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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e1f4be9e5cd9c0f2196045d9eae82e270c395ef3 | [
"opening, count = (0, 0)\nfor ch in S:\n if ch == '(':\n opening += 1\n elif opening > 0:\n opening -= 1\n else:\n count += 1\nreturn count + opening",
"dq = collections.deque()\nl = []\nstackEmpty = True\nfor ch in S:\n if ch == ')':\n if len(dq) == 0:\n l.appen... | <|body_start_0|>
opening, count = (0, 0)
for ch in S:
if ch == '(':
opening += 1
elif opening > 0:
opening -= 1
else:
count += 1
return count + opening
<|end_body_0|>
<|body_start_1|>
dq = collections.de... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minAddToMakeValid(self, S):
""":type S: str :rtype: int"""
<|body_0|>
def minAddToMakeValid2(self, S):
""":type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
opening, count = (0, 0)
for ch in S:
... | stack_v2_sparse_classes_36k_train_008700 | 1,042 | no_license | [
{
"docstring": ":type S: str :rtype: int",
"name": "minAddToMakeValid",
"signature": "def minAddToMakeValid(self, S)"
},
{
"docstring": ":type S: str :rtype: int",
"name": "minAddToMakeValid2",
"signature": "def minAddToMakeValid2(self, S)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013414 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAddToMakeValid(self, S): :type S: str :rtype: int
- def minAddToMakeValid2(self, S): :type S: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAddToMakeValid(self, S): :type S: str :rtype: int
- def minAddToMakeValid2(self, S): :type S: str :rtype: int
<|skeleton|>
class Solution:
def minAddToMakeValid(self... | 813235789ce422a3bab198317aafc46fbc61625e | <|skeleton|>
class Solution:
def minAddToMakeValid(self, S):
""":type S: str :rtype: int"""
<|body_0|>
def minAddToMakeValid2(self, S):
""":type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minAddToMakeValid(self, S):
""":type S: str :rtype: int"""
opening, count = (0, 0)
for ch in S:
if ch == '(':
opening += 1
elif opening > 0:
opening -= 1
else:
count += 1
return co... | the_stack_v2_python_sparse | 11. STRING MANIP/921_Minimum Add to Make Parentheses Valid/solution.py | kimmyoo/python_leetcode | train | 1 | |
2b3d9dee1a08c017f17e621e995a8ecd1e8aed43 | [
"mol = Chem.MolFromSmiles(smiles)\nengine = ScaffoldGenerator(include_chirality=include_chirality)\nscaffold = engine.get_scaffold(mol)\nreturn scaffold",
"np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.0)\nscaffolds = {}\nlog('About to generate scaffolds', self.verbose)\ndata_len = len(dat... | <|body_start_0|>
mol = Chem.MolFromSmiles(smiles)
engine = ScaffoldGenerator(include_chirality=include_chirality)
scaffold = engine.get_scaffold(mol)
return scaffold
<|end_body_0|>
<|body_start_1|>
np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.0)
... | Class for doing data splits based on the scaffold of small molecules. | ScaffoldSplitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScaffoldSplitter:
"""Class for doing data splits based on the scaffold of small molecules."""
def generate_scaffold(self, smiles, include_chirality=False):
"""Compute the Bemis-Murcko scaffold for a SMILES string."""
<|body_0|>
def split(self, dataset, frac_train=0.5, fr... | stack_v2_sparse_classes_36k_train_008701 | 3,303 | no_license | [
{
"docstring": "Compute the Bemis-Murcko scaffold for a SMILES string.",
"name": "generate_scaffold",
"signature": "def generate_scaffold(self, smiles, include_chirality=False)"
},
{
"docstring": "Splits internal compounds into train/validation/test by scaffold.",
"name": "split",
"signa... | 2 | stack_v2_sparse_classes_30k_train_008356 | Implement the Python class `ScaffoldSplitter` described below.
Class description:
Class for doing data splits based on the scaffold of small molecules.
Method signatures and docstrings:
- def generate_scaffold(self, smiles, include_chirality=False): Compute the Bemis-Murcko scaffold for a SMILES string.
- def split(s... | Implement the Python class `ScaffoldSplitter` described below.
Class description:
Class for doing data splits based on the scaffold of small molecules.
Method signatures and docstrings:
- def generate_scaffold(self, smiles, include_chirality=False): Compute the Bemis-Murcko scaffold for a SMILES string.
- def split(s... | 57e40d04181059ca39890d22361606edfadcc930 | <|skeleton|>
class ScaffoldSplitter:
"""Class for doing data splits based on the scaffold of small molecules."""
def generate_scaffold(self, smiles, include_chirality=False):
"""Compute the Bemis-Murcko scaffold for a SMILES string."""
<|body_0|>
def split(self, dataset, frac_train=0.5, fr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScaffoldSplitter:
"""Class for doing data splits based on the scaffold of small molecules."""
def generate_scaffold(self, smiles, include_chirality=False):
"""Compute the Bemis-Murcko scaffold for a SMILES string."""
mol = Chem.MolFromSmiles(smiles)
engine = ScaffoldGenerator(incl... | the_stack_v2_python_sparse | utils/splitter/scaffoldsplitter.py | moguizhizi/Adaptive-Graph-Convolutional-Network | train | 0 |
d8e10ba53d21360d27236c6a9c75ac9a0a26fdad | [
"self.data = data\nself.page_size = page_size\nself.is_start = False\nself.is_end = False\nself.page_count = len(data)\nself.next_page = 0\nself.previous_page = 0\nself.page_nmuber = self.page_count / page_size\nif self.page_nmuber == int(self.page_nmuber):\n self.page_nmuber = int(self.page_nmuber)\nelse:\n ... | <|body_start_0|>
self.data = data
self.page_size = page_size
self.is_start = False
self.is_end = False
self.page_count = len(data)
self.next_page = 0
self.previous_page = 0
self.page_nmuber = self.page_count / page_size
if self.page_nmuber == int(s... | flask分页通过sqlalachemy查询进行分页 offset 偏移，开始查询的位置 limit 单页条数 分页器需要具备的功能 页码 分页数据 是否第一页 是否最后一页 | Pager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pager:
"""flask分页通过sqlalachemy查询进行分页 offset 偏移，开始查询的位置 limit 单页条数 分页器需要具备的功能 页码 分页数据 是否第一页 是否最后一页"""
def __init__(self, data, page_size):
""":param data: 要分页的数据 :param page_size: 每页多少条"""
<|body_0|>
def page_data(self, page):
"""返回分页数据 :param page: 页码 page_size =... | stack_v2_sparse_classes_36k_train_008702 | 12,240 | permissive | [
{
"docstring": ":param data: 要分页的数据 :param page_size: 每页多少条",
"name": "__init__",
"signature": "def __init__(self, data, page_size)"
},
{
"docstring": "返回分页数据 :param page: 页码 page_size = 10 1 offect 0 limit(10) 2 offect 10 limit(10) page_size = 10 1 start 0 end 10 2 start 10 end 20 3 start 20 en... | 2 | stack_v2_sparse_classes_30k_train_004456 | Implement the Python class `Pager` described below.
Class description:
flask分页通过sqlalachemy查询进行分页 offset 偏移，开始查询的位置 limit 单页条数 分页器需要具备的功能 页码 分页数据 是否第一页 是否最后一页
Method signatures and docstrings:
- def __init__(self, data, page_size): :param data: 要分页的数据 :param page_size: 每页多少条
- def page_data(self, page): 返回分页数据 :param... | Implement the Python class `Pager` described below.
Class description:
flask分页通过sqlalachemy查询进行分页 offset 偏移，开始查询的位置 limit 单页条数 分页器需要具备的功能 页码 分页数据 是否第一页 是否最后一页
Method signatures and docstrings:
- def __init__(self, data, page_size): :param data: 要分页的数据 :param page_size: 每页多少条
- def page_data(self, page): 返回分页数据 :param... | 2fce76763eee9a177ace466c43169e80d5c5b73c | <|skeleton|>
class Pager:
"""flask分页通过sqlalachemy查询进行分页 offset 偏移，开始查询的位置 limit 单页条数 分页器需要具备的功能 页码 分页数据 是否第一页 是否最后一页"""
def __init__(self, data, page_size):
""":param data: 要分页的数据 :param page_size: 每页多少条"""
<|body_0|>
def page_data(self, page):
"""返回分页数据 :param page: 页码 page_size =... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pager:
"""flask分页通过sqlalachemy查询进行分页 offset 偏移，开始查询的位置 limit 单页条数 分页器需要具备的功能 页码 分页数据 是否第一页 是否最后一页"""
def __init__(self, data, page_size):
""":param data: 要分页的数据 :param page_size: 每页多少条"""
self.data = data
self.page_size = page_size
self.is_start = False
self.is_end... | the_stack_v2_python_sparse | Flasknew/app/main/views.py | bestwishfang/PersonWork | train | 0 |
05c9918378c9f6e5a98a47c1c5f20ae76eeea900 | [
"heights.append(0)\nstack = []\ni = 0\nans = 0\nwhile i < len(heights):\n if len(stack) < 1 or heights[i] > heights[stack[-1]]:\n stack.append(i)\n i += 1\n else:\n tmp = stack.pop()\n ans = max(ans, heights[tmp] * (i if len(stack) < 1 else i - stack[-1] - 1))\nreturn ans",
"n = ... | <|body_start_0|>
heights.append(0)
stack = []
i = 0
ans = 0
while i < len(heights):
if len(stack) < 1 or heights[i] > heights[stack[-1]]:
stack.append(i)
i += 1
else:
tmp = stack.pop()
ans = m... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_0|>
def maximalRectangle(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
heights.append(... | stack_v2_sparse_classes_36k_train_008703 | 1,372 | no_license | [
{
"docstring": ":type heights: List[int] :rtype: int",
"name": "largestRectangleArea",
"signature": "def largestRectangleArea(self, heights)"
},
{
"docstring": ":type matrix: List[List[str]] :rtype: int",
"name": "maximalRectangle",
"signature": "def maximalRectangle(self, matrix)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int
- def maximalRectangle(self, matrix): :type matrix: List[List[str]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): :type heights: List[int] :rtype: int
- def maximalRectangle(self, matrix): :type matrix: List[List[str]] :rtype: int
<|skeleton|>
class ... | e890bd480de93418ce10867085b52137be2caa7a | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
<|body_0|>
def maximalRectangle(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largestRectangleArea(self, heights):
""":type heights: List[int] :rtype: int"""
heights.append(0)
stack = []
i = 0
ans = 0
while i < len(heights):
if len(stack) < 1 or heights[i] > heights[stack[-1]]:
stack.append(i)
... | the_stack_v2_python_sparse | python/85.py | LichAmnesia/LeetCode | train | 0 | |
ba931855d2dac4e79e0c64076540876b6b60f0c7 | [
"super(NeutronSubnetARMTranslator, self).get_variables()\ncidr = self._heat_resource.properties['cidr']\nreturn {'subNetAddressPrefix_%s' % self._heat_resource_name: cidr}",
"super(NeutronSubnetARMTranslator, self).get_resource_data()\nnet_name = self._context.heat_resource_stack[self._heat_resource.properties['n... | <|body_start_0|>
super(NeutronSubnetARMTranslator, self).get_variables()
cidr = self._heat_resource.properties['cidr']
return {'subNetAddressPrefix_%s' % self._heat_resource_name: cidr}
<|end_body_0|>
<|body_start_1|>
super(NeutronSubnetARMTranslator, self).get_resource_data()
n... | NeutronSubnetARMTranslator is the translator associated to a Neutron subnet. This translator leads to the defining of a new virtual network; as Neutron nets themselves have no real resulting translation without them. | NeutronSubnetARMTranslator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeutronSubnetARMTranslator:
"""NeutronSubnetARMTranslator is the translator associated to a Neutron subnet. This translator leads to the defining of a new virtual network; as Neutron nets themselves have no real resulting translation without them."""
def get_variables(self):
"""get_v... | stack_v2_sparse_classes_36k_train_008704 | 4,905 | permissive | [
{
"docstring": "get_variables resurns the dict of ARM template variables associated with the Neutron subnet.",
"name": "get_variables",
"signature": "def get_variables(self)"
},
{
"docstring": "get_resource_data retuns the list of all characteristics representing the subnet which can be directly... | 2 | stack_v2_sparse_classes_30k_train_021677 | Implement the Python class `NeutronSubnetARMTranslator` described below.
Class description:
NeutronSubnetARMTranslator is the translator associated to a Neutron subnet. This translator leads to the defining of a new virtual network; as Neutron nets themselves have no real resulting translation without them.
Method si... | Implement the Python class `NeutronSubnetARMTranslator` described below.
Class description:
NeutronSubnetARMTranslator is the translator associated to a Neutron subnet. This translator leads to the defining of a new virtual network; as Neutron nets themselves have no real resulting translation without them.
Method si... | 83472c7a4af3496e28c1b7b4021e31c373f37784 | <|skeleton|>
class NeutronSubnetARMTranslator:
"""NeutronSubnetARMTranslator is the translator associated to a Neutron subnet. This translator leads to the defining of a new virtual network; as Neutron nets themselves have no real resulting translation without them."""
def get_variables(self):
"""get_v... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NeutronSubnetARMTranslator:
"""NeutronSubnetARMTranslator is the translator associated to a Neutron subnet. This translator leads to the defining of a new virtual network; as Neutron nets themselves have no real resulting translation without them."""
def get_variables(self):
"""get_variables resu... | the_stack_v2_python_sparse | heat2arm/translators/networking/neutron_net.py | travlaw/heat2arm | train | 0 |
e54efb15c51dff9e2990d56eae3315ff7365116b | [
"byte_string = erd_decode_bytes(value)\ncook_mode_code = byte_string[0]\ntemperature = int.from_bytes(byte_string[1:3], 'big')\ncook_mode = ErdOvenCookMode(cook_mode_code)\nreturn OvenCookSetting(cook_mode=OVEN_COOK_MODE_MAP[cook_mode], temperature=temperature, raw_bytes=byte_string)",
"cook_mode = value.cook_mod... | <|body_start_0|>
byte_string = erd_decode_bytes(value)
cook_mode_code = byte_string[0]
temperature = int.from_bytes(byte_string[1:3], 'big')
cook_mode = ErdOvenCookMode(cook_mode_code)
return OvenCookSetting(cook_mode=OVEN_COOK_MODE_MAP[cook_mode], temperature=temperature, raw_by... | OvenCookModeConverter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OvenCookModeConverter:
def erd_decode(self, value: str) -> OvenCookSetting:
"""Get the cook mode and temperature. TODO: Figure out what the other 10 bytes are for. I'm guessing they have to do with two-temp cooking, probes, delayed starts, timers, etc."""
<|body_0|>
def erd_... | stack_v2_sparse_classes_36k_train_008705 | 1,279 | permissive | [
{
"docstring": "Get the cook mode and temperature. TODO: Figure out what the other 10 bytes are for. I'm guessing they have to do with two-temp cooking, probes, delayed starts, timers, etc.",
"name": "erd_decode",
"signature": "def erd_decode(self, value: str) -> OvenCookSetting"
},
{
"docstring... | 2 | stack_v2_sparse_classes_30k_train_019551 | Implement the Python class `OvenCookModeConverter` described below.
Class description:
Implement the OvenCookModeConverter class.
Method signatures and docstrings:
- def erd_decode(self, value: str) -> OvenCookSetting: Get the cook mode and temperature. TODO: Figure out what the other 10 bytes are for. I'm guessing t... | Implement the Python class `OvenCookModeConverter` described below.
Class description:
Implement the OvenCookModeConverter class.
Method signatures and docstrings:
- def erd_decode(self, value: str) -> OvenCookSetting: Get the cook mode and temperature. TODO: Figure out what the other 10 bytes are for. I'm guessing t... | 017aeca860f231f60bc70fc747067388ad577b18 | <|skeleton|>
class OvenCookModeConverter:
def erd_decode(self, value: str) -> OvenCookSetting:
"""Get the cook mode and temperature. TODO: Figure out what the other 10 bytes are for. I'm guessing they have to do with two-temp cooking, probes, delayed starts, timers, etc."""
<|body_0|>
def erd_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OvenCookModeConverter:
def erd_decode(self, value: str) -> OvenCookSetting:
"""Get the cook mode and temperature. TODO: Figure out what the other 10 bytes are for. I'm guessing they have to do with two-temp cooking, probes, delayed starts, timers, etc."""
byte_string = erd_decode_bytes(value)
... | the_stack_v2_python_sparse | gehomesdk/erd/converters/oven/oven_cook_mode_converter.py | bendavis/gehome | train | 0 | |
b0885b3053ff65667b86eb1a0d192b8ef818f1f8 | [
"import re\nfor int_pat in self.patterns:\n match = re.search(int_pat, text, flags=re.IGNORECASE)\n if match:\n return match[1]\nreturn False",
"if self.recept(text, *args, **kwargs):\n return True\nelse:\n return False"
] | <|body_start_0|>
import re
for int_pat in self.patterns:
match = re.search(int_pat, text, flags=re.IGNORECASE)
if match:
return match[1]
return False
<|end_body_0|>
<|body_start_1|>
if self.recept(text, *args, **kwargs):
return True
... | Slot which validates answer by patterns in regexp | PatternedTextSlot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PatternedTextSlot:
"""Slot which validates answer by patterns in regexp"""
def recept(self, text, *args, **kwargs):
"""Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:"""
<|body_0|>
def... | stack_v2_sparse_classes_36k_train_008706 | 26,321 | no_license | [
{
"docstring": "Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:",
"name": "recept",
"signature": "def recept(self, text, *args, **kwargs)"
},
{
"docstring": "Method that checks if UserMessage can be recepted b... | 2 | null | Implement the Python class `PatternedTextSlot` described below.
Class description:
Slot which validates answer by patterns in regexp
Method signatures and docstrings:
- def recept(self, text, *args, **kwargs): Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str)... | Implement the Python class `PatternedTextSlot` described below.
Class description:
Slot which validates answer by patterns in regexp
Method signatures and docstrings:
- def recept(self, text, *args, **kwargs): Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str)... | 7a0bc78ca03ee8ca1202e8ad2a6860444f0ce75d | <|skeleton|>
class PatternedTextSlot:
"""Slot which validates answer by patterns in regexp"""
def recept(self, text, *args, **kwargs):
"""Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:"""
<|body_0|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PatternedTextSlot:
"""Slot which validates answer by patterns in regexp"""
def recept(self, text, *args, **kwargs):
"""Method that actually recepts message and extracts Slot's Value from it Args: text: text to be analyzed (str) *args: **kwargs: Returns:"""
import re
for int_pat in... | the_stack_v2_python_sparse | ruler_bot/components/slots/slots.py | acriptis/dj_bot | train | 3 |
55a8d31018ec74d8722fc0afe894a7a192e2d665 | [
"audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)\nif audit['submitted'] == True:\n abort(400, 'Already submitted')\nif audit['approved'] == True:\n abort(400, 'Already approved by administrator(s)')\nschema = AuditUpdateSchema(only=['submitted', 'rejected_reason'])\... | <|body_start_0|>
audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)
if audit['submitted'] == True:
abort(400, 'Already submitted')
if audit['approved'] == True:
abort(400, 'Already approved by administrator(s)')
schema = Au... | AuditSubmission | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
<|body_0|>
def delete(self, audit_uuid):
"""Withdraw the submission of the specified audit result"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
audit = AuditResou... | stack_v2_sparse_classes_36k_train_008707 | 18,857 | no_license | [
{
"docstring": "Submit the specified audit result",
"name": "post",
"signature": "def post(self, audit_uuid)"
},
{
"docstring": "Withdraw the submission of the specified audit result",
"name": "delete",
"signature": "def delete(self, audit_uuid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006016 | Implement the Python class `AuditSubmission` described below.
Class description:
Implement the AuditSubmission class.
Method signatures and docstrings:
- def post(self, audit_uuid): Submit the specified audit result
- def delete(self, audit_uuid): Withdraw the submission of the specified audit result | Implement the Python class `AuditSubmission` described below.
Class description:
Implement the AuditSubmission class.
Method signatures and docstrings:
- def post(self, audit_uuid): Submit the specified audit result
- def delete(self, audit_uuid): Withdraw the submission of the specified audit result
<|skeleton|>
cl... | 7b67aa682d73c8a8d7f0f19b2a90e69c40761c58 | <|skeleton|>
class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
<|body_0|>
def delete(self, audit_uuid):
"""Withdraw the submission of the specified audit result"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)
if audit['submitted'] == True:
abort(400, 'Already submitted')
if audit['approved'] == Tr... | the_stack_v2_python_sparse | rem/apis/audit.py | recruit-tech/casval | train | 6 | |
f8ae41e4bfa3a3e2ba7c7d28a46d8bb90429e5fb | [
"if selections:\n selection = selections[0]\n editors = self.window.application.get_extensions(EDITORS)\n exts = [ext for factory in editors for ext in factory().extensions]\n if isinstance(selection, File) and selection.ext in exts:\n self.enabled = True\n else:\n self.enabled = False\... | <|body_start_0|>
if selections:
selection = selections[0]
editors = self.window.application.get_extensions(EDITORS)
exts = [ext for factory in editors for ext in factory().extensions]
if isinstance(selection, File) and selection.ext in exts:
self.e... | Defines an action that open the current resource. | OpenAction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenAction:
"""Defines an action that open the current resource."""
def _selection_changed_for_window(self, selections):
"""Makes the action visible if a File is selected."""
<|body_0|>
def _enabled_default(self):
"""Trait initialiser."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_008708 | 5,755 | permissive | [
{
"docstring": "Makes the action visible if a File is selected.",
"name": "_selection_changed_for_window",
"signature": "def _selection_changed_for_window(self, selections)"
},
{
"docstring": "Trait initialiser.",
"name": "_enabled_default",
"signature": "def _enabled_default(self)"
},... | 4 | null | Implement the Python class `OpenAction` described below.
Class description:
Defines an action that open the current resource.
Method signatures and docstrings:
- def _selection_changed_for_window(self, selections): Makes the action visible if a File is selected.
- def _enabled_default(self): Trait initialiser.
- def ... | Implement the Python class `OpenAction` described below.
Class description:
Defines an action that open the current resource.
Method signatures and docstrings:
- def _selection_changed_for_window(self, selections): Makes the action visible if a File is selected.
- def _enabled_default(self): Trait initialiser.
- def ... | e8fc0b2d6b9b08e60389fc4714a5cf51f628b57f | <|skeleton|>
class OpenAction:
"""Defines an action that open the current resource."""
def _selection_changed_for_window(self, selections):
"""Makes the action visible if a File is selected."""
<|body_0|>
def _enabled_default(self):
"""Trait initialiser."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OpenAction:
"""Defines an action that open the current resource."""
def _selection_changed_for_window(self, selections):
"""Makes the action visible if a File is selected."""
if selections:
selection = selections[0]
editors = self.window.application.get_extensions(... | the_stack_v2_python_sparse | puddle/resource/action/open_action.py | rwl/puddle | train | 2 |
6971f209acaf0cbbb0f0e2790f8b0befdd9d4317 | [
"if k == 0:\n return s\nif k == 1:\n return min((s[i:] + s[:i] for i in range(len(s))))\nelse:\n return ''.join(sorted(list(s)))",
"if k > 2:\n return ''.join(sorted(s))\nret = s\nfor i in range(1, len(s)):\n ret = min(ret, s[i:] + s[:i])\nreturn ret"
] | <|body_start_0|>
if k == 0:
return s
if k == 1:
return min((s[i:] + s[:i] for i in range(len(s))))
else:
return ''.join(sorted(list(s)))
<|end_body_0|>
<|body_start_1|>
if k > 2:
return ''.join(sorted(s))
ret = s
for i in r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def orderlyQueue(self, s: str, k: int) -> str:
"""09/22/2021 21:15"""
<|body_0|>
def orderlyQueue(self, s: str, k: int) -> str:
"""11/13/2022 18:09"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if k == 0:
return s
if ... | stack_v2_sparse_classes_36k_train_008709 | 1,850 | no_license | [
{
"docstring": "09/22/2021 21:15",
"name": "orderlyQueue",
"signature": "def orderlyQueue(self, s: str, k: int) -> str"
},
{
"docstring": "11/13/2022 18:09",
"name": "orderlyQueue",
"signature": "def orderlyQueue(self, s: str, k: int) -> str"
}
] | 2 | stack_v2_sparse_classes_30k_train_015011 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def orderlyQueue(self, s: str, k: int) -> str: 09/22/2021 21:15
- def orderlyQueue(self, s: str, k: int) -> str: 11/13/2022 18:09 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def orderlyQueue(self, s: str, k: int) -> str: 09/22/2021 21:15
- def orderlyQueue(self, s: str, k: int) -> str: 11/13/2022 18:09
<|skeleton|>
class Solution:
def orderlyQu... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def orderlyQueue(self, s: str, k: int) -> str:
"""09/22/2021 21:15"""
<|body_0|>
def orderlyQueue(self, s: str, k: int) -> str:
"""11/13/2022 18:09"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def orderlyQueue(self, s: str, k: int) -> str:
"""09/22/2021 21:15"""
if k == 0:
return s
if k == 1:
return min((s[i:] + s[:i] for i in range(len(s))))
else:
return ''.join(sorted(list(s)))
def orderlyQueue(self, s: str, k: int... | the_stack_v2_python_sparse | leetcode/solved/935_Orderly_Queue/solution.py | sungminoh/algorithms | train | 0 | |
592a010bf240f8442e6015118c0ab5076aad0380 | [
"description = data_utils.rand_name('test_create_consumer')\nconsumer = self.oauth_consumers_client.create_consumer(description)['consumer']\nself.addCleanup(test_utils.call_and_ignore_notfound_exc, self.oauth_consumers_client.delete_consumer, consumer['id'])\nreturn consumer",
"consumer = self._create_consumer()... | <|body_start_0|>
description = data_utils.rand_name('test_create_consumer')
consumer = self.oauth_consumers_client.create_consumer(description)['consumer']
self.addCleanup(test_utils.call_and_ignore_notfound_exc, self.oauth_consumers_client.delete_consumer, consumer['id'])
return consume... | OAUTHConsumersV3Test | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OAUTHConsumersV3Test:
def _create_consumer(self):
"""Creates a consumer with a random description."""
<|body_0|>
def test_create_and_show_consumer(self):
"""Tests to make sure that a consumer with parameters is made"""
<|body_1|>
def test_delete_consumer... | stack_v2_sparse_classes_36k_train_008710 | 4,451 | permissive | [
{
"docstring": "Creates a consumer with a random description.",
"name": "_create_consumer",
"signature": "def _create_consumer(self)"
},
{
"docstring": "Tests to make sure that a consumer with parameters is made",
"name": "test_create_and_show_consumer",
"signature": "def test_create_and... | 5 | null | Implement the Python class `OAUTHConsumersV3Test` described below.
Class description:
Implement the OAUTHConsumersV3Test class.
Method signatures and docstrings:
- def _create_consumer(self): Creates a consumer with a random description.
- def test_create_and_show_consumer(self): Tests to make sure that a consumer wi... | Implement the Python class `OAUTHConsumersV3Test` described below.
Class description:
Implement the OAUTHConsumersV3Test class.
Method signatures and docstrings:
- def _create_consumer(self): Creates a consumer with a random description.
- def test_create_and_show_consumer(self): Tests to make sure that a consumer wi... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class OAUTHConsumersV3Test:
def _create_consumer(self):
"""Creates a consumer with a random description."""
<|body_0|>
def test_create_and_show_consumer(self):
"""Tests to make sure that a consumer with parameters is made"""
<|body_1|>
def test_delete_consumer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OAUTHConsumersV3Test:
def _create_consumer(self):
"""Creates a consumer with a random description."""
description = data_utils.rand_name('test_create_consumer')
consumer = self.oauth_consumers_client.create_consumer(description)['consumer']
self.addCleanup(test_utils.call_and_i... | the_stack_v2_python_sparse | tempest/api/identity/admin/v3/test_oauth_consumers.py | openstack/tempest | train | 270 | |
0b3bc52a223e3032880b4ddd37fb04225a1bd2a8 | [
"ctx.save_for_backward(input)\nout = torch.zeros_like(input)\nout[input > 0] = 1.0\nreturn out",
"input, = ctx.saved_tensors\ngrad_input = grad_output.clone()\ngrad = grad_input / (SuperSpike.scale * torch.abs(input) + 1.0) ** 2\nreturn grad"
] | <|body_start_0|>
ctx.save_for_backward(input)
out = torch.zeros_like(input)
out[input > 0] = 1.0
return out
<|end_body_0|>
<|body_start_1|>
input, = ctx.saved_tensors
grad_input = grad_output.clone()
grad = grad_input / (SuperSpike.scale * torch.abs(input) + 1.0)... | Here we implement our spiking nonlinearity which also implements the surrogate gradient. By subclassing torch.autograd.Function, we will be able to use all of PyTorch's autograd functionality. Here we use the normalized negative part of a fast sigmoid as this was done in Zenke & Ganguli (2018). | SuperSpike | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperSpike:
"""Here we implement our spiking nonlinearity which also implements the surrogate gradient. By subclassing torch.autograd.Function, we will be able to use all of PyTorch's autograd functionality. Here we use the normalized negative part of a fast sigmoid as this was done in Zenke & Ga... | stack_v2_sparse_classes_36k_train_008711 | 16,829 | permissive | [
{
"docstring": "In the forward pass we compute a step function of the input Tensor and return it. ctx is a context object that we use to stash information which we need to later backpropagate our error signals. To achieve this we use the ctx.save_for_backward method.",
"name": "forward",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_013736 | Implement the Python class `SuperSpike` described below.
Class description:
Here we implement our spiking nonlinearity which also implements the surrogate gradient. By subclassing torch.autograd.Function, we will be able to use all of PyTorch's autograd functionality. Here we use the normalized negative part of a fast... | Implement the Python class `SuperSpike` described below.
