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
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value | solution stringlengths 302 7.33k | source stringclasses 1
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38a0c87c79c24c4430ef0a5b66f5467064c2ffd6 | [
"self.pivotParameter = None\nself.order = None\nself.localDistance = None",
"self.requiredKeywords = set(['pivotParameter', 'order', 'localDistance'])\nself.wrongKeywords = set()\nfor child in xmlNode:\n if child.tag == 'order':\n if child.text in ['0', '1']:\n self.order = float(child.text)\... | <|body_start_0|>
self.pivotParameter = None
self.order = None
self.localDistance = None
<|end_body_0|>
<|body_start_1|>
self.requiredKeywords = set(['pivotParameter', 'order', 'localDistance'])
self.wrongKeywords = set()
for child in xmlNode:
if child.tag == ... | Dynamic Time Warping metrics which can be employed only for historySets | DTW | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DTW:
"""Dynamic Time Warping metrics which can be employed only for historySets"""
def initialize(self, inputDict):
"""This method initialize the metric object @ In, inputDict, dict, dictionary containing initialization parameters @ Out, none"""
<|body_0|>
def _localRead... | stack_v2_sparse_classes_36k_train_027600 | 6,156 | permissive | [
{
"docstring": "This method initialize the metric object @ In, inputDict, dict, dictionary containing initialization parameters @ Out, none",
"name": "initialize",
"signature": "def initialize(self, inputDict)"
},
{
"docstring": "Method that reads the portion of the xml input that belongs to thi... | 5 | null | Implement the Python class `DTW` described below.
Class description:
Dynamic Time Warping metrics which can be employed only for historySets
Method signatures and docstrings:
- def initialize(self, inputDict): This method initialize the metric object @ In, inputDict, dict, dictionary containing initialization paramet... | Implement the Python class `DTW` described below.
Class description:
Dynamic Time Warping metrics which can be employed only for historySets
Method signatures and docstrings:
- def initialize(self, inputDict): This method initialize the metric object @ In, inputDict, dict, dictionary containing initialization paramet... | fbee9e3def3c1ee576d1af85f3258cc816ceaaaf | <|skeleton|>
class DTW:
"""Dynamic Time Warping metrics which can be employed only for historySets"""
def initialize(self, inputDict):
"""This method initialize the metric object @ In, inputDict, dict, dictionary containing initialization parameters @ Out, none"""
<|body_0|>
def _localRead... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DTW:
"""Dynamic Time Warping metrics which can be employed only for historySets"""
def initialize(self, inputDict):
"""This method initialize the metric object @ In, inputDict, dict, dictionary containing initialization parameters @ Out, none"""
self.pivotParameter = None
self.ord... | the_stack_v2_python_sparse | framework/Metrics/DTW.py | jbae11/raven | train | 0 |
d114dc29a96f514967e75a8945f43353dbfe08a0 | [
"res = ''\n\ndef postOrder(root):\n nonlocal res\n if not root:\n res += '# '\n return\n postOrder(root.left)\n postOrder(root.right)\n res += str(root.val) + ' '\npostOrder(root)\nreturn res",
"datas = data.split()\n\ndef deOrder():\n val = datas.pop()\n if val == '#':\n ... | <|body_start_0|>
res = ''
def postOrder(root):
nonlocal res
if not root:
res += '# '
return
postOrder(root.left)
postOrder(root.right)
res += str(root.val) + ' '
postOrder(root)
return res
<|end_... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_027601 | 907 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_008374 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | bcc04d49969654cb44f79218a7ef2fd5c1e5449a | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = ''
def postOrder(root):
nonlocal res
if not root:
res += '# '
return
postOrder(root.left)
p... | the_stack_v2_python_sparse | src/0297-Serialize-and-Deserialize-Binary-Tree/0297.py | luliyucoordinate/Leetcode | train | 1,575 | |
ddf37877c7d17d389f42ff1651129f159edc0a06 | [
"dataseries.DataSeries.__init__(self, *args, **kwargs)\nif not isinstance(self.overlay, fslmelimage.MelodicImage):\n raise ValueError('Overlay is not a MelodicImage')\nself.varNorm = False\nself.disableProperty('varNorm')",
"display = self.displayCtx.getDisplay(self.overlay)\nopts = display.opts\ncomponent = o... | <|body_start_0|>
dataseries.DataSeries.__init__(self, *args, **kwargs)
if not isinstance(self.overlay, fslmelimage.MelodicImage):
raise ValueError('Overlay is not a MelodicImage')
self.varNorm = False
self.disableProperty('varNorm')
<|end_body_0|>
<|body_start_1|>
di... | The ``MelodicPowerSpectrumSeries`` class encapsulates the power spectrum of the time course for a single component of a :class:`.MelodicImage`. The component is dictated by the :attr:`.NiftiOpts.volume` property. | MelodicPowerSpectrumSeries | [
"Apache-2.0",
"CC-BY-3.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MelodicPowerSpectrumSeries:
"""The ``MelodicPowerSpectrumSeries`` class encapsulates the power spectrum of the time course for a single component of a :class:`.MelodicImage`. The component is dictated by the :attr:`.NiftiOpts.volume` property."""
def __init__(self, *args, **kwargs):
... | stack_v2_sparse_classes_36k_train_027602 | 19,177 | permissive | [
{
"docstring": "Create a ``MelodicPowerSpectrumSeries``. All arguments are passed through to the :meth:`PowerSpectrumSeries.__init__` method.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Returns a label that can be used for this ``MelodicPowerSpectr... | 3 | null | Implement the Python class `MelodicPowerSpectrumSeries` described below.
Class description:
The ``MelodicPowerSpectrumSeries`` class encapsulates the power spectrum of the time course for a single component of a :class:`.MelodicImage`. The component is dictated by the :attr:`.NiftiOpts.volume` property.
Method signat... | Implement the Python class `MelodicPowerSpectrumSeries` described below.
Class description:
The ``MelodicPowerSpectrumSeries`` class encapsulates the power spectrum of the time course for a single component of a :class:`.MelodicImage`. The component is dictated by the :attr:`.NiftiOpts.volume` property.
Method signat... | 37b45d034d60660b6de3e4bdf5dd6349ed6d853b | <|skeleton|>
class MelodicPowerSpectrumSeries:
"""The ``MelodicPowerSpectrumSeries`` class encapsulates the power spectrum of the time course for a single component of a :class:`.MelodicImage`. The component is dictated by the :attr:`.NiftiOpts.volume` property."""
def __init__(self, *args, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MelodicPowerSpectrumSeries:
"""The ``MelodicPowerSpectrumSeries`` class encapsulates the power spectrum of the time course for a single component of a :class:`.MelodicImage`. The component is dictated by the :attr:`.NiftiOpts.volume` property."""
def __init__(self, *args, **kwargs):
"""Create a `... | the_stack_v2_python_sparse | fsleyes/plotting/powerspectrumseries.py | CGSchwarzMayo/fsleyes | train | 0 |
3dd91cc93c8bc86f00eac0d0ee85f03854951643 | [
"if not prices:\n return 0\nlowest_buy, max_profit = (prices[0], 0)\nfor i in range(len(prices)):\n lowest_buy = min(prices[i], lowest_buy)\n max_profit = max(prices[i] - lowest_buy, max_profit)\nreturn max_profit",
"lowest_buy, max_profit = (2147483647, 0)\nfor price in prices:\n if price < lowest_bu... | <|body_start_0|>
if not prices:
return 0
lowest_buy, max_profit = (prices[0], 0)
for i in range(len(prices)):
lowest_buy = min(prices[i], lowest_buy)
max_profit = max(prices[i] - lowest_buy, max_profit)
return max_profit
<|end_body_0|>
<|body_start_1|... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not prices:
return 0
... | stack_v2_sparse_classes_36k_train_027603 | 1,138 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit1",
"signature": "def maxProfit1(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004719 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxPro... | 4a1747b6497305f3821612d9c358a6795b1690da | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
if not prices:
return 0
lowest_buy, max_profit = (prices[0], 0)
for i in range(len(prices)):
lowest_buy = min(prices[i], lowest_buy)
max_profit = max(prices[i] ... | the_stack_v2_python_sparse | DynamicProgramming/q121_best_time_to_buy_and_sell_stock.py | sevenhe716/LeetCode | train | 0 | |
229b8bd0948f2cfb35bd9d404b01a304abfd4d60 | [
"if not cls.check_bases(bases):\n raise TypeError('Class %s is not a subclass of TextCommand' % classname)\nc = super(HybridCommandMeta, cls).__new__(cls, classname, bases, dictionary)\nif c:\n win_class = HybridCommandMeta.make_window_version(classname, dictionary)\n app_class = HybridCommandMeta.make_app... | <|body_start_0|>
if not cls.check_bases(bases):
raise TypeError('Class %s is not a subclass of TextCommand' % classname)
c = super(HybridCommandMeta, cls).__new__(cls, classname, bases, dictionary)
if c:
win_class = HybridCommandMeta.make_window_version(classname, diction... | A TextCommand can use this as its metaclass to automatically create a window command and an application command that will run the given text command for the active window and view. Useful when writing a text command that you want to run as a build system. | HybridCommandMeta | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HybridCommandMeta:
"""A TextCommand can use this as its metaclass to automatically create a window command and an application command that will run the given text command for the active window and view. Useful when writing a text command that you want to run as a build system."""
def __new__... | stack_v2_sparse_classes_36k_train_027604 | 17,290 | no_license | [
{
"docstring": "Creates a WindowCommand that will run this text command. If an is_enabled attribute is defined, the window command will call it as a condition before running the text command.",
"name": "__new__",
"signature": "def __new__(cls, classname, bases, dictionary)"
},
{
"docstring": "Fu... | 5 | stack_v2_sparse_classes_30k_train_009350 | Implement the Python class `HybridCommandMeta` described below.
Class description:
A TextCommand can use this as its metaclass to automatically create a window command and an application command that will run the given text command for the active window and view. Useful when writing a text command that you want to run... | Implement the Python class `HybridCommandMeta` described below.
Class description:
A TextCommand can use this as its metaclass to automatically create a window command and an application command that will run the given text command for the active window and view. Useful when writing a text command that you want to run... | cd02a3a50e2eb97dd8368b72ea5669784a81dddd | <|skeleton|>
class HybridCommandMeta:
"""A TextCommand can use this as its metaclass to automatically create a window command and an application command that will run the given text command for the active window and view. Useful when writing a text command that you want to run as a build system."""
def __new__... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HybridCommandMeta:
"""A TextCommand can use this as its metaclass to automatically create a window command and an application command that will run the given text command for the active window and view. Useful when writing a text command that you want to run as a build system."""
def __new__(cls, classna... | the_stack_v2_python_sparse | classes/command_templates.py | kbaskett248/Focus | train | 0 |
937764634aea8e414b00d1cf39c0d92a8b1fa877 | [
"if id is None:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects\nelse:\n self.id = id",
"if list_dictionaries is None or list_dictionaries is []:\n return '[]'\nreturn json.dumps(list_dictionaries)",
"mtlist = []\nmtfile = cls.__name__ + '.json'\nif list_objs:\n for increment in list_objs:... | <|body_start_0|>
if id is None:
Base.__nb_objects += 1
self.id = Base.__nb_objects
else:
self.id = id
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is None or list_dictionaries is []:
return '[]'
return json.dumps(list_dictionaries)... | Fragile. Don't drop | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""Fragile. Don't drop"""
def __init__(self, id=None):
"""Base constructor"""
<|body_0|>
def to_json_string(list_dictionaries):
"""return json string"""
<|body_1|>
def save_to_file(cls, list_objs):
"""Save list_objs to json string"""
... | stack_v2_sparse_classes_36k_train_027605 | 1,767 | no_license | [
{
"docstring": "Base constructor",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "return json string",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "Save list_objs to json string",
"name": ... | 4 | stack_v2_sparse_classes_30k_train_005510 | Implement the Python class `Base` described below.
Class description:
Fragile. Don't drop
Method signatures and docstrings:
- def __init__(self, id=None): Base constructor
- def to_json_string(list_dictionaries): return json string
- def save_to_file(cls, list_objs): Save list_objs to json string
- def from_json_stri... | Implement the Python class `Base` described below.
Class description:
Fragile. Don't drop
Method signatures and docstrings:
- def __init__(self, id=None): Base constructor
- def to_json_string(list_dictionaries): return json string
- def save_to_file(cls, list_objs): Save list_objs to json string
- def from_json_stri... | dcad3daba72465b20fa1d1dee7c728981b5e33b1 | <|skeleton|>
class Base:
"""Fragile. Don't drop"""
def __init__(self, id=None):
"""Base constructor"""
<|body_0|>
def to_json_string(list_dictionaries):
"""return json string"""
<|body_1|>
def save_to_file(cls, list_objs):
"""Save list_objs to json string"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base:
"""Fragile. Don't drop"""
def __init__(self, id=None):
"""Base constructor"""
if id is None:
Base.__nb_objects += 1
self.id = Base.__nb_objects
else:
self.id = id
def to_json_string(list_dictionaries):
"""return json string"""... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | Christopher-Caswell/holbertonschool-higher_level_programming | train | 0 |
9280b8a652b605b6c18b40ac13aa790e819341b4 | [
"content_type = ContentType.objects.get_for_model(instance.__class__)\nobject_id = instance.id\nqueryset = super(UserTrackerManager, self).filter(content_type=content_type, object_id=object_id)\nreturn queryset",
"if request.user.is_authenticated:\n viewed_item = self.filter_by_model(instance=instance).filter(... | <|body_start_0|>
content_type = ContentType.objects.get_for_model(instance.__class__)
object_id = instance.id
queryset = super(UserTrackerManager, self).filter(content_type=content_type, object_id=object_id)
return queryset
<|end_body_0|>
<|body_start_1|>
if request.user.is_auth... | UserTrackerManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserTrackerManager:
def filter_by_model(self, instance):
"""bar assasse model filter mikone"""
<|body_0|>
def recommended_list(self, request, instance):
"""ye recommended list bar assasse category va session"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_027606 | 3,879 | permissive | [
{
"docstring": "bar assasse model filter mikone",
"name": "filter_by_model",
"signature": "def filter_by_model(self, instance)"
},
{
"docstring": "ye recommended list bar assasse category va session",
"name": "recommended_list",
"signature": "def recommended_list(self, request, instance)... | 2 | stack_v2_sparse_classes_30k_train_017753 | Implement the Python class `UserTrackerManager` described below.
Class description:
Implement the UserTrackerManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): bar assasse model filter mikone
- def recommended_list(self, request, instance): ye recommended list bar assasse category... | Implement the Python class `UserTrackerManager` described below.
Class description:
Implement the UserTrackerManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): bar assasse model filter mikone
- def recommended_list(self, request, instance): ye recommended list bar assasse category... | aef47922fdd6488550881ed9d42bf30a0d33a32a | <|skeleton|>
class UserTrackerManager:
def filter_by_model(self, instance):
"""bar assasse model filter mikone"""
<|body_0|>
def recommended_list(self, request, instance):
"""ye recommended list bar assasse category va session"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserTrackerManager:
def filter_by_model(self, instance):
"""bar assasse model filter mikone"""
content_type = ContentType.objects.get_for_model(instance.__class__)
object_id = instance.id
queryset = super(UserTrackerManager, self).filter(content_type=content_type, object_id=obj... | the_stack_v2_python_sparse | src/usertrackers/models.py | m3h-D/Myinfoblog | train | 0 | |
5796750b78980b4ac77ea21cb1d8cd39b1c538d0 | [
"filter_data = dict(self.request.arguments)\nconfigurations = get_all_config_dicts(self.session, filter_data)\ngrouped_configurations = {}\nfor config in configurations:\n if config['section'] not in grouped_configurations:\n grouped_configurations[config['section']] = []\n grouped_configurations[confi... | <|body_start_0|>
filter_data = dict(self.request.arguments)
configurations = get_all_config_dicts(self.session, filter_data)
grouped_configurations = {}
for config in configurations:
if config['section'] not in grouped_configurations:
grouped_configurations[co... | Update framework settings and tool paths. | ConfigurationHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigurationHandler:
"""Update framework settings and tool paths."""
def get(self):
"""Return all configuration items. **Example request**: .. sourcecode:: http GET /api/v1/configuration HTTP/1.1 Accept: application/json **Example response**: .. sourcecode:: http HTTP/1.1 200 OK Con... | stack_v2_sparse_classes_36k_train_027607 | 2,791 | permissive | [
{
"docstring": "Return all configuration items. **Example request**: .. sourcecode:: http GET /api/v1/configuration HTTP/1.1 Accept: application/json **Example response**: .. sourcecode:: http HTTP/1.1 200 OK Content-Type: application/json { \"status\": \"success\", \"data\": [ { \"dirty\": false, \"key\": \"AT... | 2 | stack_v2_sparse_classes_30k_train_003254 | Implement the Python class `ConfigurationHandler` described below.
Class description:
Update framework settings and tool paths.
Method signatures and docstrings:
- def get(self): Return all configuration items. **Example request**: .. sourcecode:: http GET /api/v1/configuration HTTP/1.1 Accept: application/json **Exa... | Implement the Python class `ConfigurationHandler` described below.
Class description:
Update framework settings and tool paths.
Method signatures and docstrings:
- def get(self): Return all configuration items. **Example request**: .. sourcecode:: http GET /api/v1/configuration HTTP/1.1 Accept: application/json **Exa... | 240825989a3850241b6b5dba6bcae1042a5dc384 | <|skeleton|>
class ConfigurationHandler:
"""Update framework settings and tool paths."""
def get(self):
"""Return all configuration items. **Example request**: .. sourcecode:: http GET /api/v1/configuration HTTP/1.1 Accept: application/json **Example response**: .. sourcecode:: http HTTP/1.1 200 OK Con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigurationHandler:
"""Update framework settings and tool paths."""
def get(self):
"""Return all configuration items. **Example request**: .. sourcecode:: http GET /api/v1/configuration HTTP/1.1 Accept: application/json **Example response**: .. sourcecode:: http HTTP/1.1 200 OK Content-Type: ap... | the_stack_v2_python_sparse | owtf/api/handlers/config.py | owtf/owtf | train | 1,683 |
5159c412f7c30d9092558bdee9c06cbfcf490bf0 | [
"if os.path.exists(fname):\n self.file = open(fname, 'rb')\n self.magic_t, self.elsize, _, self.dim, _ = _read_header(self.file, False)\n self.gz = False\nelse:\n import gzip\n self.file = gzip.open(fname + '.gz', 'rb')\n self.magic_t, self.elsize, _, self.dim, _ = _read_header(self.file, False, T... | <|body_start_0|>
if os.path.exists(fname):
self.file = open(fname, 'rb')
self.magic_t, self.elsize, _, self.dim, _ = _read_header(self.file, False)
self.gz = False
else:
import gzip
self.file = gzip.open(fname + '.gz', 'rb')
self.ma... | FTFile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FTFile:
def __init__(self, fname, scale=1, dtype=None):
"""Tests: >>> f = FTFile('/data/lisa/data/nist/by_class/digits/digits_test_labels.ft')"""
<|body_0|>
def skip(self, num):
"""Skips `num` items in the file. If `num` is negative, skips size-num. Tests: >>> f = FT... | stack_v2_sparse_classes_36k_train_027608 | 9,679 | permissive | [
{
"docstring": "Tests: >>> f = FTFile('/data/lisa/data/nist/by_class/digits/digits_test_labels.ft')",
"name": "__init__",
"signature": "def __init__(self, fname, scale=1, dtype=None)"
},
{
"docstring": "Skips `num` items in the file. If `num` is negative, skips size-num. Tests: >>> f = FTFile('/... | 3 | stack_v2_sparse_classes_30k_train_003756 | Implement the Python class `FTFile` described below.
Class description:
Implement the FTFile class.
Method signatures and docstrings:
- def __init__(self, fname, scale=1, dtype=None): Tests: >>> f = FTFile('/data/lisa/data/nist/by_class/digits/digits_test_labels.ft')
- def skip(self, num): Skips `num` items in the fi... | Implement the Python class `FTFile` described below.
Class description:
Implement the FTFile class.
Method signatures and docstrings:
- def __init__(self, fname, scale=1, dtype=None): Tests: >>> f = FTFile('/data/lisa/data/nist/by_class/digits/digits_test_labels.ft')
- def skip(self, num): Skips `num` items in the fi... | 7881458caaf2f5ab82b130ee50cb933cf12f6de7 | <|skeleton|>
class FTFile:
def __init__(self, fname, scale=1, dtype=None):
"""Tests: >>> f = FTFile('/data/lisa/data/nist/by_class/digits/digits_test_labels.ft')"""
<|body_0|>
def skip(self, num):
"""Skips `num` items in the file. If `num` is negative, skips size-num. Tests: >>> f = FT... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FTFile:
def __init__(self, fname, scale=1, dtype=None):
"""Tests: >>> f = FTFile('/data/lisa/data/nist/by_class/digits/digits_test_labels.ft')"""
if os.path.exists(fname):
self.file = open(fname, 'rb')
self.magic_t, self.elsize, _, self.dim, _ = _read_header(self.file, ... | the_stack_v2_python_sparse | datasets/ift6266/datasets/ftfile.py | sauravbiswasiupr/image_transformations | train | 0 | |
56ce47752cabfbc1604a1d051a305a6a741bfae4 | [
"res = 0\nn = len(nums)\nevs = [nums[x] for x in range(n) if x % 2 == 0]\nods = [nums[x] for x in range(n) if x % 2 != 0]\nreturn sum((min(evs[x], ods[x]) for x in range(n / 2)))",
"nums.sort()\nneg = []\nres = 0\nres += self.get_sum(nums)\nreturn res"
] | <|body_start_0|>
res = 0
n = len(nums)
evs = [nums[x] for x in range(n) if x % 2 == 0]
ods = [nums[x] for x in range(n) if x % 2 != 0]
return sum((min(evs[x], ods[x]) for x in range(n / 2)))
<|end_body_0|>
<|body_start_1|>
nums.sort()
neg = []
res = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def get_sum(self, nums):
"""Doc"""
<|body_0|>
def arrayPairSum(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = 0
n = len(nums)
evs = [nums[x] for x in range(n) if x % ... | stack_v2_sparse_classes_36k_train_027609 | 517 | no_license | [
{
"docstring": "Doc",
"name": "get_sum",
"signature": "def get_sum(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "arrayPairSum",
"signature": "def arrayPairSum(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def get_sum(self, nums): Doc
- def arrayPairSum(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def get_sum(self, nums): Doc
- def arrayPairSum(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def get_sum(self, nums):
"""Doc"""
... | b00f649598a6e57af30b517baa304f3094345f6d | <|skeleton|>
class Solution:
def get_sum(self, nums):
"""Doc"""
<|body_0|>
def arrayPairSum(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def get_sum(self, nums):
"""Doc"""
res = 0
n = len(nums)
evs = [nums[x] for x in range(n) if x % 2 == 0]
ods = [nums[x] for x in range(n) if x % 2 != 0]
return sum((min(evs[x], ods[x]) for x in range(n / 2)))
def arrayPairSum(self, nums):
... | the_stack_v2_python_sparse | array_pair_sum.py | grewy/practice_py | train | 0 | |
51f56fb37962b9359abc76f42f1d2731b8b11e46 | [
"super().__init__(axis, sample_weight, from_logits, ignore_index, cutoff, label_smooth, reduction, name)\nself.smooth = smooth\nself.is_logsoftmax = False\nself.need_target_onehot = True\nself.is_multiselection = False\nself._built = True",
"if self.is_logsoftmax:\n output = exp(output)\nreduce_axes = list(ran... | <|body_start_0|>
super().__init__(axis, sample_weight, from_logits, ignore_index, cutoff, label_smooth, reduction, name)
self.smooth = smooth
self.is_logsoftmax = False
self.need_target_onehot = True
self.is_multiselection = False
self._built = True
<|end_body_0|>
<|body... | This criterion combines :func:`nn.LogSoftmax` and :func:`nn.NLLLoss` in one single class. It is useful when training a classification problem with `C` classes. If provided, the optional argument :attr:`weight` should be a 1D `Tensor` assigning weight to each of the classes. This is particularly useful when you have an ... | DiceLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiceLoss:
"""This criterion combines :func:`nn.LogSoftmax` and :func:`nn.NLLLoss` in one single class. It is useful when training a classification problem with `C` classes. If provided, the optional argument :attr:`weight` should be a 1D `Tensor` assigning weight to each of the classes. This is p... | stack_v2_sparse_classes_36k_train_027610 | 35,108 | permissive | [
{
"docstring": "Args: axis (int): the axis where the class label is. sample_weight (): from_logits (): ignore_index (): cutoff (): label_smooth (): reduction (string): name (stringf):",
"name": "__init__",
"signature": "def __init__(self, smooth=1.0, axis=-1, sample_weight=None, from_logits=False, ignor... | 2 | stack_v2_sparse_classes_30k_train_008427 | Implement the Python class `DiceLoss` described below.
Class description:
This criterion combines :func:`nn.LogSoftmax` and :func:`nn.NLLLoss` in one single class. It is useful when training a classification problem with `C` classes. If provided, the optional argument :attr:`weight` should be a 1D `Tensor` assigning w... | Implement the Python class `DiceLoss` described below.
Class description:
This criterion combines :func:`nn.LogSoftmax` and :func:`nn.NLLLoss` in one single class. It is useful when training a classification problem with `C` classes. If provided, the optional argument :attr:`weight` should be a 1D `Tensor` assigning w... | 8d0726c77836599238004252485cad971fca31bc | <|skeleton|>
class DiceLoss:
"""This criterion combines :func:`nn.LogSoftmax` and :func:`nn.NLLLoss` in one single class. It is useful when training a classification problem with `C` classes. If provided, the optional argument :attr:`weight` should be a 1D `Tensor` assigning weight to each of the classes. This is p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiceLoss:
"""This criterion combines :func:`nn.LogSoftmax` and :func:`nn.NLLLoss` in one single class. It is useful when training a classification problem with `C` classes. If provided, the optional argument :attr:`weight` should be a 1D `Tensor` assigning weight to each of the classes. This is particularly u... | the_stack_v2_python_sparse | trident/optims/tensorflow_losses.py | yingkung/trident | train | 0 |
1ab16b9729a3c1b686096029639b287cb9201cb7 | [
"org_id = self.get_organization(request)\norg = Organization.objects.get(pk=org_id)\ndatasets = []\nfor d in ImportRecord.objects.filter(super_organization=org):\n importfiles = [obj_to_dict(f) for f in d.files]\n dataset = obj_to_dict(d)\n dataset['importfiles'] = importfiles\n if d.last_modified_by:\n... | <|body_start_0|>
org_id = self.get_organization(request)
org = Organization.objects.get(pk=org_id)
datasets = []
for d in ImportRecord.objects.filter(super_organization=org):
importfiles = [obj_to_dict(f) for f in d.files]
dataset = obj_to_dict(d)
data... | DatasetViewSet | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatasetViewSet:
def list(self, request):
"""Retrieves all datasets for the user's organization."""
<|body_0|>
def update(self, request, pk=None):
"""Updates the name of a dataset (ImportRecord)."""
<|body_1|>
def retrieve(self, request, pk=None):
... | stack_v2_sparse_classes_36k_train_027611 | 8,810 | permissive | [
{
"docstring": "Retrieves all datasets for the user's organization.",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "Updates the name of a dataset (ImportRecord).",
"name": "update",
"signature": "def update(self, request, pk=None)"
},
{
"docstring": "R... | 6 | null | Implement the Python class `DatasetViewSet` described below.
Class description:
Implement the DatasetViewSet class.
Method signatures and docstrings:
- def list(self, request): Retrieves all datasets for the user's organization.
- def update(self, request, pk=None): Updates the name of a dataset (ImportRecord).
- def... | Implement the Python class `DatasetViewSet` described below.
Class description:
Implement the DatasetViewSet class.
Method signatures and docstrings:
- def list(self, request): Retrieves all datasets for the user's organization.
- def update(self, request, pk=None): Updates the name of a dataset (ImportRecord).
- def... | 680b6a2b45f3c568d779d8ac86553a0b08c384c8 | <|skeleton|>
class DatasetViewSet:
def list(self, request):
"""Retrieves all datasets for the user's organization."""
<|body_0|>
def update(self, request, pk=None):
"""Updates the name of a dataset (ImportRecord)."""
<|body_1|>
def retrieve(self, request, pk=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatasetViewSet:
def list(self, request):
"""Retrieves all datasets for the user's organization."""
org_id = self.get_organization(request)
org = Organization.objects.get(pk=org_id)
datasets = []
for d in ImportRecord.objects.filter(super_organization=org):
i... | the_stack_v2_python_sparse | seed/views/v3/datasets.py | SEED-platform/seed | train | 108 | |
62773eb73917c27b01cb5ee11edba17b531017cc | [
"super(littleConv, self).__init__()\nself.main = nn.Sequential(nn.Conv2d(num_channels, 64, 4, 2, 1, bias=False), nn.ReLU(True), nn.BatchNorm2d(64), nn.Conv2d(64, 128, 4, 2, 1, bias=False), nn.ReLU(True), nn.BatchNorm2d(128), nn.Conv2d(128, 256, 4, 2, 1, bias=False), nn.ReLU(True), nn.BatchNorm2d(256), nn.Conv2d(256... | <|body_start_0|>
super(littleConv, self).__init__()
self.main = nn.Sequential(nn.Conv2d(num_channels, 64, 4, 2, 1, bias=False), nn.ReLU(True), nn.BatchNorm2d(64), nn.Conv2d(64, 128, 4, 2, 1, bias=False), nn.ReLU(True), nn.BatchNorm2d(128), nn.Conv2d(128, 256, 4, 2, 1, bias=False), nn.ReLU(True), nn.Batc... | Class encoder | littleConv | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class littleConv:
"""Class encoder"""
def __init__(self, c_dim, z_dim=200, num_channels=1, std=0.02):
"""Initialization conv -> ReLU x 4 -> (mu, sigma)"""
<|body_0|>
def init_weights(self):
"""Weight Initialization"""
<|body_1|>
def forward(self, input):
... | stack_v2_sparse_classes_36k_train_027612 | 3,780 | no_license | [
{
"docstring": "Initialization conv -> ReLU x 4 -> (mu, sigma)",
"name": "__init__",
"signature": "def __init__(self, c_dim, z_dim=200, num_channels=1, std=0.02)"
},
{
"docstring": "Weight Initialization",
"name": "init_weights",
"signature": "def init_weights(self)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_010399 | Implement the Python class `littleConv` described below.
