blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
091df8021a7aefc4e82ee59844e89e232a859dac | [
"if k <= 1:\n return 0\nprod = 1\nans = left = 0\nfor right, val in enumerate(nums):\n prod *= val\n while prod >= k:\n prod /= nums[left]\n left += 1\n ans += right - left + 1\nreturn ans",
"count = 0\nlast = 0\nfor i in range(len(nums)):\n if nums[i] >= k:\n last = i\n ... | <|body_start_0|>
if k <= 1:
return 0
prod = 1
ans = left = 0
for right, val in enumerate(nums):
prod *= val
while prod >= k:
prod /= nums[left]
left += 1
ans += right - left + 1
return ans
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numSubarrayProductLessThanK(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def numSubarrayProductLessThanK0(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_10k_train_004300 | 1,743 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "numSubarrayProductLessThanK",
"signature": "def numSubarrayProductLessThanK(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "numSubarrayProductLessThanK0",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_003497 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayProductLessThanK(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def numSubarrayProductLessThanK0(self, nums, k): :type nums: List[int] :type k: i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayProductLessThanK(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def numSubarrayProductLessThanK0(self, nums, k): :type nums: List[int] :type k: i... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def numSubarrayProductLessThanK(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def numSubarrayProductLessThanK0(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def numSubarrayProductLessThanK(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
if k <= 1:
return 0
prod = 1
ans = left = 0
for right, val in enumerate(nums):
prod *= val
while prod >= k:
... | the_stack_v2_python_sparse | 剑指 Offer II 009. 乘积小于 K 的子数组.py | yangyuxiang1996/leetcode | train | 0 | |
c0786cd138ea47293d63911108d026d7a16b37c7 | [
"test_graph = class_dependency.JavaClassDependencyGraph()\ntest_graph.add_edge_if_new(self.CLASS_1, self.CLASS_2)\ntest_graph.add_edge_if_new(self.CLASS_1, self.CLASS_3)\ntest_graph.add_edge_if_new(self.CLASS_2, self.CLASS_3)\ntest_graph.get_node_by_key(self.CLASS_1).add_nested_class(self.CLASS_1_NESTED_1)\ntest_gr... | <|body_start_0|>
test_graph = class_dependency.JavaClassDependencyGraph()
test_graph.add_edge_if_new(self.CLASS_1, self.CLASS_2)
test_graph.add_edge_if_new(self.CLASS_1, self.CLASS_3)
test_graph.add_edge_if_new(self.CLASS_2, self.CLASS_3)
test_graph.get_node_by_key(self.CLASS_1).... | Unit tests for various de/serialization functions. | TestSerialization | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSerialization:
"""Unit tests for various de/serialization functions."""
def test_class_serialization(self):
"""Tests JSON serialization of a class dependency graph."""
<|body_0|>
def test_package_serialization(self):
"""Tests JSON serialization of a package d... | stack_v2_sparse_classes_10k_train_004301 | 7,187 | permissive | [
{
"docstring": "Tests JSON serialization of a class dependency graph.",
"name": "test_class_serialization",
"signature": "def test_class_serialization(self)"
},
{
"docstring": "Tests JSON serialization of a package dependency graph.",
"name": "test_package_serialization",
"signature": "d... | 3 | null | Implement the Python class `TestSerialization` described below.
Class description:
Unit tests for various de/serialization functions.
Method signatures and docstrings:
- def test_class_serialization(self): Tests JSON serialization of a class dependency graph.
- def test_package_serialization(self): Tests JSON seriali... | Implement the Python class `TestSerialization` described below.
Class description:
Unit tests for various de/serialization functions.
Method signatures and docstrings:
- def test_class_serialization(self): Tests JSON serialization of a class dependency graph.
- def test_package_serialization(self): Tests JSON seriali... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class TestSerialization:
"""Unit tests for various de/serialization functions."""
def test_class_serialization(self):
"""Tests JSON serialization of a class dependency graph."""
<|body_0|>
def test_package_serialization(self):
"""Tests JSON serialization of a package d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSerialization:
"""Unit tests for various de/serialization functions."""
def test_class_serialization(self):
"""Tests JSON serialization of a class dependency graph."""
test_graph = class_dependency.JavaClassDependencyGraph()
test_graph.add_edge_if_new(self.CLASS_1, self.CLASS_... | the_stack_v2_python_sparse | tools/android/dependency_analysis/serialization_unittest.py | chromium/chromium | train | 17,408 |
f69d4851f1b9bcf927a08eeea912151e6891a696 | [
"self.word_dict = defaultdict(list)\nfor i, w in enumerate(words):\n self.word_dict[w].append(i)",
"mini = sys.maxint\nfor i in self.word_dict[word1]:\n idx = bisect_left(self.word_dict[word2], i)\n for nei in (-1, 0):\n if 0 <= idx + nei < len(self.word_dict[word2]):\n mini = min(mini,... | <|body_start_0|>
self.word_dict = defaultdict(list)
for i, w in enumerate(words):
self.word_dict[w].append(i)
<|end_body_0|>
<|body_start_1|>
mini = sys.maxint
for i in self.word_dict[word1]:
idx = bisect_left(self.word_dict[word2], i)
for nei in (-1,... | WordDistance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: list[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_004302 | 857 | permissive | [
{
"docstring": "initialize your data structure here. :type words: list[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortest(self, word1, word2)"
}
] | 2 | null | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: list[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: list[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int
... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: list[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: list[str]"""
self.word_dict = defaultdict(list)
for i, w in enumerate(words):
self.word_dict[w].append(i)
def shortest(self, word1, word2):
""":type word1: str :type w... | the_stack_v2_python_sparse | 244 Shortest Word Distance II.py | Aminaba123/LeetCode | train | 1 | |
63720050e77782b857fd001ea0985f1da416b840 | [
"self.numIslands = 0\nif not grid:\n return 0\nnumRows = len(grid)\nnumCols = len(grid[0])\n\ndef isValid(grid, row, col):\n return row >= 0 and col >= 0 and (row < numRows) and (col < numCols) and (grid[row][col] == '1')\n\ndef bfs(grid, row, col):\n self.numIslands += 1\n stack = [(row, col)]\n whi... | <|body_start_0|>
self.numIslands = 0
if not grid:
return 0
numRows = len(grid)
numCols = len(grid[0])
def isValid(grid, row, col):
return row >= 0 and col >= 0 and (row < numRows) and (col < numCols) and (grid[row][col] == '1')
def bfs(grid, row,... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int"""
<|body_0|>
def numIslandsDFS(self, grid):
""":type grid: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.numIslands = 0
if n... | stack_v2_sparse_classes_10k_train_004303 | 4,234 | no_license | [
{
"docstring": ":type grid: List[List[str]] :rtype: int",
"name": "numIslands",
"signature": "def numIslands(self, grid)"
},
{
"docstring": ":type grid: List[List[str]] :rtype: int",
"name": "numIslandsDFS",
"signature": "def numIslandsDFS(self, grid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000620 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid): :type grid: List[List[str]] :rtype: int
- def numIslandsDFS(self, grid): :type grid: List[List[str]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid): :type grid: List[List[str]] :rtype: int
- def numIslandsDFS(self, grid): :type grid: List[List[str]] :rtype: int
<|skeleton|>
class Solution:
de... | 28219fbc5e2e96f59e9d2b9d1da18f05187898c8 | <|skeleton|>
class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int"""
<|body_0|>
def numIslandsDFS(self, grid):
""":type grid: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int"""
self.numIslands = 0
if not grid:
return 0
numRows = len(grid)
numCols = len(grid[0])
def isValid(grid, row, col):
return row >= 0 and col >= 0 and (row <... | the_stack_v2_python_sparse | 2018/200-number-of-islands.py | the-potato-man/lc | train | 0 | |
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_10k_train_004304 | 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_003825 | 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_10k | 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 |
77ea59edc75bc37bbb84ebc9e8b4a6a458150b94 | [
"items = []\ncount = read_fmt('I', fp)[0]\nfor _ in range(count):\n key = OSType(fp.read(4))\n kls = TYPES.get(key)\n value = kls.read(fp)\n items.append(value)\nreturn cls(items)",
"written = write_fmt(fp, 'I', len(self))\nfor item in self:\n written += write_bytes(fp, item.ostype.value)\n writ... | <|body_start_0|>
items = []
count = read_fmt('I', fp)[0]
for _ in range(count):
key = OSType(fp.read(4))
kls = TYPES.get(key)
value = kls.read(fp)
items.append(value)
return cls(items)
<|end_body_0|>
<|body_start_1|>
written = writ... | List structure. .. py:attribute:: items | List | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class List:
"""List structure. .. py:attribute:: items"""
def read(cls, fp):
"""Read the element from a file-like object. :param fp: file-like object"""
<|body_0|>
def write(self, fp):
"""Write the element to a file-like object. :param fp: file-like object"""
<... | stack_v2_sparse_classes_10k_train_004305 | 19,890 | permissive | [
{
"docstring": "Read the element from a file-like object. :param fp: file-like object",
"name": "read",
"signature": "def read(cls, fp)"
},
{
"docstring": "Write the element to a file-like object. :param fp: file-like object",
"name": "write",
"signature": "def write(self, fp)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006587 | Implement the Python class `List` described below.
Class description:
List structure. .. py:attribute:: items
Method signatures and docstrings:
- def read(cls, fp): Read the element from a file-like object. :param fp: file-like object
- def write(self, fp): Write the element to a file-like object. :param fp: file-lik... | Implement the Python class `List` described below.
Class description:
List structure. .. py:attribute:: items
Method signatures and docstrings:
- def read(cls, fp): Read the element from a file-like object. :param fp: file-like object
- def write(self, fp): Write the element to a file-like object. :param fp: file-lik... | 0e3ac5b64061c7eb87c6eeacce4b9792d1f479b5 | <|skeleton|>
class List:
"""List structure. .. py:attribute:: items"""
def read(cls, fp):
"""Read the element from a file-like object. :param fp: file-like object"""
<|body_0|>
def write(self, fp):
"""Write the element to a file-like object. :param fp: file-like object"""
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class List:
"""List structure. .. py:attribute:: items"""
def read(cls, fp):
"""Read the element from a file-like object. :param fp: file-like object"""
items = []
count = read_fmt('I', fp)[0]
for _ in range(count):
key = OSType(fp.read(4))
kls = TYPES.ge... | the_stack_v2_python_sparse | psd_tools/psd/descriptor.py | sfneal/psd-tools3 | train | 30 |
e40ff04e83b425bb0e4116a2b3307c82727f2117 | [
"super(TransformerDecoder, self).__init__()\nself._hidden_size = opts.hidden_size\nself._output_size = opts.embedding_dim\nself.layers = nn.ModuleList([TransformerDecoderLayer(opts, size=opts.hidden_size, ff_size=opts.ff_size, num_heads=opts.num_heads, dropout=opts.dropout) for _ in range(opts.num_layers)])\nself.p... | <|body_start_0|>
super(TransformerDecoder, self).__init__()
self._hidden_size = opts.hidden_size
self._output_size = opts.embedding_dim
self.layers = nn.ModuleList([TransformerDecoderLayer(opts, size=opts.hidden_size, ff_size=opts.ff_size, num_heads=opts.num_heads, dropout=opts.dropout) ... | A transformer decoder with N masked layers. Decoder layers are masked so that an attention head cannot see the future. | TransformerDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerDecoder:
"""A transformer decoder with N masked layers. Decoder layers are masked so that an attention head cannot see the future."""
def __init__(self, opts, freeze: bool=False, **kwargs):
"""Initialize a Transformer decoder. :param num_layers: number of Transformer layer... | stack_v2_sparse_classes_10k_train_004306 | 4,320 | no_license | [
{
"docstring": "Initialize a Transformer decoder. :param num_layers: number of Transformer layers :param num_heads: number of heads for each layer :param hidden_size: hidden size :param ff_size: position-wise feed-forward size :param dropout: dropout probability (1-keep) :param emb_dropout: dropout probability ... | 2 | stack_v2_sparse_classes_30k_train_005510 | Implement the Python class `TransformerDecoder` described below.
Class description:
A transformer decoder with N masked layers. Decoder layers are masked so that an attention head cannot see the future.
Method signatures and docstrings:
- def __init__(self, opts, freeze: bool=False, **kwargs): Initialize a Transforme... | Implement the Python class `TransformerDecoder` described below.
Class description:
A transformer decoder with N masked layers. Decoder layers are masked so that an attention head cannot see the future.
Method signatures and docstrings:
- def __init__(self, opts, freeze: bool=False, **kwargs): Initialize a Transforme... | e213665be8d3820fa2fc0aa9afe9949fd2e3d488 | <|skeleton|>
class TransformerDecoder:
"""A transformer decoder with N masked layers. Decoder layers are masked so that an attention head cannot see the future."""
def __init__(self, opts, freeze: bool=False, **kwargs):
"""Initialize a Transformer decoder. :param num_layers: number of Transformer layer... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TransformerDecoder:
"""A transformer decoder with N masked layers. Decoder layers are masked so that an attention head cannot see the future."""
def __init__(self, opts, freeze: bool=False, **kwargs):
"""Initialize a Transformer decoder. :param num_layers: number of Transformer layers :param num_... | the_stack_v2_python_sparse | modules/transformer_decoder.py | zqp111/transformer_ar | train | 1 |
02147fa3790e806bacbb50431c4ae4eb587cdd51 | [
"if hasattr(cls, '_default_tags'):\n tags = cls._default_tags()\nelse:\n tags = deepcopy(_default_tags)\nfor cl in reversed(inspect.getmro(cls)):\n if hasattr(cl, '_more_static_tags'):\n more_tags = cl._more_static_tags()\n tags.update(more_tags)\nreturn tags",
"if hasattr(self, '_default_t... | <|body_start_0|>
if hasattr(cls, '_default_tags'):
tags = cls._default_tags()
else:
tags = deepcopy(_default_tags)
for cl in reversed(inspect.getmro(cls)):
if hasattr(cl, '_more_static_tags'):
more_tags = cl._more_static_tags()
... | TagsMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagsMixin:
def _get_tags(cls):
"""Method that collects all the static tags associated to any inheritting class. The Base class for cuML's estimators already uses this mixin, so most estimators don't need to use this Mixin directly. - Tags usage: In general, inheriting classes can use the... | stack_v2_sparse_classes_10k_train_004307 | 10,726 | permissive | [
{
"docstring": "Method that collects all the static tags associated to any inheritting class. The Base class for cuML's estimators already uses this mixin, so most estimators don't need to use this Mixin directly. - Tags usage: In general, inheriting classes can use the appropriate Mixins defined in this file. ... | 2 | stack_v2_sparse_classes_30k_train_001509 | Implement the Python class `TagsMixin` described below.
Class description:
Implement the TagsMixin class.
Method signatures and docstrings:
- def _get_tags(cls): Method that collects all the static tags associated to any inheritting class. The Base class for cuML's estimators already uses this mixin, so most estimato... | Implement the Python class `TagsMixin` described below.
Class description:
Implement the TagsMixin class.
Method signatures and docstrings:
- def _get_tags(cls): Method that collects all the static tags associated to any inheritting class. The Base class for cuML's estimators already uses this mixin, so most estimato... | 7d86042b8de06bc8acce632230fe5821bd36c17d | <|skeleton|>
class TagsMixin:
def _get_tags(cls):
"""Method that collects all the static tags associated to any inheritting class. The Base class for cuML's estimators already uses this mixin, so most estimators don't need to use this Mixin directly. - Tags usage: In general, inheriting classes can use the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TagsMixin:
def _get_tags(cls):
"""Method that collects all the static tags associated to any inheritting class. The Base class for cuML's estimators already uses this mixin, so most estimators don't need to use this Mixin directly. - Tags usage: In general, inheriting classes can use the appropriate M... | the_stack_v2_python_sparse | python/cuml/internals/mixins.py | rapidsai/cuml | train | 3,615 | |
55dc1ccf0a009ba7c6302577b9e058650eb2c233 | [
"from django.core.exceptions import ObjectDoesNotExist\nresult = super(UserSerializer, self).to_representation(value)\nif result['tenant_admin'] and result['tenant']:\n try:\n row = Tenant.objects.get(pk=result['tenant'])\n except ObjectDoesNotExist:\n logger.warning('Tenant_admin without a tena... | <|body_start_0|>
from django.core.exceptions import ObjectDoesNotExist
result = super(UserSerializer, self).to_representation(value)
if result['tenant_admin'] and result['tenant']:
try:
row = Tenant.objects.get(pk=result['tenant'])
except ObjectDoesNotExis... | Expose a subset of the available User fields, treat some as read-only, and allow tenant_adminds to read/write their Cloud row. This presently handles at most one Goldstone tenant per user, and at most one OpenStack cloud per tenant. | UserSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSerializer:
"""Expose a subset of the available User fields, treat some as read-only, and allow tenant_adminds to read/write their Cloud row. This presently handles at most one Goldstone tenant per user, and at most one OpenStack cloud per tenant."""
def to_representation(self, value):
... | stack_v2_sparse_classes_10k_train_004308 | 5,786 | permissive | [
{
"docstring": "Include Goldstone tenant and cloud information if the user is a tenant_admin.",
"name": "to_representation",
"signature": "def to_representation(self, value)"
},
{
"docstring": "Update the corresponding Cloud row for this User, if she is a tenant_admin AND changed any Cloud field... | 2 | stack_v2_sparse_classes_30k_test_000214 | Implement the Python class `UserSerializer` described below.
Class description:
Expose a subset of the available User fields, treat some as read-only, and allow tenant_adminds to read/write their Cloud row. This presently handles at most one Goldstone tenant per user, and at most one OpenStack cloud per tenant.
Metho... | Implement the Python class `UserSerializer` described below.
Class description:
Expose a subset of the available User fields, treat some as read-only, and allow tenant_adminds to read/write their Cloud row. This presently handles at most one Goldstone tenant per user, and at most one OpenStack cloud per tenant.
Metho... | d7f1f1f1ff926148d2aa541d0bd4758173aa76d5 | <|skeleton|>
class UserSerializer:
"""Expose a subset of the available User fields, treat some as read-only, and allow tenant_adminds to read/write their Cloud row. This presently handles at most one Goldstone tenant per user, and at most one OpenStack cloud per tenant."""
def to_representation(self, value):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserSerializer:
"""Expose a subset of the available User fields, treat some as read-only, and allow tenant_adminds to read/write their Cloud row. This presently handles at most one Goldstone tenant per user, and at most one OpenStack cloud per tenant."""
def to_representation(self, value):
"""Inc... | the_stack_v2_python_sparse | goldstone/user/views.py | leftees/goldstone-server | train | 0 |
7990368a530c83377c1c11cb43a1fa37ff7ad768 | [
"self.debug = False\nself.name = 'featurizer'\nself.epsilon = 1e-08\nself.max_num_inputs = max_num_inputs\nif max_num_features is None:\n self.max_num_bundles = 3 * self.max_num_inputs\n self.max_num_features = self.max_num_inputs + self.max_num_bundles\nelse:\n self.max_num_features = max_num_features\n ... | <|body_start_0|>
self.debug = False
self.name = 'featurizer'
self.epsilon = 1e-08
self.max_num_inputs = max_num_inputs
if max_num_features is None:
self.max_num_bundles = 3 * self.max_num_inputs
self.max_num_features = self.max_num_inputs + self.max_num_bu... | Convert inputs to bundles and learn new bundles. Inputs are transformed into bundles, sets of inputs that tend to co-occur. | Featurizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Featurizer:
"""Convert inputs to bundles and learn new bundles. Inputs are transformed into bundles, sets of inputs that tend to co-occur."""
def __init__(self, max_num_inputs, max_num_features=None):
"""Configure the featurizer. Parameters --------- max_num_inputs : int See Featuriz... | stack_v2_sparse_classes_10k_train_004309 | 8,848 | permissive | [
{
"docstring": "Configure the featurizer. Parameters --------- max_num_inputs : int See Featurizer.max_num_inputs. max_num_features : int See Featurizer.max_num_features.",
"name": "__init__",
"signature": "def __init__(self, max_num_inputs, max_num_features=None)"
},
{
"docstring": "Learn bundl... | 5 | stack_v2_sparse_classes_30k_train_005015 | Implement the Python class `Featurizer` described below.
Class description:
Convert inputs to bundles and learn new bundles. Inputs are transformed into bundles, sets of inputs that tend to co-occur.
Method signatures and docstrings:
- def __init__(self, max_num_inputs, max_num_features=None): Configure the featurize... | Implement the Python class `Featurizer` described below.
Class description:
Convert inputs to bundles and learn new bundles. Inputs are transformed into bundles, sets of inputs that tend to co-occur.
Method signatures and docstrings:
- def __init__(self, max_num_inputs, max_num_features=None): Configure the featurize... | 85ee5f530717518b1b43ba9a310e4f0d70b290a4 | <|skeleton|>
class Featurizer:
"""Convert inputs to bundles and learn new bundles. Inputs are transformed into bundles, sets of inputs that tend to co-occur."""
def __init__(self, max_num_inputs, max_num_features=None):
"""Configure the featurizer. Parameters --------- max_num_inputs : int See Featuriz... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Featurizer:
"""Convert inputs to bundles and learn new bundles. Inputs are transformed into bundles, sets of inputs that tend to co-occur."""
def __init__(self, max_num_inputs, max_num_features=None):
"""Configure the featurizer. Parameters --------- max_num_inputs : int See Featurizer.max_num_in... | the_stack_v2_python_sparse | becca/featurizer.py | microgold/Becca35 | train | 1 |
1a1a1961fd6805a8d208a63e22b447c6fa2da7da | [
"self._sizes = sizes\nself._opts = opts\nself._X = X\nself._Y = Y\nself.w_list = []\nself.b_list = []\ninput_size = X.shape[1]\nfor size in self._sizes + [Y.shape[1]]:\n max_range = 4 * math.sqrt(6.0 / (input_size + size))\n self.w_list.append(np.random.uniform(-max_range, max_range, [input_size, size]).astyp... | <|body_start_0|>
self._sizes = sizes
self._opts = opts
self._X = X
self._Y = Y
self.w_list = []
self.b_list = []
input_size = X.shape[1]
for size in self._sizes + [Y.shape[1]]:
max_range = 4 * math.sqrt(6.0 / (input_size + size))
se... | Docstring for NN. | NN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NN:
"""Docstring for NN."""
def __init__(self, sizes, opts, X, Y):
"""TODO: to be defined1. :sizes: TODO :opts: TODO :X: TODO"""
<|body_0|>
def load_from_dbn(self, dbn):
"""TODO: Docstring for load_from_dbn. :dbn: TODO :returns: TODO"""
<|body_1|>
de... | stack_v2_sparse_classes_10k_train_004310 | 4,462 | permissive | [
{
"docstring": "TODO: to be defined1. :sizes: TODO :opts: TODO :X: TODO",
"name": "__init__",
"signature": "def __init__(self, sizes, opts, X, Y)"
},
{
"docstring": "TODO: Docstring for load_from_dbn. :dbn: TODO :returns: TODO",
"name": "load_from_dbn",
"signature": "def load_from_dbn(se... | 4 | stack_v2_sparse_classes_30k_train_003079 | Implement the Python class `NN` described below.
Class description:
Docstring for NN.
Method signatures and docstrings:
- def __init__(self, sizes, opts, X, Y): TODO: to be defined1. :sizes: TODO :opts: TODO :X: TODO
- def load_from_dbn(self, dbn): TODO: Docstring for load_from_dbn. :dbn: TODO :returns: TODO
- def tr... | Implement the Python class `NN` described below.
Class description:
Docstring for NN.
Method signatures and docstrings:
- def __init__(self, sizes, opts, X, Y): TODO: to be defined1. :sizes: TODO :opts: TODO :X: TODO
- def load_from_dbn(self, dbn): TODO: Docstring for load_from_dbn. :dbn: TODO :returns: TODO
- def tr... | 289f230a609554db32552670c300f992a3fe068f | <|skeleton|>
class NN:
"""Docstring for NN."""
def __init__(self, sizes, opts, X, Y):
"""TODO: to be defined1. :sizes: TODO :opts: TODO :X: TODO"""
<|body_0|>
def load_from_dbn(self, dbn):
"""TODO: Docstring for load_from_dbn. :dbn: TODO :returns: TODO"""
<|body_1|>
de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NN:
"""Docstring for NN."""
def __init__(self, sizes, opts, X, Y):
"""TODO: to be defined1. :sizes: TODO :opts: TODO :X: TODO"""
self._sizes = sizes
self._opts = opts
self._X = X
self._Y = Y
self.w_list = []
self.b_list = []
input_size = X.s... | the_stack_v2_python_sparse | bagging-svm/nn_tf.py | ishidaira233/TX-Credit-Assessement | train | 0 |
c947f0277a106e692da2ec18fa03cc0049c88267 | [
"self.output_filename = output_filename\nself.onet_source = onet_source\nself.hash_function = hash_function\nself.ksa_types = ksa_types or KSA_TYPE_CONFIG.keys()",
"logging.info('Converting ONET %s to pandas', filename)\nwith self.onet_source.ensure_file(filename) as fullpath:\n with open(fullpath) as f:\n ... | <|body_start_0|>
self.output_filename = output_filename
self.onet_source = onet_source
self.hash_function = hash_function
self.ksa_types = ksa_types or KSA_TYPE_CONFIG.keys()
<|end_body_0|>
<|body_start_1|>
logging.info('Converting ONET %s to pandas', filename)
with self... | An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson | OnetSkillListProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnetSkillListProcessor:
"""An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson"""
def __init__(self, onet_source, output_filename, hash_function, ksa_types=None):
"""Args: output_filename: A filename to write the final dataset onet_sourc... | stack_v2_sparse_classes_10k_train_004311 | 4,463 | permissive | [
{
"docstring": "Args: output_filename: A filename to write the final dataset onet_source: An object that is able to fetch ONET files by name hash_function: A function that can hash a given string ksa_types: A list of onet skill types to include. All strings must be keys in KSA_TYPE_CONFIG. Defaults to all keys ... | 3 | stack_v2_sparse_classes_30k_train_001064 | Implement the Python class `OnetSkillListProcessor` described below.
Class description:
An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson
Method signatures and docstrings:
- def __init__(self, onet_source, output_filename, hash_function, ksa_types=None): Args: output_f... | Implement the Python class `OnetSkillListProcessor` described below.
Class description:
An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson
Method signatures and docstrings:
- def __init__(self, onet_source, output_filename, hash_function, ksa_types=None): Args: output_f... | feffead90815ccdecf24bf1a995f79683442b046 | <|skeleton|>
class OnetSkillListProcessor:
"""An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson"""
def __init__(self, onet_source, output_filename, hash_function, ksa_types=None):
"""Args: output_filename: A filename to write the final dataset onet_sourc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OnetSkillListProcessor:
"""An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson"""
def __init__(self, onet_source, output_filename, hash_function, ksa_types=None):
"""Args: output_filename: A filename to write the final dataset onet_source: An object ... | the_stack_v2_python_sparse | skills_ml/datasets/skills/onet_ksat.py | workforce-data-initiative/skills-ml | train | 164 |
cf451ca487aad058e094699c4823c50274f84efb | [
"self._context = context or google.datalab.Context.default()\nself._client = _utils.make_client(self._context)\nself._group_dict = None",
"if self._group_dict is None:\n self._group_dict = collections.OrderedDict(((group.name, group) for group in self._client.list_groups()))\nreturn [group for group in self._g... | <|body_start_0|>
self._context = context or google.datalab.Context.default()
self._client = _utils.make_client(self._context)
self._group_dict = None
<|end_body_0|>
<|body_start_1|>
if self._group_dict is None:
self._group_dict = collections.OrderedDict(((group.name, group) ... | Represents a list of Stackdriver groups for a project. | Groups | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Groups:
"""Represents a list of Stackdriver groups for a project."""
def __init__(self, context=None):
"""Initializes the Groups for a Stackdriver project. Args: context: An optional Context object to use instead of the global default."""
<|body_0|>
def list(self, patter... | stack_v2_sparse_classes_10k_train_004312 | 2,940 | permissive | [
{
"docstring": "Initializes the Groups for a Stackdriver project. Args: context: An optional Context object to use instead of the global default.",
"name": "__init__",
"signature": "def __init__(self, context=None)"
},
{
"docstring": "Returns a list of groups that match the filters. Args: patter... | 3 | stack_v2_sparse_classes_30k_train_000707 | Implement the Python class `Groups` described below.
Class description:
Represents a list of Stackdriver groups for a project.
Method signatures and docstrings:
- def __init__(self, context=None): Initializes the Groups for a Stackdriver project. Args: context: An optional Context object to use instead of the global ... | Implement the Python class `Groups` described below.
Class description:
Represents a list of Stackdriver groups for a project.
Method signatures and docstrings:
- def __init__(self, context=None): Initializes the Groups for a Stackdriver project. Args: context: An optional Context object to use instead of the global ... | 8bf007da3e43096aa3a3dca158fc56b286ba6f5c | <|skeleton|>
class Groups:
"""Represents a list of Stackdriver groups for a project."""
def __init__(self, context=None):
"""Initializes the Groups for a Stackdriver project. Args: context: An optional Context object to use instead of the global default."""
<|body_0|>
def list(self, patter... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Groups:
"""Represents a list of Stackdriver groups for a project."""
def __init__(self, context=None):
"""Initializes the Groups for a Stackdriver project. Args: context: An optional Context object to use instead of the global default."""
self._context = context or google.datalab.Context.... | the_stack_v2_python_sparse | google/datalab/stackdriver/monitoring/_group.py | googledatalab/pydatalab | train | 200 |
270667c8344007bf1c748b61cd25b1bf35adcbe9 | [
"has_class_permission = super(EntryAdmin, self).has_change_permission(request, obj)\nif not has_class_permission:\n return False\nif obj is not None and (not request.user.is_superuser) and (request.user.id != obj.author.id):\n return False\nreturn True",
"if request.user.is_superuser:\n return Entry.obje... | <|body_start_0|>
has_class_permission = super(EntryAdmin, self).has_change_permission(request, obj)
if not has_class_permission:
return False
if obj is not None and (not request.user.is_superuser) and (request.user.id != obj.author.id):
return False
return True
<|... | EntryAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntryAdmin:
def has_change_permission(self, request, obj=None):
"""Called from the individual object editing page, to ensure the user is allowed to edit that object. Returns ``True`` if the user has permission for change the entry, otherwise returns ``False``."""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_004313 | 2,721 | no_license | [
{
"docstring": "Called from the individual object editing page, to ensure the user is allowed to edit that object. Returns ``True`` if the user has permission for change the entry, otherwise returns ``False``.",
"name": "has_change_permission",
"signature": "def has_change_permission(self, request, obj=... | 3 | stack_v2_sparse_classes_30k_train_005884 | Implement the Python class `EntryAdmin` described below.