Class description:
Here we implement our spiking nonlinearity which also implements the surrogate gradient. By subclassing torch.autograd.Function, we will be able to use all of PyTorch's autograd functionality. Here we use the normalized negative part of a fast... | 8bf028a5aa3f545239133a5f9f2937de9a5803d7 | <|skeleton|>
class SuperSpike:
"""Here we implement our spiking nonlinearity which also implements the surrogate gradient. By subclassing torch.autograd.Function, we will be able to use all of PyTorch's autograd functionality. Here we use the normalized negative part of a fast sigmoid as this was done in Zenke & Ga... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SuperSpike:
"""Here we implement our spiking nonlinearity which also implements the surrogate gradient. By subclassing torch.autograd.Function, we will be able to use all of PyTorch's autograd functionality. Here we use the normalized negative part of a fast sigmoid as this was done in Zenke & Ganguli (2018).... | the_stack_v2_python_sparse | Code/SQN.py | vhris/Deep-Spiking-Q-Networks | train | 10 |
c110498e102aebfbc90fba86602a541e5d5ceb29 | [
"self.p = p\nfrom sage.rings.polynomial.polynomial_ring_constructor import PolynomialRing\nself.ring = PolynomialRing(FiniteField(p), 'x')\nif use_database:\n C = sage.databases.conway.ConwayPolynomials()\n self.nodes = {n: self.ring(C.polynomial(p, n)) for n in C.degrees(p)}\nelse:\n self.nodes = {}",
"... | <|body_start_0|>
self.p = p
from sage.rings.polynomial.polynomial_ring_constructor import PolynomialRing
self.ring = PolynomialRing(FiniteField(p), 'x')
if use_database:
C = sage.databases.conway.ConwayPolynomials()
self.nodes = {n: self.ring(C.polynomial(p, n)) f... | A pseudo-Conway lattice over a given finite prime field. The Conway polynomial `f_n` of degree `n` over `\\Bold{F}_p` is defined by the following four conditions: - `f_n` is irreducible. - In the quotient field `\\Bold{F}_p[x]/(f_n)`, the element `x\\bmod f_n` generates the multiplicative group. - The minimal polynomia... | PseudoConwayLattice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PseudoConwayLattice:
"""A pseudo-Conway lattice over a given finite prime field. The Conway polynomial `f_n` of degree `n` over `\\Bold{F}_p` is defined by the following four conditions: - `f_n` is irreducible. - In the quotient field `\\Bold{F}_p[x]/(f_n)`, the element `x\\bmod f_n` generates th... | stack_v2_sparse_classes_36k_train_008712 | 18,867 | no_license | [
{
"docstring": "TESTS:: sage: from sage.rings.finite_rings.conway_polynomials import PseudoConwayLattice sage: PCL = PseudoConwayLattice(3) sage: PCL.polynomial(3) x^3 + 2*x + 1 sage: PCL = PseudoConwayLattice(5, use_database=False) sage: PCL.polynomial(12) x^12 + 4*x^11 + 2*x^10 + 4*x^9 + 2*x^8 + 2*x^7 + 4*x^6... | 3 | stack_v2_sparse_classes_30k_train_018781 | Implement the Python class `PseudoConwayLattice` described below.
Class description:
A pseudo-Conway lattice over a given finite prime field. The Conway polynomial `f_n` of degree `n` over `\\Bold{F}_p` is defined by the following four conditions: - `f_n` is irreducible. - In the quotient field `\\Bold{F}_p[x]/(f_n)`,... | Implement the Python class `PseudoConwayLattice` described below.
Class description:
A pseudo-Conway lattice over a given finite prime field. The Conway polynomial `f_n` of degree `n` over `\\Bold{F}_p` is defined by the following four conditions: - `f_n` is irreducible. - In the quotient field `\\Bold{F}_p[x]/(f_n)`,... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class PseudoConwayLattice:
"""A pseudo-Conway lattice over a given finite prime field. The Conway polynomial `f_n` of degree `n` over `\\Bold{F}_p` is defined by the following four conditions: - `f_n` is irreducible. - In the quotient field `\\Bold{F}_p[x]/(f_n)`, the element `x\\bmod f_n` generates th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PseudoConwayLattice:
"""A pseudo-Conway lattice over a given finite prime field. The Conway polynomial `f_n` of degree `n` over `\\Bold{F}_p` is defined by the following four conditions: - `f_n` is irreducible. - In the quotient field `\\Bold{F}_p[x]/(f_n)`, the element `x\\bmod f_n` generates the multiplicat... | the_stack_v2_python_sparse | sage/src/sage/rings/finite_rings/conway_polynomials.py | bopopescu/geosci | train | 0 |
cb208f5b06e0a3683ece12eab844fb7c92966d80 | [
"if not head or not head.next:\n return head\nslow, fast = (head, head)\nwhile fast.next and fast.next.next:\n slow = slow.next\n fast = fast.next.next\nreturn slow",
"if not head or not head.next:\n return head\ncount = 0\ntemp = head\nwhile temp:\n count += 1\n temp = temp.next\nfor i in range... | <|body_start_0|>
if not head or not head.next:
return head
slow, fast = (head, head)
while fast.next and fast.next.next:
slow = slow.next
fast = fast.next.next
return slow
<|end_body_0|>
<|body_start_1|>
if not head or not head.next:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def middle_linked_list(self, head: ListNode) -> ListNode:
"""找出中间结点 Args: head: 头结点 Returns: 中间结点"""
<|body_0|>
def middle_linked_list2(self, head: ListNode) -> ListNode:
"""找出中间结点 Args: head: 头结点 Returns: 中间结点"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_008713 | 2,791 | permissive | [
{
"docstring": "找出中间结点 Args: head: 头结点 Returns: 中间结点",
"name": "middle_linked_list",
"signature": "def middle_linked_list(self, head: ListNode) -> ListNode"
},
{
"docstring": "找出中间结点 Args: head: 头结点 Returns: 中间结点",
"name": "middle_linked_list2",
"signature": "def middle_linked_list2(self... | 2 | stack_v2_sparse_classes_30k_train_009568 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def middle_linked_list(self, head: ListNode) -> ListNode: 找出中间结点 Args: head: 头结点 Returns: 中间结点
- def middle_linked_list2(self, head: ListNode) -> ListNode: 找出中间结点 Args: head: 头结点... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def middle_linked_list(self, head: ListNode) -> ListNode: 找出中间结点 Args: head: 头结点 Returns: 中间结点
- def middle_linked_list2(self, head: ListNode) -> ListNode: 找出中间结点 Args: head: 头结点... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def middle_linked_list(self, head: ListNode) -> ListNode:
"""找出中间结点 Args: head: 头结点 Returns: 中间结点"""
<|body_0|>
def middle_linked_list2(self, head: ListNode) -> ListNode:
"""找出中间结点 Args: head: 头结点 Returns: 中间结点"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def middle_linked_list(self, head: ListNode) -> ListNode:
"""找出中间结点 Args: head: 头结点 Returns: 中间结点"""
if not head or not head.next:
return head
slow, fast = (head, head)
while fast.next and fast.next.next:
slow = slow.next
fast = fas... | the_stack_v2_python_sparse | src/leetcodepython/list/middle_linked_list_876.py | zhangyu345293721/leetcode | train | 101 | |
001556dc0613a70bb7af7de995cf9a37e75ec170 | [
"self.grid = ugrid\npts = self.grid.GetPoints()\nnumPoints = pts.GetNumberOfPoints()\ndata = vtk.vtkDoubleArray()\ndata.SetName(name)\ndata.SetNumberOfComponents(1)\ndata.SetNumberOfTuples(numPoints)\nfor i in range(numPoints):\n xyz = pts.GetPoint(i)\n f = nodalFunc(xyz)\n data.SetTuple(i, (f,))\nself.gri... | <|body_start_0|>
self.grid = ugrid
pts = self.grid.GetPoints()
numPoints = pts.GetNumberOfPoints()
data = vtk.vtkDoubleArray()
data.SetName(name)
data.SetNumberOfComponents(1)
data.SetNumberOfTuples(numPoints)
for i in range(numPoints):
xyz = p... | NodalFunctionWriter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodalFunctionWriter:
def __init__(self, ugrid, nodalFunc, name='nodalFunction'):
"""Constructor @param ugrid vtkUnstructuredGrid instance @param nodalFunc"""
<|body_0|>
def save(self, filename):
"""Save data in file @param filename file name"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_008714 | 962 | no_license | [
{
"docstring": "Constructor @param ugrid vtkUnstructuredGrid instance @param nodalFunc",
"name": "__init__",
"signature": "def __init__(self, ugrid, nodalFunc, name='nodalFunction')"
},
{
"docstring": "Save data in file @param filename file name",
"name": "save",
"signature": "def save(s... | 2 | stack_v2_sparse_classes_30k_train_017377 | Implement the Python class `NodalFunctionWriter` described below.
Class description:
Implement the NodalFunctionWriter class.
Method signatures and docstrings:
- def __init__(self, ugrid, nodalFunc, name='nodalFunction'): Constructor @param ugrid vtkUnstructuredGrid instance @param nodalFunc
- def save(self, filename... | Implement the Python class `NodalFunctionWriter` described below.
Class description:
Implement the NodalFunctionWriter class.
Method signatures and docstrings:
- def __init__(self, ugrid, nodalFunc, name='nodalFunction'): Constructor @param ugrid vtkUnstructuredGrid instance @param nodalFunc
- def save(self, filename... | 383bfa5e8b450eda0cbc6bdebf092e81712034e4 | <|skeleton|>
class NodalFunctionWriter:
def __init__(self, ugrid, nodalFunc, name='nodalFunction'):
"""Constructor @param ugrid vtkUnstructuredGrid instance @param nodalFunc"""
<|body_0|>
def save(self, filename):
"""Save data in file @param filename file name"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NodalFunctionWriter:
def __init__(self, ugrid, nodalFunc, name='nodalFunction'):
"""Constructor @param ugrid vtkUnstructuredGrid instance @param nodalFunc"""
self.grid = ugrid
pts = self.grid.GetPoints()
numPoints = pts.GetNumberOfPoints()
data = vtk.vtkDoubleArray()
... | the_stack_v2_python_sparse | py/igNodalFunctionWriter.py | pletzer/inugrid | train | 0 | |
f2dd0adc1e4e1d42062a7456aeee4218dc58244d | [
"if root is None:\n return root\nif root.val > key:\n root.left = self.deleteNode(root.left, key)\nelif root.val < key:\n root.right = self.deleteNode(root.right, key)\nelif root.left is None and root.right is None:\n root = None\nelif root.right is not None:\n root.val = self.successor(root.right)\n... | <|body_start_0|>
if root is None:
return root
if root.val > key:
root.left = self.deleteNode(root.left, key)
elif root.val < key:
root.right = self.deleteNode(root.right, key)
elif root.left is None and root.right is None:
root = None
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def successor(self, root):
"""always left"""
<|body_1|>
def predecessor(self, root):
"""always right"""
<|body_2|>
<|end_ske... | stack_v2_sparse_classes_36k_train_008715 | 2,055 | no_license | [
{
"docstring": ":type root: TreeNode :type key: int :rtype: TreeNode",
"name": "deleteNode",
"signature": "def deleteNode(self, root, key)"
},
{
"docstring": "always left",
"name": "successor",
"signature": "def successor(self, root)"
},
{
"docstring": "always right",
"name":... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def successor(self, root): always left
- def predecessor(self, root): always right | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def successor(self, root): always left
- def predecessor(self, root): always right
<|skel... | e4d21223c85b622b5a905d1a056dfb2f300964b1 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def successor(self, root):
"""always left"""
<|body_1|>
def predecessor(self, root):
"""always right"""
<|body_2|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
if root is None:
return root
if root.val > key:
root.left = self.deleteNode(root.left, key)
elif root.val < key:
root.right = self.deleteNod... | the_stack_v2_python_sparse | Algorithms/tree/450.delete-node-in-a-bst/delete-node-in-a-bst.py | gosyang/leetcode | train | 1 | |
2ef601b6b82a6cd9749b697cd4c42d0d4ce7c62e | [
"self.t = t0\nself.y = y0\nself.t_bound = t_bound\nself.step_size = stepsize\nself._fun = fun\nself.direction = 1 * (self.t_bound >= t0) - 1 * (not self.t_bound < t0)",
"if self.t >= self.t_bound and self.direction == 1 or (self.t <= self.t_bound and self.direction == -1):\n warnings.warn('Out of bounds set by... | <|body_start_0|>
self.t = t0
self.y = y0
self.t_bound = t_bound
self.step_size = stepsize
self._fun = fun
self.direction = 1 * (self.t_bound >= t0) - 1 * (not self.t_bound < t0)
<|end_body_0|>
<|body_start_1|>
if self.t >= self.t_bound and self.direction == 1 or ... | Class for Defining Runge-Kutta 4th Order ODE solving method | RK4naive | [
"LicenseRef-scancode-proprietary-license",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RK4naive:
"""Class for Defining Runge-Kutta 4th Order ODE solving method"""
def __init__(self, fun, t0, y0, t_bound, stepsize):
"""Initialization Parameters ---------- fun : function Should accept t, y as parameters, and return same type as y t0 : float Initial t y0 : ~numpy.array or... | stack_v2_sparse_classes_36k_train_008716 | 3,387 | permissive | [
{
"docstring": "Initialization Parameters ---------- fun : function Should accept t, y as parameters, and return same type as y t0 : float Initial t y0 : ~numpy.array or float Initial y t_bound : float Boundary time - the integration won't continue beyond it. It also determines the direction of the integration.... | 2 | stack_v2_sparse_classes_30k_train_012033 | Implement the Python class `RK4naive` described below.
Class description:
Class for Defining Runge-Kutta 4th Order ODE solving method
Method signatures and docstrings:
- def __init__(self, fun, t0, y0, t_bound, stepsize): Initialization Parameters ---------- fun : function Should accept t, y as parameters, and return... | Implement the Python class `RK4naive` described below.
Class description:
Class for Defining Runge-Kutta 4th Order ODE solving method
Method signatures and docstrings:
- def __init__(self, fun, t0, y0, t_bound, stepsize): Initialization Parameters ---------- fun : function Should accept t, y as parameters, and return... | 1bd1b27e142b0a0ec2e26bf2611468dbf50d9cf8 | <|skeleton|>
class RK4naive:
"""Class for Defining Runge-Kutta 4th Order ODE solving method"""
def __init__(self, fun, t0, y0, t_bound, stepsize):
"""Initialization Parameters ---------- fun : function Should accept t, y as parameters, and return same type as y t0 : float Initial t y0 : ~numpy.array or... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RK4naive:
"""Class for Defining Runge-Kutta 4th Order ODE solving method"""
def __init__(self, fun, t0, y0, t_bound, stepsize):
"""Initialization Parameters ---------- fun : function Should accept t, y as parameters, and return same type as y t0 : float Initial t y0 : ~numpy.array or float Initia... | the_stack_v2_python_sparse | src/einsteinpy/integrators/runge_kutta.py | einsteinpy/einsteinpy | train | 594 |
960cc124a1921cf3d712310bf0d4b13f51b795bc | [
"nums.sort()\ndic = collections.defaultdict(set)\nres = set()\nn = len(nums)\nfor i in range(n):\n for j in range(i + 1, n):\n sum = nums[i] + nums[j]\n for half in dic[target - sum]:\n res.add(tuple(list(half) + [nums[i], nums[j]]))\n for j in range(i):\n dic[nums[i] + nums[j]... | <|body_start_0|>
nums.sort()
dic = collections.defaultdict(set)
res = set()
n = len(nums)
for i in range(n):
for j in range(i + 1, n):
sum = nums[i] + nums[j]
for half in dic[target - sum]:
res.add(tuple(list(half) +... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def fourSum_error(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_008717 | 1,783 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum",
"signature": "def fourSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum_error",
"signature": "def fourSum_erro... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]]
- def fourSum_error(self, nums, target): :type nums: List[int] :type target: int ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]]
- def fourSum_error(self, nums, target): :type nums: List[int] :type target: int ... | a2cd0dc5e098080df87c4fb57d16877d21ca47a3 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def fourSum_error(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
nums.sort()
dic = collections.defaultdict(set)
res = set()
n = len(nums)
for i in range(n):
for j in range(i + 1, n):
sum... | the_stack_v2_python_sparse | 0018_4Sum/solution.py | benjaminhuanghuang/ben-leetcode | train | 1 | |
16ea02ac4ee8fda5c74b55f88832b245c62bf67b | [
"super(Transformer, self).__init__()\nself.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)\nself.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)\nself.linear = tf.keras.layers.Dense(target_vocab)",
"encoder_output = self.encoder(inputs, training, encoder_mas... | <|body_start_0|>
super(Transformer, self).__init__()
self.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)
self.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)
self.linear = tf.keras.layers.Dense(target_vocab)
<|end_body_0|>
<|body_... | class that instantiates a Transformer | Transformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformer:
"""class that instantiates a Transformer"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""constructor"""
<|body_0|>
def call(self, inputs, target, training, encoder_mask, look_ahead_mask, de... | stack_v2_sparse_classes_36k_train_008718 | 1,537 | no_license | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1)"
},
{
"docstring": "function that builds a Transformer",
"name": "call",
"signature": "def call(self, inputs, targ... | 2 | stack_v2_sparse_classes_30k_train_002178 | Implement the Python class `Transformer` described below.
Class description:
class that instantiates a Transformer
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): constructor
- def call(self, inputs, target, training, e... | Implement the Python class `Transformer` described below.
Class description:
class that instantiates a Transformer
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): constructor
- def call(self, inputs, target, training, e... | 7d3b348aec3b20da25b162b71f150c87c7c28d71 | <|skeleton|>
class Transformer:
"""class that instantiates a Transformer"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""constructor"""
<|body_0|>
def call(self, inputs, target, training, encoder_mask, look_ahead_mask, de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Transformer:
"""class that instantiates a Transformer"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""constructor"""
super(Transformer, self).__init__()
self.encoder = Encoder(N, dm, h, hidden, input_vocab, max_s... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/11-transformer.py | dacastanogo/holbertonschool-machine_learning | train | 0 |
ff79daf1a4ef52b2731218f8f93fbd105208a5a0 | [
"self.data_dir = data_dir\nself.dims = dims\nself.channels = channels",
"keys_to_features = {'volume': tf.FixedLenFeature(self.dims + [1], tf.float32), 'label': tf.FixedLenFeature(self.dims + [self.channels], tf.float32)}\nparsed = tf.parse_single_example(value, keys_to_features)\nprint(parsed['volume'].shape)\np... | <|body_start_0|>
self.data_dir = data_dir
self.dims = dims
self.channels = channels
<|end_body_0|>
<|body_start_1|>
keys_to_features = {'volume': tf.FixedLenFeature(self.dims + [1], tf.float32), 'label': tf.FixedLenFeature(self.dims + [self.channels], tf.float32)}
parsed = tf.pa... | Reader reads from a tfrecord file to produce an image. | Reader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reader:
"""Reader reads from a tfrecord file to produce an image."""
def __init__(self, data_dir, dims, channels):
"""initialize the reader with a tfrecord dir and dims."""
<|body_0|>
def dataset_parser(self, value):
"""parse the tfrecords."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_008719 | 2,755 | no_license | [
{
"docstring": "initialize the reader with a tfrecord dir and dims.",
"name": "__init__",
"signature": "def __init__(self, data_dir, dims, channels)"
},
{
"docstring": "parse the tfrecords.",
"name": "dataset_parser",
"signature": "def dataset_parser(self, value)"
},
{
"docstring... | 4 | stack_v2_sparse_classes_30k_train_005214 | Implement the Python class `Reader` described below.
Class description:
Reader reads from a tfrecord file to produce an image.
Method signatures and docstrings:
- def __init__(self, data_dir, dims, channels): initialize the reader with a tfrecord dir and dims.
- def dataset_parser(self, value): parse the tfrecords.
-... | Implement the Python class `Reader` described below.
Class description:
Reader reads from a tfrecord file to produce an image.
Method signatures and docstrings:
- def __init__(self, data_dir, dims, channels): initialize the reader with a tfrecord dir and dims.
- def dataset_parser(self, value): parse the tfrecords.
-... | a7273c01d02528f5c547992fda482bbfb690fa6c | <|skeleton|>
class Reader:
"""Reader reads from a tfrecord file to produce an image."""
def __init__(self, data_dir, dims, channels):
"""initialize the reader with a tfrecord dir and dims."""
<|body_0|>
def dataset_parser(self, value):
"""parse the tfrecords."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Reader:
"""Reader reads from a tfrecord file to produce an image."""
def __init__(self, data_dir, dims, channels):
"""initialize the reader with a tfrecord dir and dims."""
self.data_dir = data_dir
self.dims = dims
self.channels = channels
def dataset_parser(self, val... | the_stack_v2_python_sparse | records.py | drewlinsley/tpu_connectomics | train | 0 |
b6e96817fcf960555a54c57f718a954f2aa1ee44 | [
"self.pre_sum = w\nself.len = len(w)\nfor i in range(1, self.len):\n self.pre_sum[i] += self.pre_sum[i - 1]",
"w_sum = self.pre_sum[-1]\nl = 0\nr = self.len - 1\nnum = random.randint(1, w_sum)\nwhile l < r:\n mid = l + (r - l) // 2\n if self.pre_sum[mid] < num:\n l = mid + 1\n elif self.pre_sum... | <|body_start_0|>
self.pre_sum = w
self.len = len(w)
for i in range(1, self.len):
self.pre_sum[i] += self.pre_sum[i - 1]
<|end_body_0|>
<|body_start_1|>
w_sum = self.pre_sum[-1]
l = 0
r = self.len - 1
num = random.randint(1, w_sum)
while l < r:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.pre_sum = w
self.len = len(w)
for i in range(1, self.len):
self... | stack_v2_sparse_classes_36k_train_008720 | 1,325 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | 238995bd23c8a6c40c6035890e94baa2473d4bbc | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.pre_sum = w
self.len = len(w)
for i in range(1, self.len):
self.pre_sum[i] += self.pre_sum[i - 1]
def pickIndex(self):
""":rtype: int"""
w_sum = self.pre_sum[-1]
l = 0
... | the_stack_v2_python_sparse | problems/N528_Random_Pick_With_Weight.py | wan-catherine/Leetcode | train | 5 | |
5f91f428235bb57d6fb884366cacf1365c6a02ca | [
"self.dst_site_name = dst_site_name\nself.dst_site_uuid = dst_site_uuid\nself.dst_site_web_url = dst_site_web_url\nself.parent_source_sharepoint_domain_name = parent_source_sharepoint_domain_name\nself.restore_template = restore_template\nself.restore_to_original = restore_to_original\nself.site_owner_vec = site_ow... | <|body_start_0|>
self.dst_site_name = dst_site_name
self.dst_site_uuid = dst_site_uuid
self.dst_site_web_url = dst_site_web_url
self.parent_source_sharepoint_domain_name = parent_source_sharepoint_domain_name
self.restore_template = restore_template
self.restore_to_origin... | Implementation of the 'RestoreSiteParams' model. TODO: type description here. Attributes: dst_site_name (string): Entity name of target site in case of sharepoint restore. dst_site_uuid (string): Entity uuid of target site in case of sharepoint restore. dst_site_web_url (string): Entity web url of target site in case o... | RestoreSiteParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreSiteParams:
"""Implementation of the 'RestoreSiteParams' model. TODO: type description here. Attributes: dst_site_name (string): Entity name of target site in case of sharepoint restore. dst_site_uuid (string): Entity uuid of target site in case of sharepoint restore. dst_site_web_url (str... | stack_v2_sparse_classes_36k_train_008721 | 9,050 | permissive | [
{
"docstring": "Constructor for the RestoreSiteParams class",
"name": "__init__",
"signature": "def __init__(self, dst_site_name=None, dst_site_uuid=None, dst_site_web_url=None, parent_source_sharepoint_domain_name=None, restore_template=None, restore_to_original=None, site_owner_vec=None, site_result=N... | 2 | stack_v2_sparse_classes_30k_train_013926 | Implement the Python class `RestoreSiteParams` described below.
Class description:
Implementation of the 'RestoreSiteParams' model. TODO: type description here. Attributes: dst_site_name (string): Entity name of target site in case of sharepoint restore. dst_site_uuid (string): Entity uuid of target site in case of sh... | Implement the Python class `RestoreSiteParams` described below.
Class description:
Implementation of the 'RestoreSiteParams' model. TODO: type description here. Attributes: dst_site_name (string): Entity name of target site in case of sharepoint restore. dst_site_uuid (string): Entity uuid of target site in case of sh... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreSiteParams:
"""Implementation of the 'RestoreSiteParams' model. TODO: type description here. Attributes: dst_site_name (string): Entity name of target site in case of sharepoint restore. dst_site_uuid (string): Entity uuid of target site in case of sharepoint restore. dst_site_web_url (str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreSiteParams:
"""Implementation of the 'RestoreSiteParams' model. TODO: type description here. Attributes: dst_site_name (string): Entity name of target site in case of sharepoint restore. dst_site_uuid (string): Entity uuid of target site in case of sharepoint restore. dst_site_web_url (string): Entity ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_site_params.py | cohesity/management-sdk-python | train | 24 |
9c7f8fd6d4c422e379bf79c3263c14975a9ceaa3 | [
"self.name = pname\nself.max_items = pmax\nself.items = plist",
"if len(self.items) == 0:\n print('The player has no items')\nelse:\n print(self.items)",
"if self.max_items <= len(self.items):\n print('The player item list has been exceeded the maximum number of \\n items the player can carry')\nelse:\... | <|body_start_0|>
self.name = pname
self.max_items = pmax
self.items = plist
<|end_body_0|>
<|body_start_1|>
if len(self.items) == 0:
print('The player has no items')
else:
print(self.items)
<|end_body_1|>
<|body_start_2|>
if self.max_items <= len... | represents a player carrying a list of items attributes: name(str), max_items(int), items(list) | Player | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Player:
"""represents a player carrying a list of items attributes: name(str), max_items(int), items(list)"""
def __init__(self, pname, pmax, plist):
"""initializes Player with name, max items carry avaliable, list of items Player , str, int, list -> None"""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_008722 | 1,787 | no_license | [
{
"docstring": "initializes Player with name, max items carry avaliable, list of items Player , str, int, list -> None",
"name": "__init__",
"signature": "def __init__(self, pname, pmax, plist)"
},
{
"docstring": "displays the players inventory items Player -> None",
"name": "inventory",
... | 4 | stack_v2_sparse_classes_30k_train_018362 | Implement the Python class `Player` described below.
Class description:
represents a player carrying a list of items attributes: name(str), max_items(int), items(list)
Method signatures and docstrings:
- def __init__(self, pname, pmax, plist): initializes Player with name, max items carry avaliable, list of items Pla... | Implement the Python class `Player` described below.
Class description:
represents a player carrying a list of items attributes: name(str), max_items(int), items(list)
Method signatures and docstrings:
- def __init__(self, pname, pmax, plist): initializes Player with name, max items carry avaliable, list of items Pla... | c9a7604147d9efee5bc2386cc9ae8d5240eaf450 | <|skeleton|>
class Player:
"""represents a player carrying a list of items attributes: name(str), max_items(int), items(list)"""
def __init__(self, pname, pmax, plist):
"""initializes Player with name, max items carry avaliable, list of items Player , str, int, list -> None"""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Player:
"""represents a player carrying a list of items attributes: name(str), max_items(int), items(list)"""
def __init__(self, pname, pmax, plist):
"""initializes Player with name, max items carry avaliable, list of items Player , str, int, list -> None"""
self.name = pname
self... | the_stack_v2_python_sparse | Intro-to-Programming/pa11/pa11-b.py | jaeyoung-jane-choi/2019_Indiana_University | train | 1 |
642960814c0821d0d06322e9da12496af63bcd35 | [
"self.tenant_id = tenant_id\nself.client_key = client_key\nself.secret_key = secret_key\nself.publisher_id = publisher_id\nself._headers = None",
"if not self._headers:\n self._headers = self.login()\nreturn self._headers",
"headers = {'Content-Type': 'application/x-www-form-urlencoded'}\nauth_url = 'https:/... | <|body_start_0|>
self.tenant_id = tenant_id
self.client_key = client_key
self.secret_key = secret_key
self.publisher_id = publisher_id
self._headers = None
<|end_body_0|>
<|body_start_1|>
if not self._headers:
self._headers = self.login()
return self.... | ApiConnection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApiConnection:
def __init__(self, tenant_id=None, client_key=None, secret_key=None, publisher_id=None, **kwargs):
"""Object that creates the authorization headers for- and sends API requests to the Microsoft Office APIs'. Taken from a Microsoft sample script that I cannot find the origin... | stack_v2_sparse_classes_36k_train_008723 | 3,347 | permissive | [
{
"docstring": "Object that creates the authorization headers for- and sends API requests to the Microsoft Office APIs'. Taken from a Microsoft sample script that I cannot find the original of to reference. :param tenant_id: tenant ID of of Office/Azure subscription :param client_key: key (ID) of the applicatio... | 4 | stack_v2_sparse_classes_30k_train_014357 | Implement the Python class `ApiConnection` described below.
Class description:
Implement the ApiConnection class.
Method signatures and docstrings:
- def __init__(self, tenant_id=None, client_key=None, secret_key=None, publisher_id=None, **kwargs): Object that creates the authorization headers for- and sends API requ... | Implement the Python class `ApiConnection` described below.
Class description:
Implement the ApiConnection class.
Method signatures and docstrings:
- def __init__(self, tenant_id=None, client_key=None, secret_key=None, publisher_id=None, **kwargs): Object that creates the authorization headers for- and sends API requ... | 958a5b44704ef47a979ac7110b54a092ff8ec120 | <|skeleton|>
class ApiConnection:
def __init__(self, tenant_id=None, client_key=None, secret_key=None, publisher_id=None, **kwargs):
"""Object that creates the authorization headers for- and sends API requests to the Microsoft Office APIs'. Taken from a Microsoft sample script that I cannot find the origin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApiConnection:
def __init__(self, tenant_id=None, client_key=None, secret_key=None, publisher_id=None, **kwargs):
"""Object that creates the authorization headers for- and sends API requests to the Microsoft Office APIs'. Taken from a Microsoft sample script that I cannot find the original of to refer... | the_stack_v2_python_sparse | Source/ApiConnection.py | ddbnl/office365-audit-log-collector | train | 81 | |
823a0af036affbb935f7b75a2dcbe76d2cf04691 | [
"if isinstance(self._c, np.ndarray):\n return self._c\nelse:\n return self._c * np.ones((self.nz, self.nx), dtype=np.float64)",
"vals = []\nif self.disperseFreqs:\n for i in range(len(self.freqs)):\n freq = self.freqs[i]\n fact = 1.0 + np.log(freq / self.freqBase) / (np.pi * self.Q)\n ... | <|body_start_0|>
if isinstance(self._c, np.ndarray):
return self._c
else:
return self._c * np.ones((self.nz, self.nx), dtype=np.float64)
<|end_body_0|>
<|body_start_1|>
vals = []
if self.disperseFreqs:
for i in range(len(self.freqs)):
... | Wrapper to carry out forward-modelling using the stored discretization over a series of frequencies. Preserves causality by modelling velocity dispersion in the presence of a non-infinite Q model. | ViscoMultiGridMultiFreq | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViscoMultiGridMultiFreq:
"""Wrapper to carry out forward-modelling using the stored discretization over a series of frequencies. Preserves causality by modelling velocity dispersion in the presence of a non-infinite Q model."""
def c(self):
"""Complex wave velocity"""
<|body_... | stack_v2_sparse_classes_36k_train_008724 | 16,781 | permissive | [
{
"docstring": "Complex wave velocity",
"name": "c",
"signature": "def c(self)"
},
{
"docstring": "Updates for frequency subProblems",
"name": "spUpdates",
"signature": "def spUpdates(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000012 | Implement the Python class `ViscoMultiGridMultiFreq` described below.
Class description:
Wrapper to carry out forward-modelling using the stored discretization over a series of frequencies. Preserves causality by modelling velocity dispersion in the presence of a non-infinite Q model.
Method signatures and docstrings... | Implement the Python class `ViscoMultiGridMultiFreq` described below.