Class description:
Class encoder
Method signatures and docstrings:
- def __init__(self, c_dim, z_dim=200, num_channels=1, std=0.02): Initialization conv -> ReLU x 4 -> (mu, sigma)
- def init_weights(self): Weight Initialization
- def forward(self, input): Defin... | Implement the Python class `littleConv` described below.
Class description:
Class encoder
Method signatures and docstrings:
- def __init__(self, c_dim, z_dim=200, num_channels=1, std=0.02): Initialization conv -> ReLU x 4 -> (mu, sigma)
- def init_weights(self): Weight Initialization
- def forward(self, input): Defin... | 21c0bf459388bd616a64afc1a34441123b1f41fe | <|skeleton|>
class littleConv:
"""Class encoder"""
def __init__(self, c_dim, z_dim=200, num_channels=1, std=0.02):
"""Initialization conv -> ReLU x 4 -> (mu, sigma)"""
<|body_0|>
def init_weights(self):
"""Weight Initialization"""
<|body_1|>
def forward(self, input):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class littleConv:
"""Class encoder"""
def __init__(self, c_dim, z_dim=200, num_channels=1, std=0.02):
"""Initialization conv -> ReLU x 4 -> (mu, sigma)"""
super(littleConv, self).__init__()
self.main = nn.Sequential(nn.Conv2d(num_channels, 64, 4, 2, 1, bias=False), nn.ReLU(True), nn.Bat... | the_stack_v2_python_sparse | classification/models/littleConv.py | CHOcho-quan/CS385ML | train | 1 |
f57f8c67a69c06f9a5ecfa2a4448e33dce196d67 | [
"self.stock = {}\nfor order_item, order_value in items_dictionary.items():\n self.stock[order_item] = Item(order_item, order_value)",
"item_in_stock = self.stock.get(item.name, None)\nif item_in_stock:\n return item_in_stock.quantity\nelse:\n return 0",
"item_in_stock = self.stock.get(order_item.name, ... | <|body_start_0|>
self.stock = {}
for order_item, order_value in items_dictionary.items():
self.stock[order_item] = Item(order_item, order_value)
<|end_body_0|>
<|body_start_1|>
item_in_stock = self.stock.get(item.name, None)
if item_in_stock:
return item_in_stock... | This is the implementation of the Inventory class, which keeps stocks item available in a warehouse | Inventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inventory:
"""This is the implementation of the Inventory class, which keeps stocks item available in a warehouse"""
def __init__(self, items_dictionary):
"""This method initializes an instance of the the Inventory Input: items_dictionary (dict) - Specifies how much of a particular i... | stack_v2_sparse_classes_36k_train_027613 | 1,874 | no_license | [
{
"docstring": "This method initializes an instance of the the Inventory Input: items_dictionary (dict) - Specifies how much of a particular item is present",
"name": "__init__",
"signature": "def __init__(self, items_dictionary)"
},
{
"docstring": "Aim: Checks how much of an item is in the inve... | 3 | stack_v2_sparse_classes_30k_train_017298 | Implement the Python class `Inventory` described below.
Class description:
This is the implementation of the Inventory class, which keeps stocks item available in a warehouse
Method signatures and docstrings:
- def __init__(self, items_dictionary): This method initializes an instance of the the Inventory Input: items... | Implement the Python class `Inventory` described below.
Class description:
This is the implementation of the Inventory class, which keeps stocks item available in a warehouse
Method signatures and docstrings:
- def __init__(self, items_dictionary): This method initializes an instance of the the Inventory Input: items... | 090727798af5ddaa948bcfd05924481ba1b45d1c | <|skeleton|>
class Inventory:
"""This is the implementation of the Inventory class, which keeps stocks item available in a warehouse"""
def __init__(self, items_dictionary):
"""This method initializes an instance of the the Inventory Input: items_dictionary (dict) - Specifies how much of a particular i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Inventory:
"""This is the implementation of the Inventory class, which keeps stocks item available in a warehouse"""
def __init__(self, items_dictionary):
"""This method initializes an instance of the the Inventory Input: items_dictionary (dict) - Specifies how much of a particular item is presen... | the_stack_v2_python_sparse | inventory-allocator/Inventory.py | Priyansdesai/recruiting-exercises | train | 0 |
2ef2d4c6fec829adb6502f7c13ec3acaa227ec87 | [
"self._input_size = input_size\nself._num_classes = num_classes\nself._num_channels = num_channels\nself._image_field_key = image_field_key\nself._label_field_key = label_field_key\nself._dtype = dtype\nself._label_dtype = label_dtype",
"image = tf.io.decode_raw(data[self._image_field_key], tf.as_dtype(tf.float32... | <|body_start_0|>
self._input_size = input_size
self._num_classes = num_classes
self._num_channels = num_channels
self._image_field_key = image_field_key
self._label_field_key = label_field_key
self._dtype = dtype
self._label_dtype = label_dtype
<|end_body_0|>
<|b... | Parser to parse an image and its annotations into a dictionary of tensors. | Parser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Parser:
"""Parser to parse an image and its annotations into a dictionary of tensors."""
def __init__(self, input_size: Sequence[int], num_classes: int, num_channels: int=3, image_field_key: str='image/encoded', label_field_key: str='image/class/label', dtype: str='float32', label_dtype: str... | stack_v2_sparse_classes_36k_train_027614 | 4,231 | permissive | [
{
"docstring": "Initializes parameters for parsing annotations in the dataset. Args: input_size: The input tensor size of [height, width, volume] of input image. num_classes: The number of classes to be segmented. num_channels: The channel of input images. image_field_key: A `str` of the key name to encoded ima... | 4 | stack_v2_sparse_classes_30k_train_000788 | Implement the Python class `Parser` described below.
Class description:
Parser to parse an image and its annotations into a dictionary of tensors.
Method signatures and docstrings:
- def __init__(self, input_size: Sequence[int], num_classes: int, num_channels: int=3, image_field_key: str='image/encoded', label_field_... | Implement the Python class `Parser` described below.
Class description:
Parser to parse an image and its annotations into a dictionary of tensors.
Method signatures and docstrings:
- def __init__(self, input_size: Sequence[int], num_classes: int, num_channels: int=3, image_field_key: str='image/encoded', label_field_... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class Parser:
"""Parser to parse an image and its annotations into a dictionary of tensors."""
def __init__(self, input_size: Sequence[int], num_classes: int, num_channels: int=3, image_field_key: str='image/encoded', label_field_key: str='image/class/label', dtype: str='float32', label_dtype: str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Parser:
"""Parser to parse an image and its annotations into a dictionary of tensors."""
def __init__(self, input_size: Sequence[int], num_classes: int, num_channels: int=3, image_field_key: str='image/encoded', label_field_key: str='image/class/label', dtype: str='float32', label_dtype: str='float32'):
... | the_stack_v2_python_sparse | official/projects/volumetric_models/dataloaders/segmentation_input_3d.py | jianzhnie/models | train | 2 |
4f13b37cf7239e4fc3e6a88bc36c2126c8395cbf | [
"self.root = root\nself.root.geometry(f'{WIDTH}x{HEIGHT}')\ngrid_configure(self.root, 2, 0, row_weights=[1, 1, 20])\nself._init_menu()\nself._init_viz()",
"self.menu = tk.Menu(master=self.root, relief='raised')\nself.root.config(menu=self.menu)\nself.menu_config = tk.Menu(master=self.menu, tearoff=0)\nself.menu.a... | <|body_start_0|>
self.root = root
self.root.geometry(f'{WIDTH}x{HEIGHT}')
grid_configure(self.root, 2, 0, row_weights=[1, 1, 20])
self._init_menu()
self._init_viz()
<|end_body_0|>
<|body_start_1|>
self.menu = tk.Menu(master=self.root, relief='raised')
self.root.c... | ScientistView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScientistView:
def __init__(self, root):
"""GUI initialization"""
<|body_0|>
def _init_menu(self):
"""Menu initialization"""
<|body_1|>
def _init_viz(self):
"""Visualization initialization"""
<|body_2|>
def activate_viz(self):
... | stack_v2_sparse_classes_36k_train_027615 | 3,535 | permissive | [
{
"docstring": "GUI initialization",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": "Menu initialization",
"name": "_init_menu",
"signature": "def _init_menu(self)"
},
{
"docstring": "Visualization initialization",
"name": "_init_viz",
"sign... | 4 | stack_v2_sparse_classes_30k_train_013596 | Implement the Python class `ScientistView` described below.
Class description:
Implement the ScientistView class.
Method signatures and docstrings:
- def __init__(self, root): GUI initialization
- def _init_menu(self): Menu initialization
- def _init_viz(self): Visualization initialization
- def activate_viz(self): a... | Implement the Python class `ScientistView` described below.
Class description:
Implement the ScientistView class.
Method signatures and docstrings:
- def __init__(self, root): GUI initialization
- def _init_menu(self): Menu initialization
- def _init_viz(self): Visualization initialization
- def activate_viz(self): a... | 272d88be7ab617a58d3f241d10f4f9fd17b91cbc | <|skeleton|>
class ScientistView:
def __init__(self, root):
"""GUI initialization"""
<|body_0|>
def _init_menu(self):
"""Menu initialization"""
<|body_1|>
def _init_viz(self):
"""Visualization initialization"""
<|body_2|>
def activate_viz(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScientistView:
def __init__(self, root):
"""GUI initialization"""
self.root = root
self.root.geometry(f'{WIDTH}x{HEIGHT}')
grid_configure(self.root, 2, 0, row_weights=[1, 1, 20])
self._init_menu()
self._init_viz()
def _init_menu(self):
"""Menu initi... | the_stack_v2_python_sparse | system/scientist/view/main.py | thuchula6792/AutoOED | train | 0 | |
599335427fffc97d46e9023de8f0dba1753c4857 | [
"self.passive_copy_preference_server_guid_list = passive_copy_preference_server_guid_list\nself.passive_only = passive_only\nself.use_user_specified_passive_preference_order = use_user_specified_passive_preference_order",
"if dictionary is None:\n return None\npassive_copy_preference_server_guid_list = diction... | <|body_start_0|>
self.passive_copy_preference_server_guid_list = passive_copy_preference_server_guid_list
self.passive_only = passive_only
self.use_user_specified_passive_preference_order = use_user_specified_passive_preference_order
<|end_body_0|>
<|body_start_1|>
if dictionary is None... | Implementation of the 'ExchangeDAGProtectionPreference' model. Specifies the information about the preference order while choosing between which database copy of the database which is part of DAG should be protected. Attributes: passive_copy_preference_server_guid_list (list of string): Specifies the preference order o... | ExchangeDAGProtectionPreference | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExchangeDAGProtectionPreference:
"""Implementation of the 'ExchangeDAGProtectionPreference' model. Specifies the information about the preference order while choosing between which database copy of the database which is part of DAG should be protected. Attributes: passive_copy_preference_server_g... | stack_v2_sparse_classes_36k_train_027616 | 3,474 | permissive | [
{
"docstring": "Constructor for the ExchangeDAGProtectionPreference class",
"name": "__init__",
"signature": "def __init__(self, passive_copy_preference_server_guid_list=None, passive_only=None, use_user_specified_passive_preference_order=None)"
},
{
"docstring": "Creates an instance of this mod... | 2 | stack_v2_sparse_classes_30k_train_005914 | Implement the Python class `ExchangeDAGProtectionPreference` described below.
Class description:
Implementation of the 'ExchangeDAGProtectionPreference' model. Specifies the information about the preference order while choosing between which database copy of the database which is part of DAG should be protected. Attri... | Implement the Python class `ExchangeDAGProtectionPreference` described below.
Class description:
Implementation of the 'ExchangeDAGProtectionPreference' model. Specifies the information about the preference order while choosing between which database copy of the database which is part of DAG should be protected. Attri... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ExchangeDAGProtectionPreference:
"""Implementation of the 'ExchangeDAGProtectionPreference' model. Specifies the information about the preference order while choosing between which database copy of the database which is part of DAG should be protected. Attributes: passive_copy_preference_server_g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExchangeDAGProtectionPreference:
"""Implementation of the 'ExchangeDAGProtectionPreference' model. Specifies the information about the preference order while choosing between which database copy of the database which is part of DAG should be protected. Attributes: passive_copy_preference_server_guid_list (lis... | the_stack_v2_python_sparse | cohesity_management_sdk/models/exchange_dag_protection_preference.py | cohesity/management-sdk-python | train | 24 |
360344bffecce399a668c5a77d9d76a15d9dd637 | [
"super().__init__(syncthru, name)\nself._name = f'{name} Drum {color}'\nself._color = color\nself._unit_of_measurement = PERCENTAGE\nself._id_suffix = f'_drum_{color}'",
"if self.syncthru.is_online():\n self._attributes = self.syncthru.drum_status().get(self._color, {})\n self._state = self._attributes.get(... | <|body_start_0|>
super().__init__(syncthru, name)
self._name = f'{name} Drum {color}'
self._color = color
self._unit_of_measurement = PERCENTAGE
self._id_suffix = f'_drum_{color}'
<|end_body_0|>
<|body_start_1|>
if self.syncthru.is_online():
self._attributes ... | Implementation of a Samsung Printer toner sensor platform. | SyncThruDrumSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyncThruDrumSensor:
"""Implementation of a Samsung Printer toner sensor platform."""
def __init__(self, syncthru, name, color):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from SyncThru and update the state."""
<|body_... | stack_v2_sparse_classes_36k_train_027617 | 8,262 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, syncthru, name, color)"
},
{
"docstring": "Get the latest data from SyncThru and update the state.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014320 | Implement the Python class `SyncThruDrumSensor` described below.
Class description:
Implementation of a Samsung Printer toner sensor platform.
Method signatures and docstrings:
- def __init__(self, syncthru, name, color): Initialize the sensor.
- def update(self): Get the latest data from SyncThru and update the stat... | Implement the Python class `SyncThruDrumSensor` described below.
Class description:
Implementation of a Samsung Printer toner sensor platform.
Method signatures and docstrings:
- def __init__(self, syncthru, name, color): Initialize the sensor.
- def update(self): Get the latest data from SyncThru and update the stat... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class SyncThruDrumSensor:
"""Implementation of a Samsung Printer toner sensor platform."""
def __init__(self, syncthru, name, color):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from SyncThru and update the state."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SyncThruDrumSensor:
"""Implementation of a Samsung Printer toner sensor platform."""
def __init__(self, syncthru, name, color):
"""Initialize the sensor."""
super().__init__(syncthru, name)
self._name = f'{name} Drum {color}'
self._color = color
self._unit_of_measu... | the_stack_v2_python_sparse | homeassistant/components/syncthru/sensor.py | tchellomello/home-assistant | train | 8 |
a83cd5f7267b566e3b482e1ab6acec71a54a0d8c | [
"data = parse(filename)\ntotal = 0\nfor equation in data:\n total += p1_eval(equation)\nreturn total",
"data = parse(filename)\ntotal = 0\nfor equation in data:\n total += p2_eval(equation)\nreturn total"
] | <|body_start_0|>
data = parse(filename)
total = 0
for equation in data:
total += p1_eval(equation)
return total
<|end_body_0|>
<|body_start_1|>
data = parse(filename)
total = 0
for equation in data:
total += p2_eval(equation)
retur... | AoC 2020 Day 18 | Day18 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Day18:
"""AoC 2020 Day 18"""
def part1(filename: str) -> int:
"""Given a filename, solve 2020 day 18 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2020 day 18 part 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_027618 | 3,361 | no_license | [
{
"docstring": "Given a filename, solve 2020 day 18 part 1",
"name": "part1",
"signature": "def part1(filename: str) -> int"
},
{
"docstring": "Given a filename, solve 2020 day 18 part 2",
"name": "part2",
"signature": "def part2(filename: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_011139 | Implement the Python class `Day18` described below.
Class description:
AoC 2020 Day 18
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2020 day 18 part 1
- def part2(filename: str) -> int: Given a filename, solve 2020 day 18 part 2 | Implement the Python class `Day18` described below.
Class description:
AoC 2020 Day 18
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2020 day 18 part 1
- def part2(filename: str) -> int: Given a filename, solve 2020 day 18 part 2
<|skeleton|>
class Day18:
"""AoC 202... | e89db235837d2d05848210a18c9c2a4456085570 | <|skeleton|>
class Day18:
"""AoC 2020 Day 18"""
def part1(filename: str) -> int:
"""Given a filename, solve 2020 day 18 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2020 day 18 part 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Day18:
"""AoC 2020 Day 18"""
def part1(filename: str) -> int:
"""Given a filename, solve 2020 day 18 part 1"""
data = parse(filename)
total = 0
for equation in data:
total += p1_eval(equation)
return total
def part2(filename: str) -> int:
"... | the_stack_v2_python_sparse | 2020/python2020/aoc/day18.py | mreishus/aoc | train | 16 |
a3365003191c1ce10b7709b99d7a085d92f282c9 | [
"super().__init__(category, owner, ttl=ttl)\nself.lock_id_seq = itertools.count()\nself.items: Dict[str, Set[str]] = {}\nself.items_condition = Condition()",
"def is_ready():\n for locked in self.items.values():\n if locked.intersection(items_set):\n metrics[f'lock_{self.category}_misses'] +=... | <|body_start_0|>
super().__init__(category, owner, ttl=ttl)
self.lock_id_seq = itertools.count()
self.items: Dict[str, Set[str]] = {}
self.items_condition = Condition()
<|end_body_0|>
<|body_start_1|>
def is_ready():
for locked in self.items.values():
... | Distributed locking primitive. Allows exclusive access to all requested items within category between the threads of single process. Example ------- ``` lock = ProcessLock("test", "test:12") with lock.acquire(["obj1", "obj2"]): ... ``` | ProcessLock | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessLock:
"""Distributed locking primitive. Allows exclusive access to all requested items within category between the threads of single process. Example ------- ``` lock = ProcessLock("test", "test:12") with lock.acquire(["obj1", "obj2"]): ... ```"""
def __init__(self, category: str, own... | stack_v2_sparse_classes_36k_train_027619 | 2,673 | permissive | [
{
"docstring": ":param category: Lock category name :param owner: Lock owner id :param ttl: Default lock ttl in seconds",
"name": "__init__",
"signature": "def __init__(self, category: str, owner: str, ttl: Optional[float]=None)"
},
{
"docstring": "Acquire lock by list of items",
"name": "ac... | 3 | stack_v2_sparse_classes_30k_train_000762 | Implement the Python class `ProcessLock` described below.
Class description:
Distributed locking primitive. Allows exclusive access to all requested items within category between the threads of single process. Example ------- ``` lock = ProcessLock("test", "test:12") with lock.acquire(["obj1", "obj2"]): ... ```
Metho... | Implement the Python class `ProcessLock` described below.
Class description:
Distributed locking primitive. Allows exclusive access to all requested items within category between the threads of single process. Example ------- ``` lock = ProcessLock("test", "test:12") with lock.acquire(["obj1", "obj2"]): ... ```
Metho... | 6e6d71574e9b9d822bec572cc629a0ea73604a59 | <|skeleton|>
class ProcessLock:
"""Distributed locking primitive. Allows exclusive access to all requested items within category between the threads of single process. Example ------- ``` lock = ProcessLock("test", "test:12") with lock.acquire(["obj1", "obj2"]): ... ```"""
def __init__(self, category: str, own... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcessLock:
"""Distributed locking primitive. Allows exclusive access to all requested items within category between the threads of single process. Example ------- ``` lock = ProcessLock("test", "test:12") with lock.acquire(["obj1", "obj2"]): ... ```"""
def __init__(self, category: str, owner: str, ttl:... | the_stack_v2_python_sparse | core/lock/process.py | nocproject/noc | train | 105 |
a34dee34c65159293b8e595fd0ea592df2f3d049 | [
"@lru_cache(None)\ndef dfs(index: int, remain: int) -> int:\n if index == len(goods):\n return 0\n res = dfs(index + 1, remain)\n cost, score = goods[index]\n if remain >= cost:\n res = max(res, dfs(index + 1, remain - cost) + score)\n return res\ngoods = [(cur, next - cur) for cur, nex... | <|body_start_0|>
@lru_cache(None)
def dfs(index: int, remain: int) -> int:
if index == len(goods):
return 0
res = dfs(index + 1, remain)
cost, score = goods[index]
if remain >= cost:
res = max(res, dfs(index + 1, remain - co... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maximumProfit(self, A: List[int], B: List[int], k: int) -> int:
"""2564 ms"""
<|body_0|>
def maximumProfit2(self, A: List[int], B: List[int], k: int) -> int:
"""852 ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
@lru_cache(None)
... | stack_v2_sparse_classes_36k_train_027620 | 1,192 | no_license | [
{
"docstring": "2564 ms",
"name": "maximumProfit",
"signature": "def maximumProfit(self, A: List[int], B: List[int], k: int) -> int"
},
{
"docstring": "852 ms",
"name": "maximumProfit2",
"signature": "def maximumProfit2(self, A: List[int], B: List[int], k: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximumProfit(self, A: List[int], B: List[int], k: int) -> int: 2564 ms
- def maximumProfit2(self, A: List[int], B: List[int], k: int) -> int: 852 ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximumProfit(self, A: List[int], B: List[int], k: int) -> int: 2564 ms
- def maximumProfit2(self, A: List[int], B: List[int], k: int) -> int: 852 ms
<|skeleton|>
class Solu... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def maximumProfit(self, A: List[int], B: List[int], k: int) -> int:
"""2564 ms"""
<|body_0|>
def maximumProfit2(self, A: List[int], B: List[int], k: int) -> int:
"""852 ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maximumProfit(self, A: List[int], B: List[int], k: int) -> int:
"""2564 ms"""
@lru_cache(None)
def dfs(index: int, remain: int) -> int:
if index == len(goods):
return 0
res = dfs(index + 1, remain)
cost, score = goods[in... | the_stack_v2_python_sparse | 11_动态规划/背包问题/01背包/2291. Maximum Profit From Trading Stocks.py | 981377660LMT/algorithm-study | train | 225 | |
dfe5f02b50716f99ace689d257d999318f32bf80 | [
"def dfs(nums, k, val):\n \"\"\"\n Check if there is a subset with sum equal to val\n k: the number of elements to check. Current subset should be [0..k-1]\n Reduce this problem into two sub-problems:\n 1. Do search val in [0..k-2]\n 2. Do search val-nums[k-... | <|body_start_0|>
def dfs(nums, k, val):
"""
Check if there is a subset with sum equal to val
k: the number of elements to check. Current subset should be [0..k-1]
Reduce this problem into two sub-problems:
1. Do search v... | @ eBay dp Given a non-empty array containing only positive integers, find if the array can be partitioned into two subsets such that the sum of elements in both subsets is equal. Note: Each of the array element will not exceed 100. The array size will not exceed 200. Example 1: Input: [1, 5, 11, 5] Output: true Explana... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""@ eBay dp Given a non-empty array containing only positive integers, find if the array can be partitioned into two subsets such that the sum of elements in both subsets is equal. Note: Each of the array element will not exceed 100. The array size will not exceed 200. Example 1: Input... | stack_v2_sparse_classes_36k_train_027621 | 3,413 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition_recursive",
"signature": "def canPartition_recursive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition_dp",
"signature": "def canPartition_dp(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001474 | Implement the Python class `Solution` described below.
Class description:
@ eBay dp Given a non-empty array containing only positive integers, find if the array can be partitioned into two subsets such that the sum of elements in both subsets is equal. Note: Each of the array element will not exceed 100. The array siz... | Implement the Python class `Solution` described below.
Class description:
@ eBay dp Given a non-empty array containing only positive integers, find if the array can be partitioned into two subsets such that the sum of elements in both subsets is equal. Note: Each of the array element will not exceed 100. The array siz... | cbe6a7e7f05eccb4f9c5fce8651c0d87e5168516 | <|skeleton|>
class Solution:
"""@ eBay dp Given a non-empty array containing only positive integers, find if the array can be partitioned into two subsets such that the sum of elements in both subsets is equal. Note: Each of the array element will not exceed 100. The array size will not exceed 200. Example 1: Input... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""@ eBay dp Given a non-empty array containing only positive integers, find if the array can be partitioned into two subsets such that the sum of elements in both subsets is equal. Note: Each of the array element will not exceed 100. The array size will not exceed 200. Example 1: Input: [1, 5, 11, ... | the_stack_v2_python_sparse | src/dp/leetcode416_PartitionEqualSubsetSum.py | apepkuss/Cracking-Leetcode-in-Python | train | 2 |
dd24ee8c8805e85348974c914551a1525393978c | [
"def wrapper(*arg):\n t1 = time.clock()\n res = func(*arg)\n t2 = time.clock()\n print('%0.3fms' % ((t2 - t1) * 1000.0))\n return res\nreturn wrapper",
"@wraps(f)\ndef wrapp(*args, **kwargs):\n time_start = round(time.time(), 5)\n result = f(*args, **kwargs)\n time_end = round(time.time(),... | <|body_start_0|>
def wrapper(*arg):
t1 = time.clock()
res = func(*arg)
t2 = time.clock()
print('%0.3fms' % ((t2 - t1) * 1000.0))
return res
return wrapper
<|end_body_0|>
<|body_start_1|>
@wraps(f)
def wrapp(*args, **kwargs):
... | Decorators | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decorators:
def decor0(self, func):
"""декоратор 0, позволяющий вместе с результатом функции возвращать время ее работы"""
<|body_0|>
def decor1(self, f):
"""декоратор 1, позволяющий вместе с результатом функции возвращать время ее работы"""
<|body_1|>
d... | stack_v2_sparse_classes_36k_train_027622 | 3,283 | no_license | [
{
"docstring": "декоратор 0, позволяющий вместе с результатом функции возвращать время ее работы",
"name": "decor0",
"signature": "def decor0(self, func)"
},
{
"docstring": "декоратор 1, позволяющий вместе с результатом функции возвращать время ее работы",
"name": "decor1",
"signature": ... | 5 | stack_v2_sparse_classes_30k_train_019296 | Implement the Python class `Decorators` described below.
Class description:
Implement the Decorators class.
Method signatures and docstrings:
- def decor0(self, func): декоратор 0, позволяющий вместе с результатом функции возвращать время ее работы
- def decor1(self, f): декоратор 1, позволяющий вместе с результатом ... | Implement the Python class `Decorators` described below.
Class description:
Implement the Decorators class.
Method signatures and docstrings:
- def decor0(self, func): декоратор 0, позволяющий вместе с результатом функции возвращать время ее работы
- def decor1(self, f): декоратор 1, позволяющий вместе с результатом ... | c3225516640d872b97139a5c2919d216d5370b17 | <|skeleton|>
class Decorators:
def decor0(self, func):
"""декоратор 0, позволяющий вместе с результатом функции возвращать время ее работы"""
<|body_0|>
def decor1(self, f):
"""декоратор 1, позволяющий вместе с результатом функции возвращать время ее работы"""
<|body_1|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decorators:
def decor0(self, func):
"""декоратор 0, позволяющий вместе с результатом функции возвращать время ее работы"""
def wrapper(*arg):
t1 = time.clock()
res = func(*arg)
t2 = time.clock()
print('%0.3fms' % ((t2 - t1) * 1000.0))
... | the_stack_v2_python_sparse | Homework11-20+22.03/Task0(decors).py | Twicer/Homeworks | train | 0 | |
74d2eb33645925e71f2abbb450e02ec2a2db890b | [
"self.name = name\nself.org_no = org_no\nself.uni_customer_no = uni_customer_no\nself.created_before = APIHelper.RFC3339DateTime(created_before) if created_before else None\nself.created_after = APIHelper.RFC3339DateTime(created_after) if created_after else None\nself.last_modified_before = APIHelper.RFC3339DateTim... | <|body_start_0|>
self.name = name
self.org_no = org_no
self.uni_customer_no = uni_customer_no
self.created_before = APIHelper.RFC3339DateTime(created_before) if created_before else None
self.created_after = APIHelper.RFC3339DateTime(created_after) if created_after else None
... | Implementation of the 'AccountSearchFilter' model. TODO: type model description here. Attributes: name (string): TODO: type description here. org_no (string): TODO: type description here. uni_customer_no (string): TODO: type description here. created_before (datetime): TODO: type description here. created_after (dateti... | AccountSearchFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountSearchFilter:
"""Implementation of the 'AccountSearchFilter' model. TODO: type model description here. Attributes: name (string): TODO: type description here. org_no (string): TODO: type description here. uni_customer_no (string): TODO: type description here. created_before (datetime): TOD... | stack_v2_sparse_classes_36k_train_027623 | 4,978 | permissive | [
{
"docstring": "Constructor for the AccountSearchFilter class",
"name": "__init__",
"signature": "def __init__(self, name=None, org_no=None, uni_customer_no=None, created_before=None, created_after=None, last_modified_before=None, last_modified_after=None, dealer_name=None, dealer_reference=None, enable... | 2 | stack_v2_sparse_classes_30k_train_013166 | Implement the Python class `AccountSearchFilter` described below.
Class description:
Implementation of the 'AccountSearchFilter' model. TODO: type model description here. Attributes: name (string): TODO: type description here. org_no (string): TODO: type description here. uni_customer_no (string): TODO: type descripti... | Implement the Python class `AccountSearchFilter` described below.
