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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d25a60fd706303e81a9eac9e4071776e34e9ba98 | [
"self.surface = surface\nself.beans = []\nself.framecount = 1",
"self.framecount += 1\nx_off = self.framecount * 0.0003\ny_off = x_off + 20\nx = noise.pnoise1(x_off, octaves=8) * self.surface.get_width()\ny = noise.pnoise1(y_off, octaves=8) * self.surface.get_height()\nif self.framecount % 4 == 0:\n self.beans... | <|body_start_0|>
self.surface = surface
self.beans = []
self.framecount = 1
<|end_body_0|>
<|body_start_1|>
self.framecount += 1
x_off = self.framecount * 0.0003
y_off = x_off + 20
x = noise.pnoise1(x_off, octaves=8) * self.surface.get_width()
y = noise.p... | draws nice colored lines on surface | CoffeeDraw | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoffeeDraw:
"""draws nice colored lines on surface"""
def __init__(self, surface):
"""(pygame.Surface) surface - surface to draw on"""
<|body_0|>
def update(self):
"""update every frame"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.surfac... | stack_v2_sparse_classes_36k_train_027800 | 3,495 | no_license | [
{
"docstring": "(pygame.Surface) surface - surface to draw on",
"name": "__init__",
"signature": "def __init__(self, surface)"
},
{
"docstring": "update every frame",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004261 | Implement the Python class `CoffeeDraw` described below.
Class description:
draws nice colored lines on surface
Method signatures and docstrings:
- def __init__(self, surface): (pygame.Surface) surface - surface to draw on
- def update(self): update every frame | Implement the Python class `CoffeeDraw` described below.
Class description:
draws nice colored lines on surface
Method signatures and docstrings:
- def __init__(self, surface): (pygame.Surface) surface - surface to draw on
- def update(self): update every frame
<|skeleton|>
class CoffeeDraw:
"""draws nice colore... | 1fd421195a2888c0588a49f5a043a1110eedcdbf | <|skeleton|>
class CoffeeDraw:
"""draws nice colored lines on surface"""
def __init__(self, surface):
"""(pygame.Surface) surface - surface to draw on"""
<|body_0|>
def update(self):
"""update every frame"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoffeeDraw:
"""draws nice colored lines on surface"""
def __init__(self, surface):
"""(pygame.Surface) surface - surface to draw on"""
self.surface = surface
self.beans = []
self.framecount = 1
def update(self):
"""update every frame"""
self.framecount... | the_stack_v2_python_sparse | effects/CoffeeBean.py | gunny26/pygame | train | 5 |
91634db380917c9365f2b9e7cb4de4a49b27517a | [
"pool = ForkedProcessPool(name=self.test_01_sys_exit_1.__name__)\nimport pytest\nwith pytest.raises(FailedProcessException, match=ForkedProcessPool.NONZERO_EXIT_STATUS_ERROR_REGEX) as exec_info:\n pool.submit(_sys_exit_1.__name__, _sys_exit_1)\n pool.shutdown()",
"pool = ForkedProcessPool(name=self.test_02_... | <|body_start_0|>
pool = ForkedProcessPool(name=self.test_01_sys_exit_1.__name__)
import pytest
with pytest.raises(FailedProcessException, match=ForkedProcessPool.NONZERO_EXIT_STATUS_ERROR_REGEX) as exec_info:
pool.submit(_sys_exit_1.__name__, _sys_exit_1)
pool.shutdown()
... | TestForkedProcessPool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestForkedProcessPool:
def test_01_sys_exit_1(self):
"""Check that processes that exit with sys.exit(1) are detected. :return:"""
<|body_0|>
def test_02_exception(self):
"""Check that processes that exit with sys.exit(1) are detected. :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_027801 | 13,482 | permissive | [
{
"docstring": "Check that processes that exit with sys.exit(1) are detected. :return:",
"name": "test_01_sys_exit_1",
"signature": "def test_01_sys_exit_1(self)"
},
{
"docstring": "Check that processes that exit with sys.exit(1) are detected. :return:",
"name": "test_02_exception",
"sig... | 3 | stack_v2_sparse_classes_30k_train_013922 | Implement the Python class `TestForkedProcessPool` described below.
Class description:
Implement the TestForkedProcessPool class.
Method signatures and docstrings:
- def test_01_sys_exit_1(self): Check that processes that exit with sys.exit(1) are detected. :return:
- def test_02_exception(self): Check that processes... | Implement the Python class `TestForkedProcessPool` described below.
Class description:
Implement the TestForkedProcessPool class.
Method signatures and docstrings:
- def test_01_sys_exit_1(self): Check that processes that exit with sys.exit(1) are detected. :return:
- def test_02_exception(self): Check that processes... | cdd9bbdc2a3a832be24f20105b8c9fe28149cb63 | <|skeleton|>
class TestForkedProcessPool:
def test_01_sys_exit_1(self):
"""Check that processes that exit with sys.exit(1) are detected. :return:"""
<|body_0|>
def test_02_exception(self):
"""Check that processes that exit with sys.exit(1) are detected. :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestForkedProcessPool:
def test_01_sys_exit_1(self):
"""Check that processes that exit with sys.exit(1) are detected. :return:"""
pool = ForkedProcessPool(name=self.test_01_sys_exit_1.__name__)
import pytest
with pytest.raises(FailedProcessException, match=ForkedProcessPool.NON... | the_stack_v2_python_sparse | rlscope/profiler/concurrent.py | UofT-EcoSystem/rlscope | train | 42 | |
9184cb39bebd2bbbad3ad44212c6f27a74219ede | [
"fields = cls.IMPORT_FIELDS\nfor name, field in fields.items():\n base_field = None\n for f in cls._meta.fields:\n if f.name == name:\n base_field = f\n break\n if base_field:\n if 'label' not in field:\n field['label'] = base_field.verbose_name\n if 'h... | <|body_start_0|>
fields = cls.IMPORT_FIELDS
for name, field in fields.items():
base_field = None
for f in cls._meta.fields:
if f.name == name:
base_field = f
break
if base_field:
if 'label' not in... | Model mixin class which provides support for 'data import' functionality. Models which implement this mixin should provide information on the fields available for import | DataImportMixin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataImportMixin:
"""Model mixin class which provides support for 'data import' functionality. Models which implement this mixin should provide information on the fields available for import"""
def get_import_fields(cls):
"""Return all available import fields. Where information on a p... | stack_v2_sparse_classes_36k_train_027802 | 29,718 | permissive | [
{
"docstring": "Return all available import fields. Where information on a particular field is not explicitly provided, introspect the base model to (attempt to) find that information.",
"name": "get_import_fields",
"signature": "def get_import_fields(cls)"
},
{
"docstring": "Return all *require... | 2 | stack_v2_sparse_classes_30k_train_002037 | Implement the Python class `DataImportMixin` described below.
Class description:
Model mixin class which provides support for 'data import' functionality. Models which implement this mixin should provide information on the fields available for import
Method signatures and docstrings:
- def get_import_fields(cls): Ret... | Implement the Python class `DataImportMixin` described below.
Class description:
Model mixin class which provides support for 'data import' functionality. Models which implement this mixin should provide information on the fields available for import
Method signatures and docstrings:
- def get_import_fields(cls): Ret... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class DataImportMixin:
"""Model mixin class which provides support for 'data import' functionality. Models which implement this mixin should provide information on the fields available for import"""
def get_import_fields(cls):
"""Return all available import fields. Where information on a p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataImportMixin:
"""Model mixin class which provides support for 'data import' functionality. Models which implement this mixin should provide information on the fields available for import"""
def get_import_fields(cls):
"""Return all available import fields. Where information on a particular fie... | the_stack_v2_python_sparse | InvenTree/InvenTree/models.py | inventree/InvenTree | train | 3,077 |
d6042ec81b5d80b63131d038f9032f8b9d76b978 | [
"WAITLIST = ['__lll_lock_wait', 'futex_abstimed_wait', 'futex_abstimed_wait_cancelable', 'futex_reltimed_wait', 'futex_reltimed_wait_cancelable', 'futex_wait', 'futex_wait_cancelable']\nif is_thread_blocked_with_frame(thread_id, top_line, WAITLIST, 'pthread_mutex'):\n return MutexType.PTHREAD_MUTEX_T\nif is_thre... | <|body_start_0|>
WAITLIST = ['__lll_lock_wait', 'futex_abstimed_wait', 'futex_abstimed_wait_cancelable', 'futex_reltimed_wait', 'futex_reltimed_wait_cancelable', 'futex_wait', 'futex_wait_cancelable']
if is_thread_blocked_with_frame(thread_id, top_line, WAITLIST, 'pthread_mutex'):
return Mut... | Types of mutexes that we can detect deadlocks. | MutexType | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MutexType:
"""Types of mutexes that we can detect deadlocks."""
def get_mutex_type(thread_id, top_line):
"""Returns the probable mutex type, based on the first line of the thread's stack. Returns None if not found."""
<|body_0|>
def get_mutex_owner_and_address_func_for_t... | stack_v2_sparse_classes_36k_train_027803 | 16,226 | permissive | [
{
"docstring": "Returns the probable mutex type, based on the first line of the thread's stack. Returns None if not found.",
"name": "get_mutex_type",
"signature": "def get_mutex_type(thread_id, top_line)"
},
{
"docstring": "Returns a function to resolve the mutex owner and address for the given... | 2 | stack_v2_sparse_classes_30k_train_003022 | Implement the Python class `MutexType` described below.
Class description:
Types of mutexes that we can detect deadlocks.
Method signatures and docstrings:
- def get_mutex_type(thread_id, top_line): Returns the probable mutex type, based on the first line of the thread's stack. Returns None if not found.
- def get_mu... | Implement the Python class `MutexType` described below.
Class description:
Types of mutexes that we can detect deadlocks.
Method signatures and docstrings:
- def get_mutex_type(thread_id, top_line): Returns the probable mutex type, based on the first line of the thread's stack. Returns None if not found.
- def get_mu... | ab45d9b6a7a2a24b2a725447387f36772dd2cc4a | <|skeleton|>
class MutexType:
"""Types of mutexes that we can detect deadlocks."""
def get_mutex_type(thread_id, top_line):
"""Returns the probable mutex type, based on the first line of the thread's stack. Returns None if not found."""
<|body_0|>
def get_mutex_owner_and_address_func_for_t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MutexType:
"""Types of mutexes that we can detect deadlocks."""
def get_mutex_type(thread_id, top_line):
"""Returns the probable mutex type, based on the first line of the thread's stack. Returns None if not found."""
WAITLIST = ['__lll_lock_wait', 'futex_abstimed_wait', 'futex_abstimed_w... | the_stack_v2_python_sparse | folly/experimental/gdb/deadlock.py | facebook/folly | train | 23,991 |
f6e0b997e0ab73243c7e9380538a593e2e0e5dbc | [
"if self._disable:\n return False\nif self.spectrograph is None or self.telescope is None:\n return False\nif self.unknown != 'snr':\n raise NotImplementedError('Only SNR calculations currently supported')\nself._update_snr()",
"if self.verbose:\n msg1 = 'Creating exposure for {} ({})'.format(self.tel... | <|body_start_0|>
if self._disable:
return False
if self.spectrograph is None or self.telescope is None:
return False
if self.unknown != 'snr':
raise NotImplementedError('Only SNR calculations currently supported')
self._update_snr()
<|end_body_0|>
<|b... | A subclass of the base Exposure model, for spectroscopic ETC calculations. | SpectrographicExposure | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpectrographicExposure:
"""A subclass of the base Exposure model, for spectroscopic ETC calculations."""
def calculate(self):
"""Wrapper to calculate the exposure time, SNR, or limiting magnitude, based on the other two. The "unknown" attribute controls which of these parameters is c... | stack_v2_sparse_classes_36k_train_027804 | 18,852 | no_license | [
{
"docstring": "Wrapper to calculate the exposure time, SNR, or limiting magnitude, based on the other two. The \"unknown\" attribute controls which of these parameters is calculated.",
"name": "calculate",
"signature": "def calculate(self)"
},
{
"docstring": "Calculate the SNR based on the curr... | 2 | stack_v2_sparse_classes_30k_train_002685 | Implement the Python class `SpectrographicExposure` described below.
Class description:
A subclass of the base Exposure model, for spectroscopic ETC calculations.
Method signatures and docstrings:
- def calculate(self): Wrapper to calculate the exposure time, SNR, or limiting magnitude, based on the other two. The "u... | Implement the Python class `SpectrographicExposure` described below.
Class description:
A subclass of the base Exposure model, for spectroscopic ETC calculations.
Method signatures and docstrings:
- def calculate(self): Wrapper to calculate the exposure time, SNR, or limiting magnitude, based on the other two. The "u... | ccd63cc79671fb333b892c3125861be2128e5ee8 | <|skeleton|>
class SpectrographicExposure:
"""A subclass of the base Exposure model, for spectroscopic ETC calculations."""
def calculate(self):
"""Wrapper to calculate the exposure time, SNR, or limiting magnitude, based on the other two. The "unknown" attribute controls which of these parameters is c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpectrographicExposure:
"""A subclass of the base Exposure model, for spectroscopic ETC calculations."""
def calculate(self):
"""Wrapper to calculate the exposure time, SNR, or limiting magnitude, based on the other two. The "unknown" attribute controls which of these parameters is calculated."""... | the_stack_v2_python_sparse | syotools/models/exposure.py | tumlinson/luvoir_simtools | train | 1 |
7eaba6bd8242c467d2422136ebc2ec5b4dcd7bf8 | [
"super().__init__()\nself.N = neighbor_graph\nself.stylesheet = stylesheet\nself.style = next(self.stylesheet[style])\nself._ball()\nself._hull()\nself._edges()\nself._points()\nself._vertices()",
"point_style = self.style.get('graph_point')\nif point_style is not None:\n point_style_dict = next(self.styleshee... | <|body_start_0|>
super().__init__()
self.N = neighbor_graph
self.stylesheet = stylesheet
self.style = next(self.stylesheet[style])
self._ball()
self._hull()
self._edges()
self._points()
self._vertices()
<|end_body_0|>
<|body_start_1|>
poin... | A utility class used to draw visualizations of NeighborGraph objects as a series of points, edges, as well as convex hulls. Attributes ---------- neighbor_graph: NeighborGraph a NeighborGraph object to draw to a canvas. style: str The object style used to draw a NeighborGraph as an str. (default 'neighbor_graph') style... | VizNeighborGraph | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VizNeighborGraph:
"""A utility class used to draw visualizations of NeighborGraph objects as a series of points, edges, as well as convex hulls. Attributes ---------- neighbor_graph: NeighborGraph a NeighborGraph object to draw to a canvas. style: str The object style used to draw a NeighborGraph... | stack_v2_sparse_classes_36k_train_027805 | 4,615 | permissive | [
{
"docstring": "Parameters ---------- neighbor_graph: NeighborGraph a NeighborGraph object to draw to a canvas. style: str, optional The object style used to draw a NeighborGraph as an str. (default 'neighbor_graph') stylesheet: StyleSheet, optional The stylesheet used to describe which elements to draw an how ... | 6 | stack_v2_sparse_classes_30k_train_013502 | Implement the Python class `VizNeighborGraph` described below.
Class description:
A utility class used to draw visualizations of NeighborGraph objects as a series of points, edges, as well as convex hulls. Attributes ---------- neighbor_graph: NeighborGraph a NeighborGraph object to draw to a canvas. style: str The ob... | Implement the Python class `VizNeighborGraph` described below.
Class description:
A utility class used to draw visualizations of NeighborGraph objects as a series of points, edges, as well as convex hulls. Attributes ---------- neighbor_graph: NeighborGraph a NeighborGraph object to draw to a canvas. style: str The ob... | 1383b7b005ce59d35b4e012524382c08675594c6 | <|skeleton|>
class VizNeighborGraph:
"""A utility class used to draw visualizations of NeighborGraph objects as a series of points, edges, as well as convex hulls. Attributes ---------- neighbor_graph: NeighborGraph a NeighborGraph object to draw to a canvas. style: str The object style used to draw a NeighborGraph... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VizNeighborGraph:
"""A utility class used to draw visualizations of NeighborGraph objects as a series of points, edges, as well as convex hulls. Attributes ---------- neighbor_graph: NeighborGraph a NeighborGraph object to draw to a canvas. style: str The object style used to draw a NeighborGraph as an str. (... | the_stack_v2_python_sparse | greedypermutation/vizneighborgraph.py | donsheehy/greedypermutation | train | 6 |
5999a49edf907a298784b8e808c03c1961fff2b2 | [
"super().__init__(cost_func)\nself.support_for_bounds = True\nself.no_bounds_minimizers = ['lm-scipy']\nself.param_ranges = None\nself.result = None\nself._status = None\nself._popt = None\nself._minimizer = ''",
"if self.minimizer == 'lm-scipy':\n self._minimizer = 'lm'\nelse:\n self._minimizer = self.mini... | <|body_start_0|>
super().__init__(cost_func)
self.support_for_bounds = True
self.no_bounds_minimizers = ['lm-scipy']
self.param_ranges = None
self.result = None
self._status = None
self._popt = None
self._minimizer = ''
<|end_body_0|>
<|body_start_1|>
... | Controller for the Scipy Least-Squares fitting software. | ScipyLSController | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScipyLSController:
"""Controller for the Scipy Least-Squares fitting software."""
def __init__(self, cost_func):
"""Initialise the class. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostF... | stack_v2_sparse_classes_36k_train_027806 | 3,366 | permissive | [
{
"docstring": "Initialise the class. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostFunc`",
"name": "__init__",
"signature": "def __init__(self, cost_func)"
},
{
"docstring": "Setup problem ready t... | 4 | null | Implement the Python class `ScipyLSController` described below.
Class description:
Controller for the Scipy Least-Squares fitting software.
Method signatures and docstrings:
- def __init__(self, cost_func): Initialise the class. :param cost_func: Cost function object selected from options. :type cost_func: subclass o... | Implement the Python class `ScipyLSController` described below.
Class description:
Controller for the Scipy Least-Squares fitting software.
