blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e4b14379eb670afab61944937403deb312e03268 | [
"if num1 == num2:\n return 0\npos1 = []\npos2 = []\nfor i, v in enumerate(nums):\n if v == num1:\n pos1.append(i)\n if v == num2:\n pos2.append(i)\nif len(pos1) == 0 or len(pos2) == 0:\n return -1\nmindistance = len(nums)\nfor i in pos1:\n for j in pos2:\n t = abs(i - j)\n ... | <|body_start_0|>
if num1 == num2:
return 0
pos1 = []
pos2 = []
for i, v in enumerate(nums):
if v == num1:
pos1.append(i)
if v == num2:
pos2.append(i)
if len(pos1) == 0 or len(pos2) == 0:
return -1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDistance1(self, nums: List[int], num1: int, num2: int) -> int:
"""数组存在重复元素，求num1和num2的最短距离"""
<|body_0|>
def minDistance(self, nums: List[int], num1: int, num2: int) -> int:
"""数组存在重复元素，求num1和num2的最短距离 最优解"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_001800 | 1,707 | no_license | [
{
"docstring": "数组存在重复元素，求num1和num2的最短距离",
"name": "minDistance1",
"signature": "def minDistance1(self, nums: List[int], num1: int, num2: int) -> int"
},
{
"docstring": "数组存在重复元素，求num1和num2的最短距离 最优解",
"name": "minDistance",
"signature": "def minDistance(self, nums: List[int], num1: int, ... | 2 | stack_v2_sparse_classes_30k_train_013215 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance1(self, nums: List[int], num1: int, num2: int) -> int: 数组存在重复元素，求num1和num2的最短距离
- def minDistance(self, nums: List[int], num1: int, num2: int) -> int: 数组存在重复元素，求nu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance1(self, nums: List[int], num1: int, num2: int) -> int: 数组存在重复元素，求num1和num2的最短距离
- def minDistance(self, nums: List[int], num1: int, num2: int) -> int: 数组存在重复元素，求nu... | 3fd69b85f52af861ff7e2c74d8aacc515b192615 | <|skeleton|>
class Solution:
def minDistance1(self, nums: List[int], num1: int, num2: int) -> int:
"""数组存在重复元素，求num1和num2的最短距离"""
<|body_0|>
def minDistance(self, nums: List[int], num1: int, num2: int) -> int:
"""数组存在重复元素，求num1和num2的最短距离 最优解"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minDistance1(self, nums: List[int], num1: int, num2: int) -> int:
"""数组存在重复元素，求num1和num2的最短距离"""
if num1 == num2:
return 0
pos1 = []
pos2 = []
for i, v in enumerate(nums):
if v == num1:
pos1.append(i)
if ... | the_stack_v2_python_sparse | Other/NumsDistance.py | helloprogram6/leetcode_Cookbook_python | train | 0 | |
6d8fd81c0713e853944ff19070cb15a1af041ce7 | [
"db = connect(db_url)\ndb_proxy.initialize(db)\nWeatherStats.create_table()",
"stats = [stats] if not isinstance(stats, list) else stats\nfor stat in stats:\n _ = WeatherStats.insert(**stat.dict).on_conflict('replace').execute()",
"if end_date:\n stats = WeatherStats.select().where((WeatherStats.city == c... | <|body_start_0|>
db = connect(db_url)
db_proxy.initialize(db)
WeatherStats.create_table()
<|end_body_0|>
<|body_start_1|>
stats = [stats] if not isinstance(stats, list) else stats
for stat in stats:
_ = WeatherStats.insert(**stat.dict).on_conflict('replace').execute(... | Класс для работы с БД | DatabaseUpdater | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseUpdater:
"""Класс для работы с БД"""
def __init__(self, db_url):
""":param db_url: str Путь к бд. См. https://peewee.readthedocs.io/en/latest/peewee/playhouse.html#db-url"""
<|body_0|>
def add_stats(self, stats):
"""Добавляет прогноз в базу данных :param ... | stack_v2_sparse_classes_36k_train_001801 | 1,822 | no_license | [
{
"docstring": ":param db_url: str Путь к бд. См. https://peewee.readthedocs.io/en/latest/peewee/playhouse.html#db-url",
"name": "__init__",
"signature": "def __init__(self, db_url)"
},
{
"docstring": "Добавляет прогноз в базу данных :param stats: [Stats, ] список прогнозов погоды",
"name": ... | 3 | stack_v2_sparse_classes_30k_train_019483 | Implement the Python class `DatabaseUpdater` described below.
Class description:
Класс для работы с БД
Method signatures and docstrings:
- def __init__(self, db_url): :param db_url: str Путь к бд. См. https://peewee.readthedocs.io/en/latest/peewee/playhouse.html#db-url
- def add_stats(self, stats): Добавляет прогноз ... | Implement the Python class `DatabaseUpdater` described below.
Class description:
Класс для работы с БД
Method signatures and docstrings:
- def __init__(self, db_url): :param db_url: str Путь к бд. См. https://peewee.readthedocs.io/en/latest/peewee/playhouse.html#db-url
- def add_stats(self, stats): Добавляет прогноз ... | d2c0014dffccadb8232a1034e4ea9b427016a1d1 | <|skeleton|>
class DatabaseUpdater:
"""Класс для работы с БД"""
def __init__(self, db_url):
""":param db_url: str Путь к бд. См. https://peewee.readthedocs.io/en/latest/peewee/playhouse.html#db-url"""
<|body_0|>
def add_stats(self, stats):
"""Добавляет прогноз в базу данных :param ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatabaseUpdater:
"""Класс для работы с БД"""
def __init__(self, db_url):
""":param db_url: str Путь к бд. См. https://peewee.readthedocs.io/en/latest/peewee/playhouse.html#db-url"""
db = connect(db_url)
db_proxy.initialize(db)
WeatherStats.create_table()
def add_stats... | the_stack_v2_python_sparse | lesson_016/engine/db_updater.py | glotyuids/skillbox_learning | train | 0 |
36f781fa6b60eca68a5f6a3cd792800d741592b7 | [
"nums.sort()\nn = len(nums)\ncount = 0\npre = nums[0]\nif n == 1:\n return pre\nfor num in nums:\n if num != pre:\n if count == 1:\n return pre\n pre = num\n count = 1\n else:\n count += 1\nreturn num",
"sum = 0\nfor n in nums:\n sum ^= n\nreturn sum"
] | <|body_start_0|>
nums.sort()
n = len(nums)
count = 0
pre = nums[0]
if n == 1:
return pre
for num in nums:
if num != pre:
if count == 1:
return pre
pre = num
count = 1
e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def singleNumber0(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nums.sort()
n = len(nums)
... | stack_v2_sparse_classes_36k_train_001802 | 668 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "singleNumber",
"signature": "def singleNumber(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "singleNumber0",
"signature": "def singleNumber0(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def singleNumber(self, nums): :type nums: List[int] :rtype: int
- def singleNumber0(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 singleNumber(self, nums): :type nums: List[int] :rtype: int
- def singleNumber0(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def singleNu... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def singleNumber0(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
nums.sort()
n = len(nums)
count = 0
pre = nums[0]
if n == 1:
return pre
for num in nums:
if num != pre:
if count == 1:
... | the_stack_v2_python_sparse | PythonCode/src/0136_Single_Number.py | oneyuan/CodeforFun | train | 0 | |
13a705286855428685854833d92523ae412d3d60 | [
"dir_name = os.path.dirname(outfile)\ninfile_stub = P.snip(os.path.basename(infile), '.bam')\ncontrol_stub = P.snip(os.path.basename(controlfile), '.bam')\noutfile_stub = infile_stub + '_VS_' + control_stub\noutfile_stub = os.path.join(dir_name, outfile_stub)\nstatement = ['macs2 callpeak --treatment %(infile)s --c... | <|body_start_0|>
dir_name = os.path.dirname(outfile)
infile_stub = P.snip(os.path.basename(infile), '.bam')
control_stub = P.snip(os.path.basename(controlfile), '.bam')
outfile_stub = infile_stub + '_VS_' + control_stub
outfile_stub = os.path.join(dir_name, outfile_stub)
... | macs2IDRPeaks | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class macs2IDRPeaks:
def getRunStatement(self, infile, outfile, controlfile):
"""Generate a specific run statement for each peakcaller class"""
<|body_0|>
def postProcess(self, infile, outfile, controlfile):
"""Takes the narrowPeak files output by macs2. If macs2 given pva... | stack_v2_sparse_classes_36k_train_001803 | 19,216 | permissive | [
{
"docstring": "Generate a specific run statement for each peakcaller class",
"name": "getRunStatement",
"signature": "def getRunStatement(self, infile, outfile, controlfile)"
},
{
"docstring": "Takes the narrowPeak files output by macs2. If macs2 given pvalue, then sorts by column 8 (-log10(pva... | 2 | null | Implement the Python class `macs2IDRPeaks` described below.
Class description:
Implement the macs2IDRPeaks class.
Method signatures and docstrings:
- def getRunStatement(self, infile, outfile, controlfile): Generate a specific run statement for each peakcaller class
- def postProcess(self, infile, outfile, controlfil... | Implement the Python class `macs2IDRPeaks` described below.
Class description:
Implement the macs2IDRPeaks class.
Method signatures and docstrings:
- def getRunStatement(self, infile, outfile, controlfile): Generate a specific run statement for each peakcaller class
- def postProcess(self, infile, outfile, controlfil... | 7ae2e893a41f952c07f35b5cebb4c3c408d8477b | <|skeleton|>
class macs2IDRPeaks:
def getRunStatement(self, infile, outfile, controlfile):
"""Generate a specific run statement for each peakcaller class"""
<|body_0|>
def postProcess(self, infile, outfile, controlfile):
"""Takes the narrowPeak files output by macs2. If macs2 given pva... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class macs2IDRPeaks:
def getRunStatement(self, infile, outfile, controlfile):
"""Generate a specific run statement for each peakcaller class"""
dir_name = os.path.dirname(outfile)
infile_stub = P.snip(os.path.basename(infile), '.bam')
control_stub = P.snip(os.path.basename(controlfil... | the_stack_v2_python_sparse | obsolete/PipelineIDR.py | cgat-developers/cgat-flow | train | 13 | |
6863ad675ef48d1df9abc65224fc909dbd046a16 | [
"sorted_nums = sorted(nums)\nlength = len(nums)\nclosest = float('inf')\nfor a in range(length - 2):\n b = a + 1\n c = length - 1\n while b < c:\n s = sorted_nums[a] + sorted_nums[b] + sorted_nums[c]\n if s == target:\n return s\n if abs(target - s) < abs(target - closest):\... | <|body_start_0|>
sorted_nums = sorted(nums)
length = len(nums)
closest = float('inf')
for a in range(length - 2):
b = a + 1
c = length - 1
while b < c:
s = sorted_nums[a] + sorted_nums[b] + sorted_nums[c]
if s == target:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums, target):
"""Optimized solution First sort the list in ascending order and use two pointers to narrow down search. Time: O(n^2) Space: O(n) * if we sort the list in-place, this would be O(1) :type nums: List[int] :type target: int :rtype: int"""
... | stack_v2_sparse_classes_36k_train_001804 | 1,494 | no_license | [
{
"docstring": "Optimized solution First sort the list in ascending order and use two pointers to narrow down search. Time: O(n^2) Space: O(n) * if we sort the list in-place, this would be O(1) :type nums: List[int] :type target: int :rtype: int",
"name": "threeSumClosest",
"signature": "def threeSumClo... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums, target): Optimized solution First sort the list in ascending order and use two pointers to narrow down search. Time: O(n^2) Space: O(n) * if we so... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums, target): Optimized solution First sort the list in ascending order and use two pointers to narrow down search. Time: O(n^2) Space: O(n) * if we so... | c14d8829c95f61ff6691816e8c0de76b9319f389 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums, target):
"""Optimized solution First sort the list in ascending order and use two pointers to narrow down search. Time: O(n^2) Space: O(n) * if we sort the list in-place, this would be O(1) :type nums: List[int] :type target: int :rtype: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeSumClosest(self, nums, target):
"""Optimized solution First sort the list in ascending order and use two pointers to narrow down search. Time: O(n^2) Space: O(n) * if we sort the list in-place, this would be O(1) :type nums: List[int] :type target: int :rtype: int"""
sorted_... | the_stack_v2_python_sparse | medium/3sum-closest/solution.py | hsuanhauliu/leetcode-solutions | train | 0 | |
d6697b69f888aa83ef7cbd034c6a20d4dd7f0745 | [
"super(DeepLPFNet, self).__init__()\nself.backbonenet = unet.UNetModel()\nself.deeplpfnet = DeepLPFParameterPrediction()",
"feat = self.backbonenet(img)\nimg = self.deeplpfnet(feat)\nreturn img"
] | <|body_start_0|>
super(DeepLPFNet, self).__init__()
self.backbonenet = unet.UNetModel()
self.deeplpfnet = DeepLPFParameterPrediction()
<|end_body_0|>
<|body_start_1|>
feat = self.backbonenet(img)
img = self.deeplpfnet(feat)
return img
<|end_body_1|>
| DeepLPFNet | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepLPFNet:
def __init__(self):
"""Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A"""
<|body_0|>
def forward(self, img):
"""Neural network forward function :param img: forward the data img through the network :returns: residu... | stack_v2_sparse_classes_36k_train_001805 | 38,578 | permissive | [
{
"docstring": "Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Neural network forward function :param img: forward the data img through the network :returns: residual image :rtyp... | 2 | stack_v2_sparse_classes_30k_train_014160 | Implement the Python class `DeepLPFNet` described below.
Class description:
Implement the DeepLPFNet class.
Method signatures and docstrings:
- def __init__(self): Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A
- def forward(self, img): Neural network forward function :param... | Implement the Python class `DeepLPFNet` described below.
Class description:
Implement the DeepLPFNet class.
Method signatures and docstrings:
- def __init__(self): Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A
- def forward(self, img): Neural network forward function :param... | 82c49c36b76987a46dec8479793f7cf0150839c6 | <|skeleton|>
class DeepLPFNet:
def __init__(self):
"""Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A"""
<|body_0|>
def forward(self, img):
"""Neural network forward function :param img: forward the data img through the network :returns: residu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeepLPFNet:
def __init__(self):
"""Initialisation function :returns: initialises parameters of the neural networ :rtype: N/A"""
super(DeepLPFNet, self).__init__()
self.backbonenet = unet.UNetModel()
self.deeplpfnet = DeepLPFParameterPrediction()
def forward(self, img):
... | the_stack_v2_python_sparse | DeepLPF/model.py | huawei-noah/noah-research | train | 816 | |
e3444f0f65c68ffc8c264445b411017eb4b67aeb | [
"super().__init__(parent, Part.get_unscoped_name(part_name).split('.')[-1:])\nself.setFlags(Qt.ItemIsEnabled | Qt.ItemIsUserCheckable)\nself.setCheckState(0, Qt.Unchecked)\nself.part_name = part_name\nself.part = part\nself.target_availability = []",
"if len(self.target_availability) == 0:\n self.setForeground... | <|body_start_0|>
super().__init__(parent, Part.get_unscoped_name(part_name).split('.')[-1:])
self.setFlags(Qt.ItemIsEnabled | Qt.ItemIsUserCheckable)
self.setCheckState(0, Qt.Unchecked)
self.part_name = part_name
self.part = part
self.target_availability = []
<|end_body_0... | An item in a QTreeWidget that encapsulates a public part. | PartItem | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PartItem:
"""An item in a QTreeWidget that encapsulates a public part."""
def __init__(self, parent, part_name, part):
"""Initialise the item."""
<|body_0|>
def set_availability(self):
"""Set the availability of the part."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_001806 | 13,213 | permissive | [
{
"docstring": "Initialise the item.",
"name": "__init__",
"signature": "def __init__(self, parent, part_name, part)"
},
{
"docstring": "Set the availability of the part.",
"name": "set_availability",
"signature": "def set_availability(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006316 | Implement the Python class `PartItem` described below.
Class description:
An item in a QTreeWidget that encapsulates a public part.
Method signatures and docstrings:
- def __init__(self, parent, part_name, part): Initialise the item.
- def set_availability(self): Set the availability of the part. | Implement the Python class `PartItem` described below.
Class description:
An item in a QTreeWidget that encapsulates a public part.
Method signatures and docstrings:
- def __init__(self, parent, part_name, part): Initialise the item.
- def set_availability(self): Set the availability of the part.
<|skeleton|>
class ... | 4ed2b1b9a2407afcbffdf304020d42b81c4c8cdc | <|skeleton|>
class PartItem:
"""An item in a QTreeWidget that encapsulates a public part."""
def __init__(self, parent, part_name, part):
"""Initialise the item."""
<|body_0|>
def set_availability(self):
"""Set the availability of the part."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PartItem:
"""An item in a QTreeWidget that encapsulates a public part."""
def __init__(self, parent, part_name, part):
"""Initialise the item."""
super().__init__(parent, Part.get_unscoped_name(part_name).split('.')[-1:])
self.setFlags(Qt.ItemIsEnabled | Qt.ItemIsUserCheckable)
... | the_stack_v2_python_sparse | note/demo/pyqt_demo/pyqtdeploy-3.3.0/pyqtdeploy/gui/packages_page.py | onsunsl/onsunsl.github.io | train | 1 |
9b163d2f2dc761fcedc6068ae000b1c5faa7b4d5 | [
"try:\n qr_code = qrcode.make(message)\n qr_code.save('/')\n return True\nexcept:\n return False",
"print('Looking for valid QR code...')\nvid_stream = VideoStream('http://10.247.193.162:8080/video').start()\ntime.sleep(2.0)\nfound = set()\nwhile True:\n frame = vid_stream.read()\n frame = imuti... | <|body_start_0|>
try:
qr_code = qrcode.make(message)
qr_code.save('/')
return True
except:
return False
<|end_body_0|>
<|body_start_1|>
print('Looking for valid QR code...')
vid_stream = VideoStream('http://10.247.193.162:8080/video').star... | QR class for QR code authentication | Qr_auth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Qr_auth:
"""QR class for QR code authentication"""
def create_qr(self, message):
"""Function to create QR code"""
<|body_0|>
def read_qr(self):
"""Function to read QR code from IP Webcam"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_001807 | 2,307 | no_license | [
{
"docstring": "Function to create QR code",
"name": "create_qr",
"signature": "def create_qr(self, message)"
},
{
"docstring": "Function to read QR code from IP Webcam",
"name": "read_qr",
"signature": "def read_qr(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007525 | Implement the Python class `Qr_auth` described below.
Class description:
QR class for QR code authentication
Method signatures and docstrings:
- def create_qr(self, message): Function to create QR code
- def read_qr(self): Function to read QR code from IP Webcam | Implement the Python class `Qr_auth` described below.
Class description:
QR class for QR code authentication
Method signatures and docstrings:
- def create_qr(self, message): Function to create QR code
- def read_qr(self): Function to read QR code from IP Webcam
<|skeleton|>
class Qr_auth:
"""QR class for QR cod... | 8a54132766ce38a7e338218cc70fd58093edd820 | <|skeleton|>
class Qr_auth:
"""QR class for QR code authentication"""
def create_qr(self, message):
"""Function to create QR code"""
<|body_0|>
def read_qr(self):
"""Function to read QR code from IP Webcam"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Qr_auth:
"""QR class for QR code authentication"""
def create_qr(self, message):
"""Function to create QR code"""
try:
qr_code = qrcode.make(message)
qr_code.save('/')
return True
except:
return False
def read_qr(self):
... | the_stack_v2_python_sparse | AgentPi/qr_auth.py | chrisho251/Car-Share-IoT-Application | train | 0 |
b2214986256a7b21b23d166354d12bf373f729e3 | [
"self.message_received = message_container\nmessage = ''.join(message_container)\nmessage = message.split('X')[0]\nlogger.debug(f'the message after formatting and transforming: {message}')\nposes = message.split('|')\nposition_list = list()\nrotation_list = list()\nfor individual_pose in poses:\n position, rotat... | <|body_start_0|>
self.message_received = message_container
message = ''.join(message_container)
message = message.split('X')[0]
logger.debug(f'the message after formatting and transforming: {message}')
poses = message.split('|')
position_list = list()
rotation_lis... | InformationProcessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InformationProcessor:
async def process_hololens_data(self, message_container: List[str]) -> Tuple[List[float], List[float]]:
"""this method takes the data received from the hololens and processes into a data format which can be processed furhter The data may either be : 1. trans+quat 2.... | stack_v2_sparse_classes_36k_train_001808 | 3,853 | no_license | [
{
"docstring": "this method takes the data received from the hololens and processes into a data format which can be processed furhter The data may either be : 1. trans+quat 2. 3 rows of 4 elements =>rotationmatrix 3. list of n points The transmission format is as follows: 1. \"x,y,z:i,j,k,w|x,y,z:i,j,k,w|....X\... | 2 | stack_v2_sparse_classes_30k_test_000639 | Implement the Python class `InformationProcessor` described below.
Class description:
Implement the InformationProcessor class.
Method signatures and docstrings:
- async def process_hololens_data(self, message_container: List[str]) -> Tuple[List[float], List[float]]: this method takes the data received from the holol... | Implement the Python class `InformationProcessor` described below.
Class description:
Implement the InformationProcessor class.
Method signatures and docstrings:
- async def process_hololens_data(self, message_container: List[str]) -> Tuple[List[float], List[float]]: this method takes the data received from the holol... | f779f93d2672a6e6d2ecbf789bdf0322a210c1a5 | <|skeleton|>
class InformationProcessor:
async def process_hololens_data(self, message_container: List[str]) -> Tuple[List[float], List[float]]:
"""this method takes the data received from the hololens and processes into a data format which can be processed furhter The data may either be : 1. trans+quat 2.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InformationProcessor:
async def process_hololens_data(self, message_container: List[str]) -> Tuple[List[float], List[float]]:
"""this method takes the data received from the hololens and processes into a data format which can be processed furhter The data may either be : 1. trans+quat 2. 3 rows of 4 e... | the_stack_v2_python_sparse | backend_core/backend_utils/information_processor.py | MarvinGravert/Master_thesis_backend | train | 0 | |
e125e655a8febcb816ca069eaaa3bbd2076ae4e7 | [
"super(Conv1dGenerated, self).__init__()\nself.in_channels = in_channels\nself.out_channels = out_channels\nself.kernel_size = kernel_size\nself.groups = groups\nself.stride = stride\nself.padding = padding\nself.dilation = dilation\nself.bottleneck = nn.Linear(E_1, E_2) if E_1 is not None else nn.Parameter(torch.r... | <|body_start_0|>
super(Conv1dGenerated, self).__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.kernel_size = kernel_size
self.groups = groups
self.stride = stride
self.padding = padding
self.dilation = dilation
self.b... | 1D convolution with a kernel generated by a linear transformation of the instrument embedding | Conv1dGenerated | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv1dGenerated:
"""1D convolution with a kernel generated by a linear transformation of the instrument embedding"""
def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=False):
"""Arguments: E_1 {int} -- Dimension of th... | stack_v2_sparse_classes_36k_train_001809 | 37,269 | no_license | [
{
"docstring": "Arguments: E_1 {int} -- Dimension of the instrument embedding E_2 {int} -- Dimension of the instrument embedding bottleneck in_channels {int} -- Number of channels of the input out_channels {int} -- Number of channels of the output kernel_size {int} -- Kernel size of the convolution Keyword Argu... | 2 | stack_v2_sparse_classes_30k_train_015725 | Implement the Python class `Conv1dGenerated` described below.
Class description:
1D convolution with a kernel generated by a linear transformation of the instrument embedding
Method signatures and docstrings:
- def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, group... | Implement the Python class `Conv1dGenerated` described below.
Class description:
1D convolution with a kernel generated by a linear transformation of the instrument embedding
Method signatures and docstrings:
- def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, group... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Conv1dGenerated:
"""1D convolution with a kernel generated by a linear transformation of the instrument embedding"""
def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=False):
"""Arguments: E_1 {int} -- Dimension of th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Conv1dGenerated:
"""1D convolution with a kernel generated by a linear transformation of the instrument embedding"""
def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=False):
"""Arguments: E_1 {int} -- Dimension of the instrument ... | the_stack_v2_python_sparse | generated/test_pfnet_research_meta_tasnet.py | jansel/pytorch-jit-paritybench | train | 35 |
892cbc07a1524f47caaf9eddeb1e1485bb79c915 | [
"data = form.cleaned_data\nself.success_url = reverse('registered_courses', kwargs={'level': int(data['level']), 'semester': int(data['semester'])})\nreturn super().form_valid(form)",
"context = super().get_context_data(**kwargs)\ncontext['title_text'] = 'Choose Registered Courses To Display'\ncontext['detail_tex... | <|body_start_0|>
data = form.cleaned_data
self.success_url = reverse('registered_courses', kwargs={'level': int(data['level']), 'semester': int(data['semester'])})
return super().form_valid(form)
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(**kwargs)
contex... | View for choosing which registered course to display. Check that the user's account is still active. Redirects to registered_courses view on form valid. | ShowRegisteredCourseView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShowRegisteredCourseView:
"""View for choosing which registered course to display. Check that the user's account is still active. Redirects to registered_courses view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|bod... | stack_v2_sparse_classes_36k_train_001810 | 29,759 | no_license | [
{
"docstring": "Compute the success URL and call super.form_valid()",
"name": "form_valid",
"signature": "def form_valid(self, form)"
},
{
"docstring": "Return the data used in the templates rendering.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
... | 2 | stack_v2_sparse_classes_30k_train_000090 | Implement the Python class `ShowRegisteredCourseView` described below.
Class description:
View for choosing which registered course to display. Check that the user's account is still active. Redirects to registered_courses view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the... | Implement the Python class `ShowRegisteredCourseView` described below.
Class description:
View for choosing which registered course to display. Check that the user's account is still active. Redirects to registered_courses view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the... | 06bc577d01d3dbf6c425e03dcb903977a38e377c | <|skeleton|>
class ShowRegisteredCourseView:
"""View for choosing which registered course to display. Check that the user's account is still active. Redirects to registered_courses view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShowRegisteredCourseView:
"""View for choosing which registered course to display. Check that the user's account is still active. Redirects to registered_courses view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
data = form.cleane... | the_stack_v2_python_sparse | cbt/views.py | Festusali/CBTest | train | 6 |
6ceeea63df91d96bd9f043a37ad31b4253134693 | [
"super().__init__()\nif all((var is None for var in (hidden_conv_layers, n_filters, kernel_sizes, strides))):\n hidden_conv_layers = EncoderNet.DEFAULT_PARAMS['hidden_conv_layers']\n n_filters = EncoderNet.DEFAULT_PARAMS['n_filters']\n kernel_sizes = EncoderNet.DEFAULT_PARAMS['kernel_sizes']\n strides =... | <|body_start_0|>
super().__init__()
if all((var is None for var in (hidden_conv_layers, n_filters, kernel_sizes, strides))):
hidden_conv_layers = EncoderNet.DEFAULT_PARAMS['hidden_conv_layers']
n_filters = EncoderNet.DEFAULT_PARAMS['n_filters']
kernel_sizes = EncoderN... | Implementation of the encoder network, that encodes the input frames sequence into a distribution over the latent space and samples with the common reparametrization trick. The network expects the images to be concatenated along channel dimension. This means that if a batch of sequences has shape (batch_size, seq_len, ... | EncoderNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderNet:
"""Implementation of the encoder network, that encodes the input frames sequence into a distribution over the latent space and samples with the common reparametrization trick. The network expects the images to be concatenated along channel dimension. This means that if a batch of sequ... | stack_v2_sparse_classes_36k_train_001811 | 6,277 | permissive | [
{
"docstring": "Instantiate the convolutional layers that compose the input network with the appropriate shapes. If K is the total number of layers, then hidden_conv_layers = K - 2. The length of n_filters must be K - 1, and that of kernel_sizes and strides must be K. If all them are None, EncoderNet.DEFAULT_PA... | 2 | stack_v2_sparse_classes_30k_train_010067 | Implement the Python class `EncoderNet` described below.
Class description:
Implementation of the encoder network, that encodes the input frames sequence into a distribution over the latent space and samples with the common reparametrization trick. The network expects the images to be concatenated along channel dimens... | Implement the Python class `EncoderNet` described below.
Class description:
Implementation of the encoder network, that encodes the input frames sequence into a distribution over the latent space and samples with the common reparametrization trick. The network expects the images to be concatenated along channel dimens... | 702d3ff3aec40eba20e17c5a1612b5b0b1e2f831 | <|skeleton|>
class EncoderNet:
"""Implementation of the encoder network, that encodes the input frames sequence into a distribution over the latent space and samples with the common reparametrization trick. The network expects the images to be concatenated along channel dimension. This means that if a batch of sequ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderNet:
"""Implementation of the encoder network, that encodes the input frames sequence into a distribution over the latent space and samples with the common reparametrization trick. The network expects the images to be concatenated along channel dimension. This means that if a batch of sequences has sha... | the_stack_v2_python_sparse | networks/encoder_net.py | CampusAI/Hamiltonian-Generative-Networks | train | 35 |
58f5d344a33a5fcca3f0e93fa0cd831eaa8cfd76 | [
"try:\n advice = Advices.objects.filter(description=self.request.data['description'], type_diagnostic=self.request.data['type_diagnostic'], deleted=0)\nexcept:\n advice = None\nif advice:\n raise ValidationError({'description': ['Ya se registró esta recomendación.']})\nserializer.save()",
"try:\n advi... | <|body_start_0|>
try:
advice = Advices.objects.filter(description=self.request.data['description'], type_diagnostic=self.request.data['type_diagnostic'], deleted=0)
except:
advice = None
if advice:
raise ValidationError({'description': ['Ya se registró esta re... | Type diagnostic view FILTERS: 'id': ['exact'], 'description':['exact', 'icontains'], 'type_diagnostic':['exact',], 'created_at': ['exact', 'year', 'year__gte', 'year__lte', 'month', 'month__lte', 'month__gte', 'day', 'day__lte', 'day__gte', 'year__in', 'month__in', 'day__in'], 'created_by': ['exact'], | AdvicesViewSet | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdvicesViewSet:
"""Type diagnostic view FILTERS: 'id': ['exact'], 'description':['exact', 'icontains'], 'type_diagnostic':['exact',], 'created_at': ['exact', 'year', 'year__gte', 'year__lte', 'month', 'month__lte', 'month__gte', 'day', 'day__lte', 'day__gte', 'year__in', 'month__in', 'day__in'], ... | stack_v2_sparse_classes_36k_train_001812 | 3,244 | permissive | [
{
"docstring": "Overwrite create",
"name": "perform_create",
"signature": "def perform_create(self, serializer)"
},
{
"docstring": "Overwrite update",
"name": "perform_update",
"signature": "def perform_update(self, serializer)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010242 | Implement the Python class `AdvicesViewSet` described below.
Class description:
Type diagnostic view FILTERS: 'id': ['exact'], 'description':['exact', 'icontains'], 'type_diagnostic':['exact',], 'created_at': ['exact', 'year', 'year__gte', 'year__lte', 'month', 'month__lte', 'month__gte', 'day', 'day__lte', 'day__gte'... | Implement the Python class `AdvicesViewSet` described below.
