def get_qs_parts(self, context)"
},
{
"docstring": "By default, simply split the querystring in parts for use in other views, and put the parts and the whole querystring in the context",
"name"... | 2 | stack_v2_sparse_classes_30k_train_016279 | Implement the Python class `WithQueryStringViewMixin` described below.
Class description:
Implement the WithQueryStringViewMixin class.
Method signatures and docstrings:
- def get_qs_parts(self, context): Get the querystring parts from the context
- def get_context_data(self, **kwargs): By default, simply split the q... | Implement the Python class `WithQueryStringViewMixin` described below.
Class description:
Implement the WithQueryStringViewMixin class.
Method signatures and docstrings:
- def get_qs_parts(self, context): Get the querystring parts from the context
- def get_context_data(self, **kwargs): By default, simply split the q... | 63a405b993e77f10b9c2b6d9790aae7576d9d84f | <|skeleton|>
class WithQueryStringViewMixin:
def get_qs_parts(self, context):
"""Get the querystring parts from the context"""
<|body_0|>
def get_context_data(self, **kwargs):
"""By default, simply split the querystring in parts for use in other views, and put the parts and the whole q... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WithQueryStringViewMixin:
def get_qs_parts(self, context):
"""Get the querystring parts from the context"""
if 'querystring_parts' not in context:
context['querystring_parts'] = {}
return deepcopy(context['querystring_parts'])
def get_context_data(self, **kwargs):
... | the_stack_v2_python_sparse | gim/front/mixins/views.py | derekey/github-issues-manager | train | 1 | |
b7cd1529e270beeb6207689743e8bead6b45fb25 | [
"super().__init__(self.PROBLEM_NAME)\nself.root_node1 = root_node1\nself.root_node2 = root_node2",
"print('Solving {} problem ...'.format(self.PROBLEM_NAME))\nif self.root_node2 is None:\n return True\nif self.root_node2 is None:\n return True\nreturn self.are_identical(self.root_node1, self.root_node2) or ... | <|body_start_0|>
super().__init__(self.PROBLEM_NAME)
self.root_node1 = root_node1
self.root_node2 = root_node2
<|end_body_0|>
<|body_start_1|>
print('Solving {} problem ...'.format(self.PROBLEM_NAME))
if self.root_node2 is None:
return True
if self.root_node2... | Check Binary Tree Is Subtree | CheckBinaryTreeIsSubtree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckBinaryTreeIsSubtree:
"""Check Binary Tree Is Subtree"""
def __init__(self, root_node1, root_node2):
"""CheckBinaryTreeIsSubtree Args: root_node1: node of the 1st tree root_node2: node of the 2nd tree Returns: None Raises: None"""
<|body_0|>
def solve(self):
... | stack_v2_sparse_classes_36k_train_012305 | 2,482 | no_license | [
{
"docstring": "CheckBinaryTreeIsSubtree Args: root_node1: node of the 1st tree root_node2: node of the 2nd tree Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, root_node1, root_node2)"
},
{
"docstring": "Solve the problem Note: O(nm) (runtime) solution recursiv... | 3 | null | Implement the Python class `CheckBinaryTreeIsSubtree` described below.
Class description:
Check Binary Tree Is Subtree
Method signatures and docstrings:
- def __init__(self, root_node1, root_node2): CheckBinaryTreeIsSubtree Args: root_node1: node of the 1st tree root_node2: node of the 2nd tree Returns: None Raises: ... | Implement the Python class `CheckBinaryTreeIsSubtree` described below.
Class description:
Check Binary Tree Is Subtree
Method signatures and docstrings:
- def __init__(self, root_node1, root_node2): CheckBinaryTreeIsSubtree Args: root_node1: node of the 1st tree root_node2: node of the 2nd tree Returns: None Raises: ... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class CheckBinaryTreeIsSubtree:
"""Check Binary Tree Is Subtree"""
def __init__(self, root_node1, root_node2):
"""CheckBinaryTreeIsSubtree Args: root_node1: node of the 1st tree root_node2: node of the 2nd tree Returns: None Raises: None"""
<|body_0|>
def solve(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckBinaryTreeIsSubtree:
"""Check Binary Tree Is Subtree"""
def __init__(self, root_node1, root_node2):
"""CheckBinaryTreeIsSubtree Args: root_node1: node of the 1st tree root_node2: node of the 2nd tree Returns: None Raises: None"""
super().__init__(self.PROBLEM_NAME)
self.root_... | the_stack_v2_python_sparse | python/problems/binary_tree/check_binary_tree_is_subtree.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
1633e726570eb038def367dbda4bac4a1edbd892 | [
"print('Loading weights: ', path)\nsuper(MidasNet, self).__init__()\nuse_pretrained = False if path is None else True\nself.pretrained, self.scratch = _make_encoder(backbone='resnext101_wsl', features=features, use_pretrained=use_pretrained)\nself.scratch.refinenet4 = FeatureFusionBlock(features)\nself.scratch.refi... | <|body_start_0|>
print('Loading weights: ', path)
super(MidasNet, self).__init__()
use_pretrained = False if path is None else True
self.pretrained, self.scratch = _make_encoder(backbone='resnext101_wsl', features=features, use_pretrained=use_pretrained)
self.scratch.refinenet4 =... | Network for monocular depth estimation. | MidasNet | [
"MIT",
"Apache-2.0",
"Python-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MidasNet:
"""Network for monocular depth estimation."""
def __init__(self, path=None, features=256, non_negative=True):
"""Init. Args: path (str, optional): Path to saved model. Defaults to None. features (int, optional): Number of features. Defaults to 256. backbone (str, optional):... | stack_v2_sparse_classes_36k_train_012306 | 2,934 | permissive | [
{
"docstring": "Init. Args: path (str, optional): Path to saved model. Defaults to None. features (int, optional): Number of features. Defaults to 256. backbone (str, optional): Backbone network for encoder. Defaults to resnet50",
"name": "__init__",
"signature": "def __init__(self, path=None, features=... | 2 | stack_v2_sparse_classes_30k_train_018643 | Implement the Python class `MidasNet` described below.
Class description:
Network for monocular depth estimation.
Method signatures and docstrings:
- def __init__(self, path=None, features=256, non_negative=True): Init. Args: path (str, optional): Path to saved model. Defaults to None. features (int, optional): Numbe... | Implement the Python class `MidasNet` described below.
Class description:
Network for monocular depth estimation.
Method signatures and docstrings:
- def __init__(self, path=None, features=256, non_negative=True): Init. Args: path (str, optional): Path to saved model. Defaults to None. features (int, optional): Numbe... | 038fb5afe017b82334ad39a256531d2c4e9e1e1a | <|skeleton|>
class MidasNet:
"""Network for monocular depth estimation."""
def __init__(self, path=None, features=256, non_negative=True):
"""Init. Args: path (str, optional): Path to saved model. Defaults to None. features (int, optional): Number of features. Defaults to 256. backbone (str, optional):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MidasNet:
"""Network for monocular depth estimation."""
def __init__(self, path=None, features=256, non_negative=True):
"""Init. Args: path (str, optional): Path to saved model. Defaults to None. features (int, optional): Number of features. Defaults to 256. backbone (str, optional): Backbone net... | the_stack_v2_python_sparse | 15.PaddleGAN/PaddleGAN/ppgan/apps/midas/midas_net.py | yingshaoxo/ML | train | 5 |
a1abb29738ddf87c9452c3724c7399dddc73aabf | [
"x, y = polar_cartesian(1, 0)\nself.assertEqual(x, 1)\nself.assertEqual(y, 0)\nx, y = polar_cartesian(1, math.pi / 2)\nself.assertEqual(round(x, 4), 0)\nself.assertEqual(round(y, 4), 1)\nx, y = polar_cartesian(1, math.pi)\nself.assertEqual(round(x, 4), -1)\nself.assertEqual(round(y, 4), 0)\nx, y = polar_cartesian(1... | <|body_start_0|>
x, y = polar_cartesian(1, 0)
self.assertEqual(x, 1)
self.assertEqual(y, 0)
x, y = polar_cartesian(1, math.pi / 2)
self.assertEqual(round(x, 4), 0)
self.assertEqual(round(y, 4), 1)
x, y = polar_cartesian(1, math.pi)
self.assertEqual(round(x... | Class to test module. | TestCoordinateConversion | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCoordinateConversion:
"""Class to test module."""
def test_polar_cartesian(self):
"""Test method for polar to cartesioan conversion."""
<|body_0|>
def test_cartesian_polar(self):
"""Test method for cartesian to polar conversion."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_012307 | 3,712 | no_license | [
{
"docstring": "Test method for polar to cartesioan conversion.",
"name": "test_polar_cartesian",
"signature": "def test_polar_cartesian(self)"
},
{
"docstring": "Test method for cartesian to polar conversion.",
"name": "test_cartesian_polar",
"signature": "def test_cartesian_polar(self)... | 2 | null | Implement the Python class `TestCoordinateConversion` described below.
Class description:
Class to test module.
Method signatures and docstrings:
- def test_polar_cartesian(self): Test method for polar to cartesioan conversion.
- def test_cartesian_polar(self): Test method for cartesian to polar conversion. | Implement the Python class `TestCoordinateConversion` described below.
Class description:
Class to test module.
Method signatures and docstrings:
- def test_polar_cartesian(self): Test method for polar to cartesioan conversion.
- def test_cartesian_polar(self): Test method for cartesian to polar conversion.
<|skelet... | 848a3143e1f808d919a48b527637a96fe0aea47d | <|skeleton|>
class TestCoordinateConversion:
"""Class to test module."""
def test_polar_cartesian(self):
"""Test method for polar to cartesioan conversion."""
<|body_0|>
def test_cartesian_polar(self):
"""Test method for cartesian to polar conversion."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCoordinateConversion:
"""Class to test module."""
def test_polar_cartesian(self):
"""Test method for polar to cartesioan conversion."""
x, y = polar_cartesian(1, 0)
self.assertEqual(x, 1)
self.assertEqual(y, 0)
x, y = polar_cartesian(1, math.pi / 2)
sel... | the_stack_v2_python_sparse | blog/kode/part6/tools.py | christopheblomsen/ast2000 | train | 0 |
3ee4b072e1c54fc37139b7cc3c02b779dfe2248f | [
"super().__init__(coordinator=coordinator)\nself.entity_description = entity_description\nself.entity_id = f'{SENSOR_DOMAIN}.{entity_description.key}'\nself._attr_unique_id = f'{entry_id}_{entity_description.key}'\nself._attr_device_info = DeviceInfo(entry_type=DeviceEntryType.SERVICE, identifiers={(DOMAIN, entry_i... | <|body_start_0|>
super().__init__(coordinator=coordinator)
self.entity_description = entity_description
self.entity_id = f'{SENSOR_DOMAIN}.{entity_description.key}'
self._attr_unique_id = f'{entry_id}_{entity_description.key}'
self._attr_device_info = DeviceInfo(entry_type=Device... | Defines a Forecast.Solar sensor. | ForecastSolarSensorEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForecastSolarSensorEntity:
"""Defines a Forecast.Solar sensor."""
def __init__(self, *, entry_id: str, coordinator: ForecastSolarDataUpdateCoordinator, entity_description: ForecastSolarSensorEntityDescription) -> None:
"""Initialize Forecast.Solar sensor."""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_012308 | 7,317 | permissive | [
{
"docstring": "Initialize Forecast.Solar sensor.",
"name": "__init__",
"signature": "def __init__(self, *, entry_id: str, coordinator: ForecastSolarDataUpdateCoordinator, entity_description: ForecastSolarSensorEntityDescription) -> None"
},
{
"docstring": "Return the state of the sensor.",
... | 2 | stack_v2_sparse_classes_30k_train_012302 | Implement the Python class `ForecastSolarSensorEntity` described below.
Class description:
Defines a Forecast.Solar sensor.
Method signatures and docstrings:
- def __init__(self, *, entry_id: str, coordinator: ForecastSolarDataUpdateCoordinator, entity_description: ForecastSolarSensorEntityDescription) -> None: Initi... | Implement the Python class `ForecastSolarSensorEntity` described below.
Class description:
Defines a Forecast.Solar sensor.
Method signatures and docstrings:
- def __init__(self, *, entry_id: str, coordinator: ForecastSolarDataUpdateCoordinator, entity_description: ForecastSolarSensorEntityDescription) -> None: Initi... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ForecastSolarSensorEntity:
"""Defines a Forecast.Solar sensor."""
def __init__(self, *, entry_id: str, coordinator: ForecastSolarDataUpdateCoordinator, entity_description: ForecastSolarSensorEntityDescription) -> None:
"""Initialize Forecast.Solar sensor."""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ForecastSolarSensorEntity:
"""Defines a Forecast.Solar sensor."""
def __init__(self, *, entry_id: str, coordinator: ForecastSolarDataUpdateCoordinator, entity_description: ForecastSolarSensorEntityDescription) -> None:
"""Initialize Forecast.Solar sensor."""
super().__init__(coordinator=c... | the_stack_v2_python_sparse | homeassistant/components/forecast_solar/sensor.py | home-assistant/core | train | 35,501 |
56c71e68686c9e9c9d2f087a2752c95546385dff | [
"product_total_cost_price = TradeComplete.objects.filter(commission_buy_user_id_id=user_id, c_type=2, created_date__lte=the_date).aggregate(total=Coalesce(Sum('total'), 0.0))['total']\nsales_amount = TradeComplete.objects.filter(commission_sale_user_id_id=user_id, created_date__lte=the_date).aggregate(total=Coalesc... | <|body_start_0|>
product_total_cost_price = TradeComplete.objects.filter(commission_buy_user_id_id=user_id, c_type=2, created_date__lte=the_date).aggregate(total=Coalesce(Sum('total'), 0.0))['total']
sales_amount = TradeComplete.objects.filter(commission_sale_user_id_id=user_id, created_date__lte=the_da... | AssetsUtil | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssetsUtil:
def get_profit_up_to_thd_day(user_id, the_date):
"""返回指定用户截至某天的累计收益 :param user_id: :param the_date:截至此日期 :return: 累计收益"""
<|body_0|>
def get_profit(user_id):
"""返回指定用户累计收益(截至昨天)、昨天收益 :param user_id: :return: (累计收益, 昨天收益)"""
<|body_1|>
def ge... | stack_v2_sparse_classes_36k_train_012309 | 5,250 | no_license | [
{
"docstring": "返回指定用户截至某天的累计收益 :param user_id: :param the_date:截至此日期 :return: 累计收益",
"name": "get_profit_up_to_thd_day",
"signature": "def get_profit_up_to_thd_day(user_id, the_date)"
},
{
"docstring": "返回指定用户累计收益(截至昨天)、昨天收益 :param user_id: :return: (累计收益, 昨天收益)",
"name": "get_profit",
... | 3 | null | Implement the Python class `AssetsUtil` described below.
Class description:
Implement the AssetsUtil class.
Method signatures and docstrings:
- def get_profit_up_to_thd_day(user_id, the_date): 返回指定用户截至某天的累计收益 :param user_id: :param the_date:截至此日期 :return: 累计收益
- def get_profit(user_id): 返回指定用户累计收益(截至昨天)、昨天收益 :param u... | Implement the Python class `AssetsUtil` described below.
Class description:
Implement the AssetsUtil class.
Method signatures and docstrings:
- def get_profit_up_to_thd_day(user_id, the_date): 返回指定用户截至某天的累计收益 :param user_id: :param the_date:截至此日期 :return: 累计收益
- def get_profit(user_id): 返回指定用户累计收益(截至昨天)、昨天收益 :param u... | 3d6198c2a1abc97fa9286408f52c1f5153883b7a | <|skeleton|>
class AssetsUtil:
def get_profit_up_to_thd_day(user_id, the_date):
"""返回指定用户截至某天的累计收益 :param user_id: :param the_date:截至此日期 :return: 累计收益"""
<|body_0|>
def get_profit(user_id):
"""返回指定用户累计收益(截至昨天)、昨天收益 :param user_id: :return: (累计收益, 昨天收益)"""
<|body_1|>
def ge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssetsUtil:
def get_profit_up_to_thd_day(user_id, the_date):
"""返回指定用户截至某天的累计收益 :param user_id: :param the_date:截至此日期 :return: 累计收益"""
product_total_cost_price = TradeComplete.objects.filter(commission_buy_user_id_id=user_id, c_type=2, created_date__lte=the_date).aggregate(total=Coalesce(Sum('... | the_stack_v2_python_sparse | stars/apps/customer/assets/utils.py | lisongwei15931/stars | train | 0 | |
04c56c2e9e61d645f540c027a4e0742fdc9093a6 | [
"super().__init__(client, api_object_id=api_object_id, api_object_prefix=self.__API_OBJECT_PREFIX, retry_opts=retry_opts, cache_opts=cache_opts)\nself.description = None\nself.locked_by = None\nself.created = None\nself.management_ip = None\nself.memory_count = None\nself.cpu_topology = None\nself.ipmi_ip = None\ns... | <|body_start_0|>
super().__init__(client, api_object_id=api_object_id, api_object_prefix=self.__API_OBJECT_PREFIX, retry_opts=retry_opts, cache_opts=cache_opts)
self.description = None
self.locked_by = None
self.created = None
self.management_ip = None
self.memory_count =... | Veil node entity. Attributes: client: https_client instance. api_object_id: VeiL node id(uuid). cluster_id: VeiL cluster id(uuid) for extra filtering. | VeilNode | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VeilNode:
"""Veil node entity. Attributes: client: https_client instance. api_object_id: VeiL node id(uuid). cluster_id: VeiL cluster id(uuid) for extra filtering."""
def __init__(self, client, api_object_id: Optional[str]=None, cluster_id: Optional[str]=None, resource_pool_id: Optional[str]... | stack_v2_sparse_classes_36k_train_012310 | 2,870 | permissive | [
{
"docstring": "Please see help(VeilNode) for more info.",
"name": "__init__",
"signature": "def __init__(self, client, api_object_id: Optional[str]=None, cluster_id: Optional[str]=None, resource_pool_id: Optional[str]=None, retry_opts: Optional[VeilRetryConfiguration]=None, cache_opts: Optional[VeilCac... | 4 | stack_v2_sparse_classes_30k_train_009993 | Implement the Python class `VeilNode` described below.
Class description:
Veil node entity. Attributes: client: https_client instance. api_object_id: VeiL node id(uuid). cluster_id: VeiL cluster id(uuid) for extra filtering.
Method signatures and docstrings:
- def __init__(self, client, api_object_id: Optional[str]=N... | Implement the Python class `VeilNode` described below.
Class description:
Veil node entity. Attributes: client: https_client instance. api_object_id: VeiL node id(uuid). cluster_id: VeiL cluster id(uuid) for extra filtering.
Method signatures and docstrings:
- def __init__(self, client, api_object_id: Optional[str]=N... | 65c7adf3280217c9f9523a7dd7664d7d4d3f46fe | <|skeleton|>
class VeilNode:
"""Veil node entity. Attributes: client: https_client instance. api_object_id: VeiL node id(uuid). cluster_id: VeiL cluster id(uuid) for extra filtering."""
def __init__(self, client, api_object_id: Optional[str]=None, cluster_id: Optional[str]=None, resource_pool_id: Optional[str]... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VeilNode:
"""Veil node entity. Attributes: client: https_client instance. api_object_id: VeiL node id(uuid). cluster_id: VeiL cluster id(uuid) for extra filtering."""
def __init__(self, client, api_object_id: Optional[str]=None, cluster_id: Optional[str]=None, resource_pool_id: Optional[str]=None, retry_... | the_stack_v2_python_sparse | veil_api_client/api_objects/node.py | devalv/veil-api-client | train | 1 |
1c0665372e79a83ee7c08b36d35b7471595eecfd | [
"try:\n topic = topic_fetchers.get_topic_from_model(topic_model)\n topic.validate()\nexcept Exception as e:\n logging.exception(e)\n return result.Err((topic_id, e))\nreturn result.Ok((topic_id, topic))",
"subtopic_version = topic_model.subtopic_schema_version\nif subtopic_version < feconf.CURRENT_SUB... | <|body_start_0|>
try:
topic = topic_fetchers.get_topic_from_model(topic_model)
topic.validate()
except Exception as e:
logging.exception(e)
return result.Err((topic_id, e))
return result.Ok((topic_id, topic))
<|end_body_0|>
<|body_start_1|>
... | Transform that gets all Topic models, performs migration and filters any error results. | MigrateTopicModels | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MigrateTopicModels:
"""Transform that gets all Topic models, performs migration and filters any error results."""
def _migrate_topic(topic_id: str, topic_model: topic_models.TopicModel) -> result.Result[Tuple[str, topic_domain.Topic], Tuple[str, Exception]]:
"""Migrates topic and tra... | stack_v2_sparse_classes_36k_train_012311 | 13,939 | permissive | [
{
"docstring": "Migrates topic and transform topic model into topic object. Args: topic_id: str. The id of the topic. topic_model: TopicModel. The topic model to migrate. Returns: Result((str, Topic), (str, Exception)). Result containing tuple that consist of topic ID and either topic object or Exception. Topic... | 3 | null | Implement the Python class `MigrateTopicModels` described below.
Class description:
Transform that gets all Topic models, performs migration and filters any error results.
Method signatures and docstrings:
- def _migrate_topic(topic_id: str, topic_model: topic_models.TopicModel) -> result.Result[Tuple[str, topic_doma... | Implement the Python class `MigrateTopicModels` described below.
Class description:
Transform that gets all Topic models, performs migration and filters any error results.
Method signatures and docstrings:
- def _migrate_topic(topic_id: str, topic_model: topic_models.TopicModel) -> result.Result[Tuple[str, topic_doma... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class MigrateTopicModels:
"""Transform that gets all Topic models, performs migration and filters any error results."""
def _migrate_topic(topic_id: str, topic_model: topic_models.TopicModel) -> result.Result[Tuple[str, topic_domain.Topic], Tuple[str, Exception]]:
"""Migrates topic and tra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MigrateTopicModels:
"""Transform that gets all Topic models, performs migration and filters any error results."""
def _migrate_topic(topic_id: str, topic_model: topic_models.TopicModel) -> result.Result[Tuple[str, topic_domain.Topic], Tuple[str, Exception]]:
"""Migrates topic and transform topic ... | the_stack_v2_python_sparse | core/jobs/batch_jobs/topic_migration_jobs.py | oppia/oppia | train | 6,172 |
c2c2fa39d93dae474258a44ec5daa0c3725a55ad | [
"self.amount = amount\nself.currency_code = currency_code\nself.formatted_price = formatted_price",
"if dictionary is None:\n return None\nformatted_price = dictionary.get('FormattedPrice')\namount = dictionary.get('Amount')\ncurrency_code = dictionary.get('CurrencyCode')\nreturn cls(formatted_price, amount, c... | <|body_start_0|>
self.amount = amount
self.currency_code = currency_code
self.formatted_price = formatted_price
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
formatted_price = dictionary.get('FormattedPrice')
amount = dictionary.get('Amou... | Implementation of the 'Price' model. TODO: type model description here. Attributes: amount (int): TODO: type description here. currency_code (string): TODO: type description here. formatted_price (string): TODO: type description here. | Price | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Price:
"""Implementation of the 'Price' model. TODO: type model description here. Attributes: amount (int): TODO: type description here. currency_code (string): TODO: type description here. formatted_price (string): TODO: type description here."""
def __init__(self, formatted_price=None, amo... | stack_v2_sparse_classes_36k_train_012312 | 1,870 | permissive | [
{
"docstring": "Constructor for the Price class",
"name": "__init__",
"signature": "def __init__(self, formatted_price=None, amount=None, currency_code=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the ... | 2 | stack_v2_sparse_classes_30k_test_000587 | Implement the Python class `Price` described below.
Class description:
Implementation of the 'Price' model. TODO: type model description here. Attributes: amount (int): TODO: type description here. currency_code (string): TODO: type description here. formatted_price (string): TODO: type description here.
Method signa... | Implement the Python class `Price` described below.
Class description:
Implementation of the 'Price' model. TODO: type model description here. Attributes: amount (int): TODO: type description here. currency_code (string): TODO: type description here. formatted_price (string): TODO: type description here.
Method signa... | 26ea1019115a1de3b1b37a4b830525e164ac55ce | <|skeleton|>
class Price:
"""Implementation of the 'Price' model. TODO: type model description here. Attributes: amount (int): TODO: type description here. currency_code (string): TODO: type description here. formatted_price (string): TODO: type description here."""
def __init__(self, formatted_price=None, amo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Price:
"""Implementation of the 'Price' model. TODO: type model description here. Attributes: amount (int): TODO: type description here. currency_code (string): TODO: type description here. formatted_price (string): TODO: type description here."""
def __init__(self, formatted_price=None, amount=None, cur... | the_stack_v2_python_sparse | awsecommerceservice/models/price.py | nidaizamir/Test-PY | train | 0 |
8f45220716cfdf9575c2221252cdea69b86ef8c6 | [
"RAMSTKWorkView.__init__(self, controller, module='Function')\nself._lst_assess_labels[1].append(_(u'Total Mode Count:'))\nself._function_id = None\nself.txtModeCount = ramstk.RAMSTKEntry(width=125, editable=False, bold=True, tooltip=_(u'Displays the total number of failure modes associated with the selected Functi... | <|body_start_0|>
RAMSTKWorkView.__init__(self, controller, module='Function')
self._lst_assess_labels[1].append(_(u'Total Mode Count:'))
self._function_id = None
self.txtModeCount = ramstk.RAMSTKEntry(width=125, editable=False, bold=True, tooltip=_(u'Displays the total number of failure ... | Display Function attribute data in the RAMSTK Work Book. The Function Assessment Results view displays all the assessment results for the selected Function. The attributes of a Function Assessment Results View are: :ivar int _function_id: the ID of the Function currently being displayed. | AssessmentResults | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssessmentResults:
"""Display Function attribute data in the RAMSTK Work Book. The Function Assessment Results view displays all the assessment results for the selected Function. The attributes of a Function Assessment Results View are: :ivar int _function_id: the ID of the Function currently bei... | stack_v2_sparse_classes_36k_train_012313 | 16,082 | permissive | [
{
"docstring": "Initialize the Work View for the Function package. :param controller: the RAMSTK master data controller instance. :type controller: :class:`ramstk.RAMSTK.RAMSTK`",
"name": "__init__",
"signature": "def __init__(self, controller, **kwargs)"
},
{
"docstring": "Load the Function Ass... | 4 | stack_v2_sparse_classes_30k_train_020263 | Implement the Python class `AssessmentResults` described below.
Class description:
Display Function attribute data in the RAMSTK Work Book. The Function Assessment Results view displays all the assessment results for the selected Function. The attributes of a Function Assessment Results View are: :ivar int _function_i... | Implement the Python class `AssessmentResults` described below.
Class description:
Display Function attribute data in the RAMSTK Work Book. The Function Assessment Results view displays all the assessment results for the selected Function. The attributes of a Function Assessment Results View are: :ivar int _function_i... | 488ffed8b842399ddcae93007de6c6f1dda23d05 | <|skeleton|>
class AssessmentResults:
"""Display Function attribute data in the RAMSTK Work Book. The Function Assessment Results view displays all the assessment results for the selected Function. The attributes of a Function Assessment Results View are: :ivar int _function_id: the ID of the Function currently bei... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssessmentResults:
"""Display Function attribute data in the RAMSTK Work Book. The Function Assessment Results view displays all the assessment results for the selected Function. The attributes of a Function Assessment Results View are: :ivar int _function_id: the ID of the Function currently being displayed.... | the_stack_v2_python_sparse | src/ramstk/gui/gtk/workviews/Function.py | JmiXIII/ramstk | train | 0 |
c8dedbc240007f0f1b271698e2a85448f1f93533 | [
"candidate = math.gcd(len(str1), len(str2))\nif str1 + str2 != str2 + str1:\n return ''\nreturn str1[:candidate]",
"candidate = math.gcd(len(str1), len(str2))\nif len(str1) // candidate * str1[:candidate] == str1 and len(str2) // candidate * str1[:candidate] == str2:\n return str1[:candidate]\nreturn ''"
] | <|body_start_0|>
candidate = math.gcd(len(str1), len(str2))
if str1 + str2 != str2 + str1:
return ''
return str1[:candidate]
<|end_body_0|>
<|body_start_1|>
candidate = math.gcd(len(str1), len(str2))
if len(str1) // candidate * str1[:candidate] == str1 and len(str2) ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def gcdOfStrings(self, str1: str, str2: str) -> str:
"""执行用时 :40 ms, 在所有 Python3 提交中击败了44.21%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了7.48%的用户 数学法： 1、先计算出两个字符串最大公因子长度 2、如果两个字符串存在最大公因子T，str1=m*T,str2=n*T.必定满足str1 + str2 == str2 + str1 :param str1: :param str2: :return:"""
<|... | stack_v2_sparse_classes_36k_train_012314 | 2,028 | no_license | [
{
"docstring": "执行用时 :40 ms, 在所有 Python3 提交中击败了44.21%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了7.48%的用户 数学法： 1、先计算出两个字符串最大公因子长度 2、如果两个字符串存在最大公因子T，str1=m*T,str2=n*T.必定满足str1 + str2 == str2 + str1 :param str1: :param str2: :return:",
"name": "gcdOfStrings",
"signature": "def gcdOfStrings(self, str1: str, str2:... | 2 | stack_v2_sparse_classes_30k_train_013023 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def gcdOfStrings(self, str1: str, str2: str) -> str: 执行用时 :40 ms, 在所有 Python3 提交中击败了44.21%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了7.48%的用户 数学法： 1、先计算出两个字符串最大公因子长度 2、如果两个字符串存在最大公因子T，... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def gcdOfStrings(self, str1: str, str2: str) -> str: 执行用时 :40 ms, 在所有 Python3 提交中击败了44.21%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了7.48%的用户 数学法： 1、先计算出两个字符串最大公因子长度 2、如果两个字符串存在最大公因子T，... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def gcdOfStrings(self, str1: str, str2: str) -> str:
"""执行用时 :40 ms, 在所有 Python3 提交中击败了44.21%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了7.48%的用户 数学法： 1、先计算出两个字符串最大公因子长度 2、如果两个字符串存在最大公因子T，str1=m*T,str2=n*T.必定满足str1 + str2 == str2 + str1 :param str1: :param str2: :return:"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def gcdOfStrings(self, str1: str, str2: str) -> str:
"""执行用时 :40 ms, 在所有 Python3 提交中击败了44.21%的用户 内存消耗 :13.5 MB, 在所有 Python3 提交中击败了7.48%的用户 数学法： 1、先计算出两个字符串最大公因子长度 2、如果两个字符串存在最大公因子T，str1=m*T,str2=n*T.必定满足str1 + str2 == str2 + str1 :param str1: :param str2: :return:"""
candidate = math... | the_stack_v2_python_sparse | LeetCode/1071. Greatest Common Divisor of Strings.py | yiming1012/MyLeetCode | train | 2 | |
1726098070ee974cf2eed92807f8c43476f44d65 | [
"name_to_features = mention_encoder_task.MentionEncoderTask.get_name_to_features(config)\nif config.apply_answer_mask:\n name_to_features['dense_answer_mask'] = tf.io.FixedLenFeature(config.model_config.encoder_config.max_length, tf.int64)\nreturn name_to_features",
"max_length = config.model_config.encoder_co... | <|body_start_0|>
name_to_features = mention_encoder_task.MentionEncoderTask.get_name_to_features(config)
if config.apply_answer_mask:
name_to_features['dense_answer_mask'] = tf.io.FixedLenFeature(config.model_config.encoder_config.max_length, tf.int64)
return name_to_features
<|end_b... | Abstract class for all entity-answer question answering tasks. | EntityQATask | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntityQATask:
"""Abstract class for all entity-answer question answering tasks."""
def get_name_to_features(config: ml_collections.ConfigDict) -> Dict[str, Any]:
"""Return feature dict for decoding purposes. See BaseTask."""