Method signatures and docstrings:
- def __init__(self, cost_func): Initialise the class. :param cost_func: Cost function object selected from options. :type cost_func: subclass o... | 5ee7e66d963ebe9296c0a62c24b9616f6c65537e | <|skeleton|>
class ScipyLSController:
"""Controller for the Scipy Least-Squares fitting software."""
def __init__(self, cost_func):
"""Initialise the class. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostF... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScipyLSController:
"""Controller for the Scipy Least-Squares fitting software."""
def __init__(self, cost_func):
"""Initialise the class. :param cost_func: Cost function object selected from options. :type cost_func: subclass of :class:`~fitbenchmarking.cost_func.base_cost_func.CostFunc`"""
... | the_stack_v2_python_sparse | fitbenchmarking/controllers/scipy_ls_controller.py | fitbenchmarking/fitbenchmarking | train | 15 |
5097d0a34fd70661e0574a0905fe8896d195c89f | [
"lst = [None] * len(S)\ntargets = []\nfor i in range(len(S)):\n if S[i] == C:\n targets.append(i)\nfor i in range(len(S)):\n if i in targets:\n lst[i] = 0\n else:\n lst[i] = min([abs(i - x) for x in targets])\nreturn lst",
"lst = [n] * len(S)\npos = -n\nfor i in range(n) + range(n, 0... | <|body_start_0|>
lst = [None] * len(S)
targets = []
for i in range(len(S)):
if S[i] == C:
targets.append(i)
for i in range(len(S)):
if i in targets:
lst[i] = 0
else:
lst[i] = min([abs(i - x) for x in targ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shortestToChar(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
<|body_0|>
def shortestToChar(self, S, C):
""":param S: :param C: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
lst = [None] * len(S)
targ... | stack_v2_sparse_classes_36k_train_027807 | 1,497 | no_license | [
{
"docstring": ":type S: str :type C: str :rtype: List[int]",
"name": "shortestToChar",
"signature": "def shortestToChar(self, S, C)"
},
{
"docstring": ":param S: :param C: :return:",
"name": "shortestToChar",
"signature": "def shortestToChar(self, S, C)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestToChar(self, S, C): :type S: str :type C: str :rtype: List[int]
- def shortestToChar(self, S, C): :param S: :param C: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestToChar(self, S, C): :type S: str :type C: str :rtype: List[int]
- def shortestToChar(self, S, C): :param S: :param C: :return:
<|skeleton|>
class Solution:
def ... | 8595b04cf5a024c2cd8a97f750d890a818568401 | <|skeleton|>
class Solution:
def shortestToChar(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
<|body_0|>
def shortestToChar(self, S, C):
""":param S: :param C: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def shortestToChar(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
lst = [None] * len(S)
targets = []
for i in range(len(S)):
if S[i] == C:
targets.append(i)
for i in range(len(S)):
if i in targets:
... | the_stack_v2_python_sparse | python/821.shortest-distance-to-a-character.py | tainenko/Leetcode2019 | train | 5 | |
4c23b1be8795ddcf1fa3ff07f86023bc149f0b48 | [
"c = collections.Counter(arr)\nfor i in c:\n if c[i] * 4 > len(arr):\n return i",
"n = len(arr)\nspan = n // 4 + 1\nfor i in range(0, n, span):\n iter_l = bisect.bisect_left(arr, arr[i])\n iter_r = bisect.bisect_right(arr, arr[i])\n if iter_r - iter_l >= span:\n return arr[i]"
] | <|body_start_0|>
c = collections.Counter(arr)
for i in c:
if c[i] * 4 > len(arr):
return i
<|end_body_0|>
<|body_start_1|>
n = len(arr)
span = n // 4 + 1
for i in range(0, n, span):
iter_l = bisect.bisect_left(arr, arr[i])
iter... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findSpecialInteger(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_0|>
def findSpecialInteger(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
c = collections.Counter(arr)
... | stack_v2_sparse_classes_36k_train_027808 | 855 | no_license | [
{
"docstring": ":type arr: List[int] :rtype: int",
"name": "findSpecialInteger",
"signature": "def findSpecialInteger(self, arr)"
},
{
"docstring": ":type arr: List[int] :rtype: int",
"name": "findSpecialInteger",
"signature": "def findSpecialInteger(self, arr)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000425 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSpecialInteger(self, arr): :type arr: List[int] :rtype: int
- def findSpecialInteger(self, arr): :type arr: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSpecialInteger(self, arr): :type arr: List[int] :rtype: int
- def findSpecialInteger(self, arr): :type arr: List[int] :rtype: int
<|skeleton|>
class Solution:
def f... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def findSpecialInteger(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_0|>
def findSpecialInteger(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findSpecialInteger(self, arr):
""":type arr: List[int] :rtype: int"""
c = collections.Counter(arr)
for i in c:
if c[i] * 4 > len(arr):
return i
def findSpecialInteger(self, arr):
""":type arr: List[int] :rtype: int"""
n = l... | the_stack_v2_python_sparse | 1287_Element_Appearing_More_Than_25%_In_Sorted_Array.py | bingli8802/leetcode | train | 0 | |
16ff082144c2081e4919ec95f8ad1718a944b27f | [
"self.list = []\nself.key_value = {}\nself.cap = capacity",
"if key not in self.list:\n return -1\nelse:\n self.list.remove(key)\n self.list.append(key)\n return self.key_value[key]",
"if len(self.list) < self.cap:\n if key not in self.list:\n self.list.append(key)\n self.key_value[... | <|body_start_0|>
self.list = []
self.key_value = {}
self.cap = capacity
<|end_body_0|>
<|body_start_1|>
if key not in self.list:
return -1
else:
self.list.remove(key)
self.list.append(key)
return self.key_value[key]
<|end_body_1|>
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_027809 | 3,513 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_004802 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | 9f949ae6b5ee178c7153f1c402a92accbf710111 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.list = []
self.key_value = {}
self.cap = capacity
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.list:
return -1
else:
self.list.... | the_stack_v2_python_sparse | 算法题/LRU缓存机制.py | yllzxzyq/Nick-life-of-code | train | 1 | |
17881f8ea30d6a578e1b0280d01b753254485b6b | [
"self.width = width\nself.height = height\nself.food = food\nself.snake = [[0, 0]]\nself.score = 0",
"nextx, nexty = self.snake[0]\nif direction == 'U':\n nextx -= 1\nelif direction == 'L':\n nexty -= 1\nelif direction == 'D':\n nextx += 1\nelif direction == 'R':\n nexty += 1\nif self.food and [nextx,... | <|body_start_0|>
self.width = width
self.height = height
self.food = food
self.snake = [[0, 0]]
self.score = 0
<|end_body_0|>
<|body_start_1|>
nextx, nexty = self.snake[0]
if direction == 'U':
nextx -= 1
elif direction == 'L':
next... | 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_027810 | 2,161 | 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_003210 | 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 -... | 16b329e5eafffb3cee14a054a35cfe7c6eb9268a | <|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 | ixl/353DesignSnakeGame.py | CheLcodes/leetcode_python_practice | train | 0 | |
e70651ef79d9ddeb6338d8757744f83e07b1bdef | [
"self.df = data\nself.feats = feats\nself.df.drop(['addr_state', 'installment', 'purpose'], 1, inplace=True)\nself.df = pd.get_dummies(self.df)\ny = self.df.int_rate.values\nself.df.drop('int_rate', axis=1, inplace=True)\nX, y = shuffle(self.df.values, y, random_state=30)\nX = X.astype(np.float32)\noffset = int(X.s... | <|body_start_0|>
self.df = data
self.feats = feats
self.df.drop(['addr_state', 'installment', 'purpose'], 1, inplace=True)
self.df = pd.get_dummies(self.df)
y = self.df.int_rate.values
self.df.drop('int_rate', axis=1, inplace=True)
X, y = shuffle(self.df.values, y... | This is the class for visulization methods of GBT | GBT_model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GBT_model:
"""This is the class for visulization methods of GBT"""
def __init__(self, data, feats):
"""Constructor"""
<|body_0|>
def gbt_model(self):
"""get the dataframe, test and training data Return ====== return accuracy of GBT regression"""
<|body_1|... | stack_v2_sparse_classes_36k_train_027811 | 4,025 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, data, feats)"
},
{
"docstring": "get the dataframe, test and training data Return ====== return accuracy of GBT regression",
"name": "gbt_model",
"signature": "def gbt_model(self)"
},
{
"docstring"... | 5 | stack_v2_sparse_classes_30k_train_014886 | Implement the Python class `GBT_model` described below.
Class description:
This is the class for visulization methods of GBT
Method signatures and docstrings:
- def __init__(self, data, feats): Constructor
- def gbt_model(self): get the dataframe, test and training data Return ====== return accuracy of GBT regression... | Implement the Python class `GBT_model` described below.
Class description:
This is the class for visulization methods of GBT
Method signatures and docstrings:
- def __init__(self, data, feats): Constructor
- def gbt_model(self): get the dataframe, test and training data Return ====== return accuracy of GBT regression... | dc9185cbc5e65650d985ebecf877a157c8c19a13 | <|skeleton|>
class GBT_model:
"""This is the class for visulization methods of GBT"""
def __init__(self, data, feats):
"""Constructor"""
<|body_0|>
def gbt_model(self):
"""get the dataframe, test and training data Return ====== return accuracy of GBT regression"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GBT_model:
"""This is the class for visulization methods of GBT"""
def __init__(self, data, feats):
"""Constructor"""
self.df = data
self.feats = feats
self.df.drop(['addr_state', 'installment', 'purpose'], 1, inplace=True)
self.df = pd.get_dummies(self.df)
... | the_stack_v2_python_sparse | sj2384/GBT_model.py | ds-ga-1007/final_project | train | 0 |
9e3e9c30f9b8440388e8e6677e1d7cc7b14c7f91 | [
"e = Furniture('test product code', 'test description', 'test market price', 'test rental price', 'test material', 'test size')\nself.assertEqual(e.product_code, 'test product code')\nself.assertEqual(e.description, 'test description')\nself.assertEqual(e.market_price, 'test market price')\nself.assertEqual(e.renta... | <|body_start_0|>
e = Furniture('test product code', 'test description', 'test market price', 'test rental price', 'test material', 'test size')
self.assertEqual(e.product_code, 'test product code')
self.assertEqual(e.description, 'test description')
self.assertEqual(e.market_price, 'test... | FurnitureTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FurnitureTest:
def test_furniture_init(self):
"""Tests that Furniture can be initiated"""
<|body_0|>
def test_furniture_return(self):
"""Tests Furniture return_as_dictionary"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
e = Furniture('test product... | stack_v2_sparse_classes_36k_train_027812 | 9,076 | no_license | [
{
"docstring": "Tests that Furniture can be initiated",
"name": "test_furniture_init",
"signature": "def test_furniture_init(self)"
},
{
"docstring": "Tests Furniture return_as_dictionary",
"name": "test_furniture_return",
"signature": "def test_furniture_return(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011838 | Implement the Python class `FurnitureTest` described below.
Class description:
Implement the FurnitureTest class.
Method signatures and docstrings:
- def test_furniture_init(self): Tests that Furniture can be initiated
- def test_furniture_return(self): Tests Furniture return_as_dictionary | Implement the Python class `FurnitureTest` described below.
Class description:
Implement the FurnitureTest class.
Method signatures and docstrings:
- def test_furniture_init(self): Tests that Furniture can be initiated
- def test_furniture_return(self): Tests Furniture return_as_dictionary
<|skeleton|>
class Furnitu... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class FurnitureTest:
def test_furniture_init(self):
"""Tests that Furniture can be initiated"""
<|body_0|>
def test_furniture_return(self):
"""Tests Furniture return_as_dictionary"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FurnitureTest:
def test_furniture_init(self):
"""Tests that Furniture can be initiated"""
e = Furniture('test product code', 'test description', 'test market price', 'test rental price', 'test material', 'test size')
self.assertEqual(e.product_code, 'test product code')
self.as... | the_stack_v2_python_sparse | students/kyle_lehning/Lesson01/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 | |
6536469631939640f12ced1d33068590fdcb876c | [
"level = {s}\nwhile True:\n valid = []\n for s in level:\n try:\n eval('0,' + filter('()'.count, s).replace(')', '),'))\n valid.append(s)\n except Exception:\n pass\n if valid:\n return valid\n level = {s[:i] + s[i + 1:] for s in level for i in range... | <|body_start_0|>
level = {s}
while True:
valid = []
for s in level:
try:
eval('0,' + filter('()'.count, s).replace(')', '),'))
valid.append(s)
except Exception:
pass
if valid:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeInvalidParentheses(self, s):
""":type s: str :rtype: List[str] BFS 起手勢變形~ 將 root 加入 list."""
<|body_0|>
def rewrite(self, s):
""":type s: str :rtype: List[str] my best and clear solution :-) BFS 起手勢變形~ 將 root 加入 list."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_027813 | 3,225 | no_license | [
{
"docstring": ":type s: str :rtype: List[str] BFS 起手勢變形~ 將 root 加入 list.",
"name": "removeInvalidParentheses",
"signature": "def removeInvalidParentheses(self, s)"
},
{
"docstring": ":type s: str :rtype: List[str] my best and clear solution :-) BFS 起手勢變形~ 將 root 加入 list.",
"name": "rewrite"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeInvalidParentheses(self, s): :type s: str :rtype: List[str] BFS 起手勢變形~ 將 root 加入 list.
- def rewrite(self, s): :type s: str :rtype: List[str] my best and clear solution... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeInvalidParentheses(self, s): :type s: str :rtype: List[str] BFS 起手勢變形~ 將 root 加入 list.
- def rewrite(self, s): :type s: str :rtype: List[str] my best and clear solution... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def removeInvalidParentheses(self, s):
""":type s: str :rtype: List[str] BFS 起手勢變形~ 將 root 加入 list."""
<|body_0|>
def rewrite(self, s):
""":type s: str :rtype: List[str] my best and clear solution :-) BFS 起手勢變形~ 將 root 加入 list."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeInvalidParentheses(self, s):
""":type s: str :rtype: List[str] BFS 起手勢變形~ 將 root 加入 list."""
level = {s}
while True:
valid = []
for s in level:
try:
eval('0,' + filter('()'.count, s).replace(')', '),'))
... | the_stack_v2_python_sparse | co_twitter/301_Remove_Invalid_Parentheses.py | vsdrun/lc_public | train | 6 | |
bc82625bc4ea04ca856b77ff8d2056f58299ba77 | [
"references = ['nothing']\nif not metrics:\n aidegen_metrics.starts_asuite_metrics(references)\n self.assertFalse(mock_print_data.called)\nelse:\n with mock.patch.object(metrics_utils, 'get_start_time') as mk_get:\n with mock.patch.object(metrics, 'AtestStartEvent') as mk_start:\n aidegen... | <|body_start_0|>
references = ['nothing']
if not metrics:
aidegen_metrics.starts_asuite_metrics(references)
self.assertFalse(mock_print_data.called)
else:
with mock.patch.object(metrics_utils, 'get_start_time') as mk_get:
with mock.patch.object... | Unit tests for aidegen_metrics.py. | AidegenMetricsUnittests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AidegenMetricsUnittests:
"""Unit tests for aidegen_metrics.py."""
def test_starts_asuite_metrics(self, mock_print_data):
"""Test starts_asuite_metrics."""
<|body_0|>
def test_ends_asuite_metrics(self):
"""Test ends_asuite_metrics."""
<|body_1|>
def t... | stack_v2_sparse_classes_36k_train_027814 | 2,531 | no_license | [
{
"docstring": "Test starts_asuite_metrics.",
"name": "test_starts_asuite_metrics",
"signature": "def test_starts_asuite_metrics(self, mock_print_data)"
},
{
"docstring": "Test ends_asuite_metrics.",
"name": "test_ends_asuite_metrics",
"signature": "def test_ends_asuite_metrics(self)"
... | 3 | null | Implement the Python class `AidegenMetricsUnittests` described below.
Class description:
Unit tests for aidegen_metrics.py.
Method signatures and docstrings:
- def test_starts_asuite_metrics(self, mock_print_data): Test starts_asuite_metrics.
- def test_ends_asuite_metrics(self): Test ends_asuite_metrics.
- def test_... | Implement the Python class `AidegenMetricsUnittests` described below.
Class description:
Unit tests for aidegen_metrics.py.
Method signatures and docstrings:
- def test_starts_asuite_metrics(self, mock_print_data): Test starts_asuite_metrics.
- def test_ends_asuite_metrics(self): Test ends_asuite_metrics.
- def test_... | 78a61ca023cbf1a0cecfef8b97df2b274ac3a988 | <|skeleton|>
class AidegenMetricsUnittests:
"""Unit tests for aidegen_metrics.py."""
def test_starts_asuite_metrics(self, mock_print_data):
"""Test starts_asuite_metrics."""
<|body_0|>
def test_ends_asuite_metrics(self):
"""Test ends_asuite_metrics."""
<|body_1|>
def t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AidegenMetricsUnittests:
"""Unit tests for aidegen_metrics.py."""
def test_starts_asuite_metrics(self, mock_print_data):
"""Test starts_asuite_metrics."""
references = ['nothing']
if not metrics:
aidegen_metrics.starts_asuite_metrics(references)
self.assert... | the_stack_v2_python_sparse | tools/asuite/aidegen/lib/aidegen_metrics_unittest.py | ZYHGOD-1/Aosp11 | train | 0 |
2c773aa30db86b7ded2d0b92e51924565ac64813 | [
"cube = set_up_variable_cube(np.ones((3, 3), dtype=np.float32))\nset_history_attribute(cube, 'Nowcast')\nself.assertTrue('history' in cube.attributes)\nself.assertTrue('Nowcast' in cube.attributes['history'])",
"cube = set_up_variable_cube(np.ones((3, 3), dtype=np.float32))\nold_history = '2018-09-13T11:28:29: St... | <|body_start_0|>
cube = set_up_variable_cube(np.ones((3, 3), dtype=np.float32))
set_history_attribute(cube, 'Nowcast')
self.assertTrue('history' in cube.attributes)
self.assertTrue('Nowcast' in cube.attributes['history'])
<|end_body_0|>
<|body_start_1|>
cube = set_up_variable_cu... | Test the set_history_attribute function. | Test_set_history_attribute | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_set_history_attribute:
"""Test the set_history_attribute function."""
def test_add_history(self):
"""Test that a history attribute has been added."""
<|body_0|>
def test_history_already_exists(self):
"""Test that the history attribute is overwritten, if it a... | stack_v2_sparse_classes_36k_train_027815 | 12,457 | permissive | [
{
"docstring": "Test that a history attribute has been added.",
"name": "test_add_history",
"signature": "def test_add_history(self)"
},
{
"docstring": "Test that the history attribute is overwritten, if it already exists.",
"name": "test_history_already_exists",
"signature": "def test_h... | 4 | null | Implement the Python class `Test_set_history_attribute` described below.
Class description:
Test the set_history_attribute function.
Method signatures and docstrings:
- def test_add_history(self): Test that a history attribute has been added.
- def test_history_already_exists(self): Test that the history attribute is... | Implement the Python class `Test_set_history_attribute` described below.
Class description:
Test the set_history_attribute function.
Method signatures and docstrings:
- def test_add_history(self): Test that a history attribute has been added.
- def test_history_already_exists(self): Test that the history attribute is... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_set_history_attribute:
"""Test the set_history_attribute function."""
def test_add_history(self):
"""Test that a history attribute has been added."""
<|body_0|>
def test_history_already_exists(self):
"""Test that the history attribute is overwritten, if it a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_set_history_attribute:
"""Test the set_history_attribute function."""
def test_add_history(self):
"""Test that a history attribute has been added."""
cube = set_up_variable_cube(np.ones((3, 3), dtype=np.float32))
set_history_attribute(cube, 'Nowcast')
self.assertTrue(... | the_stack_v2_python_sparse | improver_tests/metadata/test_amend.py | metoppv/improver | train | 101 |
7340da8e9ddd2ab4fcb9b8103c88967cab920cda | [
"instance = cfg.GetInstanceInfo(self.inst_uuid)\ndisks = cfg.GetInstanceDisks(self.inst_uuid)\nif instance is None:\n raise errors.ProgrammerError(\"Unknown instance '%s' passed to IAllocator\" % self.inst_uuid)\nif not utils.AllDiskOfType(disks, constants.DTS_MIRRORED):\n raise errors.OpPrereqError(\"Can't r... | <|body_start_0|>
instance = cfg.GetInstanceInfo(self.inst_uuid)
disks = cfg.GetInstanceDisks(self.inst_uuid)
if instance is None:
raise errors.ProgrammerError("Unknown instance '%s' passed to IAllocator" % self.inst_uuid)
if not utils.AllDiskOfType(disks, constants.DTS_MIRROR... | A relocation request. | IAReqRelocate | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IAReqRelocate:
"""A relocation request."""
def GetRequest(self, cfg):
"""Request an relocation of an instance The checks for the completeness of the opcode must have already been done."""