Class description:
Implement the EntryAdmin class.
Method signatures and docstrings:
- def has_change_permission(self, request, obj=None): Called from the individual object editing page, to ensure the user is allowed to edit that object. Returns ``True`` if the... | Implement the Python class `EntryAdmin` described below.
Class description:
Implement the EntryAdmin class.
Method signatures and docstrings:
- def has_change_permission(self, request, obj=None): Called from the individual object editing page, to ensure the user is allowed to edit that object. Returns ``True`` if the... | a835b4e2de6e961e46ec68d3edda98530cbcf4c6 | <|skeleton|>
class EntryAdmin:
def has_change_permission(self, request, obj=None):
"""Called from the individual object editing page, to ensure the user is allowed to edit that object. Returns ``True`` if the user has permission for change the entry, otherwise returns ``False``."""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EntryAdmin:
def has_change_permission(self, request, obj=None):
"""Called from the individual object editing page, to ensure the user is allowed to edit that object. Returns ``True`` if the user has permission for change the entry, otherwise returns ``False``."""
has_class_permission = super(E... | the_stack_v2_python_sparse | diario/admin.py | sahwar/souschef | train | 0 | |
93fd211999fd389e3097dc54c6ea30cc368477e3 | [
"cell = csv_readline(line)\nif cell[0] == 'V':\n yield (cell[4], 1)",
"total = 0\ntotal = sum((i for i in visit_counts))\nyield (customer, total)"
] | <|body_start_0|>
cell = csv_readline(line)
if cell[0] == 'V':
yield (cell[4], 1)
<|end_body_0|>
<|body_start_1|>
total = 0
total = sum((i for i in visit_counts))
yield (customer, total)
<|end_body_1|>
| CustomerVisit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerVisit:
def mapper(self, line_no, line):
"""Extracts the Customer that visit a page"""
<|body_0|>
def reducer(self, customer, visit_counts):
"""Sumarizes the visit counts by adding them together."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_004314 | 1,020 | no_license | [
{
"docstring": "Extracts the Customer that visit a page",
"name": "mapper",
"signature": "def mapper(self, line_no, line)"
},
{
"docstring": "Sumarizes the visit counts by adding them together.",
"name": "reducer",
"signature": "def reducer(self, customer, visit_counts)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000997 | Implement the Python class `CustomerVisit` described below.
Class description:
Implement the CustomerVisit class.
Method signatures and docstrings:
- def mapper(self, line_no, line): Extracts the Customer that visit a page
- def reducer(self, customer, visit_counts): Sumarizes the visit counts by adding them together... | Implement the Python class `CustomerVisit` described below.
Class description:
Implement the CustomerVisit class.
Method signatures and docstrings:
- def mapper(self, line_no, line): Extracts the Customer that visit a page
- def reducer(self, customer, visit_counts): Sumarizes the visit counts by adding them together... | dc1b55b1ca0b989ff65df04fc96df2afc102ee0d | <|skeleton|>
class CustomerVisit:
def mapper(self, line_no, line):
"""Extracts the Customer that visit a page"""
<|body_0|>
def reducer(self, customer, visit_counts):
"""Sumarizes the visit counts by adding them together."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CustomerVisit:
def mapper(self, line_no, line):
"""Extracts the Customer that visit a page"""
cell = csv_readline(line)
if cell[0] == 'V':
yield (cell[4], 1)
def reducer(self, customer, visit_counts):
"""Sumarizes the visit counts by adding them together."""
... | the_stack_v2_python_sparse | week4/visits_per_customer_solution.py | hchandaria/UCB_MIDS_W261 | train | 0 | |
00daafeb4e8f16d5acde7ff5459533b177935bea | [
"res = []\nstack = []\nwhile root or stack:\n while root:\n stack.append(root)\n root = root.left\n root = stack.pop()\n res.append(root.val)\n root = root.right\nreturn res",
"def getSuccessor(root: TreeNode) -> TreeNode:\n succ = root.left\n while succ.right and succ.right != roo... | <|body_start_0|>
res = []
stack = []
while root or stack:
while root:
stack.append(root)
root = root.left
root = stack.pop()
res.append(root.val)
root = root.right
return res
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]:
"""Iterating method using Stack Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def inorderTraversal_MK2(self, root: Optional[TreeNode]) -> List[int]:
"""Morris Traversal Time... | stack_v2_sparse_classes_10k_train_004315 | 1,513 | no_license | [
{
"docstring": "Iterating method using Stack Time complexity: O(n) Space complexity: O(n)",
"name": "inorderTraversal_MK1",
"signature": "def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]"
},
{
"docstring": "Morris Traversal Time complexity: O(n) Space complexity: O(1)",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]: Iterating method using Stack Time complexity: O(n) Space complexity: O(n)
- def inorderTraversal_MK2(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]: Iterating method using Stack Time complexity: O(n) Space complexity: O(n)
- def inorderTraversal_MK2(self, ... | d7ba416d22becfa8f2a2ae4eee04c86617cd9332 | <|skeleton|>
class Solution:
def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]:
"""Iterating method using Stack Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def inorderTraversal_MK2(self, root: Optional[TreeNode]) -> List[int]:
"""Morris Traversal Time... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def inorderTraversal_MK1(self, root: Optional[TreeNode]) -> List[int]:
"""Iterating method using Stack Time complexity: O(n) Space complexity: O(n)"""
res = []
stack = []
while root or stack:
while root:
stack.append(root)
r... | the_stack_v2_python_sparse | 0094. Binary Tree Inorder Traversal/Solution.py | faterazer/LeetCode | train | 4 | |
19d9f9b11a6aed5c2e6d70303378a9655551e521 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Interface exported by the server. | TrainingCoordinatorServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainingCoordinatorServicer:
"""Interface exported by the server."""
def Train(self, request, context):
"""Train a model"""
<|body_0|>
def GetStatus(self, request, context):
"""Get status of training job"""
<|body_1|>
def GetEvaluations(self, request... | stack_v2_sparse_classes_10k_train_004316 | 10,496 | no_license | [
{
"docstring": "Train a model",
"name": "Train",
"signature": "def Train(self, request, context)"
},
{
"docstring": "Get status of training job",
"name": "GetStatus",
"signature": "def GetStatus(self, request, context)"
},
{
"docstring": "Get evaluation metrics for the training j... | 6 | stack_v2_sparse_classes_30k_val_000037 | Implement the Python class `TrainingCoordinatorServicer` described below.
Class description:
Interface exported by the server.
Method signatures and docstrings:
- def Train(self, request, context): Train a model
- def GetStatus(self, request, context): Get status of training job
- def GetEvaluations(self, request, co... | Implement the Python class `TrainingCoordinatorServicer` described below.
Class description:
Interface exported by the server.
Method signatures and docstrings:
- def Train(self, request, context): Train a model
- def GetStatus(self, request, context): Get status of training job
- def GetEvaluations(self, request, co... | 49dc92036e71ca758cc35e8851a803b89d76ef52 | <|skeleton|>
class TrainingCoordinatorServicer:
"""Interface exported by the server."""
def Train(self, request, context):
"""Train a model"""
<|body_0|>
def GetStatus(self, request, context):
"""Get status of training job"""
<|body_1|>
def GetEvaluations(self, request... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TrainingCoordinatorServicer:
"""Interface exported by the server."""
def Train(self, request, context):
"""Train a model"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
... | the_stack_v2_python_sparse | proto/trainer/trainer_pb2_grpc.py | selwynClarifai/video-manager | train | 2 |
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_10k_train_004317 | 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 | null | 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_10k | 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 | |
ece7029545ec3110ba2e0536cf1fb5f2897efe67 | [
"file_dir = os.path.dirname(__file__)\nfilename = 'data_items.csv'\nabsolute_file_path = os.path.join(file_dir, filename)\nwith open(absolute_file_path, 'r') as csv_file:\n csv_reader = csv.reader(csv_file)\n inventory = []\n for row in csv_reader:\n inventory.append({'name': row[0], 'sell_in': int(... | <|body_start_0|>
file_dir = os.path.dirname(__file__)
filename = 'data_items.csv'
absolute_file_path = os.path.join(file_dir, filename)
with open(absolute_file_path, 'r') as csv_file:
csv_reader = csv.reader(csv_file)
inventory = []
for row in csv_read... | Factory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Factory:
def loadInventory():
"""Let us get the data of some Items from "data_items.csv" file which contains some basic items to insert them into database in other functions Returns: (list): Returns a List where each element it's a Dictionary which contains the item"""
<|body_0|>... | stack_v2_sparse_classes_10k_train_004318 | 2,875 | permissive | [
{
"docstring": "Let us get the data of some Items from \"data_items.csv\" file which contains some basic items to insert them into database in other functions Returns: (list): Returns a List where each element it's a Dictionary which contains the item",
"name": "loadInventory",
"signature": "def loadInv... | 2 | stack_v2_sparse_classes_30k_train_006541 | Implement the Python class `Factory` described below.
Class description:
Implement the Factory class.
Method signatures and docstrings:
- def loadInventory(): Let us get the data of some Items from "data_items.csv" file which contains some basic items to insert them into database in other functions Returns: (list): R... | Implement the Python class `Factory` described below.
Class description:
Implement the Factory class.
Method signatures and docstrings:
- def loadInventory(): Let us get the data of some Items from "data_items.csv" file which contains some basic items to insert them into database in other functions Returns: (list): R... | 0f9f2589b567c57bd56a8a4161de3043d5639a8b | <|skeleton|>
class Factory:
def loadInventory():
"""Let us get the data of some Items from "data_items.csv" file which contains some basic items to insert them into database in other functions Returns: (list): Returns a List where each element it's a Dictionary which contains the item"""
<|body_0|>... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Factory:
def loadInventory():
"""Let us get the data of some Items from "data_items.csv" file which contains some basic items to insert them into database in other functions Returns: (list): Returns a List where each element it's a Dictionary which contains the item"""
file_dir = os.path.dirna... | the_stack_v2_python_sparse | repository/repository_sql/repo.py | cifpfbmoll/ollivanders-in-a-docker-pau13-loop | train | 0 | |
58d3221be982627f8f28b3f01ecd59f961cf2b64 | [
"i = 0\nwhile i != row:\n if borad[i][col] == 'Q':\n return False\n i += 1\ni, j = (row - 1, col - 1)\nwhile i >= 0 and j >= 0:\n if borad[i][j] == 'Q':\n return False\n i -= 1\n j -= 1\ni, j = (row - 1, col + 1)\nwhile i >= 0 and j < n:\n if borad[i][j] == 'Q':\n return False... | <|body_start_0|>
i = 0
while i != row:
if borad[i][col] == 'Q':
return False
i += 1
i, j = (row - 1, col - 1)
while i >= 0 and j >= 0:
if borad[i][j] == 'Q':
return False
i -= 1
j -= 1
i, ... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkvalid(self, borad, row, col, n):
"""set board[row][col]=='Q' check whether it's valid result"""
<|body_0|>
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i = 0
... | stack_v2_sparse_classes_10k_train_004319 | 1,288 | permissive | [
{
"docstring": "set board[row][col]=='Q' check whether it's valid result",
"name": "checkvalid",
"signature": "def checkvalid(self, borad, row, col, n)"
},
{
"docstring": ":type n: int :rtype: List[List[str]]",
"name": "solveNQueens",
"signature": "def solveNQueens(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000278 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkvalid(self, borad, row, col, n): set board[row][col]=='Q' check whether it's valid result
- def solveNQueens(self, n): :type n: int :rtype: List[List[str]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkvalid(self, borad, row, col, n): set board[row][col]=='Q' check whether it's valid result
- def solveNQueens(self, n): :type n: int :rtype: List[List[str]]
<|skeleton|>... | 86f1cb98de801f58c39d9a48ce9de12df7303d20 | <|skeleton|>
class Solution:
def checkvalid(self, borad, row, col, n):
"""set board[row][col]=='Q' check whether it's valid result"""
<|body_0|>
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def checkvalid(self, borad, row, col, n):
"""set board[row][col]=='Q' check whether it's valid result"""
i = 0
while i != row:
if borad[i][col] == 'Q':
return False
i += 1
i, j = (row - 1, col - 1)
while i >= 0 and j >= ... | the_stack_v2_python_sparse | 51-N-Queens/solution.py | Tanych/CodeTracking | train | 0 | |
b7c9d0a622882f42d91684702fba4df6979b3b9e | [
"security_group = self.os_conn.create_sec_group_for_ssh()\nself.instance_keypair = self.os_conn.create_key(key_name='instancekey')\nself.os_conn.nova.security_group_rules.create(security_group.id, ip_protocol='tcp', from_port=1, to_port=65535, cidr='0.0.0.0/0')\nnet, subnet = self.create_internal_network_with_subne... | <|body_start_0|>
security_group = self.os_conn.create_sec_group_for_ssh()
self.instance_keypair = self.os_conn.create_key(key_name='instancekey')
self.os_conn.nova.security_group_rules.create(security_group.id, ip_protocol='tcp', from_port=1, to_port=65535, cidr='0.0.0.0/0')
net, subnet ... | Check association and disassociation floating ip | TestFloatingIP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFloatingIP:
"""Check association and disassociation floating ip"""
def prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Create network net01, subnet net01__subnet with CIDR 10.1.1.0/24 2. Create new security group sec_group1 3. Add Ingress rule for TCP pr... | stack_v2_sparse_classes_10k_train_004320 | 5,007 | no_license | [
{
"docstring": "Prepare OpenStack for scenarios run Steps: 1. Create network net01, subnet net01__subnet with CIDR 10.1.1.0/24 2. Create new security group sec_group1 3. Add Ingress rule for TCP protocol to sec_group1 4. Boot vm1 net01 with sec_group1",
"name": "prepare_openstack",
"signature": "def pre... | 2 | stack_v2_sparse_classes_30k_train_001581 | Implement the Python class `TestFloatingIP` described below.
Class description:
Check association and disassociation floating ip
Method signatures and docstrings:
- def prepare_openstack(self): Prepare OpenStack for scenarios run Steps: 1. Create network net01, subnet net01__subnet with CIDR 10.1.1.0/24 2. Create new... | Implement the Python class `TestFloatingIP` described below.
Class description:
Check association and disassociation floating ip
Method signatures and docstrings:
- def prepare_openstack(self): Prepare OpenStack for scenarios run Steps: 1. Create network net01, subnet net01__subnet with CIDR 10.1.1.0/24 2. Create new... | 8aced2855b78b5f123195d188c80e27b43888a2e | <|skeleton|>
class TestFloatingIP:
"""Check association and disassociation floating ip"""
def prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Create network net01, subnet net01__subnet with CIDR 10.1.1.0/24 2. Create new security group sec_group1 3. Add Ingress rule for TCP pr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestFloatingIP:
"""Check association and disassociation floating ip"""
def prepare_openstack(self):
"""Prepare OpenStack for scenarios run Steps: 1. Create network net01, subnet net01__subnet with CIDR 10.1.1.0/24 2. Create new security group sec_group1 3. Add Ingress rule for TCP protocol to sec... | the_stack_v2_python_sparse | mos_tests/neutron/python_tests/test_floating_ip.py | Mirantis/mos-integration-tests | train | 16 |
46e9bccabda90b55a81ca1b8dae84645425c2c53 | [
"self.entry = entry\nself.id = entry.id\nself.title = entry.title\nself.date = entry.date\nself.time_spent = entry.time_spent\nself.learned = entry.learned\n_resources = self.entry.get_resources()\n_tags = self.entry.get_tags()\nself.resources = [(resource.id, resource.title) for resource in list(_resources)]\nself... | <|body_start_0|>
self.entry = entry
self.id = entry.id
self.title = entry.title
self.date = entry.date
self.time_spent = entry.time_spent
self.learned = entry.learned
_resources = self.entry.get_resources()
_tags = self.entry.get_tags()
self.resour... | helper class that is not stored in the database it is used to update an entry along with its tags and resources | EntryWithResourcesandTags | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntryWithResourcesandTags:
"""helper class that is not stored in the database it is used to update an entry along with its tags and resources"""
def __init__(self, entry):
"""the combined record is initilized in the way it exists before the update"""
<|body_0|>
def updat... | stack_v2_sparse_classes_10k_train_004321 | 10,083 | no_license | [
{
"docstring": "the combined record is initilized in the way it exists before the update",
"name": "__init__",
"signature": "def __init__(self, entry)"
},
{
"docstring": "the update is performed",
"name": "update",
"signature": "def update(self, form)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006531 | Implement the Python class `EntryWithResourcesandTags` described below.
Class description:
helper class that is not stored in the database it is used to update an entry along with its tags and resources
Method signatures and docstrings:
- def __init__(self, entry): the combined record is initilized in the way it exis... | Implement the Python class `EntryWithResourcesandTags` described below.
Class description:
helper class that is not stored in the database it is used to update an entry along with its tags and resources
Method signatures and docstrings:
- def __init__(self, entry): the combined record is initilized in the way it exis... | 8bfbba09132b405f7c68cbfd9a0e7596223c3a53 | <|skeleton|>
class EntryWithResourcesandTags:
"""helper class that is not stored in the database it is used to update an entry along with its tags and resources"""
def __init__(self, entry):
"""the combined record is initilized in the way it exists before the update"""
<|body_0|>
def updat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EntryWithResourcesandTags:
"""helper class that is not stored in the database it is used to update an entry along with its tags and resources"""
def __init__(self, entry):
"""the combined record is initilized in the way it exists before the update"""
self.entry = entry
self.id = e... | the_stack_v2_python_sparse | project05_flask_learningjournal/learning_journal/models.py | sabinem/treehouse-python-techdegree | train | 3 |
2f822b306f083dd100852e90bd0ce7b8022ac1b5 | [
"if '_read' not in data and '_seen' not in data:\n raise ValidationError('Please provide at least one field to update. Valid fields to update are: read, seen')\nreturn data",
"unwanted_fields = ['resource_type']\nfor field in unwanted_fields:\n if field in data:\n data.pop(field)\nreturn data"
] | <|body_start_0|>
if '_read' not in data and '_seen' not in data:
raise ValidationError('Please provide at least one field to update. Valid fields to update are: read, seen')
return data
<|end_body_0|>
<|body_start_1|>
unwanted_fields = ['resource_type']
for field in unwanted... | Class to serialize and deserialize notification models. | NotificationSchema | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationSchema:
"""Class to serialize and deserialize notification models."""
def validate_read_and_seen(self, data, **kwargs):
"""Raise a ValidationError if both read and seen aren't present in the data on load."""
<|body_0|>
def strip_unwanted_fields(self, data, ma... | stack_v2_sparse_classes_10k_train_004322 | 1,963 | no_license | [
{
"docstring": "Raise a ValidationError if both read and seen aren't present in the data on load.",
"name": "validate_read_and_seen",
"signature": "def validate_read_and_seen(self, data, **kwargs)"
},
{
"docstring": "Remove unwanted fields from the input data before deserialization.",
"name"... | 2 | stack_v2_sparse_classes_30k_val_000281 | Implement the Python class `NotificationSchema` described below.
Class description:
Class to serialize and deserialize notification models.
Method signatures and docstrings:
- def validate_read_and_seen(self, data, **kwargs): Raise a ValidationError if both read and seen aren't present in the data on load.
- def stri... | Implement the Python class `NotificationSchema` described below.
Class description:
Class to serialize and deserialize notification models.
Method signatures and docstrings:
- def validate_read_and_seen(self, data, **kwargs): Raise a ValidationError if both read and seen aren't present in the data on load.
- def stri... | 55ce20945bea8a6348bea64726aaf209936723c2 | <|skeleton|>
class NotificationSchema:
"""Class to serialize and deserialize notification models."""
def validate_read_and_seen(self, data, **kwargs):
"""Raise a ValidationError if both read and seen aren't present in the data on load."""
<|body_0|>
def strip_unwanted_fields(self, data, ma... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NotificationSchema:
"""Class to serialize and deserialize notification models."""
def validate_read_and_seen(self, data, **kwargs):
"""Raise a ValidationError if both read and seen aren't present in the data on load."""
if '_read' not in data and '_seen' not in data:
raise Val... | the_stack_v2_python_sparse | api/app/schemas/notification.py | EricMontague/Flask-Chat-Server | train | 0 |
a4a17d12b3aa4a8266b98c4e28f4cbf48e0014d5 | [
"self.format = format\nself.trigmode = tmod\nself.atwa = [None] * 4\nself.atwb = [None] * 4\nself.atwd = [None] * 8\nself.fadc = []\nif format & 1:\n self.atwa[0] = self.atwd[0] = struct.unpack('128h', zbuf.read(256))\nif format & 2:\n self.atwa[1] = self.atwd[1] = struct.unpack('128h', zbuf.read(256))\nif fo... | <|body_start_0|>
self.format = format
self.trigmode = tmod
self.atwa = [None] * 4
self.atwb = [None] * 4
self.atwd = [None] * 8
self.fadc = []
if format & 1:
self.atwa[0] = self.atwd[0] = struct.unpack('128h', zbuf.read(256))
if format & 2:
... | Waveform hit class. This class contains data members that hold information about a 'hit' or waveform capture in the ATWD and/or FADC. There are also slots for the DOM clock information. - hit.atwa[i][j] : holds j-th sample of ATWD-A channel i - hit.atwb[i][j] : ibid. but for ATWD-B - hit.fadc[j] : only one FADC - hit.c... | hit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class hit:
"""Waveform hit class. This class contains data members that hold information about a 'hit' or waveform capture in the ATWD and/or FADC. There are also slots for the DOM clock information. - hit.atwa[i][j] : holds j-th sample of ATWD-A channel i - hit.atwb[i][j] : ibid. but for ATWD-B - hit.... | stack_v2_sparse_classes_10k_train_004323 | 21,290 | no_license | [
{
"docstring": "Unpack from acqX memory dump",
"name": "__init__",
"signature": "def __init__(self, zbuf, format, tmod)"
},
{
"docstring": "Write self out as engineering event",
"name": "toeng",
"signature": "def toeng(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006186 | Implement the Python class `hit` described below.
Class description:
Waveform hit class. This class contains data members that hold information about a 'hit' or waveform capture in the ATWD and/or FADC. There are also slots for the DOM clock information. - hit.atwa[i][j] : holds j-th sample of ATWD-A channel i - hit.a... | Implement the Python class `hit` described below.
Class description:
Waveform hit class. This class contains data members that hold information about a 'hit' or waveform capture in the ATWD and/or FADC. There are also slots for the DOM clock information. - hit.atwa[i][j] : holds j-th sample of ATWD-A channel i - hit.a... | 13cb63ba2390bbd49facb2d9093da528ae52cd91 | <|skeleton|>
class hit:
"""Waveform hit class. This class contains data members that hold information about a 'hit' or waveform capture in the ATWD and/or FADC. There are also slots for the DOM clock information. - hit.atwa[i][j] : holds j-th sample of ATWD-A channel i - hit.atwb[i][j] : ibid. but for ATWD-B - hit.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class hit:
"""Waveform hit class. This class contains data members that hold information about a 'hit' or waveform capture in the ATWD and/or FADC. There are also slots for the DOM clock information. - hit.atwa[i][j] : holds j-th sample of ATWD-A channel i - hit.atwb[i][j] : ibid. but for ATWD-B - hit.fadc[j] : onl... | the_stack_v2_python_sparse | icecube/domtest/ibidaq.py | dglo/PyDOM | train | 0 |
f9d3c7f1e9ffe1e3c38cee5eeafd17c93abe2304 | [
"self.alphabet = alphabet\nself.initial_population = 500\nself.min_generations = 10\nself._set_up_genetic_algorithm()",
"self.motif_generator = RandomMotifGenerator(self.alphabet)\nself.mutator = SinglePositionMutation(mutation_rate=0.1)\nself.crossover = SinglePointCrossover(crossover_prob=0.25)\nself.repair = A... | <|body_start_0|>
self.alphabet = alphabet
self.initial_population = 500
self.min_generations = 10
self._set_up_genetic_algorithm()
<|end_body_0|>
<|body_start_1|>
self.motif_generator = RandomMotifGenerator(self.alphabet)
self.mutator = SinglePositionMutation(mutation_ra... | Find schemas using a genetic algorithm approach. This approach to finding schema uses Genetic Algorithms to evolve a set of schema and find the best schema for a specific set of records. The 'default' finder searches for ambiguous DNA elements. This can be overridden easily by creating a GeneticAlgorithmFinder with a d... | GeneticAlgorithmFinder | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneticAlgorithmFinder:
"""Find schemas using a genetic algorithm approach. This approach to finding schema uses Genetic Algorithms to evolve a set of schema and find the best schema for a specific set of records. The 'default' finder searches for ambiguous DNA elements. This can be overridden ea... | stack_v2_sparse_classes_10k_train_004324 | 26,199 | permissive | [
{
"docstring": "Initialize a finder to get schemas using Genetic Algorithms. Arguments: o alphabet -- The alphabet which specifies the contents of the schemas we'll be generating. This alphabet must contain the attribute 'alphabet_matches', which is a dictionary specifying the potential ambiguities of each lett... | 3 | stack_v2_sparse_classes_30k_train_004779 | Implement the Python class `GeneticAlgorithmFinder` described below.
Class description:
Find schemas using a genetic algorithm approach. This approach to finding schema uses Genetic Algorithms to evolve a set of schema and find the best schema for a specific set of records. The 'default' finder searches for ambiguous ... | Implement the Python class `GeneticAlgorithmFinder` described below.
Class description:
Find schemas using a genetic algorithm approach. This approach to finding schema uses Genetic Algorithms to evolve a set of schema and find the best schema for a specific set of records. The 'default' finder searches for ambiguous ... | 1d9a8e84a8572809ee3260ede44290e14de3bdd1 | <|skeleton|>
class GeneticAlgorithmFinder:
"""Find schemas using a genetic algorithm approach. This approach to finding schema uses Genetic Algorithms to evolve a set of schema and find the best schema for a specific set of records. The 'default' finder searches for ambiguous DNA elements. This can be overridden ea... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeneticAlgorithmFinder:
"""Find schemas using a genetic algorithm approach. This approach to finding schema uses Genetic Algorithms to evolve a set of schema and find the best schema for a specific set of records. The 'default' finder searches for ambiguous DNA elements. This can be overridden easily by creat... | the_stack_v2_python_sparse | bin/last_wrapper/Bio/NeuralNetwork/Gene/Schema.py | LyonsLab/coge | train | 41 |
96a19ae28090fb7340b0bbe18b3a13d0bb1c170d | [
"user = request.user\ncheck_user_status(user)\nuser_id = user.id\nrestaurant_owner = RestaurantOwner.get_by_user_id(user_id=user_id)\nreturn JsonResponse(model_to_json(restaurant_owner))",
"user = request.user\ncheck_user_status(user)\nuser_id = user.id\nvalidate(instance=request.data, schema=schemas.restaurant_o... | <|body_start_0|>
user = request.user
check_user_status(user)
user_id = user.id
restaurant_owner = RestaurantOwner.get_by_user_id(user_id=user_id)
return JsonResponse(model_to_json(restaurant_owner))
<|end_body_0|>
<|body_start_1|>
user = request.user
check_user_s... | Restaurant Owner view | RestaurantOwnerView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestaurantOwnerView:
"""Restaurant Owner view"""
def get(self, request):
"""Retrieves a restaurant owner profile"""
<|body_0|>
def put(self, request):
"""Updates a restaurant owner profile"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = r... | stack_v2_sparse_classes_10k_train_004325 | 3,080 | no_license | [
{
"docstring": "Retrieves a restaurant owner profile",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Updates a restaurant owner profile",
"name": "put",
"signature": "def put(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000368 | Implement the Python class `RestaurantOwnerView` described below.
Class description:
Restaurant Owner view
Method signatures and docstrings:
- def get(self, request): Retrieves a restaurant owner profile
- def put(self, request): Updates a restaurant owner profile | Implement the Python class `RestaurantOwnerView` described below.
Class description:
Restaurant Owner view
Method signatures and docstrings:
- def get(self, request): Retrieves a restaurant owner profile
- def put(self, request): Updates a restaurant owner profile
<|skeleton|>
class RestaurantOwnerView:
"""Resta... | 2707062c9a9a8bb4baca955e8a60ba08cc9f8953 | <|skeleton|>
class RestaurantOwnerView:
"""Restaurant Owner view"""
def get(self, request):
"""Retrieves a restaurant owner profile"""
<|body_0|>
def put(self, request):
"""Updates a restaurant owner profile"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RestaurantOwnerView:
"""Restaurant Owner view"""
def get(self, request):
"""Retrieves a restaurant owner profile"""
user = request.user
check_user_status(user)
user_id = user.id
restaurant_owner = RestaurantOwner.get_by_user_id(user_id=user_id)
return JsonR... | the_stack_v2_python_sparse | backend/restaurant_owner/views.py | MochiTarts/Find-Dining-The-Bridge | train | 1 |
ed18dc549cac4a8f59c8cd89083adb4c5b6b1866 | [
"login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'\nheaders = {'Content-Type': 'application/json;charset=UTF-8', 'Authorization': GetToken().token()}\nresponse_data = requests.get(login_url, headers=headers).json()\nself.assertEqual(response_data['message'], 'SUCCESS')",
"login_url = 'http://... | <|body_start_0|>
login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'
headers = {'Content-Type': 'application/json;charset=UTF-8', 'Authorization': GetToken().token()}
response_data = requests.get(login_url, headers=headers).json()
self.assertEqual(response_data['messag... | TestGongDan | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGongDan:
def test1_gongzt(self):
"""工作台，工单统计接口，正常登录后请求"""
<|body_0|>
def test2_gongzt_notoken(self):
"""工作台，工单统计接口，不登录直接请求"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'
... | stack_v2_sparse_classes_10k_train_004326 | 1,541 | no_license | [
{
"docstring": "工作台，工单统计接口，正常登录后请求",
"name": "test1_gongzt",
"signature": "def test1_gongzt(self)"
},
{
"docstring": "工作台，工单统计接口，不登录直接请求",
"name": "test2_gongzt_notoken",
"signature": "def test2_gongzt_notoken(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005685 | Implement the Python class `TestGongDan` described below.
Class description:
Implement the TestGongDan class.
Method signatures and docstrings:
- def test1_gongzt(self): 工作台，工单统计接口，正常登录后请求
- def test2_gongzt_notoken(self): 工作台，工单统计接口，不登录直接请求 | Implement the Python class `TestGongDan` described below.
Class description:
Implement the TestGongDan class.