<|body_0|>
def make_preprocess_fn(config: ml_c... | stack_v2_sparse_classes_36k_train_012315 | 5,499 | permissive | [
{
"docstring": "Return feature dict for decoding purposes. See BaseTask.",
"name": "get_name_to_features",
"signature": "def get_name_to_features(config: ml_collections.ConfigDict) -> Dict[str, Any]"
},
{
"docstring": "Produces function to preprocess samples. See BaseTask. During preprocessing w... | 3 | null | Implement the Python class `EntityQATask` described below.
Class description:
Abstract class for all entity-answer question answering tasks.
Method signatures and docstrings:
- def get_name_to_features(config: ml_collections.ConfigDict) -> Dict[str, Any]: Return feature dict for decoding purposes. See BaseTask.
- def... | Implement the Python class `EntityQATask` described below.
Class description:
Abstract class for all entity-answer question answering tasks.
Method signatures and docstrings:
- def get_name_to_features(config: ml_collections.ConfigDict) -> Dict[str, Any]: Return feature dict for decoding purposes. See BaseTask.
- def... | ac9447064195e06de48cc91ff642f7fffa28ffe8 | <|skeleton|>
class EntityQATask:
"""Abstract class for all entity-answer question answering tasks."""
def get_name_to_features(config: ml_collections.ConfigDict) -> Dict[str, Any]:
"""Return feature dict for decoding purposes. See BaseTask."""
<|body_0|>
def make_preprocess_fn(config: ml_c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EntityQATask:
"""Abstract class for all entity-answer question answering tasks."""
def get_name_to_features(config: ml_collections.ConfigDict) -> Dict[str, Any]:
"""Return feature dict for decoding purposes. See BaseTask."""
name_to_features = mention_encoder_task.MentionEncoderTask.get_n... | the_stack_v2_python_sparse | language/mentionmemory/tasks/entity_qa_task.py | google-research/language | train | 1,567 |
2c1a39263c8aabf0ed5134fc355ffb55a65dfce9 | [
"log.trace('Getting the diff for users.')\nusers = await self.bot.api_client.get('bot/users')\ndb_users = {user_dict['id']: _User(roles=tuple(sorted(user_dict.pop('roles'))), **user_dict) for user_dict in users}\nguild_users = {member.id: _User(id=member.id, name=member.name, discriminator=int(member.discriminator)... | <|body_start_0|>
log.trace('Getting the diff for users.')
users = await self.bot.api_client.get('bot/users')
db_users = {user_dict['id']: _User(roles=tuple(sorted(user_dict.pop('roles'))), **user_dict) for user_dict in users}
guild_users = {member.id: _User(id=member.id, name=member.name... | Synchronise the database with users in the cache. | UserSyncer | [
"Python-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSyncer:
"""Synchronise the database with users in the cache."""
async def _get_diff(self, guild: Guild) -> _Diff:
"""Return the difference of users between the cache of `guild` and the database."""
<|body_0|>
async def _sync(self, diff: _Diff) -> None:
"""Syn... | stack_v2_sparse_classes_36k_train_012316 | 14,281 | permissive | [
{
"docstring": "Return the difference of users between the cache of `guild` and the database.",
"name": "_get_diff",
"signature": "async def _get_diff(self, guild: Guild) -> _Diff"
},
{
"docstring": "Synchronise the database with the user cache of `guild`.",
"name": "_sync",
"signature":... | 2 | null | Implement the Python class `UserSyncer` described below.
Class description:
Synchronise the database with users in the cache.
Method signatures and docstrings:
- async def _get_diff(self, guild: Guild) -> _Diff: Return the difference of users between the cache of `guild` and the database.
- async def _sync(self, diff... | Implement the Python class `UserSyncer` described below.
Class description:
Synchronise the database with users in the cache.
Method signatures and docstrings:
- async def _get_diff(self, guild: Guild) -> _Diff: Return the difference of users between the cache of `guild` and the database.
- async def _sync(self, diff... | 232cc68b0a0ef210027beacb9b4f50ffeeaddd00 | <|skeleton|>
class UserSyncer:
"""Synchronise the database with users in the cache."""
async def _get_diff(self, guild: Guild) -> _Diff:
"""Return the difference of users between the cache of `guild` and the database."""
<|body_0|>
async def _sync(self, diff: _Diff) -> None:
"""Syn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserSyncer:
"""Synchronise the database with users in the cache."""
async def _get_diff(self, guild: Guild) -> _Diff:
"""Return the difference of users between the cache of `guild` and the database."""
log.trace('Getting the diff for users.')
users = await self.bot.api_client.get(... | the_stack_v2_python_sparse | bot/cogs/sync/syncers.py | pormes/bot | train | 2 |
5f179d2316f534c147804fae97e19d3704c0ea27 | [
"if not self.created_date:\n self.created_date = datetime.utcnow()\nself.modified_date = datetime.utcnow()\nsuper(Message, self).save(*args, **kwargs)",
"logging.info('getting %s %s for Message %s (%s)' % (asset_class, mime_type, self, self.pk))\nif isinstance(asset_class, AssetClass):\n return self.assets.... | <|body_start_0|>
if not self.created_date:
self.created_date = datetime.utcnow()
self.modified_date = datetime.utcnow()
super(Message, self).save(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
logging.info('getting %s %s for Message %s (%s)' % (asset_class, mime_type, self... | Message | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
def save(self, *args, **kwargs):
"""Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time"""
<|body_0|>
def get_asset(self, asset_class, mime_type)... | stack_v2_sparse_classes_36k_train_012317 | 23,088 | no_license | [
{
"docstring": "Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time",
"name": "save",
"signature": "def save(self, *args, **kwargs)"
},
{
"docstring": "Get an asset associated... | 2 | stack_v2_sparse_classes_30k_train_020643 | Implement the Python class `Message` described below.
Class description:
Implement the Message class.
Method signatures and docstrings:
- def save(self, *args, **kwargs): Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and loca... | Implement the Python class `Message` described below.
Class description:
Implement the Message class.
Method signatures and docstrings:
- def save(self, *args, **kwargs): Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and loca... | e5a0d666ff11c812518cecb0f57257c64ca5cdfd | <|skeleton|>
class Message:
def save(self, *args, **kwargs):
"""Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time"""
<|body_0|>
def get_asset(self, asset_class, mime_type)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Message:
def save(self, *args, **kwargs):
"""Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time"""
if not self.created_date:
self.created_date = datetime.utcnow... | the_stack_v2_python_sparse | donomo_archive/lib/donomo/archive/models.py | alexissmirnov/donomo | train | 0 | |
42eaa465a6e4d010e0e90eab0a216a3628419bba | [
"self.radius = radius\nself.max_neighbors = int(max_neighbors)\nself.step = step",
"from pymatgen import Structure\ns = Structure.from_dict(struct)\nfeatures = self._get_structure_graph_features(s)\nfeatures = np.array(features)\nreturn features",
"atom_features = np.array([site.specie.Z for site in struct], dt... | <|body_start_0|>
self.radius = radius
self.max_neighbors = int(max_neighbors)
self.step = step
<|end_body_0|>
<|body_start_1|>
from pymatgen import Structure
s = Structure.from_dict(struct)
features = self._get_structure_graph_features(s)
features = np.array(feat... | Calculate structure graph features for crystals. Based on the implementation in Crystal Graph Convolutional Neural Networks (CGCNN). The method constructs a crystal graph representation including atom features (atomic numbers) and bond features (neighbor distances). Neighbors are determined by searching in a sphere aro... | StructureGraphFeaturizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StructureGraphFeaturizer:
"""Calculate structure graph features for crystals. Based on the implementation in Crystal Graph Convolutional Neural Networks (CGCNN). The method constructs a crystal graph representation including atom features (atomic numbers) and bond features (neighbor distances). N... | stack_v2_sparse_classes_36k_train_012318 | 8,595 | permissive | [
{
"docstring": "Parameters ---------- radius : float (default 8.0) Radius of sphere for finding neighbors of atoms in unit cell. max_neighbors : int (default 12) Maximum number of neighbors to consider when constructing graph. step : float (default 0.2) Step size for Gaussian filter.",
"name": "__init__",
... | 4 | stack_v2_sparse_classes_30k_train_007475 | Implement the Python class `StructureGraphFeaturizer` described below.
Class description:
Calculate structure graph features for crystals. Based on the implementation in Crystal Graph Convolutional Neural Networks (CGCNN). The method constructs a crystal graph representation including atom features (atomic numbers) an... | Implement the Python class `StructureGraphFeaturizer` described below.
Class description:
Calculate structure graph features for crystals. Based on the implementation in Crystal Graph Convolutional Neural Networks (CGCNN). The method constructs a crystal graph representation including atom features (atomic numbers) an... | c9eaf1b64b6969cec692893288ca92439f9b6dda | <|skeleton|>
class StructureGraphFeaturizer:
"""Calculate structure graph features for crystals. Based on the implementation in Crystal Graph Convolutional Neural Networks (CGCNN). The method constructs a crystal graph representation including atom features (atomic numbers) and bond features (neighbor distances). N... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StructureGraphFeaturizer:
"""Calculate structure graph features for crystals. Based on the implementation in Crystal Graph Convolutional Neural Networks (CGCNN). The method constructs a crystal graph representation including atom features (atomic numbers) and bond features (neighbor distances). Neighbors are ... | the_stack_v2_python_sparse | deepchem/feat/materials_featurizers.py | borisdayma/deepchem | train | 1 |
f7bec886dda157a2574e0bcd9887e4fd6eb2662e | [
"field = model._meta.get_field(field_name)\nif isinstance(field, ForeignKey):\n fk_model = field.rel.to\n if fk_model.__name__ in FK_DISPLAY_FIELDS:\n report_field = FK_DISPLAY_FIELDS[fk_model.__name__]\n if fk_model == User:\n path = '%s__' % field_name\n else:\n pa... | <|body_start_0|>
field = model._meta.get_field(field_name)
if isinstance(field, ForeignKey):
fk_model = field.rel.to
if fk_model.__name__ in FK_DISPLAY_FIELDS:
report_field = FK_DISPLAY_FIELDS[fk_model.__name__]
if fk_model == User:
... | Command | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
def add_field_to_report(self, report, model, field_name, allow_recursion=True):
"""Adds the given field to the report. Includes logic to follow foreign keys in order to display their text value properly."""
<|body_0|>
def add_display_fields_to_report(self, report, m... | stack_v2_sparse_classes_36k_train_012319 | 6,409 | permissive | [
{
"docstring": "Adds the given field to the report. Includes logic to follow foreign keys in order to display their text value properly.",
"name": "add_field_to_report",
"signature": "def add_field_to_report(self, report, model, field_name, allow_recursion=True)"
},
{
"docstring": "Adds all fiel... | 4 | stack_v2_sparse_classes_30k_train_017346 | Implement the Python class `Command` described below.
Class description:
Implement the Command class.
Method signatures and docstrings:
- def add_field_to_report(self, report, model, field_name, allow_recursion=True): Adds the given field to the report. Includes logic to follow foreign keys in order to display their ... | Implement the Python class `Command` described below.
Class description:
Implement the Command class.
Method signatures and docstrings:
- def add_field_to_report(self, report, model, field_name, allow_recursion=True): Adds the given field to the report. Includes logic to follow foreign keys in order to display their ... | f0ed6ad723d70fae4737e517d4dca07b2aef176a | <|skeleton|>
class Command:
def add_field_to_report(self, report, model, field_name, allow_recursion=True):
"""Adds the given field to the report. Includes logic to follow foreign keys in order to display their text value properly."""
<|body_0|>
def add_display_fields_to_report(self, report, m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Command:
def add_field_to_report(self, report, model, field_name, allow_recursion=True):
"""Adds the given field to the report. Includes logic to follow foreign keys in order to display their text value properly."""
field = model._meta.get_field(field_name)
if isinstance(field, Foreign... | the_stack_v2_python_sparse | ovpr_atp/core/management/commands/set_up_reports.py | pawanacharya1979/Awdportal | train | 0 | |
220e44708c0c78b79b996070a4bcad6bf46a0164 | [
"num = len(s)\nsum = 0\nfor i in range(num):\n chr = s[i]\n sum += (ord(chr) - 64) * pow(26, num - 1 - i)\nreturn sum",
"sum = 0\nfor chr in list(s):\n x = ord(chr) - 64\n sum = sum * 26 + x\nreturn sum"
] | <|body_start_0|>
num = len(s)
sum = 0
for i in range(num):
chr = s[i]
sum += (ord(chr) - 64) * pow(26, num - 1 - i)
return sum
<|end_body_0|>
<|body_start_1|>
sum = 0
for chr in list(s):
x = ord(chr) - 64
sum = sum * 26 + x... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def titleToNumber(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def titleToNumber2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
num = len(s)
sum = 0
for i in range(num):
... | stack_v2_sparse_classes_36k_train_012320 | 675 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "titleToNumber",
"signature": "def titleToNumber(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "titleToNumber2",
"signature": "def titleToNumber2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def titleToNumber(self, s): :type s: str :rtype: int
- def titleToNumber2(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 titleToNumber(self, s): :type s: str :rtype: int
- def titleToNumber2(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def titleToNumber(self, s):
... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def titleToNumber(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def titleToNumber2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def titleToNumber(self, s):
""":type s: str :rtype: int"""
num = len(s)
sum = 0
for i in range(num):
chr = s[i]
sum += (ord(chr) - 64) * pow(26, num - 1 - i)
return sum
def titleToNumber2(self, s):
""":type s: str :rtype: i... | the_stack_v2_python_sparse | 171. Excel Sheet Column Number/sheet.py | Macielyoung/LeetCode | train | 1 | |
699b6d59a29ed093e53631af4003f3164b2a9a61 | [
"super(MyConv2d, self).__init__()\nself.gpu = 'cuda:0'\nself.kernel = nn.Parameter(kernel, requires_grad=False)\nself.mode = mode\nself.stride = stride\nif padding == 0:\n size_padding = int((kernel[0, 0].size(0) - 1) / 2)\nelse:\n size_padding = padding\nif pad_type == 'replicate':\n self.padding = nn.Rep... | <|body_start_0|>
super(MyConv2d, self).__init__()
self.gpu = 'cuda:0'
self.kernel = nn.Parameter(kernel, requires_grad=False)
self.mode = mode
self.stride = stride
if padding == 0:
size_padding = int((kernel[0, 0].size(0) - 1) / 2)
else:
si... | Performs circular convolution on images with a constant filter. Attributes ---------- kernel (torch.cuda.FloatTensor): size c*c*h*w filter mode (str): 'single' or 'batch' stride (int): dilation factor padding : instance of CircularPadding or torch.nn.ReplicationPad2d | MyConv2d | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyConv2d:
"""Performs circular convolution on images with a constant filter. Attributes ---------- kernel (torch.cuda.FloatTensor): size c*c*h*w filter mode (str): 'single' or 'batch' stride (int): dilation factor padding : instance of CircularPadding or torch.nn.ReplicationPad2d"""
def __in... | stack_v2_sparse_classes_36k_train_012321 | 17,849 | no_license | [
{
"docstring": "Parameters ---------- gpu (str): gpu id kernel (torch.FloatTensor): convolution filter mode (str): indicates if the input is a single image of a batch of images pad_type (str): padding type (default is 'circular') padding (int): padding size (default is 0) stride (int): dilation factor (default ... | 2 | stack_v2_sparse_classes_30k_train_017751 | Implement the Python class `MyConv2d` described below.
Class description:
Performs circular convolution on images with a constant filter. Attributes ---------- kernel (torch.cuda.FloatTensor): size c*c*h*w filter mode (str): 'single' or 'batch' stride (int): dilation factor padding : instance of CircularPadding or tor... | Implement the Python class `MyConv2d` described below.
Class description:
Performs circular convolution on images with a constant filter. Attributes ---------- kernel (torch.cuda.FloatTensor): size c*c*h*w filter mode (str): 'single' or 'batch' stride (int): dilation factor padding : instance of CircularPadding or tor... | 6c4182add8135830c5e55e239b63cf65ee385ba8 | <|skeleton|>
class MyConv2d:
"""Performs circular convolution on images with a constant filter. Attributes ---------- kernel (torch.cuda.FloatTensor): size c*c*h*w filter mode (str): 'single' or 'batch' stride (int): dilation factor padding : instance of CircularPadding or torch.nn.ReplicationPad2d"""
def __in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyConv2d:
"""Performs circular convolution on images with a constant filter. Attributes ---------- kernel (torch.cuda.FloatTensor): size c*c*h*w filter mode (str): 'single' or 'batch' stride (int): dilation factor padding : instance of CircularPadding or torch.nn.ReplicationPad2d"""
def __init__(self, ke... | the_stack_v2_python_sparse | OLD/Copy/modules.py | ceciledellavalle/phd | train | 1 |
ba2e6254bf560d2d9a1c38f9237a0e26b096551f | [
"ugrid_filename = os.path.join(PKG_PATH, 'converters', 'aflr', 'ugrid', 'models', 'two_blade_wake_sym_extended.surf')\nlog = SimpleLogger(level='warning')\ntest = SurfGui()\ntest.log = log\ntest.on_load_geometry(ugrid_filename, geometry_format='surf', raise_error=True)",
"log = SimpleLogger(level='error')\nMODEL_... | <|body_start_0|>
ugrid_filename = os.path.join(PKG_PATH, 'converters', 'aflr', 'ugrid', 'models', 'two_blade_wake_sym_extended.surf')
log = SimpleLogger(level='warning')
test = SurfGui()
test.log = log
test.on_load_geometry(ugrid_filename, geometry_format='surf', raise_error=True... | defines *.surf tests | TestSurfGui | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSurfGui:
"""defines *.surf tests"""
def test_surf_gui_01(self):
"""tests two_blade_wake_sym_extended.surf"""
<|body_0|>
def test_surf_01(self):
"""tests two_blade_wake_sym_extended.surf"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ugrid_f... | stack_v2_sparse_classes_36k_train_012322 | 4,370 | no_license | [
{
"docstring": "tests two_blade_wake_sym_extended.surf",
"name": "test_surf_gui_01",
"signature": "def test_surf_gui_01(self)"
},
{
"docstring": "tests two_blade_wake_sym_extended.surf",
"name": "test_surf_01",
"signature": "def test_surf_01(self)"
}
] | 2 | null | Implement the Python class `TestSurfGui` described below.
Class description:
defines *.surf tests
Method signatures and docstrings:
- def test_surf_gui_01(self): tests two_blade_wake_sym_extended.surf
- def test_surf_01(self): tests two_blade_wake_sym_extended.surf | Implement the Python class `TestSurfGui` described below.
Class description:
defines *.surf tests
Method signatures and docstrings:
- def test_surf_gui_01(self): tests two_blade_wake_sym_extended.surf
- def test_surf_01(self): tests two_blade_wake_sym_extended.surf
<|skeleton|>
class TestSurfGui:
"""defines *.su... | cc596e637b53cf0a997f92e0e09f43222960052c | <|skeleton|>
class TestSurfGui:
"""defines *.surf tests"""
def test_surf_gui_01(self):
"""tests two_blade_wake_sym_extended.surf"""
<|body_0|>
def test_surf_01(self):
"""tests two_blade_wake_sym_extended.surf"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSurfGui:
"""defines *.surf tests"""
def test_surf_gui_01(self):
"""tests two_blade_wake_sym_extended.surf"""
ugrid_filename = os.path.join(PKG_PATH, 'converters', 'aflr', 'ugrid', 'models', 'two_blade_wake_sym_extended.surf')
log = SimpleLogger(level='warning')
test = ... | the_stack_v2_python_sparse | pyNastran/converters/aflr/surf/test_surf_gui.py | lnderuiter/pyNastran | train | 0 |
f85f4ce87c4a43d8679cf531f43382f6ba565849 | [
"if len(nums) == 0:\n return 0\nlens_value_list = list()\nlens_value_list.append(nums[0])\nfor i in range(1, len(nums)):\n index_just_less = self.binary_search_just_less(lens_value_list, nums[i])\n if index_just_less + 1 > len(lens_value_list) - 1:\n lens_value_list.append(nums[i])\n elif lens_va... | <|body_start_0|>
if len(nums) == 0:
return 0
lens_value_list = list()
lens_value_list.append(nums[0])
for i in range(1, len(nums)):
index_just_less = self.binary_search_just_less(lens_value_list, nums[i])
if index_just_less + 1 > len(lens_value_list) -... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def binary_search_just_less(self, arr, target, begin=None, end=None):
"""找到arr中小于等于target的最大元素位置 :param arr: :param target: :param begin: :param end: :return:"""
<|body_... | stack_v2_sparse_classes_36k_train_012323 | 1,717 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
},
{
"docstring": "找到arr中小于等于target的最大元素位置 :param arr: :param target: :param begin: :param end: :return:",
"name": "binary_search_just_less",
"signature": "def binary_sea... | 2 | stack_v2_sparse_classes_30k_train_012026 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def binary_search_just_less(self, arr, target, begin=None, end=None): 找到arr中小于等于target的最大元素位置 :param arr: :param ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def binary_search_just_less(self, arr, target, begin=None, end=None): 找到arr中小于等于target的最大元素位置 :param arr: :param ... | 6ddba1f3b86c40639a8203cbc3373d52301c1b1f | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def binary_search_just_less(self, arr, target, begin=None, end=None):
"""找到arr中小于等于target的最大元素位置 :param arr: :param target: :param begin: :param end: :return:"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
if len(nums) == 0:
return 0
lens_value_list = list()
lens_value_list.append(nums[0])
for i in range(1, len(nums)):
index_just_less = self.binary_search_just_less(lens_... | the_stack_v2_python_sparse | algorithms/python/leetcode/LongestIncreasingSubsequence.py | ytjia/leetcode | train | 0 | |
fe7ce80200d059705407185c30f706d57a15c7b0 | [
"if num == 0:\n return [0]\nres = [0, 1]\nn = int(math.log2(num))\nfor i in range(0, n - 1):\n last = res[-2 ** i:]\n res.extend(last)\n res.extend([k + 1 for k in last])\nif len(res) < num + 1:\n last = res[-2 ** (n - 1):]\n last += [k + 1 for k in last]\n res += last[:num + 1 - len(res)]\nret... | <|body_start_0|>
if num == 0:
return [0]
res = [0, 1]
n = int(math.log2(num))
for i in range(0, n - 1):
last = res[-2 ** i:]
res.extend(last)
res.extend([k + 1 for k in last])
if len(res) < num + 1:
last = res[-2 ** (n -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countBitsDP(self, num):
""":type num: int :rtype: List[int]"""
<|body_0|>
def countBits(self, num):
""":type num: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if num == 0:
return [0]
res = [... | stack_v2_sparse_classes_36k_train_012324 | 1,640 | no_license | [
{
"docstring": ":type num: int :rtype: List[int]",
"name": "countBitsDP",
"signature": "def countBitsDP(self, num)"
},
{
"docstring": ":type num: int :rtype: List[int]",
"name": "countBits",
"signature": "def countBits(self, num)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBitsDP(self, num): :type num: int :rtype: List[int]
- def countBits(self, num): :type num: int :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countBitsDP(self, num): :type num: int :rtype: List[int]
- def countBits(self, num): :type num: int :rtype: List[int]
<|skeleton|>
class Solution:
def countBitsDP(self,... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def countBitsDP(self, num):
""":type num: int :rtype: List[int]"""
<|body_0|>
def countBits(self, num):
""":type num: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countBitsDP(self, num):
""":type num: int :rtype: List[int]"""
if num == 0:
return [0]
res = [0, 1]
n = int(math.log2(num))
for i in range(0, n - 1):
last = res[-2 ** i:]
res.extend(last)
res.extend([k + 1 fo... | the_stack_v2_python_sparse | C/CountingBits.py | bssrdf/pyleet | train | 2 | |
47ccfa5b464a8d72d4507953373650945169f5ac | [
"if s == '':\n return ''\n\ndef isPalindrome(sub):\n m = len(sub)\n for i in range(m / 2):\n if sub[i] != sub[m - 1 - i]:\n return False\n return True\nres = ''\nn = len(s)\nfor i in range(n):\n for j in range(n, i, -1):\n if isPalindrome(s[i:j]):\n if j - i + 1 > ... | <|body_start_0|>
if s == '':
return ''
def isPalindrome(sub):
m = len(sub)
for i in range(m / 2):
if sub[i] != sub[m - 1 - i]:
return False
return True
res = ''
n = len(s)
for i in range(n):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_1|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_2|>
d... | stack_v2_sparse_classes_36k_train_012325 | 2,492 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: s... | 4 | null | 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(self, s): :type s: str :rtype: str
- def longestPalindrome(self, s): :type s: str :rtype: str
- d... | 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(self, s): :type s: str :rtype: str
- def longestPalindrome(self, s): :type s: str :rtype: str
- d... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_1|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_2|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
if s == '':
return ''
def isPalindrome(sub):
m = len(sub)
for i in range(m / 2):
if sub[i] != sub[m - 1 - i]:
return False
retur... | the_stack_v2_python_sparse | 0005_Longest_Palindromic_Substring.py | bingli8802/leetcode | train | 0 | |
164c21ebb623bf1d6355dc5671e72e16d0149d7b | [
"self.mean = mean\nself.std = std\nself.norm_factor = norm_factor\nself.bias = bias\nself.preproc = Preproc(size, 0.6)\nself.size = size\nif pipeline is None:\n self.pipeline = None\nelse:\n self.pipeline = Compose(pipeline)",
"if self.pipeline is not None:\n return {k: v for k, v in self.pipeline({'img'... | <|body_start_0|>
self.mean = mean
self.std = std
self.norm_factor = norm_factor
self.bias = bias
self.preproc = Preproc(size, 0.6)
self.size = size
if pipeline is None:
self.pipeline = None
else:
self.pipeline = Compose(pipeline)
<|... | TrainAugmentation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainAugmentation:
def __init__(self, pipeline, size, mean, std, norm_factor=255.0, bias=0.0):
"""Args: size: the size the of final image. mean: mean pixel value per channel."""
<|body_0|>
def __call__(self, img, boxes, labels):
"""Args: img: the output of cv.imread ... | stack_v2_sparse_classes_36k_train_012326 | 2,877 | permissive | [
{
"docstring": "Args: size: the size the of final image. mean: mean pixel value per channel.",
"name": "__init__",
"signature": "def __init__(self, pipeline, size, mean, std, norm_factor=255.0, bias=0.0)"
},
{
"docstring": "Args: img: the output of cv.imread in RGB layout. boxes: boundding boxes... | 2 | stack_v2_sparse_classes_30k_train_007675 | Implement the Python class `TrainAugmentation` described below.
Class description:
Implement the TrainAugmentation class.
Method signatures and docstrings:
- def __init__(self, pipeline, size, mean, std, norm_factor=255.0, bias=0.0): Args: size: the size the of final image. mean: mean pixel value per channel.
- def _... | Implement the Python class `TrainAugmentation` described below.
Class description:
Implement the TrainAugmentation class.
Method signatures and docstrings:
- def __init__(self, pipeline, size, mean, std, norm_factor=255.0, bias=0.0): Args: size: the size the of final image. mean: mean pixel value per channel.
- def _... | 8a32196ce342b8ad9e3885895735d1286e25beba | <|skeleton|>
class TrainAugmentation:
def __init__(self, pipeline, size, mean, std, norm_factor=255.0, bias=0.0):
"""Args: size: the size the of final image. mean: mean pixel value per channel."""
<|body_0|>
def __call__(self, img, boxes, labels):
"""Args: img: the output of cv.imread ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainAugmentation:
def __init__(self, pipeline, size, mean, std, norm_factor=255.0, bias=0.0):
"""Args: size: the size the of final image. mean: mean pixel value per channel."""
self.mean = mean
self.std = std
self.norm_factor = norm_factor
self.bias = bias
self... | the_stack_v2_python_sparse | aw_nas/dataset/det_transform.py | blyucs/aw_nas | train | 0 | |
9b42a9cdebe9c8d70d467c6afe09e9f31d74560e | [
"self.continue_on_error = continue_on_error\nself.file_recovery_method = file_recovery_method\nself.filenames = filenames\nself.filter_ip_config = filter_ip_config\nself.is_file_based_volume_restore = is_file_based_volume_restore\nself.mount_disks_on_vm = mount_disks_on_vm\nself.name = name\nself.new_base_directory... | <|body_start_0|>
self.continue_on_error = continue_on_error
self.file_recovery_method = file_recovery_method
self.filenames = filenames
self.filter_ip_config = filter_ip_config
self.is_file_based_volume_restore = is_file_based_volume_restore
self.mount_disks_on_vm = mount... | Implementation of the 'RestoreFilesTaskRequest' model. Specifies information about a Restore Task that recovers files and folders. Attributes: continue_on_error (bool): Specifies if the Restore Task should continue even if the copy operation of some files and folders fails. If true, the Cohesity Cluster ignores intermi... | RestoreFilesTaskRequest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreFilesTaskRequest:
"""Implementation of the 'RestoreFilesTaskRequest' model. Specifies information about a Restore Task that recovers files and folders. Attributes: continue_on_error (bool): Specifies if the Restore Task should continue even if the copy operation of some files and folders f... | stack_v2_sparse_classes_36k_train_012327 | 10,417 | permissive | [
{
"docstring": "Constructor for the RestoreFilesTaskRequest class",
"name": "__init__",
"signature": "def __init__(self, continue_on_error=None, file_recovery_method=None, filenames=None, filter_ip_config=None, is_file_based_volume_restore=None, mount_disks_on_vm=None, name=None, new_base_directory=None... | 2 | stack_v2_sparse_classes_30k_train_006689 | Implement the Python class `RestoreFilesTaskRequest` described below.