<|body_0|>
def ValidateResult(self, ia, result):
"""Validates the result of... | stack_v2_sparse_classes_36k_train_027816 | 29,971 | permissive | [
{
"docstring": "Request an relocation of an instance The checks for the completeness of the opcode must have already been done.",
"name": "GetRequest",
"signature": "def GetRequest(self, cfg)"
},
{
"docstring": "Validates the result of an relocation request.",
"name": "ValidateResult",
"... | 3 | stack_v2_sparse_classes_30k_train_019083 | Implement the Python class `IAReqRelocate` described below.
Class description:
A relocation request.
Method signatures and docstrings:
- def GetRequest(self, cfg): Request an relocation of an instance The checks for the completeness of the opcode must have already been done.
- def ValidateResult(self, ia, result): Va... | Implement the Python class `IAReqRelocate` described below.
Class description:
A relocation request.
Method signatures and docstrings:
- def GetRequest(self, cfg): Request an relocation of an instance The checks for the completeness of the opcode must have already been done.
- def ValidateResult(self, ia, result): Va... | 456ea285a7583183c2c8e5bcffe9006ec8a9d658 | <|skeleton|>
class IAReqRelocate:
"""A relocation request."""
def GetRequest(self, cfg):
"""Request an relocation of an instance The checks for the completeness of the opcode must have already been done."""
<|body_0|>
def ValidateResult(self, ia, result):
"""Validates the result of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IAReqRelocate:
"""A relocation request."""
def GetRequest(self, cfg):
"""Request an relocation of an instance The checks for the completeness of the opcode must have already been done."""
instance = cfg.GetInstanceInfo(self.inst_uuid)
disks = cfg.GetInstanceDisks(self.inst_uuid)
... | the_stack_v2_python_sparse | lib/masterd/iallocator.py | ganeti/ganeti | train | 465 |
c7159a6993b9e9de81c46b3ac79f6b21865e34f6 | [
"model = gan.load('models/nn/ScalarIncremental.model')\nmodel_g = model['generator'].eval()\nstate_g = model['state_g']\ninput_g = model_g.generate_input(N)\npred_g, state_g = model_g(input_g.detach(), state_g)\nsentences = []\nfor sentence_idx in range(N):\n words = []\n for word_idx in range(config.seq_len)... | <|body_start_0|>
model = gan.load('models/nn/ScalarIncremental.model')
model_g = model['generator'].eval()
state_g = model['state_g']
input_g = model_g.generate_input(N)
pred_g, state_g = model_g(input_g.detach(), state_g)
sentences = []
for sentence_idx in range(... | generate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class generate:
def ScalarIncremental(N=1):
"""Generates text from ScalarIncremental. Args: N (int): Number of samples."""
<|body_0|>
def ClosestWord2Vec(N=1):
"""Generates text from ClosestWord2Vec. Args: N (int): Number of samples."""
<|body_1|>
def Bert(N=1... | stack_v2_sparse_classes_36k_train_027817 | 11,310 | permissive | [
{
"docstring": "Generates text from ScalarIncremental. Args: N (int): Number of samples.",
"name": "ScalarIncremental",
"signature": "def ScalarIncremental(N=1)"
},
{
"docstring": "Generates text from ClosestWord2Vec. Args: N (int): Number of samples.",
"name": "ClosestWord2Vec",
"signat... | 3 | stack_v2_sparse_classes_30k_train_016923 | Implement the Python class `generate` described below.
Class description:
Implement the generate class.
Method signatures and docstrings:
- def ScalarIncremental(N=1): Generates text from ScalarIncremental. Args: N (int): Number of samples.
- def ClosestWord2Vec(N=1): Generates text from ClosestWord2Vec. Args: N (int... | Implement the Python class `generate` described below.
Class description:
Implement the generate class.
Method signatures and docstrings:
- def ScalarIncremental(N=1): Generates text from ScalarIncremental. Args: N (int): Number of samples.
- def ClosestWord2Vec(N=1): Generates text from ClosestWord2Vec. Args: N (int... | c82cd38e7890b9843e2b9a91f14f004d6a54a562 | <|skeleton|>
class generate:
def ScalarIncremental(N=1):
"""Generates text from ScalarIncremental. Args: N (int): Number of samples."""
<|body_0|>
def ClosestWord2Vec(N=1):
"""Generates text from ClosestWord2Vec. Args: N (int): Number of samples."""
<|body_1|>
def Bert(N=1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class generate:
def ScalarIncremental(N=1):
"""Generates text from ScalarIncremental. Args: N (int): Number of samples."""
model = gan.load('models/nn/ScalarIncremental.model')
model_g = model['generator'].eval()
state_g = model['state_g']
input_g = model_g.generate_input(N)
... | the_stack_v2_python_sparse | src/evaluate.py | martinbenes1996/732A92-project | train | 0 | |
3ca280ea2b0b584187cefc7cc5b96ec3447e4983 | [
"super(OpsimFieldSlicer, self).__init__(verbose=verbose, badval=badval, plotFuncs=plotFuncs)\nself.fieldID = None\nself.simDataFieldIDColName = simDataFieldIDColName\nself.fieldIDColName = fieldIDColName\nself.fieldRaColName = fieldRaColName\nself.fieldDecColName = fieldDecColName\nself.columnsNeeded = [simDataFiel... | <|body_start_0|>
super(OpsimFieldSlicer, self).__init__(verbose=verbose, badval=badval, plotFuncs=plotFuncs)
self.fieldID = None
self.simDataFieldIDColName = simDataFieldIDColName
self.fieldIDColName = fieldIDColName
self.fieldRaColName = fieldRaColName
self.fieldDecColNa... | Index-based slicer, matched ID's between simData and fieldData. Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more generally for any kind of data slicing where the match is based on a simple ID value. Note that this slicer uses the fieldID of the opsim fields to generate spatial matc... | OpsimFieldSlicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpsimFieldSlicer:
"""Index-based slicer, matched ID's between simData and fieldData. Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more generally for any kind of data slicing where the match is based on a simple ID value. Note that this slicer uses the fieldID ... | stack_v2_sparse_classes_36k_train_027818 | 6,744 | no_license | [
{
"docstring": "Instantiate opsim field slicer (an index-based slicer that can do spatial plots). simDataFieldIDColName = the column name in simData for the field ID simDataFieldRaColName = the column name in simData for the field RA simDataFieldDecColName = the column name in simData for the field Dec fieldIDc... | 4 | stack_v2_sparse_classes_30k_train_010742 | Implement the Python class `OpsimFieldSlicer` described below.
Class description:
Index-based slicer, matched ID's between simData and fieldData. Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more generally for any kind of data slicing where the match is based on a simple ID value. ... | Implement the Python class `OpsimFieldSlicer` described below.
Class description:
Index-based slicer, matched ID's between simData and fieldData. Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more generally for any kind of data slicing where the match is based on a simple ID value. ... | 2b0faebd60fb4387366954d3531ac4d9df8c6fc4 | <|skeleton|>
class OpsimFieldSlicer:
"""Index-based slicer, matched ID's between simData and fieldData. Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more generally for any kind of data slicing where the match is based on a simple ID value. Note that this slicer uses the fieldID ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OpsimFieldSlicer:
"""Index-based slicer, matched ID's between simData and fieldData. Slicer uses fieldData RA and Dec values to do sky map plotting, but could be used more generally for any kind of data slicing where the match is based on a simple ID value. Note that this slicer uses the fieldID of the opsim ... | the_stack_v2_python_sparse | python/lsst/sims/maf/slicers/opsimFieldSlicer.py | nanchenchen/sims_maf | train | 0 |
bf52cdb366bf2827c2168f9a33a80c59443be497 | [
"super().__init__()\nself._momentum = momentum\nself._eps = eps",
"self.running_mean = self.add_weight(name='running_mean', shape=input_shape[1:], dtype=tf.float32, initializer=tf.keras.initializers.Zeros(), trainable=False)\nself.running_var = self.add_weight(name='running_var', shape=input_shape[1:], dtype=tf.f... | <|body_start_0|>
super().__init__()
self._momentum = momentum
self._eps = eps
<|end_body_0|>
<|body_start_1|>
self.running_mean = self.add_weight(name='running_mean', shape=input_shape[1:], dtype=tf.float32, initializer=tf.keras.initializers.Zeros(), trainable=False)
self.runnin... | Revertible batch normalization. Attributes: _momentum: _eps: | BatchNorm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchNorm:
"""Revertible batch normalization. Attributes: _momentum: _eps:"""
def __init__(self, momentum=0.9, eps=1e-05):
"""Initializes the object. Args: momentum: eps:"""
<|body_0|>
def build(self, input_shape):
"""Adds variables to the layer. Args: input_shap... | stack_v2_sparse_classes_36k_train_027819 | 12,897 | no_license | [
{
"docstring": "Initializes the object. Args: momentum: eps:",
"name": "__init__",
"signature": "def __init__(self, momentum=0.9, eps=1e-05)"
},
{
"docstring": "Adds variables to the layer. Args: input_shape: Returns:",
"name": "build",
"signature": "def build(self, input_shape)"
},
... | 3 | stack_v2_sparse_classes_30k_train_003448 | Implement the Python class `BatchNorm` described below.
Class description:
Revertible batch normalization. Attributes: _momentum: _eps:
Method signatures and docstrings:
- def __init__(self, momentum=0.9, eps=1e-05): Initializes the object. Args: momentum: eps:
- def build(self, input_shape): Adds variables to the la... | Implement the Python class `BatchNorm` described below.
Class description:
Revertible batch normalization. Attributes: _momentum: _eps:
Method signatures and docstrings:
- def __init__(self, momentum=0.9, eps=1e-05): Initializes the object. Args: momentum: eps:
- def build(self, input_shape): Adds variables to the la... | 6d04861ef87ba2ba2a4182ad36f3b322fcf47cfa | <|skeleton|>
class BatchNorm:
"""Revertible batch normalization. Attributes: _momentum: _eps:"""
def __init__(self, momentum=0.9, eps=1e-05):
"""Initializes the object. Args: momentum: eps:"""
<|body_0|>
def build(self, input_shape):
"""Adds variables to the layer. Args: input_shap... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BatchNorm:
"""Revertible batch normalization. Attributes: _momentum: _eps:"""
def __init__(self, momentum=0.9, eps=1e-05):
"""Initializes the object. Args: momentum: eps:"""
super().__init__()
self._momentum = momentum
self._eps = eps
def build(self, input_shape):
... | the_stack_v2_python_sparse | flow.py | gaotianxiang/text-to-image-synthesis | train | 0 |
79a4d20bbab4094e5bafae11d9cdb248e8195e24 | [
"try:\n matching_host = next((host for host, ref in self.__hosts.items() if platform_name in ref['platforms']))\n return matching_host\nexcept StopIteration:\n raise ConfigurationError('Unconfigured platform_name in RegionalRiotapiHosts()') from None",
"try:\n matching_host = next((host for host, ref ... | <|body_start_0|>
try:
matching_host = next((host for host, ref in self.__hosts.items() if platform_name in ref['platforms']))
return matching_host
except StopIteration:
raise ConfigurationError('Unconfigured platform_name in RegionalRiotapiHosts()') from None
<|end_bo... | Region <=references=> Platform <=references=> Host; Platforms are multiple for NA1/NA | RegionalRiotapiHosts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegionalRiotapiHosts:
"""Region <=references=> Platform <=references=> Host; Platforms are multiple for NA1/NA"""
def get_host_by_platform(self, platform_name):
"""This could be one-liner (using next's default argument), but more explicit using StopIteration instead"""
<|body... | stack_v2_sparse_classes_36k_train_027820 | 3,007 | no_license | [
{
"docstring": "This could be one-liner (using next's default argument), but more explicit using StopIteration instead",
"name": "get_host_by_platform",
"signature": "def get_host_by_platform(self, platform_name)"
},
{
"docstring": "This could be one-liner (using next's default argument), but mo... | 4 | stack_v2_sparse_classes_30k_train_008114 | Implement the Python class `RegionalRiotapiHosts` described below.
Class description:
Region <=references=> Platform <=references=> Host; Platforms are multiple for NA1/NA
Method signatures and docstrings:
- def get_host_by_platform(self, platform_name): This could be one-liner (using next's default argument), but mo... | Implement the Python class `RegionalRiotapiHosts` described below.
Class description:
Region <=references=> Platform <=references=> Host; Platforms are multiple for NA1/NA
Method signatures and docstrings:
- def get_host_by_platform(self, platform_name): This could be one-liner (using next's default argument), but mo... | 267fa63991e7d7b510e0c13e6a1d5005e79f560a | <|skeleton|>
class RegionalRiotapiHosts:
"""Region <=references=> Platform <=references=> Host; Platforms are multiple for NA1/NA"""
def get_host_by_platform(self, platform_name):
"""This could be one-liner (using next's default argument), but more explicit using StopIteration instead"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegionalRiotapiHosts:
"""Region <=references=> Platform <=references=> Host; Platforms are multiple for NA1/NA"""
def get_host_by_platform(self, platform_name):
"""This could be one-liner (using next's default argument), but more explicit using StopIteration instead"""
try:
ma... | the_stack_v2_python_sparse | dj_lol_dcs/lolapi/app_lib/regional_riotapi_hosts.py | Mew-www/lol-data-collection-system | train | 2 |
de2f29a2de5eafcafa9f37574a0190371524b568 | [
"super().__init__(data, device)\nself._data = data\nself._device = device\nself._operated_remote = None\nself._operated_keypad = None\nself._operated_autorelock = None\nself._operated_time = None\nself._attr_unique_id = f'{self._device_id}_lock_operator'\nself._update_from_data()",
"lock_activity = self._data.act... | <|body_start_0|>
super().__init__(data, device)
self._data = data
self._device = device
self._operated_remote = None
self._operated_keypad = None
self._operated_autorelock = None
self._operated_time = None
self._attr_unique_id = f'{self._device_id}_lock_op... | Representation of an August lock operation sensor. | AugustOperatorSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AugustOperatorSensor:
"""Representation of an August lock operation sensor."""
def __init__(self, data, device):
"""Initialize the sensor."""
<|body_0|>
def _update_from_data(self):
"""Get the latest state of the sensor and update activity."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_027821 | 9,526 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, data, device)"
},
{
"docstring": "Get the latest state of the sensor and update activity.",
"name": "_update_from_data",
"signature": "def _update_from_data(self)"
},
{
"docstring": "Ret... | 4 | null | Implement the Python class `AugustOperatorSensor` described below.
Class description:
Representation of an August lock operation sensor.
Method signatures and docstrings:
- def __init__(self, data, device): Initialize the sensor.
- def _update_from_data(self): Get the latest state of the sensor and update activity.
-... | Implement the Python class `AugustOperatorSensor` described below.
Class description:
Representation of an August lock operation sensor.
Method signatures and docstrings:
- def __init__(self, data, device): Initialize the sensor.
- def _update_from_data(self): Get the latest state of the sensor and update activity.
-... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AugustOperatorSensor:
"""Representation of an August lock operation sensor."""
def __init__(self, data, device):
"""Initialize the sensor."""
<|body_0|>
def _update_from_data(self):
"""Get the latest state of the sensor and update activity."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AugustOperatorSensor:
"""Representation of an August lock operation sensor."""
def __init__(self, data, device):
"""Initialize the sensor."""
super().__init__(data, device)
self._data = data
self._device = device
self._operated_remote = None
self._operated_... | the_stack_v2_python_sparse | homeassistant/components/august/sensor.py | home-assistant/core | train | 35,501 |
392be3f3af0ae3f2a7a7bf2092f9d89359db73d1 | [
"self.name = 'Binary KDE'\nself.pos_class = pos_class\nself.train_together(X, y)",
"bandwidths = np.linspace(0.0001, 1, 100)\nkernels = ['exponential', 'gaussian']\nbest_loss, best_bw, best_kernel = find_best_params(X, y, bandwidths, kernels)\nprint('\\n' + self.pos_class + ' best bandwidth: ' + str(best_bw) + ' ... | <|body_start_0|>
self.name = 'Binary KDE'
self.pos_class = pos_class
self.train_together(X, y)
<|end_body_0|>
<|body_start_1|>
bandwidths = np.linspace(0.0001, 1, 100)
kernels = ['exponential', 'gaussian']
best_loss, best_bw, best_kernel = find_best_params(X, y, bandwidt... | Multivariate KDE classifier | KDEClassifier | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KDEClassifier:
"""Multivariate KDE classifier"""
def __init__(self, X, y, pos_class, model_dir):
"""Init classifier through training :param X: DataFrame of training data features :param y: DataFrame of TARGET_LABEL with 1 for pos_class and 0 for not pos_class :param pos_class: Name o... | stack_v2_sparse_classes_36k_train_027822 | 7,053 | permissive | [
{
"docstring": "Init classifier through training :param X: DataFrame of training data features :param y: DataFrame of TARGET_LABEL with 1 for pos_class and 0 for not pos_class :param pos_class: Name of positive class :param model_dir: Model directory to save output to",
"name": "__init__",
"signature": ... | 4 | stack_v2_sparse_classes_30k_train_017028 | Implement the Python class `KDEClassifier` described below.
Class description:
Multivariate KDE classifier
Method signatures and docstrings:
- def __init__(self, X, y, pos_class, model_dir): Init classifier through training :param X: DataFrame of training data features :param y: DataFrame of TARGET_LABEL with 1 for p... | Implement the Python class `KDEClassifier` described below.
Class description:
Multivariate KDE classifier
Method signatures and docstrings:
- def __init__(self, X, y, pos_class, model_dir): Init classifier through training :param X: DataFrame of training data features :param y: DataFrame of TARGET_LABEL with 1 for p... | 9d498b697b7c4b03e1db31cae4d7a469311229f7 | <|skeleton|>
class KDEClassifier:
"""Multivariate KDE classifier"""
def __init__(self, X, y, pos_class, model_dir):
"""Init classifier through training :param X: DataFrame of training data features :param y: DataFrame of TARGET_LABEL with 1 for pos_class and 0 for not pos_class :param pos_class: Name o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KDEClassifier:
"""Multivariate KDE classifier"""
def __init__(self, X, y, pos_class, model_dir):
"""Init classifier through training :param X: DataFrame of training data features :param y: DataFrame of TARGET_LABEL with 1 for pos_class and 0 for not pos_class :param pos_class: Name of positive cl... | the_stack_v2_python_sparse | classifiers/binary/kdeclassifier.py | marinakiseleva/thex_model | train | 4 |
bcd5d58a4b1789a205e03f69fe2458b9b4a5b5a2 | [
"while m > 0 and n > 0:\n if nums1[m - 1] > nums2[n - 1]:\n nums1[m + n - 1] = nums1[m - 1]\n m -= 1\n else:\n nums1[m + n - 1] = nums2[n - 1]\n n -= 1\nif m == 0:\n nums1[:n] = nums2[:n]\n nums1[m:] = nums2[j:]",
"i = 0\nj = 0\nwhile j < n:\n while i < m and nums1[i] <=... | <|body_start_0|>
while m > 0 and n > 0:
if nums1[m - 1] > nums2[n - 1]:
nums1[m + n - 1] = nums1[m - 1]
m -= 1
else:
nums1[m + n - 1] = nums2[n - 1]
n -= 1
if m == 0:
nums1[:n] = nums2[:n]
num... | Do not return anything, modify nums1 in-place instead. | Solution | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Do not return anything, modify nums1 in-place instead."""
def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge1(self, nums1, m, nums2, n):
"""Tw... | stack_v2_sparse_classes_36k_train_027823 | 2,069 | permissive | [
{
"docstring": "Do not return anything, modify nums1 in-place instead.",
"name": "merge",
"signature": "def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None"
},
{
"docstring": "Two Pointers",
"name": "merge1",
"signature": "def merge1(self, nums1, m, nums2, n)"
}... | 3 | stack_v2_sparse_classes_30k_train_012375 | Implement the Python class `Solution` described below.