Class description:
Implementation of the 'AccountSearchFilter' model. TODO: type model description here. Attributes: name (string): TODO: type description here. org_no (string): TODO: type description here. uni_customer_no (string): TODO: type descripti... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class AccountSearchFilter:
"""Implementation of the 'AccountSearchFilter' model. TODO: type model description here. Attributes: name (string): TODO: type description here. org_no (string): TODO: type description here. uni_customer_no (string): TODO: type description here. created_before (datetime): TOD... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountSearchFilter:
"""Implementation of the 'AccountSearchFilter' model. TODO: type model description here. Attributes: name (string): TODO: type description here. org_no (string): TODO: type description here. uni_customer_no (string): TODO: type description here. created_before (datetime): TODO: type descr... | the_stack_v2_python_sparse | idfy_rest_client/models/account_search_filter.py | dealflowteam/Idfy | train | 0 |
312d98cc9a1d211b5c6bccf390a19ca0c3251c49 | [
"existing_rows = self.select(table, columns)\nunique = diff(existing_rows, values, y_only=True)\nkeys = self.get_primary_key_vals(table)\npk_col = self.get_primary_key(table)\npk_index = columns.index(pk_col)\nto_insert, to_update = ([], [])\nfor index, row in enumerate(unique):\n if row[pk_index] not in keys:\n... | <|body_start_0|>
existing_rows = self.select(table, columns)
unique = diff(existing_rows, values, y_only=True)
keys = self.get_primary_key_vals(table)
pk_col = self.get_primary_key(table)
pk_index = columns.index(pk_col)
to_insert, to_update = ([], [])
for index, ... | Insert | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Insert:
def insert_uniques(self, table, columns, values):
"""Insert multiple rows into a table that do not already exist. If the rows primary key already exists, the rows values will be updated. If the rows primary key does not exists, a new row will be inserted"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_027624 | 3,676 | permissive | [
{
"docstring": "Insert multiple rows into a table that do not already exist. If the rows primary key already exists, the rows values will be updated. If the rows primary key does not exists, a new row will be inserted",
"name": "insert_uniques",
"signature": "def insert_uniques(self, table, columns, val... | 3 | stack_v2_sparse_classes_30k_train_010499 | Implement the Python class `Insert` described below.
Class description:
Implement the Insert class.
Method signatures and docstrings:
- def insert_uniques(self, table, columns, values): Insert multiple rows into a table that do not already exist. If the rows primary key already exists, the rows values will be updated... | Implement the Python class `Insert` described below.
Class description:
Implement the Insert class.
Method signatures and docstrings:
- def insert_uniques(self, table, columns, values): Insert multiple rows into a table that do not already exist. If the rows primary key already exists, the rows values will be updated... | 6964f718f4b72eb30f2259adfcfaf3090526c53d | <|skeleton|>
class Insert:
def insert_uniques(self, table, columns, values):
"""Insert multiple rows into a table that do not already exist. If the rows primary key already exists, the rows values will be updated. If the rows primary key does not exists, a new row will be inserted"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Insert:
def insert_uniques(self, table, columns, values):
"""Insert multiple rows into a table that do not already exist. If the rows primary key already exists, the rows values will be updated. If the rows primary key does not exists, a new row will be inserted"""
existing_rows = self.select(... | the_stack_v2_python_sparse | mysql/toolkit/components/manipulate/insert.py | sfneal/mysql-toolkit | train | 6 | |
7f059613ef04f577e94365a2aa502c6eb26ccbbc | [
"super().__init__(framework=framework)\nassert schedule_timesteps > 0\nself.schedule_timesteps = schedule_timesteps\nself.initial_p = initial_p\nself.decay_rate = decay_rate",
"if self.framework == 'torch' and torch and isinstance(t, torch.Tensor):\n t = t.float()\nreturn self.initial_p * self.decay_rate ** (t... | <|body_start_0|>
super().__init__(framework=framework)
assert schedule_timesteps > 0
self.schedule_timesteps = schedule_timesteps
self.initial_p = initial_p
self.decay_rate = decay_rate
<|end_body_0|>
<|body_start_1|>
if self.framework == 'torch' and torch and isinstance... | ExponentialSchedule | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExponentialSchedule:
def __init__(self, schedule_timesteps, framework, initial_p=1.0, decay_rate=0.1):
"""Exponential decay schedule from initial_p to final_p over schedule_timesteps. After this many time steps always `final_p` is returned. Agrs: schedule_timesteps (int): Number of time ... | stack_v2_sparse_classes_36k_train_027625 | 1,632 | permissive | [
{
"docstring": "Exponential decay schedule from initial_p to final_p over schedule_timesteps. After this many time steps always `final_p` is returned. Agrs: schedule_timesteps (int): Number of time steps for which to linearly anneal initial_p to final_p initial_p (float): Initial output value. decay_rate (float... | 2 | stack_v2_sparse_classes_30k_train_019885 | Implement the Python class `ExponentialSchedule` described below.
Class description:
Implement the ExponentialSchedule class.
Method signatures and docstrings:
- def __init__(self, schedule_timesteps, framework, initial_p=1.0, decay_rate=0.1): Exponential decay schedule from initial_p to final_p over schedule_timeste... | Implement the Python class `ExponentialSchedule` described below.
Class description:
Implement the ExponentialSchedule class.
Method signatures and docstrings:
- def __init__(self, schedule_timesteps, framework, initial_p=1.0, decay_rate=0.1): Exponential decay schedule from initial_p to final_p over schedule_timeste... | a03cd14a50d87d58effea1d749391af530d7609c | <|skeleton|>
class ExponentialSchedule:
def __init__(self, schedule_timesteps, framework, initial_p=1.0, decay_rate=0.1):
"""Exponential decay schedule from initial_p to final_p over schedule_timesteps. After this many time steps always `final_p` is returned. Agrs: schedule_timesteps (int): Number of time ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExponentialSchedule:
def __init__(self, schedule_timesteps, framework, initial_p=1.0, decay_rate=0.1):
"""Exponential decay schedule from initial_p to final_p over schedule_timesteps. After this many time steps always `final_p` is returned. Agrs: schedule_timesteps (int): Number of time steps for whic... | the_stack_v2_python_sparse | rllib/utils/schedules/exponential_schedule.py | ray-project/maze-raylit | train | 5 | |
6b1fab8fc003b11352e9d8a062cd525e7569b399 | [
"try:\n self.User.objects.get(email=email)\n return 'user_existed'\nexcept self.User.DoesNotExist:\n return None",
"try:\n self.User.objects.get(phone=phone)\n return 'user_existed'\nexcept self.User.DoesNotExist:\n return None",
"try:\n self.User.objects.get(phone=phone)\n return None\n... | <|body_start_0|>
try:
self.User.objects.get(email=email)
return 'user_existed'
except self.User.DoesNotExist:
return None
<|end_body_0|>
<|body_start_1|>
try:
self.User.objects.get(phone=phone)
return 'user_existed'
except self... | 验证码基类 | VerificationBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VerificationBase:
"""验证码基类"""
def user_email_none(self, email):
"""发送邮箱验证码用于 用户 or 商家 注册"""
<|body_0|>
def user_phone_none(self, phone):
"""发送手机号验证码用于用户 or 商家 注册"""
<|body_1|>
def user_phone_exist(self, phone):
"""发送手机验证码用于商家注册"""
<|b... | stack_v2_sparse_classes_36k_train_027626 | 9,344 | permissive | [
{
"docstring": "发送邮箱验证码用于 用户 or 商家 注册",
"name": "user_email_none",
"signature": "def user_email_none(self, email)"
},
{
"docstring": "发送手机号验证码用于用户 or 商家 注册",
"name": "user_phone_none",
"signature": "def user_phone_none(self, phone)"
},
{
"docstring": "发送手机验证码用于商家注册",
"name": ... | 4 | stack_v2_sparse_classes_30k_train_017483 | Implement the Python class `VerificationBase` described below.
Class description:
验证码基类
Method signatures and docstrings:
- def user_email_none(self, email): 发送邮箱验证码用于 用户 or 商家 注册
- def user_phone_none(self, phone): 发送手机号验证码用于用户 or 商家 注册
- def user_phone_exist(self, phone): 发送手机验证码用于商家注册
- def user_email_exist(self, ... | Implement the Python class `VerificationBase` described below.
Class description:
验证码基类
Method signatures and docstrings:
- def user_email_none(self, email): 发送邮箱验证码用于 用户 or 商家 注册
- def user_phone_none(self, phone): 发送手机号验证码用于用户 or 商家 注册
- def user_phone_exist(self, phone): 发送手机验证码用于商家注册
- def user_email_exist(self, ... | 13cb59130d15e782f78bc5148409bef0f1c516e0 | <|skeleton|>
class VerificationBase:
"""验证码基类"""
def user_email_none(self, email):
"""发送邮箱验证码用于 用户 or 商家 注册"""
<|body_0|>
def user_phone_none(self, phone):
"""发送手机号验证码用于用户 or 商家 注册"""
<|body_1|>
def user_phone_exist(self, phone):
"""发送手机验证码用于商家注册"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VerificationBase:
"""验证码基类"""
def user_email_none(self, email):
"""发送邮箱验证码用于 用户 or 商家 注册"""
try:
self.User.objects.get(email=email)
return 'user_existed'
except self.User.DoesNotExist:
return None
def user_phone_none(self, phone):
"... | the_stack_v2_python_sparse | user_app/views/verification_code.py | lmyfzx/Django-Mall | train | 0 |
c3125a0d0eef093a3321d450f5a836bd3dfc81fe | [
"user = auth.get_current_user()\nif not user:\n return self.error('not authenticated', 401)\ntoken = UserApiToken.query.filter(UserApiToken.user == user).one_or_none()\nreturn self.respond_with_schema(token_schema, token)",
"user = auth.get_current_user()\nif not user:\n return self.error('not authenticated... | <|body_start_0|>
user = auth.get_current_user()
if not user:
return self.error('not authenticated', 401)
token = UserApiToken.query.filter(UserApiToken.user == user).one_or_none()
return self.respond_with_schema(token_schema, token)
<|end_body_0|>
<|body_start_1|>
us... | UserTokenResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserTokenResource:
def get(self):
"""Return the API token for the user."""
<|body_0|>
def post(self):
"""Create a new API token for the user."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = auth.get_current_user()
if not user:
... | stack_v2_sparse_classes_36k_train_027627 | 1,278 | permissive | [
{
"docstring": "Return the API token for the user.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create a new API token for the user.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `UserTokenResource` described below.
Class description:
Implement the UserTokenResource class.
Method signatures and docstrings:
- def get(self): Return the API token for the user.
- def post(self): Create a new API token for the user. | Implement the Python class `UserTokenResource` described below.
Class description:
Implement the UserTokenResource class.
Method signatures and docstrings:
- def get(self): Return the API token for the user.
- def post(self): Create a new API token for the user.
<|skeleton|>
class UserTokenResource:
def get(sel... | 6d4a490c19ebe406b551641a022ca08f26c21fcb | <|skeleton|>
class UserTokenResource:
def get(self):
"""Return the API token for the user."""
<|body_0|>
def post(self):
"""Create a new API token for the user."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserTokenResource:
def get(self):
"""Return the API token for the user."""
user = auth.get_current_user()
if not user:
return self.error('not authenticated', 401)
token = UserApiToken.query.filter(UserApiToken.user == user).one_or_none()
return self.respond_... | the_stack_v2_python_sparse | zeus/api/resources/user_token.py | getsentry/zeus | train | 222 | |
5b8ac5314640320d9c6bb845602cc412f1877306 | [
"if allow_version and format_or_version == '1.0.0':\n return OutputFormat.XML\nif allow_version and format_or_version == '2.0.0':\n return OutputFormat.JSON\nif '/' in format_or_version:\n format_or_version = get_extension(format_or_version, dot=False)\nreturn super(OutputFormat, cls).get(str(format_or_ver... | <|body_start_0|>
if allow_version and format_or_version == '1.0.0':
return OutputFormat.XML
if allow_version and format_or_version == '2.0.0':
return OutputFormat.JSON
if '/' in format_or_version:
format_or_version = get_extension(format_or_version, dot=False)... | Renderer output formats for :term:`CLI`, `OpenAPI` and HTTP response content generation. | OutputFormat | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OutputFormat:
"""Renderer output formats for :term:`CLI`, `OpenAPI` and HTTP response content generation."""
def get(cls, format_or_version, default=JSON, allow_version=True):
"""Resolve the applicable output format. :param format_or_version: Either a :term:`WPS` version, a known val... | stack_v2_sparse_classes_36k_train_027628 | 34,693 | permissive | [
{
"docstring": "Resolve the applicable output format. :param format_or_version: Either a :term:`WPS` version, a known value for a ``f``/``format`` query parameter, or an ``Accept`` header that can be mapped to one of the supported output formats. :param default: Default output format if none could be resolved. ... | 2 | stack_v2_sparse_classes_30k_train_002773 | Implement the Python class `OutputFormat` described below.
Class description:
Renderer output formats for :term:`CLI`, `OpenAPI` and HTTP response content generation.
Method signatures and docstrings:
- def get(cls, format_or_version, default=JSON, allow_version=True): Resolve the applicable output format. :param for... | Implement the Python class `OutputFormat` described below.
Class description:
Renderer output formats for :term:`CLI`, `OpenAPI` and HTTP response content generation.
Method signatures and docstrings:
- def get(cls, format_or_version, default=JSON, allow_version=True): Resolve the applicable output format. :param for... | f07cfea0776af6c5797d2a2e06566d1e77858213 | <|skeleton|>
class OutputFormat:
"""Renderer output formats for :term:`CLI`, `OpenAPI` and HTTP response content generation."""
def get(cls, format_or_version, default=JSON, allow_version=True):
"""Resolve the applicable output format. :param format_or_version: Either a :term:`WPS` version, a known val... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OutputFormat:
"""Renderer output formats for :term:`CLI`, `OpenAPI` and HTTP response content generation."""
def get(cls, format_or_version, default=JSON, allow_version=True):
"""Resolve the applicable output format. :param format_or_version: Either a :term:`WPS` version, a known value for a ``f`... | the_stack_v2_python_sparse | weaver/formats.py | crim-ca/weaver | train | 22 |
968567c98a74c5f5a1bba207d50b0bffa7535fc6 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn CalendarSharingMessage()",
"from .calendar_sharing_message_action import CalendarSharingMessageAction\nfrom .message import Message\nfrom .calendar_sharing_message_action import CalendarSharingMessageAction\nfrom .message import Messag... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return CalendarSharingMessage()
<|end_body_0|>
<|body_start_1|>
from .calendar_sharing_message_action import CalendarSharingMessageAction
from .message import Message
from .calendar_sha... | CalendarSharingMessage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarSharingMessage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessage:
"""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 ... | stack_v2_sparse_classes_36k_train_027629 | 3,281 | 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: CalendarSharingMessage",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimina... | 3 | null | Implement the Python class `CalendarSharingMessage` described below.
Class description:
Implement the CalendarSharingMessage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessage: Creates a new instance of the appropriate class b... | Implement the Python class `CalendarSharingMessage` described below.
Class description:
Implement the CalendarSharingMessage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessage: Creates a new instance of the appropriate class b... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class CalendarSharingMessage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessage:
"""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 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalendarSharingMessage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CalendarSharingMessage:
"""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... | the_stack_v2_python_sparse | msgraph/generated/models/calendar_sharing_message.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
aaf06090255286caa526f1d98760fdde623367cb | [
"jewels_set = set(J)\nret = 0\nfor c in S:\n if c in jewels_set:\n ret += 1\nreturn ret",
"jewels_map = {}\nfor c in J:\n jewels_map[c] = 1\nret = 0\nfor c in S:\n if jewels_map.get(c, 0) == 1:\n ret += 1\nreturn ret"
] | <|body_start_0|>
jewels_set = set(J)
ret = 0
for c in S:
if c in jewels_set:
ret += 1
return ret
<|end_body_0|>
<|body_start_1|>
jewels_map = {}
for c in J:
jewels_map[c] = 1
ret = 0
for c in S:
if jewel... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numJewelsInStones(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_0|>
def numJewelsInStones1(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
jewels_set = set(J)
... | stack_v2_sparse_classes_36k_train_027630 | 730 | no_license | [
{
"docstring": ":type J: str :type S: str :rtype: int",
"name": "numJewelsInStones",
"signature": "def numJewelsInStones(self, J, S)"
},
{
"docstring": ":type J: str :type S: str :rtype: int",
"name": "numJewelsInStones1",
"signature": "def numJewelsInStones1(self, J, S)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018990 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numJewelsInStones(self, J, S): :type J: str :type S: str :rtype: int
- def numJewelsInStones1(self, J, S): :type J: str :type S: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numJewelsInStones(self, J, S): :type J: str :type S: str :rtype: int
- def numJewelsInStones1(self, J, S): :type J: str :type S: str :rtype: int
<|skeleton|>
class Solution:... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def numJewelsInStones(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_0|>
def numJewelsInStones1(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numJewelsInStones(self, J, S):
""":type J: str :type S: str :rtype: int"""
jewels_set = set(J)
ret = 0
for c in S:
if c in jewels_set:
ret += 1
return ret
def numJewelsInStones1(self, J, S):
""":type J: str :type S:... | the_stack_v2_python_sparse | python/leetcode_bak/771_Jewels_and_Stones.py | bobcaoge/my-code | train | 0 | |
60ed32f60505eda82276a4f77abdcf7a7f9abee5 | [
"builder = GraphBuilder()\na = Value('a')\nb = Value('b')\nc = Value('c')\nops = Sum()\nbuilder.add(c).with_ops(ops)\nbuilder.add(b).with_ops(ops).with_dependant(c)\nbuilder.add(a).with_ops(ops).with_dependant(c)\nbuilder.add(1).with_dependant(a)\nbuilder.add(2).with_dependant(a)\nbuilder.add(3).with_dependant(b)\n... | <|body_start_0|>
builder = GraphBuilder()
a = Value('a')
b = Value('b')
c = Value('c')
ops = Sum()
builder.add(c).with_ops(ops)
builder.add(b).with_ops(ops).with_dependant(c)
builder.add(a).with_ops(ops).with_dependant(c)
builder.add(1).with_depend... | DagTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DagTest:
def test_simple(self):
"""Test evaluation of a simple arithmetic tree"""
<|body_0|>
def test_disparate(self):
"""Test evaluation of two disconnected graphs in a single object"""
<|body_1|>
def test_proxy(self):
"""Test replacement of ope... | stack_v2_sparse_classes_36k_train_027631 | 5,150 | no_license | [
{
"docstring": "Test evaluation of a simple arithmetic tree",
"name": "test_simple",
"signature": "def test_simple(self)"
},
{
"docstring": "Test evaluation of two disconnected graphs in a single object",
"name": "test_disparate",
"signature": "def test_disparate(self)"
},
{
"doc... | 5 | null | Implement the Python class `DagTest` described below.
Class description:
Implement the DagTest class.
Method signatures and docstrings:
- def test_simple(self): Test evaluation of a simple arithmetic tree
- def test_disparate(self): Test evaluation of two disconnected graphs in a single object
- def test_proxy(self):... | Implement the Python class `DagTest` described below.
Class description:
Implement the DagTest class.
Method signatures and docstrings:
- def test_simple(self): Test evaluation of a simple arithmetic tree
- def test_disparate(self): Test evaluation of two disconnected graphs in a single object
- def test_proxy(self):... | 5813fa8b589b7b80d6bc09fb3e7362bb637d8d99 | <|skeleton|>
class DagTest:
def test_simple(self):
"""Test evaluation of a simple arithmetic tree"""
<|body_0|>
def test_disparate(self):
"""Test evaluation of two disconnected graphs in a single object"""
<|body_1|>
def test_proxy(self):
"""Test replacement of ope... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DagTest:
def test_simple(self):
"""Test evaluation of a simple arithmetic tree"""
builder = GraphBuilder()
a = Value('a')
b = Value('b')
c = Value('c')
ops = Sum()
builder.add(c).with_ops(ops)
builder.add(b).with_ops(ops).with_dependant(c)
... | the_stack_v2_python_sparse | src/app/test-server/test_dag.py | Radhika-Envision/Upmark | train | 0 | |
ebe18aa4e505eef9e01190484fb2682040ad6920 | [
"res = []\n\ndef preorder(root):\n if not root:\n res.append('#')\n return\n res.append(str(root.val))\n preorder(root.left)\n preorder(root.right)\npreorder(root)\nreturn ','.join(res)",
"queue = deque()\nfor d in data.split(','):\n queue.append(d)\n\ndef recursion(data):\n if not... | <|body_start_0|>
res = []
def preorder(root):
if not root:
res.append('#')
return
res.append(str(root.val))
preorder(root.left)
preorder(root.right)
preorder(root)
return ','.join(res)
<|end_body_0|>
<|body... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_027632 | 2,642 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | f0ad1e671de99574e00b4e78391d001677d60d82 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = []
def preorder(root):
if not root:
res.append('#')
return
res.append(str(root.val))
preorder(root.left... | the_stack_v2_python_sparse | hard/Serialize_And_Deserialize_Binary_Tree.py | junghyun4425/myleetcode | train | 0 | |
c017564474bc8acdf5dc261e94bb3511259eb62a | [
"sketch = Sketch.query.get_with_acl(sketch_id)\nif not sketch:\n abort(HTTP_STATUS_CODE_NOT_FOUND, 'No sketch found with this ID.')\nif not sketch.has_permission(current_user, 'read'):\n abort(HTTP_STATUS_CODE_FORBIDDEN, 'User does not have read access controls on sketch.')\nstories = []\nfor story in Story.q... | <|body_start_0|>
sketch = Sketch.query.get_with_acl(sketch_id)
if not sketch:
abort(HTTP_STATUS_CODE_NOT_FOUND, 'No sketch found with this ID.')
if not sketch.has_permission(current_user, 'read'):
abort(HTTP_STATUS_CODE_FORBIDDEN, 'User does not have read access controls ... | Resource to get all stories for a sketch or to create a new story. | StoryListResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StoryListResource:
"""Resource to get all stories for a sketch or to create a new story."""
def get(self, sketch_id):
"""Handles GET request to the resource. Args: sketch_id: Integer primary key for a sketch database model Returns: Stories in JSON (instance of flask.wrappers.Response... | stack_v2_sparse_classes_36k_train_027633 | 9,982 | permissive | [
{
"docstring": "Handles GET request to the resource. Args: sketch_id: Integer primary key for a sketch database model Returns: Stories in JSON (instance of flask.wrappers.Response)",
"name": "get",
"signature": "def get(self, sketch_id)"
},
{
"docstring": "Handles POST request to the resource. A... | 2 | null | Implement the Python class `StoryListResource` described below.
Class description:
Resource to get all stories for a sketch or to create a new story.
Method signatures and docstrings:
- def get(self, sketch_id): Handles GET request to the resource. Args: sketch_id: Integer primary key for a sketch database model Retu... | Implement the Python class `StoryListResource` described below.
Class description:
Resource to get all stories for a sketch or to create a new story.
Method signatures and docstrings:
- def get(self, sketch_id): Handles GET request to the resource. Args: sketch_id: Integer primary key for a sketch database model Retu... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class StoryListResource:
"""Resource to get all stories for a sketch or to create a new story."""
def get(self, sketch_id):
"""Handles GET request to the resource. Args: sketch_id: Integer primary key for a sketch database model Returns: Stories in JSON (instance of flask.wrappers.Response... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StoryListResource:
"""Resource to get all stories for a sketch or to create a new story."""
def get(self, sketch_id):
"""Handles GET request to the resource. Args: sketch_id: Integer primary key for a sketch database model Returns: Stories in JSON (instance of flask.wrappers.Response)"""
... | the_stack_v2_python_sparse | timesketch/api/v1/resources/story.py | google/timesketch | train | 2,263 |
3667a6c0b11f3cbe4f6c1bac746f63742f239fd4 | [
"Settings.constructSettings()\nMainFramework.settings = Settings.getSettings()\nlogging.info('construct settings successfully')",
"try:\n wb_plan = self.settings.loadPanFileAndSetCaseNumber()\n wk_plan_sheet = wb_plan['Sheet1']\n for test_case_number in range(2, self.settings.TestCaseNumbers + 2):\n ... | <|body_start_0|>
Settings.constructSettings()
MainFramework.settings = Settings.getSettings()
logging.info('construct settings successfully')
<|end_body_0|>
<|body_start_1|>
try:
wb_plan = self.settings.loadPanFileAndSetCaseNumber()
wk_plan_sheet = wb_plan['Sheet... | a circulator | MainFramework | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainFramework:
"""a circulator"""
def setUpClass(cls):
"""set up before execute test"""
<|body_0|>
def test_execute(self):
"""execute each test step by step"""
<|body_1|>
def tearDownClass(cls):
"""generate HTML report after execute test fini... | stack_v2_sparse_classes_36k_train_027634 | 4,747 | no_license | [
{
"docstring": "set up before execute test",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "execute each test step by step",
"name": "test_execute",
"signature": "def test_execute(self)"
},
{
"docstring": "generate HTML report after execute test finis... | 3 | null | Implement the Python class `MainFramework` described below.
Class description:
a circulator
Method signatures and docstrings:
- def setUpClass(cls): set up before execute test
- def test_execute(self): execute each test step by step
- def tearDownClass(cls): generate HTML report after execute test finished | Implement the Python class `MainFramework` described below.
Class description:
a circulator
Method signatures and docstrings:
- def setUpClass(cls): set up before execute test
- def test_execute(self): execute each test step by step
- def tearDownClass(cls): generate HTML report after execute test finished
<|skeleto... | ac197b0a73a5ba62cf2e2133399853a7bf678d3c | <|skeleton|>
class MainFramework:
"""a circulator"""
def setUpClass(cls):
"""set up before execute test"""
<|body_0|>
def test_execute(self):
"""execute each test step by step"""
<|body_1|>
def tearDownClass(cls):
"""generate HTML report after execute test fini... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MainFramework:
"""a circulator"""
def setUpClass(cls):
"""set up before execute test"""
Settings.constructSettings()
MainFramework.settings = Settings.getSettings()
logging.info('construct settings successfully')
def test_execute(self):
"""execute each test st... | the_stack_v2_python_sparse | SeleniumPythonFramework/src/main_framework.py | xuanyuanchl/AutomationFrameworks | train | 2 |
82a4f2137c89ee6aa3b9eaa799afeece6364bea8 | [
"datasets = tfds.load('ted_hrlr_translate/pt_to_en', as_supervised=True)\nself.data_train = datasets['train']\nself.data_valid = datasets['validation']\nself.tokenizer_pt, self.tokenizer_en = self.tokenize_dataset(self.data_train)",
"pt = tfds.deprecated.text.SubwordTextEncoder.build_from_corpus((pt.numpy() for p... | <|body_start_0|>
datasets = tfds.load('ted_hrlr_translate/pt_to_en', as_supervised=True)
self.data_train = datasets['train']
self.data_valid = datasets['validation']
self.tokenizer_pt, self.tokenizer_en = self.tokenize_dataset(self.data_train)
<|end_body_0|>
<|body_start_1|>
pt ... | Class | Dataset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""Class"""
def __init__(self):
"""Initialize"""
<|body_0|>
def tokenize_dataset(self, data):
"""Method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
datasets = tfds.load('ted_hrlr_translate/pt_to_en', as_supervised=True)
self... | stack_v2_sparse_classes_36k_train_027635 | 751 | no_license | [
{
"docstring": "Initialize",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method",
"name": "tokenize_dataset",
"signature": "def tokenize_dataset(self, data)"
}
] | 2 | null | Implement the Python class `Dataset` described below.
Class description:
Class
Method signatures and docstrings:
- def __init__(self): Initialize
- def tokenize_dataset(self, data): Method | Implement the Python class `Dataset` described below.
