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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a16403fcf0714da7e9242cdb04eeba1445888cdb | [
"if n < 0:\n n = -n\n x = 1 / x\nres = 1\nwhile n:\n if n & 1:\n res *= x\n x *= x\n n >>= 1\nreturn res",
"if n == 0:\n return 1\nif n < 0:\n return 1 / self.myPow1(x, -n)\nif n & 1:\n return x * self.myPow1(x * x, n >> 1)\nelse:\n return self.myPow1(x * x, n >> 1)"
] | <|body_start_0|>
if n < 0:
n = -n
x = 1 / x
res = 1
while n:
if n & 1:
res *= x
x *= x
n >>= 1
return res
<|end_body_0|>
<|body_start_1|>
if n == 0:
return 1
if n < 0:
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def myPow(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_0|>
def myPow1(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n < 0:
n = -n
... | stack_v2_sparse_classes_36k_train_022400 | 714 | no_license | [
{
"docstring": ":type x: float :type n: int :rtype: float",
"name": "myPow",
"signature": "def myPow(self, x, n)"
},
{
"docstring": ":type x: float :type n: int :rtype: float",
"name": "myPow1",
"signature": "def myPow1(self, x, n)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000603 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow(self, x, n): :type x: float :type n: int :rtype: float
- def myPow1(self, x, n): :type x: float :type n: int :rtype: float | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow(self, x, n): :type x: float :type n: int :rtype: float
- def myPow1(self, x, n): :type x: float :type n: int :rtype: float
<|skeleton|>
class Solution:
def myPow(... | f1d780b7e8b91b4df704651514018143c6931f9d | <|skeleton|>
class Solution:
def myPow(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_0|>
def myPow1(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def myPow(self, x, n):
""":type x: float :type n: int :rtype: float"""
if n < 0:
n = -n
x = 1 / x
res = 1
while n:
if n & 1:
res *= x
x *= x
n >>= 1
return res
def myPow1(self, x,... | the_stack_v2_python_sparse | ProgramForLeetCode/LeetCode/50_myPow.py | DQDH/Algorithm_Code | train | 0 | |
b80a62e3d9cf9b64f7eea7804561c77a30029a91 | [
"result = [0 for _ in range(len(nums))]\nlow = 0\nhigh = len(result) - 1\nfor x in nums:\n if x & 1 == 1:\n result[low] = x\n low += 1\n else:\n result[high] = x\n high -= 1\nreturn result",
"low = 0\nhigh = len(nums) - 1\nwhile low < high:\n if nums[low] & 1 == 0 and nums[hig... | <|body_start_0|>
result = [0 for _ in range(len(nums))]
low = 0
high = len(result) - 1
for x in nums:
if x & 1 == 1:
result[low] = x
low += 1
else:
result[high] = x
high -= 1
return result
<|e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def exchange(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def exchange2(self, nums):
"""双端指针"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = [0 for _ in range(len(nums))]
low = 0
high = len... | stack_v2_sparse_classes_36k_train_022401 | 1,548 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "exchange",
"signature": "def exchange(self, nums)"
},
{
"docstring": "双端指针",
"name": "exchange2",
"signature": "def exchange2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000656 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange(self, nums): :type nums: List[int] :rtype: List[int]
- def exchange2(self, nums): 双端指针 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange(self, nums): :type nums: List[int] :rtype: List[int]
- def exchange2(self, nums): 双端指针
<|skeleton|>
class Solution:
def exchange(self, nums):
""":type ... | 837957ea22aa07ce28a6c23ea0419bd2011e1f88 | <|skeleton|>
class Solution:
def exchange(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def exchange2(self, nums):
"""双端指针"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def exchange(self, nums):
""":type nums: List[int] :rtype: List[int]"""
result = [0 for _ in range(len(nums))]
low = 0
high = len(result) - 1
for x in nums:
if x & 1 == 1:
result[low] = x
low += 1
else:
... | the_stack_v2_python_sparse | 剑指/二刷/调整数组顺序使奇数位于偶数前面_S.py | 2226171237/Algorithmpractice | train | 0 | |
e24f77a7ec4c63a0c1ac7d553b9bc43a5beba174 | [
"b = x.max()\ny = np.exp(x - b)\nx = (y.T / y.sum(axis=1)).T\nself.x = x\nreturn x",
"dx = np.zeros(dout.shape, dtype=np.float64)\nfor i in range(0, dout.shape[0]):\n delta = self.x[i, :].reshape(-1, 1)\n delta = np.diagflat(delta) - np.dot(delta, delta.T)\n dx[i, :] = np.dot(delta, dout[i, :])\nreturn d... | <|body_start_0|>
b = x.max()
y = np.exp(x - b)
x = (y.T / y.sum(axis=1)).T
self.x = x
return x
<|end_body_0|>
<|body_start_1|>
dx = np.zeros(dout.shape, dtype=np.float64)
for i in range(0, dout.shape[0]):
delta = self.x[i, :].reshape(-1, 1)
... | Softmax activation module. | SoftMaxModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftMaxModule:
"""Softmax activation module."""
def forward(self, x):
"""Forward pass. Args: x: input to the module Returns: out: output of the module"""
<|body_0|>
def backward(self, dout):
"""Backward pass. Args: dout: gradients of the previous modul Returns: d... | stack_v2_sparse_classes_36k_train_022402 | 3,644 | no_license | [
{
"docstring": "Forward pass. Args: x: input to the module Returns: out: output of the module",
"name": "forward",
"signature": "def forward(self, x)"
},
{
"docstring": "Backward pass. Args: dout: gradients of the previous modul Returns: dx: gradients with respect to the input of the module",
... | 2 | stack_v2_sparse_classes_30k_train_001182 | Implement the Python class `SoftMaxModule` described below.
Class description:
Softmax activation module.
Method signatures and docstrings:
- def forward(self, x): Forward pass. Args: x: input to the module Returns: out: output of the module
- def backward(self, dout): Backward pass. Args: dout: gradients of the prev... | Implement the Python class `SoftMaxModule` described below.
Class description:
Softmax activation module.
Method signatures and docstrings:
- def forward(self, x): Forward pass. Args: x: input to the module Returns: out: output of the module
- def backward(self, dout): Backward pass. Args: dout: gradients of the prev... | 19e8ac762cedda82410a0dda676edaf659c55d6a | <|skeleton|>
class SoftMaxModule:
"""Softmax activation module."""
def forward(self, x):
"""Forward pass. Args: x: input to the module Returns: out: output of the module"""
<|body_0|>
def backward(self, dout):
"""Backward pass. Args: dout: gradients of the previous modul Returns: d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SoftMaxModule:
"""Softmax activation module."""
def forward(self, x):
"""Forward pass. Args: x: input to the module Returns: out: output of the module"""
b = x.max()
y = np.exp(x - b)
x = (y.T / y.sum(axis=1)).T
self.x = x
return x
def backward(self, d... | the_stack_v2_python_sparse | assignment_1/code/modules.py | RancyChepchirchir/dl-assignments | train | 0 |
f148e743bb4383215204e8589fc5d3e0870ec399 | [
"company = ShopCompanyService.get_by_id(id)\ncontact_list = ShopCompanyContactService.get_by_company_id(id)\ncompany['contact_list'] = contact_list\nreturn api_response(data=company)",
"parsed_data = self.parsed_data\ntry:\n ShopCompanyService.update_shop_company_by_id(id, **parsed_data)\nexcept ClientError as... | <|body_start_0|>
company = ShopCompanyService.get_by_id(id)
contact_list = ShopCompanyContactService.get_by_company_id(id)
company['contact_list'] = contact_list
return api_response(data=company)
<|end_body_0|>
<|body_start_1|>
parsed_data = self.parsed_data
try:
... | ShopCompanyApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShopCompanyApi:
def get(self, id):
"""根据ID查询公司"""
<|body_0|>
def put(self, id):
"""根据ID修改公司信息"""
<|body_1|>
def delete(self, id):
"""根据ID删除公司"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
company = ShopCompanyService.get_by_id... | stack_v2_sparse_classes_36k_train_022403 | 8,580 | no_license | [
{
"docstring": "根据ID查询公司",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "根据ID修改公司信息",
"name": "put",
"signature": "def put(self, id)"
},
{
"docstring": "根据ID删除公司",
"name": "delete",
"signature": "def delete(self, id)"
}
] | 3 | stack_v2_sparse_classes_30k_train_000446 | Implement the Python class `ShopCompanyApi` described below.
Class description:
Implement the ShopCompanyApi class.
Method signatures and docstrings:
- def get(self, id): 根据ID查询公司
- def put(self, id): 根据ID修改公司信息
- def delete(self, id): 根据ID删除公司 | Implement the Python class `ShopCompanyApi` described below.
Class description:
Implement the ShopCompanyApi class.
Method signatures and docstrings:
- def get(self, id): 根据ID查询公司
- def put(self, id): 根据ID修改公司信息
- def delete(self, id): 根据ID删除公司
<|skeleton|>
class ShopCompanyApi:
def get(self, id):
"""根据... | e87f98f5fbe42c465473d83cb2a535209a8e8287 | <|skeleton|>
class ShopCompanyApi:
def get(self, id):
"""根据ID查询公司"""
<|body_0|>
def put(self, id):
"""根据ID修改公司信息"""
<|body_1|>
def delete(self, id):
"""根据ID删除公司"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShopCompanyApi:
def get(self, id):
"""根据ID查询公司"""
company = ShopCompanyService.get_by_id(id)
contact_list = ShopCompanyContactService.get_by_company_id(id)
company['contact_list'] = contact_list
return api_response(data=company)
def put(self, id):
"""根据ID修改... | the_stack_v2_python_sparse | creole/wsgi/api/v1/endpoint/shop.py | Creoles/creole | train | 0 | |
2838e391f1189495be50e9eade0a4e7cb23b20d4 | [
"QTreeWidgetItem.__init__(self, parent)\nself.siz = len(key)\nself.setText(0, unicode(key, 'utf8'))\nself.setKeyFont(type=type)",
"font = QFont()\nif type == 2:\n font.setItalic(True)\n self.setFont(0, font)\nelif type == 0 and self.siz > 0:\n self.setForeground(0, QColor(Qt.darkBlue))\n self.setIcon(... | <|body_start_0|>
QTreeWidgetItem.__init__(self, parent)
self.siz = len(key)
self.setText(0, unicode(key, 'utf8'))
self.setKeyFont(type=type)
<|end_body_0|>
<|body_start_1|>
font = QFont()
if type == 2:
font.setItalic(True)
self.setFont(0, font)
... | Treewidget item for key | KeyItem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeyItem:
"""Treewidget item for key"""
def __init__(self, key, parent=None, type=None):
"""Constructs KeyItem widget item @param key: @type key: @param parent: @type parent: @param type: @type type:"""
<|body_0|>
def setKeyFont(self, type):
"""Set the font of the... | stack_v2_sparse_classes_36k_train_022404 | 9,389 | permissive | [
{
"docstring": "Constructs KeyItem widget item @param key: @type key: @param parent: @type parent: @param type: @type type:",
"name": "__init__",
"signature": "def __init__(self, key, parent=None, type=None)"
},
{
"docstring": "Set the font of the key @param type: @type type:",
"name": "setK... | 2 | null | Implement the Python class `KeyItem` described below.
Class description:
Treewidget item for key
Method signatures and docstrings:
- def __init__(self, key, parent=None, type=None): Constructs KeyItem widget item @param key: @type key: @param parent: @type parent: @param type: @type type:
- def setKeyFont(self, type)... | Implement the Python class `KeyItem` described below.
Class description:
Treewidget item for key
Method signatures and docstrings:
- def __init__(self, key, parent=None, type=None): Constructs KeyItem widget item @param key: @type key: @param parent: @type parent: @param type: @type type:
- def setKeyFont(self, type)... | 66f65dd6e4a48909120f63239f630147c733df3f | <|skeleton|>
class KeyItem:
"""Treewidget item for key"""
def __init__(self, key, parent=None, type=None):
"""Constructs KeyItem widget item @param key: @type key: @param parent: @type parent: @param type: @type type:"""
<|body_0|>
def setKeyFont(self, type):
"""Set the font of the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KeyItem:
"""Treewidget item for key"""
def __init__(self, key, parent=None, type=None):
"""Constructs KeyItem widget item @param key: @type key: @param parent: @type parent: @param type: @type type:"""
QTreeWidgetItem.__init__(self, parent)
self.siz = len(key)
self.setText... | the_stack_v2_python_sparse | ServerExplorer/ReleaseNotes.py | ExtensiveAutomation/extensiveautomation-appclient | train | 2 |
dc8c925bad73a2b18c14df33c8f168e8f0e51155 | [
"rc_mock = cros_build_lib_unittest.RunCommandMock()\nnoarch = 'target=foo\\ncategory=bla\\n'\nrc_mock.SetDefaultCmdResult(output=noarch)\nwith rc_mock:\n self.assertEqual(None, toolchain.GetArchForTarget('fake_target'))\namd64arch = 'arch=amd64\\ntarget=foo\\n'\nrc_mock.SetDefaultCmdResult(output=amd64arch)\nwit... | <|body_start_0|>
rc_mock = cros_build_lib_unittest.RunCommandMock()
noarch = 'target=foo\ncategory=bla\n'
rc_mock.SetDefaultCmdResult(output=noarch)
with rc_mock:
self.assertEqual(None, toolchain.GetArchForTarget('fake_target'))
amd64arch = 'arch=amd64\ntarget=foo\n'
... | Tests for lib.toolchain. | ToolchainTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToolchainTest:
"""Tests for lib.toolchain."""
def testArchForToolchain(self):
"""Tests that we correctly parse crossdev's output."""
<|body_0|>
def testReadsBoardToolchains(self, find_overlays_mock):
"""Tests that we correctly parse toolchain configs for an overl... | stack_v2_sparse_classes_36k_train_022405 | 2,556 | permissive | [
{
"docstring": "Tests that we correctly parse crossdev's output.",
"name": "testArchForToolchain",
"signature": "def testArchForToolchain(self)"
},
{
"docstring": "Tests that we correctly parse toolchain configs for an overlay stack.",
"name": "testReadsBoardToolchains",
"signature": "de... | 2 | null | Implement the Python class `ToolchainTest` described below.
Class description:
Tests for lib.toolchain.
Method signatures and docstrings:
- def testArchForToolchain(self): Tests that we correctly parse crossdev's output.
- def testReadsBoardToolchains(self, find_overlays_mock): Tests that we correctly parse toolchain... | Implement the Python class `ToolchainTest` described below.
Class description:
Tests for lib.toolchain.
Method signatures and docstrings:
- def testArchForToolchain(self): Tests that we correctly parse crossdev's output.
- def testReadsBoardToolchains(self, find_overlays_mock): Tests that we correctly parse toolchain... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ToolchainTest:
"""Tests for lib.toolchain."""
def testArchForToolchain(self):
"""Tests that we correctly parse crossdev's output."""
<|body_0|>
def testReadsBoardToolchains(self, find_overlays_mock):
"""Tests that we correctly parse toolchain configs for an overl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ToolchainTest:
"""Tests for lib.toolchain."""
def testArchForToolchain(self):
"""Tests that we correctly parse crossdev's output."""
rc_mock = cros_build_lib_unittest.RunCommandMock()
noarch = 'target=foo\ncategory=bla\n'
rc_mock.SetDefaultCmdResult(output=noarch)
... | the_stack_v2_python_sparse | third_party/chromite/lib/toolchain_unittest.py | metux/chromium-suckless | train | 5 |
619f2cff6e97da7a8707040c73527b2da13c2190 | [
"if len(xcols) == 0 or xcols is None:\n return 0.0\nsample_size = len(df.index)\ndf1 = df.copy()\ndf1 = df1.groupby(xcols)[xcols].size()\ndf1 = df1.apply(lambda x: x / sample_size)\nlocal_ent = -df1 * np.log(df1 + 1e-07)\nall_ent = local_ent.sum()\nif verbose:\n print('\\nprobs for ', xcols)\n print(df1)\n... | <|body_start_0|>
if len(xcols) == 0 or xcols is None:
return 0.0
sample_size = len(df.index)
df1 = df.copy()
df1 = df1.groupby(xcols)[xcols].size()
df1 = df1.apply(lambda x: x / sample_size)
local_ent = -df1 * np.log(df1 + 1e-07)
all_ent = local_ent.su... | This class calculates classical (not quantum yet) entropy, conditional information (CI), mutual information (MI) and conditional mutual info ( CMI) from a dataframe (hence, from empirical data, not from the true distributions of a bnet). logs's in entropies are base e, natural logs Error in entropy is ln(n+1) - ln(n) ... | DataEntropy | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataEntropy:
"""This class calculates classical (not quantum yet) entropy, conditional information (CI), mutual information (MI) and conditional mutual info ( CMI) from a dataframe (hence, from empirical data, not from the true distributions of a bnet). logs's in entropies are base e, natural log... | stack_v2_sparse_classes_36k_train_022406 | 5,703 | permissive | [
{
"docstring": "Returns the entropy H(x) where x is given by the list of columns xcols in the dataframe df. Parameters ---------- df : pandas.DataFrame dataframe for which entropy is calculated xcols : list[str] list of column names in df. The x in H(x) verbose : bool If True, print extra info in console. Retur... | 4 | stack_v2_sparse_classes_30k_train_007065 | Implement the Python class `DataEntropy` described below.
Class description:
This class calculates classical (not quantum yet) entropy, conditional information (CI), mutual information (MI) and conditional mutual info ( CMI) from a dataframe (hence, from empirical data, not from the true distributions of a bnet). logs... | Implement the Python class `DataEntropy` described below.
Class description:
This class calculates classical (not quantum yet) entropy, conditional information (CI), mutual information (MI) and conditional mutual info ( CMI) from a dataframe (hence, from empirical data, not from the true distributions of a bnet). logs... | 5b4a3055ea14c2ee9c80c339f759fe2b9c8c51e2 | <|skeleton|>
class DataEntropy:
"""This class calculates classical (not quantum yet) entropy, conditional information (CI), mutual information (MI) and conditional mutual info ( CMI) from a dataframe (hence, from empirical data, not from the true distributions of a bnet). logs's in entropies are base e, natural log... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataEntropy:
"""This class calculates classical (not quantum yet) entropy, conditional information (CI), mutual information (MI) and conditional mutual info ( CMI) from a dataframe (hence, from empirical data, not from the true distributions of a bnet). logs's in entropies are base e, natural logs Error in en... | the_stack_v2_python_sparse | shannon_info_theory/DataEntropy.py | artiste-qb-net/quantum-fog | train | 95 |
b19efcf993d2b8a09d399f1690d2f8a72a300d54 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn DeviceEnrollmentWindowsHelloForBusinessConfiguration()",
"from .device_enrollment_configuration import DeviceEnrollmentConfiguration\nfrom .enablement import Enablement\nfrom .windows_hello_for_business_pin_usage import WindowsHelloFor... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return DeviceEnrollmentWindowsHelloForBusinessConfiguration()
<|end_body_0|>
<|body_start_1|>
from .device_enrollment_configuration import DeviceEnrollmentConfiguration
from .enablement import ... | Windows Hello for Business settings lets users access their devices using a gesture, such as biometric authentication, or a PIN. Configure settings for enrolled Windows 10, Windows 10 Mobile and later. | DeviceEnrollmentWindowsHelloForBusinessConfiguration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceEnrollmentWindowsHelloForBusinessConfiguration:
"""Windows Hello for Business settings lets users access their devices using a gesture, such as biometric authentication, or a PIN. Configure settings for enrolled Windows 10, Windows 10 Mobile and later."""
def create_from_discriminator_... | stack_v2_sparse_classes_36k_train_022407 | 7,971 | 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: DeviceEnrollmentWindowsHelloForBusinessConfiguration",
"name": "create_from_discriminator_value",
"signature... | 3 | null | Implement the Python class `DeviceEnrollmentWindowsHelloForBusinessConfiguration` described below.
Class description:
Windows Hello for Business settings lets users access their devices using a gesture, such as biometric authentication, or a PIN. Configure settings for enrolled Windows 10, Windows 10 Mobile and later.... | Implement the Python class `DeviceEnrollmentWindowsHelloForBusinessConfiguration` described below.
Class description:
Windows Hello for Business settings lets users access their devices using a gesture, such as biometric authentication, or a PIN. Configure settings for enrolled Windows 10, Windows 10 Mobile and later.... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class DeviceEnrollmentWindowsHelloForBusinessConfiguration:
"""Windows Hello for Business settings lets users access their devices using a gesture, such as biometric authentication, or a PIN. Configure settings for enrolled Windows 10, Windows 10 Mobile and later."""
def create_from_discriminator_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeviceEnrollmentWindowsHelloForBusinessConfiguration:
"""Windows Hello for Business settings lets users access their devices using a gesture, such as biometric authentication, or a PIN. Configure settings for enrolled Windows 10, Windows 10 Mobile and later."""
def create_from_discriminator_value(parse_n... | the_stack_v2_python_sparse | msgraph/generated/models/device_enrollment_windows_hello_for_business_configuration.py | microsoftgraph/msgraph-sdk-python | train | 135 |
9d103301eba188e9e5902485ef494b2c32d4e38e | [
"if not RUNNING_TESTS:\n print(f'Instantiating a FalseCeleryApp for {an_function.__name__}.')\nself.an_function = an_function",
"if not RUNNING_TESTS:\n print(f'task declared, args: {args}, kwargs:{kwargs}')\nreturn FalseCeleryApp",
"if not RUNNING_TESTS:\n print(f'apply_async running, args:{args}, kwa... | <|body_start_0|>
if not RUNNING_TESTS:
print(f'Instantiating a FalseCeleryApp for {an_function.__name__}.')
self.an_function = an_function
<|end_body_0|>
<|body_start_1|>
if not RUNNING_TESTS:
print(f'task declared, args: {args}, kwargs:{kwargs}')
return FalseCel... | Class that mimics enough functionality of a Celery app for us to be able to execute our celery infrastructure from the shell, single-threaded, without queuing. | FalseCeleryApp | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FalseCeleryApp:
"""Class that mimics enough functionality of a Celery app for us to be able to execute our celery infrastructure from the shell, single-threaded, without queuing."""
def __init__(self, an_function: callable):
"""at instantiation (aka when used as a decorator) stash th... | stack_v2_sparse_classes_36k_train_022408 | 9,856 | permissive | [
{
"docstring": "at instantiation (aka when used as a decorator) stash the function we wrap",
"name": "__init__",
"signature": "def __init__(self, an_function: callable)"
},
{
"docstring": "Our pattern is that we wrap our celery functions in the task decorator. This function executes at-import-ti... | 3 | stack_v2_sparse_classes_30k_train_010862 | Implement the Python class `FalseCeleryApp` described below.
Class description:
Class that mimics enough functionality of a Celery app for us to be able to execute our celery infrastructure from the shell, single-threaded, without queuing.
Method signatures and docstrings:
- def __init__(self, an_function: callable):... | Implement the Python class `FalseCeleryApp` described below.
Class description:
Class that mimics enough functionality of a Celery app for us to be able to execute our celery infrastructure from the shell, single-threaded, without queuing.
Method signatures and docstrings:
- def __init__(self, an_function: callable):... | cc25a60bfa8ccab953c55ac82f68d160ab00652a | <|skeleton|>
class FalseCeleryApp:
"""Class that mimics enough functionality of a Celery app for us to be able to execute our celery infrastructure from the shell, single-threaded, without queuing."""
def __init__(self, an_function: callable):
"""at instantiation (aka when used as a decorator) stash th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FalseCeleryApp:
"""Class that mimics enough functionality of a Celery app for us to be able to execute our celery infrastructure from the shell, single-threaded, without queuing."""
def __init__(self, an_function: callable):
"""at instantiation (aka when used as a decorator) stash the function we... | the_stack_v2_python_sparse | libs/celery_control.py | onnela-lab/beiwe-backend | train | 68 |
4d620b8a55919ed2257ee6eaca57727c67c037ec | [
"if not root:\n return 'null,'\nstack = [root]\nss = [str(root.val) + ',']\ns = ''\nwhile stack:\n p = stack.pop()\n s += ss.pop()\n if p:\n if p.right:\n stack.append(p.right)\n ss.append(str(p.right.val) + ',')\n else:\n stack.append(None)\n ss... | <|body_start_0|>
if not root:
return 'null,'
stack = [root]
ss = [str(root.val) + ',']
s = ''
while stack:
p = stack.pop()
s += ss.pop()
if p:
if p.right:
stack.append(p.right)
... | 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_022409 | 2,873 | 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 | null | 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... | 276d2137a929e41120c2e8a3a8e4d09023a2abd5 | <|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 'null,'
stack = [root]
ss = [str(root.val) + ',']
s = ''
while stack:
p = stack.pop()
s += ss.pop()
if... | the_stack_v2_python_sparse | 449.序列化和反序列化二叉搜索树.py | kangkang59812/LeetCode-python | train | 0 | |
f6c7c3f08e3e0cae17e1175d5f664ee3ee17ca5c | [
"super().__init__(parent)\nself._entry = entry\nself._log_entry_available_signal = log_entry_available_signal\nobserver = _TesterListener(entry=entry, log_entry_available_signal=log_entry_available_signal)\nself._tester = Tester(configuration=cast(RootConfiguration, entry.configuration), yes_we_hack_api_clients_fac... | <|body_start_0|>
super().__init__(parent)
self._entry = entry
self._log_entry_available_signal = log_entry_available_signal
observer = _TesterListener(entry=entry, log_entry_available_signal=log_entry_available_signal)
self._tester = Tester(configuration=cast(RootConfiguration, e... | A thread for testing configuration. | TesterThread | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TesterThread:
"""A thread for testing configuration."""
def __init__(self, parent: QObject, entry: RootConfigurationEntry, log_entry_available_signal: SignalInstance):
"""Initialize self. Args: parent: a parent widget entry: a root configuration entry log_entry_available_signal: a si... | stack_v2_sparse_classes_36k_train_022410 | 5,260 | no_license | [
{
"docstring": "Initialize self. Args: parent: a parent widget entry: a root configuration entry log_entry_available_signal: a signal that receive events from the thread",
"name": "__init__",
"signature": "def __init__(self, parent: QObject, entry: RootConfigurationEntry, log_entry_available_signal: Sig... | 2 | stack_v2_sparse_classes_30k_train_005288 | Implement the Python class `TesterThread` described below.
Class description:
A thread for testing configuration.
Method signatures and docstrings:
- def __init__(self, parent: QObject, entry: RootConfigurationEntry, log_entry_available_signal: SignalInstance): Initialize self. Args: parent: a parent widget entry: a ... | Implement the Python class `TesterThread` described below.
Class description:
A thread for testing configuration.
Method signatures and docstrings:
- def __init__(self, parent: QObject, entry: RootConfigurationEntry, log_entry_available_signal: SignalInstance): Initialize self. Args: parent: a parent widget entry: a ... | 3da2161c3c9e0652c2cfc78ab514359bcf2e436b | <|skeleton|>
class TesterThread:
"""A thread for testing configuration."""
def __init__(self, parent: QObject, entry: RootConfigurationEntry, log_entry_available_signal: SignalInstance):
"""Initialize self. Args: parent: a parent widget entry: a root configuration entry log_entry_available_signal: a si... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TesterThread:
"""A thread for testing configuration."""
def __init__(self, parent: QObject, entry: RootConfigurationEntry, log_entry_available_signal: SignalInstance):
"""Initialize self. Args: parent: a parent widget entry: a root configuration entry log_entry_available_signal: a signal that rec... | the_stack_v2_python_sparse | ywh2bt/gui/widgets/thread/tester.py | yeswehack/ywh2bugtracker | train | 10 |
6c6ac057635eebd1df8111204b50153a6dd79733 | [
"n = len(heights)\nif n == 0:\n return 0\narea = 0\nfor i in range(n):\n curr_height = heights[i]\n left = i\n while left > 0 and heights[left - 1] >= curr_height:\n left -= 1\n right = i\n while right < n - 1 and heights[right + 1] >= curr_height:\n right += 1\n curr_area = (righ... | <|body_start_0|>
n = len(heights)
if n == 0:
return 0
area = 0
for i in range(n):
curr_height = heights[i]
left = i
while left > 0 and heights[left - 1] >= curr_height:
left -= 1
right = i
while right... | OfficialSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfficialSolution:
def largest_rectangle_area(self, heights: List[int]) -> int:
"""暴力解法（两边扩散）。"""
<|body_0|>
def largest_rectangle_area_2(self, heights: List[int]) -> int:
"""单调栈（递增）。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(heights)
... | stack_v2_sparse_classes_36k_train_022411 | 4,345 | no_license | [
{
"docstring": "暴力解法（两边扩散）。",
"name": "largest_rectangle_area",
"signature": "def largest_rectangle_area(self, heights: List[int]) -> int"
},
{
"docstring": "单调栈（递增）。",
"name": "largest_rectangle_area_2",
"signature": "def largest_rectangle_area_2(self, heights: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_009508 | Implement the Python class `OfficialSolution` described below.
Class description:
Implement the OfficialSolution class.
Method signatures and docstrings:
- def largest_rectangle_area(self, heights: List[int]) -> int: 暴力解法（两边扩散）。
- def largest_rectangle_area_2(self, heights: List[int]) -> int: 单调栈（递增）。 | Implement the Python class `OfficialSolution` described below.
Class description:
Implement the OfficialSolution class.
Method signatures and docstrings:
- def largest_rectangle_area(self, heights: List[int]) -> int: 暴力解法（两边扩散）。
- def largest_rectangle_area_2(self, heights: List[int]) -> int: 单调栈（递增）。
<|skeleton|>
c... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class OfficialSolution:
def largest_rectangle_area(self, heights: List[int]) -> int:
"""暴力解法（两边扩散）。"""
<|body_0|>
def largest_rectangle_area_2(self, heights: List[int]) -> int:
"""单调栈（递增）。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OfficialSolution:
def largest_rectangle_area(self, heights: List[int]) -> int:
"""暴力解法（两边扩散）。"""
n = len(heights)
if n == 0:
return 0
area = 0
for i in range(n):
curr_height = heights[i]
left = i
while left > 0 and heights... | the_stack_v2_python_sparse | 0084_largest-rectangle-in-histogram.py | Nigirimeshi/leetcode | train | 0 | |
a3f22992479fd8bb4c69e2294966637bbf79436c | [
"self.id = id\nif id:\n self.id = id\nelse:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects",
"if list_dictionaries:\n dict = json.dumps(list_dictionaries)\n return dict\nreturn '[]'",
"new = []\nopen_name = cls.__name__ + '.json'\nif list_objs is not None:\n for obj in list_objs:\n ... | <|body_start_0|>
self.id = id
if id:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries:
dict = json.dumps(list_dictionaries)
return dict
return '[... | First class | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""First class"""
def __init__(self, id=None):
"""class constructor"""
<|body_0|>
def to_json_string(list_dictionaries):
"""sharing data representation"""
<|body_1|>
def save_to_file(cls, list_objs):
"""writes the JSON string representa... | stack_v2_sparse_classes_36k_train_022412 | 1,660 | no_license | [
{
"docstring": "class constructor",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "sharing data representation",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "writes the JSON string representat... | 5 | stack_v2_sparse_classes_30k_train_007514 | Implement the Python class `Base` described below.
Class description:
First class
Method signatures and docstrings:
- def __init__(self, id=None): class constructor
- def to_json_string(list_dictionaries): sharing data representation
- def save_to_file(cls, list_objs): writes the JSON string representation of list_ob... | Implement the Python class `Base` described below.