Method signatures and docstrings:
- def test1_gongzt(self): 工作台，工单统计接口，正常登录后请求
- def test2_gongzt_notoken(self): 工作台，工单统计接口，不登录直接请求
<|skeleton|>
class TestGongDan:
def test1_gongzt(self):
"""工作台... | 204856bd33c06d25f2970eba13799db75d4fd4fe | <|skeleton|>
class TestGongDan:
def test1_gongzt(self):
"""工作台，工单统计接口，正常登录后请求"""
<|body_0|>
def test2_gongzt_notoken(self):
"""工作台，工单统计接口，不登录直接请求"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestGongDan:
def test1_gongzt(self):
"""工作台，工单统计接口，正常登录后请求"""
login_url = 'http://uat-c2b.taoche.com/basegate/work/order/statistics'
headers = {'Content-Type': 'application/json;charset=UTF-8', 'Authorization': GetToken().token()}
response_data = requests.get(login_url, headers... | the_stack_v2_python_sparse | mc/xmdCW/testcase/test_gongzuotai.py | boeai/mc | train | 0 | |
865522c4fbc8a9b0cc486b75c0b8347c18ea0a34 | [
"self.base_url = 'http://weatherstation.wunderground.com/' + 'weatherstation/updateweatherstation.php'\nself.url_items = {}\nself.valid_keys = ('action', 'ID', 'PASSWORD', 'dateutc', 'winddir', 'windspeedmph', 'windgustmph', 'windgustdir', 'windspdmph_avg2m', 'winddir_avg2m', 'windgustmph_10m', 'windgustdir_10m', '... | <|body_start_0|>
self.base_url = 'http://weatherstation.wunderground.com/' + 'weatherstation/updateweatherstation.php'
self.url_items = {}
self.valid_keys = ('action', 'ID', 'PASSWORD', 'dateutc', 'winddir', 'windspeedmph', 'windgustmph', 'windgustdir', 'windspdmph_avg2m', 'winddir_avg2m', 'wind... | this class represents a weather under ground upload url | WUURL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WUURL:
"""this class represents a weather under ground upload url"""
def __init__(self):
"""initialize a url"""
<|body_0|>
def __str__(self):
"""converst url to string"""
<|body_1|>
def add_item(self, key, value):
"""adds an item to url argum... | stack_v2_sparse_classes_10k_train_004327 | 7,715 | no_license | [
{
"docstring": "initialize a url",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "converst url to string",
"name": "__str__",
"signature": "def __str__(self)"
},
{
"docstring": "adds an item to url arguments: key: (string) value: (string)",
"name": "... | 4 | stack_v2_sparse_classes_30k_train_004964 | Implement the Python class `WUURL` described below.
Class description:
this class represents a weather under ground upload url
Method signatures and docstrings:
- def __init__(self): initialize a url
- def __str__(self): converst url to string
- def add_item(self, key, value): adds an item to url arguments: key: (str... | Implement the Python class `WUURL` described below.
Class description:
this class represents a weather under ground upload url
Method signatures and docstrings:
- def __init__(self): initialize a url
- def __str__(self): converst url to string
- def add_item(self, key, value): adds an item to url arguments: key: (str... | 95d0c102d649c5b028d262f5254106f997a7c77a | <|skeleton|>
class WUURL:
"""this class represents a weather under ground upload url"""
def __init__(self):
"""initialize a url"""
<|body_0|>
def __str__(self):
"""converst url to string"""
<|body_1|>
def add_item(self, key, value):
"""adds an item to url argum... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WUURL:
"""this class represents a weather under ground upload url"""
def __init__(self):
"""initialize a url"""
self.base_url = 'http://weatherstation.wunderground.com/' + 'weatherstation/updateweatherstation.php'
self.url_items = {}
self.valid_keys = ('action', 'ID', 'PAS... | the_stack_v2_python_sparse | wunder_formatter.py | rwspicer/csv_utilities | train | 1 |
546a0bbe47034f3443306888432d8e84a792c4e7 | [
"low, high = (0, len(nums) - 1)\nwhile low <= high:\n mid = low + (high - low) // 2\n if nums[mid] == target:\n return mid\n if nums[mid] < target:\n low = mid + 1\n else:\n high = mid - 1\nif high >= 0 and nums[high] > target:\n return high\nreturn low",
"start = 0\nend = len(... | <|body_start_0|>
low, high = (0, len(nums) - 1)
while low <= high:
mid = low + (high - low) // 2
if nums[mid] == target:
return mid
if nums[mid] < target:
low = mid + 1
else:
high = mid - 1
if high >=... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchInsert2(self, nums: List[int], target: int) -> int:
"""20210824 do it again Runtime: 63 ms, faster than 22.19% Memory Usage: 15 MB, less than 56.94% :param nums: :param target: :return:"""
<|body_0|>
def searchInsert(self, nums, target):
""":type ... | stack_v2_sparse_classes_10k_train_004328 | 2,922 | permissive | [
{
"docstring": "20210824 do it again Runtime: 63 ms, faster than 22.19% Memory Usage: 15 MB, less than 56.94% :param nums: :param target: :return:",
"name": "searchInsert2",
"signature": "def searchInsert2(self, nums: List[int], target: int) -> int"
},
{
"docstring": ":type nums: List[int] :type... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert2(self, nums: List[int], target: int) -> int: 20210824 do it again Runtime: 63 ms, faster than 22.19% Memory Usage: 15 MB, less than 56.94% :param nums: :param ta... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert2(self, nums: List[int], target: int) -> int: 20210824 do it again Runtime: 63 ms, faster than 22.19% Memory Usage: 15 MB, less than 56.94% :param nums: :param ta... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def searchInsert2(self, nums: List[int], target: int) -> int:
"""20210824 do it again Runtime: 63 ms, faster than 22.19% Memory Usage: 15 MB, less than 56.94% :param nums: :param target: :return:"""
<|body_0|>
def searchInsert(self, nums, target):
""":type ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def searchInsert2(self, nums: List[int], target: int) -> int:
"""20210824 do it again Runtime: 63 ms, faster than 22.19% Memory Usage: 15 MB, less than 56.94% :param nums: :param target: :return:"""
low, high = (0, len(nums) - 1)
while low <= high:
mid = low + (hi... | the_stack_v2_python_sparse | src/35-SearchInsertPosition.py | Jiezhi/myleetcode | train | 1 | |
a8333756ca8a2856aefe89a4af6986e9dc3f0845 | [
"super().__init__(config)\nself.kg_start_idx = kg_start_idx\nself.prot_start_idx = prot_start_idx\nself.text_decoder = nn.Linear(config.hidden_size, config.lm_vocab_size, bias=False)\nself.entity_decoder = nn.Linear(config.hidden_size, config.kg_vocab_size, bias=False)\nself.prot_decoder = nn.Linear(config.hidden_s... | <|body_start_0|>
super().__init__(config)
self.kg_start_idx = kg_start_idx
self.prot_start_idx = prot_start_idx
self.text_decoder = nn.Linear(config.hidden_size, config.lm_vocab_size, bias=False)
self.entity_decoder = nn.Linear(config.hidden_size, config.kg_vocab_size, bias=False... | Custom masked protein, entity and language modeling (PELM) head for proteins, entities and text tokens. | ProtSTonKGsPELMPredictionHead | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtSTonKGsPELMPredictionHead:
"""Custom masked protein, entity and language modeling (PELM) head for proteins, entities and text tokens."""
def __init__(self, config, kg_start_idx: int=768, prot_start_idx: int=1024):
"""Initialize the ELM head based on the (hyper)parameters in the p... | stack_v2_sparse_classes_10k_train_004329 | 17,026 | permissive | [
{
"docstring": "Initialize the ELM head based on the (hyper)parameters in the provided BertConfig.",
"name": "__init__",
"signature": "def __init__(self, config, kg_start_idx: int=768, prot_start_idx: int=1024)"
},
{
"docstring": "Map hidden states to values for the text (1st part), kg (2nd part... | 2 | stack_v2_sparse_classes_30k_train_005593 | Implement the Python class `ProtSTonKGsPELMPredictionHead` described below.
Class description:
Custom masked protein, entity and language modeling (PELM) head for proteins, entities and text tokens.
Method signatures and docstrings:
- def __init__(self, config, kg_start_idx: int=768, prot_start_idx: int=1024): Initia... | Implement the Python class `ProtSTonKGsPELMPredictionHead` described below.
Class description:
Custom masked protein, entity and language modeling (PELM) head for proteins, entities and text tokens.
Method signatures and docstrings:
- def __init__(self, config, kg_start_idx: int=768, prot_start_idx: int=1024): Initia... | 2810353739a785ab9aee75ec15ffc738470bc288 | <|skeleton|>
class ProtSTonKGsPELMPredictionHead:
"""Custom masked protein, entity and language modeling (PELM) head for proteins, entities and text tokens."""
def __init__(self, config, kg_start_idx: int=768, prot_start_idx: int=1024):
"""Initialize the ELM head based on the (hyper)parameters in the p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProtSTonKGsPELMPredictionHead:
"""Custom masked protein, entity and language modeling (PELM) head for proteins, entities and text tokens."""
def __init__(self, config, kg_start_idx: int=768, prot_start_idx: int=1024):
"""Initialize the ELM head based on the (hyper)parameters in the provided BertC... | the_stack_v2_python_sparse | src/stonkgs/models/protstonkgs_model.py | stonkgs/stonkgs | train | 30 |
6d8964c999013cf9977488687b806acf9a02c107 | [
"shots = 100\ncircuits = ref_unitary_gate.unitary_gate_circuits_deterministic(final_measure=True)\ntargets = ref_unitary_gate.unitary_gate_counts_deterministic(shots)\nresult = execute(circuits, self.SIMULATOR, shots=shots).result()\nself.assertTrue(getattr(result, 'success', False))\nself.compare_counts(result, ci... | <|body_start_0|>
shots = 100
circuits = ref_unitary_gate.unitary_gate_circuits_deterministic(final_measure=True)
targets = ref_unitary_gate.unitary_gate_counts_deterministic(shots)
result = execute(circuits, self.SIMULATOR, shots=shots).result()
self.assertTrue(getattr(result, 's... | QasmSimulator additional tests. | QasmUnitaryGateTests | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QasmUnitaryGateTests:
"""QasmSimulator additional tests."""
def test_unitary_gate(self):
"""Test simulation with unitary gate circuit instructions."""
<|body_0|>
def test_random_unitary_gate(self):
"""Test simulation with random unitary gate circuit instructions.... | stack_v2_sparse_classes_10k_train_004330 | 3,511 | permissive | [
{
"docstring": "Test simulation with unitary gate circuit instructions.",
"name": "test_unitary_gate",
"signature": "def test_unitary_gate(self)"
},
{
"docstring": "Test simulation with random unitary gate circuit instructions.",
"name": "test_random_unitary_gate",
"signature": "def test... | 2 | stack_v2_sparse_classes_30k_train_005589 | Implement the Python class `QasmUnitaryGateTests` described below.
Class description:
QasmSimulator additional tests.
Method signatures and docstrings:
- def test_unitary_gate(self): Test simulation with unitary gate circuit instructions.
- def test_random_unitary_gate(self): Test simulation with random unitary gate ... | Implement the Python class `QasmUnitaryGateTests` described below.
Class description:
QasmSimulator additional tests.
Method signatures and docstrings:
- def test_unitary_gate(self): Test simulation with unitary gate circuit instructions.
- def test_random_unitary_gate(self): Test simulation with random unitary gate ... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class QasmUnitaryGateTests:
"""QasmSimulator additional tests."""
def test_unitary_gate(self):
"""Test simulation with unitary gate circuit instructions."""
<|body_0|>
def test_random_unitary_gate(self):
"""Test simulation with random unitary gate circuit instructions.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QasmUnitaryGateTests:
"""QasmSimulator additional tests."""
def test_unitary_gate(self):
"""Test simulation with unitary gate circuit instructions."""
shots = 100
circuits = ref_unitary_gate.unitary_gate_circuits_deterministic(final_measure=True)
targets = ref_unitary_gate... | the_stack_v2_python_sparse | artifacts/old_dataset_versions/original_commits/qiskit-aer/qiskit-aer#707/before/qasm_unitary_gate.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
591292c85b964332f06cc0d06447f267977ac71f | [
"super().__init__()\nself.cost_class = cost_class\nself.cost_bbox = cost_bbox\nself.cost_giou = cost_giou\nassert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, 'all costs cant be 0'",
"with torch.no_grad():\n targets = [targets[1]]\n out_bbox = outputs['pred_boxes'].flatten(0, 1)\n out_bbox = out_... | <|body_start_0|>
super().__init__()
self.cost_class = cost_class
self.cost_bbox = cost_bbox
self.cost_giou = cost_giou
assert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, 'all costs cant be 0'
<|end_body_0|>
<|body_start_1|>
with torch.no_grad():
targ... | SimpleMatcher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleMatcher:
def __init__(self, cost_class: float=1, cost_bbox: float=1, cost_giou: float=1):
"""Creates the matcher Params: cost_class: This is the relative weight of the classification error in the matching cost cost_bbox: This is the relative weight of the L1 error of the bounding b... | stack_v2_sparse_classes_10k_train_004331 | 2,835 | no_license | [
{
"docstring": "Creates the matcher Params: cost_class: This is the relative weight of the classification error in the matching cost cost_bbox: This is the relative weight of the L1 error of the bounding box coordinates in the matching cost cost_giou: This is the relative weight of the giou loss of the bounding... | 2 | stack_v2_sparse_classes_30k_train_000556 | Implement the Python class `SimpleMatcher` described below.
Class description:
Implement the SimpleMatcher class.
Method signatures and docstrings:
- def __init__(self, cost_class: float=1, cost_bbox: float=1, cost_giou: float=1): Creates the matcher Params: cost_class: This is the relative weight of the classificati... | Implement the Python class `SimpleMatcher` described below.
Class description:
Implement the SimpleMatcher class.
Method signatures and docstrings:
- def __init__(self, cost_class: float=1, cost_bbox: float=1, cost_giou: float=1): Creates the matcher Params: cost_class: This is the relative weight of the classificati... | 24e1f80b24fb786039932603232b4c5801de1e37 | <|skeleton|>
class SimpleMatcher:
def __init__(self, cost_class: float=1, cost_bbox: float=1, cost_giou: float=1):
"""Creates the matcher Params: cost_class: This is the relative weight of the classification error in the matching cost cost_bbox: This is the relative weight of the L1 error of the bounding b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SimpleMatcher:
def __init__(self, cost_class: float=1, cost_bbox: float=1, cost_giou: float=1):
"""Creates the matcher Params: cost_class: This is the relative weight of the classification error in the matching cost cost_bbox: This is the relative weight of the L1 error of the bounding box coordinates... | the_stack_v2_python_sparse | utils/simple_matcher.py | ZYWZ/rltracking | train | 1 | |
f8e035b9b474e6fe48f26bd751f494f141c91db0 | [
"if obstacleGrid[0][0]:\n return 0\nrow = len(obstacleGrid)\ncol = len(obstacleGrid[0])\nres = [[0 for _ in range(col)] for _ in range(row)]\nfor i in range(row):\n if not obstacleGrid[i][0]:\n res[i][0] = 1\n else:\n break\nfor i in range(col):\n if not obstacleGrid[0][i]:\n res[0]... | <|body_start_0|>
if obstacleGrid[0][0]:
return 0
row = len(obstacleGrid)
col = len(obstacleGrid[0])
res = [[0 for _ in range(col)] for _ in range(row)]
for i in range(row):
if not obstacleGrid[i][0]:
res[i][0] = 1
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePathsWithObstacles(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int res[i][j] = res[i-1][j]+res[i][j-1]"""
<|body_0|>
def uniquePathsWithObstacles2(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int"""
... | stack_v2_sparse_classes_10k_train_004332 | 2,225 | no_license | [
{
"docstring": ":type obstacleGrid: List[List[int]] :rtype: int res[i][j] = res[i-1][j]+res[i][j-1]",
"name": "uniquePathsWithObstacles",
"signature": "def uniquePathsWithObstacles(self, obstacleGrid)"
},
{
"docstring": ":type obstacleGrid: List[List[int]] :rtype: int",
"name": "uniquePathsW... | 2 | stack_v2_sparse_classes_30k_val_000098 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePathsWithObstacles(self, obstacleGrid): :type obstacleGrid: List[List[int]] :rtype: int res[i][j] = res[i-1][j]+res[i][j-1]
- def uniquePathsWithObstacles2(self, obstac... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePathsWithObstacles(self, obstacleGrid): :type obstacleGrid: List[List[int]] :rtype: int res[i][j] = res[i-1][j]+res[i][j-1]
- def uniquePathsWithObstacles2(self, obstac... | 013f6f222c6c2a617787b258f8a37003a9f51526 | <|skeleton|>
class Solution:
def uniquePathsWithObstacles(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int res[i][j] = res[i-1][j]+res[i][j-1]"""
<|body_0|>
def uniquePathsWithObstacles2(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePathsWithObstacles(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int res[i][j] = res[i-1][j]+res[i][j-1]"""
if obstacleGrid[0][0]:
return 0
row = len(obstacleGrid)
col = len(obstacleGrid[0])
res = [[0 for _ in range(... | the_stack_v2_python_sparse | dp/unique_paths_withobstacles.py | terrifyzhao/leetcode | train | 0 | |
828dbb37ef0e139c616567fbff25f6d9e0e420af | [
"try:\n send_health_message(KAFKA_SERVER, HEALTHTOPIC, SERVICENAME)\nexcept Exception as error:\n LogMessage(str(error), LogMessage.LogTyp.ERROR, SERVICENAME).log()",
"try:\n report = json.loads(report.value.decode('UTF-8'))\n misp_connection = PyMISP(MISP_SERVER, MISP_TOKEN, MISP_CERT_VERIFY)\n ha... | <|body_start_0|>
try:
send_health_message(KAFKA_SERVER, HEALTHTOPIC, SERVICENAME)
except Exception as error:
LogMessage(str(error), LogMessage.LogTyp.ERROR, SERVICENAME).log()
<|end_body_0|>
<|body_start_1|>
try:
report = json.loads(report.value.decode('UTF-8... | Reporter will be a class representing the reporter-service. | Reporter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reporter:
"""Reporter will be a class representing the reporter-service."""
def healthpush():
"""healthpush will send a health message to KAFKA."""
<|body_0|>
def push_misp_report(report):
"""push_misp_report will send the misp report to the misp-platfrom."""
... | stack_v2_sparse_classes_10k_train_004333 | 3,082 | permissive | [
{
"docstring": "healthpush will send a health message to KAFKA.",
"name": "healthpush",
"signature": "def healthpush()"
},
{
"docstring": "push_misp_report will send the misp report to the misp-platfrom.",
"name": "push_misp_report",
"signature": "def push_misp_report(report)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_005630 | Implement the Python class `Reporter` described below.
Class description:
Reporter will be a class representing the reporter-service.
Method signatures and docstrings:
- def healthpush(): healthpush will send a health message to KAFKA.
- def push_misp_report(report): push_misp_report will send the misp report to the ... | Implement the Python class `Reporter` described below.
Class description:
Reporter will be a class representing the reporter-service.
Method signatures and docstrings:
- def healthpush(): healthpush will send a health message to KAFKA.
- def push_misp_report(report): push_misp_report will send the misp report to the ... | cdad9966ab2aef495d0dca51a06cf567dd38a315 | <|skeleton|>
class Reporter:
"""Reporter will be a class representing the reporter-service."""
def healthpush():
"""healthpush will send a health message to KAFKA."""
<|body_0|>
def push_misp_report(report):
"""push_misp_report will send the misp report to the misp-platfrom."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Reporter:
"""Reporter will be a class representing the reporter-service."""
def healthpush():
"""healthpush will send a health message to KAFKA."""
try:
send_health_message(KAFKA_SERVER, HEALTHTOPIC, SERVICENAME)
except Exception as error:
LogMessage(str(er... | the_stack_v2_python_sparse | iocreporter/core/server.py | hm-seclab/YAFRA | train | 32 |
aa688f8d1c0b68b516e455eec4b6c191291e4b51 | [
"self.newLines = self.__newCreateLines(quasimode)\nself.__newSmoothRags()\nself.__newRoundCorners()\nself.__setBackgroundColors()",
"lines = []\nsuggestionList = quasimode.getSuggestionList()\ndescription = suggestionList.getDescription()\ndescription = escape_xml(description)\nsuggestions = suggestionList.getSug... | <|body_start_0|>
self.newLines = self.__newCreateLines(quasimode)
self.__newSmoothRags()
self.__newRoundCorners()
self.__setBackgroundColors()
<|end_body_0|>
<|body_start_1|>
lines = []
suggestionList = quasimode.getSuggestionList()
description = suggestionList.g... | Class for calculating and storing layout metrics of the quasimode window. | QuasimodeLayout | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuasimodeLayout:
"""Class for calculating and storing layout metrics of the quasimode window."""
def __init__(self, quasimode):
"""Computes and stores the layout metrics for the quasimode."""
<|body_0|>
def __newCreateLines(self, quasimode):
"""LONGTERM TODO: Doc... | stack_v2_sparse_classes_10k_train_004334 | 14,287 | permissive | [
{
"docstring": "Computes and stores the layout metrics for the quasimode.",
"name": "__init__",
"signature": "def __init__(self, quasimode)"
},
{
"docstring": "LONGTERM TODO: Document this.",
"name": "__newCreateLines",
"signature": "def __newCreateLines(self, quasimode)"
},
{
"d... | 5 | stack_v2_sparse_classes_30k_train_002566 | Implement the Python class `QuasimodeLayout` described below.
Class description:
Class for calculating and storing layout metrics of the quasimode window.
Method signatures and docstrings:
- def __init__(self, quasimode): Computes and stores the layout metrics for the quasimode.
- def __newCreateLines(self, quasimode... | Implement the Python class `QuasimodeLayout` described below.
Class description:
Class for calculating and storing layout metrics of the quasimode window.
Method signatures and docstrings:
- def __init__(self, quasimode): Computes and stores the layout metrics for the quasimode.
- def __newCreateLines(self, quasimode... | 61351f52f01367439e8810d2c482a9c9897545d8 | <|skeleton|>
class QuasimodeLayout:
"""Class for calculating and storing layout metrics of the quasimode window."""
def __init__(self, quasimode):
"""Computes and stores the layout metrics for the quasimode."""
<|body_0|>
def __newCreateLines(self, quasimode):
"""LONGTERM TODO: Doc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QuasimodeLayout:
"""Class for calculating and storing layout metrics of the quasimode window."""
def __init__(self, quasimode):
"""Computes and stores the layout metrics for the quasimode."""
self.newLines = self.__newCreateLines(quasimode)
self.__newSmoothRags()
self.__ne... | the_stack_v2_python_sparse | enso/enso/quasimode/layout.py | GChristensen/enso-portable | train | 144 |
45f5ef3cc47674d3c2b7e9a7d6bc6d700dc24d0d | [
"fleet_veh = self.pool.get('fleet.vehicle')\nrangs = fleet_veh._selection_year(self, cr, uid)\nlist_year = []\nfor years in rangs[1:len(rangs)]:\n list_year.append(years)\nreturn list_year",
"data = self.read(cr, uid, ids, [], context=context)[0]\ndatas = {'ids': [], 'model': 'fleet.vehicle.log.contract', 'for... | <|body_start_0|>
fleet_veh = self.pool.get('fleet.vehicle')
rangs = fleet_veh._selection_year(self, cr, uid)
list_year = []
for years in rangs[1:len(rangs)]:
list_year.append(years)
return list_year
<|end_body_0|>
<|body_start_1|>
data = self.read(cr, uid, id... | To manage rented cars reports | rented_cars_wiz | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class rented_cars_wiz:
"""To manage rented cars reports"""
def _year(self, cr, uid, context=None):
"""Select cars manufacturing years between 1970 and Current year. @return: list of years"""
<|body_0|>
def print_report(self, cr, uid, ids, context=None):
"""Print report... | stack_v2_sparse_classes_10k_train_004335 | 2,273 | no_license | [
{
"docstring": "Select cars manufacturing years between 1970 and Current year. @return: list of years",
"name": "_year",
"signature": "def _year(self, cr, uid, context=None)"
},
{
"docstring": "Print report. @return: Dictionary of print attributes",
"name": "print_report",
"signature": "... | 2 | null | Implement the Python class `rented_cars_wiz` described below.
Class description:
To manage rented cars reports
Method signatures and docstrings:
- def _year(self, cr, uid, context=None): Select cars manufacturing years between 1970 and Current year. @return: list of years
- def print_report(self, cr, uid, ids, contex... | Implement the Python class `rented_cars_wiz` described below.
Class description:
To manage rented cars reports
Method signatures and docstrings:
- def _year(self, cr, uid, context=None): Select cars manufacturing years between 1970 and Current year. @return: list of years
- def print_report(self, cr, uid, ids, contex... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class rented_cars_wiz:
"""To manage rented cars reports"""
def _year(self, cr, uid, context=None):
"""Select cars manufacturing years between 1970 and Current year. @return: list of years"""
<|body_0|>
def print_report(self, cr, uid, ids, context=None):
"""Print report... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class rented_cars_wiz:
"""To manage rented cars reports"""
def _year(self, cr, uid, context=None):
"""Select cars manufacturing years between 1970 and Current year. @return: list of years"""
fleet_veh = self.pool.get('fleet.vehicle')
rangs = fleet_veh._selection_year(self, cr, uid)
... | the_stack_v2_python_sparse | v_7/Dongola/admin_affairs/service/wizard/rented_cars.py | musabahmed/baba | train | 0 |
c8c00c2f7e6dd27cdb5ca5748ee9b011b527e0f2 | [
"body = dict(request.data)\norg_id = self.get_organization(request)\nproperty_view_ids = body.get('property_view_ids')\ntaxlot_view_ids = body.get('taxlot_view_ids')\nif property_view_ids:\n property_views = PropertyView.objects.filter(id__in=property_view_ids, cycle__organization_id=org_id)\n properties = Pr... | <|body_start_0|>
body = dict(request.data)
org_id = self.get_organization(request)
property_view_ids = body.get('property_view_ids')
taxlot_view_ids = body.get('taxlot_view_ids')
if property_view_ids:
property_views = PropertyView.objects.filter(id__in=property_view_i... | GeocodeViewSet | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeocodeViewSet:
def geocode_by_ids(self, request):
"""Submit a request to geocode property and tax lot records."""
<|body_0|>
def confidence_summary(self, request):
"""Generate a summary of geocoding confidence values for property and tax lot records."""
<|bo... | stack_v2_sparse_classes_10k_train_004336 | 6,094 | permissive | [
{
"docstring": "Submit a request to geocode property and tax lot records.",
"name": "geocode_by_ids",
"signature": "def geocode_by_ids(self, request)"
},
{
"docstring": "Generate a summary of geocoding confidence values for property and tax lot records.",
"name": "confidence_summary",
"s... | 2 | stack_v2_sparse_classes_30k_train_005324 | Implement the Python class `GeocodeViewSet` described below.
Class description:
Implement the GeocodeViewSet class.
Method signatures and docstrings:
- def geocode_by_ids(self, request): Submit a request to geocode property and tax lot records.
- def confidence_summary(self, request): Generate a summary of geocoding ... | Implement the Python class `GeocodeViewSet` described below.
Class description:
Implement the GeocodeViewSet class.
Method signatures and docstrings:
- def geocode_by_ids(self, request): Submit a request to geocode property and tax lot records.
- def confidence_summary(self, request): Generate a summary of geocoding ... | 680b6a2b45f3c568d779d8ac86553a0b08c384c8 | <|skeleton|>
class GeocodeViewSet:
def geocode_by_ids(self, request):
"""Submit a request to geocode property and tax lot records."""
<|body_0|>
def confidence_summary(self, request):
"""Generate a summary of geocoding confidence values for property and tax lot records."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeocodeViewSet:
def geocode_by_ids(self, request):
"""Submit a request to geocode property and tax lot records."""
body = dict(request.data)
org_id = self.get_organization(request)
property_view_ids = body.get('property_view_ids')
taxlot_view_ids = body.get('taxlot_view... | the_stack_v2_python_sparse | seed/views/v3/geocode.py | SEED-platform/seed | train | 108 | |
3332f40223004e1be18d1012f79910850736edf9 | [
"defined_fields = self.form.used_field_names\nrequired_fields = self.form.get_required_field_names()\nmissing_fields = []\nfor field in required_fields:\n if field not in defined_fields:\n missing_fields.append(field)\nif len(missing_fields) > 0:\n raise ValidationError('The save instance handler can o... | <|body_start_0|>
defined_fields = self.form.used_field_names
required_fields = self.form.get_required_field_names()
missing_fields = []
for field in required_fields:
if field not in defined_fields:
missing_fields.append(field)
if len(missing_fields) > ... | Handler for saving the form instance | OmniFormSaveInstanceHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OmniFormSaveInstanceHandler:
"""Handler for saving the form instance"""
def assert_has_all_required_fields(self):
"""Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError"""
<|body_0|>
def clean(self):
... | stack_v2_sparse_classes_10k_train_004337 | 47,532 | permissive | [
{
"docstring": "Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError",
"name": "assert_has_all_required_fields",
"signature": "def assert_has_all_required_fields(self)"
},
{
"docstring": "Cleans the handler for saving a model ins... | 3 | stack_v2_sparse_classes_30k_train_004259 | Implement the Python class `OmniFormSaveInstanceHandler` described below.
Class description:
Handler for saving the form instance
Method signatures and docstrings:
- def assert_has_all_required_fields(self): Property that determines whether or not the associated form defines all of the required fields :raises: Valida... | Implement the Python class `OmniFormSaveInstanceHandler` described below.
Class description:
Handler for saving the form instance
Method signatures and docstrings:
- def assert_has_all_required_fields(self): Property that determines whether or not the associated form defines all of the required fields :raises: Valida... | 0c96162445f8b5ddf7f326f6b0a2e6ec239c4bd5 | <|skeleton|>
class OmniFormSaveInstanceHandler:
"""Handler for saving the form instance"""
def assert_has_all_required_fields(self):
"""Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError"""
<|body_0|>
def clean(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OmniFormSaveInstanceHandler:
"""Handler for saving the form instance"""
def assert_has_all_required_fields(self):
"""Property that determines whether or not the associated form defines all of the required fields :raises: ValidationError"""
defined_fields = self.form.used_field_names
... | the_stack_v2_python_sparse | omniforms/models.py | omni-digital/omni-forms | train | 6 |
8c2fd26e0624f01504a6e1e2fdd6d2b363a3d6ab | [
"response = self.client.get('/shopping_bag/')\nself.assertEqual(response.status_code, 200)\nself.assertTemplateUsed(response, 'shopping_bag/bag.html')",
"user = User.objects.create(username='test')\nimage = Image.objects.create(img_title='test', base_price=0, user_id=user)\nbag = {image.id: 1}\nresponse = self.cl... | <|body_start_0|>
response = self.client.get('/shopping_bag/')
self.assertEqual(response.status_code, 200)
self.assertTemplateUsed(response, 'shopping_bag/bag.html')
<|end_body_0|>
<|body_start_1|>
user = User.objects.create(username='test')
image = Image.objects.create(img_title... | test shpopping bag views | TestShoppingBagViews | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestShoppingBagViews:
"""test shpopping bag views"""
def test_show_bag(self):
"""test show bag view"""
<|body_0|>
def test_add_to_bag(self):
"""test add to bag view"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
response = self.client.get('/sho... | stack_v2_sparse_classes_10k_train_004338 | 799 | no_license | [
{
"docstring": "test show bag view",
"name": "test_show_bag",
"signature": "def test_show_bag(self)"
},
{
"docstring": "test add to bag view",
"name": "test_add_to_bag",
"signature": "def test_add_to_bag(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001596 | Implement the Python class `TestShoppingBagViews` described below.