Class description:
Type diagnostic view FILTERS: 'id': ['exact'], 'description':['exact', 'icontains'], 'type_diagnostic':['exact',], 'created_at': ['exact', 'year', 'year__gte', 'year__lte', 'month', 'month__lte', 'month__gte', 'day', 'day__lte', 'day__gte'... | 6a18a137e0a16138607413925727d7e5f8486777 | <|skeleton|>
class AdvicesViewSet:
"""Type diagnostic view FILTERS: 'id': ['exact'], 'description':['exact', 'icontains'], 'type_diagnostic':['exact',], 'created_at': ['exact', 'year', 'year__gte', 'year__lte', 'month', 'month__lte', 'month__gte', 'day', 'day__lte', 'day__gte', 'year__in', 'month__in', 'day__in'], ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdvicesViewSet:
"""Type diagnostic view FILTERS: 'id': ['exact'], 'description':['exact', 'icontains'], 'type_diagnostic':['exact',], 'created_at': ['exact', 'year', 'year__gte', 'year__lte', 'month', 'month__lte', 'month__gte', 'day', 'day__lte', 'day__gte', 'year__in', 'month__in', 'day__in'], 'created_by':... | the_stack_v2_python_sparse | api/views/advices.py | jcasmer/grow_control_backend | train | 2 |
386e3380ed2f0aa97b54aebfd55fe0ff611a2b34 | [
"django_logs = hub_container.get_logs().decode('utf-8')\nassert 'Running migrations' in django_logs\npsql_output = postgresql_container.exec_psql(\"SELECT COUNT(*) FROM information_schema.tables WHERE table_schema='public';\")\ncount = int(psql_output.output.strip())\nassert count > 0",
"client = hub_container.ht... | <|body_start_0|>
django_logs = hub_container.get_logs().decode('utf-8')
assert 'Running migrations' in django_logs
psql_output = postgresql_container.exec_psql("SELECT COUNT(*) FROM information_schema.tables WHERE table_schema='public';")
count = int(psql_output.output.strip())
a... | TestHubContainer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestHubContainer:
def test_db_tables_created(self, hub_container, postgresql_container):
"""When the Django container starts, it should run its migrations"""
<|body_0|>
def test_admin_page(self, hub_container, postgresql_container):
"""When we try to access the djang... | stack_v2_sparse_classes_36k_train_001813 | 1,166 | permissive | [
{
"docstring": "When the Django container starts, it should run its migrations",
"name": "test_db_tables_created",
"signature": "def test_db_tables_created(self, hub_container, postgresql_container)"
},
{
"docstring": "When we try to access the django admin page, it should be returned",
"nam... | 2 | null | Implement the Python class `TestHubContainer` described below.
Class description:
Implement the TestHubContainer class.
Method signatures and docstrings:
- def test_db_tables_created(self, hub_container, postgresql_container): When the Django container starts, it should run its migrations
- def test_admin_page(self, ... | Implement the Python class `TestHubContainer` described below.
Class description:
Implement the TestHubContainer class.
Method signatures and docstrings:
- def test_db_tables_created(self, hub_container, postgresql_container): When the Django container starts, it should run its migrations
- def test_admin_page(self, ... | e1ea0beaf079f4f4d5f9562fb9d9a4f0670f459f | <|skeleton|>
class TestHubContainer:
def test_db_tables_created(self, hub_container, postgresql_container):
"""When the Django container starts, it should run its migrations"""
<|body_0|>
def test_admin_page(self, hub_container, postgresql_container):
"""When we try to access the djang... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestHubContainer:
def test_db_tables_created(self, hub_container, postgresql_container):
"""When the Django container starts, it should run its migrations"""
django_logs = hub_container.get_logs().decode('utf-8')
assert 'Running migrations' in django_logs
psql_output = postgres... | the_stack_v2_python_sparse | seaworthy/test.py | praekeltfoundation/ndoh-hub | train | 0 | |
a41cbba17ea89f17dfcf3123be2ca308b2fdd219 | [
"unique_slug = slug = slugify(self.name)\nnum = 1\nwhile Tag.objects.filter(slug=unique_slug).exists():\n unique_slug = '{}-{}'.format(slug, num)\n num += 1\nreturn unique_slug",
"if not self.slug:\n self.slug = self._generate_unique_slug()\nsuper().save(*args, **kwargs)"
] | <|body_start_0|>
unique_slug = slug = slugify(self.name)
num = 1
while Tag.objects.filter(slug=unique_slug).exists():
unique_slug = '{}-{}'.format(slug, num)
num += 1
return unique_slug
<|end_body_0|>
<|body_start_1|>
if not self.slug:
self.sl... | Tag | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tag:
def _generate_unique_slug(self):
"""Generates a unique slug based on the tag name."""
<|body_0|>
def save(self, *args, **kwargs):
"""Tag save method. Before checking it creates a unique tag slug if does not exist already."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_001814 | 1,249 | permissive | [
{
"docstring": "Generates a unique slug based on the tag name.",
"name": "_generate_unique_slug",
"signature": "def _generate_unique_slug(self)"
},
{
"docstring": "Tag save method. Before checking it creates a unique tag slug if does not exist already.",
"name": "save",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_015075 | Implement the Python class `Tag` described below.
Class description:
Implement the Tag class.
Method signatures and docstrings:
- def _generate_unique_slug(self): Generates a unique slug based on the tag name.
- def save(self, *args, **kwargs): Tag save method. Before checking it creates a unique tag slug if does not... | Implement the Python class `Tag` described below.
Class description:
Implement the Tag class.
Method signatures and docstrings:
- def _generate_unique_slug(self): Generates a unique slug based on the tag name.
- def save(self, *args, **kwargs): Tag save method. Before checking it creates a unique tag slug if does not... | 11896f17d0a30d1ae7e7f0ee8ccd6ab7652b25a7 | <|skeleton|>
class Tag:
def _generate_unique_slug(self):
"""Generates a unique slug based on the tag name."""
<|body_0|>
def save(self, *args, **kwargs):
"""Tag save method. Before checking it creates a unique tag slug if does not exist already."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tag:
def _generate_unique_slug(self):
"""Generates a unique slug based on the tag name."""
unique_slug = slug = slugify(self.name)
num = 1
while Tag.objects.filter(slug=unique_slug).exists():
unique_slug = '{}-{}'.format(slug, num)
num += 1
retur... | the_stack_v2_python_sparse | tags/models.py | pkmanish2611/plio-backend | train | 0 | |
d25f54f2efc7874765e4adc0c2892d643feb27fb | [
"self.delete_old = False\nself.service = service\nself.config = config\nself.validate_config()\nself.events: dict[Calendar, list[Event]] = {}\nself.dst_src: dict[Calendar, list[Calendar]] = {}\nself.src_cals: set[Calendar] = set()\nself.dst_cals: set[Calendar] = set()\nself.lock = asyncio.Lock()",
"want_destinati... | <|body_start_0|>
self.delete_old = False
self.service = service
self.config = config
self.validate_config()
self.events: dict[Calendar, list[Event]] = {}
self.dst_src: dict[Calendar, list[Calendar]] = {}
self.src_cals: set[Calendar] = set()
self.dst_cals: ... | Google Calendar Aggregator. | GCalAggregator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GCalAggregator:
"""Google Calendar Aggregator."""
def __init__(self, service, config) -> None:
"""Initialize an Aggregator."""
<|body_0|>
def validate_config(self) -> None:
"""Validate the calendar names in the config."""
<|body_1|>
def load_calendar... | stack_v2_sparse_classes_36k_train_001815 | 17,423 | no_license | [
{
"docstring": "Initialize an Aggregator.",
"name": "__init__",
"signature": "def __init__(self, service, config) -> None"
},
{
"docstring": "Validate the calendar names in the config.",
"name": "validate_config",
"signature": "def validate_config(self) -> None"
},
{
"docstring":... | 6 | stack_v2_sparse_classes_30k_train_014505 | Implement the Python class `GCalAggregator` described below.
Class description:
Google Calendar Aggregator.
Method signatures and docstrings:
- def __init__(self, service, config) -> None: Initialize an Aggregator.
- def validate_config(self) -> None: Validate the calendar names in the config.
- def load_calendars(se... | Implement the Python class `GCalAggregator` described below.
Class description:
Google Calendar Aggregator.
Method signatures and docstrings:
- def __init__(self, service, config) -> None: Initialize an Aggregator.
- def validate_config(self) -> None: Validate the calendar names in the config.
- def load_calendars(se... | ce37b68f5e869b8fa9390c278aee716dda7f085d | <|skeleton|>
class GCalAggregator:
"""Google Calendar Aggregator."""
def __init__(self, service, config) -> None:
"""Initialize an Aggregator."""
<|body_0|>
def validate_config(self) -> None:
"""Validate the calendar names in the config."""
<|body_1|>
def load_calendar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GCalAggregator:
"""Google Calendar Aggregator."""
def __init__(self, service, config) -> None:
"""Initialize an Aggregator."""
self.delete_old = False
self.service = service
self.config = config
self.validate_config()
self.events: dict[Calendar, list[Event]... | the_stack_v2_python_sparse | gcal_aggregator/aggregate.py | IsaacG/python-projects | train | 1 |
4cab805cc8d6819f74aed5c0ab39268c11263522 | [
"if self.display_location != DISPLAY_LOCATIONS[0][0] and (not self.page):\n raise ValidationError({'page': 'This field is required'})\nreturn super().clean()",
"if not page:\n return cls.objects.none()\ndismissed = cls.dismissed(request)\nlocation = DISPLAY_LOCATIONS[1][0]\nnotices = cls.objects.all().filte... | <|body_start_0|>
if self.display_location != DISPLAY_LOCATIONS[0][0] and (not self.page):
raise ValidationError({'page': 'This field is required'})
return super().clean()
<|end_body_0|>
<|body_start_1|>
if not page:
return cls.objects.none()
dismissed = cls.dismi... | A snippet class for page notices. | PageNotice | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PageNotice:
"""A snippet class for page notices."""
def clean(self):
"""Page field is optional, so raise a validation error when a notice is not global."""
<|body_0|>
def get_notice(cls, page, request):
"""Class method for finding most specific notice to match a ... | stack_v2_sparse_classes_36k_train_001816 | 6,697 | permissive | [
{
"docstring": "Page field is optional, so raise a validation error when a notice is not global.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Class method for finding most specific notice to match a page.",
"name": "get_notice",
"signature": "def get_notice(cls, p... | 2 | null | Implement the Python class `PageNotice` described below.
Class description:
A snippet class for page notices.
Method signatures and docstrings:
- def clean(self): Page field is optional, so raise a validation error when a notice is not global.
- def get_notice(cls, page, request): Class method for finding most specif... | Implement the Python class `PageNotice` described below.
Class description:
A snippet class for page notices.
Method signatures and docstrings:
- def clean(self): Page field is optional, so raise a validation error when a notice is not global.
- def get_notice(cls, page, request): Class method for finding most specif... | 4cf7be72b6b3d0c46dcadcc9d9904b471215ea81 | <|skeleton|>
class PageNotice:
"""A snippet class for page notices."""
def clean(self):
"""Page field is optional, so raise a validation error when a notice is not global."""
<|body_0|>
def get_notice(cls, page, request):
"""Class method for finding most specific notice to match a ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PageNotice:
"""A snippet class for page notices."""
def clean(self):
"""Page field is optional, so raise a validation error when a notice is not global."""
if self.display_location != DISPLAY_LOCATIONS[0][0] and (not self.page):
raise ValidationError({'page': 'This field is re... | the_stack_v2_python_sparse | notices/models.py | IATI/IATI-Standard-Website | train | 4 |
f420d6fe0349a4db5d669fd5128fb93c6898bb0d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SharingInvitation()",
"from .identity_set import IdentitySet\nfrom .identity_set import IdentitySet\nfields: Dict[str, Callable[[Any], None]] = {'email': lambda n: setattr(self, 'email', n.get_str_value()), 'invitedBy': lambda n: setat... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return SharingInvitation()
<|end_body_0|>
<|body_start_1|>
from .identity_set import IdentitySet
from .identity_set import IdentitySet
fields: Dict[str, Callable[[Any], None]] = {'email... | SharingInvitation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SharingInvitation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharingInvitation:
"""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... | stack_v2_sparse_classes_36k_train_001817 | 3,527 | 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: SharingInvitation",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_v... | 3 | stack_v2_sparse_classes_30k_train_011291 | Implement the Python class `SharingInvitation` described below.
Class description:
Implement the SharingInvitation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharingInvitation: Creates a new instance of the appropriate class based on discrim... | Implement the Python class `SharingInvitation` described below.
Class description:
Implement the SharingInvitation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharingInvitation: Creates a new instance of the appropriate class based on discrim... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class SharingInvitation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharingInvitation:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SharingInvitation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharingInvitation:
"""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: Shar... | the_stack_v2_python_sparse | msgraph/generated/models/sharing_invitation.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
1e64394032698e6ddfc25913ea5923e7e8e750d0 | [
"self.meta_path = graph_saver.get_meta_and_checkpoint_path(working_dir)\nif starting_ops:\n self.starting_ops = starting_ops\nelse:\n self.starting_ops = []\nif ending_ops:\n self.ending_ops = ending_ops\nelse:\n self.ending_ops = []\nself.input_shape = input_shape\ngraph_saver.save_model_to_meta(model=... | <|body_start_0|>
self.meta_path = graph_saver.get_meta_and_checkpoint_path(working_dir)
if starting_ops:
self.starting_ops = starting_ops
else:
self.starting_ops = []
if ending_ops:
self.ending_ops = ending_ops
else:
self.ending_ops... | Stores, creates and updates the Layer database. Also stores compressible layers to model optimization. | LayerDatabase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerDatabase:
"""Stores, creates and updates the Layer database. Also stores compressible layers to model optimization."""
def __init__(self, model: tf.compat.v1.Session, input_shape: Union[Tuple, List[Tuple]], working_dir: str, starting_ops: List[str]=None, ending_ops: List[str]=None):
... | stack_v2_sparse_classes_36k_train_001818 | 11,506 | permissive | [
{
"docstring": ":param model: TensorFlow Session :param input_shape: tuple or list of tuples of input shapes to the model :param working_dir: path to working directory to store intermediate graphs :param starting_ops: Starting ops of the graph, used in a top down DFS search :param ending_ops: Ending ops of the ... | 6 | null | Implement the Python class `LayerDatabase` described below.
Class description:
Stores, creates and updates the Layer database. Also stores compressible layers to model optimization.
Method signatures and docstrings:
- def __init__(self, model: tf.compat.v1.Session, input_shape: Union[Tuple, List[Tuple]], working_dir:... | Implement the Python class `LayerDatabase` described below.
Class description:
Stores, creates and updates the Layer database. Also stores compressible layers to model optimization.
Method signatures and docstrings:
- def __init__(self, model: tf.compat.v1.Session, input_shape: Union[Tuple, List[Tuple]], working_dir:... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class LayerDatabase:
"""Stores, creates and updates the Layer database. Also stores compressible layers to model optimization."""
def __init__(self, model: tf.compat.v1.Session, input_shape: Union[Tuple, List[Tuple]], working_dir: str, starting_ops: List[str]=None, ending_ops: List[str]=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayerDatabase:
"""Stores, creates and updates the Layer database. Also stores compressible layers to model optimization."""
def __init__(self, model: tf.compat.v1.Session, input_shape: Union[Tuple, List[Tuple]], working_dir: str, starting_ops: List[str]=None, ending_ops: List[str]=None):
""":para... | the_stack_v2_python_sparse | TrainingExtensions/tensorflow/src/python/aimet_tensorflow/layer_database.py | quic/aimet | train | 1,676 |
f5a742cc3f4d3a074f29c6b122eea154e5c577d6 | [
"self.k = k\nself.model = model\nself.args = [list() for i in range(k)]",
"probs = tf.nn.softmax(logits, axis=-1)\ntopk_probs = tf.math.top_k(probs, self.k)[0].numpy()\ntopk_args = np.squeeze(tf.math.top_k(probs, self.k)[1].numpy())\n_ = [self.args[i].append(topk_args[i]) for i in range(self.k)]\ndec_input = np.a... | <|body_start_0|>
self.k = k
self.model = model
self.args = [list() for i in range(k)]
<|end_body_0|>
<|body_start_1|>
probs = tf.nn.softmax(logits, axis=-1)
topk_probs = tf.math.top_k(probs, self.k)[0].numpy()
topk_args = np.squeeze(tf.math.top_k(probs, self.k)[1].numpy(... | BeamSearch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeamSearch:
def __init__(self, k, model):
"""k- beam search width model- decoding model"""
<|body_0|>
def first_step(self, logits):
"""logits- (seqlen=1, target_vocab_size)"""
<|body_1|>
def multisteps(self, enc_input, dec_input, topk_probs, tar_vocab_si... | stack_v2_sparse_classes_36k_train_001819 | 2,733 | permissive | [
{
"docstring": "k- beam search width model- decoding model",
"name": "__init__",
"signature": "def __init__(self, k, model)"
},
{
"docstring": "logits- (seqlen=1, target_vocab_size)",
"name": "first_step",
"signature": "def first_step(self, logits)"
},
{
"docstring": "enc_input- ... | 5 | stack_v2_sparse_classes_30k_train_006406 | Implement the Python class `BeamSearch` described below.
Class description:
Implement the BeamSearch class.
Method signatures and docstrings:
- def __init__(self, k, model): k- beam search width model- decoding model
- def first_step(self, logits): logits- (seqlen=1, target_vocab_size)
- def multisteps(self, enc_inpu... | Implement the Python class `BeamSearch` described below.
Class description:
Implement the BeamSearch class.
Method signatures and docstrings:
- def __init__(self, k, model): k- beam search width model- decoding model
- def first_step(self, logits): logits- (seqlen=1, target_vocab_size)
- def multisteps(self, enc_inpu... | bdd5493cbb99c3eb1b12979745dacd20be62c51d | <|skeleton|>
class BeamSearch:
def __init__(self, k, model):
"""k- beam search width model- decoding model"""
<|body_0|>
def first_step(self, logits):
"""logits- (seqlen=1, target_vocab_size)"""
<|body_1|>
def multisteps(self, enc_input, dec_input, topk_probs, tar_vocab_si... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BeamSearch:
def __init__(self, k, model):
"""k- beam search width model- decoding model"""
self.k = k
self.model = model
self.args = [list() for i in range(k)]
def first_step(self, logits):
"""logits- (seqlen=1, target_vocab_size)"""
probs = tf.nn.softmax(l... | the_stack_v2_python_sparse | tf_lightning/utils/beam_search.py | MukundVarmaT/tf-lightning | train | 0 | |
20ef8e584e16577c207e2acd7e93d6bbf64f7b6e | [
"super(Generator, self).__init__()\nself.song_len, self.batch_size, self.num_feature = (song_len, batch_size, num_feature)\nself.rand_feature_dim = rand_feature_dim\n'Song Generator'\nself.fc1 = nn.Linear(self.rand_feature_dim * 2, num_hidden)\nself.lstm_g1 = nn.LSTMCell(num_hidden, num_hidden)\nself.ht1, self.ct1 ... | <|body_start_0|>
super(Generator, self).__init__()
self.song_len, self.batch_size, self.num_feature = (song_len, batch_size, num_feature)
self.rand_feature_dim = rand_feature_dim
'Song Generator'
self.fc1 = nn.Linear(self.rand_feature_dim * 2, num_hidden)
self.lstm_g1 = n... | Generator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generator:
def __init__(self, song_len, batch_size, num_feature, rand_feature_dim, num_hidden=350, keep_prob=0.5):
"""Generator of C-R-GAN. Get a midi sequence which is similar to a real music. :var input_dim: Input song dimension = [song_len, batch_size, num_feature]. A random input. :p... | stack_v2_sparse_classes_36k_train_001820 | 5,393 | no_license | [
{
"docstring": "Generator of C-R-GAN. Get a midi sequence which is similar to a real music. :var input_dim: Input song dimension = [song_len, batch_size, num_feature]. A random input. :param song_len: :param batch_size: :param num_feature: :param rand_feature_dim: Num feature of rand_inputs :param num_hidden: H... | 2 | stack_v2_sparse_classes_30k_train_019101 | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def __init__(self, song_len, batch_size, num_feature, rand_feature_dim, num_hidden=350, keep_prob=0.5): Generator of C-R-GAN. Get a midi sequence which is similar to a real mus... | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def __init__(self, song_len, batch_size, num_feature, rand_feature_dim, num_hidden=350, keep_prob=0.5): Generator of C-R-GAN. Get a midi sequence which is similar to a real mus... | aab5bf469d00506a4d2782e90f6fe9fc55bb50fb | <|skeleton|>
class Generator:
def __init__(self, song_len, batch_size, num_feature, rand_feature_dim, num_hidden=350, keep_prob=0.5):
"""Generator of C-R-GAN. Get a midi sequence which is similar to a real music. :var input_dim: Input song dimension = [song_len, batch_size, num_feature]. A random input. :p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Generator:
def __init__(self, song_len, batch_size, num_feature, rand_feature_dim, num_hidden=350, keep_prob=0.5):
"""Generator of C-R-GAN. Get a midi sequence which is similar to a real music. :var input_dim: Input song dimension = [song_len, batch_size, num_feature]. A random input. :param song_len:... | the_stack_v2_python_sparse | c-rnn-gan/model.py | pzq7025/Music | train | 0 | |
0b3484f7d2692e39751cb995b88ee51339c4cb4d | [
"if opt is None:\n opt = ConvCnstrMODMaskDcpl_IterSM.Options()\nsuper(ConvCnstrMODMaskDcpl_IterSM, self).__init__(Z, S, W, dsz, opt, dimK, dimN)",
"self.YU[:] = self.Y - self.U\nself.block_sep0(self.YU)[:] += self.S\nYUf = sl.rfftn(self.YU, None, self.cri.axisN)\nb = sl.inner(np.conj(self.Zf), self.block_sep0(... | <|body_start_0|>
if opt is None:
opt = ConvCnstrMODMaskDcpl_IterSM.Options()
super(ConvCnstrMODMaskDcpl_IterSM, self).__init__(Z, S, W, dsz, opt, dimK, dimN)
<|end_body_0|>
<|body_start_1|>
self.YU[:] = self.Y - self.U
self.block_sep0(self.YU)[:] += self.S
YUf = sl.r... | ADMM algorithm for Convolutional Constrained MOD with Mask Decoupling :cite:`heide-2015-fast` with the :math:`\\mathbf{x}` step solved via iterated application of the Sherman-Morrison equation :cite:`wohlberg-2016-efficient`. | .. inheritance-diagram:: ConvCnstrMODMaskDcpl_IterSM :parts: 2 | Multi-channel signals/image... | ConvCnstrMODMaskDcpl_IterSM | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvCnstrMODMaskDcpl_IterSM:
"""ADMM algorithm for Convolutional Constrained MOD with Mask Decoupling :cite:`heide-2015-fast` with the :math:`\\mathbf{x}` step solved via iterated application of the Sherman-Morrison equation :cite:`wohlberg-2016-efficient`. | .. inheritance-diagram:: ConvCnstrMOD... | stack_v2_sparse_classes_36k_train_001821 | 39,880 | permissive | [
{
"docstring": "| **Call graph** .. image:: ../_static/jonga/ccmodmdism_init.svg :width: 20% :target: ../_static/jonga/ccmodmdism_init.svg",
"name": "__init__",
"signature": "def __init__(self, Z, S, W, dsz, opt=None, dimK=1, dimN=2)"
},
{
"docstring": "Minimise Augmented Lagrangian with respect... | 2 | null | Implement the Python class `ConvCnstrMODMaskDcpl_IterSM` described below.
Class description:
ADMM algorithm for Convolutional Constrained MOD with Mask Decoupling :cite:`heide-2015-fast` with the :math:`\\mathbf{x}` step solved via iterated application of the Sherman-Morrison equation :cite:`wohlberg-2016-efficient`. ... | Implement the Python class `ConvCnstrMODMaskDcpl_IterSM` described below.
Class description:
ADMM algorithm for Convolutional Constrained MOD with Mask Decoupling :cite:`heide-2015-fast` with the :math:`\\mathbf{x}` step solved via iterated application of the Sherman-Morrison equation :cite:`wohlberg-2016-efficient`. ... | 5a64fbe456f3a117275c45ee1f10c60d6e133915 | <|skeleton|>
class ConvCnstrMODMaskDcpl_IterSM:
"""ADMM algorithm for Convolutional Constrained MOD with Mask Decoupling :cite:`heide-2015-fast` with the :math:`\\mathbf{x}` step solved via iterated application of the Sherman-Morrison equation :cite:`wohlberg-2016-efficient`. | .. inheritance-diagram:: ConvCnstrMOD... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvCnstrMODMaskDcpl_IterSM:
"""ADMM algorithm for Convolutional Constrained MOD with Mask Decoupling :cite:`heide-2015-fast` with the :math:`\\mathbf{x}` step solved via iterated application of the Sherman-Morrison equation :cite:`wohlberg-2016-efficient`. | .. inheritance-diagram:: ConvCnstrMODMaskDcpl_Iter... | the_stack_v2_python_sparse | benchmarks/other/sporco/admm/ccmodmd.py | tomMoral/dicodile | train | 17 |
9cc119613e1c46cda66c3272a9d549a78fbb1e57 | [
"while True:\n r = s.replace('()', '').replace('[]', '').replace('{}', '')\n if r == '':\n return True\n elif r == s:\n return False\n else:\n s = r",
"pair = {'(': ')', '[': ']', '{': '}'}\nstack = []\nfor p in s:\n if p in pair:\n stack.append(p)\n else:\n if... | <|body_start_0|>
while True:
r = s.replace('()', '').replace('[]', '').replace('{}', '')
if r == '':
return True
elif r == s:
return False
else:
s = r
<|end_body_0|>
<|body_start_1|>
pair = {'(': ')', '[': '... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid2(self, s):
"""Using stack."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
while True:
r = s.replace('()', '').replace('[]', '').replace('{}', '')
... | stack_v2_sparse_classes_36k_train_001822 | 996 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isValid",
"signature": "def isValid(self, s)"
},
{
"docstring": "Using stack.",
"name": "isValid2",
"signature": "def isValid2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid(self, s): :type s: str :rtype: bool
- def isValid2(self, s): Using stack. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid(self, s): :type s: str :rtype: bool
- def isValid2(self, s): Using stack.
<|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: boo... | 11942efcf481ab79a1c4a7e020e4353e0e0d3901 | <|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isValid2(self, s):
"""Using stack."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
while True:
r = s.replace('()', '').replace('[]', '').replace('{}', '')
if r == '':
return True
elif r == s:
return False
else:
s = r
... | the_stack_v2_python_sparse | python/solveleet/validParentheses.py | clumsyme/learn | train | 0 | |
c26c2039ea0afa6f699a7decc83a72fff7344846 | [
"tiles = data_input('test_data')\nresult = part_1(tiles)\nself.assertEqual(result, 20899048083289)",
"tiles = data_input('data')\nresult = part_1(tiles)\nself.assertEqual(result, 18482479935793)",
"tiles = data_input('test_data')\nresult = part_2(tiles)\nself.assertEqual(result, 273)",
"tiles = data_input('da... | <|body_start_0|>
tiles = data_input('test_data')
result = part_1(tiles)
self.assertEqual(result, 20899048083289)
<|end_body_0|>
<|body_start_1|>
tiles = data_input('data')
result = part_1(tiles)
self.assertEqual(result, 18482479935793)
<|end_body_1|>
<|body_start_2|>
... | () | TestAoC20 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAoC20:
"""()"""
def test_part_1_1(self):
"""()"""
<|body_0|>
def test_part_1_2(self):
"""()"""
<|body_1|>
def test_part_2_1(self):
"""()"""
<|body_2|>
def test_part_2_2(self):
"""()"""
<|body_3|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_001823 | 953 | no_license | [
{
"docstring": "()",
"name": "test_part_1_1",
"signature": "def test_part_1_1(self)"
},
{
"docstring": "()",
"name": "test_part_1_2",
"signature": "def test_part_1_2(self)"
},
{
"docstring": "()",
"name": "test_part_2_1",
"signature": "def test_part_2_1(self)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_014527 | Implement the Python class `TestAoC20` described below.
Class description:
()
Method signatures and docstrings:
- def test_part_1_1(self): ()
- def test_part_1_2(self): ()
- def test_part_2_1(self): ()
- def test_part_2_2(self): () | Implement the Python class `TestAoC20` described below.
Class description:
()
Method signatures and docstrings:
- def test_part_1_1(self): ()
- def test_part_1_2(self): ()
- def test_part_2_1(self): ()
- def test_part_2_2(self): ()
<|skeleton|>
class TestAoC20:
"""()"""
def test_part_1_1(self):
"""(... | 934c1c45daf189ce2f517b70abe896fedb152b88 | <|skeleton|>
class TestAoC20:
"""()"""
def test_part_1_1(self):
"""()"""
<|body_0|>
def test_part_1_2(self):
"""()"""
<|body_1|>
def test_part_2_1(self):
"""()"""
<|body_2|>
def test_part_2_2(self):
"""()"""
<|body_3|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAoC20:
"""()"""
def test_part_1_1(self):
"""()"""
tiles = data_input('test_data')
result = part_1(tiles)
self.assertEqual(result, 20899048083289)
def test_part_1_2(self):
"""()"""
tiles = data_input('data')
result = part_1(tiles)
se... | the_stack_v2_python_sparse | 20/test.py | iveL91/Advent-of-Code-2020 | train | 0 |
0e4d80688909d5ef80563e4ea41ffef8c72b2b8c | [
"buff = BytesIO()\nbuff.write(stream)\nbuff.seek(0)\ntry:\n Img.open(buff)\n result = True\nexcept UnidentifiedImageError:\n result = False\nbuff.close()\nreturn result",
"buff = BytesIO()\nbuff.write(image_stream)\nbuff.seek(0)\nimage = Img.open(buff)\nrotated_buff = BytesIO()\nimage.rotate(rotation, ex... | <|body_start_0|>
buff = BytesIO()
buff.write(stream)
buff.seek(0)
try:
Img.open(buff)
result = True
except UnidentifiedImageError:
result = False
buff.close()
return result
<|end_body_0|>
<|body_start_1|>
buff = BytesIO... | Contains methods for interacting with images. | Image | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Image:
"""Contains methods for interacting with images."""
def is_image(stream: bytes) -> bool:
"""Checks if a stream is indeed an image."""
<|body_0|>
def rotate_image(image_stream: bytes, rotation: Union[float, int]) -> bytes:
"""Rotates an image by a rotation ... | stack_v2_sparse_classes_36k_train_001824 | 1,678 | no_license | [
{
"docstring": "Checks if a stream is indeed an image.",
"name": "is_image",
"signature": "def is_image(stream: bytes) -> bool"
},
{
"docstring": "Rotates an image by a rotation angle.",
"name": "rotate_image",
"signature": "def rotate_image(image_stream: bytes, rotation: Union[float, in... | 3 | stack_v2_sparse_classes_30k_train_012614 | Implement the Python class `Image` described below.
Class description:
Contains methods for interacting with images.
Method signatures and docstrings:
- def is_image(stream: bytes) -> bool: Checks if a stream is indeed an image.
- def rotate_image(image_stream: bytes, rotation: Union[float, int]) -> bytes: Rotates an... | Implement the Python class `Image` described below.
Class description:
Contains methods for interacting with images.
Method signatures and docstrings:
- def is_image(stream: bytes) -> bool: Checks if a stream is indeed an image.
- def rotate_image(image_stream: bytes, rotation: Union[float, int]) -> bytes: Rotates an... | 11b213da49ef00a82fc7a2c9488291d03f6a56ae | <|skeleton|>
class Image:
"""Contains methods for interacting with images."""
def is_image(stream: bytes) -> bool:
"""Checks if a stream is indeed an image."""