Class description:
Do not return anything, modify nums1 in-place instead.
Method signatures and docstrings:
- def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None: Do not return anything, modify nums1 in-place instead.
- def merge1(self, nu... | Implement the Python class `Solution` described below.
Class description:
Do not return anything, modify nums1 in-place instead.
Method signatures and docstrings:
- def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None: Do not return anything, modify nums1 in-place instead.
- def merge1(self, nu... | 49a0b03c55d8a702785888d473ef96539265ce9c | <|skeleton|>
class Solution:
"""Do not return anything, modify nums1 in-place instead."""
def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge1(self, nums1, m, nums2, n):
"""Tw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Do not return anything, modify nums1 in-place instead."""
def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""Do not return anything, modify nums1 in-place instead."""
while m > 0 and n > 0:
if nums1[m - 1] > nums2[n - 1]:
... | the_stack_v2_python_sparse | leetcode/0088_merge_sorted_array.py | chaosWsF/Python-Practice | train | 1 |
e0758aee29a3830dc4e7c64f7506a8a18b68bafe | [
"super().__init__(args)\nself.matmul_shapes = [[128, 128, 12288]]\nself.split_k_slices = [2, 4, 16, 18]\nself.dispatches_collection_list = []",
"for matmul_shape in matmul_shapes:\n for split_k_slice in split_k_slices:\n operation = MatmulOperation(matmul_shape, TensorDescription(data_type[0], LayoutTyp... | <|body_start_0|>
super().__init__(args)
self.matmul_shapes = [[128, 128, 12288]]
self.split_k_slices = [2, 4, 16, 18]
self.dispatches_collection_list = []
<|end_body_0|>
<|body_start_1|>
for matmul_shape in matmul_shapes:
for split_k_slice in split_k_slices:
... | SplitK Matmul dispatch generator class. | CudaSplitKMatmulGenerator | [
"Apache-2.0",
"LLVM-exception",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CudaSplitKMatmulGenerator:
"""SplitK Matmul dispatch generator class."""
def __init__(self, args):
"""Initializes the splitK matmul generator."""
<|body_0|>
def _append_matmul_dispatch_collection(self, matmul_shapes, split_k_slices, data_type, configuration_list):
... | stack_v2_sparse_classes_36k_train_027824 | 3,866 | permissive | [
{
"docstring": "Initializes the splitK matmul generator.",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "Appends the split-k matmul dispatches collection with the given configuration list.",
"name": "_append_matmul_dispatch_collection",
"signature": "def ... | 5 | stack_v2_sparse_classes_30k_test_000513 | Implement the Python class `CudaSplitKMatmulGenerator` described below.
Class description:
SplitK Matmul dispatch generator class.
Method signatures and docstrings:
- def __init__(self, args): Initializes the splitK matmul generator.
- def _append_matmul_dispatch_collection(self, matmul_shapes, split_k_slices, data_t... | Implement the Python class `CudaSplitKMatmulGenerator` described below.
Class description:
SplitK Matmul dispatch generator class.
Method signatures and docstrings:
- def __init__(self, args): Initializes the splitK matmul generator.
- def _append_matmul_dispatch_collection(self, matmul_shapes, split_k_slices, data_t... | 13ef677e556d0a1d154e45b052fe016256057f65 | <|skeleton|>
class CudaSplitKMatmulGenerator:
"""SplitK Matmul dispatch generator class."""
def __init__(self, args):
"""Initializes the splitK matmul generator."""
<|body_0|>
def _append_matmul_dispatch_collection(self, matmul_shapes, split_k_slices, data_type, configuration_list):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CudaSplitKMatmulGenerator:
"""SplitK Matmul dispatch generator class."""
def __init__(self, args):
"""Initializes the splitK matmul generator."""
super().__init__(args)
self.matmul_shapes = [[128, 128, 12288]]
self.split_k_slices = [2, 4, 16, 18]
self.dispatches_co... | the_stack_v2_python_sparse | experimental/dispatch_profiler/split_k_matmul.py | openxla/iree | train | 387 |
d307fa01b0eae33736e7d9a5bddb91e2caf3c17f | [
"self.filename = filename\nself.temp_directory = Path('unzipped-{}'.format(self.filename))\nself.user_input1 = x\nself.user_input2 = y",
"print(self.temp_directory)\nprint(self.temp_directory.iterdir)\nfor filename in self.temp_directory.iterdir():\n if filename.name == '__MACOSX':\n continue\n im = ... | <|body_start_0|>
self.filename = filename
self.temp_directory = Path('unzipped-{}'.format(self.filename))
self.user_input1 = x
self.user_input2 = y
<|end_body_0|>
<|body_start_1|>
print(self.temp_directory)
print(self.temp_directory.iterdir)
for filename in self.... | ScaleZip | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScaleZip:
def __init__(self, filename, x, y):
"""Initiate parameters :param filename: archieve"""
<|body_0|>
def process(self):
"""Scale each image in the directory to 640x480"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.filename = filename
... | stack_v2_sparse_classes_36k_train_027825 | 2,295 | no_license | [
{
"docstring": "Initiate parameters :param filename: archieve",
"name": "__init__",
"signature": "def __init__(self, filename, x, y)"
},
{
"docstring": "Scale each image in the directory to 640x480",
"name": "process",
"signature": "def process(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004586 | Implement the Python class `ScaleZip` described below.
Class description:
Implement the ScaleZip class.
Method signatures and docstrings:
- def __init__(self, filename, x, y): Initiate parameters :param filename: archieve
- def process(self): Scale each image in the directory to 640x480 | Implement the Python class `ScaleZip` described below.
Class description:
Implement the ScaleZip class.
Method signatures and docstrings:
- def __init__(self, filename, x, y): Initiate parameters :param filename: archieve
- def process(self): Scale each image in the directory to 640x480
<|skeleton|>
class ScaleZip:
... | 9837a5a738a2b9ddcd2d9dcf2f069f89dc410bbd | <|skeleton|>
class ScaleZip:
def __init__(self, filename, x, y):
"""Initiate parameters :param filename: archieve"""
<|body_0|>
def process(self):
"""Scale each image in the directory to 640x480"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScaleZip:
def __init__(self, filename, x, y):
"""Initiate parameters :param filename: archieve"""
self.filename = filename
self.temp_directory = Path('unzipped-{}'.format(self.filename))
self.user_input1 = x
self.user_input2 = y
def process(self):
"""Scale ... | the_stack_v2_python_sparse | 3_Абстрактні класи. Керування атрибутами. Методи класу та статичні методи/task1/scale_zip.py | sophiashuv/UCU_labs_2term | train | 0 | |
51ef5aef183d3d9518cb0325c7b68ee765aac927 | [
"self.treeName = 'SixJetTreeProducer'\nself.selComps = selComps\nself.varName = varName\nself.cut = cut\nself.bins = bins\nself.xmin = xmin\nself.xmax = xmax\nsuper(StackPlot, self).__init__(varName, directory, weights)\nself.legendBorders = (0.651, 0.463, 0.895, 0.892)",
"if not hasattr(comp, 'tree'):\n comp.... | <|body_start_0|>
self.treeName = 'SixJetTreeProducer'
self.selComps = selComps
self.varName = varName
self.cut = cut
self.bins = bins
self.xmin = xmin
self.xmax = xmax
super(StackPlot, self).__init__(varName, directory, weights)
self.legendBorders ... | StackPlot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StackPlot:
def __init__(self, varName, directory, selComps, weights, bins=None, xmin=None, xmax=None, cut=''):
"""Data/MC plotter adapted to the LEP3 analysis. The plotter takes a collection of trees in input. The trees are found according to the dictionary of selected components selComp... | stack_v2_sparse_classes_36k_train_027826 | 4,059 | no_license | [
{
"docstring": "Data/MC plotter adapted to the LEP3 analysis. The plotter takes a collection of trees in input. The trees are found according to the dictionary of selected components selComps. The global weighting information for each component is read from the weights dictionary.",
"name": "__init__",
... | 4 | stack_v2_sparse_classes_30k_val_000345 | Implement the Python class `StackPlot` described below.
Class description:
Implement the StackPlot class.
Method signatures and docstrings:
- def __init__(self, varName, directory, selComps, weights, bins=None, xmin=None, xmax=None, cut=''): Data/MC plotter adapted to the LEP3 analysis. The plotter takes a collection... | Implement the Python class `StackPlot` described below.
Class description:
Implement the StackPlot class.
Method signatures and docstrings:
- def __init__(self, varName, directory, selComps, weights, bins=None, xmin=None, xmax=None, cut=''): Data/MC plotter adapted to the LEP3 analysis. The plotter takes a collection... | 7bec46d27e491397c4e13a52b34cf414a692d867 | <|skeleton|>
class StackPlot:
def __init__(self, varName, directory, selComps, weights, bins=None, xmin=None, xmax=None, cut=''):
"""Data/MC plotter adapted to the LEP3 analysis. The plotter takes a collection of trees in input. The trees are found according to the dictionary of selected components selComp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StackPlot:
def __init__(self, varName, directory, selComps, weights, bins=None, xmin=None, xmax=None, cut=''):
"""Data/MC plotter adapted to the LEP3 analysis. The plotter takes a collection of trees in input. The trees are found according to the dictionary of selected components selComps. The global ... | the_stack_v2_python_sparse | CMGTools/LEP3/python/plotter/StackPlot.py | HemantAHK/CMG | train | 0 | |
64e25d923b0cb98d7949b97099008f1e7cc7dbd2 | [
"b1, b2 = parse(filename)\nb2 = np.array(b2, dtype=np.int16)\nb2 = np.pad(b2, (4, 4), 'constant', constant_values=(0, 0))\nb2 = enhance(b1, b2)\nb2 = enhance(b1, b2)\nreturn np.count_nonzero(b2)",
"data = parse(filename)\nb1, b2 = parse(filename)\nb2 = np.array(b2, dtype=np.int16)\nb2 = np.pad(b2, (3, 3), 'consta... | <|body_start_0|>
b1, b2 = parse(filename)
b2 = np.array(b2, dtype=np.int16)
b2 = np.pad(b2, (4, 4), 'constant', constant_values=(0, 0))
b2 = enhance(b1, b2)
b2 = enhance(b1, b2)
return np.count_nonzero(b2)
<|end_body_0|>
<|body_start_1|>
data = parse(filename)
... | AoC 2021 Day 20 | Day20 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Day20:
"""AoC 2021 Day 20"""
def part1(filename: str) -> int:
"""Given a filename, solve 2021 day 20 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2021 day 20 part 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_027827 | 1,992 | no_license | [
{
"docstring": "Given a filename, solve 2021 day 20 part 1",
"name": "part1",
"signature": "def part1(filename: str) -> int"
},
{
"docstring": "Given a filename, solve 2021 day 20 part 2",
"name": "part2",
"signature": "def part2(filename: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_018768 | Implement the Python class `Day20` described below.
Class description:
AoC 2021 Day 20
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2021 day 20 part 1
- def part2(filename: str) -> int: Given a filename, solve 2021 day 20 part 2 | Implement the Python class `Day20` described below.
Class description:
AoC 2021 Day 20
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2021 day 20 part 1
- def part2(filename: str) -> int: Given a filename, solve 2021 day 20 part 2
<|skeleton|>
class Day20:
"""AoC 202... | e89db235837d2d05848210a18c9c2a4456085570 | <|skeleton|>
class Day20:
"""AoC 2021 Day 20"""
def part1(filename: str) -> int:
"""Given a filename, solve 2021 day 20 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2021 day 20 part 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Day20:
"""AoC 2021 Day 20"""
def part1(filename: str) -> int:
"""Given a filename, solve 2021 day 20 part 1"""
b1, b2 = parse(filename)
b2 = np.array(b2, dtype=np.int16)
b2 = np.pad(b2, (4, 4), 'constant', constant_values=(0, 0))
b2 = enhance(b1, b2)
b2 = e... | the_stack_v2_python_sparse | 2021/python2021/aoc/day20.py | mreishus/aoc | train | 16 |
bd05a8664b0fb26fd41702c0f3fffe653052aa0c | [
"maxi, maxj = (0, 0)\nmax_len = 0\nfor i in range(0, len(s)):\n if len(s) - i <= max_len:\n break\n for j in range(len(s) - 1, i, -1):\n if j - i + 1 <= max_len:\n break\n if s[i] == s[j]:\n k = 1\n while i + k < j - k and s[i + k] == s[j - k]:\n ... | <|body_start_0|>
maxi, maxj = (0, 0)
max_len = 0
for i in range(0, len(s)):
if len(s) - i <= max_len:
break
for j in range(len(s) - 1, i, -1):
if j - i + 1 <= max_len:
break
if s[i] == s[j]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome1(self, s):
""":type s: str :rtype: str"""
<|body_1|>
def longestPalindrome2(self, s):
""":type s: str :rtype: str"""
<|body_2|>
<|e... | stack_v2_sparse_classes_36k_train_027828 | 3,382 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome1",
"signature": "def longestPalindrome1(self, s)"
},
{
"docstring": ":type s: str :rtype:... | 3 | null | 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: str
- def longestPalindrome1(self, s): :type s: str :rtype: str
- def longestPalindrome2(self, s): :type s: str :rtype: str | 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: str
- def longestPalindrome1(self, s): :type s: str :rtype: str
- def longestPalindrome2(self, s): :type s: str :rtype: str
... | 22f208400cd7e13fcf2ebf189e61ccad7e22b098 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome1(self, s):
""":type s: str :rtype: str"""
<|body_1|>
def longestPalindrome2(self, s):
""":type s: str :rtype: str"""
<|body_2|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
maxi, maxj = (0, 0)
max_len = 0
for i in range(0, len(s)):
if len(s) - i <= max_len:
break
for j in range(len(s) - 1, i, -1):
if j - i + 1 <= max_len... | the_stack_v2_python_sparse | previously_completed/1-30/5-longestPalindrome.py | learnerjiahao/leetcode-solve | train | 0 | |
520c85458badb9b29eaba638f48d4e2ec304597f | [
"row = len(matrix)\ncol = len(matrix[0])\nrow_zero = set()\ncol_zero = set()\nfor i in range(row):\n for j in range(col):\n if matrix[i][j] == 0:\n row_zero.add(i)\n col_zero.add(j)\nfor i in range(row):\n for j in range(col):\n if i in row_zero or j in col_zero:\n ... | <|body_start_0|>
row = len(matrix)
col = len(matrix[0])
row_zero = set()
col_zero = set()
for i in range(row):
for j in range(col):
if matrix[i][j] == 0:
row_zero.add(i)
col_zero.add(j)
for i in range(row... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def setZeroes(self, matrix):
""":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-place instead. O(m+n)额外空间"""
<|body_0|>
def setZeroes1(self, matrix):
""":type matrix: List[List[int]] :rtype: None Do not return anything, m... | stack_v2_sparse_classes_36k_train_027829 | 1,551 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-place instead. O(m+n)额外空间",
"name": "setZeroes",
"signature": "def setZeroes(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-p... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def setZeroes(self, matrix): :type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-place instead. O(m+n)额外空间
- def setZeroes1(self, matrix): :type m... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def setZeroes(self, matrix): :type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-place instead. O(m+n)额外空间
- def setZeroes1(self, matrix): :type m... | 3f4284330f9771037ca59e2e6a94122e51e58540 | <|skeleton|>
class Solution:
def setZeroes(self, matrix):
""":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-place instead. O(m+n)额外空间"""
<|body_0|>
def setZeroes1(self, matrix):
""":type matrix: List[List[int]] :rtype: None Do not return anything, m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def setZeroes(self, matrix):
""":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-place instead. O(m+n)额外空间"""
row = len(matrix)
col = len(matrix[0])
row_zero = set()
col_zero = set()
for i in range(row):
f... | the_stack_v2_python_sparse | Leetcode/73.矩阵置零.py | myf-algorithm/Leetcode | train | 1 | |
485eae12827f3fa0ece146d1f76146250bb47904 | [
"if not HomepageSysApi._api:\n HomepageSysApi._api = HomepageSysApi()\nreturn HomepageSysApi._api",
"r = self.career_category_service.get_all_career_category()\nif len(r) > 4:\n r = r[:4]\nr = self.n_obj('CareerCategory', r)\n\ndef _worker(cc):\n cs = self.career_category_service.get_distinct_related_cou... | <|body_start_0|>
if not HomepageSysApi._api:
HomepageSysApi._api = HomepageSysApi()
return HomepageSysApi._api
<|end_body_0|>
<|body_start_1|>
r = self.career_category_service.get_all_career_category()
if len(r) > 4:
r = r[:4]
r = self.n_obj('CareerCatego... | HomepageSysApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HomepageSysApi:
def default_instance():
"""@brief 默认api对象"""
<|body_0|>
def get_homepage_all_hot_course(self):
"""@brief 主页推荐热门课程 @return [(CareerCategory， [Course])]."""
<|body_1|>
def get_home_page_article(self):
"""@brief 主页推荐热门文章 @return [(Ar... | stack_v2_sparse_classes_36k_train_027830 | 1,726 | no_license | [
{
"docstring": "@brief 默认api对象",
"name": "default_instance",
"signature": "def default_instance()"
},
{
"docstring": "@brief 主页推荐热门课程 @return [(CareerCategory， [Course])].",
"name": "get_homepage_all_hot_course",
"signature": "def get_homepage_all_hot_course(self)"
},
{
"docstrin... | 3 | null | Implement the Python class `HomepageSysApi` described below.
Class description:
Implement the HomepageSysApi class.
Method signatures and docstrings:
- def default_instance(): @brief 默认api对象
- def get_homepage_all_hot_course(self): @brief 主页推荐热门课程 @return [(CareerCategory， [Course])].
- def get_home_page_article(self... | Implement the Python class `HomepageSysApi` described below.
Class description:
Implement the HomepageSysApi class.
Method signatures and docstrings:
- def default_instance(): @brief 默认api对象
- def get_homepage_all_hot_course(self): @brief 主页推荐热门课程 @return [(CareerCategory， [Course])].
- def get_home_page_article(self... | aec5d23bb412f7dfca374fb5c5b9988c1b817347 | <|skeleton|>
class HomepageSysApi:
def default_instance():
"""@brief 默认api对象"""
<|body_0|>
def get_homepage_all_hot_course(self):
"""@brief 主页推荐热门课程 @return [(CareerCategory， [Course])]."""
<|body_1|>
def get_home_page_article(self):
"""@brief 主页推荐热门文章 @return [(Ar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HomepageSysApi:
def default_instance():
"""@brief 默认api对象"""
if not HomepageSysApi._api:
HomepageSysApi._api = HomepageSysApi()
return HomepageSysApi._api
def get_homepage_all_hot_course(self):
"""@brief 主页推荐热门课程 @return [(CareerCategory， [Course])]."""