Class description:
Implementation of the 'RestoreFilesTaskRequest' model. Specifies information about a Restore Task that recovers files and folders. Attributes: continue_on_error (bool): Specifies if the Restore Task should continue even if the cop... | Implement the Python class `RestoreFilesTaskRequest` described below.
Class description:
Implementation of the 'RestoreFilesTaskRequest' model. Specifies information about a Restore Task that recovers files and folders. Attributes: continue_on_error (bool): Specifies if the Restore Task should continue even if the cop... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreFilesTaskRequest:
"""Implementation of the 'RestoreFilesTaskRequest' model. Specifies information about a Restore Task that recovers files and folders. Attributes: continue_on_error (bool): Specifies if the Restore Task should continue even if the copy operation of some files and folders f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreFilesTaskRequest:
"""Implementation of the 'RestoreFilesTaskRequest' model. Specifies information about a Restore Task that recovers files and folders. Attributes: continue_on_error (bool): Specifies if the Restore Task should continue even if the copy operation of some files and folders fails. If true... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_files_task_request.py | cohesity/management-sdk-python | train | 24 |
0a7e8b5836dd5b0956f3104b80ac4105992964e1 | [
"if 'AVALON_TASK' in session:\n return True\nreturn False",
"with pype.modified_environ(**session):\n print(self.name)\n app = lib.get_application(self.name)\n executable = lib.which(app['executable'])\n arguments = []\n tools_env = acre.get_tools([self.name])\n env = acre.compute(tools_env)\... | <|body_start_0|>
if 'AVALON_TASK' in session:
return True
return False
<|end_body_0|>
<|body_start_1|>
with pype.modified_environ(**session):
print(self.name)
app = lib.get_application(self.name)
executable = lib.which(app['executable'])
... | Aport | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Aport:
def is_compatible(self, session):
"""Return whether the action is compatible with the session"""
<|body_0|>
def process(self, session, **kwargs):
"""Implement the behavior for when the action is triggered Args: session (dict): environment dictionary Returns: P... | stack_v2_sparse_classes_36k_train_012328 | 1,606 | permissive | [
{
"docstring": "Return whether the action is compatible with the session",
"name": "is_compatible",
"signature": "def is_compatible(self, session)"
},
{
"docstring": "Implement the behavior for when the action is triggered Args: session (dict): environment dictionary Returns: Popen instance of n... | 2 | stack_v2_sparse_classes_30k_test_000468 | Implement the Python class `Aport` described below.
Class description:
Implement the Aport class.
Method signatures and docstrings:
- def is_compatible(self, session): Return whether the action is compatible with the session
- def process(self, session, **kwargs): Implement the behavior for when the action is trigger... | Implement the Python class `Aport` described below.
Class description:
Implement the Aport class.
Method signatures and docstrings:
- def is_compatible(self, session): Return whether the action is compatible with the session
- def process(self, session, **kwargs): Implement the behavior for when the action is trigger... | 47ef4b64f297186c6d929a8f56ecfb93dd0f44e8 | <|skeleton|>
class Aport:
def is_compatible(self, session):
"""Return whether the action is compatible with the session"""
<|body_0|>
def process(self, session, **kwargs):
"""Implement the behavior for when the action is triggered Args: session (dict): environment dictionary Returns: P... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Aport:
def is_compatible(self, session):
"""Return whether the action is compatible with the session"""
if 'AVALON_TASK' in session:
return True
return False
def process(self, session, **kwargs):
"""Implement the behavior for when the action is triggered Args: ... | the_stack_v2_python_sparse | pype/plugins/launcher/actions/Aport.py | jrsndl/pype | train | 1 | |
8ea4028e00ca0f7ee162c29ac0becc77d4069c33 | [
"asteroidset = set()\nfor i, row in enumerate(inputmap.split('\\n')):\n for j, asteroid in enumerate(row):\n if asteroid == '#':\n asteroidset.add((j, i))\nself.asteroidset = asteroidset",
"visibleangle = dict()\nxp, yp = position\nfor asteroid in self.asteroidset:\n if position == asteroi... | <|body_start_0|>
asteroidset = set()
for i, row in enumerate(inputmap.split('\n')):
for j, asteroid in enumerate(row):
if asteroid == '#':
asteroidset.add((j, i))
self.asteroidset = asteroidset
<|end_body_0|>
<|body_start_1|>
visibleangle ... | Asteroid map | AsteroidMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsteroidMap:
"""Asteroid map"""
def __init__(self, inputmap):
"""Turn an input map into a set of coordinates"""
<|body_0|>
def visiblefrom(self, position):
"""Finds all asteroids that are visible from a given position"""
<|body_1|>
def destroyasteroi... | stack_v2_sparse_classes_36k_train_012329 | 3,238 | no_license | [
{
"docstring": "Turn an input map into a set of coordinates",
"name": "__init__",
"signature": "def __init__(self, inputmap)"
},
{
"docstring": "Finds all asteroids that are visible from a given position",
"name": "visiblefrom",
"signature": "def visiblefrom(self, position)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_020076 | Implement the Python class `AsteroidMap` described below.
Class description:
Asteroid map
Method signatures and docstrings:
- def __init__(self, inputmap): Turn an input map into a set of coordinates
- def visiblefrom(self, position): Finds all asteroids that are visible from a given position
- def destroyasteroids(s... | Implement the Python class `AsteroidMap` described below.
Class description:
Asteroid map
Method signatures and docstrings:
- def __init__(self, inputmap): Turn an input map into a set of coordinates
- def visiblefrom(self, position): Finds all asteroids that are visible from a given position
- def destroyasteroids(s... | 2ffc427f42332ca76813c0732e170ceaffadf6dc | <|skeleton|>
class AsteroidMap:
"""Asteroid map"""
def __init__(self, inputmap):
"""Turn an input map into a set of coordinates"""
<|body_0|>
def visiblefrom(self, position):
"""Finds all asteroids that are visible from a given position"""
<|body_1|>
def destroyasteroi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsteroidMap:
"""Asteroid map"""
def __init__(self, inputmap):
"""Turn an input map into a set of coordinates"""
asteroidset = set()
for i, row in enumerate(inputmap.split('\n')):
for j, asteroid in enumerate(row):
if asteroid == '#':
... | the_stack_v2_python_sparse | day10/day10.py | riccardosven/adventofcode2019 | train | 0 |
48b50c0e2b96caf223f4991ae64ae86248aac133 | [
"for _ng in cls.WORD_LIST:\n m = re.search(_ng, text)\n if m:\n return True\nreturn False",
"for _ng_word in cls.WORD_LIST:\n text = re.sub('%s' % _ng_word, '', text)\nreturn text"
] | <|body_start_0|>
for _ng in cls.WORD_LIST:
m = re.search(_ng, text)
if m:
return True
return False
<|end_body_0|>
<|body_start_1|>
for _ng_word in cls.WORD_LIST:
text = re.sub('%s' % _ng_word, '', text)
return text
<|end_body_1|>
| NGBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NGBase:
def check(cls, text):
"""マッチしたらTrue"""
<|body_0|>
def remove(cls, text):
"""textからNGワードを除外して返却"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for _ng in cls.WORD_LIST:
m = re.search(_ng, text)
if m:
r... | stack_v2_sparse_classes_36k_train_012330 | 844 | no_license | [
{
"docstring": "マッチしたらTrue",
"name": "check",
"signature": "def check(cls, text)"
},
{
"docstring": "textからNGワードを除外して返却",
"name": "remove",
"signature": "def remove(cls, text)"
}
] | 2 | null | Implement the Python class `NGBase` described below.
Class description:
Implement the NGBase class.
Method signatures and docstrings:
- def check(cls, text): マッチしたらTrue
- def remove(cls, text): textからNGワードを除外して返却 | Implement the Python class `NGBase` described below.
Class description:
Implement the NGBase class.
Method signatures and docstrings:
- def check(cls, text): マッチしたらTrue
- def remove(cls, text): textからNGワードを除外して返却
<|skeleton|>
class NGBase:
def check(cls, text):
"""マッチしたらTrue"""
<|body_0|>
d... | eefd311c6f1edad483b89f9a513bcc2f9dfabe14 | <|skeleton|>
class NGBase:
def check(cls, text):
"""マッチしたらTrue"""
<|body_0|>
def remove(cls, text):
"""textからNGワードを除外して返却"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NGBase:
def check(cls, text):
"""マッチしたらTrue"""
for _ng in cls.WORD_LIST:
m = re.search(_ng, text)
if m:
return True
return False
def remove(cls, text):
"""textからNGワードを除外して返却"""
for _ng_word in cls.WORD_LIST:
text ... | the_stack_v2_python_sparse | anchovy/module/mecab/ng_word.py | arpsabbir/anchovy | train | 0 | |
6efa6c275d8c110a5c176c2ef483c601bc164466 | [
"try:\n registry = oai_registry_api.get_all()\n serializer = serializers.RegistrySerializer(registry, many=True)\n return Response(serializer.data, status=status.HTTP_200_OK)\nexcept Exception as e:\n content = OaiPmhMessage.get_message_labelled(str(e))\n return Response(content, status=status.HTTP_5... | <|body_start_0|>
try:
registry = oai_registry_api.get_all()
serializer = serializers.RegistrySerializer(registry, many=True)
return Response(serializer.data, status=status.HTTP_200_OK)
except Exception as e:
content = OaiPmhMessage.get_message_labelled(str... | RegistryList | [
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistryList:
def get(self, request):
"""Get all Registries (Data provider) Args: request: HTTP request Returns: - code: 200 content: List of Registries - code: 500 content: Internal server error"""
<|body_0|>
def post(self, request):
"""Create a Registry (Data provi... | stack_v2_sparse_classes_36k_train_012331 | 16,118 | permissive | [
{
"docstring": "Get all Registries (Data provider) Args: request: HTTP request Returns: - code: 200 content: List of Registries - code: 500 content: Internal server error",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create a Registry (Data provider) Parameters: { \"u... | 2 | stack_v2_sparse_classes_30k_test_000595 | Implement the Python class `RegistryList` described below.
Class description:
Implement the RegistryList class.
Method signatures and docstrings:
- def get(self, request): Get all Registries (Data provider) Args: request: HTTP request Returns: - code: 200 content: List of Registries - code: 500 content: Internal serv... | Implement the Python class `RegistryList` described below.
Class description:
Implement the RegistryList class.
Method signatures and docstrings:
- def get(self, request): Get all Registries (Data provider) Args: request: HTTP request Returns: - code: 200 content: List of Registries - code: 500 content: Internal serv... | e41fd9c5a75b51dc626995e753a5840f238a557d | <|skeleton|>
class RegistryList:
def get(self, request):
"""Get all Registries (Data provider) Args: request: HTTP request Returns: - code: 200 content: List of Registries - code: 500 content: Internal server error"""
<|body_0|>
def post(self, request):
"""Create a Registry (Data provi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegistryList:
def get(self, request):
"""Get all Registries (Data provider) Args: request: HTTP request Returns: - code: 200 content: List of Registries - code: 500 content: Internal server error"""
try:
registry = oai_registry_api.get_all()
serializer = serializers.Reg... | the_stack_v2_python_sparse | core_oaipmh_harvester_app/rest/oai_registry/views.py | faical-yannick-congo/core_oaipmh_harvester_app | train | 0 | |
a8a148c64de5c00d6e3e3fb29f6fa235012c3aa1 | [
"self.front = -1\nself.rare = -1\nself.max_size = 5\nself.queue = [0] * self.max_size",
"if self.front == 0 and self.rare == self.max_size - 1 or self.front == self.rare + 1:\n print('Overflow')\nelse:\n if self.front == -1:\n self.front = 0\n self.rare = 0\n elif self.rare == self.max_size... | <|body_start_0|>
self.front = -1
self.rare = -1
self.max_size = 5
self.queue = [0] * self.max_size
<|end_body_0|>
<|body_start_1|>
if self.front == 0 and self.rare == self.max_size - 1 or self.front == self.rare + 1:
print('Overflow')
else:
if sel... | This class contains functions for doubly ended queue. | deQueue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class deQueue:
"""This class contains functions for doubly ended queue."""
def __init__(self):
"""Constructor function. Argument: self -- represents the object of the class."""
<|body_0|>
def insert_rare(self, item):
"""This function inserts at the rare position. Argum... | stack_v2_sparse_classes_36k_train_012332 | 3,636 | no_license | [
{
"docstring": "Constructor function. Argument: self -- represents the object of the class.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "This function inserts at the rare position. Arguments: self -- represents the object of the class. item -- integer value, the val... | 6 | stack_v2_sparse_classes_30k_train_003763 | Implement the Python class `deQueue` described below.
Class description:
This class contains functions for doubly ended queue.
Method signatures and docstrings:
- def __init__(self): Constructor function. Argument: self -- represents the object of the class.
- def insert_rare(self, item): This function inserts at the... | Implement the Python class `deQueue` described below.
Class description:
This class contains functions for doubly ended queue.
Method signatures and docstrings:
- def __init__(self): Constructor function. Argument: self -- represents the object of the class.
- def insert_rare(self, item): This function inserts at the... | 6870426104aef417086788221dad29e887ddfe3f | <|skeleton|>
class deQueue:
"""This class contains functions for doubly ended queue."""
def __init__(self):
"""Constructor function. Argument: self -- represents the object of the class."""
<|body_0|>
def insert_rare(self, item):
"""This function inserts at the rare position. Argum... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class deQueue:
"""This class contains functions for doubly ended queue."""
def __init__(self):
"""Constructor function. Argument: self -- represents the object of the class."""
self.front = -1
self.rare = -1
self.max_size = 5
self.queue = [0] * self.max_size
def ins... | the_stack_v2_python_sparse | Data Structure/03. Queue/03. Doubly Ended Queue/py_code.py | Slothfulwave612/Coding-Problems | train | 5 |
002c469bd1ed9c15918a9194cb968ec187203d0b | [
"self.check_file(infile, need_seek)\nself.infile = infile\nself.closed = self.infile_closed = None\nself.inbuf = ''\nself.outbuf = array.array('c')\nself.eof = self.infile_eof = None",
"if not hasattr(file, 'read'):\n raise TypeError('Basis file must have a read() method')\nif not hasattr(file, 'close'):\n ... | <|body_start_0|>
self.check_file(infile, need_seek)
self.infile = infile
self.closed = self.infile_closed = None
self.inbuf = ''
self.outbuf = array.array('c')
self.eof = self.infile_eof = None
<|end_body_0|>
<|body_start_1|>
if not hasattr(file, 'read'):
... | File-like object used by SigFile, DeltaFile, and PatchFile | LikeFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LikeFile:
"""File-like object used by SigFile, DeltaFile, and PatchFile"""
def __init__(self, infile, need_seek=None):
"""LikeFile initializer - zero buffers, set eofs off"""
<|body_0|>
def check_file(self, file, need_seek=None):
"""Raise type error if file doesn... | stack_v2_sparse_classes_36k_train_012333 | 8,383 | no_license | [
{
"docstring": "LikeFile initializer - zero buffers, set eofs off",
"name": "__init__",
"signature": "def __init__(self, infile, need_seek=None)"
},
{
"docstring": "Raise type error if file doesn't have necessary attributes",
"name": "check_file",
"signature": "def check_file(self, file,... | 6 | stack_v2_sparse_classes_30k_train_000163 | Implement the Python class `LikeFile` described below.
Class description:
File-like object used by SigFile, DeltaFile, and PatchFile
Method signatures and docstrings:
- def __init__(self, infile, need_seek=None): LikeFile initializer - zero buffers, set eofs off
- def check_file(self, file, need_seek=None): Raise typ... | Implement the Python class `LikeFile` described below.
Class description:
File-like object used by SigFile, DeltaFile, and PatchFile
Method signatures and docstrings:
- def __init__(self, infile, need_seek=None): LikeFile initializer - zero buffers, set eofs off
- def check_file(self, file, need_seek=None): Raise typ... | ef6d0f4bdff52be379784325e504de22cfe149de | <|skeleton|>
class LikeFile:
"""File-like object used by SigFile, DeltaFile, and PatchFile"""
def __init__(self, infile, need_seek=None):
"""LikeFile initializer - zero buffers, set eofs off"""
<|body_0|>
def check_file(self, file, need_seek=None):
"""Raise type error if file doesn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LikeFile:
"""File-like object used by SigFile, DeltaFile, and PatchFile"""
def __init__(self, infile, need_seek=None):
"""LikeFile initializer - zero buffers, set eofs off"""
self.check_file(infile, need_seek)
self.infile = infile
self.closed = self.infile_closed = None
... | the_stack_v2_python_sparse | duplicity/librsync.py | henrysher/duplicity | train | 90 |
abcfc42589ba95e61fb11ff1f0e218828f139f42 | [
"if type(data) != np.ndarray or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nn = data.shape[1]\nif n < 2:\n raise ValueError('data must contain multiple data points')\nd = data.shape[0]\nself.mean = np.mean(data, axis=1).reshape(d, 1)\nX = data - self.mean\nself.cov = np.dot(X, ... | <|body_start_0|>
if type(data) != np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
n = data.shape[1]
if n < 2:
raise ValueError('data must contain multiple data points')
d = data.shape[0]
self.mean = np.mean(data, axis... | Class that represents a Multivariate Normal distribution | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Class that represents a Multivariate Normal distribution"""
def __init__(self, data):
"""Constructor funtcion Arguments: - data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data po... | stack_v2_sparse_classes_36k_train_012334 | 2,132 | no_license | [
{
"docstring": "Constructor funtcion Arguments: - data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data point Public instance variables: - mean - a numpy.ndarray of shape (d, 1) containing the mean of data - cov - a numpy.n... | 2 | null | Implement the Python class `MultiNormal` described below.
Class description:
Class that represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): Constructor funtcion Arguments: - data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of da... | Implement the Python class `MultiNormal` described below.
Class description:
Class that represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): Constructor funtcion Arguments: - data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of da... | fc2cec306961f7ca2448965ddd3a2f656bbe10c7 | <|skeleton|>
class MultiNormal:
"""Class that represents a Multivariate Normal distribution"""
def __init__(self, data):
"""Constructor funtcion Arguments: - data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data po... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""Class that represents a Multivariate Normal distribution"""
def __init__(self, data):
"""Constructor funtcion Arguments: - data is a numpy.ndarray of shape (d, n) containing the data set: - n is the number of data points - d is the number of dimensions in each data point Public in... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | dalexach/holbertonschool-machine_learning | train | 2 |
3dac4473e9fa80d202f36bbda543413e08bcc674 | [
"try:\n count = current_app.redis_slave.zscore(cls.key, user_id)\nexcept RedisError as e:\n current_app.logger.error(e)\n raise e\nif count:\n return int(count) if int(count) > 0 else 0\nelse:\n return 0",
"try:\n current_app.redis_master.zincrby(cls.key, user_id)\nexcept RedisError as e:\n c... | <|body_start_0|>
try:
count = current_app.redis_slave.zscore(cls.key, user_id)
except RedisError as e:
current_app.logger.error(e)
raise e
if count:
return int(count) if int(count) > 0 else 0
else:
return 0
<|end_body_0|>
<|bod... | 数据统计的基类 | BaseCountStorage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseCountStorage:
"""数据统计的基类"""
def get(cls, user_id):
"""获取指定用户的统计量 :return: 数量"""
<|body_0|>
def incr(cls, user_id):
"""更新用户指定的统计量 :return: None"""
<|body_1|>
def reset(cls, db_query_ret):
"""重置对应的数据集 :data: 数据集合 :return:"""
<|body_... | stack_v2_sparse_classes_36k_train_012335 | 3,455 | permissive | [
{
"docstring": "获取指定用户的统计量 :return: 数量",
"name": "get",
"signature": "def get(cls, user_id)"
},
{
"docstring": "更新用户指定的统计量 :return: None",
"name": "incr",
"signature": "def incr(cls, user_id)"
},
{
"docstring": "重置对应的数据集 :data: 数据集合 :return:",
"name": "reset",
"signature"... | 3 | stack_v2_sparse_classes_30k_test_000192 | Implement the Python class `BaseCountStorage` described below.
Class description:
数据统计的基类
Method signatures and docstrings:
- def get(cls, user_id): 获取指定用户的统计量 :return: 数量
- def incr(cls, user_id): 更新用户指定的统计量 :return: None
- def reset(cls, db_query_ret): 重置对应的数据集 :data: 数据集合 :return: | Implement the Python class `BaseCountStorage` described below.
Class description:
数据统计的基类
Method signatures and docstrings:
- def get(cls, user_id): 获取指定用户的统计量 :return: 数量
- def incr(cls, user_id): 更新用户指定的统计量 :return: None
- def reset(cls, db_query_ret): 重置对应的数据集 :data: 数据集合 :return:
<|skeleton|>
class BaseCountStor... | dbdf0f3790d0dc5f233b4c9e7bd69927bbfff28d | <|skeleton|>
class BaseCountStorage:
"""数据统计的基类"""
def get(cls, user_id):
"""获取指定用户的统计量 :return: 数量"""
<|body_0|>
def incr(cls, user_id):
"""更新用户指定的统计量 :return: None"""
<|body_1|>
def reset(cls, db_query_ret):
"""重置对应的数据集 :data: 数据集合 :return:"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseCountStorage:
"""数据统计的基类"""
def get(cls, user_id):
"""获取指定用户的统计量 :return: 数量"""
try:
count = current_app.redis_slave.zscore(cls.key, user_id)
except RedisError as e:
current_app.logger.error(e)
raise e
if count:
return in... | the_stack_v2_python_sparse | common/cache/statistic.py | qls7/xinwen | train | 0 |
baeca08d23207a0224ba2009160b44f5de2f0b65 | [
"path = os.path.join(self.directory, self.filepath)\nlog_report('INFO', 'path: ' + str(path), self)\nself.image_dp = self.get_default_image_path(path, self.image_dp)\ncameras, points, mesh_fp, image_dp = MeshroomFileHandler.parse_meshroom_file(path, self.use_workspace_images, self.image_dp, self.image_fp_type, self... | <|body_start_0|>
path = os.path.join(self.directory, self.filepath)
log_report('INFO', 'path: ' + str(path), self)
self.image_dp = self.get_default_image_path(path, self.image_dp)
cameras, points, mesh_fp, image_dp = MeshroomFileHandler.parse_meshroom_file(path, self.use_workspace_images... | Import a :code:`Meshroom` MG/SfM/JSON file. | ImportMeshroomOperator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImportMeshroomOperator:
"""Import a :code:`Meshroom` MG/SfM/JSON file."""
def execute(self, context):
"""Import a :code:`Meshroom` file/workspace."""
<|body_0|>
def invoke(self, context, event):
"""Set the default import options before running the operator."""
... | stack_v2_sparse_classes_36k_train_012336 | 5,448 | permissive | [
{
"docstring": "Import a :code:`Meshroom` file/workspace.",
"name": "execute",
"signature": "def execute(self, context)"
},
{
"docstring": "Set the default import options before running the operator.",
"name": "invoke",
"signature": "def invoke(self, context, event)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_001766 | Implement the Python class `ImportMeshroomOperator` described below.
Class description:
Import a :code:`Meshroom` MG/SfM/JSON file.
Method signatures and docstrings:
- def execute(self, context): Import a :code:`Meshroom` file/workspace.
- def invoke(self, context, event): Set the default import options before runnin... | Implement the Python class `ImportMeshroomOperator` described below.
Class description:
Import a :code:`Meshroom` MG/SfM/JSON file.
Method signatures and docstrings:
- def execute(self, context): Import a :code:`Meshroom` file/workspace.
- def invoke(self, context, event): Set the default import options before runnin... | da404ebf8d4412196c2740f0b569cbf9e542952d | <|skeleton|>
class ImportMeshroomOperator:
"""Import a :code:`Meshroom` MG/SfM/JSON file."""
def execute(self, context):
"""Import a :code:`Meshroom` file/workspace."""
<|body_0|>
def invoke(self, context, event):
"""Set the default import options before running the operator."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImportMeshroomOperator:
"""Import a :code:`Meshroom` MG/SfM/JSON file."""
def execute(self, context):
"""Import a :code:`Meshroom` file/workspace."""
path = os.path.join(self.directory, self.filepath)
log_report('INFO', 'path: ' + str(path), self)
self.image_dp = self.get_... | the_stack_v2_python_sparse | photogrammetry_importer/operators/meshroom_import_op.py | SBCV/Blender-Addon-Photogrammetry-Importer | train | 718 |
f42ec257bbf40bc57b982776371775865744bd0b | [
"albums = Album.objects.all()\nalbums = album_filter(request, albums)\nif type(albums) == Response:\n return albums\nreturn Response(AlbumSerializer(albums, many=True).data)",
"serializer = AlbumSerializerCreate(data=request.data, context={'request': request})\nif serializer.is_valid():\n serializer.save()\... | <|body_start_0|>
albums = Album.objects.all()
albums = album_filter(request, albums)
if type(albums) == Response:
return albums
return Response(AlbumSerializer(albums, many=True).data)
<|end_body_0|>
<|body_start_1|>
serializer = AlbumSerializerCreate(data=request.da... | AlbumView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlbumView:
def get(request):
"""List albums"""
<|body_0|>
def post(request):
"""Create album"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
albums = Album.objects.all()
albums = album_filter(request, albums)
if type(albums) == Respo... | stack_v2_sparse_classes_36k_train_012337 | 2,230 | permissive | [
{
"docstring": "List albums",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "Create album",
"name": "post",
"signature": "def post(request)"
}
] | 2 | null | Implement the Python class `AlbumView` described below.
Class description:
Implement the AlbumView class.
Method signatures and docstrings:
- def get(request): List albums
- def post(request): Create album | Implement the Python class `AlbumView` described below.
Class description:
Implement the AlbumView class.
Method signatures and docstrings:
- def get(request): List albums
- def post(request): Create album
<|skeleton|>
class AlbumView:
def get(request):
"""List albums"""
<|body_0|>
def post... | b93fa2fea8d45df9f19c3c58037e59dad4981921 | <|skeleton|>
class AlbumView:
def get(request):
"""List albums"""
<|body_0|>
def post(request):
"""Create album"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlbumView:
def get(request):
"""List albums"""
albums = Album.objects.all()
albums = album_filter(request, albums)
if type(albums) == Response:
return albums
return Response(AlbumSerializer(albums, many=True).data)
def post(request):
"""Create a... | the_stack_v2_python_sparse | v1/music/views/album.py | lawiz22/PLOUC-Backend-master | train | 0 | |
b0db2db35fed328278562d03ca063003c5146a3c | [
"super().__init__(**kwargs)\ntrain_factory, inference_factory, validation_factory, test_factory = (kwargs.get('triples_factory'), kwargs.get('inference_factory'), kwargs.get('validation_factory'), kwargs.get('test_factory'))\nif gnn_encoder is None:\n dim = self.entity_representations[0].shape[0]\n gnn_encode... | <|body_start_0|>
super().__init__(**kwargs)
train_factory, inference_factory, validation_factory, test_factory = (kwargs.get('triples_factory'), kwargs.get('inference_factory'), kwargs.get('validation_factory'), kwargs.get('test_factory'))
if gnn_encoder is None:
dim = self.entity_re... | Inductive NodePiece with a GNN encoder on top. Overall, it's a 3-step procedure: 1. Featurizing nodes via NodePiece 2. Message passing over the active graph using NodePiece features 3. Scoring function for a given batch of triples As of now, message passing is expected to be over the full graph | InductiveNodePieceGNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InductiveNodePieceGNN:
"""Inductive NodePiece with a GNN encoder on top. Overall, it's a 3-step procedure: 1. Featurizing nodes via NodePiece 2. Message passing over the active graph using NodePiece features 3. Scoring function for a given batch of triples As of now, message passing is expected t... | stack_v2_sparse_classes_36k_train_012338 | 5,554 | permissive | [
{
"docstring": "Initialize the model. :param gnn_encoder: an iterable of message passing layers. Defaults to 2-layer CompGCN with Hadamard composition. :param kwargs: additional keyword-based parameters passed to `InductiveNodePiece.__init__`.",
"name": "__init__",
"signature": "def __init__(self, *, gn... | 3 | stack_v2_sparse_classes_30k_train_016714 | Implement the Python class `InductiveNodePieceGNN` described below.
Class description:
Inductive NodePiece with a GNN encoder on top. Overall, it's a 3-step procedure: 1. Featurizing nodes via NodePiece 2. Message passing over the active graph using NodePiece features 3. Scoring function for a given batch of triples A... | Implement the Python class `InductiveNodePieceGNN` described below.