<|body_0|>
def rotate_image(image_stream: bytes, rotation: Union[float, int]) -> bytes:
"""Rotates an image by a rotation ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Image:
"""Contains methods for interacting with images."""
def is_image(stream: bytes) -> bool:
"""Checks if a stream is indeed an image."""
buff = BytesIO()
buff.write(stream)
buff.seek(0)
try:
Img.open(buff)
result = True
except Un... | the_stack_v2_python_sparse | venv/Lib/site-packages/PyPDFForm/core/image.py | KevinIbel/WebScraper | train | 0 |
7e9c0b7d49556895dd6c79bd7e349b3cb06abd0b | [
"order_id = request.GET.get('order_id')\ntry:\n order = OrderInfo.objects.get(order_id=order_id, user=request.user)\nexcept OrderInfo.DoesNotExist:\n return http.HttpResponseForbidden('订单不存在')\ntry:\n uncomment_goods = order.skus.filter(is_commented=False, order_id=order_id)\nexcept OrderInfo.DoesNotExist:... | <|body_start_0|>
order_id = request.GET.get('order_id')
try:
order = OrderInfo.objects.get(order_id=order_id, user=request.user)
except OrderInfo.DoesNotExist:
return http.HttpResponseForbidden('订单不存在')
try:
uncomment_goods = order.skus.filter(is_comme... | 订单商品评价 | OrderCommentView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""订单商品评价 :param request: :return:"""
<|body_0|>
def post(self, request):
"""获取参数修改评论页面的内容"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
order_id = request.GET.get('order_id')
try:... | stack_v2_sparse_classes_36k_train_001825 | 14,520 | permissive | [
{
"docstring": "订单商品评价 :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "获取参数修改评论页面的内容",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016754 | Implement the Python class `OrderCommentView` described below.
Class description:
订单商品评价
Method signatures and docstrings:
- def get(self, request): 订单商品评价 :param request: :return:
- def post(self, request): 获取参数修改评论页面的内容 | Implement the Python class `OrderCommentView` described below.
Class description:
订单商品评价
Method signatures and docstrings:
- def get(self, request): 订单商品评价 :param request: :return:
- def post(self, request): 获取参数修改评论页面的内容
<|skeleton|>
class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""订... | fecdf074ddb6844f33d6fadf05d40b0e562b46fb | <|skeleton|>
class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""订单商品评价 :param request: :return:"""
<|body_0|>
def post(self, request):
"""获取参数修改评论页面的内容"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""订单商品评价 :param request: :return:"""
order_id = request.GET.get('order_id')
try:
order = OrderInfo.objects.get(order_id=order_id, user=request.user)
except OrderInfo.DoesNotExist:
return http.H... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/orders/views.py | qls7/dianshang | train | 0 |
45c282e5451e9b9c2e4ffd94629784853dfa1c92 | [
"log.debug('POST request from user %s to create a new project stage' % request.user)\nproj = Project.objects.get(project_number=project_number)\nif not check_project_write_acl(proj, request.user):\n log.debug('Refusing POST request for project %s from user %s' % (project_number, request.user))\n return rc.FOR... | <|body_start_0|>
log.debug('POST request from user %s to create a new project stage' % request.user)
proj = Project.objects.get(project_number=project_number)
if not check_project_write_acl(proj, request.user):
log.debug('Refusing POST request for project %s from user %s' % (project_... | URL: /api/stageplan/%project_number%/ VERBS: GET, POST Returns a list of Stage Plans associated with a project | StageplanListHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StageplanListHandler:
"""URL: /api/stageplan/%project_number%/ VERBS: GET, POST Returns a list of Stage Plans associated with a project"""
def create(self, request, project_number):
"""Create a new Project Stage"""
<|body_0|>
def read(self, request, project_number):
... | stack_v2_sparse_classes_36k_train_001826 | 19,350 | no_license | [
{
"docstring": "Create a new Project Stage",
"name": "create",
"signature": "def create(self, request, project_number)"
},
{
"docstring": "Return a list of project stages associated with projects filtered by ACL",
"name": "read",
"signature": "def read(self, request, project_number)"
}... | 2 | stack_v2_sparse_classes_30k_train_010297 | Implement the Python class `StageplanListHandler` described below.
Class description:
URL: /api/stageplan/%project_number%/ VERBS: GET, POST Returns a list of Stage Plans associated with a project
Method signatures and docstrings:
- def create(self, request, project_number): Create a new Project Stage
- def read(self... | Implement the Python class `StageplanListHandler` described below.
Class description:
URL: /api/stageplan/%project_number%/ VERBS: GET, POST Returns a list of Stage Plans associated with a project
Method signatures and docstrings:
- def create(self, request, project_number): Create a new Project Stage
- def read(self... | 106a96307612318fb66246486e7226069e5508ac | <|skeleton|>
class StageplanListHandler:
"""URL: /api/stageplan/%project_number%/ VERBS: GET, POST Returns a list of Stage Plans associated with a project"""
def create(self, request, project_number):
"""Create a new Project Stage"""
<|body_0|>
def read(self, request, project_number):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StageplanListHandler:
"""URL: /api/stageplan/%project_number%/ VERBS: GET, POST Returns a list of Stage Plans associated with a project"""
def create(self, request, project_number):
"""Create a new Project Stage"""
log.debug('POST request from user %s to create a new project stage' % requ... | the_stack_v2_python_sparse | branches/rest-api-branch/django-project-management/wbs/api_views.py | NhaTrang/django-project-management | train | 0 |
bb1185333c3133df7f6a4cbe3bc184095b54eca6 | [
"self.archival_runs = archival_runs\nself.backup_runs = backup_runs\nself.replication_runs = replication_runs",
"if dictionary is None:\n return None\narchival_runs = None\nif dictionary.get('archivalRuns') != None:\n archival_runs = list()\n for structure in dictionary.get('archivalRuns'):\n arch... | <|body_start_0|>
self.archival_runs = archival_runs
self.backup_runs = backup_runs
self.replication_runs = replication_runs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
archival_runs = None
if dictionary.get('archivalRuns') != None:
... | Implementation of the 'ProtectionRunResponse' model. Specifies the information about the Protection Runs across all snapshot target locations. Attributes: archival_runs (list of LatestProtectionJobRunInfo): Specifies the list of archival job information. backup_runs (list of LatestProtectionJobRunInfo): Specifies the l... | ProtectionRunResponse | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectionRunResponse:
"""Implementation of the 'ProtectionRunResponse' model. Specifies the information about the Protection Runs across all snapshot target locations. Attributes: archival_runs (list of LatestProtectionJobRunInfo): Specifies the list of archival job information. backup_runs (lis... | stack_v2_sparse_classes_36k_train_001827 | 3,040 | permissive | [
{
"docstring": "Constructor for the ProtectionRunResponse class",
"name": "__init__",
"signature": "def __init__(self, archival_runs=None, backup_runs=None, replication_runs=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary ... | 2 | null | Implement the Python class `ProtectionRunResponse` described below.
Class description:
Implementation of the 'ProtectionRunResponse' model. Specifies the information about the Protection Runs across all snapshot target locations. Attributes: archival_runs (list of LatestProtectionJobRunInfo): Specifies the list of arc... | Implement the Python class `ProtectionRunResponse` described below.
Class description:
Implementation of the 'ProtectionRunResponse' model. Specifies the information about the Protection Runs across all snapshot target locations. Attributes: archival_runs (list of LatestProtectionJobRunInfo): Specifies the list of arc... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ProtectionRunResponse:
"""Implementation of the 'ProtectionRunResponse' model. Specifies the information about the Protection Runs across all snapshot target locations. Attributes: archival_runs (list of LatestProtectionJobRunInfo): Specifies the list of archival job information. backup_runs (lis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectionRunResponse:
"""Implementation of the 'ProtectionRunResponse' model. Specifies the information about the Protection Runs across all snapshot target locations. Attributes: archival_runs (list of LatestProtectionJobRunInfo): Specifies the list of archival job information. backup_runs (list of LatestPr... | the_stack_v2_python_sparse | cohesity_management_sdk/models/protection_run_response.py | cohesity/management-sdk-python | train | 24 |
d58c3d0ba58abc3161954ae2dd6df303f0f3b343 | [
"for i, matr in enumerate(self.transition_matrices):\n print(matrix_name + '_' + str(i), ':', file=file)\n matr_print(matr, file=file)\nprint('Average intensity:', self.avg_intensity, file=file)\nprint('Average batch intensity:', self.batch_intensity, file=file)\nprint('Variation coefficient:', self.c_var, fi... | <|body_start_0|>
for i, matr in enumerate(self.transition_matrices):
print(matrix_name + '_' + str(i), ':', file=file)
matr_print(matr, file=file)
print('Average intensity:', self.avg_intensity, file=file)
print('Average batch intensity:', self.batch_intensity, file=file)... | BMAP stream class. Contains list of transition matrices, stream average intensity, stream batches intensity, variation coefficient and correlation coefficient. | BMAPStream | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BMAPStream:
"""BMAP stream class. Contains list of transition matrices, stream average intensity, stream batches intensity, variation coefficient and correlation coefficient."""
def print_characteristics(self, matrix_name, file=sys.stdout):
"""Prints characteristics of BMAP stream: M... | stack_v2_sparse_classes_36k_train_001828 | 15,627 | no_license | [
{
"docstring": "Prints characteristics of BMAP stream: Matrices Average intensity Average batch intensity Variation coefficient Correlation coefficient :return: None",
"name": "print_characteristics",
"signature": "def print_characteristics(self, matrix_name, file=sys.stdout)"
},
{
"docstring": ... | 3 | stack_v2_sparse_classes_30k_train_018477 | Implement the Python class `BMAPStream` described below.
Class description:
BMAP stream class. Contains list of transition matrices, stream average intensity, stream batches intensity, variation coefficient and correlation coefficient.
Method signatures and docstrings:
- def print_characteristics(self, matrix_name, f... | Implement the Python class `BMAPStream` described below.
Class description:
BMAP stream class. Contains list of transition matrices, stream average intensity, stream batches intensity, variation coefficient and correlation coefficient.
Method signatures and docstrings:
- def print_characteristics(self, matrix_name, f... | 6173e0d279893f0da4f8ad09b824cd5897c4e5e7 | <|skeleton|>
class BMAPStream:
"""BMAP stream class. Contains list of transition matrices, stream average intensity, stream batches intensity, variation coefficient and correlation coefficient."""
def print_characteristics(self, matrix_name, file=sys.stdout):
"""Prints characteristics of BMAP stream: M... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BMAPStream:
"""BMAP stream class. Contains list of transition matrices, stream average intensity, stream batches intensity, variation coefficient and correlation coefficient."""
def print_characteristics(self, matrix_name, file=sys.stdout):
"""Prints characteristics of BMAP stream: Matrices Avera... | the_stack_v2_python_sparse | streams.py | pishchynski/magister_work | train | 0 |
d9d3eaa9d356f048e0815dc6e82d2cdfb377e3a3 | [
"self.trainloader = trainloader\nself.N_trn = len(trainloader.sampler.data_source)\nself.online = online\nself.indices = None\nself.gammas = None",
"if self.online or self.indices is None:\n self.indices = np.random.choice(self.N_trn, size=budget, replace=False)\n self.gammas = torch.ones(budget)\nreturn (s... | <|body_start_0|>
self.trainloader = trainloader
self.N_trn = len(trainloader.sampler.data_source)
self.online = online
self.indices = None
self.gammas = None
<|end_body_0|>
<|body_start_1|>
if self.online or self.indices is None:
self.indices = np.random.choi... | This is the Random Selection Strategy class where we select a set of random points as a datasubset and often acts as baselines to compare other subset selection strategies. Parameters ---------- trainloader: class Loading the training data using pytorch DataLoader | RandomStrategy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomStrategy:
"""This is the Random Selection Strategy class where we select a set of random points as a datasubset and often acts as baselines to compare other subset selection strategies. Parameters ---------- trainloader: class Loading the training data using pytorch DataLoader"""
def _... | stack_v2_sparse_classes_36k_train_001829 | 1,305 | permissive | [
{
"docstring": "Constructor method",
"name": "__init__",
"signature": "def __init__(self, trainloader, online=False)"
},
{
"docstring": "Perform random sampling of indices of size budget. Parameters ---------- budget: int The number of data points to be selected Returns ---------- indices: ndarr... | 2 | stack_v2_sparse_classes_30k_train_003671 | Implement the Python class `RandomStrategy` described below.
Class description:
This is the Random Selection Strategy class where we select a set of random points as a datasubset and often acts as baselines to compare other subset selection strategies. Parameters ---------- trainloader: class Loading the training data... | Implement the Python class `RandomStrategy` described below.
Class description:
This is the Random Selection Strategy class where we select a set of random points as a datasubset and often acts as baselines to compare other subset selection strategies. Parameters ---------- trainloader: class Loading the training data... | 8d10c7f5d96e071f98c20e4e9ff4c41c2c4ea2af | <|skeleton|>
class RandomStrategy:
"""This is the Random Selection Strategy class where we select a set of random points as a datasubset and often acts as baselines to compare other subset selection strategies. Parameters ---------- trainloader: class Loading the training data using pytorch DataLoader"""
def _... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomStrategy:
"""This is the Random Selection Strategy class where we select a set of random points as a datasubset and often acts as baselines to compare other subset selection strategies. Parameters ---------- trainloader: class Loading the training data using pytorch DataLoader"""
def __init__(self,... | the_stack_v2_python_sparse | cords/selectionstrategies/SSL/randomstrategy.py | decile-team/cords | train | 289 |
dd0e79641c04113ec232cca837850e2b1e1faa84 | [
"super(AngularPenaltySMLoss, self).__init__()\nloss_type = loss_type.lower()\nassert loss_type in ['arcface', 'sphereface', 'cosface']\nif loss_type == 'arcface':\n self.s = 64.0 if not s else s\n self.m = 0.5 if not m else m\nif loss_type == 'sphereface':\n self.s = 64.0 if not s else s\n self.m = 1.35... | <|body_start_0|>
super(AngularPenaltySMLoss, self).__init__()
loss_type = loss_type.lower()
assert loss_type in ['arcface', 'sphereface', 'cosface']
if loss_type == 'arcface':
self.s = 64.0 if not s else s
self.m = 0.5 if not m else m
if loss_type == 'sphe... | AngularPenaltySMLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AngularPenaltySMLoss:
def __init__(self, loss_type='arcface', eps=1e-07, s=None, m=None):
"""Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arxiv.org/abs/1801.07698 Spher... | stack_v2_sparse_classes_36k_train_001830 | 4,130 | no_license | [
{
"docstring": "Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arxiv.org/abs/1801.07698 SphereFace: https://arxiv.org/abs/1704.08063 CosFace/Ad Margin: https://arxiv.org/abs/1801.05599",
"na... | 2 | stack_v2_sparse_classes_30k_train_021318 | Implement the Python class `AngularPenaltySMLoss` described below.
Class description:
Implement the AngularPenaltySMLoss class.
Method signatures and docstrings:
- def __init__(self, loss_type='arcface', eps=1e-07, s=None, m=None): Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', '... | Implement the Python class `AngularPenaltySMLoss` described below.
Class description:
Implement the AngularPenaltySMLoss class.
Method signatures and docstrings:
- def __init__(self, loss_type='arcface', eps=1e-07, s=None, m=None): Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', '... | 5acd3faaffb4e1de798f236a2733620ce36fb9e9 | <|skeleton|>
class AngularPenaltySMLoss:
def __init__(self, loss_type='arcface', eps=1e-07, s=None, m=None):
"""Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arxiv.org/abs/1801.07698 Spher... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AngularPenaltySMLoss:
def __init__(self, loss_type='arcface', eps=1e-07, s=None, m=None):
"""Angular Penalty Softmax Loss Three 'loss_types' available: ['arcface', 'sphereface', 'cosface'] These losses are described in the following papers: ArcFace: https://arxiv.org/abs/1801.07698 SphereFace: https:/... | the_stack_v2_python_sparse | b06504102_hw2/Mynet_.py | brianw0924/ML2021 | train | 0 | |
d4961af8d2a99ad6e323ac347f155cec722e519e | [
"self.id1 = id1\nself.id2 = id2\nself.path = path\nself.max_size = max_size\nself.file1 = None\nself.file2 = None\nself.written = 0\nself.counter = 0\nself.next_files()",
"if self.file1:\n self.file1.close()\nif self.file2:\n self.file2.close()\npath1 = os.path.join(self.path, '{}-{}.txt'.format(self.id1, s... | <|body_start_0|>
self.id1 = id1
self.id2 = id2
self.path = path
self.max_size = max_size
self.file1 = None
self.file2 = None
self.written = 0
self.counter = 0
self.next_files()
<|end_body_0|>
<|body_start_1|>
if self.file1:
sel... | FileStorage allows store text corpora in parallel files | FileStorage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileStorage:
"""FileStorage allows store text corpora in parallel files"""
def __init__(self, id1, id2, path, max_size):
""":id1: prefix for first file :id2: prifix for second file :path: path for storing files :max_size: maximal file size in symbols"""
<|body_0|>
def ne... | stack_v2_sparse_classes_36k_train_001831 | 1,803 | no_license | [
{
"docstring": ":id1: prefix for first file :id2: prifix for second file :path: path for storing files :max_size: maximal file size in symbols",
"name": "__init__",
"signature": "def __init__(self, id1, id2, path, max_size)"
},
{
"docstring": "@todo: Docstring for next_files. :returns: @todo",
... | 3 | null | Implement the Python class `FileStorage` described below.
Class description:
FileStorage allows store text corpora in parallel files
Method signatures and docstrings:
- def __init__(self, id1, id2, path, max_size): :id1: prefix for first file :id2: prifix for second file :path: path for storing files :max_size: maxim... | Implement the Python class `FileStorage` described below.
Class description:
FileStorage allows store text corpora in parallel files
Method signatures and docstrings:
- def __init__(self, id1, id2, path, max_size): :id1: prefix for first file :id2: prifix for second file :path: path for storing files :max_size: maxim... | 6da94fbb74e803bea337e0c171c8abff3b17d7ee | <|skeleton|>
class FileStorage:
"""FileStorage allows store text corpora in parallel files"""
def __init__(self, id1, id2, path, max_size):
""":id1: prefix for first file :id2: prifix for second file :path: path for storing files :max_size: maximal file size in symbols"""
<|body_0|>
def ne... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileStorage:
"""FileStorage allows store text corpora in parallel files"""
def __init__(self, id1, id2, path, max_size):
""":id1: prefix for first file :id2: prifix for second file :path: path for storing files :max_size: maximal file size in symbols"""
self.id1 = id1
self.id2 = i... | the_stack_v2_python_sparse | pc/filestorage.py | CLARIN-PL/yalign | train | 0 |
329c87cb4e874d5aaa281b7afd07ba72a0709dee | [
"header('Content-Type', 'application/json')\ntry:\n scopes = get_scopes(account, vo=ctx.env.get('vo'))\nexcept AccountNotFound as error:\n raise generate_http_error(404, 'AccountNotFound', error.args[0])\nexcept RucioException as error:\n raise generate_http_error(500, error.__class__.__name__, error.args[... | <|body_start_0|>
header('Content-Type', 'application/json')
try:
scopes = get_scopes(account, vo=ctx.env.get('vo'))
except AccountNotFound as error:
raise generate_http_error(404, 'AccountNotFound', error.args[0])
except RucioException as error:
raise ... | Scopes | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Scopes:
def GET(self, account):
"""list all scopes for an account. HTTP Success: 200 OK HTTP Error: 401 Unauthorized 404 Not Found 406 Not Acceptable 500 InternalError :param Rucio-Account: Account identifier. :param Rucio-Auth-Token: as an 32 character hex string. :returns: A list conta... | stack_v2_sparse_classes_36k_train_001832 | 27,871 | permissive | [
{
"docstring": "list all scopes for an account. HTTP Success: 200 OK HTTP Error: 401 Unauthorized 404 Not Found 406 Not Acceptable 500 InternalError :param Rucio-Account: Account identifier. :param Rucio-Auth-Token: as an 32 character hex string. :returns: A list containing all scope names for an account.",
... | 2 | null | Implement the Python class `Scopes` described below.
Class description:
Implement the Scopes class.
Method signatures and docstrings:
- def GET(self, account): list all scopes for an account. HTTP Success: 200 OK HTTP Error: 401 Unauthorized 404 Not Found 406 Not Acceptable 500 InternalError :param Rucio-Account: Acc... | Implement the Python class `Scopes` described below.
Class description:
Implement the Scopes class.
Method signatures and docstrings:
- def GET(self, account): list all scopes for an account. HTTP Success: 200 OK HTTP Error: 401 Unauthorized 404 Not Found 406 Not Acceptable 500 InternalError :param Rucio-Account: Acc... | bf33d9441d3b4ff160a392eed56724f635a03fe6 | <|skeleton|>
class Scopes:
def GET(self, account):
"""list all scopes for an account. HTTP Success: 200 OK HTTP Error: 401 Unauthorized 404 Not Found 406 Not Acceptable 500 InternalError :param Rucio-Account: Account identifier. :param Rucio-Auth-Token: as an 32 character hex string. :returns: A list conta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Scopes:
def GET(self, account):
"""list all scopes for an account. HTTP Success: 200 OK HTTP Error: 401 Unauthorized 404 Not Found 406 Not Acceptable 500 InternalError :param Rucio-Account: Account identifier. :param Rucio-Auth-Token: as an 32 character hex string. :returns: A list containing all scop... | the_stack_v2_python_sparse | lib/rucio/web/rest/webpy/v1/account.py | viveknigam3003/rucio | train | 1 | |
67a4b43d67a9b41c295d91ba4769a25ee64c2738 | [
"self.all_annotators = {}\nself.all_importers = {}\nself.all_exporters = {}\nself.all_installers = {}\nself.all_uninstallers = {}\nself.all_custom_annotators = {}\nself.all_preloaders = {}\nself.named_targets = []\nself.export_targets = []\nself.import_targets = []\nself.install_targets = []\nself.uninstall_targets... | <|body_start_0|>
self.all_annotators = {}
self.all_importers = {}
self.all_exporters = {}
self.all_installers = {}
self.all_uninstallers = {}
self.all_custom_annotators = {}
self.all_preloaders = {}
self.named_targets = []
self.export_targets = []
... | Object to store variables involving all rules. | SnakeStorage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeStorage:
"""Object to store variables involving all rules."""
def __init__(self):
"""Init attributes."""
<|body_0|>
def source_files(self) -> List[str]:
"""Get list of all available source files."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_001833 | 40,470 | permissive | [
{
"docstring": "Init attributes.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get list of all available source files.",
"name": "source_files",
"signature": "def source_files(self) -> List[str]"
}
] | 2 | null | Implement the Python class `SnakeStorage` described below.
Class description:
Object to store variables involving all rules.
Method signatures and docstrings:
- def __init__(self): Init attributes.
- def source_files(self) -> List[str]: Get list of all available source files. | Implement the Python class `SnakeStorage` described below.
Class description:
Object to store variables involving all rules.
Method signatures and docstrings:
- def __init__(self): Init attributes.
- def source_files(self) -> List[str]: Get list of all available source files.
<|skeleton|>
class SnakeStorage:
"""... | d3eb0db9de7fca6b6945192dd7f0c9e4bbeebb55 | <|skeleton|>
class SnakeStorage:
"""Object to store variables involving all rules."""
def __init__(self):
"""Init attributes."""
<|body_0|>
def source_files(self) -> List[str]:
"""Get list of all available source files."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeStorage:
"""Object to store variables involving all rules."""
def __init__(self):
"""Init attributes."""
self.all_annotators = {}
self.all_importers = {}
self.all_exporters = {}
self.all_installers = {}
self.all_uninstallers = {}
self.all_custo... | the_stack_v2_python_sparse | sparv/core/snake_utils.py | spraakbanken/sparv-pipeline | train | 22 |
241ef0f5d59ff12b9faee262aa85915498c394a6 | [
"denvec = self[self['frame'] == frame]['coef'].values\nsquare = pd.DataFrame(density_as_square(denvec))\nsquare.index.name = 'chi0'\nsquare.columns.name = 'chi1'\nreturn square",
"cmat = momatrix.square(column=mocoefs).values\nchi0, chi1, dens, frame = density_from_momatrix(cmat, occvec)\nreturn cls.from_dict({'c... | <|body_start_0|>
denvec = self[self['frame'] == frame]['coef'].values
square = pd.DataFrame(density_as_square(denvec))
square.index.name = 'chi0'
square.columns.name = 'chi1'
return square
<|end_body_0|>
<|body_start_1|>
cmat = momatrix.square(column=mocoefs).values
... | The density matrix in a contracted basis set. As it is square symmetric, only n_basis_functions * (n_basis_functions + 1) / 2 rows are stored. +-------------------+----------+-------------------------------------------+ | Column | Type | Description | +===================+==========+====================================... | DensityMatrix | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DensityMatrix:
"""The density matrix in a contracted basis set. As it is square symmetric, only n_basis_functions * (n_basis_functions + 1) / 2 rows are stored. +-------------------+----------+-------------------------------------------+ | Column | Type | Description | +===================+======... | stack_v2_sparse_classes_36k_train_001834 | 21,790 | permissive | [
{
"docstring": "Returns a square dataframe of the density matrix.",
"name": "square",
"signature": "def square(self, frame=0)"
},
{
"docstring": "A density matrix can be constructed from an MOMatrix by: .. math:: D_{uv} = \\\\sum_{i}^{N} C_{ui} C_{vi} n_{i} Args: momatrix (:class:`~exatomic.orbi... | 3 | null | Implement the Python class `DensityMatrix` described below.
Class description:
The density matrix in a contracted basis set. As it is square symmetric, only n_basis_functions * (n_basis_functions + 1) / 2 rows are stored. +-------------------+----------+-------------------------------------------+ | Column | Type | De... | Implement the Python class `DensityMatrix` described below.
Class description:
The density matrix in a contracted basis set. As it is square symmetric, only n_basis_functions * (n_basis_functions + 1) / 2 rows are stored. +-------------------+----------+-------------------------------------------+ | Column | Type | De... | 2e87bae3e043e6958129fc823c83ab0b46add8b5 | <|skeleton|>
class DensityMatrix:
"""The density matrix in a contracted basis set. As it is square symmetric, only n_basis_functions * (n_basis_functions + 1) / 2 rows are stored. +-------------------+----------+-------------------------------------------+ | Column | Type | Description | +===================+======... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DensityMatrix:
"""The density matrix in a contracted basis set. As it is square symmetric, only n_basis_functions * (n_basis_functions + 1) / 2 rows are stored. +-------------------+----------+-------------------------------------------+ | Column | Type | Description | +===================+==========+========... | the_stack_v2_python_sparse | exatomic/core/orbital.py | exa-analytics/exatomic | train | 15 |
f405fb4fef1954a8e71a7b7ac0a4120c50d1c07b | [
"self.__k = 300\nself.__dq = collections.deque()\nself.__count = 0",
"self.getHits(timestamp)\nif self.__dq and self.__dq[-1][0] == timestamp:\n self.__dq[-1][1] += 1\nelse:\n self.__dq.append([timestamp, 1])\nself.__count += 1",
"while self.__dq and self.__dq[0][0] <= timestamp - self.__k:\n self.__co... | <|body_start_0|>
self.__k = 300
self.__dq = collections.deque()
self.__count = 0
<|end_body_0|>
<|body_start_1|>
self.getHits(timestamp)
if self.__dq and self.__dq[-1][0] == timestamp:
self.__dq[-1][1] += 1
else:
self.__dq.append([timestamp, 1])
... | HitCounter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity)."""
<|body_1|>
def getHits(self, timestamp: in... | stack_v2_sparse_classes_36k_train_001835 | 4,308 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Record a hit. @param timestamp - The current timestamp (in seconds granularity).",
"name": "hit",
"signature": "def hit(self, timestamp: int) -> None"
},
{
... | 3 | null | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp: int) -> None: Record a hit. @param timestamp - The current timestamp (in seconds granulari... | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp: int) -> None: Record a hit. @param timestamp - The current timestamp (in seconds granulari... | 44765a7d89423b7ec2c159f70b1a6f6e446523c2 | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity)."""
<|body_1|>
def getHits(self, timestamp: in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
self.__k = 300
self.__dq = collections.deque()
self.__count = 0
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity)."""
... | the_stack_v2_python_sparse | python/_0001_0500/0362_design-hit-counter.py | Wang-Yann/LeetCodeMe | train | 0 | |
1ba68903d537747d9e6327c7d491a9385220f8b4 | [
"def check(t1: 'TreeNode', t2: 'TreeNode') -> bool:\n if not t1 and (not t2):\n return True\n if not t1 or not t2:\n return False\n if t1.val != t2.val:\n return False\n return True\nfrom collections import deque\ndeq = deque([(t1, t2)])\nwhile deq:\n t1, t2 = deque.popleft()\n ... | <|body_start_0|>
def check(t1: 'TreeNode', t2: 'TreeNode') -> bool:
if not t1 and (not t2):
return True
if not t1 or not t2:
return False
if t1.val != t2.val:
return False
return True
from collections import ... | Tree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tree:
def is_same(self, t1: 'TreeNode', t2: 'TreeNode') -> bool:
"""Approach: Iteration Time Complexity: O(N) Space Complexity: O(log N) :param t1: :param t2: :return:"""
<|body_0|>
def is_same_(self, t1: 'TreeNode', t2: 'TreeNode') -> bool:
"""Approach: Recursion Ti... | stack_v2_sparse_classes_36k_train_001836 | 1,496 | no_license | [
{
"docstring": "Approach: Iteration Time Complexity: O(N) Space Complexity: O(log N) :param t1: :param t2: :return:",
"name": "is_same",
"signature": "def is_same(self, t1: 'TreeNode', t2: 'TreeNode') -> bool"
},
{
"docstring": "Approach: Recursion Time Complexity: O(N) Space Complexity: O(log N... | 2 | null | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def is_same(self, t1: 'TreeNode', t2: 'TreeNode') -> bool: Approach: Iteration Time Complexity: O(N) Space Complexity: O(log N) :param t1: :param t2: :return:
- def is_same_(self, t1: 'T... | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def is_same(self, t1: 'TreeNode', t2: 'TreeNode') -> bool: Approach: Iteration Time Complexity: O(N) Space Complexity: O(log N) :param t1: :param t2: :return:
- def is_same_(self, t1: 'T... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Tree:
def is_same(self, t1: 'TreeNode', t2: 'TreeNode') -> bool:
"""Approach: Iteration Time Complexity: O(N) Space Complexity: O(log N) :param t1: :param t2: :return:"""
<|body_0|>
def is_same_(self, t1: 'TreeNode', t2: 'TreeNode') -> bool:
"""Approach: Recursion Ti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tree:
def is_same(self, t1: 'TreeNode', t2: 'TreeNode') -> bool:
"""Approach: Iteration Time Complexity: O(N) Space Complexity: O(log N) :param t1: :param t2: :return:"""
def check(t1: 'TreeNode', t2: 'TreeNode') -> bool:
if not t1 and (not t2):
return True
... | the_stack_v2_python_sparse | revisited_2021/tree/same_tree.py | Shiv2157k/leet_code | train | 1 | |
3bebf16c316320c3646a4f90dcb238cd5e8bd28c | [
"cpu_stats = psutil.cpu_times_percent(percpu=False)\ncpu_stats_dict = {StatsKeys.CPU: {StatsKeys.IDLE: cpu_stats.idle, StatsKeys.SYSTEM: cpu_stats.system, StatsKeys.USER: cpu_stats.user, StatsKeys.COUNT: len(psutil.cpu_times(percpu=True))}}\nlogger.debug('CPU stats: {}'.format(cpu_stats_dict))\nreturn cpu_stats_dic... | <|body_start_0|>
cpu_stats = psutil.cpu_times_percent(percpu=False)
cpu_stats_dict = {StatsKeys.CPU: {StatsKeys.IDLE: cpu_stats.idle, StatsKeys.SYSTEM: cpu_stats.system, StatsKeys.USER: cpu_stats.user, StatsKeys.COUNT: len(psutil.cpu_times(percpu=True))}}
logger.debug('CPU stats: {}'.format(cpu_... | SystemManager class is the entry point for queries regarding system stats. This service reports statistics about disk, memory and CPU usage, Monit summary, and number of running appservers, if any. | SystemManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SystemManager:
"""SystemManager class is the entry point for queries regarding system stats. This service reports statistics about disk, memory and CPU usage, Monit summary, and number of running appservers, if any."""
def get_cpu_usage(cls):
"""Discovers CPU usage on this node. Retu... | stack_v2_sparse_classes_36k_train_001837 | 5,532 | permissive | [
{
"docstring": "Discovers CPU usage on this node. Returns: A dictionary containing the idle, system and user percentages.",
"name": "get_cpu_usage",
"signature": "def get_cpu_usage(cls)"
},
{
"docstring": "Discovers disk usage per mount point on this node. Returns: A dictionary containing free b... | 6 | stack_v2_sparse_classes_30k_train_020072 | Implement the Python class `SystemManager` described below.