Class description:
Class
Method signatures and docstrings:
- def __init__(self): Initialize
- def tokenize_dataset(self, data): Method
<|skeleton|>
class Dataset:
"""Class"""
def __init__(self):
"""Initialize"""
<|body_0|>
def tokeni... | b5e8f1253309567ca7be71b9575a150de1be3820 | <|skeleton|>
class Dataset:
"""Class"""
def __init__(self):
"""Initialize"""
<|body_0|>
def tokenize_dataset(self, data):
"""Method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataset:
"""Class"""
def __init__(self):
"""Initialize"""
datasets = tfds.load('ted_hrlr_translate/pt_to_en', as_supervised=True)
self.data_train = datasets['train']
self.data_valid = datasets['validation']
self.tokenizer_pt, self.tokenizer_en = self.tokenize_datas... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/0-dataset.py | jadsm98/holbertonschool-machine_learning | train | 0 |
fcc49692f1522fe4cd91f45539cfab743bde6903 | [
"if len(strs) == 1:\n return strs[0]\nans = ''\nstrs.sort(key=lambda x: len(x))\nfor i in range(len(strs[0])):\n substr = strs[0][:i + 1]\n for other in strs[1:]:\n not_prefix = False\n for k in range(len(substr)):\n if substr[k] != other[k]:\n not_prefix = True\n ... | <|body_start_0|>
if len(strs) == 1:
return strs[0]
ans = ''
strs.sort(key=lambda x: len(x))
for i in range(len(strs[0])):
substr = strs[0][:i + 1]
for other in strs[1:]:
not_prefix = False
for k in range(len(substr)):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix2(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(strs) == 1:
... | stack_v2_sparse_classes_36k_train_027636 | 2,282 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix",
"signature": "def longestCommonPrefix(self, strs)"
},
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix2",
"signature": "def longestCommonPrefix2(self, strs)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix2(self, strs): :type strs: List[str] :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix2(self, strs): :type strs: List[str] :rtype: str
<|skeleton|>
class Solution:
... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix2(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
if len(strs) == 1:
return strs[0]
ans = ''
strs.sort(key=lambda x: len(x))
for i in range(len(strs[0])):
substr = strs[0][:i + 1]
for other in strs... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00014.Longest Common Prefix.py | roger6blog/LeetCode | train | 0 | |
1c7d2f05f112fe0cc7903e99deee3399dbda45ea | [
"ou = 0\nji = 1\nlength = len(A)\nwhile ou < length and ji < length:\n while ou < length and A[ou] % 2 == 0:\n ou += 2\n if ou < length and ji < length:\n A[ou], A[ji] = (A[ji], A[ou])\n while ji < length and A[ji] % 2 != 0:\n ji += 2\n if ou < length and ji < length:\n A[ji]... | <|body_start_0|>
ou = 0
ji = 1
length = len(A)
while ou < length and ji < length:
while ou < length and A[ou] % 2 == 0:
ou += 2
if ou < length and ji < length:
A[ou], A[ji] = (A[ji], A[ou])
while ji < length and A[ji] % ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortArrayByParityII(self, A: List[int]) -> List[int]:
"""func: 双指针法 param {list} return {list}"""
<|body_0|>
def sortArrayByParityII2(self, A: List[int]) -> List[int]:
"""func: 遍历一遍数组把所有的偶数放进 ans[0]，ans[2]，ans[4]，依次类推。 再遍历一遍数组把所有的奇数依次放进 ans[1]，ans[3]，an... | stack_v2_sparse_classes_36k_train_027637 | 1,599 | no_license | [
{
"docstring": "func: 双指针法 param {list} return {list}",
"name": "sortArrayByParityII",
"signature": "def sortArrayByParityII(self, A: List[int]) -> List[int]"
},
{
"docstring": "func: 遍历一遍数组把所有的偶数放进 ans[0]，ans[2]，ans[4]，依次类推。 再遍历一遍数组把所有的奇数依次放进 ans[1]，ans[3]，ans[5]，依次类推。 param {list} return {list... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParityII(self, A: List[int]) -> List[int]: func: 双指针法 param {list} return {list}
- def sortArrayByParityII2(self, A: List[int]) -> List[int]: func: 遍历一遍数组把所有的偶数放进 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParityII(self, A: List[int]) -> List[int]: func: 双指针法 param {list} return {list}
- def sortArrayByParityII2(self, A: List[int]) -> List[int]: func: 遍历一遍数组把所有的偶数放进 ... | 62c9dc7f04d6f4122274e82427901af55af113f9 | <|skeleton|>
class Solution:
def sortArrayByParityII(self, A: List[int]) -> List[int]:
"""func: 双指针法 param {list} return {list}"""
<|body_0|>
def sortArrayByParityII2(self, A: List[int]) -> List[int]:
"""func: 遍历一遍数组把所有的偶数放进 ans[0]，ans[2]，ans[4]，依次类推。 再遍历一遍数组把所有的奇数依次放进 ans[1]，ans[3]，an... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortArrayByParityII(self, A: List[int]) -> List[int]:
"""func: 双指针法 param {list} return {list}"""
ou = 0
ji = 1
length = len(A)
while ou < length and ji < length:
while ou < length and A[ou] % 2 == 0:
ou += 2
if ou <... | the_stack_v2_python_sparse | 双指针/932.py | CodingProgrammer/Algorithm | train | 0 | |
cfa46d65a20a4a901beed2eb9fbdc2c25b80f446 | [
"if root is None:\n return ''\ns = str(root.val)\nif root.children:\n for child in root.children:\n s += '{' + self.serialize(child) + '}'\nreturn s",
"start = data.find('{')\nif start < 0:\n return Node(int(data), []) if data else None\nroot, loc = (Node(int(data[:start]), []), 0)\nfor index, cha... | <|body_start_0|>
if root is None:
return ''
s = str(root.val)
if root.children:
for child in root.children:
s += '{' + self.serialize(child) + '}'
return s
<|end_body_0|>
<|body_start_1|>
start = data.find('{')
if start < 0:
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_027638 | 1,314 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def deserialize(self, ... | 2 | stack_v2_sparse_classes_30k_train_000621 | 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: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | 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: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Nod... | 63442050851125b4358b0046e0f52255086793c6 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|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: Node :rtype: str"""
if root is None:
return ''
s = str(root.val)
if root.children:
for child in root.children:
s += '{' + self.serialize(child) + '}'
... | the_stack_v2_python_sparse | serializeDeserializeTree.py | SarthakDubey/Algorithms_and_Data_Structures_in_Python | train | 1 | |
eac0161a70cd6ae7415ac33de27bbd97916a5be8 | [
"res = 0\nflag = 0\ncount = {}\nfor i in s:\n if i in count:\n count[i] += 1\n else:\n count[i] = 1\nfor c in count.values():\n if c % 2 == 0:\n res += c\n else:\n res += c - 1\n flag = 1\nif flag == 1:\n return res + 1\nreturn res",
"letter = [chr(i) for i in ran... | <|body_start_0|>
res = 0
flag = 0
count = {}
for i in s:
if i in count:
count[i] += 1
else:
count[i] = 1
for c in count.values():
if c % 2 == 0:
res += c
else:
res += c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = 0
flag = 0
count = {}
for i... | stack_v2_sparse_classes_36k_train_027639 | 1,286 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005889 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: int
- def longestPalindrome(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 longestPalindrome(self, s): :type s: str :rtype: int
- def longestPalindrome(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def longestPalindrome(self,... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestPalindrome(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 longestPalindrome(self, s):
""":type s: str :rtype: int"""
res = 0
flag = 0
count = {}
for i in s:
if i in count:
count[i] += 1
else:
count[i] = 1
for c in count.values():
if c % 2... | the_stack_v2_python_sparse | code/409#Longest Palindrome.py | EachenKuang/LeetCode | train | 28 | |
21a44d601ba534026203509f13c85f04e5ea12ac | [
"super(TabularQAttackerBotAgent, self).__init__(game_config)\nif q_table_path is None:\n raise ValueError('Cannot create a TabularQAttackerBotAgent without specifying the path to the Q-table')\nself.q_table_path = q_table_path\nself.Q = np.load(q_table_path)",
"actions = list(range(self.game_config.num_attack_... | <|body_start_0|>
super(TabularQAttackerBotAgent, self).__init__(game_config)
if q_table_path is None:
raise ValueError('Cannot create a TabularQAttackerBotAgent without specifying the path to the Q-table')
self.q_table_path = q_table_path
self.Q = np.load(q_table_path)
<|end_... | Class implementing an attack policy that acts greedily according to a given Q-table | TabularQAttackerBotAgent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TabularQAttackerBotAgent:
"""Class implementing an attack policy that acts greedily according to a given Q-table"""
def __init__(self, game_config: GameConfig, q_table_path: str=None):
"""Constructor, initializes the policy :param game_config: the game configuration"""
<|body... | stack_v2_sparse_classes_36k_train_027640 | 2,005 | permissive | [
{
"docstring": "Constructor, initializes the policy :param game_config: the game configuration",
"name": "__init__",
"signature": "def __init__(self, game_config: GameConfig, q_table_path: str=None)"
},
{
"docstring": "Samples an action from the policy. :param game_state: the game state :return:... | 2 | stack_v2_sparse_classes_30k_train_017427 | Implement the Python class `TabularQAttackerBotAgent` described below.
Class description:
Class implementing an attack policy that acts greedily according to a given Q-table
Method signatures and docstrings:
- def __init__(self, game_config: GameConfig, q_table_path: str=None): Constructor, initializes the policy :pa... | Implement the Python class `TabularQAttackerBotAgent` described below.
Class description:
Class implementing an attack policy that acts greedily according to a given Q-table
Method signatures and docstrings:
- def __init__(self, game_config: GameConfig, q_table_path: str=None): Constructor, initializes the policy :pa... | d10830fef55308d383c98b41b34688a7fceae357 | <|skeleton|>
class TabularQAttackerBotAgent:
"""Class implementing an attack policy that acts greedily according to a given Q-table"""
def __init__(self, game_config: GameConfig, q_table_path: str=None):
"""Constructor, initializes the policy :param game_config: the game configuration"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TabularQAttackerBotAgent:
"""Class implementing an attack policy that acts greedily according to a given Q-table"""
def __init__(self, game_config: GameConfig, q_table_path: str=None):
"""Constructor, initializes the policy :param game_config: the game configuration"""
super(TabularQAttac... | the_stack_v2_python_sparse | gym_idsgame/agents/training_agents/q_learning/tabular_q_learning/tabular_q_attacker_bot_agent.py | Limmen/gym-idsgame | train | 49 |
5762f256dc366fd4f990c4aab5d2940aa6ff5eb2 | [
"super(MeasureAfterSuccessScenario, self).__init__(egp=egp, request_cycle=request_cycle, request_prob=request_prob, min_pairs=min_pairs, max_pairs=max_pairs, min_fidelity=min_fidelity, tmax_pair=tmax_pair, num_requests=num_requests, purpose_id=purpose_id, priority=priority, store=store, atomic=atomic, t0=t0)\nself.... | <|body_start_0|>
super(MeasureAfterSuccessScenario, self).__init__(egp=egp, request_cycle=request_cycle, request_prob=request_prob, min_pairs=min_pairs, max_pairs=max_pairs, min_fidelity=min_fidelity, tmax_pair=tmax_pair, num_requests=num_requests, purpose_id=purpose_id, priority=priority, store=store, atomic=a... | MeasureAfterSuccessScenario | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MeasureAfterSuccessScenario:
def __init__(self, egp, request_cycle, request_prob=1, min_pairs=1, max_pairs=1, min_fidelity=0.2, tmax_pair=0, num_requests=0, purpose_id=1, priority=10, store=False, atomic=False, t0=0):
"""A simulation scenario that will immediately measure any entangled q... | stack_v2_sparse_classes_36k_train_027641 | 23,433 | permissive | [
{
"docstring": "A simulation scenario that will immediately measure any entangled qubits generated by the EGP. EGP simulation scenario that schedules create calls onto the EGP and acts as a higher layer protocol that can collect the ok messages and errors returned by the EGP operation. A request is scheduled ev... | 3 | stack_v2_sparse_classes_30k_train_021569 | Implement the Python class `MeasureAfterSuccessScenario` described below.
Class description:
Implement the MeasureAfterSuccessScenario class.
Method signatures and docstrings:
- def __init__(self, egp, request_cycle, request_prob=1, min_pairs=1, max_pairs=1, min_fidelity=0.2, tmax_pair=0, num_requests=0, purpose_id=1... | Implement the Python class `MeasureAfterSuccessScenario` described below.
Class description:
Implement the MeasureAfterSuccessScenario class.
Method signatures and docstrings:
- def __init__(self, egp, request_cycle, request_prob=1, min_pairs=1, max_pairs=1, min_fidelity=0.2, tmax_pair=0, num_requests=0, purpose_id=1... | 552f4b59d4deb5e838b21d569b5c4fd835fa1494 | <|skeleton|>
class MeasureAfterSuccessScenario:
def __init__(self, egp, request_cycle, request_prob=1, min_pairs=1, max_pairs=1, min_fidelity=0.2, tmax_pair=0, num_requests=0, purpose_id=1, priority=10, store=False, atomic=False, t0=0):
"""A simulation scenario that will immediately measure any entangled q... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MeasureAfterSuccessScenario:
def __init__(self, egp, request_cycle, request_prob=1, min_pairs=1, max_pairs=1, min_fidelity=0.2, tmax_pair=0, num_requests=0, purpose_id=1, priority=10, store=False, atomic=False, t0=0):
"""A simulation scenario that will immediately measure any entangled qubits generate... | the_stack_v2_python_sparse | qlinklayer/scenario.py | SoftwareQuTech/QLinkLayerSimulations | train | 9 | |
7c3468c1036066a2fceabc8abd2cbb06a707d7e0 | [
"if lang in self.ASIAN_TYPED_LANGUAGES:\n super(sppasNumAsianType, self).__init__(lang, dictionary)\nelse:\n raise sppasValueError(lang, str(sppasNumBase.ASIAN_TYPED_LANGUAGES))\nfor i in sppasNumAsianType.NUMBER_LIST:\n if self._lang_dict.is_unk(str(i)):\n raise sppasValueError(self._lang_dict, str... | <|body_start_0|>
if lang in self.ASIAN_TYPED_LANGUAGES:
super(sppasNumAsianType, self).__init__(lang, dictionary)
else:
raise sppasValueError(lang, str(sppasNumBase.ASIAN_TYPED_LANGUAGES))
for i in sppasNumAsianType.NUMBER_LIST:
if self._lang_dict.is_unk(str(i... | sppasNumAsianType | [
"MIT",
"GFDL-1.1-or-later",
"GPL-3.0-only",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sppasNumAsianType:
def __init__(self, lang=None, dictionary=None):
"""Create an instance of sppasNumAsianType :param lang: (str) name of the language"""
<|body_0|>
def _tenth_of_thousands(self, number):
"""Return the "wordified" version of a tenth of a thousand numbe... | stack_v2_sparse_classes_36k_train_027642 | 4,832 | permissive | [
{
"docstring": "Create an instance of sppasNumAsianType :param lang: (str) name of the language",
"name": "__init__",
"signature": "def __init__(self, lang=None, dictionary=None)"
},
{
"docstring": "Return the \"wordified\" version of a tenth of a thousand number Returns the word corresponding t... | 3 | stack_v2_sparse_classes_30k_train_003941 | Implement the Python class `sppasNumAsianType` described below.
Class description:
Implement the sppasNumAsianType class.
Method signatures and docstrings:
- def __init__(self, lang=None, dictionary=None): Create an instance of sppasNumAsianType :param lang: (str) name of the language
- def _tenth_of_thousands(self, ... | Implement the Python class `sppasNumAsianType` described below.
Class description:
Implement the sppasNumAsianType class.
Method signatures and docstrings:
- def __init__(self, lang=None, dictionary=None): Create an instance of sppasNumAsianType :param lang: (str) name of the language
- def _tenth_of_thousands(self, ... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class sppasNumAsianType:
def __init__(self, lang=None, dictionary=None):
"""Create an instance of sppasNumAsianType :param lang: (str) name of the language"""
<|body_0|>
def _tenth_of_thousands(self, number):
"""Return the "wordified" version of a tenth of a thousand numbe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class sppasNumAsianType:
def __init__(self, lang=None, dictionary=None):
"""Create an instance of sppasNumAsianType :param lang: (str) name of the language"""
if lang in self.ASIAN_TYPED_LANGUAGES:
super(sppasNumAsianType, self).__init__(lang, dictionary)
else:
raise ... | the_stack_v2_python_sparse | sppas/sppas/src/annotations/TextNorm/num2text/num_asian_lang.py | mirfan899/MTTS | train | 0 | |
7bc1783af65e3191d92d49d03a6a53ff5acd504c | [
"super().__init__()\nself.dense_h_h4 = nn.Linear(n_hidden, n_hidden * 4)\nself.activation = nn.GELU()\nself.dense_h4_h = nn.Linear(n_hidden * 4, n_hidden)",
"x = self.dense_h_h4(x)\nx = self.activation(x)\nx = self.dense_h4_h(x)\nreturn x"
] | <|body_start_0|>
super().__init__()
self.dense_h_h4 = nn.Linear(n_hidden, n_hidden * 4)
self.activation = nn.GELU()
self.dense_h4_h = nn.Linear(n_hidden * 4, n_hidden)
<|end_body_0|>
<|body_start_1|>
x = self.dense_h_h4(x)
x = self.activation(x)
x = self.dense_h4... | ## Feedforward Network | FFNLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FFNLayer:
"""## Feedforward Network"""
def __init__(self, n_hidden: int=6144):
""":param n_hidden: is the embedding size"""
<|body_0|>
def forward(self, x: torch.Tensor):
""":param x: has shape `[batch_size, seq_len, n_hidden]`"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_027643 | 13,522 | no_license | [
{
"docstring": ":param n_hidden: is the embedding size",
"name": "__init__",
"signature": "def __init__(self, n_hidden: int=6144)"
},
{
"docstring": ":param x: has shape `[batch_size, seq_len, n_hidden]`",
"name": "forward",
"signature": "def forward(self, x: torch.Tensor)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000611 | Implement the Python class `FFNLayer` described below.
Class description:
## Feedforward Network
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144): :param n_hidden: is the embedding size
- def forward(self, x: torch.Tensor): :param x: has shape `[batch_size, seq_len, n_hidden]` | Implement the Python class `FFNLayer` described below.
Class description:
## Feedforward Network
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144): :param n_hidden: is the embedding size
- def forward(self, x: torch.Tensor): :param x: has shape `[batch_size, seq_len, n_hidden]`
<|skeleton|>
... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class FFNLayer:
"""## Feedforward Network"""
def __init__(self, n_hidden: int=6144):
""":param n_hidden: is the embedding size"""
<|body_0|>
def forward(self, x: torch.Tensor):
""":param x: has shape `[batch_size, seq_len, n_hidden]`"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FFNLayer:
"""## Feedforward Network"""
def __init__(self, n_hidden: int=6144):
""":param n_hidden: is the embedding size"""
super().__init__()
self.dense_h_h4 = nn.Linear(n_hidden, n_hidden * 4)
self.activation = nn.GELU()
self.dense_h4_h = nn.Linear(n_hidden * 4, ... | the_stack_v2_python_sparse | generated/test_labmlai_neox.py | jansel/pytorch-jit-paritybench | train | 35 |
d3282307ef6ab6885b00a49eea9b3477644a4f65 | [
"if nums == []:\n return\nroot_val = max(nums)\nroot_idx = nums.index(root_val)\nroot = TreeNode(root_val)\nroot.left = self.constructMaximumBinaryTree(nums[:root_idx])\nroot.right = self.constructMaximumBinaryTree(nums[root_idx + 1:])\nreturn root",
"if len(nums) == 0:\n return None\nstack = []\nfor num in... | <|body_start_0|>
if nums == []:
return
root_val = max(nums)
root_idx = nums.index(root_val)
root = TreeNode(root_val)
root.left = self.constructMaximumBinaryTree(nums[:root_idx])
root.right = self.constructMaximumBinaryTree(nums[root_idx + 1:])
return ... | Recursive solution Stats: O(n^2) runtime -- need to find max for every single num in worse case | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Recursive solution Stats: O(n^2) runtime -- need to find max for every single num in worse case"""
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_0|>
def constructMaximumBinaryTree(self, nums):
""":typ... | stack_v2_sparse_classes_36k_train_027644 | 1,897 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "constructMaximumBinaryTree",
"signature": "def constructMaximumBinaryTree(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "constructMaximumBinaryTree",
"signature": "def constructMaximumBin... | 2 | stack_v2_sparse_classes_30k_train_016470 | Implement the Python class `Solution` described below.
Class description:
Recursive solution Stats: O(n^2) runtime -- need to find max for every single num in worse case
Method signatures and docstrings:
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def constructMaximumBinaryT... | Implement the Python class `Solution` described below.
Class description:
Recursive solution Stats: O(n^2) runtime -- need to find max for every single num in worse case
Method signatures and docstrings:
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def constructMaximumBinaryT... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
"""Recursive solution Stats: O(n^2) runtime -- need to find max for every single num in worse case"""
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_0|>
def constructMaximumBinaryTree(self, nums):
""":typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Recursive solution Stats: O(n^2) runtime -- need to find max for every single num in worse case"""
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
if nums == []:
return
root_val = max(nums)
root_idx = nums.i... | the_stack_v2_python_sparse | 654-max-binary_tree.py | stevestar888/leetcode-problems | train | 2 |
f3c2e4533417e6a493e634bf4091e7f6bcb93dbf | [
"self.chron_schedule = chron_schedule\nself.max_reminders = max_reminders\nself.email = email\nself.sms = sms\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nchron_schedule = dictionary.get('chronSchedule')\nmax_reminders = dictionary.get('maxReminders')\nemail = No... | <|body_start_0|>
self.chron_schedule = chron_schedule
self.max_reminders = max_reminders
self.email = email
self.sms = sms
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
chron_sche... | Implementation of the 'Reminder188' model. Here you can setup email/sms notifications reminding the signers that they have unsigned documents. Attributes: chron_schedule (string): Define a chron expression to control the interval of the reminders (Use utc time). We use quartz cron expressions, read more about it here: ... | Reminder188 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reminder188:
"""Implementation of the 'Reminder188' model. Here you can setup email/sms notifications reminding the signers that they have unsigned documents. Attributes: chron_schedule (string): Define a chron expression to control the interval of the reminders (Use utc time). We use quartz cron... | stack_v2_sparse_classes_36k_train_027645 | 3,499 | permissive | [
{
"docstring": "Constructor for the Reminder188 class",
"name": "__init__",
"signature": "def __init__(self, chron_schedule=None, max_reminders=None, email=None, sms=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictiona... | 2 | null | Implement the Python class `Reminder188` described below.
Class description:
Implementation of the 'Reminder188' model. Here you can setup email/sms notifications reminding the signers that they have unsigned documents. Attributes: chron_schedule (string): Define a chron expression to control the interval of the remin... | Implement the Python class `Reminder188` described below.
Class description:
Implementation of the 'Reminder188' model. Here you can setup email/sms notifications reminding the signers that they have unsigned documents. Attributes: chron_schedule (string): Define a chron expression to control the interval of the remin... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class Reminder188:
"""Implementation of the 'Reminder188' model. Here you can setup email/sms notifications reminding the signers that they have unsigned documents. Attributes: chron_schedule (string): Define a chron expression to control the interval of the reminders (Use utc time). We use quartz cron... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Reminder188:
"""Implementation of the 'Reminder188' model. Here you can setup email/sms notifications reminding the signers that they have unsigned documents. Attributes: chron_schedule (string): Define a chron expression to control the interval of the reminders (Use utc time). We use quartz cron expressions,... | the_stack_v2_python_sparse | idfy_rest_client/models/reminder_188.py | dealflowteam/Idfy | train | 0 |
22e16b7044620e303415369fdf25b03a7db23921 | [
"super().__init__(coordinator=coordinator)\nself._service_key = service_key\nself.entity_id = f'{SENSOR_DOMAIN}.{service}_{description.key}'\nself.entity_description = description\nself._attr_unique_id = f'{coordinator.config_entry.entry_id}_{service_key}_{description.key}'\nself._attr_device_info = DeviceInfo(entr... | <|body_start_0|>
super().__init__(coordinator=coordinator)
self._service_key = service_key
self.entity_id = f'{SENSOR_DOMAIN}.{service}_{description.key}'
self.entity_description = description
self._attr_unique_id = f'{coordinator.config_entry.entry_id}_{service_key}_{description... | Defines an P1 Monitor sensor. | P1MonitorSensorEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class P1MonitorSensorEntity:
"""Defines an P1 Monitor sensor."""
def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None:
"""Initialize ... | stack_v2_sparse_classes_36k_train_027646 | 11,570 | permissive | [
{
"docstring": "Initialize P1 Monitor sensor.",
"name": "__init__",
"signature": "def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None"
},
{
... | 2 | null | Implement the Python class `P1MonitorSensorEntity` described below.
Class description:
Defines an P1 Monitor sensor.
Method signatures and docstrings:
- def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', '... | Implement the Python class `P1MonitorSensorEntity` described below.
Class description:
Defines an P1 Monitor sensor.
Method signatures and docstrings:
- def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', '... | 2e65b77b2b5c17919939481f327963abdfdc53f0 | <|skeleton|>
class P1MonitorSensorEntity:
"""Defines an P1 Monitor sensor."""
def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None:
"""Initialize ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class P1MonitorSensorEntity:
"""Defines an P1 Monitor sensor."""
def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None:
"""Initialize P1 Monitor se... | the_stack_v2_python_sparse | homeassistant/components/p1_monitor/sensor.py | konnected-io/home-assistant | train | 24 |
1c585f5c401c87591a6dd2ac654fcc2390ee2943 | [
"self.snake = deque()\nself.snake.append([0, 0])\nself.snake_set = set()\nself.snake_set.add((0, 0))\nself.score = 0\nself.food = deque()\nfor ele in food:\n self.food.append(ele)\nself.width = width\nself.height = height\nself.directions = {'U': [-1, 0], 'L': [0, -1], 'R': [0, 1], 'D': [1, 0]}",
"head = self.... | <|body_start_0|>
self.snake = deque()
self.snake.append([0, 0])
self.snake_set = set()
self.snake_set.add((0, 0))
self.score = 0
self.food = deque()
for ele in food:
self.food.append(ele)
self.width = width
self.height = height
... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], t... | stack_v2_sparse_classes_36k_train_027647 | 2,425 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0].",
"name": "__init__",
"signature": "def __init__(self, widt... | 2 | stack_v2_sparse_classes_30k_train_006206 | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | 9b38a7742a819ac3795ea295e371e26bb5bfc28c | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is a... | the_stack_v2_python_sparse | 353. Design Snake Game.py | dundunmao/LeetCode2019 | train | 0 | |
4dbbcf3dfff4a5869f24b96809f25d1690474439 | [
"super().__init__(object_list, per_page, orphans, allow_empty_first_page)\nself.now_page = int(now_page)\nself.max_display_page = int(max_display_page)",
"if self.num_pages < self.max_display_page:\n return range(1, self.num_pages + 1)\nhalf_page = int(self.max_display_page // 2)\nif self.now_page <= half_page... | <|body_start_0|>
super().__init__(object_list, per_page, orphans, allow_empty_first_page)
self.now_page = int(now_page)
self.max_display_page = int(max_display_page)
<|end_body_0|>
<|body_start_1|>
if self.num_pages < self.max_display_page:
return range(1, self.num_pages + 1... | MyPaginator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyPaginator:
def __init__(self, now_page, max_display_page, object_list, per_page, orphans=0, allow_empty_first_page=True):
"""对这个类进行重写 :param now_page: 当前页数 :param max_display_page: 最大展示页数, 如果数据量很大， 我们只能让他动态的展示最大页数"""
<|body_0|>
def page_range(self):
"""重写这个页码范围显示办法... | stack_v2_sparse_classes_36k_train_027648 | 1,588 | no_license | [
{
"docstring": "对这个类进行重写 :param now_page: 当前页数 :param max_display_page: 最大展示页数, 如果数据量很大， 我们只能让他动态的展示最大页数",
"name": "__init__",
"signature": "def __init__(self, now_page, max_display_page, object_list, per_page, orphans=0, allow_empty_first_page=True)"
},
{
"docstring": "重写这个页码范围显示办法 :return: 返回自... | 2 | stack_v2_sparse_classes_30k_train_017096 | Implement the Python class `MyPaginator` described below.
Class description:
Implement the MyPaginator class.
Method signatures and docstrings:
- def __init__(self, now_page, max_display_page, object_list, per_page, orphans=0, allow_empty_first_page=True): 对这个类进行重写 :param now_page: 当前页数 :param max_display_page: 最大展示页... | Implement the Python class `MyPaginator` described below.
Class description:
Implement the MyPaginator class.
Method signatures and docstrings:
- def __init__(self, now_page, max_display_page, object_list, per_page, orphans=0, allow_empty_first_page=True): 对这个类进行重写 :param now_page: 当前页数 :param max_display_page: 最大展示页... | 8106b160411027e52676a3093188f819a18dd793 | <|skeleton|>
class MyPaginator:
def __init__(self, now_page, max_display_page, object_list, per_page, orphans=0, allow_empty_first_page=True):
"""对这个类进行重写 :param now_page: 当前页数 :param max_display_page: 最大展示页数, 如果数据量很大， 我们只能让他动态的展示最大页数"""
<|body_0|>
def page_range(self):
"""重写这个页码范围显示办法... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyPaginator:
def __init__(self, now_page, max_display_page, object_list, per_page, orphans=0, allow_empty_first_page=True):
"""对这个类进行重写 :param now_page: 当前页数 :param max_display_page: 最大展示页数, 如果数据量很大， 我们只能让他动态的展示最大页数"""
super().__init__(object_list, per_page, orphans, allow_empty_first_page)
... | the_stack_v2_python_sparse | cst/MyPaginator.py | shalouzaixiayu/Django-Web | train | 1 | |
f95c21747e1138c18742f474651a3ba08acf832f | [
"category = Category.objects.as_admin(request.user, project_id, category_id)\nserializer = CategorySerializer(category)\nreturn Response(serializer.data)",
"category = Category.objects.as_admin(request.user, project_id, category_id)\nserializer = CategorySerializer(category, data=request.data, partial=True, field... | <|body_start_0|>
category = Category.objects.as_admin(request.user, project_id, category_id)
serializer = CategorySerializer(category)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
category = Category.objects.as_admin(request.user, project_id, category_id)
ser... | API endpoints for a category in the AJAX API. | CategoryUpdate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CategoryUpdate:
"""API endpoints for a category in the AJAX API."""
def get(self, request, project_id, category_id):
"""Handles the GET request. Parameters ---------- request : rest_framework.request.Request Object representing the request project_id : int Identifies the project in t... | stack_v2_sparse_classes_36k_train_027649 | 31,602 | permissive | [
{
"docstring": "Handles the GET request. Parameters ---------- request : rest_framework.request.Request Object representing the request project_id : int Identifies the project in the database category_id : int Identifies the category in the database Return ------ rest_framework.response.Response Response to the... | 2 | null | Implement the Python class `CategoryUpdate` described below.
Class description:
API endpoints for a category in the AJAX API.
Method signatures and docstrings:
- def get(self, request, project_id, category_id): Handles the GET request. Parameters ---------- request : rest_framework.request.Request Object representing... | Implement the Python class `CategoryUpdate` described below.
Class description:
API endpoints for a category in the AJAX API.
Method signatures and docstrings:
- def get(self, request, project_id, category_id): Handles the GET request. Parameters ---------- request : rest_framework.request.Request Object representing... | 16d31b5207de9f699fc01054baad1fe65ad1c3ca | <|skeleton|>
class CategoryUpdate:
"""API endpoints for a category in the AJAX API."""
def get(self, request, project_id, category_id):
"""Handles the GET request. Parameters ---------- request : rest_framework.request.Request Object representing the request project_id : int Identifies the project in t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CategoryUpdate:
"""API endpoints for a category in the AJAX API."""
def get(self, request, project_id, category_id):
"""Handles the GET request. Parameters ---------- request : rest_framework.request.Request Object representing the request project_id : int Identifies the project in the database c... | the_stack_v2_python_sparse | geokey/categories/views.py | NeolithEra/geokey | train | 0 |
1813abf401214184a47e0f68daeb9397d7fffd2e | [
"self.driver.switch_to.default_content()\nself.driver.switch_to.frame(self.frame_menu)\nif not self.menu_snmp.is_visible():\n self.menu_system_maintenance.click()\nself.menu_snmp.click()\nself.driver.switch_to.default_content()\nself.driver.switch_to.frame(self.frame_main)",
"self.driver.switch_to.default_cont... | <|body_start_0|>
self.driver.switch_to.default_content()
self.driver.switch_to.frame(self.frame_menu)
if not self.menu_snmp.is_visible():
self.menu_system_maintenance.click()
self.menu_snmp.click()
self.driver.switch_to.default_content()
self.driver.switch_to.... | Selenium Page Object Model: Menu Navigation. | MenuNavigator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MenuNavigator:
"""Selenium Page Object Model: Menu Navigation."""
def open_sysmain_snmp(self):
"""Navigate the menus to open the SNMP configuration panel."""