Class description:
Inductive NodePiece with a GNN encoder on top. Overall, it's a 3-step procedure: 1. Featurizing nodes via NodePiece 2. Message passing over the active graph using NodePiece features 3. Scoring function for a given batch of triples A... | 5ff3597b18ab9a220e34361d3c3f262060811df1 | <|skeleton|>
class InductiveNodePieceGNN:
"""Inductive NodePiece with a GNN encoder on top. Overall, it's a 3-step procedure: 1. Featurizing nodes via NodePiece 2. Message passing over the active graph using NodePiece features 3. Scoring function for a given batch of triples As of now, message passing is expected t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InductiveNodePieceGNN:
"""Inductive NodePiece with a GNN encoder on top. Overall, it's a 3-step procedure: 1. Featurizing nodes via NodePiece 2. Message passing over the active graph using NodePiece features 3. Scoring function for a given batch of triples As of now, message passing is expected to be over the... | the_stack_v2_python_sparse | src/pykeen/models/inductive/inductive_nodepiece_gnn.py | pykeen/pykeen | train | 1,308 |
841a8573b4336388f38566486a0f77934f33c60b | [
"if path.endswith('/'):\n path = path + 'index.html'\nreturn self.server.pages[path]",
"try:\n content = self.load_page(self.path)\nexcept KeyError:\n self.send_response(404)\n self.end_headers()\nelse:\n self.send_response(200)\n self.end_headers()\n self.wfile.write(content)"
] | <|body_start_0|>
if path.endswith('/'):
path = path + 'index.html'
return self.server.pages[path]
<|end_body_0|>
<|body_start_1|>
try:
content = self.load_page(self.path)
except KeyError:
self.send_response(404)
self.end_headers()
... | Handler for the PreviewServer. | _PreviewHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _PreviewHandler:
"""Handler for the PreviewServer."""
def load_page(self, path):
"""Load a page, or raise KeyError."""
<|body_0|>
def do_GET(self):
"""Handle GET requests."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if path.endswith('/'):
... | stack_v2_sparse_classes_36k_train_012339 | 1,528 | permissive | [
{
"docstring": "Load a page, or raise KeyError.",
"name": "load_page",
"signature": "def load_page(self, path)"
},
{
"docstring": "Handle GET requests.",
"name": "do_GET",
"signature": "def do_GET(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005409 | Implement the Python class `_PreviewHandler` described below.
Class description:
Handler for the PreviewServer.
Method signatures and docstrings:
- def load_page(self, path): Load a page, or raise KeyError.
- def do_GET(self): Handle GET requests. | Implement the Python class `_PreviewHandler` described below.
Class description:
Handler for the PreviewServer.
Method signatures and docstrings:
- def load_page(self, path): Load a page, or raise KeyError.
- def do_GET(self): Handle GET requests.
<|skeleton|>
class _PreviewHandler:
"""Handler for the PreviewSer... | 08b037518fafd9afef7b6dc34a9fd0960cc1de07 | <|skeleton|>
class _PreviewHandler:
"""Handler for the PreviewServer."""
def load_page(self, path):
"""Load a page, or raise KeyError."""
<|body_0|>
def do_GET(self):
"""Handle GET requests."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _PreviewHandler:
"""Handler for the PreviewServer."""
def load_page(self, path):
"""Load a page, or raise KeyError."""
if path.endswith('/'):
path = path + 'index.html'
return self.server.pages[path]
def do_GET(self):
"""Handle GET requests."""
try... | the_stack_v2_python_sparse | scarab/servers.py | cknv/scarab | train | 0 |
86547aa61b3731edf1b4add87a115491cc54d68a | [
"length = len(nums)\nfor i in range(length):\n for j in range(i + 1, length):\n if nums[i] + nums[j] == target:\n print([i, j])\n return [i, j]\nelse:\n return []",
"n = len(nums)\nmap = {}\nfor i in range(n):\n a = nums[i]\n b = target - a\n if b in map and map.get(b) ... | <|body_start_0|>
length = len(nums)
for i in range(length):
for j in range(i + 1, length):
if nums[i] + nums[j] == target:
print([i, j])
return [i, j]
else:
return []
<|end_body_0|>
<|body_start_1|>
n = len(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def two_sum(self, nums, target):
"""暴力法时间复杂度O(n^2) :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def two_sum2(self, nums, target):
"""一遍哈希表法，时间复杂度O(n) :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_012340 | 1,873 | no_license | [
{
"docstring": "暴力法时间复杂度O(n^2) :type nums: List[int] :type target: int :rtype: List[int]",
"name": "two_sum",
"signature": "def two_sum(self, nums, target)"
},
{
"docstring": "一遍哈希表法，时间复杂度O(n) :type nums: List[int] :type target: int :rtype: List[int]",
"name": "two_sum2",
"signature": "d... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def two_sum(self, nums, target): 暴力法时间复杂度O(n^2) :type nums: List[int] :type target: int :rtype: List[int]
- def two_sum2(self, nums, target): 一遍哈希表法，时间复杂度O(n) :type nums: List[in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def two_sum(self, nums, target): 暴力法时间复杂度O(n^2) :type nums: List[int] :type target: int :rtype: List[int]
- def two_sum2(self, nums, target): 一遍哈希表法，时间复杂度O(n) :type nums: List[in... | 3b13b36f37eb364410b3b5b4f10a1808d8b1111e | <|skeleton|>
class Solution:
def two_sum(self, nums, target):
"""暴力法时间复杂度O(n^2) :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def two_sum2(self, nums, target):
"""一遍哈希表法，时间复杂度O(n) :type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def two_sum(self, nums, target):
"""暴力法时间复杂度O(n^2) :type nums: List[int] :type target: int :rtype: List[int]"""
length = len(nums)
for i in range(length):
for j in range(i + 1, length):
if nums[i] + nums[j] == target:
print([i, ... | the_stack_v2_python_sparse | leetcode/1.py | yanggelinux/algorithm-data-structure | train | 0 | |
74f9eafdea97ac8b9552b795b3af81549c804fc5 | [
"current_user = request.user\nhighlight_data = request.data.get('highlight_data', {})\ntry:\n article = Articles.objects.get(slug=slug)\nexcept Articles.DoesNotExist:\n return Response({'errors': HIGHLIGHT_MSGS['ARTICLE_NOT_FOUND']}, status=status.HTTP_404_NOT_FOUND)\nhighlights = Highlights.objects.filter(ar... | <|body_start_0|>
current_user = request.user
highlight_data = request.data.get('highlight_data', {})
try:
article = Articles.objects.get(slug=slug)
except Articles.DoesNotExist:
return Response({'errors': HIGHLIGHT_MSGS['ARTICLE_NOT_FOUND']}, status=status.HTTP_40... | Provide methods for creating a highlight | CreateGetDeleteMyHighlightsAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateGetDeleteMyHighlightsAPIView:
"""Provide methods for creating a highlight"""
def get(self, request, slug):
"""Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { "message": "message body", "hig... | stack_v2_sparse_classes_36k_train_012341 | 12,153 | permissive | [
{
"docstring": "Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { \"message\": \"message body\", \"highlights\": list of highlights and their details } OR { \"errors\": \"error details body\" }",
"name": "get",
"signa... | 2 | stack_v2_sparse_classes_30k_train_020182 | Implement the Python class `CreateGetDeleteMyHighlightsAPIView` described below.
Class description:
Provide methods for creating a highlight
Method signatures and docstrings:
- def get(self, request, slug): Get all my highlights for an article Params ------- request: Object with request data and functions. Returns --... | Implement the Python class `CreateGetDeleteMyHighlightsAPIView` described below.
Class description:
Provide methods for creating a highlight
Method signatures and docstrings:
- def get(self, request, slug): Get all my highlights for an article Params ------- request: Object with request data and functions. Returns --... | 5a31840856de4b361fe2594dfa7a33d7774d3fe2 | <|skeleton|>
class CreateGetDeleteMyHighlightsAPIView:
"""Provide methods for creating a highlight"""
def get(self, request, slug):
"""Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { "message": "message body", "hig... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateGetDeleteMyHighlightsAPIView:
"""Provide methods for creating a highlight"""
def get(self, request, slug):
"""Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { "message": "message body", "highlights": lis... | the_stack_v2_python_sparse | authors/apps/highlights/views.py | bl4ck4ndbr0wn/ah-centauri-backend | train | 0 |
7bfcc0611b92fb47dbaa63385e7a3f3decd9eb05 | [
"DBFormatter.__init__(self, logger, dbi)\nself.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''\nself.sql = 'UPDATE {owner}FILES F SET LAST_MODIFIED_BY=:myuser,\\n LAST_MODIFICATION_DATE=:mydate,\\n IS_FILE_VALID = :is_file_valid\\n '.format(owner=self.owner)",
"binds = dict(my... | <|body_start_0|>
DBFormatter.__init__(self, logger, dbi)
self.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''
self.sql = 'UPDATE {owner}FILES F SET LAST_MODIFIED_BY=:myuser,\n LAST_MODIFICATION_DATE=:mydate,\n IS_FILE_VALID = :is_file_valid\n '.format(owner=s... | File Update Status DAO class. | UpdateStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateStatus:
"""File Update Status DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
<|body_0|>
def execute(self, conn, logical_file_name, is_file_valid, lost, dataset, transaction=False):
"""for a given file or a list of file... | stack_v2_sparse_classes_36k_train_012342 | 2,612 | permissive | [
{
"docstring": "Add schema owner and sql.",
"name": "__init__",
"signature": "def __init__(self, logger, dbi, owner)"
},
{
"docstring": "for a given file or a list of files",
"name": "execute",
"signature": "def execute(self, conn, logical_file_name, is_file_valid, lost, dataset, transac... | 2 | null | Implement the Python class `UpdateStatus` described below.
Class description:
File Update Status DAO class.
Method signatures and docstrings:
- def __init__(self, logger, dbi, owner): Add schema owner and sql.
- def execute(self, conn, logical_file_name, is_file_valid, lost, dataset, transaction=False): for a given f... | Implement the Python class `UpdateStatus` described below.
Class description:
File Update Status DAO class.
Method signatures and docstrings:
- def __init__(self, logger, dbi, owner): Add schema owner and sql.
- def execute(self, conn, logical_file_name, is_file_valid, lost, dataset, transaction=False): for a given f... | 14df8bbe8ee8f874fe423399b18afef911fe78c7 | <|skeleton|>
class UpdateStatus:
"""File Update Status DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
<|body_0|>
def execute(self, conn, logical_file_name, is_file_valid, lost, dataset, transaction=False):
"""for a given file or a list of file... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateStatus:
"""File Update Status DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
DBFormatter.__init__(self, logger, dbi)
self.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''
self.sql = 'UPDATE {owner}FILES F SET LAST... | the_stack_v2_python_sparse | Server/Python/src/dbs/dao/Oracle/File/UpdateStatus.py | vkuznet/DBS | train | 0 |
685701112523a6ca58daa5e3744648887070eaef | [
"self.name = info_dict['name']\nself.path = info_dict['path']\nself.save_path = info_dict['save_path']",
"video = cv2.VideoCapture(self.path)\ncount = video.get(cv2.CAP_PROP_FRAME_COUNT)\nframes = []\nret, frame = video.read()\nassert ret\ncv2.imwrite(self.save_path + '.jpg', frame)\nreturn frames"
] | <|body_start_0|>
self.name = info_dict['name']
self.path = info_dict['path']
self.save_path = info_dict['save_path']
<|end_body_0|>
<|body_start_1|>
video = cv2.VideoCapture(self.path)
count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frames = []
ret, frame = video.rea... | Video3D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Video3D:
def __init__(self, info_dict):
"""keys of info_dict: name, path notes: if indexs of your img is 0,1,2,3, your frame num should be 4."""
<|body_0|>
def get_cover_frames(self):
"""return: num_frames * height * width * channel (rgb:3 , flow:2)"""
<|body... | stack_v2_sparse_classes_36k_train_012343 | 2,997 | no_license | [
{
"docstring": "keys of info_dict: name, path notes: if indexs of your img is 0,1,2,3, your frame num should be 4.",
"name": "__init__",
"signature": "def __init__(self, info_dict)"
},
{
"docstring": "return: num_frames * height * width * channel (rgb:3 , flow:2)",
"name": "get_cover_frames"... | 2 | stack_v2_sparse_classes_30k_train_020206 | Implement the Python class `Video3D` described below.
Class description:
Implement the Video3D class.
Method signatures and docstrings:
- def __init__(self, info_dict): keys of info_dict: name, path notes: if indexs of your img is 0,1,2,3, your frame num should be 4.
- def get_cover_frames(self): return: num_frames *... | Implement the Python class `Video3D` described below.
Class description:
Implement the Video3D class.
Method signatures and docstrings:
- def __init__(self, info_dict): keys of info_dict: name, path notes: if indexs of your img is 0,1,2,3, your frame num should be 4.
- def get_cover_frames(self): return: num_frames *... | b401a487a613b6e9dcfb42ce9ca134e7bda8b4f8 | <|skeleton|>
class Video3D:
def __init__(self, info_dict):
"""keys of info_dict: name, path notes: if indexs of your img is 0,1,2,3, your frame num should be 4."""
<|body_0|>
def get_cover_frames(self):
"""return: num_frames * height * width * channel (rgb:3 , flow:2)"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Video3D:
def __init__(self, info_dict):
"""keys of info_dict: name, path notes: if indexs of your img is 0,1,2,3, your frame num should be 4."""
self.name = info_dict['name']
self.path = info_dict['path']
self.save_path = info_dict['save_path']
def get_cover_frames(self):
... | the_stack_v2_python_sparse | preprocessing/preparation/2.extract_first.py | subburajs/ChaLearn-2021-ISLR-Challenge | train | 0 | |
5eaaaf7a891fe628366957175dac812bb10f7455 | [
"l = 0\nr = len(List) - 1\nif l > r:\n return None\nif l == r:\n return TreeNode(List[l])\nmid = int((l + r) / 2)\nroot = TreeNode(List[mid])\nroot.left = self.build_tree(List[:mid])\nroot.right = self.build_tree(List[mid + 1:])\nreturn root",
"if not root:\n return []\nqueue = []\nresult = []\nqueue.app... | <|body_start_0|>
l = 0
r = len(List) - 1
if l > r:
return None
if l == r:
return TreeNode(List[l])
mid = int((l + r) / 2)
root = TreeNode(List[mid])
root.left = self.build_tree(List[:mid])
root.right = self.build_tree(List[mid + 1:]... | 二叉树结构类 | BinaryTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryTree:
"""二叉树结构类"""
def build_tree(self, List):
"""构建一棵平衡二叉树，数组必须为排序好地数组，才能使得是平衡二叉树 前提：输入中序遍历，该列表必须满足一棵满二叉树，才能取中间结点为根结点，然后左右子树递归"""
<|body_0|>
def PrintFromTopToBottom(self, root):
"""从上往下打印二叉树——层序遍历"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_012344 | 4,104 | no_license | [
{
"docstring": "构建一棵平衡二叉树，数组必须为排序好地数组，才能使得是平衡二叉树 前提：输入中序遍历，该列表必须满足一棵满二叉树，才能取中间结点为根结点，然后左右子树递归",
"name": "build_tree",
"signature": "def build_tree(self, List)"
},
{
"docstring": "从上往下打印二叉树——层序遍历",
"name": "PrintFromTopToBottom",
"signature": "def PrintFromTopToBottom(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014033 | Implement the Python class `BinaryTree` described below.
Class description:
二叉树结构类
Method signatures and docstrings:
- def build_tree(self, List): 构建一棵平衡二叉树，数组必须为排序好地数组，才能使得是平衡二叉树 前提：输入中序遍历，该列表必须满足一棵满二叉树，才能取中间结点为根结点，然后左右子树递归
- def PrintFromTopToBottom(self, root): 从上往下打印二叉树——层序遍历 | Implement the Python class `BinaryTree` described below.
Class description:
二叉树结构类
Method signatures and docstrings:
- def build_tree(self, List): 构建一棵平衡二叉树，数组必须为排序好地数组，才能使得是平衡二叉树 前提：输入中序遍历，该列表必须满足一棵满二叉树，才能取中间结点为根结点，然后左右子树递归
- def PrintFromTopToBottom(self, root): 从上往下打印二叉树——层序遍历
<|skeleton|>
class BinaryTree:
"... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class BinaryTree:
"""二叉树结构类"""
def build_tree(self, List):
"""构建一棵平衡二叉树，数组必须为排序好地数组，才能使得是平衡二叉树 前提：输入中序遍历，该列表必须满足一棵满二叉树，才能取中间结点为根结点，然后左右子树递归"""
<|body_0|>
def PrintFromTopToBottom(self, root):
"""从上往下打印二叉树——层序遍历"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryTree:
"""二叉树结构类"""
def build_tree(self, List):
"""构建一棵平衡二叉树，数组必须为排序好地数组，才能使得是平衡二叉树 前提：输入中序遍历，该列表必须满足一棵满二叉树，才能取中间结点为根结点，然后左右子树递归"""
l = 0
r = len(List) - 1
if l > r:
return None
if l == r:
return TreeNode(List[l])
mid = int((l +... | the_stack_v2_python_sparse | 剑指offer/17.树的子结构.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 |
98b705b8745ea9f539f4e9a08af27bd40be13a13 | [
"today = datetime.date.today().strftime('%y%m%d')\nkey = 'num:{shop_id}:{order_type}:{today}'.format(shop_id=shop_id, order_type=order_type, today=today)\nredis_conn = get_redis_connection('num_generate')\nnum = redis_conn.incr(key)\nredis_conn.expire(key, 3600 * 24)\nresult = '{shop_type}{shop_id_fill}{today}{orde... | <|body_start_0|>
today = datetime.date.today().strftime('%y%m%d')
key = 'num:{shop_id}:{order_type}:{today}'.format(shop_id=shop_id, order_type=order_type, today=today)
redis_conn = get_redis_connection('num_generate')
num = redis_conn.incr(key)
redis_conn.expire(key, 3600 * 24)
... | 单号生成器 | NumGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumGenerator:
"""单号生成器"""
def generate(shop_id: int, order_type: int) -> str:
"""生成订单号，规则：店铺类型2位 + 店铺自增编号5位 + 订单日期6位 + 订单类型2位 + 订单自增编号4位 :param order_type: 订单类型: 1:普通订单，5:拼团订单"""
<|body_0|>
def decode(num: str) -> tuple:
"""解码订单号 :param num: 订单号码 :return: 店铺id, 订... | stack_v2_sparse_classes_36k_train_012345 | 6,425 | permissive | [
{
"docstring": "生成订单号，规则：店铺类型2位 + 店铺自增编号5位 + 订单日期6位 + 订单类型2位 + 订单自增编号4位 :param order_type: 订单类型: 1:普通订单，5:拼团订单",
"name": "generate",
"signature": "def generate(shop_id: int, order_type: int) -> str"
},
{
"docstring": "解码订单号 :param num: 订单号码 :return: 店铺id, 订单类型",
"name": "decode",
"signat... | 2 | stack_v2_sparse_classes_30k_test_000937 | Implement the Python class `NumGenerator` described below.
Class description:
单号生成器
Method signatures and docstrings:
- def generate(shop_id: int, order_type: int) -> str: 生成订单号，规则：店铺类型2位 + 店铺自增编号5位 + 订单日期6位 + 订单类型2位 + 订单自增编号4位 :param order_type: 订单类型: 1:普通订单，5:拼团订单
- def decode(num: str) -> tuple: 解码订单号 :param num: ... | Implement the Python class `NumGenerator` described below.
Class description:
单号生成器
Method signatures and docstrings:
- def generate(shop_id: int, order_type: int) -> str: 生成订单号，规则：店铺类型2位 + 店铺自增编号5位 + 订单日期6位 + 订单类型2位 + 订单自增编号4位 :param order_type: 订单类型: 1:普通订单，5:拼团订单
- def decode(num: str) -> tuple: 解码订单号 :param num: ... | c0a4de1a4479fe83f36108c1fdd4d68d18348b8d | <|skeleton|>
class NumGenerator:
"""单号生成器"""
def generate(shop_id: int, order_type: int) -> str:
"""生成订单号，规则：店铺类型2位 + 店铺自增编号5位 + 订单日期6位 + 订单类型2位 + 订单自增编号4位 :param order_type: 订单类型: 1:普通订单，5:拼团订单"""
<|body_0|>
def decode(num: str) -> tuple:
"""解码订单号 :param num: 订单号码 :return: 店铺id, 订... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumGenerator:
"""单号生成器"""
def generate(shop_id: int, order_type: int) -> str:
"""生成订单号，规则：店铺类型2位 + 店铺自增编号5位 + 订单日期6位 + 订单类型2位 + 订单自增编号4位 :param order_type: 订单类型: 1:普通订单，5:拼团订单"""
today = datetime.date.today().strftime('%y%m%d')
key = 'num:{shop_id}:{order_type}:{today}'.format(sho... | the_stack_v2_python_sparse | wsc_django/wsc_django/utils/core.py | hzh595395786/wsc_django | train | 2 |
6b195ac6442a1965b29863fe210658327ae9ea5b | [
"def residual(x):\n y_, log_dy_dx = bijection(x)\n return (y_ - y, log_dy_dx)\nwith torch.no_grad():\n x, log_dx_dy = root_finder(residual, x0=y)\nctx.save_for_backward(x, *params)\nctx.bijection = bijection\nreturn (x, log_dx_dy)",
"x, *params = ctx.saved_tensors\nwith torch.enable_grad():\n x = x.de... | <|body_start_0|>
def residual(x):
y_, log_dy_dx = bijection(x)
return (y_ - y, log_dy_dx)
with torch.no_grad():
x, log_dx_dy = root_finder(residual, x0=y)
ctx.save_for_backward(x, *params)
ctx.bijection = bijection
return (x, log_dx_dy)
<|end_b... | First-order-differentiation of an elementwise bijection under black-box inversion. | DifferentiableApproximateInverse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DifferentiableApproximateInverse:
"""First-order-differentiation of an elementwise bijection under black-box inversion."""
def forward(ctx, root_finder, bijection, y, *params):
"""Inverse pass Parameters ---------- ctx : object context object to stash information for the backward cal... | stack_v2_sparse_classes_36k_train_012346 | 8,727 | no_license | [
{
"docstring": "Inverse pass Parameters ---------- ctx : object context object to stash information for the backward call root_finder : Callable Root finding method, which takes two parameters (residue, x0) bijection : Flow a flow object, whose forward function returns (y, dlogp) y : torch.Tensor the input to t... | 2 | stack_v2_sparse_classes_30k_train_002511 | Implement the Python class `DifferentiableApproximateInverse` described below.
Class description:
First-order-differentiation of an elementwise bijection under black-box inversion.
Method signatures and docstrings:
- def forward(ctx, root_finder, bijection, y, *params): Inverse pass Parameters ---------- ctx : object... | Implement the Python class `DifferentiableApproximateInverse` described below.
Class description:
First-order-differentiation of an elementwise bijection under black-box inversion.
Method signatures and docstrings:
- def forward(ctx, root_finder, bijection, y, *params): Inverse pass Parameters ---------- ctx : object... | 15835d43a5ec2d29f05d325d65ffd973a6c8a201 | <|skeleton|>
class DifferentiableApproximateInverse:
"""First-order-differentiation of an elementwise bijection under black-box inversion."""
def forward(ctx, root_finder, bijection, y, *params):
"""Inverse pass Parameters ---------- ctx : object context object to stash information for the backward cal... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DifferentiableApproximateInverse:
"""First-order-differentiation of an elementwise bijection under black-box inversion."""
def forward(ctx, root_finder, bijection, y, *params):
"""Inverse pass Parameters ---------- ctx : object context object to stash information for the backward call root_finder... | the_stack_v2_python_sparse | bgflow/bgflow/nn/flow/root_finding/approx_inverse.py | noegroup/smooth_normalizing_flows | train | 1 |
c5c5c9e51526029c580e1690e6c14ca4d7f0583f | [
"Parameter.checkFloat(tau, 0.0, 1.0)\nParameter.checkClass(kernelX, AbstractKernel)\nParameter.checkClass(kernelY, AbstractKernel)\nself.kernelX = kernelX\nself.kernelY = kernelY\nself.tau = tau",
"self.trainX = X\nself.trainY = Y\nKx = self.kernelX.evaluate(X, X)\nKy = self.kernelX.evaluate(Y, Y)\nKxx = numpy.do... | <|body_start_0|>
Parameter.checkFloat(tau, 0.0, 1.0)
Parameter.checkClass(kernelX, AbstractKernel)
Parameter.checkClass(kernelY, AbstractKernel)
self.kernelX = kernelX
self.kernelY = kernelY
self.tau = tau
<|end_body_0|>
<|body_start_1|>
self.trainX = X
s... | KernelCCA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KernelCCA:
def __init__(self, kernelX, kernelY, tau):
"""Intialise the object with kernels (i.e an object instantiating a subclass of AbstractKernel) on the X and Y spaces and regularisation parameter tau between 0 (no regularisation) and 1 (full regularisation). :param kernelX: The kern... | stack_v2_sparse_classes_36k_train_012347 | 3,998 | no_license | [
{
"docstring": "Intialise the object with kernels (i.e an object instantiating a subclass of AbstractKernel) on the X and Y spaces and regularisation parameter tau between 0 (no regularisation) and 1 (full regularisation). :param kernelX: The kernel object on the X examples. :type kernelX: :class:`apgl.kernel.A... | 3 | null | Implement the Python class `KernelCCA` described below.
Class description:
Implement the KernelCCA class.
Method signatures and docstrings:
- def __init__(self, kernelX, kernelY, tau): Intialise the object with kernels (i.e an object instantiating a subclass of AbstractKernel) on the X and Y spaces and regularisation... | Implement the Python class `KernelCCA` described below.
Class description:
Implement the KernelCCA class.
Method signatures and docstrings:
- def __init__(self, kernelX, kernelY, tau): Intialise the object with kernels (i.e an object instantiating a subclass of AbstractKernel) on the X and Y spaces and regularisation... | 1703510cbb51ec6df0efe1de850cd48ef7004b00 | <|skeleton|>
class KernelCCA:
def __init__(self, kernelX, kernelY, tau):
"""Intialise the object with kernels (i.e an object instantiating a subclass of AbstractKernel) on the X and Y spaces and regularisation parameter tau between 0 (no regularisation) and 1 (full regularisation). :param kernelX: The kern... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KernelCCA:
def __init__(self, kernelX, kernelY, tau):
"""Intialise the object with kernels (i.e an object instantiating a subclass of AbstractKernel) on the X and Y spaces and regularisation parameter tau between 0 (no regularisation) and 1 (full regularisation). :param kernelX: The kernel object on t... | the_stack_v2_python_sparse | apgl/features/KernelCCA.py | malcolmreynolds/APGL | train | 0 | |
e05abbef9c25320578f58a3065230ba6d8503014 | [
"if not root:\n return '[]'\nfrom collections import deque\nq = deque()\nq.append(root)\nres = []\nwhile q:\n temp = q.popleft()\n if temp:\n res.append(str(temp.val))\n q.append(temp.left)\n q.append(temp.right)\n else:\n res.append('null')\nreturn '[' + ','.join(res) + ']'"... | <|body_start_0|>
if not root:
return '[]'
from collections import deque
q = deque()
q.append(root)
res = []
while q:
temp = q.popleft()
if temp:
res.append(str(temp.val))
q.append(temp.left)
... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_012348 | 3,372 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | a81007908e3c2f65a6be3ff2d62dfb92d0753b0d | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return '[]'
from collections import deque
q = deque()
q.append(root)
res = []
while q:
temp = q.popleft()
... | the_stack_v2_python_sparse | algo_probs/jzoffer/jz37.py | Jackthebighead/recruiment-2022 | train | 0 | |
9287250760624f3e344034fb105186a21f6ae4f2 | [
"response = utility.ExecutorResponse()\nerr_msg = 'Testing handling of OSError'\nwith patch('subprocess.run') as mock_run:\n mock_run.side_effect = MagicMock(side_effect=OSError(err_msg))\n response.execute_command([])\nself.assertEqual(response._stdout, '')\nself.assertEqual(response._stderr, err_msg)",
"t... | <|body_start_0|>
response = utility.ExecutorResponse()
err_msg = 'Testing handling of OSError'
with patch('subprocess.run') as mock_run:
mock_run.side_effect = MagicMock(side_effect=OSError(err_msg))
response.execute_command([])
self.assertEqual(response._stdout, ... | UtilityTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UtilityTest:
def test_execute_command_oserror(self):
"""Testing stdout and stderr is correctly captured upon OSError."""
<|body_0|>
def test_execute_command_stdout(self):
"""Testing stdout output is correctly captured."""
<|body_1|>
def test_execute_comm... | stack_v2_sparse_classes_36k_train_012349 | 2,714 | permissive | [
{
"docstring": "Testing stdout and stderr is correctly captured upon OSError.",
"name": "test_execute_command_oserror",
"signature": "def test_execute_command_oserror(self)"
},
{
"docstring": "Testing stdout output is correctly captured.",
"name": "test_execute_command_stdout",
"signatur... | 5 | stack_v2_sparse_classes_30k_train_013368 | Implement the Python class `UtilityTest` described below.
Class description:
Implement the UtilityTest class.
Method signatures and docstrings:
- def test_execute_command_oserror(self): Testing stdout and stderr is correctly captured upon OSError.
- def test_execute_command_stdout(self): Testing stdout output is corr... | Implement the Python class `UtilityTest` described below.
Class description:
Implement the UtilityTest class.
Method signatures and docstrings:
- def test_execute_command_oserror(self): Testing stdout and stderr is correctly captured upon OSError.
- def test_execute_command_stdout(self): Testing stdout output is corr... | 3fb199658f68e7debf4906d9ce32a9a307e39243 | <|skeleton|>
class UtilityTest:
def test_execute_command_oserror(self):
"""Testing stdout and stderr is correctly captured upon OSError."""
<|body_0|>
def test_execute_command_stdout(self):
"""Testing stdout output is correctly captured."""