Class description:
Wrapper to carry out forward-modelling using the stored discretization over a series of frequencies. Preserves causality by modelling velocity dispersion in the presence of a non-infinite Q model.
Method signatures and docstrings... | e4228be3947021f2b983c919c51bb1f67df90eb0 | <|skeleton|>
class ViscoMultiGridMultiFreq:
"""Wrapper to carry out forward-modelling using the stored discretization over a series of frequencies. Preserves causality by modelling velocity dispersion in the presence of a non-infinite Q model."""
def c(self):
"""Complex wave velocity"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViscoMultiGridMultiFreq:
"""Wrapper to carry out forward-modelling using the stored discretization over a series of frequencies. Preserves causality by modelling velocity dispersion in the presence of a non-infinite Q model."""
def c(self):
"""Complex wave velocity"""
if isinstance(self._... | the_stack_v2_python_sparse | zephyr/backend/distributors.py | uwoseis/zephyr | train | 18 |
aaa99592abccd1d8b637c008abd56385a3fa5bb8 | [
"self.V = vertices\nself.graph = [[0 for column in range(vertices)] for row in range(vertices)]\nself.graph_dict = graph_dict",
"print('(Edge) - Weight')\nweight = 0\nfor i in range(1, self.V):\n print('(' + str(self.graph_dict[p[i]]) + ',', str(self.graph_dict[i]) + ')', '-', self.graph[i][p[i]][1])\n weig... | <|body_start_0|>
self.V = vertices
self.graph = [[0 for column in range(vertices)] for row in range(vertices)]
self.graph_dict = graph_dict
<|end_body_0|>
<|body_start_1|>
print('(Edge) - Weight')
weight = 0
for i in range(1, self.V):
print('(' + str(self.gra... | Class to contain the algorithms for MST-Prim and graph data. Graph data should be stored a an adjacency list with the matching nodes containing the weight of the edge. | Graph | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Graph:
"""Class to contain the algorithms for MST-Prim and graph data. Graph data should be stored a an adjacency list with the matching nodes containing the weight of the edge."""
def __init__(self, vertices, graph_dict):
"""Initializes a new instance of the Graph class ---------- P... | stack_v2_sparse_classes_36k_train_008725 | 9,187 | no_license | [
{
"docstring": "Initializes a new instance of the Graph class ---------- Parameters graph_dict : {} The graph dictionary containing the node labels.",
"name": "__init__",
"signature": "def __init__(self, vertices, graph_dict)"
},
{
"docstring": "Prints out the MST tree and the total weight of th... | 4 | stack_v2_sparse_classes_30k_test_000199 | Implement the Python class `Graph` described below.
Class description:
Class to contain the algorithms for MST-Prim and graph data. Graph data should be stored a an adjacency list with the matching nodes containing the weight of the edge.
Method signatures and docstrings:
- def __init__(self, vertices, graph_dict): I... | Implement the Python class `Graph` described below.
Class description:
Class to contain the algorithms for MST-Prim and graph data. Graph data should be stored a an adjacency list with the matching nodes containing the weight of the edge.
Method signatures and docstrings:
- def __init__(self, vertices, graph_dict): I... | a699bfe92d5c074d26dde540d86dc663ddddccea | <|skeleton|>
class Graph:
"""Class to contain the algorithms for MST-Prim and graph data. Graph data should be stored a an adjacency list with the matching nodes containing the weight of the edge."""
def __init__(self, vertices, graph_dict):
"""Initializes a new instance of the Graph class ---------- P... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Graph:
"""Class to contain the algorithms for MST-Prim and graph data. Graph data should be stored a an adjacency list with the matching nodes containing the weight of the edge."""
def __init__(self, vertices, graph_dict):
"""Initializes a new instance of the Graph class ---------- Parameters gra... | the_stack_v2_python_sparse | Exam/Final/whitesidesMatthew_Zip/5/5a.py | mattwhitesides/CS5200 | train | 0 |
7b9d5bfbf68daa7fd521258e9be4a069bc64fc28 | [
"node = Node(item)\nif self.is_empty():\n self.head = node\nelse:\n cur = self.head\n while cur.next != None:\n cur = cur.next\n cur.next = node",
"node = Node(item)\nnode.next = self.head\nself.head = node",
"if pos < 0:\n self.add(item)\nelif pos > self.lenth() - 1:\n self.append(item... | <|body_start_0|>
node = Node(item)
if self.is_empty():
self.head = node
else:
cur = self.head
while cur.next != None:
cur = cur.next
cur.next = node
<|end_body_0|>
<|body_start_1|>
node = Node(item)
node.next = self... | 单向链表 | Singelink | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Singelink:
"""单向链表"""
def append(self, item):
"""尾部添加元素"""
<|body_0|>
def add(self, item):
"""链表头部添加 要做的就是将新加的node的next指向原来的下一个node，而head指向新加的node"""
<|body_1|>
def insert(self, pos, item):
"""在链表的指定位置添加，这里以0为开始"""
<|body_2|>
def... | stack_v2_sparse_classes_36k_train_008726 | 2,554 | permissive | [
{
"docstring": "尾部添加元素",
"name": "append",
"signature": "def append(self, item)"
},
{
"docstring": "链表头部添加 要做的就是将新加的node的next指向原来的下一个node，而head指向新加的node",
"name": "add",
"signature": "def add(self, item)"
},
{
"docstring": "在链表的指定位置添加，这里以0为开始",
"name": "insert",
"signatur... | 4 | null | Implement the Python class `Singelink` described below.
Class description:
单向链表
Method signatures and docstrings:
- def append(self, item): 尾部添加元素
- def add(self, item): 链表头部添加 要做的就是将新加的node的next指向原来的下一个node，而head指向新加的node
- def insert(self, pos, item): 在链表的指定位置添加，这里以0为开始
- def remove(self, item): 从链表中删除元素 | Implement the Python class `Singelink` described below.
Class description:
单向链表
Method signatures and docstrings:
- def append(self, item): 尾部添加元素
- def add(self, item): 链表头部添加 要做的就是将新加的node的next指向原来的下一个node，而head指向新加的node
- def insert(self, pos, item): 在链表的指定位置添加，这里以0为开始
- def remove(self, item): 从链表中删除元素
<|skeleto... | 912dc05a3bd0ded9544166a68da23ca0a97b84da | <|skeleton|>
class Singelink:
"""单向链表"""
def append(self, item):
"""尾部添加元素"""
<|body_0|>
def add(self, item):
"""链表头部添加 要做的就是将新加的node的next指向原来的下一个node，而head指向新加的node"""
<|body_1|>
def insert(self, pos, item):
"""在链表的指定位置添加，这里以0为开始"""
<|body_2|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Singelink:
"""单向链表"""
def append(self, item):
"""尾部添加元素"""
node = Node(item)
if self.is_empty():
self.head = node
else:
cur = self.head
while cur.next != None:
cur = cur.next
cur.next = node
def add(self,... | the_stack_v2_python_sparse | jiaocheng/08-数据结构与算法/07-单向链表.py | kellanfan/python | train | 3 |
26c7bdbdae1cf623979a4049f8329cc1a39c7c2a | [
"super(ProductAttention, self).__init__()\nself.decoder_att = nn.Linear(decoder_dim, encoder_dim)\nself.dk = encoder_dim\nself.softmax = nn.Softmax(dim=1)",
"query = self.decoder_att(decoder_hidden).unsqueeze(1)\nscores = torch.matmul(query, encoder_out.transpose(-2, -1)) / math.sqrt(self.dk)\nscores = scores.squ... | <|body_start_0|>
super(ProductAttention, self).__init__()
self.decoder_att = nn.Linear(decoder_dim, encoder_dim)
self.dk = encoder_dim
self.softmax = nn.Softmax(dim=1)
<|end_body_0|>
<|body_start_1|>
query = self.decoder_att(decoder_hidden).unsqueeze(1)
scores = torch.ma... | Attention Network. | ProductAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductAttention:
"""Attention Network."""
def __init__(self, encoder_dim, decoder_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
<|body_0|>
def forward(self, en... | stack_v2_sparse_classes_36k_train_008727 | 4,708 | no_license | [
{
"docstring": ":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network",
"name": "__init__",
"signature": "def __init__(self, encoder_dim, decoder_dim)"
},
{
"docstring": "Forward propagation. :param encode... | 2 | stack_v2_sparse_classes_30k_train_004094 | Implement the Python class `ProductAttention` described below.
Class description:
Attention Network.
Method signatures and docstrings:
- def __init__(self, encoder_dim, decoder_dim): :param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attentio... | Implement the Python class `ProductAttention` described below.
Class description:
Attention Network.
Method signatures and docstrings:
- def __init__(self, encoder_dim, decoder_dim): :param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attentio... | 426d97b5d3688f6c52c51ef6e33872554d55751a | <|skeleton|>
class ProductAttention:
"""Attention Network."""
def __init__(self, encoder_dim, decoder_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
<|body_0|>
def forward(self, en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductAttention:
"""Attention Network."""
def __init__(self, encoder_dim, decoder_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
super(ProductAttention, self).__init__()
... | the_stack_v2_python_sparse | src/models/continuous_encoder_decoder_models/encoder_decoder_variants/attention_product_image.py | RitaRamo/remote-sensing-images-caption | train | 3 |
b00cae28d998f7f7f404078cceeea0fe50e5b5af | [
"where = [['ParentId', '=', parentSfId], 'and', ['Title', '=', title]]\nqueryList = self.query(NOTE_OBJ, where=where, sc='all')\nif queryList in BAD_INFO_LIST:\n note = None\n msg = 'findNote: NO Note found with parent %s and title %s' % (parentSfId, title)\n self.setLog(msg, 'debug')\nelse:\n if len(qu... | <|body_start_0|>
where = [['ParentId', '=', parentSfId], 'and', ['Title', '=', title]]
queryList = self.query(NOTE_OBJ, where=where, sc='all')
if queryList in BAD_INFO_LIST:
note = None
msg = 'findNote: NO Note found with parent %s and title %s' % (parentSfId, title)
... | SFNoteTool | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SFNoteTool:
def findNote(self, parentSfId, title):
"""Try to find a note attached to the entity with parentSfId and having title. Return a note object if found, None if not."""
<|body_0|>
def retrieveNote(self, noteId):
"""Given a noteID, return the note object for t... | stack_v2_sparse_classes_36k_train_008728 | 3,364 | permissive | [
{
"docstring": "Try to find a note attached to the entity with parentSfId and having title. Return a note object if found, None if not.",
"name": "findNote",
"signature": "def findNote(self, parentSfId, title)"
},
{
"docstring": "Given a noteID, return the note object for that note",
"name":... | 3 | null | Implement the Python class `SFNoteTool` described below.
Class description:
Implement the SFNoteTool class.
Method signatures and docstrings:
- def findNote(self, parentSfId, title): Try to find a note attached to the entity with parentSfId and having title. Return a note object if found, None if not.
- def retrieveN... | Implement the Python class `SFNoteTool` described below.
Class description:
Implement the SFNoteTool class.
Method signatures and docstrings:
- def findNote(self, parentSfId, title): Try to find a note attached to the entity with parentSfId and having title. Return a note object if found, None if not.
- def retrieveN... | 8aa2ff2340707eecae6514943e86f5afba9cd54a | <|skeleton|>
class SFNoteTool:
def findNote(self, parentSfId, title):
"""Try to find a note attached to the entity with parentSfId and having title. Return a note object if found, None if not."""
<|body_0|>
def retrieveNote(self, noteId):
"""Given a noteID, return the note object for t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SFNoteTool:
def findNote(self, parentSfId, title):
"""Try to find a note attached to the entity with parentSfId and having title. Return a note object if found, None if not."""
where = [['ParentId', '=', parentSfId], 'and', ['Title', '=', title]]
queryList = self.query(NOTE_OBJ, where=... | the_stack_v2_python_sparse | python-trunk/sfapi2/sflib/sfNote.py | raychorn/svn_molten-magma | train | 0 | |
aeede243f60600e080ec9bee7e0cd54734f9cfb0 | [
"if v is not None:\n if not v.get('eapType'):\n raise ValueError('eapType must be defined')\n try:\n wifi.eap_check_config(v)\n except wifi.ConfigureArgsError as e:\n raise ValueError(str(e))\nreturn v",
"security_type = values.get('securityType')\npsk = values.get('psk')\neapconfig ... | <|body_start_0|>
if v is not None:
if not v.get('eapType'):
raise ValueError('eapType must be defined')
try:
wifi.eap_check_config(v)
except wifi.ConfigureArgsError as e:
raise ValueError(str(e))
return v
<|end_body_0|>
... | WifiConfiguration | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WifiConfiguration:
def eap_config_validate(cls, v):
"""Custom validator for the eapConfig field"""
<|body_0|>
def validate_configuration(cls, values):
"""Validate the configuration"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if v is not None:
... | stack_v2_sparse_classes_36k_train_008729 | 13,352 | permissive | [
{
"docstring": "Custom validator for the eapConfig field",
"name": "eap_config_validate",
"signature": "def eap_config_validate(cls, v)"
},
{
"docstring": "Validate the configuration",
"name": "validate_configuration",
"signature": "def validate_configuration(cls, values)"
}
] | 2 | null | Implement the Python class `WifiConfiguration` described below.
Class description:
Implement the WifiConfiguration class.
Method signatures and docstrings:
- def eap_config_validate(cls, v): Custom validator for the eapConfig field
- def validate_configuration(cls, values): Validate the configuration | Implement the Python class `WifiConfiguration` described below.
Class description:
Implement the WifiConfiguration class.
Method signatures and docstrings:
- def eap_config_validate(cls, v): Custom validator for the eapConfig field
- def validate_configuration(cls, values): Validate the configuration
<|skeleton|>
cl... | 026b523c8c9e5d45910c490efb89194d72595be9 | <|skeleton|>
class WifiConfiguration:
def eap_config_validate(cls, v):
"""Custom validator for the eapConfig field"""
<|body_0|>
def validate_configuration(cls, values):
"""Validate the configuration"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WifiConfiguration:
def eap_config_validate(cls, v):
"""Custom validator for the eapConfig field"""
if v is not None:
if not v.get('eapType'):
raise ValueError('eapType must be defined')
try:
wifi.eap_check_config(v)
except wif... | the_stack_v2_python_sparse | robot-server/robot_server/service/legacy/models/networking.py | Opentrons/opentrons | train | 326 | |
b3251c49875ba86b2fead916634215a682a73710 | [
"self.miningStatus = miningStatus\nself.lock = lock\nself.canStartMiningCondition = canStartMiningCondition\nThread.__init__(self)",
"while True:\n with self.lock:\n self.removeTransactionsAlreadyMinedIfAny()\n while not self.miningStatus.canStartMining:\n self.canStartMiningCondition.... | <|body_start_0|>
self.miningStatus = miningStatus
self.lock = lock
self.canStartMiningCondition = canStartMiningCondition
Thread.__init__(self)
<|end_body_0|>
<|body_start_1|>
while True:
with self.lock:
self.removeTransactionsAlreadyMinedIfAny()
... | Class that handle mining algorithm. The main lifecycle is: Receiving mining requests and if there are any transaction in common (transactions already mined by me or others) it make symmetric difference between mined transactions and received transactions Wait start mining Calculate proof of lottery, verify it and send ... | MinerAlgorithm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinerAlgorithm:
"""Class that handle mining algorithm. The main lifecycle is: Receiving mining requests and if there are any transaction in common (transactions already mined by me or others) it make symmetric difference between mined transactions and received transactions Wait start mining Calcu... | stack_v2_sparse_classes_36k_train_008730 | 8,020 | no_license | [
{
"docstring": "Constructor with parameters :param miningStatus: Shared current status of mining :param lock: Re entrant lock used to handle shared data :param canStartMiningCondition: Condition that told us to mining or sleep",
"name": "__init__",
"signature": "def __init__(self, miningStatus, lock, ca... | 3 | stack_v2_sparse_classes_30k_train_007394 | Implement the Python class `MinerAlgorithm` described below.
Class description:
Class that handle mining algorithm. The main lifecycle is: Receiving mining requests and if there are any transaction in common (transactions already mined by me or others) it make symmetric difference between mined transactions and receiv... | Implement the Python class `MinerAlgorithm` described below.
Class description:
Class that handle mining algorithm. The main lifecycle is: Receiving mining requests and if there are any transaction in common (transactions already mined by me or others) it make symmetric difference between mined transactions and receiv... | f5df62e34265ce5185031ebc7c694b759c2a73a2 | <|skeleton|>
class MinerAlgorithm:
"""Class that handle mining algorithm. The main lifecycle is: Receiving mining requests and if there are any transaction in common (transactions already mined by me or others) it make symmetric difference between mined transactions and received transactions Wait start mining Calcu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MinerAlgorithm:
"""Class that handle mining algorithm. The main lifecycle is: Receiving mining requests and if there are any transaction in common (transactions already mined by me or others) it make symmetric difference between mined transactions and received transactions Wait start mining Calculate proof of... | the_stack_v2_python_sparse | blockchain/mining/MinerAlgorithm.py | packo97/Blockchain_Project | train | 1 |
9ba46b93a94feb252896217120877ff6eb7a2bd1 | [
"queryset = BookInfo.objects.all()\nbook_list = []\nfor book in queryset:\n book_list.append({'id': book.id, 'title': book.title, 'pub_date': book.pub_date, 'read': book.read, 'comment': book.comment, 'image': book.image.url if book.image else ''})\nreturn JsonResponse(book_list, safe=False)",
"json_bytes = re... | <|body_start_0|>
queryset = BookInfo.objects.all()
book_list = []
for book in queryset:
book_list.append({'id': book.id, 'title': book.title, 'pub_date': book.pub_date, 'read': book.read, 'comment': book.comment, 'image': book.image.url if book.image else ''})
return JsonResp... | 查询所有图书、增加图书 | BooksAPIVIew | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BooksAPIVIew:
"""查询所有图书、增加图书"""
def get(self, request):
"""查询所有图书 路由：GET /books/"""
<|body_0|>
def post(self, request):
"""新增图书 路由：POST /books/"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
queryset = BookInfo.objects.all()
book_list =... | stack_v2_sparse_classes_36k_train_008731 | 5,895 | no_license | [
{
"docstring": "查询所有图书 路由：GET /books/",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "新增图书 路由：POST /books/",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014390 | Implement the Python class `BooksAPIVIew` described below.
Class description:
查询所有图书、增加图书
Method signatures and docstrings:
- def get(self, request): 查询所有图书 路由：GET /books/
- def post(self, request): 新增图书 路由：POST /books/ | Implement the Python class `BooksAPIVIew` described below.
Class description:
查询所有图书、增加图书
Method signatures and docstrings:
- def get(self, request): 查询所有图书 路由：GET /books/
- def post(self, request): 新增图书 路由：POST /books/
<|skeleton|>
class BooksAPIVIew:
"""查询所有图书、增加图书"""
def get(self, request):
"""查询... | 0f123a99856238af5f1aab0b555f6501e635fc52 | <|skeleton|>
class BooksAPIVIew:
"""查询所有图书、增加图书"""
def get(self, request):
"""查询所有图书 路由：GET /books/"""
<|body_0|>
def post(self, request):
"""新增图书 路由：POST /books/"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BooksAPIVIew:
"""查询所有图书、增加图书"""
def get(self, request):
"""查询所有图书 路由：GET /books/"""
queryset = BookInfo.objects.all()
book_list = []
for book in queryset:
book_list.append({'id': book.id, 'title': book.title, 'pub_date': book.pub_date, 'read': book.read, 'comme... | the_stack_v2_python_sparse | DRF_Tutorial/app/views.py | YDongY/PythonCode | train | 1 |
9c0565a7a799b4d983060bea22a4462692fd3731 | [
"if key:\n if cls.objects.filter(key=key).exists():\n return cls.objects.filter(key=key).first()\nif cls.objects.filter(key=None).exists():\n return cls.objects.filter(key=None).first()\nreturn None",
"if self.is_default_value:\n if self.key is None and self.__class__.objects.exclude(pk=self.pk).f... | <|body_start_0|>
if key:
if cls.objects.filter(key=key).exists():
return cls.objects.filter(key=key).first()
if cls.objects.filter(key=None).exists():
return cls.objects.filter(key=None).first()
return None
<|end_body_0|>
<|body_start_1|>
if self.... | Mixin for storing value with a unique default value for all and a unique default value for each item associated by key | StoreDataWithDefaultValueByKey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StoreDataWithDefaultValueByKey:
"""Mixin for storing value with a unique default value for all and a unique default value for each item associated by key"""
def default_value(cls, key=None):
"""Return default value which is: - default value for the key if exists - else generic defaul... | stack_v2_sparse_classes_36k_train_008732 | 2,174 | no_license | [
{
"docstring": "Return default value which is: - default value for the key if exists - else generic default value if exists - else None",
"name": "default_value",
"signature": "def default_value(cls, key=None)"
},
{
"docstring": "verify that: - an unique value exists without a key - an unique va... | 2 | stack_v2_sparse_classes_30k_train_010591 | Implement the Python class `StoreDataWithDefaultValueByKey` described below.
Class description:
Mixin for storing value with a unique default value for all and a unique default value for each item associated by key
Method signatures and docstrings:
- def default_value(cls, key=None): Return default value which is: - ... | Implement the Python class `StoreDataWithDefaultValueByKey` described below.
Class description:
Mixin for storing value with a unique default value for all and a unique default value for each item associated by key
Method signatures and docstrings:
- def default_value(cls, key=None): Return default value which is: - ... | 95d21cd6036a99c5f399b700a5426e9e2e17e878 | <|skeleton|>
class StoreDataWithDefaultValueByKey:
"""Mixin for storing value with a unique default value for all and a unique default value for each item associated by key"""
def default_value(cls, key=None):
"""Return default value which is: - default value for the key if exists - else generic defaul... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StoreDataWithDefaultValueByKey:
"""Mixin for storing value with a unique default value for all and a unique default value for each item associated by key"""
def default_value(cls, key=None):
"""Return default value which is: - default value for the key if exists - else generic default value if ex... | the_stack_v2_python_sparse | helpers/mixins/store_data_with_default_value_by_key.py | alexandrenorman/mixeur | train | 0 |
fd1b89d8497e9e94f091b471a451d199d73f0715 | [
"super(Game, self).__init__(screen, bg_color)\nself.status_font = pygame.font.SysFont('monospace', 20)\nself.status_font.set_bold(True)\nself.game_data = game_data",
"self.screen.fill((0, 0, 0))\nself.game_data.clear()\nif result_id != -1:\n if result_id < 5:\n result = self.status_font.render('Player %... | <|body_start_0|>
super(Game, self).__init__(screen, bg_color)
self.status_font = pygame.font.SysFont('monospace', 20)
self.status_font.set_bold(True)
self.game_data = game_data
<|end_body_0|>
<|body_start_1|>
self.screen.fill((0, 0, 0))
self.game_data.clear()
if ... | Game screeen state | Game | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game:
"""Game screeen state"""
def __init__(self, screen, game_data, bg_color=(0, 0, 0)):
"""Generates initial screen :param screen: PyGame screen :param game_data: data of game session :param bg_color: background color :return:"""
<|body_0|>
def stop_game(self, result_i... | stack_v2_sparse_classes_36k_train_008733 | 5,538 | no_license | [
{
"docstring": "Generates initial screen :param screen: PyGame screen :param game_data: data of game session :param bg_color: background color :return:",
"name": "__init__",
"signature": "def __init__(self, screen, game_data, bg_color=(0, 0, 0))"
},
{
"docstring": "Stops state and returns to pre... | 6 | stack_v2_sparse_classes_30k_train_000146 | Implement the Python class `Game` described below.
Class description:
Game screeen state
Method signatures and docstrings:
- def __init__(self, screen, game_data, bg_color=(0, 0, 0)): Generates initial screen :param screen: PyGame screen :param game_data: data of game session :param bg_color: background color :return... | Implement the Python class `Game` described below.
Class description:
Game screeen state
Method signatures and docstrings:
- def __init__(self, screen, game_data, bg_color=(0, 0, 0)): Generates initial screen :param screen: PyGame screen :param game_data: data of game session :param bg_color: background color :return... | 51a2f2ecc09a05672a2c3deb00ab8c273d3b756b | <|skeleton|>
class Game:
"""Game screeen state"""
def __init__(self, screen, game_data, bg_color=(0, 0, 0)):
"""Generates initial screen :param screen: PyGame screen :param game_data: data of game session :param bg_color: background color :return:"""
<|body_0|>
def stop_game(self, result_i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Game:
"""Game screeen state"""
def __init__(self, screen, game_data, bg_color=(0, 0, 0)):
"""Generates initial screen :param screen: PyGame screen :param game_data: data of game session :param bg_color: background color :return:"""
super(Game, self).__init__(screen, bg_color)
self... | the_stack_v2_python_sparse | application/game_state.py | asmodeii/tanki | train | 0 |
1dbb773362acfd3160a1d8b170da3cefccf81b82 | [
"self._renderer = renderer\nself._width = self._renderer.width\nself._height = self._renderer.height\nself._small = int(self._height / 20)\nself._extra_small = int(self._height / 30)\nself._lines = []",
"if audio_info[0]:\n self._lines.append(['MUSIC ON', self._small, self._width / 2, self._height / 2 - self._... | <|body_start_0|>
self._renderer = renderer
self._width = self._renderer.width
self._height = self._renderer.height
self._small = int(self._height / 20)
self._extra_small = int(self._height / 30)
self._lines = []
<|end_body_0|>
<|body_start_1|>
if audio_info[0]:
... | A class to represent setup view of UI. Attributes: renderer: Renderer object. | SetupView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SetupView:
"""A class to represent setup view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_008734 | 2,268 | no_license | [
{
"docstring": "Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display.",
"name": "__init__",
"signature": "def __init__(self, renderer)"
},
{
"docstring": "Prepares all information to show for the renderer object. Check musi... | 2 | stack_v2_sparse_classes_30k_train_011047 | Implement the Python class `SetupView` described below.
Class description:
A class to represent setup view of UI. Attributes: renderer: Renderer object.
Method signatures and docstrings:
- def __init__(self, renderer): Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object... | Implement the Python class `SetupView` described below.
Class description:
A class to represent setup view of UI. Attributes: renderer: Renderer object.
Method signatures and docstrings:
- def __init__(self, renderer): Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object... | 29cd15dddff620de068a479595a5cb9aba855343 | <|skeleton|>
class SetupView:
"""A class to represent setup view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SetupView:
"""A class to represent setup view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
self._renderer = renderer
... | the_stack_v2_python_sparse | src/ui/setup_view.py | TopiasHarjunpaa/ot-harjoitustyo | train | 0 |
dc12a647ff51f627a7e8ab55c733c3935da11dc8 | [
"grey_scale_image = cv.cvtColor(img, cv.COLOR_BGR2GRAY)\namount_of_x_samples = 18\ndots_amount = 12\nx_index = 0\nx_step = (grey_scale_image.shape[1] - 1) / amount_of_x_samples\ny_index = grey_scale_image.shape[0] - 1\ny_step = y_index / dots_amount\nall_lines = []\nwhile x_index < grey_scale_image.shape[1] - 1:\n ... | <|body_start_0|>
grey_scale_image = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
amount_of_x_samples = 18
dots_amount = 12
x_index = 0
x_step = (grey_scale_image.shape[1] - 1) / amount_of_x_samples
y_index = grey_scale_image.shape[0] - 1
y_step = y_index / dots_amount
... | Class which extracts the line coordinates from an image. Given an image, grey, and white pixels are recognized and clustered together into separate points at certain steps, indicating the line's position. The image is first greyscaled and appropriate indices and steps are determined. | Sampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sampler:
"""Class which extracts the line coordinates from an image. Given an image, grey, and white pixels are recognized and clustered together into separate points at certain steps, indicating the line's position. The image is first greyscaled and appropriate indices and steps are determined."... | stack_v2_sparse_classes_36k_train_008735 | 5,195 | permissive | [
{
"docstring": "The function find_dots takes an input image, grayscales it, makes sub images of the grayscaled image and runs the functions image_sample, find_line, get_valid_elements and line_merger in this order on all the sub images. Args: img: The output from the neural network Returns: all_lines: A list co... | 5 | null | Implement the Python class `Sampler` described below.
Class description:
Class which extracts the line coordinates from an image. Given an image, grey, and white pixels are recognized and clustered together into separate points at certain steps, indicating the line's position. The image is first greyscaled and appropr... | Implement the Python class `Sampler` described below.
Class description:
Class which extracts the line coordinates from an image. Given an image, grey, and white pixels are recognized and clustered together into separate points at certain steps, indicating the line's position. The image is first greyscaled and appropr... | 2dd5c5e90adf2c29e5c1e81e8639813edbf65903 | <|skeleton|>
class Sampler:
"""Class which extracts the line coordinates from an image. Given an image, grey, and white pixels are recognized and clustered together into separate points at certain steps, indicating the line's position. The image is first greyscaled and appropriate indices and steps are determined."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sampler:
"""Class which extracts the line coordinates from an image. Given an image, grey, and white pixels are recognized and clustered together into separate points at certain steps, indicating the line's position. The image is first greyscaled and appropriate indices and steps are determined."""
def f... | the_stack_v2_python_sparse | ImageProcessing/Sampler.py | florias/TNO-RU-Lane-detection-project | train | 2 |
bd2813189edc886cbc7053321bed37d4dd1f88b0 | [
"if not datastore_id:\n datastores = get_datastore(user=request.user)\n return Response({'datastores': DatastoreOverviewSerializer(datastores, many=True).data}, status=status.HTTP_200_OK)\nelse:\n datastore = get_datastore(datastore_id, request.user)\n if not datastore:\n raise PermissionDenied({... | <|body_start_0|>
if not datastore_id:
datastores = get_datastore(user=request.user)
return Response({'datastores': DatastoreOverviewSerializer(datastores, many=True).data}, status=status.HTTP_200_OK)
else:
datastore = get_datastore(datastore_id, request.user)
... | DatastoreView | [
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"BSD-2-Clause",
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatastoreView:
def get(self, request, datastore_id=None, *args, **kwargs):
"""Lists all datastores of the user or returns a specific datastore with content :param request: :type request: :param datastore_id: PK of the datastore :type datastore_id: uuid :param args: :type args: :param kwa... | stack_v2_sparse_classes_36k_train_008736 | 6,140 | permissive | [
{
"docstring": "Lists all datastores of the user or returns a specific datastore with content :param request: :type request: :param datastore_id: PK of the datastore :type datastore_id: uuid :param args: :type args: :param kwargs: :type kwargs: :return: :rtype:",
"name": "get",
"signature": "def get(sel... | 4 | null | Implement the Python class `DatastoreView` described below.
Class description:
Implement the DatastoreView class.
Method signatures and docstrings:
- def get(self, request, datastore_id=None, *args, **kwargs): Lists all datastores of the user or returns a specific datastore with content :param request: :type request:... | Implement the Python class `DatastoreView` described below.
Class description:
Implement the DatastoreView class.