... | the_stack_v2_python_sparse | hotfix/mz_platform/apis/homepage_sys_api.py | az0ne/python | train | 0 | |
147b063c1a0b2bc61f60d961c3ebc509fbb3dc64 | [
"comp = protprop.Composition()\npp = protprop.ProteinProperties()\naa_classes = ['FY', 'P', 'NQ']\nfor xi in range(5):\n seq = genMotif(aa_classes, [(0, 2), (1, 1), (2, 2), (0, 2), (1, 1), (2, 2)])\n self.assertTrue(pp.count(seq, 'FY') == 4)\n mot = pp.motif(seq, aa_classes)\n self.assertTrue(mot == 'aa... | <|body_start_0|>
comp = protprop.Composition()
pp = protprop.ProteinProperties()
aa_classes = ['FY', 'P', 'NQ']
for xi in range(5):
seq = genMotif(aa_classes, [(0, 2), (1, 1), (2, 2), (0, 2), (1, 1), (2, 2)])
self.assertTrue(pp.count(seq, 'FY') == 4)
m... | test003 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test003:
def test_run(self):
"""Composition and motifs"""
<|body_0|>
def test_run_skip(self):
"""Composition and motifs with skips"""
<|body_1|>
def test_comp_counts(self):
"""Composition and motifs with skips"""
<|body_2|>
def test_... | stack_v2_sparse_classes_36k_train_027831 | 4,558 | no_license | [
{
"docstring": "Composition and motifs",
"name": "test_run",
"signature": "def test_run(self)"
},
{
"docstring": "Composition and motifs with skips",
"name": "test_run_skip",
"signature": "def test_run_skip(self)"
},
{
"docstring": "Composition and motifs with skips",
"name":... | 6 | stack_v2_sparse_classes_30k_val_000164 | Implement the Python class `test003` described below.
Class description:
Implement the test003 class.
Method signatures and docstrings:
- def test_run(self): Composition and motifs
- def test_run_skip(self): Composition and motifs with skips
- def test_comp_counts(self): Composition and motifs with skips
- def test_n... | Implement the Python class `test003` described below.
Class description:
Implement the test003 class.
Method signatures and docstrings:
- def test_run(self): Composition and motifs
- def test_run_skip(self): Composition and motifs with skips
- def test_comp_counts(self): Composition and motifs with skips
- def test_n... | d7ddd2b585a841c6d986974a24a53e4d1abe71ba | <|skeleton|>
class test003:
def test_run(self):
"""Composition and motifs"""
<|body_0|>
def test_run_skip(self):
"""Composition and motifs with skips"""
<|body_1|>
def test_comp_counts(self):
"""Composition and motifs with skips"""
<|body_2|>
def test_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test003:
def test_run(self):
"""Composition and motifs"""
comp = protprop.Composition()
pp = protprop.ProteinProperties()
aa_classes = ['FY', 'P', 'NQ']
for xi in range(5):
seq = genMotif(aa_classes, [(0, 2), (1, 1), (2, 2), (0, 2), (1, 1), (2, 2)])
... | the_stack_v2_python_sparse | src/protprop_test.py | dad/base | train | 0 | |
9c0c3b64e469c154e4385b71e27e8bd3a22eebf6 | [
"query = {'uuid': metadata_id}\nprojection = {'_id': False}\nlogging.debug(f'MONGO-START: db.Metadata.find_one(filter={query}, projection={projection})')\nret = await self.db.Metadata.find_one(filter=query, projection=projection)\nlogging.debug('MONGO-END: db.Metadata.find_one(filter, projection)')\nif not ret:\n... | <|body_start_0|>
query = {'uuid': metadata_id}
projection = {'_id': False}
logging.debug(f'MONGO-START: db.Metadata.find_one(filter={query}, projection={projection})')
ret = await self.db.Metadata.find_one(filter=query, projection=projection)
logging.debug('MONGO-END: db.Metada... | MetadataSingleHandler handles object level routes for Metadata. | MetadataSingleHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetadataSingleHandler:
"""MetadataSingleHandler handles object level routes for Metadata."""
async def get(self, metadata_id: str) -> None:
"""Handle GET /Metadata/{uuid}."""
<|body_0|>
async def delete(self, metadata_id: str) -> None:
"""Handle DELETE /Metadata/... | stack_v2_sparse_classes_36k_train_027832 | 42,572 | permissive | [
{
"docstring": "Handle GET /Metadata/{uuid}.",
"name": "get",
"signature": "async def get(self, metadata_id: str) -> None"
},
{
"docstring": "Handle DELETE /Metadata/{uuid}.",
"name": "delete",
"signature": "async def delete(self, metadata_id: str) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_009323 | Implement the Python class `MetadataSingleHandler` described below.
Class description:
MetadataSingleHandler handles object level routes for Metadata.
Method signatures and docstrings:
- async def get(self, metadata_id: str) -> None: Handle GET /Metadata/{uuid}.
- async def delete(self, metadata_id: str) -> None: Han... | Implement the Python class `MetadataSingleHandler` described below.
Class description:
MetadataSingleHandler handles object level routes for Metadata.
Method signatures and docstrings:
- async def get(self, metadata_id: str) -> None: Handle GET /Metadata/{uuid}.
- async def delete(self, metadata_id: str) -> None: Han... | 12719efa84be2281debe98a18c69bbe7a6d0f399 | <|skeleton|>
class MetadataSingleHandler:
"""MetadataSingleHandler handles object level routes for Metadata."""
async def get(self, metadata_id: str) -> None:
"""Handle GET /Metadata/{uuid}."""
<|body_0|>
async def delete(self, metadata_id: str) -> None:
"""Handle DELETE /Metadata/... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetadataSingleHandler:
"""MetadataSingleHandler handles object level routes for Metadata."""
async def get(self, metadata_id: str) -> None:
"""Handle GET /Metadata/{uuid}."""
query = {'uuid': metadata_id}
projection = {'_id': False}
logging.debug(f'MONGO-START: db.Metadata... | the_stack_v2_python_sparse | lta/rest_server.py | blinkdog/lta | train | 0 |
37894ebd2417402c047a0f492707e5acb428afff | [
"from collections import Counter\nsize = len(p)\nans = []\nfor i in range(len(s) - size + 1):\n c = Counter(s[i:size + i]) - Counter(p)\n if len(list(c.elements())) == 0:\n ans.append(i)\nreturn ans",
"ans = []\nsize = len(p)\npd = {}\nfor c in p:\n if c in pd:\n pd[c] += 1\n else:\n ... | <|body_start_0|>
from collections import Counter
size = len(p)
ans = []
for i in range(len(s) - size + 1):
c = Counter(s[i:size + i]) - Counter(p)
if len(list(c.elements())) == 0:
ans.append(i)
return ans
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findAnagrams2(self, s, p):
""":type s: str :type p: str :rtype: List[int]"""
<|body_0|>
def findAnagrams(self, s, p):
""":type s: str :type p: str :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from collections impor... | stack_v2_sparse_classes_36k_train_027833 | 3,017 | no_license | [
{
"docstring": ":type s: str :type p: str :rtype: List[int]",
"name": "findAnagrams2",
"signature": "def findAnagrams2(self, s, p)"
},
{
"docstring": ":type s: str :type p: str :rtype: List[int]",
"name": "findAnagrams",
"signature": "def findAnagrams(self, s, p)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009804 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAnagrams2(self, s, p): :type s: str :type p: str :rtype: List[int]
- def findAnagrams(self, s, p): :type s: str :type p: str :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAnagrams2(self, s, p): :type s: str :type p: str :rtype: List[int]
- def findAnagrams(self, s, p): :type s: str :type p: str :rtype: List[int]
<|skeleton|>
class Solutio... | a57282895fb213b68e5d81db301903721a92d80f | <|skeleton|>
class Solution:
def findAnagrams2(self, s, p):
""":type s: str :type p: str :rtype: List[int]"""
<|body_0|>
def findAnagrams(self, s, p):
""":type s: str :type p: str :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findAnagrams2(self, s, p):
""":type s: str :type p: str :rtype: List[int]"""
from collections import Counter
size = len(p)
ans = []
for i in range(len(s) - size + 1):
c = Counter(s[i:size + i]) - Counter(p)
if len(list(c.elements())... | the_stack_v2_python_sparse | Python/438_find-all-anagrams-in-a-string.py | antonylu/leetcode2 | train | 0 | |
f50a563a8913dfdff5e01ca7db1d41c1013c046a | [
"record = dict()\ni = 0\nwhile i < len(equations):\n record[equations[i][0]] = record.get(equations[i][0], dict())\n record[equations[i][0]][equations[i][1]] = values[i]\n record[equations[i][1]] = record.get(equations[i][1], dict())\n record[equations[i][1]][equations[i][0]] = 1 / values[i]\n i += 1... | <|body_start_0|>
record = dict()
i = 0
while i < len(equations):
record[equations[i][0]] = record.get(equations[i][0], dict())
record[equations[i][0]][equations[i][1]] = values[i]
record[equations[i][1]] = record.get(equations[i][1], dict())
record... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def calcEquation(self, equations, values, queries):
""":type equations: List[List[str]] :type values: List[float] :type queries: List[List[str]] :rtype: List[float]"""
<|body_0|>
def dfs(self, record, d, b, visited):
""":param record: 图的record :param d: 前一个... | stack_v2_sparse_classes_36k_train_027834 | 5,414 | no_license | [
{
"docstring": ":type equations: List[List[str]] :type values: List[float] :type queries: List[List[str]] :rtype: List[float]",
"name": "calcEquation",
"signature": "def calcEquation(self, equations, values, queries)"
},
{
"docstring": ":param record: 图的record :param d: 前一个点的后继点集，用一个dict存储 :para... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calcEquation(self, equations, values, queries): :type equations: List[List[str]] :type values: List[float] :type queries: List[List[str]] :rtype: List[float]
- def dfs(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calcEquation(self, equations, values, queries): :type equations: List[List[str]] :type values: List[float] :type queries: List[List[str]] :rtype: List[float]
- def dfs(self, ... | 9eb44afa4233fdedc2e5c72be0fdf54b25d1c45c | <|skeleton|>
class Solution:
def calcEquation(self, equations, values, queries):
""":type equations: List[List[str]] :type values: List[float] :type queries: List[List[str]] :rtype: List[float]"""
<|body_0|>
def dfs(self, record, d, b, visited):
""":param record: 图的record :param d: 前一个... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def calcEquation(self, equations, values, queries):
""":type equations: List[List[str]] :type values: List[float] :type queries: List[List[str]] :rtype: List[float]"""
record = dict()
i = 0
while i < len(equations):
record[equations[i][0]] = record.get(equ... | the_stack_v2_python_sparse | Google/Pro399. Evaluate Division.py | YoyinZyc/Leetcode_Python | train | 0 | |
c5eb839a9dac997e981ffe034c4abcbf0b68b6db | [
"Figure.__init__(self, size=size, parent=figure)\nself._aspect = aspect\nself._fg_color = fg_color\nself._bg_color = bg_color",
"W, H = (self.parent.width, self.parent.height)\nw, h = (self._size[0] * W, self._size[1] * H)\nif self._aspect is not None:\n if w / float(h) > self._aspect:\n w = self._aspec... | <|body_start_0|>
Figure.__init__(self, size=size, parent=figure)
self._aspect = aspect
self._fg_color = fg_color
self._bg_color = bg_color
<|end_body_0|>
<|body_start_1|>
W, H = (self.parent.width, self.parent.height)
w, h = (self._size[0] * W, self._size[1] * H)
... | A Frame is a special king of figure that can drawns itself and preserves a given aspect ratio. | Frame | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Frame:
"""A Frame is a special king of figure that can drawns itself and preserves a given aspect ratio."""
def __init__(self, figure, size=(1.0, 1.0), aspect=None, fg_color=(0, 0, 0, 1), bg_color=(1, 1, 1, 1)):
"""Create a new frame within given figures. :Parameters: ``figure``: Fig... | stack_v2_sparse_classes_36k_train_027835 | 27,991 | permissive | [
{
"docstring": "Create a new frame within given figures. :Parameters: ``figure``: Figure Figure to put frame into ``size``: (float,float) Frame relative size ``aspect``: float Frame aspect ``fg_color``: 4-floats tuple Foreground color (border) ``bg_color``: 4-floats tuple Background color",
"name": "__init_... | 6 | stack_v2_sparse_classes_30k_train_007662 | Implement the Python class `Frame` described below.
Class description:
A Frame is a special king of figure that can drawns itself and preserves a given aspect ratio.
Method signatures and docstrings:
- def __init__(self, figure, size=(1.0, 1.0), aspect=None, fg_color=(0, 0, 0, 1), bg_color=(1, 1, 1, 1)): Create a new... | Implement the Python class `Frame` described below.
Class description:
A Frame is a special king of figure that can drawns itself and preserves a given aspect ratio.
Method signatures and docstrings:
- def __init__(self, figure, size=(1.0, 1.0), aspect=None, fg_color=(0, 0, 0, 1), bg_color=(1, 1, 1, 1)): Create a new... | 26100b30e3bdb800c448c2f983675a752827e827 | <|skeleton|>
class Frame:
"""A Frame is a special king of figure that can drawns itself and preserves a given aspect ratio."""
def __init__(self, figure, size=(1.0, 1.0), aspect=None, fg_color=(0, 0, 0, 1), bg_color=(1, 1, 1, 1)):
"""Create a new frame within given figures. :Parameters: ``figure``: Fig... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Frame:
"""A Frame is a special king of figure that can drawns itself and preserves a given aspect ratio."""
def __init__(self, figure, size=(1.0, 1.0), aspect=None, fg_color=(0, 0, 0, 1), bg_color=(1, 1, 1, 1)):
"""Create a new frame within given figures. :Parameters: ``figure``: Figure Figure to... | the_stack_v2_python_sparse | glumpy/figure.py | davidcox/glumpy | train | 2 |
f7480e71fa8ee1ff0e6b60d4eb1a71cd28c036cb | [
"if not root:\n return 'None'\nreturn str(root.val) + ',' + self.serialize(root.left) + ',' + self.serialize(root.right)",
"s = data.split(',')\n\ndef helper(s):\n num = s.pop(0)\n if num == 'None':\n return None\n root = TreeNode(num)\n root.left = helper(s)\n root.right = helper(s)\n ... | <|body_start_0|>
if not root:
return 'None'
return str(root.val) + ',' + self.serialize(root.left) + ',' + self.serialize(root.right)
<|end_body_0|>
<|body_start_1|>
s = data.split(',')
def helper(s):
num = s.pop(0)
if num == 'None':
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_027836 | 1,484 | 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:... | 882724c8d50b2f21193c81e5072c31385c5e6b8e | <|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"""
if not root:
return 'None'
return str(root.val) + ',' + self.serialize(root.left) + ',' + self.serialize(root.right)
def deserialize(self, data):
"""Deco... | the_stack_v2_python_sparse | 297. Serialize and Deserialize Binary Tree.py | QIAOZHIBAO0104/My-Leetcode-Records | train | 0 | |
ede75bf36d6fa477cba76131105a65ece35bc352 | [
"expression = ''\nfor date, cash in trades.items():\n td = round_to((end_date - date).days / 365, 0.001)\n expression = expression + str(cash) + '*(1 + x) **' + str(td) + '+'\nexpression = expression[:-1] + '-' + str(end_cash)\nreturn expression",
"pre_result = 0\nresult = 0\nfor as_annual_return in range(1... | <|body_start_0|>
expression = ''
for date, cash in trades.items():
td = round_to((end_date - date).days / 365, 0.001)
expression = expression + str(cash) + '*(1 + x) **' + str(td) + '+'
expression = expression[:-1] + '-' + str(end_cash)
return expression
<|end_bod... | CalReturns | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalReturns:
def cal_annual_returns(trades: {}, end_date, end_cash):
"""计算年化收益，需要交易日、金额， 截止日：金额"""
<|body_0|>
def annual_returns(trades: {}, end_date, end_cash):
"""此处只考虑正年化收益，且年化收益率到100%停止搜索 :param trades: 字典，key: date, value: cash :param end_date: 最终统计日期 :param end_... | stack_v2_sparse_classes_36k_train_027837 | 1,668 | permissive | [
{
"docstring": "计算年化收益，需要交易日、金额， 截止日：金额",
"name": "cal_annual_returns",
"signature": "def cal_annual_returns(trades: {}, end_date, end_cash)"
},
{
"docstring": "此处只考虑正年化收益，且年化收益率到100%停止搜索 :param trades: 字典，key: date, value: cash :param end_date: 最终统计日期 :param end_cash: 最终资金 :return:",
"name"... | 2 | null | Implement the Python class `CalReturns` described below.
Class description:
Implement the CalReturns class.
Method signatures and docstrings:
- def cal_annual_returns(trades: {}, end_date, end_cash): 计算年化收益，需要交易日、金额， 截止日：金额
- def annual_returns(trades: {}, end_date, end_cash): 此处只考虑正年化收益，且年化收益率到100%停止搜索 :param trades... | Implement the Python class `CalReturns` described below.
Class description:
Implement the CalReturns class.
Method signatures and docstrings:
- def cal_annual_returns(trades: {}, end_date, end_cash): 计算年化收益，需要交易日、金额， 截止日：金额
- def annual_returns(trades: {}, end_date, end_cash): 此处只考虑正年化收益，且年化收益率到100%停止搜索 :param trades... | 7901a0fb80a5b44d6fc752bd4b2b64ec62c8f84b | <|skeleton|>
class CalReturns:
def cal_annual_returns(trades: {}, end_date, end_cash):
"""计算年化收益，需要交易日、金额， 截止日：金额"""
<|body_0|>
def annual_returns(trades: {}, end_date, end_cash):
"""此处只考虑正年化收益，且年化收益率到100%停止搜索 :param trades: 字典，key: date, value: cash :param end_date: 最终统计日期 :param end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalReturns:
def cal_annual_returns(trades: {}, end_date, end_cash):
"""计算年化收益，需要交易日、金额， 截止日：金额"""
expression = ''
for date, cash in trades.items():
td = round_to((end_date - date).days / 365, 0.001)
expression = expression + str(cash) + '*(1 + x) **' + str(td) +... | the_stack_v2_python_sparse | vnpy/analyze/util/cal_returns.py | CatTiger/vnpy | train | 0 | |
184e7c2648927302e015ff0cc1b095808cbb7df7 | [
"super().__init__()\nself.original_features_num = original_features_num\nself.num_blocks = num_blocks\nself.in_features = in_features\nself.out_features = out_features\nself.depth_of_mlp = depth_of_mlp\nself.node_embedder = embedding_class(original_features_num, num_blocks, in_features, out_features, depth_of_mlp)"... | <|body_start_0|>
super().__init__()
self.original_features_num = original_features_num
self.num_blocks = num_blocks
self.in_features = in_features
self.out_features = out_features
self.depth_of_mlp = depth_of_mlp
self.node_embedder = embedding_class(original_featu... | Siamese_Model | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Siamese_Model:
def __init__(self, original_features_num, num_blocks, in_features, out_features, depth_of_mlp, embedding_class=Simple_Node_Embedding):
"""take a batch of pair of graphs ((bs, n_vertices, n_vertices, in_features) (bs,n_vertices, n_vertices, in_features)) and return a batch ... | stack_v2_sparse_classes_36k_train_027838 | 4,148 | permissive | [
{
"docstring": "take a batch of pair of graphs ((bs, n_vertices, n_vertices, in_features) (bs,n_vertices, n_vertices, in_features)) and return a batch of node similarities (bs, n_vertices, n_vertices) for each node the sum over the second dim should be one: sum(torch.exp(out[b,i,:]))==1 graphs must have same si... | 2 | stack_v2_sparse_classes_30k_train_017474 | Implement the Python class `Siamese_Model` described below.