<|body_1|>
def test_execute_comm... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UtilityTest:
def test_execute_command_oserror(self):
"""Testing stdout and stderr is correctly captured upon OSError."""
response = utility.ExecutorResponse()
err_msg = 'Testing handling of OSError'
with patch('subprocess.run') as mock_run:
mock_run.side_effect = Ma... | the_stack_v2_python_sparse | sdk/python/kfp/cli/diagnose_me/utility_test.py | kubeflow/pipelines | train | 3,434 | |
6f352844dd7a9acce659d9b4f688fbda3ab5b746 | [
"self.data = data\nself.eof = eof\nself.error = error\nself.file_length = file_length\nself.start_offset = start_offset",
"if dictionary is None:\n return None\ndata = dictionary.get('data')\neof = dictionary.get('eof')\nerror = cohesity_management_sdk.models.error_proto.ErrorProto.from_dictionary(dictionary.g... | <|body_start_0|>
self.data = data
self.eof = eof
self.error = error
self.file_length = file_length
self.start_offset = start_offset
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
data = dictionary.get('data')
eof = dictiona... | Implementation of the 'ExtractFileRangeResult' model. This will capture output of ExtractFileRange and ExtractNFSFileRange. Attributes: data (list of long|int): The actual data bytes. eof (bool): Will be true if start_offset > file length or EOF is reached. This is an alternative to using file_length to determine when ... | ExtractFileRangeResult | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtractFileRangeResult:
"""Implementation of the 'ExtractFileRangeResult' model. This will capture output of ExtractFileRange and ExtractNFSFileRange. Attributes: data (list of long|int): The actual data bytes. eof (bool): Will be true if start_offset > file length or EOF is reached. This is an a... | stack_v2_sparse_classes_36k_train_012350 | 2,663 | permissive | [
{
"docstring": "Constructor for the ExtractFileRangeResult class",
"name": "__init__",
"signature": "def __init__(self, data=None, eof=None, error=None, file_length=None, start_offset=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A d... | 2 | null | Implement the Python class `ExtractFileRangeResult` described below.
Class description:
Implementation of the 'ExtractFileRangeResult' model. This will capture output of ExtractFileRange and ExtractNFSFileRange. Attributes: data (list of long|int): The actual data bytes. eof (bool): Will be true if start_offset > file... | Implement the Python class `ExtractFileRangeResult` described below.
Class description:
Implementation of the 'ExtractFileRangeResult' model. This will capture output of ExtractFileRange and ExtractNFSFileRange. Attributes: data (list of long|int): The actual data bytes. eof (bool): Will be true if start_offset > file... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ExtractFileRangeResult:
"""Implementation of the 'ExtractFileRangeResult' model. This will capture output of ExtractFileRange and ExtractNFSFileRange. Attributes: data (list of long|int): The actual data bytes. eof (bool): Will be true if start_offset > file length or EOF is reached. This is an a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExtractFileRangeResult:
"""Implementation of the 'ExtractFileRangeResult' model. This will capture output of ExtractFileRange and ExtractNFSFileRange. Attributes: data (list of long|int): The actual data bytes. eof (bool): Will be true if start_offset > file length or EOF is reached. This is an alternative to... | the_stack_v2_python_sparse | cohesity_management_sdk/models/extract_file_range_result.py | cohesity/management-sdk-python | train | 24 |
bb44a0ff42db36d942dbe184c7a09a2e11a3791c | [
"sq = []\ntq = []\nfor s in S:\n if s != '#':\n sq.append(s)\n else:\n try:\n sq.pop()\n except:\n pass\nfor t in T:\n if t != '#':\n tq.append(t)\n else:\n try:\n tq.pop()\n except:\n pass\nreturn tq == sq",
"s_str ... | <|body_start_0|>
sq = []
tq = []
for s in S:
if s != '#':
sq.append(s)
else:
try:
sq.pop()
except:
pass
for t in T:
if t != '#':
tq.append(t)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sq = []
tq = []
... | stack_v2_sparse_classes_36k_train_012351 | 2,623 | permissive | [
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "_backspaceCompare",
"signature": "def _backspaceCompare(self, S, T)"
},
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "backspaceCompare",
"signature": "def backspaceCompare(self, S, T)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
<|skeleton|>
class Solution:... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
sq = []
tq = []
for s in S:
if s != '#':
sq.append(s)
else:
try:
sq.pop()
except:
... | the_stack_v2_python_sparse | 844.backspace-string-compare.py | windard/leeeeee | train | 0 | |
85093ce0dde3042a1641d214fe093650ef2e44d4 | [
"if not nums:\n return 1\nzeros = [0] * (max(nums) + 2)\nfor num in nums:\n if num > 0:\n zeros[num] = 1\nfor i in range(1, len(zeros)):\n if zeros[i] != 1:\n return i",
"nums = set(nums)\nfor i in range(1, len(nums) + 2):\n if i not in nums:\n return i",
"zeros = [0] * (len(num... | <|body_start_0|>
if not nums:
return 1
zeros = [0] * (max(nums) + 2)
for num in nums:
if num > 0:
zeros[num] = 1
for i in range(1, len(zeros)):
if zeros[i] != 1:
return i
<|end_body_0|>
<|body_start_1|>
nums = s... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def __firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def ___firstMissingPositive(self, nums):
""":type nums:... | stack_v2_sparse_classes_36k_train_012352 | 2,642 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "_firstMissingPositive",
"signature": "def _firstMissingPositive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "__firstMissingPositive",
"signature": "def __firstMissingPositive(self, nums)"
},
... | 4 | stack_v2_sparse_classes_30k_train_012351 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def __firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def ___firstMissingPositive... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def __firstMissingPositive(self, nums): :type nums: List[int] :rtype: int
- def ___firstMissingPositive... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def __firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def ___firstMissingPositive(self, nums):
""":type nums:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 1
zeros = [0] * (max(nums) + 2)
for num in nums:
if num > 0:
zeros[num] = 1
for i in range(1, len(zeros)):
if... | the_stack_v2_python_sparse | 41.first-missing-positive.py | windard/leeeeee | train | 0 | |
8d9be2ff8b8ac9e088adef79f4e58bfeccb68d13 | [
"context = {'measurements_form': forms.DatasetTypeMeasurementsForm(), 'flags_definition_form': forms.DatasetTypeFlagsDefinitionForm(), 'dataset_type_id': dataset_type_id}\ndataset_type = models.DatasetType.objects.using('agdc').get(id=dataset_type_id)\ncontext.update(utils.forms_from_definition(dataset_type.definit... | <|body_start_0|>
context = {'measurements_form': forms.DatasetTypeMeasurementsForm(), 'flags_definition_form': forms.DatasetTypeFlagsDefinitionForm(), 'dataset_type_id': dataset_type_id}
dataset_type = models.DatasetType.objects.using('agdc').get(id=dataset_type_id)
context.update(utils.forms_fr... | Main end piont for viewing or adding a dataset type | DatasetTypeView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatasetTypeView:
"""Main end piont for viewing or adding a dataset type"""
def get(self, request, dataset_type_id=None):
"""View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the d... | stack_v2_sparse_classes_36k_train_012353 | 10,227 | permissive | [
{
"docstring": "View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the dataset type",
"name": "get",
"signature": "def get(self, request, dataset_type_id=None)"
},
{
"docstring": "Add a datase... | 2 | stack_v2_sparse_classes_30k_train_011957 | Implement the Python class `DatasetTypeView` described below.
Class description:
Main end piont for viewing or adding a dataset type
Method signatures and docstrings:
- def get(self, request, dataset_type_id=None): View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, Datas... | Implement the Python class `DatasetTypeView` described below.
Class description:
Main end piont for viewing or adding a dataset type
Method signatures and docstrings:
- def get(self, request, dataset_type_id=None): View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, Datas... | ef50e918df89313f130d735e7cb7c0a069da410e | <|skeleton|>
class DatasetTypeView:
"""Main end piont for viewing or adding a dataset type"""
def get(self, request, dataset_type_id=None):
"""View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatasetTypeView:
"""Main end piont for viewing or adding a dataset type"""
def get(self, request, dataset_type_id=None):
"""View a dataset type and all its attributes Context: Bound forms for: DatasetTypeMeasurementsForm, DatasetTypeFlagsDefinitionForm dataset_type_id: id/pk of the dataset type""... | the_stack_v2_python_sparse | apps/data_cube_manager/views/dataset_type.py | ceos-seo/data_cube_ui | train | 47 |
af037bb5ad00faf28b049035574e0958ac91e08f | [
"super(MotionFieldEncoder, self).__init__()\nconv_prop_0 = {'kernel_size': 3, 'strides': 2, 'activation': 'relu', 'padding': 'same', 'kernel_regularizer': tf.keras.regularizers.L2(weight_reg)}\nself.conv_encoder = []\nnum_conv_enc = 7\nchannels = [6]\nfor i in range(1, num_conv_enc + 1):\n channels.append(2 ** (... | <|body_start_0|>
super(MotionFieldEncoder, self).__init__()
conv_prop_0 = {'kernel_size': 3, 'strides': 2, 'activation': 'relu', 'padding': 'same', 'kernel_regularizer': tf.keras.regularizers.L2(weight_reg)}
self.conv_encoder = []
num_conv_enc = 7
channels = [6]
for i in ... | MotionFieldEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MotionFieldEncoder:
def __init__(self, weight_reg=0.0):
"""Predict object-motion vectors from a stack of frames. auto_mask: True to automatically masking out the residual translations by thresholding on their mean values. weight_reg: A float scalar, the amount of weight regularization.""... | stack_v2_sparse_classes_36k_train_012354 | 18,266 | no_license | [
{
"docstring": "Predict object-motion vectors from a stack of frames. auto_mask: True to automatically masking out the residual translations by thresholding on their mean values. weight_reg: A float scalar, the amount of weight regularization.",
"name": "__init__",
"signature": "def __init__(self, weigh... | 2 | stack_v2_sparse_classes_30k_train_017842 | Implement the Python class `MotionFieldEncoder` described below.
Class description:
Implement the MotionFieldEncoder class.
Method signatures and docstrings:
- def __init__(self, weight_reg=0.0): Predict object-motion vectors from a stack of frames. auto_mask: True to automatically masking out the residual translatio... | Implement the Python class `MotionFieldEncoder` described below.
Class description:
Implement the MotionFieldEncoder class.
Method signatures and docstrings:
- def __init__(self, weight_reg=0.0): Predict object-motion vectors from a stack of frames. auto_mask: True to automatically masking out the residual translatio... | a7be32bad38fc9555f480d2db1174aa4dd4d5d37 | <|skeleton|>
class MotionFieldEncoder:
def __init__(self, weight_reg=0.0):
"""Predict object-motion vectors from a stack of frames. auto_mask: True to automatically masking out the residual translations by thresholding on their mean values. weight_reg: A float scalar, the amount of weight regularization.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MotionFieldEncoder:
def __init__(self, weight_reg=0.0):
"""Predict object-motion vectors from a stack of frames. auto_mask: True to automatically masking out the residual translations by thresholding on their mean values. weight_reg: A float scalar, the amount of weight regularization."""
supe... | the_stack_v2_python_sparse | models/motion_filed_net.py | dexter2406/Monodepth2-TF2 | train | 3 | |
6e2f8466664eddb8afcb5c87a0f6feb57fb95fc8 | [
"super(ChoicePhoneField, self).validate(value)\nif value and (not self.valid_value(value)):\n raise ValidationError(self.error_messages['invalid_choice'] % {'value': value})",
"for k, v, j, f in self.choices:\n if isinstance(v, (list, tuple)):\n for k2, v2 in v:\n if value == smart_unicode... | <|body_start_0|>
super(ChoicePhoneField, self).validate(value)
if value and (not self.valid_value(value)):
raise ValidationError(self.error_messages['invalid_choice'] % {'value': value})
<|end_body_0|>
<|body_start_1|>
for k, v, j, f in self.choices:
if isinstance(v, (li... | ChoicePhoneField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChoicePhoneField:
def validate(self, value):
"""Validates that the input is in self.choices."""
<|body_0|>
def valid_value(self, value):
"""Check to see if the provided value is a valid choice"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(Ch... | stack_v2_sparse_classes_36k_train_012355 | 9,752 | no_license | [
{
"docstring": "Validates that the input is in self.choices.",
"name": "validate",
"signature": "def validate(self, value)"
},
{
"docstring": "Check to see if the provided value is a valid choice",
"name": "valid_value",
"signature": "def valid_value(self, value)"
}
] | 2 | null | Implement the Python class `ChoicePhoneField` described below.
Class description:
Implement the ChoicePhoneField class.
Method signatures and docstrings:
- def validate(self, value): Validates that the input is in self.choices.
- def valid_value(self, value): Check to see if the provided value is a valid choice | Implement the Python class `ChoicePhoneField` described below.
Class description:
Implement the ChoicePhoneField class.
Method signatures and docstrings:
- def validate(self, value): Validates that the input is in self.choices.
- def valid_value(self, value): Check to see if the provided value is a valid choice
<|sk... | 302324dccc135f55d92fb705c58314c55fed22aa | <|skeleton|>
class ChoicePhoneField:
def validate(self, value):
"""Validates that the input is in self.choices."""
<|body_0|>
def valid_value(self, value):
"""Check to see if the provided value is a valid choice"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChoicePhoneField:
def validate(self, value):
"""Validates that the input is in self.choices."""
super(ChoicePhoneField, self).validate(value)
if value and (not self.valid_value(value)):
raise ValidationError(self.error_messages['invalid_choice'] % {'value': value})
def... | the_stack_v2_python_sparse | django-shared/geobase/phone_code_widget.py | riyanhax/a-demo | train | 0 | |
16361925bc8dc93e9b8e3925fca08a72a4481964 | [
"handler = self.get_handler()\nattrdate = handler.getncattr('first_meas_time')\nreturn datetime.strptime(attrdate, '%Y-%m-%d %H:%M:%S.%f')",
"handler = self.get_handler()\nattrdate = handler.getncattr('last_meas_time')\nreturn datetime.strptime(attrdate, '%Y-%m-%d %H:%M:%S.%f')"
] | <|body_start_0|>
handler = self.get_handler()
attrdate = handler.getncattr('first_meas_time')
return datetime.strptime(attrdate, '%Y-%m-%d %H:%M:%S.%f')
<|end_body_0|>
<|body_start_1|>
handler = self.get_handler()
attrdate = handler.getncattr('last_meas_time')
return dat... | Mapper for CryoSat-2 Altimeter files from NOAA RADS 4.0. Overrides the NCFile mapper to take into account some specific attributes naming | Cryosat2NCFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cryosat2NCFile:
"""Mapper for CryoSat-2 Altimeter files from NOAA RADS 4.0. Overrides the NCFile mapper to take into account some specific attributes naming"""
def get_start_time(self):
"""Returns the minimum date of the file temporal coverage"""
<|body_0|>
def get_end_t... | stack_v2_sparse_classes_36k_train_012356 | 1,156 | no_license | [
{
"docstring": "Returns the minimum date of the file temporal coverage",
"name": "get_start_time",
"signature": "def get_start_time(self)"
},
{
"docstring": "Returns the maximum date of the file temporal coverage",
"name": "get_end_time",
"signature": "def get_end_time(self)"
}
] | 2 | null | Implement the Python class `Cryosat2NCFile` described below.
Class description:
Mapper for CryoSat-2 Altimeter files from NOAA RADS 4.0. Overrides the NCFile mapper to take into account some specific attributes naming
Method signatures and docstrings:
- def get_start_time(self): Returns the minimum date of the file t... | Implement the Python class `Cryosat2NCFile` described below.
Class description:
Mapper for CryoSat-2 Altimeter files from NOAA RADS 4.0. Overrides the NCFile mapper to take into account some specific attributes naming
Method signatures and docstrings:
- def get_start_time(self): Returns the minimum date of the file t... | 3c354f2ca69dc981eb4117976351e8d7454ad505 | <|skeleton|>
class Cryosat2NCFile:
"""Mapper for CryoSat-2 Altimeter files from NOAA RADS 4.0. Overrides the NCFile mapper to take into account some specific attributes naming"""
def get_start_time(self):
"""Returns the minimum date of the file temporal coverage"""
<|body_0|>
def get_end_t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cryosat2NCFile:
"""Mapper for CryoSat-2 Altimeter files from NOAA RADS 4.0. Overrides the NCFile mapper to take into account some specific attributes naming"""
def get_start_time(self):
"""Returns the minimum date of the file temporal coverage"""
handler = self.get_handler()
attrd... | the_stack_v2_python_sparse | cerbere/cerbere/mapper/cryosat2ncfile.py | whigg/PySOL | train | 0 |
b56a033581dd529f285a21ea85b11b295499f7c2 | [
"context = {'page_title': 'Forgot Password', 'email_form': EmailForm(auto_id=True)}\ncontext.update(csrf(request))\nreturn render(request, 'authentication/forgot_password.html', context)",
"email_form = EmailForm(request.POST, auto_id=True)\nif email_form.is_valid():\n try:\n input_email = email_form.cl... | <|body_start_0|>
context = {'page_title': 'Forgot Password', 'email_form': EmailForm(auto_id=True)}
context.update(csrf(request))
return render(request, 'authentication/forgot_password.html', context)
<|end_body_0|>
<|body_start_1|>
email_form = EmailForm(request.POST, auto_id=True)
... | This class allows user to send account recovery email. | ForgotPasswordView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForgotPasswordView:
"""This class allows user to send account recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse."""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_012357 | 17,941 | permissive | [
{
"docstring": "Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Handles the POST request to the 'account_forgot_password' ... | 2 | null | Implement the Python class `ForgotPasswordView` described below.
Class description:
This class allows user to send account recovery email.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template... | Implement the Python class `ForgotPasswordView` described below.
Class description:
This class allows user to send account recovery email.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template... | 3704cbe6e69ba3e4c53401d3bbc339208e9ebccd | <|skeleton|>
class ForgotPasswordView:
"""This class allows user to send account recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse."""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ForgotPasswordView:
"""This class allows user to send account recovery email."""
def get(self, request, *args, **kwargs):
"""Handles GET requests to the 'account_forgot_password' named route. Returns: A forgot-password template rendered to a HttpResponse."""
context = {'page_title': 'Forg... | the_stack_v2_python_sparse | troupon/authentication/views.py | morristech/troupon | train | 0 |
d7734a6fe05cf6219c28e93dffecae0c932c3fdf | [
"optimal_policy_path = os.path.dirname(os.getcwd()) + '/optimal_policy.pkl'\nself.optimal_policy, _ = pickle.load(open(optimal_policy_path, 'rb'))\nprint('Optimal policy loaded.')\n' Load the policy to be evaluated \\n '\npolicy_path = os.path.dirname(os.getcwd()) + '/policy_evaluation.pkl'\nself.policy, i... | <|body_start_0|>
optimal_policy_path = os.path.dirname(os.getcwd()) + '/optimal_policy.pkl'
self.optimal_policy, _ = pickle.load(open(optimal_policy_path, 'rb'))
print('Optimal policy loaded.')
' Load the policy to be evaluated \n '
policy_path = os.path.dirname(os.getcw... | EvaluateAgainstOptimal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvaluateAgainstOptimal:
def __init__(self):
"""Load an optimal policy"""
<|body_0|>
def Run(self):
"""Evaluate the performance of the policy as player X"""
<|body_1|>
def AutoPlay(self, policy_1, policy_2, n_games=100):
"""Let policy_1 and policy... | stack_v2_sparse_classes_36k_train_012358 | 2,769 | no_license | [
{
"docstring": "Load an optimal policy",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Evaluate the performance of the policy as player X",
"name": "Run",
"signature": "def Run(self)"
},
{
"docstring": "Let policy_1 and policy_2 play against each other ... | 4 | stack_v2_sparse_classes_30k_train_005543 | Implement the Python class `EvaluateAgainstOptimal` described below.
Class description:
Implement the EvaluateAgainstOptimal class.
Method signatures and docstrings:
- def __init__(self): Load an optimal policy
- def Run(self): Evaluate the performance of the policy as player X
- def AutoPlay(self, policy_1, policy_2... | Implement the Python class `EvaluateAgainstOptimal` described below.
Class description:
Implement the EvaluateAgainstOptimal class.
Method signatures and docstrings:
- def __init__(self): Load an optimal policy
- def Run(self): Evaluate the performance of the policy as player X
- def AutoPlay(self, policy_1, policy_2... | 5831d4c1eaf21d41007eb6988f3c9885b55d13b2 | <|skeleton|>
class EvaluateAgainstOptimal:
def __init__(self):
"""Load an optimal policy"""
<|body_0|>
def Run(self):
"""Evaluate the performance of the policy as player X"""
<|body_1|>
def AutoPlay(self, policy_1, policy_2, n_games=100):
"""Let policy_1 and policy... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EvaluateAgainstOptimal:
def __init__(self):
"""Load an optimal policy"""
optimal_policy_path = os.path.dirname(os.getcwd()) + '/optimal_policy.pkl'
self.optimal_policy, _ = pickle.load(open(optimal_policy_path, 'rb'))
print('Optimal policy loaded.')
' Load the policy to... | the_stack_v2_python_sparse | ttt_evaluate_against_optimal.py | sw2703/rl_tictactoe | train | 0 | |
6bb5f0336d6b43662b746260bedb007303a47f96 | [
"q = [root]\nstr_res = ''\nwhile q:\n q_temp = []\n for node in q:\n if node:\n str_res += ',' + str(node.val)\n q_temp.append(node.left)\n q_temp.append(node.right)\n else:\n str_res += ',None'\n q = q_temp\nreturn str_res[1:]",
"if not data or d... | <|body_start_0|>
q = [root]
str_res = ''
while q:
q_temp = []
for node in q:
if node:
str_res += ',' + str(node.val)
q_temp.append(node.left)
q_temp.append(node.right)
else:
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_012359 | 1,809 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 13e61c13c406a73debcfc996937cf16f715d55d1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
q = [root]
str_res = ''
while q:
q_temp = []
for node in q:
if node:
str_res += ',' + str(node.val)
... | the_stack_v2_python_sparse | src/297_serialize_and_deserialize_binary_tree/297_serialize_and_deserialize_binary_tree_BasedBfs.py | ypliu/leetcode-python | train | 0 | |
116afa45e8b6a56bb2c18a1ad75127a152ede077 | [
"if type is not None:\n assert type >= 256, type\nif content is not None:\n assert not isinstance(content, str), repr(content)\n newcontent = list(content)\n for i, item in enumerate(newcontent):\n assert isinstance(item, BasePattern), (i, item)\n if isinstance(item, WildcardPattern):\n ... | <|body_start_0|>
if type is not None:
assert type >= 256, type
if content is not None:
assert not isinstance(content, str), repr(content)
newcontent = list(content)
for i, item in enumerate(newcontent):
assert isinstance(item, BasePattern),... | NodePattern | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-other-copyleft",
"GPL-1.0-or-later",
"Python-2.0",
"LicenseRef-scancode-python-cwi"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodePattern:
def __init__(self, type: Optional[int]=None, content: Optional[Iterable[str]]=None, name: Optional[str]=None) -> None:
"""Initializer. Takes optional type, content, and name. The type, if given, must be a symbol type (>= 256). If the type is None this matches *any* single no... | stack_v2_sparse_classes_36k_train_012360 | 32,569 | permissive | [
{
"docstring": "Initializer. Takes optional type, content, and name. The type, if given, must be a symbol type (>= 256). If the type is None this matches *any* single node (leaf or not), except if content is not None, in which it only matches non-leaf nodes that also match the content pattern. The content, if n... | 2 | stack_v2_sparse_classes_30k_train_018095 | Implement the Python class `NodePattern` described below.
Class description:
Implement the NodePattern class.
Method signatures and docstrings:
- def __init__(self, type: Optional[int]=None, content: Optional[Iterable[str]]=None, name: Optional[str]=None) -> None: Initializer. Takes optional type, content, and name. ... | Implement the Python class `NodePattern` described below.
Class description:
Implement the NodePattern class.
Method signatures and docstrings:
- def __init__(self, type: Optional[int]=None, content: Optional[Iterable[str]]=None, name: Optional[str]=None) -> None: Initializer. Takes optional type, content, and name. ... | 47676bf5939ae5c8e670d947917bc8af4732eab6 | <|skeleton|>
class NodePattern:
def __init__(self, type: Optional[int]=None, content: Optional[Iterable[str]]=None, name: Optional[str]=None) -> None:
"""Initializer. Takes optional type, content, and name. The type, if given, must be a symbol type (>= 256). If the type is None this matches *any* single no... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NodePattern:
def __init__(self, type: Optional[int]=None, content: Optional[Iterable[str]]=None, name: Optional[str]=None) -> None:
"""Initializer. Takes optional type, content, and name. The type, if given, must be a symbol type (>= 256). If the type is None this matches *any* single node (leaf or no... | the_stack_v2_python_sparse | src/blib2to3/pytree.py | psf/black | train | 23,453 | |
90e3d66ea7b36248c213bcae2c8fd2a12a388b1c | [
"self.config = get_config()\nself.config[STATES_KEYWORD] = {'attrs': self.config[STATES_KEYWORD]['attrs'], 'subset': [0]}\nself.base_path = path_to_base_field\nif randomizer is not None:\n self.randomizer = {}\n for key, def_r in self.default_randomizer.items():\n if key not in randomizer.keys() or ran... | <|body_start_0|>
self.config = get_config()
self.config[STATES_KEYWORD] = {'attrs': self.config[STATES_KEYWORD]['attrs'], 'subset': [0]}
self.base_path = path_to_base_field
if randomizer is not None:
self.randomizer = {}
for key, def_r in self.default_randomizer.i... | Randomization of Fields, based on some base model. | FieldRandomizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FieldRandomizer:
"""Randomization of Fields, based on some base model."""
def __init__(self, path_to_base_field, randomizer=None):
"""Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for... | stack_v2_sparse_classes_36k_train_012361 | 13,810 | permissive | [
{
"docstring": "Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for states, rock and control (wells) Should have keys the following form: randomizer = { 'states': states_rand, 'rock': rock_rand, 'wells': control_r... | 4 | stack_v2_sparse_classes_30k_train_014398 | Implement the Python class `FieldRandomizer` described below.
Class description:
Randomization of Fields, based on some base model.
Method signatures and docstrings:
- def __init__(self, path_to_base_field, randomizer=None): Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around... | Implement the Python class `FieldRandomizer` described below.
Class description:
Randomization of Fields, based on some base model.
Method signatures and docstrings:
- def __init__(self, path_to_base_field, randomizer=None): Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around... | 3b336ed110ff806316f1f6a99b212f99256a6b56 | <|skeleton|>
class FieldRandomizer:
"""Randomization of Fields, based on some base model."""
def __init__(self, path_to_base_field, randomizer=None):
"""Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FieldRandomizer:
"""Randomization of Fields, based on some base model."""
def __init__(self, path_to_base_field, randomizer=None):
"""Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for states, rock... | the_stack_v2_python_sparse | deepfield/datasets/randomize.py | scuervo91/DeepField | train | 0 |
76d64f53001b8c812ba2d1c6c5c78bd4ba8d11c0 | [
"super().__init__(maxiter=maxiter, gtol=gtol, etol=etol, **kwargs)\nself._line_search_type = line_search_type\nself._hessian_update_types = [BFGSUpdate, NullUpdate]\nself._alpha = init_alpha",
"assert self._coords is not None and self._coords.g is not None and (self._species is not None) and (self._method is not ... | <|body_start_0|>
super().__init__(maxiter=maxiter, gtol=gtol, etol=etol, **kwargs)
self._line_search_type = line_search_type
self._hessian_update_types = [BFGSUpdate, NullUpdate]
self._alpha = init_alpha
<|end_body_0|>
<|body_start_1|>
assert self._coords is not None and self._c... | BFGSOptimiser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BFGSOptimiser:
def __init__(self, maxiter: int, gtol: GradientRMS, etol: PotentialEnergy, init_alpha: float=1.0, line_search_type: Type[LineSearchOptimiser]=ArmijoLineSearch, **kwargs):
"""Broyden–Fletcher–Goldfarb–Shanno optimiser. Implementation taken from: https://tinyurl.com/526yymsw... | stack_v2_sparse_classes_36k_train_012362 | 3,008 | permissive | [
{
"docstring": "Broyden–Fletcher–Goldfarb–Shanno optimiser. Implementation taken from: https://tinyurl.com/526yymsw ---------------------------------------------------------------------- Arguments: init_alpha (float): Length of the initial step to take in the line search. Units of distance See Also: :py:meth:`N... | 2 | null | Implement the Python class `BFGSOptimiser` described below.
Class description:
Implement the BFGSOptimiser class.
Method signatures and docstrings:
- def __init__(self, maxiter: int, gtol: GradientRMS, etol: PotentialEnergy, init_alpha: float=1.0, line_search_type: Type[LineSearchOptimiser]=ArmijoLineSearch, **kwargs... | Implement the Python class `BFGSOptimiser` described below.
Class description:
Implement the BFGSOptimiser class.