Method signatures and docstrings:
- def get(self, request, datastore_id=None, *args, **kwargs): Lists all datastores of the user or returns a specific datastore with content :param request: :type request:... | 8936aa8ccdee8b9617ef7d894cb9a9a9f6f473cf | <|skeleton|>
class DatastoreView:
def get(self, request, datastore_id=None, *args, **kwargs):
"""Lists all datastores of the user or returns a specific datastore with content :param request: :type request: :param datastore_id: PK of the datastore :type datastore_id: uuid :param args: :type args: :param kwa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatastoreView:
def get(self, request, datastore_id=None, *args, **kwargs):
"""Lists all datastores of the user or returns a specific datastore with content :param request: :type request: :param datastore_id: PK of the datastore :type datastore_id: uuid :param args: :type args: :param kwargs: :type kwa... | the_stack_v2_python_sparse | psono/restapi/views/datastore.py | psono/psono-server | train | 76 | |
8541e79f37853bfab328138a5dba6cd679f4fc5f | [
"if self.parentNode is None:\n return None\nsiblings = self.parentNode.childNodes\nfor i in range(siblings.index(self), 0, -1):\n n = siblings[i - 1]\n if n.nodeType == Node.ELEMENT_NODE:\n return n\nreturn None",
"if self.parentNode is None:\n return None\nsiblings = self.parentNode.childNodes... | <|body_start_0|>
if self.parentNode is None:
return None
siblings = self.parentNode.childNodes
for i in range(siblings.index(self), 0, -1):
n = siblings[i - 1]
if n.nodeType == Node.ELEMENT_NODE:
return n
return None
<|end_body_0|>
<|b... | Mixin class for ``CharacterData`` and ``DocumentType`` class. | NonDocumentTypeChildNode | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NonDocumentTypeChildNode:
"""Mixin class for ``CharacterData`` and ``DocumentType`` class."""
def previousElementSibling(self) -> Optional[AbstractNode]:
"""Previous Element Node. If this node has no previous element node, return None."""
<|body_0|>
def nextElementSiblin... | stack_v2_sparse_classes_36k_train_008737 | 22,053 | permissive | [
{
"docstring": "Previous Element Node. If this node has no previous element node, return None.",
"name": "previousElementSibling",
"signature": "def previousElementSibling(self) -> Optional[AbstractNode]"
},
{
"docstring": "Next Element Node. If this node has no next element node, return None.",... | 2 | null | Implement the Python class `NonDocumentTypeChildNode` described below.
Class description:
Mixin class for ``CharacterData`` and ``DocumentType`` class.
Method signatures and docstrings:
- def previousElementSibling(self) -> Optional[AbstractNode]: Previous Element Node. If this node has no previous element node, retu... | Implement the Python class `NonDocumentTypeChildNode` described below.
Class description:
Mixin class for ``CharacterData`` and ``DocumentType`` class.
Method signatures and docstrings:
- def previousElementSibling(self) -> Optional[AbstractNode]: Previous Element Node. If this node has no previous element node, retu... | c7cd8b3428ca154af6fb1ecb6c7d2f0e17551802 | <|skeleton|>
class NonDocumentTypeChildNode:
"""Mixin class for ``CharacterData`` and ``DocumentType`` class."""
def previousElementSibling(self) -> Optional[AbstractNode]:
"""Previous Element Node. If this node has no previous element node, return None."""
<|body_0|>
def nextElementSiblin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NonDocumentTypeChildNode:
"""Mixin class for ``CharacterData`` and ``DocumentType`` class."""
def previousElementSibling(self) -> Optional[AbstractNode]:
"""Previous Element Node. If this node has no previous element node, return None."""
if self.parentNode is None:
return Non... | the_stack_v2_python_sparse | wdom/node.py | miyakogi/wdom | train | 72 |
4b42b73fdb1a36f31b0f36dcd082f9c769b92a5c | [
"self.size = size\nself.current_size = 0\nself.values = collections.deque()",
"if self.current_size < self.size:\n self.values.append(val)\n self.current_size += 1\n return 1.0 * sum(self.values) / len(self.values)\nelse:\n self.values.append(val)\n self.values.popleft()\n return 1.0 * sum(self.... | <|body_start_0|>
self.size = size
self.current_size = 0
self.values = collections.deque()
<|end_body_0|>
<|body_start_1|>
if self.current_size < self.size:
self.values.append(val)
self.current_size += 1
return 1.0 * sum(self.values) / len(self.values)... | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.size = size
self.current... | stack_v2_sparse_classes_36k_train_008738 | 1,304 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018399 | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | 6de551327f96ec4d4b63d0045281b65bbb4f5d0f | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.size = size
self.current_size = 0
self.values = collections.deque()
def next(self, val):
""":type val: int :rtype: float"""
if self.current_size < self.... | the_stack_v2_python_sparse | MovingAverage.py | JingweiTu/leetcode | train | 0 | |
4f01e3c7f90ddc29cb003287dedb12568ab8d808 | [
"if isolation_window is None:\n raise ValueError('An isolation window None!')\ntry:\n forest = self.forest_for_isolation_window[isolation_window]\nexcept KeyError:\n forest = self.forest_type(error_tolerance=self.error_tolerance)\n self.forest_for_isolation_window[isolation_window] = forest\nreturn fore... | <|body_start_0|>
if isolation_window is None:
raise ValueError('An isolation window None!')
try:
forest = self.forest_for_isolation_window[isolation_window]
except KeyError:
forest = self.forest_type(error_tolerance=self.error_tolerance)
self.fores... | IsolationWindowDemultiplexerBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsolationWindowDemultiplexerBase:
def forest_for(self, isolation_window: IsolationWindow) -> FeatureForestType:
"""Get the :class:`~.DeconvolutedLCMSFeatureForest` for a specific isolation window, or if one does not exist, create it. Parameters ---------- isolation_window : :class:`~.Iso... | stack_v2_sparse_classes_36k_train_008739 | 8,612 | permissive | [
{
"docstring": "Get the :class:`~.DeconvolutedLCMSFeatureForest` for a specific isolation window, or if one does not exist, create it. Parameters ---------- isolation_window : :class:`~.IsolationWindow` The isolation window to select with Returns ------- :class:`~.DeconvolutedLCMSFeatureForest`",
"name": "f... | 2 | stack_v2_sparse_classes_30k_test_001161 | Implement the Python class `IsolationWindowDemultiplexerBase` described below.
Class description:
Implement the IsolationWindowDemultiplexerBase class.
Method signatures and docstrings:
- def forest_for(self, isolation_window: IsolationWindow) -> FeatureForestType: Get the :class:`~.DeconvolutedLCMSFeatureForest` for... | Implement the Python class `IsolationWindowDemultiplexerBase` described below.
Class description:
Implement the IsolationWindowDemultiplexerBase class.
Method signatures and docstrings:
- def forest_for(self, isolation_window: IsolationWindow) -> FeatureForestType: Get the :class:`~.DeconvolutedLCMSFeatureForest` for... | 0912a6bbf3eab4163f3b0f122a8a6ec9814d75b1 | <|skeleton|>
class IsolationWindowDemultiplexerBase:
def forest_for(self, isolation_window: IsolationWindow) -> FeatureForestType:
"""Get the :class:`~.DeconvolutedLCMSFeatureForest` for a specific isolation window, or if one does not exist, create it. Parameters ---------- isolation_window : :class:`~.Iso... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IsolationWindowDemultiplexerBase:
def forest_for(self, isolation_window: IsolationWindow) -> FeatureForestType:
"""Get the :class:`~.DeconvolutedLCMSFeatureForest` for a specific isolation window, or if one does not exist, create it. Parameters ---------- isolation_window : :class:`~.IsolationWindow` ... | the_stack_v2_python_sparse | src/ms_deisotope/feature_map/demultiplex.py | mobiusklein/ms_deisotope | train | 24 | |
8dfa77ac06f9c6d910e6f0fe7e6d280fb000864f | [
"elements = self.root.findall('./resolution')\npresets = []\nfor element in elements:\n presets.append(element.get('name'))\nreturn presets",
"element = self.root.find(\"./resolution[@name='%s']/%s\" % (preset, setting))\nif element is not None:\n text = element.text\n if text is not None:\n retur... | <|body_start_0|>
elements = self.root.findall('./resolution')
presets = []
for element in elements:
presets.append(element.get('name'))
return presets
<|end_body_0|>
<|body_start_1|>
element = self.root.find("./resolution[@name='%s']/%s" % (preset, setting))
... | Manipulates XML database to store resolution presets. Inherits XMLData class. | ResPresets | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResPresets:
"""Manipulates XML database to store resolution presets. Inherits XMLData class."""
def getPresets(self):
"""Return a list of resolution presets."""
<|body_0|>
def getValue(self, preset, setting):
"""Get the specified value."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_008740 | 1,399 | permissive | [
{
"docstring": "Return a list of resolution presets.",
"name": "getPresets",
"signature": "def getPresets(self)"
},
{
"docstring": "Get the specified value.",
"name": "getValue",
"signature": "def getValue(self, preset, setting)"
},
{
"docstring": "Return a resolution preset give... | 3 | null | Implement the Python class `ResPresets` described below.
Class description:
Manipulates XML database to store resolution presets. Inherits XMLData class.
Method signatures and docstrings:
- def getPresets(self): Return a list of resolution presets.
- def getValue(self, preset, setting): Get the specified value.
- def... | Implement the Python class `ResPresets` described below.
Class description:
Manipulates XML database to store resolution presets. Inherits XMLData class.
Method signatures and docstrings:
- def getPresets(self): Return a list of resolution presets.
- def getValue(self, preset, setting): Get the specified value.
- def... | a05abc916f0b6a9ee2c00e9f9b3dec12c09e6abe | <|skeleton|>
class ResPresets:
"""Manipulates XML database to store resolution presets. Inherits XMLData class."""
def getPresets(self):
"""Return a list of resolution presets."""
<|body_0|>
def getValue(self, preset, setting):
"""Get the specified value."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResPresets:
"""Manipulates XML database to store resolution presets. Inherits XMLData class."""
def getPresets(self):
"""Return a list of resolution presets."""
elements = self.root.findall('./resolution')
presets = []
for element in elements:
presets.append(el... | the_stack_v2_python_sparse | shared/resPresets.py | mjbonnington/icarus-gps | train | 0 |
5cca1ac2fe7164c920ed2acad40200bc8ac45e37 | [
"super(EncoderDecoder, self).__init__(conf, output_dim, name)\nself.encoder = encoder_factory.factory(conf)\nself.decoder = asr_decoder_factory.factory(conf, self.output_dim)",
"std_input_noise = float(self.conf['std_input_noise'])\nif is_training and std_input_noise > 0:\n noisy_inputs = inputs + tf.random_no... | <|body_start_0|>
super(EncoderDecoder, self).__init__(conf, output_dim, name)
self.encoder = encoder_factory.factory(conf)
self.decoder = asr_decoder_factory.factory(conf, self.output_dim)
<|end_body_0|>
<|body_start_1|>
std_input_noise = float(self.conf['std_input_noise'])
if i... | a general class for an encoder decoder system | EncoderDecoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderDecoder:
"""a general class for an encoder decoder system"""
def __init__(self, conf, output_dim, name=None):
"""LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name"""
<|body_0|>
def _get_o... | stack_v2_sparse_classes_36k_train_008741 | 3,642 | permissive | [
{
"docstring": "LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name",
"name": "__init__",
"signature": "def __init__(self, conf, output_dim, name=None)"
},
{
"docstring": "Add the neural net variables and operations to th... | 2 | stack_v2_sparse_classes_30k_train_006681 | Implement the Python class `EncoderDecoder` described below.
Class description:
a general class for an encoder decoder system
Method signatures and docstrings:
- def __init__(self, conf, output_dim, name=None): LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: ... | Implement the Python class `EncoderDecoder` described below.
Class description:
a general class for an encoder decoder system
Method signatures and docstrings:
- def __init__(self, conf, output_dim, name=None): LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: ... | 09586e57bf4c6d29a6679e9bb3a488e09451f08e | <|skeleton|>
class EncoderDecoder:
"""a general class for an encoder decoder system"""
def __init__(self, conf, output_dim, name=None):
"""LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name"""
<|body_0|>
def _get_o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderDecoder:
"""a general class for an encoder decoder system"""
def __init__(self, conf, output_dim, name=None):
"""LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name"""
super(EncoderDecoder, self).__init__(co... | the_stack_v2_python_sparse | nabu/neuralnetworks/classifiers/asr/encoder_decoder.py | chenxinglili/nabu | train | 0 |
03928cd54a36b58b6cf48f056501d67f7d187655 | [
"for line in tokens_by_line:\n assign_ix = _find_assign_op(line)\n if assign_ix is not None and len(line) >= assign_ix + 2 and (line[assign_ix + 1].string == '%') and (line[assign_ix + 2].type == tokenize.NAME):\n return cls(line[assign_ix + 1].start)",
"start_line, start_col = (self.start_line, self... | <|body_start_0|>
for line in tokens_by_line:
assign_ix = _find_assign_op(line)
if assign_ix is not None and len(line) >= assign_ix + 2 and (line[assign_ix + 1].string == '%') and (line[assign_ix + 2].type == tokenize.NAME):
return cls(line[assign_ix + 1].start)
<|end_body... | Transformer for assignments from magics (a = %foo) | MagicAssign | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MagicAssign:
"""Transformer for assignments from magics (a = %foo)"""
def find(cls, tokens_by_line):
"""Find the first magic assignment (a = %foo) in the cell."""
<|body_0|>
def transform(self, lines: List[str]):
"""Transform a magic assignment found by the ``fin... | stack_v2_sparse_classes_36k_train_008742 | 29,393 | permissive | [
{
"docstring": "Find the first magic assignment (a = %foo) in the cell.",
"name": "find",
"signature": "def find(cls, tokens_by_line)"
},
{
"docstring": "Transform a magic assignment found by the ``find()`` classmethod.",
"name": "transform",
"signature": "def transform(self, lines: List... | 2 | stack_v2_sparse_classes_30k_train_020009 | Implement the Python class `MagicAssign` described below.
Class description:
Transformer for assignments from magics (a = %foo)
Method signatures and docstrings:
- def find(cls, tokens_by_line): Find the first magic assignment (a = %foo) in the cell.
- def transform(self, lines: List[str]): Transform a magic assignme... | Implement the Python class `MagicAssign` described below.
Class description:
Transformer for assignments from magics (a = %foo)
Method signatures and docstrings:
- def find(cls, tokens_by_line): Find the first magic assignment (a = %foo) in the cell.
- def transform(self, lines: List[str]): Transform a magic assignme... | e5103f971233fd66b558585cce7a4f52a716cd56 | <|skeleton|>
class MagicAssign:
"""Transformer for assignments from magics (a = %foo)"""
def find(cls, tokens_by_line):
"""Find the first magic assignment (a = %foo) in the cell."""
<|body_0|>
def transform(self, lines: List[str]):
"""Transform a magic assignment found by the ``fin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MagicAssign:
"""Transformer for assignments from magics (a = %foo)"""
def find(cls, tokens_by_line):
"""Find the first magic assignment (a = %foo) in the cell."""
for line in tokens_by_line:
assign_ix = _find_assign_op(line)
if assign_ix is not None and len(line) >... | the_stack_v2_python_sparse | IPython/core/inputtransformer2.py | ipython/ipython | train | 13,673 |
dff3540d647350e1afdfacf321ff916dc2db23dc | [
"if n in [0, 1]:\n return 1\nreturn self.climbStairs(n - 1) + self.climbStairs(n - 2)",
"mem = {0: 1, 1: 1}\nfor i in range(n + 1):\n if i not in mem:\n mem[i] = mem[i - 1] + mem[i - 2]\nreturn mem[n]"
] | <|body_start_0|>
if n in [0, 1]:
return 1
return self.climbStairs(n - 1) + self.climbStairs(n - 2)
<|end_body_0|>
<|body_start_1|>
mem = {0: 1, 1: 1}
for i in range(n + 1):
if i not in mem:
mem[i] = mem[i - 1] + mem[i - 2]
return mem[n]
<|... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs1(self, n):
""":type: n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n in [0, 1]:
return 1
return self.climbStair... | stack_v2_sparse_classes_36k_train_008743 | 664 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
},
{
"docstring": ":type: n: int :rtype: int",
"name": "climbStairs1",
"signature": "def climbStairs1(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017326 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs1(self, n): :type: n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs1(self, n): :type: n: int :rtype: int
<|skeleton|>
class Solution:
def climbStairs(self, n):
"""... | 857b8c7fccfe8216da59228c1cf3675444855673 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs1(self, n):
""":type: n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
if n in [0, 1]:
return 1
return self.climbStairs(n - 1) + self.climbStairs(n - 2)
def climbStairs1(self, n):
""":type: n: int :rtype: int"""
mem = {0: 1, 1: 1}
for i in range(n +... | the_stack_v2_python_sparse | algorithm/Climbing-Stairs.py | atashi/LLL | train | 0 | |
031c1d960d11127c13f1f2bc7b4f5bf4f6917765 | [
"super(Network, self).__init__()\nself.seed = torch.manual_seed(seed)\n'*** YOUR CODE HERE ***'\nfeature_size = 64\nself.feature_layer = nn.Sequential(nn.Linear(state_size, feature_size), nn.ReLU())\nvalue_size = 64\nself.value_layer = nn.Sequential(nn.Linear(feature_size, value_size), nn.ReLU(), nn.Linear(value_si... | <|body_start_0|>
super(Network, self).__init__()
self.seed = torch.manual_seed(seed)
'*** YOUR CODE HERE ***'
feature_size = 64
self.feature_layer = nn.Sequential(nn.Linear(state_size, feature_size), nn.ReLU())
value_size = 64
self.value_layer = nn.Sequential(nn.L... | Actor (Policy) Model. | Network | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Network:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
<|body_0|>
def... | stack_v2_sparse_classes_36k_train_008744 | 1,441 | permissive | [
{
"docstring": "Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed",
"name": "__init__",
"signature": "def __init__(self, state_size, action_size, seed)"
},
{
"docstring": "Build a net... | 2 | stack_v2_sparse_classes_30k_train_019332 | Implement the Python class `Network` described below.
Class description:
Actor (Policy) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each acti... | Implement the Python class `Network` described below.
Class description:
Actor (Policy) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each acti... | 9b1653b7aedeb4dc0e4aab9351cc4a7f4ccb4f32 | <|skeleton|>
class Network:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
<|body_0|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Network:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
super(Network, self).__init__()
... | the_stack_v2_python_sparse | p1_navigation/dueling_network.py | weicheng113/deep-reinforcement-learning | train | 0 |
9c4bb1ab64b3d3e0cbcc036288cbd4a5e986c27d | [
"try:\n response = Database.Table.get_item(Key={'DocumentID': document_id})\nexcept Exception as e:\n response = None\n Logger.info(f'Database GetDocument : document_id = {document_id} : exception = {e}')\nif response and response.get('Item') and (response['ResponseMetadata']['HTTPStatusCode'] == 200):\n ... | <|body_start_0|>
try:
response = Database.Table.get_item(Key={'DocumentID': document_id})
except Exception as e:
response = None
Logger.info(f'Database GetDocument : document_id = {document_id} : exception = {e}')
if response and response.get('Item') and (resp... | Database Abstraction Layer | Database | [
"Apache-2.0",
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Database:
"""Database Abstraction Layer"""
def GetDocument(document_id: str) -> Document:
"""Fetch a specific document"""
<|body_0|>
def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]:
"""Fetch a specific document set"""
<|body_1... | stack_v2_sparse_classes_36k_train_008745 | 3,107 | permissive | [
{
"docstring": "Fetch a specific document",
"name": "GetDocument",
"signature": "def GetDocument(document_id: str) -> Document"
},
{
"docstring": "Fetch a specific document set",
"name": "GetDocuments",
"signature": "def GetDocuments(stages: List[Stage], states: List[State]) -> List[Docu... | 4 | stack_v2_sparse_classes_30k_train_004886 | Implement the Python class `Database` described below.
Class description:
Database Abstraction Layer
Method signatures and docstrings:
- def GetDocument(document_id: str) -> Document: Fetch a specific document
- def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]: Fetch a specific document se... | Implement the Python class `Database` described below.
Class description:
Database Abstraction Layer
Method signatures and docstrings:
- def GetDocument(document_id: str) -> Document: Fetch a specific document
- def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]: Fetch a specific document se... | 633e6291eea95a3933d34cae53b68cf6570b9bbb | <|skeleton|>
class Database:
"""Database Abstraction Layer"""
def GetDocument(document_id: str) -> Document:
"""Fetch a specific document"""
<|body_0|>
def GetDocuments(stages: List[Stage], states: List[State]) -> List[Document]:
"""Fetch a specific document set"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Database:
"""Database Abstraction Layer"""
def GetDocument(document_id: str) -> Document:
"""Fetch a specific document"""
try:
response = Database.Table.get_item(Key={'DocumentID': document_id})
except Exception as e:
response = None
Logger.info... | the_stack_v2_python_sparse | source/lambdas/shared/database.py | jhasatis/TabularDocumentDigitization | train | 0 |
af534ffadd9ac19e25e2c33d81a21eb6ca4c758f | [
"self.state = state\nself.waiting_circuits = {}\nself.expected_streams = {}\nself.state.add_stream_listener(self)\nself.state.add_circuit_listener(self)",
"circ_deferred = defer.Deferred()\nkey = (str(host), int(port))\nself.expected_streams[key] = circ_deferred\n\ndef add_to_waiting(circ):\n self.waiting_circ... | <|body_start_0|>
self.state = state
self.waiting_circuits = {}
self.expected_streams = {}
self.state.add_stream_listener(self)
self.state.add_circuit_listener(self)
<|end_body_0|>
<|body_start_1|>
circ_deferred = defer.Deferred()
key = (str(host), int(port))
... | An attacher that builds a chosen path for a client identified by its source port and ip address. | SOCKSClientStreamAttacher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SOCKSClientStreamAttacher:
"""An attacher that builds a chosen path for a client identified by its source port and ip address."""
def __init__(self, state):
"""Instantiates a SOCKSClientStreamAttacher with a txtorcon.torstate.TorState instance."""
<|body_0|>
def create_c... | stack_v2_sparse_classes_36k_train_008746 | 5,595 | no_license | [
{
"docstring": "Instantiates a SOCKSClientStreamAttacher with a txtorcon.torstate.TorState instance.",
"name": "__init__",
"signature": "def __init__(self, state)"
},
{
"docstring": "Specify the path for streams created on a specific client SOCKS connection. Returns a deferred that calls back wi... | 5 | stack_v2_sparse_classes_30k_train_015858 | Implement the Python class `SOCKSClientStreamAttacher` described below.
Class description:
An attacher that builds a chosen path for a client identified by its source port and ip address.
Method signatures and docstrings:
- def __init__(self, state): Instantiates a SOCKSClientStreamAttacher with a txtorcon.torstate.T... | Implement the Python class `SOCKSClientStreamAttacher` described below.
Class description:
An attacher that builds a chosen path for a client identified by its source port and ip address.
Method signatures and docstrings:
- def __init__(self, state): Instantiates a SOCKSClientStreamAttacher with a txtorcon.torstate.T... | c3834e47c12315468d686a7b7fef62d35bd28cd3 | <|skeleton|>
class SOCKSClientStreamAttacher:
"""An attacher that builds a chosen path for a client identified by its source port and ip address."""
def __init__(self, state):
"""Instantiates a SOCKSClientStreamAttacher with a txtorcon.torstate.TorState instance."""
<|body_0|>
def create_c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SOCKSClientStreamAttacher:
"""An attacher that builds a chosen path for a client identified by its source port and ip address."""
def __init__(self, state):
"""Instantiates a SOCKSClientStreamAttacher with a txtorcon.torstate.TorState instance."""
self.state = state
self.waiting_c... | the_stack_v2_python_sparse | bwscanner/attacher.py | poorboy23/bwscanner | train | 0 |
c696f7f5133fcfad1e7b93a9db114b6cd3b75b28 | [
"post = PostFactory(is_active=True)\nReportFactory.create_batch(3, post=post)\nself.assertFalse(post.is_active)",
"user = UserFactory()\npost = PostFactory()\nrequest = MagicMock()\nrequest.user = user\nrequest.method = 'POST'\nrequest.POST = {'reason': Report.HARASSMENT}\nview = ReportCreate()\nview.kwargs = {'p... | <|body_start_0|>
post = PostFactory(is_active=True)
ReportFactory.create_batch(3, post=post)
self.assertFalse(post.is_active)
<|end_body_0|>
<|body_start_1|>
user = UserFactory()
post = PostFactory()
request = MagicMock()
request.user = user
request.metho... | TestReports | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestReports:
def test_post_disable(self, mock):
"""Reports from 3 different user block post"""
<|body_0|>
def test_report_only_once(self):
"""Report can be sent only once"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
post = PostFactory(is_active=T... | stack_v2_sparse_classes_36k_train_008747 | 1,170 | no_license | [
{
"docstring": "Reports from 3 different user block post",
"name": "test_post_disable",
"signature": "def test_post_disable(self, mock)"
},
{
"docstring": "Report can be sent only once",
"name": "test_report_only_once",
"signature": "def test_report_only_once(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019102 | Implement the Python class `TestReports` described below.
Class description:
Implement the TestReports class.
Method signatures and docstrings:
- def test_post_disable(self, mock): Reports from 3 different user block post
- def test_report_only_once(self): Report can be sent only once | Implement the Python class `TestReports` described below.
Class description:
Implement the TestReports class.
Method signatures and docstrings:
- def test_post_disable(self, mock): Reports from 3 different user block post
- def test_report_only_once(self): Report can be sent only once
<|skeleton|>
class TestReports:... | 4089c3f084d7460f64517158eefb54b3b93a01e8 | <|skeleton|>
class TestReports:
def test_post_disable(self, mock):
"""Reports from 3 different user block post"""
<|body_0|>
def test_report_only_once(self):
"""Report can be sent only once"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestReports:
def test_post_disable(self, mock):
"""Reports from 3 different user block post"""
post = PostFactory(is_active=True)
ReportFactory.create_batch(3, post=post)
self.assertFalse(post.is_active)
def test_report_only_once(self):
"""Report can be sent only o... | the_stack_v2_python_sparse | apps/reports/tests.py | maxwell912/social-app | train | 0 | |
d1210513ae82ff7de006c7e70aba3632ee09b9fb | [
"delta_lon_lat = np.array(meters, dtype=np.float64)\nif len(delta_lon_lat.shape) == 1:\n if delta_lon_lat.shape[0] == 2:\n delta_lon_lat = delta_lon_lat.reshape(1, 2)\n else:\n delta_lon_lat = delta_lon_lat.reshape(1, 3)\nref_positions = np.asarray(ref_positions, dtype=np.float64)\nif len(ref_po... | <|body_start_0|>
delta_lon_lat = np.array(meters, dtype=np.float64)
if len(delta_lon_lat.shape) == 1:
if delta_lon_lat.shape[0] == 2:
delta_lon_lat = delta_lon_lat.reshape(1, 2)
else:
delta_lon_lat = delta_lon_lat.reshape(1, 3)
ref_position... | class to define a "flat earth" projection: longitude is scaled to the cosine of the mid-latitude -- but that's it. not conforming to equal area, distance, bearing, or any other nifty map properties -- but easy to compute, and it looks OK. | FlatEarthProjection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlatEarthProjection:
"""class to define a "flat earth" projection: longitude is scaled to the cosine of the mid-latitude -- but that's it. not conforming to equal area, distance, bearing, or any other nifty map properties -- but easy to compute, and it looks OK."""
def meters_to_lonlat(meter... | stack_v2_sparse_classes_36k_train_008748 | 25,780 | no_license | [
{
"docstring": "Converts from delta meters to delta latitude-longitude, using the Flat-Earth projection. dlat = dy * 8.9992801e-06 dlon = dy * 8.9992801e-06 * cos(ref_lat) (based on previous GNOME value: and/or average radius of the earth of 6366706.989 m) :param meters: Distances in meters :type meters: NX3 nu... | 4 | null | Implement the Python class `FlatEarthProjection` described below.
Class description:
class to define a "flat earth" projection: longitude is scaled to the cosine of the mid-latitude -- but that's it. not conforming to equal area, distance, bearing, or any other nifty map properties -- but easy to compute, and it looks... | Implement the Python class `FlatEarthProjection` described below.
Class description:
class to define a "flat earth" projection: longitude is scaled to the cosine of the mid-latitude -- but that's it. not conforming to equal area, distance, bearing, or any other nifty map properties -- but easy to compute, and it looks... | 2e24d53b8b1099022a08ad73377ed6d1c7838f0f | <|skeleton|>
class FlatEarthProjection:
"""class to define a "flat earth" projection: longitude is scaled to the cosine of the mid-latitude -- but that's it. not conforming to equal area, distance, bearing, or any other nifty map properties -- but easy to compute, and it looks OK."""
def meters_to_lonlat(meter... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlatEarthProjection:
"""class to define a "flat earth" projection: longitude is scaled to the cosine of the mid-latitude -- but that's it. not conforming to equal area, distance, bearing, or any other nifty map properties -- but easy to compute, and it looks OK."""
def meters_to_lonlat(meters, ref_positi... | the_stack_v2_python_sparse | py_gnome/gnome/utilities/projections.py | bhattvihang/PyGnome | train | 1 |
8a7c3af27f3ac2ee6ce60d451e2abdfd2e6ba5ea | [
"if not isinstance(condition, PassPredicate):\n raise TypeError('Expected PassPredicate, got %s.' % type(condition))\nself.condition = condition\nself.on_true = Workflow(on_true)\nself.on_false = Workflow(on_false) if on_false is not None else None",
"if self.condition(circuit, data):\n _logger.debug('True ... | <|body_start_0|>
if not isinstance(condition, PassPredicate):
raise TypeError('Expected PassPredicate, got %s.' % type(condition))
self.condition = condition
self.on_true = Workflow(on_true)
self.on_false = Workflow(on_false) if on_false is not None else None
<|end_body_0|>
... | The IfThenElsePass class. This is a control pass that conditionally executes a workflow. | IfThenElsePass | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IfThenElsePass:
"""The IfThenElsePass class. This is a control pass that conditionally executes a workflow."""
def __init__(self, condition: PassPredicate, on_true: WorkflowLike, on_false: WorkflowLike | None=None) -> None:
"""Construct a IfThenElsePass. Args: condition (PassPredicat... | stack_v2_sparse_classes_36k_train_008749 | 1,960 | permissive | [
{
"docstring": "Construct a IfThenElsePass. Args: condition (PassPredicate): The condition checked. on_true (WorkflowLike): The pass or passes to execute if `condition` is true. on_false (WorkflowLike | None): If specified, the pass or passes to execute if `condition` is false. Defaults to None, which does is e... | 2 | stack_v2_sparse_classes_30k_test_001057 | Implement the Python class `IfThenElsePass` described below.
Class description:
The IfThenElsePass class. This is a control pass that conditionally executes a workflow.
Method signatures and docstrings:
- def __init__(self, condition: PassPredicate, on_true: WorkflowLike, on_false: WorkflowLike | None=None) -> None: ... | Implement the Python class `IfThenElsePass` described below.