Class description:
First class
Method signatures and docstrings:
- def __init__(self, id=None): class constructor
- def to_json_string(list_dictionaries): sharing data representation
- def save_to_file(cls, list_objs): writes the JSON string representation of list_ob... | 46c04cdc7b76afbd79c650ff258f85aef7d2d5fe | <|skeleton|>
class Base:
"""First class"""
def __init__(self, id=None):
"""class constructor"""
<|body_0|>
def to_json_string(list_dictionaries):
"""sharing data representation"""
<|body_1|>
def save_to_file(cls, list_objs):
"""writes the JSON string representa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base:
"""First class"""
def __init__(self, id=None):
"""class constructor"""
self.id = id
if id:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
def to_json_string(list_dictionaries):
"""sharing data re... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | Leidysalda/holbertonschool-higher_level_programming | train | 0 |
82bb39dbb7391161dd61f37312a2e56b4923b0f9 | [
"if self.request.get('continue') != '' and self.request.get('commit') == 'Yes':\n self.redirect(self.request.get('continue').encode('ascii', 'ignore'), self.response)\nelse:\n self.redirect('/', self.response)",
"continue_url = urllib.unquote(self.request.get('continue'))\nurl_match = re.search(self.CONTINU... | <|body_start_0|>
if self.request.get('continue') != '' and self.request.get('commit') == 'Yes':
self.redirect(self.request.get('continue').encode('ascii', 'ignore'), self.response)
else:
self.redirect('/', self.response)
<|end_body_0|>
<|body_start_1|>
continue_url = url... | Class to handle requests to /users/confirm and /users/verify pages. | LoginVerify | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginVerify:
"""Class to handle requests to /users/confirm and /users/verify pages."""
def post(self):
"""Handler for POST requests."""
<|body_0|>
def get(self):
"""Handler for GET requests."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if sel... | stack_v2_sparse_classes_36k_train_022413 | 37,207 | permissive | [
{
"docstring": "Handler for POST requests.",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Handler for GET requests.",
"name": "get",
"signature": "def get(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012960 | Implement the Python class `LoginVerify` described below.
Class description:
Class to handle requests to /users/confirm and /users/verify pages.
Method signatures and docstrings:
- def post(self): Handler for POST requests.
- def get(self): Handler for GET requests. | Implement the Python class `LoginVerify` described below.
Class description:
Class to handle requests to /users/confirm and /users/verify pages.
Method signatures and docstrings:
- def post(self): Handler for POST requests.
- def get(self): Handler for GET requests.
<|skeleton|>
class LoginVerify:
"""Class to ha... | aa36e8dfaa295d53bec616ed07f91ec8c02fa4e1 | <|skeleton|>
class LoginVerify:
"""Class to handle requests to /users/confirm and /users/verify pages."""
def post(self):
"""Handler for POST requests."""
<|body_0|>
def get(self):
"""Handler for GET requests."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginVerify:
"""Class to handle requests to /users/confirm and /users/verify pages."""
def post(self):
"""Handler for POST requests."""
if self.request.get('continue') != '' and self.request.get('commit') == 'Yes':
self.redirect(self.request.get('continue').encode('ascii', 'ig... | the_stack_v2_python_sparse | AppDashboard/dashboard.py | shatterednirvana/appscale | train | 6 |
00994d2f261e4ddc3044ce0393f2d3aff7762dee | [
"u_id = self.token_data.get('userId')\ntry:\n nickname = self.parse_body('nickname', '')\n company = self.parse_body('company', '')\n customer_type = self.parse_body('customerType', 0)\n contact = self.parse_body('contact', '')\n contact_type = self.parse_body('contactType', 1)\nexcept ValueError:\n ... | <|body_start_0|>
u_id = self.token_data.get('userId')
try:
nickname = self.parse_body('nickname', '')
company = self.parse_body('company', '')
customer_type = self.parse_body('customerType', 0)
contact = self.parse_body('contact', '')
contact_t... | 用户基本资料 | InfoHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InfoHandler:
"""用户基本资料"""
def post(self, *args, **kwargs):
"""更新"""
<|body_0|>
def get(self, *args, **kwargs):
"""获取"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
u_id = self.token_data.get('userId')
try:
nickname = self.pa... | stack_v2_sparse_classes_36k_train_022414 | 18,392 | no_license | [
{
"docstring": "更新",
"name": "post",
"signature": "def post(self, *args, **kwargs)"
},
{
"docstring": "获取",
"name": "get",
"signature": "def get(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017553 | Implement the Python class `InfoHandler` described below.
Class description:
用户基本资料
Method signatures and docstrings:
- def post(self, *args, **kwargs): 更新
- def get(self, *args, **kwargs): 获取 | Implement the Python class `InfoHandler` described below.
Class description:
用户基本资料
Method signatures and docstrings:
- def post(self, *args, **kwargs): 更新
- def get(self, *args, **kwargs): 获取
<|skeleton|>
class InfoHandler:
"""用户基本资料"""
def post(self, *args, **kwargs):
"""更新"""
<|body_0|>
... | e31b674d38ce62c0ee30bf3dda4462060631974e | <|skeleton|>
class InfoHandler:
"""用户基本资料"""
def post(self, *args, **kwargs):
"""更新"""
<|body_0|>
def get(self, *args, **kwargs):
"""获取"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InfoHandler:
"""用户基本资料"""
def post(self, *args, **kwargs):
"""更新"""
u_id = self.token_data.get('userId')
try:
nickname = self.parse_body('nickname', '')
company = self.parse_body('company', '')
customer_type = self.parse_body('customerType', 0)
... | the_stack_v2_python_sparse | taotao/api/handlers/operateHandler.py | leolinf/tornado-demo | train | 3 |
e69a253017953ed1d8f8f62ad2bb5d04f8c3b6e5 | [
"if rest_filter is None:\n rest_filter = dict()\nrest_filter['genepanel_name', 'genepanel_version'] = [(gp.name, gp.version) for gp in user.group.genepanels]\nreturn self.list_query(session, annotationjob.AnnotationJob, schemas.AnnotationJobSchema(), rest_filter=rest_filter, order_by=annotationjob.AnnotationJob.... | <|body_start_0|>
if rest_filter is None:
rest_filter = dict()
rest_filter['genepanel_name', 'genepanel_version'] = [(gp.name, gp.version) for gp in user.group.genepanels]
return self.list_query(session, annotationjob.AnnotationJob, schemas.AnnotationJobSchema(), rest_filter=rest_filt... | AnnotationJobList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnnotationJobList:
def get(self, session, rest_filter=None, page=None, per_page=None, user=None):
"""Lists annotation jobs in the system. --- summary: List annotation jobs tags: - Import"""
<|body_0|>
def post(self, session, data=None, user=None):
"""Creates an annot... | stack_v2_sparse_classes_36k_train_022415 | 3,720 | permissive | [
{
"docstring": "Lists annotation jobs in the system. --- summary: List annotation jobs tags: - Import",
"name": "get",
"signature": "def get(self, session, rest_filter=None, page=None, per_page=None, user=None)"
},
{
"docstring": "Creates an annotation job in the system. --- summary: Create anno... | 2 | null | Implement the Python class `AnnotationJobList` described below.
Class description:
Implement the AnnotationJobList class.
Method signatures and docstrings:
- def get(self, session, rest_filter=None, page=None, per_page=None, user=None): Lists annotation jobs in the system. --- summary: List annotation jobs tags: - Im... | Implement the Python class `AnnotationJobList` described below.
Class description:
Implement the AnnotationJobList class.
Method signatures and docstrings:
- def get(self, session, rest_filter=None, page=None, per_page=None, user=None): Lists annotation jobs in the system. --- summary: List annotation jobs tags: - Im... | e38631d302611a143c9baaa684bcbd014d9734e4 | <|skeleton|>
class AnnotationJobList:
def get(self, session, rest_filter=None, page=None, per_page=None, user=None):
"""Lists annotation jobs in the system. --- summary: List annotation jobs tags: - Import"""
<|body_0|>
def post(self, session, data=None, user=None):
"""Creates an annot... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AnnotationJobList:
def get(self, session, rest_filter=None, page=None, per_page=None, user=None):
"""Lists annotation jobs in the system. --- summary: List annotation jobs tags: - Import"""
if rest_filter is None:
rest_filter = dict()
rest_filter['genepanel_name', 'genepane... | the_stack_v2_python_sparse | src/api/v1/resources/annotationjob.py | dabble-of-devops-consulting/ella | train | 0 | |
e58cd79f1d25175c204ec9244c29c2bf0ebdf6da | [
"self.index = index\nself.source_name = source_name\nself.file_extension = file_extension\nself.sourcetype = sourcetype\nself.host = host",
"fields_str = None\nfor field_name, field_value in fields_dict.items():\n if fields_str is None:\n fields_str = ''\n elif fields_str is not None:\n fields... | <|body_start_0|>
self.index = index
self.source_name = source_name
self.file_extension = file_extension
self.sourcetype = sourcetype
self.host = host
<|end_body_0|>
<|body_start_1|>
fields_str = None
for field_name, field_value in fields_dict.items():
... | The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly). | StashNewWriter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StashNewWriter:
"""The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly)."""
def __init__(self, index, source_name, file_extension='.stash_new', sourcetype=None, host=None):
"""Constructor... | stack_v2_sparse_classes_36k_train_022416 | 13,683 | permissive | [
{
"docstring": "Constructor for the stash writer,=. Arguments: index -- the index to send the events to source_name -- the search that is being used to generate the results file_extension -- the extension of the stash file (usually .stash_new) sourcetype -- the sourcetype to use for the event host -- the host t... | 5 | stack_v2_sparse_classes_30k_train_006502 | Implement the Python class `StashNewWriter` described below.
Class description:
The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly).
Method signatures and docstrings:
- def __init__(self, index, source_name, file_extensi... | Implement the Python class `StashNewWriter` described below.
Class description:
The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly).
Method signatures and docstrings:
- def __init__(self, index, source_name, file_extensi... | 9c1027f1b1a58d30973256412fb72a6fe6bf029c | <|skeleton|>
class StashNewWriter:
"""The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly)."""
def __init__(self, index, source_name, file_extension='.stash_new', sourcetype=None, host=None):
"""Constructor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StashNewWriter:
"""The Stash writer class provides a mechanism for writing out events that will be processed by Splunk as stash events (and summary indexed accordingly)."""
def __init__(self, index, source_name, file_extension='.stash_new', sourcetype=None, host=None):
"""Constructor for the stas... | the_stack_v2_python_sparse | src/bin/network_tools_app/event_writer.py | LukeMurphey/splunk-network-tools | train | 6 |
31f8d6cc31229840b78f926eafbc35ca467ac21e | [
"model = getattr(self, '_model', None)\nif model is None:\n raise RuntimeError('Model is not set. Please call set_model() first.')\nreturn model",
"if not isinstance(model, nn.Module):\n raise TypeError('model must be an instance of nn.Module')\nself._model = model"
] | <|body_start_0|>
model = getattr(self, '_model', None)
if model is None:
raise RuntimeError('Model is not set. Please call set_model() first.')
return model
<|end_body_0|>
<|body_start_1|>
if not isinstance(model, nn.Module):
raise TypeError('model must be an ins... | Basic wrapper of generated model. Lightning modules used in NNI should inherit this class. It's a subclass of ``pytorch_lightning.LightningModule``. See https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html See :class:`SupervisedLearningModule` as an example. | LightningModule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LightningModule:
"""Basic wrapper of generated model. Lightning modules used in NNI should inherit this class. It's a subclass of ``pytorch_lightning.LightningModule``. See https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html See :class:`SupervisedLearningModule` as an ... | stack_v2_sparse_classes_36k_train_022417 | 22,209 | permissive | [
{
"docstring": "The inner model (architecture) to train / evaluate. It will be only available after calling :meth:`set_model`.",
"name": "model",
"signature": "def model(self) -> nn.Module"
},
{
"docstring": "Set the inner model (architecture) to train / evaluate. As there is no explicit method ... | 2 | null | Implement the Python class `LightningModule` described below.
Class description:
Basic wrapper of generated model. Lightning modules used in NNI should inherit this class. It's a subclass of ``pytorch_lightning.LightningModule``. See https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html See :... | Implement the Python class `LightningModule` described below.
Class description:
Basic wrapper of generated model. Lightning modules used in NNI should inherit this class. It's a subclass of ``pytorch_lightning.LightningModule``. See https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html See :... | b84d25bec15ece54bf1703b1acb15d9f8919f656 | <|skeleton|>
class LightningModule:
"""Basic wrapper of generated model. Lightning modules used in NNI should inherit this class. It's a subclass of ``pytorch_lightning.LightningModule``. See https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html See :class:`SupervisedLearningModule` as an ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LightningModule:
"""Basic wrapper of generated model. Lightning modules used in NNI should inherit this class. It's a subclass of ``pytorch_lightning.LightningModule``. See https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html See :class:`SupervisedLearningModule` as an example."""
... | the_stack_v2_python_sparse | nni/nas/evaluator/pytorch/lightning.py | Eurus-Holmes/nni | train | 3 |
b99ef3f10853928c3655a3ac4350334d6f6eb16b | [
"self.CHC = Abstract_Channel_Creator\nself.em_gain = ccd_operation_mode['em_gain']\nself.binn = ccd_operation_mode['binn']\nself.t_exp = ccd_operation_mode['t_exp']\nself.image_size = ccd_operation_mode['image_size']\nself.ccd_gain = ccd_gain",
"t_exp = self.t_exp\nem_gain = self.em_gain\nccd_gain = self.ccd_gain... | <|body_start_0|>
self.CHC = Abstract_Channel_Creator
self.em_gain = ccd_operation_mode['em_gain']
self.binn = ccd_operation_mode['binn']
self.t_exp = ccd_operation_mode['t_exp']
self.image_size = ccd_operation_mode['image_size']
self.ccd_gain = ccd_gain
<|end_body_0|>
<|... | Point Spread Function Class. This class creates the image of the star. The PSF of the object is based on a 2D gaussian distribution. Initially, the star flux is calculated using the library Flux_Calculation. Over this flux, the contribution of the atmosphere, the telescope, and the SPARC4 are considered as a function o... | Point_Spread_Function | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Point_Spread_Function:
"""Point Spread Function Class. This class creates the image of the star. The PSF of the object is based on a 2D gaussian distribution. Initially, the star flux is calculated using the library Flux_Calculation. Over this flux, the contribution of the atmosphere, the telesco... | stack_v2_sparse_classes_36k_train_022418 | 3,709 | permissive | [
{
"docstring": "Initialize the class.",
"name": "__init__",
"signature": "def __init__(self, Abstract_Channel_Creator, ccd_operation_mode, ccd_gain)"
},
{
"docstring": "Create the star point spread function. Parameters ---------- star_coordinates: tuple XY star coordinates in the image. gaussian... | 2 | stack_v2_sparse_classes_30k_train_011865 | Implement the Python class `Point_Spread_Function` described below.
Class description:
Point Spread Function Class. This class creates the image of the star. The PSF of the object is based on a 2D gaussian distribution. Initially, the star flux is calculated using the library Flux_Calculation. Over this flux, the cont... | Implement the Python class `Point_Spread_Function` described below.
Class description:
Point Spread Function Class. This class creates the image of the star. The PSF of the object is based on a 2D gaussian distribution. Initially, the star flux is calculated using the library Flux_Calculation. Over this flux, the cont... | 6f75bbfd52a7b6684ad04002f9818b4d8e7d2c96 | <|skeleton|>
class Point_Spread_Function:
"""Point Spread Function Class. This class creates the image of the star. The PSF of the object is based on a 2D gaussian distribution. Initially, the star flux is calculated using the library Flux_Calculation. Over this flux, the contribution of the atmosphere, the telesco... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Point_Spread_Function:
"""Point Spread Function Class. This class creates the image of the star. The PSF of the object is based on a 2D gaussian distribution. Initially, the star flux is calculated using the library Flux_Calculation. Over this flux, the contribution of the atmosphere, the telescope, and the S... | the_stack_v2_python_sparse | AIS/Point_Spread_Function/point_spread_function.py | juliotux/AIS | train | 0 |
a7f2cfc2a00feec3a4656898afc46df083090709 | [
"self.clerk = clerk\nself.name = atr\nself.fkey = fkey\nself.linksetAttr = linksetAttr",
"if name == self.name:\n box.removeInjector(self.inject)\n box.removeObserver(self.inject)\n childType = self.linksetAttr.type\n backName = self.linksetAttr.back\n theLinkSet = getattr(box.private, name)\n i... | <|body_start_0|>
self.clerk = clerk
self.name = atr
self.fkey = fkey
self.linksetAttr = linksetAttr
<|end_body_0|>
<|body_start_1|>
if name == self.name:
box.removeInjector(self.inject)
box.removeObserver(self.inject)
childType = self.linksetA... | LinkSetInjector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkSetInjector:
def __init__(self, atr, clerk, linksetAttr, fkey):
"""atr: the attribute name for the linkset clerk: a clerk fclass: the type of the linkset fkey: column name of the foreign key that points back to the parent"""
<|body_0|>
def inject(self, box, name, value=U... | stack_v2_sparse_classes_36k_train_022419 | 20,272 | no_license | [
{
"docstring": "atr: the attribute name for the linkset clerk: a clerk fclass: the type of the linkset fkey: column name of the foreign key that points back to the parent",
"name": "__init__",
"signature": "def __init__(self, atr, clerk, linksetAttr, fkey)"
},
{
"docstring": "box: the Strongbox ... | 2 | stack_v2_sparse_classes_30k_train_006896 | Implement the Python class `LinkSetInjector` described below.
Class description:
Implement the LinkSetInjector class.
Method signatures and docstrings:
- def __init__(self, atr, clerk, linksetAttr, fkey): atr: the attribute name for the linkset clerk: a clerk fclass: the type of the linkset fkey: column name of the f... | Implement the Python class `LinkSetInjector` described below.
Class description:
Implement the LinkSetInjector class.
Method signatures and docstrings:
- def __init__(self, atr, clerk, linksetAttr, fkey): atr: the attribute name for the linkset clerk: a clerk fclass: the type of the linkset fkey: column name of the f... | 1ea55a754a7568b8df2bab297a8036c0b3a671e0 | <|skeleton|>
class LinkSetInjector:
def __init__(self, atr, clerk, linksetAttr, fkey):
"""atr: the attribute name for the linkset clerk: a clerk fclass: the type of the linkset fkey: column name of the foreign key that points back to the parent"""
<|body_0|>
def inject(self, box, name, value=U... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkSetInjector:
def __init__(self, atr, clerk, linksetAttr, fkey):
"""atr: the attribute name for the linkset clerk: a clerk fclass: the type of the linkset fkey: column name of the foreign key that points back to the parent"""
self.clerk = clerk
self.name = atr
self.fkey = fk... | the_stack_v2_python_sparse | code/clerks.py | tangentstorm/workshop | train | 0 | |
6c952ce6ef498b3213542d60cb26c72a2df90e6d | [
"self.x = x\nself.fs = fs\nself.N = len(self.x)\nself.K = K",
"X = np.zeros(self.N, dtype=np.complex)\nE = np.zeros(self.N)\nX_K = np.zeros(self.K, dtype=np.complex)\nindex = np.zeros(self.K)\nfor k in range(self.N):\n for n in range(self.N):\n X[k] = X[k] + 1 / np.sqrt(self.N) * self.x[n] * np.exp(-1j ... | <|body_start_0|>
self.x = x
self.fs = fs
self.N = len(self.x)
self.K = K
<|end_body_0|>
<|body_start_1|>
X = np.zeros(self.N, dtype=np.complex)
E = np.zeros(self.N)
X_K = np.zeros(self.K, dtype=np.complex)
index = np.zeros(self.K)
for k in range(s... | idft Inverse Discrete Fourier transform. | dft_K_q16 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class dft_K_q16:
"""idft Inverse Discrete Fourier transform."""
def __init__(self, x, fs, K):
""":param X: Input DFT X :param fs: Input integer fs contains the sample frequency :param K: Input positive integer that determines the number of coeffients used to calculate the iDFT."""
... | stack_v2_sparse_classes_36k_train_022420 | 25,417 | no_license | [
{
"docstring": ":param X: Input DFT X :param fs: Input integer fs contains the sample frequency :param K: Input positive integer that determines the number of coeffients used to calculate the iDFT.",
"name": "__init__",
"signature": "def __init__(self, x, fs, K)"
},
{
"docstring": "\\\\\\\\\\\\ ... | 2 | stack_v2_sparse_classes_30k_train_016995 | Implement the Python class `dft_K_q16` described below.
Class description:
idft Inverse Discrete Fourier transform.
Method signatures and docstrings:
- def __init__(self, x, fs, K): :param X: Input DFT X :param fs: Input integer fs contains the sample frequency :param K: Input positive integer that determines the num... | Implement the Python class `dft_K_q16` described below.
Class description:
idft Inverse Discrete Fourier transform.
Method signatures and docstrings:
- def __init__(self, x, fs, K): :param X: Input DFT X :param fs: Input integer fs contains the sample frequency :param K: Input positive integer that determines the num... | b72322cfc6d81c996117cea2160ee312da62d3ed | <|skeleton|>
class dft_K_q16:
"""idft Inverse Discrete Fourier transform."""
def __init__(self, x, fs, K):
""":param X: Input DFT X :param fs: Input integer fs contains the sample frequency :param K: Input positive integer that determines the number of coeffients used to calculate the iDFT."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class dft_K_q16:
"""idft Inverse Discrete Fourier transform."""
def __init__(self, x, fs, K):
""":param X: Input DFT X :param fs: Input integer fs contains the sample frequency :param K: Input positive integer that determines the number of coeffients used to calculate the iDFT."""
self.x = x
... | the_stack_v2_python_sparse | Inverse Discrete Fourier Transform/iDFT_main.py | FG-14/Signals-and-Information-Processing-DSP- | train | 0 |
db6c850e25ed5f3dbe5e6da7f7a36fc517ab6936 | [
"self.left = left\nself.right = right\nself.data = data",
"if self.data is None:\n self.data = val\n return\nif val <= self.data:\n if self.left is None:\n self.left = BinaryTreeNode(data=val)\n else:\n self.left.insert(val)\nelif self.right is None:\n self.right = BinaryTreeNode(data... | <|body_start_0|>
self.left = left
self.right = right
self.data = data
<|end_body_0|>
<|body_start_1|>
if self.data is None:
self.data = val
return
if val <= self.data:
if self.left is None:
self.left = BinaryTreeNode(data=val)
... | A class representation of binary tree node | BinaryTreeNode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryTreeNode:
"""A class representation of binary tree node"""
def __init__(self, left=None, right=None, data=None):
"""Initializes a binary tree"""
<|body_0|>
def insert(self, val):
"""Inserts a value (data in Node object) in order"""
<|body_1|>
d... | stack_v2_sparse_classes_36k_train_022421 | 2,378 | no_license | [
{
"docstring": "Initializes a binary tree",
"name": "__init__",
"signature": "def __init__(self, left=None, right=None, data=None)"
},
{
"docstring": "Inserts a value (data in Node object) in order",
"name": "insert",
"signature": "def insert(self, val)"
},
{
"docstring": "Checks... | 6 | stack_v2_sparse_classes_30k_train_001612 | Implement the Python class `BinaryTreeNode` described below.
Class description:
A class representation of binary tree node
Method signatures and docstrings:
- def __init__(self, left=None, right=None, data=None): Initializes a binary tree
- def insert(self, val): Inserts a value (data in Node object) in order
- def c... | Implement the Python class `BinaryTreeNode` described below.
Class description:
A class representation of binary tree node
Method signatures and docstrings:
- def __init__(self, left=None, right=None, data=None): Initializes a binary tree
- def insert(self, val): Inserts a value (data in Node object) in order
- def c... | 0e8b528207faa44977f5b9d446d45d13c4fb430d | <|skeleton|>
class BinaryTreeNode:
"""A class representation of binary tree node"""
def __init__(self, left=None, right=None, data=None):
"""Initializes a binary tree"""
<|body_0|>
def insert(self, val):
"""Inserts a value (data in Node object) in order"""
<|body_1|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryTreeNode:
"""A class representation of binary tree node"""
def __init__(self, left=None, right=None, data=None):
"""Initializes a binary tree"""
self.left = left
self.right = right
self.data = data
def insert(self, val):
"""Inserts a value (data in Node ... | the_stack_v2_python_sparse | data_structures/tree/binary_tree_node.py | marcus-grant/python-cs | train | 0 |
a07b79b600b6f5af6a7b3d446c8dcc03234771a0 | [
"if not prices:\n return 0\nmaxValue = 0\nfor i in range(1, len(prices)):\n num = prices[-i]\n validScope = prices[:len(prices) - i]\n if num - min(validScope) > 0:\n maxValue = max(maxValue, num - min(validScope))\nreturn maxValue",
"if not prices or len(prices) == 1:\n return 0\ndif_list =... | <|body_start_0|>
if not prices:
return 0
maxValue = 0
for i in range(1, len(prices)):
num = prices[-i]
validScope = prices[:len(prices) - i]
if num - min(validScope) > 0:
maxValue = max(maxValue, num - min(validScope))
retur... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit_TLE(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
"""transfer the question to max subarray :type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022422 | 1,028 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit_TLE",
"signature": "def maxProfit_TLE(self, prices)"
},
{
"docstring": "transfer the question to max subarray :type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
}... | 2 | stack_v2_sparse_classes_30k_train_021460 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_TLE(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): transfer the question to max subarray :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_TLE(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): transfer the question to max subarray :type prices: List[int] :rtype: int
<|s... | 5436c2e67a80a58021eab309704e3fc2ba9755b5 | <|skeleton|>
class Solution:
def maxProfit_TLE(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
"""transfer the question to max subarray :type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit_TLE(self, prices):
""":type prices: List[int] :rtype: int"""
if not prices:
return 0
maxValue = 0
for i in range(1, len(prices)):
num = prices[-i]
validScope = prices[:len(prices) - i]
if num - min(validSco... | the_stack_v2_python_sparse | 121. Best Time to Buy and Sell Stock.py | sheldonzhao/LeetCodeFighting | train | 0 | |
edea30083027e1b0df41cf9d3ffffe637b3b5c65 | [
"QObject.__init__(self, ui)\nself.__ui = ui\nself.__action = None\nself.__translator = None\nself.__loadTranslator()\nself.__initAction()",
"e5App().getObject('ToolbarManager').addAction(self.__action, 'Tools')\nmenu = self.__ui.getMenu('extras')\nmenu.addAction(self.__action)\nreturn (None, True)",
"e5App().ge... | <|body_start_0|>
QObject.__init__(self, ui)
self.__ui = ui
self.__action = None
self.__translator = None
self.__loadTranslator()
self.__initAction()
<|end_body_0|>
<|body_start_1|>
e5App().getObject('ToolbarManager').addAction(self.__action, 'Tools')
menu... | Class implementing the virtualenv wizard plug-in. | WizardVirtualenvPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WizardVirtualenvPlugin:
"""Class implementing the virtualenv wizard plug-in."""
def __init__(self, ui):
"""Constructor @param ui reference to the user interface object (UI.UserInterface)"""
<|body_0|>
def activate(self):
"""Public method to activate this plug-in.... | stack_v2_sparse_classes_36k_train_022423 | 4,443 | no_license | [
{
"docstring": "Constructor @param ui reference to the user interface object (UI.UserInterface)",
"name": "__init__",
"signature": "def __init__(self, ui)"
},
{
"docstring": "Public method to activate this plug-in. @return tuple of None and activation status (boolean)",
"name": "activate",
... | 6 | null | Implement the Python class `WizardVirtualenvPlugin` described below.
Class description:
Class implementing the virtualenv wizard plug-in.
Method signatures and docstrings:
- def __init__(self, ui): Constructor @param ui reference to the user interface object (UI.UserInterface)
- def activate(self): Public method to a... | Implement the Python class `WizardVirtualenvPlugin` described below.
Class description:
Class implementing the virtualenv wizard plug-in.
Method signatures and docstrings:
- def __init__(self, ui): Constructor @param ui reference to the user interface object (UI.UserInterface)
- def activate(self): Public method to a... | 3df0c805225a8d4f2709565d7eda4e07a050c986 | <|skeleton|>
class WizardVirtualenvPlugin:
"""Class implementing the virtualenv wizard plug-in."""
def __init__(self, ui):
"""Constructor @param ui reference to the user interface object (UI.UserInterface)"""
<|body_0|>
def activate(self):
"""Public method to activate this plug-in.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WizardVirtualenvPlugin:
"""Class implementing the virtualenv wizard plug-in."""
def __init__(self, ui):
"""Constructor @param ui reference to the user interface object (UI.UserInterface)"""
QObject.__init__(self, ui)
self.__ui = ui
self.__action = None
self.__trans... | the_stack_v2_python_sparse | eric6/.eric6/eric6plugins/PluginWizardVirtualenv.py | metamarcdw/.dotfiles | train | 0 |
1a1419043d1ebd510aa252d4ce92c044319aa886 | [
"if self.mode in (EFFECT_AUTO, EFFECT_EXPERT):\n if self.style in ('FOLLOW_VIDEO', 'FOLLOW_AUDIO'):\n return powerstate in ('On', None)\n if self.style == 'OFF':\n return False\n return True\nif self.mode == EFFECT_MODE:\n if self.style == 'internal':\n return powerstate in ('On', N... | <|body_start_0|>
if self.mode in (EFFECT_AUTO, EFFECT_EXPERT):
if self.style in ('FOLLOW_VIDEO', 'FOLLOW_AUDIO'):
return powerstate in ('On', None)
if self.style == 'OFF':
return False
return True
if self.mode == EFFECT_MODE:
... | Data class describing the ambilight effect. | AmbilightEffect | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AmbilightEffect:
"""Data class describing the ambilight effect."""
def is_on(self, powerstate) -> bool:
"""Check whether the ambilight is considered on."""
<|body_0|>
def is_valid(self) -> bool:
"""Validate the effect configuration."""
<|body_1|>
def... | stack_v2_sparse_classes_36k_train_022424 | 13,195 | permissive | [
{
"docstring": "Check whether the ambilight is considered on.",
"name": "is_on",
"signature": "def is_on(self, powerstate) -> bool"
},
{
"docstring": "Validate the effect configuration.",
"name": "is_valid",
"signature": "def is_valid(self) -> bool"
},
{
"docstring": "Create Ambi... | 4 | null | Implement the Python class `AmbilightEffect` described below.
Class description:
Data class describing the ambilight effect.
Method signatures and docstrings:
- def is_on(self, powerstate) -> bool: Check whether the ambilight is considered on.
- def is_valid(self) -> bool: Validate the effect configuration.
- def fro... | Implement the Python class `AmbilightEffect` described below.
Class description:
Data class describing the ambilight effect.
Method signatures and docstrings:
- def is_on(self, powerstate) -> bool: Check whether the ambilight is considered on.
- def is_valid(self) -> bool: Validate the effect configuration.
- def fro... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AmbilightEffect:
"""Data class describing the ambilight effect."""
def is_on(self, powerstate) -> bool:
"""Check whether the ambilight is considered on."""
<|body_0|>
def is_valid(self) -> bool:
"""Validate the effect configuration."""