Class description:
test shpopping bag views
Method signatures and docstrings:
- def test_show_bag(self): test show bag view
- def test_add_to_bag(self): test add to bag view | Implement the Python class `TestShoppingBagViews` described below.
Class description:
test shpopping bag views
Method signatures and docstrings:
- def test_show_bag(self): test show bag view
- def test_add_to_bag(self): test add to bag view
<|skeleton|>
class TestShoppingBagViews:
"""test shpopping bag views"""
... | 3b12c46beb5b04a506ef6c9fe252d1c891cdd49f | <|skeleton|>
class TestShoppingBagViews:
"""test shpopping bag views"""
def test_show_bag(self):
"""test show bag view"""
<|body_0|>
def test_add_to_bag(self):
"""test add to bag view"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestShoppingBagViews:
"""test shpopping bag views"""
def test_show_bag(self):
"""test show bag view"""
response = self.client.get('/shopping_bag/')
self.assertEqual(response.status_code, 200)
self.assertTemplateUsed(response, 'shopping_bag/bag.html')
def test_add_to_b... | the_stack_v2_python_sparse | shopping_bag/test_shopping_bag_views.py | Code-Institute-Submissions/Final_Milestone_Project | train | 0 |
afbf0983e90d9efac98652276eec985fadbb9700 | [
"super(RelativePosition, self).__init__()\nself.num_units = num_units\nself.device = device\nself.max_relative_position = max_relative_position\nself.embeddings_table = nn.Parameter(torch.Tensor(max_relative_position * 2 + 1, num_units))\nnn.init.xavier_uniform_(self.embeddings_table)",
"range_vec_q = torch.arang... | <|body_start_0|>
super(RelativePosition, self).__init__()
self.num_units = num_units
self.device = device
self.max_relative_position = max_relative_position
self.embeddings_table = nn.Parameter(torch.Tensor(max_relative_position * 2 + 1, num_units))
nn.init.xavier_uniform... | RelativePosition | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelativePosition:
def __init__(self, num_units, max_relative_position, device=None):
""":param num_units: d_a :param max_relative_position: k"""
<|body_0|>
def forward(self, length_q, length_k):
"""for self-att: length_q == length_k == length_x return: embeddings: le... | stack_v2_sparse_classes_10k_train_004339 | 1,268 | no_license | [
{
"docstring": ":param num_units: d_a :param max_relative_position: k",
"name": "__init__",
"signature": "def __init__(self, num_units, max_relative_position, device=None)"
},
{
"docstring": "for self-att: length_q == length_k == length_x return: embeddings: length_q x length_k x d_a",
"name... | 2 | stack_v2_sparse_classes_30k_train_001980 | Implement the Python class `RelativePosition` described below.
Class description:
Implement the RelativePosition class.
Method signatures and docstrings:
- def __init__(self, num_units, max_relative_position, device=None): :param num_units: d_a :param max_relative_position: k
- def forward(self, length_q, length_k): ... | Implement the Python class `RelativePosition` described below.
Class description:
Implement the RelativePosition class.
Method signatures and docstrings:
- def __init__(self, num_units, max_relative_position, device=None): :param num_units: d_a :param max_relative_position: k
- def forward(self, length_q, length_k): ... | 1bfff12c6b03f64f57d118b435c0040431befcdf | <|skeleton|>
class RelativePosition:
def __init__(self, num_units, max_relative_position, device=None):
""":param num_units: d_a :param max_relative_position: k"""
<|body_0|>
def forward(self, length_q, length_k):
"""for self-att: length_q == length_k == length_x return: embeddings: le... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RelativePosition:
def __init__(self, num_units, max_relative_position, device=None):
""":param num_units: d_a :param max_relative_position: k"""
super(RelativePosition, self).__init__()
self.num_units = num_units
self.device = device
self.max_relative_position = max_rel... | the_stack_v2_python_sparse | nag/modules/relative_position.py | liu-hz18/Non-Autoregressive-Neural-Dialogue-Generation | train | 0 | |
b62173335183be65b5f41cc1779a5b84b3e2cbfb | [
"super(DRQN, self).__init__()\nobs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))\nif head_hidden_size is None:\n head_hidden_size = encoder_hidden_size_list[-1]\nif isinstance(obs_shape, int) or len(obs_shape) == 1:\n self.encoder = FCEncoder(obs_shape, encoder_hidden_size_list, activation... | <|body_start_0|>
super(DRQN, self).__init__()
obs_shape, action_shape = (squeeze(obs_shape), squeeze(action_shape))
if head_hidden_size is None:
head_hidden_size = encoder_hidden_size_list[-1]
if isinstance(obs_shape, int) or len(obs_shape) == 1:
self.encoder = FC... | Overview: DQN + RNN = DRQN | DRQN | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DRQN:
"""Overview: DQN + RNN = DRQN"""
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size: Optional[int]=None, head_layer_num: int=1, lstm_type: Optional[s... | stack_v2_sparse_classes_10k_train_004340 | 30,380 | permissive | [
{
"docstring": "Overview: Init the DRQN Model according to arguments. Arguments: - obs_shape (:obj:`Union[int, SequenceType]`): Observation's space. - action_shape (:obj:`Union[int, SequenceType]`): Action's space. - encoder_hidden_size_list (:obj:`SequenceType`): Collection of ``hidden_size`` to pass to ``Enco... | 2 | null | Implement the Python class `DRQN` described below.
Class description:
Overview: DQN + RNN = DRQN
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_si... | Implement the Python class `DRQN` described below.
Class description:
Overview: DQN + RNN = DRQN
Method signatures and docstrings:
- def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_si... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class DRQN:
"""Overview: DQN + RNN = DRQN"""
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size: Optional[int]=None, head_layer_num: int=1, lstm_type: Optional[s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DRQN:
"""Overview: DQN + RNN = DRQN"""
def __init__(self, obs_shape: Union[int, SequenceType], action_shape: Union[int, SequenceType], encoder_hidden_size_list: SequenceType=[128, 128, 64], dueling: bool=True, head_hidden_size: Optional[int]=None, head_layer_num: int=1, lstm_type: Optional[str]='normal',... | the_stack_v2_python_sparse | ding/model/template/q_learning.py | shengxuesun/DI-engine | train | 1 |
c8c69eeb76a952a5d513aaf6b8cabbfe5803e075 | [
"QUiLoader.__init__(self, baseinstance)\nself.baseinstance = baseinstance\nif customWidgets is None:\n self.customWidgets = {}\nelse:\n self.customWidgets = customWidgets",
"if parent is None and self.baseinstance:\n return self.baseinstance\nelse:\n if class_name in self.availableWidgets() or class_n... | <|body_start_0|>
QUiLoader.__init__(self, baseinstance)
self.baseinstance = baseinstance
if customWidgets is None:
self.customWidgets = {}
else:
self.customWidgets = customWidgets
<|end_body_0|>
<|body_start_1|>
if parent is None and self.baseinstance:
... | Subclass of :class:`~PySide.QtUiTools.QUiLoader` to create the user interface in a base instance. Unlike :class:`~PySide.QtUiTools.QUiLoader` itself this class does not create a new instance of the top-level widget, but creates the user interface in an existing instance of the top-level class if needed. This mimics the... | UiLoader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UiLoader:
"""Subclass of :class:`~PySide.QtUiTools.QUiLoader` to create the user interface in a base instance. Unlike :class:`~PySide.QtUiTools.QUiLoader` itself this class does not create a new instance of the top-level widget, but creates the user interface in an existing instance of the top-le... | stack_v2_sparse_classes_10k_train_004341 | 11,582 | permissive | [
{
"docstring": "Create a loader for the given ``baseinstance``. The user interface is created in ``baseinstance``, which must be an instance of the top-level class in the user interface to load, or a subclass thereof. ``customWidgets`` is a dictionary mapping from class name to class object for custom widgets. ... | 2 | stack_v2_sparse_classes_30k_train_003204 | Implement the Python class `UiLoader` described below.
Class description:
Subclass of :class:`~PySide.QtUiTools.QUiLoader` to create the user interface in a base instance. Unlike :class:`~PySide.QtUiTools.QUiLoader` itself this class does not create a new instance of the top-level widget, but creates the user interfac... | Implement the Python class `UiLoader` described below.
Class description:
Subclass of :class:`~PySide.QtUiTools.QUiLoader` to create the user interface in a base instance. Unlike :class:`~PySide.QtUiTools.QUiLoader` itself this class does not create a new instance of the top-level widget, but creates the user interfac... | 323c6fef4100220a84daf964ed0b78058862bc29 | <|skeleton|>
class UiLoader:
"""Subclass of :class:`~PySide.QtUiTools.QUiLoader` to create the user interface in a base instance. Unlike :class:`~PySide.QtUiTools.QUiLoader` itself this class does not create a new instance of the top-level widget, but creates the user interface in an existing instance of the top-le... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UiLoader:
"""Subclass of :class:`~PySide.QtUiTools.QUiLoader` to create the user interface in a base instance. Unlike :class:`~PySide.QtUiTools.QUiLoader` itself this class does not create a new instance of the top-level widget, but creates the user interface in an existing instance of the top-level class if ... | the_stack_v2_python_sparse | winpython/_vendor/qtpy/uic.py | winpython/winpython | train | 1,796 |
5bf508a5d1476c83e97a645f47e391f00f0ca9da | [
"res = []\nif not root:\n return res\nres.append(root.val)\nfrontier = deque([root])\nwhile frontier:\n expand = frontier.popleft()\n for kid in (expand.left, expand.right):\n if kid is None:\n res.append(None)\n else:\n res.append(kid.val)\n frontier.append(k... | <|body_start_0|>
res = []
if not root:
return res
res.append(root.val)
frontier = deque([root])
while frontier:
expand = frontier.popleft()
for kid in (expand.left, expand.right):
if kid is None:
res.append(N... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_004342 | 2,351 | 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:... | 11d6bf2ba7b50c07e048df37c4e05c8f46b92241 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = []
if not root:
return res
res.append(root.val)
frontier = deque([root])
while frontier:
expand = frontier.popleft()
... | the_stack_v2_python_sparse | LeetCodes/facebook/Serialize and Deserialize Binary Tree.py | chutianwen/LeetCodes | train | 0 | |
4d794a4365ba31422de5927118c4608dfeb53c46 | [
"super(EncodedTextReader, self).__init__()\nself._buffer = ''\nself._buffer_size = buffer_size\nself._current_offset = 0\nself._encoding = encoding\nself.lines = ''",
"if len(self._buffer) < self._buffer_size:\n content = file_object.read(self._buffer_size)\n content = content.decode(self._encoding)\n se... | <|body_start_0|>
super(EncodedTextReader, self).__init__()
self._buffer = ''
self._buffer_size = buffer_size
self._current_offset = 0
self._encoding = encoding
self.lines = ''
<|end_body_0|>
<|body_start_1|>
if len(self._buffer) < self._buffer_size:
c... | Encoded text reader. | EncodedTextReader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncodedTextReader:
"""Encoded text reader."""
def __init__(self, encoding, buffer_size=2048):
"""Initializes the encoded text reader object. Args: encoding (str): encoding. buffer_size (Optional[int]): buffer size."""
<|body_0|>
def _ReadLine(self, file_object):
... | stack_v2_sparse_classes_10k_train_004343 | 24,154 | permissive | [
{
"docstring": "Initializes the encoded text reader object. Args: encoding (str): encoding. buffer_size (Optional[int]): buffer size.",
"name": "__init__",
"signature": "def __init__(self, encoding, buffer_size=2048)"
},
{
"docstring": "Reads a line from the file object. Args: file_object (dfvfs... | 6 | stack_v2_sparse_classes_30k_train_000805 | Implement the Python class `EncodedTextReader` described below.
Class description:
Encoded text reader.
Method signatures and docstrings:
- def __init__(self, encoding, buffer_size=2048): Initializes the encoded text reader object. Args: encoding (str): encoding. buffer_size (Optional[int]): buffer size.
- def _ReadL... | Implement the Python class `EncodedTextReader` described below.
Class description:
Encoded text reader.
Method signatures and docstrings:
- def __init__(self, encoding, buffer_size=2048): Initializes the encoded text reader object. Args: encoding (str): encoding. buffer_size (Optional[int]): buffer size.
- def _ReadL... | c69b2952b608cfce47ff8fd0d1409d856be35cb1 | <|skeleton|>
class EncodedTextReader:
"""Encoded text reader."""
def __init__(self, encoding, buffer_size=2048):
"""Initializes the encoded text reader object. Args: encoding (str): encoding. buffer_size (Optional[int]): buffer size."""
<|body_0|>
def _ReadLine(self, file_object):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncodedTextReader:
"""Encoded text reader."""
def __init__(self, encoding, buffer_size=2048):
"""Initializes the encoded text reader object. Args: encoding (str): encoding. buffer_size (Optional[int]): buffer size."""
super(EncodedTextReader, self).__init__()
self._buffer = ''
... | the_stack_v2_python_sparse | plaso/parsers/text_parser.py | cyb3rfox/plaso | train | 3 |
c570b89332ebcfa5b6aee651c4b0a0c773dac507 | [
"super().__init__(self.PROBLEM_NAME)\nself.root_node = root_node\nself.label1 = label1\nself.label2 = label2",
"print('Solving {} problem ...'.format(self.PROBLEM_NAME))\npath1 = []\nself.path_to_node(self.root_node, path1, self.label1)\npath2 = []\nself.path_to_node(self.root_node, path2, self.label2)\ni = 0\nwh... | <|body_start_0|>
super().__init__(self.PROBLEM_NAME)
self.root_node = root_node
self.label1 = label1
self.label2 = label2
<|end_body_0|>
<|body_start_1|>
print('Solving {} problem ...'.format(self.PROBLEM_NAME))
path1 = []
self.path_to_node(self.root_node, path1,... | Find Distance Between Two Nodes | FindDistanceBetweenTwoNodes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FindDistanceBetweenTwoNodes:
"""Find Distance Between Two Nodes"""
def __init__(self, root_node, label1, label2):
"""Find Distance Between Two Nodes Args: root_node: node of the tree label1: First node's label label2: Second node's label Returns: None Raises: None"""
<|body_0... | stack_v2_sparse_classes_10k_train_004344 | 2,695 | no_license | [
{
"docstring": "Find Distance Between Two Nodes Args: root_node: node of the tree label1: First node's label label2: Second node's label Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, root_node, label1, label2)"
},
{
"docstring": "Solve the problem Note: O(n) (... | 3 | stack_v2_sparse_classes_30k_train_006747 | Implement the Python class `FindDistanceBetweenTwoNodes` described below.
Class description:
Find Distance Between Two Nodes
Method signatures and docstrings:
- def __init__(self, root_node, label1, label2): Find Distance Between Two Nodes Args: root_node: node of the tree label1: First node's label label2: Second no... | Implement the Python class `FindDistanceBetweenTwoNodes` described below.
Class description:
Find Distance Between Two Nodes
Method signatures and docstrings:
- def __init__(self, root_node, label1, label2): Find Distance Between Two Nodes Args: root_node: node of the tree label1: First node's label label2: Second no... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class FindDistanceBetweenTwoNodes:
"""Find Distance Between Two Nodes"""
def __init__(self, root_node, label1, label2):
"""Find Distance Between Two Nodes Args: root_node: node of the tree label1: First node's label label2: Second node's label Returns: None Raises: None"""
<|body_0... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FindDistanceBetweenTwoNodes:
"""Find Distance Between Two Nodes"""
def __init__(self, root_node, label1, label2):
"""Find Distance Between Two Nodes Args: root_node: node of the tree label1: First node's label label2: Second node's label Returns: None Raises: None"""
super().__init__(self... | the_stack_v2_python_sparse | python/problems/binary_tree/find_distance_between_two_nodes.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
79205759e44904843ef5999daeaeaf4fb8e02563 | [
"s = sum(nums)\nif s % k != 0:\n return False\ntarget = s // k\nvisited = [False for _ in nums]\nreturn self.dfs(nums, None, target, visited, k)",
"if k == 0:\n return True\nif cur_sum and cur_sum == target_sum:\n return self.dfs(nums, None, target_sum, visited, k - 1)\nfor i in range(len(nums)):\n if... | <|body_start_0|>
s = sum(nums)
if s % k != 0:
return False
target = s // k
visited = [False for _ in nums]
return self.dfs(nums, None, target, visited, k)
<|end_body_0|>
<|body_start_1|>
if k == 0:
return True
if cur_sum and cur_sum == tar... | Solution_TLE | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_TLE:
def canPartitionKSubsets(self, nums: List[int], k: int) -> bool:
"""resurive search"""
<|body_0|>
def dfs(self, nums, cur_sum, target_sum, visited, k):
"""some corner cases: 1. target_sum default at 0: sum or empty array is 0? 2. nxt_sum = (cur_sum or 0... | stack_v2_sparse_classes_10k_train_004345 | 3,307 | no_license | [
{
"docstring": "resurive search",
"name": "canPartitionKSubsets",
"signature": "def canPartitionKSubsets(self, nums: List[int], k: int) -> bool"
},
{
"docstring": "some corner cases: 1. target_sum default at 0: sum or empty array is 0? 2. nxt_sum = (cur_sum or 0) + nums[i] rather than cur_sum or... | 2 | stack_v2_sparse_classes_30k_train_002214 | Implement the Python class `Solution_TLE` described below.
Class description:
Implement the Solution_TLE class.
Method signatures and docstrings:
- def canPartitionKSubsets(self, nums: List[int], k: int) -> bool: resurive search
- def dfs(self, nums, cur_sum, target_sum, visited, k): some corner cases: 1. target_sum ... | Implement the Python class `Solution_TLE` described below.
Class description:
Implement the Solution_TLE class.
Method signatures and docstrings:
- def canPartitionKSubsets(self, nums: List[int], k: int) -> bool: resurive search
- def dfs(self, nums, cur_sum, target_sum, visited, k): some corner cases: 1. target_sum ... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution_TLE:
def canPartitionKSubsets(self, nums: List[int], k: int) -> bool:
"""resurive search"""
<|body_0|>
def dfs(self, nums, cur_sum, target_sum, visited, k):
"""some corner cases: 1. target_sum default at 0: sum or empty array is 0? 2. nxt_sum = (cur_sum or 0... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution_TLE:
def canPartitionKSubsets(self, nums: List[int], k: int) -> bool:
"""resurive search"""
s = sum(nums)
if s % k != 0:
return False
target = s // k
visited = [False for _ in nums]
return self.dfs(nums, None, target, visited, k)
def df... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/698 Partition to K Equal Sum Subsets.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
c1aa2c79ec02ea2569d041088936be373b090142 | [
"s.dingding = dingding\ns.subscription_dictionary = d\ns.match_pattern = d['MatchPattern']\ns.xmlrpc_recv_url = d['XmlRpcRecvUrl']\ns.recv_password = d.get('RecvPassword', None)\ns.subscription_passwords = d.get('SubscriptionPasswords', [])\ns.who_can_see_this = d.get('WhoCanSeeThis', s.dingding.options.get_default... | <|body_start_0|>
s.dingding = dingding
s.subscription_dictionary = d
s.match_pattern = d['MatchPattern']
s.xmlrpc_recv_url = d['XmlRpcRecvUrl']
s.recv_password = d.get('RecvPassword', None)
s.subscription_passwords = d.get('SubscriptionPasswords', [])
s.who_can_se... | Subscription - augment a subscription dictionary | Subscription | [
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Subscription:
"""Subscription - augment a subscription dictionary"""
def __init__(s, d, dingding):
"""subscription dictionary: * MatchPattern (*REQUIRED* - pattern of data matching out) * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL for receiving Notify messages * RecvPassword (OPTIONAL - ... | stack_v2_sparse_classes_10k_train_004346 | 25,098 | permissive | [
{
"docstring": "subscription dictionary: * MatchPattern (*REQUIRED* - pattern of data matching out) * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL for receiving Notify messages * RecvPassword (OPTIONAL - used when posting a NOTIFY, also a legitimizing recipient password) * SubscriptionPasswords (OPTIONAL - group pass... | 2 | stack_v2_sparse_classes_30k_train_002744 | Implement the Python class `Subscription` described below.
Class description:
Subscription - augment a subscription dictionary
Method signatures and docstrings:
- def __init__(s, d, dingding): subscription dictionary: * MatchPattern (*REQUIRED* - pattern of data matching out) * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL ... | Implement the Python class `Subscription` described below.
Class description:
Subscription - augment a subscription dictionary
Method signatures and docstrings:
- def __init__(s, d, dingding): subscription dictionary: * MatchPattern (*REQUIRED* - pattern of data matching out) * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL ... | da65d948b346d3f455e79168a8753b2b16d8fc5f | <|skeleton|>
class Subscription:
"""Subscription - augment a subscription dictionary"""
def __init__(s, d, dingding):
"""subscription dictionary: * MatchPattern (*REQUIRED* - pattern of data matching out) * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL for receiving Notify messages * RecvPassword (OPTIONAL - ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Subscription:
"""Subscription - augment a subscription dictionary"""
def __init__(s, d, dingding):
"""subscription dictionary: * MatchPattern (*REQUIRED* - pattern of data matching out) * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL for receiving Notify messages * RecvPassword (OPTIONAL - used when pos... | the_stack_v2_python_sparse | ancient/src/dingding/dingding.py | BackupTheBerlios/onebigsoup-svn | train | 0 |
910897d88113ab288cdb465e40036e3a92f90c45 | [
"coord_name = 'air_temperature status_flag'\ntry:\n coord = cube.coord(coord_name)\nexcept CoordinateNotFoundError:\n coord = None\nif coord:\n if coord.attributes != {'flag_meanings': 'above_surface_pressure below_surface_pressure', 'flag_values': np.array([0, 1], dtype='int8')}:\n raise ValueError... | <|body_start_0|>
coord_name = 'air_temperature status_flag'
try:
coord = cube.coord(coord_name)
except CoordinateNotFoundError:
coord = None
if coord:
if coord.attributes != {'flag_meanings': 'above_surface_pressure below_surface_pressure', 'flag_value... | Plugin to standardise cube metadata | StandardiseMetadata | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardiseMetadata:
"""Plugin to standardise cube metadata"""
def _rm_air_temperature_status_flag(cube: Cube) -> Cube:
"""Remove air_temperature status_flag coord by applying as NaN to cube data. See https://github.com/metoppv/improver/pull/1839 for further details."""
<|bod... | stack_v2_sparse_classes_10k_train_004347 | 8,621 | permissive | [
{
"docstring": "Remove air_temperature status_flag coord by applying as NaN to cube data. See https://github.com/metoppv/improver/pull/1839 for further details.",
"name": "_rm_air_temperature_status_flag",
"signature": "def _rm_air_temperature_status_flag(cube: Cube) -> Cube"
},
{
"docstring": "... | 6 | stack_v2_sparse_classes_30k_train_004657 | Implement the Python class `StandardiseMetadata` described below.
Class description:
Plugin to standardise cube metadata
Method signatures and docstrings:
- def _rm_air_temperature_status_flag(cube: Cube) -> Cube: Remove air_temperature status_flag coord by applying as NaN to cube data. See https://github.com/metoppv... | Implement the Python class `StandardiseMetadata` described below.
Class description:
Plugin to standardise cube metadata
Method signatures and docstrings:
- def _rm_air_temperature_status_flag(cube: Cube) -> Cube: Remove air_temperature status_flag coord by applying as NaN to cube data. See https://github.com/metoppv... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class StandardiseMetadata:
"""Plugin to standardise cube metadata"""
def _rm_air_temperature_status_flag(cube: Cube) -> Cube:
"""Remove air_temperature status_flag coord by applying as NaN to cube data. See https://github.com/metoppv/improver/pull/1839 for further details."""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StandardiseMetadata:
"""Plugin to standardise cube metadata"""
def _rm_air_temperature_status_flag(cube: Cube) -> Cube:
"""Remove air_temperature status_flag coord by applying as NaN to cube data. See https://github.com/metoppv/improver/pull/1839 for further details."""
coord_name = 'air_... | the_stack_v2_python_sparse | improver/standardise.py | metoppv/improver | train | 101 |
e06f0aecbc9c0f40b7bea990f1e68d6d37df31ad | [
"if not isinstance(loader, SAMLMetadataLoader):\n raise ValueError(\"Argument 'loader' must be an instance of {0} class\".format(SAMLMetadataLoader))\nif not isinstance(validator, SAMLFederatedMetadataValidator):\n raise ValueError(\"Argument 'validator' must be an instance of {0} class\".format(SAMLFederated... | <|body_start_0|>
if not isinstance(loader, SAMLMetadataLoader):
raise ValueError("Argument 'loader' must be an instance of {0} class".format(SAMLMetadataLoader))
if not isinstance(validator, SAMLFederatedMetadataValidator):
raise ValueError("Argument 'validator' must be an instan... | Loads metadata of federated IdPs from the specified metadata service. | SAMLFederatedIdentityProviderLoader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SAMLFederatedIdentityProviderLoader:
"""Loads metadata of federated IdPs from the specified metadata service."""
def __init__(self, loader, validator, parser):
"""Initialize a new instance of SAMLFederatedIdentityProviderLoader class. :param loader: SAML metadata loader :type loader:... | stack_v2_sparse_classes_10k_train_004348 | 6,037 | permissive | [
{
"docstring": "Initialize a new instance of SAMLFederatedIdentityProviderLoader class. :param loader: SAML metadata loader :type loader: api.saml.metadata.federations.loader.SAMLMetadataLoader :param validator: SAML metadata validator :type validator: api.saml.metadata.federations.validator.SAMLFederatedMetada... | 3 | stack_v2_sparse_classes_30k_train_003537 | Implement the Python class `SAMLFederatedIdentityProviderLoader` described below.
Class description:
Loads metadata of federated IdPs from the specified metadata service.
Method signatures and docstrings:
- def __init__(self, loader, validator, parser): Initialize a new instance of SAMLFederatedIdentityProviderLoader... | Implement the Python class `SAMLFederatedIdentityProviderLoader` described below.
Class description:
Loads metadata of federated IdPs from the specified metadata service.
Method signatures and docstrings:
- def __init__(self, loader, validator, parser): Initialize a new instance of SAMLFederatedIdentityProviderLoader... | 662cc7e0721d0153857c8c17a37e2a6df86f8ce6 | <|skeleton|>
class SAMLFederatedIdentityProviderLoader:
"""Loads metadata of federated IdPs from the specified metadata service."""
def __init__(self, loader, validator, parser):
"""Initialize a new instance of SAMLFederatedIdentityProviderLoader class. :param loader: SAML metadata loader :type loader:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SAMLFederatedIdentityProviderLoader:
"""Loads metadata of federated IdPs from the specified metadata service."""
def __init__(self, loader, validator, parser):
"""Initialize a new instance of SAMLFederatedIdentityProviderLoader class. :param loader: SAML metadata loader :type loader: api.saml.met... | the_stack_v2_python_sparse | api/saml/metadata/federations/loader.py | NYPL-Simplified/circulation | train | 20 |
27438849b800c9fa65cba43b03818eb13c7d7d86 | [
"self._vectorizer = TfidfVectorizer(ngram_range=ngram_range, min_df=min_df, max_df=max_df, analyzer=analyzer.value)\nself._documents = documents\nself._index = self._vectorizer.fit_transform(map(text_getter, self._documents))",
"query_vector = self._vectorizer.transform([query])\nscores = zip(self._documents, sel... | <|body_start_0|>
self._vectorizer = TfidfVectorizer(ngram_range=ngram_range, min_df=min_df, max_df=max_df, analyzer=analyzer.value)
self._documents = documents
self._index = self._vectorizer.fit_transform(map(text_getter, self._documents))
<|end_body_0|>
<|body_start_1|>
query_vector = ... | A simple text index from a corpus of text using tf-idf similarity. | TextIndex | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextIndex:
"""A simple text index from a corpus of text using tf-idf similarity."""
def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9):
"""Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and r... | stack_v2_sparse_classes_10k_train_004349 | 4,223 | permissive | [
{
"docstring": "Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and retrieved. text_getter: Function to extract text from documents. ngram_range: tuple (min_n, max_n), default=(1, 2) The lower and upper boundary of the range of n-values for different n-grams to be extracted. Al... | 2 | stack_v2_sparse_classes_30k_train_005983 | Implement the Python class `TextIndex` described below.
Class description:
A simple text index from a corpus of text using tf-idf similarity.
Method signatures and docstrings:
- def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9): Init parameters for TextIndex.... | Implement the Python class `TextIndex` described below.
Class description:
A simple text index from a corpus of text using tf-idf similarity.
Method signatures and docstrings:
- def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9): Init parameters for TextIndex.... | 569a3c31451d941165bd10783f73f494406b3906 | <|skeleton|>
class TextIndex:
"""A simple text index from a corpus of text using tf-idf similarity."""
def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9):
"""Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextIndex:
"""A simple text index from a corpus of text using tf-idf similarity."""
def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9):
"""Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and retrieved. tex... | the_stack_v2_python_sparse | tapas/utils/text_index.py | google-research/tapas | train | 1,043 |
5976a2dd80d24ba694dad84da69c4cae4b9f5dd8 | [
"super(ESPNETMultiHeadedAttention, self).__init__()\nassert n_feat % n_head == 0\nself.d_k = n_feat // n_head\nself.h = n_head\nself.linear_q = nn.Linear(n_feat, n_feat)\nself.linear_k = nn.Linear(n_feat, n_feat)\nself.linear_v = nn.Linear(n_feat, n_feat)\nself.linear_out = nn.Linear(n_feat, n_feat)\nself.attn = No... | <|body_start_0|>
super(ESPNETMultiHeadedAttention, self).__init__()
assert n_feat % n_head == 0
self.d_k = n_feat // n_head
self.h = n_head
self.linear_q = nn.Linear(n_feat, n_feat)
self.linear_k = nn.Linear(n_feat, n_feat)
self.linear_v = nn.Linear(n_feat, n_feat... | Multi-Head Attention layer. Args: n_head: The number of heads. n_feat: The number of features. dropout: Dropout rate. | ESPNETMultiHeadedAttention | [
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"LGPL-2.1-or-later",
"LicenseRef-scancode-free-unknown",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ESPNETMultiHeadedAttention:
"""Multi-Head Attention layer. Args: n_head: The number of heads. n_feat: The number of features. dropout: Dropout rate."""
def __init__(self, n_feat, n_head, dropout):
"""Construct an MultiHeadedAttention object."""