Class description:
SystemManager class is the entry point for queries regarding system stats. This service reports statistics about disk, memory and CPU usage, Monit summary, and number of running appservers, if any.
Method signatures and docstrings:
- def g... | Implement the Python class `SystemManager` described below.
Class description:
SystemManager class is the entry point for queries regarding system stats. This service reports statistics about disk, memory and CPU usage, Monit summary, and number of running appservers, if any.
Method signatures and docstrings:
- def g... | 4940c719df1b50ad4af5af4adf675414e225e5a6 | <|skeleton|>
class SystemManager:
"""SystemManager class is the entry point for queries regarding system stats. This service reports statistics about disk, memory and CPU usage, Monit summary, and number of running appservers, if any."""
def get_cpu_usage(cls):
"""Discovers CPU usage on this node. Retu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SystemManager:
"""SystemManager class is the entry point for queries regarding system stats. This service reports statistics about disk, memory and CPU usage, Monit summary, and number of running appservers, if any."""
def get_cpu_usage(cls):
"""Discovers CPU usage on this node. Returns: A dictio... | the_stack_v2_python_sparse | InfrastructureManager/appscale/infrastructure/system_manager.py | whoarethebritons/appscale | train | 0 |
092fcb63eadda58ea620701802e49bfe0340abbb | [
"__path = '/_features'\n__query: t.Dict[str, t.Any] = {}\nif error_trace is not None:\n __query['error_trace'] = error_trace\nif filter_path is not None:\n __query['filter_path'] = filter_path\nif human is not None:\n __query['human'] = human\nif pretty is not None:\n __query['pretty'] = pretty\n__heade... | <|body_start_0|>
__path = '/_features'
__query: t.Dict[str, t.Any] = {}
if error_trace is not None:
__query['error_trace'] = error_trace
if filter_path is not None:
__query['filter_path'] = filter_path
if human is not None:
__query['human'] = h... | FeaturesClient | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeaturesClient:
async def get_features(self, *, error_trace: t.Optional[bool]=None, filter_path: t.Optional[t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]]=None, human: t.Optional[bool]=None, pretty: t.Optional[bool]=None) -> ObjectApiResponse[t.Any]:
"""Gets a list of features wh... | stack_v2_sparse_classes_36k_train_001838 | 3,309 | permissive | [
{
"docstring": "Gets a list of features which can be included in snapshots using the feature_states field when creating a snapshot `<https://www.elastic.co/guide/en/elasticsearch/reference/master/get-features-api.html>`_",
"name": "get_features",
"signature": "async def get_features(self, *, error_trace... | 2 | stack_v2_sparse_classes_30k_train_010240 | Implement the Python class `FeaturesClient` described below.
Class description:
Implement the FeaturesClient class.
Method signatures and docstrings:
- async def get_features(self, *, error_trace: t.Optional[bool]=None, filter_path: t.Optional[t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]]=None, human: t.Opti... | Implement the Python class `FeaturesClient` described below.
Class description:
Implement the FeaturesClient class.
Method signatures and docstrings:
- async def get_features(self, *, error_trace: t.Optional[bool]=None, filter_path: t.Optional[t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]]=None, human: t.Opti... | 915bbd784831ccb84e1559af0f829736652d2e78 | <|skeleton|>
class FeaturesClient:
async def get_features(self, *, error_trace: t.Optional[bool]=None, filter_path: t.Optional[t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]]=None, human: t.Optional[bool]=None, pretty: t.Optional[bool]=None) -> ObjectApiResponse[t.Any]:
"""Gets a list of features wh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeaturesClient:
async def get_features(self, *, error_trace: t.Optional[bool]=None, filter_path: t.Optional[t.Union[str, t.Union[t.List[str], t.Tuple[str, ...]]]]=None, human: t.Optional[bool]=None, pretty: t.Optional[bool]=None) -> ObjectApiResponse[t.Any]:
"""Gets a list of features which can be inc... | the_stack_v2_python_sparse | elasticsearch/_async/client/features.py | elastic/elasticsearch-py | train | 3,845 | |
6f07312fa13518413ccaa6d8a4b00f67d49a1d93 | [
"self._check_access(request)\nawait self._check_login(data[ATTR_USERNAME], data[ATTR_PASSWORD])\nreturn web.Response(status=HTTP_OK)",
"provider = self._get_provider()\ntry:\n await provider.async_validate_login(username, password)\nexcept HomeAssistantError:\n raise HTTPUnauthorized() from None"
] | <|body_start_0|>
self._check_access(request)
await self._check_login(data[ATTR_USERNAME], data[ATTR_PASSWORD])
return web.Response(status=HTTP_OK)
<|end_body_0|>
<|body_start_1|>
provider = self._get_provider()
try:
await provider.async_validate_login(username, passw... | Hass.io view to handle auth requests. | HassIOAuth | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HassIOAuth:
"""Hass.io view to handle auth requests."""
async def post(self, request, data):
"""Handle auth requests."""
<|body_0|>
async def _check_login(self, username, password):
"""Check User credentials."""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_001839 | 4,251 | permissive | [
{
"docstring": "Handle auth requests.",
"name": "post",
"signature": "async def post(self, request, data)"
},
{
"docstring": "Check User credentials.",
"name": "_check_login",
"signature": "async def _check_login(self, username, password)"
}
] | 2 | null | Implement the Python class `HassIOAuth` described below.
Class description:
Hass.io view to handle auth requests.
Method signatures and docstrings:
- async def post(self, request, data): Handle auth requests.
- async def _check_login(self, username, password): Check User credentials. | Implement the Python class `HassIOAuth` described below.
Class description:
Hass.io view to handle auth requests.
Method signatures and docstrings:
- async def post(self, request, data): Handle auth requests.
- async def _check_login(self, username, password): Check User credentials.
<|skeleton|>
class HassIOAuth:
... | ba55b4b8338a2dc0ba3f1d750efea49d86571291 | <|skeleton|>
class HassIOAuth:
"""Hass.io view to handle auth requests."""
async def post(self, request, data):
"""Handle auth requests."""
<|body_0|>
async def _check_login(self, username, password):
"""Check User credentials."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HassIOAuth:
"""Hass.io view to handle auth requests."""
async def post(self, request, data):
"""Handle auth requests."""
self._check_access(request)
await self._check_login(data[ATTR_USERNAME], data[ATTR_PASSWORD])
return web.Response(status=HTTP_OK)
async def _check_... | the_stack_v2_python_sparse | homeassistant/components/hassio/auth.py | basnijholt/home-assistant | train | 5 |
0fce2b0191799408092d7ff9a62a5fe807552d7a | [
"params = dict(((key, val) for key, val in request.QUERY_PARAMS.iteritems()))\nform = MultiGetForm(params)\nif not form.is_valid():\n raise BadRequestException()\nreturn Response(form.submit(request))",
"params = dict(((key, val) for key, val in request.DATA.iteritems()))\nparams.update(request.QUERY_PARAMS)\n... | <|body_start_0|>
params = dict(((key, val) for key, val in request.QUERY_PARAMS.iteritems()))
form = MultiGetForm(params)
if not form.is_valid():
raise BadRequestException()
return Response(form.submit(request))
<|end_body_0|>
<|body_start_1|>
params = dict(((key, va... | Class for rendering the view for creating PublicationRequests and searching through the PublicationRequests. | PublicationRequestList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublicationRequestList:
"""Class for rendering the view for creating PublicationRequests and searching through the PublicationRequests."""
def get(self, request):
"""Method for getting multiple PublicationRequests either through search or general listing."""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_001840 | 3,336 | no_license | [
{
"docstring": "Method for getting multiple PublicationRequests either through search or general listing.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Method for creating a new PublicationRequest.",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015834 | Implement the Python class `PublicationRequestList` described below.
Class description:
Class for rendering the view for creating PublicationRequests and searching through the PublicationRequests.
Method signatures and docstrings:
- def get(self, request): Method for getting multiple PublicationRequests either throug... | Implement the Python class `PublicationRequestList` described below.
Class description:
Class for rendering the view for creating PublicationRequests and searching through the PublicationRequests.
Method signatures and docstrings:
- def get(self, request): Method for getting multiple PublicationRequests either throug... | 22c1ce3c5a8e4ed99c2f014672d60ad3c5a4003c | <|skeleton|>
class PublicationRequestList:
"""Class for rendering the view for creating PublicationRequests and searching through the PublicationRequests."""
def get(self, request):
"""Method for getting multiple PublicationRequests either through search or general listing."""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PublicationRequestList:
"""Class for rendering the view for creating PublicationRequests and searching through the PublicationRequests."""
def get(self, request):
"""Method for getting multiple PublicationRequests either through search or general listing."""
params = dict(((key, val) for ... | the_stack_v2_python_sparse | biodig/rest/v2/PublicationRequests/views.py | asmariyaz23/BioDIG | train | 0 |
30e73f6250f205a9661885c894af206e954dec9d | [
"import re\nself.regexes = set()\nif regex_strings is not None:\n for regex_string in regex_strings:\n self.regexes.add(re.compile(regex_string))\nif use_default:\n default_regex_string = 'SG\\\\.[0-9a-zA-Z]+\\\\.[0-9a-zA-Z]+'\n self.regexes.add(re.compile(default_regex_string))",
"if isinstance(r... | <|body_start_0|>
import re
self.regexes = set()
if regex_strings is not None:
for regex_string in regex_strings:
self.regexes.add(re.compile(regex_string))
if use_default:
default_regex_string = 'SG\\.[0-9a-zA-Z]+\\.[0-9a-zA-Z]+'
self.r... | Validates content to ensure SendGrid API key is not present | ValidateApiKey | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidateApiKey:
"""Validates content to ensure SendGrid API key is not present"""
def __init__(self, regex_strings=None, use_default=True):
"""Create an API key validator :param regex_strings: list of regex strings :type regex_strings: list(str) :param use_default: Whether or not to ... | stack_v2_sparse_classes_36k_train_001841 | 2,652 | permissive | [
{
"docstring": "Create an API key validator :param regex_strings: list of regex strings :type regex_strings: list(str) :param use_default: Whether or not to include default regex :type use_default: bool",
"name": "__init__",
"signature": "def __init__(self, regex_strings=None, use_default=True)"
},
... | 3 | stack_v2_sparse_classes_30k_train_014472 | Implement the Python class `ValidateApiKey` described below.
Class description:
Validates content to ensure SendGrid API key is not present
Method signatures and docstrings:
- def __init__(self, regex_strings=None, use_default=True): Create an API key validator :param regex_strings: list of regex strings :type regex_... | Implement the Python class `ValidateApiKey` described below.
Class description:
Validates content to ensure SendGrid API key is not present
Method signatures and docstrings:
- def __init__(self, regex_strings=None, use_default=True): Create an API key validator :param regex_strings: list of regex strings :type regex_... | 2fe145956a1ee50355f5da8deab401e1e118c736 | <|skeleton|>
class ValidateApiKey:
"""Validates content to ensure SendGrid API key is not present"""
def __init__(self, regex_strings=None, use_default=True):
"""Create an API key validator :param regex_strings: list of regex strings :type regex_strings: list(str) :param use_default: Whether or not to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidateApiKey:
"""Validates content to ensure SendGrid API key is not present"""
def __init__(self, regex_strings=None, use_default=True):
"""Create an API key validator :param regex_strings: list of regex strings :type regex_strings: list(str) :param use_default: Whether or not to include defau... | the_stack_v2_python_sparse | sendgrid/helpers/mail/validators.py | sendgrid/sendgrid-python | train | 1,470 |
402bad30f81c9bf2a3c4faca5e710825b32eb91a | [
"self.criteria = kwargs.pop('criteria')\nsuper().__init__(*args, **kwargs)\nself.fields['levels_of_attainment'].initial = ', '.join(self.criteria[0].categories)",
"form_data = super().clean()\nn_loas = len([loa for loa in form_data['levels_of_attainment'].split(',') if loa])\nif n_loas != len(self.criteria[0].cat... | <|body_start_0|>
self.criteria = kwargs.pop('criteria')
super().__init__(*args, **kwargs)
self.fields['levels_of_attainment'].initial = ', '.join(self.criteria[0].categories)
<|end_body_0|>
<|body_start_1|>
form_data = super().clean()
n_loas = len([loa for loa in form_data['leve... | Edit the levels of attainment of a rubric. | RubricLOAForm | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RubricLOAForm:
"""Edit the levels of attainment of a rubric."""
def __init__(self, *args, **kwargs):
"""Store the criteria."""
<|body_0|>
def clean(self) -> Dict:
"""Check that the number of LOAs didn't change."""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_001842 | 4,556 | permissive | [
{
"docstring": "Store the criteria.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Check that the number of LOAs didn't change.",
"name": "clean",
"signature": "def clean(self) -> Dict"
}
] | 2 | stack_v2_sparse_classes_30k_train_020120 | Implement the Python class `RubricLOAForm` described below.
Class description:
Edit the levels of attainment of a rubric.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Store the criteria.
- def clean(self) -> Dict: Check that the number of LOAs didn't change. | Implement the Python class `RubricLOAForm` described below.
Class description:
Edit the levels of attainment of a rubric.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Store the criteria.
- def clean(self) -> Dict: Check that the number of LOAs didn't change.
<|skeleton|>
class RubricLOAFo... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class RubricLOAForm:
"""Edit the levels of attainment of a rubric."""
def __init__(self, *args, **kwargs):
"""Store the criteria."""
<|body_0|>
def clean(self) -> Dict:
"""Check that the number of LOAs didn't change."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RubricLOAForm:
"""Edit the levels of attainment of a rubric."""
def __init__(self, *args, **kwargs):
"""Store the criteria."""
self.criteria = kwargs.pop('criteria')
super().__init__(*args, **kwargs)
self.fields['levels_of_attainment'].initial = ', '.join(self.criteria[0].... | the_stack_v2_python_sparse | ontask/action/forms/crud.py | abelardopardo/ontask_b | train | 43 |
5a9daab4114da3539b8233b71115e085b5a9a4fe | [
"paginated = Paginator(models.SiteInvite.objects.filter(user=request.user).order_by('-created_date'), PAGE_LENGTH)\npage = paginated.get_page(request.GET.get('page'))\ndata = {'invites': page, 'page_range': paginated.get_elided_page_range(page.number, on_each_side=2, on_ends=1), 'form': forms.CreateInviteForm()}\nr... | <|body_start_0|>
paginated = Paginator(models.SiteInvite.objects.filter(user=request.user).order_by('-created_date'), PAGE_LENGTH)
page = paginated.get_page(request.GET.get('page'))
data = {'invites': page, 'page_range': paginated.get_elided_page_range(page.number, on_each_side=2, on_ends=1), 'f... | create invites | ManageInvites | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageInvites:
"""create invites"""
def get(self, request):
"""invite management page"""
<|body_0|>
def post(self, request):
"""creates an invite database entry"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
paginated = Paginator(models.SiteInv... | stack_v2_sparse_classes_36k_train_001843 | 6,414 | no_license | [
{
"docstring": "invite management page",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "creates an invite database entry",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021061 | Implement the Python class `ManageInvites` described below.
Class description:
create invites
Method signatures and docstrings:
- def get(self, request): invite management page
- def post(self, request): creates an invite database entry | Implement the Python class `ManageInvites` described below.
Class description:
create invites
Method signatures and docstrings:
- def get(self, request): invite management page
- def post(self, request): creates an invite database entry
<|skeleton|>
class ManageInvites:
"""create invites"""
def get(self, re... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class ManageInvites:
"""create invites"""
def get(self, request):
"""invite management page"""
<|body_0|>
def post(self, request):
"""creates an invite database entry"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManageInvites:
"""create invites"""
def get(self, request):
"""invite management page"""
paginated = Paginator(models.SiteInvite.objects.filter(user=request.user).order_by('-created_date'), PAGE_LENGTH)
page = paginated.get_page(request.GET.get('page'))
data = {'invites': ... | the_stack_v2_python_sparse | bookwyrm/views/admin/invite.py | bookwyrm-social/bookwyrm | train | 1,398 |
964426d5b91a14f8753ff1b5145b2912c09f1b67 | [
"super().__init__(driver)\nself.driver = driver\nself.util = Util()",
"try:\n actualTitle = self.getTitle()\n return self.util.verifyTextContains(actualTitle, textToVerify)\nexcept:\n self.log.error('Failed to get the page title')\n traceback.print_exc()\n return False"
] | <|body_start_0|>
super().__init__(driver)
self.driver = driver
self.util = Util()
<|end_body_0|>
<|body_start_1|>
try:
actualTitle = self.getTitle()
return self.util.verifyTextContains(actualTitle, textToVerify)
except:
self.log.error('Failed ... | Basepage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Basepage:
def __init__(self, driver):
"""Base page inherites from the selenium driver which takes care of all the operations related to selenium driver So further we can just inherit this Base page into all our prages so we can have both the functionality :param driver:"""
<|body... | stack_v2_sparse_classes_36k_train_001844 | 1,243 | no_license | [
{
"docstring": "Base page inherites from the selenium driver which takes care of all the operations related to selenium driver So further we can just inherit this Base page into all our prages so we can have both the functionality :param driver:",
"name": "__init__",
"signature": "def __init__(self, dri... | 2 | stack_v2_sparse_classes_30k_train_013569 | Implement the Python class `Basepage` described below.
Class description:
Implement the Basepage class.
Method signatures and docstrings:
- def __init__(self, driver): Base page inherites from the selenium driver which takes care of all the operations related to selenium driver So further we can just inherit this Bas... | Implement the Python class `Basepage` described below.
Class description:
Implement the Basepage class.
Method signatures and docstrings:
- def __init__(self, driver): Base page inherites from the selenium driver which takes care of all the operations related to selenium driver So further we can just inherit this Bas... | 8afe6771a96d5a70ca1dcee98b7a6123218dc0d1 | <|skeleton|>
class Basepage:
def __init__(self, driver):
"""Base page inherites from the selenium driver which takes care of all the operations related to selenium driver So further we can just inherit this Base page into all our prages so we can have both the functionality :param driver:"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Basepage:
def __init__(self, driver):
"""Base page inherites from the selenium driver which takes care of all the operations related to selenium driver So further we can just inherit this Base page into all our prages so we can have both the functionality :param driver:"""
super().__init__(dri... | the_stack_v2_python_sparse | base/basepage.py | karthikpalameri/PythonFramework | train | 0 | |
7831333ba65890712bf632196c9181d7696f0464 | [
"self.tx_table = dict()\nself.tx_table['#'] = []\nself.tx_table['Agent Role'] = []\nself.tx_table['Counterparty'] = []\nself.tx_table['Amount'] = []\nself.tx_table['Goods Exchanged'] = []",
"self.tx_table['#'].append(str(len(self.tx_table['#'])))\nself.tx_table['Agent Role'].append('Buyer' if tx.is_sender_buyer e... | <|body_start_0|>
self.tx_table = dict()
self.tx_table['#'] = []
self.tx_table['Agent Role'] = []
self.tx_table['Counterparty'] = []
self.tx_table['Amount'] = []
self.tx_table['Goods Exchanged'] = []
<|end_body_0|>
<|body_start_1|>
self.tx_table['#'].append(str(le... | Class maintaining a html table of transactions. | TransactionTable | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransactionTable:
"""Class maintaining a html table of transactions."""
def __init__(self):
"""Instantiate a TransactionTable."""
<|body_0|>
def add_transaction(self, tx: Transaction, agent_name: Optional[str]=None) -> None:
"""Add a transaction to the table. :pa... | stack_v2_sparse_classes_36k_train_001845 | 11,245 | permissive | [
{
"docstring": "Instantiate a TransactionTable.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Add a transaction to the table. :param tx: the Transaction object :param agent_name: the name of the agent :return: None",
"name": "add_transaction",
"signature": "d... | 3 | null | Implement the Python class `TransactionTable` described below.
Class description:
Class maintaining a html table of transactions.
Method signatures and docstrings:
- def __init__(self): Instantiate a TransactionTable.
- def add_transaction(self, tx: Transaction, agent_name: Optional[str]=None) -> None: Add a transact... | Implement the Python class `TransactionTable` described below.
Class description:
Class maintaining a html table of transactions.
Method signatures and docstrings:
- def __init__(self): Instantiate a TransactionTable.
- def add_transaction(self, tx: Transaction, agent_name: Optional[str]=None) -> None: Add a transact... | 33c4aa24ca8daf26f2c8f2d2fa38d7f4bf750cfa | <|skeleton|>
class TransactionTable:
"""Class maintaining a html table of transactions."""
def __init__(self):
"""Instantiate a TransactionTable."""
<|body_0|>
def add_transaction(self, tx: Transaction, agent_name: Optional[str]=None) -> None:
"""Add a transaction to the table. :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransactionTable:
"""Class maintaining a html table of transactions."""
def __init__(self):
"""Instantiate a TransactionTable."""
self.tx_table = dict()
self.tx_table['#'] = []
self.tx_table['Agent Role'] = []
self.tx_table['Counterparty'] = []
self.tx_tabl... | the_stack_v2_python_sparse | tac/gui/dashboards/agent.py | fetchai/agents-tac | train | 30 |
be2644616b6b0ede0bd3af743843ea8b722aeb0e | [
"if not root:\n return '_'\nelse:\n left_repr = f'({self.serialize(root.left)})' if root.left else '_'\n right_repr = f'({self.serialize(root.right)})' if root.right else '_'\n return f'{root.val} {left_repr} {right_repr}'",
"if data[0] == '_':\n return None\narr = data.split()\nrootVal = arr[0]\nd... | <|body_start_0|>
if not root:
return '_'
else:
left_repr = f'({self.serialize(root.left)})' if root.left else '_'
right_repr = f'({self.serialize(root.right)})' if root.right else '_'
return f'{root.val} {left_repr} {right_repr}'
<|end_body_0|>
<|body_sta... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_36k_train_001846 | 1,743 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_012806 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | ec14ad04893073ff911b6d11aacc26b372766b6d | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if not root:
return '_'
else:
left_repr = f'({self.serialize(root.left)})' if root.left else '_'
right_repr = f'({self.serialize(root.right)})' if root.right ... | the_stack_v2_python_sparse | problems/Medium/serialize-and-deserialize-binary-tree/sol.py | Zahidsqldba07/leetcode-3 | train | 0 | |
8cc0dc9633f9b9cee52b2c36367c06a63ea75666 | [
"self.terms = terms\n\ndef form():\n res = 0\n for x in terms:\n res += x.base ** x.power\n return res\nself.form = form",
"if isinstance(target, Formula) == False:\n raise ValueError('Require Formula instance!')\n\ndef form():\n res = 0\n for t in target.terms:\n for x in self.ter... | <|body_start_0|>
self.terms = terms
def form():
res = 0
for x in terms:
res += x.base ** x.power
return res
self.form = form
<|end_body_0|>
<|body_start_1|>
if isinstance(target, Formula) == False:
raise ValueError('Requir... | Formula class. Have base number and multiplier. | Formula | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Formula:
"""Formula class. Have base number and multiplier."""
def __init__(self, terms):
"""Recieved Term object list."""
<|body_0|>
def __mul__(self, target):
"""Multiply out."""
<|body_1|>
def calc(self):
"""Retaining formula caluculate.""... | stack_v2_sparse_classes_36k_train_001847 | 7,281 | no_license | [
{
"docstring": "Recieved Term object list.",
"name": "__init__",
"signature": "def __init__(self, terms)"
},
{
"docstring": "Multiply out.",
"name": "__mul__",
"signature": "def __mul__(self, target)"
},
{
"docstring": "Retaining formula caluculate.",
"name": "calc",
"sig... | 3 | stack_v2_sparse_classes_30k_train_019529 | Implement the Python class `Formula` described below.
Class description:
Formula class. Have base number and multiplier.
Method signatures and docstrings:
- def __init__(self, terms): Recieved Term object list.
- def __mul__(self, target): Multiply out.
- def calc(self): Retaining formula caluculate. | Implement the Python class `Formula` described below.
Class description:
Formula class. Have base number and multiplier.
Method signatures and docstrings:
- def __init__(self, terms): Recieved Term object list.
- def __mul__(self, target): Multiply out.
- def calc(self): Retaining formula caluculate.
<|skeleton|>
cl... | 0c4f79ce5c370027b76ec9a336b392ee61b12a7a | <|skeleton|>
class Formula:
"""Formula class. Have base number and multiplier."""
def __init__(self, terms):
"""Recieved Term object list."""
<|body_0|>
def __mul__(self, target):
"""Multiply out."""
<|body_1|>
def calc(self):
"""Retaining formula caluculate.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Formula:
"""Formula class. Have base number and multiplier."""
def __init__(self, terms):
"""Recieved Term object list."""
self.terms = terms
def form():
res = 0
for x in terms:
res += x.base ** x.power
return res
self.f... | the_stack_v2_python_sparse | pheasant/numtheory.py | moguonyanko/pheasant | train | 0 |
8ad5bc49a6aaeb048c0caf0b861c4cdfd88c7334 | [
"if not root or (not root.left and (not root.right)):\n return True\nleft_depth = self.get_depth(root.left)\nright_depth = self.get_depth(root.right)\nreturn abs(left_depth - right_depth) <= 1 and self.isBalanced(root.left) and self.isBalanced(root.right)",
"if not tree:\n return 0\nreturn 1 + max(self.get_... | <|body_start_0|>
if not root or (not root.left and (not root.right)):
return True
left_depth = self.get_depth(root.left)
right_depth = self.get_depth(root.right)
return abs(left_depth - right_depth) <= 1 and self.isBalanced(root.left) and self.isBalanced(root.right)
<|end_bod... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isBalanced(self, root: TreeNode) -> bool:
"""判断根节点左右节点的高度差，依次递归，记得采用functools； 也可以直接在计算高度时进行判断，返回高度差，采用全局变量获取是否平衡的结果； :param root: :return:"""
<|body_0|>
def get_depth(self, tree):
""":param tree: :return:"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_001848 | 1,203 | no_license | [
{
"docstring": "判断根节点左右节点的高度差，依次递归，记得采用functools； 也可以直接在计算高度时进行判断，返回高度差，采用全局变量获取是否平衡的结果； :param root: :return:",
"name": "isBalanced",
"signature": "def isBalanced(self, root: TreeNode) -> bool"
},
{
"docstring": ":param tree: :return:",
"name": "get_depth",
"signature": "def get_depth(s... | 2 | stack_v2_sparse_classes_30k_train_015267 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root: TreeNode) -> bool: 判断根节点左右节点的高度差，依次递归，记得采用functools； 也可以直接在计算高度时进行判断，返回高度差，采用全局变量获取是否平衡的结果； :param root: :return:
- def get_depth(self, tree): :param t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root: TreeNode) -> bool: 判断根节点左右节点的高度差，依次递归，记得采用functools； 也可以直接在计算高度时进行判断，返回高度差，采用全局变量获取是否平衡的结果； :param root: :return:
- def get_depth(self, tree): :param t... | f2c162654a83c51495ebd161f42a1d0b69caf72d | <|skeleton|>
class Solution:
def isBalanced(self, root: TreeNode) -> bool:
"""判断根节点左右节点的高度差，依次递归，记得采用functools； 也可以直接在计算高度时进行判断，返回高度差，采用全局变量获取是否平衡的结果； :param root: :return:"""
<|body_0|>
def get_depth(self, tree):
""":param tree: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isBalanced(self, root: TreeNode) -> bool:
"""判断根节点左右节点的高度差，依次递归，记得采用functools； 也可以直接在计算高度时进行判断，返回高度差，采用全局变量获取是否平衡的结果； :param root: :return:"""
if not root or (not root.left and (not root.right)):
return True
left_depth = self.get_depth(root.left)
right... | the_stack_v2_python_sparse | 110 isBalanced.py | ABenxj/leetcode | train | 1 | |
a60711a7d4477f72c22695b57ddd9e31403a92c4 | [
"self.screen_width = 800\nself.screen_height = 600\nself.bg_color = (30, 30, 30)\nself.ship_limit = 3\nself.ship_slow_speed_factor = 1 / 7\nself.bullet_width = 1\nself.bullet_height = 30\nself.bullet_color = (255, 255, 0)\nself.speedup_scale = 1.01\nself.score_scale = 1.5\nself.yellow_prob = 20.0\nself.red_prob = s... | <|body_start_0|>
self.screen_width = 800
self.screen_height = 600
self.bg_color = (30, 30, 30)
self.ship_limit = 3
self.ship_slow_speed_factor = 1 / 7
self.bullet_width = 1
self.bullet_height = 30
self.bullet_color = (255, 255, 0)
self.speedup_scal... | A class to store all settings for Alien Invasion. | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""A class to store all settings for Alien Invasion."""
def __init__(self):
"""Initialize the game's static settings."""
<|body_0|>
def initialize_dynamic_settings(self):
"""Initialize settings that change throughout the game."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_001849 | 2,834 | no_license | [
{
"docstring": "Initialize the game's static settings.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Initialize settings that change throughout the game.",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_015412 | Implement the Python class `Settings` described below.
Class description:
A class to store all settings for Alien Invasion.
Method signatures and docstrings:
- def __init__(self): Initialize the game's static settings.
- def initialize_dynamic_settings(self): Initialize settings that change throughout the game.
- def... | Implement the Python class `Settings` described below.
Class description:
A class to store all settings for Alien Invasion.
Method signatures and docstrings:
- def __init__(self): Initialize the game's static settings.
- def initialize_dynamic_settings(self): Initialize settings that change throughout the game.
- def... | 61d8a85c33f54cd138c94433f062b74d396cc57f | <|skeleton|>
class Settings:
"""A class to store all settings for Alien Invasion."""
def __init__(self):
"""Initialize the game's static settings."""
<|body_0|>
def initialize_dynamic_settings(self):
"""Initialize settings that change throughout the game."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Settings:
"""A class to store all settings for Alien Invasion."""
def __init__(self):
"""Initialize the game's static settings."""
self.screen_width = 800
self.screen_height = 600
self.bg_color = (30, 30, 30)
self.ship_limit = 3
self.ship_slow_speed_factor ... | the_stack_v2_python_sparse | settings.py | JankaGramofonomanka/alien_invasion | train | 0 |
446bf7099ab4ed6cb081b1b6c553ef8b568e75e1 | [
"super().__init__(description.key, api, coordinator)\nself.field = description.field\nself.entity_description = description\nself.data_type = description.field.field_type\nself.raw_format = description.raw_format",
"all_data = self.coordinator.data\nvalue = self.api.get_field_value(all_data, self.field.name)\nif ... | <|body_start_0|>
super().__init__(description.key, api, coordinator)
self.field = description.field
self.entity_description = description
self.data_type = description.field.field_type
self.raw_format = description.raw_format
<|end_body_0|>
<|body_start_1|>
all_data = sel... | Get a sensor data from the Renson API and store it in the state of the class. | RensonSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RensonSensor:
"""Get a sensor data from the Renson API and store it in the state of the class."""
def __init__(self, description: RensonSensorEntityDescription, api: RensonVentilation, coordinator: RensonCoordinator) -> None:
"""Initialize class."""