Method signatures and docstrings:
- def __init__(self, maxiter: int, gtol: GradientRMS, etol: PotentialEnergy, init_alpha: float=1.0, line_search_type: Type[LineSearchOptimiser]=ArmijoLineSearch, **kwargs... | 4d6667592f083dfcf38de6b75c4222c0a0e7b60b | <|skeleton|>
class BFGSOptimiser:
def __init__(self, maxiter: int, gtol: GradientRMS, etol: PotentialEnergy, init_alpha: float=1.0, line_search_type: Type[LineSearchOptimiser]=ArmijoLineSearch, **kwargs):
"""Broyden–Fletcher–Goldfarb–Shanno optimiser. Implementation taken from: https://tinyurl.com/526yymsw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BFGSOptimiser:
def __init__(self, maxiter: int, gtol: GradientRMS, etol: PotentialEnergy, init_alpha: float=1.0, line_search_type: Type[LineSearchOptimiser]=ArmijoLineSearch, **kwargs):
"""Broyden–Fletcher–Goldfarb–Shanno optimiser. Implementation taken from: https://tinyurl.com/526yymsw -------------... | the_stack_v2_python_sparse | autode/opt/optimisers/bfgs.py | duartegroup/autodE | train | 132 | |
04d60c9c440f4649566f636ebb4f13702a25aeb4 | [
"res = []\nself.backtrack([], [], [], n, res)\nprint(res)\nfinal_res = []\nfor sol in res:\n str_res = [['.' for _ in range(n)] for _ in range(n)]\n for i, j in enumerate(sol):\n str_res[i][j] = 'Q'\n final_res.append(map(lambda x: ''.join(x), str_res))\nreturn final_res",
"if len(queens) == n:\n ... | <|body_start_0|>
res = []
self.backtrack([], [], [], n, res)
print(res)
final_res = []
for sol in res:
str_res = [['.' for _ in range(n)] for _ in range(n)]
for i, j in enumerate(sol):
str_res[i][j] = 'Q'
final_res.append(map(la... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
<|body_0|>
def backtrack(self, queens, xy_sum, xy_diff, n, results):
"""queens: its indices are queens horizontal locations its values are queens vertical locations"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_012363 | 1,125 | no_license | [
{
"docstring": ":type n: int :rtype: List[List[str]]",
"name": "solveNQueens",
"signature": "def solveNQueens(self, n)"
},
{
"docstring": "queens: its indices are queens horizontal locations its values are queens vertical locations",
"name": "backtrack",
"signature": "def backtrack(self,... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solveNQueens(self, n): :type n: int :rtype: List[List[str]]
- def backtrack(self, queens, xy_sum, xy_diff, n, results): queens: its indices are queens horizontal locations it... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solveNQueens(self, n): :type n: int :rtype: List[List[str]]
- def backtrack(self, queens, xy_sum, xy_diff, n, results): queens: its indices are queens horizontal locations it... | 24aaca7585c59255a86474c1f8088bd5b81ebf51 | <|skeleton|>
class Solution:
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
<|body_0|>
def backtrack(self, queens, xy_sum, xy_diff, n, results):
"""queens: its indices are queens horizontal locations its values are queens vertical locations"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
res = []
self.backtrack([], [], [], n, res)
print(res)
final_res = []
for sol in res:
str_res = [['.' for _ in range(n)] for _ in range(n)]
for i, j in enumer... | the_stack_v2_python_sparse | Backtracking/51. N-Queens.py | burnmg/LC_algorithms_practice | train | 0 | |
aeb3ab99d75b26bd66743ad4a6bee3666807a4ab | [
"fmt = 'PO-{abc:02f}-{ref:04d}-{date}-???'\ninfo = InvenTree.format.parse_format_string(fmt)\nself.assertIn('abc', info)\nself.assertIn('ref', info)\nself.assertIn('date', info)\nfor fmt in ['PO-{{xyz}', 'PO-{xyz}}', 'PO-{xyz}-{']:\n with self.assertRaises(ValueError):\n InvenTree.format.parse_format_stri... | <|body_start_0|>
fmt = 'PO-{abc:02f}-{ref:04d}-{date}-???'
info = InvenTree.format.parse_format_string(fmt)
self.assertIn('abc', info)
self.assertIn('ref', info)
self.assertIn('date', info)
for fmt in ['PO-{{xyz}', 'PO-{xyz}}', 'PO-{xyz}-{']:
with self.assertR... | Unit tests for custom string formatting functionality | FormatTest | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FormatTest:
"""Unit tests for custom string formatting functionality"""
def test_parse(self):
"""Tests for the 'parse_format_string' function"""
<|body_0|>
def test_create_regex(self):
"""Test function for creating a regex from a format string"""
<|body_1... | stack_v2_sparse_classes_36k_train_012364 | 41,191 | permissive | [
{
"docstring": "Tests for the 'parse_format_string' function",
"name": "test_parse",
"signature": "def test_parse(self)"
},
{
"docstring": "Test function for creating a regex from a format string",
"name": "test_create_regex",
"signature": "def test_create_regex(self)"
},
{
"docs... | 4 | null | Implement the Python class `FormatTest` described below.
Class description:
Unit tests for custom string formatting functionality
Method signatures and docstrings:
- def test_parse(self): Tests for the 'parse_format_string' function
- def test_create_regex(self): Test function for creating a regex from a format strin... | Implement the Python class `FormatTest` described below.
Class description:
Unit tests for custom string formatting functionality
Method signatures and docstrings:
- def test_parse(self): Tests for the 'parse_format_string' function
- def test_create_regex(self): Test function for creating a regex from a format strin... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class FormatTest:
"""Unit tests for custom string formatting functionality"""
def test_parse(self):
"""Tests for the 'parse_format_string' function"""
<|body_0|>
def test_create_regex(self):
"""Test function for creating a regex from a format string"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FormatTest:
"""Unit tests for custom string formatting functionality"""
def test_parse(self):
"""Tests for the 'parse_format_string' function"""
fmt = 'PO-{abc:02f}-{ref:04d}-{date}-???'
info = InvenTree.format.parse_format_string(fmt)
self.assertIn('abc', info)
se... | the_stack_v2_python_sparse | InvenTree/InvenTree/tests.py | inventree/InvenTree | train | 3,077 |
c079ccd79ea0b2e24628d41bb02a42ab6dcae4e2 | [
"self.model_type = model_type\nself.model_name = model_name\nself.model_task = model_task\nself.model_description = model_description\nself.model_folder = os.path.join(ROOT_DIR, self.model_type, self.model_task, self.model_name)\nself.bucket = s3.S3Bucket(bucket_name='s3ludos')\nif not os.path.isdir(self.model_fold... | <|body_start_0|>
self.model_type = model_type
self.model_name = model_name
self.model_task = model_task
self.model_description = model_description
self.model_folder = os.path.join(ROOT_DIR, self.model_type, self.model_task, self.model_name)
self.bucket = s3.S3Bucket(bucke... | Base class for the model | BaseModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseModel:
"""Base class for the model"""
def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'):
"""Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task o... | stack_v2_sparse_classes_36k_train_012365 | 3,053 | no_license | [
{
"docstring": "Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task of your model stage (str): training or prediction expname (str): Name of the experiment",
"name": "__init__",
"signature": "def __init__(self, model_name: str, model_task: str,... | 2 | stack_v2_sparse_classes_30k_train_002676 | Implement the Python class `BaseModel` described below.
Class description:
Base class for the model
Method signatures and docstrings:
- def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'): Args: model_type (str): Type of the model, 'models' mode... | Implement the Python class `BaseModel` described below.
Class description:
Base class for the model
Method signatures and docstrings:
- def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'): Args: model_type (str): Type of the model, 'models' mode... | fd09eb1bceafe794d8784a21cfd3753cfd371258 | <|skeleton|>
class BaseModel:
"""Base class for the model"""
def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'):
"""Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseModel:
"""Base class for the model"""
def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'):
"""Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task of your model ... | the_stack_v2_python_sparse | ludos/models/common.py | cthorey/ludos | train | 0 |
7444b5029f2d1205696058eceaf2a7ba9aafa096 | [
"ret = self.libssock.SCIONListen(self.fd)\nself.port = self.libssock.SCIONGetPort(self.fd)\nreturn ret",
"newfd = self.libssock.SCIONAccept(self.fd)\nlogging.debug('Accepted socket %d' % newfd)\nreturn (ScionBaseSocket(self.proto, self.sciond_addr, newfd), None)"
] | <|body_start_0|>
ret = self.libssock.SCIONListen(self.fd)
self.port = self.libssock.SCIONGetPort(self.fd)
return ret
<|end_body_0|>
<|body_start_1|>
newfd = self.libssock.SCIONAccept(self.fd)
logging.debug('Accepted socket %d' % newfd)
return (ScionBaseSocket(self.proto,... | Server side wrapper of the SCION Multi-Path Socket. | ScionServerSocket | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScionServerSocket:
"""Server side wrapper of the SCION Multi-Path Socket."""
def listen(self):
"""Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int"""
<|body_0|>
def accept(self):
"""Accepts a connection. ... | stack_v2_sparse_classes_36k_train_012366 | 19,489 | permissive | [
{
"docstring": "Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int",
"name": "listen",
"signature": "def listen(self)"
},
{
"docstring": "Accepts a connection. The return value is a pair (conn, address) where conn is a new ScionBaseSocket ... | 2 | null | Implement the Python class `ScionServerSocket` described below.
Class description:
Server side wrapper of the SCION Multi-Path Socket.
Method signatures and docstrings:
- def listen(self): Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int
- def accept(self): A... | Implement the Python class `ScionServerSocket` described below.
Class description:
Server side wrapper of the SCION Multi-Path Socket.
Method signatures and docstrings:
- def listen(self): Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int
- def accept(self): A... | 06f3f0b82dc8a535ce8b0a128282af00a8425a06 | <|skeleton|>
class ScionServerSocket:
"""Server side wrapper of the SCION Multi-Path Socket."""
def listen(self):
"""Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int"""
<|body_0|>
def accept(self):
"""Accepts a connection. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScionServerSocket:
"""Server side wrapper of the SCION Multi-Path Socket."""
def listen(self):
"""Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int"""
ret = self.libssock.SCIONListen(self.fd)
self.port = self.libssock.SCION... | the_stack_v2_python_sparse | endhost/scion_socket.py | marcoeilers/scion | train | 1 |
d85516d4ba096d42f025f84bf5a5b90a5ba73204 | [
"\"\"\"\n [1,1,3,4,5,7,7,9]\n \"\"\"\nnums.sort()\nlo, hi = (0, nums[-1] - nums[0])\nself.count(nums, 4)\nwhile lo < hi:\n mid = (hi + lo) / 2\n if self.count(nums, mid) >= k:\n hi = mid\n else:\n lo = mid + 1\nreturn lo",
"count = right = 0\nfor left, n in enumerate(nums):\n ... | <|body_start_0|>
"""
[1,1,3,4,5,7,7,9]
"""
nums.sort()
lo, hi = (0, nums[-1] - nums[0])
self.count(nums, 4)
while lo < hi:
mid = (hi + lo) / 2
if self.count(nums, mid) >= k:
hi = mid
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def count(self, nums, val):
"""Count the total number of pair distance which is smaller than val"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_012367 | 1,574 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "smallestDistancePair",
"signature": "def smallestDistancePair(self, nums, k)"
},
{
"docstring": "Count the total number of pair distance which is smaller than val",
"name": "count",
"signature": "def count(self, nu... | 2 | stack_v2_sparse_classes_30k_train_006006 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def count(self, nums, val): Count the total number of pair distance which is smaller tha... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def count(self, nums, val): Count the total number of pair distance which is smaller tha... | 0127190b27862ec7e7f4f2fcce5ce958d480cdac | <|skeleton|>
class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def count(self, nums, val):
"""Count the total number of pair distance which is smaller than val"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
"""
[1,1,3,4,5,7,7,9]
"""
nums.sort()
lo, hi = (0, nums[-1] - nums[0])
self.count(nums, 4)
while lo < hi:
mid = (h... | the_stack_v2_python_sparse | 719.find-k-th-smallest-pair-distance.py | Iverance/leetcode | train | 0 | |
584d61b0847c65baca43054c5189a65d7b5100d3 | [
"self.path = path\nself.name = path.split('.')[-1]\nself.cls = None",
"if not self.cls:\n self.cls = _istring(self.path)\nreturn self.cls()"
] | <|body_start_0|>
self.path = path
self.name = path.split('.')[-1]
self.cls = None
<|end_body_0|>
<|body_start_1|>
if not self.cls:
self.cls = _istring(self.path)
return self.cls()
<|end_body_1|>
| Handles lazily importing and instantiating a class. | _lazy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _lazy:
"""Handles lazily importing and instantiating a class."""
def __init__(self, path):
"""Specify the path to the class to lazily import and instantiate."""
<|body_0|>
def __call__(self):
"""Import the specified class and return a new instantiation of it."""
... | stack_v2_sparse_classes_36k_train_012368 | 1,315 | no_license | [
{
"docstring": "Specify the path to the class to lazily import and instantiate.",
"name": "__init__",
"signature": "def __init__(self, path)"
},
{
"docstring": "Import the specified class and return a new instantiation of it.",
"name": "__call__",
"signature": "def __call__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008791 | Implement the Python class `_lazy` described below.
Class description:
Handles lazily importing and instantiating a class.
Method signatures and docstrings:
- def __init__(self, path): Specify the path to the class to lazily import and instantiate.
- def __call__(self): Import the specified class and return a new ins... | Implement the Python class `_lazy` described below.
Class description:
Handles lazily importing and instantiating a class.
Method signatures and docstrings:
- def __init__(self, path): Specify the path to the class to lazily import and instantiate.
- def __call__(self): Import the specified class and return a new ins... | 40aeb38397041d042b7497c6090d75a03d751dd6 | <|skeleton|>
class _lazy:
"""Handles lazily importing and instantiating a class."""
def __init__(self, path):
"""Specify the path to the class to lazily import and instantiate."""
<|body_0|>
def __call__(self):
"""Import the specified class and return a new instantiation of it."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _lazy:
"""Handles lazily importing and instantiating a class."""
def __init__(self, path):
"""Specify the path to the class to lazily import and instantiate."""
self.path = path
self.name = path.split('.')[-1]
self.cls = None
def __call__(self):
"""Import the ... | the_stack_v2_python_sparse | lib/LazyControllerLoader.py | dound/CraigNotes | train | 0 |
f8dec2f4fdb7a9faf91673eef84a5716bb3fcd26 | [
"self.dynamic = True\nself.type = 'DynamicMetadataTree'\nMetadataTree.__init__(self, rootName)\nself.pivotParam = pivotParam",
"pivotVal = float(pivotVal)\npNode = self._findPivot(root, pivotVal)\ntNode = MetadataTree._findTarget(self, pNode, target)\nreturn tNode",
"found = False\nfor child in root:\n if ch... | <|body_start_0|>
self.dynamic = True
self.type = 'DynamicMetadataTree'
MetadataTree.__init__(self, rootName)
self.pivotParam = pivotParam
<|end_body_0|>
<|body_start_1|>
pivotVal = float(pivotVal)
pNode = self._findPivot(root, pivotVal)
tNode = MetadataTree._find... | Class for construction of metadata xml trees used in data objects. Usually contains summary data such as that produced by postprocessor models. Two types of tree exist: dynamic and static. See RAVEN Output type of Files object. | DynamicMetadataTree | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynamicMetadataTree:
"""Class for construction of metadata xml trees used in data objects. Usually contains summary data such as that produced by postprocessor models. Two types of tree exist: dynamic and static. See RAVEN Output type of Files object."""
def __init__(self, rootName, pivotPar... | stack_v2_sparse_classes_36k_train_012369 | 36,827 | permissive | [
{
"docstring": "Constructor. @ In, rootName, str, root of tree if provided @ In, pivotParam, str, pivot variable @ Out, None",
"name": "__init__",
"signature": "def __init__(self, rootName, pivotParam)"
},
{
"docstring": "Used to find target node. Extension of base class method for Dynamic mode ... | 3 | null | Implement the Python class `DynamicMetadataTree` described below.
Class description:
Class for construction of metadata xml trees used in data objects. Usually contains summary data such as that produced by postprocessor models. Two types of tree exist: dynamic and static. See RAVEN Output type of Files object.
Metho... | Implement the Python class `DynamicMetadataTree` described below.
Class description:
Class for construction of metadata xml trees used in data objects. Usually contains summary data such as that produced by postprocessor models. Two types of tree exist: dynamic and static. See RAVEN Output type of Files object.
Metho... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class DynamicMetadataTree:
"""Class for construction of metadata xml trees used in data objects. Usually contains summary data such as that produced by postprocessor models. Two types of tree exist: dynamic and static. See RAVEN Output type of Files object."""
def __init__(self, rootName, pivotPar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DynamicMetadataTree:
"""Class for construction of metadata xml trees used in data objects. Usually contains summary data such as that produced by postprocessor models. Two types of tree exist: dynamic and static. See RAVEN Output type of Files object."""
def __init__(self, rootName, pivotParam):
... | the_stack_v2_python_sparse | ravenframework/utils/TreeStructure.py | idaholab/raven | train | 201 |
4046811e93de72963611a2fb2572f66c84fbd7f4 | [
"db = getUtility(IDatabase, name='variation.stockdatabase')\nconnection = db.connection\nstatement = sql.select([PhenotypeMethod.c.id, PhenotypeMethod.c.short_name], distinct=True)\nresults = connection.execute(statement).fetchall()\n\"\\n\\t\\treturn [ dict(film_code=film.film_code,\\n\\t\\t\\t\\t\\t url=film.get... | <|body_start_0|>
db = getUtility(IDatabase, name='variation.stockdatabase')
connection = db.connection
statement = sql.select([PhenotypeMethod.c.id, PhenotypeMethod.c.short_name], distinct=True)
results = connection.execute(statement).fetchall()
"\n\t\treturn [ dict(film_code=fil... | Find phenotype in db | PhenotypeLocator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhenotypeLocator:
"""Find phenotype in db"""
def get_phenotype_method_id_ls(self):
"""Return a list of all films showing at the particular ICinema between the specified dates. Returns a list of dictionaries with keys 'film_code', 'url', 'title' and 'summary'."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_012370 | 6,707 | no_license | [
{
"docstring": "Return a list of all films showing at the particular ICinema between the specified dates. Returns a list of dictionaries with keys 'film_code', 'url', 'title' and 'summary'.",
"name": "get_phenotype_method_id_ls",
"signature": "def get_phenotype_method_id_ls(self)"
},
{
"docstrin... | 2 | null | Implement the Python class `PhenotypeLocator` described below.
Class description:
Find phenotype in db
Method signatures and docstrings:
- def get_phenotype_method_id_ls(self): Return a list of all films showing at the particular ICinema between the specified dates. Returns a list of dictionaries with keys 'film_code... | Implement the Python class `PhenotypeLocator` described below.
Class description:
Find phenotype in db
Method signatures and docstrings:
- def get_phenotype_method_id_ls(self): Return a list of all films showing at the particular ICinema between the specified dates. Returns a list of dictionaries with keys 'film_code... | 7b402496aae81665e6a915b5021b94d56e034c9d | <|skeleton|>
class PhenotypeLocator:
"""Find phenotype in db"""
def get_phenotype_method_id_ls(self):
"""Return a list of all films showing at the particular ICinema between the specified dates. Returns a list of dictionaries with keys 'film_code', 'url', 'title' and 'summary'."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhenotypeLocator:
"""Find phenotype in db"""
def get_phenotype_method_id_ls(self):
"""Return a list of all films showing at the particular ICinema between the specified dates. Returns a list of dictionaries with keys 'film_code', 'url', 'title' and 'summary'."""
db = getUtility(IDatabase,... | the_stack_v2_python_sparse | variation/trunk/web_interface/Variation/Products/Variation/dbphenotype.py | polyactis/repos | train | 1 |
218be082072ea0834c7c206ec2895abdcfb895f6 | [
"desc = self.db.desc\noutfit_list = []\nfor garment in get_worn_clothes(self, exclude_covered=True):\n wearstyle = garment.db.worn\n if type(wearstyle) is str:\n outfit_list.append(f'{garment.name} {wearstyle}')\n else:\n outfit_list.append(garment.name)\nif outfit_list:\n outfit = f'{self... | <|body_start_0|>
desc = self.db.desc
outfit_list = []
for garment in get_worn_clothes(self, exclude_covered=True):
wearstyle = garment.db.worn
if type(wearstyle) is str:
outfit_list.append(f'{garment.name} {wearstyle}')
else:
ou... | Character that displays worn clothing when looked at. You can also just copy the return_appearance hook defined below to your own game's character typeclass. | ClothedCharacter | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClothedCharacter:
"""Character that displays worn clothing when looked at. You can also just copy the return_appearance hook defined below to your own game's character typeclass."""
def get_display_desc(self, looker, **kwargs):
"""Get the 'desc' component of the object description. C... | stack_v2_sparse_classes_36k_train_012371 | 24,575 | permissive | [
{
"docstring": "Get the 'desc' component of the object description. Called by `return_appearance`. Args: looker (Object): Object doing the looking. **kwargs: Arbitrary data for use when overriding. Returns: str: The desc display string.",
"name": "get_display_desc",
"signature": "def get_display_desc(se... | 2 | null | Implement the Python class `ClothedCharacter` described below.
Class description:
Character that displays worn clothing when looked at. You can also just copy the return_appearance hook defined below to your own game's character typeclass.
Method signatures and docstrings:
- def get_display_desc(self, looker, **kwarg... | Implement the Python class `ClothedCharacter` described below.
Class description:
Character that displays worn clothing when looked at. You can also just copy the return_appearance hook defined below to your own game's character typeclass.
Method signatures and docstrings:
- def get_display_desc(self, looker, **kwarg... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class ClothedCharacter:
"""Character that displays worn clothing when looked at. You can also just copy the return_appearance hook defined below to your own game's character typeclass."""
def get_display_desc(self, looker, **kwargs):
"""Get the 'desc' component of the object description. C... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClothedCharacter:
"""Character that displays worn clothing when looked at. You can also just copy the return_appearance hook defined below to your own game's character typeclass."""
def get_display_desc(self, looker, **kwargs):
"""Get the 'desc' component of the object description. Called by `ret... | the_stack_v2_python_sparse | evennia/contrib/game_systems/clothing/clothing.py | evennia/evennia | train | 1,781 |
5984271ee7cd364ff3b41be0b4c8a6b8522d13b8 | [
"post_body = json.dumps({'security_group_default_rule': kwargs})\nurl = 'os-security-group-default-rules'\nresp, body = self.post(url, post_body)\nbody = json.loads(body)\nself.validate_response(schema.create_get_security_group_default_rule, resp, body)\nreturn rest_client.ResponseBody(resp, body)",
"resp, body =... | <|body_start_0|>
post_body = json.dumps({'security_group_default_rule': kwargs})
url = 'os-security-group-default-rules'
resp, body = self.post(url, post_body)
body = json.loads(body)
self.validate_response(schema.create_get_security_group_default_rule, resp, body)
return... | SecurityGroupDefaultRulesClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecurityGroupDefaultRulesClient:
def create_security_default_group_rule(self, **kwargs):
"""Create security group default rule. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#create-default-security-group-r... | stack_v2_sparse_classes_36k_train_012372 | 2,984 | permissive | [
{
"docstring": "Create security group default rule. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#create-default-security-group-rule",
"name": "create_security_default_group_rule",
"signature": "def create_security_defaul... | 4 | null | Implement the Python class `SecurityGroupDefaultRulesClient` described below.
Class description:
Implement the SecurityGroupDefaultRulesClient class.
Method signatures and docstrings:
- def create_security_default_group_rule(self, **kwargs): Create security group default rule. For a full list of available parameters,... | Implement the Python class `SecurityGroupDefaultRulesClient` described below.
Class description:
Implement the SecurityGroupDefaultRulesClient class.
Method signatures and docstrings:
- def create_security_default_group_rule(self, **kwargs): Create security group default rule. For a full list of available parameters,... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class SecurityGroupDefaultRulesClient:
def create_security_default_group_rule(self, **kwargs):
"""Create security group default rule. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#create-default-security-group-r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecurityGroupDefaultRulesClient:
def create_security_default_group_rule(self, **kwargs):
"""Create security group default rule. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#create-default-security-group-rule"""
... | the_stack_v2_python_sparse | tempest/lib/services/compute/security_group_default_rules_client.py | openstack/tempest | train | 270 | |
750b447436090e8c0fb0557f14b8f50704e6aa59 | [
"self.logger = get_logger(log_to_screen)\nself._factory = ServerFactory()\nself._factory.protocol = Worker\nself._factory.logger = self.logger\nself._factory.protocol.parser = parser()\nself._port = port\nself._reactor = SelectReactor()\nself._reactor.listenTCP(port, self._factory)\nself._resource_manager = Manager... | <|body_start_0|>
self.logger = get_logger(log_to_screen)
self._factory = ServerFactory()
self._factory.protocol = Worker
self._factory.logger = self.logger
self._factory.protocol.parser = parser()
self._port = port
self._reactor = SelectReactor()
self._rea... | Resource manager server. | ResourceManagerServer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceManagerServer:
"""Resource manager server."""
def __init__(self, port=RESOURCE_MANAGER_PORT, parser=DEFAULT_PARSER, log_to_screen=True):
"""Initialize the resource manager server. Args: port (number): client listener port. parser (object): messages parser of type `AbstractPar... | stack_v2_sparse_classes_36k_train_012373 | 2,498 | permissive | [
{
"docstring": "Initialize the resource manager server. Args: port (number): client listener port. parser (object): messages parser of type `AbstractParser`. log_to_screen (bool): Enable log prints to screen.",
"name": "__init__",
"signature": "def __init__(self, port=RESOURCE_MANAGER_PORT, parser=DEFAU... | 3 | stack_v2_sparse_classes_30k_train_013578 | Implement the Python class `ResourceManagerServer` described below.
Class description:
Resource manager server.
Method signatures and docstrings:
- def __init__(self, port=RESOURCE_MANAGER_PORT, parser=DEFAULT_PARSER, log_to_screen=True): Initialize the resource manager server. Args: port (number): client listener po... | Implement the Python class `ResourceManagerServer` described below.
Class description:
Resource manager server.
Method signatures and docstrings:
- def __init__(self, port=RESOURCE_MANAGER_PORT, parser=DEFAULT_PARSER, log_to_screen=True): Initialize the resource manager server. Args: port (number): client listener po... | 746fdc07c4f8de7f98c6ab7fa1d5c95dcadbf6dc | <|skeleton|>
class ResourceManagerServer:
"""Resource manager server."""
def __init__(self, port=RESOURCE_MANAGER_PORT, parser=DEFAULT_PARSER, log_to_screen=True):
"""Initialize the resource manager server. Args: port (number): client listener port. parser (object): messages parser of type `AbstractPar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResourceManagerServer:
"""Resource manager server."""
def __init__(self, port=RESOURCE_MANAGER_PORT, parser=DEFAULT_PARSER, log_to_screen=True):
"""Initialize the resource manager server. Args: port (number): client listener port. parser (object): messages parser of type `AbstractParser`. log_to_... | the_stack_v2_python_sparse | src/rotest/management/server/main.py | IamShobe/rotest | train | 3 |
77f53bbafd788a02cb176f60090420a83104146f | [
"if 'pow' not in conf['feature']:\n raise Exception('expecting feature to be in power domain')\nself.comp = feature_computer_factory.factory(conf['feature'])(conf)\nself.segment_lengths = segment_lengths\nself.dim = self.comp.get_dim()\nself.nontime_dims = [self.dim]\nsuper(IdealRatioProcessor, self).__init__(co... | <|body_start_0|>
if 'pow' not in conf['feature']:
raise Exception('expecting feature to be in power domain')
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
self.segment_lengths = segment_lengths
self.dim = self.comp.get_dim()
self.nontime_dims = [... | a processor for audio files, this will compute the ideal ratio masks | IdealRatioProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdealRatioProcessor:
"""a processor for audio files, this will compute the ideal ratio masks"""
def __init__(self, conf, segment_lengths):
"""IdealRatioProcessor constructor Args: conf: IdealRatioProcessor configuration as a dict of strings segment_lengths: A list containing the desi... | stack_v2_sparse_classes_36k_train_012374 | 3,843 | permissive | [
{
"docstring": "IdealRatioProcessor constructor Args: conf: IdealRatioProcessor configuration as a dict of strings segment_lengths: A list containing the desired lengths of segments. Possibly multiple segment lengths",
"name": "__init__",
"signature": "def __init__(self, conf, segment_lengths)"
},
{... | 3 | null | Implement the Python class `IdealRatioProcessor` described below.
Class description:
a processor for audio files, this will compute the ideal ratio masks
Method signatures and docstrings:
- def __init__(self, conf, segment_lengths): IdealRatioProcessor constructor Args: conf: IdealRatioProcessor configuration as a di... | Implement the Python class `IdealRatioProcessor` described below.
Class description:
a processor for audio files, this will compute the ideal ratio masks
Method signatures and docstrings:
- def __init__(self, conf, segment_lengths): IdealRatioProcessor constructor Args: conf: IdealRatioProcessor configuration as a di... | 5e862cbf846d45b8a317f87588533f3fde9f0726 | <|skeleton|>
class IdealRatioProcessor:
"""a processor for audio files, this will compute the ideal ratio masks"""
def __init__(self, conf, segment_lengths):
"""IdealRatioProcessor constructor Args: conf: IdealRatioProcessor configuration as a dict of strings segment_lengths: A list containing the desi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IdealRatioProcessor:
"""a processor for audio files, this will compute the ideal ratio masks"""
def __init__(self, conf, segment_lengths):
"""IdealRatioProcessor constructor Args: conf: IdealRatioProcessor configuration as a dict of strings segment_lengths: A list containing the desired lengths o... | the_stack_v2_python_sparse | nabu/processing/processors/ideal_ratio_processor.py | JeroenZegers/Nabu-MSSS | train | 19 |
5f74d2d9173fb1ddd102625fc8f122dca8d7b73e | [
"self.script = script\nself.example_command = example_command\nself.searchtext = 'output'",
"opt_dict = parse_example_command(self.example_command)\noutputs = {}\nfor key, value in opt_dict.iteritems():\n if self.searchtext in key:\n for i, line in enumerate(self.script):\n line = line.strip(... | <|body_start_0|>
self.script = script
self.example_command = example_command
self.searchtext = 'output'
<|end_body_0|>
<|body_start_1|>
opt_dict = parse_example_command(self.example_command)
outputs = {}
for key, value in opt_dict.iteritems():
if self.searcht... | Output class for parsing outputs. | Output | [
"CC-BY-2.5",
"AFL-2.1",
"AFL-3.0",
"CC-BY-3.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Output:
"""Output class for parsing outputs."""
def __init__(self, script, example_command):
"""Initialize Input with searchtext - output."""
<|body_0|>
def find_outputs(self):
"""Find outputs in example command."""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_012375 | 5,433 | permissive | [
{
"docstring": "Initialize Input with searchtext - output.",
"name": "__init__",
"signature": "def __init__(self, script, example_command)"
},
{
"docstring": "Find outputs in example command.",
"name": "find_outputs",
"signature": "def find_outputs(self)"
}
] | 2 | null | Implement the Python class `Output` described below.
Class description:
Output class for parsing outputs.
Method signatures and docstrings:
- def __init__(self, script, example_command): Initialize Input with searchtext - output.
- def find_outputs(self): Find outputs in example command. | Implement the Python class `Output` described below.
Class description:
Output class for parsing outputs.
Method signatures and docstrings:
- def __init__(self, script, example_command): Initialize Input with searchtext - output.
- def find_outputs(self): Find outputs in example command.
<|skeleton|>
class Output:
... | 063bf0dca5d465466aefa77edaf47df12c4ff932 | <|skeleton|>
class Output:
"""Output class for parsing outputs."""
def __init__(self, script, example_command):
"""Initialize Input with searchtext - output."""