<|body_0|>
def open_sysmain_management(self, tab: Link):
"""Navigate the menus to open the SNMP configura... | stack_v2_sparse_classes_36k_train_027650 | 3,160 | permissive | [
{
"docstring": "Navigate the menus to open the SNMP configuration panel.",
"name": "open_sysmain_snmp",
"signature": "def open_sysmain_snmp(self)"
},
{
"docstring": "Navigate the menus to open the SNMP configuration panel.",
"name": "open_sysmain_management",
"signature": "def open_sysma... | 5 | stack_v2_sparse_classes_30k_train_001732 | Implement the Python class `MenuNavigator` described below.
Class description:
Selenium Page Object Model: Menu Navigation.
Method signatures and docstrings:
- def open_sysmain_snmp(self): Navigate the menus to open the SNMP configuration panel.
- def open_sysmain_management(self, tab: Link): Navigate the menus to op... | Implement the Python class `MenuNavigator` described below.
Class description:
Selenium Page Object Model: Menu Navigation.
Method signatures and docstrings:
- def open_sysmain_snmp(self): Navigate the menus to open the SNMP configuration panel.
- def open_sysmain_management(self, tab: Link): Navigate the menus to op... | 0b3e96b892fb332a1252fc231b30561b2374071f | <|skeleton|>
class MenuNavigator:
"""Selenium Page Object Model: Menu Navigation."""
def open_sysmain_snmp(self):
"""Navigate the menus to open the SNMP configuration panel."""
<|body_0|>
def open_sysmain_management(self, tab: Link):
"""Navigate the menus to open the SNMP configura... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MenuNavigator:
"""Selenium Page Object Model: Menu Navigation."""
def open_sysmain_snmp(self):
"""Navigate the menus to open the SNMP configuration panel."""
self.driver.switch_to.default_content()
self.driver.switch_to.frame(self.frame_menu)
if not self.menu_snmp.is_visib... | the_stack_v2_python_sparse | draytekwebadmin/pages/menu_navigator.py | dMajoIT/Draytek-Web-Auto-Configuration | train | 0 |
61b4ed94a064db234aba21de68d1ecd81cffc9fa | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IosHomeScreenFolder()",
"from .ios_home_screen_folder_page import IosHomeScreenFolderPage\nfrom .ios_home_screen_item import IosHomeScreenItem\nfrom .ios_home_screen_folder_page import IosHomeScreenFolderPage\nfrom .ios_home_screen_ite... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IosHomeScreenFolder()
<|end_body_0|>
<|body_start_1|>
from .ios_home_screen_folder_page import IosHomeScreenFolderPage
from .ios_home_screen_item import IosHomeScreenItem
from .i... | A folder containing pages of apps and web clips on the Home Screen. | IosHomeScreenFolder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IosHomeScreenFolder:
"""A folder containing pages of apps and web clips on the Home Screen."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenFolder:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse... | stack_v2_sparse_classes_36k_train_027651 | 2,589 | 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: IosHomeScreenFolder",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | null | Implement the Python class `IosHomeScreenFolder` described below.
Class description:
A folder containing pages of apps and web clips on the Home Screen.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenFolder: Creates a new instance of the a... | Implement the Python class `IosHomeScreenFolder` described below.
Class description:
A folder containing pages of apps and web clips on the Home Screen.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenFolder: Creates a new instance of the a... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IosHomeScreenFolder:
"""A folder containing pages of apps and web clips on the Home Screen."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenFolder:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IosHomeScreenFolder:
"""A folder containing pages of apps and web clips on the Home Screen."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosHomeScreenFolder:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pa... | the_stack_v2_python_sparse | msgraph/generated/models/ios_home_screen_folder.py | microsoftgraph/msgraph-sdk-python | train | 135 |
f82cdf9cae7087f97bd0d929c1c672c938c762f7 | [
"table_name, key_name = store.cls_infos[tname][:2]\ndata = values.copy()\n_id = data.pop(key_name, None)\nif _id is None:\n if not store.cls_infos[tname][AUTO_INC_IDX]:\n raise KeyError\n _id = auto_inc(store, table_name)\n if tname == 'player':\n _id = int(str(_id) + config.serverNo)\n va... | <|body_start_0|>
table_name, key_name = store.cls_infos[tname][:2]
data = values.copy()
_id = data.pop(key_name, None)
if _id is None:
if not store.cls_infos[tname][AUTO_INC_IDX]:
raise KeyError
_id = auto_inc(store, table_name)
if tnam... | 保存(新增或者更新) | SaveProc | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveProc:
"""保存(新增或者更新)"""
def simple(store, tname, values):
"""简单保存,保存序列化字典"""
<|body_0|>
def multi(store, tname, objs, insert):
"""批量保存,只支持批量新增或者批量修改,不要混新增和修改"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
table_name, key_name = store.cls_inf... | stack_v2_sparse_classes_36k_train_027652 | 15,019 | no_license | [
{
"docstring": "简单保存,保存序列化字典",
"name": "simple",
"signature": "def simple(store, tname, values)"
},
{
"docstring": "批量保存,只支持批量新增或者批量修改,不要混新增和修改",
"name": "multi",
"signature": "def multi(store, tname, objs, insert)"
}
] | 2 | null | Implement the Python class `SaveProc` described below.
Class description:
保存(新增或者更新)
Method signatures and docstrings:
- def simple(store, tname, values): 简单保存,保存序列化字典
- def multi(store, tname, objs, insert): 批量保存,只支持批量新增或者批量修改,不要混新增和修改 | Implement the Python class `SaveProc` described below.
Class description:
保存(新增或者更新)
Method signatures and docstrings:
- def simple(store, tname, values): 简单保存,保存序列化字典
- def multi(store, tname, objs, insert): 批量保存,只支持批量新增或者批量修改,不要混新增和修改
<|skeleton|>
class SaveProc:
"""保存(新增或者更新)"""
def simple(store, tname, ... | 026f95bd073288a273f64c339b1d414ff09df6e9 | <|skeleton|>
class SaveProc:
"""保存(新增或者更新)"""
def simple(store, tname, values):
"""简单保存,保存序列化字典"""
<|body_0|>
def multi(store, tname, objs, insert):
"""批量保存,只支持批量新增或者批量修改,不要混新增和修改"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaveProc:
"""保存(新增或者更新)"""
def simple(store, tname, values):
"""简单保存,保存序列化字典"""
table_name, key_name = store.cls_infos[tname][:2]
data = values.copy()
_id = data.pop(key_name, None)
if _id is None:
if not store.cls_infos[tname][AUTO_INC_IDX]:
... | the_stack_v2_python_sparse | code/lib/store/mongodb.py | hw233/gsdld_pokemon2 | train | 0 |
76eb52def293791c2c576ee9926e7ca84d2a3360 | [
"from .system import System\nsys: System = System.current()\nret = sys._op_cache.get_circt_mod(self)\nif ret is None:\n return sys._create_circt_mod(self)\nreturn ret",
"if len(self.generators) > 0:\n return msft.MSFTModuleOp(symbol, [(n, t._type) for n, t in self.inputs], [(n, t._type) for n, t in self.out... | <|body_start_0|>
from .system import System
sys: System = System.current()
ret = sys._op_cache.get_circt_mod(self)
if ret is None:
return sys._create_circt_mod(self)
return ret
<|end_body_0|>
<|body_start_1|>
if len(self.generators) > 0:
return ms... | Defines how a `Module` gets built. Extend the base class and customize. | ModuleBuilder | [
"LLVM-exception",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModuleBuilder:
"""Defines how a `Module` gets built. Extend the base class and customize."""
def circt_mod(self):
"""Get the raw CIRCT operation for the module definition. DO NOT store the returned value!!! It needs to get reaped after the current action (e.g. instantiation, generati... | stack_v2_sparse_classes_36k_train_027653 | 23,396 | permissive | [
{
"docstring": "Get the raw CIRCT operation for the module definition. DO NOT store the returned value!!! It needs to get reaped after the current action (e.g. instantiation, generation). Memory safety when interacting with native code can be painful.",
"name": "circt_mod",
"signature": "def circt_mod(s... | 4 | null | Implement the Python class `ModuleBuilder` described below.
Class description:
Defines how a `Module` gets built. Extend the base class and customize.
Method signatures and docstrings:
- def circt_mod(self): Get the raw CIRCT operation for the module definition. DO NOT store the returned value!!! It needs to get reap... | Implement the Python class `ModuleBuilder` described below.
Class description:
Defines how a `Module` gets built. Extend the base class and customize.
Method signatures and docstrings:
- def circt_mod(self): Get the raw CIRCT operation for the module definition. DO NOT store the returned value!!! It needs to get reap... | e6057090973eb8a428dce9d3e9ddb63ec4088b55 | <|skeleton|>
class ModuleBuilder:
"""Defines how a `Module` gets built. Extend the base class and customize."""
def circt_mod(self):
"""Get the raw CIRCT operation for the module definition. DO NOT store the returned value!!! It needs to get reaped after the current action (e.g. instantiation, generati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModuleBuilder:
"""Defines how a `Module` gets built. Extend the base class and customize."""
def circt_mod(self):
"""Get the raw CIRCT operation for the module definition. DO NOT store the returned value!!! It needs to get reaped after the current action (e.g. instantiation, generation). Memory s... | the_stack_v2_python_sparse | frontends/PyCDE/src/module.py | llvm/circt | train | 1,242 |
03a373cb1aaa5410629fd2820cc9f6ba06efb8d2 | [
"current_user = User.objects.get(pk=request.auth.user.id)\ntry:\n job = Job.objects.get(pk=request.data['job'], user=current_user)\nexcept Job.DoesNotExist as ex:\n return Response({'reason': ex.args[0]}, status=status.HTTP_404_NOT_FOUND)\nnote = JobNote()\nnote.author = current_user\nnote.job = job\nnote.con... | <|body_start_0|>
current_user = User.objects.get(pk=request.auth.user.id)
try:
job = Job.objects.get(pk=request.data['job'], user=current_user)
except Job.DoesNotExist as ex:
return Response({'reason': ex.args[0]}, status=status.HTTP_404_NOT_FOUND)
note = JobNote(... | JobNoteView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobNoteView:
def create(self, request):
"""Handle POST requests to create new job note"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Handle GET requests for a specific job note"""
<|body_1|>
def list(self, request):
"""Handle GET request... | stack_v2_sparse_classes_36k_train_027654 | 3,704 | no_license | [
{
"docstring": "Handle POST requests to create new job note",
"name": "create",
"signature": "def create(self, request)"
},
{
"docstring": "Handle GET requests for a specific job note",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
},
{
"docstring": "Han... | 5 | stack_v2_sparse_classes_30k_train_020273 | Implement the Python class `JobNoteView` described below.
Class description:
Implement the JobNoteView class.
Method signatures and docstrings:
- def create(self, request): Handle POST requests to create new job note
- def retrieve(self, request, pk=None): Handle GET requests for a specific job note
- def list(self, ... | Implement the Python class `JobNoteView` described below.
Class description:
Implement the JobNoteView class.
Method signatures and docstrings:
- def create(self, request): Handle POST requests to create new job note
- def retrieve(self, request, pk=None): Handle GET requests for a specific job note
- def list(self, ... | 12cb34b9a290a8445e8baaa6c454dd386a01fe29 | <|skeleton|>
class JobNoteView:
def create(self, request):
"""Handle POST requests to create new job note"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Handle GET requests for a specific job note"""
<|body_1|>
def list(self, request):
"""Handle GET request... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobNoteView:
def create(self, request):
"""Handle POST requests to create new job note"""
current_user = User.objects.get(pk=request.auth.user.id)
try:
job = Job.objects.get(pk=request.data['job'], user=current_user)
except Job.DoesNotExist as ex:
return... | the_stack_v2_python_sparse | apptrakzapi/views/job_note.py | nswalters/AppTrakz-API | train | 0 | |
baf5c2a9cff42f62d9b7da9f67955c9625444a67 | [
"if type(data) is not np.ndarray or len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nif data.shape[1] < 2:\n raise ValueError('data must contain multiple data points')\nmean = np.mean(data, axis=1).reshape((data.shape[0], 1))\nself.mean = mean\nself.cov = np.matmul(data - self.mean,... | <|body_start_0|>
if type(data) is not np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data must contain multiple data points')
mean = np.mean(data, axis=1).reshape((data.shape[0], 1))
s... | Multinormal Class | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Multinormal Class"""
def __init__(self, data):
"""Class contructor"""
<|body_0|>
def pdf(self, x):
"""public instance method that calculates the PDF at a data point"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if type(data) is... | stack_v2_sparse_classes_36k_train_027655 | 1,454 | no_license | [
{
"docstring": "Class contructor",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "public instance method that calculates the PDF at a data point",
"name": "pdf",
"signature": "def pdf(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006305 | Implement the Python class `MultiNormal` described below.
Class description:
Multinormal Class
Method signatures and docstrings:
- def __init__(self, data): Class contructor
- def pdf(self, x): public instance method that calculates the PDF at a data point | Implement the Python class `MultiNormal` described below.
Class description:
Multinormal Class
Method signatures and docstrings:
- def __init__(self, data): Class contructor
- def pdf(self, x): public instance method that calculates the PDF at a data point
<|skeleton|>
class MultiNormal:
"""Multinormal Class"""
... | cfc519b3290a1b8ecd6dc94f70c5220538ee7aa0 | <|skeleton|>
class MultiNormal:
"""Multinormal Class"""
def __init__(self, data):
"""Class contructor"""
<|body_0|>
def pdf(self, x):
"""public instance method that calculates the PDF at a data point"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""Multinormal Class"""
def __init__(self, data):
"""Class contructor"""
if type(data) is not np.ndarray or len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data must contain multi... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | shincap8/holbertonschool-machine_learning | train | 0 |
eb99e8040780d0bf89416f894726fc7d2d97cddc | [
"self.Z_map = Z_map\nperiods = list(Z_map.keys())\nvalues = list(Z_map.values())\nself.f = np.array([1 / x for x in periods[::-1]])\nself.omega = 2 * math.pi * self.f\nself.Zxx_interp = CubicSpline(self.omega, [x[0, 0] for x in values[::-1]], extrapolate=False)\nself.Zxy_interp = CubicSpline(self.omega, [x[0, 1] fo... | <|body_start_0|>
self.Z_map = Z_map
periods = list(Z_map.keys())
values = list(Z_map.values())
self.f = np.array([1 / x for x in periods[::-1]])
self.omega = 2 * math.pi * self.f
self.Zxx_interp = CubicSpline(self.omega, [x[0, 0] for x in values[::-1]], extrapolate=False)... | Zw_interpolator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Zw_interpolator:
def __init__(self, Z_map, extrapolate0=False):
"""Construct a cubic-spline 3-D E-M transfer function interpolater using the information in *Z_map* returned from :func:`parse_xml` as the function samples. If *extrapolate0*, then 0s are inserted in the transfer function re... | stack_v2_sparse_classes_36k_train_027656 | 15,502 | permissive | [
{
"docstring": "Construct a cubic-spline 3-D E-M transfer function interpolater using the information in *Z_map* returned from :func:`parse_xml` as the function samples. If *extrapolate0*, then 0s are inserted in the transfer function response where extrapolation would occur (this happens when transfer function... | 2 | stack_v2_sparse_classes_30k_train_002790 | Implement the Python class `Zw_interpolator` described below.
Class description:
Implement the Zw_interpolator class.
Method signatures and docstrings:
- def __init__(self, Z_map, extrapolate0=False): Construct a cubic-spline 3-D E-M transfer function interpolater using the information in *Z_map* returned from :func:... | Implement the Python class `Zw_interpolator` described below.
Class description:
Implement the Zw_interpolator class.
Method signatures and docstrings:
- def __init__(self, Z_map, extrapolate0=False): Construct a cubic-spline 3-D E-M transfer function interpolater using the information in *Z_map* returned from :func:... | e364be68cb0cadbeea10ca569963b8f99aa7b05b | <|skeleton|>
class Zw_interpolator:
def __init__(self, Z_map, extrapolate0=False):
"""Construct a cubic-spline 3-D E-M transfer function interpolater using the information in *Z_map* returned from :func:`parse_xml` as the function samples. If *extrapolate0*, then 0s are inserted in the transfer function re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Zw_interpolator:
def __init__(self, Z_map, extrapolate0=False):
"""Construct a cubic-spline 3-D E-M transfer function interpolater using the information in *Z_map* returned from :func:`parse_xml` as the function samples. If *extrapolate0*, then 0s are inserted in the transfer function response where e... | the_stack_v2_python_sparse | pyrsss/emtf/calc_e_3d.py | butala/pyrsss | train | 7 | |
6e4435718141c981c035f16699d94327133d63fd | [
"var_data = self.loadCustomData(save_filename=save_filename)\nif var_data:\n width = var_data.get('width', -1)\n height = var_data.get('height', -1)\n if width > 0 and height > 0:\n self.SetSize(wx.Size(width, height))\n x = var_data.get('x', -1)\n y = var_data.get('y', -1)\n if x <= 0 and ... | <|body_start_0|>
var_data = self.loadCustomData(save_filename=save_filename)
if var_data:
width = var_data.get('width', -1)
height = var_data.get('height', -1)
if width > 0 and height > 0:
self.SetSize(wx.Size(width, height))
x = var_data.g... | Manager for storing properties of wxPython forms. | iqStoredWxFormsManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iqStoredWxFormsManager:
"""Manager for storing properties of wxPython forms."""
def loadCustomProperties(self, save_filename=None):
"""Load custom properties. :param save_filename: Stored file name. :return: True/False."""
<|body_0|>
def saveCustomProperties(self, save_f... | stack_v2_sparse_classes_36k_train_027657 | 1,564 | no_license | [
{
"docstring": "Load custom properties. :param save_filename: Stored file name. :return: True/False.",
"name": "loadCustomProperties",
"signature": "def loadCustomProperties(self, save_filename=None)"
},
{
"docstring": "Save custom properties. :param save_filename: Stored file name. :return: Tru... | 2 | stack_v2_sparse_classes_30k_train_018328 | Implement the Python class `iqStoredWxFormsManager` described below.
Class description:
Manager for storing properties of wxPython forms.
Method signatures and docstrings:
- def loadCustomProperties(self, save_filename=None): Load custom properties. :param save_filename: Stored file name. :return: True/False.
- def s... | Implement the Python class `iqStoredWxFormsManager` described below.
Class description:
Manager for storing properties of wxPython forms.
Method signatures and docstrings:
- def loadCustomProperties(self, save_filename=None): Load custom properties. :param save_filename: Stored file name. :return: True/False.
- def s... | 7550e242746cb2fb1219474463f8db21f8e3e114 | <|skeleton|>
class iqStoredWxFormsManager:
"""Manager for storing properties of wxPython forms."""
def loadCustomProperties(self, save_filename=None):
"""Load custom properties. :param save_filename: Stored file name. :return: True/False."""
<|body_0|>
def saveCustomProperties(self, save_f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class iqStoredWxFormsManager:
"""Manager for storing properties of wxPython forms."""
def loadCustomProperties(self, save_filename=None):
"""Load custom properties. :param save_filename: Stored file name. :return: True/False."""
var_data = self.loadCustomData(save_filename=save_filename)
... | the_stack_v2_python_sparse | iq/engine/wx/stored_wx_form_manager.py | XHermitOne/iq_framework | train | 1 |
298a0fd207189d1adcb5c82b6d53c16d8b3815bb | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn PlannerPlanDetails()",
"from .entity import Entity\nfrom .planner_category_descriptions import PlannerCategoryDescriptions\nfrom .planner_user_ids import PlannerUserIds\nfrom .entity import Entity\nfrom .planner_category_descriptions i... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return PlannerPlanDetails()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .planner_category_descriptions import PlannerCategoryDescriptions
from .planner_user_ids impo... | PlannerPlanDetails | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlannerPlanDetails:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PlannerPlanDetails:
"""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 obje... | stack_v2_sparse_classes_36k_train_027658 | 3,086 | 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: PlannerPlanDetails",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_... | 3 | stack_v2_sparse_classes_30k_train_021099 | Implement the Python class `PlannerPlanDetails` described below.
Class description:
Implement the PlannerPlanDetails class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PlannerPlanDetails: Creates a new instance of the appropriate class based on disc... | Implement the Python class `PlannerPlanDetails` described below.
Class description:
Implement the PlannerPlanDetails class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PlannerPlanDetails: Creates a new instance of the appropriate class based on disc... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class PlannerPlanDetails:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PlannerPlanDetails:
"""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 obje... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlannerPlanDetails:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> PlannerPlanDetails:
"""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: Pl... | the_stack_v2_python_sparse | msgraph/generated/models/planner_plan_details.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
74cada21c63162ab8915a1fd637e80d2a82fa9ff | [
"super(BaseWatcherBuilder, self).__init__()\nself._logger = None\nself.node = node\nself.parameters = parameters\nself.event = event\nself.name = name\nself.output = output\nself._product = None\nself._output_file = None\nself._arguments = None\nreturn",
"if self._arguments is None:\n try:\n self._argum... | <|body_start_0|>
super(BaseWatcherBuilder, self).__init__()
self._logger = None
self.node = node
self.parameters = parameters
self.event = event
self.name = name
self.output = output
self._product = None
self._output_file = None
self._argum... | A class to base other builders on | BaseWatcherBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseWatcherBuilder:
"""A class to base other builders on"""
def __init__(self, node, parameters, output, name=None, event=None):
""":param: - `node`: device to watch - `parameters`: named tuple built from config file - `output`: storageobject to send output to - `name`: a name to add... | stack_v2_sparse_classes_36k_train_027659 | 7,765 | permissive | [
{
"docstring": ":param: - `node`: device to watch - `parameters`: named tuple built from config file - `output`: storageobject to send output to - `name`: a name to add to the output file - `event`: event to watch to decide when to stop",
"name": "__init__",
"signature": "def __init__(self, node, parame... | 3 | null | Implement the Python class `BaseWatcherBuilder` described below.
Class description:
A class to base other builders on
Method signatures and docstrings:
- def __init__(self, node, parameters, output, name=None, event=None): :param: - `node`: device to watch - `parameters`: named tuple built from config file - `output`... | Implement the Python class `BaseWatcherBuilder` described below.
Class description:
A class to base other builders on
Method signatures and docstrings:
- def __init__(self, node, parameters, output, name=None, event=None): :param: - `node`: device to watch - `parameters`: named tuple built from config file - `output`... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class BaseWatcherBuilder:
"""A class to base other builders on"""
def __init__(self, node, parameters, output, name=None, event=None):
""":param: - `node`: device to watch - `parameters`: named tuple built from config file - `output`: storageobject to send output to - `name`: a name to add... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseWatcherBuilder:
"""A class to base other builders on"""
def __init__(self, node, parameters, output, name=None, event=None):
""":param: - `node`: device to watch - `parameters`: named tuple built from config file - `output`: storageobject to send output to - `name`: a name to add to the outpu... | the_stack_v2_python_sparse | apetools/builders/subbuilders/logwatcherbuilders.py | russell-n/oldape | train | 0 |
558a0153cc127a1e24d017c22e9d8f437bcee1a2 | [
"if head is None:\n return None\nif head.next is None:\n return head\np1, c1 = (ListNode(-1), head)\np2, c2 = (head, head.next)\nhead = c2\nwhile True:\n p1.next = c2\n p2.next = c1\n temp = c1.next\n c1.next = c2.next\n c2.next = temp\n if c1.next and c1.next.next:\n p1, c1 = (c1, c1... | <|body_start_0|>
if head is None:
return None
if head.next is None:
return head
p1, c1 = (ListNode(-1), head)
p2, c2 = (head, head.next)
head = c2
while True:
p1.next = c2
p2.next = c1
temp = c1.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def print_list(self, head):
""":type head: ListNode :rtype: None"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if head is None:
return None
... | stack_v2_sparse_classes_36k_train_027660 | 3,198 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "swapPairs",
"signature": "def swapPairs(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: None",
"name": "print_list",
"signature": "def print_list(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021140 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs(self, head): :type head: ListNode :rtype: ListNode
- def print_list(self, head): :type head: ListNode :rtype: None | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs(self, head): :type head: ListNode :rtype: ListNode
- def print_list(self, head): :type head: ListNode :rtype: None
<|skeleton|>
class Solution:
def swapPairs(... | b155895c90169ec97372b2517f556fd50deac2bc | <|skeleton|>
class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def print_list(self, head):
""":type head: ListNode :rtype: None"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
if head is None:
return None
if head.next is None:
return head
p1, c1 = (ListNode(-1), head)
p2, c2 = (head, head.next)
head = c2
while True:
... | the_stack_v2_python_sparse | linked_list_swap_node_pairs.py | claytonjwong/Sandbox-Python | train | 0 | |
88000392ff7ed945a764d5d379e590379727bad8 | [
"super().__init__()\nself.enc = enc\nself.dec = dec\nself.timestep = timestep\nself.seq_len = seq_len\nself.decoder_start = 0 if timestep == seq_len else timestep",
"_, (hn, cn) = self.enc(*args)\ndevice = hn.device\nseq_cont_data = args[1]\nseq_cat_data = args[0]\nbatch_size = seq_cont_data.shape[0]\ndecoder_inp... | <|body_start_0|>
super().__init__()
self.enc = enc
self.dec = dec
self.timestep = timestep
self.seq_len = seq_len
self.decoder_start = 0 if timestep == seq_len else timestep
<|end_body_0|>
<|body_start_1|>
_, (hn, cn) = self.enc(*args)
device = hn.device
... | Teacher Training based autoencoder. | AutoencoderTeacherTraining | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoencoderTeacherTraining:
"""Teacher Training based autoencoder."""
def __init__(self, enc, dec, timestep=15, seq_len=15):
"""Initialize model with params."""
<|body_0|>
def forward(self, *args):
"""Run a forward pass of model over the data."""
<|body_1... | stack_v2_sparse_classes_36k_train_027661 | 15,906 | permissive | [
{
"docstring": "Initialize model with params.",
"name": "__init__",
"signature": "def __init__(self, enc, dec, timestep=15, seq_len=15)"
},
{
"docstring": "Run a forward pass of model over the data.",
"name": "forward",
"signature": "def forward(self, *args)"
},
{
"docstring": "R... | 3 | stack_v2_sparse_classes_30k_train_018384 | Implement the Python class `AutoencoderTeacherTraining` described below.
Class description:
Teacher Training based autoencoder.
Method signatures and docstrings:
- def __init__(self, enc, dec, timestep=15, seq_len=15): Initialize model with params.
- def forward(self, *args): Run a forward pass of model over the data... | Implement the Python class `AutoencoderTeacherTraining` described below.
Class description:
Teacher Training based autoencoder.
Method signatures and docstrings:
- def __init__(self, enc, dec, timestep=15, seq_len=15): Initialize model with params.
- def forward(self, *args): Run a forward pass of model over the data... | 9cdbf270487751a0ad6862b2fea2ccc0e23a0b67 | <|skeleton|>
class AutoencoderTeacherTraining:
"""Teacher Training based autoencoder."""
def __init__(self, enc, dec, timestep=15, seq_len=15):
"""Initialize model with params."""
<|body_0|>
def forward(self, *args):
"""Run a forward pass of model over the data."""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutoencoderTeacherTraining:
"""Teacher Training based autoencoder."""
def __init__(self, enc, dec, timestep=15, seq_len=15):
"""Initialize model with params."""
super().__init__()
self.enc = enc
self.dec = dec
self.timestep = timestep
self.seq_len = seq_len... | the_stack_v2_python_sparse | caspr/models/model_wrapper.py | microsoft/CASPR | train | 29 |
dce5a55cac443f3df30378f99e8f7a4789e40c2a | [
"hostname = 'nosuchname'\ntimedgethostbyname(hostname, 5)\nckey = '%s_lookup' % hostname\nip = cache.get(ckey)\nself.assertEqual(ip, None)",
"hostname = 'localhost'\ntimedgethostbyname(hostname, 5)\nckey = '%s_lookup' % hostname\nip = cache.get(ckey)\nself.assertEqual(ip, '127.0.0.1')"
] | <|body_start_0|>
hostname = 'nosuchname'
timedgethostbyname(hostname, 5)
ckey = '%s_lookup' % hostname
ip = cache.get(ckey)
self.assertEqual(ip, None)
<|end_body_0|>
<|body_start_1|>
hostname = 'localhost'
timedgethostbyname(hostname, 5)
ckey = '%s_lookup... | UtilsTests | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UtilsTests:
def test_timedgethostbyname_nosuchname(self):
"""timedgethostbyname() stores IP's in Django cache. A none existing key should return None."""
<|body_0|>
def test_timedgethostbyname_localhost(self):
"""timedgethostbyname() should cache an IP for a hostname... | stack_v2_sparse_classes_36k_train_027662 | 840 | permissive | [
{
"docstring": "timedgethostbyname() stores IP's in Django cache. A none existing key should return None.",
"name": "test_timedgethostbyname_nosuchname",
"signature": "def test_timedgethostbyname_nosuchname(self)"
},
{
"docstring": "timedgethostbyname() should cache an IP for a hostname passed t... | 2 | stack_v2_sparse_classes_30k_train_010120 | Implement the Python class `UtilsTests` described below.
Class description:
Implement the UtilsTests class.
Method signatures and docstrings:
- def test_timedgethostbyname_nosuchname(self): timedgethostbyname() stores IP's in Django cache. A none existing key should return None.
- def test_timedgethostbyname_localhos... | Implement the Python class `UtilsTests` described below.
Class description:
Implement the UtilsTests class.
Method signatures and docstrings:
- def test_timedgethostbyname_nosuchname(self): timedgethostbyname() stores IP's in Django cache. A none existing key should return None.
- def test_timedgethostbyname_localhos... | 64d9f42fc4298f6d0854441f0e514ecb042bfd9d | <|skeleton|>
class UtilsTests:
def test_timedgethostbyname_nosuchname(self):
"""timedgethostbyname() stores IP's in Django cache. A none existing key should return None."""