<|body_0|>
def _handl... | stack_v2_sparse_classes_36k_train_001850 | 10,303 | permissive | [
{
"docstring": "Initialize class.",
"name": "__init__",
"signature": "def __init__(self, description: RensonSensorEntityDescription, api: RensonVentilation, coordinator: RensonCoordinator) -> None"
},
{
"docstring": "Handle updated data from the coordinator.",
"name": "_handle_coordinator_up... | 2 | null | Implement the Python class `RensonSensor` described below.
Class description:
Get a sensor data from the Renson API and store it in the state of the class.
Method signatures and docstrings:
- def __init__(self, description: RensonSensorEntityDescription, api: RensonVentilation, coordinator: RensonCoordinator) -> None... | Implement the Python class `RensonSensor` described below.
Class description:
Get a sensor data from the Renson API and store it in the state of the class.
Method signatures and docstrings:
- def __init__(self, description: RensonSensorEntityDescription, api: RensonVentilation, coordinator: RensonCoordinator) -> None... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class RensonSensor:
"""Get a sensor data from the Renson API and store it in the state of the class."""
def __init__(self, description: RensonSensorEntityDescription, api: RensonVentilation, coordinator: RensonCoordinator) -> None:
"""Initialize class."""
<|body_0|>
def _handl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RensonSensor:
"""Get a sensor data from the Renson API and store it in the state of the class."""
def __init__(self, description: RensonSensorEntityDescription, api: RensonVentilation, coordinator: RensonCoordinator) -> None:
"""Initialize class."""
super().__init__(description.key, api, ... | the_stack_v2_python_sparse | homeassistant/components/renson/sensor.py | home-assistant/core | train | 35,501 |
5f5c9015bfe5d81e4f9b193024f9317e73164efa | [
"if regrid_mode not in self.REGRID_REQUIRES_LANDMASK:\n msg = 'Unrecognised regrid mode {}'\n raise ValueError(msg.format(regrid_mode))\nif landmask is None and self.REGRID_REQUIRES_LANDMASK[regrid_mode]:\n msg = 'Regrid mode {} requires an input landmask cube'\n raise ValueError(msg.format(regrid_mode)... | <|body_start_0|>
if regrid_mode not in self.REGRID_REQUIRES_LANDMASK:
msg = 'Unrecognised regrid mode {}'
raise ValueError(msg.format(regrid_mode))
if landmask is None and self.REGRID_REQUIRES_LANDMASK[regrid_mode]:
msg = 'Regrid mode {} requires an input landmask cub... | Nearest-neighbour and bilinear regridding with or without land-sea mask awareness. When land-sea mask considered, surface-type-mismatched source points are excluded from field regridding calculation for target points. For example, for regridding a field using nearest-neighbour approach with land-sea awareness, regridde... | RegridLandSea | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegridLandSea:
"""Nearest-neighbour and bilinear regridding with or without land-sea mask awareness. When land-sea mask considered, surface-type-mismatched source points are excluded from field regridding calculation for target points. For example, for regridding a field using nearest-neighbour a... | stack_v2_sparse_classes_36k_train_001851 | 17,882 | permissive | [
{
"docstring": "Initialise regridding parameters. Args: regrid_mode: Mode of interpolation in regridding. Valid options are \"bilinear\", \"nearest\", \"nearest-with-mask\", \"bilinear-2\",\"nearest-2\", \"nearest-with-mask-2\" or \"bilinear-with-mask-2\". \"***-with-mask**\" option triggers adjustment of regri... | 3 | stack_v2_sparse_classes_30k_train_007510 | Implement the Python class `RegridLandSea` described below.
Class description:
Nearest-neighbour and bilinear regridding with or without land-sea mask awareness. When land-sea mask considered, surface-type-mismatched source points are excluded from field regridding calculation for target points. For example, for regri... | Implement the Python class `RegridLandSea` described below.
Class description:
Nearest-neighbour and bilinear regridding with or without land-sea mask awareness. When land-sea mask considered, surface-type-mismatched source points are excluded from field regridding calculation for target points. For example, for regri... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class RegridLandSea:
"""Nearest-neighbour and bilinear regridding with or without land-sea mask awareness. When land-sea mask considered, surface-type-mismatched source points are excluded from field regridding calculation for target points. For example, for regridding a field using nearest-neighbour a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegridLandSea:
"""Nearest-neighbour and bilinear regridding with or without land-sea mask awareness. When land-sea mask considered, surface-type-mismatched source points are excluded from field regridding calculation for target points. For example, for regridding a field using nearest-neighbour approach with ... | the_stack_v2_python_sparse | improver/regrid/landsea.py | metoppv/improver | train | 101 |
1fade49394ddb6490be49c5a9a6c02e2f2af05e7 | [
"len_s = len(strs)\ndp = [[[0] * (n + 1) for i in range(m + 1)] for j in range(len_s + 1)]\nfor k in range(1, len_s + 1):\n count_0 = strs[k - 1].count('0')\n count_1 = strs[k - 1].count('1')\n for i in range(m + 1):\n for j in range(n + 1):\n dp[k][i][j] = dp[k - 1][i][j]\n if... | <|body_start_0|>
len_s = len(strs)
dp = [[[0] * (n + 1) for i in range(m + 1)] for j in range(len_s + 1)]
for k in range(1, len_s + 1):
count_0 = strs[k - 1].count('0')
count_1 = strs[k - 1].count('1')
for i in range(m + 1):
for j in range(n + ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""执行用时： 5960 ms , 在所有 Python3 提交中击败了 12.47% 的用户 内存消耗： 70.1 MB , 在所有 Python3 提交中击败了 10.96% 的用户"""
<|body_0|>
def findMaxForm1(self, strs: List[str], m: int, n: int) -> int:
"""执行用时： 3024 ms , 在所... | stack_v2_sparse_classes_36k_train_001852 | 2,621 | no_license | [
{
"docstring": "执行用时： 5960 ms , 在所有 Python3 提交中击败了 12.47% 的用户 内存消耗： 70.1 MB , 在所有 Python3 提交中击败了 10.96% 的用户",
"name": "findMaxForm",
"signature": "def findMaxForm(self, strs: List[str], m: int, n: int) -> int"
},
{
"docstring": "执行用时： 3024 ms , 在所有 Python3 提交中击败了 75.50% 的用户 内存消耗： 15 MB , 在所有 Pyt... | 2 | stack_v2_sparse_classes_30k_train_005199 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm(self, strs: List[str], m: int, n: int) -> int: 执行用时： 5960 ms , 在所有 Python3 提交中击败了 12.47% 的用户 内存消耗： 70.1 MB , 在所有 Python3 提交中击败了 10.96% 的用户
- def findMaxForm1(self... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm(self, strs: List[str], m: int, n: int) -> int: 执行用时： 5960 ms , 在所有 Python3 提交中击败了 12.47% 的用户 内存消耗： 70.1 MB , 在所有 Python3 提交中击败了 10.96% 的用户
- def findMaxForm1(self... | d613ed8a5a2c15ace7d513965b372d128845d66a | <|skeleton|>
class Solution:
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""执行用时： 5960 ms , 在所有 Python3 提交中击败了 12.47% 的用户 内存消耗： 70.1 MB , 在所有 Python3 提交中击败了 10.96% 的用户"""
<|body_0|>
def findMaxForm1(self, strs: List[str], m: int, n: int) -> int:
"""执行用时： 3024 ms , 在所... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaxForm(self, strs: List[str], m: int, n: int) -> int:
"""执行用时： 5960 ms , 在所有 Python3 提交中击败了 12.47% 的用户 内存消耗： 70.1 MB , 在所有 Python3 提交中击败了 10.96% 的用户"""
len_s = len(strs)
dp = [[[0] * (n + 1) for i in range(m + 1)] for j in range(len_s + 1)]
for k in range(1, ... | the_stack_v2_python_sparse | 一和零.py | nomboy/leetcode | train | 0 | |
aae9886c497007d76f76c70320050dbe0dabddec | [
"size = len(candidates)\nif size <= 0:\n return []\ncandidates.sort()\npath = []\nres = []\nself._find_path(target, path, res, candidates, 0, size)\nreturn res",
"if target == 0:\n res.append(path.copy())\nelse:\n for i in range(begin, size):\n left_num = target - candidates[i]\n if left_nu... | <|body_start_0|>
size = len(candidates)
if size <= 0:
return []
candidates.sort()
path = []
res = []
self._find_path(target, path, res, candidates, 0, size)
return res
<|end_body_0|>
<|body_start_1|>
if target == 0:
res.append(path... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；"""
<|body_0|>
def _find_path(self, target, path, res, candidates, begin, size):
"""沿着路径往下走"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_001853 | 2,269 | no_license | [
{
"docstring": "回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；",
"name": "combinationSum",
"signature": "def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]"
},
{
"docstring": "沿着路径往下走",
"name": "_find_path",
"signature": "def _find_path(self, target, path... | 2 | stack_v2_sparse_classes_30k_test_000658 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]: 回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；
- def _find_path(self, target, path, res, cand... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]: 回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；
- def _find_path(self, target, path, res, cand... | 13e9f74be18949875b271a742b1dfe87485ff3a2 | <|skeleton|>
class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；"""
<|body_0|>
def _find_path(self, target, path, res, candidates, begin, size):
"""沿着路径往下走"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
"""回溯法，层层递减，得到符合条件的路径就加入结果集中，超出则剪枝； 主要是要注意一些细节，避免重复等；"""
size = len(candidates)
if size <= 0:
return []
candidates.sort()
path = []
res = []
self._find... | the_stack_v2_python_sparse | 39_Combination_Sum.py | Joker-Jerome/leetcode | train | 1 | |
6dc481e5f463f2677c05316be025fe7e4c5214b2 | [
"self.udp_target = udp_target\nself.udp_port = udp_port\nself.verbosity = verbosity\nself.peer = '{}:{}'.format(self.udp_target, self.udp_port)\nif is_ipv4(self.udp_target):\n self.udp_client = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\nelif is_ipv6(self.udp_target):\n self.udp_client = socket.socket(s... | <|body_start_0|>
self.udp_target = udp_target
self.udp_port = udp_port
self.verbosity = verbosity
self.peer = '{}:{}'.format(self.udp_target, self.udp_port)
if is_ipv4(self.udp_target):
self.udp_client = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
elif is... | UDP Client provides methods to handle communication with UDP server | UDPCli | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UDPCli:
"""UDP Client provides methods to handle communication with UDP server"""
def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None:
"""UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server po... | stack_v2_sparse_classes_36k_train_001854 | 3,289 | permissive | [
{
"docstring": "UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server port :param bool verbosity: display verbose output :return None:",
"name": "__init__",
"signature": "def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False)... | 4 | null | Implement the Python class `UDPCli` described below.
Class description:
UDP Client provides methods to handle communication with UDP server
Method signatures and docstrings:
- def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None: UDP client constructor :param str udp_target: target UDP se... | Implement the Python class `UDPCli` described below.
Class description:
UDP Client provides methods to handle communication with UDP server
Method signatures and docstrings:
- def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None: UDP client constructor :param str udp_target: target UDP se... | 56ae6325c08bcedd22c57b9fe11b58f1b38314ca | <|skeleton|>
class UDPCli:
"""UDP Client provides methods to handle communication with UDP server"""
def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None:
"""UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server po... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UDPCli:
"""UDP Client provides methods to handle communication with UDP server"""
def __init__(self, udp_target: str, udp_port: int, verbosity: bool=False) -> None:
"""UDP client constructor :param str udp_target: target UDP server ip address :param int udp_port: target UDP server port :param boo... | the_stack_v2_python_sparse | maza/core/udp/udp_client.py | ArturSpirin/maza | train | 2 |
e1bba41fb22da447998c05e1ec3c5c3ff2c1ebf1 | [
"self.ad_restore_params = ad_restore_params\nself.clone_task_id = clone_task_id\nself.exchange_restore_params = exchange_restore_params\nself.oracle_restore_params = oracle_restore_params\nself.sql_restore_params = sql_restore_params\nself.target_host = target_host\nself.target_host_parent_source = target_host_pare... | <|body_start_0|>
self.ad_restore_params = ad_restore_params
self.clone_task_id = clone_task_id
self.exchange_restore_params = exchange_restore_params
self.oracle_restore_params = oracle_restore_params
self.sql_restore_params = sql_restore_params
self.target_host = target_... | Implementation of the 'RestoreAppObjectParams' model. TODO: type description here. Attributes: ad_restore_params (RestoreADAppObjectParams): The AD specific application object restore params. Only applicable if the RestoreAppObject.app_entity is of type kAD. clone_task_id (long|int): Id of finished clone task which has... | RestoreAppObjectParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreAppObjectParams:
"""Implementation of the 'RestoreAppObjectParams' model. TODO: type description here. Attributes: ad_restore_params (RestoreADAppObjectParams): The AD specific application object restore params. Only applicable if the RestoreAppObject.app_entity is of type kAD. clone_task_... | stack_v2_sparse_classes_36k_train_001855 | 5,270 | permissive | [
{
"docstring": "Constructor for the RestoreAppObjectParams class",
"name": "__init__",
"signature": "def __init__(self, ad_restore_params=None, clone_task_id=None, exchange_restore_params=None, oracle_restore_params=None, sql_restore_params=None, target_host=None, target_host_parent_source=None)"
},
... | 2 | null | Implement the Python class `RestoreAppObjectParams` described below.
Class description:
Implementation of the 'RestoreAppObjectParams' model. TODO: type description here. Attributes: ad_restore_params (RestoreADAppObjectParams): The AD specific application object restore params. Only applicable if the RestoreAppObject... | Implement the Python class `RestoreAppObjectParams` described below.
Class description:
Implementation of the 'RestoreAppObjectParams' model. TODO: type description here. Attributes: ad_restore_params (RestoreADAppObjectParams): The AD specific application object restore params. Only applicable if the RestoreAppObject... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreAppObjectParams:
"""Implementation of the 'RestoreAppObjectParams' model. TODO: type description here. Attributes: ad_restore_params (RestoreADAppObjectParams): The AD specific application object restore params. Only applicable if the RestoreAppObject.app_entity is of type kAD. clone_task_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreAppObjectParams:
"""Implementation of the 'RestoreAppObjectParams' model. TODO: type description here. Attributes: ad_restore_params (RestoreADAppObjectParams): The AD specific application object restore params. Only applicable if the RestoreAppObject.app_entity is of type kAD. clone_task_id (long|int)... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_app_object_params.py | cohesity/management-sdk-python | train | 24 |
42aa0adc6de70271db0420d402122aa7be5401b5 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('vinwah', 'vinwah')\nuri = 'https://data.boston.gov/api/3/action/datastore_search?resource_id=062fc6fa-b5ff-4270-86cf-202225e40858&limit=171000'\nresponse = urllib.request.urlopen(uri).read().decode('utf-... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('vinwah', 'vinwah')
uri = 'https://data.boston.gov/api/3/action/datastore_search?resource_id=062fc6fa-b5ff-4270-86cf-202225e40858&limit=171000'
res... | retrieveProperties | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class retrieveProperties:
def execute(trial=False):
"""Retrieves data about properties in Boston from Analyze Boston"""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening... | stack_v2_sparse_classes_36k_train_001856 | 3,579 | no_license | [
{
"docstring": "Retrieves data about properties in Boston from Analyze Boston",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describ... | 2 | null | Implement the Python class `retrieveProperties` described below.
Class description:
Implement the retrieveProperties class.
Method signatures and docstrings:
- def execute(trial=False): Retrieves data about properties in Boston from Analyze Boston
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTim... | Implement the Python class `retrieveProperties` described below.
Class description:
Implement the retrieveProperties class.
Method signatures and docstrings:
- def execute(trial=False): Retrieves data about properties in Boston from Analyze Boston
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTim... | b5ccaad97f6e35f9580e645ca764f36eb3406f43 | <|skeleton|>
class retrieveProperties:
def execute(trial=False):
"""Retrieves data about properties in Boston from Analyze Boston"""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class retrieveProperties:
def execute(trial=False):
"""Retrieves data about properties in Boston from Analyze Boston"""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('vinwah', 'vinwah')
uri = 'https://data.... | the_stack_v2_python_sparse | vinwah/retrieveProperties.py | dwang1995/course-2018-spr-proj | train | 1 | |
755d7f98a52f0deb4da9799518bc1bf3c096ebda | [
"super(QuestionRightsDomainTest, self).setUp()\nself.question_id = 'question_id'\nself.signup('user@example.com', 'User')\nself.skill_ids = ['skill_1']\nself.question = question_domain.Question.create_default_question(self.question_id, self.skill_ids)\nself.user_id = self.get_user_id_from_email('user@example.com')"... | <|body_start_0|>
super(QuestionRightsDomainTest, self).setUp()
self.question_id = 'question_id'
self.signup('user@example.com', 'User')
self.skill_ids = ['skill_1']
self.question = question_domain.Question.create_default_question(self.question_id, self.skill_ids)
self.use... | Test for Question Rights Domain object. | QuestionRightsDomainTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionRightsDomainTest:
"""Test for Question Rights Domain object."""
def setUp(self):
"""Before each individual test, create a question and user."""
<|body_0|>
def test_to_dict(self):
"""Test to verify to_dict method of the Question Rights Domain object."""
... | stack_v2_sparse_classes_36k_train_001857 | 20,931 | permissive | [
{
"docstring": "Before each individual test, create a question and user.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test to verify to_dict method of the Question Rights Domain object.",
"name": "test_to_dict",
"signature": "def test_to_dict(self)"
},
{
"... | 3 | null | Implement the Python class `QuestionRightsDomainTest` described below.
Class description:
Test for Question Rights Domain object.
Method signatures and docstrings:
- def setUp(self): Before each individual test, create a question and user.
- def test_to_dict(self): Test to verify to_dict method of the Question Rights... | Implement the Python class `QuestionRightsDomainTest` described below.
Class description:
Test for Question Rights Domain object.
Method signatures and docstrings:
- def setUp(self): Before each individual test, create a question and user.
- def test_to_dict(self): Test to verify to_dict method of the Question Rights... | 899b9755a6b795a8991e596055ac24065a8435e0 | <|skeleton|>
class QuestionRightsDomainTest:
"""Test for Question Rights Domain object."""
def setUp(self):
"""Before each individual test, create a question and user."""
<|body_0|>
def test_to_dict(self):
"""Test to verify to_dict method of the Question Rights Domain object."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuestionRightsDomainTest:
"""Test for Question Rights Domain object."""
def setUp(self):
"""Before each individual test, create a question and user."""
super(QuestionRightsDomainTest, self).setUp()
self.question_id = 'question_id'
self.signup('user@example.com', 'User')
... | the_stack_v2_python_sparse | core/domain/question_domain_test.py | import-keshav/oppia | train | 4 |
570467c274b2d03c6f3dee82a79b7dd7c5c31759 | [
"if isinstance(event_data.values, list) and event_data.data_type in ('windows:registry:key_value', 'windows:registry:service'):\n values = []\n for name, data_type, data in sorted(event_data.values):\n if isinstance(data, bytes):\n byte_stream = base64.urlsafe_b64encode(data)\n da... | <|body_start_0|>
if isinstance(event_data.values, list) and event_data.data_type in ('windows:registry:key_value', 'windows:registry:service'):
values = []
for name, data_type, data in sorted(event_data.values):
if isinstance(data, bytes):
byte_stream ... | JSON output module field formatting helper. | JSONFieldFormattingHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONFieldFormattingHelper:
"""JSON output module field formatting helper."""
def _FormatValues(self, output_mediator, event, event_data, event_data_stream):
"""Formats a values. Args: output_mediator (OutputMediator): mediates interactions between output modules and other components,... | stack_v2_sparse_classes_36k_train_001858 | 7,537 | permissive | [
{
"docstring": "Formats a values. Args: output_mediator (OutputMediator): mediates interactions between output modules and other components, such as storage and dfVFS. event (EventObject): event. event_data (EventData): event data. event_data_stream (EventDataStream): event data stream. Returns: list[dict[str, ... | 2 | null | Implement the Python class `JSONFieldFormattingHelper` described below.
Class description:
JSON output module field formatting helper.
Method signatures and docstrings:
- def _FormatValues(self, output_mediator, event, event_data, event_data_stream): Formats a values. Args: output_mediator (OutputMediator): mediates ... | Implement the Python class `JSONFieldFormattingHelper` described below.
Class description:
JSON output module field formatting helper.
Method signatures and docstrings:
- def _FormatValues(self, output_mediator, event, event_data, event_data_stream): Formats a values. Args: output_mediator (OutputMediator): mediates ... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class JSONFieldFormattingHelper:
"""JSON output module field formatting helper."""
def _FormatValues(self, output_mediator, event, event_data, event_data_stream):
"""Formats a values. Args: output_mediator (OutputMediator): mediates interactions between output modules and other components,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONFieldFormattingHelper:
"""JSON output module field formatting helper."""
def _FormatValues(self, output_mediator, event, event_data, event_data_stream):
"""Formats a values. Args: output_mediator (OutputMediator): mediates interactions between output modules and other components, such as stor... | the_stack_v2_python_sparse | plaso/output/shared_json.py | log2timeline/plaso | train | 1,506 |
3b6dc827ac0d21d3013b82b46121a4ee3c1fb239 | [
"handler = logging.FileHandler(filename)\nhandler.setFormatter(logging.Formatter(output_format))\nlogger = logging.getLogger(loggername)\nlogger.setLevel(level)\nlogger.addHandler(handler)\nreturn logger",
"data = json.load(open('crypto_tulips/config/logger_setting.json'))\nif level == LoggingLevel.DEBUG:\n lo... | <|body_start_0|>
handler = logging.FileHandler(filename)
handler.setFormatter(logging.Formatter(output_format))
logger = logging.getLogger(loggername)
logger.setLevel(level)
logger.addHandler(handler)
return logger
<|end_body_0|>
<|body_start_1|>
data = json.load... | The Logger Class that has static methods to help with different logging | Logger | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Logger:
"""The Logger Class that has static methods to help with different logging"""
def generate_logger(level, filename, output_format, loggername):
"""Generates and returns the logger object Keyword arugments: level -- Type of Logging Level filename -- The file that the logged mes... | stack_v2_sparse_classes_36k_train_001859 | 4,339 | no_license | [
{
"docstring": "Generates and returns the logger object Keyword arugments: level -- Type of Logging Level filename -- The file that the logged messages will be saved to output_format -- The format the data will be logged in loggername -- the logger id name Returns: logger -- the logger object so the log functio... | 3 | null | Implement the Python class `Logger` described below.
Class description:
The Logger Class that has static methods to help with different logging
Method signatures and docstrings:
- def generate_logger(level, filename, output_format, loggername): Generates and returns the logger object Keyword arugments: level -- Type ... | Implement the Python class `Logger` described below.
Class description:
The Logger Class that has static methods to help with different logging
Method signatures and docstrings:
- def generate_logger(level, filename, output_format, loggername): Generates and returns the logger object Keyword arugments: level -- Type ... | b0f168293dbb06bf0d95935de2b3b3b86f07069f | <|skeleton|>
class Logger:
"""The Logger Class that has static methods to help with different logging"""
def generate_logger(level, filename, output_format, loggername):
"""Generates and returns the logger object Keyword arugments: level -- Type of Logging Level filename -- The file that the logged mes... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Logger:
"""The Logger Class that has static methods to help with different logging"""
def generate_logger(level, filename, output_format, loggername):
"""Generates and returns the logger object Keyword arugments: level -- Type of Logging Level filename -- The file that the logged messages will be... | the_stack_v2_python_sparse | crypto_tulips/logger/crypt_logger.py | StevenJohnston/py-crypto-tulips | train | 0 |
a09e42d3aa5b1a4c5c364fc1c7004a80c9f86acf | [
"if isinstance(paths, six.string_types):\n self._paths = [paths]\nelse:\n self._paths = paths",
"event_files = []\nfor path in paths:\n dirs = tf.gfile.Glob(path)\n dirs = filter(lambda x: tf.gfile.IsDirectory(x), dirs)\n for dir in dirs:\n if recursive:\n dir_files_pair = [(root,... | <|body_start_0|>
if isinstance(paths, six.string_types):
self._paths = [paths]
else:
self._paths = paths
<|end_body_0|>
<|body_start_1|>
event_files = []
for path in paths:
dirs = tf.gfile.Glob(path)
dirs = filter(lambda x: tf.gfile.IsDire... | Represents TensorFlow summary events from files under specified directories. | Summary | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Summary:
"""Represents TensorFlow summary events from files under specified directories."""
def __init__(self, paths):
"""Initializes an instance of a Summary. Args: path: a path or a list of paths to directories which hold TensorFlow events files. Can be local path or GCS paths. Wil... | stack_v2_sparse_classes_36k_train_001860 | 5,983 | permissive | [
{
"docstring": "Initializes an instance of a Summary. Args: path: a path or a list of paths to directories which hold TensorFlow events files. Can be local path or GCS paths. Wild cards allowed.",
"name": "__init__",
"signature": "def __init__(self, paths)"
},
{
"docstring": "Find all tf events ... | 5 | stack_v2_sparse_classes_30k_train_019173 | Implement the Python class `Summary` described below.
Class description:
Represents TensorFlow summary events from files under specified directories.
Method signatures and docstrings:
- def __init__(self, paths): Initializes an instance of a Summary. Args: path: a path or a list of paths to directories which hold Ten... | Implement the Python class `Summary` described below.
Class description:
Represents TensorFlow summary events from files under specified directories.
Method signatures and docstrings:
- def __init__(self, paths): Initializes an instance of a Summary. Args: path: a path or a list of paths to directories which hold Ten... | 8bf007da3e43096aa3a3dca158fc56b286ba6f5c | <|skeleton|>
class Summary:
"""Represents TensorFlow summary events from files under specified directories."""
def __init__(self, paths):
"""Initializes an instance of a Summary. Args: path: a path or a list of paths to directories which hold TensorFlow events files. Can be local path or GCS paths. Wil... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Summary:
"""Represents TensorFlow summary events from files under specified directories."""
def __init__(self, paths):
"""Initializes an instance of a Summary. Args: path: a path or a list of paths to directories which hold TensorFlow events files. Can be local path or GCS paths. Wild cards allow... | the_stack_v2_python_sparse | google/datalab/ml/_summary.py | googledatalab/pydatalab | train | 200 |
a8b07d767c6a6536dfa0ffc4a1aeac856bcd547f | [
"super(EmCgwshUniRouteMerge, self).__init__()\nsuper(EmCgwshServiceFlavor, self).__init__()\nself.service = GlobalModule.SERVICE_CGWSH_UNI_ROUTE\nself.order_type = GlobalModule.ORDER_MERGE\nself._xml_ns = '{%s}' % GlobalModule.EM_NAME_SPACES[self.service]\nself._scenario_name = 'CgwshUniRouteMerge'",
"xml_elm = e... | <|body_start_0|>
super(EmCgwshUniRouteMerge, self).__init__()
super(EmCgwshServiceFlavor, self).__init__()
self.service = GlobalModule.SERVICE_CGWSH_UNI_ROUTE
self.order_type = GlobalModule.ORDER_MERGE
self._xml_ns = '{%s}' % GlobalModule.EM_NAME_SPACES[self.service]
self... | Class for adding Cgwsh servive UNI static route. | EmCgwshUniRouteMerge | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmCgwshUniRouteMerge:
"""Class for adding Cgwsh servive UNI static route."""
def __init__(self):
"""Constructor"""
<|body_0|>
def _creating_json(self, device_message):
"""EC message(XML) divided into that for device is converted to JSON. Parameter: device_message... | stack_v2_sparse_classes_36k_train_001861 | 1,731 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "EC message(XML) divided into that for device is converted to JSON. Parameter: device_message: message for ech device Return value: device_json_message: JSON message",
"name": "_creating_jso... | 2 | null | Implement the Python class `EmCgwshUniRouteMerge` described below.
Class description:
Class for adding Cgwsh servive UNI static route.
Method signatures and docstrings:
- def __init__(self): Constructor
- def _creating_json(self, device_message): EC message(XML) divided into that for device is converted to JSON. Para... | Implement the Python class `EmCgwshUniRouteMerge` described below.
Class description:
Class for adding Cgwsh servive UNI static route.
Method signatures and docstrings:
- def __init__(self): Constructor
- def _creating_json(self, device_message): EC message(XML) divided into that for device is converted to JSON. Para... | e550d1b5ec9419f1fb3eb6e058ce46b57c92ee2f | <|skeleton|>
class EmCgwshUniRouteMerge:
"""Class for adding Cgwsh servive UNI static route."""
def __init__(self):
"""Constructor"""
<|body_0|>
def _creating_json(self, device_message):
"""EC message(XML) divided into that for device is converted to JSON. Parameter: device_message... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmCgwshUniRouteMerge:
"""Class for adding Cgwsh servive UNI static route."""
def __init__(self):
"""Constructor"""
super(EmCgwshUniRouteMerge, self).__init__()
super(EmCgwshServiceFlavor, self).__init__()
self.service = GlobalModule.SERVICE_CGWSH_UNI_ROUTE
self.ord... | the_stack_v2_python_sparse | lib/Scenario/CGW-SH/EmCgwshUniRouteMerge.py | lixiaochun/element-manager | train | 0 |
6851df1936dfa6ca1718231b09f74df8edd44c82 | [
"self.images = np.array(images).astype(np.float32)\nif labels is not None:\n self.labels = np.array(labels).astype(np.int32)\n self.n_labels = len(np.unique(labels))\nelse:\n self.labels = None\nself.num_examples = len(self.images)",
"current_permutation = np.random.permutation(range(len(self.images)))\n... | <|body_start_0|>
self.images = np.array(images).astype(np.float32)
if labels is not None:
self.labels = np.array(labels).astype(np.int32)
self.n_labels = len(np.unique(labels))
else:
self.labels = None
self.num_examples = len(self.images)
<|end_body_0|... | Utility class for batching data and handling multiple splits. Attributes ---------- current_batch_idx : int Description images : np.ndarray Xs of the dataset. Not necessarily images. labels : np.ndarray ys of the dataset. n_labels : int Number of possible labels num_examples : int Number of total observations | DatasetSplit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatasetSplit:
"""Utility class for batching data and handling multiple splits. Attributes ---------- current_batch_idx : int Description images : np.ndarray Xs of the dataset. Not necessarily images. labels : np.ndarray ys of the dataset. n_labels : int Number of possible labels num_examples : in... | stack_v2_sparse_classes_36k_train_001862 | 6,886 | no_license | [
{
"docstring": "Initialize a DatasetSplit object. Parameters ---------- images : np.ndarray Xs/inputs labels : np.ndarray ys/outputs",
"name": "__init__",
"signature": "def __init__(self, images, labels)"
},
{
"docstring": "Batch generator with randomization. Parameters ---------- batch_size : i... | 2 | stack_v2_sparse_classes_30k_train_012071 | Implement the Python class `DatasetSplit` described below.
Class description:
Utility class for batching data and handling multiple splits. Attributes ---------- current_batch_idx : int Description images : np.ndarray Xs of the dataset. Not necessarily images. labels : np.ndarray ys of the dataset. n_labels : int Numb... | Implement the Python class `DatasetSplit` described below.