<|body_1|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AmbilightEffect:
"""Data class describing the ambilight effect."""
def is_on(self, powerstate) -> bool:
"""Check whether the ambilight is considered on."""
if self.mode in (EFFECT_AUTO, EFFECT_EXPERT):
if self.style in ('FOLLOW_VIDEO', 'FOLLOW_AUDIO'):
return p... | the_stack_v2_python_sparse | homeassistant/components/philips_js/light.py | home-assistant/core | train | 35,501 |
b1b1579a8d77c0e7385b02f61a623292f6ebc4ef | [
"n = len(s)\nvisited, res = (set(), set())\nfor i in range(n - 9):\n tmp = s[i:i + 10]\n if tmp in visited:\n res.add(tmp)\n visited.add(tmp)\nreturn list(res)",
"L, n = (10, len(s))\nif n <= L:\n return []\ndic = {'A': 0, 'C': 1, 'G': 2, 'T': 3}\nnums = [dic[s[i]] for i in range(n)]\nvisited, ... | <|body_start_0|>
n = len(s)
visited, res = (set(), set())
for i in range(n - 9):
tmp = s[i:i + 10]
if tmp in visited:
res.add(tmp)
visited.add(tmp)
return list(res)
<|end_body_0|>
<|body_start_1|>
L, n = (10, len(s))
if... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findRepeatedDnaSequences1(self, s: str) -> List[str]:
"""思路：hash @param s: @return:"""
<|body_0|>
def findRepeatedDnaSequences2(self, s: str) -> List[str]:
"""思路：Rabin-Karp @param s: @return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022425 | 2,391 | no_license | [
{
"docstring": "思路：hash @param s: @return:",
"name": "findRepeatedDnaSequences1",
"signature": "def findRepeatedDnaSequences1(self, s: str) -> List[str]"
},
{
"docstring": "思路：Rabin-Karp @param s: @return:",
"name": "findRepeatedDnaSequences2",
"signature": "def findRepeatedDnaSequences2... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findRepeatedDnaSequences1(self, s: str) -> List[str]: 思路：hash @param s: @return:
- def findRepeatedDnaSequences2(self, s: str) -> List[str]: 思路：Rabin-Karp @param s: @return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findRepeatedDnaSequences1(self, s: str) -> List[str]: 思路：hash @param s: @return:
- def findRepeatedDnaSequences2(self, s: str) -> List[str]: 思路：Rabin-Karp @param s: @return:
... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def findRepeatedDnaSequences1(self, s: str) -> List[str]:
"""思路：hash @param s: @return:"""
<|body_0|>
def findRepeatedDnaSequences2(self, s: str) -> List[str]:
"""思路：Rabin-Karp @param s: @return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findRepeatedDnaSequences1(self, s: str) -> List[str]:
"""思路：hash @param s: @return:"""
n = len(s)
visited, res = (set(), set())
for i in range(n - 9):
tmp = s[i:i + 10]
if tmp in visited:
res.add(tmp)
visited.add... | the_stack_v2_python_sparse | LeetCode/字符串/Rabin-Karp/187. 重复的DNA序列.py | yiming1012/MyLeetCode | train | 2 | |
558d56f7b12cc69848044feba82b7a4fb63f1586 | [
"self.attrs = {'history': '2018-12-10Z: StaGE Decoupler', 'title': 'Temperature on UK 2 km Standard Grid', 'source': 'Met Office Unified Model'}\nself.cube = set_up_variable_cube(np.ones((3, 11, 11), dtype=np.float32), spatial_grid='equalarea', standard_grid_metadata='uk_det', attributes=self.attrs)\nself.cube_1d =... | <|body_start_0|>
self.attrs = {'history': '2018-12-10Z: StaGE Decoupler', 'title': 'Temperature on UK 2 km Standard Grid', 'source': 'Met Office Unified Model'}
self.cube = set_up_variable_cube(np.ones((3, 11, 11), dtype=np.float32), spatial_grid='equalarea', standard_grid_metadata='uk_det', attributes=... | Tests for the remove_cube_halo function | Test_remove_cube_halo | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_remove_cube_halo:
"""Tests for the remove_cube_halo function"""
def setUp(self):
"""Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart."""
<|body_0|>
def test_basic(self):
"""Test function ret... | stack_v2_sparse_classes_36k_train_022426 | 25,212 | permissive | [
{
"docstring": "Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test function returns a cube with expected attributes and shape",
"name": "test_basic",
... | 3 | null | Implement the Python class `Test_remove_cube_halo` described below.
Class description:
Tests for the remove_cube_halo function
Method signatures and docstrings:
- def setUp(self): Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart.
- def test_basic(sel... | Implement the Python class `Test_remove_cube_halo` described below.
Class description:
Tests for the remove_cube_halo function
Method signatures and docstrings:
- def setUp(self): Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart.
- def test_basic(sel... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_remove_cube_halo:
"""Tests for the remove_cube_halo function"""
def setUp(self):
"""Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart."""
<|body_0|>
def test_basic(self):
"""Test function ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_remove_cube_halo:
"""Tests for the remove_cube_halo function"""
def setUp(self):
"""Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart."""
self.attrs = {'history': '2018-12-10Z: StaGE Decoupler', 'title': 'Temperature ... | the_stack_v2_python_sparse | improver_tests/utilities/test_pad_spatial.py | metoppv/improver | train | 101 |
668caf3beee50d8e05323253dd442794bc8ac9e5 | [
"url = '/api/itsystems/'\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, 200)\nself.assertNotContains(response, self.it2.name)\nself.assertNotContains(response, self.it_dec.name)",
"url = '/api/itsystems/?all'\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, 200)\n... | <|body_start_0|>
url = '/api/itsystems/'
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
self.assertNotContains(response, self.it2.name)
self.assertNotContains(response, self.it_dec.name)
<|end_body_0|>
<|body_start_1|>
url = '/api/itsystems/?... | ITSystemResourceTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ITSystemResourceTestCase:
def test_list(self):
"""Test the ITSystemResource list response"""
<|body_0|>
def test_list_all(self):
"""Test the ITSystemResource list response with all param"""
<|body_1|>
def test_list_filter(self):
"""Test the ITSys... | stack_v2_sparse_classes_36k_train_022427 | 2,926 | permissive | [
{
"docstring": "Test the ITSystemResource list response",
"name": "test_list",
"signature": "def test_list(self)"
},
{
"docstring": "Test the ITSystemResource list response with all param",
"name": "test_list_all",
"signature": "def test_list_all(self)"
},
{
"docstring": "Test th... | 3 | null | Implement the Python class `ITSystemResourceTestCase` described below.
Class description:
Implement the ITSystemResourceTestCase class.
Method signatures and docstrings:
- def test_list(self): Test the ITSystemResource list response
- def test_list_all(self): Test the ITSystemResource list response with all param
- d... | Implement the Python class `ITSystemResourceTestCase` described below.
Class description:
Implement the ITSystemResourceTestCase class.
Method signatures and docstrings:
- def test_list(self): Test the ITSystemResource list response
- def test_list_all(self): Test the ITSystemResource list response with all param
- d... | 4d5caceba69cac7f59b63745a0f52322004df2eb | <|skeleton|>
class ITSystemResourceTestCase:
def test_list(self):
"""Test the ITSystemResource list response"""
<|body_0|>
def test_list_all(self):
"""Test the ITSystemResource list response with all param"""
<|body_1|>
def test_list_filter(self):
"""Test the ITSys... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ITSystemResourceTestCase:
def test_list(self):
"""Test the ITSystemResource list response"""
url = '/api/itsystems/'
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
self.assertNotContains(response, self.it2.name)
self.assertNotContain... | the_stack_v2_python_sparse | registers/test_api.py | bryceprince0/it-assets | train | 0 | |
3940690f65fb79bd3277b1d959e6c57abed7ff3e | [
"deq = collections.deque()\nif root is None:\n return ''\nelse:\n deq.appendleft(root)\n s = ''\n while deq:\n curoot = deq.popleft()\n s = s + '*' + str(curoot.val)\n if curoot.left:\n deq.append(curoot.left)\n if curoot.right:\n deq.append(curoot.right... | <|body_start_0|>
deq = collections.deque()
if root is None:
return ''
else:
deq.appendleft(root)
s = ''
while deq:
curoot = deq.popleft()
s = s + '*' + str(curoot.val)
if curoot.left:
... | Codec | [
"MIT"
] | 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|>
deq = collecti... | stack_v2_sparse_classes_36k_train_022428 | 1,832 | permissive | [
{
"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_012425 | 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... | f828642d01a708515fbc0b6fc38d01251db36dd3 | <|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."""
deq = collections.deque()
if root is None:
return ''
else:
deq.appendleft(root)
s = ''
while deq:
curoot = deq.popleft()
... | the_stack_v2_python_sparse | Medium/Serialize and Deserialize BST.py | KoushikDeb007/LeetCode | train | 0 | |
c5fbdbd6432380ce8f71c5e2cd5716f6a17a6263 | [
"super(Up, self).__init__()\nself.in_ch = in_ch\nself.out_ch = out_ch\nself.up = nn.ConvTranspose2d(in_ch, in_ch // 2, 2, stride=2)\nself.conv = DoubleConv(in_ch, out_ch)",
"x1 = self.up(x1)\ndiff_y = x2.size()[2] - x1.size()[2]\ndiff_x = x2.size()[3] - x1.size()[3]\nx1 = F.pad(x1, (diff_x // 2, diff_x - diff_x /... | <|body_start_0|>
super(Up, self).__init__()
self.in_ch = in_ch
self.out_ch = out_ch
self.up = nn.ConvTranspose2d(in_ch, in_ch // 2, 2, stride=2)
self.conv = DoubleConv(in_ch, out_ch)
<|end_body_0|>
<|body_start_1|>
x1 = self.up(x1)
diff_y = x2.size()[2] - x1.size... | UNet upscaling. | Up | [
"LicenseRef-scancode-protobuf",
"MPL-2.0",
"MIT",
"BSD-3-Clause",
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Up:
"""UNet upscaling."""
def __init__(self, in_ch, out_ch):
"""Initialize. Args: in_ch: number of input channels out_ch: number of output channels"""
<|body_0|>
def forward(self, x1, x2):
"""Run forward."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022429 | 2,875 | permissive | [
{
"docstring": "Initialize. Args: in_ch: number of input channels out_ch: number of output channels",
"name": "__init__",
"signature": "def __init__(self, in_ch, out_ch)"
},
{
"docstring": "Run forward.",
"name": "forward",
"signature": "def forward(self, x1, x2)"
}
] | 2 | null | Implement the Python class `Up` described below.
Class description:
UNet upscaling.
Method signatures and docstrings:
- def __init__(self, in_ch, out_ch): Initialize. Args: in_ch: number of input channels out_ch: number of output channels
- def forward(self, x1, x2): Run forward. | Implement the Python class `Up` described below.
Class description:
UNet upscaling.
Method signatures and docstrings:
- def __init__(self, in_ch, out_ch): Initialize. Args: in_ch: number of input channels out_ch: number of output channels
- def forward(self, x1, x2): Run forward.
<|skeleton|>
class Up:
"""UNet u... | bd73b749a9ea1b92dbcdd07e639752101d769fc0 | <|skeleton|>
class Up:
"""UNet upscaling."""
def __init__(self, in_ch, out_ch):
"""Initialize. Args: in_ch: number of input channels out_ch: number of output channels"""
<|body_0|>
def forward(self, x1, x2):
"""Run forward."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Up:
"""UNet upscaling."""
def __init__(self, in_ch, out_ch):
"""Initialize. Args: in_ch: number of input channels out_ch: number of output channels"""
super(Up, self).__init__()
self.in_ch = in_ch
self.out_ch = out_ch
self.up = nn.ConvTranspose2d(in_ch, in_ch // 2,... | the_stack_v2_python_sparse | openfl-workspace/torch_unet_kvasir/src/pt_unet_parts.py | PDuckworth/openfl | train | 0 |
70aea394f0fb3011e15cedd38e33307cf82c6e89 | [
"dico = {'dir': directory}\nmagic.log.info(_(u'create remote directory %(dir)s...') % dico)\ncmd = 'mkdir -p %(dir)s' % dico\nres = self._exec_command(cmd)\ncmd = 'chmod 0700 %(dir)s' % dico\nres = self._exec_command(cmd)\nmagic.log.info(_(u'returns %s'), res[0])\nreturn res",
"cmd = 'rm -rf %s' % self.proxy_dir\... | <|body_start_0|>
dico = {'dir': directory}
magic.log.info(_(u'create remote directory %(dir)s...') % dico)
cmd = 'mkdir -p %(dir)s' % dico
res = self._exec_command(cmd)
cmd = 'chmod 0700 %(dir)s' % dico
res = self._exec_command(cmd)
magic.log.info(_(u'returns %s')... | Definition of a RCP server. | RCPServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RCPServer:
"""Definition of a RCP server."""
def _create_dir(self, directory):
"""Create a directory on the server."""
<|body_0|>
def delete_proxy_dir(self):
"""Erase the proxy_dir directory on the server."""
<|body_1|>
def _copyoneto(self, src, conv... | stack_v2_sparse_classes_36k_train_022430 | 4,960 | no_license | [
{
"docstring": "Create a directory on the server.",
"name": "_create_dir",
"signature": "def _create_dir(self, directory)"
},
{
"docstring": "Erase the proxy_dir directory on the server.",
"name": "delete_proxy_dir",
"signature": "def delete_proxy_dir(self)"
},
{
"docstring": "Co... | 4 | null | Implement the Python class `RCPServer` described below.
Class description:
Definition of a RCP server.
Method signatures and docstrings:
- def _create_dir(self, directory): Create a directory on the server.
- def delete_proxy_dir(self): Erase the proxy_dir directory on the server.
- def _copyoneto(self, src, convert=... | Implement the Python class `RCPServer` described below.
Class description:
Definition of a RCP server.
Method signatures and docstrings:
- def _create_dir(self, directory): Create a directory on the server.
- def delete_proxy_dir(self): Erase the proxy_dir directory on the server.
- def _copyoneto(self, src, convert=... | 62592c0f17be823caad8ea71cd52841acbab6185 | <|skeleton|>
class RCPServer:
"""Definition of a RCP server."""
def _create_dir(self, directory):
"""Create a directory on the server."""
<|body_0|>
def delete_proxy_dir(self):
"""Erase the proxy_dir directory on the server."""
<|body_1|>
def _copyoneto(self, src, conv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RCPServer:
"""Definition of a RCP server."""
def _create_dir(self, directory):
"""Create a directory on the server."""
dico = {'dir': directory}
magic.log.info(_(u'create remote directory %(dir)s...') % dico)
cmd = 'mkdir -p %(dir)s' % dico
res = self._exec_command... | the_stack_v2_python_sparse | asrun/plugins/rsh_server.py | zhanxiangqian/salome | train | 1 |
0a62250b1f1415545f2e037195970fd73d8e591a | [
"iri = annotation.get('id')\nif not iri:\n abort(400, 'Invalid Annotation passed in request')\nreturn unquote(iri).rstrip('/').split('/')[-1]",
"if not request.data:\n abort(400)\njson_data = json.loads(request.data.decode('utf8'))\nif type(json_data) != list:\n abort(400)\nannotation_ids = [self._get_ba... | <|body_start_0|>
iri = annotation.get('id')
if not iri:
abort(400, 'Invalid Annotation passed in request')
return unquote(iri).rstrip('/').split('/')[-1]
<|end_body_0|>
<|body_start_1|>
if not request.data:
abort(400)
json_data = json.loads(request.data.d... | Batch API class. | BatchAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchAPI:
"""Batch API class."""
def _get_base_id(self, annotation):
"""Return the base ID extracted from the full IRI."""
<|body_0|>
def delete(self):
"""Batch delete items."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
iri = annotation.get('... | stack_v2_sparse_classes_36k_train_022431 | 1,384 | permissive | [
{
"docstring": "Return the base ID extracted from the full IRI.",
"name": "_get_base_id",
"signature": "def _get_base_id(self, annotation)"
},
{
"docstring": "Batch delete items.",
"name": "delete",
"signature": "def delete(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017687 | Implement the Python class `BatchAPI` described below.
Class description:
Batch API class.
Method signatures and docstrings:
- def _get_base_id(self, annotation): Return the base ID extracted from the full IRI.
- def delete(self): Batch delete items. | Implement the Python class `BatchAPI` described below.
Class description:
Batch API class.
Method signatures and docstrings:
- def _get_base_id(self, annotation): Return the base ID extracted from the full IRI.
- def delete(self): Batch delete items.
<|skeleton|>
class BatchAPI:
"""Batch API class."""
def _... | bc504498ef330fab46f2334f96631457d520ec90 | <|skeleton|>
class BatchAPI:
"""Batch API class."""
def _get_base_id(self, annotation):
"""Return the base ID extracted from the full IRI."""
<|body_0|>
def delete(self):
"""Batch delete items."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BatchAPI:
"""Batch API class."""
def _get_base_id(self, annotation):
"""Return the base ID extracted from the full IRI."""
iri = annotation.get('id')
if not iri:
abort(400, 'Invalid Annotation passed in request')
return unquote(iri).rstrip('/').split('/')[-1]
... | the_stack_v2_python_sparse | explicates/api/batch.py | alexandermendes/explicates | train | 8 |
3ff36a6b3da7b14c44d0deebb97a1cfbc57cbceb | [
"self.title = title\nself.fail_jobs = fail_jobs\nself.job_display = 'none'\nself.fail_job_content = ''\nself.env_content = ''\nself.alarm_info = ''\nself.log_path = log_path\nself.__construct_mail_env(env)\nself.__construct_alarm_info(results)\nself.__construct_fail_job(fail_jobs)",
"if isinstance(env, dict):\n ... | <|body_start_0|>
self.title = title
self.fail_jobs = fail_jobs
self.job_display = 'none'
self.fail_job_content = ''
self.env_content = ''
self.alarm_info = ''
self.log_path = log_path
self.__construct_mail_env(env)
self.__construct_alarm_info(resul... | construct email for benchmark result. | EmailTemplate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailTemplate:
"""construct email for benchmark result."""
def __init__(self, title, env, results, log_path, fail_jobs=[]):
"""Args: title(str): benchmark | op_benchmark | benchmark_distribute env(dict): running environment. results(dict): {"Speed": {"header": [table_header0, table_h... | stack_v2_sparse_classes_36k_train_022432 | 5,907 | no_license | [
{
"docstring": "Args: title(str): benchmark | op_benchmark | benchmark_distribute env(dict): running environment. results(dict): {\"Speed\": {\"header\": [table_header0, table_header1, table_header2,] \"data\": [[{'value':, 'color':, }, {'value':, 'color':, }, {'value':, 'color':, }] ...]} \"Mem\": {\"header\":... | 5 | stack_v2_sparse_classes_30k_train_019823 | Implement the Python class `EmailTemplate` described below.
Class description:
construct email for benchmark result.
Method signatures and docstrings:
- def __init__(self, title, env, results, log_path, fail_jobs=[]): Args: title(str): benchmark | op_benchmark | benchmark_distribute env(dict): running environment. re... | Implement the Python class `EmailTemplate` described below.
Class description:
construct email for benchmark result.
Method signatures and docstrings:
- def __init__(self, title, env, results, log_path, fail_jobs=[]): Args: title(str): benchmark | op_benchmark | benchmark_distribute env(dict): running environment. re... | f0e0a303e9af29abb2e86e8918c102b152a37883 | <|skeleton|>
class EmailTemplate:
"""construct email for benchmark result."""
def __init__(self, title, env, results, log_path, fail_jobs=[]):
"""Args: title(str): benchmark | op_benchmark | benchmark_distribute env(dict): running environment. results(dict): {"Speed": {"header": [table_header0, table_h... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmailTemplate:
"""construct email for benchmark result."""
def __init__(self, title, env, results, log_path, fail_jobs=[]):
"""Args: title(str): benchmark | op_benchmark | benchmark_distribute env(dict): running environment. results(dict): {"Speed": {"header": [table_header0, table_header1, table... | the_stack_v2_python_sparse | scripts/template.py | PaddlePaddle/benchmark | train | 78 |
27a9995676b055c0fdbef5c2fb8df0007d6e5e67 | [
"super().__init__()\nassert len(rnns) == len(convrelus)\nself.blocks = len(rnns)\nfor index, (rnn, convrelu) in enumerate(zip(rnns, convrelus), 1):\n setattr(self, 'rnn' + str(index), rnn)\n setattr(self, 'convrelu' + str(index), convrelu)",
"T = inputs.size(1)\nhidden_states = []\nif len(initial_state) == ... | <|body_start_0|>
super().__init__()
assert len(rnns) == len(convrelus)
self.blocks = len(rnns)
for index, (rnn, convrelu) in enumerate(zip(rnns, convrelus), 1):
setattr(self, 'rnn' + str(index), rnn)
setattr(self, 'convrelu' + str(index), convrelu)
<|end_body_0|>
... | encoding a certain length of sequence The Encoder network consists of multiple pairs of (ConvRelu, CLSTM) cells. The input will first go through a convrelu cell, and then to a convlstm cell, and then to another convrelu cell, so on and so forth. | Encoder_pro | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder_pro:
"""encoding a certain length of sequence The Encoder network consists of multiple pairs of (ConvRelu, CLSTM) cells. The input will first go through a convrelu cell, and then to a convlstm cell, and then to another convrelu cell, so on and so forth."""
def __init__(self, rnns, co... | stack_v2_sparse_classes_36k_train_022433 | 41,120 | no_license | [
{
"docstring": "rnns are a list of convlstm cells, convrelus are a list of convrelu cells",
"name": "__init__",
"signature": "def __init__(self, rnns, convrelus)"
},
{
"docstring": "forward pass of the encoder :param inputs: a tensor of shape (B, S, C, H, W) :param initial_state: Either a list c... | 2 | stack_v2_sparse_classes_30k_train_004234 | Implement the Python class `Encoder_pro` described below.
Class description:
encoding a certain length of sequence The Encoder network consists of multiple pairs of (ConvRelu, CLSTM) cells. The input will first go through a convrelu cell, and then to a convlstm cell, and then to another convrelu cell, so on and so for... | Implement the Python class `Encoder_pro` described below.
Class description:
encoding a certain length of sequence The Encoder network consists of multiple pairs of (ConvRelu, CLSTM) cells. The input will first go through a convrelu cell, and then to a convlstm cell, and then to another convrelu cell, so on and so for... | b6a3161635bfa3b5da8ec871e1025e01f878e732 | <|skeleton|>
class Encoder_pro:
"""encoding a certain length of sequence The Encoder network consists of multiple pairs of (ConvRelu, CLSTM) cells. The input will first go through a convrelu cell, and then to a convlstm cell, and then to another convrelu cell, so on and so forth."""
def __init__(self, rnns, co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder_pro:
"""encoding a certain length of sequence The Encoder network consists of multiple pairs of (ConvRelu, CLSTM) cells. The input will first go through a convrelu cell, and then to a convlstm cell, and then to another convrelu cell, so on and so forth."""
def __init__(self, rnns, convrelus):
... | the_stack_v2_python_sparse | src/bayesian_neural_net.py | KEHUIYAO/BCLS | train | 0 |
c338681e887f5d89c6f5acf9a6c60e67f63a2c69 | [
"self.center = center\nself.blocks = []\nself.kind = ''\nself.block_control = None\nself.color = ''",
"piece = Piece(center)\npiece.kind = kind\npiece.blocks = cls.kinds[kind]\npiece.color = cls.colors[kind]\npiece.block_control = copy.copy(Piece.blocks_controls[kind])\nreturn piece",
"new_blocks = []\ncoef = n... | <|body_start_0|>
self.center = center
self.blocks = []
self.kind = ''
self.block_control = None
self.color = ''
<|end_body_0|>
<|body_start_1|>
piece = Piece(center)
piece.kind = kind
piece.blocks = cls.kinds[kind]
piece.color = cls.colors[kind]
... | Défini chacune des différentes pièces qui peuvent être jouer dans le tetris : O, I, L, T, S, Z, J | Piece | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Piece:
"""Défini chacune des différentes pièces qui peuvent être jouer dans le tetris : O, I, L, T, S, Z, J"""
def __init__(self, center):
"""Créer une pièce, centrée en center. Attributs : - center : tableau 2D de coordonnée, généralement égale à Piece.centers_init[kind] Retour : - ... | stack_v2_sparse_classes_36k_train_022434 | 4,438 | no_license | [
{
"docstring": "Créer une pièce, centrée en center. Attributs : - center : tableau 2D de coordonnée, généralement égale à Piece.centers_init[kind] Retour : - piece : instance Piece / nouvelle piece",
"name": "__init__",
"signature": "def __init__(self, center)"
},
{
"docstring": "Méthode de clas... | 4 | stack_v2_sparse_classes_30k_train_010803 | Implement the Python class `Piece` described below.
Class description:
Défini chacune des différentes pièces qui peuvent être jouer dans le tetris : O, I, L, T, S, Z, J
Method signatures and docstrings:
- def __init__(self, center): Créer une pièce, centrée en center. Attributs : - center : tableau 2D de coordonnée, ... | Implement the Python class `Piece` described below.
Class description:
Défini chacune des différentes pièces qui peuvent être jouer dans le tetris : O, I, L, T, S, Z, J
Method signatures and docstrings:
- def __init__(self, center): Créer une pièce, centrée en center. Attributs : - center : tableau 2D de coordonnée, ... | bd6591d25a978d8889e56cdb394e01560f5b8ac3 | <|skeleton|>
class Piece:
"""Défini chacune des différentes pièces qui peuvent être jouer dans le tetris : O, I, L, T, S, Z, J"""
def __init__(self, center):
"""Créer une pièce, centrée en center. Attributs : - center : tableau 2D de coordonnée, généralement égale à Piece.centers_init[kind] Retour : - ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Piece:
"""Défini chacune des différentes pièces qui peuvent être jouer dans le tetris : O, I, L, T, S, Z, J"""
def __init__(self, center):
"""Créer une pièce, centrée en center. Attributs : - center : tableau 2D de coordonnée, généralement égale à Piece.centers_init[kind] Retour : - piece : insta... | the_stack_v2_python_sparse | tetris/Jeu/Piece.py | Naowak/projet_nao | train | 0 |
eb86da42e35090952e8c205885c9fd6b3f4df7c2 | [
"if self.request.method == 'GET':\n return (IsInActiveCommunity(), IsAbleToRetrieveAlbumImage())\nelif self.request.method == 'POST':\n return (permissions.IsAuthenticated(),)\nelif self.request.method == 'DELETE':\n return (permissions.IsAuthenticated(), IsInActiveCommunity(), IsStaffOfCommunity())\nretur... | <|body_start_0|>
if self.request.method == 'GET':
return (IsInActiveCommunity(), IsAbleToRetrieveAlbumImage())
elif self.request.method == 'POST':
return (permissions.IsAuthenticated(),)
elif self.request.method == 'DELETE':
return (permissions.IsAuthenticated... | Album image view set | AlbumImageViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlbumImageViewSet:
"""Album image view set"""
def get_permissions(self):
"""Get permissions"""
<|body_0|>
def list(self, request, *args, **kwargs):
"""List album images"""
<|body_1|>
def create(self, request, *args, **kwargs):
"""Create album... | stack_v2_sparse_classes_36k_train_022435 | 8,383 | permissive | [
{
"docstring": "Get permissions",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "List album images",
"name": "list",
"signature": "def list(self, request, *args, **kwargs)"
},
{
"docstring": "Create album image",
"name": "create",
"... | 4 | null | Implement the Python class `AlbumImageViewSet` described below.
Class description:
Album image view set
Method signatures and docstrings:
- def get_permissions(self): Get permissions
- def list(self, request, *args, **kwargs): List album images
- def create(self, request, *args, **kwargs): Create album image
- def de... | Implement the Python class `AlbumImageViewSet` described below.
Class description:
Album image view set
Method signatures and docstrings:
- def get_permissions(self): Get permissions
- def list(self, request, *args, **kwargs): List album images
- def create(self, request, *args, **kwargs): Create album image
- def de... | cf429f43251ad7e77c0d9bc9fe91bb030ca8bae8 | <|skeleton|>
class AlbumImageViewSet:
"""Album image view set"""
def get_permissions(self):
"""Get permissions"""
<|body_0|>
def list(self, request, *args, **kwargs):
"""List album images"""
<|body_1|>
def create(self, request, *args, **kwargs):
"""Create album... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlbumImageViewSet:
"""Album image view set"""
def get_permissions(self):
"""Get permissions"""
if self.request.method == 'GET':
return (IsInActiveCommunity(), IsAbleToRetrieveAlbumImage())
elif self.request.method == 'POST':
return (permissions.IsAuthentica... | the_stack_v2_python_sparse | asset/views.py | 810Teams/clubs-and-events-backend | train | 3 |
d8a06be246e308f5c1ff503bc83a9e40eb19be3b | [
"tdc_Fields_Plotter.__init__(self, (f_e, f_p), xlabel, ylabel, idlabel)\nif not ylabel:\n self.plot_ylabel = '$\\\\eta_{\\\\pm}$'\nif not idlabel:\n self.plot_idlabel = 'N_{e,p}:' + self.data[0].calc_id\nif e_density_negative:\n self.e_sign = -1\nelse:\n self.e_sign = 1",
"self.lines[0], = ax.plot(sel... | <|body_start_0|>
tdc_Fields_Plotter.__init__(self, (f_e, f_p), xlabel, ylabel, idlabel)
if not ylabel:
self.plot_ylabel = '$\\eta_{\\pm}$'
if not idlabel:
self.plot_idlabel = 'N_{e,p}:' + self.data[0].calc_id
if e_density_negative:
self.e_sign = -1
... | This class is plotter for (e)lectron, (p)ositron number densities =========== - it implements plot() function fron tdc_Fields_Plotter - sets plot label | tdc_EP_Density_Plotter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class tdc_EP_Density_Plotter:
"""This class is plotter for (e)lectron, (p)ositron number densities =========== - it implements plot() function fron tdc_Fields_Plotter - sets plot label"""
def __init__(self, f_e, f_p, e_density_negative=True, xlabel=None, ylabel=None, idlabel=None):
"""f_e ... | stack_v2_sparse_classes_36k_train_022436 | 5,286 | no_license | [
{
"docstring": "f_e -- field with electron number density f_p -- field with positron number density e_density_negative -- <True> if true Electron density is negative",
"name": "__init__",
"signature": "def __init__(self, f_e, f_p, e_density_negative=True, xlabel=None, ylabel=None, idlabel=None)"
},
... | 3 | null | Implement the Python class `tdc_EP_Density_Plotter` described below.
Class description:
This class is plotter for (e)lectron, (p)ositron number densities =========== - it implements plot() function fron tdc_Fields_Plotter - sets plot label
Method signatures and docstrings:
- def __init__(self, f_e, f_p, e_density_neg... | Implement the Python class `tdc_EP_Density_Plotter` described below.
Class description:
This class is plotter for (e)lectron, (p)ositron number densities =========== - it implements plot() function fron tdc_Fields_Plotter - sets plot label
Method signatures and docstrings:
- def __init__(self, f_e, f_p, e_density_neg... | 775dc841b1d8538584c8c68a5f75ae997191e685 | <|skeleton|>
class tdc_EP_Density_Plotter:
"""This class is plotter for (e)lectron, (p)ositron number densities =========== - it implements plot() function fron tdc_Fields_Plotter - sets plot label"""
def __init__(self, f_e, f_p, e_density_negative=True, xlabel=None, ylabel=None, idlabel=None):
"""f_e ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class tdc_EP_Density_Plotter:
"""This class is plotter for (e)lectron, (p)ositron number densities =========== - it implements plot() function fron tdc_Fields_Plotter - sets plot label"""
def __init__(self, f_e, f_p, e_density_negative=True, xlabel=None, ylabel=None, idlabel=None):
"""f_e -- field with... | the_stack_v2_python_sparse | Fields/tdc_ep_density_plotter.py | atimokhin/tdc_vis | train | 0 |
e51fe33231fa32c8eb804eedd0e2ddebe14c80ca | [
"self._maxsize = maxsize\nself._queue = collections.deque()\nself._closed = False\nself._mutex = threading.Lock()\nself._not_empty = threading.Condition(self._mutex)\nself._not_full = threading.Condition(self._mutex)",
"with self._not_empty:\n while not self._queue:\n self._not_empty.wait()\n item = ... | <|body_start_0|>
self._maxsize = maxsize
self._queue = collections.deque()
self._closed = False
self._mutex = threading.Lock()
self._not_empty = threading.Condition(self._mutex)
self._not_full = threading.Condition(self._mutex)
<|end_body_0|>
<|body_start_1|>
wit... | Stripped-down fork of the standard library Queue that is closeable. | CloseableQueue | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CloseableQueue:
"""Stripped-down fork of the standard library Queue that is closeable."""
def __init__(self, maxsize=0):
"""Create a queue object with a given maximum size. Args: maxsize: int size of queue. If <= 0, the queue size is infinite."""
<|body_0|>
def get(self)... | stack_v2_sparse_classes_36k_train_022437 | 10,399 | permissive | [
{
"docstring": "Create a queue object with a given maximum size. Args: maxsize: int size of queue. If <= 0, the queue size is infinite.",
"name": "__init__",
"signature": "def __init__(self, maxsize=0)"
},
{
"docstring": "Remove and return an item from the queue. If the queue is empty, blocks un... | 4 | null | Implement the Python class `CloseableQueue` described below.
Class description:
Stripped-down fork of the standard library Queue that is closeable.
Method signatures and docstrings:
- def __init__(self, maxsize=0): Create a queue object with a given maximum size. Args: maxsize: int size of queue. If <= 0, the queue s... | Implement the Python class `CloseableQueue` described below.
Class description:
Stripped-down fork of the standard library Queue that is closeable.