<|body_0|>
def test_timedgethostbyname_localhost(self):
"""timedgethostbyname() should cache an IP for a hostname... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UtilsTests:
def test_timedgethostbyname_nosuchname(self):
"""timedgethostbyname() stores IP's in Django cache. A none existing key should return None."""
hostname = 'nosuchname'
timedgethostbyname(hostname, 5)
ckey = '%s_lookup' % hostname
ip = cache.get(ckey)
s... | the_stack_v2_python_sparse | assets/tests.py | continual-delivery/stratahq | train | 1 | |
c97bdc9758500115d00dd12e74d8b9f2a1772596 | [
"self.groups: set[LcnAddr] = set()\nself.groups_known = asyncio.Event()\nsuper().__init__(addr_conn, num_tries, timeout_msec)",
"if isinstance(inp, inputs.ModStatusGroups):\n if not inp.dynamic:\n self.groups.update(inp.groups)\n self.groups_known.set()\n await self.cancel()",
"if not fa... | <|body_start_0|>
self.groups: set[LcnAddr] = set()
self.groups_known = asyncio.Event()
super().__init__(addr_conn, num_tries, timeout_msec)
<|end_body_0|>
<|body_start_1|>
if isinstance(inp, inputs.ModStatusGroups):
if not inp.dynamic:
self.groups.update(inp.... | Request handler to request static group membership of a module. | GroupMembershipStaticRequestHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupMembershipStaticRequestHandler:
"""Request handler to request static group membership of a module."""
def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500):
"""Initialize class instance."""
<|body_0|>
async def async_process_input... | stack_v2_sparse_classes_36k_train_027663 | 24,302 | permissive | [
{
"docstring": "Initialize class instance.",
"name": "__init__",
"signature": "def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500)"
},
{
"docstring": "Process incoming input object. Method to handle incoming commands for this specific request handler.",
... | 4 | stack_v2_sparse_classes_30k_test_000286 | Implement the Python class `GroupMembershipStaticRequestHandler` described below.
Class description:
Request handler to request static group membership of a module.
Method signatures and docstrings:
- def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500): Initialize class instance.... | Implement the Python class `GroupMembershipStaticRequestHandler` described below.
Class description:
Request handler to request static group membership of a module.
Method signatures and docstrings:
- def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500): Initialize class instance.... | 00b45d5dcec8fccd4b13d218ac56194f44959e68 | <|skeleton|>
class GroupMembershipStaticRequestHandler:
"""Request handler to request static group membership of a module."""
def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500):
"""Initialize class instance."""
<|body_0|>
async def async_process_input... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupMembershipStaticRequestHandler:
"""Request handler to request static group membership of a module."""
def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500):
"""Initialize class instance."""
self.groups: set[LcnAddr] = set()
self.groups_know... | the_stack_v2_python_sparse | pypck/request_handlers.py | alengwenus/pypck | train | 6 |
dbf08522c773933fcd1634c4a91876ba93fd76f8 | [
"from random import randint\n\ndef helper(left: int, right: int) -> 'TreeNode':\n if left > right:\n return None\n pivot = left + (left + right) // 2\n if (left + right) % 2:\n pivot += randint(0, 1)\n root = TreeNode(nums[pivot])\n root.left = helper(left, pivot - 1)\n root.right = ... | <|body_start_0|>
from random import randint
def helper(left: int, right: int) -> 'TreeNode':
if left > right:
return None
pivot = left + (left + right) // 2
if (left + right) % 2:
pivot += randint(0, 1)
root = TreeNode(nums... | BinarySearchTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinarySearchTree:
def convert(self, nums: List[int]) -> 'TreeNode':
"""Approach: Recursion with right mid elem as root node Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:"""
<|body_0|>
def convert_(self, nums: List[int]) -> 'TreeNode':
"""Approach... | stack_v2_sparse_classes_36k_train_027664 | 2,175 | no_license | [
{
"docstring": "Approach: Recursion with right mid elem as root node Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:",
"name": "convert",
"signature": "def convert(self, nums: List[int]) -> 'TreeNode'"
},
{
"docstring": "Approach: Recursion with right mid elem as root node Tim... | 3 | null | Implement the Python class `BinarySearchTree` described below.
Class description:
Implement the BinarySearchTree class.
Method signatures and docstrings:
- def convert(self, nums: List[int]) -> 'TreeNode': Approach: Recursion with right mid elem as root node Time Complexity: O(N) Space Complexity: O(N) :param nums: :... | Implement the Python class `BinarySearchTree` described below.
Class description:
Implement the BinarySearchTree class.
Method signatures and docstrings:
- def convert(self, nums: List[int]) -> 'TreeNode': Approach: Recursion with right mid elem as root node Time Complexity: O(N) Space Complexity: O(N) :param nums: :... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class BinarySearchTree:
def convert(self, nums: List[int]) -> 'TreeNode':
"""Approach: Recursion with right mid elem as root node Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:"""
<|body_0|>
def convert_(self, nums: List[int]) -> 'TreeNode':
"""Approach... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinarySearchTree:
def convert(self, nums: List[int]) -> 'TreeNode':
"""Approach: Recursion with right mid elem as root node Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:"""
from random import randint
def helper(left: int, right: int) -> 'TreeNode':
if ... | the_stack_v2_python_sparse | revisited_2021/tree/sorted_array_to_bst.py | Shiv2157k/leet_code | train | 1 | |
fb8dd6d4cc33516382820700188dfb5442ceadbe | [
"super().__init__()\nif len(kernel_sizes) != len(dilations):\n raise ValueError(f'kernel_sizes and dilations length must match, got kernel_sizes={len(kernel_sizes)} dilations={len(dilations)}.')\npads = tuple((same_padding(k, d) for k, d in zip(kernel_sizes, dilations)))\nself.convs = nn.ModuleList()\nfor k, d, ... | <|body_start_0|>
super().__init__()
if len(kernel_sizes) != len(dilations):
raise ValueError(f'kernel_sizes and dilations length must match, got kernel_sizes={len(kernel_sizes)} dilations={len(dilations)}.')
pads = tuple((same_padding(k, d) for k, d in zip(kernel_sizes, dilations)))
... | A simplified version of the atrous spatial pyramid pooling (ASPP) module. Chen et al., Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. https://arxiv.org/abs/1802.02611 Wang et al., A Noise-robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesions from CT Images. https:... | SimpleASPP | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleASPP:
"""A simplified version of the atrous spatial pyramid pooling (ASPP) module. Chen et al., Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. https://arxiv.org/abs/1802.02611 Wang et al., A Noise-robust Framework for Automatic Segmentation of COVID-19 Pn... | stack_v2_sparse_classes_36k_train_027665 | 4,380 | permissive | [
{
"docstring": "Args: spatial_dims: number of spatial dimensions, could be 1, 2, or 3. in_channels: number of input channels. conv_out_channels: number of output channels of each atrous conv. The final number of output channels is conv_out_channels * len(kernel_sizes). kernel_sizes: a sequence of four convoluti... | 2 | null | Implement the Python class `SimpleASPP` described below.
Class description:
A simplified version of the atrous spatial pyramid pooling (ASPP) module. Chen et al., Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. https://arxiv.org/abs/1802.02611 Wang et al., A Noise-robust Framework fo... | Implement the Python class `SimpleASPP` described below.
Class description:
A simplified version of the atrous spatial pyramid pooling (ASPP) module. Chen et al., Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. https://arxiv.org/abs/1802.02611 Wang et al., A Noise-robust Framework fo... | e48c3e2c741fa3fc705c4425d17ac4a5afac6c47 | <|skeleton|>
class SimpleASPP:
"""A simplified version of the atrous spatial pyramid pooling (ASPP) module. Chen et al., Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. https://arxiv.org/abs/1802.02611 Wang et al., A Noise-robust Framework for Automatic Segmentation of COVID-19 Pn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimpleASPP:
"""A simplified version of the atrous spatial pyramid pooling (ASPP) module. Chen et al., Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation. https://arxiv.org/abs/1802.02611 Wang et al., A Noise-robust Framework for Automatic Segmentation of COVID-19 Pneumonia Lesio... | the_stack_v2_python_sparse | monai/networks/blocks/aspp.py | Project-MONAI/MONAI | train | 4,805 |
27e81e336fa7b33e2e4dff6c3eb0598e261850e7 | [
"async for batch in self.batches(in_q):\n content_q_by_type = defaultdict(lambda: Q(pk=None))\n for declarative_content in batch:\n model_type = type(declarative_content.content)\n unit_key = declarative_content.content.natural_key_dict()\n content_q_by_type[model_type] = content_q_by_typ... | <|body_start_0|>
async for batch in self.batches(in_q):
content_q_by_type = defaultdict(lambda: Q(pk=None))
for declarative_content in batch:
model_type = type(declarative_content.content)
unit_key = declarative_content.content.natural_key_dict()
... | A Stages API stage that saves :attr:`DeclarativeContent.content` objects and saves its related :class:`~pulpcore.plugin.models.ContentArtifact` and :class:`~pulpcore.plugin.models.RemoteArtifact` objects too. This stage expects :class:`~pulpcore.plugin.stages.DeclarativeContent` units from `in_q` and inspects their ass... | QueryExistingContentUnits | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueryExistingContentUnits:
"""A Stages API stage that saves :attr:`DeclarativeContent.content` objects and saves its related :class:`~pulpcore.plugin.models.ContentArtifact` and :class:`~pulpcore.plugin.models.RemoteArtifact` objects too. This stage expects :class:`~pulpcore.plugin.stages.Declara... | stack_v2_sparse_classes_36k_train_027666 | 6,533 | no_license | [
{
"docstring": "The coroutine for this stage. Args: in_q (:class:`asyncio.Queue`): The queue to receive :class:`~pulpcore.plugin.stages.DeclarativeContent` objects from. out_q (:class:`asyncio.Queue`): The queue to put :class:`~pulpcore.plugin.stages.DeclarativeContent` into. Returns: The coroutine for this sta... | 2 | stack_v2_sparse_classes_30k_train_020647 | Implement the Python class `QueryExistingContentUnits` described below.
Class description:
A Stages API stage that saves :attr:`DeclarativeContent.content` objects and saves its related :class:`~pulpcore.plugin.models.ContentArtifact` and :class:`~pulpcore.plugin.models.RemoteArtifact` objects too. This stage expects ... | Implement the Python class `QueryExistingContentUnits` described below.
Class description:
A Stages API stage that saves :attr:`DeclarativeContent.content` objects and saves its related :class:`~pulpcore.plugin.models.ContentArtifact` and :class:`~pulpcore.plugin.models.RemoteArtifact` objects too. This stage expects ... | f667ec77eb5325ae68d091eac7dbd1d22b0b33f0 | <|skeleton|>
class QueryExistingContentUnits:
"""A Stages API stage that saves :attr:`DeclarativeContent.content` objects and saves its related :class:`~pulpcore.plugin.models.ContentArtifact` and :class:`~pulpcore.plugin.models.RemoteArtifact` objects too. This stage expects :class:`~pulpcore.plugin.stages.Declara... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueryExistingContentUnits:
"""A Stages API stage that saves :attr:`DeclarativeContent.content` objects and saves its related :class:`~pulpcore.plugin.models.ContentArtifact` and :class:`~pulpcore.plugin.models.RemoteArtifact` objects too. This stage expects :class:`~pulpcore.plugin.stages.DeclarativeContent` ... | the_stack_v2_python_sparse | synchronize_refactor/trashbin/queryandsavecontent.py | asmacdo/sandbox | train | 0 |
4f98552f0e559f617ec311f4d3261eceae59e4d2 | [
"res_list = []\nif root is None:\n return res_list\nres_left_list = self.postorderTraversal(root.left)\nres_list += res_left_list\nres_right_list = self.postorderTraversal(root.right)\nres_list += res_right_list\nres_list.append(root.val)\nreturn res_list",
"res_list = []\nif root is None:\n return res_list... | <|body_start_0|>
res_list = []
if root is None:
return res_list
res_left_list = self.postorderTraversal(root.left)
res_list += res_left_list
res_right_list = self.postorderTraversal(root.right)
res_list += res_right_list
res_list.append(root.val)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def postorderTraversal(self, root):
"""递归法 :type root: TreeNode :rtype: List[int]"""
<|body_0|>
def postorderTraversal2(self, root):
"""递归法 :type root: TreeNode :rtype: List[int]"""
<|body_1|>
def postorderTraversal3(self, root):
"""迭代法... | stack_v2_sparse_classes_36k_train_027667 | 2,642 | no_license | [
{
"docstring": "递归法 :type root: TreeNode :rtype: List[int]",
"name": "postorderTraversal",
"signature": "def postorderTraversal(self, root)"
},
{
"docstring": "递归法 :type root: TreeNode :rtype: List[int]",
"name": "postorderTraversal2",
"signature": "def postorderTraversal2(self, root)"
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorderTraversal(self, root): 递归法 :type root: TreeNode :rtype: List[int]
- def postorderTraversal2(self, root): 递归法 :type root: TreeNode :rtype: List[int]
- def postorderTr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorderTraversal(self, root): 递归法 :type root: TreeNode :rtype: List[int]
- def postorderTraversal2(self, root): 递归法 :type root: TreeNode :rtype: List[int]
- def postorderTr... | 3b13b36f37eb364410b3b5b4f10a1808d8b1111e | <|skeleton|>
class Solution:
def postorderTraversal(self, root):
"""递归法 :type root: TreeNode :rtype: List[int]"""
<|body_0|>
def postorderTraversal2(self, root):
"""递归法 :type root: TreeNode :rtype: List[int]"""
<|body_1|>
def postorderTraversal3(self, root):
"""迭代法... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def postorderTraversal(self, root):
"""递归法 :type root: TreeNode :rtype: List[int]"""
res_list = []
if root is None:
return res_list
res_left_list = self.postorderTraversal(root.left)
res_list += res_left_list
res_right_list = self.postorder... | the_stack_v2_python_sparse | leetcode/145.py | yanggelinux/algorithm-data-structure | train | 0 | |
2890f57dc91465d8636f31769d006e8708045dec | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Print()",
"from .print_connector import PrintConnector\nfrom .printer import Printer\nfrom .printer_share import PrinterShare\nfrom .print_operation import PrintOperation\nfrom .print_service import PrintService\nfrom .print_settings i... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Print()
<|end_body_0|>
<|body_start_1|>
from .print_connector import PrintConnector
from .printer import Printer
from .printer_share import PrinterShare
from .print_opera... | Print | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Print:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Print:
"""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: Print"""
... | stack_v2_sparse_classes_36k_train_027668 | 5,372 | 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: Print",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse_n... | 3 | null | Implement the Python class `Print` described below.
Class description:
Implement the Print class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Print: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The p... | Implement the Python class `Print` described below.
Class description:
Implement the Print class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Print: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The p... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Print:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Print:
"""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: Print"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Print:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Print:
"""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: Print"""
if not pars... | the_stack_v2_python_sparse | msgraph/generated/models/print.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e48c83471542a278e0ebfb29d6ca3eea740e630a | [
"b = bin(n)[2:]\nb = '0' * (32 - len(b)) + b\nreturn int(b[::-1], 2)",
"n = (n & 2863311530) >> 1 | (n & 1431655765) << 1\nn = (n & 3435973836) >> 2 | (n & 858993459) << 2\nn = (n & 4042322160) >> 4 | (n & 252645135) << 4\nn = (n & 4278255360) >> 8 | (n & 16711935) << 8\nreturn (n & 4294901760) >> 16 | (n & 65535... | <|body_start_0|>
b = bin(n)[2:]
b = '0' * (32 - len(b)) + b
return int(b[::-1], 2)
<|end_body_0|>
<|body_start_1|>
n = (n & 2863311530) >> 1 | (n & 1431655765) << 1
n = (n & 3435973836) >> 2 | (n & 858993459) << 2
n = (n & 4042322160) >> 4 | (n & 252645135) << 4
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseBits(self, n):
"""转成二进制的字符串来翻转"""
<|body_0|>
def reverseBits_2(self, n):
"""不依赖任何语言特性的实现"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
b = bin(n)[2:]
b = '0' * (32 - len(b)) + b
return int(b[::-1], 2)
<|end_bod... | stack_v2_sparse_classes_36k_train_027669 | 584 | permissive | [
{
"docstring": "转成二进制的字符串来翻转",
"name": "reverseBits",
"signature": "def reverseBits(self, n)"
},
{
"docstring": "不依赖任何语言特性的实现",
"name": "reverseBits_2",
"signature": "def reverseBits_2(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBits(self, n): 转成二进制的字符串来翻转
- def reverseBits_2(self, n): 不依赖任何语言特性的实现 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBits(self, n): 转成二进制的字符串来翻转
- def reverseBits_2(self, n): 不依赖任何语言特性的实现
<|skeleton|>
class Solution:
def reverseBits(self, n):
"""转成二进制的字符串来翻转"""
... | d203aecd1afe1af13a0384a9c657c8424aab322d | <|skeleton|>
class Solution:
def reverseBits(self, n):
"""转成二进制的字符串来翻转"""
<|body_0|>
def reverseBits_2(self, n):
"""不依赖任何语言特性的实现"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseBits(self, n):
"""转成二进制的字符串来翻转"""
b = bin(n)[2:]
b = '0' * (32 - len(b)) + b
return int(b[::-1], 2)
def reverseBits_2(self, n):
"""不依赖任何语言特性的实现"""
n = (n & 2863311530) >> 1 | (n & 1431655765) << 1
n = (n & 3435973836) >> 2 | (n ... | the_stack_v2_python_sparse | easy/Q190_ReserveBits.py | Kaciras/leetcode | train | 0 | |
3e626f92e92602192afb86f04d6408699dbc6959 | [
"self.image = image\nself.T_camera_world = T_camera_world\nself.obj_key = obj_key\nself.stable_pose = stable_pose",
"if self.stable_pose is None:\n T_obj_world = RigidTransform(from_frame='obj', to_frame='world')\nelse:\n T_obj_world = self.stable_pose.T_obj_table.as_frames('obj', 'world')\nT_camera_obj = T... | <|body_start_0|>
self.image = image
self.T_camera_world = T_camera_world
self.obj_key = obj_key
self.stable_pose = stable_pose
<|end_body_0|>
<|body_start_1|>
if self.stable_pose is None:
T_obj_world = RigidTransform(from_frame='obj', to_frame='world')
else:
... | Class to encapsulate images of an object rendered from a virtual camera. Note ---- In this class, the table's frame of reference is the 'world' frame for the renderer. | ObjectRender | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjectRender:
"""Class to encapsulate images of an object rendered from a virtual camera. Note ---- In this class, the table's frame of reference is the 'world' frame for the renderer."""
def __init__(self, image, T_camera_world=RigidTransform(from_frame='camera', to_frame='table'), obj_key=... | stack_v2_sparse_classes_36k_train_027670 | 3,973 | permissive | [
{
"docstring": "Create an ObjectRender. Parameters ---------- image : :obj:`Image` The image to be encapsulated. T_camera_world : :obj:`autolab_core.RigidTransform` A rigid transform from camera to world coordinates (positions the camera in the world). TODO -- this should be renamed. obj_key : :obj:`str`, optio... | 2 | stack_v2_sparse_classes_30k_train_005426 | Implement the Python class `ObjectRender` described below.
Class description:
Class to encapsulate images of an object rendered from a virtual camera. Note ---- In this class, the table's frame of reference is the 'world' frame for the renderer.
Method signatures and docstrings:
- def __init__(self, image, T_camera_w... | Implement the Python class `ObjectRender` described below.
Class description:
Class to encapsulate images of an object rendered from a virtual camera. Note ---- In this class, the table's frame of reference is the 'world' frame for the renderer.
Method signatures and docstrings:
- def __init__(self, image, T_camera_w... | 61217d65f040d536e54804150ce8abcf97343410 | <|skeleton|>
class ObjectRender:
"""Class to encapsulate images of an object rendered from a virtual camera. Note ---- In this class, the table's frame of reference is the 'world' frame for the renderer."""
def __init__(self, image, T_camera_world=RigidTransform(from_frame='camera', to_frame='table'), obj_key=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObjectRender:
"""Class to encapsulate images of an object rendered from a virtual camera. Note ---- In this class, the table's frame of reference is the 'world' frame for the renderer."""
def __init__(self, image, T_camera_world=RigidTransform(from_frame='camera', to_frame='table'), obj_key=None, stable_... | the_stack_v2_python_sparse | perception/object_render.py | jhu-lcsr/good_robot | train | 95 |
2d56f0a72a916d220b9ad9f32d5544b596c80c10 | [
"if all((isinstance(x, numbers.Number) for x in [R, P, A, B, O])):\n self.R = max(0, R)\n self.P = max(0, min(P, 1))\n self.A = A\n self.B = B\n self.O = O\n self.name = name\n self._constants = model_constants\nelse:\n raise TypeError('First five arguments must be numeric.')",
"epsilon = ... | <|body_start_0|>
if all((isinstance(x, numbers.Number) for x in [R, P, A, B, O])):
self.R = max(0, R)
self.P = max(0, min(P, 1))
self.A = A
self.B = B
self.O = O
self.name = name
self._constants = model_constants
else:
... | Environment | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Environment:
def __init__(self, R, P, A, B, O, name=''):
"""Creates an Environment instance with given properties"""
<|body_0|>
def evaluate(self, t):
"""Returns environment value E and cue C for given time t"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_027671 | 1,205 | permissive | [
{
"docstring": "Creates an Environment instance with given properties",
"name": "__init__",
"signature": "def __init__(self, R, P, A, B, O, name='')"
},
{
"docstring": "Returns environment value E and cue C for given time t",
"name": "evaluate",
"signature": "def evaluate(self, t)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002900 | Implement the Python class `Environment` described below.
Class description:
Implement the Environment class.
Method signatures and docstrings:
- def __init__(self, R, P, A, B, O, name=''): Creates an Environment instance with given properties
- def evaluate(self, t): Returns environment value E and cue C for given t... | Implement the Python class `Environment` described below.
Class description:
Implement the Environment class.
Method signatures and docstrings:
- def __init__(self, R, P, A, B, O, name=''): Creates an Environment instance with given properties
- def evaluate(self, t): Returns environment value E and cue C for given t... | c516968deb177c876079afada902ba3a2320d77f | <|skeleton|>
class Environment:
def __init__(self, R, P, A, B, O, name=''):
"""Creates an Environment instance with given properties"""
<|body_0|>
def evaluate(self, t):
"""Returns environment value E and cue C for given time t"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Environment:
def __init__(self, R, P, A, B, O, name=''):
"""Creates an Environment instance with given properties"""
if all((isinstance(x, numbers.Number) for x in [R, P, A, B, O])):
self.R = max(0, R)
self.P = max(0, min(P, 1))
self.A = A
self.B... | the_stack_v2_python_sparse | src/environment.py | pengzug/cces-sem-botero | train | 0 | |
945d1d70883afcd6b84dfbe6c7457509e94f9623 | [
"params = kwarg['params']\ncmd = 'bridge mdb {} '.format(command)\nreturn cmd",
"params = kwarg['params']\ncmd = 'bridge mdb {} '.format(command)\nreturn cmd"
] | <|body_start_0|>
params = kwarg['params']
cmd = 'bridge mdb {} '.format(command)
return cmd
<|end_body_0|>
<|body_start_1|>
params = kwarg['params']
cmd = 'bridge mdb {} '.format(command)
return cmd
<|end_body_1|>
| The corresponding commands display mdb entries, add new entries, and delete old ones. | LinuxBridgeMdbImpl | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinuxBridgeMdbImpl:
"""The corresponding commands display mdb entries, add new entries, and delete old ones."""
def format_update(self, command, *argv, **kwarg):
"""bridge mdb { add | del } dev DEV port PORT grp GROUP [ permanent | temp ] [ vid VID ]"""
<|body_0|>
def fo... | stack_v2_sparse_classes_36k_train_027672 | 820 | permissive | [
{
"docstring": "bridge mdb { add | del } dev DEV port PORT grp GROUP [ permanent | temp ] [ vid VID ]",
"name": "format_update",
"signature": "def format_update(self, command, *argv, **kwarg)"
},
{
"docstring": "bridge mdb show [ dev DEV ]",
"name": "format_show",
"signature": "def forma... | 2 | stack_v2_sparse_classes_30k_train_021165 | Implement the Python class `LinuxBridgeMdbImpl` described below.
Class description:
The corresponding commands display mdb entries, add new entries, and delete old ones.
Method signatures and docstrings:
- def format_update(self, command, *argv, **kwarg): bridge mdb { add | del } dev DEV port PORT grp GROUP [ permane... | Implement the Python class `LinuxBridgeMdbImpl` described below.
Class description:
The corresponding commands display mdb entries, add new entries, and delete old ones.
Method signatures and docstrings:
- def format_update(self, command, *argv, **kwarg): bridge mdb { add | del } dev DEV port PORT grp GROUP [ permane... | e4c8221e18cd94e7424c30e12eb0fb82f7767267 | <|skeleton|>
class LinuxBridgeMdbImpl:
"""The corresponding commands display mdb entries, add new entries, and delete old ones."""
def format_update(self, command, *argv, **kwarg):
"""bridge mdb { add | del } dev DEV port PORT grp GROUP [ permanent | temp ] [ vid VID ]"""
<|body_0|>
def fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinuxBridgeMdbImpl:
"""The corresponding commands display mdb entries, add new entries, and delete old ones."""
def format_update(self, command, *argv, **kwarg):
"""bridge mdb { add | del } dev DEV port PORT grp GROUP [ permanent | temp ] [ vid VID ]"""
params = kwarg['params']
cm... | the_stack_v2_python_sparse | Amazon_Framework/DentOsTestbedLib/src/dent_os_testbed/lib/bridge/linux/linux_bridge_mdb_impl.py | tld3daniel/testing | train | 0 |
0a7790123676e528073c1ac474a916fcd4fe8062 | [
"qs = self.get_query_set()\nif user is not None:\n qs = qs.filter(user=user)\nif search_key is not None:\n qs = qs.filter(search_key=search_key)\nif collapsed is True:\n initial_list_qs = qs.values('user_query').order_by().annotate(times_seen=models.Count('user_query'))\n return initial_list_qs.values('... | <|body_start_0|>
qs = self.get_query_set()
if user is not None:
qs = qs.filter(user=user)
if search_key is not None:
qs = qs.filter(search_key=search_key)
if collapsed is True:
initial_list_qs = qs.values('user_query').order_by().annotate(times_seen=mo... | SavedSearchManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SavedSearchManager:
def most_recent(self, user=None, search_key=None, collapsed=True, threshold=1):
"""Returns the most recently seen queries. By default, only shows collapsed queries. This means that if the same query was executed several times in a row, only the most recent is shown an... | stack_v2_sparse_classes_36k_train_027673 | 29,990 | no_license | [
{
"docstring": "Returns the most recently seen queries. By default, only shows collapsed queries. This means that if the same query was executed several times in a row, only the most recent is shown and a count of ``times_seen`` is additionally provided. If you want to saw all queries (regardless of duplicates)... | 2 | null | Implement the Python class `SavedSearchManager` described below.
Class description:
Implement the SavedSearchManager class.
Method signatures and docstrings:
- def most_recent(self, user=None, search_key=None, collapsed=True, threshold=1): Returns the most recently seen queries. By default, only shows collapsed queri... | Implement the Python class `SavedSearchManager` described below.
Class description:
Implement the SavedSearchManager class.
Method signatures and docstrings:
- def most_recent(self, user=None, search_key=None, collapsed=True, threshold=1): Returns the most recently seen queries. By default, only shows collapsed queri... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class SavedSearchManager:
def most_recent(self, user=None, search_key=None, collapsed=True, threshold=1):
"""Returns the most recently seen queries. By default, only shows collapsed queries. This means that if the same query was executed several times in a row, only the most recent is shown an... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SavedSearchManager:
def most_recent(self, user=None, search_key=None, collapsed=True, threshold=1):
"""Returns the most recently seen queries. By default, only shows collapsed queries. This means that if the same query was executed several times in a row, only the most recent is shown and a count of `... | the_stack_v2_python_sparse | repoData/toastdriven-saved_searches/allPythonContent.py | aCoffeeYin/pyreco | train | 0 | |
f995504d94d30dcbf82e32553b3c348b1b29da55 | [
"SafeASTTraversal.__init__(self, tree)\nself.payoffScript = payoffScript\nself.variables = variables\nself.builtnodes = {}",
"self._add_variables()\nself.postorder()\n'A zero start node Id means that the tree has no statements \\n (it can still have declarations). '\nstartNodeId = len(self.ast) > 1 and... | <|body_start_0|>
SafeASTTraversal.__init__(self, tree)
self.payoffScript = payoffScript
self.variables = variables
self.builtnodes = {}
<|end_body_0|>
<|body_start_1|>
self._add_variables()
self.postorder()
'A zero start node Id means that the tree has no stateme... | Traverse tree and write to a FObject representation for execution | FUDMCValuationFunctionBuilder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FUDMCValuationFunctionBuilder:
"""Traverse tree and write to a FObject representation for execution"""
def __init__(self, payoffScript, tree, variables):
"""Initialize FUDMCValuationFunctionBuilder payoffScript -- an FUDMCScriptPayoff instance tree -- final tree representation of PEL... | stack_v2_sparse_classes_36k_train_027674 | 3,052 | no_license | [
{
"docstring": "Initialize FUDMCValuationFunctionBuilder payoffScript -- an FUDMCScriptPayoff instance tree -- final tree representation of PEL code, McAstNode variables-- list of variables",
"name": "__init__",
"signature": "def __init__(self, payoffScript, tree, variables)"
},
{
"docstring": "... | 4 | null | Implement the Python class `FUDMCValuationFunctionBuilder` described below.
Class description:
Traverse tree and write to a FObject representation for execution
Method signatures and docstrings:
- def __init__(self, payoffScript, tree, variables): Initialize FUDMCValuationFunctionBuilder payoffScript -- an FUDMCScrip... | Implement the Python class `FUDMCValuationFunctionBuilder` described below.