Class description:
Utility class for batching data and handling multiple splits. Attributes ---------- current_batch_idx : int Description images : np.ndarray Xs of the dataset. Not necessarily images. labels : np.ndarray ys of the dataset. n_labels : int Numb... | 431e991e8e61f741f5b6739619ab2379301091e2 | <|skeleton|>
class DatasetSplit:
"""Utility class for batching data and handling multiple splits. Attributes ---------- current_batch_idx : int Description images : np.ndarray Xs of the dataset. Not necessarily images. labels : np.ndarray ys of the dataset. n_labels : int Number of possible labels num_examples : in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatasetSplit:
"""Utility class for batching data and handling multiple splits. Attributes ---------- current_batch_idx : int Description images : np.ndarray Xs of the dataset. Not necessarily images. labels : np.ndarray ys of the dataset. n_labels : int Number of possible labels num_examples : int Number of t... | the_stack_v2_python_sparse | Submission/VAE-model/libs/dataset_utils.py | parijitkedia/ETH_CIL_Cosmology_VAE_CNN | train | 0 |
4de260c1ed7876014a08e354a78ffa139202e792 | [
"E2ETransformer.add_arguments(parser)\nE2E.add_conformer_arguments(parser)\nreturn parser",
"group = parser.add_argument_group('conformer model specific setting')\ngroup = add_arguments_conformer_common(group)\nreturn parser",
"super().__init__(idim, odim, args, ignore_id)\nif args.transformer_attn_dropout_rate... | <|body_start_0|>
E2ETransformer.add_arguments(parser)
E2E.add_conformer_arguments(parser)
return parser
<|end_body_0|>
<|body_start_1|>
group = parser.add_argument_group('conformer model specific setting')
group = add_arguments_conformer_common(group)
return parser
<|end... | E2E module. :param int idim: dimension of inputs :param int odim: dimension of outputs :param Namespace args: argument Namespace containing options | E2E | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class E2E:
"""E2E module. :param int idim: dimension of inputs :param int odim: dimension of outputs :param Namespace args: argument Namespace containing options"""
def add_arguments(parser):
"""Add arguments."""
<|body_0|>
def add_conformer_arguments(parser):
"""Add a... | stack_v2_sparse_classes_36k_train_001863 | 2,955 | permissive | [
{
"docstring": "Add arguments.",
"name": "add_arguments",
"signature": "def add_arguments(parser)"
},
{
"docstring": "Add arguments for conformer model.",
"name": "add_conformer_arguments",
"signature": "def add_conformer_arguments(parser)"
},
{
"docstring": "Construct an E2E obj... | 3 | stack_v2_sparse_classes_30k_test_000351 | Implement the Python class `E2E` described below.
Class description:
E2E module. :param int idim: dimension of inputs :param int odim: dimension of outputs :param Namespace args: argument Namespace containing options
Method signatures and docstrings:
- def add_arguments(parser): Add arguments.
- def add_conformer_arg... | Implement the Python class `E2E` described below.
Class description:
E2E module. :param int idim: dimension of inputs :param int odim: dimension of outputs :param Namespace args: argument Namespace containing options
Method signatures and docstrings:
- def add_arguments(parser): Add arguments.
- def add_conformer_arg... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class E2E:
"""E2E module. :param int idim: dimension of inputs :param int odim: dimension of outputs :param Namespace args: argument Namespace containing options"""
def add_arguments(parser):
"""Add arguments."""
<|body_0|>
def add_conformer_arguments(parser):
"""Add a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class E2E:
"""E2E module. :param int idim: dimension of inputs :param int odim: dimension of outputs :param Namespace args: argument Namespace containing options"""
def add_arguments(parser):
"""Add arguments."""
E2ETransformer.add_arguments(parser)
E2E.add_conformer_arguments(parser)
... | the_stack_v2_python_sparse | espnet/nets/pytorch_backend/e2e_asr_conformer.py | espnet/espnet | train | 7,242 |
3fb00a21f97f646ba4ab320e994df23835338d57 | [
"self.rects = rects\nself.rands = []\ntotal_area = 0\nfor i in range(len(rects)):\n total_area += (rects[i][2] - rects[i][0] + 1) * (rects[i][3] - rects[i][1] + 1)\n self.rands.append(total_area)",
"rand_area = randint(0, self.rands[-1] - 1)\nrect = self.rects[bisect.bisect_right(self.rands, rand_area)]\nra... | <|body_start_0|>
self.rects = rects
self.rands = []
total_area = 0
for i in range(len(rects)):
total_area += (rects[i][2] - rects[i][0] + 1) * (rects[i][3] - rects[i][1] + 1)
self.rands.append(total_area)
<|end_body_0|>
<|body_start_1|>
rand_area = randin... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.rects = rects
self.rands = []
total_area = 0
for i i... | stack_v2_sparse_classes_36k_train_001864 | 2,656 | no_license | [
{
"docstring": ":type rects: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, rects)"
},
{
"docstring": ":rtype: List[int]",
"name": "pick",
"signature": "def pick(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int]
<|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: ... | 8595b04cf5a024c2cd8a97f750d890a818568401 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
self.rects = rects
self.rands = []
total_area = 0
for i in range(len(rects)):
total_area += (rects[i][2] - rects[i][0] + 1) * (rects[i][3] - rects[i][1] + 1)
self.rands.appen... | the_stack_v2_python_sparse | python/497.random-point-in-non-overlapping-rectangles.py | tainenko/Leetcode2019 | train | 5 | |
dd2546313d4a79311c0115b1d873bac1821667c7 | [
"tmp = []\nwhile head:\n tmp.append(head.val)\n head = head.next\ni, j = (0, len(tmp) - 1)\nwhile i <= j:\n if tmp[i] == tmp[j]:\n i += 1\n j -= 1\n else:\n return False\nreturn True",
"nod1, nod2 = (head, head)\nwhile nod2.next and nod2.next.next:\n nod1 = nod1.next\n nod2 ... | <|body_start_0|>
tmp = []
while head:
tmp.append(head.val)
head = head.next
i, j = (0, len(tmp) - 1)
while i <= j:
if tmp[i] == tmp[j]:
i += 1
j -= 1
else:
return False
return True
<|e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""先遍历全都放到数组里判断 时间复杂度：O(n) 空间复杂度：O(n) 用了额外数组 :param head: :return:"""
<|body_0|>
def isPalindrome2(self, head: ListNode) -> bool:
"""先用快慢指针找到中点，然后反转后面的链表，最后再与原链表进行比较 :param head: :return:"""
<|body_1|>... | stack_v2_sparse_classes_36k_train_001865 | 1,780 | no_license | [
{
"docstring": "先遍历全都放到数组里判断 时间复杂度：O(n) 空间复杂度：O(n) 用了额外数组 :param head: :return:",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head: ListNode) -> bool"
},
{
"docstring": "先用快慢指针找到中点，然后反转后面的链表，最后再与原链表进行比较 :param head: :return:",
"name": "isPalindrome2",
"signature": "def i... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: ListNode) -> bool: 先遍历全都放到数组里判断 时间复杂度：O(n) 空间复杂度：O(n) 用了额外数组 :param head: :return:
- def isPalindrome2(self, head: ListNode) -> bool: 先用快慢指针找到中点，然后反转... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: ListNode) -> bool: 先遍历全都放到数组里判断 时间复杂度：O(n) 空间复杂度：O(n) 用了额外数组 :param head: :return:
- def isPalindrome2(self, head: ListNode) -> bool: 先用快慢指针找到中点，然后反转... | 578cacff5851c5c2522981693c34e3c318002d30 | <|skeleton|>
class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""先遍历全都放到数组里判断 时间复杂度：O(n) 空间复杂度：O(n) 用了额外数组 :param head: :return:"""
<|body_0|>
def isPalindrome2(self, head: ListNode) -> bool:
"""先用快慢指针找到中点，然后反转后面的链表，最后再与原链表进行比较 :param head: :return:"""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, head: ListNode) -> bool:
"""先遍历全都放到数组里判断 时间复杂度：O(n) 空间复杂度：O(n) 用了额外数组 :param head: :return:"""
tmp = []
while head:
tmp.append(head.val)
head = head.next
i, j = (0, len(tmp) - 1)
while i <= j:
if tmp[i... | the_stack_v2_python_sparse | 回文链表.py | cjrzs/MyLeetCode | train | 8 | |
b32971aa817e7716fadef1467c16697b7dcbb8d1 | [
"cnp = self.cleaned_data.get('cnp')\nqs = User.objects.filter(cnp=cnp)\nif qs.exists():\n raise forms.ValidationError('cnp is taken')\nif CNP.validation(cnp) != 'Good CNP':\n raise forms.ValidationError('cnp is not corect')\nreturn cnp",
"email = self.cleaned_data.get('email')\nqs = User.objects.filter(emai... | <|body_start_0|>
cnp = self.cleaned_data.get('cnp')
qs = User.objects.filter(cnp=cnp)
if qs.exists():
raise forms.ValidationError('cnp is taken')
if CNP.validation(cnp) != 'Good CNP':
raise forms.ValidationError('cnp is not corect')
return cnp
<|end_body_0... | UserUpdateForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserUpdateForm:
def clean_cnp(self) -> str:
"""Verifies the availability and validity of the CNP"""
<|body_0|>
def clean_email(self) -> str:
"""Verify email is available."""
<|body_1|>
def clean_username(self) -> str:
"""Verifies the username is ... | stack_v2_sparse_classes_36k_train_001866 | 7,415 | permissive | [
{
"docstring": "Verifies the availability and validity of the CNP",
"name": "clean_cnp",
"signature": "def clean_cnp(self) -> str"
},
{
"docstring": "Verify email is available.",
"name": "clean_email",
"signature": "def clean_email(self) -> str"
},
{
"docstring": "Verifies the us... | 4 | stack_v2_sparse_classes_30k_train_010348 | Implement the Python class `UserUpdateForm` described below.
Class description:
Implement the UserUpdateForm class.
Method signatures and docstrings:
- def clean_cnp(self) -> str: Verifies the availability and validity of the CNP
- def clean_email(self) -> str: Verify email is available.
- def clean_username(self) ->... | Implement the Python class `UserUpdateForm` described below.
Class description:
Implement the UserUpdateForm class.
Method signatures and docstrings:
- def clean_cnp(self) -> str: Verifies the availability and validity of the CNP
- def clean_email(self) -> str: Verify email is available.
- def clean_username(self) ->... | 7f7cde94939f02f13df5afa865cddc72981481e2 | <|skeleton|>
class UserUpdateForm:
def clean_cnp(self) -> str:
"""Verifies the availability and validity of the CNP"""
<|body_0|>
def clean_email(self) -> str:
"""Verify email is available."""
<|body_1|>
def clean_username(self) -> str:
"""Verifies the username is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserUpdateForm:
def clean_cnp(self) -> str:
"""Verifies the availability and validity of the CNP"""
cnp = self.cleaned_data.get('cnp')
qs = User.objects.filter(cnp=cnp)
if qs.exists():
raise forms.ValidationError('cnp is taken')
if CNP.validation(cnp) != 'Go... | the_stack_v2_python_sparse | CustomUsers/forms.py | PopaGabriel/Food-Ecommerce-Site | train | 1 | |
ba095f8d49006181f7700d1b4b4db7099af1f932 | [
"context = super(NewUserView, self).get_context_data(**kwargs)\nif 'user_is_active' in self.request.session:\n context['user_is_active'] = self.request.session['user_is_active']\nif 'user_is_none' in self.request.session:\n context['user_is_none'] = self.request.session['user_is_none']\nreturn context",
"ne... | <|body_start_0|>
context = super(NewUserView, self).get_context_data(**kwargs)
if 'user_is_active' in self.request.session:
context['user_is_active'] = self.request.session['user_is_active']
if 'user_is_none' in self.request.session:
context['user_is_none'] = self.request... | Base generic view for user login or registration. | NewUserView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewUserView:
"""Base generic view for user login or registration."""
def get_context_data(self, **kwargs):
"""Method for get_context_date implementing from generic.DetailView class."""
<|body_0|>
def new_user_form_valid(self, form):
"""Method for new user registr... | stack_v2_sparse_classes_36k_train_001867 | 5,315 | permissive | [
{
"docstring": "Method for get_context_date implementing from generic.DetailView class.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "Method for new user registration.",
"name": "new_user_form_valid",
"signature": "def new_user_form_... | 3 | stack_v2_sparse_classes_30k_train_015241 | Implement the Python class `NewUserView` described below.
Class description:
Base generic view for user login or registration.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Method for get_context_date implementing from generic.DetailView class.
- def new_user_form_valid(self, form): Method... | Implement the Python class `NewUserView` described below.
Class description:
Base generic view for user login or registration.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Method for get_context_date implementing from generic.DetailView class.
- def new_user_form_valid(self, form): Method... | 5effabfaee8ff5d1294d1b4de576cde718cd24ae | <|skeleton|>
class NewUserView:
"""Base generic view for user login or registration."""
def get_context_data(self, **kwargs):
"""Method for get_context_date implementing from generic.DetailView class."""
<|body_0|>
def new_user_form_valid(self, form):
"""Method for new user registr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewUserView:
"""Base generic view for user login or registration."""
def get_context_data(self, **kwargs):
"""Method for get_context_date implementing from generic.DetailView class."""
context = super(NewUserView, self).get_context_data(**kwargs)
if 'user_is_active' in self.reques... | the_stack_v2_python_sparse | user_account/views.py | piemar1/Schedule_django | train | 0 |
7ada38ce3f9e547a2bbc91c707b9c16f68211b33 | [
"view = ElasticListAPIView()\nview.Meta.model = MagicMock()\nview.Meta.model.field_has_raw.return_value = False\nexpectation = {'query': {'match': {'param1': 'value1'}}}\nelasticfilter = ElasticFilter()\nqueryset = Search()\nresult = elasticfilter._add_query('param1', 'value1', view, queryset)\nself.assertTrue(view... | <|body_start_0|>
view = ElasticListAPIView()
view.Meta.model = MagicMock()
view.Meta.model.field_has_raw.return_value = False
expectation = {'query': {'match': {'param1': 'value1'}}}
elasticfilter = ElasticFilter()
queryset = Search()
result = elasticfilter._add_q... | Filter tests. | FilterTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterTests:
"""Filter tests."""
def test__add_query_no_raw(self):
"""Test proper handling of mapping without raw field."""
<|body_0|>
def test__add_query_with_raw(self):
"""Test proper handling of mapping with raw field."""
<|body_1|>
def test__coer... | stack_v2_sparse_classes_36k_train_001868 | 12,045 | permissive | [
{
"docstring": "Test proper handling of mapping without raw field.",
"name": "test__add_query_no_raw",
"signature": "def test__add_query_no_raw(self)"
},
{
"docstring": "Test proper handling of mapping with raw field.",
"name": "test__add_query_with_raw",
"signature": "def test__add_quer... | 6 | stack_v2_sparse_classes_30k_train_011281 | Implement the Python class `FilterTests` described below.
Class description:
Filter tests.
Method signatures and docstrings:
- def test__add_query_no_raw(self): Test proper handling of mapping without raw field.
- def test__add_query_with_raw(self): Test proper handling of mapping with raw field.
- def test__coerce_v... | Implement the Python class `FilterTests` described below.
Class description:
Filter tests.
Method signatures and docstrings:
- def test__add_query_no_raw(self): Test proper handling of mapping without raw field.
- def test__add_query_with_raw(self): Test proper handling of mapping with raw field.
- def test__coerce_v... | 73d334a9f0df7c044c06989977a9a22dd2ff9b7a | <|skeleton|>
class FilterTests:
"""Filter tests."""
def test__add_query_no_raw(self):
"""Test proper handling of mapping without raw field."""
<|body_0|>
def test__add_query_with_raw(self):
"""Test proper handling of mapping with raw field."""
<|body_1|>
def test__coer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FilterTests:
"""Filter tests."""
def test__add_query_no_raw(self):
"""Test proper handling of mapping without raw field."""
view = ElasticListAPIView()
view.Meta.model = MagicMock()
view.Meta.model.field_has_raw.return_value = False
expectation = {'query': {'match'... | the_stack_v2_python_sparse | goldstone/drfes/tests.py | bhuvan-rk/goldstone-server | train | 0 |
575be922c01f426a914e348146a7ef462b34d296 | [
"super(SanMenNoFengDealer, self).__init__()\nself.__card_colors = [MTile.TILE_WAN, MTile.TILE_TONG, MTile.TILE_TIAO]\nself.__card_count = len(self.__card_colors)\nself.setCardTiles(MTile.getTiles(self.__card_colors))\nftlog.debug(self.cardTiles)",
"for color in self.__card_colors:\n random.shuffle(self.cardTil... | <|body_start_0|>
super(SanMenNoFengDealer, self).__init__()
self.__card_colors = [MTile.TILE_WAN, MTile.TILE_TONG, MTile.TILE_TIAO]
self.__card_count = len(self.__card_colors)
self.setCardTiles(MTile.getTiles(self.__card_colors))
ftlog.debug(self.cardTiles)
<|end_body_0|>
<|body... | SanMenNoFengDealer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SanMenNoFengDealer:
def __init__(self):
"""初始化 子类在自己的初始化方法里，初始化麻将牌池范围，准备发牌 四川玩法，只有三门，没有风"""
<|body_0|>
def shuffle(self, goodPointCount, cardCountPerHand):
"""参数说明 goodPointCount : 好牌点的人数 cardCountPerHand ： 每手牌的麻将牌张数"""
<|body_1|>
def getGoodCard(self, c... | stack_v2_sparse_classes_36k_train_001869 | 3,073 | no_license | [
{
"docstring": "初始化 子类在自己的初始化方法里，初始化麻将牌池范围，准备发牌 四川玩法，只有三门，没有风",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "参数说明 goodPointCount : 好牌点的人数 cardCountPerHand ： 每手牌的麻将牌张数",
"name": "shuffle",
"signature": "def shuffle(self, goodPointCount, cardCountPerHand)"
},
... | 4 | null | Implement the Python class `SanMenNoFengDealer` described below.
Class description:
Implement the SanMenNoFengDealer class.
Method signatures and docstrings:
- def __init__(self): 初始化 子类在自己的初始化方法里，初始化麻将牌池范围，准备发牌 四川玩法，只有三门，没有风
- def shuffle(self, goodPointCount, cardCountPerHand): 参数说明 goodPointCount : 好牌点的人数 cardCoun... | Implement the Python class `SanMenNoFengDealer` described below.
Class description:
Implement the SanMenNoFengDealer class.
Method signatures and docstrings:
- def __init__(self): 初始化 子类在自己的初始化方法里，初始化麻将牌池范围，准备发牌 四川玩法，只有三门，没有风
- def shuffle(self, goodPointCount, cardCountPerHand): 参数说明 goodPointCount : 好牌点的人数 cardCoun... | b5b08a85d49c3bed460255a62dc5201b998d88d4 | <|skeleton|>
class SanMenNoFengDealer:
def __init__(self):
"""初始化 子类在自己的初始化方法里，初始化麻将牌池范围，准备发牌 四川玩法，只有三门，没有风"""
<|body_0|>
def shuffle(self, goodPointCount, cardCountPerHand):
"""参数说明 goodPointCount : 好牌点的人数 cardCountPerHand ： 每手牌的麻将牌张数"""
<|body_1|>
def getGoodCard(self, c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SanMenNoFengDealer:
def __init__(self):
"""初始化 子类在自己的初始化方法里，初始化麻将牌池范围，准备发牌 四川玩法，只有三门，没有风"""
super(SanMenNoFengDealer, self).__init__()
self.__card_colors = [MTile.TILE_WAN, MTile.TILE_TONG, MTile.TILE_TIAO]
self.__card_count = len(self.__card_colors)
self.setCardTiles(M... | the_stack_v2_python_sparse | majiang2/src/majiang2/dealer/dealer_sanmen_nofeng.py | cnbcloud/mjserver | train | 1 | |
18515dc63d418c56d9edbc4931ab80fe02984372 | [
"if is_zip(path):\n hosts, services, vulns, notes = (Pdict(), Pdict(), Pdict(), Pdict())\n with ZipFile(path) as fzip:\n for ftmp in [fname for fname in fzip.namelist() if re.match(cls.ARCHIVE_PATHS, fname)]:\n thosts, tservices, tvulns, tnotes = NmapParser._parse_data(file_from_zip(path, ft... | <|body_start_0|>
if is_zip(path):
hosts, services, vulns, notes = (Pdict(), Pdict(), Pdict(), Pdict())
with ZipFile(path) as fzip:
for ftmp in [fname for fname in fzip.namelist() if re.match(cls.ARCHIVE_PATHS, fname)]:
thosts, tservices, tvulns, tnotes... | nmap xml output parser | NmapParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NmapParser:
"""nmap xml output parser"""
def parse_path(cls, path):
"""parse data from path"""
<|body_0|>
def _parse_data(data):
"""parse raw string data"""
<|body_1|>
def _parse_hosts(report):
"""parse hosts"""
<|body_2|>
def _p... | stack_v2_sparse_classes_36k_train_001870 | 4,535 | permissive | [
{
"docstring": "parse data from path",
"name": "parse_path",
"signature": "def parse_path(cls, path)"
},
{
"docstring": "parse raw string data",
"name": "_parse_data",
"signature": "def _parse_data(data)"
},
{
"docstring": "parse hosts",
"name": "_parse_hosts",
"signature... | 5 | stack_v2_sparse_classes_30k_train_003391 | Implement the Python class `NmapParser` described below.
Class description:
nmap xml output parser
Method signatures and docstrings:
- def parse_path(cls, path): parse data from path
- def _parse_data(data): parse raw string data
- def _parse_hosts(report): parse hosts
- def _parse_services(report): parse services
- ... | Implement the Python class `NmapParser` described below.
Class description:
nmap xml output parser
Method signatures and docstrings:
- def parse_path(cls, path): parse data from path
- def _parse_data(data): parse raw string data
- def _parse_hosts(report): parse hosts
- def _parse_services(report): parse services
- ... | dc382da4fb60f2cfba69a4456a4fa430d6cb77ba | <|skeleton|>
class NmapParser:
"""nmap xml output parser"""
def parse_path(cls, path):
"""parse data from path"""
<|body_0|>
def _parse_data(data):
"""parse raw string data"""
<|body_1|>
def _parse_hosts(report):
"""parse hosts"""
<|body_2|>
def _p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NmapParser:
"""nmap xml output parser"""
def parse_path(cls, path):
"""parse data from path"""
if is_zip(path):
hosts, services, vulns, notes = (Pdict(), Pdict(), Pdict(), Pdict())
with ZipFile(path) as fzip:
for ftmp in [fname for fname in fzip.nam... | the_stack_v2_python_sparse | sner/server/parser/nmap.py | kovariktomas/sner4 | train | 0 |
4ecb8a240e7df6395d900f382e37fdcf3f608dcb | [
"form = super(AddAlbumView, self).get_form()\nform.fields['cover_photo'].queryset = self.request.user.profile.photos.all()\nform.fields['photos'].queryset = self.request.user.profile.photos.all()\nreturn form",
"self.object = form.save()\nself.object.owner = self.request.user.profile\nself.object.save()\nreturn H... | <|body_start_0|>
form = super(AddAlbumView, self).get_form()
form.fields['cover_photo'].queryset = self.request.user.profile.photos.all()
form.fields['photos'].queryset = self.request.user.profile.photos.all()
return form
<|end_body_0|>
<|body_start_1|>
self.object = form.save()... | Add a new album. | AddAlbumView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddAlbumView:
"""Add a new album."""
def get_form(self):
"""Retrieve form and customize some fields."""
<|body_0|>
def form_valid(self, form):
"""If form post is successful, set the object's owner."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_001871 | 6,669 | permissive | [
{
"docstring": "Retrieve form and customize some fields.",
"name": "get_form",
"signature": "def get_form(self)"
},
{
"docstring": "If form post is successful, set the object's owner.",
"name": "form_valid",
"signature": "def form_valid(self, form)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008943 | Implement the Python class `AddAlbumView` described below.
Class description:
Add a new album.
Method signatures and docstrings:
- def get_form(self): Retrieve form and customize some fields.
- def form_valid(self, form): If form post is successful, set the object's owner. | Implement the Python class `AddAlbumView` described below.
Class description:
Add a new album.
Method signatures and docstrings:
- def get_form(self): Retrieve form and customize some fields.
- def form_valid(self, form): If form post is successful, set the object's owner.
<|skeleton|>
class AddAlbumView:
"""Add... | ae0dd708fe29e9b2aec9125d649b06fc7b724e45 | <|skeleton|>
class AddAlbumView:
"""Add a new album."""
def get_form(self):
"""Retrieve form and customize some fields."""
<|body_0|>
def form_valid(self, form):
"""If form post is successful, set the object's owner."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddAlbumView:
"""Add a new album."""
def get_form(self):
"""Retrieve form and customize some fields."""
form = super(AddAlbumView, self).get_form()
form.fields['cover_photo'].queryset = self.request.user.profile.photos.all()
form.fields['photos'].queryset = self.request.us... | the_stack_v2_python_sparse | imagersite/imager_images/views.py | fordf/django-imager | train | 0 |
99788cb75b4f5ef4f4da740a7c66f487329af00d | [
"path_, savedir = os.path.split(saveloc)\nif path_ == '':\n path_ = '.'\nif not os.path.exists(path_):\n raise ValueError('\"{0}\" does not exist. \\nCannot create \"{1}\"'.format(path_, savedir))\nif not os.path.exists(saveloc):\n os.mkdir(saveloc)\nself.saveloc = saveloc\nself.model = model\nself._certai... | <|body_start_0|>
path_, savedir = os.path.split(saveloc)
if path_ == '':
path_ = '.'
if not os.path.exists(path_):
raise ValueError('"{0}" does not exist. \nCannot create "{1}"'.format(path_, savedir))
if not os.path.exists(saveloc):
os.mkdir(saveloc)
... | Create a class that contains functionality to load/save a model scenario | Scenario | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Scenario:
"""Create a class that contains functionality to load/save a model scenario"""
def __init__(self, saveloc, model=None):
"""Constructor for a Scenario object. It's main function is to either 'save' and model or to 'load' an already existing model. If a model is loaded from s... | stack_v2_sparse_classes_36k_train_001872 | 16,771 | no_license | [
{
"docstring": "Constructor for a Scenario object. It's main function is to either 'save' and model or to 'load' an already existing model. If a model is loaded from saveloc, the 'model' attribute will contain the re-created model object. 'saveloc' is given as /path_to_save_directory/save_directory if /path_to_... | 6 | null | Implement the Python class `Scenario` described below.
Class description:
Create a class that contains functionality to load/save a model scenario
Method signatures and docstrings:
- def __init__(self, saveloc, model=None): Constructor for a Scenario object. It's main function is to either 'save' and model or to 'loa... | Implement the Python class `Scenario` described below.
Class description:
Create a class that contains functionality to load/save a model scenario
Method signatures and docstrings:
- def __init__(self, saveloc, model=None): Constructor for a Scenario object. It's main function is to either 'save' and model or to 'loa... | 81f0e73b50b83022bf8327e181a3799fa2d980c1 | <|skeleton|>
class Scenario:
"""Create a class that contains functionality to load/save a model scenario"""
def __init__(self, saveloc, model=None):
"""Constructor for a Scenario object. It's main function is to either 'save' and model or to 'load' an already existing model. If a model is loaded from s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Scenario:
"""Create a class that contains functionality to load/save a model scenario"""
def __init__(self, saveloc, model=None):
"""Constructor for a Scenario object. It's main function is to either 'save' and model or to 'load' an already existing model. If a model is loaded from saveloc, the '... | the_stack_v2_python_sparse | py_gnome/gnome/persist/scenario.py | kthyng/GNOME2 | train | 1 |
891f56b5c63b41812626f1a4c927af7165e88396 | [
"d.screen_on()\ntime.sleep(1)\nd.drag(0.5, 0.8, 0.5, 0.1)\ntime.sleep(2)\nfor i in range(4):\n d(resourceId='com.android.systemui:id/key7').click()",
"d.app_start('com.guodong.guodong')\ntime.sleep(2)\nd.set_fastinput_ime(True)\nd.clear_text()\nd(text='请输入手机号').set_text('18008062016')\ntime.sleep(2)\nd.click(0... | <|body_start_0|>
d.screen_on()
time.sleep(1)
d.drag(0.5, 0.8, 0.5, 0.1)
time.sleep(2)
for i in range(4):
d(resourceId='com.android.systemui:id/key7').click()
<|end_body_0|>
<|body_start_1|>
d.app_start('com.guodong.guodong')
time.sleep(2)
d.se... | LiveWaveTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LiveWaveTestCase:
def test_01(self):
"""打开手机"""
<|body_0|>
def test_02(self):
"""登录"""
<|body_1|>
def test_03(self):
"""首页"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
d.screen_on()
time.sleep(1)
d.drag(0.5, 0... | stack_v2_sparse_classes_36k_train_001873 | 2,310 | no_license | [
{
"docstring": "打开手机",
"name": "test_01",
"signature": "def test_01(self)"
},
{
"docstring": "登录",
"name": "test_02",
"signature": "def test_02(self)"
},
{
"docstring": "首页",
"name": "test_03",
"signature": "def test_03(self)"
}
] | 3 | stack_v2_sparse_classes_30k_train_003867 | Implement the Python class `LiveWaveTestCase` described below.
Class description:
Implement the LiveWaveTestCase class.
Method signatures and docstrings:
- def test_01(self): 打开手机
- def test_02(self): 登录
- def test_03(self): 首页 | Implement the Python class `LiveWaveTestCase` described below.
Class description:
Implement the LiveWaveTestCase class.
Method signatures and docstrings:
- def test_01(self): 打开手机
- def test_02(self): 登录
- def test_03(self): 首页
<|skeleton|>
class LiveWaveTestCase:
def test_01(self):
"""打开手机"""
<... | fe221e4187a26da9b5f93d5f68bf6ff64d581d73 | <|skeleton|>
class LiveWaveTestCase:
def test_01(self):
"""打开手机"""
<|body_0|>
def test_02(self):
"""登录"""
<|body_1|>
def test_03(self):
"""首页"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LiveWaveTestCase:
def test_01(self):
"""打开手机"""
d.screen_on()
time.sleep(1)
d.drag(0.5, 0.8, 0.5, 0.1)
time.sleep(2)
for i in range(4):
d(resourceId='com.android.systemui:id/key7').click()
def test_02(self):
"""登录"""
d.app_start(... | the_stack_v2_python_sparse | uiautomator2/LiveWave.py | quqiao/eshare | train | 0 | |
980e7804901a30bc37d9f3ff8fa6e30ab1f8211c | [
"self.data_format = data_format\nself.channel_axis = 1 if data_format == 'channels_first' else 3\nself.load_path = load_path",
"shortcut = x\nif expansion != 1:\n x = tf.layers.conv2d(x, input_filters * expansion, kernel_size=1, use_bias=False, padding='same', data_format=self.data_format)\n x = tf.layers.b... | <|body_start_0|>
self.data_format = data_format
self.channel_axis = 1 if data_format == 'channels_first' else 3
self.load_path = load_path
<|end_body_0|>
<|body_start_1|>
shortcut = x
if expansion != 1:
x = tf.layers.conv2d(x, input_filters * expansion, kernel_size=1... | Backbone of mobilenet v2. | MobileNetV2Backbone | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MobileNetV2Backbone:
"""Backbone of mobilenet v2."""
def __init__(self, load_path=None, data_format='channels_first'):
"""Construct MobileNetV2 class. :param load_path: path for saved model"""
<|body_0|>
def block(self, x, input_filters, output_filters, expansion, stride... | stack_v2_sparse_classes_36k_train_001874 | 3,285 | permissive | [
{
"docstring": "Construct MobileNetV2 class. :param load_path: path for saved model",
"name": "__init__",
"signature": "def __init__(self, load_path=None, data_format='channels_first')"
},
{
"docstring": "Mobilenetv2 block.",
"name": "block",
"signature": "def block(self, x, input_filter... | 4 | null | Implement the Python class `MobileNetV2Backbone` described below.
Class description:
Backbone of mobilenet v2.