Method signatures and docstrings:
- def __init__(self, maxsize=0): Create a queue object with a given maximum size. Args: maxsize: int size of queue. If <= 0, the queue s... | a7f3934a67900720af3d3b15389551483bee50b8 | <|skeleton|>
class CloseableQueue:
"""Stripped-down fork of the standard library Queue that is closeable."""
def __init__(self, maxsize=0):
"""Create a queue object with a given maximum size. Args: maxsize: int size of queue. If <= 0, the queue size is infinite."""
<|body_0|>
def get(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CloseableQueue:
"""Stripped-down fork of the standard library Queue that is closeable."""
def __init__(self, maxsize=0):
"""Create a queue object with a given maximum size. Args: maxsize: int size of queue. If <= 0, the queue size is infinite."""
self._maxsize = maxsize
self._queu... | the_stack_v2_python_sparse | tensorflow/python/summary/writer/event_file_writer.py | tensorflow/tensorflow | train | 208,740 |
9c375b26c59ee3b8feacbe911cd5934fd9d5ed71 | [
"def winner(nums, s, e, turn):\n if s == e:\n return turn * nums[s]\n a = turn * nums[s] + winner(nums, s + 1, e, -turn)\n b = turn * nums[e] + winner(nums, s, e - 1, -turn)\n return turn * max(turn * a, turn * b)\nreturn winner(nums, 0, len(nums) - 1, 1) >= 0",
"n = len(nums)\ndp = [[0 for i i... | <|body_start_0|>
def winner(nums, s, e, turn):
if s == e:
return turn * nums[s]
a = turn * nums[s] + winner(nums, s + 1, e, -turn)
b = turn * nums[e] + winner(nums, s, e - 1, -turn)
return turn * max(turn * a, turn * b)
return winner(nums, ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def PredictTheWinner1(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def PredictTheWinner(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def winner(nums, s, e, turn):
... | stack_v2_sparse_classes_36k_train_022438 | 923 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "PredictTheWinner1",
"signature": "def PredictTheWinner1(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "PredictTheWinner",
"signature": "def PredictTheWinner(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def PredictTheWinner1(self, nums): :type nums: List[int] :rtype: bool
- def PredictTheWinner(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def PredictTheWinner1(self, nums): :type nums: List[int] :rtype: bool
- def PredictTheWinner(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
de... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def PredictTheWinner1(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def PredictTheWinner(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def PredictTheWinner1(self, nums):
""":type nums: List[int] :rtype: bool"""
def winner(nums, s, e, turn):
if s == e:
return turn * nums[s]
a = turn * nums[s] + winner(nums, s + 1, e, -turn)
b = turn * nums[e] + winner(nums, s, e - 1... | the_stack_v2_python_sparse | py/leetcode/486.py | wfeng1991/learnpy | train | 0 | |
b18cb7257fdbe56ffa350f031633452a4354cc28 | [
"headers = self._get_default_headers()\ntry:\n if self.request_validator.client_authentication_required(request):\n log.debug('Authenticating client, %r.', request)\n if not self.request_validator.authenticate_client(request):\n log.debug('Client authentication failed, %r.', request)\n ... | <|body_start_0|>
headers = self._get_default_headers()
try:
if self.request_validator.client_authentication_required(request):
log.debug('Authenticating client, %r.', request)
if not self.request_validator.authenticate_client(request):
log.... | `Resource Owner Password Credentials Grant`_ The resource owner password credentials grant type is suitable in cases where the resource owner has a trust relationship with the client, such as the device operating system or a highly privileged application. The authorization server should take special care when enabling ... | ResourceOwnerPasswordCredentialsGrant | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceOwnerPasswordCredentialsGrant:
"""`Resource Owner Password Credentials Grant`_ The resource owner password credentials grant type is suitable in cases where the resource owner has a trust relationship with the client, such as the device operating system or a highly privileged application.... | stack_v2_sparse_classes_36k_train_022439 | 8,484 | permissive | [
{
"docstring": "Return token or error in json format. :param request: OAuthlib request. :type request: oauthlib.common.Request :param token_handler: A token handler instance, for example of type oauthlib.oauth2.BearerToken. If the access token request is valid and authorized, the authorization server issues an ... | 2 | stack_v2_sparse_classes_30k_train_006756 | Implement the Python class `ResourceOwnerPasswordCredentialsGrant` described below.
Class description:
`Resource Owner Password Credentials Grant`_ The resource owner password credentials grant type is suitable in cases where the resource owner has a trust relationship with the client, such as the device operating sys... | Implement the Python class `ResourceOwnerPasswordCredentialsGrant` described below.
Class description:
`Resource Owner Password Credentials Grant`_ The resource owner password credentials grant type is suitable in cases where the resource owner has a trust relationship with the client, such as the device operating sys... | 00f9a212004a80df790ed071a59af53a05f5e3f2 | <|skeleton|>
class ResourceOwnerPasswordCredentialsGrant:
"""`Resource Owner Password Credentials Grant`_ The resource owner password credentials grant type is suitable in cases where the resource owner has a trust relationship with the client, such as the device operating system or a highly privileged application.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResourceOwnerPasswordCredentialsGrant:
"""`Resource Owner Password Credentials Grant`_ The resource owner password credentials grant type is suitable in cases where the resource owner has a trust relationship with the client, such as the device operating system or a highly privileged application. The authoriz... | the_stack_v2_python_sparse | oauthlib/oauth2/rfc6749/grant_types/resource_owner_password_credentials.py | oauthlib/oauthlib | train | 1,223 |
eb1a6b62d61c5ed5fdedb3ca32ae7f3ff57eebec | [
"MenuEntryWidget.__init__(self, entry, fontSize=28, width=width, height=height)\nself.entry = entry\nattack = self.entry.attack\nself.typeImage = TypeImage(attack.type)\nself.ppTextLabel = Label('PP', size=18)\nself.ppValuesLabel = Label('{0}/{1}'.format(attack.currPowerPoints, attack.powerPoints), size=18)",
"se... | <|body_start_0|>
MenuEntryWidget.__init__(self, entry, fontSize=28, width=width, height=height)
self.entry = entry
attack = self.entry.attack
self.typeImage = TypeImage(attack.type)
self.ppTextLabel = Label('PP', size=18)
self.ppValuesLabel = Label('{0}/{1}'.format(attack... | Represents the widget for an Attack Menu Entry | AttackMenuEntryWidget | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttackMenuEntryWidget:
"""Represents the widget for an Attack Menu Entry"""
def __init__(self, entry, width, height):
"""Initialize the widget"""
<|body_0|>
def drawSurface(self):
"""Draw the Widget"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022440 | 1,224 | no_license | [
{
"docstring": "Initialize the widget",
"name": "__init__",
"signature": "def __init__(self, entry, width, height)"
},
{
"docstring": "Draw the Widget",
"name": "drawSurface",
"signature": "def drawSurface(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017564 | Implement the Python class `AttackMenuEntryWidget` described below.
Class description:
Represents the widget for an Attack Menu Entry
Method signatures and docstrings:
- def __init__(self, entry, width, height): Initialize the widget
- def drawSurface(self): Draw the Widget | Implement the Python class `AttackMenuEntryWidget` described below.
Class description:
Represents the widget for an Attack Menu Entry
Method signatures and docstrings:
- def __init__(self, entry, width, height): Initialize the widget
- def drawSurface(self): Draw the Widget
<|skeleton|>
class AttackMenuEntryWidget:
... | 3931eee5fd04e18bb1738a0b27a4c6979dc4db01 | <|skeleton|>
class AttackMenuEntryWidget:
"""Represents the widget for an Attack Menu Entry"""
def __init__(self, entry, width, height):
"""Initialize the widget"""
<|body_0|>
def drawSurface(self):
"""Draw the Widget"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttackMenuEntryWidget:
"""Represents the widget for an Attack Menu Entry"""
def __init__(self, entry, width, height):
"""Initialize the widget"""
MenuEntryWidget.__init__(self, entry, fontSize=28, width=width, height=height)
self.entry = entry
attack = self.entry.attack
... | the_stack_v2_python_sparse | src/Screen/Pygame/Menu/ActionMenu/AttackMenu/attack_menu_entry_widget.py | sgtnourry/Pokemon-Project | train | 0 |
9a53d11f715febef8cf7c0128aedcd37925eb383 | [
"max_area = 0\nn = len(height)\nfor i in range(n):\n for j in range(i + 1, n):\n area = (j - i) * min(height[i], height[j])\n max_area = max(max_area, area)\nprint(max_area)\nreturn max_area",
"max_area = 0\nn = len(height)\ni = 0\nj = n - 1\nwhile i < j:\n if height[i] < height[j]:\n a... | <|body_start_0|>
max_area = 0
n = len(height)
for i in range(n):
for j in range(i + 1, n):
area = (j - i) * min(height[i], height[j])
max_area = max(max_area, area)
print(max_area)
return max_area
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def max_area(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def max_area2(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max_area = 0
n = len(height)
... | stack_v2_sparse_classes_36k_train_022441 | 1,597 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "max_area",
"signature": "def max_area(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "max_area2",
"signature": "def max_area2(self, height)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005457 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def max_area(self, height): :type height: List[int] :rtype: int
- def max_area2(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def max_area(self, height): :type height: List[int] :rtype: int
- def max_area2(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class Solution:
def max_area... | 3b13b36f37eb364410b3b5b4f10a1808d8b1111e | <|skeleton|>
class Solution:
def max_area(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def max_area2(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def max_area(self, height):
""":type height: List[int] :rtype: int"""
max_area = 0
n = len(height)
for i in range(n):
for j in range(i + 1, n):
area = (j - i) * min(height[i], height[j])
max_area = max(max_area, area)
... | the_stack_v2_python_sparse | leetcode/11.py | yanggelinux/algorithm-data-structure | train | 0 | |
5a2e57b60a6b5d2016d3e5711de1276e0fc493eb | [
"if not self._dapver or parse(self._dapver) < self.__min_dapall_version__:\n raise MarvinError('DAPall is not available for versions before MPL-6.')\nif hasattr(self, '_dapall') and self._dapall is not None:\n return self._dapall\nif self.data_origin == 'file':\n try:\n dapall_data = self._get_dapal... | <|body_start_0|>
if not self._dapver or parse(self._dapver) < self.__min_dapall_version__:
raise MarvinError('DAPall is not available for versions before MPL-6.')
if hasattr(self, '_dapall') and self._dapall is not None:
return self._dapall
if self.data_origin == 'file':
... | A mixin that provides access to DAPall paremeters. Must be used in combination with `.MarvinToolsClass` and initialised before `~.DAPallMixIn.dapall` can be called. `DAPallMixIn` uses the `.MarvinToolsClass.data_origin` of the object to determine how to obtain the DAPall information. However, if the object contains a `... | DAPallMixIn | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DAPallMixIn:
"""A mixin that provides access to DAPall paremeters. Must be used in combination with `.MarvinToolsClass` and initialised before `~.DAPallMixIn.dapall` can be called. `DAPallMixIn` uses the `.MarvinToolsClass.data_origin` of the object to determine how to obtain the DAPall informati... | stack_v2_sparse_classes_36k_train_022442 | 4,554 | permissive | [
{
"docstring": "Returns the contents of the DAPall data for this target.",
"name": "dapall",
"signature": "def dapall(self)"
},
{
"docstring": "Uses DAPAll file to retrieve information.",
"name": "_get_dapall_from_file",
"signature": "def _get_dapall_from_file(self)"
},
{
"docstr... | 4 | stack_v2_sparse_classes_30k_train_018759 | Implement the Python class `DAPallMixIn` described below.
Class description:
A mixin that provides access to DAPall paremeters. Must be used in combination with `.MarvinToolsClass` and initialised before `~.DAPallMixIn.dapall` can be called. `DAPallMixIn` uses the `.MarvinToolsClass.data_origin` of the object to deter... | Implement the Python class `DAPallMixIn` described below.
Class description:
A mixin that provides access to DAPall paremeters. Must be used in combination with `.MarvinToolsClass` and initialised before `~.DAPallMixIn.dapall` can be called. `DAPallMixIn` uses the `.MarvinToolsClass.data_origin` of the object to deter... | db4c536a65fb2f16fee05a4f34996a7fd35f0527 | <|skeleton|>
class DAPallMixIn:
"""A mixin that provides access to DAPall paremeters. Must be used in combination with `.MarvinToolsClass` and initialised before `~.DAPallMixIn.dapall` can be called. `DAPallMixIn` uses the `.MarvinToolsClass.data_origin` of the object to determine how to obtain the DAPall informati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DAPallMixIn:
"""A mixin that provides access to DAPall paremeters. Must be used in combination with `.MarvinToolsClass` and initialised before `~.DAPallMixIn.dapall` can be called. `DAPallMixIn` uses the `.MarvinToolsClass.data_origin` of the object to determine how to obtain the DAPall information. However, ... | the_stack_v2_python_sparse | python/marvin/tools/mixins/dapall.py | sdss/marvin | train | 56 |
6ae0fb393a980ccb01cf42cf091fb1cb562bcc5d | [
"self.tags = tags\nself.attachments = attachments\nself.required_signatures = required_signatures\nself.created_by_application = created_by_application\nself.get_social_security_number = get_social_security_number\nself.extra_info = extra_info\nself.security = security\nself.time_to_live = time_to_live\nself.depart... | <|body_start_0|>
self.tags = tags
self.attachments = attachments
self.required_signatures = required_signatures
self.created_by_application = created_by_application
self.get_social_security_number = get_social_security_number
self.extra_info = extra_info
self.secu... | Implementation of the 'Advanced' model. TODO: type model description here. Attributes: tags (list of string): Mark the document with tags, these tags can be used to query for document data / events at a later time. attachments (int): Set how many attachments this signjob should have, when the document is created you ca... | Advanced | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Advanced:
"""Implementation of the 'Advanced' model. TODO: type model description here. Attributes: tags (list of string): Mark the document with tags, these tags can be used to query for document data / events at a later time. attachments (int): Set how many attachments this signjob should have,... | stack_v2_sparse_classes_36k_train_022443 | 5,427 | permissive | [
{
"docstring": "Constructor for the Advanced class",
"name": "__init__",
"signature": "def __init__(self, tags=None, attachments=None, required_signatures=None, created_by_application=None, get_social_security_number=None, extra_info=None, security=None, time_to_live=None, department_id=None, additional... | 2 | stack_v2_sparse_classes_30k_train_007251 | Implement the Python class `Advanced` described below.
Class description:
Implementation of the 'Advanced' model. TODO: type model description here. Attributes: tags (list of string): Mark the document with tags, these tags can be used to query for document data / events at a later time. attachments (int): Set how man... | Implement the Python class `Advanced` described below.
Class description:
Implementation of the 'Advanced' model. TODO: type model description here. Attributes: tags (list of string): Mark the document with tags, these tags can be used to query for document data / events at a later time. attachments (int): Set how man... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class Advanced:
"""Implementation of the 'Advanced' model. TODO: type model description here. Attributes: tags (list of string): Mark the document with tags, these tags can be used to query for document data / events at a later time. attachments (int): Set how many attachments this signjob should have,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Advanced:
"""Implementation of the 'Advanced' model. TODO: type model description here. Attributes: tags (list of string): Mark the document with tags, these tags can be used to query for document data / events at a later time. attachments (int): Set how many attachments this signjob should have, when the doc... | the_stack_v2_python_sparse | idfy_rest_client/models/advanced.py | dealflowteam/Idfy | train | 0 |
d142100cc4b2d4577aec3c84b23455009d27ac43 | [
"rows = self._parse_int_lines(data)\nwhile len(rows) > 0:\n first = rows.pop()\n if first > self._limit:\n continue\n for second in rows:\n if first + second == self._limit:\n return first * second\nreturn 0",
"rows = self._parse_int_lines(data)\nwhile len(rows) > 0:\n first =... | <|body_start_0|>
rows = self._parse_int_lines(data)
while len(rows) > 0:
first = rows.pop()
if first > self._limit:
continue
for second in rows:
if first + second == self._limit:
return first * second
return ... | Solver for day 1, 2020. | Solver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solver:
"""Solver for day 1, 2020."""
def part_one(self, data: str) -> int:
"""Solve part one."""
<|body_0|>
def part_two(self, data: str) -> int:
"""Solve part two."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
rows = self._parse_int_lines(da... | stack_v2_sparse_classes_36k_train_022444 | 1,146 | no_license | [
{
"docstring": "Solve part one.",
"name": "part_one",
"signature": "def part_one(self, data: str) -> int"
},
{
"docstring": "Solve part two.",
"name": "part_two",
"signature": "def part_two(self, data: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_test_001143 | Implement the Python class `Solver` described below.
Class description:
Solver for day 1, 2020.
Method signatures and docstrings:
- def part_one(self, data: str) -> int: Solve part one.
- def part_two(self, data: str) -> int: Solve part two. | Implement the Python class `Solver` described below.
Class description:
Solver for day 1, 2020.
Method signatures and docstrings:
- def part_one(self, data: str) -> int: Solve part one.
- def part_two(self, data: str) -> int: Solve part two.
<|skeleton|>
class Solver:
"""Solver for day 1, 2020."""
def part_... | b1e7f12318c5bd642dfe29f862680f51c0f66bb5 | <|skeleton|>
class Solver:
"""Solver for day 1, 2020."""
def part_one(self, data: str) -> int:
"""Solve part one."""
<|body_0|>
def part_two(self, data: str) -> int:
"""Solve part two."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solver:
"""Solver for day 1, 2020."""
def part_one(self, data: str) -> int:
"""Solve part one."""
rows = self._parse_int_lines(data)
while len(rows) > 0:
first = rows.pop()
if first > self._limit:
continue
for second in rows:
... | the_stack_v2_python_sparse | app/y2020/d01_report_repair.py | bolmstedt/advent-of-code-python | train | 0 |
1156dae05e641403082e891e000e447d1090a9b7 | [
"self.key2node = {}\nself.freq2list = defaultdict(OrderedDict)\nself.capacity = capacity\nself.minf = 0",
"if key not in self.key2node:\n return -1\nkey, value, freq = self.key2node[key]\nself.freq2list[freq].pop(key)\nself.key2node.pop(key)\nif not self.freq2list[freq] and freq == self.minf:\n self.minf +=... | <|body_start_0|>
self.key2node = {}
self.freq2list = defaultdict(OrderedDict)
self.capacity = capacity
self.minf = 0
<|end_body_0|>
<|body_start_1|>
if key not in self.key2node:
return -1
key, value, freq = self.key2node[key]
self.freq2list[freq].pop(... | LFUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_022445 | 2,950 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_014668 | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | 547cdc7365716660a9d9590c1cc97d95bc38d315 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.key2node = {}
self.freq2list = defaultdict(OrderedDict)
self.capacity = capacity
self.minf = 0
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.key2node:
... | the_stack_v2_python_sparse | 460.lfu-cache.py | zhch-sun/leetcode_szc | train | 0 | |
98814a0f204e4c9f69dd359e1e92974fbc51e5d9 | [
"super(RestDataCollection, self).__init__()\nself.ResourceModel = kwargs['RestResourceModel']\nself.Database = self.ResourceModel.Database\nself.dbTable = self.ResourceModel.Table\nself.CollectionTitle = self.ResourceModel.CollectionTitle\nself.SingleElementTitle = self.ResourceModel.SingleElementTitle\nself.Displa... | <|body_start_0|>
super(RestDataCollection, self).__init__()
self.ResourceModel = kwargs['RestResourceModel']
self.Database = self.ResourceModel.Database
self.dbTable = self.ResourceModel.Table
self.CollectionTitle = self.ResourceModel.CollectionTitle
self.SingleElementTit... | RestDataCollection: Manage with REST a collection of elements : - POST : is allowing to add an element to the collection - GET : is allowing to display all elements of the collection | RestDataCollection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestDataCollection:
"""RestDataCollection: Manage with REST a collection of elements : - POST : is allowing to add an element to the collection - GET : is allowing to display all elements of the collection"""
def __init__(self, **kwargs):
"""RestDataCollection constructor: - RestReso... | stack_v2_sparse_classes_36k_train_022446 | 5,412 | no_license | [
{
"docstring": "RestDataCollection constructor: - RestResourceModel : REST Resource description (data model, display format, put and post parser)",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Manage ParentKey filtering for GET method appied on Childs",
... | 5 | null | Implement the Python class `RestDataCollection` described below.
Class description:
RestDataCollection: Manage with REST a collection of elements : - POST : is allowing to add an element to the collection - GET : is allowing to display all elements of the collection
Method signatures and docstrings:
- def __init__(se... | Implement the Python class `RestDataCollection` described below.
Class description:
RestDataCollection: Manage with REST a collection of elements : - POST : is allowing to add an element to the collection - GET : is allowing to display all elements of the collection
Method signatures and docstrings:
- def __init__(se... | 8f107644a74fe46827ec5ed53d0457022bd1608b | <|skeleton|>
class RestDataCollection:
"""RestDataCollection: Manage with REST a collection of elements : - POST : is allowing to add an element to the collection - GET : is allowing to display all elements of the collection"""
def __init__(self, **kwargs):
"""RestDataCollection constructor: - RestReso... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestDataCollection:
"""RestDataCollection: Manage with REST a collection of elements : - POST : is allowing to add an element to the collection - GET : is allowing to display all elements of the collection"""
def __init__(self, **kwargs):
"""RestDataCollection constructor: - RestResourceModel : R... | the_stack_v2_python_sparse | restapp/view_RestDataCollection_v3.py | ldurandadomia/Flask-Restful | train | 0 |
9faf15f211e4b8f520e45e2b4ed51621461bd23e | [
"properties = {'env_vars': {}, 'inputs': [], 'outputs': []}\nreader = self._get_reader(filepath)\nparser = self._get_parser(reader.language)\nif not parser:\n return properties\nfor chunk in reader.read_next_code_chunk():\n if chunk:\n for line in chunk:\n matches = parser.parse_environment_... | <|body_start_0|>
properties = {'env_vars': {}, 'inputs': [], 'outputs': []}
reader = self._get_reader(filepath)
parser = self._get_parser(reader.language)
if not parser:
return properties
for chunk in reader.read_next_code_chunk():
if chunk:
... | ContentParser | [
"Apache-2.0",
"CC-BY-4.0",
"LicenseRef-scancode-unknown-license-reference",
"CC-BY-SA-4.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContentParser:
def parse(self, filepath: str) -> dict:
"""Returns a model dictionary of all the regex matches for each key in the regex dictionary"""
<|body_0|>
def _validate_file(self, filepath: str):
"""Validate file exists and is file (e.g. not a directory)"""
... | stack_v2_sparse_classes_36k_train_022447 | 7,437 | permissive | [
{
"docstring": "Returns a model dictionary of all the regex matches for each key in the regex dictionary",
"name": "parse",
"signature": "def parse(self, filepath: str) -> dict"
},
{
"docstring": "Validate file exists and is file (e.g. not a directory)",
"name": "_validate_file",
"signat... | 4 | stack_v2_sparse_classes_30k_train_001495 | Implement the Python class `ContentParser` described below.
Class description:
Implement the ContentParser class.
Method signatures and docstrings:
- def parse(self, filepath: str) -> dict: Returns a model dictionary of all the regex matches for each key in the regex dictionary
- def _validate_file(self, filepath: st... | Implement the Python class `ContentParser` described below.
Class description:
Implement the ContentParser class.
Method signatures and docstrings:
- def parse(self, filepath: str) -> dict: Returns a model dictionary of all the regex matches for each key in the regex dictionary
- def _validate_file(self, filepath: st... | 3c27ada25a27b719529e88268bed38d135e40805 | <|skeleton|>
class ContentParser:
def parse(self, filepath: str) -> dict:
"""Returns a model dictionary of all the regex matches for each key in the regex dictionary"""
<|body_0|>
def _validate_file(self, filepath: str):
"""Validate file exists and is file (e.g. not a directory)"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContentParser:
def parse(self, filepath: str) -> dict:
"""Returns a model dictionary of all the regex matches for each key in the regex dictionary"""
properties = {'env_vars': {}, 'inputs': [], 'outputs': []}
reader = self._get_reader(filepath)
parser = self._get_parser(reader.... | the_stack_v2_python_sparse | elyra/contents/parser.py | elyra-ai/elyra | train | 1,707 | |
50fa9c31970a6943b86f2a1025687b143816f900 | [
"super(Encoder, self).__init__()\nself.dm = dm\nself.N = N\nself.embedding = tf.keras.layers.Embedding(input_vocab, dm)\nself.positional_encoding = positional_encoding(max_seq_len, self.dm)\nself.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]\nself.dropout = tf.keras.layers.Dropout(drop_rate)",... | <|body_start_0|>
super(Encoder, self).__init__()
self.dm = dm
self.N = N
self.embedding = tf.keras.layers.Embedding(input_vocab, dm)
self.positional_encoding = positional_encoding(max_seq_len, self.dm)
self.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for _ in range(N... | to encoder for machine translation | Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""to encoder for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""constructor @N: number of blocks in encoder @dm: dimensionality of model @h: number of heads @hidden: number of hidden units in fully connected layer @i... | stack_v2_sparse_classes_36k_train_022448 | 2,368 | no_license | [
{
"docstring": "constructor @N: number of blocks in encoder @dm: dimensionality of model @h: number of heads @hidden: number of hidden units in fully connected layer @input_vocab: size of input vocabulary @max_seq_len: maximum sequence length possible @drop_rate: dropout rate *Sets following public instance att... | 2 | null | Implement the Python class `Encoder` described below.
Class description:
to encoder for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): constructor @N: number of blocks in encoder @dm: dimensionality of model @h: number of heads @h... | Implement the Python class `Encoder` described below.
Class description:
to encoder for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): constructor @N: number of blocks in encoder @dm: dimensionality of model @h: number of heads @h... | e20b284d5f1841952104d7d9a0274cff80eb304d | <|skeleton|>
class Encoder:
"""to encoder for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""constructor @N: number of blocks in encoder @dm: dimensionality of model @h: number of heads @hidden: number of hidden units in fully connected layer @i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
"""to encoder for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""constructor @N: number of blocks in encoder @dm: dimensionality of model @h: number of heads @hidden: number of hidden units in fully connected layer @input_vocab: s... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/9-transformer_encoder.py | jgadelugo/holbertonschool-machine_learning | train | 1 |
7178b04f118b7a96827146d612776936e49a22cb | [
"self.driver = driver\nself.comp_name = comp_name\nself.element = self.get_component()",
"elem = self.find_element('[name=\"' + compname + '\"]')\ndiscript = elem.get_attribute('data-discription')\ndps = self.find_elements('div.formfield-wrap>label')\nfor dp in dps:\n if dp.text == discript:\n return Tr... | <|body_start_0|>
self.driver = driver
self.comp_name = comp_name
self.element = self.get_component()
<|end_body_0|>
<|body_start_1|>
elem = self.find_element('[name="' + compname + '"]')
discript = elem.get_attribute('data-discription')
dps = self.find_elements('div.form... | 微信录音控件 | RecordPhonePage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecordPhonePage:
"""微信录音控件"""
def __init__(self, driver, comp_name):
"""类初始化执行"""
<|body_0|>
def is_desription_effect(self, compname):
"""判断描述是否生效"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.driver = driver
self.comp_name = comp... | stack_v2_sparse_classes_36k_train_022449 | 3,115 | no_license | [
{
"docstring": "类初始化执行",
"name": "__init__",
"signature": "def __init__(self, driver, comp_name)"
},
{
"docstring": "判断描述是否生效",
"name": "is_desription_effect",
"signature": "def is_desription_effect(self, compname)"
}
] | 2 | null | Implement the Python class `RecordPhonePage` described below.
Class description:
微信录音控件
Method signatures and docstrings:
- def __init__(self, driver, comp_name): 类初始化执行
- def is_desription_effect(self, compname): 判断描述是否生效 | Implement the Python class `RecordPhonePage` described below.
Class description:
微信录音控件
Method signatures and docstrings:
- def __init__(self, driver, comp_name): 类初始化执行
- def is_desription_effect(self, compname): 判断描述是否生效
<|skeleton|>
class RecordPhonePage:
"""微信录音控件"""
def __init__(self, driver, comp_name... | 78768989a79a14013b983024cf6e4838d51ed595 | <|skeleton|>
class RecordPhonePage:
"""微信录音控件"""
def __init__(self, driver, comp_name):
"""类初始化执行"""
<|body_0|>
def is_desription_effect(self, compname):
"""判断描述是否生效"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecordPhonePage:
"""微信录音控件"""
def __init__(self, driver, comp_name):
"""类初始化执行"""
self.driver = driver
self.comp_name = comp_name
self.element = self.get_component()
def is_desription_effect(self, compname):
"""判断描述是否生效"""
elem = self.find_element('[na... | the_stack_v2_python_sparse | test_case/page_obj/form/record_page.py | pylk/pythonSelenium | train | 0 |
a8fd8388eb5c14ea67d0fab815be2483836985ff | [
"self.aDJM = aDJM\nself.order = len(aDJM)\nself.vs = [Graph.Vertex(self, i, self.no_labeling_num) for i in range(self.order)]",
"result = []\nfor v in vs:\n if v.label == self.no_labeling_num:\n result.append(v)\nreturn result",
"label = 0\nv = self.vs[0]\nv.label = label\nif v.adjacentVs() == []:\n ... | <|body_start_0|>
self.aDJM = aDJM
self.order = len(aDJM)
self.vs = [Graph.Vertex(self, i, self.no_labeling_num) for i in range(self.order)]
<|end_body_0|>
<|body_start_1|>
result = []
for v in vs:
if v.label == self.no_labeling_num:
result.append(v)
... | Graph | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Graph:
def __init__(self, aDJM):
""":param aDJM:隣接行列"""
<|body_0|>
def no_labelingVs(self, vs):
"""渡された頂点リストにおいてlabelingされていない頂点のリストを返す :return:"""
<|body_1|>
def isconnected(self):
"""このグラフが連結グラフであるかどうかを判定する :return:"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k_train_022450 | 4,624 | permissive | [
{
"docstring": ":param aDJM:隣接行列",
"name": "__init__",
"signature": "def __init__(self, aDJM)"
},
{
"docstring": "渡された頂点リストにおいてlabelingされていない頂点のリストを返す :return:",
"name": "no_labelingVs",
"signature": "def no_labelingVs(self, vs)"
},
{
"docstring": "このグラフが連結グラフであるかどうかを判定する :return... | 3 | null | Implement the Python class `Graph` described below.
Class description:
Implement the Graph class.
Method signatures and docstrings:
- def __init__(self, aDJM): :param aDJM:隣接行列
- def no_labelingVs(self, vs): 渡された頂点リストにおいてlabelingされていない頂点のリストを返す :return:
- def isconnected(self): このグラフが連結グラフであるかどうかを判定する :return: | Implement the Python class `Graph` described below.
Class description:
Implement the Graph class.
Method signatures and docstrings:
- def __init__(self, aDJM): :param aDJM:隣接行列
- def no_labelingVs(self, vs): 渡された頂点リストにおいてlabelingされていない頂点のリストを返す :return:
- def isconnected(self): このグラフが連結グラフであるかどうかを判定する :return:
<|ske... | 50f6d5c92a01792552c31ac912ce1cd557b06fb0 | <|skeleton|>
class Graph:
def __init__(self, aDJM):
""":param aDJM:隣接行列"""
<|body_0|>
def no_labelingVs(self, vs):
"""渡された頂点リストにおいてlabelingされていない頂点のリストを返す :return:"""
<|body_1|>
def isconnected(self):
"""このグラフが連結グラフであるかどうかを判定する :return:"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Graph:
def __init__(self, aDJM):
""":param aDJM:隣接行列"""
self.aDJM = aDJM
self.order = len(aDJM)
self.vs = [Graph.Vertex(self, i, self.no_labeling_num) for i in range(self.order)]
def no_labelingVs(self, vs):
"""渡された頂点リストにおいてlabelingされていない頂点のリストを返す :return:"""
... | the_stack_v2_python_sparse | airoiro/iro4.py | yosho-18/AtCoder | train | 0 | |
43637705175d3e7cbb33ea7c17e2058772e23e7e | [
"errors = {}\nif user_input is not None:\n if user_input[CONF_GATEWAY]:\n return await self.async_step_gateway()\n errors['base'] = 'no_device_selected'\nreturn self.async_show_form(step_id='user', data_schema=CONFIG_SCHEMA, errors=errors)",
"errors = {}\nif user_input is not None:\n host = user_i... | <|body_start_0|>
errors = {}
if user_input is not None:
if user_input[CONF_GATEWAY]:
return await self.async_step_gateway()
errors['base'] = 'no_device_selected'
return self.async_show_form(step_id='user', data_schema=CONFIG_SCHEMA, errors=errors)
<|end_bo... | Handle a Xiaomi Miio config flow. | XiaomiMiioFlowHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XiaomiMiioFlowHandler:
"""Handle a Xiaomi Miio config flow."""
async def async_step_user(self, user_input=None):
"""Handle a flow initialized by the user."""