Class description:
Implement the Siamese_Model class.
Method signatures and docstrings:
- def __init__(self, original_features_num, num_blocks, in_features, out_features, depth_of_mlp, embedding_class=Simple_Node_Embedding): take a batch of pair of graphs ((... | Implement the Python class `Siamese_Model` described below.
Class description:
Implement the Siamese_Model class.
Method signatures and docstrings:
- def __init__(self, original_features_num, num_blocks, in_features, out_features, depth_of_mlp, embedding_class=Simple_Node_Embedding): take a batch of pair of graphs ((... | 58912098b9c98bb8eeb79bab9539c5c6c3a6420b | <|skeleton|>
class Siamese_Model:
def __init__(self, original_features_num, num_blocks, in_features, out_features, depth_of_mlp, embedding_class=Simple_Node_Embedding):
"""take a batch of pair of graphs ((bs, n_vertices, n_vertices, in_features) (bs,n_vertices, n_vertices, in_features)) and return a batch ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Siamese_Model:
def __init__(self, original_features_num, num_blocks, in_features, out_features, depth_of_mlp, embedding_class=Simple_Node_Embedding):
"""take a batch of pair of graphs ((bs, n_vertices, n_vertices, in_features) (bs,n_vertices, n_vertices, in_features)) and return a batch of node simila... | the_stack_v2_python_sparse | models/siamese_net.py | mlelarge/graph_neural_net | train | 42 | |
ae0daed613857aaab835a422fa526906df3749e3 | [
"super(InputAtoms, self).store()\nself.natoms.store(atoms.natoms)\nself.q.store(dstrip(atoms.q))\nself.p.store(dstrip(atoms.p))\nself.m.store(dstrip(atoms.m))\nself.names.store(dstrip(atoms.names))",
"super(InputAtoms, self).fetch()\natoms = Atoms(self.natoms.fetch())\natoms.q = self.q.fetch()\natoms.p = self.p.f... | <|body_start_0|>
super(InputAtoms, self).store()
self.natoms.store(atoms.natoms)
self.q.store(dstrip(atoms.q))
self.p.store(dstrip(atoms.p))
self.m.store(dstrip(atoms.m))
self.names.store(dstrip(atoms.names))
<|end_body_0|>
<|body_start_1|>
super(InputAtoms, self... | Atoms input class. Handles generating the appropriate atoms class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: natoms: An optional integer giving the number of atoms. Defaults to 0. q: An optional array giving the atom positions. Defaults to an emp... | InputAtoms | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputAtoms:
"""Atoms input class. Handles generating the appropriate atoms class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: natoms: An optional integer giving the number of atoms. Defaults to 0. q: An optional array giving ... | stack_v2_sparse_classes_36k_train_027839 | 4,340 | no_license | [
{
"docstring": "Takes an Atoms instance and stores a minimal representation of it. Args: atoms: An Atoms object from which to initialise from. filename: An optional string giving a filename to take the atom positions from. Defaults to ''.",
"name": "store",
"signature": "def store(self, atoms)"
},
{... | 3 | null | Implement the Python class `InputAtoms` described below.
Class description:
Atoms input class. Handles generating the appropriate atoms class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: natoms: An optional integer giving the number of atoms. Defa... | Implement the Python class `InputAtoms` described below.
Class description:
Atoms input class. Handles generating the appropriate atoms class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: natoms: An optional integer giving the number of atoms. Defa... | 57f255266d4668bafef0881d1e7cbf8a27270ddd | <|skeleton|>
class InputAtoms:
"""Atoms input class. Handles generating the appropriate atoms class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: natoms: An optional integer giving the number of atoms. Defaults to 0. q: An optional array giving ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InputAtoms:
"""Atoms input class. Handles generating the appropriate atoms class from the xml input file, and generating the xml checkpoint tags and data from an instance of the object. Attributes: natoms: An optional integer giving the number of atoms. Defaults to 0. q: An optional array giving the atom posi... | the_stack_v2_python_sparse | ipi/inputs/atoms.py | i-pi/i-pi | train | 170 |
973415825e49ea6743413cdfa55faa94ca472001 | [
"BaseController.__init__(self, veh_id, car_following_params, delay=1.0, fail_safe='safe_velocity')\nself.v_des = v_des\nself.max_accel = car_following_params.controller_params['accel']\nself.dx_1_0 = 4.5\nself.dx_2_0 = 5.25\nself.dx_3_0 = 6.0\nself.d_1 = 1.5\nself.d_2 = 1.0\nself.d_3 = 0.5\nself.danger_edges = dang... | <|body_start_0|>
BaseController.__init__(self, veh_id, car_following_params, delay=1.0, fail_safe='safe_velocity')
self.v_des = v_des
self.max_accel = car_following_params.controller_params['accel']
self.dx_1_0 = 4.5
self.dx_2_0 = 5.25
self.dx_3_0 = 6.0
self.d_1 =... | Inspired by Dan Work's... work. Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments https://arxiv.org/abs/1705.01693 Usage ----- See base class for example. Parameters ---------- veh_id : str unique vehicle identifier v_des : float, optional desired speed of the vehicles (m/s) | FollowerStopper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FollowerStopper:
"""Inspired by Dan Work's... work. Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments https://arxiv.org/abs/1705.01693 Usage ----- See base class for example. Parameters ---------- veh_id : str unique vehicle identifier v_des : float, optional ... | stack_v2_sparse_classes_36k_train_027840 | 7,700 | permissive | [
{
"docstring": "Instantiate FollowerStopper.",
"name": "__init__",
"signature": "def __init__(self, veh_id, car_following_params, v_des=15, danger_edges=None)"
},
{
"docstring": "Find distance to intersection. Parameters ---------- env : flow.envs.Env see flow/envs/base.py Returns ------- float ... | 3 | null | Implement the Python class `FollowerStopper` described below.
Class description:
Inspired by Dan Work's... work. Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments https://arxiv.org/abs/1705.01693 Usage ----- See base class for example. Parameters ---------- veh_id : str unique vehi... | Implement the Python class `FollowerStopper` described below.
Class description:
Inspired by Dan Work's... work. Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments https://arxiv.org/abs/1705.01693 Usage ----- See base class for example. Parameters ---------- veh_id : str unique vehi... | badac3da17f04d8d8ae5691ee8ba2af9d56fac35 | <|skeleton|>
class FollowerStopper:
"""Inspired by Dan Work's... work. Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments https://arxiv.org/abs/1705.01693 Usage ----- See base class for example. Parameters ---------- veh_id : str unique vehicle identifier v_des : float, optional ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FollowerStopper:
"""Inspired by Dan Work's... work. Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments https://arxiv.org/abs/1705.01693 Usage ----- See base class for example. Parameters ---------- veh_id : str unique vehicle identifier v_des : float, optional desired speed... | the_stack_v2_python_sparse | flow/controllers/velocity_controllers.py | parthjaggi/flow | train | 6 |
989a1f4d7ee01dca0dc4a6f147342bb921b0d98b | [
"if not nums:\n return None\n' run outer loop `k` times, and not for `n` times\\n since we only need to bubble kth largest element\\n to its sorted place in the array\\n '\nfor i in range(k):\n ' for each iteration of outer loop, run inner\\n loop one less than the ... | <|body_start_0|>
if not nums:
return None
' run outer loop `k` times, and not for `n` times\n since we only need to bubble kth largest element\n to its sorted place in the array\n '
for i in range(k):
' for each iteration of outer loop, run in... | KLargestElement | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KLargestElement:
def find_bubble_sort(self, nums: List[int], k: int) -> int:
"""using bubble sort complexity : O(nk) -> outer loop `k` times, inner loop `n` times"""
<|body_0|>
def find_heap(self, nums: List[int], k: int) -> int:
"""using heap complexity : O(n + k lo... | stack_v2_sparse_classes_36k_train_027841 | 2,275 | permissive | [
{
"docstring": "using bubble sort complexity : O(nk) -> outer loop `k` times, inner loop `n` times",
"name": "find_bubble_sort",
"signature": "def find_bubble_sort(self, nums: List[int], k: int) -> int"
},
{
"docstring": "using heap complexity : O(n + k log n) -> O(n) for creating the heap -> O(... | 2 | stack_v2_sparse_classes_30k_test_000523 | Implement the Python class `KLargestElement` described below.
Class description:
Implement the KLargestElement class.
Method signatures and docstrings:
- def find_bubble_sort(self, nums: List[int], k: int) -> int: using bubble sort complexity : O(nk) -> outer loop `k` times, inner loop `n` times
- def find_heap(self,... | Implement the Python class `KLargestElement` described below.
Class description:
Implement the KLargestElement class.
Method signatures and docstrings:
- def find_bubble_sort(self, nums: List[int], k: int) -> int: using bubble sort complexity : O(nk) -> outer loop `k` times, inner loop `n` times
- def find_heap(self,... | 14356c6adb1946417482eaaf6f42dde4b8351d2f | <|skeleton|>
class KLargestElement:
def find_bubble_sort(self, nums: List[int], k: int) -> int:
"""using bubble sort complexity : O(nk) -> outer loop `k` times, inner loop `n` times"""
<|body_0|>
def find_heap(self, nums: List[int], k: int) -> int:
"""using heap complexity : O(n + k lo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KLargestElement:
def find_bubble_sort(self, nums: List[int], k: int) -> int:
"""using bubble sort complexity : O(nk) -> outer loop `k` times, inner loop `n` times"""
if not nums:
return None
' run outer loop `k` times, and not for `n` times\n since we only need t... | the_stack_v2_python_sparse | simple_array/m_kth_largest.py | dhrubach/python-code-recipes | train | 1 | |
b9d3c82cc5afd29e76b63012ce67187dff1ec233 | [
"self.copy_snapshot_tasks = copy_snapshot_tasks\nself.data_lock_constraints = data_lock_constraints\nself.error = error\nself.expiry_time_usecs = expiry_time_usecs\nself.hold_for_legal_purpose = hold_for_legal_purpose\nself.legal_holdings = legal_holdings\nself.run_start_time_usecs = run_start_time_usecs\nself.stat... | <|body_start_0|>
self.copy_snapshot_tasks = copy_snapshot_tasks
self.data_lock_constraints = data_lock_constraints
self.error = error
self.expiry_time_usecs = expiry_time_usecs
self.hold_for_legal_purpose = hold_for_legal_purpose
self.legal_holdings = legal_holdings
... | Implementation of the 'CopyRun' model. Specifies details about the Copy Run for a backup run of a Job Run. A Copy task copies snapshots resulted from a backup run to a snapshot target which could be 'kLocal', 'kArchival', or 'kRemote'. Attributes: copy_snapshot_tasks (list of CopySnapshotTaskStatus): Specifies the stat... | CopyRun | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CopyRun:
"""Implementation of the 'CopyRun' model. Specifies details about the Copy Run for a backup run of a Job Run. A Copy task copies snapshots resulted from a backup run to a snapshot target which could be 'kLocal', 'kArchival', or 'kRemote'. Attributes: copy_snapshot_tasks (list of CopySnap... | stack_v2_sparse_classes_36k_train_027842 | 7,628 | permissive | [
{
"docstring": "Constructor for the CopyRun class",
"name": "__init__",
"signature": "def __init__(self, copy_snapshot_tasks=None, data_lock_constraints=None, error=None, expiry_time_usecs=None, hold_for_legal_purpose=None, legal_holdings=None, run_start_time_usecs=None, stats=None, status=None, target=... | 2 | stack_v2_sparse_classes_30k_train_018533 | Implement the Python class `CopyRun` described below.
Class description:
Implementation of the 'CopyRun' model. Specifies details about the Copy Run for a backup run of a Job Run. A Copy task copies snapshots resulted from a backup run to a snapshot target which could be 'kLocal', 'kArchival', or 'kRemote'. Attributes... | Implement the Python class `CopyRun` described below.
Class description:
Implementation of the 'CopyRun' model. Specifies details about the Copy Run for a backup run of a Job Run. A Copy task copies snapshots resulted from a backup run to a snapshot target which could be 'kLocal', 'kArchival', or 'kRemote'. Attributes... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CopyRun:
"""Implementation of the 'CopyRun' model. Specifies details about the Copy Run for a backup run of a Job Run. A Copy task copies snapshots resulted from a backup run to a snapshot target which could be 'kLocal', 'kArchival', or 'kRemote'. Attributes: copy_snapshot_tasks (list of CopySnap... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CopyRun:
"""Implementation of the 'CopyRun' model. Specifies details about the Copy Run for a backup run of a Job Run. A Copy task copies snapshots resulted from a backup run to a snapshot target which could be 'kLocal', 'kArchival', or 'kRemote'. Attributes: copy_snapshot_tasks (list of CopySnapshotTaskStatu... | the_stack_v2_python_sparse | cohesity_management_sdk/models/copy_run.py | cohesity/management-sdk-python | train | 24 |
3c5ccabd61ebb30610d25a6c995ccbfc4b730de5 | [
"pytest.importorskip('pysteps')\nshape = (30, 30)\nearlier_cube = set_up_test_cube(np.zeros(shape, dtype=np.float32), name='lwe_precipitation_rate', units='m s-1', time=datetime(2018, 2, 20, 4, 15))\nlater_cube = set_up_test_cube(np.zeros(shape, dtype=np.float32), name='lwe_precipitation_rate', units='m s-1', time=... | <|body_start_0|>
pytest.importorskip('pysteps')
shape = (30, 30)
earlier_cube = set_up_test_cube(np.zeros(shape, dtype=np.float32), name='lwe_precipitation_rate', units='m s-1', time=datetime(2018, 2, 20, 4, 15))
later_cube = set_up_test_cube(np.zeros(shape, dtype=np.float32), name='lwe_... | Tests for the generate_advection_velocities_from_winds function. Optical flow velocity values are tested within the Test_optical_flow module; this class tests metadata only. | Test_generate_advection_velocities_from_winds | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_generate_advection_velocities_from_winds:
"""Tests for the generate_advection_velocities_from_winds function. Optical flow velocity values are tested within the Test_optical_flow module; this class tests metadata only."""
def setUp(self):
"""Set up test input cubes"""
<|... | stack_v2_sparse_classes_36k_train_027843 | 5,214 | permissive | [
{
"docstring": "Set up test input cubes",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test function returns a cubelist with the expected components",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test output time coordinates a... | 4 | stack_v2_sparse_classes_30k_train_019057 | Implement the Python class `Test_generate_advection_velocities_from_winds` described below.
Class description:
Tests for the generate_advection_velocities_from_winds function. Optical flow velocity values are tested within the Test_optical_flow module; this class tests metadata only.
Method signatures and docstrings:... | Implement the Python class `Test_generate_advection_velocities_from_winds` described below.
Class description:
Tests for the generate_advection_velocities_from_winds function. Optical flow velocity values are tested within the Test_optical_flow module; this class tests metadata only.
Method signatures and docstrings:... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_generate_advection_velocities_from_winds:
"""Tests for the generate_advection_velocities_from_winds function. Optical flow velocity values are tested within the Test_optical_flow module; this class tests metadata only."""
def setUp(self):
"""Set up test input cubes"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_generate_advection_velocities_from_winds:
"""Tests for the generate_advection_velocities_from_winds function. Optical flow velocity values are tested within the Test_optical_flow module; this class tests metadata only."""
def setUp(self):
"""Set up test input cubes"""
pytest.importor... | the_stack_v2_python_sparse | improver_tests/nowcasting/optical_flow/test_generate_advection_velocities_from_winds.py | metoppv/improver | train | 101 |
9a8f01f0088d86c0e17a4fefece37d34fbd94b5b | [
"self.snake = [(0, 0)]\nself.head = [0, 0]\nself.foods = food\nself.width = width\nself.height = height\nself.score = 0",
"x, y = self.head\nif direction == 'U':\n x -= 1\nelif direction == 'L':\n y -= 1\nelif direction == 'R':\n y += 1\nelif direction == 'D':\n x += 1\nif not (0 <= x <= self.height -... | <|body_start_0|>
self.snake = [(0, 0)]
self.head = [0, 0]
self.foods = food
self.width = width
self.height = height
self.score = 0
<|end_body_0|>
<|body_start_1|>
x, y = self.head
if direction == 'U':
x -= 1
elif direction == 'L':
... | 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_027844 | 4,665 | 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 | null | 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 -... | 44765a7d89423b7ec2c159f70b1a6f6e446523c2 | <|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 | python/_0001_0500/0353_design-snake-game.py | Wang-Yann/LeetCodeMe | train | 0 | |
aa25bf553e61e9c747cdcb8d93a2cc2fce97f1d7 | [
"parts = parse.urlsplit(await super()._api_url())\nnetloc = f\"{parts.netloc.split(':')[0]}\"\nreturn URL(parse.urlunsplit((parts.scheme, netloc, f'{parts.path}/reports', '', '')))",
"measurement_dates = []\nfor report in await self._get_reports(response):\n for subject in report.get('subjects', {}).values():\... | <|body_start_0|>
parts = parse.urlsplit(await super()._api_url())
netloc = f"{parts.netloc.split(':')[0]}"
return URL(parse.urlunsplit((parts.scheme, netloc, f'{parts.path}/reports', '', '')))
<|end_body_0|>
<|body_start_1|>
measurement_dates = []
for report in await self._get_r... | Collector to get the "source up-to-dateness" metric from Quality-time. | QualityTimeSourceUpToDateness | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QualityTimeSourceUpToDateness:
"""Collector to get the "source up-to-dateness" metric from Quality-time."""
async def _api_url(self) -> URL:
"""Extend to add the reports API path."""
<|body_0|>
async def _parse_source_response_date_time(self, response: Response) -> datet... | stack_v2_sparse_classes_36k_train_027845 | 1,417 | permissive | [
{
"docstring": "Extend to add the reports API path.",
"name": "_api_url",
"signature": "async def _api_url(self) -> URL"
},
{
"docstring": "Override to parse the oldest datetime from the recent measurements.",
"name": "_parse_source_response_date_time",
"signature": "async def _parse_sou... | 2 | null | Implement the Python class `QualityTimeSourceUpToDateness` described below.
Class description:
Collector to get the "source up-to-dateness" metric from Quality-time.
Method signatures and docstrings:
- async def _api_url(self) -> URL: Extend to add the reports API path.
- async def _parse_source_response_date_time(se... | Implement the Python class `QualityTimeSourceUpToDateness` described below.
Class description:
Collector to get the "source up-to-dateness" metric from Quality-time.
Method signatures and docstrings:
- async def _api_url(self) -> URL: Extend to add the reports API path.
- async def _parse_source_response_date_time(se... | 5d9952bf0bd47895824fa78428d3e4f4d6b5d9b3 | <|skeleton|>
class QualityTimeSourceUpToDateness:
"""Collector to get the "source up-to-dateness" metric from Quality-time."""
async def _api_url(self) -> URL:
"""Extend to add the reports API path."""