Method signatures and docstrings:
- def __init__(self, load_path=None, data_format='channels_first'): Construct MobileNetV2 class. :param load_path: path for saved model
- def block(self, x, input_filters, o... | Implement the Python class `MobileNetV2Backbone` described below.
Class description:
Backbone of mobilenet v2.
Method signatures and docstrings:
- def __init__(self, load_path=None, data_format='channels_first'): Construct MobileNetV2 class. :param load_path: path for saved model
- def block(self, x, input_filters, o... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class MobileNetV2Backbone:
"""Backbone of mobilenet v2."""
def __init__(self, load_path=None, data_format='channels_first'):
"""Construct MobileNetV2 class. :param load_path: path for saved model"""
<|body_0|>
def block(self, x, input_filters, output_filters, expansion, stride... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MobileNetV2Backbone:
"""Backbone of mobilenet v2."""
def __init__(self, load_path=None, data_format='channels_first'):
"""Construct MobileNetV2 class. :param load_path: path for saved model"""
self.data_format = data_format
self.channel_axis = 1 if data_format == 'channels_first' ... | the_stack_v2_python_sparse | built-in/TensorFlow/Official/cv/image_classification/ResnetVariant_for_TensorFlow/automl/vega/search_space/networks/tensorflow/customs/adelaide_nn/mobilenetv2_backbone.py | Huawei-Ascend/modelzoo | train | 1 |
3372b3a9694e8b64f8b2b6d5e411dd76e992a929 | [
"if id is not None:\n self.id = id\nelse:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects",
"if list_dictionaries is not None or []:\n return json.dumps(list_dictionaries)\nelse:\n return '[]'",
"filename = cls.__name__ + '.json'\nelements = []\nif list_objs is not None:\n for el in lis... | <|body_start_0|>
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is not None or []:
return json.dumps(list_dictionaries)
else:
return... | private class attribute __nb_objects = 0 class constructor: def __init__(self, id=None):: | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""private class attribute __nb_objects = 0 class constructor: def __init__(self, id=None)::"""
def __init__(self, id=None):
"""constructor"""
<|body_0|>
def to_json_string(list_dictionaries):
"""Returns a json string"""
<|body_1|>
def save_to_... | stack_v2_sparse_classes_36k_train_001875 | 2,507 | no_license | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "Returns a json string",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "filename, contains class name + .json extensio... | 6 | stack_v2_sparse_classes_30k_train_003503 | Implement the Python class `Base` described below.
Class description:
private class attribute __nb_objects = 0 class constructor: def __init__(self, id=None)::
Method signatures and docstrings:
- def __init__(self, id=None): constructor
- def to_json_string(list_dictionaries): Returns a json string
- def save_to_file... | Implement the Python class `Base` described below.
Class description:
private class attribute __nb_objects = 0 class constructor: def __init__(self, id=None)::
Method signatures and docstrings:
- def __init__(self, id=None): constructor
- def to_json_string(list_dictionaries): Returns a json string
- def save_to_file... | 83b0c509580d2ef0daf0e5be2a597a9bd39f2f26 | <|skeleton|>
class Base:
"""private class attribute __nb_objects = 0 class constructor: def __init__(self, id=None)::"""
def __init__(self, id=None):
"""constructor"""
<|body_0|>
def to_json_string(list_dictionaries):
"""Returns a json string"""
<|body_1|>
def save_to_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base:
"""private class attribute __nb_objects = 0 class constructor: def __init__(self, id=None)::"""
def __init__(self, id=None):
"""constructor"""
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
de... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | sandovbarr/holbertonschool-higher_level_programming | train | 0 |
466ce09f4213dd5a6caa416605f696f5679d1a71 | [
"self.user = username\nself.address = server_address\nself.dest_path = dest_path\nself.comp_filename = comp_filename\nself.zip_path = zip_path\nself.send_cmd = 'scp %s %s@%s:%s' % (self.comp_filename, self.user, self.address, self.dest_path)\nself.copy_cmd = 'cp -R %s/%s %s' % (self.zip_path, self.comp_filename, se... | <|body_start_0|>
self.user = username
self.address = server_address
self.dest_path = dest_path
self.comp_filename = comp_filename
self.zip_path = zip_path
self.send_cmd = 'scp %s %s@%s:%s' % (self.comp_filename, self.user, self.address, self.dest_path)
self.copy_c... | S2S (Send 2 Server) is designed for use with a public ssh key. | S2S | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S2S:
"""S2S (Send 2 Server) is designed for use with a public ssh key."""
def __init__(self, username=None, server_address=None, dest_path=None, remote=True, comp_filename='', zip_path=None, compressed=True, auto=False):
""":param username (string): Remote server username. :param ser... | stack_v2_sparse_classes_36k_train_001876 | 3,888 | no_license | [
{
"docstring": ":param username (string): Remote server username. :param server_address (string): Remote server address. :param dest_path (string): Remote server destination. :param comp_filename (string): This is the name of the compressed file that will be generated (eg 'test.zip') :param zip_path: This is th... | 5 | stack_v2_sparse_classes_30k_train_007713 | Implement the Python class `S2S` described below.
Class description:
S2S (Send 2 Server) is designed for use with a public ssh key.
Method signatures and docstrings:
- def __init__(self, username=None, server_address=None, dest_path=None, remote=True, comp_filename='', zip_path=None, compressed=True, auto=False): :pa... | Implement the Python class `S2S` described below.
Class description:
S2S (Send 2 Server) is designed for use with a public ssh key.
Method signatures and docstrings:
- def __init__(self, username=None, server_address=None, dest_path=None, remote=True, comp_filename='', zip_path=None, compressed=True, auto=False): :pa... | e207046ec36387751fe2bba8b6782fdc2a580107 | <|skeleton|>
class S2S:
"""S2S (Send 2 Server) is designed for use with a public ssh key."""
def __init__(self, username=None, server_address=None, dest_path=None, remote=True, comp_filename='', zip_path=None, compressed=True, auto=False):
""":param username (string): Remote server username. :param ser... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class S2S:
"""S2S (Send 2 Server) is designed for use with a public ssh key."""
def __init__(self, username=None, server_address=None, dest_path=None, remote=True, comp_filename='', zip_path=None, compressed=True, auto=False):
""":param username (string): Remote server username. :param server_address (... | the_stack_v2_python_sparse | OrthoEvol/Tools/send2server/s2s.py | datasnakes/OrthoEvolution | train | 19 |
edbc0a6dd17a9328f386a10ad5496d3c02ef4c38 | [
"sql = \" select s.student_id, pbc.full_name as student_name, s.up_station_id, s.off_station_id, s1.bus_station_name as up_station_name, s2.bus_station_name as off_station_name, aa.up_station_id as original_up_station_id, aa.off_station_id as original_off_station_id, s3.bus_station_name as original_up_station_na... | <|body_start_0|>
sql = " select s.student_id, pbc.full_name as student_name, s.up_station_id, s.off_station_id, s1.bus_station_name as up_station_name, s2.bus_station_name as off_station_name, aa.up_station_id as original_up_station_id, aa.off_station_id as original_off_station_id, s3.bus_station_name as ori... | StudentLineSeatLog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StudentLineSeatLog:
def query_sa_line_tooltips(self, login_user_id, create_dt):
"""获取有无学生调整线路 :param login_user_id :param create_dt :return:"""
<|body_0|>
def add_student_line_seat_log(self, student_obj, login_user_id, now_time):
"""插入一条学生座位日志 :return:"""
<|b... | stack_v2_sparse_classes_36k_train_001877 | 4,377 | no_license | [
{
"docstring": "获取有无学生调整线路 :param login_user_id :param create_dt :return:",
"name": "query_sa_line_tooltips",
"signature": "def query_sa_line_tooltips(self, login_user_id, create_dt)"
},
{
"docstring": "插入一条学生座位日志 :return:",
"name": "add_student_line_seat_log",
"signature": "def add_stud... | 2 | stack_v2_sparse_classes_30k_train_014949 | Implement the Python class `StudentLineSeatLog` described below.
Class description:
Implement the StudentLineSeatLog class.
Method signatures and docstrings:
- def query_sa_line_tooltips(self, login_user_id, create_dt): 获取有无学生调整线路 :param login_user_id :param create_dt :return:
- def add_student_line_seat_log(self, st... | Implement the Python class `StudentLineSeatLog` described below.
Class description:
Implement the StudentLineSeatLog class.
Method signatures and docstrings:
- def query_sa_line_tooltips(self, login_user_id, create_dt): 获取有无学生调整线路 :param login_user_id :param create_dt :return:
- def add_student_line_seat_log(self, st... | a7cf5a0b6daa372ed860dc43d92c55fcde764eb9 | <|skeleton|>
class StudentLineSeatLog:
def query_sa_line_tooltips(self, login_user_id, create_dt):
"""获取有无学生调整线路 :param login_user_id :param create_dt :return:"""
<|body_0|>
def add_student_line_seat_log(self, student_obj, login_user_id, now_time):
"""插入一条学生座位日志 :return:"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StudentLineSeatLog:
def query_sa_line_tooltips(self, login_user_id, create_dt):
"""获取有无学生调整线路 :param login_user_id :param create_dt :return:"""
sql = " select s.student_id, pbc.full_name as student_name, s.up_station_id, s.off_station_id, s1.bus_station_name as up_station_name, s2.bus_station... | the_stack_v2_python_sparse | python_project/smart_schoolBus_project/app/schoolbus_situation/models/student_line_seat_log_model.py | malqch/aibus | train | 0 | |
92038d1c9c73a6d572035f4fcee28ffa11cafb53 | [
"streamList = Stream.Stream.query.filter_by(id=streamID).all()\ndb.session.commit()\nreturn {'results': [ob.serialize() for ob in streamList]}",
"if 'X-API-KEY' in request.headers:\n requestAPIKey = apikey.apikey.query.filter_by(key=request.headers['X-API-KEY']).first()\n if requestAPIKey is not None:\n ... | <|body_start_0|>
streamList = Stream.Stream.query.filter_by(id=streamID).all()
db.session.commit()
return {'results': [ob.serialize() for ob in streamList]}
<|end_body_0|>
<|body_start_1|>
if 'X-API-KEY' in request.headers:
requestAPIKey = apikey.apikey.query.filter_by(key=r... | api_1_ListStream | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class api_1_ListStream:
def get(self, streamID):
"""Returns Info on a Single Active Streams"""
<|body_0|>
def put(self, streamID):
"""Change a Streams's Name or Topic"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
streamList = Stream.Stream.query.filter_... | stack_v2_sparse_classes_36k_train_001878 | 3,398 | permissive | [
{
"docstring": "Returns Info on a Single Active Streams",
"name": "get",
"signature": "def get(self, streamID)"
},
{
"docstring": "Change a Streams's Name or Topic",
"name": "put",
"signature": "def put(self, streamID)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001029 | Implement the Python class `api_1_ListStream` described below.
Class description:
Implement the api_1_ListStream class.
Method signatures and docstrings:
- def get(self, streamID): Returns Info on a Single Active Streams
- def put(self, streamID): Change a Streams's Name or Topic | Implement the Python class `api_1_ListStream` described below.
Class description:
Implement the api_1_ListStream class.
Method signatures and docstrings:
- def get(self, streamID): Returns Info on a Single Active Streams
- def put(self, streamID): Change a Streams's Name or Topic
<|skeleton|>
class api_1_ListStream:... | 9088c44616a2e94f6771216af6f22c241064e321 | <|skeleton|>
class api_1_ListStream:
def get(self, streamID):
"""Returns Info on a Single Active Streams"""
<|body_0|>
def put(self, streamID):
"""Change a Streams's Name or Topic"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class api_1_ListStream:
def get(self, streamID):
"""Returns Info on a Single Active Streams"""
streamList = Stream.Stream.query.filter_by(id=streamID).all()
db.session.commit()
return {'results': [ob.serialize() for ob in streamList]}
def put(self, streamID):
"""Change a... | the_stack_v2_python_sparse | blueprints/apis/stream_ns.py | codions-forks/flask-nginx-rtmp-manager | train | 1 | |
cf0a99d362c3982a82258fef1c7ad9b13fa50320 | [
"n = len(s)\nt = [None for i in range(n)]\nreturn self.word_break_aux(s, wordDict, n - 1, t)",
"if s[:i + 1] in wordDict:\n return True\nelif t[i] is not None:\n return t[i]\nelse:\n for j in range(i):\n if self.word_break_aux(s, wordDict, j, t) is True and s[j + 1:i + 1] in wordDict:\n ... | <|body_start_0|>
n = len(s)
t = [None for i in range(n)]
return self.word_break_aux(s, wordDict, n - 1, t)
<|end_body_0|>
<|body_start_1|>
if s[:i + 1] in wordDict:
return True
elif t[i] is not None:
return t[i]
else:
for j in range(i)... | Solution | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: Set[str] :rtype: bool"""
<|body_0|>
def word_break_aux(self, s, wordDict, i, t):
"""Determine if s[:i + 1] can be segmented by dict wordDict"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_001879 | 1,231 | permissive | [
{
"docstring": ":type s: str :type wordDict: Set[str] :rtype: bool",
"name": "wordBreak",
"signature": "def wordBreak(self, s, wordDict)"
},
{
"docstring": "Determine if s[:i + 1] can be segmented by dict wordDict",
"name": "word_break_aux",
"signature": "def word_break_aux(self, s, word... | 2 | stack_v2_sparse_classes_30k_train_015166 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: Set[str] :rtype: bool
- def word_break_aux(self, s, wordDict, i, t): Determine if s[:i + 1] can be segmented by dic... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: Set[str] :rtype: bool
- def word_break_aux(self, s, wordDict, i, t): Determine if s[:i + 1] can be segmented by dic... | 38acc65fa4315f86acb62874ca488620c5d77e17 | <|skeleton|>
class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: Set[str] :rtype: bool"""
<|body_0|>
def word_break_aux(self, s, wordDict, i, t):
"""Determine if s[:i + 1] can be segmented by dict wordDict"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: Set[str] :rtype: bool"""
n = len(s)
t = [None for i in range(n)]
return self.word_break_aux(s, wordDict, n - 1, t)
def word_break_aux(self, s, wordDict, i, t):
"""Determine if s[:i + 1] can... | the_stack_v2_python_sparse | word_break/solution2.py | mahimadubey/leetcode-python | train | 0 | |
60d4b3a8df552bebc24e6433a3652920e7cfdae5 | [
"response = self.get(reverse('api-user-list'), expected_code=200)\nself.assertEqual(len(response.data), User.objects.count())\nfor key in ['username', 'pk', 'email']:\n self.assertIn(key, response.data[0])\npk = response.data[0]['pk']\nresponse = self.get(reverse('api-user-detail', kwargs={'pk': pk}), expected_c... | <|body_start_0|>
response = self.get(reverse('api-user-list'), expected_code=200)
self.assertEqual(len(response.data), User.objects.count())
for key in ['username', 'pk', 'email']:
self.assertIn(key, response.data[0])
pk = response.data[0]['pk']
response = self.get(re... | Tests for user API endpoints | UserAPITests | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserAPITests:
"""Tests for user API endpoints"""
def test_user_api(self):
"""Tests for User API endpoints"""
<|body_0|>
def test_group_api(self):
"""Tests for the Group API endpoints"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
response = sel... | stack_v2_sparse_classes_36k_train_001880 | 1,498 | permissive | [
{
"docstring": "Tests for User API endpoints",
"name": "test_user_api",
"signature": "def test_user_api(self)"
},
{
"docstring": "Tests for the Group API endpoints",
"name": "test_group_api",
"signature": "def test_group_api(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021414 | Implement the Python class `UserAPITests` described below.
Class description:
Tests for user API endpoints
Method signatures and docstrings:
- def test_user_api(self): Tests for User API endpoints
- def test_group_api(self): Tests for the Group API endpoints | Implement the Python class `UserAPITests` described below.
Class description:
Tests for user API endpoints
Method signatures and docstrings:
- def test_user_api(self): Tests for User API endpoints
- def test_group_api(self): Tests for the Group API endpoints
<|skeleton|>
class UserAPITests:
"""Tests for user API... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class UserAPITests:
"""Tests for user API endpoints"""
def test_user_api(self):
"""Tests for User API endpoints"""
<|body_0|>
def test_group_api(self):
"""Tests for the Group API endpoints"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserAPITests:
"""Tests for user API endpoints"""
def test_user_api(self):
"""Tests for User API endpoints"""
response = self.get(reverse('api-user-list'), expected_code=200)
self.assertEqual(len(response.data), User.objects.count())
for key in ['username', 'pk', 'email']:
... | the_stack_v2_python_sparse | InvenTree/users/test_api.py | inventree/InvenTree | train | 3,077 |
0e8cc52db41cde801e0436c78f04692eeae707b0 | [
"if len(prices) <= 1:\n return 0\nmaxPro = 0\nminPrice = prices[0]\nfor i in range(1, len(prices)):\n maxPro = max(maxPro, prices[i] - minPrice)\n minPrice = min(minPrice, prices[i])\nreturn maxPro",
"minPirce = prices[0]\nmaxPro = 0\nlength = len(prices)\nfor i in range(1, length):\n if prices[i] < m... | <|body_start_0|>
if len(prices) <= 1:
return 0
maxPro = 0
minPrice = prices[0]
for i in range(1, len(prices)):
maxPro = max(maxPro, prices[i] - minPrice)
minPrice = min(minPrice, prices[i])
return maxPro
<|end_body_0|>
<|body_start_1|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int 动态规划"""
<|body_0|>
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int 非动态规划"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(prices) <= 1:
... | stack_v2_sparse_classes_36k_train_001881 | 854 | permissive | [
{
"docstring": ":type prices: List[int] :rtype: int 动态规划",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int 非动态规划",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int 动态规划
- def maxProfit(self, prices): :type prices: List[int] :rtype: int 非动态规划 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int 动态规划
- def maxProfit(self, prices): :type prices: List[int] :rtype: int 非动态规划
<|skeleton|>
class Solution:
... | d2b8a1dfe986d71d02d2568b55bad6e5b1c81492 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int 动态规划"""
<|body_0|>
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int 非动态规划"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int 动态规划"""
if len(prices) <= 1:
return 0
maxPro = 0
minPrice = prices[0]
for i in range(1, len(prices)):
maxPro = max(maxPro, prices[i] - minPrice)
minPrice = ... | the_stack_v2_python_sparse | Easy/Que121.py | HuangZengPei/LeetCode | train | 2 | |
7cf88e1645d8accf7097a420974ba659944b7549 | [
"self.g = g\nself.user_type = user_type\nself.item_type = item_type\nself.user_to_item_etype = list(g.metagraph()[user_type][item_type])[0]\nself.item_to_user_etype = list(g.metagraph()[item_type][user_type])[0]\nself.samplers = [dgl.sampling.PinSAGESampler(g, item_type, user_type, random_walk_length, random_walk_r... | <|body_start_0|>
self.g = g
self.user_type = user_type
self.item_type = item_type
self.user_to_item_etype = list(g.metagraph()[user_type][item_type])[0]
self.item_to_user_etype = list(g.metagraph()[item_type][user_type])[0]
self.samplers = [dgl.sampling.PinSAGESampler(g, ... | Neighbor Sampler class that uses PinSAGE Sampler. | NeighborSampler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeighborSampler:
"""Neighbor Sampler class that uses PinSAGE Sampler."""
def __init__(self, g, user_type, item_type, random_walk_length, random_walk_restart_prob, num_random_walks, num_neighbors, num_layers):
"""Constructor for NeighborSampler class. Args: g (dgl.DGLGraph): graph of ... | stack_v2_sparse_classes_36k_train_001882 | 12,447 | no_license | [
{
"docstring": "Constructor for NeighborSampler class. Args: g (dgl.DGLGraph): graph of training datset user_type (str): user node name item_type (str): item node name random_walk_length (int): the maximum number traversals for a single random walk random_walk_restart_prob (int): termination probability after e... | 3 | stack_v2_sparse_classes_30k_train_016960 | Implement the Python class `NeighborSampler` described below.
Class description:
Neighbor Sampler class that uses PinSAGE Sampler.
Method signatures and docstrings:
- def __init__(self, g, user_type, item_type, random_walk_length, random_walk_restart_prob, num_random_walks, num_neighbors, num_layers): Constructor for... | Implement the Python class `NeighborSampler` described below.
Class description:
Neighbor Sampler class that uses PinSAGE Sampler.
Method signatures and docstrings:
- def __init__(self, g, user_type, item_type, random_walk_length, random_walk_restart_prob, num_random_walks, num_neighbors, num_layers): Constructor for... | f1c385e46d2d5475b28dec91b57a933ac81c23c5 | <|skeleton|>
class NeighborSampler:
"""Neighbor Sampler class that uses PinSAGE Sampler."""
def __init__(self, g, user_type, item_type, random_walk_length, random_walk_restart_prob, num_random_walks, num_neighbors, num_layers):
"""Constructor for NeighborSampler class. Args: g (dgl.DGLGraph): graph of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NeighborSampler:
"""Neighbor Sampler class that uses PinSAGE Sampler."""
def __init__(self, g, user_type, item_type, random_walk_length, random_walk_restart_prob, num_random_walks, num_neighbors, num_layers):
"""Constructor for NeighborSampler class. Args: g (dgl.DGLGraph): graph of training dats... | the_stack_v2_python_sparse | projects/project_19/src/pinsage/sampler.py | amuamushu/projects-2020-2021 | train | 0 |
fcfa8741c846c2fd476e85ad1a2446adca5a3c43 | [
"if node is not self:\n self.vertices.add(node)\n node.vertices.add(self)",
"for vertex in self.vertices:\n vertex.vertices.discard(self)\ndel self.vertices"
] | <|body_start_0|>
if node is not self:
self.vertices.add(node)
node.vertices.add(self)
<|end_body_0|>
<|body_start_1|>
for vertex in self.vertices:
vertex.vertices.discard(self)
del self.vertices
<|end_body_1|>
| An internal graph node class for the proximity handler. | GraphNode | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphNode:
"""An internal graph node class for the proximity handler."""
def link(self, node):
"""Link this node with another vertex. Parameters ---------- node : GraphNode The node to link with this vertex."""
<|body_0|>
def unlink(self):
"""Unlink this node fro... | stack_v2_sparse_classes_36k_train_001883 | 5,910 | permissive | [
{
"docstring": "Link this node with another vertex. Parameters ---------- node : GraphNode The node to link with this vertex.",
"name": "link",
"signature": "def link(self, node)"
},
{
"docstring": "Unlink this node from the connected vertices.",
"name": "unlink",
"signature": "def unlin... | 2 | stack_v2_sparse_classes_30k_train_000589 | Implement the Python class `GraphNode` described below.
Class description:
An internal graph node class for the proximity handler.
Method signatures and docstrings:
- def link(self, node): Link this node with another vertex. Parameters ---------- node : GraphNode The node to link with this vertex.
- def unlink(self):... | Implement the Python class `GraphNode` described below.
Class description:
An internal graph node class for the proximity handler.
Method signatures and docstrings:
- def link(self, node): Link this node with another vertex. Parameters ---------- node : GraphNode The node to link with this vertex.
- def unlink(self):... | 1544e7fb371b8f941cfa2fde682795e479380284 | <|skeleton|>
class GraphNode:
"""An internal graph node class for the proximity handler."""
def link(self, node):
"""Link this node with another vertex. Parameters ---------- node : GraphNode The node to link with this vertex."""
<|body_0|>
def unlink(self):
"""Unlink this node fro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GraphNode:
"""An internal graph node class for the proximity handler."""
def link(self, node):
"""Link this node with another vertex. Parameters ---------- node : GraphNode The node to link with this vertex."""
if node is not self:
self.vertices.add(node)
node.vert... | the_stack_v2_python_sparse | enaml/qt/docking/proximity_handler.py | MatthieuDartiailh/enaml | train | 26 |
a9e3820380e53c537b1714c713958b46f295e37d | [
"self.server = server\nself.name = name\nself.meta_data = None\nself.controllers = {}\nself.models = {}\nself.repositories = {}\nself.views = {}\nself.routes = {}",
"fs_root = self.server.user_directory\nmetadatas_path = os.path.join(fs_root, 'bundles', self.name, 'bundle.yml')\nself.meta_datas = MetadatasConfigu... | <|body_start_0|>
self.server = server
self.name = name
self.meta_data = None
self.controllers = {}
self.models = {}
self.repositories = {}
self.views = {}
self.routes = {}
<|end_body_0|>
<|body_start_1|>
fs_root = self.server.user_directory
... | Class representing a user bundle, part of a Python Aboard application. The bundles defined by the user contains part of his application. The whole bundles almost constitute the entire application itself. As a matter of fact, the bundle contains: * Configuration (like, for instance, routing informations) * Controllers a... | Bundle | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bundle:
"""Class representing a user bundle, part of a Python Aboard application. The bundles defined by the user contains part of his application. The whole bundles almost constitute the entire application itself. As a matter of fact, the bundle contains: * Configuration (like, for instance, rou... | stack_v2_sparse_classes_36k_train_001884 | 6,504 | permissive | [
{
"docstring": "Create a new bundle.",
"name": "__init__",
"signature": "def __init__(self, server, name)"
},
{
"docstring": "Setup the bundle following the setup process. Note that the bundles dictionary is passed to the setup method. It allows the bundle, when reading its meta-datas, to check ... | 3 | stack_v2_sparse_classes_30k_train_010674 | Implement the Python class `Bundle` described below.
Class description:
Class representing a user bundle, part of a Python Aboard application. The bundles defined by the user contains part of his application. The whole bundles almost constitute the entire application itself. As a matter of fact, the bundle contains: *... | Implement the Python class `Bundle` described below.
Class description:
Class representing a user bundle, part of a Python Aboard application. The bundles defined by the user contains part of his application. The whole bundles almost constitute the entire application itself. As a matter of fact, the bundle contains: *... | f459733c9307c2f843dd9ad5d1d82feafc065816 | <|skeleton|>
class Bundle:
"""Class representing a user bundle, part of a Python Aboard application. The bundles defined by the user contains part of his application. The whole bundles almost constitute the entire application itself. As a matter of fact, the bundle contains: * Configuration (like, for instance, rou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bundle:
"""Class representing a user bundle, part of a Python Aboard application. The bundles defined by the user contains part of his application. The whole bundles almost constitute the entire application itself. As a matter of fact, the bundle contains: * Configuration (like, for instance, routing informat... | the_stack_v2_python_sparse | src/bundle/bundle.py | v-legoff/pa-poc3 | train | 0 |
30d2e156aa3e4b2352c8b054cd03835d444e1a85 | [
"pdata_current_point = pv.PolyData(curr_animal_point)\npc_current_point = pdata_current_point.glyph(scale=False, geom=point_location_circle)\nself.plots_data[plot_name] = {'pdata_current_point': pdata_current_point, 'pc_current_point': pc_current_point}\nself.plots[plot_name] = self.p.add_mesh(pc_current_point, nam... | <|body_start_0|>
pdata_current_point = pv.PolyData(curr_animal_point)
pc_current_point = pdata_current_point.glyph(scale=False, geom=point_location_circle)
self.plots_data[plot_name] = {'pdata_current_point': pdata_current_point, 'pc_current_point': pc_current_point}
self.plots[plot_name... | Implementor can render location points and paths/trails in the plotter Requires (Implementor Must Provide): p plots plots_data Provides: Provided Properties: None Provided Methods: perform_plot_location_point(...) perform_plot_location_trail(...) | InteractivePyvistaPlotter_PointAndPathPlottingMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InteractivePyvistaPlotter_PointAndPathPlottingMixin:
"""Implementor can render location points and paths/trails in the plotter Requires (Implementor Must Provide): p plots plots_data Provides: Provided Properties: None Provided Methods: perform_plot_location_point(...) perform_plot_location_trail... | stack_v2_sparse_classes_36k_train_001885 | 7,895 | permissive | [
{
"docstring": "will render a flat indicator of a single point like is used for the animal's current location. Updates the existing plot if the same plot_name is reused.",
"name": "perform_plot_location_point",
"signature": "def perform_plot_location_point(self, plot_name, curr_animal_point, render=True... | 2 | null | Implement the Python class `InteractivePyvistaPlotter_PointAndPathPlottingMixin` described below.
Class description:
Implementor can render location points and paths/trails in the plotter Requires (Implementor Must Provide): p plots plots_data Provides: Provided Properties: None Provided Methods: perform_plot_location... | Implement the Python class `InteractivePyvistaPlotter_PointAndPathPlottingMixin` described below.
Class description:
Implementor can render location points and paths/trails in the plotter Requires (Implementor Must Provide): p plots plots_data Provides: Provided Properties: None Provided Methods: perform_plot_location... | 212399d826284b394fce8894ff1a93133aef783f | <|skeleton|>
class InteractivePyvistaPlotter_PointAndPathPlottingMixin:
"""Implementor can render location points and paths/trails in the plotter Requires (Implementor Must Provide): p plots plots_data Provides: Provided Properties: None Provided Methods: perform_plot_location_point(...) perform_plot_location_trail... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InteractivePyvistaPlotter_PointAndPathPlottingMixin:
"""Implementor can render location points and paths/trails in the plotter Requires (Implementor Must Provide): p plots plots_data Provides: Provided Properties: None Provided Methods: perform_plot_location_point(...) perform_plot_location_trail(...)"""
... | the_stack_v2_python_sparse | src/pyphoplacecellanalysis/GUI/PyVista/InteractivePlotter/Mixins/InteractivePlotterMixins.py | CommanderPho/pyPhoPlaceCellAnalysis | train | 1 |
6e92ecd8c43ecccb67746ae75ed6fef2be8cb177 | [
"result, odd, even = ([], [], [])\nfor i in A:\n if i % 2 == 0:\n odd.append(i)\n else:\n even.append(i)\nwhile odd and even:\n result.append(odd.pop(0))\n result.append(even.pop(0))\nreturn result",
"n = len(A)\ni, j = (0, 1)\nresult = [0] * n\nfor a in A:\n if a & 1 == 0:\n r... | <|body_start_0|>
result, odd, even = ([], [], [])
for i in A:
if i % 2 == 0:
odd.append(i)
else:
even.append(i)
while odd and even:
result.append(odd.pop(0))
result.append(even.pop(0))
return result
<|end_bod... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortArrayByParityII(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_0|>
def sortArrayByParityII2(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_1|>
def sortArrayByParityII3(self, A):
""":type A: List[int] :r... | stack_v2_sparse_classes_36k_train_001886 | 2,735 | no_license | [
{
"docstring": ":type A: List[int] :rtype: List[int]",
"name": "sortArrayByParityII",
"signature": "def sortArrayByParityII(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: List[int]",
"name": "sortArrayByParityII2",
"signature": "def sortArrayByParityII2(self, A)"
},
{
"d... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParityII(self, A): :type A: List[int] :rtype: List[int]
- def sortArrayByParityII2(self, A): :type A: List[int] :rtype: List[int]
- def sortArrayByParityII3(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParityII(self, A): :type A: List[int] :rtype: List[int]
- def sortArrayByParityII2(self, A): :type A: List[int] :rtype: List[int]
- def sortArrayByParityII3(self, ... | f022677c042db3598003df1a320a70f0edc4f870 | <|skeleton|>
class Solution:
def sortArrayByParityII(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_0|>
def sortArrayByParityII2(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_1|>
def sortArrayByParityII3(self, A):
""":type A: List[int] :r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortArrayByParityII(self, A):
""":type A: List[int] :rtype: List[int]"""
result, odd, even = ([], [], [])
for i in A:
if i % 2 == 0:
odd.append(i)
else:
even.append(i)
while odd and even:
result.a... | the_stack_v2_python_sparse | ArrayDeal/anjioupaixushuzu2.py | daisyzl/program-exercise-python | train | 0 | |
3270429165a2922e01dae4ea6667dba020249e6c | [
"if 'password1' in self.cleaned_data and 'password2' in self.cleaned_data:\n if self.cleaned_data['password1'] != self.cleaned_data['password2']:\n raise forms.ValidationError(_(u'Passwords do not match. Please enter the same password in both fields.'))\nreturn self.cleaned_data",
"email = self.cleaned_... | <|body_start_0|>
if 'password1' in self.cleaned_data and 'password2' in self.cleaned_data:
if self.cleaned_data['password1'] != self.cleaned_data['password2']:
raise forms.ValidationError(_(u'Passwords do not match. Please enter the same password in both fields.'))
return sel... | RegisterForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterForm:
def clean(self):
"""Verify that the values entered into the two password fields match. Note that an error here will end up in non_field_errors() because it doesn't apply to a single field."""