<|body_0|>
async def async_step_gateway(self, user_input=None):
"""Handle a flow initialized by the user ... | stack_v2_sparse_classes_36k_train_022451 | 2,817 | permissive | [
{
"docstring": "Handle a flow initialized by the user.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input=None)"
},
{
"docstring": "Handle a flow initialized by the user to configure a gateway.",
"name": "async_step_gateway",
"signature": "async def asy... | 2 | stack_v2_sparse_classes_30k_train_015909 | Implement the Python class `XiaomiMiioFlowHandler` described below.
Class description:
Handle a Xiaomi Miio config flow.
Method signatures and docstrings:
- async def async_step_user(self, user_input=None): Handle a flow initialized by the user.
- async def async_step_gateway(self, user_input=None): Handle a flow ini... | Implement the Python class `XiaomiMiioFlowHandler` described below.
Class description:
Handle a Xiaomi Miio config flow.
Method signatures and docstrings:
- async def async_step_user(self, user_input=None): Handle a flow initialized by the user.
- async def async_step_gateway(self, user_input=None): Handle a flow ini... | ecdcfb835dc708aa8cd035adbe41dfb104203586 | <|skeleton|>
class XiaomiMiioFlowHandler:
"""Handle a Xiaomi Miio config flow."""
async def async_step_user(self, user_input=None):
"""Handle a flow initialized by the user."""
<|body_0|>
async def async_step_gateway(self, user_input=None):
"""Handle a flow initialized by the user ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XiaomiMiioFlowHandler:
"""Handle a Xiaomi Miio config flow."""
async def async_step_user(self, user_input=None):
"""Handle a flow initialized by the user."""
errors = {}
if user_input is not None:
if user_input[CONF_GATEWAY]:
return await self.async_ste... | the_stack_v2_python_sparse | homeassistant/components/xiaomi_miio/config_flow.py | callsSolve/core | train | 1 |
bc8d8c344fede5ed0c5737dec5870c3cd46f1a53 | [
"mock_get_root.return_value = 'a/b'\nvscode_workspace_file_gen.generate_code_workspace_file(['a/b/path_to_project1', 'a/b/path_to_project2'])\nself.assertTrue(mock_get_root.called)\nself.assertTrue(mock_ws_content.called)\nself.assertTrue(mock_get_unique.called)",
"abs_path = 'a/b'\nfolder_name = 'Settings'\nres ... | <|body_start_0|>
mock_get_root.return_value = 'a/b'
vscode_workspace_file_gen.generate_code_workspace_file(['a/b/path_to_project1', 'a/b/path_to_project2'])
self.assertTrue(mock_get_root.called)
self.assertTrue(mock_ws_content.called)
self.assertTrue(mock_get_unique.called)
<|end... | Unit tests for ide_util.py. | WorkspaceProjectFileGenUnittests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkspaceProjectFileGenUnittests:
"""Unit tests for ide_util.py."""
def test_vdcode_apply_optional_config(self, mock_get_root, mock_ws_content, mock_get_unique):
"""Test IdeVSCode's apply_optional_config method."""
<|body_0|>
def test_create_code_workspace_file_content(s... | stack_v2_sparse_classes_36k_train_022452 | 2,875 | no_license | [
{
"docstring": "Test IdeVSCode's apply_optional_config method.",
"name": "test_vdcode_apply_optional_config",
"signature": "def test_vdcode_apply_optional_config(self, mock_get_root, mock_ws_content, mock_get_unique)"
},
{
"docstring": "Test _create_code_workspace_file_content function.",
"n... | 3 | null | Implement the Python class `WorkspaceProjectFileGenUnittests` described below.
Class description:
Unit tests for ide_util.py.
Method signatures and docstrings:
- def test_vdcode_apply_optional_config(self, mock_get_root, mock_ws_content, mock_get_unique): Test IdeVSCode's apply_optional_config method.
- def test_crea... | Implement the Python class `WorkspaceProjectFileGenUnittests` described below.
Class description:
Unit tests for ide_util.py.
Method signatures and docstrings:
- def test_vdcode_apply_optional_config(self, mock_get_root, mock_ws_content, mock_get_unique): Test IdeVSCode's apply_optional_config method.
- def test_crea... | 78a61ca023cbf1a0cecfef8b97df2b274ac3a988 | <|skeleton|>
class WorkspaceProjectFileGenUnittests:
"""Unit tests for ide_util.py."""
def test_vdcode_apply_optional_config(self, mock_get_root, mock_ws_content, mock_get_unique):
"""Test IdeVSCode's apply_optional_config method."""
<|body_0|>
def test_create_code_workspace_file_content(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkspaceProjectFileGenUnittests:
"""Unit tests for ide_util.py."""
def test_vdcode_apply_optional_config(self, mock_get_root, mock_ws_content, mock_get_unique):
"""Test IdeVSCode's apply_optional_config method."""
mock_get_root.return_value = 'a/b'
vscode_workspace_file_gen.gener... | the_stack_v2_python_sparse | tools/asuite/aidegen/vscode/vscode_workspace_file_gen_unittest.py | ZYHGOD-1/Aosp11 | train | 0 |
9a902a69e308a9068ac7806a347d715ab2e2e75d | [
"self.microphys_data = microphysdata\nself.basemap = basemap\nself.fields = microphys_data['fields']\nif lon_name is None:\n self.longitude = self.microphys_data['longitude']\nelse:\n self.longitude = self.microphys_data[lon_name]\nif lat_name is None:\n self.latitude = self.microphys_data['latitude']\nels... | <|body_start_0|>
self.microphys_data = microphysdata
self.basemap = basemap
self.fields = microphys_data['fields']
if lon_name is None:
self.longitude = self.microphys_data['longitude']
else:
self.longitude = self.microphys_data[lon_name]
if lat_na... | Create a vertical plot of microphysical data. This class was created for microphysical retrievals from radar systems, for example the LATMOS French Falcon. | MicrophysicalVerticalPlot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MicrophysicalVerticalPlot:
"""Create a vertical plot of microphysical data. This class was created for microphysical retrievals from radar systems, for example the LATMOS French Falcon."""
def __init__(self, microphysdata, basemap=None, lon_name=None, lat_name=None, height_name=None, time_na... | stack_v2_sparse_classes_36k_train_022453 | 31,840 | no_license | [
{
"docstring": "Intitialize the class to create plots Parameters ---------- radar : dict AWOT radar instance. basemap : basemap instance lon_name : str Key in radar instance for longitude variable. None uses AWOT default. lat_name : str Key in radar instance for latitude variable. None uses AWOT default. height... | 5 | stack_v2_sparse_classes_30k_train_001790 | Implement the Python class `MicrophysicalVerticalPlot` described below.
Class description:
Create a vertical plot of microphysical data. This class was created for microphysical retrievals from radar systems, for example the LATMOS French Falcon.
Method signatures and docstrings:
- def __init__(self, microphysdata, b... | Implement the Python class `MicrophysicalVerticalPlot` described below.
Class description:
Create a vertical plot of microphysical data. This class was created for microphysical retrievals from radar systems, for example the LATMOS French Falcon.
Method signatures and docstrings:
- def __init__(self, microphysdata, b... | 0be59e6d8e500767634551c11d876252190111ac | <|skeleton|>
class MicrophysicalVerticalPlot:
"""Create a vertical plot of microphysical data. This class was created for microphysical retrievals from radar systems, for example the LATMOS French Falcon."""
def __init__(self, microphysdata, basemap=None, lon_name=None, lat_name=None, height_name=None, time_na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MicrophysicalVerticalPlot:
"""Create a vertical plot of microphysical data. This class was created for microphysical retrievals from radar systems, for example the LATMOS French Falcon."""
def __init__(self, microphysdata, basemap=None, lon_name=None, lat_name=None, height_name=None, time_name=None):
... | the_stack_v2_python_sparse | awot/graph/radar_vertical.py | tjlang/AWOT | train | 0 |
706903ab7fc75bee1dbf4feabb11a502f0c2182e | [
"self.data = data\nif instruments is None:\n self.instruments = []\nelif set.intersection(set(exog), set(instruments)) != set([]):\n raise ValueError(\"Don't put cols in exog and instruments.\")\nelse:\n self.instruments = list(instruments)\nself.endog = endog\nself.exog = list(exog)\nself.n_moms = len(sel... | <|body_start_0|>
self.data = data
if instruments is None:
self.instruments = []
elif set.intersection(set(exog), set(instruments)) != set([]):
raise ValueError("Don't put cols in exog and instruments.")
else:
self.instruments = list(instruments)
... | Earns a class. example endog = ['hhninc'] exog = ['const', 'age', 'educ', 'female'] instruments = ['hsat', 'married'] obj = GMM(dta_gmm, endog, exog, instruments) res = obj.fit([-1, 1, .1, .2]) | GMM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GMM:
"""Earns a class. example endog = ['hhninc'] exog = ['const', 'age', 'educ', 'female'] instruments = ['hsat', 'married'] obj = GMM(dta_gmm, endog, exog, instruments) res = obj.fit([-1, 1, .1, .2])"""
def __init__(self, data, endog, exog, instruments=None, form='linear'):
"""data... | stack_v2_sparse_classes_36k_train_022454 | 3,058 | no_license | [
{
"docstring": "data: An entire dataframe endog: Str. Column name. exog: List: exogenous variables. instruments: list. Doesn't include exog. Probably want to add a formula option and integrate with patsy.",
"name": "__init__",
"signature": "def __init__(self, data, endog, exog, instruments=None, form='l... | 3 | stack_v2_sparse_classes_30k_train_008542 | Implement the Python class `GMM` described below.
Class description:
Earns a class. example endog = ['hhninc'] exog = ['const', 'age', 'educ', 'female'] instruments = ['hsat', 'married'] obj = GMM(dta_gmm, endog, exog, instruments) res = obj.fit([-1, 1, .1, .2])
Method signatures and docstrings:
- def __init__(self, ... | Implement the Python class `GMM` described below.
Class description:
Earns a class. example endog = ['hhninc'] exog = ['const', 'age', 'educ', 'female'] instruments = ['hsat', 'married'] obj = GMM(dta_gmm, endog, exog, instruments) res = obj.fit([-1, 1, .1, .2])
Method signatures and docstrings:
- def __init__(self, ... | c987277e1eee12c17aa2febdc63a21dc587d9792 | <|skeleton|>
class GMM:
"""Earns a class. example endog = ['hhninc'] exog = ['const', 'age', 'educ', 'female'] instruments = ['hsat', 'married'] obj = GMM(dta_gmm, endog, exog, instruments) res = obj.fit([-1, 1, .1, .2])"""
def __init__(self, data, endog, exog, instruments=None, form='linear'):
"""data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GMM:
"""Earns a class. example endog = ['hhninc'] exog = ['const', 'age', 'educ', 'female'] instruments = ['hsat', 'married'] obj = GMM(dta_gmm, endog, exog, instruments) res = obj.fit([-1, 1, .1, .2])"""
def __init__(self, data, endog, exog, instruments=None, form='linear'):
"""data: An entire d... | the_stack_v2_python_sparse | new_start/GMM.py | TomAugspurger/data-wrangling | train | 0 |
d9e557ec3e189281715e55d81fa18c5f3dcfe623 | [
"B, C = features.shape[:2]\nfeatures = features.contiguous()\ncoords = coords.contiguous()\nouts, inds, wgts = trilinear_devoxelize_forward(resolution, is_training, coords, features)\nif is_training:\n ctx.save_for_backward(inds, wgts)\n ctx.r = resolution\nreturn outs",
"inds, wgts = ctx.saved_tensors\ngra... | <|body_start_0|>
B, C = features.shape[:2]
features = features.contiguous()
coords = coords.contiguous()
outs, inds, wgts = trilinear_devoxelize_forward(resolution, is_training, coords, features)
if is_training:
ctx.save_for_backward(inds, wgts)
ctx.r = re... | TrilinearDevoxelization | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrilinearDevoxelization:
def forward(ctx, features, coords, resolution, is_training=True):
"""Forward pass for the Op. Args: ctx: torch Autograd context. coords: the coordinates of points, FloatTensor[B, 3, N] features: FloatTensor[B, C, R, R, R] resolution: int, the voxel resolution. is... | stack_v2_sparse_classes_36k_train_022455 | 22,879 | permissive | [
{
"docstring": "Forward pass for the Op. Args: ctx: torch Autograd context. coords: the coordinates of points, FloatTensor[B, 3, N] features: FloatTensor[B, C, R, R, R] resolution: int, the voxel resolution. is_training: bool, training mode. Returns: torch.FloatTensor: devoxelized features (B, C, N)",
"name... | 2 | stack_v2_sparse_classes_30k_train_013063 | Implement the Python class `TrilinearDevoxelization` described below.
Class description:
Implement the TrilinearDevoxelization class.
Method signatures and docstrings:
- def forward(ctx, features, coords, resolution, is_training=True): Forward pass for the Op. Args: ctx: torch Autograd context. coords: the coordinate... | Implement the Python class `TrilinearDevoxelization` described below.
Class description:
Implement the TrilinearDevoxelization class.
Method signatures and docstrings:
- def forward(ctx, features, coords, resolution, is_training=True): Forward pass for the Op. Args: ctx: torch Autograd context. coords: the coordinate... | 51482281dc180786e7563c73c12ac5df89289748 | <|skeleton|>
class TrilinearDevoxelization:
def forward(ctx, features, coords, resolution, is_training=True):
"""Forward pass for the Op. Args: ctx: torch Autograd context. coords: the coordinates of points, FloatTensor[B, 3, N] features: FloatTensor[B, C, R, R, R] resolution: int, the voxel resolution. is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrilinearDevoxelization:
def forward(ctx, features, coords, resolution, is_training=True):
"""Forward pass for the Op. Args: ctx: torch Autograd context. coords: the coordinates of points, FloatTensor[B, 3, N] features: FloatTensor[B, C, R, R, R] resolution: int, the voxel resolution. is_training: boo... | the_stack_v2_python_sparse | ml3d/torch/models/pvcnn.py | CosmosHua/Open3D-ML | train | 0 | |
608eda567b1c98079ef6384daee47e21bb89f84b | [
"writer = KvDbWriter(KvDbClient(**config))\nfor configured_stream in configured_catalog.streams:\n if configured_stream.destination_sync_mode == DestinationSyncMode.overwrite:\n writer.delete_stream_entries(configured_stream.stream.name)\nfor message in input_messages:\n if message.type == Type.STATE:\... | <|body_start_0|>
writer = KvDbWriter(KvDbClient(**config))
for configured_stream in configured_catalog.streams:
if configured_stream.destination_sync_mode == DestinationSyncMode.overwrite:
writer.delete_stream_entries(configured_stream.stream.name)
for message in inpu... | DestinationKvdb | [
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"Elastic-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DestinationKvdb:
def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]:
"""Reads the input stream of messages, config, and catalog to write data to the destination. This method return... | stack_v2_sparse_classes_36k_train_022456 | 3,439 | permissive | [
{
"docstring": "Reads the input stream of messages, config, and catalog to write data to the destination. This method returns an iterable (typically a generator of AirbyteMessages via yield) containing state messages received in the input message stream. Outputting a state message means that every AirbyteRecord... | 2 | stack_v2_sparse_classes_30k_train_013932 | Implement the Python class `DestinationKvdb` described below.
Class description:
Implement the DestinationKvdb class.
Method signatures and docstrings:
- def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]: Read... | Implement the Python class `DestinationKvdb` described below.
Class description:
Implement the DestinationKvdb class.
Method signatures and docstrings:
- def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]: Read... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class DestinationKvdb:
def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]:
"""Reads the input stream of messages, config, and catalog to write data to the destination. This method return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DestinationKvdb:
def write(self, config: Mapping[str, Any], configured_catalog: ConfiguredAirbyteCatalog, input_messages: Iterable[AirbyteMessage]) -> Iterable[AirbyteMessage]:
"""Reads the input stream of messages, config, and catalog to write data to the destination. This method returns an iterable ... | the_stack_v2_python_sparse | dts/airbyte/airbyte-integrations/connectors/destination-kvdb/destination_kvdb/destination.py | alldatacenter/alldata | train | 774 | |
15707efd7e60e88e0f8a7fed6443b354c96b9833 | [
"self.archive_log_enabled = archive_log_enabled\nself.bct_enabled = bct_enabled\nself.container_database_info = container_database_info\nself.data_guard_info = data_guard_info\nself.database_unique_name = database_unique_name\nself.db_type = db_type\nself.domain = domain\nself.fra_size = fra_size\nself.hosts = host... | <|body_start_0|>
self.archive_log_enabled = archive_log_enabled
self.bct_enabled = bct_enabled
self.container_database_info = container_database_info
self.data_guard_info = data_guard_info
self.database_unique_name = database_unique_name
self.db_type = db_type
sel... | Implementation of the 'OracleProtectionSource' model. Specifies an Object representing one Oracle database. Attributes: archive_log_enabled (bool): Specifies whether the database is running in ARCHIVELOG mode. It enables the redo of log files into archived redo log files. bct_enabled (bool): Specifies whether the Block... | OracleProtectionSource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OracleProtectionSource:
"""Implementation of the 'OracleProtectionSource' model. Specifies an Object representing one Oracle database. Attributes: archive_log_enabled (bool): Specifies whether the database is running in ARCHIVELOG mode. It enables the redo of log files into archived redo log file... | stack_v2_sparse_classes_36k_train_022457 | 8,462 | permissive | [
{
"docstring": "Constructor for the OracleProtectionSource class",
"name": "__init__",
"signature": "def __init__(self, archive_log_enabled=None, bct_enabled=None, container_database_info=None, data_guard_info=None, database_unique_name=None, db_type=None, domain=None, fra_size=None, hosts=None, name=No... | 2 | null | Implement the Python class `OracleProtectionSource` described below.
Class description:
Implementation of the 'OracleProtectionSource' model. Specifies an Object representing one Oracle database. Attributes: archive_log_enabled (bool): Specifies whether the database is running in ARCHIVELOG mode. It enables the redo o... | Implement the Python class `OracleProtectionSource` described below.
Class description:
Implementation of the 'OracleProtectionSource' model. Specifies an Object representing one Oracle database. Attributes: archive_log_enabled (bool): Specifies whether the database is running in ARCHIVELOG mode. It enables the redo o... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class OracleProtectionSource:
"""Implementation of the 'OracleProtectionSource' model. Specifies an Object representing one Oracle database. Attributes: archive_log_enabled (bool): Specifies whether the database is running in ARCHIVELOG mode. It enables the redo of log files into archived redo log file... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OracleProtectionSource:
"""Implementation of the 'OracleProtectionSource' model. Specifies an Object representing one Oracle database. Attributes: archive_log_enabled (bool): Specifies whether the database is running in ARCHIVELOG mode. It enables the redo of log files into archived redo log files. bct_enable... | the_stack_v2_python_sparse | cohesity_management_sdk/models/oracle_protection_source.py | cohesity/management-sdk-python | train | 24 |
b38a14bc6c01abfa6d91e42a678285ac9adef3dc | [
"self.url: str | None = None\nself.token: str | None = None\nself.uuid: str | None = None",
"errors = {}\nplaceholders = {'local_token': '/112f7a4a-0051-cc2b-3b61-1898181b9950', 'find_token': '0481effe8a5c6f757b455babb678dc0e764feae279/112f7a4a-0051-cc2b-3b61-1898181b9950', 'local_url': 'ws://192.168.1.39:8083', ... | <|body_start_0|>
self.url: str | None = None
self.token: str | None = None
self.uuid: str | None = None
<|end_body_0|>
<|body_start_1|>
errors = {}
placeholders = {'local_token': '/112f7a4a-0051-cc2b-3b61-1898181b9950', 'find_token': '0481effe8a5c6f757b455babb678dc0e764feae279/1... | ZWaveMe integration config flow. | ZWaveMeConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZWaveMeConfigFlow:
"""ZWaveMe integration config flow."""
def __init__(self) -> None:
"""Initialize flow."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, str] | None=None) -> FlowResult:
"""Handle a flow initialized by the user or started with... | stack_v2_sparse_classes_36k_train_022458 | 3,507 | permissive | [
{
"docstring": "Initialize flow.",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Handle a flow initialized by the user or started with zeroconf.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input: dict[str, str] | None... | 3 | null | Implement the Python class `ZWaveMeConfigFlow` described below.
Class description:
ZWaveMe integration config flow.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize flow.
- async def async_step_user(self, user_input: dict[str, str] | None=None) -> FlowResult: Handle a flow initialized by the... | Implement the Python class `ZWaveMeConfigFlow` described below.
Class description:
ZWaveMe integration config flow.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize flow.
- async def async_step_user(self, user_input: dict[str, str] | None=None) -> FlowResult: Handle a flow initialized by the... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ZWaveMeConfigFlow:
"""ZWaveMe integration config flow."""
def __init__(self) -> None:
"""Initialize flow."""
<|body_0|>
async def async_step_user(self, user_input: dict[str, str] | None=None) -> FlowResult:
"""Handle a flow initialized by the user or started with... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZWaveMeConfigFlow:
"""ZWaveMe integration config flow."""
def __init__(self) -> None:
"""Initialize flow."""
self.url: str | None = None
self.token: str | None = None
self.uuid: str | None = None
async def async_step_user(self, user_input: dict[str, str] | None=None) ... | the_stack_v2_python_sparse | homeassistant/components/zwave_me/config_flow.py | home-assistant/core | train | 35,501 |
ffbcf06dfb4ca6f267808f4235baf87d86dcaf11 | [
"E0 = a0 * m_e * c ** 2 * k0 / e\nzr = 0.5 * k0 * waist ** 2\nself.m = m\nself.n = n\nself.k0 = k0\nself.waist = waist\nself.zr = zr\nself.inv_tau = 1.0 / tau\nself.t_peak = t_peak\nself.E0 = E0\nself.v_antenna = source_v\nself.focal_length = focal_length\nself.boost = boost\nself.temporal_order = temporal_order\ns... | <|body_start_0|>
E0 = a0 * m_e * c ** 2 * k0 / e
zr = 0.5 * k0 * waist ** 2
self.m = m
self.n = n
self.k0 = k0
self.waist = waist
self.zr = zr
self.inv_tau = 1.0 / tau
self.t_peak = t_peak
self.E0 = E0
self.v_antenna = source_v
... | Class that calculates a Laguerre-Gaussian laser pulse. A typical LG pulse is defined as : E(x,y,z) = \\left( rac{r \\sqrt{2}}{w} ight)^n L_{mn} \\left[ rac{2 r^2}{w^2} ight] e^{- i n arphi} \\; GaussianProfile where r = (x^2 + y^2)^(1/2) and \\phi = arctan(y/x). n and m are specific parameters to calculate the Laguerre... | LaguerreGaussianProfile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LaguerreGaussianProfile:
"""Class that calculates a Laguerre-Gaussian laser pulse. A typical LG pulse is defined as : E(x,y,z) = \\left( rac{r \\sqrt{2}}{w} ight)^n L_{mn} \\left[ rac{2 r^2}{w^2} ight] e^{- i n arphi} \\; GaussianProfile where r = (x^2 + y^2)^(1/2) and \\phi = arctan(y/x). n and ... | stack_v2_sparse_classes_36k_train_022459 | 34,589 | permissive | [
{
"docstring": "Define a Laguerre-Gaussian laser profile. (Laguerre-Gaussian transversally, hypergaussian longitudinally) This object can then be passed to the `EM3D` class, as the argument `laser_func`, in order to have a LG laser emitted by the antenna. Parameters: ----------- m, n: integer (dimensionless) La... | 2 | null | Implement the Python class `LaguerreGaussianProfile` described below.
Class description:
Class that calculates a Laguerre-Gaussian laser pulse. A typical LG pulse is defined as : E(x,y,z) = \\left( rac{r \\sqrt{2}}{w} ight)^n L_{mn} \\left[ rac{2 r^2}{w^2} ight] e^{- i n arphi} \\; GaussianProfile where r = (x^2 + y^2... | Implement the Python class `LaguerreGaussianProfile` described below.
Class description:
Class that calculates a Laguerre-Gaussian laser pulse. A typical LG pulse is defined as : E(x,y,z) = \\left( rac{r \\sqrt{2}}{w} ight)^n L_{mn} \\left[ rac{2 r^2}{w^2} ight] e^{- i n arphi} \\; GaussianProfile where r = (x^2 + y^2... | 091c982f82788209017315e13eb7d0e743687d46 | <|skeleton|>
class LaguerreGaussianProfile:
"""Class that calculates a Laguerre-Gaussian laser pulse. A typical LG pulse is defined as : E(x,y,z) = \\left( rac{r \\sqrt{2}}{w} ight)^n L_{mn} \\left[ rac{2 r^2}{w^2} ight] e^{- i n arphi} \\; GaussianProfile where r = (x^2 + y^2)^(1/2) and \\phi = arctan(y/x). n and ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LaguerreGaussianProfile:
"""Class that calculates a Laguerre-Gaussian laser pulse. A typical LG pulse is defined as : E(x,y,z) = \\left( rac{r \\sqrt{2}}{w} ight)^n L_{mn} \\left[ rac{2 r^2}{w^2} ight] e^{- i n arphi} \\; GaussianProfile where r = (x^2 + y^2)^(1/2) and \\phi = arctan(y/x). n and m are specifi... | the_stack_v2_python_sparse | scripts/field_solvers/laser/laser_profiles.py | giadarol/warp | train | 0 |
809e0ddfe452d0539740c3110e4a7058ae5de761 | [
"user_events = self.user_events(user_obj)\nsubmitted_cases = set()\nfor event in user_events:\n if event.get('verb') != 'mme_add':\n continue\n case_obj = self.case(case_id=event.get('case'))\n if case_obj is None:\n continue\n if case_obj.get('mme_submission') is None or case_obj['mme_sub... | <|body_start_0|>
user_events = self.user_events(user_obj)
submitted_cases = set()
for event in user_events:
if event.get('verb') != 'mme_add':
continue
case_obj = self.case(case_id=event.get('case'))
if case_obj is None:
continu... | Class to handle case submissions to MatchMaker Exchange | MMEHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MMEHandler:
"""Class to handle case submissions to MatchMaker Exchange"""
def user_mme_submissions(self, user_obj):
"""Return a set of all case _ids submitted to the Matchmaker Exchange by a user. Args: user_obj(dict): a scout user object Returns: submitted_cases(set); a set of case ... | stack_v2_sparse_classes_36k_train_022460 | 6,236 | permissive | [
{
"docstring": "Return a set of all case _ids submitted to the Matchmaker Exchange by a user. Args: user_obj(dict): a scout user object Returns: submitted_cases(set); a set of case _ids",
"name": "user_mme_submissions",
"signature": "def user_mme_submissions(self, user_obj)"
},
{
"docstring": "R... | 4 | null | Implement the Python class `MMEHandler` described below.
Class description:
Class to handle case submissions to MatchMaker Exchange
Method signatures and docstrings:
- def user_mme_submissions(self, user_obj): Return a set of all case _ids submitted to the Matchmaker Exchange by a user. Args: user_obj(dict): a scout ... | Implement the Python class `MMEHandler` described below.
Class description:
Class to handle case submissions to MatchMaker Exchange
Method signatures and docstrings:
- def user_mme_submissions(self, user_obj): Return a set of all case _ids submitted to the Matchmaker Exchange by a user. Args: user_obj(dict): a scout ... | 1e6a633ba0a83495047ee7b66db1ebf690ee465f | <|skeleton|>
class MMEHandler:
"""Class to handle case submissions to MatchMaker Exchange"""
def user_mme_submissions(self, user_obj):
"""Return a set of all case _ids submitted to the Matchmaker Exchange by a user. Args: user_obj(dict): a scout user object Returns: submitted_cases(set); a set of case ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MMEHandler:
"""Class to handle case submissions to MatchMaker Exchange"""
def user_mme_submissions(self, user_obj):
"""Return a set of all case _ids submitted to the Matchmaker Exchange by a user. Args: user_obj(dict): a scout user object Returns: submitted_cases(set); a set of case _ids"""
... | the_stack_v2_python_sparse | scout/adapter/mongo/matchmaker.py | Clinical-Genomics/scout | train | 143 |
2526648dfc1c8c959ea71e3f19dddf33015f6782 | [
"parsed = item.parsed\nstatus_list = ['HPR status = %s' % self.DecodeChar(parsed.flag, self.decoder.GBS_FLAG_DECODE)]\nself.FormatGBS(item, extra=status_list)",
"parsed = item.parsed\ndecoded = item.decoded\ntime_list = ['SBAS status for GPS week/second %s/%s' % (parsed.week, parsed.second)]\nif decoded.dtime:\n ... | <|body_start_0|>
parsed = item.parsed
status_list = ['HPR status = %s' % self.DecodeChar(parsed.flag, self.decoder.GBS_FLAG_DECODE)]
self.FormatGBS(item, extra=status_list)
<|end_body_0|>
<|body_start_1|>
parsed = item.parsed
decoded = item.decoded
time_list = ['SBAS sta... | Class for Hemisphere/Geneq NMEA formatter objects. | NmeaFormatter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NmeaFormatter:
"""Class for Hemisphere/Geneq NMEA formatter objects."""
def FormatPSAT_GBS(self, item):
"""Format a PSAT,GBS sentence."""
<|body_0|>
def FormatRD1(self, item):
"""Format an RD1 sentence."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022461 | 23,235 | no_license | [
{
"docstring": "Format a PSAT,GBS sentence.",
"name": "FormatPSAT_GBS",
"signature": "def FormatPSAT_GBS(self, item)"
},
{
"docstring": "Format an RD1 sentence.",
"name": "FormatRD1",
"signature": "def FormatRD1(self, item)"
}
] | 2 | null | Implement the Python class `NmeaFormatter` described below.
Class description:
Class for Hemisphere/Geneq NMEA formatter objects.
Method signatures and docstrings:
- def FormatPSAT_GBS(self, item): Format a PSAT,GBS sentence.
- def FormatRD1(self, item): Format an RD1 sentence. | Implement the Python class `NmeaFormatter` described below.
Class description:
Class for Hemisphere/Geneq NMEA formatter objects.
Method signatures and docstrings:
- def FormatPSAT_GBS(self, item): Format a PSAT,GBS sentence.
- def FormatRD1(self, item): Format an RD1 sentence.
<|skeleton|>
class NmeaFormatter:
... | 1a6471dfbd7ec27f3d9f42b49173d18761a8f5aa | <|skeleton|>
class NmeaFormatter:
"""Class for Hemisphere/Geneq NMEA formatter objects."""
def FormatPSAT_GBS(self, item):
"""Format a PSAT,GBS sentence."""
<|body_0|>
def FormatRD1(self, item):
"""Format an RD1 sentence."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NmeaFormatter:
"""Class for Hemisphere/Geneq NMEA formatter objects."""
def FormatPSAT_GBS(self, item):
"""Format a PSAT,GBS sentence."""
parsed = item.parsed
status_list = ['HPR status = %s' % self.DecodeChar(parsed.flag, self.decoder.GBS_FLAG_DECODE)]
self.FormatGBS(item... | the_stack_v2_python_sparse | fwgnss/format/hemisphere.py | fhgwright/fwgnss | train | 2 |
347742d07c623bc4c91b6d8fa90d2bb14ae0ee3b | [
"super().__init__(config, global_config, parent)\nself._temp_dir = self.config.get('temp_dir')\nself.register([self.temp_dir_context])",
"if path is None and self._temp_dir is None:\n return TemporaryDirectory()\nreturn nullcontext(path or self._temp_dir)"
] | <|body_start_0|>
super().__init__(config, global_config, parent)
self._temp_dir = self.config.get('temp_dir')
self.register([self.temp_dir_context])
<|end_body_0|>
<|body_start_1|>
if path is None and self._temp_dir is None:
return TemporaryDirectory()
return nullcon... | A *base* service class that provides a method to create a temporary directory context for local scripts. It is inherited by LocalExecService and MockLocalExecService. This class is not supposed to be used as a standalone service. | TempDirContextService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempDirContextService:
"""A *base* service class that provides a method to create a temporary directory context for local scripts. It is inherited by LocalExecService and MockLocalExecService. This class is not supposed to be used as a standalone service."""
def __init__(self, config: Option... | stack_v2_sparse_classes_36k_train_022462 | 2,199 | permissive | [
{
"docstring": "Create a new instance of a service that provides temporary directory context for local exec service. Parameters ---------- config : dict Free-format dictionary that contains parameters for the service. (E.g., root path for config files, etc.) global_config : dict Free-format dictionary of global... | 2 | stack_v2_sparse_classes_30k_train_008572 | Implement the Python class `TempDirContextService` described below.