Class description:
The IfThenElsePass class. This is a control pass that conditionally executes a workflow.
Method signatures and docstrings:
- def __init__(self, condition: PassPredicate, on_true: WorkflowLike, on_false: WorkflowLike | None=None) -> None: ... | c89112d15072e8ffffb68cf1757b184e2aeb3dc8 | <|skeleton|>
class IfThenElsePass:
"""The IfThenElsePass class. This is a control pass that conditionally executes a workflow."""
def __init__(self, condition: PassPredicate, on_true: WorkflowLike, on_false: WorkflowLike | None=None) -> None:
"""Construct a IfThenElsePass. Args: condition (PassPredicat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IfThenElsePass:
"""The IfThenElsePass class. This is a control pass that conditionally executes a workflow."""
def __init__(self, condition: PassPredicate, on_true: WorkflowLike, on_false: WorkflowLike | None=None) -> None:
"""Construct a IfThenElsePass. Args: condition (PassPredicate): The condi... | the_stack_v2_python_sparse | bqskit/passes/control/ifthenelse.py | BQSKit/bqskit | train | 54 |
3b39f3c879cbd63430ff7245031c96769f9e7fbd | [
"source = GithubSource()\nsource.path = 'some/bad/path'\nwith self.assertRaises(IncorrectDirectoryException):\n list(iterate_github_source('a/different/path', source, mock.MagicMock()))",
"source = GithubSource()\nsource.path = '.'\nfacade = mock.MagicMock()\nmock_llsd.return_value = [('file', False), ('direct... | <|body_start_0|>
source = GithubSource()
source.path = 'some/bad/path'
with self.assertRaises(IncorrectDirectoryException):
list(iterate_github_source('a/different/path', source, mock.MagicMock()))
<|end_body_0|>
<|body_start_1|>
source = GithubSource()
source.path =... | Test the behaviour of the `iterate_github_source` function. | TestIterateGithubSource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestIterateGithubSource:
"""Test the behaviour of the `iterate_github_source` function."""
def test_iterate_github_source_incorrect_directory(self):
"""If `iterate_github_source` is called with a source that is not inside the directory passed in, an `IncorrectDirectoryException` shou... | stack_v2_sparse_classes_36k_train_008750 | 17,513 | permissive | [
{
"docstring": "If `iterate_github_source` is called with a source that is not inside the directory passed in, an `IncorrectDirectoryException` should be raised.",
"name": "test_iterate_github_source_incorrect_directory",
"signature": "def test_iterate_github_source_incorrect_directory(self)"
},
{
... | 3 | null | Implement the Python class `TestIterateGithubSource` described below.
Class description:
Test the behaviour of the `iterate_github_source` function.
Method signatures and docstrings:
- def test_iterate_github_source_incorrect_directory(self): If `iterate_github_source` is called with a source that is not inside the d... | Implement the Python class `TestIterateGithubSource` described below.
Class description:
Test the behaviour of the `iterate_github_source` function.
Method signatures and docstrings:
- def test_iterate_github_source_incorrect_directory(self): If `iterate_github_source` is called with a source that is not inside the d... | 47c6377ccbfe8576b35854053d726537e533e78c | <|skeleton|>
class TestIterateGithubSource:
"""Test the behaviour of the `iterate_github_source` function."""
def test_iterate_github_source_incorrect_directory(self):
"""If `iterate_github_source` is called with a source that is not inside the directory passed in, an `IncorrectDirectoryException` shou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestIterateGithubSource:
"""Test the behaviour of the `iterate_github_source` function."""
def test_iterate_github_source_incorrect_directory(self):
"""If `iterate_github_source` is called with a source that is not inside the directory passed in, an `IncorrectDirectoryException` should be raised.... | the_stack_v2_python_sparse | director/projects/test_source_operations.py | gxf1986/hub | train | 0 |
9fde606ade16252bad5d05584853b2c887c4def4 | [
"data = {'model_id': self._id, 'queries_dataset_id': queries_dataset_id, 'queries_dataset_content_column': queries_dataset_content_column, 'top_k': top_k}\nif matching_id_description_column:\n data['queries_dataset_matching_id_description_column'] = matching_id_description_column\nendpoint = '/usecase-versions/{... | <|body_start_0|>
data = {'model_id': self._id, 'queries_dataset_id': queries_dataset_id, 'queries_dataset_content_column': queries_dataset_content_column, 'top_k': top_k}
if matching_id_description_column:
data['queries_dataset_matching_id_description_column'] = matching_id_description_colum... | TextSimilarityModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextSimilarityModel:
def _predict_bulk(self, queries_dataset_id: str, queries_dataset_content_column: str, top_k: int, matching_id_description_column: str=None):
"""(Util method) Private method used to handle bulk predict. .. note:: This function should not be used directly. Use predict_... | stack_v2_sparse_classes_36k_train_008751 | 22,476 | permissive | [
{
"docstring": "(Util method) Private method used to handle bulk predict. .. note:: This function should not be used directly. Use predict_from_* methods instead. Args: queries_dataset_id (str): Unique id of the quries dataset to predict with queries_dataset_content_column (str): Content queries column name que... | 2 | stack_v2_sparse_classes_30k_train_000096 | Implement the Python class `TextSimilarityModel` described below.
Class description:
Implement the TextSimilarityModel class.
Method signatures and docstrings:
- def _predict_bulk(self, queries_dataset_id: str, queries_dataset_content_column: str, top_k: int, matching_id_description_column: str=None): (Util method) P... | Implement the Python class `TextSimilarityModel` described below.
Class description:
Implement the TextSimilarityModel class.
Method signatures and docstrings:
- def _predict_bulk(self, queries_dataset_id: str, queries_dataset_content_column: str, top_k: int, matching_id_description_column: str=None): (Util method) P... | 0860c931e2b466ac4be910350890085111ae32ce | <|skeleton|>
class TextSimilarityModel:
def _predict_bulk(self, queries_dataset_id: str, queries_dataset_content_column: str, top_k: int, matching_id_description_column: str=None):
"""(Util method) Private method used to handle bulk predict. .. note:: This function should not be used directly. Use predict_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextSimilarityModel:
def _predict_bulk(self, queries_dataset_id: str, queries_dataset_content_column: str, top_k: int, matching_id_description_column: str=None):
"""(Util method) Private method used to handle bulk predict. .. note:: This function should not be used directly. Use predict_from_* methods... | the_stack_v2_python_sparse | previsionio/model.py | FrancoisA-prevision/prevision-python | train | 0 | |
b5a4ab25ea68c36b4bb8d8ccef5108c0c2d6949a | [
"try:\n if document_type == DocumentType.TERMS_OF_USE.value:\n token = g.jwt_oidc_token_info\n if token.get('accessType', None) == AccessType.ANONYMOUS.value:\n document_type = DocumentType.TERMS_OF_USE_DIRECTOR_SEARCH.value\n elif token.get('loginSource', None) == LoginSource.STA... | <|body_start_0|>
try:
if document_type == DocumentType.TERMS_OF_USE.value:
token = g.jwt_oidc_token_info
if token.get('accessType', None) == AccessType.ANONYMOUS.value:
document_type = DocumentType.TERMS_OF_USE_DIRECTOR_SEARCH.value
... | Resource for managing Terms Of Use. | Documents | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Documents:
"""Resource for managing Terms Of Use."""
def get(document_type):
"""Return the latest terms of use."""
<|body_0|>
def _replace_current_date(doc):
"""Replace any dynamic contents."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_008752 | 3,921 | permissive | [
{
"docstring": "Return the latest terms of use.",
"name": "get",
"signature": "def get(document_type)"
},
{
"docstring": "Replace any dynamic contents.",
"name": "_replace_current_date",
"signature": "def _replace_current_date(doc)"
}
] | 2 | null | Implement the Python class `Documents` described below.
Class description:
Resource for managing Terms Of Use.
Method signatures and docstrings:
- def get(document_type): Return the latest terms of use.
- def _replace_current_date(doc): Replace any dynamic contents. | Implement the Python class `Documents` described below.
Class description:
Resource for managing Terms Of Use.
Method signatures and docstrings:
- def get(document_type): Return the latest terms of use.
- def _replace_current_date(doc): Replace any dynamic contents.
<|skeleton|>
class Documents:
"""Resource for ... | 923cb8a3ee88dcbaf0fe800ca70022b3c13c1d01 | <|skeleton|>
class Documents:
"""Resource for managing Terms Of Use."""
def get(document_type):
"""Return the latest terms of use."""
<|body_0|>
def _replace_current_date(doc):
"""Replace any dynamic contents."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Documents:
"""Resource for managing Terms Of Use."""
def get(document_type):
"""Return the latest terms of use."""
try:
if document_type == DocumentType.TERMS_OF_USE.value:
token = g.jwt_oidc_token_info
if token.get('accessType', None) == Access... | the_stack_v2_python_sparse | auth-api/src/auth_api/resources/documents.py | bcgov/sbc-auth | train | 13 |
f0c44e3007ba2317060e986275d026abcf4eba97 | [
"if len(grid) == 0 or (len(grid) == 0 and len(grid[0]) == 0):\n return 0\nacross_length = len(grid[0])\nvertical_length = len(grid)\nisland_nums = 0\nfor i in range(vertical_length):\n for j in range(across_length):\n if grid[i][j] == '1':\n grid[i][j] = '0'\n island_nums += 1\n ... | <|body_start_0|>
if len(grid) == 0 or (len(grid) == 0 and len(grid[0]) == 0):
return 0
across_length = len(grid[0])
vertical_length = len(grid)
island_nums = 0
for i in range(vertical_length):
for j in range(across_length):
if grid[i][j] ==... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numIslands(self, grid: [[int]]) -> int:
"""get islands from arrays :param grid: :type: [[str]] example: [ ["1", "1", "0", "0", "0"], ["1", "1", "0", "0", "0"], ["0", "0", "1", "0", "0"], ["0", "0", "0", "1", "1"] ] :return: :rtype: int"""
<|body_0|>
def __get_i... | stack_v2_sparse_classes_36k_train_008753 | 3,570 | no_license | [
{
"docstring": "get islands from arrays :param grid: :type: [[str]] example: [ [\"1\", \"1\", \"0\", \"0\", \"0\"], [\"1\", \"1\", \"0\", \"0\", \"0\"], [\"0\", \"0\", \"1\", \"0\", \"0\"], [\"0\", \"0\", \"0\", \"1\", \"1\"] ] :return: :rtype: int",
"name": "numIslands",
"signature": "def numIslands(se... | 2 | stack_v2_sparse_classes_30k_train_021190 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid: [[int]]) -> int: get islands from arrays :param grid: :type: [[str]] example: [ ["1", "1", "0", "0", "0"], ["1", "1", "0", "0", "0"], ["0", "0", "1", "... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid: [[int]]) -> int: get islands from arrays :param grid: :type: [[str]] example: [ ["1", "1", "0", "0", "0"], ["1", "1", "0", "0", "0"], ["0", "0", "1", "... | 37710292b2cfc6060098363c8d5f8881a4c22b26 | <|skeleton|>
class Solution:
def numIslands(self, grid: [[int]]) -> int:
"""get islands from arrays :param grid: :type: [[str]] example: [ ["1", "1", "0", "0", "0"], ["1", "1", "0", "0", "0"], ["0", "0", "1", "0", "0"], ["0", "0", "0", "1", "1"] ] :return: :rtype: int"""
<|body_0|>
def __get_i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numIslands(self, grid: [[int]]) -> int:
"""get islands from arrays :param grid: :type: [[str]] example: [ ["1", "1", "0", "0", "0"], ["1", "1", "0", "0", "0"], ["0", "0", "1", "0", "0"], ["0", "0", "0", "1", "1"] ] :return: :rtype: int"""
if len(grid) == 0 or (len(grid) == 0 and ... | the_stack_v2_python_sparse | python/pyleetcode/queue_and_stack/numIslands.py | yudongnan23/algorithmRoad | train | 0 | |
f1120224241851c19baa225fddf63173832d53ab | [
"try:\n serializer = PatientHistorySerializers(PatientHistory.objects.all(), many=True)\n return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)\nexcept Exception as e:\n info_message = 'Internal Server Error'\n logger.error(info_message, e)\n return JsonResponse({'error'... | <|body_start_0|>
try:
serializer = PatientHistorySerializers(PatientHistory.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
except Exception as e:
info_message = 'Internal Server Error'
logger.e... | PatientHistoryView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PatientHistoryView:
def get(self, request):
"""Get all patients"""
<|body_0|>
def post(self, request):
"""Save patient data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
serializer = PatientHistorySerializers(PatientHistory.object... | stack_v2_sparse_classes_36k_train_008754 | 12,219 | no_license | [
{
"docstring": "Get all patients",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Save patient data",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014105 | Implement the Python class `PatientHistoryView` described below.
Class description:
Implement the PatientHistoryView class.
Method signatures and docstrings:
- def get(self, request): Get all patients
- def post(self, request): Save patient data | Implement the Python class `PatientHistoryView` described below.
Class description:
Implement the PatientHistoryView class.
Method signatures and docstrings:
- def get(self, request): Get all patients
- def post(self, request): Save patient data
<|skeleton|>
class PatientHistoryView:
def get(self, request):
... | b63849983a592fd6a1f654191020fd86aa0787ae | <|skeleton|>
class PatientHistoryView:
def get(self, request):
"""Get all patients"""
<|body_0|>
def post(self, request):
"""Save patient data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PatientHistoryView:
def get(self, request):
"""Get all patients"""
try:
serializer = PatientHistorySerializers(PatientHistory.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
except Exception as e:
... | the_stack_v2_python_sparse | patient/views.py | RupeshKurlekar/biocare | train | 1 | |
54d8caf37eba3d253c75a50580b7eccb518873fc | [
"super(MewloModelManager, self).__init__(mewlosite, debugmode)\nself.modelclass = modelclass\nif flag_set_objmanager:\n modelclass.set_objectmanager(self)",
"outstr = ' ' * indent + \"MewloModelManager ({0}) which manages model class '{1}' reporting in.\\n\".format(self.__class__.__name__, self.modelclass.__na... | <|body_start_0|>
super(MewloModelManager, self).__init__(mewlosite, debugmode)
self.modelclass = modelclass
if flag_set_objmanager:
modelclass.set_objectmanager(self)
<|end_body_0|>
<|body_start_1|>
outstr = ' ' * indent + "MewloModelManager ({0}) which manages model class '... | Manager class specialized to manage a database model class. | MewloModelManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MewloModelManager:
"""Manager class specialized to manage a database model class."""
def __init__(self, mewlosite, debugmode, modelclass, flag_set_objmanager):
"""construct and initialize the stored modelclass that we manage."""
<|body_0|>
def dumps(self, indent=0):
... | stack_v2_sparse_classes_36k_train_008755 | 1,178 | no_license | [
{
"docstring": "construct and initialize the stored modelclass that we manage.",
"name": "__init__",
"signature": "def __init__(self, mewlosite, debugmode, modelclass, flag_set_objmanager)"
},
{
"docstring": "Return a string (with newlines and indents) that displays some debugging useful informa... | 2 | null | Implement the Python class `MewloModelManager` described below.
Class description:
Manager class specialized to manage a database model class.
Method signatures and docstrings:
- def __init__(self, mewlosite, debugmode, modelclass, flag_set_objmanager): construct and initialize the stored modelclass that we manage.
-... | Implement the Python class `MewloModelManager` described below.
Class description:
Manager class specialized to manage a database model class.
Method signatures and docstrings:
- def __init__(self, mewlosite, debugmode, modelclass, flag_set_objmanager): construct and initialize the stored modelclass that we manage.
-... | 0c101169767935da1de22de7e6be1e5862592971 | <|skeleton|>
class MewloModelManager:
"""Manager class specialized to manage a database model class."""
def __init__(self, mewlosite, debugmode, modelclass, flag_set_objmanager):
"""construct and initialize the stored modelclass that we manage."""
<|body_0|>
def dumps(self, indent=0):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MewloModelManager:
"""Manager class specialized to manage a database model class."""
def __init__(self, mewlosite, debugmode, modelclass, flag_set_objmanager):
"""construct and initialize the stored modelclass that we manage."""
super(MewloModelManager, self).__init__(mewlosite, debugmode... | the_stack_v2_python_sparse | mewlo/mpacks/core/manager/modelmanager.py | dcmouser/mewlo | train | 0 |
9f17e3be7533862af50e6aaf856cfce6c275feab | [
"ret = [nums[0]]\nfor num in nums[1:]:\n if num > ret[-1]:\n ret.append(num)\n else:\n pos = bisect.bisect_left(ret, num)\n ret[pos] = num\nreturn len(ret)",
"dp = [1] * len(nums)\nfor i in range(1, len(nums)):\n dp[i] = max((dp[x] + 1 if nums[x] < nums[i] else 1 for x in range(i)))\... | <|body_start_0|>
ret = [nums[0]]
for num in nums[1:]:
if num > ret[-1]:
ret.append(num)
else:
pos = bisect.bisect_left(ret, num)
ret[pos] = num
return len(ret)
<|end_body_0|>
<|body_start_1|>
dp = [1] * len(nums)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""CREATED AT: 2022/5/25 Runtime: 118 ms, faster than 80.84% Memory Usage: 14.2 MB, less than 48.57% 1 <= nums.length <= 2500 -10^4 <= nums[i] <= 10^4 :param nums: :return:"""
<|body_0|>
def lengthOfLIS3(self, nums: Li... | stack_v2_sparse_classes_36k_train_008756 | 2,918 | permissive | [
{
"docstring": "CREATED AT: 2022/5/25 Runtime: 118 ms, faster than 80.84% Memory Usage: 14.2 MB, less than 48.57% 1 <= nums.length <= 2500 -10^4 <= nums[i] <= 10^4 :param nums: :return:",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums: List[int]) -> int"
},
{
"docstring": "CREAT... | 3 | stack_v2_sparse_classes_30k_train_017705 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums: List[int]) -> int: CREATED AT: 2022/5/25 Runtime: 118 ms, faster than 80.84% Memory Usage: 14.2 MB, less than 48.57% 1 <= nums.length <= 2500 -10^4 <=... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums: List[int]) -> int: CREATED AT: 2022/5/25 Runtime: 118 ms, faster than 80.84% Memory Usage: 14.2 MB, less than 48.57% 1 <= nums.length <= 2500 -10^4 <=... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""CREATED AT: 2022/5/25 Runtime: 118 ms, faster than 80.84% Memory Usage: 14.2 MB, less than 48.57% 1 <= nums.length <= 2500 -10^4 <= nums[i] <= 10^4 :param nums: :return:"""
<|body_0|>
def lengthOfLIS3(self, nums: Li... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS(self, nums: List[int]) -> int:
"""CREATED AT: 2022/5/25 Runtime: 118 ms, faster than 80.84% Memory Usage: 14.2 MB, less than 48.57% 1 <= nums.length <= 2500 -10^4 <= nums[i] <= 10^4 :param nums: :return:"""
ret = [nums[0]]
for num in nums[1:]:
if n... | the_stack_v2_python_sparse | src/300-LongestIncreasingSubsequence.py | Jiezhi/myleetcode | train | 1 | |
c194d7084b8230c7c9c73e2f2d8d4015261c2c79 | [
"self.SetStartDate(2010, 1, 1)\nself.SetEndDate(2013, 12, 31)\nself.SetCash(100000)\nIntrinioConfig.SetUserAndPassword('intrinio-username', 'intrinio-password')\nIntrinioConfig.SetTimeIntervalBetweenCalls(timedelta(minutes=1))\nself.uso = self.AddEquity('USO', Resolution.Daily).Symbol\nself.Securities[self.uso].Set... | <|body_start_0|>
self.SetStartDate(2010, 1, 1)
self.SetEndDate(2013, 12, 31)
self.SetCash(100000)
IntrinioConfig.SetUserAndPassword('intrinio-username', 'intrinio-password')
IntrinioConfig.SetTimeIntervalBetweenCalls(timedelta(minutes=1))
self.uso = self.AddEquity('USO', ... | BasicTemplateIntrinioEconomicData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicTemplateIntrinioEconomicData:
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
<|body_0|>
def OnData(self, slice):
"""OnData event is the primary... | stack_v2_sparse_classes_36k_train_008757 | 2,830 | permissive | [
{
"docstring": "Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.",
"name": "Initialize",
"signature": "def Initialize(self)"
},
{
"docstring": "OnData event is the primary entry point for your algorithm. Eac... | 2 | stack_v2_sparse_classes_30k_train_018729 | Implement the Python class `BasicTemplateIntrinioEconomicData` described below.
Class description:
Implement the BasicTemplateIntrinioEconomicData class.
Method signatures and docstrings:
- def Initialize(self): Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. A... | Implement the Python class `BasicTemplateIntrinioEconomicData` described below.
Class description:
Implement the BasicTemplateIntrinioEconomicData class.
Method signatures and docstrings:
- def Initialize(self): Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. A... | b33dd3bc140e14b883f39ecf848a793cf7292277 | <|skeleton|>
class BasicTemplateIntrinioEconomicData:
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
<|body_0|>
def OnData(self, slice):
"""OnData event is the primary... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicTemplateIntrinioEconomicData:
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
self.SetStartDate(2010, 1, 1)
self.SetEndDate(2013, 12, 31)
self.SetCash(1000... | the_stack_v2_python_sparse | Algorithm.Python/BasicTemplateIntrinioEconomicData.py | Capnode/Algoloop | train | 87 | |
3c7a89fd6c25f688db1b3c9f92e9b02bd5fcad35 | [
"self.ad_special_parameters = ad_special_parameters\nself.exchange_special_parameters = exchange_special_parameters\nself.oracle_special_parameters = oracle_special_parameters\nself.physical_special_parameters = physical_special_parameters\nself.skip_indexing = skip_indexing\nself.source_id = source_id\nself.sql_sp... | <|body_start_0|>
self.ad_special_parameters = ad_special_parameters
self.exchange_special_parameters = exchange_special_parameters
self.oracle_special_parameters = oracle_special_parameters
self.physical_special_parameters = physical_special_parameters
self.skip_indexing = skip_i... | Implementation of the 'SourceSpecialParameter' model. Specifies additional special settings for a single Source in a Protection Job. This Source must be a leaf node in the Source tree. Attributes: ad_special_parameters (ApplicationSpecialParameters): Specifies additional special parameters that are applicable only to P... | SourceSpecialParameter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceSpecialParameter:
"""Implementation of the 'SourceSpecialParameter' model. Specifies additional special settings for a single Source in a Protection Job. This Source must be a leaf node in the Source tree. Attributes: ad_special_parameters (ApplicationSpecialParameters): Specifies additiona... | stack_v2_sparse_classes_36k_train_008758 | 7,702 | permissive | [
{
"docstring": "Constructor for the SourceSpecialParameter class",
"name": "__init__",
"signature": "def __init__(self, ad_special_parameters=None, exchange_special_parameters=None, oracle_special_parameters=None, physical_special_parameters=None, skip_indexing=None, source_id=None, sql_special_paramete... | 2 | null | Implement the Python class `SourceSpecialParameter` described below.
Class description:
Implementation of the 'SourceSpecialParameter' model. Specifies additional special settings for a single Source in a Protection Job. This Source must be a leaf node in the Source tree. Attributes: ad_special_parameters (Application... | Implement the Python class `SourceSpecialParameter` described below.
Class description:
Implementation of the 'SourceSpecialParameter' model. Specifies additional special settings for a single Source in a Protection Job. This Source must be a leaf node in the Source tree. Attributes: ad_special_parameters (Application... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class SourceSpecialParameter:
"""Implementation of the 'SourceSpecialParameter' model. Specifies additional special settings for a single Source in a Protection Job. This Source must be a leaf node in the Source tree. Attributes: ad_special_parameters (ApplicationSpecialParameters): Specifies additiona... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SourceSpecialParameter:
"""Implementation of the 'SourceSpecialParameter' model. Specifies additional special settings for a single Source in a Protection Job. This Source must be a leaf node in the Source tree. Attributes: ad_special_parameters (ApplicationSpecialParameters): Specifies additional special par... | the_stack_v2_python_sparse | cohesity_management_sdk/models/source_special_parameter.py | cohesity/management-sdk-python | train | 24 |
ff067d31886eebc3b3257b088bcb5d86d1d3633a | [
"if not os.path.isfile(_preferencesFilePath):\n Preferences.save(Preferences())\nelse:\n Preferences.get()",
"global _preferences\nif _preferences is None:\n with open(_preferencesFilePath, 'r') as jsonFile:\n json = jsonFile.read()\n persistentContainer = PersistentContainer[Preferences].f... | <|body_start_0|>
if not os.path.isfile(_preferencesFilePath):
Preferences.save(Preferences())
else:
Preferences.get()
<|end_body_0|>
<|body_start_1|>
global _preferences
if _preferences is None:
with open(_preferencesFilePath, 'r') as jsonFile:
... | A description of the persistent preferences that the user should be able to change in the program. | Preferences | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Preferences:
"""A description of the persistent preferences that the user should be able to change in the program."""
def initFile() -> None:
"""Creates the preferences file if it does not exist."""
<|body_0|>
def get() -> 'Preferences':
"""Returns the persistent... | stack_v2_sparse_classes_36k_train_008759 | 2,394 | no_license | [
{
"docstring": "Creates the preferences file if it does not exist.",
"name": "initFile",
"signature": "def initFile() -> None"
},
{
"docstring": "Returns the persistent preferences object. It will be loaded from the disk if that has not already been done.",
"name": "get",
"signature": "d... | 3 | null | Implement the Python class `Preferences` described below.
Class description:
A description of the persistent preferences that the user should be able to change in the program.
Method signatures and docstrings:
- def initFile() -> None: Creates the preferences file if it does not exist.
- def get() -> 'Preferences': R... | Implement the Python class `Preferences` described below.
Class description:
A description of the persistent preferences that the user should be able to change in the program.
Method signatures and docstrings:
- def initFile() -> None: Creates the preferences file if it does not exist.
- def get() -> 'Preferences': R... | 6ec5d6d9e63c34535ef4488acbea47ec2a7ec496 | <|skeleton|>
class Preferences:
"""A description of the persistent preferences that the user should be able to change in the program."""
def initFile() -> None:
"""Creates the preferences file if it does not exist."""
<|body_0|>
def get() -> 'Preferences':
"""Returns the persistent... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Preferences:
"""A description of the persistent preferences that the user should be able to change in the program."""
def initFile() -> None:
"""Creates the preferences file if it does not exist."""
if not os.path.isfile(_preferencesFilePath):
Preferences.save(Preferences())
... | the_stack_v2_python_sparse | frcpredict/ui/preferences.py | TestaLab/Resolution_prediction_software | train | 0 |
57079aded9db70048585b9f3b509c2f89e3e9e11 | [
"send_url = self.get_peizhi_(name='shiming', yaml_ming='yilou_fangdong.yaml')\nsend_url = send_url['bindIdentity']\nlogging.info('url is %s' % send_url)\nsend_dict = {'realName': realName, 'idCard': idCard}\nresponse = self.request_post(base_url=send_url, dict_data=send_dict)\nreturn response",
"send_url = self.g... | <|body_start_0|>
send_url = self.get_peizhi_(name='shiming', yaml_ming='yilou_fangdong.yaml')
send_url = send_url['bindIdentity']
logging.info('url is %s' % send_url)
send_dict = {'realName': realName, 'idCard': idCard}
response = self.request_post(base_url=send_url, dict_data=se... | ShiMing | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShiMing:
def bindIdentity(self, realName, idCard):
"""提交实名认证 :return:"""
<|body_0|>
def getSupportBankList(self):
"""#86、获取支持银行列表 :return:"""
<|body_1|>
def getCardBin(self, bankCardNo):
"""#87、获取银行卡开户行 :return:"""
<|body_2|>
def rea... | stack_v2_sparse_classes_36k_train_008760 | 2,689 | no_license | [
{
"docstring": "提交实名认证 :return:",
"name": "bindIdentity",
"signature": "def bindIdentity(self, realName, idCard)"
},
{
"docstring": "#86、获取支持银行列表 :return:",
"name": "getSupportBankList",
"signature": "def getSupportBankList(self)"
},
{
"docstring": "#87、获取银行卡开户行 :return:",
"n... | 4 | stack_v2_sparse_classes_30k_train_004412 | Implement the Python class `ShiMing` described below.
Class description:
Implement the ShiMing class.
Method signatures and docstrings:
- def bindIdentity(self, realName, idCard): 提交实名认证 :return:
- def getSupportBankList(self): #86、获取支持银行列表 :return:
- def getCardBin(self, bankCardNo): #87、获取银行卡开户行 :return:
- def real... | Implement the Python class `ShiMing` described below.
Class description:
Implement the ShiMing class.
Method signatures and docstrings:
- def bindIdentity(self, realName, idCard): 提交实名认证 :return:
- def getSupportBankList(self): #86、获取支持银行列表 :return:
- def getCardBin(self, bankCardNo): #87、获取银行卡开户行 :return:
- def real... | e173d4e535ac22b72b67371b8a2524ee425cdcbf | <|skeleton|>
class ShiMing:
def bindIdentity(self, realName, idCard):
"""提交实名认证 :return:"""
<|body_0|>
def getSupportBankList(self):
"""#86、获取支持银行列表 :return:"""
<|body_1|>
def getCardBin(self, bankCardNo):
"""#87、获取银行卡开户行 :return:"""
<|body_2|>
def rea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShiMing:
def bindIdentity(self, realName, idCard):
"""提交实名认证 :return:"""
send_url = self.get_peizhi_(name='shiming', yaml_ming='yilou_fangdong.yaml')
send_url = send_url['bindIdentity']
logging.info('url is %s' % send_url)
send_dict = {'realName': realName, 'idCard': id... | the_stack_v2_python_sparse | public/aYiLou_fangdong/yilou_fangdong_business/yilou_fangdong_shiMing.py | GSIL-Monitor/mrbao_python | train | 0 | |
e5ac35471abe7ab422469777481358136a79089f | [
"proxy_ip = IpRedis().random()\nlogger.info('获取了IP: {}'.format(proxy_ip))\nreturn proxy_ip",
"result = IpRedis().delete(ip)\nif result:\n logger.info('删除ip: {}成功'.format(result))\n print('删除ip: {}成功'.format(ip))\nelse:\n print('删除ip: {}失败'.format(ip))"
] | <|body_start_0|>
proxy_ip = IpRedis().random()
logger.info('获取了IP: {}'.format(proxy_ip))
return proxy_ip
<|end_body_0|>
<|body_start_1|>
result = IpRedis().delete(ip)
if result:
logger.info('删除ip: {}成功'.format(result))
print('删除ip: {}成功'.format(ip))
... | IpsPool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IpsPool:
def get_ip_from_pool(cls):
"""从 IP 池获取 IP，没有 IP 则返回空 str :return:"""
<|body_0|>
def delete_ip(cls, ip):
"""从 IP 池删除失效 IP :param ip: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
proxy_ip = IpRedis().random()
logger.info('... | stack_v2_sparse_classes_36k_train_008761 | 2,277 | permissive | [
{
"docstring": "从 IP 池获取 IP，没有 IP 则返回空 str :return:",
"name": "get_ip_from_pool",
"signature": "def get_ip_from_pool(cls)"
},
{
"docstring": "从 IP 池删除失效 IP :param ip: :return:",
"name": "delete_ip",
"signature": "def delete_ip(cls, ip)"
}
] | 2 | null | Implement the Python class `IpsPool` described below.