<|body_0|>
def clean_email(self):
"""Verify that the email en... | stack_v2_sparse_classes_36k_train_001887 | 15,236 | no_license | [
{
"docstring": "Verify that the values entered into the two password fields match. Note that an error here will end up in non_field_errors() because it doesn't apply to a single field.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Verify that the email entered does not exi... | 3 | null | Implement the Python class `RegisterForm` described below.
Class description:
Implement the RegisterForm class.
Method signatures and docstrings:
- def clean(self): Verify that the values entered into the two password fields match. Note that an error here will end up in non_field_errors() because it doesn't apply to ... | Implement the Python class `RegisterForm` described below.
Class description:
Implement the RegisterForm class.
Method signatures and docstrings:
- def clean(self): Verify that the values entered into the two password fields match. Note that an error here will end up in non_field_errors() because it doesn't apply to ... | 8c2163320d4381e815524dc322c76602bea212c7 | <|skeleton|>
class RegisterForm:
def clean(self):
"""Verify that the values entered into the two password fields match. Note that an error here will end up in non_field_errors() because it doesn't apply to a single field."""
<|body_0|>
def clean_email(self):
"""Verify that the email en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegisterForm:
def clean(self):
"""Verify that the values entered into the two password fields match. Note that an error here will end up in non_field_errors() because it doesn't apply to a single field."""
if 'password1' in self.cleaned_data and 'password2' in self.cleaned_data:
if... | the_stack_v2_python_sparse | akvo/rsr/forms.py | supermari0/akvo-rsr | train | 0 | |
8a88a22ace11fa29fa287a4d0ba89ec06e9ecc0b | [
"if num == 1:\n return 1\nreturn num * Solution.factorial(num - 1)",
"result = 1\nstack = []\nstack.append(num)\nwhile result == 1:\n num = stack[-1]\n if stack[-1] == 1:\n for item in stack:\n result *= item\n else:\n stack.append(num - 1)\n print(stack)\nreturn result"
] | <|body_start_0|>
if num == 1:
return 1
return num * Solution.factorial(num - 1)
<|end_body_0|>
<|body_start_1|>
result = 1
stack = []
stack.append(num)
while result == 1:
num = stack[-1]
if stack[-1] == 1:
for item in s... | Solution | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Solution"""
def factorial(num):
"""Factorial recursive approach"""
<|body_0|>
def fac_iterative(num):
"""Factorial iterative approach"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if num == 1:
return 1
return n... | stack_v2_sparse_classes_36k_train_001888 | 802 | no_license | [
{
"docstring": "Factorial recursive approach",
"name": "factorial",
"signature": "def factorial(num)"
},
{
"docstring": "Factorial iterative approach",
"name": "fac_iterative",
"signature": "def fac_iterative(num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008549 | Implement the Python class `Solution` described below.
Class description:
Solution
Method signatures and docstrings:
- def factorial(num): Factorial recursive approach
- def fac_iterative(num): Factorial iterative approach | Implement the Python class `Solution` described below.
Class description:
Solution
Method signatures and docstrings:
- def factorial(num): Factorial recursive approach
- def fac_iterative(num): Factorial iterative approach
<|skeleton|>
class Solution:
"""Solution"""
def factorial(num):
"""Factorial ... | 139a20063476f9847652b334a8495b7df1e80e27 | <|skeleton|>
class Solution:
"""Solution"""
def factorial(num):
"""Factorial recursive approach"""
<|body_0|>
def fac_iterative(num):
"""Factorial iterative approach"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Solution"""
def factorial(num):
"""Factorial recursive approach"""
if num == 1:
return 1
return num * Solution.factorial(num - 1)
def fac_iterative(num):
"""Factorial iterative approach"""
result = 1
stack = []
stack.ap... | the_stack_v2_python_sparse | archive-20200922/math/factorial_iterative.py | clarkngo/python-projects | train | 0 |
c7482a4492bc592cc99600fee56a50122fb06b53 | [
"self.kw = kwargs\nStep.__init__(self, *args, routine=routine, **kwargs)\nqscale_settings = self.parse_settings(self.get_requested_settings())\nqbcal.QScale.__init__(self, dev=self.dev, **qscale_settings)",
"kwargs = {}\ntask_list = []\nfor qb in self.qubits:\n task = {}\n task_list_fields = requested_kwarg... | <|body_start_0|>
self.kw = kwargs
Step.__init__(self, *args, routine=routine, **kwargs)
qscale_settings = self.parse_settings(self.get_requested_settings())
qbcal.QScale.__init__(self, dev=self.dev, **qscale_settings)
<|end_body_0|>
<|body_start_1|>
kwargs = {}
task_list... | A wrapper class for the QScale experiment. | QScaleStep | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QScaleStep:
"""A wrapper class for the QScale experiment."""
def __init__(self, routine, *args, **kwargs):
"""Initializes the QScaleStep class, which also includes initialization of the QScale experiment. Arguments: routine (Step): The parent routine. Keyword args: qubits (list): Lis... | stack_v2_sparse_classes_36k_train_001889 | 48,290 | permissive | [
{
"docstring": "Initializes the QScaleStep class, which also includes initialization of the QScale experiment. Arguments: routine (Step): The parent routine. Keyword args: qubits (list): List of qubits to be used in the routine. Configuration parameters (coming from the configuration parameter dictionary): tran... | 3 | stack_v2_sparse_classes_30k_train_011662 | Implement the Python class `QScaleStep` described below.
Class description:
A wrapper class for the QScale experiment.
Method signatures and docstrings:
- def __init__(self, routine, *args, **kwargs): Initializes the QScaleStep class, which also includes initialization of the QScale experiment. Arguments: routine (St... | Implement the Python class `QScaleStep` described below.
Class description:
A wrapper class for the QScale experiment.
Method signatures and docstrings:
- def __init__(self, routine, *args, **kwargs): Initializes the QScaleStep class, which also includes initialization of the QScale experiment. Arguments: routine (St... | bc6733d774fe31a23f4c7e73e5eb0beed8d30e7d | <|skeleton|>
class QScaleStep:
"""A wrapper class for the QScale experiment."""
def __init__(self, routine, *args, **kwargs):
"""Initializes the QScaleStep class, which also includes initialization of the QScale experiment. Arguments: routine (Step): The parent routine. Keyword args: qubits (list): Lis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QScaleStep:
"""A wrapper class for the QScale experiment."""
def __init__(self, routine, *args, **kwargs):
"""Initializes the QScaleStep class, which also includes initialization of the QScale experiment. Arguments: routine (Step): The parent routine. Keyword args: qubits (list): List of qubits t... | the_stack_v2_python_sparse | pycqed/measurement/calibration/automatic_calibration_routines/single_qubit_routines.py | QudevETH/PycQED_py3 | train | 8 |
f36544964ab2a32eec870eed70a41fc7979871be | [
"super().parse_command_line(argv)\nself.build_kernel_argv(self.extra_args)\nself.filenames_to_run = self.extra_args[:]",
"self.log.debug('jupyter run: initialize...')\nsuper().initialize(argv)\nJupyterConsoleApp.initialize(self)\nsignal.signal(signal.SIGINT, self.handle_sigint)\nself.init_kernel_info()",
"if se... | <|body_start_0|>
super().parse_command_line(argv)
self.build_kernel_argv(self.extra_args)
self.filenames_to_run = self.extra_args[:]
<|end_body_0|>
<|body_start_1|>
self.log.debug('jupyter run: initialize...')
super().initialize(argv)
JupyterConsoleApp.initialize(self)
... | An Jupyter Console app to run files. | RunApp | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunApp:
"""An Jupyter Console app to run files."""
def parse_command_line(self, argv=None):
"""Parse the command line arguments."""
<|body_0|>
def initialize(self, argv=None):
"""Initialize the app."""
<|body_1|>
def handle_sigint(self, *args):
... | stack_v2_sparse_classes_36k_train_001890 | 4,496 | permissive | [
{
"docstring": "Parse the command line arguments.",
"name": "parse_command_line",
"signature": "def parse_command_line(self, argv=None)"
},
{
"docstring": "Initialize the app.",
"name": "initialize",
"signature": "def initialize(self, argv=None)"
},
{
"docstring": "Handle SIGINT.... | 5 | stack_v2_sparse_classes_30k_val_001066 | Implement the Python class `RunApp` described below.
Class description:
An Jupyter Console app to run files.
Method signatures and docstrings:
- def parse_command_line(self, argv=None): Parse the command line arguments.
- def initialize(self, argv=None): Initialize the app.
- def handle_sigint(self, *args): Handle SI... | Implement the Python class `RunApp` described below.
Class description:
An Jupyter Console app to run files.
Method signatures and docstrings:
- def parse_command_line(self, argv=None): Parse the command line arguments.
- def initialize(self, argv=None): Initialize the app.
- def handle_sigint(self, *args): Handle SI... | f5042e35b945aded77b23470ead62d7eacefde92 | <|skeleton|>
class RunApp:
"""An Jupyter Console app to run files."""
def parse_command_line(self, argv=None):
"""Parse the command line arguments."""
<|body_0|>
def initialize(self, argv=None):
"""Initialize the app."""
<|body_1|>
def handle_sigint(self, *args):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunApp:
"""An Jupyter Console app to run files."""
def parse_command_line(self, argv=None):
"""Parse the command line arguments."""
super().parse_command_line(argv)
self.build_kernel_argv(self.extra_args)
self.filenames_to_run = self.extra_args[:]
def initialize(self,... | the_stack_v2_python_sparse | contrib/python/jupyter-client/py3/jupyter_client/runapp.py | catboost/catboost | train | 8,012 |
45844ad7c7b92b2fd86013ea9b9ae8d4052b01d9 | [
"self.settings = ai_game.settings\nself.reset_stats()\nself.game_active = False\nself.second_game_active = False\nwith open('highscoreThirteen.txt') as f:\n score = int(f.readline())\nself.high_score = score",
"self.ships_left = self.settings.ship_limit\nself.score = 0\nself.level = 1"
] | <|body_start_0|>
self.settings = ai_game.settings
self.reset_stats()
self.game_active = False
self.second_game_active = False
with open('highscoreThirteen.txt') as f:
score = int(f.readline())
self.high_score = score
<|end_body_0|>
<|body_start_1|>
se... | Track statistics for Alien Invasion | GameStats | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameStats:
"""Track statistics for Alien Invasion"""
def __init__(self, ai_game):
"""Initialize statistics"""
<|body_0|>
def reset_stats(self):
"""Inits stats that can change during game"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.setti... | stack_v2_sparse_classes_36k_train_001891 | 689 | no_license | [
{
"docstring": "Initialize statistics",
"name": "__init__",
"signature": "def __init__(self, ai_game)"
},
{
"docstring": "Inits stats that can change during game",
"name": "reset_stats",
"signature": "def reset_stats(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000157 | Implement the Python class `GameStats` described below.
Class description:
Track statistics for Alien Invasion
Method signatures and docstrings:
- def __init__(self, ai_game): Initialize statistics
- def reset_stats(self): Inits stats that can change during game | Implement the Python class `GameStats` described below.
Class description:
Track statistics for Alien Invasion
Method signatures and docstrings:
- def __init__(self, ai_game): Initialize statistics
- def reset_stats(self): Inits stats that can change during game
<|skeleton|>
class GameStats:
"""Track statistics ... | 7c49f8f05afa58c99979bf490f7bc4ff85a87167 | <|skeleton|>
class GameStats:
"""Track statistics for Alien Invasion"""
def __init__(self, ai_game):
"""Initialize statistics"""
<|body_0|>
def reset_stats(self):
"""Inits stats that can change during game"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameStats:
"""Track statistics for Alien Invasion"""
def __init__(self, ai_game):
"""Initialize statistics"""
self.settings = ai_game.settings
self.reset_stats()
self.game_active = False
self.second_game_active = False
with open('highscoreThirteen.txt') as ... | the_stack_v2_python_sparse | chapter_13/thirteenSix_gamestats.py | kelvDp/CC_python_cc_projects | train | 0 |
95da979057c51bcc76a88baa12c8c2ff63d10d91 | [
"super().__init__()\nself.dims = dims\nself.__model_fn()",
"layers = []\nfor i in range(len(self.dims) - 1):\n layers.append(torch.nn.Linear(self.dims[i], self.dims[i + 1]))\nself.layers = nn.ModuleList(layers)",
"for layer in self.layers:\n X = F.relu(layer(X))\nreturn X"
] | <|body_start_0|>
super().__init__()
self.dims = dims
self.__model_fn()
<|end_body_0|>
<|body_start_1|>
layers = []
for i in range(len(self.dims) - 1):
layers.append(torch.nn.Linear(self.dims[i], self.dims[i + 1]))
self.layers = nn.ModuleList(layers)
<|end_bod... | Class Net. | Net | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Net:
"""Class Net."""
def __init__(self, dims):
"""Constructor. :param dims: layer dimensionalities"""
<|body_0|>
def __model_fn(self):
"""Specifies the network."""
<|body_1|>
def forward(self, X):
"""Performs a forward-pass on the data. :par... | stack_v2_sparse_classes_36k_train_001892 | 4,225 | no_license | [
{
"docstring": "Constructor. :param dims: layer dimensionalities",
"name": "__init__",
"signature": "def __init__(self, dims)"
},
{
"docstring": "Specifies the network.",
"name": "__model_fn",
"signature": "def __model_fn(self)"
},
{
"docstring": "Performs a forward-pass on the d... | 3 | stack_v2_sparse_classes_30k_train_020379 | Implement the Python class `Net` described below.
Class description:
Class Net.
Method signatures and docstrings:
- def __init__(self, dims): Constructor. :param dims: layer dimensionalities
- def __model_fn(self): Specifies the network.
- def forward(self, X): Performs a forward-pass on the data. :param X: network i... | Implement the Python class `Net` described below.
Class description:
Class Net.
Method signatures and docstrings:
- def __init__(self, dims): Constructor. :param dims: layer dimensionalities
- def __model_fn(self): Specifies the network.
- def forward(self, X): Performs a forward-pass on the data. :param X: network i... | 98b71b76f664d5f6493bd7f90036531d8f6644a7 | <|skeleton|>
class Net:
"""Class Net."""
def __init__(self, dims):
"""Constructor. :param dims: layer dimensionalities"""
<|body_0|>
def __model_fn(self):
"""Specifies the network."""
<|body_1|>
def forward(self, X):
"""Performs a forward-pass on the data. :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Net:
"""Class Net."""
def __init__(self, dims):
"""Constructor. :param dims: layer dimensionalities"""
super().__init__()
self.dims = dims
self.__model_fn()
def __model_fn(self):
"""Specifies the network."""
layers = []
for i in range(len(self.... | the_stack_v2_python_sparse | 06_python/unsupervised/decomposition/auto_encoder.py | pfisterer/Applied_ML_Fundamentals | train | 0 |
e9ee9f9afcb5ec4266e57963e3065a2b9d2cf24e | [
"self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')\nself.n_win = hyper_parameters['model'].get('n_win', 3)\nsuper().__init__(hyper_parameters)",
"super().create_model(hyper_parameters)\nembedding = self.word_embedding.output\n\ndef win_mean(x):\n res_list = []\n for i in range(self.len_... | <|body_start_0|>
self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')
self.n_win = hyper_parameters['model'].get('n_win', 3)
super().__init__(hyper_parameters)
<|end_body_0|>
<|body_start_1|>
super().create_model(hyper_parameters)
embedding = self.word_embeddin... | SWEMGraph | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_001893 | 2,341 | permissive | [
{
"docstring": "初始化 :param hyper_parameters: json，超参",
"name": "__init__",
"signature": "def __init__(self, hyper_parameters)"
},
{
"docstring": "构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl",
"name": "create_model",
"signature": "def create_mod... | 2 | stack_v2_sparse_classes_30k_train_014633 | Implement the Python class `SWEMGraph` described below.
Class description:
Implement the SWEMGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper parameters of ... | Implement the Python class `SWEMGraph` described below.
Class description:
Implement the SWEMGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper parameters of ... | 640e3f44f90d9d8046546f7e1a93a29ebe5c8d30 | <|skeleton|>
class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')
self.n_win = hyper_parameters['model'].get('n_win', 3)
super().__init__(hyper_parameters)
def create_model(sel... | the_stack_v2_python_sparse | keras_textclassification/m15_SWEM/graph.py | wzjames/Keras-TextClassification | train | 1 | |
a64ce38bc6d8d72d593e2af71603b61b7ef07503 | [
"self.nets.encoder = encoder\nif task_idx != {}:\n self.task_idx = task_idx\nelif config is None:\n raise ValueError('config and classifier_task_idx not provided.')\nelif 'classifier_idx' not in config.keys():\n raise ValueError('classifier_idx must be provided in config')\nelse:\n self.task_idx = confi... | <|body_start_0|>
self.nets.encoder = encoder
if task_idx != {}:
self.task_idx = task_idx
elif config is None:
raise ValueError('config and classifier_task_idx not provided.')
elif 'classifier_idx' not in config.keys():
raise ValueError('classifier_idx ... | Basic classification module. This module forms several classifiers which plug into the encoder. | ClassificationEval | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassificationEval:
"""Basic classification module. This module forms several classifiers which plug into the encoder."""
def build(self, encoder, config, task_idx={}, layers=[dict(layer='linear', args=(200,), bn=True, do=0.1, act='ReLU', bias=True)]):
"""Builds the classifiers. Args... | stack_v2_sparse_classes_36k_train_001894 | 3,743 | permissive | [
{
"docstring": "Builds the classifiers. Args: task_idx: Dictionary of (name, index) pairs of encoder output to classify. layers: Layers for classifiers.",
"name": "build",
"signature": "def build(self, encoder, config, task_idx={}, layers=[dict(layer='linear', args=(200,), bn=True, do=0.1, act='ReLU', b... | 2 | stack_v2_sparse_classes_30k_train_011786 | Implement the Python class `ClassificationEval` described below.
Class description:
Basic classification module. This module forms several classifiers which plug into the encoder.
Method signatures and docstrings:
- def build(self, encoder, config, task_idx={}, layers=[dict(layer='linear', args=(200,), bn=True, do=0.... | Implement the Python class `ClassificationEval` described below.
Class description:
Basic classification module. This module forms several classifiers which plug into the encoder.
Method signatures and docstrings:
- def build(self, encoder, config, task_idx={}, layers=[dict(layer='linear', args=(200,), bn=True, do=0.... | 980c91c3d997ce2bfb10c052842d39e2c416913c | <|skeleton|>
class ClassificationEval:
"""Basic classification module. This module forms several classifiers which plug into the encoder."""
def build(self, encoder, config, task_idx={}, layers=[dict(layer='linear', args=(200,), bn=True, do=0.1, act='ReLU', bias=True)]):
"""Builds the classifiers. Args... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassificationEval:
"""Basic classification module. This module forms several classifiers which plug into the encoder."""
def build(self, encoder, config, task_idx={}, layers=[dict(layer='linear', args=(200,), bn=True, do=0.1, act='ReLU', bias=True)]):
"""Builds the classifiers. Args: task_idx: D... | the_stack_v2_python_sparse | cortex_DIM/evaluation_models/classification_eval.py | tanimutomo/DIM | train | 1 |
71d467ecf86b110fb80d9ae771e67fc874cc1f5e | [
"work_time = WorkTime.objects.all().first()\nif work_time:\n data = {'id': id, 'morning_start_time': work_time.morning_start_time, 'morning_end_time': work_time.morning_end_time, 'afternoon_start_time': work_time.afternoon_start_time, 'afternoon_end_time': work_time.afternoon_end_time}\nelse:\n data = {}\nret... | <|body_start_0|>
work_time = WorkTime.objects.all().first()
if work_time:
data = {'id': id, 'morning_start_time': work_time.morning_start_time, 'morning_end_time': work_time.morning_end_time, 'afternoon_start_time': work_time.afternoon_start_time, 'afternoon_end_time': work_time.afternoon_en... | 查询一天的工作时间 | WorkTimeView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkTimeView:
"""查询一天的工作时间"""
def get(self, request):
"""获取工作时间信息"""
<|body_0|>
def post(self, request):
"""# "添加或者修改工作时间信息" :param request: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
work_time = WorkTime.objects.all().first()
... | stack_v2_sparse_classes_36k_train_001895 | 2,556 | no_license | [
{
"docstring": "获取工作时间信息",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "# \"添加或者修改工作时间信息\" :param request: :return:",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `WorkTimeView` described below.
Class description:
查询一天的工作时间
Method signatures and docstrings:
- def get(self, request): 获取工作时间信息
- def post(self, request): # "添加或者修改工作时间信息" :param request: :return: | Implement the Python class `WorkTimeView` described below.
Class description:
查询一天的工作时间
Method signatures and docstrings:
- def get(self, request): 获取工作时间信息
- def post(self, request): # "添加或者修改工作时间信息" :param request: :return:
<|skeleton|>
class WorkTimeView:
"""查询一天的工作时间"""
def get(self, request):
"... | d6e025d7e9d9e3aecfd399c77f376130edd8a2df | <|skeleton|>
class WorkTimeView:
"""查询一天的工作时间"""
def get(self, request):
"""获取工作时间信息"""
<|body_0|>
def post(self, request):
"""# "添加或者修改工作时间信息" :param request: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkTimeView:
"""查询一天的工作时间"""
def get(self, request):
"""获取工作时间信息"""
work_time = WorkTime.objects.all().first()
if work_time:
data = {'id': id, 'morning_start_time': work_time.morning_start_time, 'morning_end_time': work_time.morning_end_time, 'afternoon_start_time': w... | the_stack_v2_python_sparse | soc_user/views/work_time.py | sundw2015/841 | train | 4 |
b8352ef22b3ff5ab3435bfae9ae27192c503ac9f | [
"self.token = {'access_token': Mytest.access_token}\ntag_name = {'tag': {'name': '545656'}}\nhost = 'https://api.weixin.qq.com/cgi-bin/tags/create'\nr6 = ApiDefine().creatertagname(self.session, host, params=self.token, data=json.dumps(tag_name))\ntime.sleep(2)\nprint('创建标签', r6.text)",
"self.token = {'assess_tok... | <|body_start_0|>
self.token = {'access_token': Mytest.access_token}
tag_name = {'tag': {'name': '545656'}}
host = 'https://api.weixin.qq.com/cgi-bin/tags/create'
r6 = ApiDefine().creatertagname(self.session, host, params=self.token, data=json.dumps(tag_name))
time.sleep(2)
... | Mytest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mytest:
def test_createtag(self):
"""创建标签"""
<|body_0|>
def test_createtag30(self):
"""超过30个字符"""
<|body_1|>
def test_gettag(self):
"""获取标签列表"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.token = {'access_token': Mytest.a... | stack_v2_sparse_classes_36k_train_001896 | 1,828 | no_license | [
{
"docstring": "创建标签",
"name": "test_createtag",
"signature": "def test_createtag(self)"
},
{
"docstring": "超过30个字符",
"name": "test_createtag30",
"signature": "def test_createtag30(self)"
},
{
"docstring": "获取标签列表",
"name": "test_gettag",
"signature": "def test_gettag(sel... | 3 | null | Implement the Python class `Mytest` described below.
Class description:
Implement the Mytest class.
Method signatures and docstrings:
- def test_createtag(self): 创建标签
- def test_createtag30(self): 超过30个字符
- def test_gettag(self): 获取标签列表 | Implement the Python class `Mytest` described below.
Class description:
Implement the Mytest class.
Method signatures and docstrings:
- def test_createtag(self): 创建标签
- def test_createtag30(self): 超过30个字符
- def test_gettag(self): 获取标签列表
<|skeleton|>
class Mytest:
def test_createtag(self):
"""创建标签"""
... | 7b790f675419224bfdbe1542eddc5a638982e68a | <|skeleton|>
class Mytest:
def test_createtag(self):
"""创建标签"""
<|body_0|>
def test_createtag30(self):
"""超过30个字符"""
<|body_1|>
def test_gettag(self):
"""获取标签列表"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mytest:
def test_createtag(self):
"""创建标签"""
self.token = {'access_token': Mytest.access_token}
tag_name = {'tag': {'name': '545656'}}
host = 'https://api.weixin.qq.com/cgi-bin/tags/create'
r6 = ApiDefine().creatertagname(self.session, host, params=self.token, data=json... | the_stack_v2_python_sparse | P9/weixin_apitest/testcases/weixin_createtag.py | liousAlready/NewDream_learning | train | 0 | |
b994c3f6a80a2d7889e40b81438638aee0dfda64 | [
"super().__init__()\nself.conv = nn.Conv1d(in_channels=in_channels, out_channels=out_channels, dilation=dilation, padding=dilation, kernel_size=3, bias=False)\nnn.init.xavier_uniform_(self.conv.weight)\nself.leaky_relu = nn.LeakyReLU(negative_slope=0.2)\nself.adaptive_batch_norm = AdaptiveBatchNorm1d(num_features=o... | <|body_start_0|>
super().__init__()
self.conv = nn.Conv1d(in_channels=in_channels, out_channels=out_channels, dilation=dilation, padding=dilation, kernel_size=3, bias=False)
nn.init.xavier_uniform_(self.conv.weight)
self.leaky_relu = nn.LeakyReLU(negative_slope=0.2)
self.adaptive... | Single convolutional unit for the speech denoising network. Input tensor: (batch_size, in_channels, length) Output tensor: (batch_size, out_channels, length) | ConvLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvLayer:
"""Single convolutional unit for the speech denoising network. Input tensor: (batch_size, in_channels, length) Output tensor: (batch_size, out_channels, length)"""
def __init__(self, in_channels, out_channels, dilation):
"""Setup the layer. in_channels: number of input cha... | stack_v2_sparse_classes_36k_train_001897 | 3,173 | no_license | [
{
"docstring": "Setup the layer. in_channels: number of input channels to be convoluted out_channels: number of output channels to be produced",
"name": "__init__",
"signature": "def __init__(self, in_channels, out_channels, dilation)"
},
{
"docstring": "Compute output tensor from input tensor",... | 2 | stack_v2_sparse_classes_30k_train_008981 | Implement the Python class `ConvLayer` described below.
Class description:
Single convolutional unit for the speech denoising network. Input tensor: (batch_size, in_channels, length) Output tensor: (batch_size, out_channels, length)
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, dil... | Implement the Python class `ConvLayer` described below.
Class description:
Single convolutional unit for the speech denoising network. Input tensor: (batch_size, in_channels, length) Output tensor: (batch_size, out_channels, length)
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, dil... | af986a9a86060ce661e62cc444baf0e6d6757cc9 | <|skeleton|>
class ConvLayer:
"""Single convolutional unit for the speech denoising network. Input tensor: (batch_size, in_channels, length) Output tensor: (batch_size, out_channels, length)"""
def __init__(self, in_channels, out_channels, dilation):
"""Setup the layer. in_channels: number of input cha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvLayer:
"""Single convolutional unit for the speech denoising network. Input tensor: (batch_size, in_channels, length) Output tensor: (batch_size, out_channels, length)"""
def __init__(self, in_channels, out_channels, dilation):
"""Setup the layer. in_channels: number of input channels to be c... | the_stack_v2_python_sparse | src/tasks/speech_denoise/model.py | MattSegal/speech-enhancement | train | 22 |
8dd64a58b95182ccdba65de699b9dad39646f26f | [
"self.screen_width = 1200\nself.screen_height = 800\nself.bg_color = (230, 230, 230)\nself.ship_limit = 3\nself.fleet_drop_factor = 100\nself.bullet_width = 6\nself.bullet_height = 30\nself.bullet_color = (60, 60, 60)\nself.bullets_allowed = 100\nself.speedup_scale = 1.1\nself.score_scale = 1.5\nself.initialize_dyn... | <|body_start_0|>
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.fleet_drop_factor = 100
self.bullet_width = 6
self.bullet_height = 30
self.bullet_color = (60, 60, 60)
self.bullets_allowed ... | 存储《外星人入侵》的所有设置的类 | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_001898 | 1,291 | no_license | [
{
"docstring": "初始化游戏的设置",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "初始化随游戏进行而变化的设置",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
"docstring": "提高速度设置",
"name": "increase_speed",
"signatur... | 3 | stack_v2_sparse_classes_30k_val_000474 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的设置
- def initialize_dynamic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的设置
- def initialize_dynamic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置
<|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __ini... | aee7092ad4af2e61996ddab5fa29f62b79174b14 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.fleet_drop_factor = 100
self.bullet_width = 6
self.bullet_height =... | the_stack_v2_python_sparse | 12/alien_invasion/settings.py | Zandela/Python_Work | train | 0 |
bb6461316648e8f55465aca457bb4b121ca710cb | [
"self.ensure_one()\nexpense_obj = self.env['hr.expense']\njournal = self.env['account.journal']\nif emp_contribution + company_contribution > expense_total:\n raise UserError(_('Contribution should be either greater then 0 or should not be more that total expense'))\nif not product_id:\n raise UserError(_('Pl... | <|body_start_0|>
self.ensure_one()
expense_obj = self.env['hr.expense']
journal = self.env['account.journal']
if emp_contribution + company_contribution > expense_total:
raise UserError(_('Contribution should be either greater then 0 or should not be more that total expense')... | HrExpensePayment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HrExpensePayment:
def generate_expense_payment(self, catch_obj, description, emp_contribution, company_contribution, payment_mode, name, product_id, expense_total):
"""Generate total expense of employee. return: created expense ID"""
<|body_0|>
def redirect_to_expense(self, ... | stack_v2_sparse_classes_36k_train_001899 | 5,650 | no_license | [
{
"docstring": "Generate total expense of employee. return: created expense ID",
"name": "generate_expense_payment",
"signature": "def generate_expense_payment(self, catch_obj, description, emp_contribution, company_contribution, payment_mode, name, product_id, expense_total)"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_train_003146 | Implement the Python class `HrExpensePayment` described below.
Class description:
Implement the HrExpensePayment class.
Method signatures and docstrings:
- def generate_expense_payment(self, catch_obj, description, emp_contribution, company_contribution, payment_mode, name, product_id, expense_total): Generate total ... | Implement the Python class `HrExpensePayment` described below.
Class description:
Implement the HrExpensePayment class.
Method signatures and docstrings:
- def generate_expense_payment(self, catch_obj, description, emp_contribution, company_contribution, payment_mode, name, product_id, expense_total): Generate total ... | 59cd55edd536ce9feb85c772e163a2560c224cad | <|skeleton|>
class HrExpensePayment:
def generate_expense_payment(self, catch_obj, description, emp_contribution, company_contribution, payment_mode, name, product_id, expense_total):
"""Generate total expense of employee. return: created expense ID"""
<|body_0|>
def redirect_to_expense(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HrExpensePayment:
def generate_expense_payment(self, catch_obj, description, emp_contribution, company_contribution, payment_mode, name, product_id, expense_total):
"""Generate total expense of employee. return: created expense ID"""
self.ensure_one()
expense_obj = self.env['hr.expense... | the_stack_v2_python_sparse | hr_expense_payment/models/hr_expense.py | zamzamintl/SLNEE-MASTER | train | 0 |
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