Class description:
A *base* service class that provides a method to create a temporary directory context for local scripts. It is inherited by LocalExecService and MockLocalExecService. This class is not supposed to be used as a standalone service.
M... | Implement the Python class `TempDirContextService` described below.
Class description:
A *base* service class that provides a method to create a temporary directory context for local scripts. It is inherited by LocalExecService and MockLocalExecService. This class is not supposed to be used as a standalone service.
M... | 0db80043dad256d77dc4c2b4fc54aa0b0aa2597f | <|skeleton|>
class TempDirContextService:
"""A *base* service class that provides a method to create a temporary directory context for local scripts. It is inherited by LocalExecService and MockLocalExecService. This class is not supposed to be used as a standalone service."""
def __init__(self, config: Option... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TempDirContextService:
"""A *base* service class that provides a method to create a temporary directory context for local scripts. It is inherited by LocalExecService and MockLocalExecService. This class is not supposed to be used as a standalone service."""
def __init__(self, config: Optional[Dict[str, ... | the_stack_v2_python_sparse | mlos_bench/mlos_bench/services/local/temp_dir_context.py | microsoft/MLOS | train | 109 |
9e3e9c30f9b8440388e8e6677e1d7cc7b14c7f91 | [
"e = Inventory('test product code', 'test description', 'test market price', 'test rental price')\nself.assertEqual(e.product_code, 'test product code')\nself.assertEqual(e.description, 'test description')\nself.assertEqual(e.market_price, 'test market price')\nself.assertEqual(e.rental_price, 'test rental price')"... | <|body_start_0|>
e = Inventory('test product code', 'test description', 'test market price', 'test rental price')
self.assertEqual(e.product_code, 'test product code')
self.assertEqual(e.description, 'test description')
self.assertEqual(e.market_price, 'test market price')
self.a... | InventoryTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InventoryTest:
def test_inventory_init(self):
"""Tests that Inventory can be initiated"""
<|body_0|>
def test_inventory_return(self):
"""Tests Inventory return_as_dictionary"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
e = Inventory('test product... | stack_v2_sparse_classes_36k_train_022463 | 9,076 | no_license | [
{
"docstring": "Tests that Inventory can be initiated",
"name": "test_inventory_init",
"signature": "def test_inventory_init(self)"
},
{
"docstring": "Tests Inventory return_as_dictionary",
"name": "test_inventory_return",
"signature": "def test_inventory_return(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010590 | Implement the Python class `InventoryTest` described below.
Class description:
Implement the InventoryTest class.
Method signatures and docstrings:
- def test_inventory_init(self): Tests that Inventory can be initiated
- def test_inventory_return(self): Tests Inventory return_as_dictionary | Implement the Python class `InventoryTest` described below.
Class description:
Implement the InventoryTest class.
Method signatures and docstrings:
- def test_inventory_init(self): Tests that Inventory can be initiated
- def test_inventory_return(self): Tests Inventory return_as_dictionary
<|skeleton|>
class Invento... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class InventoryTest:
def test_inventory_init(self):
"""Tests that Inventory can be initiated"""
<|body_0|>
def test_inventory_return(self):
"""Tests Inventory return_as_dictionary"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InventoryTest:
def test_inventory_init(self):
"""Tests that Inventory can be initiated"""
e = Inventory('test product code', 'test description', 'test market price', 'test rental price')
self.assertEqual(e.product_code, 'test product code')
self.assertEqual(e.description, 'test... | the_stack_v2_python_sparse | students/kyle_lehning/Lesson01/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 | |
f41d9aa5ce5dcd04cc01b1109a73dcee668ac3df | [
"super(Decoder, self).__init__()\nself.batch_size = batch_size\nself.dec_units = dec_units\nself.embedding = tf.keras.layers.Embedding(input_dim=vocab_size, output_dim=embedding_dim)\nself.gru = tf.keras.layers.GRU(units=self.dec_units, return_sequences=True, return_state=True, recurrent_initializer='glorot_uniform... | <|body_start_0|>
super(Decoder, self).__init__()
self.batch_size = batch_size
self.dec_units = dec_units
self.embedding = tf.keras.layers.Embedding(input_dim=vocab_size, output_dim=embedding_dim)
self.gru = tf.keras.layers.GRU(units=self.dec_units, return_sequences=True, return_s... | The decoder model. | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""The decoder model."""
def __init__(self, vocab_size, embedding_dim, dec_units, batch_size):
"""The structure function. Args: vocab_size: The target language vocabulary size. embedding_dim: The embedding dimension. dec_units: The decoder hidden units. batch_size: The batch... | stack_v2_sparse_classes_36k_train_022464 | 20,417 | no_license | [
{
"docstring": "The structure function. Args: vocab_size: The target language vocabulary size. embedding_dim: The embedding dimension. dec_units: The decoder hidden units. batch_size: The batch size.",
"name": "__init__",
"signature": "def __init__(self, vocab_size, embedding_dim, dec_units, batch_size)... | 2 | stack_v2_sparse_classes_30k_train_018424 | Implement the Python class `Decoder` described below.
Class description:
The decoder model.
Method signatures and docstrings:
- def __init__(self, vocab_size, embedding_dim, dec_units, batch_size): The structure function. Args: vocab_size: The target language vocabulary size. embedding_dim: The embedding dimension. d... | Implement the Python class `Decoder` described below.
Class description:
The decoder model.
Method signatures and docstrings:
- def __init__(self, vocab_size, embedding_dim, dec_units, batch_size): The structure function. Args: vocab_size: The target language vocabulary size. embedding_dim: The embedding dimension. d... | d1b70b2a954f4665b628ba252b03c1a74b95559f | <|skeleton|>
class Decoder:
"""The decoder model."""
def __init__(self, vocab_size, embedding_dim, dec_units, batch_size):
"""The structure function. Args: vocab_size: The target language vocabulary size. embedding_dim: The embedding dimension. dec_units: The decoder hidden units. batch_size: The batch... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""The decoder model."""
def __init__(self, vocab_size, embedding_dim, dec_units, batch_size):
"""The structure function. Args: vocab_size: The target language vocabulary size. embedding_dim: The embedding dimension. dec_units: The decoder hidden units. batch_size: The batch size."""
... | the_stack_v2_python_sparse | NeuralNetworks-tensorflow/RNN/nmt_with_attention/nmt.py | zhaocc1106/machine_learn | train | 15 |
435f48322403ca8e571f3bccfe8cc3a0a1677b7e | [
"super().__init__()\ncheck_boundaries(boundaries)\nself.boundaries = boundaries",
"self.randomize(None)\nself.magnitude = self.R.uniform(low=self.boundaries[0], high=self.boundaries[1])\nsignal = convert_to_tensor(self.magnitude * signal)\nreturn signal"
] | <|body_start_0|>
super().__init__()
check_boundaries(boundaries)
self.boundaries = boundaries
<|end_body_0|>
<|body_start_1|>
self.randomize(None)
self.magnitude = self.R.uniform(low=self.boundaries[0], high=self.boundaries[1])
signal = convert_to_tensor(self.magnitude *... | Apply a random rescaling on a signal | SignalRandScale | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignalRandScale:
"""Apply a random rescaling on a signal"""
def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``"""
<|body_0|>
def __call__(sel... | stack_v2_sparse_classes_36k_train_022465 | 16,322 | permissive | [
{
"docstring": "Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``",
"name": "__init__",
"signature": "def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None"
},
{
"docstring": "Args: signal: input 1 dimension signal to be sc... | 2 | stack_v2_sparse_classes_30k_val_001174 | Implement the Python class `SignalRandScale` described below.
Class description:
Apply a random rescaling on a signal
Method signatures and docstrings:
- def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None: Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``... | Implement the Python class `SignalRandScale` described below.
Class description:
Apply a random rescaling on a signal
Method signatures and docstrings:
- def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None: Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``... | e48c3e2c741fa3fc705c4425d17ac4a5afac6c47 | <|skeleton|>
class SignalRandScale:
"""Apply a random rescaling on a signal"""
def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``"""
<|body_0|>
def __call__(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SignalRandScale:
"""Apply a random rescaling on a signal"""
def __init__(self, boundaries: Sequence[float]=(-1.0, 1.0)) -> None:
"""Args: boundaries: list defining lower and upper boundaries for the signal scaling, default : ``[-1.0, 1.0]``"""
super().__init__()
check_boundaries(b... | the_stack_v2_python_sparse | monai/transforms/signal/array.py | Project-MONAI/MONAI | train | 4,805 |
d45c0a98cf5d1ee7a2f539e6448716fb3487232a | [
"out_module_path = self.path + module_name + '/' + self.outpath_foldername + '/' + project_name + '/' + self.map_outputpath_folder[self.projects[project_name]['by']] + '/'\nif not os.path.exists(out_module_path):\n os.makedirs(out_module_path)\nreturn out_module_path",
"res_module_path = self.path + module_nam... | <|body_start_0|>
out_module_path = self.path + module_name + '/' + self.outpath_foldername + '/' + project_name + '/' + self.map_outputpath_folder[self.projects[project_name]['by']] + '/'
if not os.path.exists(out_module_path):
os.makedirs(out_module_path)
return out_module_path
<|en... | Framework | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Framework:
def get_outfolder_path(self, project_name, module_name):
"""Get the output folder path :param project_name: :param module_name: :return:"""
<|body_0|>
def get_resfolder_path(self, project_name, module_name):
"""Get the output folder path :param project_nam... | stack_v2_sparse_classes_36k_train_022466 | 1,538 | no_license | [
{
"docstring": "Get the output folder path :param project_name: :param module_name: :return:",
"name": "get_outfolder_path",
"signature": "def get_outfolder_path(self, project_name, module_name)"
},
{
"docstring": "Get the output folder path :param project_name: :param module_name: :return:",
... | 2 | null | Implement the Python class `Framework` described below.
Class description:
Implement the Framework class.
Method signatures and docstrings:
- def get_outfolder_path(self, project_name, module_name): Get the output folder path :param project_name: :param module_name: :return:
- def get_resfolder_path(self, project_nam... | Implement the Python class `Framework` described below.
Class description:
Implement the Framework class.
Method signatures and docstrings:
- def get_outfolder_path(self, project_name, module_name): Get the output folder path :param project_name: :param module_name: :return:
- def get_resfolder_path(self, project_nam... | f434776eb5966f706e6190b8ab576bf98229715f | <|skeleton|>
class Framework:
def get_outfolder_path(self, project_name, module_name):
"""Get the output folder path :param project_name: :param module_name: :return:"""
<|body_0|>
def get_resfolder_path(self, project_name, module_name):
"""Get the output folder path :param project_nam... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Framework:
def get_outfolder_path(self, project_name, module_name):
"""Get the output folder path :param project_name: :param module_name: :return:"""
out_module_path = self.path + module_name + '/' + self.outpath_foldername + '/' + project_name + '/' + self.map_outputpath_folder[self.projects... | the_stack_v2_python_sparse | mailib/workflow/workflow.py | TomCMM/sib2_reg_lcb | train | 0 | |
601b34671aee6f548308167563fc3ef7fa7b2aeb | [
"if 'username' in request.COOKIES:\n username = request.COOKIES.get('username')\n checked = 'checked'\nelse:\n username = ''\n checked = ''\nreturn render(request, 'login.html', {'username': username, 'checked': checked})",
"username = request.POST.get('username')\npassword = request.POST.get('pwd')\n... | <|body_start_0|>
if 'username' in request.COOKIES:
username = request.COOKIES.get('username')
checked = 'checked'
else:
username = ''
checked = ''
return render(request, 'login.html', {'username': username, 'checked': checked})
<|end_body_0|>
<|bo... | 登录 | LoginView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginView:
"""登录"""
def get(self, request):
"""显示登录页面"""
<|body_0|>
def post(self, request):
"""登录校验"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if 'username' in request.COOKIES:
username = request.COOKIES.get('username')
... | stack_v2_sparse_classes_36k_train_022467 | 12,479 | no_license | [
{
"docstring": "显示登录页面",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "登录校验",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007048 | Implement the Python class `LoginView` described below.
Class description:
登录
Method signatures and docstrings:
- def get(self, request): 显示登录页面
- def post(self, request): 登录校验 | Implement the Python class `LoginView` described below.
Class description:
登录
Method signatures and docstrings:
- def get(self, request): 显示登录页面
- def post(self, request): 登录校验
<|skeleton|>
class LoginView:
"""登录"""
def get(self, request):
"""显示登录页面"""
<|body_0|>
def post(self, request)... | e19d2aee1aa9433598ac3c0a2a73b0c1e8fa6dc2 | <|skeleton|>
class LoginView:
"""登录"""
def get(self, request):
"""显示登录页面"""
<|body_0|>
def post(self, request):
"""登录校验"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginView:
"""登录"""
def get(self, request):
"""显示登录页面"""
if 'username' in request.COOKIES:
username = request.COOKIES.get('username')
checked = 'checked'
else:
username = ''
checked = ''
return render(request, 'login.html', {... | the_stack_v2_python_sparse | Django天天生鲜项目/dailyfresh/apps/user/views.py | sunday2146/notes-python | train | 0 |
2aca7201a16cc48e3c2f8c1e1c24ab5e6ea33946 | [
"if analysis == 'default':\n analysis = ProcessTomographyAnalysis()\nsuper().__init__(circuit, backend=backend, physical_qubits=physical_qubits, measurement_basis=measurement_basis, measurement_indices=measurement_indices, preparation_basis=preparation_basis, preparation_indices=preparation_indices, basis_indice... | <|body_start_0|>
if analysis == 'default':
analysis = ProcessTomographyAnalysis()
super().__init__(circuit, backend=backend, physical_qubits=physical_qubits, measurement_basis=measurement_basis, measurement_indices=measurement_indices, preparation_basis=preparation_basis, preparation_indices... | An experiment to reconstruct the quantum channel from measurement data. # section: overview Quantum process tomography (QPT) is a method for experimentally reconstructing the quantum channel from measurement data. A QPT experiment prepares multiple input states, evolves them by the circuit, then performs multiple measu... | ProcessTomography | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessTomography:
"""An experiment to reconstruct the quantum channel from measurement data. # section: overview Quantum process tomography (QPT) is a method for experimentally reconstructing the quantum channel from measurement data. A QPT experiment prepares multiple input states, evolves them... | stack_v2_sparse_classes_36k_train_022468 | 8,445 | permissive | [
{
"docstring": "Initialize a quantum process tomography experiment. Args: circuit: the quantum process circuit. If not a quantum circuit it must be a class that can be appended to a quantum circuit. backend: The backend to run the experiment on. physical_qubits: Optional, the physical qubits for the initial sta... | 2 | null | Implement the Python class `ProcessTomography` described below.
Class description:
An experiment to reconstruct the quantum channel from measurement data. # section: overview Quantum process tomography (QPT) is a method for experimentally reconstructing the quantum channel from measurement data. A QPT experiment prepa... | Implement the Python class `ProcessTomography` described below.
Class description:
An experiment to reconstruct the quantum channel from measurement data. # section: overview Quantum process tomography (QPT) is a method for experimentally reconstructing the quantum channel from measurement data. A QPT experiment prepa... | a387675a3fe817cef05b968bbf3e05799a09aaae | <|skeleton|>
class ProcessTomography:
"""An experiment to reconstruct the quantum channel from measurement data. # section: overview Quantum process tomography (QPT) is a method for experimentally reconstructing the quantum channel from measurement data. A QPT experiment prepares multiple input states, evolves them... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcessTomography:
"""An experiment to reconstruct the quantum channel from measurement data. # section: overview Quantum process tomography (QPT) is a method for experimentally reconstructing the quantum channel from measurement data. A QPT experiment prepares multiple input states, evolves them by the circu... | the_stack_v2_python_sparse | qiskit_experiments/library/tomography/qpt_experiment.py | oliverdial/qiskit-experiments | train | 0 |
53973b6b80f6edba5b116abe619814ed25b840bd | [
"self.time_horizon = 6 * 3600\nlength_scale = np.array([_DISTANCE_SCALING, _DISTANCE_SCALING, _PRESSURE_SCALING, _TIME_SCALING])\nself.kernel = _SIGMA_EXP_SQUARED * gaussian_process.kernels.Matern(length_scale=length_scale, length_scale_bounds='fixed', nu=0.5)\nself.model = gaussian_process.GaussianProcessRegressor... | <|body_start_0|>
self.time_horizon = 6 * 3600
length_scale = np.array([_DISTANCE_SCALING, _DISTANCE_SCALING, _PRESSURE_SCALING, _TIME_SCALING])
self.kernel = _SIGMA_EXP_SQUARED * gaussian_process.kernels.Matern(length_scale=length_scale, length_scale_bounds='fixed', nu=0.5)
self.model = ... | Wrapper around a Gaussian Process that handles wind measurements. This object models deviations from the forecast ("errors") using a Gaussian process over the 4-dimensional space (x, y, pressure, time). New measurements are integrated into the GP. Queries return the GP's prediction regarding particular 4D location's wi... | WindGP | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindGP:
"""Wrapper around a Gaussian Process that handles wind measurements. This object models deviations from the forecast ("errors") using a Gaussian process over the 4-dimensional space (x, y, pressure, time). New measurements are integrated into the GP. Queries return the GP's prediction reg... | stack_v2_sparse_classes_36k_train_022469 | 9,541 | permissive | [
{
"docstring": "Constructor for the WindGP. TODO(bellemare): Currently a forecast is required. This simplifies the code somewhat. Whether we keep this depends on a design choice: is a new environment built up and torn down per episode, or do we instead use reset() functions to reuse objects? Args: forecast: the... | 6 | null | Implement the Python class `WindGP` described below.
Class description:
Wrapper around a Gaussian Process that handles wind measurements. This object models deviations from the forecast ("errors") using a Gaussian process over the 4-dimensional space (x, y, pressure, time). New measurements are integrated into the GP.... | Implement the Python class `WindGP` described below.
Class description:
Wrapper around a Gaussian Process that handles wind measurements. This object models deviations from the forecast ("errors") using a Gaussian process over the 4-dimensional space (x, y, pressure, time). New measurements are integrated into the GP.... | 72082feccf404e5bf946e513e4f6c0ae8fb279ad | <|skeleton|>
class WindGP:
"""Wrapper around a Gaussian Process that handles wind measurements. This object models deviations from the forecast ("errors") using a Gaussian process over the 4-dimensional space (x, y, pressure, time). New measurements are integrated into the GP. Queries return the GP's prediction reg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WindGP:
"""Wrapper around a Gaussian Process that handles wind measurements. This object models deviations from the forecast ("errors") using a Gaussian process over the 4-dimensional space (x, y, pressure, time). New measurements are integrated into the GP. Queries return the GP's prediction regarding partic... | the_stack_v2_python_sparse | balloon_learning_environment/env/wind_gp.py | google/balloon-learning-environment | train | 108 |
02210bcca96804748a836b6cc4f8043162ef4535 | [
"try:\n db_creds = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../config/db_creds.json')\n user_creds = json.load(open(db_creds, 'r'))['elastic'][access]\n hosts = user_creds['hosts']\n http_auth = (user_creds['user'], user_creds['pass'])\nexcept:\n env_vars = ['ELASTIC_HOST', 'ELASTIC_... | <|body_start_0|>
try:
db_creds = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../config/db_creds.json')
user_creds = json.load(open(db_creds, 'r'))['elastic'][access]
hosts = user_creds['hosts']
http_auth = (user_creds['user'], user_creds['pass'])
... | Class representing a connection to the Elastic Cloud cluster (ElasticSearch) | ElasticConnection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElasticConnection:
"""Class representing a connection to the Elastic Cloud cluster (ElasticSearch)"""
def __init__(self, local=local, access='read_only'):
"""Args: local (bool): True to use local config file, False for environment variables. Default: False access (str): Level of acce... | stack_v2_sparse_classes_36k_train_022470 | 6,259 | no_license | [
{
"docstring": "Args: local (bool): True to use local config file, False for environment variables. Default: False access (str): Level of access. e.g. \"admin\", \"read_only\", or \"annotator\" db (str): Desired database. e.g. \"test\" or \"production\" Returns: pymongo Client.",
"name": "__init__",
"si... | 2 | stack_v2_sparse_classes_30k_train_009533 | Implement the Python class `ElasticConnection` described below.
Class description:
Class representing a connection to the Elastic Cloud cluster (ElasticSearch)
Method signatures and docstrings:
- def __init__(self, local=local, access='read_only'): Args: local (bool): True to use local config file, False for environm... | Implement the Python class `ElasticConnection` described below.
Class description:
Class representing a connection to the Elastic Cloud cluster (ElasticSearch)
Method signatures and docstrings:
- def __init__(self, local=local, access='read_only'): Args: local (bool): True to use local config file, False for environm... | b10cd933cbfaa969e00f68ad7a895be447472163 | <|skeleton|>
class ElasticConnection:
"""Class representing a connection to the Elastic Cloud cluster (ElasticSearch)"""
def __init__(self, local=local, access='read_only'):
"""Args: local (bool): True to use local config file, False for environment variables. Default: False access (str): Level of acce... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElasticConnection:
"""Class representing a connection to the Elastic Cloud cluster (ElasticSearch)"""
def __init__(self, local=local, access='read_only'):
"""Args: local (bool): True to use local config file, False for environment variables. Default: False access (str): Level of access. e.g. "adm... | the_stack_v2_python_sparse | matstract/models/database.py | abhinavwidak/matstract | train | 0 |
fa5ebecb56a13ae944e4edc225880237395e5342 | [
"if isinstance(init, type(self)):\n self.elec = fields.electric(init.elec)\n self.magn = fields.magnetic(init.magn)\nelif isinstance(init, tuple) and (init[1] is None or isinstance(init[1], MPI.Intracomm)) and isinstance(init[2], np.dtype):\n if isinstance(val, int) or isinstance(val, float) or val is None... | <|body_start_0|>
if isinstance(init, type(self)):
self.elec = fields.electric(init.elec)
self.magn = fields.magnetic(init.magn)
elif isinstance(init, tuple) and (init[1] is None or isinstance(init[1], MPI.Intracomm)) and isinstance(init[2], np.dtype):
if isinstance(va... | Field data type for 3 dimensions This data type can be used for electric and magnetic fields in 3 dimensions Attributes: elec: contains the electric field magn: contains the magnetic field | fields | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class fields:
"""Field data type for 3 dimensions This data type can be used for electric and magnetic fields in 3 dimensions Attributes: elec: contains the electric field magn: contains the magnetic field"""
def __init__(self, init=None, val=None):
"""Initialization routine Args: init: ca... | stack_v2_sparse_classes_36k_train_022471 | 10,653 | permissive | [
{
"docstring": "Initialization routine Args: init: can either be a number or another fields object val: initial tuple of values for electric and magnetic (default: (None,None)) Raises: DataError: if init is none of the types above",
"name": "__init__",
"signature": "def __init__(self, init=None, val=Non... | 4 | stack_v2_sparse_classes_30k_train_000949 | Implement the Python class `fields` described below.
Class description:
Field data type for 3 dimensions This data type can be used for electric and magnetic fields in 3 dimensions Attributes: elec: contains the electric field magn: contains the magnetic field
Method signatures and docstrings:
- def __init__(self, in... | Implement the Python class `fields` described below.
Class description:
Field data type for 3 dimensions This data type can be used for electric and magnetic fields in 3 dimensions Attributes: elec: contains the electric field magn: contains the magnetic field
Method signatures and docstrings:
- def __init__(self, in... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class fields:
"""Field data type for 3 dimensions This data type can be used for electric and magnetic fields in 3 dimensions Attributes: elec: contains the electric field magn: contains the magnetic field"""
def __init__(self, init=None, val=None):
"""Initialization routine Args: init: ca... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class fields:
"""Field data type for 3 dimensions This data type can be used for electric and magnetic fields in 3 dimensions Attributes: elec: contains the electric field magn: contains the magnetic field"""
def __init__(self, init=None, val=None):
"""Initialization routine Args: init: can either be a... | the_stack_v2_python_sparse | pySDC/implementations/datatype_classes/particles.py | Parallel-in-Time/pySDC | train | 30 |
a15b47281b8f27ebdee044ce287707f5ccb39a37 | [
"self.Whf = np.random.normal(size=(h + i, h))\nself.Whb = np.random.normal(size=(h + i, h))\nself.Wy = np.random.normal(size=(2 * h, o))\nself.bhf = np.zeros((1, h))\nself.bhb = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"h_x = np.concatenate((h_prev, x_t), axis=1)\nh_next = np.tanh(np.matmul(h_x, self.Whf) +... | <|body_start_0|>
self.Whf = np.random.normal(size=(h + i, h))
self.Whb = np.random.normal(size=(h + i, h))
self.Wy = np.random.normal(size=(2 * h, o))
self.bhf = np.zeros((1, h))
self.bhb = np.zeros((1, h))
self.by = np.zeros((1, o))
<|end_body_0|>
<|body_start_1|>
... | epresents a bidirectional cell of an RNN | BidirectionalCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BidirectionalCell:
"""epresents a bidirectional cell of an RNN"""
def __init__(self, i, h, o):
"""- i is the dimensionality of the data - h is the dimensionality of the hidden states - o is the dimensionality of the outputs Creates the public instance attributes Whf, Whb, Wy, bhf, bh... | stack_v2_sparse_classes_36k_train_022472 | 1,728 | no_license | [
{
"docstring": "- i is the dimensionality of the data - h is the dimensionality of the hidden states - o is the dimensionality of the outputs Creates the public instance attributes Whf, Whb, Wy, bhf, bhb, by that represent the weights and biases of the cell Whf and bhfare for the hidden states in the forward di... | 2 | null | Implement the Python class `BidirectionalCell` described below.
Class description:
epresents a bidirectional cell of an RNN
Method signatures and docstrings:
- def __init__(self, i, h, o): - i is the dimensionality of the data - h is the dimensionality of the hidden states - o is the dimensionality of the outputs Cre... | Implement the Python class `BidirectionalCell` described below.
Class description:
epresents a bidirectional cell of an RNN
Method signatures and docstrings:
- def __init__(self, i, h, o): - i is the dimensionality of the data - h is the dimensionality of the hidden states - o is the dimensionality of the outputs Cre... | e10b4e9b6f3fa00639e6e9e5b35f0cdb43a339a3 | <|skeleton|>
class BidirectionalCell:
"""epresents a bidirectional cell of an RNN"""
def __init__(self, i, h, o):
"""- i is the dimensionality of the data - h is the dimensionality of the hidden states - o is the dimensionality of the outputs Creates the public instance attributes Whf, Whb, Wy, bhf, bh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BidirectionalCell:
"""epresents a bidirectional cell of an RNN"""
def __init__(self, i, h, o):
"""- i is the dimensionality of the data - h is the dimensionality of the hidden states - o is the dimensionality of the outputs Creates the public instance attributes Whf, Whb, Wy, bhf, bhb, by that re... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/5-bi_forward.py | HeimerR/holbertonschool-machine_learning | train | 0 |
b2a38b71e2e525ef5c9add99e4db7dae4daf715a | [
"try:\n selected_uuid = UUID(hex=LEGACY_CONF.get_val('Last_Selected', 'palette_uuid', ''))\nexcept ValueError:\n selected_uuid = UUID_PORTAL2\nreturn {'': cls(selected_uuid, LEGACY_CONF.get_bool('General', 'palette_save_settings'), frozenset())}",
"assert version == 1\nhidden = {UUID(hex=prop.value) for pro... | <|body_start_0|>
try:
selected_uuid = UUID(hex=LEGACY_CONF.get_val('Last_Selected', 'palette_uuid', ''))
except ValueError:
selected_uuid = UUID_PORTAL2
return {'': cls(selected_uuid, LEGACY_CONF.get_bool('General', 'palette_save_settings'), frozenset())}
<|end_body_0|>
... | Data related to palettes which is restored next run. Since we don't store in the palette, we don't need to register the UI callback. | PaletteState | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PaletteState:
"""Data related to palettes which is restored next run. Since we don't store in the palette, we don't need to register the UI callback."""
def parse_legacy(cls, conf: Property) -> dict[str, PaletteState]:
"""Convert the legacy config options to the new format."""
... | stack_v2_sparse_classes_36k_train_022473 | 3,247 | no_license | [
{
"docstring": "Convert the legacy config options to the new format.",
"name": "parse_legacy",
"signature": "def parse_legacy(cls, conf: Property) -> dict[str, PaletteState]"
},
{
"docstring": "Parse Keyvalues data.",
"name": "parse_kv1",
"signature": "def parse_kv1(cls, data: Property, ... | 5 | null | Implement the Python class `PaletteState` described below.
Class description:
Data related to palettes which is restored next run. Since we don't store in the palette, we don't need to register the UI callback.
Method signatures and docstrings:
- def parse_legacy(cls, conf: Property) -> dict[str, PaletteState]: Conve... | Implement the Python class `PaletteState` described below.
Class description:
Data related to palettes which is restored next run. Since we don't store in the palette, we don't need to register the UI callback.
Method signatures and docstrings:
- def parse_legacy(cls, conf: Property) -> dict[str, PaletteState]: Conve... | 9f9219934b8f4af3c03d0080fad6078a18f3d530 | <|skeleton|>
class PaletteState:
"""Data related to palettes which is restored next run. Since we don't store in the palette, we don't need to register the UI callback."""
def parse_legacy(cls, conf: Property) -> dict[str, PaletteState]:
"""Convert the legacy config options to the new format."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PaletteState:
"""Data related to palettes which is restored next run. Since we don't store in the palette, we don't need to register the UI callback."""
def parse_legacy(cls, conf: Property) -> dict[str, PaletteState]:
"""Convert the legacy config options to the new format."""
try:
... | the_stack_v2_python_sparse | src/config/palette.py | BEEmod/BEE2.4 | train | 276 |
f202d324831654600cd27d22b6b610efccfe9cf5 | [
"super(_RFCN_header, self).__init__(input_dim, n_classes, class_ag)\nself.position_sensitive_score_map = nn.Conv2d(input_dim, k ** 2 * n_classes, kernel_size=1)\nif class_ag:\n self.position_sensitive_bbox_map = nn.Conv2d(input_dim, k ** 2 * 4, kernel_size=1)\nelse:\n self.position_sensitive_bbox_map = nn.Con... | <|body_start_0|>
super(_RFCN_header, self).__init__(input_dim, n_classes, class_ag)
self.position_sensitive_score_map = nn.Conv2d(input_dim, k ** 2 * n_classes, kernel_size=1)
if class_ag:
self.position_sensitive_bbox_map = nn.Conv2d(input_dim, k ** 2 * 4, kernel_size=1)
else... | _RFCN_header | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _RFCN_header:
def __init__(self, input_dim, n_classes, class_ag, k=3):
""":param input_dim: feature map channel number :param n_classes: :param class_ag: :param k: grid size"""
<|body_0|>
def forward(self, x):
""":param feat: [batch_size, channel, H, W] :param rois: ... | stack_v2_sparse_classes_36k_train_022474 | 1,501 | permissive | [
{
"docstring": ":param input_dim: feature map channel number :param n_classes: :param class_ag: :param k: grid size",
"name": "__init__",
"signature": "def __init__(self, input_dim, n_classes, class_ag, k=3)"
},
{
"docstring": ":param feat: [batch_size, channel, H, W] :param rois: [batch_size, n... | 2 | stack_v2_sparse_classes_30k_train_019695 | Implement the Python class `_RFCN_header` described below.