<|body_0|>
def forward_qkv... | stack_v2_sparse_classes_10k_train_004350 | 9,673 | permissive | [
{
"docstring": "Construct an MultiHeadedAttention object.",
"name": "__init__",
"signature": "def __init__(self, n_feat, n_head, dropout)"
},
{
"docstring": "Transform query, key and value. Args: query: Query tensor B X T1 X C key: Key tensor B X T2 X C value: Value tensor B X T2 X C Returns: to... | 4 | null | Implement the Python class `ESPNETMultiHeadedAttention` described below.
Class description:
Multi-Head Attention layer. Args: n_head: The number of heads. n_feat: The number of features. dropout: Dropout rate.
Method signatures and docstrings:
- def __init__(self, n_feat, n_head, dropout): Construct an MultiHeadedAtt... | Implement the Python class `ESPNETMultiHeadedAttention` described below.
Class description:
Multi-Head Attention layer. Args: n_head: The number of heads. n_feat: The number of features. dropout: Dropout rate.
Method signatures and docstrings:
- def __init__(self, n_feat, n_head, dropout): Construct an MultiHeadedAtt... | b60c741f746877293bb85eed6806736fc8fa0ffd | <|skeleton|>
class ESPNETMultiHeadedAttention:
"""Multi-Head Attention layer. Args: n_head: The number of heads. n_feat: The number of features. dropout: Dropout rate."""
def __init__(self, n_feat, n_head, dropout):
"""Construct an MultiHeadedAttention object."""
<|body_0|>
def forward_qkv... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ESPNETMultiHeadedAttention:
"""Multi-Head Attention layer. Args: n_head: The number of heads. n_feat: The number of features. dropout: Dropout rate."""
def __init__(self, n_feat, n_head, dropout):
"""Construct an MultiHeadedAttention object."""
super(ESPNETMultiHeadedAttention, self).__in... | the_stack_v2_python_sparse | kosmos-2/fairseq/fairseq/modules/espnet_multihead_attention.py | microsoft/unilm | train | 15,313 |
ff9bb67685cdcbc507f54655b035fbf5e76aacdd | [
"if len(nums) == 1:\n return nums[0]\nelse:\n return max(self.rob1(nums[1:]), self.rob1(nums[:-1]))",
"n = len(nums)\nif n == 0:\n return 0\nif n == 1:\n return nums[0]\nsum = [0] * n\nsum[0] = nums[0]\nsum[1] = max(nums[0], nums[1])\nfor i in range(2, n):\n sum[i] = max(sum[i - 2] + nums[i], sum[i... | <|body_start_0|>
if len(nums) == 1:
return nums[0]
else:
return max(self.rob1(nums[1:]), self.rob1(nums[:-1]))
<|end_body_0|>
<|body_start_1|>
n = len(nums)
if n == 0:
return 0
if n == 1:
return nums[0]
sum = [0] * n
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(nums) == 1:
return nums[0]
else:
... | stack_v2_sparse_classes_10k_train_004351 | 1,314 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob",
"signature": "def rob(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob1",
"signature": "def rob1(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000336 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): :type nums: List[int] :rtype: int
- def rob1(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums): :type nums: List[int] :rtype: int
- def rob1(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def rob(self, nums):
"... | ba58ac60b32e261e43482d7e71b32587700e3719 | <|skeleton|>
class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
if len(nums) == 1:
return nums[0]
else:
return max(self.rob1(nums[1:]), self.rob1(nums[:-1]))
def rob1(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
... | the_stack_v2_python_sparse | python/213_house_robber_II.py | lingng/Leetcode | train | 0 | |
1473b6557152218e4e3470963ac60018f9d30532 | [
"s = '#' + s\np = '#' + p\nm, n = (len(s), len(p))\ndp = [[False] * m for _ in range(n)]\ndp[0][0] = True\nfor i in range(2, n):\n dp[i][0] = dp[i - 2][0] and p[i] == '*'\nfor j in range(m):\n for i in range(1, n):\n if p[i] != '*':\n dp[i][j] = p[i] in (s[j], '.') and dp[i - 1][j - 1]\n ... | <|body_start_0|>
s = '#' + s
p = '#' + p
m, n = (len(s), len(p))
dp = [[False] * m for _ in range(n)]
dp[0][0] = True
for i in range(2, n):
dp[i][0] = dp[i - 2][0] and p[i] == '*'
for j in range(m):
for i in range(1, n):
if ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isMatch(self, s: str, p: str) -> bool:
"""没搞定！！！！！！！"""
<|body_0|>
def isMatch1(self, s, p):
"""别人的正解！！！！"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s = '#' + s
p = '#' + p
m, n = (len(s), len(p))
dp = [[Fa... | stack_v2_sparse_classes_10k_train_004352 | 3,699 | no_license | [
{
"docstring": "没搞定！！！！！！！",
"name": "isMatch",
"signature": "def isMatch(self, s: str, p: str) -> bool"
},
{
"docstring": "别人的正解！！！！",
"name": "isMatch1",
"signature": "def isMatch1(self, s, p)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004343 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isMatch(self, s: str, p: str) -> bool: 没搞定！！！！！！！
- def isMatch1(self, s, p): 别人的正解！！！！ | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isMatch(self, s: str, p: str) -> bool: 没搞定！！！！！！！
- def isMatch1(self, s, p): 别人的正解！！！！
<|skeleton|>
class Solution:
def isMatch(self, s: str, p: str) -> bool:
... | bc895124817aa1341d15ac85e1c6d670a9420dec | <|skeleton|>
class Solution:
def isMatch(self, s: str, p: str) -> bool:
"""没搞定！！！！！！！"""
<|body_0|>
def isMatch1(self, s, p):
"""别人的正解！！！！"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isMatch(self, s: str, p: str) -> bool:
"""没搞定！！！！！！！"""
s = '#' + s
p = '#' + p
m, n = (len(s), len(p))
dp = [[False] * m for _ in range(n)]
dp[0][0] = True
for i in range(2, n):
dp[i][0] = dp[i - 2][0] and p[i] == '*'
f... | the_stack_v2_python_sparse | leetcode/10RegularExpressionMatching.py | qilaidi/leetcode_problems | train | 0 | |
1bef05abcb184ab3359113381af031fe1e35c270 | [
"super(SimpleCNN, self).__init__()\ncnn = []\nfor i in range(n_hidden_layers):\n cnn.append(torch.nn.Conv2d(in_channels=n_in_channels, out_channels=n_kernels, kernel_size=kernel_size, bias=True, padding=int(kernel_size / 2)))\n cnn.append(torch.nn.ReLU())\n n_in_channels = n_kernels\nself.hidden_layers = t... | <|body_start_0|>
super(SimpleCNN, self).__init__()
cnn = []
for i in range(n_hidden_layers):
cnn.append(torch.nn.Conv2d(in_channels=n_in_channels, out_channels=n_kernels, kernel_size=kernel_size, bias=True, padding=int(kernel_size / 2)))
cnn.append(torch.nn.ReLU())
... | SimpleCNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleCNN:
def __init__(self, n_in_channels: int=1, n_hidden_layers: int=3, n_kernels: int=32, kernel_size: int=7):
"""Simple CNN with `n_hidden_layers`, `n_kernels`, and `kernel_size` as hyperparameters"""
<|body_0|>
def forward(self, x):
"""Apply CNN to input `x` o... | stack_v2_sparse_classes_10k_train_004353 | 2,028 | no_license | [
{
"docstring": "Simple CNN with `n_hidden_layers`, `n_kernels`, and `kernel_size` as hyperparameters",
"name": "__init__",
"signature": "def __init__(self, n_in_channels: int=1, n_hidden_layers: int=3, n_kernels: int=32, kernel_size: int=7)"
},
{
"docstring": "Apply CNN to input `x` of shape (N,... | 2 | stack_v2_sparse_classes_30k_train_005787 | Implement the Python class `SimpleCNN` described below.
Class description:
Implement the SimpleCNN class.
Method signatures and docstrings:
- def __init__(self, n_in_channels: int=1, n_hidden_layers: int=3, n_kernels: int=32, kernel_size: int=7): Simple CNN with `n_hidden_layers`, `n_kernels`, and `kernel_size` as hy... | Implement the Python class `SimpleCNN` described below.
Class description:
Implement the SimpleCNN class.
Method signatures and docstrings:
- def __init__(self, n_in_channels: int=1, n_hidden_layers: int=3, n_kernels: int=32, kernel_size: int=7): Simple CNN with `n_hidden_layers`, `n_kernels`, and `kernel_size` as hy... | 26ea3306ff989de94414d50708ae30171f48ef53 | <|skeleton|>
class SimpleCNN:
def __init__(self, n_in_channels: int=1, n_hidden_layers: int=3, n_kernels: int=32, kernel_size: int=7):
"""Simple CNN with `n_hidden_layers`, `n_kernels`, and `kernel_size` as hyperparameters"""
<|body_0|>
def forward(self, x):
"""Apply CNN to input `x` o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SimpleCNN:
def __init__(self, n_in_channels: int=1, n_hidden_layers: int=3, n_kernels: int=32, kernel_size: int=7):
"""Simple CNN with `n_hidden_layers`, `n_kernels`, and `kernel_size` as hyperparameters"""
super(SimpleCNN, self).__init__()
cnn = []
for i in range(n_hidden_laye... | the_stack_v2_python_sparse | Programming-in-Python-II/example_project/architectures.py | diabeticwizard10/programming-in-python | train | 0 | |
82e51e82ada853c5ccca92ef79246a9abd7920ba | [
"norep = [num for num, _ in groupby(nums)]\ntriples = zip(norep, norep[1:], norep[2:])\nreturn sum(((b > a) == (b > c) for a, b, c in triples)) + len(norep[:2])",
"norep = [num for num, _ in groupby(nums)]\nif len(norep) < 2:\n return len(norep)\ntriples = zip(norep, norep[1:], norep[2:])\nreturn 2 + sum((a < ... | <|body_start_0|>
norep = [num for num, _ in groupby(nums)]
triples = zip(norep, norep[1:], norep[2:])
return sum(((b > a) == (b > c) for a, b, c in triples)) + len(norep[:2])
<|end_body_0|>
<|body_start_1|>
norep = [num for num, _ in groupby(nums)]
if len(norep) < 2:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wiggleMaxLength(self, nums):
""":type nums: List[int] :rtype: int beats 44.44%"""
<|body_0|>
def wiggleMaxLength1(self, nums):
""":param nums: :return: beats 97.22%"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
norep = [num for num, ... | stack_v2_sparse_classes_10k_train_004354 | 704 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int beats 44.44%",
"name": "wiggleMaxLength",
"signature": "def wiggleMaxLength(self, nums)"
},
{
"docstring": ":param nums: :return: beats 97.22%",
"name": "wiggleMaxLength1",
"signature": "def wiggleMaxLength1(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003129 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleMaxLength(self, nums): :type nums: List[int] :rtype: int beats 44.44%
- def wiggleMaxLength1(self, nums): :param nums: :return: beats 97.22% | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleMaxLength(self, nums): :type nums: List[int] :rtype: int beats 44.44%
- def wiggleMaxLength1(self, nums): :param nums: :return: beats 97.22%
<|skeleton|>
class Solutio... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def wiggleMaxLength(self, nums):
""":type nums: List[int] :rtype: int beats 44.44%"""
<|body_0|>
def wiggleMaxLength1(self, nums):
""":param nums: :return: beats 97.22%"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def wiggleMaxLength(self, nums):
""":type nums: List[int] :rtype: int beats 44.44%"""
norep = [num for num, _ in groupby(nums)]
triples = zip(norep, norep[1:], norep[2:])
return sum(((b > a) == (b > c) for a, b, c in triples)) + len(norep[:2])
def wiggleMaxLength... | the_stack_v2_python_sparse | LeetCode/376_wiggle_subsequence.py | yao23/Machine_Learning_Playground | train | 12 | |
c60b5913ef4ddf2664966045fbe0baed96323909 | [
"result = ''\ntext = wikiText\nwhile True:\n startIdx = text.find('{{')\n if startIdx >= 0:\n result += text[:startIdx]\n endIdx = text.find('}}', startIdx)\n if endIdx >= 0:\n handled = False\n templateText = text[startIdx + 2:endIdx]\n if handler is not ... | <|body_start_0|>
result = ''
text = wikiText
while True:
startIdx = text.find('{{')
if startIdx >= 0:
result += text[:startIdx]
endIdx = text.find('}}', startIdx)
if endIdx >= 0:
handled = False
... | Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler. | TemplateParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateParser:
"""Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler."""
def parse(cls, wikiText, handler):
"""Parse the given wiki text... | stack_v2_sparse_classes_10k_train_004355 | 6,755 | no_license | [
{
"docstring": "Parse the given wiki text and substitute each template in the text using the specified template handler.",
"name": "parse",
"signature": "def parse(cls, wikiText, handler)"
},
{
"docstring": "Creates a :@link Template from the given text. That is, the template's name and paramete... | 2 | stack_v2_sparse_classes_30k_train_006677 | Implement the Python class `TemplateParser` described below.
Class description:
Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler.
Method signatures and docstrings:
- def... | Implement the Python class `TemplateParser` described below.
Class description:
Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler.
Method signatures and docstrings:
- def... | 58e12957dee8b4b18127df9daeb8825d8ada7923 | <|skeleton|>
class TemplateParser:
"""Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler."""
def parse(cls, wikiText, handler):
"""Parse the given wiki text... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TemplateParser:
"""Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler."""
def parse(cls, wikiText, handler):
"""Parse the given wiki text and substitu... | the_stack_v2_python_sparse | api/util/TemplateParser.py | oldeucryptoboi/wiktionary-parser | train | 0 |
5d7122dd24dd83aff2cba2f915cb76683e8e0927 | [
"d = {c: [-1, -1] for c in string.ascii_uppercase}\nres = 0\nfor i, c in enumerate(s):\n i0, i1 = d[c]\n res += (i - i1) * (i1 - i0)\n d[c] = [d[c][1], i]\nfor i0, i1 in d.values():\n res += (len(s) - i1) * (i1 - i0)\nreturn res",
"visited = set()\n\ndef dfs(i: int, j: int, d: Dict[str, int], u: int) ... | <|body_start_0|>
d = {c: [-1, -1] for c in string.ascii_uppercase}
res = 0
for i, c in enumerate(s):
i0, i1 = d[c]
res += (i - i1) * (i1 - i0)
d[c] = [d[c][1], i]
for i0, i1 in d.values():
res += (len(s) - i1) * (i1 - i0)
return res... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniqueLetterString(self, s: str) -> int:
"""O(N) 혹은 O(NlogN) 으로 줄일 수 있는 방법? 각 자리의 문자별로 생각해보자. 양 옆으로 동일한 문자가 또 나오기 전까지 확장할 수 있음. O(N) / O(1)"""
<|body_0|>
def uniqueLetterString(self, s: str) -> int:
"""DFS로 모든 케이스를 다 돌면서 계산하면 되긴함. O(N^2) / O(N^2) (S : s... | stack_v2_sparse_classes_10k_train_004356 | 1,871 | no_license | [
{
"docstring": "O(N) 혹은 O(NlogN) 으로 줄일 수 있는 방법? 각 자리의 문자별로 생각해보자. 양 옆으로 동일한 문자가 또 나오기 전까지 확장할 수 있음. O(N) / O(1)",
"name": "uniqueLetterString",
"signature": "def uniqueLetterString(self, s: str) -> int"
},
{
"docstring": "DFS로 모든 케이스를 다 돌면서 계산하면 되긴함. O(N^2) / O(N^2) (S : s 내 문자수) Time Limit Exce... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniqueLetterString(self, s: str) -> int: O(N) 혹은 O(NlogN) 으로 줄일 수 있는 방법? 각 자리의 문자별로 생각해보자. 양 옆으로 동일한 문자가 또 나오기 전까지 확장할 수 있음. O(N) / O(1)
- def uniqueLetterString(self, s: str... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniqueLetterString(self, s: str) -> int: O(N) 혹은 O(NlogN) 으로 줄일 수 있는 방법? 각 자리의 문자별로 생각해보자. 양 옆으로 동일한 문자가 또 나오기 전까지 확장할 수 있음. O(N) / O(1)
- def uniqueLetterString(self, s: str... | c26aef2a59e5cc2d9b0658b9c7386a43267ff8a1 | <|skeleton|>
class Solution:
def uniqueLetterString(self, s: str) -> int:
"""O(N) 혹은 O(NlogN) 으로 줄일 수 있는 방법? 각 자리의 문자별로 생각해보자. 양 옆으로 동일한 문자가 또 나오기 전까지 확장할 수 있음. O(N) / O(1)"""
<|body_0|>
def uniqueLetterString(self, s: str) -> int:
"""DFS로 모든 케이스를 다 돌면서 계산하면 되긴함. O(N^2) / O(N^2) (S : s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def uniqueLetterString(self, s: str) -> int:
"""O(N) 혹은 O(NlogN) 으로 줄일 수 있는 방법? 각 자리의 문자별로 생각해보자. 양 옆으로 동일한 문자가 또 나오기 전까지 확장할 수 있음. O(N) / O(1)"""
d = {c: [-1, -1] for c in string.ascii_uppercase}
res = 0
for i, c in enumerate(s):
i0, i1 = d[c]
... | the_stack_v2_python_sparse | Leetcode/828.py | hanwgyu/algorithm_problem_solving | train | 5 | |
63bb73a8defaccea5b30bc05794977232b553b6a | [
"if self.search is None:\n return\nself.view.set_viewport_position(self.viewport)\nself.search.reset()\nmatches = self.search.find(text, self.autocorrect)\nself.search.add_matches(matches)\nrelevant_matches = self.search.forwards(update_cursors=False, viewport=self.visible_region, next_only=self.jump_only)\nif s... | <|body_start_0|>
if self.search is None:
return
self.view.set_viewport_position(self.viewport)
self.search.reset()
matches = self.search.find(text, self.autocorrect)
self.search.add_matches(matches)
relevant_matches = self.search.forwards(update_cursors=False,... | Creates the Search Input Panel VisualMode: This would stretch each cursor to the matched word Doesn't perform highlighting MultiSelect: This shows only the relevant words (ones cursors could go to) Doesn't perform highlighting = args append: reset highlights first? or add to them jump_only: doesn't mess with highlighti... | HighlightPanelCommand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HighlightPanelCommand:
"""Creates the Search Input Panel VisualMode: This would stretch each cursor to the matched word Doesn't perform highlighting MultiSelect: This shows only the relevant words (ones cursors could go to) Doesn't perform highlighting = args append: reset highlights first? or ad... | stack_v2_sparse_classes_10k_train_004357 | 31,297 | permissive | [
{
"docstring": "Event: User typing",
"name": "_on_change",
"signature": "def _on_change(self, text)"
},
{
"docstring": "Event: user Input",
"name": "_on_done",
"signature": "def _on_done(self, text)"
},
{
"docstring": "Event: user abort",
"name": "_on_cancel",
"signature"... | 4 | stack_v2_sparse_classes_30k_train_000097 | Implement the Python class `HighlightPanelCommand` described below.
Class description:
Creates the Search Input Panel VisualMode: This would stretch each cursor to the matched word Doesn't perform highlighting MultiSelect: This shows only the relevant words (ones cursors could go to) Doesn't perform highlighting = arg... | Implement the Python class `HighlightPanelCommand` described below.
Class description:
Creates the Search Input Panel VisualMode: This would stretch each cursor to the matched word Doesn't perform highlighting MultiSelect: This shows only the relevant words (ones cursors could go to) Doesn't perform highlighting = arg... | 91417d02554b89cd322d16940f59d0dd781c8001 | <|skeleton|>
class HighlightPanelCommand:
"""Creates the Search Input Panel VisualMode: This would stretch each cursor to the matched word Doesn't perform highlighting MultiSelect: This shows only the relevant words (ones cursors could go to) Doesn't perform highlighting = args append: reset highlights first? or ad... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HighlightPanelCommand:
"""Creates the Search Input Panel VisualMode: This would stretch each cursor to the matched word Doesn't perform highlighting MultiSelect: This shows only the relevant words (ones cursors could go to) Doesn't perform highlighting = args append: reset highlights first? or add to them jum... | the_stack_v2_python_sparse | highlight.py | Saevon/config-sublime | train | 0 |
e148eb9adb8ce29dbc9be62fee7af8f627ec8b18 | [
"super().__init__()\nself.N = N\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(input_dim=target_vocab, output_dim=dm)\nself.positional_encoding = positional_encoding(max_seq_len, dm)\nself.blocks = [DecoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]\nself.dropout = tf.keras.layers.Dropout(rate=dro... | <|body_start_0|>
super().__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(input_dim=target_vocab, output_dim=dm)
self.positional_encoding = positional_encoding(max_seq_len, dm)
self.blocks = [DecoderBlock(dm, h, hidden, drop_rate) for _ in ran... | Creates the decoder for a transformer | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Creates the decoder for a transformer"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor"""
<|body_0|>
def call(self, x, encoder_output, training, look_ahead_mask, padding_mask):
"""Returns: a tenso... | stack_v2_sparse_classes_10k_train_004358 | 2,240 | no_license | [
{
"docstring": "Class constructor",
"name": "__init__",
"signature": "def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1)"
},
{
"docstring": "Returns: a tensor of shape (batch, target_seq_len, dm) containing the decoder output",
"name": "call",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_006702 | Implement the Python class `Decoder` described below.
Class description:
Creates the decoder for a transformer
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): Class constructor
- def call(self, x, encoder_output, training, look_ahead_mask, padding_ma... | Implement the Python class `Decoder` described below.
Class description:
Creates the decoder for a transformer
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): Class constructor
- def call(self, x, encoder_output, training, look_ahead_mask, padding_ma... | 161e33b23d398d7d01ad0d7740b78dda3f27e787 | <|skeleton|>
class Decoder:
"""Creates the decoder for a transformer"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor"""
<|body_0|>
def call(self, x, encoder_output, training, look_ahead_mask, padding_mask):
"""Returns: a tenso... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Creates the decoder for a transformer"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor"""
super().__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(input_dim=target_vocab... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/10-transformer_decoder.py | felipeserna/holbertonschool-machine_learning | train | 0 |
000cf5339989b406fa2b55b1a9e9aefe22dfdb95 | [
"valid, message = json_validate(drange, {'type': 'object', 'properties': {'lower': {'$ref': '#/pScheduler/Duration'}, 'upper': {'$ref': '#/pScheduler/Duration'}}, 'additionalProperties': False, 'required': ['lower', 'upper']})\nif not valid:\n raise ValueError('Invalid duration range: %s' % message)\nself.lower_... | <|body_start_0|>
valid, message = json_validate(drange, {'type': 'object', 'properties': {'lower': {'$ref': '#/pScheduler/Duration'}, 'upper': {'$ref': '#/pScheduler/Duration'}}, 'additionalProperties': False, 'required': ['lower', 'upper']})
if not valid:
raise ValueError('Invalid duration ... | Range of durations | DurationRange | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DurationRange:
"""Range of durations"""
def __init__(self, drange):
"""Construct a range from a JSON DurationRange."""
<|body_0|>
def __contains__(self, duration):
"""See if the range contains the specified duration, which can be a timedelta or ISO8601 string."""... | stack_v2_sparse_classes_10k_train_004359 | 2,808 | permissive | [
{
"docstring": "Construct a range from a JSON DurationRange.",
"name": "__init__",
"signature": "def __init__(self, drange)"
},
{
"docstring": "See if the range contains the specified duration, which can be a timedelta or ISO8601 string.",
"name": "__contains__",
"signature": "def __cont... | 3 | stack_v2_sparse_classes_30k_train_006610 | Implement the Python class `DurationRange` described below.
Class description:
Range of durations
Method signatures and docstrings:
- def __init__(self, drange): Construct a range from a JSON DurationRange.
- def __contains__(self, duration): See if the range contains the specified duration, which can be a timedelta ... | Implement the Python class `DurationRange` described below.
Class description:
Range of durations
Method signatures and docstrings:
- def __init__(self, drange): Construct a range from a JSON DurationRange.
- def __contains__(self, duration): See if the range contains the specified duration, which can be a timedelta ... | f6d04c0455e5be4d490df16ec1acb377f9025d9f | <|skeleton|>
class DurationRange:
"""Range of durations"""
def __init__(self, drange):
"""Construct a range from a JSON DurationRange."""
<|body_0|>
def __contains__(self, duration):
"""See if the range contains the specified duration, which can be a timedelta or ISO8601 string."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DurationRange:
"""Range of durations"""
def __init__(self, drange):
"""Construct a range from a JSON DurationRange."""
valid, message = json_validate(drange, {'type': 'object', 'properties': {'lower': {'$ref': '#/pScheduler/Duration'}, 'upper': {'$ref': '#/pScheduler/Duration'}}, 'additio... | the_stack_v2_python_sparse | python-pscheduler/pscheduler/pscheduler/durationrange.py | perfsonar/pscheduler | train | 53 |
8b085fff21261152e2cd43b3d0704ed56eb23550 | [
"parkDict = self.getDictBykey(Index(self.Session).getParkingBaseDataTree().json(), 'name', parkName)\nself.url = '/mgr/park/park_redlist/add.do'\ndata = {'redlistParam': carNum, 'parkIds': parkDict['value']}\nre = self.post(self.api, data=data, headers=form_headers)\nreturn re.json()",
"WhilelistDict = self.getDi... | <|body_start_0|>
parkDict = self.getDictBykey(Index(self.Session).getParkingBaseDataTree().json(), 'name', parkName)
self.url = '/mgr/park/park_redlist/add.do'
data = {'redlistParam': carNum, 'parkIds': parkDict['value']}
re = self.post(self.api, data=data, headers=form_headers)
... | 白名单 | ParkWhitelist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParkWhitelist:
"""白名单"""
def addWhitelist(self, parkName, carNum):
"""录入白名单"""
<|body_0|>
def delWhilelist(self, carNum):
"""删除白名单规则"""
<|body_1|>
def getWhilelistRuleList(self):
"""获取白名单规则列表"""
<|body_2|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_10k_train_004360 | 13,467 | no_license | [
{
"docstring": "录入白名单",
"name": "addWhitelist",
"signature": "def addWhitelist(self, parkName, carNum)"
},
{
"docstring": "删除白名单规则",
"name": "delWhilelist",
"signature": "def delWhilelist(self, carNum)"
},
{
"docstring": "获取白名单规则列表",
"name": "getWhilelistRuleList",
"signa... | 3 | stack_v2_sparse_classes_30k_train_005037 | Implement the Python class `ParkWhitelist` described below.
Class description:
白名单
Method signatures and docstrings:
- def addWhitelist(self, parkName, carNum): 录入白名单
- def delWhilelist(self, carNum): 删除白名单规则
- def getWhilelistRuleList(self): 获取白名单规则列表 | Implement the Python class `ParkWhitelist` described below.
Class description:
白名单
Method signatures and docstrings:
- def addWhitelist(self, parkName, carNum): 录入白名单
- def delWhilelist(self, carNum): 删除白名单规则
- def getWhilelistRuleList(self): 获取白名单规则列表
<|skeleton|>
class ParkWhitelist:
"""白名单"""
def addWhit... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class ParkWhitelist:
"""白名单"""
def addWhitelist(self, parkName, carNum):
"""录入白名单"""
<|body_0|>
def delWhilelist(self, carNum):
"""删除白名单规则"""
<|body_1|>
def getWhilelistRuleList(self):
"""获取白名单规则列表"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ParkWhitelist:
"""白名单"""
def addWhitelist(self, parkName, carNum):
"""录入白名单"""
parkDict = self.getDictBykey(Index(self.Session).getParkingBaseDataTree().json(), 'name', parkName)
self.url = '/mgr/park/park_redlist/add.do'
data = {'redlistParam': carNum, 'parkIds': parkDict... | the_stack_v2_python_sparse | Api/parkingManage_service/carTypeManage_service/carTypeConfig.py | oyebino/pomp_api | train | 1 |
52f8ab59a6c17c6fdd3c26f46e564645874801f2 | [
"try:\n applet = Applet().load(id=applet, force=True)\nexcept:\n raise ValidationException(message='Invalid Applet ID', field='applet')\nassignmentsCollection = Collection().findOne({'name': 'Assignments'})\nif not assignmentsCollection:\n Collection().createCollection('Assignments')\ntry:\n assignment ... | <|body_start_0|>
try:
applet = Applet().load(id=applet, force=True)
except:
raise ValidationException(message='Invalid Applet ID', field='applet')
assignmentsCollection = Collection().findOne({'name': 'Assignments'})
if not assignmentsCollection:
Colle... | Assignments are access-controlled Folders, each of which contains managerially-controlled Applet Folders. | Assignment | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Assignment:
"""Assignments are access-controlled Folders, each of which contains managerially-controlled Applet Folders."""
def create(self, applet, user):
"""Create an Assignment for a given Applet, returning an existing Assignment if one or more exists. :param applet: The ID of the... | stack_v2_sparse_classes_10k_train_004361 | 8,452 | permissive | [
{
"docstring": "Create an Assignment for a given Applet, returning an existing Assignment if one or more exists. :param applet: The ID of the Applet for which to find Assignments. :type applet: str :param user: User :type user: User :returns: New Assignments",
"name": "create",
"signature": "def create(... | 3 | stack_v2_sparse_classes_30k_train_002151 | Implement the Python class `Assignment` described below.
Class description:
Assignments are access-controlled Folders, each of which contains managerially-controlled Applet Folders.
Method signatures and docstrings:
- def create(self, applet, user): Create an Assignment for a given Applet, returning an existing Assig... | Implement the Python class `Assignment` described below.
Class description:
Assignments are access-controlled Folders, each of which contains managerially-controlled Applet Folders.