<|body_0|>
async def _parse_source_response_date_time(self, response: Response) -> datet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QualityTimeSourceUpToDateness:
"""Collector to get the "source up-to-dateness" metric from Quality-time."""
async def _api_url(self) -> URL:
"""Extend to add the reports API path."""
parts = parse.urlsplit(await super()._api_url())
netloc = f"{parts.netloc.split(':')[0]}"
... | the_stack_v2_python_sparse | components/collector/src/source_collectors/quality_time/source_up_to_dateness.py | ICTU/quality-time | train | 43 |
66eacbfe8a7a267f3d601242b1fac10253f943d1 | [
"self._spawn(self.conn_cmd)\ntry:\n self.device.expect(['login:'])\n self.device.sendline(self.username)\n self.device.expect(['Password:'])\n self.device.setecho(False)\n self.device.sendline(self.password)\n self.device.setecho(True)\n self.device.expect(['OpenGear Serial Server'])\nexcept pe... | <|body_start_0|>
self._spawn(self.conn_cmd)
try:
self.device.expect(['login:'])
self.device.sendline(self.username)
self.device.expect(['Password:'])
self.device.setecho(False)
self.device.sendline(self.password)
self.device.setecho... | Allow authenticated telnet sessions to be established with a unit's serial ports by OpenGear server. If a board is connected serially to a OpenGear terminal server, this class can be used to connect to the board. | AuthenticatedTelnetConnection | [
"BSD-3-Clause-Clear"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticatedTelnetConnection:
"""Allow authenticated telnet sessions to be established with a unit's serial ports by OpenGear server. If a board is connected serially to a OpenGear terminal server, this class can be used to connect to the board."""
def connect(self):
"""Connect to t... | stack_v2_sparse_classes_36k_train_027846 | 4,580 | permissive | [
{
"docstring": "Connect to the board/station using telnet. This method spawn a pexpect session with telnet command. The telnet port must be as per the ser2net configuration file in order to connect to serial ports of the board. :raises: Exception Board is in use (connection refused).",
"name": "connect",
... | 2 | null | Implement the Python class `AuthenticatedTelnetConnection` described below.
Class description:
Allow authenticated telnet sessions to be established with a unit's serial ports by OpenGear server. If a board is connected serially to a OpenGear terminal server, this class can be used to connect to the board.
Method sig... | Implement the Python class `AuthenticatedTelnetConnection` described below.
Class description:
Allow authenticated telnet sessions to be established with a unit's serial ports by OpenGear server. If a board is connected serially to a OpenGear terminal server, this class can be used to connect to the board.
Method sig... | e722e35f937656efaa43dfd29b49df5c38795243 | <|skeleton|>
class AuthenticatedTelnetConnection:
"""Allow authenticated telnet sessions to be established with a unit's serial ports by OpenGear server. If a board is connected serially to a OpenGear terminal server, this class can be used to connect to the board."""
def connect(self):
"""Connect to t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthenticatedTelnetConnection:
"""Allow authenticated telnet sessions to be established with a unit's serial ports by OpenGear server. If a board is connected serially to a OpenGear terminal server, this class can be used to connect to the board."""
def connect(self):
"""Connect to the board/stat... | the_stack_v2_python_sparse | boardfarm/devices/authenticated_serial_connections.py | lgirdk/boardfarm | train | 20 |
3de583f2f00f4914d1aa86d9d991dd8cc02811f0 | [
"if not nums:\n return 0\nif len(nums) == 1:\n return nums[0]\nmax_sum = -2 ** 23\nsums = []\nfor i in range(len(nums)):\n sums.append(nums[i])\n if nums[i] > max_sum:\n max_sum = nums[i]\n for j in range(len(nums)):\n k = i + j + 1\n if k >= len(nums):\n break\n ... | <|body_start_0|>
if not nums:
return 0
if len(nums) == 1:
return nums[0]
max_sum = -2 ** 23
sums = []
for i in range(len(nums)):
sums.append(nums[i])
if nums[i] > max_sum:
max_sum = nums[i]
for j in range... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray1(self, nums) -> int:
"""暴力解法，时间超限，详见 https://leetcode-cn.com/submissions/detail/18022319/"""
<|body_0|>
def maxSubArray2(self, nums) -> int:
"""时间复杂度 : O(n) 执行用时 : 64 ms, 在Maximum Subarray的Python3提交中击败了72.70% 的用户 内存消耗 : 13.4 MB, 在Maximum Sub... | stack_v2_sparse_classes_36k_train_027847 | 4,928 | no_license | [
{
"docstring": "暴力解法，时间超限，详见 https://leetcode-cn.com/submissions/detail/18022319/",
"name": "maxSubArray1",
"signature": "def maxSubArray1(self, nums) -> int"
},
{
"docstring": "时间复杂度 : O(n) 执行用时 : 64 ms, 在Maximum Subarray的Python3提交中击败了72.70% 的用户 内存消耗 : 13.4 MB, 在Maximum Subarray的Python3提交中击败了96... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray1(self, nums) -> int: 暴力解法，时间超限，详见 https://leetcode-cn.com/submissions/detail/18022319/
- def maxSubArray2(self, nums) -> int: 时间复杂度 : O(n) 执行用时 : 64 ms, 在Maximum ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray1(self, nums) -> int: 暴力解法，时间超限，详见 https://leetcode-cn.com/submissions/detail/18022319/
- def maxSubArray2(self, nums) -> int: 时间复杂度 : O(n) 执行用时 : 64 ms, 在Maximum ... | 7bca9dc8ec211be15c12f89bffbb680d639f87bf | <|skeleton|>
class Solution:
def maxSubArray1(self, nums) -> int:
"""暴力解法，时间超限，详见 https://leetcode-cn.com/submissions/detail/18022319/"""
<|body_0|>
def maxSubArray2(self, nums) -> int:
"""时间复杂度 : O(n) 执行用时 : 64 ms, 在Maximum Subarray的Python3提交中击败了72.70% 的用户 内存消耗 : 13.4 MB, 在Maximum Sub... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray1(self, nums) -> int:
"""暴力解法，时间超限，详见 https://leetcode-cn.com/submissions/detail/18022319/"""
if not nums:
return 0
if len(nums) == 1:
return nums[0]
max_sum = -2 ** 23
sums = []
for i in range(len(nums)):
... | the_stack_v2_python_sparse | python/leetcode/53-maximum-subarray.py | wxnacy/study | train | 18 | |
79cb853387edc39d3b61d31a5765ee54b4ae22e2 | [
"def getNext(cells):\n ret = [0]\n for i in range(1, len(cells) - 1):\n ret.append(int(cells[i - 1] == cells[i + 1]))\n ret.append(0)\n return ret\nwhile N > 0:\n N -= 1\n cells = getNext(cells)\nreturn cells",
"def getNext(cells):\n ret = [0]\n for i in range(1, len(cells) - 1):\n ... | <|body_start_0|>
def getNext(cells):
ret = [0]
for i in range(1, len(cells) - 1):
ret.append(int(cells[i - 1] == cells[i + 1]))
ret.append(0)
return ret
while N > 0:
N -= 1
cells = getNext(cells)
return cells... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def prisonAfterNDays(self, cells, N):
""":type cells: List[int] :type N: int :rtype: List[int]"""
<|body_0|>
def prisonAfterNDays(self, cells, N):
""":type cells: List[int] :type N: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_027848 | 2,128 | no_license | [
{
"docstring": ":type cells: List[int] :type N: int :rtype: List[int]",
"name": "prisonAfterNDays",
"signature": "def prisonAfterNDays(self, cells, N)"
},
{
"docstring": ":type cells: List[int] :type N: int :rtype: List[int]",
"name": "prisonAfterNDays",
"signature": "def prisonAfterNDay... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def prisonAfterNDays(self, cells, N): :type cells: List[int] :type N: int :rtype: List[int]
- def prisonAfterNDays(self, cells, N): :type cells: List[int] :type N: int :rtype: Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def prisonAfterNDays(self, cells, N): :type cells: List[int] :type N: int :rtype: List[int]
- def prisonAfterNDays(self, cells, N): :type cells: List[int] :type N: int :rtype: Li... | d953abe2c9680f636563e76287d2f907e90ced63 | <|skeleton|>
class Solution:
def prisonAfterNDays(self, cells, N):
""":type cells: List[int] :type N: int :rtype: List[int]"""
<|body_0|>
def prisonAfterNDays(self, cells, N):
""":type cells: List[int] :type N: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def prisonAfterNDays(self, cells, N):
""":type cells: List[int] :type N: int :rtype: List[int]"""
def getNext(cells):
ret = [0]
for i in range(1, len(cells) - 1):
ret.append(int(cells[i - 1] == cells[i + 1]))
ret.append(0)
... | the_stack_v2_python_sparse | python_leetcode_2020/Python_Leetcode_2020/957_prison_cells_after_n_days.py | xiangcao/Leetcode | train | 0 | |
1e2ff366708c8c237cdd1846b30815e9c89f0dc6 | [
"if not s or not words:\n return []\nword_len = len(words[0])\nstr_len = word_len * len(words)\nres = []\ntimes = {}\nfor i in words:\n if i not in times:\n times[i] = 0\n times[i] += 1\nfor i in range(word_len):\n self.findSubstring_core(i, s, res, word_len, str_len, times)\nreturn res",
"word... | <|body_start_0|>
if not s or not words:
return []
word_len = len(words[0])
str_len = word_len * len(words)
res = []
times = {}
for i in words:
if i not in times:
times[i] = 0
times[i] += 1
for i in range(word_len... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findSubstring(self, s, words):
""":type s: str :type words: List[str] 其中每个word长度相同！！！ :rtype: List[int]"""
<|body_0|>
def findSubstring_core(self, str_start, s, res, word_len, str_len, times):
"""依照分布相同寻找与单词相关联的子串 :param str_start: :param s: :param res:... | stack_v2_sparse_classes_36k_train_027849 | 2,309 | no_license | [
{
"docstring": ":type s: str :type words: List[str] 其中每个word长度相同！！！ :rtype: List[int]",
"name": "findSubstring",
"signature": "def findSubstring(self, s, words)"
},
{
"docstring": "依照分布相同寻找与单词相关联的子串 :param str_start: :param s: :param res: :param word_len: :param str_len: :param times: :return:",... | 2 | stack_v2_sparse_classes_30k_train_000170 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSubstring(self, s, words): :type s: str :type words: List[str] 其中每个word长度相同！！！ :rtype: List[int]
- def findSubstring_core(self, str_start, s, res, word_len, str_len, time... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findSubstring(self, s, words): :type s: str :type words: List[str] 其中每个word长度相同！！！ :rtype: List[int]
- def findSubstring_core(self, str_start, s, res, word_len, str_len, time... | 328fdd303af1c8cde5bc9bb4c4f039e777de20e5 | <|skeleton|>
class Solution:
def findSubstring(self, s, words):
""":type s: str :type words: List[str] 其中每个word长度相同！！！ :rtype: List[int]"""
<|body_0|>
def findSubstring_core(self, str_start, s, res, word_len, str_len, times):
"""依照分布相同寻找与单词相关联的子串 :param str_start: :param s: :param res:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findSubstring(self, s, words):
""":type s: str :type words: List[str] 其中每个word长度相同！！！ :rtype: List[int]"""
if not s or not words:
return []
word_len = len(words[0])
str_len = word_len * len(words)
res = []
times = {}
for i in wo... | the_stack_v2_python_sparse | leetcode/x30. 与所有单词相关联的字串.py | zhangzeyang0/code | train | 0 | |
3c4780f3ce85df39a2ffc3889cd4cd0a8f0ae6fd | [
"elements = self.root.findall('./camera')\npresets = []\nfor element in elements:\n if activeOnly:\n if element.get('active') == 'True':\n presets.append(element.get('name'))\n else:\n presets.append(element.get('name'))\nreturn presets",
"try:\n sensor_w = float(self.root.find(\... | <|body_start_0|>
elements = self.root.findall('./camera')
presets = []
for element in elements:
if activeOnly:
if element.get('active') == 'True':
presets.append(element.get('name'))
else:
presets.append(element.get('nam... | Manipulates XML database to store camera presets. Inherits XMLData class. | CamPresets | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CamPresets:
"""Manipulates XML database to store camera presets. Inherits XMLData class."""
def getPresets(self, activeOnly=False):
"""Return a list of camera presets. If 'activeOnly' is True, only cameras marked as active will be returned."""
<|body_0|>
def getFilmback(... | stack_v2_sparse_classes_36k_train_027850 | 1,336 | permissive | [
{
"docstring": "Return a list of camera presets. If 'activeOnly' is True, only cameras marked as active will be returned.",
"name": "getPresets",
"signature": "def getPresets(self, activeOnly=False)"
},
{
"docstring": "Get the filmback (as a tuple) for the specified camera. Units in millimetres ... | 2 | null | Implement the Python class `CamPresets` described below.
Class description:
Manipulates XML database to store camera presets. Inherits XMLData class.
Method signatures and docstrings:
- def getPresets(self, activeOnly=False): Return a list of camera presets. If 'activeOnly' is True, only cameras marked as active will... | Implement the Python class `CamPresets` described below.
Class description:
Manipulates XML database to store camera presets. Inherits XMLData class.
Method signatures and docstrings:
- def getPresets(self, activeOnly=False): Return a list of camera presets. If 'activeOnly' is True, only cameras marked as active will... | a05abc916f0b6a9ee2c00e9f9b3dec12c09e6abe | <|skeleton|>
class CamPresets:
"""Manipulates XML database to store camera presets. Inherits XMLData class."""
def getPresets(self, activeOnly=False):
"""Return a list of camera presets. If 'activeOnly' is True, only cameras marked as active will be returned."""
<|body_0|>
def getFilmback(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CamPresets:
"""Manipulates XML database to store camera presets. Inherits XMLData class."""
def getPresets(self, activeOnly=False):
"""Return a list of camera presets. If 'activeOnly' is True, only cameras marked as active will be returned."""
elements = self.root.findall('./camera')
... | the_stack_v2_python_sparse | shared/camPresets.py | mjbonnington/icarus-gps | train | 0 |
f926f39b352247838754a578ed0b62f8df95060a | [
"if hasattr(parser, 'added_gradle_bom'):\n return\nparser.added_gradle_bom = True\nGradleCommandFactory.add_argument(parser, 'bintray_org', defaults, None, help='The bintray organization for the bintray_*_repositories.')\nGradleCommandFactory.add_argument(parser, 'bintray_debian_repository', defaults, None, help... | <|body_start_0|>
if hasattr(parser, 'added_gradle_bom'):
return
parser.added_gradle_bom = True
GradleCommandFactory.add_argument(parser, 'bintray_org', defaults, None, help='The bintray organization for the bintray_*_repositories.')
GradleCommandFactory.add_argument(parser, '... | Base class for build commands using Gradle. | GradleCommandFactory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradleCommandFactory:
"""Base class for build commands using Gradle."""
def add_bom_parser_args(parser, defaults):
"""Adds publishing arguments of interest to the BOM commands as well."""
<|body_0|>
def init_argparser(self, parser, defaults):
"""Adds command-spec... | stack_v2_sparse_classes_36k_train_027851 | 20,381 | permissive | [
{
"docstring": "Adds publishing arguments of interest to the BOM commands as well.",
"name": "add_bom_parser_args",
"signature": "def add_bom_parser_args(parser, defaults)"
},
{
"docstring": "Adds command-specific arguments.",
"name": "init_argparser",
"signature": "def init_argparser(se... | 2 | stack_v2_sparse_classes_30k_train_018757 | Implement the Python class `GradleCommandFactory` described below.
Class description:
Base class for build commands using Gradle.
Method signatures and docstrings:
- def add_bom_parser_args(parser, defaults): Adds publishing arguments of interest to the BOM commands as well.
- def init_argparser(self, parser, default... | Implement the Python class `GradleCommandFactory` described below.
Class description:
Base class for build commands using Gradle.
Method signatures and docstrings:
- def add_bom_parser_args(parser, defaults): Adds publishing arguments of interest to the BOM commands as well.
- def init_argparser(self, parser, default... | 6b672a8862e526f6b9dd3bceec6e34605e1f1998 | <|skeleton|>
class GradleCommandFactory:
"""Base class for build commands using Gradle."""
def add_bom_parser_args(parser, defaults):
"""Adds publishing arguments of interest to the BOM commands as well."""
<|body_0|>
def init_argparser(self, parser, defaults):
"""Adds command-spec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GradleCommandFactory:
"""Base class for build commands using Gradle."""
def add_bom_parser_args(parser, defaults):
"""Adds publishing arguments of interest to the BOM commands as well."""
if hasattr(parser, 'added_gradle_bom'):
return
parser.added_gradle_bom = True
... | the_stack_v2_python_sparse | dev/buildtool/gradle_support.py | spinnaker/buildtool | train | 7 |
4562e226437382e36b300ad8fc1885b738f0de67 | [
"super().__init__(x_ref=x_ref, p_val=p_val, x_ref_preprocessed=x_ref_preprocessed, preprocess_at_init=preprocess_at_init, update_x_ref=update_x_ref, preprocess_fn=preprocess_fn, sigma=sigma, configure_kernel_from_x_ref=configure_kernel_from_x_ref, n_permutations=n_permutations, input_shape=input_shape, data_type=da... | <|body_start_0|>
super().__init__(x_ref=x_ref, p_val=p_val, x_ref_preprocessed=x_ref_preprocessed, preprocess_at_init=preprocess_at_init, update_x_ref=update_x_ref, preprocess_fn=preprocess_fn, sigma=sigma, configure_kernel_from_x_ref=configure_kernel_from_x_ref, n_permutations=n_permutations, input_shape=input... | MMDDriftKeops | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MMDDriftKeops:
def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, kernel: Callable=GaussianRBF, sigma: Optional[np.ndarray]=None,... | stack_v2_sparse_classes_36k_train_027852 | 8,750 | permissive | [
{
"docstring": "Maximum Mean Discrepancy (MMD) data drift detector using a permutation test. Parameters ---------- x_ref Data used as reference distribution. p_val p-value used for the significance of the permutation test. x_ref_preprocessed Whether the given reference data `x_ref` has been preprocessed yet. If... | 3 | stack_v2_sparse_classes_30k_train_009763 | Implement the Python class `MMDDriftKeops` described below.
Class description:
Implement the MMDDriftKeops class.
Method signatures and docstrings:
- def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, in... | Implement the Python class `MMDDriftKeops` described below.
Class description:
Implement the MMDDriftKeops class.
Method signatures and docstrings:
- def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, in... | 4a1b4f74a8590117965421e86c2295bff0f33e89 | <|skeleton|>
class MMDDriftKeops:
def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, kernel: Callable=GaussianRBF, sigma: Optional[np.ndarray]=None,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MMDDriftKeops:
def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, kernel: Callable=GaussianRBF, sigma: Optional[np.ndarray]=None, configure_ker... | the_stack_v2_python_sparse | alibi_detect/cd/keops/mmd.py | SeldonIO/alibi-detect | train | 1,922 | |
215c8ce6eea8bb844c7171d1b8b43276d9381cb5 | [
"key = cache_key('followers', obj.pk, obj.__class__.__name__)\nfollowers = cache.get(key)\nif followers is None:\n follower_classname = obj.__class__.__name__.lower()\n qs = Follow.objects.select_related('follower').filter(object_id=obj.pk, content_type__model=follower_classname)\n followers = [u.follower ... | <|body_start_0|>
key = cache_key('followers', obj.pk, obj.__class__.__name__)
followers = cache.get(key)
if followers is None:
follower_classname = obj.__class__.__name__.lower()
qs = Follow.objects.select_related('follower').filter(object_id=obj.pk, content_type__model=f... | Following manager | FollowingManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FollowingManager:
"""Following manager"""
def followers(self, obj):
"""Return a list of all followers"""
<|body_0|>
def following(self, user, followee_class):
"""Return a list of all objects of the followee_class the given user follows"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_027853 | 5,784 | no_license | [
{
"docstring": "Return a list of all followers",
"name": "followers",
"signature": "def followers(self, obj)"
},
{
"docstring": "Return a list of all objects of the followee_class the given user follows",
"name": "following",
"signature": "def following(self, user, followee_class)"
},
... | 5 | stack_v2_sparse_classes_30k_train_014704 | Implement the Python class `FollowingManager` described below.