Class description:
Implement the IpsPool class.
Method signatures and docstrings:
- def get_ip_from_pool(cls): 从 IP 池获取 IP，没有 IP 则返回空 str :return:
- def delete_ip(cls, ip): 从 IP 池删除失效 IP :param ip: :return: | Implement the Python class `IpsPool` described below.
Class description:
Implement the IpsPool class.
Method signatures and docstrings:
- def get_ip_from_pool(cls): 从 IP 池获取 IP，没有 IP 则返回空 str :return:
- def delete_ip(cls, ip): 从 IP 池删除失效 IP :param ip: :return:
<|skeleton|>
class IpsPool:
def get_ip_from_pool(cl... | 29ba13905c73081097df9ef646a5c8194eb024be | <|skeleton|>
class IpsPool:
def get_ip_from_pool(cls):
"""从 IP 池获取 IP，没有 IP 则返回空 str :return:"""
<|body_0|>
def delete_ip(cls, ip):
"""从 IP 池删除失效 IP :param ip: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IpsPool:
def get_ip_from_pool(cls):
"""从 IP 池获取 IP，没有 IP 则返回空 str :return:"""
proxy_ip = IpRedis().random()
logger.info('获取了IP: {}'.format(proxy_ip))
return proxy_ip
def delete_ip(cls, ip):
"""从 IP 池删除失效 IP :param ip: :return:"""
result = IpRedis().delete(i... | the_stack_v2_python_sparse | pyspider/helper/ips_pool.py | UoToGK/crawler-pyspider | train | 0 | |
400d77524b00c0a9275ca1e13dde331d67c20c0d | [
"standard_hmm = HMM.DishonestCasino()\nmissing_hmm = DishonestCasino()\nobservations = [1, 2, 6, 6, 1, 2, 3, 4, 5, 6]\ndistances = [1] * (len(observations) - 1)\nstandard_distributions = standard_hmm.scaled_posterior_durbin(observations)\nmissing_distributions = missing_hmm.scaled_posterior_durbin(observations, dis... | <|body_start_0|>
standard_hmm = HMM.DishonestCasino()
missing_hmm = DishonestCasino()
observations = [1, 2, 6, 6, 1, 2, 3, 4, 5, 6]
distances = [1] * (len(observations) - 1)
standard_distributions = standard_hmm.scaled_posterior_durbin(observations)
missing_distributions ... | TestMissingHMM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMissingHMM:
def test_scaled_posterior_durbin_compatibility(self):
"""Test the missing observation model when no observation is missing."""
<|body_0|>
def test_scaled_posterior_durbin_general(self):
"""This test is not strict but just checks some inequalities."""
... | stack_v2_sparse_classes_36k_train_008762 | 8,288 | no_license | [
{
"docstring": "Test the missing observation model when no observation is missing.",
"name": "test_scaled_posterior_durbin_compatibility",
"signature": "def test_scaled_posterior_durbin_compatibility(self)"
},
{
"docstring": "This test is not strict but just checks some inequalities.",
"name... | 2 | stack_v2_sparse_classes_30k_train_018484 | Implement the Python class `TestMissingHMM` described below.
Class description:
Implement the TestMissingHMM class.
Method signatures and docstrings:
- def test_scaled_posterior_durbin_compatibility(self): Test the missing observation model when no observation is missing.
- def test_scaled_posterior_durbin_general(se... | Implement the Python class `TestMissingHMM` described below.
Class description:
Implement the TestMissingHMM class.
Method signatures and docstrings:
- def test_scaled_posterior_durbin_compatibility(self): Test the missing observation model when no observation is missing.
- def test_scaled_posterior_durbin_general(se... | 91c6f8331f18c914eb3dfc51bc166915998c5081 | <|skeleton|>
class TestMissingHMM:
def test_scaled_posterior_durbin_compatibility(self):
"""Test the missing observation model when no observation is missing."""
<|body_0|>
def test_scaled_posterior_durbin_general(self):
"""This test is not strict but just checks some inequalities."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestMissingHMM:
def test_scaled_posterior_durbin_compatibility(self):
"""Test the missing observation model when no observation is missing."""
standard_hmm = HMM.DishonestCasino()
missing_hmm = DishonestCasino()
observations = [1, 2, 6, 6, 1, 2, 3, 4, 5, 6]
distances = ... | the_stack_v2_python_sparse | MissingHMM.py | argriffing/xgcode | train | 1 | |
8a9c0b68b6eda7ede3d9894e7e0e1fe5fd5d836b | [
"primes = [2, 3, 5, 7, 13, 17, 19, 31]\nfor p in primes:\n euclid = (1 << p - 1) * ((1 << p) - 1)\n if euclid == num:\n break\nreturn euclid == num",
"if num < 1:\n return False\ntotal = 0\nfor i in range(1, int(num ** 0.5) + 1):\n if num % i == 0:\n total += i\n if i * i != num:\... | <|body_start_0|>
primes = [2, 3, 5, 7, 13, 17, 19, 31]
for p in primes:
euclid = (1 << p - 1) * ((1 << p) - 1)
if euclid == num:
break
return euclid == num
<|end_body_0|>
<|body_start_1|>
if num < 1:
return False
total = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkPerfectNumber(self, num):
""":type num: int :rtype: bool Using Euclid-Euler Theorem"""
<|body_0|>
def checkPerfectNumber2(self, num):
""":type num: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
primes = [2, 3, 5... | stack_v2_sparse_classes_36k_train_008763 | 1,214 | no_license | [
{
"docstring": ":type num: int :rtype: bool Using Euclid-Euler Theorem",
"name": "checkPerfectNumber",
"signature": "def checkPerfectNumber(self, num)"
},
{
"docstring": ":type num: int :rtype: bool",
"name": "checkPerfectNumber2",
"signature": "def checkPerfectNumber2(self, num)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPerfectNumber(self, num): :type num: int :rtype: bool Using Euclid-Euler Theorem
- def checkPerfectNumber2(self, num): :type num: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPerfectNumber(self, num): :type num: int :rtype: bool Using Euclid-Euler Theorem
- def checkPerfectNumber2(self, num): :type num: int :rtype: bool
<|skeleton|>
class So... | b7e92f9a7c4d6652d4901b189f51063ce5520653 | <|skeleton|>
class Solution:
def checkPerfectNumber(self, num):
""":type num: int :rtype: bool Using Euclid-Euler Theorem"""
<|body_0|>
def checkPerfectNumber2(self, num):
""":type num: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkPerfectNumber(self, num):
""":type num: int :rtype: bool Using Euclid-Euler Theorem"""
primes = [2, 3, 5, 7, 13, 17, 19, 31]
for p in primes:
euclid = (1 << p - 1) * ((1 << p) - 1)
if euclid == num:
break
return euclid ... | the_stack_v2_python_sparse | leetcode/easy/perfect_number.py | abkunal/Data-Structures-and-Algorithms | train | 2 | |
941d6c1aaeadf5e8da8e2535cdf97cde77c0c2bb | [
"if not leave_id:\n return ({'error': 'mandatory parameter leave_id not supplied'}, 400)\nrequest_payload = request.json\nstatus = request_payload['status']\nprint('making request to leave handler to post attendance')\nleave_handler = LeaveHandler()\nleave_handler.post_leave_status_admin(leave_id, status)",
"i... | <|body_start_0|>
if not leave_id:
return ({'error': 'mandatory parameter leave_id not supplied'}, 400)
request_payload = request.json
status = request_payload['status']
print('making request to leave handler to post attendance')
leave_handler = LeaveHandler()
... | ManageLeavesAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageLeavesAdmin:
def post(self, leave_id):
"""updates the status of the leave given the leave id Param: leave_id: Leave id. Request: path: api/v0/employeeleavestatus/ body: { "status": "Approved" }, accept: application/json Response: return None, 201 content-type: application/json"""
... | stack_v2_sparse_classes_36k_train_008764 | 6,574 | no_license | [
{
"docstring": "updates the status of the leave given the leave id Param: leave_id: Leave id. Request: path: api/v0/employeeleavestatus/ body: { \"status\": \"Approved\" }, accept: application/json Response: return None, 201 content-type: application/json",
"name": "post",
"signature": "def post(self, l... | 2 | stack_v2_sparse_classes_30k_train_010542 | Implement the Python class `ManageLeavesAdmin` described below.
Class description:
Implement the ManageLeavesAdmin class.
Method signatures and docstrings:
- def post(self, leave_id): updates the status of the leave given the leave id Param: leave_id: Leave id. Request: path: api/v0/employeeleavestatus/ body: { "stat... | Implement the Python class `ManageLeavesAdmin` described below.
Class description:
Implement the ManageLeavesAdmin class.
Method signatures and docstrings:
- def post(self, leave_id): updates the status of the leave given the leave id Param: leave_id: Leave id. Request: path: api/v0/employeeleavestatus/ body: { "stat... | cb990525bb9da7fef1e82735ea5ca6f5ad67825a | <|skeleton|>
class ManageLeavesAdmin:
def post(self, leave_id):
"""updates the status of the leave given the leave id Param: leave_id: Leave id. Request: path: api/v0/employeeleavestatus/ body: { "status": "Approved" }, accept: application/json Response: return None, 201 content-type: application/json"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManageLeavesAdmin:
def post(self, leave_id):
"""updates the status of the leave given the leave id Param: leave_id: Leave id. Request: path: api/v0/employeeleavestatus/ body: { "status": "Approved" }, accept: application/json Response: return None, 201 content-type: application/json"""
if not ... | the_stack_v2_python_sparse | server/services/leave_management/leave_controller.py | goel-aman/Erp-Backend-Code | train | 0 | |
02e96b51e6c1bfd0b359bfd004c0ff81e9fefdde | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Chat()",
"from .chat_message import ChatMessage\nfrom .chat_message_info import ChatMessageInfo\nfrom .chat_type import ChatType\nfrom .chat_viewpoint import ChatViewpoint\nfrom .conversation_member import ConversationMember\nfrom .ent... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Chat()
<|end_body_0|>
<|body_start_1|>
from .chat_message import ChatMessage
from .chat_message_info import ChatMessageInfo
from .chat_type import ChatType
from .chat_vie... | Chat | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chat:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Chat:
"""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: Chat"""
... | stack_v2_sparse_classes_36k_train_008765 | 8,255 | 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: Chat",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse_no... | 3 | null | Implement the Python class `Chat` described below.
Class description:
Implement the Chat class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Chat: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pars... | Implement the Python class `Chat` described below.
Class description:
Implement the Chat class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Chat: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pars... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Chat:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Chat:
"""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: Chat"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Chat:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Chat:
"""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: Chat"""
if not parse_n... | the_stack_v2_python_sparse | msgraph/generated/models/chat.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
64867d083bf89ee7e67b2eadce667609eaab2f1e | [
"super(StActiveButton, self).__init__(parent)\nself.algoEngine = algoEngine\nself.spreadName = spreadName\nself.active = False\nself.setStopped()\nself.clicked.connect(self.buttonClicked)",
"if self.active:\n self.stop()\nelse:\n self.start()",
"algoActive = self.algoEngine.stopAlgo(self.spreadName)\nif n... | <|body_start_0|>
super(StActiveButton, self).__init__(parent)
self.algoEngine = algoEngine
self.spreadName = spreadName
self.active = False
self.setStopped()
self.clicked.connect(self.buttonClicked)
<|end_body_0|>
<|body_start_1|>
if self.active:
self... | StActiveButton | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StActiveButton:
def __init__(self, algoEngine, spreadName, parent=None):
"""Constructor"""
<|body_0|>
def buttonClicked(self):
"""改变运行模式"""
<|body_1|>
def stop(self):
"""停止"""
<|body_2|>
def start(self):
"""启动"""
<|bo... | stack_v2_sparse_classes_36k_train_008766 | 22,428 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, algoEngine, spreadName, parent=None)"
},
{
"docstring": "改变运行模式",
"name": "buttonClicked",
"signature": "def buttonClicked(self)"
},
{
"docstring": "停止",
"name": "stop",
"signature": "def s... | 6 | stack_v2_sparse_classes_30k_train_000930 | Implement the Python class `StActiveButton` described below.
Class description:
Implement the StActiveButton class.
Method signatures and docstrings:
- def __init__(self, algoEngine, spreadName, parent=None): Constructor
- def buttonClicked(self): 改变运行模式
- def stop(self): 停止
- def start(self): 启动
- def setStarted(sel... | Implement the Python class `StActiveButton` described below.
Class description:
Implement the StActiveButton class.
Method signatures and docstrings:
- def __init__(self, algoEngine, spreadName, parent=None): Constructor
- def buttonClicked(self): 改变运行模式
- def stop(self): 停止
- def start(self): 启动
- def setStarted(sel... | 75f95a00e7eb569cb7cc530ea55d6646ba4595c1 | <|skeleton|>
class StActiveButton:
def __init__(self, algoEngine, spreadName, parent=None):
"""Constructor"""
<|body_0|>
def buttonClicked(self):
"""改变运行模式"""
<|body_1|>
def stop(self):
"""停止"""
<|body_2|>
def start(self):
"""启动"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StActiveButton:
def __init__(self, algoEngine, spreadName, parent=None):
"""Constructor"""
super(StActiveButton, self).__init__(parent)
self.algoEngine = algoEngine
self.spreadName = spreadName
self.active = False
self.setStopped()
self.clicked.connect(s... | the_stack_v2_python_sparse | vnpy/trader/app/spreadTrading/uiStWidget.py | KilimanjaroFreeman/vnpy | train | 3 | |
bd57c8c3a2954ec8ce319dc67205c2a7e27456fb | [
"from scenable.outsourcing.apitools.facebook import OIP_APP_ID, OIP_APP_SECRET, OIP_ACCESS_TOKEN\ntoken = get_basic_access_token(OIP_APP_ID, OIP_APP_SECRET)\nself.assertEquals(token, OIP_ACCESS_TOKEN)",
"page = facebook_client.graph_api_objects_request('40796308305')\nself.assertEquals(page['name'], 'Coca-Cola')\... | <|body_start_0|>
from scenable.outsourcing.apitools.facebook import OIP_APP_ID, OIP_APP_SECRET, OIP_ACCESS_TOKEN
token = get_basic_access_token(OIP_APP_ID, OIP_APP_SECRET)
self.assertEquals(token, OIP_ACCESS_TOKEN)
<|end_body_0|>
<|body_start_1|>
page = facebook_client.graph_api_objects... | FacebookGraphTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FacebookGraphTest:
def test_basic_access_token(self):
"""Tests basic access token retrieval"""
<|body_0|>
def test_graph_lookup(self):
"""Tests simple object lookup"""
<|body_1|>
def test_page_lookup(self):
"""Tests lookup of Facebook pages speci... | stack_v2_sparse_classes_36k_train_008767 | 18,595 | no_license | [
{
"docstring": "Tests basic access token retrieval",
"name": "test_basic_access_token",
"signature": "def test_basic_access_token(self)"
},
{
"docstring": "Tests simple object lookup",
"name": "test_graph_lookup",
"signature": "def test_graph_lookup(self)"
},
{
"docstring": "Test... | 5 | stack_v2_sparse_classes_30k_train_018916 | Implement the Python class `FacebookGraphTest` described below.
Class description:
Implement the FacebookGraphTest class.
Method signatures and docstrings:
- def test_basic_access_token(self): Tests basic access token retrieval
- def test_graph_lookup(self): Tests simple object lookup
- def test_page_lookup(self): Te... | Implement the Python class `FacebookGraphTest` described below.
Class description:
Implement the FacebookGraphTest class.
Method signatures and docstrings:
- def test_basic_access_token(self): Tests basic access token retrieval
- def test_graph_lookup(self): Tests simple object lookup
- def test_page_lookup(self): Te... | 3ed85e856a026001a1d91d09d31d944c64704824 | <|skeleton|>
class FacebookGraphTest:
def test_basic_access_token(self):
"""Tests basic access token retrieval"""
<|body_0|>
def test_graph_lookup(self):
"""Tests simple object lookup"""
<|body_1|>
def test_page_lookup(self):
"""Tests lookup of Facebook pages speci... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FacebookGraphTest:
def test_basic_access_token(self):
"""Tests basic access token retrieval"""
from scenable.outsourcing.apitools.facebook import OIP_APP_ID, OIP_APP_SECRET, OIP_ACCESS_TOKEN
token = get_basic_access_token(OIP_APP_ID, OIP_APP_SECRET)
self.assertEquals(token, OIP... | the_stack_v2_python_sparse | scenable/outsourcing/apitools/tests.py | gregarious/betasite | train | 0 | |
47d40916c55d0e12da8e7b95d58142117823a9ef | [
"assert self.query.can_filter(), 'Cannot use \"limit\" or \"offset\" with delete.'\nself.update(deleted=timezone.now())\nself._result_cache = None",
"assert self.query.can_filter(), 'Cannot use \"limit\" or \"offset\" with undelete.'\nobj: 'SoftDeletableModel'\nfor obj in self.all():\n obj.undelete()\nself._re... | <|body_start_0|>
assert self.query.can_filter(), 'Cannot use "limit" or "offset" with delete.'
self.update(deleted=timezone.now())
self._result_cache = None
<|end_body_0|>
<|body_start_1|>
assert self.query.can_filter(), 'Cannot use "limit" or "offset" with undelete.'
obj: 'Soft... | Default queryset for the SoftDeletableManager. Takes care of "lazily evaluating" safedelete QuerySets. QuerySets passed within the ``SoftDeletableQuerySet`` will have all of the models available. The deleted policy is evaluated at the very end of the chain when the QuerySet itself is evaluated. | SoftDeletableQuerySet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftDeletableQuerySet:
"""Default queryset for the SoftDeletableManager. Takes care of "lazily evaluating" safedelete QuerySets. QuerySets passed within the ``SoftDeletableQuerySet`` will have all of the models available. The deleted policy is evaluated at the very end of the chain when the Query... | stack_v2_sparse_classes_36k_train_008768 | 1,240 | no_license | [
{
"docstring": "Override bulk delete behavior.",
"name": "delete",
"signature": "def delete(self)"
},
{
"docstring": "Undelete soft-deleted instances.",
"name": "undelete",
"signature": "def undelete(self)"
}
] | 2 | null | Implement the Python class `SoftDeletableQuerySet` described below.
Class description:
Default queryset for the SoftDeletableManager. Takes care of "lazily evaluating" safedelete QuerySets. QuerySets passed within the ``SoftDeletableQuerySet`` will have all of the models available. The deleted policy is evaluated at t... | Implement the Python class `SoftDeletableQuerySet` described below.
Class description:
Default queryset for the SoftDeletableManager. Takes care of "lazily evaluating" safedelete QuerySets. QuerySets passed within the ``SoftDeletableQuerySet`` will have all of the models available. The deleted policy is evaluated at t... | 8bbdc8eec3622af22c17214051c34e36bea8e05a | <|skeleton|>
class SoftDeletableQuerySet:
"""Default queryset for the SoftDeletableManager. Takes care of "lazily evaluating" safedelete QuerySets. QuerySets passed within the ``SoftDeletableQuerySet`` will have all of the models available. The deleted policy is evaluated at the very end of the chain when the Query... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SoftDeletableQuerySet:
"""Default queryset for the SoftDeletableManager. Takes care of "lazily evaluating" safedelete QuerySets. QuerySets passed within the ``SoftDeletableQuerySet`` will have all of the models available. The deleted policy is evaluated at the very end of the chain when the QuerySet itself is... | the_stack_v2_python_sparse | core/models/soft_deletable/queryset.py | abdulwahed-mansour/modularhistory | train | 1 |
46474149d71f81d4a62389852ac87a43ffefb761 | [
"super().__init__()\nself.discriminators = torch.nn.ModuleList()\nfor _ in range(scales):\n self.discriminators += [MelGANDiscriminator(in_channels=in_channels, out_channels=out_channels, kernel_sizes=kernel_sizes, channels=channels, max_downsample_channels=max_downsample_channels, bias=bias, downsample_scales=d... | <|body_start_0|>
super().__init__()
self.discriminators = torch.nn.ModuleList()
for _ in range(scales):
self.discriminators += [MelGANDiscriminator(in_channels=in_channels, out_channels=out_channels, kernel_sizes=kernel_sizes, channels=channels, max_downsample_channels=max_downsample... | MelGAN multi-scale discriminator module. | MelGANMultiScaleDiscriminator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MelGANMultiScaleDiscriminator:
"""MelGAN multi-scale discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, scales: int=3, downsample_pooling: str='AvgPool1d', downsample_pooling_params: Dict[str, Any]={'kernel_size': 4, 'stride': 2, 'padding': 1, 'count_include... | stack_v2_sparse_classes_36k_train_008769 | 16,694 | permissive | [
{
"docstring": "Initilize MelGANMultiScaleDiscriminator module. Args: in_channels (int): Number of input channels. out_channels (int): Number of output channels. scales (int): Number of multi-scales. downsample_pooling (str): Pooling module name for downsampling of the inputs. downsample_pooling_params (Dict[st... | 5 | null | Implement the Python class `MelGANMultiScaleDiscriminator` described below.
Class description:
MelGAN multi-scale discriminator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=1, out_channels: int=1, scales: int=3, downsample_pooling: str='AvgPool1d', downsample_pooling_params: Dict[st... | Implement the Python class `MelGANMultiScaleDiscriminator` described below.
Class description:
MelGAN multi-scale discriminator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=1, out_channels: int=1, scales: int=3, downsample_pooling: str='AvgPool1d', downsample_pooling_params: Dict[st... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class MelGANMultiScaleDiscriminator:
"""MelGAN multi-scale discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, scales: int=3, downsample_pooling: str='AvgPool1d', downsample_pooling_params: Dict[str, Any]={'kernel_size': 4, 'stride': 2, 'padding': 1, 'count_include... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MelGANMultiScaleDiscriminator:
"""MelGAN multi-scale discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, scales: int=3, downsample_pooling: str='AvgPool1d', downsample_pooling_params: Dict[str, Any]={'kernel_size': 4, 'stride': 2, 'padding': 1, 'count_include_pad': False}... | the_stack_v2_python_sparse | espnet2/gan_tts/melgan/melgan.py | espnet/espnet | train | 7,242 |
54d5568e4f3f0f0d9d9292dd085a54cd3347496b | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn MailboxSettings()",
"from .automatic_replies_setting import AutomaticRepliesSetting\nfrom .delegate_meeting_message_delivery_options import DelegateMeetingMessageDeliveryOptions\nfrom .locale_info import LocaleInfo\nfrom .user_purpose ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return MailboxSettings()
<|end_body_0|>
<|body_start_1|>
from .automatic_replies_setting import AutomaticRepliesSetting
from .delegate_meeting_message_delivery_options import DelegateMeetingMes... | MailboxSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailboxSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailboxSettings:
"""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 Ret... | stack_v2_sparse_classes_36k_train_008770 | 6,262 | 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: MailboxSettings",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_val... | 3 | null | Implement the Python class `MailboxSettings` described below.
Class description:
Implement the MailboxSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailboxSettings: Creates a new instance of the appropriate class based on discriminator... | Implement the Python class `MailboxSettings` described below.
Class description:
Implement the MailboxSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailboxSettings: Creates a new instance of the appropriate class based on discriminator... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class MailboxSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailboxSettings:
"""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 Ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MailboxSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MailboxSettings:
"""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: MailboxS... | the_stack_v2_python_sparse | msgraph/generated/models/mailbox_settings.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
2478282ff41aa45808b3bb3778cfaed196131c82 | [
"buffer_layers.sort()\nx1, x2 = torch.chunk(x, 2, dim=-1)\nintermediate = []\nfor layer in layers:\n x1, x2 = layer(x1, x2)\n if layer.layer_id in buffer_layers:\n intermediate.extend([x1.detach(), x2.detach()])\nif len(buffer_layers) == 0:\n all_tensors = [x1.detach(), x2.detach()]\nelse:\n inte... | <|body_start_0|>
buffer_layers.sort()
x1, x2 = torch.chunk(x, 2, dim=-1)
intermediate = []
for layer in layers:
x1, x2 = layer(x1, x2)
if layer.layer_id in buffer_layers:
intermediate.extend([x1.detach(), x2.detach()])
if len(buffer_layers)... | Custom Backpropagation function to allow (A) flushing memory in forward and (B) activation recomputation reversibly in backward for gradient calculation. Inspired by https://github.com/RobinBruegger/RevTorch/blob/master/revtorch/revtorch.py | RevBackProp | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RevBackProp:
"""Custom Backpropagation function to allow (A) flushing memory in forward and (B) activation recomputation reversibly in backward for gradient calculation. Inspired by https://github.com/RobinBruegger/RevTorch/blob/master/revtorch/revtorch.py"""
def forward(ctx, x, layers, buff... | stack_v2_sparse_classes_36k_train_008771 | 24,265 | permissive | [
{
"docstring": "Reversible Forward pass. Any intermediate activations from `buffer_layers` are cached in ctx for forward pass. This is not necessary for standard usecases. Each reversible layer implements its own forward pass logic.",
"name": "forward",
"signature": "def forward(ctx, x, layers, buffer_l... | 2 | null | Implement the Python class `RevBackProp` described below.
Class description:
Custom Backpropagation function to allow (A) flushing memory in forward and (B) activation recomputation reversibly in backward for gradient calculation. Inspired by https://github.com/RobinBruegger/RevTorch/blob/master/revtorch/revtorch.py
... | Implement the Python class `RevBackProp` described below.
Class description:
Custom Backpropagation function to allow (A) flushing memory in forward and (B) activation recomputation reversibly in backward for gradient calculation. Inspired by https://github.com/RobinBruegger/RevTorch/blob/master/revtorch/revtorch.py
... | d2ccc44a2c8e5d49bb26187aff42f2abc90aee28 | <|skeleton|>
class RevBackProp:
"""Custom Backpropagation function to allow (A) flushing memory in forward and (B) activation recomputation reversibly in backward for gradient calculation. Inspired by https://github.com/RobinBruegger/RevTorch/blob/master/revtorch/revtorch.py"""
def forward(ctx, x, layers, buff... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RevBackProp:
"""Custom Backpropagation function to allow (A) flushing memory in forward and (B) activation recomputation reversibly in backward for gradient calculation. Inspired by https://github.com/RobinBruegger/RevTorch/blob/master/revtorch/revtorch.py"""
def forward(ctx, x, layers, buffer_layers):
... | the_stack_v2_python_sparse | mmpretrain/models/backbones/revvit.py | open-mmlab/mmpretrain | train | 652 |
0ed958b267af85532573f190a4e1eff18de4b143 | [
"row = 12\nglobal cookies\ncookies = self.cookies\nurl = self.obj.get_value(row, self.obj.get_host()) + self.obj.get_value(row, self.obj.get_urlxpath())\nmethod = self.obj.get_value(row, self.obj.get_method())\ndata = eval(self.obj.get_value(row, self.obj.get_params()))\nobj = RunMain()\nreturnvalue = obj.run_main(... | <|body_start_0|>
row = 12
global cookies
cookies = self.cookies
url = self.obj.get_value(row, self.obj.get_host()) + self.obj.get_value(row, self.obj.get_urlxpath())
method = self.obj.get_value(row, self.obj.get_method())
data = eval(self.obj.get_value(row, self.obj.get_p... | Testaddress | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Testaddress:
def test_case1(self):
"""添加收获地址失败,手机号码错误"""
<|body_0|>
def test_case2(self):
"""添加收获地址失败,联系人输入框为空"""
<|body_1|>
def test_case3(self):
"""添加收获地址成功"""
<|body_2|>
def test_case4(self):
"""查询收货地址"""
<|body_3|... | stack_v2_sparse_classes_36k_train_008772 | 6,275 | no_license | [
{
"docstring": "添加收获地址失败,手机号码错误",
"name": "test_case1",
"signature": "def test_case1(self)"
},
{
"docstring": "添加收获地址失败,联系人输入框为空",
"name": "test_case2",
"signature": "def test_case2(self)"
},
{
"docstring": "添加收获地址成功",
"name": "test_case3",
"signature": "def test_case3(se... | 6 | stack_v2_sparse_classes_30k_train_015164 | Implement the Python class `Testaddress` described below.
Class description:
Implement the Testaddress class.
Method signatures and docstrings:
- def test_case1(self): 添加收获地址失败,手机号码错误
- def test_case2(self): 添加收获地址失败,联系人输入框为空
- def test_case3(self): 添加收获地址成功
- def test_case4(self): 查询收货地址
- def test_case5(self): 修改收货... | Implement the Python class `Testaddress` described below.
Class description:
Implement the Testaddress class.
Method signatures and docstrings:
- def test_case1(self): 添加收获地址失败,手机号码错误
- def test_case2(self): 添加收获地址失败,联系人输入框为空
- def test_case3(self): 添加收获地址成功
- def test_case4(self): 查询收货地址
- def test_case5(self): 修改收货... | f073c1539c4e77fbf093b2fe6b5de6a1c3727e47 | <|skeleton|>
class Testaddress:
def test_case1(self):
"""添加收获地址失败,手机号码错误"""
<|body_0|>
def test_case2(self):
"""添加收获地址失败,联系人输入框为空"""
<|body_1|>
def test_case3(self):
"""添加收获地址成功"""
<|body_2|>
def test_case4(self):
"""查询收货地址"""
<|body_3|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Testaddress:
def test_case1(self):
"""添加收获地址失败,手机号码错误"""
row = 12
global cookies
cookies = self.cookies
url = self.obj.get_value(row, self.obj.get_host()) + self.obj.get_value(row, self.obj.get_urlxpath())
method = self.obj.get_value(row, self.obj.get_method())
... | the_stack_v2_python_sparse | Project/test_res/test_address.py | xiaotiankeyi/portTest | train | 0 | |
24dd6ce784a87b9b85863b4a6b95c022ceaa25cd | [
"self.resolve = resolve\nself.set_default_value_mode(DefaultValue.MemberMethod_Object, 'default')\nself.set_validate_mode(Validate.MemberMethod_ObjectOldNew, 'validate')",
"kind = self.resolve()\nself.set_default_value_mode(DefaultValue.Static, kind)\nreturn kind",
"kind = self.resolve()\nself.set_validate_mode... | <|body_start_0|>
self.resolve = resolve
self.set_default_value_mode(DefaultValue.MemberMethod_Object, 'default')
self.set_validate_mode(Validate.MemberMethod_ObjectOldNew, 'validate')
<|end_body_0|>
<|body_start_1|>
kind = self.resolve()
self.set_default_value_mode(DefaultValue.... | A Subclass which delays resolving the type definition. The first time the value is accessed or modified, the type will be resolved and the forward subclass will behave identically to a normal subclass. | ForwardSubclass | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForwardSubclass:
"""A Subclass which delays resolving the type definition. The first time the value is accessed or modified, the type will be resolved and the forward subclass will behave identically to a normal subclass."""
def __init__(self, resolve):
"""Initialize a ForwardSubclas... | stack_v2_sparse_classes_36k_train_008773 | 3,114 | permissive | [
{
"docstring": "Initialize a ForwardSubclass member. resolve : callable A callable which takes no arguments and returns the type or tuple of types to use for validating the subclass values.",
"name": "__init__",
"signature": "def __init__(self, resolve)"
},
{
"docstring": "Called to retrieve the... | 4 | stack_v2_sparse_classes_30k_train_000542 | Implement the Python class `ForwardSubclass` described below.