<|body_0|>
def find_outputs(self):
"""Find outputs in example command."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Output:
"""Output class for parsing outputs."""
def __init__(self, script, example_command):
"""Initialize Input with searchtext - output."""
self.script = script
self.example_command = example_command
self.searchtext = 'output'
def find_outputs(self):
"""Find... | the_stack_v2_python_sparse | .venv/lib/python2.7/site-packages/planemo/rscript_parse.py | maumauleon/galaxy-irri-dev | train | 1 |
9dc70d2f0804af2bafa3c0e5873b1f2714d54b22 | [
"self.driver.get(home_url)\nhome_page_title_actual = self.driver.get_title()\nhome_page_title_expected = '二手车市场_二手车交易市场_二手车平台-淘车网'\ntt_check.assertEqual(home_page_title_actual, home_page_title_expected, '页面title期望是%s，实际是%s' % (home_page_title_expected, home_page_title_actual))",
"self.driver.get(home_url)\nads = ... | <|body_start_0|>
self.driver.get(home_url)
home_page_title_actual = self.driver.get_title()
home_page_title_expected = '二手车市场_二手车交易市场_二手车平台-淘车网'
tt_check.assertEqual(home_page_title_actual, home_page_title_expected, '页面title期望是%s，实际是%s' % (home_page_title_expected, home_page_title_actual... | AD | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AD:
def test_title(self):
"""测试首页Title显示是否正确"""
<|body_0|>
def test_ad_displayed(self):
"""测试广告位图片请求是否正常"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.driver.get(home_url)
home_page_title_actual = self.driver.get_title()
home_... | stack_v2_sparse_classes_36k_train_012376 | 2,686 | no_license | [
{
"docstring": "测试首页Title显示是否正确",
"name": "test_title",
"signature": "def test_title(self)"
},
{
"docstring": "测试广告位图片请求是否正常",
"name": "test_ad_displayed",
"signature": "def test_ad_displayed(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013146 | Implement the Python class `AD` described below.
Class description:
Implement the AD class.
Method signatures and docstrings:
- def test_title(self): 测试首页Title显示是否正确
- def test_ad_displayed(self): 测试广告位图片请求是否正常 | Implement the Python class `AD` described below.
Class description:
Implement the AD class.
Method signatures and docstrings:
- def test_title(self): 测试首页Title显示是否正确
- def test_ad_displayed(self): 测试广告位图片请求是否正常
<|skeleton|>
class AD:
def test_title(self):
"""测试首页Title显示是否正确"""
<|body_0|>
de... | 204856bd33c06d25f2970eba13799db75d4fd4fe | <|skeleton|>
class AD:
def test_title(self):
"""测试首页Title显示是否正确"""
<|body_0|>
def test_ad_displayed(self):
"""测试广告位图片请求是否正常"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AD:
def test_title(self):
"""测试首页Title显示是否正确"""
self.driver.get(home_url)
home_page_title_actual = self.driver.get_title()
home_page_title_expected = '二手车市场_二手车交易市场_二手车平台-淘车网'
tt_check.assertEqual(home_page_title_actual, home_page_title_expected, '页面title期望是%s，实际是%s' % ... | the_stack_v2_python_sparse | mc/taochePC/test_homepage/test_ad.py | boeai/mc | train | 0 | |
371a8df8b933dac8f41e341f88e33f762315a5bc | [
"allure.dynamic.title('Test with empty string')\nallure.dynamic.severity(allure.severity_level.NORMAL)\nallure.dynamic.description_html('<h3>Codewars badge:</h3><img src=\"https://www.codewars.com/users/myFirstCode/badges/large\"><h3>Test Description:</h3><p></p>')\nwith allure.step('Pass empty string and verify th... | <|body_start_0|>
allure.dynamic.title('Test with empty string')
allure.dynamic.severity(allure.severity_level.NORMAL)
allure.dynamic.description_html('<h3>Codewars badge:</h3><img src="https://www.codewars.com/users/myFirstCode/badges/large"><h3>Test Description:</h3><p></p>')
with allur... | Testing the solution for 'Reversed Strings' problem | ReversedStringsTestCase | [
"Unlicense",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReversedStringsTestCase:
"""Testing the solution for 'Reversed Strings' problem"""
def test_reversed_strings_empty(self):
"""Test with empty string :return:"""
<|body_0|>
def test_reversed_strings_one_char(self):
"""Test with one char only :return:"""
<|b... | stack_v2_sparse_classes_36k_train_012377 | 3,430 | permissive | [
{
"docstring": "Test with empty string :return:",
"name": "test_reversed_strings_empty",
"signature": "def test_reversed_strings_empty(self)"
},
{
"docstring": "Test with one char only :return:",
"name": "test_reversed_strings_one_char",
"signature": "def test_reversed_strings_one_char(s... | 3 | null | Implement the Python class `ReversedStringsTestCase` described below.
Class description:
Testing the solution for 'Reversed Strings' problem
Method signatures and docstrings:
- def test_reversed_strings_empty(self): Test with empty string :return:
- def test_reversed_strings_one_char(self): Test with one char only :r... | Implement the Python class `ReversedStringsTestCase` described below.
Class description:
Testing the solution for 'Reversed Strings' problem
Method signatures and docstrings:
- def test_reversed_strings_empty(self): Test with empty string :return:
- def test_reversed_strings_one_char(self): Test with one char only :r... | ba3ea81125b6082d867f0ae34c6c9be15e153966 | <|skeleton|>
class ReversedStringsTestCase:
"""Testing the solution for 'Reversed Strings' problem"""
def test_reversed_strings_empty(self):
"""Test with empty string :return:"""
<|body_0|>
def test_reversed_strings_one_char(self):
"""Test with one char only :return:"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReversedStringsTestCase:
"""Testing the solution for 'Reversed Strings' problem"""
def test_reversed_strings_empty(self):
"""Test with empty string :return:"""
allure.dynamic.title('Test with empty string')
allure.dynamic.severity(allure.severity_level.NORMAL)
allure.dynam... | the_stack_v2_python_sparse | kyu_8/reversed_strings/test_reversed_strings.py | qamine-test/codewars | train | 0 |
4c1b9f3afa733f560afcc33eb38b0baf69c2bf7c | [
"super(_SelfAttentionDecoderLayer, self).__init__(**kwargs)\nself.self_attention = transformer.MultiHeadAttention(num_heads, num_units, dropout=attention_dropout, name='masked_multi_head_attention')\nself.self_attention = transformer.TransformerLayerWrapper(self.self_attention, dropout, name='sub_layer_0')\nself.at... | <|body_start_0|>
super(_SelfAttentionDecoderLayer, self).__init__(**kwargs)
self.self_attention = transformer.MultiHeadAttention(num_heads, num_units, dropout=attention_dropout, name='masked_multi_head_attention')
self.self_attention = transformer.TransformerLayerWrapper(self.self_attention, dro... | Implements one self-attention decoding layer. | _SelfAttentionDecoderLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _SelfAttentionDecoderLayer:
"""Implements one self-attention decoding layer."""
def __init__(self, num_units, num_heads, ffn_inner_dim, num_sources=1, dropout=0.1, attention_dropout=0.1, ffn_dropout=0.1, ffn_activation=tf.nn.relu, **kwargs):
"""Initializes the layer. Args: num_units:... | stack_v2_sparse_classes_36k_train_012378 | 18,943 | permissive | [
{
"docstring": "Initializes the layer. Args: num_units: The number of hidden units. num_heads: The number of heads in the multi-head attention. ffn_inner_dim: The number of units of the inner linear transformation in the feed forward layer. num_sources: The number of source contexts. dropout: The probability to... | 2 | stack_v2_sparse_classes_30k_train_007631 | Implement the Python class `_SelfAttentionDecoderLayer` described below.
Class description:
Implements one self-attention decoding layer.
Method signatures and docstrings:
- def __init__(self, num_units, num_heads, ffn_inner_dim, num_sources=1, dropout=0.1, attention_dropout=0.1, ffn_dropout=0.1, ffn_activation=tf.nn... | Implement the Python class `_SelfAttentionDecoderLayer` described below.
Class description:
Implements one self-attention decoding layer.
Method signatures and docstrings:
- def __init__(self, num_units, num_heads, ffn_inner_dim, num_sources=1, dropout=0.1, attention_dropout=0.1, ffn_dropout=0.1, ffn_activation=tf.nn... | 5a9b2e11da04a9777ec6ac4f7b54d076bea040ea | <|skeleton|>
class _SelfAttentionDecoderLayer:
"""Implements one self-attention decoding layer."""
def __init__(self, num_units, num_heads, ffn_inner_dim, num_sources=1, dropout=0.1, attention_dropout=0.1, ffn_dropout=0.1, ffn_activation=tf.nn.relu, **kwargs):
"""Initializes the layer. Args: num_units:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _SelfAttentionDecoderLayer:
"""Implements one self-attention decoding layer."""
def __init__(self, num_units, num_heads, ffn_inner_dim, num_sources=1, dropout=0.1, attention_dropout=0.1, ffn_dropout=0.1, ffn_activation=tf.nn.relu, **kwargs):
"""Initializes the layer. Args: num_units: The number o... | the_stack_v2_python_sparse | opennmt/decoders/self_attention_decoder.py | Parkchanjun/OpenNMT-tf | train | 2 |
929dd5d67761b0c0e0e09fc561a0d68c87d28a29 | [
"dirname = 'classifier'\nif extension is not None:\n dirname += '_{:s}'.format(str(extension))\npath = join(dirpath, dirname)\nif not exists(path):\n mkdir(path)\nif data:\n np.save(join(path, 'values.npy'), self._values)\nio = IO()\nio.write_json(join(path, 'parameters.json'), self.parameters)\nif image:\... | <|body_start_0|>
dirname = 'classifier'
if extension is not None:
dirname += '_{:s}'.format(str(extension))
path = join(dirpath, dirname)
if not exists(path):
mkdir(path)
if data:
np.save(join(path, 'values.npy'), self._values)
io = IO(... | Methods for saving and loading classifier objects. | ClassifierIO | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassifierIO:
"""Methods for saving and loading classifier objects."""
def save(self, dirpath, data=False, image=True, extension=None, **kwargs):
"""Save classifier to specified path. Args: dirpath (str) - directory in which classifier is to be saved data (bool) - if True, save train... | stack_v2_sparse_classes_36k_train_012379 | 9,044 | permissive | [
{
"docstring": "Save classifier to specified path. Args: dirpath (str) - directory in which classifier is to be saved data (bool) - if True, save training data image (bool) - if True, save labeled histogram image extension (str) - directory name extension kwargs: keyword arguments for image rendering",
"nam... | 2 | stack_v2_sparse_classes_30k_train_013930 | Implement the Python class `ClassifierIO` described below.
Class description:
Methods for saving and loading classifier objects.
Method signatures and docstrings:
- def save(self, dirpath, data=False, image=True, extension=None, **kwargs): Save classifier to specified path. Args: dirpath (str) - directory in which cl... | Implement the Python class `ClassifierIO` described below.
Class description:
Methods for saving and loading classifier objects.
Method signatures and docstrings:
- def save(self, dirpath, data=False, image=True, extension=None, **kwargs): Save classifier to specified path. Args: dirpath (str) - directory in which cl... | 4a622c3f5fed4456c3b9240f5a96428789fde9bd | <|skeleton|>
class ClassifierIO:
"""Methods for saving and loading classifier objects."""
def save(self, dirpath, data=False, image=True, extension=None, **kwargs):
"""Save classifier to specified path. Args: dirpath (str) - directory in which classifier is to be saved data (bool) - if True, save train... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassifierIO:
"""Methods for saving and loading classifier objects."""
def save(self, dirpath, data=False, image=True, extension=None, **kwargs):
"""Save classifier to specified path. Args: dirpath (str) - directory in which classifier is to be saved data (bool) - if True, save training data imag... | the_stack_v2_python_sparse | flyqma/annotation/classification/classifiers.py | sbernasek/flyqma | train | 1 |
1d7d8ba23a35df2fbd9c6d4bcdc9132f7ae659ec | [
"assert num_bases == len(init_weights)\nself._num_bases = int(num_bases)\nself._converge_epsilon = float(converge_epsilon)\nself._init_weights = Mat([[float(i)] for i in init_weights])\nself._data = []\nself._input = []\nself._label = []\nwith open(file_path, 'r') as file_:\n for line in file_.readlines():\n ... | <|body_start_0|>
assert num_bases == len(init_weights)
self._num_bases = int(num_bases)
self._converge_epsilon = float(converge_epsilon)
self._init_weights = Mat([[float(i)] for i in init_weights])
self._data = []
self._input = []
self._label = []
with ope... | Newton's Method Optimization | NewtonMethod | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewtonMethod:
"""Newton's Method Optimization"""
def __init__(self, file_path, num_bases, converge_epsilon, init_weights):
"""Get polynomail regression result by Newton's Method Optimization Args ---- file_path : str, path to dataset num_bases : int, degree of polynomial converge_eps... | stack_v2_sparse_classes_36k_train_012380 | 3,193 | no_license | [
{
"docstring": "Get polynomail regression result by Newton's Method Optimization Args ---- file_path : str, path to dataset num_bases : int, degree of polynomial converge_epsilon : float, the condition of convergence init_weights : list, shape=[num_bases,] the parameters of polynomial",
"name": "__init__",
... | 4 | stack_v2_sparse_classes_30k_train_004686 | Implement the Python class `NewtonMethod` described below.
Class description:
Newton's Method Optimization
Method signatures and docstrings:
- def __init__(self, file_path, num_bases, converge_epsilon, init_weights): Get polynomail regression result by Newton's Method Optimization Args ---- file_path : str, path to d... | Implement the Python class `NewtonMethod` described below.
Class description:
Newton's Method Optimization
Method signatures and docstrings:
- def __init__(self, file_path, num_bases, converge_epsilon, init_weights): Get polynomail regression result by Newton's Method Optimization Args ---- file_path : str, path to d... | b87c26e215b4ae0358d5cb79e685711691f4ced2 | <|skeleton|>
class NewtonMethod:
"""Newton's Method Optimization"""
def __init__(self, file_path, num_bases, converge_epsilon, init_weights):
"""Get polynomail regression result by Newton's Method Optimization Args ---- file_path : str, path to dataset num_bases : int, degree of polynomial converge_eps... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewtonMethod:
"""Newton's Method Optimization"""
def __init__(self, file_path, num_bases, converge_epsilon, init_weights):
"""Get polynomail regression result by Newton's Method Optimization Args ---- file_path : str, path to dataset num_bases : int, degree of polynomial converge_epsilon : float,... | the_stack_v2_python_sparse | HW1/Newton.py | chychen/NCTU_ML_2018 | train | 2 |
63d9321f25894963ef75a18b8cac17fdd6ccb80a | [
"model = User\nname = 'Users'\nsuper().__init__(model=model, collection_name=name)\nself.__dog_owner_repository = dog_owner_repository",
"users = list()\nowners = self.__dog_owner_repository.search(f'dog_id=={dog_id}')\nfor dog_owner in owners.to_list():\n try:\n user = self.read(dog_owner.owner_id)\n ... | <|body_start_0|>
model = User
name = 'Users'
super().__init__(model=model, collection_name=name)
self.__dog_owner_repository = dog_owner_repository
<|end_body_0|>
<|body_start_1|>
users = list()
owners = self.__dog_owner_repository.search(f'dog_id=={dog_id}')
for... | User repository. | UserRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRepository:
"""User repository."""
def __init__(self, dog_owner_repository):
"""Initialize user repository."""
<|body_0|>
def read_owners_of_dog(self, dog_id):
"""Get dogs associated with this user_id."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_012381 | 925 | no_license | [
{
"docstring": "Initialize user repository.",
"name": "__init__",
"signature": "def __init__(self, dog_owner_repository)"
},
{
"docstring": "Get dogs associated with this user_id.",
"name": "read_owners_of_dog",
"signature": "def read_owners_of_dog(self, dog_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019053 | Implement the Python class `UserRepository` described below.
Class description:
User repository.
Method signatures and docstrings:
- def __init__(self, dog_owner_repository): Initialize user repository.
- def read_owners_of_dog(self, dog_id): Get dogs associated with this user_id. | Implement the Python class `UserRepository` described below.
Class description:
User repository.
Method signatures and docstrings:
- def __init__(self, dog_owner_repository): Initialize user repository.
- def read_owners_of_dog(self, dog_id): Get dogs associated with this user_id.
<|skeleton|>
class UserRepository:
... | 129dc7f8213fb3112c35b1551d9ed3d8a14b7fb5 | <|skeleton|>
class UserRepository:
"""User repository."""
def __init__(self, dog_owner_repository):
"""Initialize user repository."""
<|body_0|>
def read_owners_of_dog(self, dog_id):
"""Get dogs associated with this user_id."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserRepository:
"""User repository."""
def __init__(self, dog_owner_repository):
"""Initialize user repository."""
model = User
name = 'Users'
super().__init__(model=model, collection_name=name)
self.__dog_owner_repository = dog_owner_repository
def read_owner... | the_stack_v2_python_sparse | hugbunadarfr_backend/src/app/repository/repositories/user_repository.py | birna17/veff_hugb | train | 0 |
2384517a4c9d28ca67fad3d19bc1db42df35ea2c | [
"response = session.query(AbilityModel.ID)\nresponse = response.filter(AbilityModel.HeroID == hero_id).all()\nif len(response) == 0:\n report = 'No abilities for this HeroID == {}'.format(hero_id)\n raise ValueError(report)\nmembers_ = [cls.member_type(a[0], patch=patch) for a in response]\nreturn cls(members... | <|body_start_0|>
response = session.query(AbilityModel.ID)
response = response.filter(AbilityModel.HeroID == hero_id).all()
if len(response) == 0:
report = 'No abilities for this HeroID == {}'.format(hero_id)
raise ValueError(report)
members_ = [cls.member_type(a[... | Any amount of abilities as one substance. | Abilities | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Abilities:
"""Any amount of abilities as one substance."""
def from_hero_id(cls, hero_id, patch=''):
"""Adds to members all abilities of the hero with `hero_id`."""
<|body_0|>
def all(cls):
"""Creates Abilities object with all heroes' abilities in the game."""
... | stack_v2_sparse_classes_36k_train_012382 | 1,392 | permissive | [
{
"docstring": "Adds to members all abilities of the hero with `hero_id`.",
"name": "from_hero_id",
"signature": "def from_hero_id(cls, hero_id, patch='')"
},
{
"docstring": "Creates Abilities object with all heroes' abilities in the game.",
"name": "all",
"signature": "def all(cls)"
}... | 2 | stack_v2_sparse_classes_30k_train_014345 | Implement the Python class `Abilities` described below.
Class description:
Any amount of abilities as one substance.
Method signatures and docstrings:
- def from_hero_id(cls, hero_id, patch=''): Adds to members all abilities of the hero with `hero_id`.
- def all(cls): Creates Abilities object with all heroes' abiliti... | Implement the Python class `Abilities` described below.
Class description:
Any amount of abilities as one substance.
Method signatures and docstrings:
- def from_hero_id(cls, hero_id, patch=''): Adds to members all abilities of the hero with `hero_id`.
- def all(cls): Creates Abilities object with all heroes' abiliti... | 23fc7072e734c6085a4f630a94998c268a423e20 | <|skeleton|>
class Abilities:
"""Any amount of abilities as one substance."""
def from_hero_id(cls, hero_id, patch=''):
"""Adds to members all abilities of the hero with `hero_id`."""
<|body_0|>
def all(cls):
"""Creates Abilities object with all heroes' abilities in the game."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Abilities:
"""Any amount of abilities as one substance."""
def from_hero_id(cls, hero_id, patch=''):
"""Adds to members all abilities of the hero with `hero_id`."""
response = session.query(AbilityModel.ID)
response = response.filter(AbilityModel.HeroID == hero_id).all()
i... | the_stack_v2_python_sparse | atod/models/abilities.py | gasabr/AtoD | train | 6 |
b7e27af93232c5796fac5c6476a8b4a654a90240 | [
"repo_ref = registry_model.lookup_repository(namespace_name, repository_name)\nif repo_ref is None:\n raise NotFound()\nmanifest = registry_model.lookup_manifest_by_digest(repo_ref, manifestref)\nif manifest is None:\n raise NotFound()\nlabel = registry_model.get_manifest_label(manifest, labelid)\nif label is... | <|body_start_0|>
repo_ref = registry_model.lookup_repository(namespace_name, repository_name)
if repo_ref is None:
raise NotFound()
manifest = registry_model.lookup_manifest_by_digest(repo_ref, manifestref)
if manifest is None:
raise NotFound()
label = reg... | Resource for managing the labels on a specific repository manifest. | ManageRepositoryManifestLabel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageRepositoryManifestLabel:
"""Resource for managing the labels on a specific repository manifest."""
def get(self, namespace_name, repository_name, manifestref, labelid):
"""Retrieves the label with the specific ID under the manifest."""
<|body_0|>
def delete(self, n... | stack_v2_sparse_classes_36k_train_012383 | 10,731 | permissive | [
{
"docstring": "Retrieves the label with the specific ID under the manifest.",
"name": "get",
"signature": "def get(self, namespace_name, repository_name, manifestref, labelid)"
},
{
"docstring": "Deletes an existing label from a manifest.",
"name": "delete",
"signature": "def delete(sel... | 2 | stack_v2_sparse_classes_30k_train_010857 | Implement the Python class `ManageRepositoryManifestLabel` described below.
Class description:
Resource for managing the labels on a specific repository manifest.
Method signatures and docstrings:
- def get(self, namespace_name, repository_name, manifestref, labelid): Retrieves the label with the specific ID under th... | Implement the Python class `ManageRepositoryManifestLabel` described below.
Class description:
Resource for managing the labels on a specific repository manifest.
Method signatures and docstrings:
- def get(self, namespace_name, repository_name, manifestref, labelid): Retrieves the label with the specific ID under th... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class ManageRepositoryManifestLabel:
"""Resource for managing the labels on a specific repository manifest."""
def get(self, namespace_name, repository_name, manifestref, labelid):
"""Retrieves the label with the specific ID under the manifest."""
<|body_0|>
def delete(self, n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManageRepositoryManifestLabel:
"""Resource for managing the labels on a specific repository manifest."""
def get(self, namespace_name, repository_name, manifestref, labelid):
"""Retrieves the label with the specific ID under the manifest."""
repo_ref = registry_model.lookup_repository(nam... | the_stack_v2_python_sparse | endpoints/api/manifest.py | quay/quay | train | 2,363 |
adb2ac5df13847ea6b3c15285f75b8ecd7e118a3 | [
"try:\n import spur\nexcept ImportError:\n print('You need to install spur.')\n exit(1)\nQueueBase.__init__(self, max_jobs=max_jobs)\nself._qsub_command = qsub_command\nself._shell = spur.LocalShell()",
"if task.get_traverse() is not False:\n return\njob = task.get_job()\ntid = task.get_tid()\nself._s... | <|body_start_0|>
try:
import spur
except ImportError:
print('You need to install spur.')
exit(1)
QueueBase.__init__(self, max_jobs=max_jobs)
self._qsub_command = qsub_command
self._shell = spur.LocalShell()
<|end_body_0|>
<|body_start_1|>
... | LocalQueue base class. | LocalQueueBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocalQueueBase:
"""LocalQueue base class."""
def __init__(self, max_jobs=None, qsub_command='qsub'):
"""Init method."""
<|body_0|>
def submit(self, task):
"""Submit."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
import spur
... | stack_v2_sparse_classes_36k_train_012384 | 10,513 | no_license | [
{
"docstring": "Init method.",
"name": "__init__",
"signature": "def __init__(self, max_jobs=None, qsub_command='qsub')"
},
{
"docstring": "Submit.",
"name": "submit",
"signature": "def submit(self, task)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010594 | Implement the Python class `LocalQueueBase` described below.
Class description:
LocalQueue base class.
Method signatures and docstrings:
- def __init__(self, max_jobs=None, qsub_command='qsub'): Init method.
- def submit(self, task): Submit. | Implement the Python class `LocalQueueBase` described below.
Class description:
LocalQueue base class.
Method signatures and docstrings:
- def __init__(self, max_jobs=None, qsub_command='qsub'): Init method.
- def submit(self, task): Submit.
<|skeleton|>
class LocalQueueBase:
"""LocalQueue base class."""
de... | af5478080be86ad437f831c9895954d0fa0f17e2 | <|skeleton|>
class LocalQueueBase:
"""LocalQueue base class."""
def __init__(self, max_jobs=None, qsub_command='qsub'):
"""Init method."""
<|body_0|>
def submit(self, task):
"""Submit."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocalQueueBase:
"""LocalQueue base class."""
def __init__(self, max_jobs=None, qsub_command='qsub'):
"""Init method."""
try:
import spur
except ImportError:
print('You need to install spur.')
exit(1)
QueueBase.__init__(self, max_jobs=max... | the_stack_v2_python_sparse | cogue/qsystem/queue.py | atztogo/cogue | train | 12 |
642a58bca1175a1a8d6fb1df852720568e4c8709 | [
"agent = Agent.query.filter_by(id=agent_id).first()\nif agent is None:\n return (jsonify(error='Agent %r not found' % agent_id), NOT_FOUND)\nout = []\nfor version in agent.software_versions:\n software_dict = {'software': version.software.software, 'version': version.version}\n out.append(software_dict)\nr... | <|body_start_0|>
agent = Agent.query.filter_by(id=agent_id).first()
if agent is None:
return (jsonify(error='Agent %r not found' % agent_id), NOT_FOUND)
out = []
for version in agent.software_versions:
software_dict = {'software': version.software.software, 'versi... | SoftwareInAgentIndexAPI | [
"BSD-3-Clause",
"Apache-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftwareInAgentIndexAPI:
def get(self, agent_id):
"""A ``GET`` to this endpoint will return a list of all software versions available on this agent. .. http:get:: /api/v1/agents/<str:agent_id>/software/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-... | stack_v2_sparse_classes_36k_train_012385 | 40,281 | permissive | [
{
"docstring": "A ``GET`` to this endpoint will return a list of all software versions available on this agent. .. http:get:: /api/v1/agents/<str:agent_id>/software/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-139bd8057931/software/ HTTP/1.1 Accept: application/json **Re... | 2 | stack_v2_sparse_classes_30k_train_001469 | Implement the Python class `SoftwareInAgentIndexAPI` described below.
Class description:
Implement the SoftwareInAgentIndexAPI class.
Method signatures and docstrings:
- def get(self, agent_id): A ``GET`` to this endpoint will return a list of all software versions available on this agent. .. http:get:: /api/v1/agent... | Implement the Python class `SoftwareInAgentIndexAPI` described below.
Class description:
Implement the SoftwareInAgentIndexAPI class.
Method signatures and docstrings:
- def get(self, agent_id): A ``GET`` to this endpoint will return a list of all software versions available on this agent. .. http:get:: /api/v1/agent... | ea04bbcb807eb669415c569417b4b1b68e75d29d | <|skeleton|>
class SoftwareInAgentIndexAPI:
def get(self, agent_id):
"""A ``GET`` to this endpoint will return a list of all software versions available on this agent. .. http:get:: /api/v1/agents/<str:agent_id>/software/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SoftwareInAgentIndexAPI:
def get(self, agent_id):
"""A ``GET`` to this endpoint will return a list of all software versions available on this agent. .. http:get:: /api/v1/agents/<str:agent_id>/software/ HTTP/1.1 **Request** .. sourcecode:: http GET /api/v1/agents/bbf55143-f2b1-4c15-9d41-139bd8057931/s... | the_stack_v2_python_sparse | pyfarm/master/api/agents.py | pyfarm/pyfarm-master | train | 2 | |
f57ab9dc9af422ca04c8b4014be0d0b5f43aa892 | [
"with open('config.json') as config:\n settings = json.load(config)['Notifications']\nemail = MIMEMultipart()\nemail['From'] = settings['Sender']\nemail['To'] = receiver\nif 'test' in category:\n email, message = self.set_test(email, info)\nelif 'idle' in category:\n email, message = self.set_idle(email, i... | <|body_start_0|>
with open('config.json') as config:
settings = json.load(config)['Notifications']
email = MIMEMultipart()
email['From'] = settings['Sender']
email['To'] = receiver
if 'test' in category:
email, message = self.set_test(email, info)
... | Module used to send notification emails which may include image attachments to a specified email address | Notifications | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Notifications:
"""Module used to send notification emails which may include image attachments to a specified email address"""
def send(self, receiver, category, attachment_name='', info=None):
"""Construct the notification email by setting sending and receiving members and the text m... | stack_v2_sparse_classes_36k_train_012386 | 4,735 | no_license | [
{
"docstring": "Construct the notification email by setting sending and receiving members and the text message itself Attach any received attachments and finally send the email to the specified receiver address",
"name": "send",
"signature": "def send(self, receiver, category, attachment_name='', info=N... | 5 | stack_v2_sparse_classes_30k_train_018127 | Implement the Python class `Notifications` described below.
Class description:
Module used to send notification emails which may include image attachments to a specified email address
Method signatures and docstrings:
- def send(self, receiver, category, attachment_name='', info=None): Construct the notification emai... | Implement the Python class `Notifications` described below.
Class description:
Module used to send notification emails which may include image attachments to a specified email address
Method signatures and docstrings:
- def send(self, receiver, category, attachment_name='', info=None): Construct the notification emai... | cdcdfad34691fb8434f67c69d2f8b037197028cc | <|skeleton|>
class Notifications:
"""Module used to send notification emails which may include image attachments to a specified email address"""
def send(self, receiver, category, attachment_name='', info=None):
"""Construct the notification email by setting sending and receiving members and the text m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Notifications:
"""Module used to send notification emails which may include image attachments to a specified email address"""
def send(self, receiver, category, attachment_name='', info=None):
"""Construct the notification email by setting sending and receiving members and the text message itself... | the_stack_v2_python_sparse | notifications.py | Spinarakk/defectmonitor | train | 0 |
fa6deecde967815892cac53b61d6d4438ea78f10 | [
"def helper(node):\n if node == None:\n return '#'\n return str(node.val) + '*' + helper(node.left) + helper(node.right)\nreturn helper(root)",
"def helper(index):\n if data[index] == '#':\n return (None, index)\n word = ''\n while data[index] != '*':\n word += data[index]\n ... | <|body_start_0|>
def helper(node):
if node == None:
return '#'
return str(node.val) + '*' + helper(node.left) + helper(node.right)
return helper(root)
<|end_body_0|>
<|body_start_1|>
def helper(index):
if data[index] == '#':
re... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_012387 | 4,399 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 00fd1397b65c68a303fcf963db3e28cd35c1c003 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def helper(node):
if node == None:
return '#'
return str(node.val) + '*' + helper(node.left) + helper(node.right)
return helper(root)
... | the_stack_v2_python_sparse | leetcode/449. Serialize and Deserialize BST.py | cuiy0006/Algorithms | train | 0 | |
dc7778ff12a2bcc5f6467c400da599fa05252de1 | [
"try:\n data = explorer_config.ExplorerConfigModel.Get().to_dict()\n self.RenderJson(data)\nexcept Exception as err:\n self.RenderJson(data={error_fields.MESSAGE: err.message}, status=500)",
"try:\n data = json.loads(self.request.body)\n explorer_config.ExplorerConfigModel.Update(data)\nexcept Exce... | <|body_start_0|>
try:
data = explorer_config.ExplorerConfigModel.Get().to_dict()
self.RenderJson(data)
except Exception as err:
self.RenderJson(data={error_fields.MESSAGE: err.message}, status=500)
<|end_body_0|>
<|body_start_1|>
try:
data = json.... | Http handler for getting the global config. Returns: JSON representation of the global config. | ConfigHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigHandler:
"""Http handler for getting the global config. Returns: JSON representation of the global config."""
def get(self):
"""Returns the global config."""