Class description:
Traverse tree and write to a FObject representation for execution
Method signatures and docstrings:
- def __init__(self, payoffScript, tree, variables): Initialize FUDMCValuationFunctionBuilder payoffScript -- an FUDMCScrip... | 5e7cc7de3495145501ca53deb9efee2233ab7e1c | <|skeleton|>
class FUDMCValuationFunctionBuilder:
"""Traverse tree and write to a FObject representation for execution"""
def __init__(self, payoffScript, tree, variables):
"""Initialize FUDMCValuationFunctionBuilder payoffScript -- an FUDMCScriptPayoff instance tree -- final tree representation of PEL... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FUDMCValuationFunctionBuilder:
"""Traverse tree and write to a FObject representation for execution"""
def __init__(self, payoffScript, tree, variables):
"""Initialize FUDMCValuationFunctionBuilder payoffScript -- an FUDMCScriptPayoff instance tree -- final tree representation of PEL code, McAstN... | the_stack_v2_python_sparse | Extensions/UDMCMod/FPythonCode/FUDMC_CPP.py | webclinic017/fa-absa-py3 | train | 0 |
fd5393ff8fe32578fbb7acc3dd53e79475098142 | [
"super(PointerNetwork, self).__init__()\nself._score_type = score_type\nself._name = name\nself._hidden_size = hidden_size\nself._init_scale = init_scale",
"input_dim = len(q.shape)\nif input_dim == 2:\n q = layers.unsqueeze(q, [1])\nif self._score_type == 'dot_prod':\n ptr_score = layers.matmul(q, v, trans... | <|body_start_0|>
super(PointerNetwork, self).__init__()
self._score_type = score_type
self._name = name
self._hidden_size = hidden_size
self._init_scale = init_scale
<|end_body_0|>
<|body_start_1|>
input_dim = len(q.shape)
if input_dim == 2:
q = layer... | Pointer Network | PointerNetwork | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointerNetwork:
"""Pointer Network"""
def __init__(self, score_type='dot_prod', name=None, init_scale=0.1, hidden_size=-1):
"""init of class Args: score_type (TYPE): dot_prod/affine/std name (str): param name prefix. used for parameter sharing. Default is None. init_scale (float): fo... | stack_v2_sparse_classes_36k_train_027675 | 5,544 | permissive | [
{
"docstring": "init of class Args: score_type (TYPE): dot_prod/affine/std name (str): param name prefix. used for parameter sharing. Default is None. init_scale (float): for init fc param. used when score_type is affine or std. default is 0.1 hidden_size (int): only used when score_type=std.",
"name": "__i... | 2 | null | Implement the Python class `PointerNetwork` described below.
Class description:
Pointer Network
Method signatures and docstrings:
- def __init__(self, score_type='dot_prod', name=None, init_scale=0.1, hidden_size=-1): init of class Args: score_type (TYPE): dot_prod/affine/std name (str): param name prefix. used for p... | Implement the Python class `PointerNetwork` described below.
Class description:
Pointer Network
Method signatures and docstrings:
- def __init__(self, score_type='dot_prod', name=None, init_scale=0.1, hidden_size=-1): init of class Args: score_type (TYPE): dot_prod/affine/std name (str): param name prefix. used for p... | e08f3cb7b9db4c837000316c791542580ba02624 | <|skeleton|>
class PointerNetwork:
"""Pointer Network"""
def __init__(self, score_type='dot_prod', name=None, init_scale=0.1, hidden_size=-1):
"""init of class Args: score_type (TYPE): dot_prod/affine/std name (str): param name prefix. used for parameter sharing. Default is None. init_scale (float): fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointerNetwork:
"""Pointer Network"""
def __init__(self, score_type='dot_prod', name=None, init_scale=0.1, hidden_size=-1):
"""init of class Args: score_type (TYPE): dot_prod/affine/std name (str): param name prefix. used for parameter sharing. Default is None. init_scale (float): for init fc par... | the_stack_v2_python_sparse | NLP/DuSQL-Baseline/text2sql/models/pointer_network.py | ajayvbabu/Research | train | 0 |
43845e3ec61dd8805073af5bd2c0bf7afb20db52 | [
"expected_type = kwargs.pop('expected_type', None)\nsuper(BitbucketCloudBase, self).__init__(url, *args, **kwargs)\nif expected_type is not None and (not expected_type == self.get_data('type')):\n raise ValueError('Expected type of data is [{}], got [{}].'.format(expected_type, self.get_data('type')))",
"links... | <|body_start_0|>
expected_type = kwargs.pop('expected_type', None)
super(BitbucketCloudBase, self).__init__(url, *args, **kwargs)
if expected_type is not None and (not expected_type == self.get_data('type')):
raise ValueError('Expected type of data is [{}], got [{}].'.format(expected... | BitbucketCloudBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BitbucketCloudBase:
def __init__(self, url, *args, **kwargs):
"""Init the rest api wrapper :param url: string: The base url used for the rest api. :param *args: list: The fixed arguments for the AtlassianRestApi. :param **kwargs: dict: The keyword arguments for the AtlassianRestApi. :ret... | stack_v2_sparse_classes_36k_train_027676 | 4,094 | permissive | [
{
"docstring": "Init the rest api wrapper :param url: string: The base url used for the rest api. :param *args: list: The fixed arguments for the AtlassianRestApi. :param **kwargs: dict: The keyword arguments for the AtlassianRestApi. :return: nothing",
"name": "__init__",
"signature": "def __init__(sel... | 4 | stack_v2_sparse_classes_30k_val_000280 | Implement the Python class `BitbucketCloudBase` described below.
Class description:
Implement the BitbucketCloudBase class.
Method signatures and docstrings:
- def __init__(self, url, *args, **kwargs): Init the rest api wrapper :param url: string: The base url used for the rest api. :param *args: list: The fixed argu... | Implement the Python class `BitbucketCloudBase` described below.
Class description:
Implement the BitbucketCloudBase class.
Method signatures and docstrings:
- def __init__(self, url, *args, **kwargs): Init the rest api wrapper :param url: string: The base url used for the rest api. :param *args: list: The fixed argu... | bb1c0f2d4187ba8efa1a838cd0041b54c944fee8 | <|skeleton|>
class BitbucketCloudBase:
def __init__(self, url, *args, **kwargs):
"""Init the rest api wrapper :param url: string: The base url used for the rest api. :param *args: list: The fixed arguments for the AtlassianRestApi. :param **kwargs: dict: The keyword arguments for the AtlassianRestApi. :ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BitbucketCloudBase:
def __init__(self, url, *args, **kwargs):
"""Init the rest api wrapper :param url: string: The base url used for the rest api. :param *args: list: The fixed arguments for the AtlassianRestApi. :param **kwargs: dict: The keyword arguments for the AtlassianRestApi. :return: nothing""... | the_stack_v2_python_sparse | atlassian/bitbucket/cloud/base.py | atlassian-api/atlassian-python-api | train | 1,130 | |
8c5d3028a982f74a580479b0a66eaf298f1600fd | [
"self.capacity = capacity\nself.queue = DLL()\nself.mapping = {}",
"if key not in self.mapping:\n return -1\nnode = self.mapping[key]\nself.queue.update(node)\nreturn node.val",
"if key in self.mapping:\n node = self.mapping[key]\n node.val = value\n self.queue.update(node)\n return\nnode = Node(... | <|body_start_0|>
self.capacity = capacity
self.queue = DLL()
self.mapping = {}
<|end_body_0|>
<|body_start_1|>
if key not in self.mapping:
return -1
node = self.mapping[key]
self.queue.update(node)
return node.val
<|end_body_1|>
<|body_start_2|>
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_027677 | 2,822 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: nothing",
"name": "set",
"sig... | 3 | stack_v2_sparse_classes_30k_train_001501 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing
<|skeleton|>
cla... | 05e0beff0047f0ad399d0b46d625bb8d3459814e | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.queue = DLL()
self.mapping = {}
def get(self, key):
""":rtype: int"""
if key not in self.mapping:
return -1
node = self.mapping[key]
... | the_stack_v2_python_sparse | python_1_to_1000/146_LRU_Cache.py | jakehoare/leetcode | train | 58 | |
16d2159a79e1bf886a49d7db52e067aa0a2b22f3 | [
"self._caffe = kwargs.pop('caffe')\nkwargs.setdefault('label_suffix', '')\nsuper(FullProductForm, self).__init__(*args, **kwargs)\nself.fields['product'].label = 'Produkt'\nself.fields['amount'].label = u'Ilość'\nself.fields['product'].empty_label = None\nself.fields['product'].queryset = Product.objects.filter(caf... | <|body_start_0|>
self._caffe = kwargs.pop('caffe')
kwargs.setdefault('label_suffix', '')
super(FullProductForm, self).__init__(*args, **kwargs)
self.fields['product'].label = 'Produkt'
self.fields['amount'].label = u'Ilość'
self.fields['product'].empty_label = None
... | Responsible for setting up a FullProduct - Product with its amount. | FullProductForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FullProductForm:
"""Responsible for setting up a FullProduct - Product with its amount."""
def __init__(self, *args, **kwargs):
"""Initialize all FullProduct's fields."""
<|body_0|>
def save(self, commit=True):
"""Override of save method, to add Caffe relation.""... | stack_v2_sparse_classes_36k_train_027678 | 5,569 | permissive | [
{
"docstring": "Initialize all FullProduct's fields.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Override of save method, to add Caffe relation.",
"name": "save",
"signature": "def save(self, commit=True)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017727 | Implement the Python class `FullProductForm` described below.
Class description:
Responsible for setting up a FullProduct - Product with its amount.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize all FullProduct's fields.
- def save(self, commit=True): Override of save method, to ... | Implement the Python class `FullProductForm` described below.
Class description:
Responsible for setting up a FullProduct - Product with its amount.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize all FullProduct's fields.
- def save(self, commit=True): Override of save method, to ... | cdb7f5edb29255c7e874eaa6231621063210a8b0 | <|skeleton|>
class FullProductForm:
"""Responsible for setting up a FullProduct - Product with its amount."""
def __init__(self, *args, **kwargs):
"""Initialize all FullProduct's fields."""
<|body_0|>
def save(self, commit=True):
"""Override of save method, to add Caffe relation.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FullProductForm:
"""Responsible for setting up a FullProduct - Product with its amount."""
def __init__(self, *args, **kwargs):
"""Initialize all FullProduct's fields."""
self._caffe = kwargs.pop('caffe')
kwargs.setdefault('label_suffix', '')
super(FullProductForm, self)._... | the_stack_v2_python_sparse | caffe/reports/forms.py | VirrageS/io-kawiarnie | train | 3 |
1c59d473751f81e5464c4f2ee6203f87ef7f71a9 | [
"mgr = execute_simple_run(self, slurm_sched_class=SlurmScheduler)\nrun = mgr.get_last_run()\nself.check_run_OK(run)\nself.assertTrue(run.is_complete())\nself.assertTrue(run.is_successful())\nself.assertIsNone(run.clean())\nself.assertIsNone(run.complete_clean())",
"mgr = execute_nested_run(self, slurm_sched_class... | <|body_start_0|>
mgr = execute_simple_run(self, slurm_sched_class=SlurmScheduler)
run = mgr.get_last_run()
self.check_run_OK(run)
self.assertTrue(run.is_complete())
self.assertTrue(run.is_successful())
self.assertIsNone(run.clean())
self.assertIsNone(run.complete_... | SlurmExecutionTests | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlurmExecutionTests:
def test_simple_run(self):
"""Execute a simple run."""
<|body_0|>
def test_nested_run(self):
"""Execute a nested run."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
mgr = execute_simple_run(self, slurm_sched_class=SlurmSchedule... | stack_v2_sparse_classes_36k_train_027679 | 9,814 | permissive | [
{
"docstring": "Execute a simple run.",
"name": "test_simple_run",
"signature": "def test_simple_run(self)"
},
{
"docstring": "Execute a nested run.",
"name": "test_nested_run",
"signature": "def test_nested_run(self)"
}
] | 2 | null | Implement the Python class `SlurmExecutionTests` described below.
Class description:
Implement the SlurmExecutionTests class.
Method signatures and docstrings:
- def test_simple_run(self): Execute a simple run.
- def test_nested_run(self): Execute a nested run. | Implement the Python class `SlurmExecutionTests` described below.
Class description:
Implement the SlurmExecutionTests class.
Method signatures and docstrings:
- def test_simple_run(self): Execute a simple run.
- def test_nested_run(self): Execute a nested run.
<|skeleton|>
class SlurmExecutionTests:
def test_s... | 76bc8f289f66fb133f78cb6d5689568b7d015915 | <|skeleton|>
class SlurmExecutionTests:
def test_simple_run(self):
"""Execute a simple run."""
<|body_0|>
def test_nested_run(self):
"""Execute a nested run."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SlurmExecutionTests:
def test_simple_run(self):
"""Execute a simple run."""
mgr = execute_simple_run(self, slurm_sched_class=SlurmScheduler)
run = mgr.get_last_run()
self.check_run_OK(run)
self.assertTrue(run.is_complete())
self.assertTrue(run.is_successful())
... | the_stack_v2_python_sparse | kive/fleet/tests_slurmscheduler.py | dmacmillan/Kive | train | 1 | |
400b20c58fb2011d271c03239a5ec9c7c53ec302 | [
"if value is None:\n return None\nreturn json.dumps(value, separators=self.separators)",
"if value is None:\n return None\nreturn json.loads(value)"
] | <|body_start_0|>
if value is None:
return None
return json.dumps(value, separators=self.separators)
<|end_body_0|>
<|body_start_1|>
if value is None:
return None
return json.loads(value)
<|end_body_1|>
| A JSONType is stored in the db as a string and we interact with it like a dict. | JSONType | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONType:
"""A JSONType is stored in the db as a string and we interact with it like a dict."""
def process_bind_param(self, value, dialect=None):
"""Dump our value to a form our db recognizes (a string)."""
<|body_0|>
def process_result_value(self, value, dialect=None):... | stack_v2_sparse_classes_36k_train_027680 | 3,117 | permissive | [
{
"docstring": "Dump our value to a form our db recognizes (a string).",
"name": "process_bind_param",
"signature": "def process_bind_param(self, value, dialect=None)"
},
{
"docstring": "Convert what we get from the db into a json dict",
"name": "process_result_value",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_012956 | Implement the Python class `JSONType` described below.
Class description:
A JSONType is stored in the db as a string and we interact with it like a dict.
Method signatures and docstrings:
- def process_bind_param(self, value, dialect=None): Dump our value to a form our db recognizes (a string).
- def process_result_v... | Implement the Python class `JSONType` described below.
Class description:
A JSONType is stored in the db as a string and we interact with it like a dict.
Method signatures and docstrings:
- def process_bind_param(self, value, dialect=None): Dump our value to a form our db recognizes (a string).
- def process_result_v... | b88183ac00b88f5dff9c01ad87a46da9e3615d9e | <|skeleton|>
class JSONType:
"""A JSONType is stored in the db as a string and we interact with it like a dict."""
def process_bind_param(self, value, dialect=None):
"""Dump our value to a form our db recognizes (a string)."""
<|body_0|>
def process_result_value(self, value, dialect=None):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONType:
"""A JSONType is stored in the db as a string and we interact with it like a dict."""
def process_bind_param(self, value, dialect=None):
"""Dump our value to a form our db recognizes (a string)."""
if value is None:
return None
return json.dumps(value, separa... | the_stack_v2_python_sparse | replication_handler/models/database.py | Yelp/mysql_streamer | train | 433 |
6f3fd8eb9860a76f1195f4394e208050710f33fa | [
"try:\n html = etree.HTML(content.lower())\n subject = html.xpath('//ul[@class=\"img\"]/li')\n subject_urls = list()\n for sub in subject:\n a_href = sub[0].get('href')\n subject_urls.append(a_href)\n return subject_urls\nexcept Exception as e:\n print(str(e))\n return list()",
... | <|body_start_0|>
try:
html = etree.HTML(content.lower())
subject = html.xpath('//ul[@class="img"]/li')
subject_urls = list()
for sub in subject:
a_href = sub[0].get('href')
subject_urls.append(a_href)
return subject_urls... | HtmlParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HtmlParser:
def parse_main_subjects(self, content):
"""解析美图录网站主页模特分类页面链接 :param content: 美图录主页内容 :return: ['一个模特的大图页面', '一个模特的大图页面']"""
<|body_0|>
def parse_subject_mj_info(self, content):
"""获取具体模特大图页面开头的模特信息 :param content: 一个类别的模特页面内容 :return: {'count': 该模特具备图总数, ... | stack_v2_sparse_classes_36k_train_027681 | 1,773 | permissive | [
{
"docstring": "解析美图录网站主页模特分类页面链接 :param content: 美图录主页内容 :return: ['一个模特的大图页面', '一个模特的大图页面']",
"name": "parse_main_subjects",
"signature": "def parse_main_subjects(self, content)"
},
{
"docstring": "获取具体模特大图页面开头的模特信息 :param content: 一个类别的模特页面内容 :return: {'count': 该模特具备图总数, 'mj_name': 模特名字}",
... | 3 | stack_v2_sparse_classes_30k_train_007629 | Implement the Python class `HtmlParser` described below.
Class description:
Implement the HtmlParser class.
Method signatures and docstrings:
- def parse_main_subjects(self, content): 解析美图录网站主页模特分类页面链接 :param content: 美图录主页内容 :return: ['一个模特的大图页面', '一个模特的大图页面']
- def parse_subject_mj_info(self, content): 获取具体模特大图页面开头... | Implement the Python class `HtmlParser` described below.
Class description:
Implement the HtmlParser class.
Method signatures and docstrings:
- def parse_main_subjects(self, content): 解析美图录网站主页模特分类页面链接 :param content: 美图录主页内容 :return: ['一个模特的大图页面', '一个模特的大图页面']
- def parse_subject_mj_info(self, content): 获取具体模特大图页面开头... | 6303c2df24ef3d15be205a8599ed58e7bc5ddb8a | <|skeleton|>
class HtmlParser:
def parse_main_subjects(self, content):
"""解析美图录网站主页模特分类页面链接 :param content: 美图录主页内容 :return: ['一个模特的大图页面', '一个模特的大图页面']"""
<|body_0|>
def parse_subject_mj_info(self, content):
"""获取具体模特大图页面开头的模特信息 :param content: 一个类别的模特页面内容 :return: {'count': 该模特具备图总数, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HtmlParser:
def parse_main_subjects(self, content):
"""解析美图录网站主页模特分类页面链接 :param content: 美图录主页内容 :return: ['一个模特的大图页面', '一个模特的大图页面']"""
try:
html = etree.HTML(content.lower())
subject = html.xpath('//ul[@class="img"]/li')
subject_urls = list()
fo... | the_stack_v2_python_sparse | MeiTuLuSpider/html_parser.py | motiondepp/SmallReptileTraining | train | 0 | |
4691c5a6155b170641d0c6920b2f1fa040a74cde | [
"super().__init__()\nself.vocab_size = vocab_size\nself.output_size = output_size\nself.rnn_size = rnn_size\nself.bpe = bpe\nif bpe:\n self.embedding = nn.Embedding(num_embeddings=vocab_size, embedding_dim=embedding_size, padding_idx=0)\nelse:\n self.enc_embedding = nn.Embedding(num_embeddings=vocab_size, emb... | <|body_start_0|>
super().__init__()
self.vocab_size = vocab_size
self.output_size = output_size
self.rnn_size = rnn_size
self.bpe = bpe
if bpe:
self.embedding = nn.Embedding(num_embeddings=vocab_size, embedding_dim=embedding_size, padding_idx=0)
else:
... | Seq2Seq | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Seq2Seq:
def __init__(self, vocab_size, rnn_size, embedding_size, output_size, enc_seq_len, dec_seq_len, bpe):
"""The Model class implements the LSTM-LM model. Feel free to initialize any variables that you find necessary in the constructor. :param vocab_size: The number of unique tokens... | stack_v2_sparse_classes_36k_train_027682 | 5,462 | no_license | [
{
"docstring": "The Model class implements the LSTM-LM model. Feel free to initialize any variables that you find necessary in the constructor. :param vocab_size: The number of unique tokens in the input :param rnn_size: The size of hidden cells in LSTM/GRU :param embedding_size: The dimension of embedding spac... | 2 | stack_v2_sparse_classes_30k_train_012688 | Implement the Python class `Seq2Seq` described below.
Class description:
Implement the Seq2Seq class.
Method signatures and docstrings:
- def __init__(self, vocab_size, rnn_size, embedding_size, output_size, enc_seq_len, dec_seq_len, bpe): The Model class implements the LSTM-LM model. Feel free to initialize any vari... | Implement the Python class `Seq2Seq` described below.
Class description:
Implement the Seq2Seq class.
Method signatures and docstrings:
- def __init__(self, vocab_size, rnn_size, embedding_size, output_size, enc_seq_len, dec_seq_len, bpe): The Model class implements the LSTM-LM model. Feel free to initialize any vari... | f7e5b911ce6902eae067c20240ac565a3f2b8fbd | <|skeleton|>
class Seq2Seq:
def __init__(self, vocab_size, rnn_size, embedding_size, output_size, enc_seq_len, dec_seq_len, bpe):
"""The Model class implements the LSTM-LM model. Feel free to initialize any variables that you find necessary in the constructor. :param vocab_size: The number of unique tokens... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Seq2Seq:
def __init__(self, vocab_size, rnn_size, embedding_size, output_size, enc_seq_len, dec_seq_len, bpe):
"""The Model class implements the LSTM-LM model. Feel free to initialize any variables that you find necessary in the constructor. :param vocab_size: The number of unique tokens in the input ... | the_stack_v2_python_sparse | multilingual/model.py | ziyaoh/comp-ling | train | 0 | |
521525415731cd451b4392eadfd6f355bf47c883 | [
"self.set_peaks(peakfinder)\nself.gain = None\nself.cal = None\nself.fit_channels = []\nself.fit_snrs = []\nself.fit_energies = []\nself.reset()",
"self.gain = None\nself.cal = None\nself.fit_channels = []\nself.fit_snrs = []\nself.fit_energies = []",
"if not isinstance(peakfinder, PeakFinder):\n raise AutoC... | <|body_start_0|>
self.set_peaks(peakfinder)
self.gain = None
self.cal = None
self.fit_channels = []
self.fit_snrs = []
self.fit_energies = []
self.reset()
<|end_body_0|>
<|body_start_1|>
self.gain = None
self.cal = None
self.fit_channels =... | Automatically calibrate a spectrum by convolving it with a filter. A note on nomenclature: for historic reasons, 'channels' is used in autocal.py for generic uncalibrated x-axis values. A 'channel' is no longer necessarily an integer channel number (i.e., bin) from a multi-channel analyzer, but could for instance be a ... | AutoCalibrator | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoCalibrator:
"""Automatically calibrate a spectrum by convolving it with a filter. A note on nomenclature: for historic reasons, 'channels' is used in autocal.py for generic uncalibrated x-axis values. A 'channel' is no longer necessarily an integer channel number (i.e., bin) from a multi-chan... | stack_v2_sparse_classes_36k_train_027683 | 10,991 | permissive | [
{
"docstring": "Initialize the calibration with a spectrum and kernel.",
"name": "__init__",
"signature": "def __init__(self, peakfinder)"
},
{
"docstring": "Reset all of the members.",
"name": "reset",
"signature": "def reset(self)"
},
{
"docstring": "Use the peaks found by the ... | 5 | stack_v2_sparse_classes_30k_train_013422 | Implement the Python class `AutoCalibrator` described below.
Class description:
Automatically calibrate a spectrum by convolving it with a filter. A note on nomenclature: for historic reasons, 'channels' is used in autocal.py for generic uncalibrated x-axis values. A 'channel' is no longer necessarily an integer chann... | Implement the Python class `AutoCalibrator` described below.
Class description:
Automatically calibrate a spectrum by convolving it with a filter. A note on nomenclature: for historic reasons, 'channels' is used in autocal.py for generic uncalibrated x-axis values. A 'channel' is no longer necessarily an integer chann... | d459a17dbdb0e458218637fc323bef7821c5cb5c | <|skeleton|>
class AutoCalibrator:
"""Automatically calibrate a spectrum by convolving it with a filter. A note on nomenclature: for historic reasons, 'channels' is used in autocal.py for generic uncalibrated x-axis values. A 'channel' is no longer necessarily an integer channel number (i.e., bin) from a multi-chan... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutoCalibrator:
"""Automatically calibrate a spectrum by convolving it with a filter. A note on nomenclature: for historic reasons, 'channels' is used in autocal.py for generic uncalibrated x-axis values. A 'channel' is no longer necessarily an integer channel number (i.e., bin) from a multi-channel analyzer,... | the_stack_v2_python_sparse | becquerel/core/autocal.py | lbl-anp/becquerel | train | 41 |
68b7e1d666c8e12f2128e3e382243f1bafa60ee0 | [
"super().__init__(dat, frame, box_size, centre, arrow_width=arrow_width, arrow_head_width=arrow_head_width, arrow_head_length=arrow_head_length)\nself.velocities = dat.getVelocities(frame, *self.particles)\nself.vmin, self.vmax = amplogwidth(self.velocities)\ntry:\n self.vmin = np.log10(kwargs['vmin'])\nexcept (... | <|body_start_0|>
super().__init__(dat, frame, box_size, centre, arrow_width=arrow_width, arrow_head_width=arrow_head_width, arrow_head_length=arrow_head_length)
self.velocities = dat.getVelocities(frame, *self.particles)
self.vmin, self.vmax = amplogwidth(self.velocities)
try:
... | Plotting class specific to 'velocity' mode. | Velocity | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Velocity:
"""Plotting class specific to 'velocity' mode."""
def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_label_pad, label=False, **kwargs):
"""Initialises and plots f... | stack_v2_sparse_classes_36k_train_027684 | 24,676 | permissive | [
{
"docstring": "Initialises and plots figure. Parameters ---------- dat : active_work.read.Dat Data object. frame : int Frame to render. box_size : float Length of the square box to render. centre : 2-uple like Centre of the box to render. arrow_width : float Width of the arrows. arrow_head_width : float Width ... | 2 | stack_v2_sparse_classes_30k_train_020433 | Implement the Python class `Velocity` described below.
Class description:
Plotting class specific to 'velocity' mode.
Method signatures and docstrings:
- def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_l... | Implement the Python class `Velocity` described below.
Class description:
Plotting class specific to 'velocity' mode.
Method signatures and docstrings:
- def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_l... | 99107a0d4935296b673f67469c1e2bd258954b9b | <|skeleton|>
class Velocity:
"""Plotting class specific to 'velocity' mode."""
def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_label_pad, label=False, **kwargs):
"""Initialises and plots f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Velocity:
"""Plotting class specific to 'velocity' mode."""
def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_label_pad, label=False, **kwargs):
"""Initialises and plots figure. Parame... | the_stack_v2_python_sparse | frame.py | yketa/active_work | train | 1 |
0a63623e867dcd0367f8ab7ea08ba1e903061791 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Process()",
"from .file_hash import FileHash\nfrom .process_integrity_level import ProcessIntegrityLevel\nfrom .file_hash import FileHash\nfrom .process_integrity_level import ProcessIntegrityLevel\nfields: Dict[str, Callable[[Any], No... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Process()
<|end_body_0|>
<|body_start_1|>
from .file_hash import FileHash
from .process_integrity_level import ProcessIntegrityLevel
from .file_hash import FileHash
from ... | Process | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Process:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process:
"""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: Process"""... | stack_v2_sparse_classes_36k_train_027685 | 6,144 | 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: Process",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse... | 3 | stack_v2_sparse_classes_30k_val_000085 | Implement the Python class `Process` described below.
Class description:
Implement the Process class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | Implement the Python class `Process` described below.
Class description:
Implement the Process class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Process:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process:
"""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: Process"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Process:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Process:
"""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: Process"""
if no... | the_stack_v2_python_sparse | msgraph/generated/models/process.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
439dd7901491ca85ab43d578ec12be286c266767 | [
"headers = {}\nheaders['Host'] = [self.input]\nreturn self.doRequest(self.localOptions['backend'], headers=headers)",
"if 'not censored' in body:\n self.report['trans_http_proxy'] = False\nelse:\n self.report['trans_http_proxy'] = True"
] | <|body_start_0|>
headers = {}
headers['Host'] = [self.input]
return self.doRequest(self.localOptions['backend'], headers=headers)
<|end_body_0|>
<|body_start_1|>
if 'not censored' in body:
self.report['trans_http_proxy'] = False
else:
self.report['trans_h... | This test is aimed at detecting the presence of a transparent HTTP proxy and enumerating the sites that are being censored by it. | HTTPHost | [
"BSD-2-Clause-Views"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTTPHost:
"""This test is aimed at detecting the presence of a transparent HTTP proxy and enumerating the sites that are being censored by it."""
def test_send_host_header(self):
"""Stuffs the HTTP Host header field with the site to be tested for censorship and does an HTTP request o... | stack_v2_sparse_classes_36k_train_027686 | 1,593 | permissive | [
{
"docstring": "Stuffs the HTTP Host header field with the site to be tested for censorship and does an HTTP request of this kind to our backend. We randomize the HTTP User Agent headers.",
"name": "test_send_host_header",
"signature": "def test_send_host_header(self)"
},
{
"docstring": "XXX thi... | 2 | stack_v2_sparse_classes_30k_train_020472 | Implement the Python class `HTTPHost` described below.
Class description:
This test is aimed at detecting the presence of a transparent HTTP proxy and enumerating the sites that are being censored by it.
Method signatures and docstrings:
- def test_send_host_header(self): Stuffs the HTTP Host header field with the si... | Implement the Python class `HTTPHost` described below.
Class description:
This test is aimed at detecting the presence of a transparent HTTP proxy and enumerating the sites that are being censored by it.