Class description:
A Subclass which delays resolving the type definition. The first time the value is accessed or modified, the type will be resolved and the forward subclass will behave identically to a normal subclass.
Method signatures and docstrings:
-... | Implement the Python class `ForwardSubclass` described below.
Class description:
A Subclass which delays resolving the type definition. The first time the value is accessed or modified, the type will be resolved and the forward subclass will behave identically to a normal subclass.
Method signatures and docstrings:
-... | 761a52821d8c77b5718216256963682d11599c1e | <|skeleton|>
class ForwardSubclass:
"""A Subclass which delays resolving the type definition. The first time the value is accessed or modified, the type will be resolved and the forward subclass will behave identically to a normal subclass."""
def __init__(self, resolve):
"""Initialize a ForwardSubclas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ForwardSubclass:
"""A Subclass which delays resolving the type definition. The first time the value is accessed or modified, the type will be resolved and the forward subclass will behave identically to a normal subclass."""
def __init__(self, resolve):
"""Initialize a ForwardSubclass member. res... | the_stack_v2_python_sparse | atom/subclass.py | nucleic/atom | train | 251 |
8491149bed629fec1046aea3520efb29dc71ec5d | [
"issue_id = mr.GetPositiveIntParam('issue_id')\nif not issue_id:\n return {'params': {}, 'notified': [], 'message': 'Cannot proceed without a valid issue ID.'}\ncommenter_id = mr.GetPositiveIntParam('commenter_id')\nomit_ids = [commenter_id]\nhostport = mr.GetParam('hostport')\ndelta_blocker_iids = mr.GetIntList... | <|body_start_0|>
issue_id = mr.GetPositiveIntParam('issue_id')
if not issue_id:
return {'params': {}, 'notified': [], 'message': 'Cannot proceed without a valid issue ID.'}
commenter_id = mr.GetPositiveIntParam('commenter_id')
omit_ids = [commenter_id]
hostport = mr.G... | JSON servlet that notifies appropriate users after a blocking change. | NotifyBlockingChangeTask | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotifyBlockingChangeTask:
"""JSON servlet that notifies appropriate users after a blocking change."""
def HandleRequest(self, mr):
"""Process the task to notify users after an issue blocking change. Args: mr: common information parsed from the HTTP request. Returns: Results dictionar... | stack_v2_sparse_classes_36k_train_008774 | 41,907 | permissive | [
{
"docstring": "Process the task to notify users after an issue blocking change. Args: mr: common information parsed from the HTTP request. Returns: Results dictionary in JSON format which is useful just for debugging. The main goal is the side-effect of sending emails.",
"name": "HandleRequest",
"signa... | 2 | stack_v2_sparse_classes_30k_train_000254 | Implement the Python class `NotifyBlockingChangeTask` described below.
Class description:
JSON servlet that notifies appropriate users after a blocking change.
Method signatures and docstrings:
- def HandleRequest(self, mr): Process the task to notify users after an issue blocking change. Args: mr: common information... | Implement the Python class `NotifyBlockingChangeTask` described below.
Class description:
JSON servlet that notifies appropriate users after a blocking change.
Method signatures and docstrings:
- def HandleRequest(self, mr): Process the task to notify users after an issue blocking change. Args: mr: common information... | b5d4783f99461438ca9e6a477535617fadab6ba3 | <|skeleton|>
class NotifyBlockingChangeTask:
"""JSON servlet that notifies appropriate users after a blocking change."""
def HandleRequest(self, mr):
"""Process the task to notify users after an issue blocking change. Args: mr: common information parsed from the HTTP request. Returns: Results dictionar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotifyBlockingChangeTask:
"""JSON servlet that notifies appropriate users after a blocking change."""
def HandleRequest(self, mr):
"""Process the task to notify users after an issue blocking change. Args: mr: common information parsed from the HTTP request. Returns: Results dictionary in JSON for... | the_stack_v2_python_sparse | appengine/monorail/features/notify.py | xinghun61/infra | train | 2 |
af2510a742a89fc4cb66dead9f3b0e6fff4e0522 | [
"super().__init__(containers=play_screen.get_containers('ENEMY', 'ENTITY'), image=self.sprite_image, start=start, health=Health(400), damage=10)\nself.play_screen = play_screen\nHealthBar(containers=play_screen.everything, health=self.health, size=np.array((580, 30)), start=np.array((320, 45)), border_size=3, color... | <|body_start_0|>
super().__init__(containers=play_screen.get_containers('ENEMY', 'ENTITY'), image=self.sprite_image, start=start, health=Health(400), damage=10)
self.play_screen = play_screen
HealthBar(containers=play_screen.everything, health=self.health, size=np.array((580, 30)), start=np.arra... | The big bad evil guy | Enemy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Enemy:
"""The big bad evil guy"""
def __init__(self, play_screen, start):
"""Creates the enemy"""
<|body_0|>
def new_attack_pattern(self):
"""Switches to a new attack pattern"""
<|body_1|>
def update(self):
"""Updates the enemy"""
<|b... | stack_v2_sparse_classes_36k_train_008775 | 7,992 | no_license | [
{
"docstring": "Creates the enemy",
"name": "__init__",
"signature": "def __init__(self, play_screen, start)"
},
{
"docstring": "Switches to a new attack pattern",
"name": "new_attack_pattern",
"signature": "def new_attack_pattern(self)"
},
{
"docstring": "Updates the enemy",
... | 3 | stack_v2_sparse_classes_30k_train_016414 | Implement the Python class `Enemy` described below.
Class description:
The big bad evil guy
Method signatures and docstrings:
- def __init__(self, play_screen, start): Creates the enemy
- def new_attack_pattern(self): Switches to a new attack pattern
- def update(self): Updates the enemy | Implement the Python class `Enemy` described below.
Class description:
The big bad evil guy
Method signatures and docstrings:
- def __init__(self, play_screen, start): Creates the enemy
- def new_attack_pattern(self): Switches to a new attack pattern
- def update(self): Updates the enemy
<|skeleton|>
class Enemy:
... | 8604a243baeecdd393a54c18bf2ff9e003b4b8a0 | <|skeleton|>
class Enemy:
"""The big bad evil guy"""
def __init__(self, play_screen, start):
"""Creates the enemy"""
<|body_0|>
def new_attack_pattern(self):
"""Switches to a new attack pattern"""
<|body_1|>
def update(self):
"""Updates the enemy"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Enemy:
"""The big bad evil guy"""
def __init__(self, play_screen, start):
"""Creates the enemy"""
super().__init__(containers=play_screen.get_containers('ENEMY', 'ENTITY'), image=self.sprite_image, start=start, health=Health(400), damage=10)
self.play_screen = play_screen
... | the_stack_v2_python_sparse | src/sprite/enemy.py | ZXQYC/random-shooter-game | train | 0 |
dc3d247bb1098d297aad529bf34ae5dfd0af6d33 | [
"new_prop = 'user_prop'\nnew_prop_value = rand_name('new_prop_value')\nimage = self.images_behavior.create_image_via_task()\nresponse = self.images_client.update_image(image.id_, add={new_prop: new_prop_value})\nself.assertEqual(response.status_code, 200)\nupdated_image = response.entity\nself.assertIn(new_prop, up... | <|body_start_0|>
new_prop = 'user_prop'
new_prop_value = rand_name('new_prop_value')
image = self.images_behavior.create_image_via_task()
response = self.images_client.update_image(image.id_, add={new_prop: new_prop_value})
self.assertEqual(response.status_code, 200)
upda... | TestUpdateImagePositive | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that ... | stack_v2_sparse_classes_36k_train_008776 | 6,204 | permissive | [
{
"docstring": "@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that the new property's value is correct",
"name": "test_update_image_add_additional_prope... | 4 | stack_v2_sparse_classes_30k_train_006421 | Implement the Python class `TestUpdateImagePositive` described below.
Class description:
Implement the TestUpdateImagePositive class.
Method signatures and docstrings:
- def test_update_image_add_additional_property(self): @summary: Update image add additional property 1) Create image 2) Update image adding a new pro... | Implement the Python class `TestUpdateImagePositive` described below.
Class description:
Implement the TestUpdateImagePositive class.
Method signatures and docstrings:
- def test_update_image_add_additional_property(self): @summary: Update image add additional property 1) Create image 2) Update image adding a new pro... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that the new proper... | the_stack_v2_python_sparse | cloudroast/images/v2/functional/test_update_image_positive.py | RULCSoft/cloudroast | train | 1 | |
7e7b021142e008e091a4a0ee2db95f13466f2395 | [
"self._plots = 0\nself._filename = filename\nself._x_label = x_label\nself._record_label = record_label\nself._order_by = order_by\nself._heat_map_value = heat_map_value\nself._heat_map_label = heat_map_label\nselector.select = self._update_counter(selector.select)",
"@wraps(select)\ndef inner(population: dict[T,... | <|body_start_0|>
self._plots = 0
self._filename = filename
self._x_label = x_label
self._record_label = record_label
self._order_by = order_by
self._heat_map_value = heat_map_value
self._heat_map_label = heat_map_label
selector.select = self._update_counte... | Plots which molecule records a :class:`.Selector` selects. Examples: *Plotting Which Molecule Records Got Selected* .. testcode:: plotting-which-molecule-records-got-selected import stk # Make a selector. roulette = stk.Roulette(num_batches=10) # Make a population. population = { stk.MoleculeRecord( topology_graph=stk.... | SelectionPlotter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectionPlotter:
"""Plots which molecule records a :class:`.Selector` selects. Examples: *Plotting Which Molecule Records Got Selected* .. testcode:: plotting-which-molecule-records-got-selected import stk # Make a selector. roulette = stk.Roulette(num_batches=10) # Make a population. population... | stack_v2_sparse_classes_36k_train_008777 | 8,429 | permissive | [
{
"docstring": "Parameters: filename: The basename of the files. This means it should not include file extensions. selector: The :class:`.Selector` whose selection of molecule records is plotted. x_label: The label use for the x axis. record_label: A function which takes a :class:`.MoleculeRecord` and its fitne... | 3 | stack_v2_sparse_classes_30k_train_006654 | Implement the Python class `SelectionPlotter` described below.
Class description:
Plots which molecule records a :class:`.Selector` selects. Examples: *Plotting Which Molecule Records Got Selected* .. testcode:: plotting-which-molecule-records-got-selected import stk # Make a selector. roulette = stk.Roulette(num_batc... | Implement the Python class `SelectionPlotter` described below.
Class description:
Plots which molecule records a :class:`.Selector` selects. Examples: *Plotting Which Molecule Records Got Selected* .. testcode:: plotting-which-molecule-records-got-selected import stk # Make a selector. roulette = stk.Roulette(num_batc... | 9242c29dd4b9eb6927c202611d1326c19d73caea | <|skeleton|>
class SelectionPlotter:
"""Plots which molecule records a :class:`.Selector` selects. Examples: *Plotting Which Molecule Records Got Selected* .. testcode:: plotting-which-molecule-records-got-selected import stk # Make a selector. roulette = stk.Roulette(num_batches=10) # Make a population. population... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelectionPlotter:
"""Plots which molecule records a :class:`.Selector` selects. Examples: *Plotting Which Molecule Records Got Selected* .. testcode:: plotting-which-molecule-records-got-selected import stk # Make a selector. roulette = stk.Roulette(num_batches=10) # Make a population. population = { stk.Mole... | the_stack_v2_python_sparse | src/stk/_internal/ea/plotters/selection.py | andrewtarzia/stk | train | 0 |
8cc4518f11ea7ac8b3e59d349cd828e7ce63603c | [
"partner = self.env['res.partner']\nres = super(AccountInvoice, self).onchange_partner_id(inv_type, partner_id, date_invoice, payment_term, partner_bank_id, company_id)\nif inv_type in 'out_invoice':\n acc_partner = partner._find_accounting_partner(partner.browse(partner_id))\n res['value']['wh_src_rate'] = a... | <|body_start_0|>
partner = self.env['res.partner']
res = super(AccountInvoice, self).onchange_partner_id(inv_type, partner_id, date_invoice, payment_term, partner_bank_id, company_id)
if inv_type in 'out_invoice':
acc_partner = partner._find_accounting_partner(partner.browse(partner_... | AccountInvoice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountInvoice:
def onchange_partner_id(self, inv_type, partner_id, date_invoice=False, payment_term=False, partner_bank_id=False, company_id=False):
"""Change invoice information depending of the partner @param type: Invoice type @param partner_id: Partner id of the invoice @param date_... | stack_v2_sparse_classes_36k_train_008778 | 7,789 | no_license | [
{
"docstring": "Change invoice information depending of the partner @param type: Invoice type @param partner_id: Partner id of the invoice @param date_invoice: Date invoice @param payment_term: Payment terms @param partner_bank_id: Partner bank id of the invoice @param company_id: Company id",
"name": "onch... | 5 | null | Implement the Python class `AccountInvoice` described below.
Class description:
Implement the AccountInvoice class.
Method signatures and docstrings:
- def onchange_partner_id(self, inv_type, partner_id, date_invoice=False, payment_term=False, partner_bank_id=False, company_id=False): Change invoice information depen... | Implement the Python class `AccountInvoice` described below.
Class description:
Implement the AccountInvoice class.
Method signatures and docstrings:
- def onchange_partner_id(self, inv_type, partner_id, date_invoice=False, payment_term=False, partner_bank_id=False, company_id=False): Change invoice information depen... | 718327d01e5b4408add58682c5ad1901fa35b450 | <|skeleton|>
class AccountInvoice:
def onchange_partner_id(self, inv_type, partner_id, date_invoice=False, payment_term=False, partner_bank_id=False, company_id=False):
"""Change invoice information depending of the partner @param type: Invoice type @param partner_id: Partner id of the invoice @param date_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountInvoice:
def onchange_partner_id(self, inv_type, partner_id, date_invoice=False, payment_term=False, partner_bank_id=False, company_id=False):
"""Change invoice information depending of the partner @param type: Invoice type @param partner_id: Partner id of the invoice @param date_invoice: Date ... | the_stack_v2_python_sparse | l10n_ve_withholding_src/model/invoice.py | Vauxoo/odoo-venezuela | train | 15 | |
953b784439b97b4ad06572397a978d7cee35867b | [
"people.sort(key=lambda x: (-x[0], x[1]))\noutput = []\nfor p in people:\n output.insert(p[1], p)\nreturn output",
"output = [people[0]]\nfor p in people[1:]:\n index = 0\n count = p[1]\n while index < len(output):\n if p[1] == 0 and p[0] < output[index][0]:\n break\n if p[0] ... | <|body_start_0|>
people.sort(key=lambda x: (-x[0], x[1]))
output = []
for p in people:
output.insert(p[1], p)
return output
<|end_body_0|>
<|body_start_1|>
output = [people[0]]
for p in people[1:]:
index = 0
count = p[1]
wh... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reconstructQueue(self, people):
""":type people: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def reconstructQueue_failed(self, people):
""":type people: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_008779 | 1,891 | no_license | [
{
"docstring": ":type people: List[List[int]] :rtype: List[List[int]]",
"name": "reconstructQueue",
"signature": "def reconstructQueue(self, people)"
},
{
"docstring": ":type people: List[List[int]] :rtype: List[List[int]]",
"name": "reconstructQueue_failed",
"signature": "def reconstruc... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reconstructQueue(self, people): :type people: List[List[int]] :rtype: List[List[int]]
- def reconstructQueue_failed(self, people): :type people: List[List[int]] :rtype: List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reconstructQueue(self, people): :type people: List[List[int]] :rtype: List[List[int]]
- def reconstructQueue_failed(self, people): :type people: List[List[int]] :rtype: List[... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def reconstructQueue(self, people):
""":type people: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def reconstructQueue_failed(self, people):
""":type people: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reconstructQueue(self, people):
""":type people: List[List[int]] :rtype: List[List[int]]"""
people.sort(key=lambda x: (-x[0], x[1]))
output = []
for p in people:
output.insert(p[1], p)
return output
def reconstructQueue_failed(self, people... | the_stack_v2_python_sparse | src/lt_406.py | oxhead/CodingYourWay | train | 0 | |
6e6a50744aad518130f21d5630d0cb7c11dd745f | [
"data = super().to_internal_value(data)\ndata['user'] = self.context['request'].user\nreturn data",
"attrs = super().validate(attrs)\ntry:\n required_args = attrs['required_arguments']\n assert required_args is not None\nexcept (KeyError, AssertionError):\n required_args = []\ntry:\n default_vals = at... | <|body_start_0|>
data = super().to_internal_value(data)
data['user'] = self.context['request'].user
return data
<|end_body_0|>
<|body_start_1|>
attrs = super().validate(attrs)
try:
required_args = attrs['required_arguments']
assert required_args is not No... | A serializer for a task type. | AbstractTaskTypeSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractTaskTypeSerializer:
"""A serializer for a task type."""
def to_internal_value(self, data):
"""Inject the user into validation data. Need to inject it here before the UniqueTogether validator runs. See discussion here: https://stackoverflow.com/questions/27591574/order-of-seri... | stack_v2_sparse_classes_36k_train_008780 | 4,896 | permissive | [
{
"docstring": "Inject the user into validation data. Need to inject it here before the UniqueTogether validator runs. See discussion here: https://stackoverflow.com/questions/27591574/order-of-serializer-validation-in-django-rest-framework.",
"name": "to_internal_value",
"signature": "def to_internal_v... | 2 | stack_v2_sparse_classes_30k_train_001805 | Implement the Python class `AbstractTaskTypeSerializer` described below.
Class description:
A serializer for a task type.
Method signatures and docstrings:
- def to_internal_value(self, data): Inject the user into validation data. Need to inject it here before the UniqueTogether validator runs. See discussion here: h... | Implement the Python class `AbstractTaskTypeSerializer` described below.
Class description:
A serializer for a task type.
Method signatures and docstrings:
- def to_internal_value(self, data): Inject the user into validation data. Need to inject it here before the UniqueTogether validator runs. See discussion here: h... | db498a1186fc74221f8214ad1819dd03bf4b08ac | <|skeleton|>
class AbstractTaskTypeSerializer:
"""A serializer for a task type."""
def to_internal_value(self, data):
"""Inject the user into validation data. Need to inject it here before the UniqueTogether validator runs. See discussion here: https://stackoverflow.com/questions/27591574/order-of-seri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbstractTaskTypeSerializer:
"""A serializer for a task type."""
def to_internal_value(self, data):
"""Inject the user into validation data. Need to inject it here before the UniqueTogether validator runs. See discussion here: https://stackoverflow.com/questions/27591574/order-of-serializer-valida... | the_stack_v2_python_sparse | tasksapi/serializers/abstract_tasks.py | saltant-org/saltant | train | 3 |
c1455c78dc7a1a22b2f2328125a649df0bf37ec8 | [
"assert isinstance(orientations, list), 'orientations must be a list'\nself.imsize = IMAGE_SIZE\nself.orientations = orientations\nself.nblocks = nblocks\nself.padding = PIX_PAD\nself.createGabors()\nself.nfeatures = len(self.Gabors) * pow(self.nblocks, 2)",
"self.total_size = self.imsize + 2 * self.padding\nself... | <|body_start_0|>
assert isinstance(orientations, list), 'orientations must be a list'
self.imsize = IMAGE_SIZE
self.orientations = orientations
self.nblocks = nblocks
self.padding = PIX_PAD
self.createGabors()
self.nfeatures = len(self.Gabors) * pow(self.nblocks, ... | Gist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Gist:
def __init__(self, orientations, nblocks):
"""Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list"""
<... | stack_v2_sparse_classes_36k_train_008781 | 4,223 | no_license | [
{
"docstring": "Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list",
"name": "__init__",
"signature": "def __init__(self, orientati... | 3 | null | Implement the Python class `Gist` described below.
Class description:
Implement the Gist class.
Method signatures and docstrings:
- def __init__(self, orientations, nblocks): Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a gr... | Implement the Python class `Gist` described below.
Class description:
Implement the Gist class.
Method signatures and docstrings:
- def __init__(self, orientations, nblocks): Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a gr... | 2f9c33c4e1a26b3e9e699210ac974047936f49e1 | <|skeleton|>
class Gist:
def __init__(self, orientations, nblocks):
"""Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Gist:
def __init__(self, orientations, nblocks):
"""Creates an object type Gist Args: orientations: a list of number of orientations at each scale nblocks: number of blocks considered to for a grid and compute the gist Assertions: AssertionError if orientations is not a list"""
assert isinstan... | the_stack_v2_python_sparse | vision/utils/gist.py | winkash/image-classification | train | 0 | |
d71368117861e3ff97d5936e9e363f1e4234c5e8 | [
"listr = Theme.objects.all()\nresponse = self.serializer(listr, many=True)\nreturn Response(response.data, status=status.HTTP_200_OK)",
"response = self.serializer(data=request.data)\nif response.is_valid():\n response.save()\n return Response(response.data, status=status.HTTP_201_CREATED)\nreturn Response(... | <|body_start_0|>
listr = Theme.objects.all()
response = self.serializer(listr, many=True)
return Response(response.data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
response = self.serializer(data=request.data)
if response.is_valid():
response.save()
... | ... | VThemeList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VThemeList:
"""..."""
def get(self, request, format=None):
"""..."""
<|body_0|>
def post(self, request, format=None):
"""..."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
listr = Theme.objects.all()
response = self.serializer(listr, ma... | stack_v2_sparse_classes_36k_train_008782 | 2,319 | permissive | [
{
"docstring": "...",
"name": "get",
"signature": "def get(self, request, format=None)"
},
{
"docstring": "...",
"name": "post",
"signature": "def post(self, request, format=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021436 | Implement the Python class `VThemeList` described below.
Class description:
...
Method signatures and docstrings:
- def get(self, request, format=None): ...
- def post(self, request, format=None): ... | Implement the Python class `VThemeList` described below.
Class description:
...
Method signatures and docstrings:
- def get(self, request, format=None): ...
- def post(self, request, format=None): ...
<|skeleton|>
class VThemeList:
"""..."""
def get(self, request, format=None):
"""..."""
<|b... | 660664ba2321499e92c3c5c23719756db2569e90 | <|skeleton|>
class VThemeList:
"""..."""
def get(self, request, format=None):
"""..."""
<|body_0|>
def post(self, request, format=None):
"""..."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VThemeList:
"""..."""
def get(self, request, format=None):
"""..."""
listr = Theme.objects.all()
response = self.serializer(listr, many=True)
return Response(response.data, status=status.HTTP_200_OK)
def post(self, request, format=None):
"""..."""
resp... | the_stack_v2_python_sparse | apps/theme/views/vtheme.py | magocod/djrepo | train | 1 |
d63e24a12e3ce0c526f90de101e66f3dbfba1a80 | [
"res = []\n\ndef dfs(node):\n if not node:\n return\n res.append(str(node.val))\n res.append(str(len(node.children or [])))\n if node.children:\n for child in node.children:\n dfs(child)\ndfs(root)\nreturn '#'.join(res)",
"if not data:\n return None\ndata = iter(data.split(... | <|body_start_0|>
res = []
def dfs(node):
if not node:
return
res.append(str(node.val))
res.append(str(len(node.children or [])))
if node.children:
for child in node.children:
dfs(child)
dfs(root)... | Codec1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec1:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_008783 | 4,054 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root: 'Node') -> str"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def des... | 2 | null | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to t... | Implement the Python class `Codec1` described below.
Class description:
Implement the Codec1 class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to t... | 44765a7d89423b7ec2c159f70b1a6f6e446523c2 | <|skeleton|>
class Codec1:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec1:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
res = []
def dfs(node):
if not node:
return
res.append(str(node.val))
res.append(str(len(node.children or [])))
... | the_stack_v2_python_sparse | python/_0001_0500/0428_serialize-and-deserialize-n-ary-tree.py | Wang-Yann/LeetCodeMe | train | 0 | |
0a50c471dda1461ffec90695bffdab74c93cd428 | [
"self._differ = difflib.Differ()\nself._left_class = left_class\nself._right_class = right_class",
"left = []\nright = []\nleft_open = False\nright_open = False\nfor atom in self._differ.compare(s1, s2):\n if atom.startswith(' ') or atom.startswith('? '):\n if left_open:\n left.append('</spa... | <|body_start_0|>
self._differ = difflib.Differ()
self._left_class = left_class
self._right_class = right_class
<|end_body_0|>
<|body_start_1|>
left = []
right = []
left_open = False
right_open = False
for atom in self._differ.compare(s1, s2):
... | HTMLDiffer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTMLDiffer:
def __init__(self, left_class, right_class):
"""Args: left_class: the css class to use from strings unique to the left side right_class: the css class to use from strings unique to the right side"""
<|body_0|>
def Diff(self, s1, s2):
"""Returns html for t... | stack_v2_sparse_classes_36k_train_008784 | 2,181 | no_license | [
{
"docstring": "Args: left_class: the css class to use from strings unique to the left side right_class: the css class to use from strings unique to the right side",
"name": "__init__",
"signature": "def __init__(self, left_class, right_class)"
},
{
"docstring": "Returns html for the diff of s1 ... | 2 | stack_v2_sparse_classes_30k_train_000035 | Implement the Python class `HTMLDiffer` described below.
Class description:
Implement the HTMLDiffer class.
Method signatures and docstrings:
- def __init__(self, left_class, right_class): Args: left_class: the css class to use from strings unique to the left side right_class: the css class to use from strings unique... | Implement the Python class `HTMLDiffer` described below.
Class description:
Implement the HTMLDiffer class.
Method signatures and docstrings:
- def __init__(self, left_class, right_class): Args: left_class: the css class to use from strings unique to the left side right_class: the css class to use from strings unique... | 2ce85d05eaba735a8ed2c63a26852dcab8bfd643 | <|skeleton|>
class HTMLDiffer:
def __init__(self, left_class, right_class):
"""Args: left_class: the css class to use from strings unique to the left side right_class: the css class to use from strings unique to the right side"""
<|body_0|>
def Diff(self, s1, s2):
"""Returns html for t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HTMLDiffer:
def __init__(self, left_class, right_class):
"""Args: left_class: the css class to use from strings unique to the left side right_class: the css class to use from strings unique to the right side"""
self._differ = difflib.Differ()
self._left_class = left_class
self.... | the_stack_v2_python_sparse | html_differ.py | OpenLightingProject/rdm-app | train | 15 | |
6382e1be7ae5ed612e42b5b8e5af541a421454f3 | [
"context = super().get_context_data(*args, **kwargs)\ncontext['listing'] = self.object\ncontext['listing_tags'] = context['listing'].tags.all()\nall_tags = models.shopify_models.ShopifyTag.objects.all()\ntag_groups = defaultdict(list)\nfor tag in all_tags:\n tag_groups[tag.name[0]].append(tag)\ncontext['tag_grou... | <|body_start_0|>
context = super().get_context_data(*args, **kwargs)
context['listing'] = self.object
context['listing_tags'] = context['listing'].tags.all()
all_tags = models.shopify_models.ShopifyTag.objects.all()
tag_groups = defaultdict(list)
for tag in all_tags:
... | View for setting Shopify tags. | UpdateShopifyTags | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateShopifyTags:
"""View for setting Shopify tags."""
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
<|body_0|>
def get_success_url(self):
"""Return redirect URL."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_008785 | 11,297 | no_license | [
{
"docstring": "Return context for the template.",
"name": "get_context_data",
"signature": "def get_context_data(self, *args, **kwargs)"
},
{
"docstring": "Return redirect URL.",
"name": "get_success_url",
"signature": "def get_success_url(self)"
}
] | 2 | null | Implement the Python class `UpdateShopifyTags` described below.
Class description:
View for setting Shopify tags.
Method signatures and docstrings:
- def get_context_data(self, *args, **kwargs): Return context for the template.
- def get_success_url(self): Return redirect URL. | Implement the Python class `UpdateShopifyTags` described below.
Class description:
View for setting Shopify tags.
Method signatures and docstrings:
- def get_context_data(self, *args, **kwargs): Return context for the template.
- def get_success_url(self): Return redirect URL.
<|skeleton|>
class UpdateShopifyTags:
... | ba51d4e304b1aeb296fa2fe16611c892fcdbd471 | <|skeleton|>
class UpdateShopifyTags:
"""View for setting Shopify tags."""
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
<|body_0|>
def get_success_url(self):
"""Return redirect URL."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateShopifyTags:
"""View for setting Shopify tags."""
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
context = super().get_context_data(*args, **kwargs)
context['listing'] = self.object
context['listing_tags'] = context['listing'].tag... | the_stack_v2_python_sparse | channels/views.py | stcstores/stcadmin | train | 0 |
a08d1209f461ef8e5d4072797befe8b199e6a847 | [
"self.tweets = dict()\nself.recentTweets = dict()\nself.followedBy = dict()\nself.timeCnt = 0\nself.userSet = set()",
"if userId not in self.userSet:\n self.userSet.add(userId)\nif userId not in self.recentTweets:\n self.recentTweets[userId] = []\nif userId not in self.followedBy:\n self.followedBy[userI... | <|body_start_0|>
self.tweets = dict()
self.recentTweets = dict()
self.followedBy = dict()
self.timeCnt = 0
self.userSet = set()
<|end_body_0|>
<|body_start_1|>
if userId not in self.userSet:
self.userSet.add(userId)
if userId not in self.recentTweets:... | Twitter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k_train_008786 | 4,789 | permissive | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet. :type userId: int :type tweetId: int :rtype: void",
"name": "postTweet",
"signature": "def postTweet(self, userId, tweetId)"
},
{
"... | 5 | null | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | 6c547c338eb05042cb68f57f737dce483964e2fd | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.tweets = dict()
self.recentTweets = dict()
self.followedBy = dict()
self.timeCnt = 0
self.userSet = set()
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :typ... | the_stack_v2_python_sparse | Q355DesignTwitter.py | ChenliangLi205/LeetCode | train | 0 | |
f615cf74412040847de5f243e9d488fb6440a8b0 | [
"self.new_inv_item = ['1', 'Knife Set', 10, 'n', 'n']\nself.new_furn_item = ['2', 'Couch', 25, 'y', 'Cloth', 'L']\nself.new_elec_item = ['3', 'Dryer', 100, 'n', 'y', 'Samsung', 12]",
"m.FULL_INVENTORY = {}\nwith patch('builtins.input', side_effect=self.new_inv_item):\n with patch('inventory_management.market_p... | <|body_start_0|>
self.new_inv_item = ['1', 'Knife Set', 10, 'n', 'n']
self.new_furn_item = ['2', 'Couch', 25, 'y', 'Cloth', 'L']
self.new_elec_item = ['3', 'Dryer', 100, 'n', 'y', 'Samsung', 12]
<|end_body_0|>
<|body_start_1|>
m.FULL_INVENTORY = {}
with patch('builtins.input', s... | Perform integration tests inventory_management package. | IntegrationTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IntegrationTests:
"""Perform integration tests inventory_management package."""
def setUp(self):
"""Peform setup of tests."""