<|body_0|>
def post(self):
"""Updates the global config based on the request body."""
<|bod... | stack_v2_sparse_classes_36k_train_012388 | 2,132 | permissive | [
{
"docstring": "Returns the global config.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Updates the global config based on the request body.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `ConfigHandler` described below.
Class description:
Http handler for getting the global config. Returns: JSON representation of the global config.
Method signatures and docstrings:
- def get(self): Returns the global config.
- def post(self): Updates the global config based on the request b... | Implement the Python class `ConfigHandler` described below.
Class description:
Http handler for getting the global config. Returns: JSON representation of the global config.
Method signatures and docstrings:
- def get(self): Returns the global config.
- def post(self): Updates the global config based on the request b... | 9efa61015d50c25f6d753f0212ad3bf16876d496 | <|skeleton|>
class ConfigHandler:
"""Http handler for getting the global config. Returns: JSON representation of the global config."""
def get(self):
"""Returns the global config."""
<|body_0|>
def post(self):
"""Updates the global config based on the request body."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigHandler:
"""Http handler for getting the global config. Returns: JSON representation of the global config."""
def get(self):
"""Returns the global config."""
try:
data = explorer_config.ExplorerConfigModel.Get().to_dict()
self.RenderJson(data)
except ... | the_stack_v2_python_sparse | server/perfkit/explorer/handlers/explorer_config.py | GoogleCloudPlatform/PerfKitExplorer | train | 292 |
2e75f3f70ab13799d3b163d4f2873035a0de5839 | [
"name = ''.join(filter(str.isalnum, label)).lower()\nif background_color is None:\n background_color = BACKGROUND_COLOR\nLabel.__init__(self, name, label, rect, background_color)\nself.left_click_callback = callback\nself.clicked_counter = 0\nself.redraw()\nreturn",
"Label.redraw(self)\nself.image.lock()\npyga... | <|body_start_0|>
name = ''.join(filter(str.isalnum, label)).lower()
if background_color is None:
background_color = BACKGROUND_COLOR
Label.__init__(self, name, label, rect, background_color)
self.left_click_callback = callback
self.clicked_counter = 0
self.red... | A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color | Button | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Button:
"""A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color"""
def __init__(self, label, ... | stack_v2_sparse_classes_36k_train_012389 | 27,668 | permissive | [
{
"docstring": "Initialise the Button. label is the Text to be written on the button. rect is an instance of pygame.Rect giving the dimensions. callback is the function to be called when the Button is clicked with the left mouse button.",
"name": "__init__",
"signature": "def __init__(self, label, rect,... | 4 | stack_v2_sparse_classes_30k_train_009544 | Implement the Python class `Button` described below.
Class description:
A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different c... | Implement the Python class `Button` described below.
Class description:
A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different c... | c2fc3d4e9beedb8487cfa4bfa13bdf55ec36af97 | <|skeleton|>
class Button:
"""A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color"""
def __init__(self, label, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Button:
"""A clickndrag plane which displays a text and reacts on mouse clicks. Additional attributes: Button.callback The callback function to be called upon clicking. Button.clicked_counter Counted down when the button is clicked and displays a different color"""
def __init__(self, label, rect, callbac... | the_stack_v2_python_sparse | reference_scripts/clickndrag-0.4.1/clickndrag/gui.py | stivosaurus/rpi-snippets | train | 1 |
d48eaf3f2ca2f639f53e1be750b170bc47851085 | [
"try:\n email = username\n user = self.user_class.objects.get(contact__email_addresses__email_address__iexact=email, contact__email_addresses__is_primary=True)\n if user.is_active and (user.check_password(password) or no_pass):\n return user\n return None\nexcept self.user_class.DoesNotExist:\n ... | <|body_start_0|>
try:
email = username
user = self.user_class.objects.get(contact__email_addresses__email_address__iexact=email, contact__email_addresses__is_primary=True)
if user.is_active and (user.check_password(password) or no_pass):
return user
... | Authenticate a CustomUser with e-mail address instead of username. | EmailAuthenticationBackend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailAuthenticationBackend:
"""Authenticate a CustomUser with e-mail address instead of username."""
def authenticate(self, username=None, password=None, no_pass=False):
"""Check if the user is properly authenticated, either logging in by e-mail address and password or programmatical... | stack_v2_sparse_classes_36k_train_012390 | 1,808 | no_license | [
{
"docstring": "Check if the user is properly authenticated, either logging in by e-mail address and password or programmatically logged in (e.g. upon activation of account) using no_pass=True.",
"name": "authenticate",
"signature": "def authenticate(self, username=None, password=None, no_pass=False)"
... | 3 | stack_v2_sparse_classes_30k_train_012341 | Implement the Python class `EmailAuthenticationBackend` described below.
Class description:
Authenticate a CustomUser with e-mail address instead of username.
Method signatures and docstrings:
- def authenticate(self, username=None, password=None, no_pass=False): Check if the user is properly authenticated, either lo... | Implement the Python class `EmailAuthenticationBackend` described below.
Class description:
Authenticate a CustomUser with e-mail address instead of username.
Method signatures and docstrings:
- def authenticate(self, username=None, password=None, no_pass=False): Check if the user is properly authenticated, either lo... | 0a284e2aae3ca08955215418a76bb70ad9af1f81 | <|skeleton|>
class EmailAuthenticationBackend:
"""Authenticate a CustomUser with e-mail address instead of username."""
def authenticate(self, username=None, password=None, no_pass=False):
"""Check if the user is properly authenticated, either logging in by e-mail address and password or programmatical... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmailAuthenticationBackend:
"""Authenticate a CustomUser with e-mail address instead of username."""
def authenticate(self, username=None, password=None, no_pass=False):
"""Check if the user is properly authenticated, either logging in by e-mail address and password or programmatically logged in ... | the_stack_v2_python_sparse | lily/users/auth_backends.py | rmoorman/hellolily | train | 0 |
dc4be14d2d66dac55f33e7bb47a38e6dac681354 | [
"super(SiteOrder, self).__init__(parent)\nself.parent = parent\nself.resize(400, 300)\nself.list_site = list_site\nself.populate(self.list_site)",
"mainLayout = QtGui.QGridLayout(self)\nself.list_site = QtGui.QListWidget()\nfor i in list_site:\n item = QtGui.QListWidgetItem(i)\n self.list_site.addItem(item)... | <|body_start_0|>
super(SiteOrder, self).__init__(parent)
self.parent = parent
self.resize(400, 300)
self.list_site = list_site
self.populate(self.list_site)
<|end_body_0|>
<|body_start_1|>
mainLayout = QtGui.QGridLayout(self)
self.list_site = QtGui.QListWidget()
... | display playing list | SiteOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SiteOrder:
"""display playing list"""
def __init__(self, list_site, parent=None):
"""initialisation"""
<|body_0|>
def populate(self, list_site):
"""create layout"""
<|body_1|>
def moveUp(self):
"""up is clicked"""
<|body_2|>
def ... | stack_v2_sparse_classes_36k_train_012391 | 2,368 | no_license | [
{
"docstring": "initialisation",
"name": "__init__",
"signature": "def __init__(self, list_site, parent=None)"
},
{
"docstring": "create layout",
"name": "populate",
"signature": "def populate(self, list_site)"
},
{
"docstring": "up is clicked",
"name": "moveUp",
"signatu... | 5 | null | Implement the Python class `SiteOrder` described below.
Class description:
display playing list
Method signatures and docstrings:
- def __init__(self, list_site, parent=None): initialisation
- def populate(self, list_site): create layout
- def moveUp(self): up is clicked
- def moveDown(self): down is clicked
- def sa... | Implement the Python class `SiteOrder` described below.
Class description:
display playing list
Method signatures and docstrings:
- def __init__(self, list_site, parent=None): initialisation
- def populate(self, list_site): create layout
- def moveUp(self): up is clicked
- def moveDown(self): down is clicked
- def sa... | a24b3e4e8acbd4da9ba4c83bf96c0b2d2a2cca9c | <|skeleton|>
class SiteOrder:
"""display playing list"""
def __init__(self, list_site, parent=None):
"""initialisation"""
<|body_0|>
def populate(self, list_site):
"""create layout"""
<|body_1|>
def moveUp(self):
"""up is clicked"""
<|body_2|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SiteOrder:
"""display playing list"""
def __init__(self, list_site, parent=None):
"""initialisation"""
super(SiteOrder, self).__init__(parent)
self.parent = parent
self.resize(400, 300)
self.list_site = list_site
self.populate(self.list_site)
def popul... | the_stack_v2_python_sparse | gui/menusiteorder.py | sensini42/flvdown | train | 0 |
e081707a39263b622c1f0c7fb48128b0361b3d0d | [
"if type(fndats) is str:\n fndats = [fndats]\nif len(fndats) == 1 and len(fndats) != len(scans):\n fndats *= len(scans)\nelse:\n raise NameError('check fndats/scans input')\nnscans = _check_scans(scans)\nself.fndats = fndats\nself.nscans = nscans\nself.counter = counter\nself.signal = signal\nself.monitor ... | <|body_start_0|>
if type(fndats) is str:
fndats = [fndats]
if len(fndats) == 1 and len(fndats) != len(scans):
fndats *= len(scans)
else:
raise NameError('check fndats/scans input')
nscans = _check_scans(scans)
self.fndats = fndats
self.... | wrapper | SpecfileDataCollector | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecfileDataCollector:
"""wrapper"""
def __init__(self, fndats, scans, counter=1, signal='det_dtc', monitor='I02', seconds='Seconds'):
"""collects data from a given scan list inside a single SPEC file Parameters ---------- fndats : string or list of strings -> file name(s) scans : li... | stack_v2_sparse_classes_36k_train_012392 | 3,232 | permissive | [
{
"docstring": "collects data from a given scan list inside a single SPEC file Parameters ---------- fndats : string or list of strings -> file name(s) scans : list of scans to load (parsed by str2rng) counter : counter name for x [string, 1] signal : counter name for y [string, 'det_dtc'] monitor : counter nam... | 2 | stack_v2_sparse_classes_30k_train_020587 | Implement the Python class `SpecfileDataCollector` described below.
Class description:
wrapper
Method signatures and docstrings:
- def __init__(self, fndats, scans, counter=1, signal='det_dtc', monitor='I02', seconds='Seconds'): collects data from a given scan list inside a single SPEC file Parameters ---------- fnda... | Implement the Python class `SpecfileDataCollector` described below.
Class description:
wrapper
Method signatures and docstrings:
- def __init__(self, fndats, scans, counter=1, signal='det_dtc', monitor='I02', seconds='Seconds'): collects data from a given scan list inside a single SPEC file Parameters ---------- fnda... | d0ff10530833fa8b0866f7303a6a8c99d5a9b208 | <|skeleton|>
class SpecfileDataCollector:
"""wrapper"""
def __init__(self, fndats, scans, counter=1, signal='det_dtc', monitor='I02', seconds='Seconds'):
"""collects data from a given scan list inside a single SPEC file Parameters ---------- fndats : string or list of strings -> file name(s) scans : li... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpecfileDataCollector:
"""wrapper"""
def __init__(self, fndats, scans, counter=1, signal='det_dtc', monitor='I02', seconds='Seconds'):
"""collects data from a given scan list inside a single SPEC file Parameters ---------- fndats : string or list of strings -> file name(s) scans : list of scans t... | the_stack_v2_python_sparse | sloth/io/specfile_eval_utils.py | maurov/xraysloth | train | 6 |
1096e6f8d2d49dffaaa108b71ca71f84ab5d0e1f | [
"logger.info('Overriding class: Optimizer -> GWO.')\nsuper(GWO, self).__init__()\nself.build(params)\nlogger.info('Class overrided.')",
"r1 = r.generate_uniform_random_number()\nr2 = r.generate_uniform_random_number()\nA = 2 * a * r1 - a\nC = 2 * r2\nreturn (A, C)",
"space.agents.sort(key=lambda x: x.fit)\nalph... | <|body_start_0|>
logger.info('Overriding class: Optimizer -> GWO.')
super(GWO, self).__init__()
self.build(params)
logger.info('Class overrided.')
<|end_body_0|>
<|body_start_1|>
r1 = r.generate_uniform_random_number()
r2 = r.generate_uniform_random_number()
A = ... | A GWO class, inherited from Optimizer. This is the designed class to define GWO-related variables and methods. References: S. Mirjalili, S. Mirjalili and A. Lewis. Grey Wolf Optimizer. Advances in Engineering Software (2014). | GWO | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GWO:
"""A GWO class, inherited from Optimizer. This is the designed class to define GWO-related variables and methods. References: S. Mirjalili, S. Mirjalili and A. Lewis. Grey Wolf Optimizer. Advances in Engineering Software (2014)."""
def __init__(self, params: Optional[Dict[str, Any]]=Non... | stack_v2_sparse_classes_36k_train_012393 | 3,064 | permissive | [
{
"docstring": "Initialization method. Args: params: Contains key-value parameters to the meta-heuristics.",
"name": "__init__",
"signature": "def __init__(self, params: Optional[Dict[str, Any]]=None) -> None"
},
{
"docstring": "Calculates the mathematical coefficients. Args: a: Linear constant.... | 3 | null | Implement the Python class `GWO` described below.
Class description:
A GWO class, inherited from Optimizer. This is the designed class to define GWO-related variables and methods. References: S. Mirjalili, S. Mirjalili and A. Lewis. Grey Wolf Optimizer. Advances in Engineering Software (2014).
Method signatures and d... | Implement the Python class `GWO` described below.
Class description:
A GWO class, inherited from Optimizer. This is the designed class to define GWO-related variables and methods. References: S. Mirjalili, S. Mirjalili and A. Lewis. Grey Wolf Optimizer. Advances in Engineering Software (2014).
Method signatures and d... | 7326a887ed8e3858bc99c8815048d56d02edf88c | <|skeleton|>
class GWO:
"""A GWO class, inherited from Optimizer. This is the designed class to define GWO-related variables and methods. References: S. Mirjalili, S. Mirjalili and A. Lewis. Grey Wolf Optimizer. Advances in Engineering Software (2014)."""
def __init__(self, params: Optional[Dict[str, Any]]=Non... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GWO:
"""A GWO class, inherited from Optimizer. This is the designed class to define GWO-related variables and methods. References: S. Mirjalili, S. Mirjalili and A. Lewis. Grey Wolf Optimizer. Advances in Engineering Software (2014)."""
def __init__(self, params: Optional[Dict[str, Any]]=None) -> None:
... | the_stack_v2_python_sparse | opytimizer/optimizers/population/gwo.py | gugarosa/opytimizer | train | 602 |
a7a480abc54fa1837b16567320b150a8c90f42b7 | [
"super(SearchSettingsForm, self).__init__(siteconfig, data, *args, **kwargs)\nrequest = kwargs.get('request')\ncur_search_backend_id = self['search_backend_id'].data or self.fields['search_backend_id'].initial\nchoices = []\nsearch_backend_forms = {}\nfor backend in search_backend_registry:\n search_backend_id =... | <|body_start_0|>
super(SearchSettingsForm, self).__init__(siteconfig, data, *args, **kwargs)
request = kwargs.get('request')
cur_search_backend_id = self['search_backend_id'].data or self.fields['search_backend_id'].initial
choices = []
search_backend_forms = {}
for backe... | Form for search settings. This form manages the main search settings (enabled, how many results, and what backend to use), as well as displaying per-search backend forms so that they may be configured. For example, Elasticsearch requires a URL and index name, while Whoosh requires a file path to store its index. These ... | SearchSettingsForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchSettingsForm:
"""Form for search settings. This form manages the main search settings (enabled, how many results, and what backend to use), as well as displaying per-search backend forms so that they may be configured. For example, Elasticsearch requires a URL and index name, while Whoosh r... | stack_v2_sparse_classes_36k_train_012394 | 7,792 | permissive | [
{
"docstring": "Initialize the search engine settings form. This will also initialize the settings forms for each search engine backend. Args: site_config (djblets.siteconfig.models.SiteConfiguration): The site configuration handling the server's settings. data (dict, optional): The form data. *args (tuple): Ad... | 5 | null | Implement the Python class `SearchSettingsForm` described below.
Class description:
Form for search settings. This form manages the main search settings (enabled, how many results, and what backend to use), as well as displaying per-search backend forms so that they may be configured. For example, Elasticsearch requir... | Implement the Python class `SearchSettingsForm` described below.
Class description:
Form for search settings. This form manages the main search settings (enabled, how many results, and what backend to use), as well as displaying per-search backend forms so that they may be configured. For example, Elasticsearch requir... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class SearchSettingsForm:
"""Form for search settings. This form manages the main search settings (enabled, how many results, and what backend to use), as well as displaying per-search backend forms so that they may be configured. For example, Elasticsearch requires a URL and index name, while Whoosh r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchSettingsForm:
"""Form for search settings. This form manages the main search settings (enabled, how many results, and what backend to use), as well as displaying per-search backend forms so that they may be configured. For example, Elasticsearch requires a URL and index name, while Whoosh requires a fil... | the_stack_v2_python_sparse | reviewboard/admin/forms/search_settings.py | reviewboard/reviewboard | train | 1,141 |
754f398ea0de11f9f48312804fa8758f38eccc35 | [
"a2b = self.filter(sender=sender, recipient=recipient).select_related('sender', 'recipient')\nb2a = self.filter(sender=recipient, recipient=sender).select_related('sender', 'recipient')\nreturn a2b.union(b2a).order_by('created_at')",
"try:\n qs_sent = self.filter(sender=recipient)\n qs_received = self.filte... | <|body_start_0|>
a2b = self.filter(sender=sender, recipient=recipient).select_related('sender', 'recipient')
b2a = self.filter(sender=recipient, recipient=sender).select_related('sender', 'recipient')
return a2b.union(b2a).order_by('created_at')
<|end_body_0|>
<|body_start_1|>
try:
... | MessageQueryset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageQueryset:
def get_conversation(self, sender, recipient):
"""获取用户间的私信会话"""
<|body_0|>
def get_most_recent_conversation(self, recipient):
"""获取最近一次的私信互动用户，即登录用户作为接受者，判断最后一条消息是自己发出还是发送者发出"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
a2b = sel... | stack_v2_sparse_classes_36k_train_012395 | 3,008 | no_license | [
{
"docstring": "获取用户间的私信会话",
"name": "get_conversation",
"signature": "def get_conversation(self, sender, recipient)"
},
{
"docstring": "获取最近一次的私信互动用户，即登录用户作为接受者，判断最后一条消息是自己发出还是发送者发出",
"name": "get_most_recent_conversation",
"signature": "def get_most_recent_conversation(self, recipient)... | 2 | stack_v2_sparse_classes_30k_train_021082 | Implement the Python class `MessageQueryset` described below.
Class description:
Implement the MessageQueryset class.
Method signatures and docstrings:
- def get_conversation(self, sender, recipient): 获取用户间的私信会话
- def get_most_recent_conversation(self, recipient): 获取最近一次的私信互动用户，即登录用户作为接受者，判断最后一条消息是自己发出还是发送者发出 | Implement the Python class `MessageQueryset` described below.
Class description:
Implement the MessageQueryset class.
Method signatures and docstrings:
- def get_conversation(self, sender, recipient): 获取用户间的私信会话
- def get_most_recent_conversation(self, recipient): 获取最近一次的私信互动用户，即登录用户作为接受者，判断最后一条消息是自己发出还是发送者发出
<|skel... | 221f485c7ee594adc34722f14aa94730e23a8d71 | <|skeleton|>
class MessageQueryset:
def get_conversation(self, sender, recipient):
"""获取用户间的私信会话"""
<|body_0|>
def get_most_recent_conversation(self, recipient):
"""获取最近一次的私信互动用户，即登录用户作为接受者，判断最后一条消息是自己发出还是发送者发出"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MessageQueryset:
def get_conversation(self, sender, recipient):
"""获取用户间的私信会话"""
a2b = self.filter(sender=sender, recipient=recipient).select_related('sender', 'recipient')
b2a = self.filter(sender=recipient, recipient=sender).select_related('sender', 'recipient')
return a2b.un... | the_stack_v2_python_sparse | zanhu/messager/models.py | AlaxHAM/qa | train | 0 | |
8279bd86bdc1fd1135c7b63c1facd88d2cb2dba0 | [
"sprite.Sprite.__init__(self, node, mMap, position, level)\nself.initialPosition = self.position\nself.move = MT_NONE\nmovements = node.getChildren('movement')\nif movements:\n movementNode = movements[0]\n movementType = movementNode.getAttr('type', data.D_STRING)\n if movementType == 'wander':\n s... | <|body_start_0|>
sprite.Sprite.__init__(self, node, mMap, position, level)
self.initialPosition = self.position
self.move = MT_NONE
movements = node.getChildren('movement')
if movements:
movementNode = movements[0]
movementType = movementNode.getAttr('type... | NPC class extending Sprite with auto movements and event scripts. | NPC | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NPC:
"""NPC class extending Sprite with auto movements and event scripts."""
def __init__(self, node, mMap, position=None, level=None):
"""Initialise the sprite, and set up movement and scripts. node - the <npc> node. mMap - the map to start on. position - the position to start in. I... | stack_v2_sparse_classes_36k_train_012396 | 4,934 | no_license | [
{
"docstring": "Initialise the sprite, and set up movement and scripts. node - the <npc> node. mMap - the map to start on. position - the position to start in. If unspecified gets taken from the <npc> node. level - the level to start on. If unspecified gets taken from the <npc> node.",
"name": "__init__",
... | 3 | null | Implement the Python class `NPC` described below.
Class description:
NPC class extending Sprite with auto movements and event scripts.
Method signatures and docstrings:
- def __init__(self, node, mMap, position=None, level=None): Initialise the sprite, and set up movement and scripts. node - the <npc> node. mMap - th... | Implement the Python class `NPC` described below.
Class description:
NPC class extending Sprite with auto movements and event scripts.
Method signatures and docstrings:
- def __init__(self, node, mMap, position=None, level=None): Initialise the sprite, and set up movement and scripts. node - the <npc> node. mMap - th... | 72841fc503c716ac3b524e42f2311cbd9d18a092 | <|skeleton|>
class NPC:
"""NPC class extending Sprite with auto movements and event scripts."""
def __init__(self, node, mMap, position=None, level=None):
"""Initialise the sprite, and set up movement and scripts. node - the <npc> node. mMap - the map to start on. position - the position to start in. I... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NPC:
"""NPC class extending Sprite with auto movements and event scripts."""
def __init__(self, node, mMap, position=None, level=None):
"""Initialise the sprite, and set up movement and scripts. node - the <npc> node. mMap - the map to start on. position - the position to start in. If unspecified... | the_stack_v2_python_sparse | eng/npc.py | andrew-turner/Ditto | train | 0 |
5bf3a626ae092b2fe0d1c2d8623b2609f9d3e34d | [
"if not head:\n return None\nself.reverse_iter(head)\nreturn self.head",
"if not node.next:\n self.head = node\n return node\nelse:\n parent = self.reverse_iter(node.next)\n parent.next = ListNode(node.val)\n parent = parent.next\n return parent"
] | <|body_start_0|>
if not head:
return None
self.reverse_iter(head)
return self.head
<|end_body_0|>
<|body_start_1|>
if not node.next:
self.head = node
return node
else:
parent = self.reverse_iter(node.next)
parent.next =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverse_iter(self, node):
""":type node: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not head:
return None... | stack_v2_sparse_classes_36k_train_012397 | 1,997 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
},
{
"docstring": ":type node: ListNode :rtype: ListNode",
"name": "reverse_iter",
"signature": "def reverse_iter(self, node)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012867 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reverse_iter(self, node): :type node: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode
- def reverse_iter(self, node): :type node: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def re... | f832227c4d0e0b1c0cc326561187004ef24e2a68 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverse_iter(self, node):
""":type node: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode"""
if not head:
return None
self.reverse_iter(head)
return self.head
def reverse_iter(self, node):
""":type node: ListNode :rtype: ListNode"""
if not node.next:
... | the_stack_v2_python_sparse | 206.py | Gackle/leetcode_practice | train | 0 | |
1dcb7afdfb5aa1df0f97431d261f89594d143751 | [
"if k == 1:\n return [i for i in range(1, n + 1)]\nans = [n]\ndec = True\nfor diff in range(k, 0, -1):\n if dec:\n ans.append(ans[len(ans) - 1] - diff)\n dec = False\n else:\n ans.append(ans[len(ans) - 1] + diff)\n dec = True\nlast = ans[len(ans) - 1]\nif last - 2 > 0:\n ans.... | <|body_start_0|>
if k == 1:
return [i for i in range(1, n + 1)]
ans = [n]
dec = True
for diff in range(k, 0, -1):
if dec:
ans.append(ans[len(ans) - 1] - diff)
dec = False
else:
ans.append(ans[len(ans) - 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def constructArray(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
<|body_0|>
def constructArray2(self, n, k):
"""We need k+1 numbers to generate k distinct differences. Put first (n-k-1) elements in order: [1, 2, ..., n-k-1], then for the re... | stack_v2_sparse_classes_36k_train_012398 | 1,609 | no_license | [
{
"docstring": ":type n: int :type k: int :rtype: List[int]",
"name": "constructArray",
"signature": "def constructArray(self, n, k)"
},
{
"docstring": "We need k+1 numbers to generate k distinct differences. Put first (n-k-1) elements in order: [1, 2, ..., n-k-1], then for the remaining [n-k, n... | 2 | stack_v2_sparse_classes_30k_train_010668 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructArray(self, n, k): :type n: int :type k: int :rtype: List[int]
- def constructArray2(self, n, k): We need k+1 numbers to generate k distinct differences. Put first (... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructArray(self, n, k): :type n: int :type k: int :rtype: List[int]
- def constructArray2(self, n, k): We need k+1 numbers to generate k distinct differences. Put first (... | 143aa25f92f3827aa379f29c67a9b7ec3757fef9 | <|skeleton|>
class Solution:
def constructArray(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
<|body_0|>
def constructArray2(self, n, k):
"""We need k+1 numbers to generate k distinct differences. Put first (n-k-1) elements in order: [1, 2, ..., n-k-1], then for the re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def constructArray(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
if k == 1:
return [i for i in range(1, n + 1)]
ans = [n]
dec = True
for diff in range(k, 0, -1):
if dec:
ans.append(ans[len(ans) - 1] - di... | the_stack_v2_python_sparse | py/leetcode_py/667.py | imsure/tech-interview-prep | train | 0 | |
08c3cbab67bb9c6a75f5dbc4f0bca708f0ab3cf2 | [
"self.file_itr = None\nself.path = path\nif os.path.isdir(self.path):\n self.file_itr = glob.glob(self.path + '*')\nself.transform_filename_to_tensor = transform_filename_to_tensor",
"if self.file_itr is not None:\n return map(self.transform_filename_to_tensor, self.file_itr)\nelse:\n return self.transfo... | <|body_start_0|>
self.file_itr = None
self.path = path
if os.path.isdir(self.path):
self.file_itr = glob.glob(self.path + '*')
self.transform_filename_to_tensor = transform_filename_to_tensor
<|end_body_0|>
<|body_start_1|>
if self.file_itr is not None:
r... | An auxiliary class for iterating through a dataset. | CustomIterableDataset | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomIterableDataset:
"""An auxiliary class for iterating through a dataset."""
def __init__(self, transform_filename_to_tensor: Callable, path: str) -> None:
"""Args: transform_filename_to_tensor (Callable): Function to read a data file from path and return a tensor from that file.... | stack_v2_sparse_classes_36k_train_012399 | 1,919 | permissive | [
{
"docstring": "Args: transform_filename_to_tensor (Callable): Function to read a data file from path and return a tensor from that file. path (str): Path to dataset files. This can be either a path to a directory or a file where input examples are stored.",
"name": "__init__",
"signature": "def __init_... | 2 | stack_v2_sparse_classes_30k_train_020292 | Implement the Python class `CustomIterableDataset` described below.
Class description:
An auxiliary class for iterating through a dataset.
Method signatures and docstrings:
- def __init__(self, transform_filename_to_tensor: Callable, path: str) -> None: Args: transform_filename_to_tensor (Callable): Function to read ... | Implement the Python class `CustomIterableDataset` described below.
Class description:
An auxiliary class for iterating through a dataset.
Method signatures and docstrings:
- def __init__(self, transform_filename_to_tensor: Callable, path: str) -> None: Args: transform_filename_to_tensor (Callable): Function to read ... | 945c582cc0b08885c4e2bfecb020abdfac0122f3 | <|skeleton|>
class CustomIterableDataset:
"""An auxiliary class for iterating through a dataset."""
def __init__(self, transform_filename_to_tensor: Callable, path: str) -> None:
"""Args: transform_filename_to_tensor (Callable): Function to read a data file from path and return a tensor from that file.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomIterableDataset:
"""An auxiliary class for iterating through a dataset."""
def __init__(self, transform_filename_to_tensor: Callable, path: str) -> None:
"""Args: transform_filename_to_tensor (Callable): Function to read a data file from path and return a tensor from that file. path (str): ... | the_stack_v2_python_sparse | captum/concept/_utils/data_iterator.py | pytorch/captum | train | 4,230 |
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