Method signatures and docstrings:
- def create(self, applet, user): Create an Assignment for a given Applet, returning an existing Assig... | 96b76353e59377c920570fca767fe4faa84965f7 | <|skeleton|>
class Assignment:
"""Assignments are access-controlled Folders, each of which contains managerially-controlled Applet Folders."""
def create(self, applet, user):
"""Create an Assignment for a given Applet, returning an existing Assignment if one or more exists. :param applet: The ID of the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Assignment:
"""Assignments are access-controlled Folders, each of which contains managerially-controlled Applet Folders."""
def create(self, applet, user):
"""Create an Assignment for a given Applet, returning an existing Assignment if one or more exists. :param applet: The ID of the Applet for w... | the_stack_v2_python_sparse | girderformindlogger/models/assignment.py | jj105/mindlogger-app-backend | train | 0 |
e07e35976407d5147f6c4b3c88d7e9014483afa4 | [
"if not cov.shape[0] == cov.shape[1]:\n raise ValueError('Covariance matrix is not square.')\nif not mean.shape[0] == cov.shape[0]:\n raise ValueError('Dimension mismatch between mean and covariance.')\nif not torch.allclose(cov, cov.transpose(-1, -2)):\n raise ValueError('Covariance matrix is not symmetri... | <|body_start_0|>
if not cov.shape[0] == cov.shape[1]:
raise ValueError('Covariance matrix is not square.')
if not mean.shape[0] == cov.shape[0]:
raise ValueError('Dimension mismatch between mean and covariance.')
if not torch.allclose(cov, cov.transpose(-1, -2)):
... | Engine for qMC sampling from a multivariate Normal `N(\\mu, \\Sigma)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> mean = torch.tensor([1.0, 2.0]) >>> cov = torch.tensor([... | MultivariateNormalQMCEngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultivariateNormalQMCEngine:
"""Engine for qMC sampling from a multivariate Normal `N(\\mu, \\Sigma)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> m... | stack_v2_sparse_classes_10k_train_004362 | 6,555 | permissive | [
{
"docstring": "Engine for qMC sampling from a multivariate Normal `N(\\\\mu, \\\\Sigma)`. Args: mean: The mean vector. cov: The covariance matrix. seed: The seed with which to seed the random number generator of the underlying SobolEngine. inv_transform: If True, use inverse transform instead of Box-Muller.",
... | 2 | stack_v2_sparse_classes_30k_train_004755 | Implement the Python class `MultivariateNormalQMCEngine` described below.
Class description:
Engine for qMC sampling from a multivariate Normal `N(\\mu, \\Sigma)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, s... | Implement the Python class `MultivariateNormalQMCEngine` described below.
Class description:
Engine for qMC sampling from a multivariate Normal `N(\\mu, \\Sigma)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, s... | 4cc5ed59b2e8a9c780f786830c548e05cc74d53c | <|skeleton|>
class MultivariateNormalQMCEngine:
"""Engine for qMC sampling from a multivariate Normal `N(\\mu, \\Sigma)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> m... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultivariateNormalQMCEngine:
"""Engine for qMC sampling from a multivariate Normal `N(\\mu, \\Sigma)`. By default, this implementation uses Box-Muller transformed Sobol samples following pg. 123 in [Pages2018numprob]_. To use the inverse transform instead, set `inv_transform=True`. Example: >>> mean = torch.t... | the_stack_v2_python_sparse | botorch/sampling/qmc.py | pytorch/botorch | train | 2,891 |
ae85a0038e9bc4120cbd847f29a14d052de53fbc | [
"super(MultiHeadedAttention, self).__init__()\nassert d_model % h == 0\nself.d_k = d_model // h\nself.h = h\nself.linears = clones(nn.Linear(d_model, d_model), 4)\nself.attn = None\nself.dropout = nn.Dropout(p=dropout)",
"if mask is not None:\n mask = mask.unsqueeze(1)\nnbatches = query.size(0)\nif layer_past ... | <|body_start_0|>
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_model), 4)
self.attn = None
self.dropout = nn.Dropout(p=dropout)
<|end_body_0|>
<|body_start_1|>
... | MultiHeadedAttention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def forward(self, query, key, value, mask=None, layer_past=None):
"""Implements Figure 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_10k_train_004363 | 16,634 | permissive | [
{
"docstring": "Take in model size and number of heads.",
"name": "__init__",
"signature": "def __init__(self, h, d_model, dropout=0.1)"
},
{
"docstring": "Implements Figure 2",
"name": "forward",
"signature": "def forward(self, query, key, value, mask=None, layer_past=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003195 | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def forward(self, query, key, value, mask=None, layer_past=None): I... | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def forward(self, query, key, value, mask=None, layer_past=None): I... | 6a774be5c27b1a5eecf4bcfff55249acf6c2fd5f | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def forward(self, query, key, value, mask=None, layer_past=None):
"""Implements Figure 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_mo... | the_stack_v2_python_sparse | captioning/models/cachedTransformer.py | ruotianluo/ImageCaptioning.pytorch | train | 1,247 | |
04c9db5252c3ebd00174b92e2603904182e33a68 | [
"if user_id == 'me':\n user = auth.get_current_user()\n if not user:\n return self.error('not authenticated', 401)\nelse:\n raise NotImplementedError\nuser.options = list(ItemOption.query.filter(ItemOption.item_id == user.id))\nreturn self.respond_with_schema(user_schema, user)",
"if user_id == 'm... | <|body_start_0|>
if user_id == 'me':
user = auth.get_current_user()
if not user:
return self.error('not authenticated', 401)
else:
raise NotImplementedError
user.options = list(ItemOption.query.filter(ItemOption.item_id == user.id))
ret... | UserDetailsResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserDetailsResource:
def get(self, user_id: str):
"""Return information on a user."""
<|body_0|>
def put(self, user_id: str):
"""Return information on a user."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if user_id == 'me':
user = aut... | stack_v2_sparse_classes_10k_train_004364 | 1,582 | permissive | [
{
"docstring": "Return information on a user.",
"name": "get",
"signature": "def get(self, user_id: str)"
},
{
"docstring": "Return information on a user.",
"name": "put",
"signature": "def put(self, user_id: str)"
}
] | 2 | null | Implement the Python class `UserDetailsResource` described below.
Class description:
Implement the UserDetailsResource class.
Method signatures and docstrings:
- def get(self, user_id: str): Return information on a user.
- def put(self, user_id: str): Return information on a user. | Implement the Python class `UserDetailsResource` described below.
Class description:
Implement the UserDetailsResource class.
Method signatures and docstrings:
- def get(self, user_id: str): Return information on a user.
- def put(self, user_id: str): Return information on a user.
<|skeleton|>
class UserDetailsResou... | 6d4a490c19ebe406b551641a022ca08f26c21fcb | <|skeleton|>
class UserDetailsResource:
def get(self, user_id: str):
"""Return information on a user."""
<|body_0|>
def put(self, user_id: str):
"""Return information on a user."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserDetailsResource:
def get(self, user_id: str):
"""Return information on a user."""
if user_id == 'me':
user = auth.get_current_user()
if not user:
return self.error('not authenticated', 401)
else:
raise NotImplementedError
... | the_stack_v2_python_sparse | zeus/api/resources/user_details.py | getsentry/zeus | train | 222 | |
b597bf9e047f31939535f5babc8efdc681668c97 | [
"self.sources = sources\nself.max_sentence_length = max_sentence_length\nself.limit = limit",
"for source in self.sources:\n try:\n source.seek(0)\n for line in itertools.islice(source, self.limit):\n line = to_unicode(line)\n line = list(line.strip().replace(' ', ''))\n ... | <|body_start_0|>
self.sources = sources
self.max_sentence_length = max_sentence_length
self.limit = limit
<|end_body_0|>
<|body_start_1|>
for source in self.sources:
try:
source.seek(0)
for line in itertools.islice(source, self.limit):
... | Simple format: one sentence = one line; words already preprocessed and separated by whitespace. | MyLineSentence | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyLineSentence:
"""Simple format: one sentence = one line; words already preprocessed and separated by whitespace."""
def __init__(self, sources, max_sentence_length=MAX_WORDS_IN_BATCH, limit=None):
"""`source` can be either a string or a file object. Clip the file to the first `limi... | stack_v2_sparse_classes_10k_train_004365 | 4,034 | no_license | [
{
"docstring": "`source` can be either a string or a file object. Clip the file to the first `limit` lines (or no clipped if limit is None, the default).",
"name": "__init__",
"signature": "def __init__(self, sources, max_sentence_length=MAX_WORDS_IN_BATCH, limit=None)"
},
{
"docstring": "Iterat... | 2 | stack_v2_sparse_classes_30k_train_001914 | Implement the Python class `MyLineSentence` described below.
Class description:
Simple format: one sentence = one line; words already preprocessed and separated by whitespace.
Method signatures and docstrings:
- def __init__(self, sources, max_sentence_length=MAX_WORDS_IN_BATCH, limit=None): `source` can be either a ... | Implement the Python class `MyLineSentence` described below.
Class description:
Simple format: one sentence = one line; words already preprocessed and separated by whitespace.
Method signatures and docstrings:
- def __init__(self, sources, max_sentence_length=MAX_WORDS_IN_BATCH, limit=None): `source` can be either a ... | abadb44b442aba5c579431e8697d11cff84658a6 | <|skeleton|>
class MyLineSentence:
"""Simple format: one sentence = one line; words already preprocessed and separated by whitespace."""
def __init__(self, sources, max_sentence_length=MAX_WORDS_IN_BATCH, limit=None):
"""`source` can be either a string or a file object. Clip the file to the first `limi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MyLineSentence:
"""Simple format: one sentence = one line; words already preprocessed and separated by whitespace."""
def __init__(self, sources, max_sentence_length=MAX_WORDS_IN_BATCH, limit=None):
"""`source` can be either a string or a file object. Clip the file to the first `limit` lines (or ... | the_stack_v2_python_sparse | NLPCCKBQAModels/word2vec/chars2vec.py | JuneTse/NLPCCKBQAProj | train | 1 |
609bbe9b5746cc531b44ce7089af343a05ce9a10 | [
"self.__config = config\nself.__section = section\nself.__options = options\nself.__guidata = guidata\nself.__initialised = True",
"if name not in ['_PreferencesSection__section', '_PreferencesSection__options', '_PreferencesSection__config', '_PreferencesSection__initialised', '_PreferencesSection__get_option', ... | <|body_start_0|>
self.__config = config
self.__section = section
self.__options = options
self.__guidata = guidata
self.__initialised = True
<|end_body_0|>
<|body_start_1|>
if name not in ['_PreferencesSection__section', '_PreferencesSection__options', '_PreferencesSecti... | Preferences Section Helper Class | _PreferencesSection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _PreferencesSection:
"""Preferences Section Helper Class"""
def __init__(self, config, section, options, guidata):
"""Class constructor"""
<|body_0|>
def __getattr__(self, name):
"""Get attribute method overload for accesing options"""
<|body_1|>
def... | stack_v2_sparse_classes_10k_train_004366 | 10,591 | permissive | [
{
"docstring": "Class constructor",
"name": "__init__",
"signature": "def __init__(self, config, section, options, guidata)"
},
{
"docstring": "Get attribute method overload for accesing options",
"name": "__getattr__",
"signature": "def __getattr__(self, name)"
},
{
"docstring":... | 6 | stack_v2_sparse_classes_30k_train_004362 | Implement the Python class `_PreferencesSection` described below.
Class description:
Preferences Section Helper Class
Method signatures and docstrings:
- def __init__(self, config, section, options, guidata): Class constructor
- def __getattr__(self, name): Get attribute method overload for accesing options
- def __s... | Implement the Python class `_PreferencesSection` described below.
Class description:
Preferences Section Helper Class
Method signatures and docstrings:
- def __init__(self, config, section, options, guidata): Class constructor
- def __getattr__(self, name): Get attribute method overload for accesing options
- def __s... | 9f951a08770e99ffd701a1994ba948aa8014f2af | <|skeleton|>
class _PreferencesSection:
"""Preferences Section Helper Class"""
def __init__(self, config, section, options, guidata):
"""Class constructor"""
<|body_0|>
def __getattr__(self, name):
"""Get attribute method overload for accesing options"""
<|body_1|>
def... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _PreferencesSection:
"""Preferences Section Helper Class"""
def __init__(self, config, section, options, guidata):
"""Class constructor"""
self.__config = config
self.__section = section
self.__options = options
self.__guidata = guidata
self.__initialised =... | the_stack_v2_python_sparse | evogtk/gui/preferences.py | olivergs/evogtk | train | 0 |
d67bc24e6c0aa772a829f8636e077c6afe9236a2 | [
"if method == 'BCR764':\n a = zeros(4)\n a[0] = 0.0\n a[1] = 1.5171479707207227\n a[2] = -2.0342959414414454\n a[3] = 1.5171479707207227\n b = zeros(4)\n b[0] = 0.5600879810924619\n b[1] = -0.06008798109246194\n b[2] = -0.06008798109246194\n b[3] = 0.5600879810924619\n z = zeros(6)\... | <|body_start_0|>
if method == 'BCR764':
a = zeros(4)
a[0] = 0.0
a[1] = 1.5171479707207227
a[2] = -2.0342959414414454
a[3] = 1.5171479707207227
b = zeros(4)
b[0] = 0.5600879810924619
b[1] = -0.06008798109246194
... | ProcessingSplittingParameters | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessingSplittingParameters:
def build(self, method):
""":param method: A string specifying the method for time integration. :return: Four arrays :math:`a`, :math:`b` and :math:`y`, :math:`z`. ====== ======= ================= ========= Method Order Authors Reference ====== ======= ====... | stack_v2_sparse_classes_10k_train_004367 | 3,691 | permissive | [
{
"docstring": ":param method: A string specifying the method for time integration. :return: Four arrays :math:`a`, :math:`b` and :math:`y`, :math:`z`. ====== ======= ================= ========= Method Order Authors Reference ====== ======= ================= ========= BCR764 (7,6,4) Blanes/Casas/Ros [1]_ table ... | 2 | null | Implement the Python class `ProcessingSplittingParameters` described below.
Class description:
Implement the ProcessingSplittingParameters class.
Method signatures and docstrings:
- def build(self, method): :param method: A string specifying the method for time integration. :return: Four arrays :math:`a`, :math:`b` a... | Implement the Python class `ProcessingSplittingParameters` described below.
Class description:
Implement the ProcessingSplittingParameters class.
Method signatures and docstrings:
- def build(self, method): :param method: A string specifying the method for time integration. :return: Four arrays :math:`a`, :math:`b` a... | 225b5dd9b1af1998bd40b5f6467ee959292b6a83 | <|skeleton|>
class ProcessingSplittingParameters:
def build(self, method):
""":param method: A string specifying the method for time integration. :return: Four arrays :math:`a`, :math:`b` and :math:`y`, :math:`z`. ====== ======= ================= ========= Method Order Authors Reference ====== ======= ====... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProcessingSplittingParameters:
def build(self, method):
""":param method: A string specifying the method for time integration. :return: Four arrays :math:`a`, :math:`b` and :math:`y`, :math:`z`. ====== ======= ================= ========= Method Order Authors Reference ====== ======= ================= ... | the_stack_v2_python_sparse | WaveBlocksND/ProcessingSplittingParameters.py | WaveBlocks/WaveBlocksND | train | 4 | |
b8b5162c54707bf94e61ba9396e4091258b18695 | [
"if positive_fraction < 0 or positive_fraction > 1:\n raise ValueError('positive_fraction should be in range [0,1]. Received: %s.' % positive_fraction)\nself._positive_fraction = positive_fraction",
"if len(indicator.get_shape().as_list()) != 1:\n raise ValueError('indicator must be 1 dimensional, got a ten... | <|body_start_0|>
if positive_fraction < 0 or positive_fraction > 1:
raise ValueError('positive_fraction should be in range [0,1]. Received: %s.' % positive_fraction)
self._positive_fraction = positive_fraction
<|end_body_0|>
<|body_start_1|>
if len(indicator.get_shape().as_list()) !... | Subsamples minibatches to a desired balance of positives and negatives. | BalancedPositiveNegativeSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BalancedPositiveNegativeSampler:
"""Subsamples minibatches to a desired balance of positives and negatives."""
def __init__(self, positive_fraction=0.5):
"""Constructs a minibatch sampler. Args: positive_fraction: desired fraction of positive examples (scalar in [0,1]) in the batch. ... | stack_v2_sparse_classes_10k_train_004368 | 4,434 | permissive | [
{
"docstring": "Constructs a minibatch sampler. Args: positive_fraction: desired fraction of positive examples (scalar in [0,1]) in the batch. Raises: ValueError: if positive_fraction < 0, or positive_fraction > 1",
"name": "__init__",
"signature": "def __init__(self, positive_fraction=0.5)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_006496 | Implement the Python class `BalancedPositiveNegativeSampler` described below.
Class description:
Subsamples minibatches to a desired balance of positives and negatives.
Method signatures and docstrings:
- def __init__(self, positive_fraction=0.5): Constructs a minibatch sampler. Args: positive_fraction: desired fract... | Implement the Python class `BalancedPositiveNegativeSampler` described below.
Class description:
Subsamples minibatches to a desired balance of positives and negatives.
Method signatures and docstrings:
- def __init__(self, positive_fraction=0.5): Constructs a minibatch sampler. Args: positive_fraction: desired fract... | 39272caea30ab01faa3795156af76a08aaf1455f | <|skeleton|>
class BalancedPositiveNegativeSampler:
"""Subsamples minibatches to a desired balance of positives and negatives."""
def __init__(self, positive_fraction=0.5):
"""Constructs a minibatch sampler. Args: positive_fraction: desired fraction of positive examples (scalar in [0,1]) in the batch. ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BalancedPositiveNegativeSampler:
"""Subsamples minibatches to a desired balance of positives and negatives."""
def __init__(self, positive_fraction=0.5):
"""Constructs a minibatch sampler. Args: positive_fraction: desired fraction of positive examples (scalar in [0,1]) in the batch. Raises: Value... | the_stack_v2_python_sparse | core/balanced_positive_negative_sampler.py | ambakick/Person-Detection-and-Tracking | train | 262 |
87c5dd54ebe8d2f19b1f2a6e92fceb38cb1234fa | [
"url = utils.urljoin(self.base_path, self.id, 'root')\nresp = session.post(url)\nreturn resp.json()['user']",
"url = utils.urljoin(self.base_path, self.id, 'root')\nresp = session.get(url)\nreturn resp.json()['rootEnabled']",
"body = {'restart': {}}\nurl = utils.urljoin(self.base_path, self.id, 'action')\nsessi... | <|body_start_0|>
url = utils.urljoin(self.base_path, self.id, 'root')
resp = session.post(url)
return resp.json()['user']
<|end_body_0|>
<|body_start_1|>
url = utils.urljoin(self.base_path, self.id, 'root')
resp = session.get(url)
return resp.json()['rootEnabled']
<|end_... | Instance | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Instance:
def enable_root_user(self, session):
"""Enable login for the root user. This operation enables login from any host for the root user and provides the user with a generated root password. :param session: The session to use for making this request. :type session: :class:`~keyston... | stack_v2_sparse_classes_10k_train_004369 | 3,825 | permissive | [
{
"docstring": "Enable login for the root user. This operation enables login from any host for the root user and provides the user with a generated root password. :param session: The session to use for making this request. :type session: :class:`~keystoneauth1.adapter.Adapter` :returns: A dictionary with keys `... | 5 | stack_v2_sparse_classes_30k_val_000349 | Implement the Python class `Instance` described below.
Class description:
Implement the Instance class.
Method signatures and docstrings:
- def enable_root_user(self, session): Enable login for the root user. This operation enables login from any host for the root user and provides the user with a generated root pass... | Implement the Python class `Instance` described below.
Class description:
Implement the Instance class.
Method signatures and docstrings:
- def enable_root_user(self, session): Enable login for the root user. This operation enables login from any host for the root user and provides the user with a generated root pass... | d474eb84c605c429bb9cccb166cabbdd1654d73c | <|skeleton|>
class Instance:
def enable_root_user(self, session):
"""Enable login for the root user. This operation enables login from any host for the root user and provides the user with a generated root password. :param session: The session to use for making this request. :type session: :class:`~keyston... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Instance:
def enable_root_user(self, session):
"""Enable login for the root user. This operation enables login from any host for the root user and provides the user with a generated root password. :param session: The session to use for making this request. :type session: :class:`~keystoneauth1.adapter... | the_stack_v2_python_sparse | openstack/database/v1/instance.py | openstack/openstacksdk | train | 124 | |
ff1544a50011f4fa6920b71509e27f9a3a0b1062 | [
"if '_xml_ns' in kwargs:\n self._xml_ns = kwargs['_xml_ns']\nif '_xml_ns_key' in kwargs:\n self._xml_ns_key = kwargs['_xml_ns_key']\nself.AntCoordFrame = AntCoordFrame\nself.AntPhaseCenter = AntPhaseCenter\nself.AntPattern = AntPattern\nsuper(AntennaType, self).__init__(**kwargs)",
"if self.AntCoordFrame is... | <|body_start_0|>
if '_xml_ns' in kwargs:
self._xml_ns = kwargs['_xml_ns']
if '_xml_ns_key' in kwargs:
self._xml_ns_key = kwargs['_xml_ns_key']
self.AntCoordFrame = AntCoordFrame
self.AntPhaseCenter = AntPhaseCenter
self.AntPattern = AntPattern
supe... | Parameters that describe the transmit and receive antennas used to collect the signal array(s). | AntennaType | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AntennaType:
"""Parameters that describe the transmit and receive antennas used to collect the signal array(s)."""
def __init__(self, AntCoordFrame=None, AntPhaseCenter=None, AntPattern=None, **kwargs):
"""Parameters ---------- AntCoordFrame : List[AntCoordFrameType] AntPhaseCenter :... | stack_v2_sparse_classes_10k_train_004370 | 7,511 | permissive | [
{
"docstring": "Parameters ---------- AntCoordFrame : List[AntCoordFrameType] AntPhaseCenter : List[AntPhaseCenterType] AntPattern : List[AntPatternType] kwargs",
"name": "__init__",
"signature": "def __init__(self, AntCoordFrame=None, AntPhaseCenter=None, AntPattern=None, **kwargs)"
},
{
"docst... | 4 | null | Implement the Python class `AntennaType` described below.
Class description:
Parameters that describe the transmit and receive antennas used to collect the signal array(s).
Method signatures and docstrings:
- def __init__(self, AntCoordFrame=None, AntPhaseCenter=None, AntPattern=None, **kwargs): Parameters ----------... | Implement the Python class `AntennaType` described below.
Class description:
Parameters that describe the transmit and receive antennas used to collect the signal array(s).
Method signatures and docstrings:
- def __init__(self, AntCoordFrame=None, AntPhaseCenter=None, AntPattern=None, **kwargs): Parameters ----------... | de1b1886f161a83b6c89aadc7a2c7cfc4892ef81 | <|skeleton|>
class AntennaType:
"""Parameters that describe the transmit and receive antennas used to collect the signal array(s)."""
def __init__(self, AntCoordFrame=None, AntPhaseCenter=None, AntPattern=None, **kwargs):
"""Parameters ---------- AntCoordFrame : List[AntCoordFrameType] AntPhaseCenter :... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AntennaType:
"""Parameters that describe the transmit and receive antennas used to collect the signal array(s)."""
def __init__(self, AntCoordFrame=None, AntPhaseCenter=None, AntPattern=None, **kwargs):
"""Parameters ---------- AntCoordFrame : List[AntCoordFrameType] AntPhaseCenter : List[AntPhas... | the_stack_v2_python_sparse | sarpy/io/received/crsd1_elements/Antenna.py | ngageoint/sarpy | train | 192 |
5b37a4471322a633d7ad60d4606ad9a5f6aaca7a | [
"self.maze = maze\nself.rat_1 = rat_1\nself.rat_2 = rat_2\nself.num_sprouts_left = 0\nfor i in range(len(self.maze)):\n row = self.maze[i]\n self.num_sprouts_left += row.count('@')",
"if self.maze[row][col] == '#':\n return True\nelse:\n return False",
"if row == self.rat_1.row and col == self.rat_1... | <|body_start_0|>
self.maze = maze
self.rat_1 = rat_1
self.rat_2 = rat_2
self.num_sprouts_left = 0
for i in range(len(self.maze)):
row = self.maze[i]
self.num_sprouts_left += row.count('@')
<|end_body_0|>
<|body_start_1|>
if self.maze[row][col] == ... | A 2D maze. | Maze | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Maze:
"""A 2D maze."""
def __init__(self, maze, rat_1, rat_2):
"""(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in th... | stack_v2_sparse_classes_10k_train_004371 | 6,001 | permissive | [
{
"docstring": "(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in the maze. Example call: Maze([['#', '#', '#', '#', '#', '#', '#'], ['#', '.', '.... | 5 | stack_v2_sparse_classes_30k_train_003801 | Implement the Python class `Maze` described below.
Class description:
A 2D maze.
Method signatures and docstrings:
- def __init__(self, maze, rat_1, rat_2): (Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the fi... | Implement the Python class `Maze` described below.
Class description:
A 2D maze.
Method signatures and docstrings:
- def __init__(self, maze, rat_1, rat_2): (Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the fi... | ff265343635a0109b6deab31f2a112d304d020cb | <|skeleton|>
class Maze:
"""A 2D maze."""
def __init__(self, maze, rat_1, rat_2):
"""(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Maze:
"""A 2D maze."""
def __init__(self, maze, rat_1, rat_2):
"""(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in the maze. Examp... | the_stack_v2_python_sparse | Crafting_Quality_Code_UniToronto/week5_functions/assignment/a2.py | bounty030/Coursera | train | 1 |
eca0b321a0e50117f6e6279a032335409d667249 | [
"for s, t in zip_longest(self.get_next(S), self.get_next(T)):\n if s != t:\n return False\nreturn True",
"hash_count = 0\nfor c in reversed(s):\n if c == '#':\n hash_count += 1\n elif hash_count > 0:\n hash_count -= 1\n else:\n yield c"
] | <|body_start_0|>
for s, t in zip_longest(self.get_next(S), self.get_next(T)):
if s != t:
return False
return True
<|end_body_0|>
<|body_start_1|>
hash_count = 0
for c in reversed(s):
if c == '#':
hash_count += 1
elif ha... | Runtime: 24 ms, faster than 99.92% of Python3 online submissions for Backspace String Compare. Memory Usage: 13.3 MB, less than 9.92% of Python3 online submissions for Backspace String Compare. | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Runtime: 24 ms, faster than 99.92% of Python3 online submissions for Backspace String Compare. Memory Usage: 13.3 MB, less than 9.92% of Python3 online submissions for Backspace String Compare."""
def backspaceCompare(self, S, T):
"""Given two strings S and T, return if ... | stack_v2_sparse_classes_10k_train_004372 | 1,928 | no_license | [
{
"docstring": "Given two strings S and T, return if they are equal when both are typed into empty text editors. # means a backspace character. Example 1: Input: S = \"ab#c\", T = \"ad#c\" Output: true Explanation: Both S and T become \"ac\". Example 2: Input: S = \"ab##\", T = \"c#d#\" Output: true Explanation... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Runtime: 24 ms, faster than 99.92% of Python3 online submissions for Backspace String Compare. Memory Usage: 13.3 MB, less than 9.92% of Python3 online submissions for Backspace String Compare.
Method signatures and docstrings:
- def backspaceC... | Implement the Python class `Solution` described below.
Class description:
Runtime: 24 ms, faster than 99.92% of Python3 online submissions for Backspace String Compare. Memory Usage: 13.3 MB, less than 9.92% of Python3 online submissions for Backspace String Compare.
Method signatures and docstrings:
- def backspaceC... | 01fe893ba2e37c9bda79e3081c556698f0b6d2f0 | <|skeleton|>
class Solution:
"""Runtime: 24 ms, faster than 99.92% of Python3 online submissions for Backspace String Compare. Memory Usage: 13.3 MB, less than 9.92% of Python3 online submissions for Backspace String Compare."""
def backspaceCompare(self, S, T):
"""Given two strings S and T, return if ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
"""Runtime: 24 ms, faster than 99.92% of Python3 online submissions for Backspace String Compare. Memory Usage: 13.3 MB, less than 9.92% of Python3 online submissions for Backspace String Compare."""
def backspaceCompare(self, S, T):
"""Given two strings S and T, return if they are equa... | the_stack_v2_python_sparse | LeetCode/844_backspace_string_compare.py | KKosukeee/CodingQuestions | train | 1 |
67ad328150f81565eed6168a51112866c3f59d55 | [
"counter = {}\nfor num in nums:\n if num in counter:\n counter[num] += 1\n else:\n counter[num] = 1\nusing = avoid = 0\nprev = None\nfor k in sorted(counter):\n max_value = max(using, avoid)\n if k - 1 != prev:\n using = k * counter[k] + max(using, avoid)\n avoid = max_value\... | <|body_start_0|>
counter = {}
for num in nums:
if num in counter:
counter[num] += 1
else:
counter[num] = 1
using = avoid = 0
prev = None
for k in sorted(counter):
max_value = max(using, avoid)
if k - ... | Array | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Array:
def delete_and_earn_(self, nums: List[int]) -> int:
"""Approach: DP (current and previous value) + Sorting Time Complexity: O(N log N) Space Complexity: O(N) :param nums: :return:"""
<|body_0|>
def delete_and_earn(self, nums: List[int]) -> int:
"""Approach: DP... | stack_v2_sparse_classes_10k_train_004373 | 1,643 | no_license | [
{
"docstring": "Approach: DP (current and previous value) + Sorting Time Complexity: O(N log N) Space Complexity: O(N) :param nums: :return:",
"name": "delete_and_earn_",
"signature": "def delete_and_earn_(self, nums: List[int]) -> int"
},
{
"docstring": "Approach: DP Time Complexity: O(N) Space... | 2 | null | Implement the Python class `Array` described below.
Class description:
Implement the Array class.
Method signatures and docstrings:
- def delete_and_earn_(self, nums: List[int]) -> int: Approach: DP (current and previous value) + Sorting Time Complexity: O(N log N) Space Complexity: O(N) :param nums: :return:
- def d... | Implement the Python class `Array` described below.
Class description:
Implement the Array class.
Method signatures and docstrings:
- def delete_and_earn_(self, nums: List[int]) -> int: Approach: DP (current and previous value) + Sorting Time Complexity: O(N log N) Space Complexity: O(N) :param nums: :return:
- def d... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Array:
def delete_and_earn_(self, nums: List[int]) -> int:
"""Approach: DP (current and previous value) + Sorting Time Complexity: O(N log N) Space Complexity: O(N) :param nums: :return:"""
<|body_0|>
def delete_and_earn(self, nums: List[int]) -> int:
"""Approach: DP... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Array:
def delete_and_earn_(self, nums: List[int]) -> int:
"""Approach: DP (current and previous value) + Sorting Time Complexity: O(N log N) Space Complexity: O(N) :param nums: :return:"""
counter = {}
for num in nums:
if num in counter:
counter[num] += 1
... | the_stack_v2_python_sparse | goldman_sachs/delete_and_earn.py | Shiv2157k/leet_code | train | 1 | |
f8c76d2c6a5a6595b6842ab4913feb18e056bb7a | [
"g = Grammar()\ng.train_string('Hello, world!')\nself.assertEqual('0 --(0)--> H e l l o , _ w o r l d ! \\n', g.print_grammar())",
"g = Grammar()\ng.train_string('abcabdabcabd')\nself.assertEqual('0 --(0)--> 1 1 \\n1 --(2)--> 2 c 2 d abcabd\\n2 --(2)--> a b ... | <|body_start_0|>
g = Grammar()
g.train_string('Hello, world!')
self.assertEqual('0 --(0)--> H e l l o , _ w o r l d ! \n', g.print_grammar())
<|end_body_0|>
<|body_start_1|>
g = Grammar()
g.train_string('abcabdabcabd')
self.assertEqual('0 --(0)--> 1 1 \n1 --(2)--> 2 c 2 ... | TestSequitur | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSequitur:
def test_sequitur(self):
"""docstring for test_sequitur"""
<|body_0|>
def test_sequitur_base(self):
"""docstring for test_sequitur_base"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
g = Grammar()
g.train_string('Hello, world!... | stack_v2_sparse_classes_10k_train_004374 | 696 | permissive | [
{
"docstring": "docstring for test_sequitur",
"name": "test_sequitur",
"signature": "def test_sequitur(self)"
},
{
"docstring": "docstring for test_sequitur_base",
"name": "test_sequitur_base",
"signature": "def test_sequitur_base(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000950 | Implement the Python class `TestSequitur` described below.