<|body_0|>
def test_integration(self):
"""Test all modules together."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
se... | stack_v2_sparse_classes_36k_train_008787 | 4,548 | no_license | [
{
"docstring": "Peform setup of tests.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test all modules together.",
"name": "test_integration",
"signature": "def test_integration(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000088 | Implement the Python class `IntegrationTests` described below.
Class description:
Perform integration tests inventory_management package.
Method signatures and docstrings:
- def setUp(self): Peform setup of tests.
- def test_integration(self): Test all modules together. | Implement the Python class `IntegrationTests` described below.
Class description:
Perform integration tests inventory_management package.
Method signatures and docstrings:
- def setUp(self): Peform setup of tests.
- def test_integration(self): Test all modules together.
<|skeleton|>
class IntegrationTests:
"""Pe... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class IntegrationTests:
"""Perform integration tests inventory_management package."""
def setUp(self):
"""Peform setup of tests."""
<|body_0|>
def test_integration(self):
"""Test all modules together."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IntegrationTests:
"""Perform integration tests inventory_management package."""
def setUp(self):
"""Peform setup of tests."""
self.new_inv_item = ['1', 'Knife Set', 10, 'n', 'n']
self.new_furn_item = ['2', 'Couch', 25, 'y', 'Cloth', 'L']
self.new_elec_item = ['3', 'Dryer',... | the_stack_v2_python_sparse | students/Reem_Alqaysi/Lesson_01/test_integration.py | JavaRod/SP_Python220B_2019 | train | 1 |
fc631a2b84532f18a4449a54e9b34a15b1f895b6 | [
"row, col = (len(matrix), len(matrix[0]))\nmatrix.reverse()\nfor i in range(row):\n for j in range(i + 1, col):\n matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])",
"temp = list(zip(*matrix[::-1]))\nN = len(temp)\nfor i in range(N):\n for j in range(N):\n matrix[i][j] = temp[i][j]"
] | <|body_start_0|>
row, col = (len(matrix), len(matrix[0]))
matrix.reverse()
for i in range(row):
for j in range(i + 1, col):
matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])
<|end_body_0|>
<|body_start_1|>
temp = list(zip(*matrix[::-1]))
N = l... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate1(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_008788 | 1,471 | no_license | [
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "rotate",
"signature": "def rotate(self, matrix: List[List[int]]) -> None"
},
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "rotate1",
"signature": "def rotate1(self, mat... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: Do not return anything, modify matrix in-place instead.
- def rotate1(self, matrix: List[List[int]]) -> None: Do not return any... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: Do not return anything, modify matrix in-place instead.
- def rotate1(self, matrix: List[List[int]]) -> None: Do not return any... | b7c59c826bcd17cb1333571eb9f13f5c2b89b4ee | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate1(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead."""
row, col = (len(matrix), len(matrix[0]))
matrix.reverse()
for i in range(row):
for j in range(i + 1, col):
matrix[i][j], matrix... | the_stack_v2_python_sparse | 每日一题/旋转矩阵.py | Asunqingwen/LeetCode | train | 0 | |
515f8e88c6cf560788ce9552bf6387f21702d761 | [
"if not nums:\n return []\nif len(nums) <= k:\n return [max(nums)]\ninit_nums = nums[:k]\nheapq._heapify_max(init_nums)\nresult = [init_nums[0]]\nfor i in range(k, len(nums)):\n result.append(init_nums[0])\nreturn result",
"if not nums:\n return []\nif len(nums) <= k:\n return [max(nums)]\nwindow =... | <|body_start_0|>
if not nums:
return []
if len(nums) <= k:
return [max(nums)]
init_nums = nums[:k]
heapq._heapify_max(init_nums)
result = [init_nums[0]]
for i in range(k, len(nums)):
result.append(init_nums[0])
return result
<|e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""最大堆写法 执行用时 :1572 ms, 在所有 Python3 提交中击败了5.17% 的用户 内存消耗 :20.1 MB, 在所有 Python3 提交中击败了5.39%的用户"""
<|body_0|>
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""双端队列写法, 来自覃超的算... | stack_v2_sparse_classes_36k_train_008789 | 2,614 | no_license | [
{
"docstring": "最大堆写法 执行用时 :1572 ms, 在所有 Python3 提交中击败了5.17% 的用户 内存消耗 :20.1 MB, 在所有 Python3 提交中击败了5.39%的用户",
"name": "maxSlidingWindow",
"signature": "def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]"
},
{
"docstring": "双端队列写法, 来自覃超的算法课 (看不懂代码, 先跑一遍) 执行用时 :216 ms, 在所有 Python3 提交中... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]: 最大堆写法 执行用时 :1572 ms, 在所有 Python3 提交中击败了5.17% 的用户 内存消耗 :20.1 MB, 在所有 Python3 提交中击败了5.39%的用户
- def maxSlidingWindo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]: 最大堆写法 执行用时 :1572 ms, 在所有 Python3 提交中击败了5.17% 的用户 内存消耗 :20.1 MB, 在所有 Python3 提交中击败了5.39%的用户
- def maxSlidingWindo... | 99a3abf1774933af73a8405f9b59e5e64906bca4 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""最大堆写法 执行用时 :1572 ms, 在所有 Python3 提交中击败了5.17% 的用户 内存消耗 :20.1 MB, 在所有 Python3 提交中击败了5.39%的用户"""
<|body_0|>
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""双端队列写法, 来自覃超的算... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]:
"""最大堆写法 执行用时 :1572 ms, 在所有 Python3 提交中击败了5.17% 的用户 内存消耗 :20.1 MB, 在所有 Python3 提交中击败了5.39%的用户"""
if not nums:
return []
if len(nums) <= k:
return [max(nums)]
init_nums = nums[:k]... | the_stack_v2_python_sparse | leetcode/239.sliding-window-maximum.py | iamkissg/leetcode | train | 0 | |
ca716f1deb6911b79e00e20169db93a476e9411a | [
"def tree_to_list(root):\n from collections import deque\n if root == None:\n return []\n ans = []\n q = deque([root])\n while len(q) != 0:\n node = q.popleft()\n ans.append(node.val if node else None)\n if node:\n q.append(node.left)\n q.append(node.... | <|body_start_0|>
def tree_to_list(root):
from collections import deque
if root == None:
return []
ans = []
q = deque([root])
while len(q) != 0:
node = q.popleft()
ans.append(node.val if node else None)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: stra :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_008790 | 1,924 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: stra :rtype: TreeNode",
"name": "deserialize",
"signature": "def deseriali... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: stra :rtype... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: stra :rtype... | 48ba21799f63225c104f649c3871444a29ab978a | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: stra :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def tree_to_list(root):
from collections import deque
if root == None:
return []
ans = []
q = deque([root])
wh... | the_stack_v2_python_sparse | archive/449SerializeandDeserializeBST.py | doraemon1293/Leetcode | train | 0 | |
88f02e8874b0e6ab78bd7316645f517884066e40 | [
"username = self.request.user.email\nold_password = form.cleaned_data['old_password']\ncheckCredentialsResult = bsd_api.account_checkCredentials(username, old_password)\nassert_valid_account(checkCredentialsResult)",
"username = self.request.user.email\nnew_password = form.cleaned_data['new_password1']\nsetPasswo... | <|body_start_0|>
username = self.request.user.email
old_password = form.cleaned_data['old_password']
checkCredentialsResult = bsd_api.account_checkCredentials(username, old_password)
assert_valid_account(checkCredentialsResult)
<|end_body_0|>
<|body_start_1|>
username = self.req... | PasswordChangeView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordChangeView:
def check_old_password(self, form):
"""Check if old password is valid in BSD"""
<|body_0|>
def set_new_password(self, form):
"""Set new password in BSD"""
<|body_1|>
def form_valid(self, form):
"""Check old password"""
... | stack_v2_sparse_classes_36k_train_008791 | 26,076 | permissive | [
{
"docstring": "Check if old password is valid in BSD",
"name": "check_old_password",
"signature": "def check_old_password(self, form)"
},
{
"docstring": "Set new password in BSD",
"name": "set_new_password",
"signature": "def set_new_password(self, form)"
},
{
"docstring": "Chec... | 3 | stack_v2_sparse_classes_30k_train_015990 | Implement the Python class `PasswordChangeView` described below.
Class description:
Implement the PasswordChangeView class.
Method signatures and docstrings:
- def check_old_password(self, form): Check if old password is valid in BSD
- def set_new_password(self, form): Set new password in BSD
- def form_valid(self, f... | Implement the Python class `PasswordChangeView` described below.
Class description:
Implement the PasswordChangeView class.
Method signatures and docstrings:
- def check_old_password(self, form): Check if old password is valid in BSD
- def set_new_password(self, form): Set new password in BSD
- def form_valid(self, f... | c8024b805ff5ff0e16f54dce7bf05097fd2f08e0 | <|skeleton|>
class PasswordChangeView:
def check_old_password(self, form):
"""Check if old password is valid in BSD"""
<|body_0|>
def set_new_password(self, form):
"""Set new password in BSD"""
<|body_1|>
def form_valid(self, form):
"""Check old password"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordChangeView:
def check_old_password(self, form):
"""Check if old password is valid in BSD"""
username = self.request.user.email
old_password = form.cleaned_data['old_password']
checkCredentialsResult = bsd_api.account_checkCredentials(username, old_password)
asse... | the_stack_v2_python_sparse | organizing_hub/views/views.py | Our-Revolution/site | train | 4 | |
bd6053f0f6d05ae03b1c9c007ac9b811ca9b19a2 | [
"inf = float('inf')\na = [-inf] + arr + [-inf]\nstack = []\nret = 0\nmod = 10 ** 9 + 7\nfor i in range(len(a)):\n while stack and a[stack[-1]] > a[i]:\n j = stack.pop()\n pre_j = stack[-1]\n ret += a[j] * (i - j) * (j - pre_j)\n stack.append(i)\nreturn ret % mod",
"lt = [0]\na = [0] + a... | <|body_start_0|>
inf = float('inf')
a = [-inf] + arr + [-inf]
stack = []
ret = 0
mod = 10 ** 9 + 7
for i in range(len(a)):
while stack and a[stack[-1]] > a[i]:
j = stack.pop()
pre_j = stack[-1]
ret += a[j] * (i -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sumSubarrayMins(self, arr):
""":type arr: List[int] :rtype: int formula is (i - j) * (j - k) * a[j]. simulate process: add -inf to both end of a -inf, 3, 1, 2, 5, 4, -inf index 0, 1, 2, 3, 4, 5, 6 stack = [0,2,3,5,6] # store index and value of its index are increasing index... | stack_v2_sparse_classes_36k_train_008792 | 4,605 | no_license | [
{
"docstring": ":type arr: List[int] :rtype: int formula is (i - j) * (j - k) * a[j]. simulate process: add -inf to both end of a -inf, 3, 1, 2, 5, 4, -inf index 0, 1, 2, 3, 4, 5, 6 stack = [0,2,3,5,6] # store index and value of its index are increasing index 0, val -inf stack: [0] ------- index 1, val 3 stack:... | 2 | stack_v2_sparse_classes_30k_train_008317 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumSubarrayMins(self, arr): :type arr: List[int] :rtype: int formula is (i - j) * (j - k) * a[j]. simulate process: add -inf to both end of a -inf, 3, 1, 2, 5, 4, -inf index ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumSubarrayMins(self, arr): :type arr: List[int] :rtype: int formula is (i - j) * (j - k) * a[j]. simulate process: add -inf to both end of a -inf, 3, 1, 2, 5, 4, -inf index ... | 02726da394971ef02616a038dadc126c6ff260de | <|skeleton|>
class Solution:
def sumSubarrayMins(self, arr):
""":type arr: List[int] :rtype: int formula is (i - j) * (j - k) * a[j]. simulate process: add -inf to both end of a -inf, 3, 1, 2, 5, 4, -inf index 0, 1, 2, 3, 4, 5, 6 stack = [0,2,3,5,6] # store index and value of its index are increasing index... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sumSubarrayMins(self, arr):
""":type arr: List[int] :rtype: int formula is (i - j) * (j - k) * a[j]. simulate process: add -inf to both end of a -inf, 3, 1, 2, 5, 4, -inf index 0, 1, 2, 3, 4, 5, 6 stack = [0,2,3,5,6] # store index and value of its index are increasing index 0, val -inf s... | the_stack_v2_python_sparse | subarray/N907_SumofSubarrayMinimums.py | zerghua/leetcode-python | train | 2 | |
2c4782d834471e14ae43f7b44749ec4e3854cab1 | [
"result = {}\nfor record in self.browse(cr, uid, ids, context):\n codigo_device = ''\n if record.dispositivo_m2o_id != 0:\n codigo_device = str(record.dispositivo_m2o_id.codigo)\n codigo_store = ''\n if record.sucursal_m2o_id != 0:\n codigo_store = str(record.sucursal_m2o_id.codigo)\n n... | <|body_start_0|>
result = {}
for record in self.browse(cr, uid, ids, context):
codigo_device = ''
if record.dispositivo_m2o_id != 0:
codigo_device = str(record.dispositivo_m2o_id.codigo)
codigo_store = ''
if record.sucursal_m2o_id != 0:
... | hardware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class hardware:
def _functGetKey(self, cr, uid, ids, name, arg, context={}):
"""Funcion que obtiene la clave * Para OpenERP [field.function] * Argumentos OpenERP: [cr, uid, ids, name, arg, context] :return dict"""
<|body_0|>
def onchange_model(self, cr, uid, ids, model):
"... | stack_v2_sparse_classes_36k_train_008793 | 11,110 | no_license | [
{
"docstring": "Funcion que obtiene la clave * Para OpenERP [field.function] * Argumentos OpenERP: [cr, uid, ids, name, arg, context] :return dict",
"name": "_functGetKey",
"signature": "def _functGetKey(self, cr, uid, ids, name, arg, context={})"
},
{
"docstring": "Evento OnChange del campo \"m... | 6 | stack_v2_sparse_classes_30k_train_008459 | Implement the Python class `hardware` described below.
Class description:
Implement the hardware class.
Method signatures and docstrings:
- def _functGetKey(self, cr, uid, ids, name, arg, context={}): Funcion que obtiene la clave * Para OpenERP [field.function] * Argumentos OpenERP: [cr, uid, ids, name, arg, context]... | Implement the Python class `hardware` described below.
Class description:
Implement the hardware class.
Method signatures and docstrings:
- def _functGetKey(self, cr, uid, ids, name, arg, context={}): Funcion que obtiene la clave * Para OpenERP [field.function] * Argumentos OpenERP: [cr, uid, ids, name, arg, context]... | 4d3b5812ed49df8d11a827cf92ba3e102fd8f6e8 | <|skeleton|>
class hardware:
def _functGetKey(self, cr, uid, ids, name, arg, context={}):
"""Funcion que obtiene la clave * Para OpenERP [field.function] * Argumentos OpenERP: [cr, uid, ids, name, arg, context] :return dict"""
<|body_0|>
def onchange_model(self, cr, uid, ids, model):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class hardware:
def _functGetKey(self, cr, uid, ids, name, arg, context={}):
"""Funcion que obtiene la clave * Para OpenERP [field.function] * Argumentos OpenERP: [cr, uid, ids, name, arg, context] :return dict"""
result = {}
for record in self.browse(cr, uid, ids, context):
codi... | the_stack_v2_python_sparse | python/alicia/hardware_inventory/secciones/hardware/hardware.py | aliciarom/ITALIS | train | 0 | |
a0de415e928a3c4f271ac4937288ce4d351668d6 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn OnenoteSection()",
"from .notebook import Notebook\nfrom .onenote_entity_hierarchy_model import OnenoteEntityHierarchyModel\nfrom .onenote_page import OnenotePage\nfrom .section_group import SectionGroup\nfrom .section_links import Sec... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return OnenoteSection()
<|end_body_0|>
<|body_start_1|>
from .notebook import Notebook
from .onenote_entity_hierarchy_model import OnenoteEntityHierarchyModel
from .onenote_page import ... | OnenoteSection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnenoteSection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection:
"""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 Retur... | stack_v2_sparse_classes_36k_train_008794 | 4,298 | 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: OnenoteSection",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | stack_v2_sparse_classes_30k_train_002413 | Implement the Python class `OnenoteSection` described below.
Class description:
Implement the OnenoteSection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `OnenoteSection` described below.
Class description:
Implement the OnenoteSection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class OnenoteSection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection:
"""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 Retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OnenoteSection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection:
"""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: OnenoteSec... | the_stack_v2_python_sparse | msgraph/generated/models/onenote_section.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
3fc2a68212dc0d3cd6e8f67e8ce48a396f3c6903 | [
"Thread.__init__(self)\nself.router = router\nself.config = config\nself.daemon = True",
"logging.info('%sRegister PublicKey ...', LoggerSetup.get_log_deep(1))\nif self.router.node_name == '' or self.router.public_key == '':\n logging.warning(\"%s[!] The PublicKey doesn't exist\", LoggerSetup.get_log_deep(2))\... | <|body_start_0|>
Thread.__init__(self)
self.router = router
self.config = config
self.daemon = True
<|end_body_0|>
<|body_start_1|>
logging.info('%sRegister PublicKey ...', LoggerSetup.get_log_deep(1))
if self.router.node_name == '' or self.router.public_key == '':
... | Sends the Public-Key of the Router to a given Email-Address. This is only possible if the key has been read from the wizard-page. | RegisterPublicKey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterPublicKey:
"""Sends the Public-Key of the Router to a given Email-Address. This is only possible if the key has been read from the wizard-page."""
def __init__(self, router: Router, config):
""":param router: Router-object :param config: {node_name, mesh_vpn, limit_bandwidth,... | stack_v2_sparse_classes_36k_train_008795 | 2,678 | no_license | [
{
"docstring": ":param router: Router-object :param config: {node_name, mesh_vpn, limit_bandwidth, show_location, latitude, longitude, altitude, contact,...}",
"name": "__init__",
"signature": "def __init__(self, router: Router, config)"
},
{
"docstring": "The Public-Key is send with the Router_... | 2 | null | Implement the Python class `RegisterPublicKey` described below.
Class description:
Sends the Public-Key of the Router to a given Email-Address. This is only possible if the key has been read from the wizard-page.
Method signatures and docstrings:
- def __init__(self, router: Router, config): :param router: Router-obj... | Implement the Python class `RegisterPublicKey` described below.
Class description:
Sends the Public-Key of the Router to a given Email-Address. This is only possible if the key has been read from the wizard-page.
Method signatures and docstrings:
- def __init__(self, router: Router, config): :param router: Router-obj... | 551fb53a6d4f865f076d9485e7290699d988731c | <|skeleton|>
class RegisterPublicKey:
"""Sends the Public-Key of the Router to a given Email-Address. This is only possible if the key has been read from the wizard-page."""
def __init__(self, router: Router, config):
""":param router: Router-object :param config: {node_name, mesh_vpn, limit_bandwidth,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegisterPublicKey:
"""Sends the Public-Key of the Router to a given Email-Address. This is only possible if the key has been read from the wizard-page."""
def __init__(self, router: Router, config):
""":param router: Router-object :param config: {node_name, mesh_vpn, limit_bandwidth, show_locatio... | the_stack_v2_python_sparse | util/register_public_key.py | PumucklOnTheAir/TestFramework | train | 9 |
7652bc8c9b4d40ab67a82c9f5a74fb24a749d89e | [
"temple.zhifu = mock.Mock(return_value={'result': 'success', 'reason': 'null'})\nstatues = temple.zhifu_statues()\nprint(statues)\nself.assertEqual(statues, '支付成功')",
"temple.zhifu = mock.Mock(return_value={'result': 'fail', 'reason': '余额不足'})\nstatues = temple.zhifu_statues()\nself.assertEqual(statues, '支付失败')"
... | <|body_start_0|>
temple.zhifu = mock.Mock(return_value={'result': 'success', 'reason': 'null'})
statues = temple.zhifu_statues()
print(statues)
self.assertEqual(statues, '支付成功')
<|end_body_0|>
<|body_start_1|>
temple.zhifu = mock.Mock(return_value={'result': 'fail', 'reason': '余... | 单元测试用例 | Test_zhifu_statues | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_zhifu_statues:
"""单元测试用例"""
def test_01(self):
"""测试支付成功场景"""
<|body_0|>
def test_02(self):
"""测试支付失败场景"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
temple.zhifu = mock.Mock(return_value={'result': 'success', 'reason': 'null'})
s... | stack_v2_sparse_classes_36k_train_008796 | 4,862 | no_license | [
{
"docstring": "测试支付成功场景",
"name": "test_01",
"signature": "def test_01(self)"
},
{
"docstring": "测试支付失败场景",
"name": "test_02",
"signature": "def test_02(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019181 | Implement the Python class `Test_zhifu_statues` described below.
Class description:
单元测试用例
Method signatures and docstrings:
- def test_01(self): 测试支付成功场景
- def test_02(self): 测试支付失败场景 | Implement the Python class `Test_zhifu_statues` described below.
Class description:
单元测试用例
Method signatures and docstrings:
- def test_01(self): 测试支付成功场景
- def test_02(self): 测试支付失败场景
<|skeleton|>
class Test_zhifu_statues:
"""单元测试用例"""
def test_01(self):
"""测试支付成功场景"""
<|body_0|>
def t... | a58fdcc3eb0b52c94e50a110b4f1a053c6fa0ab2 | <|skeleton|>
class Test_zhifu_statues:
"""单元测试用例"""
def test_01(self):
"""测试支付成功场景"""
<|body_0|>
def test_02(self):
"""测试支付失败场景"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_zhifu_statues:
"""单元测试用例"""
def test_01(self):
"""测试支付成功场景"""
temple.zhifu = mock.Mock(return_value={'result': 'success', 'reason': 'null'})
statues = temple.zhifu_statues()
print(statues)
self.assertEqual(statues, '支付成功')
def test_02(self):
"""测试... | the_stack_v2_python_sparse | testcase/test_temple.py | yangyilin182/IotInterFace | train | 0 |
c60575f7850c29aca253a93182fae2a80721fc5d | [
"m, n, s = (len(s1), len(s2), len(s3))\nif s != m + n:\n return False\ndp = [[False] * (n + 1) for _ in range(m + 1)]\ndp[0][0] = True\nfor i in range(1, n + 1):\n if s2[i - 1] == s3[i - 1]:\n dp[0][i] = dp[0][i - 1]\nfor i in range(1, m + 1):\n if s1[i - 1] == s3[i - 1]:\n dp[i][0] = dp[i - ... | <|body_start_0|>
m, n, s = (len(s1), len(s2), len(s3))
if s != m + n:
return False
dp = [[False] * (n + 1) for _ in range(m + 1)]
dp[0][0] = True
for i in range(1, n + 1):
if s2[i - 1] == s3[i - 1]:
dp[0][i] = dp[0][i - 1]
for i in ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isInterleave(self, s1: str, s2: str, s3: str) -> bool:
"""dp[i][j] 代表 前i个s1,与前j个s2,是否交错组成前i+j个s3 dp[0][0] = True dp[0][j] dp[j][0] dp[i][j] = dp[i-1_最短回文串.py][j] if s1[i-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i][j-1_最短回文串.py] if s2[j-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i... | stack_v2_sparse_classes_36k_train_008797 | 3,374 | no_license | [
{
"docstring": "dp[i][j] 代表 前i个s1,与前j个s2,是否交错组成前i+j个s3 dp[0][0] = True dp[0][j] dp[j][0] dp[i][j] = dp[i-1_最短回文串.py][j] if s1[i-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i][j-1_最短回文串.py] if s2[j-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i-1_最短回文串.py][j] or dp[i][j-1_最短回文串.py] if s2[j-1_最短回文串.py] == s1[i-1_最短回文串.py] =... | 2 | stack_v2_sparse_classes_30k_train_011785 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isInterleave(self, s1: str, s2: str, s3: str) -> bool: dp[i][j] 代表 前i个s1,与前j个s2,是否交错组成前i+j个s3 dp[0][0] = True dp[0][j] dp[j][0] dp[i][j] = dp[i-1_最短回文串.py][j] if s1[i-1_最短回文串... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isInterleave(self, s1: str, s2: str, s3: str) -> bool: dp[i][j] 代表 前i个s1,与前j个s2,是否交错组成前i+j个s3 dp[0][0] = True dp[0][j] dp[j][0] dp[i][j] = dp[i-1_最短回文串.py][j] if s1[i-1_最短回文串... | 57f303aa6e76f7c5292fa60bffdfddcb4ff9ddfb | <|skeleton|>
class Solution:
def isInterleave(self, s1: str, s2: str, s3: str) -> bool:
"""dp[i][j] 代表 前i个s1,与前j个s2,是否交错组成前i+j个s3 dp[0][0] = True dp[0][j] dp[j][0] dp[i][j] = dp[i-1_最短回文串.py][j] if s1[i-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i][j-1_最短回文串.py] if s2[j-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isInterleave(self, s1: str, s2: str, s3: str) -> bool:
"""dp[i][j] 代表 前i个s1,与前j个s2,是否交错组成前i+j个s3 dp[0][0] = True dp[0][j] dp[j][0] dp[i][j] = dp[i-1_最短回文串.py][j] if s1[i-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i][j-1_最短回文串.py] if s2[j-1_最短回文串.py] == s3[i+j-1_最短回文串.py] = dp[i-1_最短回文串.py][j... | the_stack_v2_python_sparse | 4_LEETCODE/2_DP/字符串匹配问题/97_交错字符串.py | fzingithub/SwordRefers2Offer | train | 1 | |
bd242a93830cc0bca3ae42a15ab4dc35501f5228 | [
"self.Wh = np.random.normal(size=(i + h, h))\nself.Wy = np.random.normal(size=(h, o))\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"h_x = np.concatenate((h_prev.T, x_t.T), axis=0)\nh_next = np.tanh(h_x.T @ self.Wh + self.bh)\ny_pred = h_next @ self.Wy + self.by\nz = y_pred\ny = np.exp(z) / np.sum(np.... | <|body_start_0|>
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.normal(size=(h, o))
self.bh = np.zeros((1, h))
self.by = np.zeros((1, o))
<|end_body_0|>
<|body_start_1|>
h_x = np.concatenate((h_prev.T, x_t.T), axis=0)
h_next = np.tanh(h_x.T @ self.Wh + s... | Vanilla model fro a RNN cell | RNNCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNCell:
"""Vanilla model fro a RNN cell"""
def __init__(self, i, h, o):
"""Initialize class constructor Args: i: dimensionality of the data h: dimensionality of the hidden state o: dimensionality of the outputs"""
<|body_0|>
def forward(self, h_prev, x_t):
"""fo... | stack_v2_sparse_classes_36k_train_008798 | 1,633 | no_license | [
{
"docstring": "Initialize class constructor Args: i: dimensionality of the data h: dimensionality of the hidden state o: dimensionality of the outputs",
"name": "__init__",
"signature": "def __init__(self, i, h, o)"
},
{
"docstring": "forward propagation vanilla RNN cell Args: h_prev: numpy.nda... | 2 | null | Implement the Python class `RNNCell` described below.
Class description:
Vanilla model fro a RNN cell
Method signatures and docstrings:
- def __init__(self, i, h, o): Initialize class constructor Args: i: dimensionality of the data h: dimensionality of the hidden state o: dimensionality of the outputs
- def forward(s... | Implement the Python class `RNNCell` described below.
Class description:
Vanilla model fro a RNN cell
Method signatures and docstrings:
- def __init__(self, i, h, o): Initialize class constructor Args: i: dimensionality of the data h: dimensionality of the hidden state o: dimensionality of the outputs
- def forward(s... | 7f9a040f23eda32c5aa154c991c930a01b490f0f | <|skeleton|>
class RNNCell:
"""Vanilla model fro a RNN cell"""
def __init__(self, i, h, o):
"""Initialize class constructor Args: i: dimensionality of the data h: dimensionality of the hidden state o: dimensionality of the outputs"""
<|body_0|>
def forward(self, h_prev, x_t):
"""fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNCell:
"""Vanilla model fro a RNN cell"""
def __init__(self, i, h, o):
"""Initialize class constructor Args: i: dimensionality of the data h: dimensionality of the hidden state o: dimensionality of the outputs"""
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.no... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/0-rnn_cell.py | dbaroli/holbertonschool-machine_learning | train | 0 |
71ac6e9debfe67d31456d98c384332719e0bc816 | [
"if additional_help is not None:\n self._help = additional_help\nelse:\n self._help = ''",
"width = 80\nlog_message = 'CLI: {}'.format(' '.join(sys.argv))\nlog.log2info(20043, log_message)\nparser = _Parser(description=self._help, formatter_class=argparse.RawTextHelpFormatter)\nsubparsers = parser.add_subpa... | <|body_start_0|>
if additional_help is not None:
self._help = additional_help
else:
self._help = ''
<|end_body_0|>
<|body_start_1|>
width = 80
log_message = 'CLI: {}'.format(' '.join(sys.argv))
log.log2info(20043, log_message)
parser = _Parser(des... | Class gathers all CLI information. | Parser | [
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Parser:
"""Class gathers all CLI information."""
def __init__(self, additional_help=None):
"""Intialize the class."""
<|body_0|>
def args(self):
"""Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI arguments as objects -... | stack_v2_sparse_classes_36k_train_008799 | 14,703 | permissive | [
{
"docstring": "Intialize the class.",
"name": "__init__",
"signature": "def __init__(self, additional_help=None)"
},
{
"docstring": "Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI arguments as objects - filename: Path to the configuration file",
... | 2 | stack_v2_sparse_classes_30k_train_008627 | Implement the Python class `Parser` described below.
Class description:
Class gathers all CLI information.
Method signatures and docstrings:
- def __init__(self, additional_help=None): Intialize the class.
- def args(self): Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI a... | Implement the Python class `Parser` described below.
Class description:
Class gathers all CLI information.
Method signatures and docstrings:
- def __init__(self, additional_help=None): Intialize the class.
- def args(self): Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI a... | 57bd3e82e49d51e3426b13ad53ed8326a735ce29 | <|skeleton|>
class Parser:
"""Class gathers all CLI information."""
def __init__(self, additional_help=None):
"""Intialize the class."""
<|body_0|>
def args(self):
"""Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI arguments as objects -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Parser:
"""Class gathers all CLI information."""
def __init__(self, additional_help=None):
"""Intialize the class."""
if additional_help is not None:
self._help = additional_help
else:
self._help = ''
def args(self):
"""Return all the CLI optio... | the_stack_v2_python_sparse | pattoo/cli/cli.py | palisadoes/pattoo | train | 0 |
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