Method signatures and docstrings:
- def test_send_host_header(self): Stuffs the HTTP Host header field with the si... | 28241124e6094b224f4a3b4f6c0a8e8a69a7eeb6 | <|skeleton|>
class HTTPHost:
"""This test is aimed at detecting the presence of a transparent HTTP proxy and enumerating the sites that are being censored by it."""
def test_send_host_header(self):
"""Stuffs the HTTP Host header field with the site to be tested for censorship and does an HTTP request o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HTTPHost:
"""This test is aimed at detecting the presence of a transparent HTTP proxy and enumerating the sites that are being censored by it."""
def test_send_host_header(self):
"""Stuffs the HTTP Host header field with the site to be tested for censorship and does an HTTP request of this kind t... | the_stack_v2_python_sparse | nettests/core/http_host.py | jonmtoz/ooni-probe | train | 0 |
a9eb50d347c6fd6763e225f6980f9ab861645760 | [
"copy = dictionary.copy()\ncount = 0\nwhile count < length / unit:\n count += 1\n word = s[start:start + unit]\n if word in copy and copy[word] > 0:\n start += unit\n copy[word] -= 1\n else:\n return False\nreturn True",
"result = {}\nkeys = set(words)\nfor key in keys:\n resul... | <|body_start_0|>
copy = dictionary.copy()
count = 0
while count < length / unit:
count += 1
word = s[start:start + unit]
if word in copy and copy[word] > 0:
start += unit
copy[word] -= 1
else:
return ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def match(self, s, start, length, dictionary, unit):
""">>> s = Solution() >>> text = "barfoothefoobarman" >>> words = {"foo": 1, "bar": 1} >>> length = 6 >>> s.match(text, 0, length, words, 3) True >>> s.match(text, 3, length, words, 3) False >>> s.match(text, 6, length, words... | stack_v2_sparse_classes_36k_train_027687 | 2,148 | no_license | [
{
"docstring": ">>> s = Solution() >>> text = \"barfoothefoobarman\" >>> words = {\"foo\": 1, \"bar\": 1} >>> length = 6 >>> s.match(text, 0, length, words, 3) True >>> s.match(text, 3, length, words, 3) False >>> s.match(text, 6, length, words, 3) False >>> s.match(text, 9, length, words, 3) True >>> s.match(t... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def match(self, s, start, length, dictionary, unit): >>> s = Solution() >>> text = "barfoothefoobarman" >>> words = {"foo": 1, "bar": 1} >>> length = 6 >>> s.match(text, 0, lengt... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def match(self, s, start, length, dictionary, unit): >>> s = Solution() >>> text = "barfoothefoobarman" >>> words = {"foo": 1, "bar": 1} >>> length = 6 >>> s.match(text, 0, lengt... | 3b13a02f9c8273f9794a57b948d2655792707f37 | <|skeleton|>
class Solution:
def match(self, s, start, length, dictionary, unit):
""">>> s = Solution() >>> text = "barfoothefoobarman" >>> words = {"foo": 1, "bar": 1} >>> length = 6 >>> s.match(text, 0, length, words, 3) True >>> s.match(text, 3, length, words, 3) False >>> s.match(text, 6, length, words... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def match(self, s, start, length, dictionary, unit):
""">>> s = Solution() >>> text = "barfoothefoobarman" >>> words = {"foo": 1, "bar": 1} >>> length = 6 >>> s.match(text, 0, length, words, 3) True >>> s.match(text, 3, length, words, 3) False >>> s.match(text, 6, length, words, 3) False >>>... | the_stack_v2_python_sparse | substring_with_concatenation.py | gsy/leetcode | train | 1 | |
0f7cc20ef0161682bf3642ac6b6aa00f37974164 | [
"for iam_policy_map in resource_from_api:\n iam_policy = iam_policy_map['iam_policy']\n bindings = iam_policy.get('bindings', [])\n for binding in bindings:\n members = binding.get('members', [])\n for member in members:\n member_type, member_name, member_domain = parser.parse_memb... | <|body_start_0|>
for iam_policy_map in resource_from_api:
iam_policy = iam_policy_map['iam_policy']
bindings = iam_policy.get('bindings', [])
for binding in bindings:
members = binding.get('members', [])
for member in members:
... | Pipeline to load project IAM policies data into Inventory. | LoadProjectsIamPoliciesPipeline | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadProjectsIamPoliciesPipeline:
"""Pipeline to load project IAM policies data into Inventory."""
def _transform(self, resource_from_api):
"""Yield an iterator of loadable iam policies. Args: resource_from_api (iterable): IAM policies as per-project dictionary. Example: {'project_num... | stack_v2_sparse_classes_36k_train_027688 | 4,687 | permissive | [
{
"docstring": "Yield an iterator of loadable iam policies. Args: resource_from_api (iterable): IAM policies as per-project dictionary. Example: {'project_number': 11111, 'iam_policy': policy} https://cloud.google.com/resource-manager/reference/rest/Shared.Types/Policy Yields: iterable: Loadable iam policies, a... | 3 | stack_v2_sparse_classes_30k_train_002926 | Implement the Python class `LoadProjectsIamPoliciesPipeline` described below.
Class description:
Pipeline to load project IAM policies data into Inventory.
Method signatures and docstrings:
- def _transform(self, resource_from_api): Yield an iterator of loadable iam policies. Args: resource_from_api (iterable): IAM p... | Implement the Python class `LoadProjectsIamPoliciesPipeline` described below.
Class description:
Pipeline to load project IAM policies data into Inventory.
Method signatures and docstrings:
- def _transform(self, resource_from_api): Yield an iterator of loadable iam policies. Args: resource_from_api (iterable): IAM p... | a6a1aa7464cda2ad5948e3e8876eb8dded5e2514 | <|skeleton|>
class LoadProjectsIamPoliciesPipeline:
"""Pipeline to load project IAM policies data into Inventory."""
def _transform(self, resource_from_api):
"""Yield an iterator of loadable iam policies. Args: resource_from_api (iterable): IAM policies as per-project dictionary. Example: {'project_num... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoadProjectsIamPoliciesPipeline:
"""Pipeline to load project IAM policies data into Inventory."""
def _transform(self, resource_from_api):
"""Yield an iterator of loadable iam policies. Args: resource_from_api (iterable): IAM policies as per-project dictionary. Example: {'project_number': 11111, ... | the_stack_v2_python_sparse | google/cloud/security/inventory/pipelines/load_projects_iam_policies_pipeline.py | shimizu19691210/forseti-security | train | 1 |
77e76addd3928f0121f333fcca306eea7ce8cec2 | [
"user_qs = User.objects.select_related('org', 'parent', 'org__subscription', 'org__subscription__current_usage').filter(id=pk)\nif len(user_qs) < 1:\n resp = {'detail': 'User not found.'}\n return Response(resp, status=400)\nuser = user_qs[0]\nuser_details = get_profile_details(user)\nreturn Response(user_det... | <|body_start_0|>
user_qs = User.objects.select_related('org', 'parent', 'org__subscription', 'org__subscription__current_usage').filter(id=pk)
if len(user_qs) < 1:
resp = {'detail': 'User not found.'}
return Response(resp, status=400)
user = user_qs[0]
user_detail... | ProfileViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileViewSet:
def retrieve(self, request, pk, format=None):
"""Response: --- { 'id': 12, 'username': 'username', 'name': 'name1', 'phone': '+88017XXXXXXXX', 'image': 'url, 'email': 'manager.email', 'domain_choices': {}, 'domain': 2, 'location_interval': 120, 'org_id': 12, 'oid': 'gp-12... | stack_v2_sparse_classes_36k_train_027689 | 27,493 | no_license | [
{
"docstring": "Response: --- { 'id': 12, 'username': 'username', 'name': 'name1', 'phone': '+88017XXXXXXXX', 'image': 'url, 'email': 'manager.email', 'domain_choices': {}, 'domain': 2, 'location_interval': 120, 'org_id': 12, 'oid': 'gp-121', 'org_name': 'Grameenphone Ltd.', 'day_start': time string, 'day_end':... | 2 | null | Implement the Python class `ProfileViewSet` described below.
Class description:
Implement the ProfileViewSet class.
Method signatures and docstrings:
- def retrieve(self, request, pk, format=None): Response: --- { 'id': 12, 'username': 'username', 'name': 'name1', 'phone': '+88017XXXXXXXX', 'image': 'url, 'email': 'm... | Implement the Python class `ProfileViewSet` described below.
Class description:
Implement the ProfileViewSet class.
Method signatures and docstrings:
- def retrieve(self, request, pk, format=None): Response: --- { 'id': 12, 'username': 'username', 'name': 'name1', 'phone': '+88017XXXXXXXX', 'image': 'url, 'email': 'm... | 11be165f85cda0ffe7a237d011de562d3dc64135 | <|skeleton|>
class ProfileViewSet:
def retrieve(self, request, pk, format=None):
"""Response: --- { 'id': 12, 'username': 'username', 'name': 'name1', 'phone': '+88017XXXXXXXX', 'image': 'url, 'email': 'manager.email', 'domain_choices': {}, 'domain': 2, 'location_interval': 120, 'org_id': 12, 'oid': 'gp-12... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfileViewSet:
def retrieve(self, request, pk, format=None):
"""Response: --- { 'id': 12, 'username': 'username', 'name': 'name1', 'phone': '+88017XXXXXXXX', 'image': 'url, 'email': 'manager.email', 'domain_choices': {}, 'domain': 2, 'location_interval': 120, 'org_id': 12, 'oid': 'gp-121', 'org_name'... | the_stack_v2_python_sparse | apps/user/views.py | ash018/FFTracker | train | 0 | |
ece2375ae0180955a9d0138170f02968e169ee1b | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn NetworkInfo()",
"from .network_connection_type import NetworkConnectionType\nfrom .network_transport_protocol import NetworkTransportProtocol\nfrom .trace_route_hop import TraceRouteHop\nfrom .wifi_band import WifiBand\nfrom .wifi_radi... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return NetworkInfo()
<|end_body_0|>
<|body_start_1|>
from .network_connection_type import NetworkConnectionType
from .network_transport_protocol import NetworkTransportProtocol
from .tr... | NetworkInfo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkInfo:
"""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: Ne... | stack_v2_sparse_classes_36k_train_027690 | 11,094 | 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: NetworkInfo",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(p... | 3 | null | Implement the Python class `NetworkInfo` described below.
Class description:
Implement the NetworkInfo class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkInfo: Creates a new instance of the appropriate class based on discriminator value Args:... | Implement the Python class `NetworkInfo` described below.
Class description:
Implement the NetworkInfo class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkInfo: Creates a new instance of the appropriate class based on discriminator value Args:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class NetworkInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkInfo:
"""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: Ne... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetworkInfo:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkInfo:
"""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: NetworkInfo"""
... | the_stack_v2_python_sparse | msgraph/generated/models/call_records/network_info.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e02b0aabb5008b838b7f54d4af78aca0cc8ac449 | [
"Parametre.__init__(self, 'créer', 'create')\nself.schema = '<cle>'\nself.aide_courte = 'crée une diligence maudite'\nself.aide_longue = \"Cette commande permet de créer une diligence maudite. Vous devez préciser la clé de la diligence à créer, sachant qu'elle ne peut pas être une clé de zone existante, car la clé ... | <|body_start_0|>
Parametre.__init__(self, 'créer', 'create')
self.schema = '<cle>'
self.aide_courte = 'crée une diligence maudite'
self.aide_longue = "Cette commande permet de créer une diligence maudite. Vous devez préciser la clé de la diligence à créer, sachant qu'elle ne peut pas êtr... | Commande 'diligence créer'. | PrmCreer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmCreer:
"""Commande 'diligence créer'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parametre._... | stack_v2_sparse_classes_36k_train_027691 | 3,158 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmCreer` described below.
Class description:
Commande 'diligence créer'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmCreer` described below.
Class description:
Commande 'diligence créer'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmCreer:
"""Commande 'diligence... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmCreer:
"""Commande 'diligence créer'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmCreer:
"""Commande 'diligence créer'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'créer', 'create')
self.schema = '<cle>'
self.aide_courte = 'crée une diligence maudite'
self.aide_longue = "Cette commande permet de créer une ... | the_stack_v2_python_sparse | src/secondaires/diligence/commandes/diligence/creer.py | vincent-lg/tsunami | train | 5 |
d1af9dce8b10ec4c9d8f7390c500db47f300e7aa | [
"data = self.get_json()\ntry:\n rund = ObservingRunPost.load(data)\nexcept ValidationError as exc:\n return self.error(f'Invalid/missing parameters: {exc.normalized_messages()}')\nrun = ObservingRun(**rund)\nrun.owner_id = self.associated_user_object.id\nDBSession().add(run)\nself.verify_and_commit()\nself.pu... | <|body_start_0|>
data = self.get_json()
try:
rund = ObservingRunPost.load(data)
except ValidationError as exc:
return self.error(f'Invalid/missing parameters: {exc.normalized_messages()}')
run = ObservingRun(**rund)
run.owner_id = self.associated_user_obje... | ObservingRunHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservingRunHandler:
def post(self):
"""--- description: Add a new observing run tags: - observing_runs requestBody: content: application/json: schema: ObservingRunPost responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object propert... | stack_v2_sparse_classes_36k_train_027692 | 8,089 | permissive | [
{
"docstring": "--- description: Add a new observing run tags: - observing_runs requestBody: content: application/json: schema: ObservingRunPost responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object properties: data: type: object properties: id: type: in... | 4 | null | Implement the Python class `ObservingRunHandler` described below.
Class description:
Implement the ObservingRunHandler class.
Method signatures and docstrings:
- def post(self): --- description: Add a new observing run tags: - observing_runs requestBody: content: application/json: schema: ObservingRunPost responses: ... | Implement the Python class `ObservingRunHandler` described below.
Class description:
Implement the ObservingRunHandler class.
Method signatures and docstrings:
- def post(self): --- description: Add a new observing run tags: - observing_runs requestBody: content: application/json: schema: ObservingRunPost responses: ... | 2433d5ae0b2f41faac3c76ed4ae8d9a4da5522fb | <|skeleton|>
class ObservingRunHandler:
def post(self):
"""--- description: Add a new observing run tags: - observing_runs requestBody: content: application/json: schema: ObservingRunPost responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object propert... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObservingRunHandler:
def post(self):
"""--- description: Add a new observing run tags: - observing_runs requestBody: content: application/json: schema: ObservingRunPost responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object properties: data: typ... | the_stack_v2_python_sparse | skyportal/handlers/api/observingrun.py | dmitryduev/skyportal | train | 1 | |
dfd23da41dd63393803aa00f5af8d6519239947b | [
"if v <= 0:\n raise ValueError('max_tokens must be a positive integer')\nreturn v",
"model = available_models[self.model_name.value]\nkwargs = model._lc_kwargs\nsecrets = {secret: getattr(model, secret) for secret in model.lc_secrets.keys()}\nkwargs.update(secrets)\nmodel_kwargs = kwargs.get('model_kwargs', {}... | <|body_start_0|>
if v <= 0:
raise ValueError('max_tokens must be a positive integer')
return v
<|end_body_0|>
<|body_start_1|>
model = available_models[self.model_name.value]
kwargs = model._lc_kwargs
secrets = {secret: getattr(model, secret) for secret in model.lc_s... | OpenAI LLM configuration. | OpenAIModelConfig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenAIModelConfig:
"""OpenAI LLM configuration."""
def max_tokens_must_be_positive(cls, v):
"""Validate that max_tokens is a positive integer."""
<|body_0|>
def get_model(self) -> BaseLanguageModel:
"""Get the model from the configuration. Returns: BaseLanguageMo... | stack_v2_sparse_classes_36k_train_027693 | 12,618 | no_license | [
{
"docstring": "Validate that max_tokens is a positive integer.",
"name": "max_tokens_must_be_positive",
"signature": "def max_tokens_must_be_positive(cls, v)"
},
{
"docstring": "Get the model from the configuration. Returns: BaseLanguageModel: The model.",
"name": "get_model",
"signatur... | 2 | stack_v2_sparse_classes_30k_val_000174 | Implement the Python class `OpenAIModelConfig` described below.
Class description:
OpenAI LLM configuration.
Method signatures and docstrings:
- def max_tokens_must_be_positive(cls, v): Validate that max_tokens is a positive integer.
- def get_model(self) -> BaseLanguageModel: Get the model from the configuration. Re... | Implement the Python class `OpenAIModelConfig` described below.
Class description:
OpenAI LLM configuration.
Method signatures and docstrings:
- def max_tokens_must_be_positive(cls, v): Validate that max_tokens is a positive integer.
- def get_model(self) -> BaseLanguageModel: Get the model from the configuration. Re... | 616cec5c43a0757495a4134c0c325e46a0b18d3b | <|skeleton|>
class OpenAIModelConfig:
"""OpenAI LLM configuration."""
def max_tokens_must_be_positive(cls, v):
"""Validate that max_tokens is a positive integer."""
<|body_0|>
def get_model(self) -> BaseLanguageModel:
"""Get the model from the configuration. Returns: BaseLanguageMo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OpenAIModelConfig:
"""OpenAI LLM configuration."""
def max_tokens_must_be_positive(cls, v):
"""Validate that max_tokens is a positive integer."""
if v <= 0:
raise ValueError('max_tokens must be a positive integer')
return v
def get_model(self) -> BaseLanguageModel... | the_stack_v2_python_sparse | module_text_llm/module_text_llm/helpers/models/openai.py | ls1intum/Athena | train | 11 |
7bbdb4a0556da7432319aafb8b61ae2fd39a4aa5 | [
"if self.instance.paid:\n return\nself.instance.status = order_status.RECEIVED\nself.instance.payment_psp_reference = psp_reference\nself.instance.paid = True\nself.instance.save()\nnew_adyen_response = AdyenResponse(order=self.instance, content=raw_data)\nnew_adyen_response.save()\nlogger.info('Order %s is paid... | <|body_start_0|>
if self.instance.paid:
return
self.instance.status = order_status.RECEIVED
self.instance.payment_psp_reference = psp_reference
self.instance.paid = True
self.instance.save()
new_adyen_response = AdyenResponse(order=self.instance, content=raw_d... | Payment seriazlier class | OrderPaymentSeriazlier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderPaymentSeriazlier:
"""Payment seriazlier class"""
def complete_payment(self, psp_reference, raw_data=None):
"""Handle logic when a payment of order is completed"""
<|body_0|>
def refund_payment(self):
"""Handle logic when a payment of order is completed"""
... | stack_v2_sparse_classes_36k_train_027694 | 1,298 | no_license | [
{
"docstring": "Handle logic when a payment of order is completed",
"name": "complete_payment",
"signature": "def complete_payment(self, psp_reference, raw_data=None)"
},
{
"docstring": "Handle logic when a payment of order is completed",
"name": "refund_payment",
"signature": "def refun... | 2 | null | Implement the Python class `OrderPaymentSeriazlier` described below.
Class description:
Payment seriazlier class
Method signatures and docstrings:
- def complete_payment(self, psp_reference, raw_data=None): Handle logic when a payment of order is completed
- def refund_payment(self): Handle logic when a payment of or... | Implement the Python class `OrderPaymentSeriazlier` described below.
Class description:
Payment seriazlier class
Method signatures and docstrings:
- def complete_payment(self, psp_reference, raw_data=None): Handle logic when a payment of order is completed
- def refund_payment(self): Handle logic when a payment of or... | 2f50b3815474845dd8c08f2a6f0213d5da3a5413 | <|skeleton|>
class OrderPaymentSeriazlier:
"""Payment seriazlier class"""
def complete_payment(self, psp_reference, raw_data=None):
"""Handle logic when a payment of order is completed"""
<|body_0|>
def refund_payment(self):
"""Handle logic when a payment of order is completed"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderPaymentSeriazlier:
"""Payment seriazlier class"""
def complete_payment(self, psp_reference, raw_data=None):
"""Handle logic when a payment of order is completed"""
if self.instance.paid:
return
self.instance.status = order_status.RECEIVED
self.instance.pay... | the_stack_v2_python_sparse | core/serializers/payment.py | raviteja2250/tabletop-backend-develop | train | 0 |
506b6b95b08ae588ba13acfd67b4c3e7e39be39e | [
"self.lib = abstract.sdk.triggers.processrestart.libs.processrestart.ProcessRestartLib(device=uut, process=self.process, abstract=abstract, verify_exclude=self.verify_exclude, obj=self)\ntry:\n self.lib.process_information()\nexcept Exception as e:\n self.skipped(\"Issue getting information about '{p}' proces... | <|body_start_0|>
self.lib = abstract.sdk.triggers.processrestart.libs.processrestart.ProcessRestartLib(device=uut, process=self.process, abstract=abstract, verify_exclude=self.verify_exclude, obj=self)
try:
self.lib.process_information()
except Exception as e:
self.skippe... | Trigger class for ProcessCliRestart action | TriggerProcessRestart | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TriggerProcessRestart:
"""Trigger class for ProcessCliRestart action"""
def verify_prerequisite(self, uut, abstract, steps):
"""Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstr... | stack_v2_sparse_classes_36k_train_027695 | 4,222 | permissive | [
{
"docstring": "Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstract (`obj`): Abstract object. steps (`step obj`): aetest step object Returns: None Raises: pyATS Results",
"name": "verify_prerequisite"... | 3 | null | Implement the Python class `TriggerProcessRestart` described below.
Class description:
Trigger class for ProcessCliRestart action
Method signatures and docstrings:
- def verify_prerequisite(self, uut, abstract, steps): Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to t... | Implement the Python class `TriggerProcessRestart` described below.
Class description:
Trigger class for ProcessCliRestart action
Method signatures and docstrings:
- def verify_prerequisite(self, uut, abstract, steps): Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to t... | e42e51475cddcb10f5c7814d0fe892ac865742ba | <|skeleton|>
class TriggerProcessRestart:
"""Trigger class for ProcessCliRestart action"""
def verify_prerequisite(self, uut, abstract, steps):
"""Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TriggerProcessRestart:
"""Trigger class for ProcessCliRestart action"""
def verify_prerequisite(self, uut, abstract, steps):
"""Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstract (`obj`): ... | the_stack_v2_python_sparse | pkgs/sdk-pkg/src/genie/libs/sdk/triggers/processrestart/processrestart.py | CiscoTestAutomation/genielibs | train | 109 |
076d1b8ec7f07af7351596ea7a9d26ea26313b1d | [
"super().__init__(hass, _LOGGER, name=f'octoprint-{config_entry.entry_id}', update_interval=timedelta(seconds=interval))\nself.config_entry = config_entry\nself._octoprint = octoprint\nself._printer_offline = False\nself.data = {'printer': None, 'job': None, 'last_read_time': None}",
"printer = None\ntry:\n jo... | <|body_start_0|>
super().__init__(hass, _LOGGER, name=f'octoprint-{config_entry.entry_id}', update_interval=timedelta(seconds=interval))
self.config_entry = config_entry
self._octoprint = octoprint
self._printer_offline = False
self.data = {'printer': None, 'job': None, 'last_rea... | Class to manage fetching Octoprint data. | OctoprintDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OctoprintDataUpdateCoordinator:
"""Class to manage fetching Octoprint data."""
def __init__(self, hass: HomeAssistant, octoprint: OctoprintClient, config_entry: ConfigEntry, interval: int) -> None:
"""Initialize."""
<|body_0|>
async def _async_update_data(self):
... | stack_v2_sparse_classes_36k_train_027696 | 3,236 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, octoprint: OctoprintClient, config_entry: ConfigEntry, interval: int) -> None"
},
{
"docstring": "Update data via API.",
"name": "_async_update_data",
"signature": "async def _async_up... | 3 | null | Implement the Python class `OctoprintDataUpdateCoordinator` described below.
Class description:
Class to manage fetching Octoprint data.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, octoprint: OctoprintClient, config_entry: ConfigEntry, interval: int) -> None: Initialize.
- async def _a... | Implement the Python class `OctoprintDataUpdateCoordinator` described below.
Class description:
Class to manage fetching Octoprint data.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, octoprint: OctoprintClient, config_entry: ConfigEntry, interval: int) -> None: Initialize.
- async def _a... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class OctoprintDataUpdateCoordinator:
"""Class to manage fetching Octoprint data."""
def __init__(self, hass: HomeAssistant, octoprint: OctoprintClient, config_entry: ConfigEntry, interval: int) -> None:
"""Initialize."""
<|body_0|>
async def _async_update_data(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OctoprintDataUpdateCoordinator:
"""Class to manage fetching Octoprint data."""
def __init__(self, hass: HomeAssistant, octoprint: OctoprintClient, config_entry: ConfigEntry, interval: int) -> None:
"""Initialize."""
super().__init__(hass, _LOGGER, name=f'octoprint-{config_entry.entry_id}'... | the_stack_v2_python_sparse | homeassistant/components/octoprint/coordinator.py | home-assistant/core | train | 35,501 |
43fa2352ea7a7ea3317f4233ab22dd198969999a | [
"exception_multiple_object_returned = False\ncreated = False\nif not party_id_temp:\n success = False\n status = 'MISSING_PARTY_TEMP_ID'\nelif not party_name:\n success = False\n status = 'MISSING_PARTY_NAME'\nelse:\n updated_values = {'party_abbreviation': party_abbreviation, 'ctcl_uuid': ctcl_uuid,... | <|body_start_0|>
exception_multiple_object_returned = False
created = False
if not party_id_temp:
success = False
status = 'MISSING_PARTY_TEMP_ID'
elif not party_name:
success = False
status = 'MISSING_PARTY_NAME'
else:
... | PartyManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PartyManager:
def update_or_create_party(self, party_id_temp='', party_name='', party_abbreviation='', ctcl_uuid=''):
"""Either update or create a party entry."""
<|body_0|>
def retrieve_all_party_names_and_ids(self):
"""Retrieves party name and corresponding party_i... | stack_v2_sparse_classes_36k_train_027697 | 4,946 | permissive | [
{
"docstring": "Either update or create a party entry.",
"name": "update_or_create_party",
"signature": "def update_or_create_party(self, party_id_temp='', party_name='', party_abbreviation='', ctcl_uuid='')"
},
{
"docstring": "Retrieves party name and corresponding party_id_temp from the databa... | 2 | null | Implement the Python class `PartyManager` described below.
Class description:
Implement the PartyManager class.
Method signatures and docstrings:
- def update_or_create_party(self, party_id_temp='', party_name='', party_abbreviation='', ctcl_uuid=''): Either update or create a party entry.
- def retrieve_all_party_na... | Implement the Python class `PartyManager` described below.
Class description:
Implement the PartyManager class.
Method signatures and docstrings:
- def update_or_create_party(self, party_id_temp='', party_name='', party_abbreviation='', ctcl_uuid=''): Either update or create a party entry.
- def retrieve_all_party_na... | be2c1367e8263f2cdcf3bd2e27e6cd4a6f35af68 | <|skeleton|>
class PartyManager:
def update_or_create_party(self, party_id_temp='', party_name='', party_abbreviation='', ctcl_uuid=''):
"""Either update or create a party entry."""
<|body_0|>
def retrieve_all_party_names_and_ids(self):
"""Retrieves party name and corresponding party_i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PartyManager:
def update_or_create_party(self, party_id_temp='', party_name='', party_abbreviation='', ctcl_uuid=''):
"""Either update or create a party entry."""
exception_multiple_object_returned = False
created = False
if not party_id_temp:
success = False
... | the_stack_v2_python_sparse | party/models.py | nickelser/WeVoteServer | train | 1 | |
5cbc3c3b2f9b8e7f6030b3ca57f807ec2f7e5ff5 | [
"if root is None:\n return 0\nif root.val == sum:\n return 1 + self.calculate(root.left, 0) + self.calculate(root.right, 0)\nelse:\n sum -= root.val\nreturn self.calculate(root.left, sum) + self.calculate(root.right, sum)",
"if root is None:\n return 0\nreturn self.calculate(root, sum) + self.pathSum(... | <|body_start_0|>
if root is None:
return 0
if root.val == sum:
return 1 + self.calculate(root.left, 0) + self.calculate(root.right, 0)
else:
sum -= root.val
return self.calculate(root.left, sum) + self.calculate(root.right, sum)
<|end_body_0|>
<|body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def calculate(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i... | stack_v2_sparse_classes_36k_train_027698 | 953 | no_license | [
{
"docstring": ":type root: TreeNode :type sum: int :rtype: int",
"name": "calculate",
"signature": "def calculate(self, root, sum)"
},
{
"docstring": ":type root: TreeNode :type sum: int :rtype: List[List[int]]",
"name": "pathSum",
"signature": "def pathSum(self, root, sum)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculate(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculate(self, root, sum): :type root: TreeNode :type sum: int :rtype: int
- def pathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: List[List[int]]
<|ske... | 9bd2d706f014ce84356ba38fc7801da0285a91d3 | <|skeleton|>
class Solution:
def calculate(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
<|body_0|>
def pathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def calculate(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: int"""
if root is None:
return 0
if root.val == sum:
return 1 + self.calculate(root.left, 0) + self.calculate(root.right, 0)
else:
sum -= root.val
... | the_stack_v2_python_sparse | leetcode/pathSum-437.py | pittcat/Algorithm_Practice | train | 0 | |
bd3a352089c1a6a8c5b80fabaf252dc2b30bf8be | [
"if self.request.user.is_superuser:\n return self.queryset\nreturn self.queryset.filter(user=self.request.user)",
"instance = self.get_object()\nif instance.contest.publish_date < timezone.now():\n raise exceptions.PermissionDenied('You cannot delete already published submission sets.')\ninstance.submission... | <|body_start_0|>
if self.request.user.is_superuser:
return self.queryset
return self.queryset.filter(user=self.request.user)
<|end_body_0|>
<|body_start_1|>
instance = self.get_object()
if instance.contest.publish_date < timezone.now():
raise exceptions.Permissio... | SubmissionSetViewSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubmissionSetViewSet:
def get_queryset(self):
"""Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions"""
<|body_0|>
def destroy(self, request, *args, **kwargs):
"""Destroy the instance... | stack_v2_sparse_classes_36k_train_027699 | 5,658 | permissive | [
{
"docstring": "Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Destroy the instance and all related submissions.",
"name... | 2 | stack_v2_sparse_classes_30k_train_004539 | Implement the Python class `SubmissionSetViewSet` described below.
Class description:
Implement the SubmissionSetViewSet class.
Method signatures and docstrings:
- def get_queryset(self): Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submis... | Implement the Python class `SubmissionSetViewSet` described below.
Class description:
Implement the SubmissionSetViewSet class.
Method signatures and docstrings:
- def get_queryset(self): Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submis... | d9876e37d8057009c10ef0c4d23a2b04d322f4eb | <|skeleton|>
class SubmissionSetViewSet:
def get_queryset(self):
"""Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions"""
<|body_0|>
def destroy(self, request, *args, **kwargs):
"""Destroy the instance... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubmissionSetViewSet:
def get_queryset(self):
"""Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions"""
if self.request.user.is_superuser:
return self.queryset
return self.queryset.filter(us... | the_stack_v2_python_sparse | src/rolca/core/api/views.py | dblenkus/rolca | train | 0 |
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