Class description:
Implement the TestSequitur class.
Method signatures and docstrings:
- def test_sequitur(self): docstring for test_sequitur
- def test_sequitur_base(self): docstring for test_sequitur_base | Implement the Python class `TestSequitur` described below.
Class description:
Implement the TestSequitur class.
Method signatures and docstrings:
- def test_sequitur(self): docstring for test_sequitur
- def test_sequitur_base(self): docstring for test_sequitur_base
<|skeleton|>
class TestSequitur:
def test_sequ... | 7192f0bf26378d8aacb21c0220cc705cb577c6dc | <|skeleton|>
class TestSequitur:
def test_sequitur(self):
"""docstring for test_sequitur"""
<|body_0|>
def test_sequitur_base(self):
"""docstring for test_sequitur_base"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSequitur:
def test_sequitur(self):
"""docstring for test_sequitur"""
g = Grammar()
g.train_string('Hello, world!')
self.assertEqual('0 --(0)--> H e l l o , _ w o r l d ! \n', g.print_grammar())
def test_sequitur_base(self):
"""docstring for test_sequitur_base""... | the_stack_v2_python_sparse | make_demo_discover_rt/pysequitur/sequiturpython/sequitur_test.py | sjtuytc/AAAI21-RoutineAugmentedPolicyLearning | train | 15 | |
f9d3c7f1e9ffe1e3c38cee5eeafd17c93abe2304 | [
"self.num_generations = 0\nself.num_schemas = num_schemas\nself.min_generations = min_generations",
"self.num_generations += 1\nif self.num_generations >= self.min_generations:\n all_seqs = []\n for org in organisms:\n if org.fitness > 0:\n if org.genome not in all_seqs:\n a... | <|body_start_0|>
self.num_generations = 0
self.num_schemas = num_schemas
self.min_generations = min_generations
<|end_body_0|>
<|body_start_1|>
self.num_generations += 1
if self.num_generations >= self.min_generations:
all_seqs = []
for org in organisms:
... | Determine when we are done evolving motifs. This takes the very simple approach of halting evolution when the GA has proceeded for a specified number of generations and has a given number of unique schema with positive fitness. | SimpleFinisher | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleFinisher:
"""Determine when we are done evolving motifs. This takes the very simple approach of halting evolution when the GA has proceeded for a specified number of generations and has a given number of unique schema with positive fitness."""
def __init__(self, num_schemas, min_genera... | stack_v2_sparse_classes_10k_train_004375 | 26,199 | permissive | [
{
"docstring": "Initialize the finisher with its parameters. Arguments: o num_schemas -- the number of useful (positive fitness) schemas we want to generation o min_generations -- The minimum number of generations to allow the GA to proceed.",
"name": "__init__",
"signature": "def __init__(self, num_sch... | 2 | stack_v2_sparse_classes_30k_train_006297 | Implement the Python class `SimpleFinisher` described below.
Class description:
Determine when we are done evolving motifs. This takes the very simple approach of halting evolution when the GA has proceeded for a specified number of generations and has a given number of unique schema with positive fitness.
Method sig... | Implement the Python class `SimpleFinisher` described below.
Class description:
Determine when we are done evolving motifs. This takes the very simple approach of halting evolution when the GA has proceeded for a specified number of generations and has a given number of unique schema with positive fitness.
Method sig... | 1d9a8e84a8572809ee3260ede44290e14de3bdd1 | <|skeleton|>
class SimpleFinisher:
"""Determine when we are done evolving motifs. This takes the very simple approach of halting evolution when the GA has proceeded for a specified number of generations and has a given number of unique schema with positive fitness."""
def __init__(self, num_schemas, min_genera... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SimpleFinisher:
"""Determine when we are done evolving motifs. This takes the very simple approach of halting evolution when the GA has proceeded for a specified number of generations and has a given number of unique schema with positive fitness."""
def __init__(self, num_schemas, min_generations=100):
... | the_stack_v2_python_sparse | bin/last_wrapper/Bio/NeuralNetwork/Gene/Schema.py | LyonsLab/coge | train | 41 |
3c6c7228a2b40b35be6604a70ac71748457e0b0f | [
"if isinstance(filter_names[0], str):\n flist = phot.load_filters(filter_names, interp=True, lamb=self.lamb, filterLib=filterLib)\n _fnames = filter_names\nelse:\n flist = phot.load_Integrationfilters(filter_names, interp=True, lamb=self.lamb)\n _fnames = [fk.name for fk in filter_names]\nif extLaw is n... | <|body_start_0|>
if isinstance(filter_names[0], str):
flist = phot.load_filters(filter_names, interp=True, lamb=self.lamb, filterLib=filterLib)
_fnames = filter_names
else:
flist = phot.load_Integrationfilters(filter_names, interp=True, lamb=self.lamb)
_fn... | Generate a grid that contains spectra. It provides an access to integrated photometry function getSEDs | SpectralGrid | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpectralGrid:
"""Generate a grid that contains spectra. It provides an access to integrated photometry function getSEDs"""
def getSEDs(self, filter_names, absFlux=True, extLaw=None, inplace=False, filterLib=None, **kwargs):
"""Extract integrated fluxes through filters Parameters ----... | stack_v2_sparse_classes_10k_train_004376 | 11,734 | permissive | [
{
"docstring": "Extract integrated fluxes through filters Parameters ---------- filter_names: list list of filter names according to the filter lib or filter instances (no mixing between name and instances) absFlux:bool returns absolute fluxes if set extLaw: extinction.ExtinctionLaw apply extinction law if prov... | 2 | stack_v2_sparse_classes_30k_val_000271 | Implement the Python class `SpectralGrid` described below.
Class description:
Generate a grid that contains spectra. It provides an access to integrated photometry function getSEDs
Method signatures and docstrings:
- def getSEDs(self, filter_names, absFlux=True, extLaw=None, inplace=False, filterLib=None, **kwargs): ... | Implement the Python class `SpectralGrid` described below.
Class description:
Generate a grid that contains spectra. It provides an access to integrated photometry function getSEDs
Method signatures and docstrings:
- def getSEDs(self, filter_names, absFlux=True, extLaw=None, inplace=False, filterLib=None, **kwargs): ... | 892940813f4b22d545b501cc596c72967d9a45bc | <|skeleton|>
class SpectralGrid:
"""Generate a grid that contains spectra. It provides an access to integrated photometry function getSEDs"""
def getSEDs(self, filter_names, absFlux=True, extLaw=None, inplace=False, filterLib=None, **kwargs):
"""Extract integrated fluxes through filters Parameters ----... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SpectralGrid:
"""Generate a grid that contains spectra. It provides an access to integrated photometry function getSEDs"""
def getSEDs(self, filter_names, absFlux=True, extLaw=None, inplace=False, filterLib=None, **kwargs):
"""Extract integrated fluxes through filters Parameters ---------- filter... | the_stack_v2_python_sparse | beast/physicsmodel/grid.py | dthilker/beast | train | 0 |
29abbd1ea85905caa5b284ecae65636de4d33fd3 | [
"if not secret_key:\n return None\nsigner_kwargs = dict(key_derivation=self.key_derivation, digest_method=self.digest_method)\nreturn URLSafeTimedSerializer(secret_key, salt=self.salt, serializer=self.serializer, signer_kwargs=signer_kwargs)",
"sscsi = SimpleSecureCookieSessionInterface()\nsigningSerializer = ... | <|body_start_0|>
if not secret_key:
return None
signer_kwargs = dict(key_derivation=self.key_derivation, digest_method=self.digest_method)
return URLSafeTimedSerializer(secret_key, salt=self.salt, serializer=self.serializer, signer_kwargs=signer_kwargs)
<|end_body_0|>
<|body_start_1... | SimpleSecureCookieSessionInterface | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleSecureCookieSessionInterface:
def get_signing_serializer(self, secret_key):
"""Used to check secret key"""
<|body_0|>
def decodeFlaskCookie(self, secret_key, cookieValue):
"""Decode a base 64 encoded string"""
<|body_1|>
def encodeFlaskCookie(self,... | stack_v2_sparse_classes_10k_train_004377 | 2,701 | no_license | [
{
"docstring": "Used to check secret key",
"name": "get_signing_serializer",
"signature": "def get_signing_serializer(self, secret_key)"
},
{
"docstring": "Decode a base 64 encoded string",
"name": "decodeFlaskCookie",
"signature": "def decodeFlaskCookie(self, secret_key, cookieValue)"
... | 3 | stack_v2_sparse_classes_30k_train_006257 | Implement the Python class `SimpleSecureCookieSessionInterface` described below.
Class description:
Implement the SimpleSecureCookieSessionInterface class.
Method signatures and docstrings:
- def get_signing_serializer(self, secret_key): Used to check secret key
- def decodeFlaskCookie(self, secret_key, cookieValue):... | Implement the Python class `SimpleSecureCookieSessionInterface` described below.
Class description:
Implement the SimpleSecureCookieSessionInterface class.
Method signatures and docstrings:
- def get_signing_serializer(self, secret_key): Used to check secret key
- def decodeFlaskCookie(self, secret_key, cookieValue):... | 24e1e25d2e512105c9bf70b5e33b1afed4790f71 | <|skeleton|>
class SimpleSecureCookieSessionInterface:
def get_signing_serializer(self, secret_key):
"""Used to check secret key"""
<|body_0|>
def decodeFlaskCookie(self, secret_key, cookieValue):
"""Decode a base 64 encoded string"""
<|body_1|>
def encodeFlaskCookie(self,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SimpleSecureCookieSessionInterface:
def get_signing_serializer(self, secret_key):
"""Used to check secret key"""
if not secret_key:
return None
signer_kwargs = dict(key_derivation=self.key_derivation, digest_method=self.digest_method)
return URLSafeTimedSerializer(s... | the_stack_v2_python_sparse | flask/app/config.py | InTheNou/InTheNou-Backend | train | 0 | |
69b8ecf656173add61531024d7d8ed636e7f6f2b | [
"stack = []\nresult = [0] * len(temperatures)\nstack.append(0)\nfor i, v in enumerate(temperatures):\n while len(stack) != 0 and v > temperatures[stack[-1]]:\n pre = stack.pop()\n result[pre] = i - pre\n stack.append(i)\nreturn result",
"n = len(temperatures)\ndays = [0] * n\nfor i in range(n ... | <|body_start_0|>
stack = []
result = [0] * len(temperatures)
stack.append(0)
for i, v in enumerate(temperatures):
while len(stack) != 0 and v > temperatures[stack[-1]]:
pre = stack.pop()
result[pre] = i - pre
stack.append(i)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def dailyTemperatures(self, temperatures):
""":type temperatures: List[int] :rtype: List[int]"""
<|body_0|>
def dailyTemperatures1(self, temperatures):
""":type temperatures: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_10k_train_004378 | 1,904 | no_license | [
{
"docstring": ":type temperatures: List[int] :rtype: List[int]",
"name": "dailyTemperatures",
"signature": "def dailyTemperatures(self, temperatures)"
},
{
"docstring": ":type temperatures: List[int] :rtype: List[int]",
"name": "dailyTemperatures1",
"signature": "def dailyTemperatures1(... | 2 | stack_v2_sparse_classes_30k_train_001727 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def dailyTemperatures(self, temperatures): :type temperatures: List[int] :rtype: List[int]
- def dailyTemperatures1(self, temperatures): :type temperatures: List[int] :rtype: Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def dailyTemperatures(self, temperatures): :type temperatures: List[int] :rtype: List[int]
- def dailyTemperatures1(self, temperatures): :type temperatures: List[int] :rtype: Lis... | eaeeb9ad2d8cf2a60517cd86f42b30678b5ad2f8 | <|skeleton|>
class Solution:
def dailyTemperatures(self, temperatures):
""":type temperatures: List[int] :rtype: List[int]"""
<|body_0|>
def dailyTemperatures1(self, temperatures):
""":type temperatures: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def dailyTemperatures(self, temperatures):
""":type temperatures: List[int] :rtype: List[int]"""
stack = []
result = [0] * len(temperatures)
stack.append(0)
for i, v in enumerate(temperatures):
while len(stack) != 0 and v > temperatures[stack[-1]]:... | the_stack_v2_python_sparse | Python/739. Daily Temperatures.py | maiwen/LeetCode | train | 0 | |
7f02a712bd24ffc1fc9155af5a78881d76225f18 | [
"self.agent_upgrade_task = agent_upgrade_task\nself.analysis_task = analysis_task\nself.backup_task = backup_task\nself.bulk_install_app_task = bulk_install_app_task\nself.clone_task = clone_task\nself.created_time_secs = created_time_secs\nself.description = description\nself.dismissed = dismissed\nself.dismissed_... | <|body_start_0|>
self.agent_upgrade_task = agent_upgrade_task
self.analysis_task = analysis_task
self.backup_task = backup_task
self.bulk_install_app_task = bulk_install_app_task
self.clone_task = clone_task
self.created_time_secs = created_time_secs
self.descript... | Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysis Task. backup_task (BackupTaskInfo): The no... | TaskNotification | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskNotification:
"""Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysi... | stack_v2_sparse_classes_10k_train_004379 | 8,762 | permissive | [
{
"docstring": "Constructor for the TaskNotification class",
"name": "__init__",
"signature": "def __init__(self, agent_upgrade_task=None, analysis_task=None, backup_task=None, bulk_install_app_task=None, clone_task=None, created_time_secs=None, description=None, dismissed=None, dismissed_time_secs=None... | 2 | null | Implement the Python class `TaskNotification` described below.
Class description:
Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo... | Implement the Python class `TaskNotification` described below.
Class description:
Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class TaskNotification:
"""Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TaskNotification:
"""Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysis Task. backu... | the_stack_v2_python_sparse | cohesity_management_sdk/models/task_notification.py | cohesity/management-sdk-python | train | 24 |
d156ae6ab06ae81eb473288ceb2de35008fe3310 | [
"if not grid or not grid[0]:\n return 0\nm, n = (len(grid), len(grid[0]))\nelapsed = [[float('inf')] * n for _ in range(m)]\n\ndef bfs(i, j, s):\n visited = set()\n queue = deque([(s, i, j)])\n while queue:\n s, i, j = queue.popleft()\n for dx, dy in ((-1, 0), (1, 0), (0, -1), (0, 1)):\n ... | <|body_start_0|>
if not grid or not grid[0]:
return 0
m, n = (len(grid), len(grid[0]))
elapsed = [[float('inf')] * n for _ in range(m)]
def bfs(i, j, s):
visited = set()
queue = deque([(s, i, j)])
while queue:
s, i, j = que... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_0|>
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k_train_004380 | 3,758 | no_license | [
{
"docstring": "Time complexity: O(n^2) Space complexity: O(n^2)",
"name": "orangesRotting",
"signature": "def orangesRotting(self, grid: List[List[int]]) -> int"
},
{
"docstring": "Time complexity: O(n^2) Space complexity: O(n^2)",
"name": "orangesRotting",
"signature": "def orangesRott... | 2 | stack_v2_sparse_classes_30k_train_003605 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity: O(n^2) Space complexity: O(n^2)
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity: O(n^2) Space complexity: O(n^2)
- def orangesRotting(self, grid: List[List[int]]) -> int: Time complexity... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_0|>
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def orangesRotting(self, grid: List[List[int]]) -> int:
"""Time complexity: O(n^2) Space complexity: O(n^2)"""
if not grid or not grid[0]:
return 0
m, n = (len(grid), len(grid[0]))
elapsed = [[float('inf')] * n for _ in range(m)]
def bfs(i, j, s):... | the_stack_v2_python_sparse | leetcode/solved/1036_Rotting_Oranges/solution.py | sungminoh/algorithms | train | 0 | |
790e1bc996d03b7d6f4aeee8cb1f4bb932117324 | [
"self.amount_total = 0.0\nfor data in self.commission_line:\n self.amount_total += data.amount",
"account_jrnl_obj = self.env['account.journal'].search([('type', '=', 'purchase')], limit=1)\nfor data in self:\n inv_line_values = {'name': 'Commission For ' + data.number or '', 'analytic_account_id': data.ten... | <|body_start_0|>
self.amount_total = 0.0
for data in self.commission_line:
self.amount_total += data.amount
<|end_body_0|>
<|body_start_1|>
account_jrnl_obj = self.env['account.journal'].search([('type', '=', 'purchase')], limit=1)
for data in self:
inv_line_valu... | CommissionInvoice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommissionInvoice:
def _amount_all(self):
"""Compute the total amounts of the SO."""
<|body_0|>
def create_invoice(self):
"""This method is used to create supplier invoice. ------------------------------------------------------------ @param self: The object pointer""... | stack_v2_sparse_classes_10k_train_004381 | 11,342 | no_license | [
{
"docstring": "Compute the total amounts of the SO.",
"name": "_amount_all",
"signature": "def _amount_all(self)"
},
{
"docstring": "This method is used to create supplier invoice. ------------------------------------------------------------ @param self: The object pointer",
"name": "create... | 5 | stack_v2_sparse_classes_30k_test_000135 | Implement the Python class `CommissionInvoice` described below.
Class description:
Implement the CommissionInvoice class.
Method signatures and docstrings:
- def _amount_all(self): Compute the total amounts of the SO.
- def create_invoice(self): This method is used to create supplier invoice. ------------------------... | Implement the Python class `CommissionInvoice` described below.
Class description:
Implement the CommissionInvoice class.
Method signatures and docstrings:
- def _amount_all(self): Compute the total amounts of the SO.
- def create_invoice(self): This method is used to create supplier invoice. ------------------------... | 163136f382faa8607db8fb6cda42a5ba07c4076b | <|skeleton|>
class CommissionInvoice:
def _amount_all(self):
"""Compute the total amounts of the SO."""
<|body_0|>
def create_invoice(self):
"""This method is used to create supplier invoice. ------------------------------------------------------------ @param self: The object pointer""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CommissionInvoice:
def _amount_all(self):
"""Compute the total amounts of the SO."""
self.amount_total = 0.0
for data in self.commission_line:
self.amount_total += data.amount
def create_invoice(self):
"""This method is used to create supplier invoice. --------... | the_stack_v2_python_sparse | property_commission_ee/models/property_commission.py | maarejsys/Roya | train | 0 | |
b219452a72cc74876124d76ca356e7c5fdb35992 | [
"self._inset = inset\nself._term_width = (maxwidth or get_terminal_size()[0]) - inset * 4\nself._items: List[Tuple[str, str]] = []\nself._max_name_width = 0\nself._max_value_width = 0",
"self._items.extend(item_list)\nfor name, value in item_list:\n self._max_name_width = max(self._max_name_width, len(name))\n... | <|body_start_0|>
self._inset = inset
self._term_width = (maxwidth or get_terminal_size()[0]) - inset * 4
self._items: List[Tuple[str, str]] = []
self._max_name_width = 0
self._max_value_width = 0
<|end_body_0|>
<|body_start_1|>
self._items.extend(item_list)
for n... | @brief Formats a set of values in multiple columns. The value_list must be a list of bi-tuples (name, value) sorted in the desired display order. The number of columns will be determined by the terminal width and maximum value width. The values will be printed in column major order. | ColumnFormatter | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColumnFormatter:
"""@brief Formats a set of values in multiple columns. The value_list must be a list of bi-tuples (name, value) sorted in the desired display order. The number of columns will be determined by the terminal width and maximum value width. The values will be printed in column major ... | stack_v2_sparse_classes_10k_train_004382 | 3,831 | permissive | [
{
"docstring": "@brief Constructor. @param self The object. @param maxwidth Number of characters to which the output width must be constrained. If not provided, then the width of the stdout terminal is used. If getting the terminal width fails, for instance if stdout is not a terminal, then a default of 80 char... | 4 | null | Implement the Python class `ColumnFormatter` described below.
Class description:
@brief Formats a set of values in multiple columns. The value_list must be a list of bi-tuples (name, value) sorted in the desired display order. The number of columns will be determined by the terminal width and maximum value width. The ... | Implement the Python class `ColumnFormatter` described below.
Class description:
@brief Formats a set of values in multiple columns. The value_list must be a list of bi-tuples (name, value) sorted in the desired display order. The number of columns will be determined by the terminal width and maximum value width. The ... | 9253740baf46ebf4eacbce6bf3369150c5fb8ee0 | <|skeleton|>
class ColumnFormatter:
"""@brief Formats a set of values in multiple columns. The value_list must be a list of bi-tuples (name, value) sorted in the desired display order. The number of columns will be determined by the terminal width and maximum value width. The values will be printed in column major ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ColumnFormatter:
"""@brief Formats a set of values in multiple columns. The value_list must be a list of bi-tuples (name, value) sorted in the desired display order. The number of columns will be determined by the terminal width and maximum value width. The values will be printed in column major order."""
... | the_stack_v2_python_sparse | pyocd/utility/columns.py | pyocd/pyOCD | train | 507 |
2fe5e1aa02b31005092dcd43d6f3fb2d697408d6 | [
"self.base_image = pygame.image.load(image)\nself.images = []\nself.duration = duration\nself.last_change = time()\nself.selected_image = 0\nsprite_w = self.base_image.get_width() / w\nsprite_h = self.base_image.get_height() / h\nself.final_size = final_size\nself.invisible_color = invisible_color\nif final_size is... | <|body_start_0|>
self.base_image = pygame.image.load(image)
self.images = []
self.duration = duration
self.last_change = time()
self.selected_image = 0
sprite_w = self.base_image.get_width() / w
sprite_h = self.base_image.get_height() / h
self.final_size =... | SpriteSheet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h... | stack_v2_sparse_classes_10k_train_004383 | 2,468 | no_license | [
{
"docstring": "This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h: the height of each frame in the sheet :param duration: the number of seconds to stay on each frame :param final_size: the final size to scale the imag... | 3 | stack_v2_sparse_classes_30k_train_005587 | Implement the Python class `SpriteSheet` described below.
Class description:
Implement the SpriteSheet class.
Method signatures and docstrings:
- def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)): This class is for creating spritesheets :par... | Implement the Python class `SpriteSheet` described below.
Class description:
Implement the SpriteSheet class.
Method signatures and docstrings:
- def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)): This class is for creating spritesheets :par... | e9e68cf3ba4f9f12e66eae81893ca9dcc534835c | <|skeleton|>
class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h: the height o... | the_stack_v2_python_sparse | Objects/SpriteSheet.py | john-palazzolo/PyGE | train | 0 | |
20dbeed40bbf3a52d73b62441485b43c7ba64eb3 | [
"self.encoding = encoding\nself.object_hook = object_hook\nself.object_pairs_hook = object_pairs_hook\nself.parse_float = parse_float or float\nself.parse_int = parse_int or int\nself.parse_constant = parse_constant or _CONSTANTS.__getitem__\nself.strict = strict\nself.parse_object = JSONObject\nself.parse_array = ... | <|body_start_0|>
self.encoding = encoding
self.object_hook = object_hook
self.object_pairs_hook = object_pairs_hook
self.parse_float = parse_float or float
self.parse_int = parse_int or int
self.parse_constant = parse_constant or _CONSTANTS.__getitem__
self.strict... | Simple JSON <http://json.org> decoder Performs the following translations in decoding by default: +---------------+-------------------+ | JSON | Python | +===============+===================+ | object | dict | +---------------+-------------------+ | array | list | +---------------+-------------------+ | string | unicod... | JSONDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONDecoder:
"""Simple JSON <http://json.org> decoder Performs the following translations in decoding by default: +---------------+-------------------+ | JSON | Python | +===============+===================+ | object | dict | +---------------+-------------------+ | array | list | +---------------... | stack_v2_sparse_classes_10k_train_004384 | 47,385 | no_license | [
{
"docstring": "``encoding`` determines the encoding used to interpret any ``str`` objects decoded by this instance (utf-8 by default). It has no effect when decoding ``unicode`` objects. Note that currently only encodings that are a superset of ASCII work, strings of other encodings should be passed in as ``un... | 3 | stack_v2_sparse_classes_30k_train_004062 | Implement the Python class `JSONDecoder` described below.
Class description:
Simple JSON <http://json.org> decoder Performs the following translations in decoding by default: +---------------+-------------------+ | JSON | Python | +===============+===================+ | object | dict | +---------------+---------------... | Implement the Python class `JSONDecoder` described below.
Class description:
Simple JSON <http://json.org> decoder Performs the following translations in decoding by default: +---------------+-------------------+ | JSON | Python | +===============+===================+ | object | dict | +---------------+---------------... | 1f5295cd6114f3f18958be0e0618ff6b35aa16d7 | <|skeleton|>
class JSONDecoder:
"""Simple JSON <http://json.org> decoder Performs the following translations in decoding by default: +---------------+-------------------+ | JSON | Python | +===============+===================+ | object | dict | +---------------+-------------------+ | array | list | +---------------... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JSONDecoder:
"""Simple JSON <http://json.org> decoder Performs the following translations in decoding by default: +---------------+-------------------+ | JSON | Python | +===============+===================+ | object | dict | +---------------+-------------------+ | array | list | +---------------+------------... | the_stack_v2_python_sparse | packages/python_compat_json.py | grid-control/grid-control | train | 32 |
1a26e4dc0293ea5e61eba87cdc6247a267ac67c2 | [
"max_profit = 0\nprev_price = prices[0]\nfor price in prices[1:]:\n if price > prev_price:\n max_profit += price - prev_price\n prev_price = price\nreturn max_profit",
"n = len(prices)\ndp = [[None, None] for _ in range(n)]\ndp[0][0], dp[0][1] = (0, -prices[0])\nfor idx in range(1, n):\n dp[idx][0... | <|body_start_0|>
max_profit = 0
prev_price = prices[0]
for price in prices[1:]:
if price > prev_price:
max_profit += price - prev_price
prev_price = price
return max_profit
<|end_body_0|>
<|body_start_1|>
n = len(prices)
dp = [[Non... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""贪心"""
<|body_0|>
def maxProfitDP(self, prices: List[int]) -> int:
"""动态规划-二维数组"""
<|body_1|>
def maxProfitDPOPT(self, prices: List[int]) -> int:
"""动态规划-空间优化"""
<|body_2|>
<|end... | stack_v2_sparse_classes_10k_train_004385 | 2,597 | no_license | [
{
"docstring": "贪心",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int]) -> int"
},
{
"docstring": "动态规划-二维数组",
"name": "maxProfitDP",
"signature": "def maxProfitDP(self, prices: List[int]) -> int"
},
{
"docstring": "动态规划-空间优化",
"name": "maxProfitDPOPT",... | 3 | stack_v2_sparse_classes_30k_train_004696 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 贪心
- def maxProfitDP(self, prices: List[int]) -> int: 动态规划-二维数组
- def maxProfitDPOPT(self, prices: List[int]) -> int: 动态规划-空间优化 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 贪心
- def maxProfitDP(self, prices: List[int]) -> int: 动态规划-二维数组
- def maxProfitDPOPT(self, prices: List[int]) -> int: 动态规划-空间优化
<|... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""贪心"""
<|body_0|>
def maxProfitDP(self, prices: List[int]) -> int:
"""动态规划-二维数组"""
<|body_1|>
def maxProfitDPOPT(self, prices: List[int]) -> int:
"""动态规划-空间优化"""
<|body_2|>
<|end... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""贪心"""
max_profit = 0
prev_price = prices[0]
for price in prices[1:]:
if price > prev_price:
max_profit += price - prev_price
prev_price = price
return max_profit
def... | the_stack_v2_python_sparse | 122.买卖股票的最佳时机II/solution.py | QtTao/daily_leetcode | train | 0 | |
6ca3259a6785bf4e58c7ec9a3cfc14a44acb3a85 | [
"if IATTopic.providedBy(context) or ICollection.providedBy(context):\n return context.queryCatalog(batch=False)\nelif IFolderish.providedBy(context):\n return context.getFolderContents(batch=False)",
"if objectimages:\n theader = '\\n <thead>\\n <tr>\\n ... | <|body_start_0|>
if IATTopic.providedBy(context) or ICollection.providedBy(context):
return context.queryCatalog(batch=False)
elif IFolderish.providedBy(context):
return context.getFolderContents(batch=False)
<|end_body_0|>
<|body_start_1|>
if objectimages:
t... | DownloadWoid_Viewlet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DownloadWoid_Viewlet:
def query(self, context):
"""Make catalog query for the folder listing."""
<|body_0|>
def createTableHeader(self, objectimages):
"""Create the Header for Table"""
<|body_1|>
def createZeileFromMF(self, obj, objectimages):
""... | stack_v2_sparse_classes_10k_train_004386 | 5,467 | no_license | [
{
"docstring": "Make catalog query for the folder listing.",
"name": "query",
"signature": "def query(self, context)"
},
{
"docstring": "Create the Header for Table",
"name": "createTableHeader",
"signature": "def createTableHeader(self, objectimages)"
},
{
"docstring": "Create a... | 5 | null | Implement the Python class `DownloadWoid_Viewlet` described below.
Class description:
Implement the DownloadWoid_Viewlet class.
Method signatures and docstrings:
- def query(self, context): Make catalog query for the folder listing.
- def createTableHeader(self, objectimages): Create the Header for Table
- def create... | Implement the Python class `DownloadWoid_Viewlet` described below.
Class description:
Implement the DownloadWoid_Viewlet class.
Method signatures and docstrings:
- def query(self, context): Make catalog query for the folder listing.
- def createTableHeader(self, objectimages): Create the Header for Table
- def create... | 62203ae995bd708dc81809cc8698c0b24208735e | <|skeleton|>
class DownloadWoid_Viewlet:
def query(self, context):
"""Make catalog query for the folder listing."""