Class description:
Implement the _RFCN_header class.
Method signatures and docstrings:
- def __init__(self, input_dim, n_classes, class_ag, k=3): :param input_dim: feature map channel number :param n_classes: :param class_ag: :param k: grid size
- def forward... | Implement the Python class `_RFCN_header` described below.
Class description:
Implement the _RFCN_header class.
Method signatures and docstrings:
- def __init__(self, input_dim, n_classes, class_ag, k=3): :param input_dim: feature map channel number :param n_classes: :param class_ag: :param k: grid size
- def forward... | f66c38c00405b22cb746cc3f5c38d2b49f77d854 | <|skeleton|>
class _RFCN_header:
def __init__(self, input_dim, n_classes, class_ag, k=3):
""":param input_dim: feature map channel number :param n_classes: :param class_ag: :param k: grid size"""
<|body_0|>
def forward(self, x):
""":param feat: [batch_size, channel, H, W] :param rois: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _RFCN_header:
def __init__(self, input_dim, n_classes, class_ag, k=3):
""":param input_dim: feature map channel number :param n_classes: :param class_ag: :param k: grid size"""
super(_RFCN_header, self).__init__(input_dim, n_classes, class_ag)
self.position_sensitive_score_map = nn.Con... | the_stack_v2_python_sparse | build/lib.linux-x86_64-3.5/model/header/RFCN.py | moli1026/regrad | train | 1 | |
d89d7b64e2a21d4d476940eb8daf9eee316de910 | [
"self.m = {}\nself.q = []\nself.cap = capacity",
"if key not in self.m:\n return -1\nval = self.m[key]\ndel self.m[key]\nself.q.remove(key)\nself.put(key, val)\nreturn val",
"if key in self.m:\n self.q.remove(key)\nself.q.append(key)\nself.m[key] = value\nif len(self.q) > self.cap:\n expire_key = self.... | <|body_start_0|>
self.m = {}
self.q = []
self.cap = capacity
<|end_body_0|>
<|body_start_1|>
if key not in self.m:
return -1
val = self.m[key]
del self.m[key]
self.q.remove(key)
self.put(key, val)
return val
<|end_body_1|>
<|body_star... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_022475 | 876 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_016029 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | c1f22911ae9b441b2d2646dc6a209880a761c9cb | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.m = {}
self.q = []
self.cap = capacity
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.m:
return -1
val = self.m[key]
del self.m[key]
... | the_stack_v2_python_sparse | external/LRU缓存机制/solution.py | u2386/leet | train | 0 | |
255d4f94087b86f574f047e44430680b0291aa2d | [
"super(ReignitionCallback, self).__init__()\nself.priority = 100\nself.desc_copy = None",
"logging.info('Start SPNas Reigniting.')\nself.desc_copy = copy.deepcopy(self.trainer.model_desc)\nbackbone = self.desc_copy.get('backbone')\ncode = backbone.get('code')\nself.trainer.model_desc = dict(type='SerialClassifica... | <|body_start_0|>
super(ReignitionCallback, self).__init__()
self.priority = 100
self.desc_copy = None
<|end_body_0|>
<|body_start_1|>
logging.info('Start SPNas Reigniting.')
self.desc_copy = copy.deepcopy(self.trainer.model_desc)
backbone = self.desc_copy.get('backbone')... | Reignition callback. | ReignitionCallback | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReignitionCallback:
"""Reignition callback."""
def __init__(self):
"""Initialize callback."""
<|body_0|>
def init_trainer(self, logs=None):
"""Be called before train."""
<|body_1|>
def after_epoch(self, epoch, logs=None):
"""Save desc into Fa... | stack_v2_sparse_classes_36k_train_022476 | 1,801 | permissive | [
{
"docstring": "Initialize callback.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Be called before train.",
"name": "init_trainer",
"signature": "def init_trainer(self, logs=None)"
},
{
"docstring": "Save desc into FasterRCNN.",
"name": "after_ep... | 3 | stack_v2_sparse_classes_30k_test_000412 | Implement the Python class `ReignitionCallback` described below.
Class description:
Reignition callback.
Method signatures and docstrings:
- def __init__(self): Initialize callback.
- def init_trainer(self, logs=None): Be called before train.
- def after_epoch(self, epoch, logs=None): Save desc into FasterRCNN. | Implement the Python class `ReignitionCallback` described below.
Class description:
Reignition callback.
Method signatures and docstrings:
- def __init__(self): Initialize callback.
- def init_trainer(self, logs=None): Be called before train.
- def after_epoch(self, epoch, logs=None): Save desc into FasterRCNN.
<|sk... | 12e37a1991eb6771a2999fe0a46ddda920c47948 | <|skeleton|>
class ReignitionCallback:
"""Reignition callback."""
def __init__(self):
"""Initialize callback."""
<|body_0|>
def init_trainer(self, logs=None):
"""Be called before train."""
<|body_1|>
def after_epoch(self, epoch, logs=None):
"""Save desc into Fa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReignitionCallback:
"""Reignition callback."""
def __init__(self):
"""Initialize callback."""
super(ReignitionCallback, self).__init__()
self.priority = 100
self.desc_copy = None
def init_trainer(self, logs=None):
"""Be called before train."""
logging.... | the_stack_v2_python_sparse | vega/algorithms/nas/sp_nas/reignition.py | huawei-noah/vega | train | 850 |
f3be8920ef40662d10f611768573385163ffc4c2 | [
"if not os.path.exists(ss.PREDICTION_BUSSTOP_PATH + '/' + ss.PREDICTION_BUSSTOP_NAME):\n logger.critical('缺失公交数据库，请检查！')\n pass\nself.data_path = ss.PREDICTION_BUSSTOP_PATH + '/' + ss.PREDICTION_BUSSTOP_NAME\nself._bus_data = self._busStop_Load_Data()\nself._busStop_Remove_Duplication()\nself._busStop_Structu... | <|body_start_0|>
if not os.path.exists(ss.PREDICTION_BUSSTOP_PATH + '/' + ss.PREDICTION_BUSSTOP_NAME):
logger.critical('缺失公交数据库，请检查！')
pass
self.data_path = ss.PREDICTION_BUSSTOP_PATH + '/' + ss.PREDICTION_BUSSTOP_NAME
self._bus_data = self._busStop_Load_Data()
se... | busStop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class busStop:
def __init__(self):
"""读入数据"""
<|body_0|>
def _busStop_Load_Data(self):
"""从源文件中读取公交站原始数据 :return:"""
<|body_1|>
def _busStop_Remove_Duplication(self):
"""清洗数据，去掉重复项，去掉不符合要求的项目 :return:"""
<|body_2|>
def _busStop_Structure(s... | stack_v2_sparse_classes_36k_train_022477 | 5,440 | no_license | [
{
"docstring": "读入数据",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "从源文件中读取公交站原始数据 :return:",
"name": "_busStop_Load_Data",
"signature": "def _busStop_Load_Data(self)"
},
{
"docstring": "清洗数据，去掉重复项，去掉不符合要求的项目 :return:",
"name": "_busStop_Remove_Dup... | 5 | null | Implement the Python class `busStop` described below.
Class description:
Implement the busStop class.
Method signatures and docstrings:
- def __init__(self): 读入数据
- def _busStop_Load_Data(self): 从源文件中读取公交站原始数据 :return:
- def _busStop_Remove_Duplication(self): 清洗数据，去掉重复项，去掉不符合要求的项目 :return:
- def _busStop_Structure(se... | Implement the Python class `busStop` described below.
Class description:
Implement the busStop class.
Method signatures and docstrings:
- def __init__(self): 读入数据
- def _busStop_Load_Data(self): 从源文件中读取公交站原始数据 :return:
- def _busStop_Remove_Duplication(self): 清洗数据，去掉重复项，去掉不符合要求的项目 :return:
- def _busStop_Structure(se... | c24d149287697f8fcb26eddce479f37b664ef04c | <|skeleton|>
class busStop:
def __init__(self):
"""读入数据"""
<|body_0|>
def _busStop_Load_Data(self):
"""从源文件中读取公交站原始数据 :return:"""
<|body_1|>
def _busStop_Remove_Duplication(self):
"""清洗数据，去掉重复项，去掉不符合要求的项目 :return:"""
<|body_2|>
def _busStop_Structure(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class busStop:
def __init__(self):
"""读入数据"""
if not os.path.exists(ss.PREDICTION_BUSSTOP_PATH + '/' + ss.PREDICTION_BUSSTOP_NAME):
logger.critical('缺失公交数据库，请检查！')
pass
self.data_path = ss.PREDICTION_BUSSTOP_PATH + '/' + ss.PREDICTION_BUSSTOP_NAME
self._bus_da... | the_stack_v2_python_sparse | Server/TransportationPredict_Tradition/BusStop.py | Kuailun/TransportTradition | train | 0 | |
d4017458ff2330ae832679fd0779d14daecf3bb1 | [
"if data is not None:\n if type(data) != list:\n raise TypeError('data must be a list')\n if len(data) < 2:\n raise ValueError('data must contain multiple values')\n mean = 0.0\n count = 0\n for element in data:\n if type(element) not in {int, float}:\n raise TypeError... | <|body_start_0|>
if data is not None:
if type(data) != list:
raise TypeError('data must be a list')
if len(data) < 2:
raise ValueError('data must contain multiple values')
mean = 0.0
count = 0
for element in data:
... | Class that represents a poisson distribution. | Poisson | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Poisson:
"""Class that represents a poisson distribution."""
def __init__(self, data=None, lambtha=1.0):
"""Constructor of the class. Sets the instance attribute lambtha as float. data is a list of the data to be used to estimate the distribution. lambtha is the expected number of oc... | stack_v2_sparse_classes_36k_train_022478 | 2,052 | no_license | [
{
"docstring": "Constructor of the class. Sets the instance attribute lambtha as float. data is a list of the data to be used to estimate the distribution. lambtha is the expected number of occurences in a given time frame.",
"name": "__init__",
"signature": "def __init__(self, data=None, lambtha=1.0)"
... | 4 | stack_v2_sparse_classes_30k_train_013044 | Implement the Python class `Poisson` described below.
Class description:
Class that represents a poisson distribution.
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Constructor of the class. Sets the instance attribute lambtha as float. data is a list of the data to be used to estima... | Implement the Python class `Poisson` described below.
Class description:
Class that represents a poisson distribution.
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Constructor of the class. Sets the instance attribute lambtha as float. data is a list of the data to be used to estima... | 1e7cd1589e6e4896ee48a24b9ca85595e16e929d | <|skeleton|>
class Poisson:
"""Class that represents a poisson distribution."""
def __init__(self, data=None, lambtha=1.0):
"""Constructor of the class. Sets the instance attribute lambtha as float. data is a list of the data to be used to estimate the distribution. lambtha is the expected number of oc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Poisson:
"""Class that represents a poisson distribution."""
def __init__(self, data=None, lambtha=1.0):
"""Constructor of the class. Sets the instance attribute lambtha as float. data is a list of the data to be used to estimate the distribution. lambtha is the expected number of occurences in a... | the_stack_v2_python_sparse | math/0x03-probability/poisson.py | Daransoto/holbertonschool-machine_learning | train | 0 |
cf326196c90ebb500cf30a9fcec9302babace189 | [
"if threshold is None or rows < 1 or cols < 1:\n return 0\nvisits = [0] * (rows * cols)\ncounts = self.moving_count_core(threshold, rows, cols, 0, 0, visits)\nreturn counts",
"moving_count = 0\nif self.check(threshold, rows, cols, row, col, visits):\n visits[row * cols + col] = 1\n moving_count = 1 + sel... | <|body_start_0|>
if threshold is None or rows < 1 or cols < 1:
return 0
visits = [0] * (rows * cols)
counts = self.moving_count_core(threshold, rows, cols, 0, 0, visits)
return counts
<|end_body_0|>
<|body_start_1|>
moving_count = 0
if self.check(threshold, r... | 计算机器人行走范围 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""计算机器人行走范围"""
def moving_count(self, threshold, rows, cols):
"""主函数，调用递归计算函数 :param threshold: 坐标数位之和的阈值 :param rows: 坐标行数 :param cols: 坐标列数 :return: 机器人行走范围之和"""
<|body_0|>
def moving_count_core(self, threshold, rows, cols, row, col, visits):
"""递归计算... | stack_v2_sparse_classes_36k_train_022479 | 4,600 | no_license | [
{
"docstring": "主函数，调用递归计算函数 :param threshold: 坐标数位之和的阈值 :param rows: 坐标行数 :param cols: 坐标列数 :return: 机器人行走范围之和",
"name": "moving_count",
"signature": "def moving_count(self, threshold, rows, cols)"
},
{
"docstring": "递归计算机器人行走范围 :param threshold: 坐标数位之和的阈值 :param rows: 行数 :param cols: 列数 :param... | 4 | null | Implement the Python class `Solution` described below.
Class description:
计算机器人行走范围
Method signatures and docstrings:
- def moving_count(self, threshold, rows, cols): 主函数，调用递归计算函数 :param threshold: 坐标数位之和的阈值 :param rows: 坐标行数 :param cols: 坐标列数 :return: 机器人行走范围之和
- def moving_count_core(self, threshold, rows, cols, ro... | Implement the Python class `Solution` described below.
Class description:
计算机器人行走范围
Method signatures and docstrings:
- def moving_count(self, threshold, rows, cols): 主函数，调用递归计算函数 :param threshold: 坐标数位之和的阈值 :param rows: 坐标行数 :param cols: 坐标列数 :return: 机器人行走范围之和
- def moving_count_core(self, threshold, rows, cols, ro... | 9fdc4b1a2b59b7aed22ddfe92aade487b4c19b71 | <|skeleton|>
class Solution:
"""计算机器人行走范围"""
def moving_count(self, threshold, rows, cols):
"""主函数，调用递归计算函数 :param threshold: 坐标数位之和的阈值 :param rows: 坐标行数 :param cols: 坐标列数 :return: 机器人行走范围之和"""
<|body_0|>
def moving_count_core(self, threshold, rows, cols, row, col, visits):
"""递归计算... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""计算机器人行走范围"""
def moving_count(self, threshold, rows, cols):
"""主函数，调用递归计算函数 :param threshold: 坐标数位之和的阈值 :param rows: 坐标行数 :param cols: 坐标列数 :return: 机器人行走范围之和"""
if threshold is None or rows < 1 or cols < 1:
return 0
visits = [0] * (rows * cols)
co... | the_stack_v2_python_sparse | my_target_offer/13_robot_run_range.py | MemoryForSky/Data-Structures-and-Algorithms | train | 0 |
fd4eb81128d522b1d27391cf3f3994a53b74282d | [
"self.idItem = itemId\nself.nombreCampo = nombreCampo\nself.tipoPrimario = tp",
"self.idItem = itemId\nself.nombreCampo = nombreCampo\nself.tipoPrimario = tp"
] | <|body_start_0|>
self.idItem = itemId
self.nombreCampo = nombreCampo
self.tipoPrimario = tp
<|end_body_0|>
<|body_start_1|>
self.idItem = itemId
self.nombreCampo = nombreCampo
self.tipoPrimario = tp
<|end_body_1|>
| Esta clase se utiliza para mapear a sus instancias con la tabla de instancia_tipo_item Hereda de la clase Base. La clase Base debe ser heredada por todas las clases que mapearan a una tabla. | InstanciaTipoItem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanciaTipoItem:
"""Esta clase se utiliza para mapear a sus instancias con la tabla de instancia_tipo_item Hereda de la clase Base. La clase Base debe ser heredada por todas las clases que mapearan a una tabla."""
def setValues(self, itemId, nombreCampo, tp):
"""Metodo para estable... | stack_v2_sparse_classes_36k_train_022480 | 6,497 | no_license | [
{
"docstring": "Metodo para establecer valores de atributos de la clase. @type idItem : Integer @param idItem : id del item @type nombreCampo : string @param nombreCampo : nombre del campo @type tp : string @param tp : Tipo primario asociado",
"name": "setValues",
"signature": "def setValues(self, itemI... | 2 | null | Implement the Python class `InstanciaTipoItem` described below.
Class description:
Esta clase se utiliza para mapear a sus instancias con la tabla de instancia_tipo_item Hereda de la clase Base. La clase Base debe ser heredada por todas las clases que mapearan a una tabla.
Method signatures and docstrings:
- def setV... | Implement the Python class `InstanciaTipoItem` described below.
Class description:
Esta clase se utiliza para mapear a sus instancias con la tabla de instancia_tipo_item Hereda de la clase Base. La clase Base debe ser heredada por todas las clases que mapearan a una tabla.
Method signatures and docstrings:
- def setV... | 9262320d4ff52bd3592365cd232f8dedff4f64da | <|skeleton|>
class InstanciaTipoItem:
"""Esta clase se utiliza para mapear a sus instancias con la tabla de instancia_tipo_item Hereda de la clase Base. La clase Base debe ser heredada por todas las clases que mapearan a una tabla."""
def setValues(self, itemId, nombreCampo, tp):
"""Metodo para estable... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstanciaTipoItem:
"""Esta clase se utiliza para mapear a sus instancias con la tabla de instancia_tipo_item Hereda de la clase Base. La clase Base debe ser heredada por todas las clases que mapearan a una tabla."""
def setValues(self, itemId, nombreCampo, tp):
"""Metodo para establecer valores d... | the_stack_v2_python_sparse | models/instanciaAtributos.py | jemaromaster/WAPM | train | 0 |
466ada61405a6edf974e20b13cc429a2f225a04e | [
"sucursal_id = self.kwargs['pk']\nsucursal = Sucursal.objects.get(id=sucursal_id)\nsucursal_repuestos = SucursalRepuesto.objects.filter(sucursal=sucursal)\nreturn sucursal_repuestos",
"context = super(RepuestoSucursalListView, self).get_context_data(**kwargs)\nsucursal_id = self.kwargs['pk']\nsucursal = Sucursal.... | <|body_start_0|>
sucursal_id = self.kwargs['pk']
sucursal = Sucursal.objects.get(id=sucursal_id)
sucursal_repuestos = SucursalRepuesto.objects.filter(sucursal=sucursal)
return sucursal_repuestos
<|end_body_0|>
<|body_start_1|>
context = super(RepuestoSucursalListView, self).get_... | Lista los vehiculos por sucursal. | RepuestoSucursalListView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RepuestoSucursalListView:
"""Lista los vehiculos por sucursal."""
def get_queryset(self):
"""Permite filtrar los vehiculos que seran mostrados. Dada la pk de la sucursal se sobre escribe el metodo para que se listen los vehiculos que pertenecen a una sucursal dada."""
<|body_... | stack_v2_sparse_classes_36k_train_022481 | 2,026 | no_license | [
{
"docstring": "Permite filtrar los vehiculos que seran mostrados. Dada la pk de la sucursal se sobre escribe el metodo para que se listen los vehiculos que pertenecen a una sucursal dada.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Perime agregar al contex... | 2 | null | Implement the Python class `RepuestoSucursalListView` described below.
Class description:
Lista los vehiculos por sucursal.
Method signatures and docstrings:
- def get_queryset(self): Permite filtrar los vehiculos que seran mostrados. Dada la pk de la sucursal se sobre escribe el metodo para que se listen los vehicul... | Implement the Python class `RepuestoSucursalListView` described below.
Class description:
Lista los vehiculos por sucursal.
Method signatures and docstrings:
- def get_queryset(self): Permite filtrar los vehiculos que seran mostrados. Dada la pk de la sucursal se sobre escribe el metodo para que se listen los vehicul... | 3e74310b47c82d2dc420e6aaa743a2bc077fd635 | <|skeleton|>
class RepuestoSucursalListView:
"""Lista los vehiculos por sucursal."""
def get_queryset(self):
"""Permite filtrar los vehiculos que seran mostrados. Dada la pk de la sucursal se sobre escribe el metodo para que se listen los vehiculos que pertenecen a una sucursal dada."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RepuestoSucursalListView:
"""Lista los vehiculos por sucursal."""
def get_queryset(self):
"""Permite filtrar los vehiculos que seran mostrados. Dada la pk de la sucursal se sobre escribe el metodo para que se listen los vehiculos que pertenecen a una sucursal dada."""
sucursal_id = self.k... | the_stack_v2_python_sparse | concesionario/apps/repuesto/views.py | DonAurelio/SIGIA | train | 2 |
084457662be19fa87d2cc684957f2775cb8e1c20 | [
"self.ref = defaults['ref']\nself.protocol = defaults['protocol']\nself.remote = defaults['remote']\nself.source = defaults['source']\nself.depth = defaults.get('depth', 0)\nself.recursive = defaults.get('recursive', False)\nself.timestamp_author = defaults.get('timestamp_author', None)",
"defaults = {'ref': self... | <|body_start_0|>
self.ref = defaults['ref']
self.protocol = defaults['protocol']
self.remote = defaults['remote']
self.source = defaults['source']
self.depth = defaults.get('depth', 0)
self.recursive = defaults.get('recursive', False)
self.timestamp_author = defau... | clowder.yaml Defaults model class :ivar str ref: Default ref :ivar str remote: Default remote name :ivar str source: Default source name :ivar str protocol: Default git protocol :ivar int depth: Default depth :ivar bool recursive: Default recursive value :ivar str timestamp_author: Default timestamp author | Defaults | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Defaults:
"""clowder.yaml Defaults model class :ivar str ref: Default ref :ivar str remote: Default remote name :ivar str source: Default source name :ivar str protocol: Default git protocol :ivar int depth: Default depth :ivar bool recursive: Default recursive value :ivar str timestamp_author: D... | stack_v2_sparse_classes_36k_train_022482 | 1,522 | permissive | [
{
"docstring": "Defaults __init__ :param dict defaults: Parsed YAML python object for defaults",
"name": "__init__",
"signature": "def __init__(self, defaults)"
},
{
"docstring": "Return python object representation for saving yaml :return: YAML python object :rtype: dict",
"name": "get_yaml... | 2 | stack_v2_sparse_classes_30k_train_010449 | Implement the Python class `Defaults` described below.
Class description:
clowder.yaml Defaults model class :ivar str ref: Default ref :ivar str remote: Default remote name :ivar str source: Default source name :ivar str protocol: Default git protocol :ivar int depth: Default depth :ivar bool recursive: Default recurs... | Implement the Python class `Defaults` described below.
Class description:
clowder.yaml Defaults model class :ivar str ref: Default ref :ivar str remote: Default remote name :ivar str source: Default source name :ivar str protocol: Default git protocol :ivar int depth: Default depth :ivar bool recursive: Default recurs... | 5e3920a386229cb143271655d5046dfda2ea3009 | <|skeleton|>
class Defaults:
"""clowder.yaml Defaults model class :ivar str ref: Default ref :ivar str remote: Default remote name :ivar str source: Default source name :ivar str protocol: Default git protocol :ivar int depth: Default depth :ivar bool recursive: Default recursive value :ivar str timestamp_author: D... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Defaults:
"""clowder.yaml Defaults model class :ivar str ref: Default ref :ivar str remote: Default remote name :ivar str source: Default source name :ivar str protocol: Default git protocol :ivar int depth: Default depth :ivar bool recursive: Default recursive value :ivar str timestamp_author: Default timest... | the_stack_v2_python_sparse | src/clowder/model/defaults.py | reidab/clowder | train | 0 |
d611e45d78aa1ba92ad8ee76474e008b6ac425fc | [
"email_regex = '^\\\\w+([\\\\.-]?\\\\w+)*@\\\\w+([\\\\.-]?\\\\w+)*(\\\\.\\\\w{2,3})+$'\nif 'email' not in login_request:\n raise ValidationError('Missing email!')\nif not re.search(email_regex, login_request['email']):\n raise ValidationError('Email is not valid!')\nCredentialView.validate_credential_request(... | <|body_start_0|>
email_regex = '^\\w+([\\.-]?\\w+)*@\\w+([\\.-]?\\w+)*(\\.\\w{2,3})+$'
if 'email' not in login_request:
raise ValidationError('Missing email!')
if not re.search(email_regex, login_request['email']):
raise ValidationError('Email is not valid!')
Cred... | Login endpoint and validator | AuthLoginView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthLoginView:
"""Login endpoint and validator"""
def validate_login_request(login_request):
"""Validates the login information received in the request body :param login_request: Login information received in the request"""
<|body_0|>
def post(request):
"""Action... | stack_v2_sparse_classes_36k_train_022483 | 3,191 | no_license | [
{
"docstring": "Validates the login information received in the request body :param login_request: Login information received in the request",
"name": "validate_login_request",
"signature": "def validate_login_request(login_request)"
},
{
"docstring": "Action when calling the endpoint with POST ... | 2 | stack_v2_sparse_classes_30k_train_015228 | Implement the Python class `AuthLoginView` described below.
Class description:
Login endpoint and validator
Method signatures and docstrings:
- def validate_login_request(login_request): Validates the login information received in the request body :param login_request: Login information received in the request
- def ... | Implement the Python class `AuthLoginView` described below.
Class description:
Login endpoint and validator
Method signatures and docstrings:
- def validate_login_request(login_request): Validates the login information received in the request body :param login_request: Login information received in the request
- def ... | 941e8b2870f8724db3d5103dda5157fd597cfcc7 | <|skeleton|>
class AuthLoginView:
"""Login endpoint and validator"""
def validate_login_request(login_request):
"""Validates the login information received in the request body :param login_request: Login information received in the request"""
<|body_0|>
def post(request):
"""Action... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthLoginView:
"""Login endpoint and validator"""
def validate_login_request(login_request):
"""Validates the login information received in the request body :param login_request: Login information received in the request"""
email_regex = '^\\w+([\\.-]?\\w+)*@\\w+([\\.-]?\\w+)*(\\.\\w{2,3}... | the_stack_v2_python_sparse | backend/martin_helder/views/auth_login_view.py | JoaoAlvaroFerreira/FEUP-LGP | train | 1 |
dd4df4ff767c5a03d051126ee78c222817264f53 | [
"component_spc = kwargs['spc'] if 'spc' in kwargs else spc.SPC\nobject_proto.iqObject.__init__(self, parent=parent, resource=resource, spc=component_spc, context=context)\ndbf_readonly.iqDBFReadOnlyFile.__init__(self, dbf_filename=self.getDBFFileName())",
"if self._dbf_file_name is None:\n self._dbf_file_name ... | <|body_start_0|>
component_spc = kwargs['spc'] if 'spc' in kwargs else spc.SPC
object_proto.iqObject.__init__(self, parent=parent, resource=resource, spc=component_spc, context=context)
dbf_readonly.iqDBFReadOnlyFile.__init__(self, dbf_filename=self.getDBFFileName())
<|end_body_0|>
<|body_start... | DBF readonly file component. | iqDBFReadOnlyFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iqDBFReadOnlyFile:
"""DBF readonly file component."""
def __init__(self, parent=None, resource=None, context=None, *args, **kwargs):
"""Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary."""
... | stack_v2_sparse_classes_36k_train_022484 | 1,140 | no_license | [
{
"docstring": "Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary.",
"name": "__init__",
"signature": "def __init__(self, parent=None, resource=None, context=None, *args, **kwargs)"
},
{
"docstring": "Get... | 2 | stack_v2_sparse_classes_30k_train_005773 | Implement the Python class `iqDBFReadOnlyFile` described below.
Class description:
DBF readonly file component.
Method signatures and docstrings:
- def __init__(self, parent=None, resource=None, context=None, *args, **kwargs): Standard component constructor. :param parent: Parent object. :param resource: Object resou... | Implement the Python class `iqDBFReadOnlyFile` described below.
Class description:
DBF readonly file component.
Method signatures and docstrings:
- def __init__(self, parent=None, resource=None, context=None, *args, **kwargs): Standard component constructor. :param parent: Parent object. :param resource: Object resou... | 7550e242746cb2fb1219474463f8db21f8e3e114 | <|skeleton|>
class iqDBFReadOnlyFile:
"""DBF readonly file component."""
def __init__(self, parent=None, resource=None, context=None, *args, **kwargs):
"""Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class iqDBFReadOnlyFile:
"""DBF readonly file component."""
def __init__(self, parent=None, resource=None, context=None, *args, **kwargs):
"""Standard component constructor. :param parent: Parent object. :param resource: Object resource dictionary. :param context: Context dictionary."""
compone... | the_stack_v2_python_sparse | iq/components/dbf_readonly_file/component.py | XHermitOne/iq_framework | train | 1 |
9c7cd047a99ca1fbb533633b29eccb858c6298cc | [
"l = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\nresult = snail(l)\nself.assertEqual(result, [1, 2, 3, 6, 9, 8, 7, 4, 5])",
"l = [[3, 78, 45, 12, 5, 3], [7, 4, 345, 76, 12, 4], [0, 0, 0, 0, 0, 0], [5456, 123, 6345, 123, 5435, 1], [1, 2, 3, 4, 5, 6], [678, 45, 12, 54, 123, 2]]\nresult = snail(l)\nself.assertEqual(result, [... | <|body_start_0|>
l = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
result = snail(l)
self.assertEqual(result, [1, 2, 3, 6, 9, 8, 7, 4, 5])
<|end_body_0|>
<|body_start_1|>
l = [[3, 78, 45, 12, 5, 3], [7, 4, 345, 76, 12, 4], [0, 0, 0, 0, 0, 0], [5456, 123, 6345, 123, 5435, 1], [1, 2, 3, 4, 5, 6], [67... | TestSnail | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSnail:
def test_snail_sort_small_list(self):
"""Tests that the snail sort algorithm returns a small list path sorted in winding snail order"""
<|body_0|>
def test_snail_sort_large_list(self):
"""Tests that the snail sort alrogrithm returns a large list path sorte... | stack_v2_sparse_classes_36k_train_022485 | 1,516 | permissive | [
{
"docstring": "Tests that the snail sort algorithm returns a small list path sorted in winding snail order",
"name": "test_snail_sort_small_list",
"signature": "def test_snail_sort_small_list(self)"
},
{
"docstring": "Tests that the snail sort alrogrithm returns a large list path sorted in wind... | 3 | null | Implement the Python class `TestSnail` described below.
Class description:
Implement the TestSnail class.
Method signatures and docstrings:
- def test_snail_sort_small_list(self): Tests that the snail sort algorithm returns a small list path sorted in winding snail order
- def test_snail_sort_large_list(self): Tests ... | Implement the Python class `TestSnail` described below.
Class description:
Implement the TestSnail class.
Method signatures and docstrings:
- def test_snail_sort_small_list(self): Tests that the snail sort algorithm returns a small list path sorted in winding snail order
- def test_snail_sort_large_list(self): Tests ... | 27ffb6b32d6d18d279c51cfa45bf305a409be5c2 | <|skeleton|>
class TestSnail:
def test_snail_sort_small_list(self):
"""Tests that the snail sort algorithm returns a small list path sorted in winding snail order"""
<|body_0|>
def test_snail_sort_large_list(self):
"""Tests that the snail sort alrogrithm returns a large list path sorte... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSnail:
def test_snail_sort_small_list(self):
"""Tests that the snail sort algorithm returns a small list path sorted in winding snail order"""
l = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
result = snail(l)
self.assertEqual(result, [1, 2, 3, 6, 9, 8, 7, 4, 5])
def test_snail_s... | the_stack_v2_python_sparse | src/codewars/4-kyu/snail/test_snail.py | nwthomas/code-challenges | train | 2 | |
90250727cacb00c40031fbd09f5ec3a28491c75b | [
"Block.__init__(self, scenario, args)\nif self.language is None:\n raise LoadingException('Language must be defined!')",
"anode = tnode.lex_anode\nif not anode:\n return\nif tnode.nodetype in ['coap', 'atom', 'dphr']:\n anode.morphcat_pos = '!'\n return\nanode.morphcat_pos = tnode.mlayer_pos or '.'\ni... | <|body_start_0|>
Block.__init__(self, scenario, args)
if self.language is None:
raise LoadingException('Language must be defined!')