<|body_0|>
def createTableHeader(self, objectimages):
"""Create the Header for Table"""
<|body_1|>
def createZeileFromMF(self, obj, objectimages):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DownloadWoid_Viewlet:
def query(self, context):
"""Make catalog query for the folder listing."""
if IATTopic.providedBy(context) or ICollection.providedBy(context):
return context.queryCatalog(batch=False)
elif IFolderish.providedBy(context):
return context.getF... | the_stack_v2_python_sparse | nva.flgdesktop/trunk/nva/flgdesktop/viewlets.py | witsch/novareto | train | 0 | |
4b2f5be965fb5274f9efeeaa05979c7e39fea8ca | [
"user_id = params.get('user_id')\nlog.debug(f'Checking if user ({user_id}) is permitted to change their nickname.')\ndata = self.db.get(self.prison_table, user_id) or {}\nif data and data.get('end_timestamp'):\n log.trace('User exists in the prison_table.')\n end_time = data.get('end_timestamp')\n if is_ex... | <|body_start_0|>
user_id = params.get('user_id')
log.debug(f'Checking if user ({user_id}) is permitted to change their nickname.')
data = self.db.get(self.prison_table, user_id) or {}
if data and data.get('end_timestamp'):
log.trace('User exists in the prison_table.')
... | SuperstarifyView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperstarifyView:
def get(self, params=None):
"""Check if the user is currently in superstar-prison. If user is currently servin' his sentence in the big house, return the name stored in the forced_nick column of prison_table. If user cannot be found in prison, or if his sentence has exp... | stack_v2_sparse_classes_10k_train_004387 | 5,973 | permissive | [
{
"docstring": "Check if the user is currently in superstar-prison. If user is currently servin' his sentence in the big house, return the name stored in the forced_nick column of prison_table. If user cannot be found in prison, or if his sentence has expired, return nothing. Data must be provided as params. AP... | 3 | stack_v2_sparse_classes_30k_train_000691 | Implement the Python class `SuperstarifyView` described below.
Class description:
Implement the SuperstarifyView class.
Method signatures and docstrings:
- def get(self, params=None): Check if the user is currently in superstar-prison. If user is currently servin' his sentence in the big house, return the name stored... | Implement the Python class `SuperstarifyView` described below.
Class description:
Implement the SuperstarifyView class.
Method signatures and docstrings:
- def get(self, params=None): Check if the user is currently in superstar-prison. If user is currently servin' his sentence in the big house, return the name stored... | bc87a43b3fc1ff3424b1c9603b0a35b28f2c3896 | <|skeleton|>
class SuperstarifyView:
def get(self, params=None):
"""Check if the user is currently in superstar-prison. If user is currently servin' his sentence in the big house, return the name stored in the forced_nick column of prison_table. If user cannot be found in prison, or if his sentence has exp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SuperstarifyView:
def get(self, params=None):
"""Check if the user is currently in superstar-prison. If user is currently servin' his sentence in the big house, return the name stored in the forced_nick column of prison_table. If user cannot be found in prison, or if his sentence has expired, return n... | the_stack_v2_python_sparse | pysite/views/api/bot/superstarify.py | landizz/site | train | 0 | |
eab34f8ac29168d50aca50b6ac8c9332437525b9 | [
"res = super(ManageCusomerBadge, self).default_get(fields)\ncustomer_id = self.env.context.get('default_customer_id')\nif customer_id:\n customer = self.env['res.partner'].browse(customer_id)\nif customer.exists():\n if 'flsp_cb_id' in fields:\n res['flsp_cb_id'] = customer.flsp_cb_id\nres = self._conv... | <|body_start_0|>
res = super(ManageCusomerBadge, self).default_get(fields)
customer_id = self.env.context.get('default_customer_id')
if customer_id:
customer = self.env['res.partner'].browse(customer_id)
if customer.exists():
if 'flsp_cb_id' in fields:
... | Class_Name: ManageCusomerBadge Model_Name: flsp.manage.customer.badge Purpose: To create a model used in the wizard to manage customer badge Date: April/09th/2021 Author: Perry He | ManageCusomerBadge | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageCusomerBadge:
"""Class_Name: ManageCusomerBadge Model_Name: flsp.manage.customer.badge Purpose: To create a model used in the wizard to manage customer badge Date: April/09th/2021 Author: Perry He"""
def default_get(self, fields):
"""Purpose: to get the default values from the ... | stack_v2_sparse_classes_10k_train_004388 | 3,247 | no_license | [
{
"docstring": "Purpose: to get the default values from the customer model and load in the wizard",
"name": "default_get",
"signature": "def default_get(self, fields)"
},
{
"docstring": "Purpose: 1) Button used in wizard to add/update the badge 2) send the email only when it is done",
"name"... | 3 | null | Implement the Python class `ManageCusomerBadge` described below.
Class description:
Class_Name: ManageCusomerBadge Model_Name: flsp.manage.customer.badge Purpose: To create a model used in the wizard to manage customer badge Date: April/09th/2021 Author: Perry He
Method signatures and docstrings:
- def default_get(se... | Implement the Python class `ManageCusomerBadge` described below.
Class description:
Class_Name: ManageCusomerBadge Model_Name: flsp.manage.customer.badge Purpose: To create a model used in the wizard to manage customer badge Date: April/09th/2021 Author: Perry He
Method signatures and docstrings:
- def default_get(se... | 4a82cd5cfd1898c6da860cb68dff3a14e037bbad | <|skeleton|>
class ManageCusomerBadge:
"""Class_Name: ManageCusomerBadge Model_Name: flsp.manage.customer.badge Purpose: To create a model used in the wizard to manage customer badge Date: April/09th/2021 Author: Perry He"""
def default_get(self, fields):
"""Purpose: to get the default values from the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManageCusomerBadge:
"""Class_Name: ManageCusomerBadge Model_Name: flsp.manage.customer.badge Purpose: To create a model used in the wizard to manage customer badge Date: April/09th/2021 Author: Perry He"""
def default_get(self, fields):
"""Purpose: to get the default values from the customer mode... | the_stack_v2_python_sparse | flsp-salesorder/models/manage_customer_badge_wizard.py | odoo-smg/firstlight | train | 3 |
60b2fba24c18be3fd65449e31e24574a42f9166d | [
"super(AnaphoraDocumentGraph, self).__init__()\nself.name = name if name else os.path.basename(anaphora_filepath)\nself.ns = namespace\nself.root = self.ns + ':root_node'\nself.tokens = []\nif anaphora_filepath:\n self.add_node(self.root, layers={self.ns})\n with open(anaphora_filepath, 'r') as anno_file:\n ... | <|body_start_0|>
super(AnaphoraDocumentGraph, self).__init__()
self.name = name if name else os.path.basename(anaphora_filepath)
self.ns = namespace
self.root = self.ns + ':root_node'
self.tokens = []
if anaphora_filepath:
self.add_node(self.root, layers={self... | represents a text in which abstract anaphora were annotated as a graph. Attributes ---------- ns : str the namespace of the graph (default: anaphoricity) tokens : list of int a list of node IDs (int) which represent the tokens in the order they occur in the text root : str name of the document root node ID (default: se... | AnaphoraDocumentGraph | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnaphoraDocumentGraph:
"""represents a text in which abstract anaphora were annotated as a graph. Attributes ---------- ns : str the namespace of the graph (default: anaphoricity) tokens : list of int a list of node IDs (int) which represent the tokens in the order they occur in the text root : s... | stack_v2_sparse_classes_10k_train_004389 | 7,148 | permissive | [
{
"docstring": "Reads an abstract anaphora annotation file, creates a directed graph and adds a node for each token, as well as an edge from the root node to each token. If a token is annotated, it will have a 'namespace:annotation' attribute, which maps to a dict with the keys 'anaphoricity' (str) and 'certain... | 2 | stack_v2_sparse_classes_30k_train_000271 | Implement the Python class `AnaphoraDocumentGraph` described below.
Class description:
represents a text in which abstract anaphora were annotated as a graph. Attributes ---------- ns : str the namespace of the graph (default: anaphoricity) tokens : list of int a list of node IDs (int) which represent the tokens in th... | Implement the Python class `AnaphoraDocumentGraph` described below.
Class description:
represents a text in which abstract anaphora were annotated as a graph. Attributes ---------- ns : str the namespace of the graph (default: anaphoricity) tokens : list of int a list of node IDs (int) which represent the tokens in th... | 108fea5a7f61030a9c11708296e06ee8ccfd7783 | <|skeleton|>
class AnaphoraDocumentGraph:
"""represents a text in which abstract anaphora were annotated as a graph. Attributes ---------- ns : str the namespace of the graph (default: anaphoricity) tokens : list of int a list of node IDs (int) which represent the tokens in the order they occur in the text root : s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AnaphoraDocumentGraph:
"""represents a text in which abstract anaphora were annotated as a graph. Attributes ---------- ns : str the namespace of the graph (default: anaphoricity) tokens : list of int a list of node IDs (int) which represent the tokens in the order they occur in the text root : str name of th... | the_stack_v2_python_sparse | src/discoursegraphs/readwrite/anaphoricity.py | dav009/discoursegraphs | train | 1 |
ae1484874866b0cae3797d25c09cef62088d97b4 | [
"res = ''\nfor e in strs:\n res += str(len(e)) + ':' + e\nreturn res",
"ans = []\ni = 0\nwhile i < len(s):\n index = s.find(':', i)\n size = int(s[i:index])\n print(s[i:index])\n ans.append(s[index + 1:index + 1 + size])\n i = index + 1 + size\nreturn ans"
] | <|body_start_0|>
res = ''
for e in strs:
res += str(len(e)) + ':' + e
return res
<|end_body_0|>
<|body_start_1|>
ans = []
i = 0
while i < len(s):
index = s.find(':', i)
size = int(s[i:index])
print(s[i:index])
a... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k_train_004390 | 854 | no_license | [
{
"docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str",
"name": "encode",
"signature": "def encode(self, strs)"
},
{
"docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]",
"name": "decode",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_004320 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type... | 0bab7ee631af6b45c0c1322fcc8ae26b6280a7d6 | <|skeleton|>
class Solution:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
res = ''
for e in strs:
res += str(len(e)) + ':' + e
return res
def decode(self, s):
"""Decodes a single string to a list of strings.... | the_stack_v2_python_sparse | python/271.encode_decode_strings.py | xiang525/leetcode_2018 | train | 0 | |
f53e8d47c874f62e63b8b4e7a2f1b6c2e94f4df6 | [
"try:\n updated_exp_model = exp_services.populate_exp_model_fields(exp_model, migrated_exp)\n commit_message = 'Update exploration states schema version to %d.' % feconf.CURRENT_STATE_SCHEMA_VERSION\n models_to_put_values = []\n with datastore_services.get_ndb_context():\n models_to_put_values = ... | <|body_start_0|>
try:
updated_exp_model = exp_services.populate_exp_model_fields(exp_model, migrated_exp)
commit_message = 'Update exploration states schema version to %d.' % feconf.CURRENT_STATE_SCHEMA_VERSION
models_to_put_values = []
with datastore_services.get... | Job that migrates Exploration models. | MigrateExplorationJob | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MigrateExplorationJob:
"""Job that migrates Exploration models."""
def _update_exploration(exp_model: exp_models.ExplorationModel, migrated_exp: exp_domain.Exploration, exp_changes: Sequence[exp_domain.ExplorationChange]) -> result.Result[Tuple[base_models.BaseModel], Tuple[str, Exception]]:... | stack_v2_sparse_classes_10k_train_004391 | 28,752 | permissive | [
{
"docstring": "Generates newly updated exploration models. Args: exp_model: ExplorationModel. The exploration which should be updated. migrated_exp: Exploration. The migrated exploration domain object. exp_changes: Sequence(ExplorationChange). The exploration changes to apply. Returns: Sequence(BaseModel). Seq... | 2 | null | Implement the Python class `MigrateExplorationJob` described below.
Class description:
Job that migrates Exploration models.
Method signatures and docstrings:
- def _update_exploration(exp_model: exp_models.ExplorationModel, migrated_exp: exp_domain.Exploration, exp_changes: Sequence[exp_domain.ExplorationChange]) ->... | Implement the Python class `MigrateExplorationJob` described below.
Class description:
Job that migrates Exploration models.
Method signatures and docstrings:
- def _update_exploration(exp_model: exp_models.ExplorationModel, migrated_exp: exp_domain.Exploration, exp_changes: Sequence[exp_domain.ExplorationChange]) ->... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class MigrateExplorationJob:
"""Job that migrates Exploration models."""
def _update_exploration(exp_model: exp_models.ExplorationModel, migrated_exp: exp_domain.Exploration, exp_changes: Sequence[exp_domain.ExplorationChange]) -> result.Result[Tuple[base_models.BaseModel], Tuple[str, Exception]]:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MigrateExplorationJob:
"""Job that migrates Exploration models."""
def _update_exploration(exp_model: exp_models.ExplorationModel, migrated_exp: exp_domain.Exploration, exp_changes: Sequence[exp_domain.ExplorationChange]) -> result.Result[Tuple[base_models.BaseModel], Tuple[str, Exception]]:
"""G... | the_stack_v2_python_sparse | core/jobs/batch_jobs/exp_migration_jobs.py | oppia/oppia | train | 6,172 |
5db9854cf3c0f1fc3907b81fa0b4d06bb72cb2d8 | [
"left, right = (0, len(height) - 1)\nleft_max = right_max = area = 0\nwhile left < right:\n if height[left] < height[right]:\n if height[left] >= left_max:\n left_max = height[left]\n area += left_max - height[left]\n left += 1\n else:\n if height[right] >= right_max:\n ... | <|body_start_0|>
left, right = (0, len(height) - 1)
left_max = right_max = area = 0
while left < right:
if height[left] < height[right]:
if height[left] >= left_max:
left_max = height[left]
area += left_max - height[left]
... | Formulae to find trapping rain water: elevation = [0, 2, 3] [0, 1, 2] current_index = 1 water_area = minimum( maximum(elevation[previous], elevation[current]), maximum(elevation[current], elevation[next]) ) - elevation[current] | ElevationMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElevationMap:
"""Formulae to find trapping rain water: elevation = [0, 2, 3] [0, 1, 2] current_index = 1 water_area = minimum( maximum(elevation[previous], elevation[current]), maximum(elevation[current], elevation[next]) ) - elevation[current]"""
def get_trapped_rain_water_area(self, height... | stack_v2_sparse_classes_10k_train_004392 | 5,285 | no_license | [
{
"docstring": "Approach: Two Pointers Time Complexity: O(n) Space Complexity: O(1) Algorithm: - Initialize left and right pointer with 0 and last elevation position - loop until left is less than right - if elevation of left positioned is less then elevation of right positioned - if left elevation is greater t... | 3 | null | Implement the Python class `ElevationMap` described below.
Class description:
Formulae to find trapping rain water: elevation = [0, 2, 3] [0, 1, 2] current_index = 1 water_area = minimum( maximum(elevation[previous], elevation[current]), maximum(elevation[current], elevation[next]) ) - elevation[current]
Method signa... | Implement the Python class `ElevationMap` described below.
Class description:
Formulae to find trapping rain water: elevation = [0, 2, 3] [0, 1, 2] current_index = 1 water_area = minimum( maximum(elevation[previous], elevation[current]), maximum(elevation[current], elevation[next]) ) - elevation[current]
Method signa... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class ElevationMap:
"""Formulae to find trapping rain water: elevation = [0, 2, 3] [0, 1, 2] current_index = 1 water_area = minimum( maximum(elevation[previous], elevation[current]), maximum(elevation[current], elevation[next]) ) - elevation[current]"""
def get_trapped_rain_water_area(self, height... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ElevationMap:
"""Formulae to find trapping rain water: elevation = [0, 2, 3] [0, 1, 2] current_index = 1 water_area = minimum( maximum(elevation[previous], elevation[current]), maximum(elevation[current], elevation[next]) ) - elevation[current]"""
def get_trapped_rain_water_area(self, height: List[int]) ... | the_stack_v2_python_sparse | data_structures/trapping_rain_water.py | Shiv2157k/leet_code | train | 1 |
76d8394392631cadec6be80a7152b68608f87a2e | [
"super().__init__(*args, **kwargs)\nxblock_resource_info = {(xblock_resource_pkg(xblock_class), xblock_class.get_resources_dir()) for __, xblock_class in XBlock.load_classes()}\nself.package_storages = [XBlockPackageStorage(pkg_name, resources_dir) for pkg_name, resources_dir in xblock_resource_info]",
"for stora... | <|body_start_0|>
super().__init__(*args, **kwargs)
xblock_resource_info = {(xblock_resource_pkg(xblock_class), xblock_class.get_resources_dir()) for __, xblock_class in XBlock.load_classes()}
self.package_storages = [XBlockPackageStorage(pkg_name, resources_dir) for pkg_name, resources_dir in xb... | A static files finder that gets static assets from xblocks. | XBlockPipelineFinder | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XBlockPipelineFinder:
"""A static files finder that gets static assets from xblocks."""
def __init__(self, *args, **kwargs):
"""The XBlockPipelineFinder creates a separate XBlockPackageStorage for every installed XBlock package when its initialized. After that initialization happens,... | stack_v2_sparse_classes_10k_train_004393 | 5,498 | permissive | [
{
"docstring": "The XBlockPipelineFinder creates a separate XBlockPackageStorage for every installed XBlock package when its initialized. After that initialization happens, we just proxy all list()/find() requests by iterating through the XBlockPackageStorage objects.",
"name": "__init__",
"signature": ... | 3 | null | Implement the Python class `XBlockPipelineFinder` described below.
Class description:
A static files finder that gets static assets from xblocks.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): The XBlockPipelineFinder creates a separate XBlockPackageStorage for every installed XBlock package... | Implement the Python class `XBlockPipelineFinder` described below.
Class description:
A static files finder that gets static assets from xblocks.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): The XBlockPipelineFinder creates a separate XBlockPackageStorage for every installed XBlock package... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class XBlockPipelineFinder:
"""A static files finder that gets static assets from xblocks."""
def __init__(self, *args, **kwargs):
"""The XBlockPipelineFinder creates a separate XBlockPackageStorage for every installed XBlock package when its initialized. After that initialization happens,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class XBlockPipelineFinder:
"""A static files finder that gets static assets from xblocks."""
def __init__(self, *args, **kwargs):
"""The XBlockPipelineFinder creates a separate XBlockPackageStorage for every installed XBlock package when its initialized. After that initialization happens, we just prox... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/lib/xblock_pipeline/finder.py | luque/better-ways-of-thinking-about-software | train | 3 |
a754919e854bb13f1e283e8e8fada59e9c1298c1 | [
"self.r = 0\nself.c = 0\nself.l = vec2d",
"re = self.l[self.r][self.c]\nself.c += 1\nreturn re",
"while self.r < len(self.l):\n if self.c < len(self.l[self.r]):\n return True\n self.r += 1\n self.c = 0\nreturn False"
] | <|body_start_0|>
self.r = 0
self.c = 0
self.l = vec2d
<|end_body_0|>
<|body_start_1|>
re = self.l[self.r][self.c]
self.c += 1
return re
<|end_body_1|>
<|body_start_2|>
while self.r < len(self.l):
if self.c < len(self.l[self.r]):
retur... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_10k_train_004394 | 1,584 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | null | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | fe79161211cc08c269cde9e1fdcfed27de11f2cb | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.r = 0
self.c = 0
self.l = vec2d
def next(self):
""":rtype: int"""
re = self.l[self.r][self.c]
self.c += 1
return re
def ha... | the_stack_v2_python_sparse | MyLeetCode/python/Flatten 2D Vector.py | ihuei801/leetcode | train | 0 | |
bb420c3ec2693ce5b78109d5345a5fd7bfe2935b | [
"shared = SharedObjects.get()\nself.flagmaterial = ba.Material()\nself.flagmaterial.add_actions(conditions=(('we_are_younger_than', 100), 'and', ('they_have_material', shared.object_material)), actions=('modify_node_collision', 'collide', False))\nself.flagmaterial.add_actions(conditions=('they_have_material', shar... | <|body_start_0|>
shared = SharedObjects.get()
self.flagmaterial = ba.Material()
self.flagmaterial.add_actions(conditions=(('we_are_younger_than', 100), 'and', ('they_have_material', shared.object_material)), actions=('modify_node_collision', 'collide', False))
self.flagmaterial.add_actio... | Wraps up media and other resources used by ba.Flags. category: Gameplay Classes A single instance of this is shared between all flags and can be retrieved via bastd.actor.flag.get_factory(). Attributes: flagmaterial The ba.Material applied to all ba.Flags. impact_sound The ba.Sound used when a ba.Flag hits the ground. ... | FlagFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlagFactory:
"""Wraps up media and other resources used by ba.Flags. category: Gameplay Classes A single instance of this is shared between all flags and can be retrieved via bastd.actor.flag.get_factory(). Attributes: flagmaterial The ba.Material applied to all ba.Flags. impact_sound The ba.Soun... | stack_v2_sparse_classes_10k_train_004395 | 13,816 | permissive | [
{
"docstring": "Instantiate a FlagFactory. You shouldn't need to do this; call bastd.actor.flag.get_factory() to get a shared instance.",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Get/create a shared FlagFactory instance.",
"name": "get",
"signature... | 2 | null | Implement the Python class `FlagFactory` described below.
Class description:
Wraps up media and other resources used by ba.Flags. category: Gameplay Classes A single instance of this is shared between all flags and can be retrieved via bastd.actor.flag.get_factory(). Attributes: flagmaterial The ba.Material applied to... | Implement the Python class `FlagFactory` described below.
Class description:
Wraps up media and other resources used by ba.Flags. category: Gameplay Classes A single instance of this is shared between all flags and can be retrieved via bastd.actor.flag.get_factory(). Attributes: flagmaterial The ba.Material applied to... | 3ffeff8ce401a00128363ff08b406471092adaa9 | <|skeleton|>
class FlagFactory:
"""Wraps up media and other resources used by ba.Flags. category: Gameplay Classes A single instance of this is shared between all flags and can be retrieved via bastd.actor.flag.get_factory(). Attributes: flagmaterial The ba.Material applied to all ba.Flags. impact_sound The ba.Soun... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FlagFactory:
"""Wraps up media and other resources used by ba.Flags. category: Gameplay Classes A single instance of this is shared between all flags and can be retrieved via bastd.actor.flag.get_factory(). Attributes: flagmaterial The ba.Material applied to all ba.Flags. impact_sound The ba.Sound used when a... | the_stack_v2_python_sparse | assets/src/ba_data/python/bastd/actor/flag.py | kakekakeka/ballistica | train | 2 |
942a1b7180ca41a8a3f2996b4b7f16f2f4ff2ae7 | [
"patient_id = data['patient_id']\npatient = Patient(data['patient'])\nanamnesis = Anamnesis(data['anamnesis'])\nrecord = Record(patient_id, patient, anamnesis)\nfilename = '{}.json'.format(str(random.randint(10000, 99999)))\nfilepath = os.path.join(os.getcwd(), self.DEFAULT_PATH_TO_PENDING_BLOCK, filename)\nwith op... | <|body_start_0|>
patient_id = data['patient_id']
patient = Patient(data['patient'])
anamnesis = Anamnesis(data['anamnesis'])
record = Record(patient_id, patient, anamnesis)
filename = '{}.json'.format(str(random.randint(10000, 99999)))
filepath = os.path.join(os.getcwd(),... | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
def add(self, data):
"""Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis"""
<|body_0|>
def get(self, id):
"""Mengambil data berdasarkan ID yang ada"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_004396 | 1,571 | no_license | [
{
"docstring": "Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis",
"name": "add",
"signature": "def add(self, data)"
},
{
"docstring": "Mengambil data berdasarkan ID yang ada",
"name": "get",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_003029 | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def add(self, data): Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis
- def get(self, id): M... | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def add(self, data): Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis
- def get(self, id): M... | 8e55e77f6a89e0e4fef60da38c318fcf97b551a3 | <|skeleton|>
class Controller:
def add(self, data):
"""Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis"""
<|body_0|>
def get(self, id):
"""Mengambil data berdasarkan ID yang ada"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Controller:
def add(self, data):
"""Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis"""
patient_id = data['patient_id']
patient = Patient(data['patient'])
anamnesis = Anamnesis(data['anamnesis'])
... | the_stack_v2_python_sparse | Distributed/Puskesmas Manado/Data/components/Controller.py | chlengkey/medchain-peer | train | 0 | |
36d2653943b5703d04b9bd44d62feace2bd260ac | [
"product_data_queue_obj = self.env['shopify.product.data.queue.ept']\nir_model_obj = self.env['ir.model']\ncommon_log_book_obj = self.env['common.log.book.ept']\nquery = \"select queue.id\\n from shopify_product_data_queue_line_ept as queue_line\\n inner join shopify_product_data_queue... | <|body_start_0|>
product_data_queue_obj = self.env['shopify.product.data.queue.ept']
ir_model_obj = self.env['ir.model']
common_log_book_obj = self.env['common.log.book.ept']
query = "select queue.id\n from shopify_product_data_queue_line_ept as queue_line\n ... | ShopifyProductDataQueueLineEpt | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShopifyProductDataQueueLineEpt:
def auto_import_product_queue_line_data(self):
"""This method used to process synced shopify product data in batch of 100 queue lines. @author: Maulik Barad on Date 31-Aug-2020."""
<|body_0|>
def process_product_queue_line_data(self):
... | stack_v2_sparse_classes_10k_train_004397 | 6,365 | no_license | [
{
"docstring": "This method used to process synced shopify product data in batch of 100 queue lines. @author: Maulik Barad on Date 31-Aug-2020.",
"name": "auto_import_product_queue_line_data",
"signature": "def auto_import_product_queue_line_data(self)"
},
{
"docstring": "This method processes p... | 3 | stack_v2_sparse_classes_30k_train_006056 | Implement the Python class `ShopifyProductDataQueueLineEpt` described below.
Class description:
Implement the ShopifyProductDataQueueLineEpt class.
Method signatures and docstrings:
- def auto_import_product_queue_line_data(self): This method used to process synced shopify product data in batch of 100 queue lines. @a... | Implement the Python class `ShopifyProductDataQueueLineEpt` described below.
Class description:
Implement the ShopifyProductDataQueueLineEpt class.
Method signatures and docstrings:
- def auto_import_product_queue_line_data(self): This method used to process synced shopify product data in batch of 100 queue lines. @a... | 581b23342122c0568407c1c42efd4b2085719335 | <|skeleton|>
class ShopifyProductDataQueueLineEpt:
def auto_import_product_queue_line_data(self):
"""This method used to process synced shopify product data in batch of 100 queue lines. @author: Maulik Barad on Date 31-Aug-2020."""
<|body_0|>
def process_product_queue_line_data(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ShopifyProductDataQueueLineEpt:
def auto_import_product_queue_line_data(self):
"""This method used to process synced shopify product data in batch of 100 queue lines. @author: Maulik Barad on Date 31-Aug-2020."""
product_data_queue_obj = self.env['shopify.product.data.queue.ept']
ir_mo... | the_stack_v2_python_sparse | modules/shopify_ept/models/product_data_queue_line.py | yspcn/odoo14-import | train | 0 | |
89bb95569b2c036cf44fa64b7ddcedfa740036f6 | [
"self.wave = wave\nself.flux = flux\nself.ivar = ivar\nself.mask = mask\nself.resolution_data = resolution_data\nself.fibermap = fibermap\nself.header = header\nself.meta = header\nself.scores = scores",
"if not isinstance(index, slice):\n index = np.atleast_1d(index)\nif self.scores is not None:\n scores =... | <|body_start_0|>
self.wave = wave
self.flux = flux
self.ivar = ivar
self.mask = mask
self.resolution_data = resolution_data
self.fibermap = fibermap
self.header = header
self.meta = header
self.scores = scores
<|end_body_0|>
<|body_start_1|>
... | Lightweight Frame object for regrouping This is intended for I/O without the overheads of float32 -> float64 conversion, correcting endianness, etc. | FrameLite | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrameLite:
"""Lightweight Frame object for regrouping This is intended for I/O without the overheads of float32 -> float64 conversion, correcting endianness, etc."""
def __init__(self, wave, flux, ivar, mask, resolution_data, fibermap, header, scores=None):
"""Create a new FrameLite ... | stack_v2_sparse_classes_10k_train_004398 | 28,251 | permissive | [
{
"docstring": "Create a new FrameLite object Args: wave: 1D array of wavlengths flux: 2D[nspec, nwave] fluxes ivar: 2D[nspec, nwave] inverse variances of flux mask: 2D[nspec, nwave] mask of flux; 0=good resolution_data 3D[nspec, ndiag, nwave] Resolution matrix diagonals fibermap: fibermap table header: FITS he... | 3 | null | Implement the Python class `FrameLite` described below.
Class description:
Lightweight Frame object for regrouping This is intended for I/O without the overheads of float32 -> float64 conversion, correcting endianness, etc.
Method signatures and docstrings:
- def __init__(self, wave, flux, ivar, mask, resolution_data... | Implement the Python class `FrameLite` described below.
Class description:
Lightweight Frame object for regrouping This is intended for I/O without the overheads of float32 -> float64 conversion, correcting endianness, etc.
Method signatures and docstrings:
- def __init__(self, wave, flux, ivar, mask, resolution_data... | d75d0540cd07df1bf46130338a33c2ced51fbead | <|skeleton|>
class FrameLite:
"""Lightweight Frame object for regrouping This is intended for I/O without the overheads of float32 -> float64 conversion, correcting endianness, etc."""
def __init__(self, wave, flux, ivar, mask, resolution_data, fibermap, header, scores=None):
"""Create a new FrameLite ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FrameLite:
"""Lightweight Frame object for regrouping This is intended for I/O without the overheads of float32 -> float64 conversion, correcting endianness, etc."""
def __init__(self, wave, flux, ivar, mask, resolution_data, fibermap, header, scores=None):
"""Create a new FrameLite object Args: ... | the_stack_v2_python_sparse | py/desispec/pixgroup.py | desihub/desispec | train | 33 |
182149bb257971bc11799a4d521e5de50e7621ac | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn BookingService()",
"from .booking_price_type import BookingPriceType\nfrom .booking_question_assignment import BookingQuestionAssignment\nfrom .booking_reminder import BookingReminder\nfrom .booking_scheduling_policy import BookingSche... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return BookingService()
<|end_body_0|>
<|body_start_1|>
from .booking_price_type import BookingPriceType
from .booking_question_assignment import BookingQuestionAssignment
from .booking... | Represents a particular service offered by a booking business. | BookingService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookingService:
"""Represents a particular service offered by a booking business."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BookingService:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pars... | stack_v2_sparse_classes_10k_train_004399 | 9,420 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: BookingService",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | null | Implement the Python class `BookingService` described below.
Class description:
Represents a particular service offered by a booking business.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BookingService: Creates a new instance of the appropriate clas... | Implement the Python class `BookingService` described below.
Class description:
Represents a particular service offered by a booking business.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BookingService: Creates a new instance of the appropriate clas... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class BookingService:
"""Represents a particular service offered by a booking business."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BookingService:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pars... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BookingService:
"""Represents a particular service offered by a booking business."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BookingService:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use... | the_stack_v2_python_sparse | msgraph/generated/models/booking_service.py | microsoftgraph/msgraph-sdk-python | train | 135 |
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