<|end_body_0|>
<|body_start_1|>
anode = tnode.lex_anode
if not anode:
return
if tnode.nodetype in ['coap', 'atom', 'dphr']:... | According to t-layer grammatemes, this initializes the morphcat structure at the a-layer that is the basis for a later POS tag limiting in the word form generation. Arguments: language: the language of the target tree selector: the selector of the target tree | InitMorphcat | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InitMorphcat:
"""According to t-layer grammatemes, this initializes the morphcat structure at the a-layer that is the basis for a later POS tag limiting in the word form generation. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__... | stack_v2_sparse_classes_36k_train_022486 | 5,591 | permissive | [
{
"docstring": "Constructor, checking the argument values",
"name": "__init__",
"signature": "def __init__(self, scenario, args)"
},
{
"docstring": "Initialize the morphcat structure in the given node",
"name": "process_tnode",
"signature": "def process_tnode(self, tnode)"
},
{
"... | 4 | stack_v2_sparse_classes_30k_train_013921 | Implement the Python class `InitMorphcat` described below.
Class description:
According to t-layer grammatemes, this initializes the morphcat structure at the a-layer that is the basis for a later POS tag limiting in the word form generation. Arguments: language: the language of the target tree selector: the selector ... | Implement the Python class `InitMorphcat` described below.
Class description:
According to t-layer grammatemes, this initializes the morphcat structure at the a-layer that is the basis for a later POS tag limiting in the word form generation. Arguments: language: the language of the target tree selector: the selector ... | 73af644ec35c8a1cd0c37cd478c2afc1db717e0b | <|skeleton|>
class InitMorphcat:
"""According to t-layer grammatemes, this initializes the morphcat structure at the a-layer that is the basis for a later POS tag limiting in the word form generation. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InitMorphcat:
"""According to t-layer grammatemes, this initializes the morphcat structure at the a-layer that is the basis for a later POS tag limiting in the word form generation. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenar... | the_stack_v2_python_sparse | alex/components/nlg/tectotpl/block/t2a/cs/initmorphcat.py | oplatek/alex | train | 0 |
defb7cf565746bf541b9015b8475cbacb7423027 | [
"if self.file_file:\n try:\n return re.search('([^\\\\/]+)$', self.file_file).groups()[0]\n except AttributeError:\n pass\nreturn None",
"if self.file_name:\n return self.file_name\nreturn self.get_filename()"
] | <|body_start_0|>
if self.file_file:
try:
return re.search('([^\\/]+)$', self.file_file).groups()[0]
except AttributeError:
pass
return None
<|end_body_0|>
<|body_start_1|>
if self.file_name:
return self.file_name
return... | Post type for a downloadable file | File | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class File:
"""Post type for a downloadable file"""
def get_filename(self):
"""Returns the filename of the uploaded file"""
<|body_0|>
def file_link_text(self):
"""Returns text to be used for a download link"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022487 | 2,384 | permissive | [
{
"docstring": "Returns the filename of the uploaded file",
"name": "get_filename",
"signature": "def get_filename(self)"
},
{
"docstring": "Returns text to be used for a download link",
"name": "file_link_text",
"signature": "def file_link_text(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000017 | Implement the Python class `File` described below.
Class description:
Post type for a downloadable file
Method signatures and docstrings:
- def get_filename(self): Returns the filename of the uploaded file
- def file_link_text(self): Returns text to be used for a download link | Implement the Python class `File` described below.
Class description:
Post type for a downloadable file
Method signatures and docstrings:
- def get_filename(self): Returns the filename of the uploaded file
- def file_link_text(self): Returns text to be used for a download link
<|skeleton|>
class File:
"""Post ty... | d5582c0e511d56998e19efa07db1e4badfec483b | <|skeleton|>
class File:
"""Post type for a downloadable file"""
def get_filename(self):
"""Returns the filename of the uploaded file"""
<|body_0|>
def file_link_text(self):
"""Returns text to be used for a download link"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class File:
"""Post type for a downloadable file"""
def get_filename(self):
"""Returns the filename of the uploaded file"""
if self.file_file:
try:
return re.search('([^\\/]+)$', self.file_file).groups()[0]
except AttributeError:
pass
... | the_stack_v2_python_sparse | tumblelog/models/contrib/file.py | registerguard/django-tumblelog | train | 0 |
63470cd7369db83d4f1c3d3fd78267ac9b5e2f14 | [
"if path.endswith('/'):\n path = path[:-1]\nreturn path",
"if not path.endswith('/'):\n path = path + '/'\nreturn path"
] | <|body_start_0|>
if path.endswith('/'):
path = path[:-1]
return path
<|end_body_0|>
<|body_start_1|>
if not path.endswith('/'):
path = path + '/'
return path
<|end_body_1|>
| PathConvertor | [
"LicenseRef-scancode-generic-cla",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PathConvertor:
def build_path_without_trailing_slash(path: str) -> str:
"""Build source path without trailing '/'. Args: path (str): Original path. Returns: str: Reformatted path."""
<|body_0|>
def build_path_with_trailing_slash(path: str) -> str:
"""Build reformatte... | stack_v2_sparse_classes_36k_train_022488 | 766 | permissive | [
{
"docstring": "Build source path without trailing '/'. Args: path (str): Original path. Returns: str: Reformatted path.",
"name": "build_path_without_trailing_slash",
"signature": "def build_path_without_trailing_slash(path: str) -> str"
},
{
"docstring": "Build reformatted target dir with trai... | 2 | null | Implement the Python class `PathConvertor` described below.
Class description:
Implement the PathConvertor class.
Method signatures and docstrings:
- def build_path_without_trailing_slash(path: str) -> str: Build source path without trailing '/'. Args: path (str): Original path. Returns: str: Reformatted path.
- def ... | Implement the Python class `PathConvertor` described below.
Class description:
Implement the PathConvertor class.
Method signatures and docstrings:
- def build_path_without_trailing_slash(path: str) -> str: Build source path without trailing '/'. Args: path (str): Original path. Returns: str: Reformatted path.
- def ... | b3c6a589ad9036b03221e776a6929b2bc1eb4680 | <|skeleton|>
class PathConvertor:
def build_path_without_trailing_slash(path: str) -> str:
"""Build source path without trailing '/'. Args: path (str): Original path. Returns: str: Reformatted path."""
<|body_0|>
def build_path_with_trailing_slash(path: str) -> str:
"""Build reformatte... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PathConvertor:
def build_path_without_trailing_slash(path: str) -> str:
"""Build source path without trailing '/'. Args: path (str): Original path. Returns: str: Reformatted path."""
if path.endswith('/'):
path = path[:-1]
return path
def build_path_with_trailing_slash... | the_stack_v2_python_sparse | maro/cli/utils/path_convertor.py | microsoft/maro | train | 764 | |
bde617e1b5e17160041b334e5b1c5d0319731dde | [
"res = []\n\ndef dfs(root):\n if not root:\n return\n res.append(root.val)\n for child in root.children:\n dfs(child)\ndfs(root)\nreturn res",
"stack = [root]\nres = []\nif not root:\n return []\nwhile stack:\n root = stack.pop()\n res.append(root.val)\n stack.extend(root.childr... | <|body_start_0|>
res = []
def dfs(root):
if not root:
return
res.append(root.val)
for child in root.children:
dfs(child)
dfs(root)
return res
<|end_body_0|>
<|body_start_1|>
stack = [root]
res = []
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorder(self, root: 'Node') -> List[int]:
"""简单的递归遍历 :param root: :return:"""
<|body_0|>
def preorder1(self, root: 'Node') -> List[int]:
"""使用迭代的方式，自己维护一个栈 :param root: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []... | stack_v2_sparse_classes_36k_train_022489 | 1,129 | no_license | [
{
"docstring": "简单的递归遍历 :param root: :return:",
"name": "preorder",
"signature": "def preorder(self, root: 'Node') -> List[int]"
},
{
"docstring": "使用迭代的方式，自己维护一个栈 :param root: :return:",
"name": "preorder1",
"signature": "def preorder1(self, root: 'Node') -> List[int]"
}
] | 2 | stack_v2_sparse_classes_30k_train_010662 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorder(self, root: 'Node') -> List[int]: 简单的递归遍历 :param root: :return:
- def preorder1(self, root: 'Node') -> List[int]: 使用迭代的方式，自己维护一个栈 :param root: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorder(self, root: 'Node') -> List[int]: 简单的递归遍历 :param root: :return:
- def preorder1(self, root: 'Node') -> List[int]: 使用迭代的方式，自己维护一个栈 :param root: :return:
<|skeleton|>... | 578cacff5851c5c2522981693c34e3c318002d30 | <|skeleton|>
class Solution:
def preorder(self, root: 'Node') -> List[int]:
"""简单的递归遍历 :param root: :return:"""
<|body_0|>
def preorder1(self, root: 'Node') -> List[int]:
"""使用迭代的方式，自己维护一个栈 :param root: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preorder(self, root: 'Node') -> List[int]:
"""简单的递归遍历 :param root: :return:"""
res = []
def dfs(root):
if not root:
return
res.append(root.val)
for child in root.children:
dfs(child)
dfs(root)
... | the_stack_v2_python_sparse | N叉树的前序遍历.py | cjrzs/MyLeetCode | train | 8 | |
b8ea05e8f4d788fde8f1d24e3bbeb991b634c448 | [
"for i in range(1, len(arr) - 1):\n if arr[i - 1] < arr[i] > arr[i + 1]:\n return i",
"n = len(arr)\nleft, right, ans = (1, n - 2, 0)\nwhile left <= right:\n mid = (left + right) // 2\n if arr[mid] > arr[mid + 1]:\n ans = mid\n right = mid - 1\n else:\n left = mid + 1\nretu... | <|body_start_0|>
for i in range(1, len(arr) - 1):
if arr[i - 1] < arr[i] > arr[i + 1]:
return i
<|end_body_0|>
<|body_start_1|>
n = len(arr)
left, right, ans = (1, n - 2, 0)
while left <= right:
mid = (left + right) // 2
if arr[mid] > ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def peakIndexInMountainArray(self, arr: List[int]) -> int:
"""遍历， :param arr: :return:"""
<|body_0|>
def peakIndexInMountainArray1(self, arr: List[int]) -> int:
"""二分查找 :param arr: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
f... | stack_v2_sparse_classes_36k_train_022490 | 1,539 | no_license | [
{
"docstring": "遍历， :param arr: :return:",
"name": "peakIndexInMountainArray",
"signature": "def peakIndexInMountainArray(self, arr: List[int]) -> int"
},
{
"docstring": "二分查找 :param arr: :return:",
"name": "peakIndexInMountainArray1",
"signature": "def peakIndexInMountainArray1(self, ar... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def peakIndexInMountainArray(self, arr: List[int]) -> int: 遍历， :param arr: :return:
- def peakIndexInMountainArray1(self, arr: List[int]) -> int: 二分查找 :param arr: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def peakIndexInMountainArray(self, arr: List[int]) -> int: 遍历， :param arr: :return:
- def peakIndexInMountainArray1(self, arr: List[int]) -> int: 二分查找 :param arr: :return:
<|ske... | 9acba92695c06406f12f997a720bfe1deb9464a8 | <|skeleton|>
class Solution:
def peakIndexInMountainArray(self, arr: List[int]) -> int:
"""遍历， :param arr: :return:"""
<|body_0|>
def peakIndexInMountainArray1(self, arr: List[int]) -> int:
"""二分查找 :param arr: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def peakIndexInMountainArray(self, arr: List[int]) -> int:
"""遍历， :param arr: :return:"""
for i in range(1, len(arr) - 1):
if arr[i - 1] < arr[i] > arr[i + 1]:
return i
def peakIndexInMountainArray1(self, arr: List[int]) -> int:
"""二分查找 :param... | the_stack_v2_python_sparse | datastructure/binary_array/PeakIndexInMountainArray.py | yinhuax/leet_code | train | 0 | |
9bd2da744ef351f2627f43339abd16cfebaae8b9 | [
"self.depth = depth\nself.otu_table = self.getBiomData(otu_path)\nself.max_num_taxa = -1\nfor val in self.otu_table.iterObservationData():\n self.max_num_taxa = max(self.max_num_taxa, val.sum())",
"if not include_lineages:\n for val, id, meta in self.otu_table.iterObservations():\n del meta['taxonomy... | <|body_start_0|>
self.depth = depth
self.otu_table = self.getBiomData(otu_path)
self.max_num_taxa = -1
for val in self.otu_table.iterObservationData():
self.max_num_taxa = max(self.max_num_taxa, val.sum())
<|end_body_0|>
<|body_start_1|>
if not include_lineages:
... | SingleRarefactionMaker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleRarefactionMaker:
def __init__(self, otu_path, depth):
"""init a singlerarefactionmaker otu_path has to be parseable when opened by parse_biom_table, we just ignore any rarefaction levels beyond any sample in the data"""
<|body_0|>
def rarefy_to_file(self, output_fname... | stack_v2_sparse_classes_36k_train_022491 | 7,880 | no_license | [
{
"docstring": "init a singlerarefactionmaker otu_path has to be parseable when opened by parse_biom_table, we just ignore any rarefaction levels beyond any sample in the data",
"name": "__init__",
"signature": "def __init__(self, otu_path, depth)"
},
{
"docstring": "computes rarefied otu tables... | 3 | stack_v2_sparse_classes_30k_train_013749 | Implement the Python class `SingleRarefactionMaker` described below.
Class description:
Implement the SingleRarefactionMaker class.
Method signatures and docstrings:
- def __init__(self, otu_path, depth): init a singlerarefactionmaker otu_path has to be parseable when opened by parse_biom_table, we just ignore any ra... | Implement the Python class `SingleRarefactionMaker` described below.
Class description:
Implement the SingleRarefactionMaker class.
Method signatures and docstrings:
- def __init__(self, otu_path, depth): init a singlerarefactionmaker otu_path has to be parseable when opened by parse_biom_table, we just ignore any ra... | afb3eb6531badeb74fc69ae4c9e698d3e9cbe70e | <|skeleton|>
class SingleRarefactionMaker:
def __init__(self, otu_path, depth):
"""init a singlerarefactionmaker otu_path has to be parseable when opened by parse_biom_table, we just ignore any rarefaction levels beyond any sample in the data"""
<|body_0|>
def rarefy_to_file(self, output_fname... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SingleRarefactionMaker:
def __init__(self, otu_path, depth):
"""init a singlerarefactionmaker otu_path has to be parseable when opened by parse_biom_table, we just ignore any rarefaction levels beyond any sample in the data"""
self.depth = depth
self.otu_table = self.getBiomData(otu_pa... | the_stack_v2_python_sparse | qiime/rarefaction.py | rob-knight/qiime | train | 2 | |
79f72871b84abe662d35840e1283341206ecc088 | [
"self.acno = int(raw_input('enter accont no : '))\nself.acname = raw_input('enter accont h name : ')\nself.acbal = float(raw_input('enter accont blance : '))",
"self.acno = int(raw_input('enter accont no : '))\nself.acname = raw_input('enter accont h name : ')\nself.acbal = float(raw_input('enter accont blance : ... | <|body_start_0|>
self.acno = int(raw_input('enter accont no : '))
self.acname = raw_input('enter accont h name : ')
self.acbal = float(raw_input('enter accont blance : '))
<|end_body_0|>
<|body_start_1|>
self.acno = int(raw_input('enter accont no : '))
self.acname = raw_input('e... | to define account class woth account info and operations | account | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account:
"""to define account class woth account info and operations"""
def __init__(self):
"""to initialise instance variables"""
<|body_0|>
def setaccountinfo(self):
"""to initialise account info"""
<|body_1|>
def getaccountinfo(self):
"""t... | stack_v2_sparse_classes_36k_train_022492 | 1,448 | no_license | [
{
"docstring": "to initialise instance variables",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "to initialise account info",
"name": "setaccountinfo",
"signature": "def setaccountinfo(self)"
},
{
"docstring": "to display account detail",
"name": "g... | 4 | stack_v2_sparse_classes_30k_train_009413 | Implement the Python class `account` described below.
Class description:
to define account class woth account info and operations
Method signatures and docstrings:
- def __init__(self): to initialise instance variables
- def setaccountinfo(self): to initialise account info
- def getaccountinfo(self): to display accou... | Implement the Python class `account` described below.
Class description:
to define account class woth account info and operations
Method signatures and docstrings:
- def __init__(self): to initialise instance variables
- def setaccountinfo(self): to initialise account info
- def getaccountinfo(self): to display accou... | a2c3cbbfa740dc39944d8a7e4ca0eaad07f44316 | <|skeleton|>
class account:
"""to define account class woth account info and operations"""
def __init__(self):
"""to initialise instance variables"""
<|body_0|>
def setaccountinfo(self):
"""to initialise account info"""
<|body_1|>
def getaccountinfo(self):
"""t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class account:
"""to define account class woth account info and operations"""
def __init__(self):
"""to initialise instance variables"""
self.acno = int(raw_input('enter accont no : '))
self.acname = raw_input('enter accont h name : ')
self.acbal = float(raw_input('enter accont ... | the_stack_v2_python_sparse | class/act2.py | kajal241199/PYTraining | train | 0 |
b7fceb47ed14d9dae30104162af0d7f20e2dec4a | [
"self.count = 0\nself.res = []\nstack = []\nwhile root or stack:\n if root:\n stack.append(root)\n root = root.left\n else:\n root = stack.pop()\n self.res.append(root.val)\n root = root.right",
"if self.count < len(self.res):\n return True\nreturn False",
"res = self... | <|body_start_0|>
self.count = 0
self.res = []
stack = []
while root or stack:
if root:
stack.append(root)
root = root.left
else:
root = stack.pop()
self.res.append(root.val)
root = roo... | BSTIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def hasNext(self):
""":rtype: bool"""
<|body_1|>
def next(self):
""":rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.count = 0
... | stack_v2_sparse_classes_36k_train_022493 | 1,954 | no_license | [
{
"docstring": ":type root: TreeNode",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",
"signature": "def hasNext(self)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
}
] | 3 | null | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def hasNext(self): :rtype: bool
- def next(self): :rtype: int | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def hasNext(self): :rtype: bool
- def next(self): :rtype: int
<|skeleton|>
class BSTIterator:
def __init__(self, root... | 07b8c34b12d05413466119a82247d7ee5cc34318 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def hasNext(self):
""":rtype: bool"""
<|body_1|>
def next(self):
""":rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
self.count = 0
self.res = []
stack = []
while root or stack:
if root:
stack.append(root)
root = root.left
else:
root = stack.pop()
... | the_stack_v2_python_sparse | 173. Binary Search Tree Iterator.py | bryantbyr/LeetCode-solutions | train | 1 | |
84447019b5b794c28c1d56a95ccd8bf8e9605986 | [
"heapq.heapify(nums)\nwhile len(nums) > k:\n heapq.heappop(nums)\nself.k = k\nself.nums = nums",
"if len(self.nums) == self.k and val <= self.nums[0]:\n return self.nums[0]\nheapq.heappush(self.nums, val)\nif len(self.nums) > self.k:\n heapq.heappop(self.nums)\nreturn self.nums[0]"
] | <|body_start_0|>
heapq.heapify(nums)
while len(nums) > k:
heapq.heappop(nums)
self.k = k
self.nums = nums
<|end_body_0|>
<|body_start_1|>
if len(self.nums) == self.k and val <= self.nums[0]:
return self.nums[0]
heapq.heappush(self.nums, val)
... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
heapq.heapify(nums)
while len(nums) > k:
... | stack_v2_sparse_classes_36k_train_022494 | 1,582 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | null | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
heapq.heapify(nums)
while len(nums) > k:
heapq.heappop(nums)
self.k = k
self.nums = nums
def add(self, val):
""":type val: int :rtype: int"""
if len(self.n... | the_stack_v2_python_sparse | python_1_to_1000/703_Kth_Largest_Element_in_a_Stream.py | jakehoare/leetcode | train | 58 | |
39adad70f87fcde5a6fa3503fa58835bcf195f43 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | A set of methods for managing access keys. | AccessKeyServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccessKeyServiceServicer:
"""A set of methods for managing access keys."""
def List(self, request, context):
"""Retrieves the list of access keys for the specified service account."""
<|body_0|>
def Get(self, request, context):
"""Returns the specified access key... | stack_v2_sparse_classes_36k_train_022495 | 13,154 | permissive | [
{
"docstring": "Retrieves the list of access keys for the specified service account.",
"name": "List",
"signature": "def List(self, request, context)"
},
{
"docstring": "Returns the specified access key. To get the list of available access keys, make a [List] request.",
"name": "Get",
"s... | 6 | stack_v2_sparse_classes_30k_test_000386 | Implement the Python class `AccessKeyServiceServicer` described below.
Class description:
A set of methods for managing access keys.
Method signatures and docstrings:
- def List(self, request, context): Retrieves the list of access keys for the specified service account.
- def Get(self, request, context): Returns the... | Implement the Python class `AccessKeyServiceServicer` described below.
Class description:
A set of methods for managing access keys.
Method signatures and docstrings:
- def List(self, request, context): Retrieves the list of access keys for the specified service account.
- def Get(self, request, context): Returns the... | b906a014dd893e2697864e1e48e814a8d9fbc48c | <|skeleton|>
class AccessKeyServiceServicer:
"""A set of methods for managing access keys."""
def List(self, request, context):
"""Retrieves the list of access keys for the specified service account."""
<|body_0|>
def Get(self, request, context):
"""Returns the specified access key... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccessKeyServiceServicer:
"""A set of methods for managing access keys."""
def List(self, request, context):
"""Retrieves the list of access keys for the specified service account."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
... | the_stack_v2_python_sparse | yandex/cloud/iam/v1/awscompatibility/access_key_service_pb2_grpc.py | yandex-cloud/python-sdk | train | 63 |
56364556a08b8fef01cc57e249ddc6f3b584acd4 | [
"binning = config['binning']\nbinsz = binning['binsz']\ncoordsys = binning.get('coordsys', 'GAL')\nroiwidth = binning['roiwidth']\nproj = binning.get('proj', 'AIT')\nra = config['selection']['ra']\ndec = config['selection']['dec']\nnpix = int(np.round(roiwidth / binsz))\nskydir = SkyCoord(ra * u.deg, dec * u.deg)\n... | <|body_start_0|>
binning = config['binning']
binsz = binning['binsz']
coordsys = binning.get('coordsys', 'GAL')
roiwidth = binning['roiwidth']
proj = binning.get('proj', 'AIT')
ra = config['selection']['ra']
dec = config['selection']['dec']
npix = int(np.r... | Small class to generate random sky directions inside an ROI This is useful for parallelizing analysis using the fermipy.jobs module. | RandomDirGen | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomDirGen:
"""Small class to generate random sky directions inside an ROI This is useful for parallelizing analysis using the fermipy.jobs module."""
def _make_wcsgeom_from_config(config):
"""Build a `WCS.Geom` object from a fermipy coniguration file"""
<|body_0|>
def... | stack_v2_sparse_classes_36k_train_022496 | 21,082 | permissive | [
{
"docstring": "Build a `WCS.Geom` object from a fermipy coniguration file",
"name": "_make_wcsgeom_from_config",
"signature": "def _make_wcsgeom_from_config(config)"
},
{
"docstring": "Build a dictionary of random directions",
"name": "_build_skydir_dict",
"signature": "def _build_skydi... | 3 | null | Implement the Python class `RandomDirGen` described below.
Class description:
Small class to generate random sky directions inside an ROI This is useful for parallelizing analysis using the fermipy.jobs module.
Method signatures and docstrings:
- def _make_wcsgeom_from_config(config): Build a `WCS.Geom` object from a... | Implement the Python class `RandomDirGen` described below.
Class description:
Small class to generate random sky directions inside an ROI This is useful for parallelizing analysis using the fermipy.jobs module.
Method signatures and docstrings:
- def _make_wcsgeom_from_config(config): Build a `WCS.Geom` object from a... | fbd4c95ffadbff31cbb9cc862ff84a78dc734ef5 | <|skeleton|>
class RandomDirGen:
"""Small class to generate random sky directions inside an ROI This is useful for parallelizing analysis using the fermipy.jobs module."""
def _make_wcsgeom_from_config(config):
"""Build a `WCS.Geom` object from a fermipy coniguration file"""
<|body_0|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomDirGen:
"""Small class to generate random sky directions inside an ROI This is useful for parallelizing analysis using the fermipy.jobs module."""
def _make_wcsgeom_from_config(config):
"""Build a `WCS.Geom` object from a fermipy coniguration file"""
binning = config['binning']
... | the_stack_v2_python_sparse | fermipy/jobs/target_sim.py | fermiPy/fermipy | train | 51 |
ccfde77d5ec110f6d84c901f2e79471f6983d23f | [
"verified_data = InterfaceSerializers.InterfaceSerializers(data=request.data)\nif verified_data.is_valid():\n verified_data.save(user=request.user)\n return Response(status=status.HTTP_201_CREATED, data=verified_data.data)\nreturn Response(status=status.HTTP_400_BAD_REQUEST, data=verified_data.errors)",
"qu... | <|body_start_0|>
verified_data = InterfaceSerializers.InterfaceSerializers(data=request.data)
if verified_data.is_valid():
verified_data.save(user=request.user)
return Response(status=status.HTTP_201_CREATED, data=verified_data.data)
return Response(status=status.HTTP_400... | UserApiInfoView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserApiInfoView:
def api_save(self, request, *args, **kwargs):
"""保存接口"""
<|body_0|>
def update_api(self, request, *args, **kwargs):
"""更新api"""
<|body_1|>
def delete_api(self, request, *args, **kwargs):
"""删除api"""
<|body_2|>
<|end_skel... | stack_v2_sparse_classes_36k_train_022497 | 1,672 | no_license | [
{
"docstring": "保存接口",
"name": "api_save",
"signature": "def api_save(self, request, *args, **kwargs)"
},
{
"docstring": "更新api",
"name": "update_api",
"signature": "def update_api(self, request, *args, **kwargs)"
},
{
"docstring": "删除api",
"name": "delete_api",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_015760 | Implement the Python class `UserApiInfoView` described below.
Class description:
Implement the UserApiInfoView class.
Method signatures and docstrings:
- def api_save(self, request, *args, **kwargs): 保存接口
- def update_api(self, request, *args, **kwargs): 更新api
- def delete_api(self, request, *args, **kwargs): 删除api | Implement the Python class `UserApiInfoView` described below.
Class description:
Implement the UserApiInfoView class.
Method signatures and docstrings:
- def api_save(self, request, *args, **kwargs): 保存接口
- def update_api(self, request, *args, **kwargs): 更新api
- def delete_api(self, request, *args, **kwargs): 删除api
... | 1c90b78a2cec1abb712b20dfed249041e45bcd36 | <|skeleton|>
class UserApiInfoView:
def api_save(self, request, *args, **kwargs):
"""保存接口"""
<|body_0|>
def update_api(self, request, *args, **kwargs):
"""更新api"""
<|body_1|>
def delete_api(self, request, *args, **kwargs):
"""删除api"""
<|body_2|>
<|end_skel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserApiInfoView:
def api_save(self, request, *args, **kwargs):
"""保存接口"""
verified_data = InterfaceSerializers.InterfaceSerializers(data=request.data)
if verified_data.is_valid():
verified_data.save(user=request.user)
return Response(status=status.HTTP_201_CREAT... | the_stack_v2_python_sparse | DjangoRESTFramework/RestFrameworkUser/InterfaceApi.py | AutomatedTestingChiefSoftwareArchitect/AutomationPlatform | train | 0 | |
798a6cefbbec2da6e0fe37f56d93a35a131dcef2 | [
"if block_range is None:\n latest = SystemStatus.get_latest_block()\n if not latest:\n return None\n block_range = [latest - 28800, latest]\nquery = f\"\"\"\\n SELECT * \\n FROM (\\n SELECT req_posting_auths,\\n op_json -> 1 -> 'following'::te... | <|body_start_0|>
if block_range is None:
latest = SystemStatus.get_latest_block()
if not latest:
return None
block_range = [latest - 28800, latest]
query = f"""\n SELECT * \n FROM (\n SELECT req_posting_auths,\n ... | SearchOps | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchOps:
def follow(cls, follower_account=None, followed_account=None, block_range=None):
""""follow" | {"follower":"idwritershive","following":"olgavita","what":["blog"]}"""
<|body_0|>
def reblog(cls, reblog_account=None, blog_author=None, blog_permlink=None, block_range=... | stack_v2_sparse_classes_36k_train_022498 | 2,841 | permissive | [
{
"docstring": "\"follow\" | {\"follower\":\"idwritershive\",\"following\":\"olgavita\",\"what\":[\"blog\"]}",
"name": "follow",
"signature": "def follow(cls, follower_account=None, followed_account=None, block_range=None)"
},
{
"docstring": "\"reblog\" | { \"account\":\"nataly2317\", \"author\"... | 2 | stack_v2_sparse_classes_30k_train_017806 | Implement the Python class `SearchOps` described below.
Class description:
Implement the SearchOps class.
Method signatures and docstrings:
- def follow(cls, follower_account=None, followed_account=None, block_range=None): "follow" | {"follower":"idwritershive","following":"olgavita","what":["blog"]}
- def reblog(cls... | Implement the Python class `SearchOps` described below.
Class description:
Implement the SearchOps class.
Method signatures and docstrings:
- def follow(cls, follower_account=None, followed_account=None, block_range=None): "follow" | {"follower":"idwritershive","following":"olgavita","what":["blog"]}
- def reblog(cls... | db801ff856bf2feb68580317e79cfd6006053e2c | <|skeleton|>
class SearchOps:
def follow(cls, follower_account=None, followed_account=None, block_range=None):
""""follow" | {"follower":"idwritershive","following":"olgavita","what":["blog"]}"""
<|body_0|>
def reblog(cls, reblog_account=None, blog_author=None, blog_permlink=None, block_range=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchOps:
def follow(cls, follower_account=None, followed_account=None, block_range=None):
""""follow" | {"follower":"idwritershive","following":"olgavita","what":["blog"]}"""
if block_range is None:
latest = SystemStatus.get_latest_block()
if not latest:
... | the_stack_v2_python_sparse | hive_plug_play/engine/plugs/follow.py | imwatsi/hive-plug-play | train | 3 | |
69f577738cfbf130400e4845012d5fefb446e338 | [
"super(TextInput, self).__init__(attrs)\nif source is None:\n raise ValueError('A source url should be given')\nself.source = source\nself.min_length = int(min_length)\nself.result_limit = result_limit\nself.force_check = force_check",
"if value is None:\n value = ''\nattrs['type'] = 'text'\nattrs['name'] =... | <|body_start_0|>
super(TextInput, self).__init__(attrs)
if source is None:
raise ValueError('A source url should be given')
self.source = source
self.min_length = int(min_length)
self.result_limit = result_limit
self.force_check = force_check
<|end_body_0|>
<... | A text input that autocompletes getting a json list | AutocompleteTextMultiInput | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutocompleteTextMultiInput:
"""A text input that autocompletes getting a json list"""
def __init__(self, attrs=None, source=None, min_length=3, result_limit=100, force_check=True):
"""It inits the widget. A source url for the json list should be given."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_022499 | 7,303 | no_license | [
{
"docstring": "It inits the widget. A source url for the json list should be given.",
"name": "__init__",
"signature": "def __init__(self, attrs=None, source=None, min_length=3, result_limit=100, force_check=True)"
},
{
"docstring": "It renders the html and the javascript",
"name": "render"... | 3 | null | Implement the Python class `AutocompleteTextMultiInput` described below.
Class description:
A text input that autocompletes getting a json list
Method signatures and docstrings:
- def __init__(self, attrs=None, source=None, min_length=3, result_limit=100, force_check=True): It inits the widget. A source url for the j... | Implement the Python class `AutocompleteTextMultiInput` described below.
Class description:
A text input that autocompletes getting a json list
Method signatures and docstrings:
- def __init__(self, attrs=None, source=None, min_length=3, result_limit=100, force_check=True): It inits the widget. A source url for the j... | 46364a9b82bee21444acf343f7f543b28a71f616 | <|skeleton|>
class AutocompleteTextMultiInput:
"""A text input that autocompletes getting a json list"""
def __init__(self, attrs=None, source=None, min_length=3, result_limit=100, force_check=True):
"""It inits the widget. A source url for the json list should be given."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutocompleteTextMultiInput:
"""A text input that autocompletes getting a json list"""
def __init__(self, attrs=None, source=None, min_length=3, result_limit=100, force_check=True):
"""It inits the widget. A source url for the json list should be given."""
super(TextInput, self).__init__(a... | the_stack_v2_python_sparse | vavilov/forms/widgets.py | pziarsolo/vavilov2 | train | 0 |
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