Class description:
Following manager
Method signatures and docstrings:
- def followers(self, obj): Return a list of all followers
- def following(self, user, followee_class): Return a list of all objects of the followee_class the given user follows
- def ... | Implement the Python class `FollowingManager` described below.
Class description:
Following manager
Method signatures and docstrings:
- def followers(self, obj): Return a list of all followers
- def following(self, user, followee_class): Return a list of all objects of the followee_class the given user follows
- def ... | 4f7aa41fd0697af61539efd1aba2062addb63009 | <|skeleton|>
class FollowingManager:
"""Following manager"""
def followers(self, obj):
"""Return a list of all followers"""
<|body_0|>
def following(self, user, followee_class):
"""Return a list of all objects of the followee_class the given user follows"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FollowingManager:
"""Following manager"""
def followers(self, obj):
"""Return a list of all followers"""
key = cache_key('followers', obj.pk, obj.__class__.__name__)
followers = cache.get(key)
if followers is None:
follower_classname = obj.__class__.__name__.lo... | the_stack_v2_python_sparse | barddo/follow/models.py | bruno-ortiz/barddo | train | 0 |
8b3cb71744e6c5560e4ff36de6fae337e3fd94ad | [
"self._parser = reqparse.RequestParser()\nself._parser.add_argument('device_ui_id', help='This field cannot be blank', required=True)\nself._parser.add_argument('name', help='This field cannot be blank', required=True)\nself._parser.add_argument('state', help='This field cannot be blank', required=True)\nself._pars... | <|body_start_0|>
self._parser = reqparse.RequestParser()
self._parser.add_argument('device_ui_id', help='This field cannot be blank', required=True)
self._parser.add_argument('name', help='This field cannot be blank', required=True)
self._parser.add_argument('state', help='This field can... | Controller to help register a device to a user. | UserDeviceRegistration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserDeviceRegistration:
"""Controller to help register a device to a user."""
def __init__(self):
"""Setup the request arguments parser in the constructor."""
<|body_0|>
def post(self):
"""POST request that requires JWT."""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_027854 | 3,279 | permissive | [
{
"docstring": "Setup the request arguments parser in the constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "POST request that requires JWT.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004087 | Implement the Python class `UserDeviceRegistration` described below.
Class description:
Controller to help register a device to a user.
Method signatures and docstrings:
- def __init__(self): Setup the request arguments parser in the constructor.
- def post(self): POST request that requires JWT. | Implement the Python class `UserDeviceRegistration` described below.
Class description:
Controller to help register a device to a user.
Method signatures and docstrings:
- def __init__(self): Setup the request arguments parser in the constructor.
- def post(self): POST request that requires JWT.
<|skeleton|>
class U... | dc4d362c1c3e34734951ab4a6cb4248a53fd6c93 | <|skeleton|>
class UserDeviceRegistration:
"""Controller to help register a device to a user."""
def __init__(self):
"""Setup the request arguments parser in the constructor."""
<|body_0|>
def post(self):
"""POST request that requires JWT."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserDeviceRegistration:
"""Controller to help register a device to a user."""
def __init__(self):
"""Setup the request arguments parser in the constructor."""
self._parser = reqparse.RequestParser()
self._parser.add_argument('device_ui_id', help='This field cannot be blank', requi... | the_stack_v2_python_sparse | backend/api/user_devices/controllers.py | KPetsas/IoTHome | train | 0 |
ed3dc8cd7c0ec56f557b7afcf46d1eaad191176c | [
"res = []\n\ndef helper(level, root):\n if len(res) == level:\n res.append([])\n res[level].append(root.val)\n for node in root.children:\n helper(level + 1, node)\nif root is not None:\n helper(0, root)\nreturn res",
"if root is None:\n return []\nres = []\nlayer = [root]\nwhile laye... | <|body_start_0|>
res = []
def helper(level, root):
if len(res) == level:
res.append([])
res[level].append(root.val)
for node in root.children:
helper(level + 1, node)
if root is not None:
helper(0, root)
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder1(self, root):
"""递归 :type root: Node :rtype: List[List[int]]"""
<|body_0|>
def levelOrder2(self, root):
"""递归 :type root: Node :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
def hel... | stack_v2_sparse_classes_36k_train_027855 | 1,347 | no_license | [
{
"docstring": "递归 :type root: Node :rtype: List[List[int]]",
"name": "levelOrder1",
"signature": "def levelOrder1(self, root)"
},
{
"docstring": "递归 :type root: Node :rtype: List[List[int]]",
"name": "levelOrder2",
"signature": "def levelOrder2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021330 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder1(self, root): 递归 :type root: Node :rtype: List[List[int]]
- def levelOrder2(self, root): 递归 :type root: Node :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder1(self, root): 递归 :type root: Node :rtype: List[List[int]]
- def levelOrder2(self, root): 递归 :type root: Node :rtype: List[List[int]]
<|skeleton|>
class Solution:
... | 840a5d4969d5541d9d92f9dbe650506af3d84a99 | <|skeleton|>
class Solution:
def levelOrder1(self, root):
"""递归 :type root: Node :rtype: List[List[int]]"""
<|body_0|>
def levelOrder2(self, root):
"""递归 :type root: Node :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder1(self, root):
"""递归 :type root: Node :rtype: List[List[int]]"""
res = []
def helper(level, root):
if len(res) == level:
res.append([])
res[level].append(root.val)
for node in root.children:
he... | the_stack_v2_python_sparse | Week_03/G20200343040184/LeetCode_429_0184.py | Z-Clark/algorithm007-class02 | train | 1 | |
81a8a2cb11688874d8203235090f5aab4e337ab4 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AuthenticationStrengthRoot()",
"from .authentication_method_mode_detail import AuthenticationMethodModeDetail\nfrom .authentication_method_modes import AuthenticationMethodModes\nfrom .authentication_strength_policy import Authenticati... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AuthenticationStrengthRoot()
<|end_body_0|>
<|body_start_1|>
from .authentication_method_mode_detail import AuthenticationMethodModeDetail
from .authentication_method_modes import Authen... | AuthenticationStrengthRoot | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationStrengthRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot:
"""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... | stack_v2_sparse_classes_36k_train_027856 | 3,660 | 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: AuthenticationStrengthRoot",
"name": "create_from_discriminator_value",
"signature": "def create_from_discri... | 3 | null | Implement the Python class `AuthenticationStrengthRoot` described below.
Class description:
Implement the AuthenticationStrengthRoot class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot: Creates a new instance of the appropr... | Implement the Python class `AuthenticationStrengthRoot` described below.
Class description:
Implement the AuthenticationStrengthRoot class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot: Creates a new instance of the appropr... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AuthenticationStrengthRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthenticationStrengthRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationStrengthRoot:
"""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 ob... | the_stack_v2_python_sparse | msgraph/generated/models/authentication_strength_root.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
de66eaf46a6325a476b5383eb4b6ed45fc8f6c90 | [
"if isinstance(xScale, PQU):\n xScale = float(xScale.inUnitsOf(xUnit).value)\nself.w = w\nparams = {'xScale': xScale, 'w': w}\nif domainMin is None:\n domainMin = -xScale / 10.0\nif domainMax is None:\n domainMax = xScale * 6.0\nUnivariatePDF.__init__(self, xUnit=xUnit, domainMin=domainMin, domainMax=domai... | <|body_start_0|>
if isinstance(xScale, PQU):
xScale = float(xScale.inUnitsOf(xUnit).value)
self.w = w
params = {'xScale': xScale, 'w': w}
if domainMin is None:
domainMin = -xScale / 10.0
if domainMax is None:
domainMax = xScale * 6.0
Un... | BrodyDistribution | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrodyDistribution:
def __init__(self, xUnit='', xScale=1.0, w=0.5, domainMin=None, domainMax=None, xLabel='indep. variable', yLabel='PDF'):
"""Brody distribution vaguely interpolates between Poisson and Wigner distributions Outside of the interval (domainMin,domainMax), getValue() evalua... | stack_v2_sparse_classes_36k_train_027857 | 43,025 | permissive | [
{
"docstring": "Brody distribution vaguely interpolates between Poisson and Wigner distributions Outside of the interval (domainMin,domainMax), getValue() evaluates to None since this pdf is undefined here :param xUnit: units to use for the x axis :param w: (float) exponent to use in the equation :param xScale:... | 2 | stack_v2_sparse_classes_30k_train_001564 | Implement the Python class `BrodyDistribution` described below.
Class description:
Implement the BrodyDistribution class.
Method signatures and docstrings:
- def __init__(self, xUnit='', xScale=1.0, w=0.5, domainMin=None, domainMax=None, xLabel='indep. variable', yLabel='PDF'): Brody distribution vaguely interpolates... | Implement the Python class `BrodyDistribution` described below.
Class description:
Implement the BrodyDistribution class.
Method signatures and docstrings:
- def __init__(self, xUnit='', xScale=1.0, w=0.5, domainMin=None, domainMax=None, xLabel='indep. variable', yLabel='PDF'): Brody distribution vaguely interpolates... | 9566131c37b45fc37f5f8ad07903264864575b6e | <|skeleton|>
class BrodyDistribution:
def __init__(self, xUnit='', xScale=1.0, w=0.5, domainMin=None, domainMax=None, xLabel='indep. variable', yLabel='PDF'):
"""Brody distribution vaguely interpolates between Poisson and Wigner distributions Outside of the interval (domainMin,domainMax), getValue() evalua... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrodyDistribution:
def __init__(self, xUnit='', xScale=1.0, w=0.5, domainMin=None, domainMax=None, xLabel='indep. variable', yLabel='PDF'):
"""Brody distribution vaguely interpolates between Poisson and Wigner distributions Outside of the interval (domainMin,domainMax), getValue() evaluates to None si... | the_stack_v2_python_sparse | fudge/core/math/pdf.py | alhajri/FUDGE | train | 0 | |
e8d7ee81f44fb5bcce2a22f7bdc785bdf4dd6fd7 | [
"super(EvaluateEnsemblePartial, self).__init__()\nself.evaluate_ensemble_partial = evaluate_ensemble_partial\nself.result_labels = result_labels\nself.every_x_epoch = every_x_epoch",
"if epoch % self.every_x_epoch == self.every_x_epoch - 1:\n results = self.evaluate_ensemble_partial()\n if results is not No... | <|body_start_0|>
super(EvaluateEnsemblePartial, self).__init__()
self.evaluate_ensemble_partial = evaluate_ensemble_partial
self.result_labels = result_labels
self.every_x_epoch = every_x_epoch
<|end_body_0|>
<|body_start_1|>
if epoch % self.every_x_epoch == self.every_x_epoch -... | Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop. | EvaluateEnsemblePartial | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvaluateEnsemblePartial:
"""Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop."""
def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1):
"""Evaluate ensemble using a ensemble.evaluate partial. Can be used in combi... | stack_v2_sparse_classes_36k_train_027858 | 20,794 | permissive | [
{
"docstring": "Evaluate ensemble using a ensemble.evaluate partial. Can be used in combination with EvaluateEnsemblePartial to evaluate the ensemble at regular intervals inside a keras model.fit() loop. Note: only ScalarStatistic's are supported. Args: evaluate_ensemble_partial: bnn.ensemble.Ensemble.evaluate ... | 2 | stack_v2_sparse_classes_30k_train_004057 | Implement the Python class `EvaluateEnsemblePartial` described below.
Class description:
Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop.
Method signatures and docstrings:
- def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1): Evaluate ensembl... | Implement the Python class `EvaluateEnsemblePartial` described below.
Class description:
Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop.
Method signatures and docstrings:
- def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1): Evaluate ensembl... | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | <|skeleton|>
class EvaluateEnsemblePartial:
"""Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop."""
def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1):
"""Evaluate ensemble using a ensemble.evaluate partial. Can be used in combi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EvaluateEnsemblePartial:
"""Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop."""
def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1):
"""Evaluate ensemble using a ensemble.evaluate partial. Can be used in combination with E... | the_stack_v2_python_sparse | cold_posterior_bnn/core/keras_utils.py | Ayoob7/google-research | train | 2 |
5c5bcfca4ed0497a23b56d5a1629686290f415c0 | [
"iOPType = self.getOperationFromGET(prequest)\nobjWMSProxy = None\nif iOPType == self.WMS_OP_GETCAPABILITIES:\n objWMSProxy = WMSGetCapabilityProxy(pobjService, prequest)\nelif iOPType == self.WMS_OP_GETMAP:\n objWMSProxy = WMSProxy(pobjService, prequest)\nelif iOPType == self.WMS_OP_GETLEGENDGRAPHIC:\n ob... | <|body_start_0|>
iOPType = self.getOperationFromGET(prequest)
objWMSProxy = None
if iOPType == self.WMS_OP_GETCAPABILITIES:
objWMSProxy = WMSGetCapabilityProxy(pobjService, prequest)
elif iOPType == self.WMS_OP_GETMAP:
objWMSProxy = WMSProxy(pobjService, prequest)... | Un proxy factory pour le WMS qui retourne le bon proxy WMS selon l'operation demande. | WMSProxyFactory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WMSProxyFactory:
"""Un proxy factory pour le WMS qui retourne le bon proxy WMS selon l'operation demande."""
def getWMSProxy(self, pobjService, prequest):
"""Recupere le proxy selon l'operation Args: pobjService: Object service prequest: La requete Returns: Un proxy WMS"""
<|... | stack_v2_sparse_classes_36k_train_027859 | 23,054 | permissive | [
{
"docstring": "Recupere le proxy selon l'operation Args: pobjService: Object service prequest: La requete Returns: Un proxy WMS",
"name": "getWMSProxy",
"signature": "def getWMSProxy(self, pobjService, prequest)"
},
{
"docstring": "Recupere l'operation dans l'url Args: prequest: La requete cont... | 2 | stack_v2_sparse_classes_30k_train_011615 | Implement the Python class `WMSProxyFactory` described below.
Class description:
Un proxy factory pour le WMS qui retourne le bon proxy WMS selon l'operation demande.
Method signatures and docstrings:
- def getWMSProxy(self, pobjService, prequest): Recupere le proxy selon l'operation Args: pobjService: Object service... | Implement the Python class `WMSProxyFactory` described below.
Class description:
Un proxy factory pour le WMS qui retourne le bon proxy WMS selon l'operation demande.
Method signatures and docstrings:
- def getWMSProxy(self, pobjService, prequest): Recupere le proxy selon l'operation Args: pobjService: Object service... | 4732fdb8a0684eb4d7fd50aa43e11b454ee71d08 | <|skeleton|>
class WMSProxyFactory:
"""Un proxy factory pour le WMS qui retourne le bon proxy WMS selon l'operation demande."""
def getWMSProxy(self, pobjService, prequest):
"""Recupere le proxy selon l'operation Args: pobjService: Object service prequest: La requete Returns: Un proxy WMS"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WMSProxyFactory:
"""Un proxy factory pour le WMS qui retourne le bon proxy WMS selon l'operation demande."""
def getWMSProxy(self, pobjService, prequest):
"""Recupere le proxy selon l'operation Args: pobjService: Object service prequest: La requete Returns: Un proxy WMS"""
iOPType = self.... | the_stack_v2_python_sparse | geoprisma/core/proxies/wmsproxy.py | groupe-conseil-nutshimit-nippour/django-geoprisma | train | 0 |
7961ed9fccc54d98ae719f2fa5695615c3c71a09 | [
"if not nums:\n return None\nelse:\n maxnum = nums[0]\n for i in range(len(nums)):\n num = nums[i]\n if num > maxnum:\n maxnum = num\n for j in range(i + 1, len(nums)):\n num += nums[j]\n if num > maxnum:\n maxnum = num\n return maxnum... | <|body_start_0|>
if not nums:
return None
else:
maxnum = nums[0]
for i in range(len(nums)):
num = nums[i]
if num > maxnum:
maxnum = num
for j in range(i + 1, len(nums)):
num += num... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int 暴力划窗，复杂度O(n^2)"""
<|body_0|>
def maxSubArray1(self, nums):
""":type nums: List[int] :rtype: int 动态规划:status[n+1] = max(status[n],status[n] + nums[n+1]) 定义一个函数f(n)，以第n个数为结束点的子数列的最大和，存在一个递推关系f(... | stack_v2_sparse_classes_36k_train_027860 | 1,970 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int 暴力划窗，复杂度O(n^2)",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int 动态规划:status[n+1] = max(status[n],status[n] + nums[n+1]) 定义一个函数f(n)，以第n个数为结束点的子数列的最大和，存在一个递推关系f(n) = max(f(n-1)... | 3 | stack_v2_sparse_classes_30k_train_016629 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int 暴力划窗，复杂度O(n^2)
- def maxSubArray1(self, nums): :type nums: List[int] :rtype: int 动态规划:status[n+1] = max(status[n],s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int 暴力划窗，复杂度O(n^2)
- def maxSubArray1(self, nums): :type nums: List[int] :rtype: int 动态规划:status[n+1] = max(status[n],s... | 2dc982e690b153c33bc7e27a63604f754a0df90c | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int 暴力划窗，复杂度O(n^2)"""
<|body_0|>
def maxSubArray1(self, nums):
""":type nums: List[int] :rtype: int 动态规划:status[n+1] = max(status[n],status[n] + nums[n+1]) 定义一个函数f(n)，以第n个数为结束点的子数列的最大和，存在一个递推关系f(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int 暴力划窗，复杂度O(n^2)"""
if not nums:
return None
else:
maxnum = nums[0]
for i in range(len(nums)):
num = nums[i]
if num > maxnum:
... | the_stack_v2_python_sparse | 53_maximum-subarray.py | 95275059/Algorithm | train | 0 | |
c516f55549f2541746ffee8c2e56d9d1f62ab314 | [
"m, n = (len(nums1), len(nums2))\nans = []\ni, j = (0, 0)\nwhile i < m and j < n:\n if nums1[i] <= nums2[j]:\n ans.append(nums1[i])\n if (m + n) % 2 == 1 and len(ans) == int((m + n) / 2) + 1:\n return ans[-1]\n if (m + n) % 2 == 0 and len(ans) == int((m + n) / 2) + 1:\n ... | <|body_start_0|>
m, n = (len(nums1), len(nums2))
ans = []
i, j = (0, 0)
while i < m and j < n:
if nums1[i] <= nums2[j]:
ans.append(nums1[i])
if (m + n) % 2 == 1 and len(ans) == int((m + n) / 2) + 1:
return ans[-1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def findMedianSortedArrays_binary_search(self, nums1, nums2):
"""O(log(min(m, n))) :param nums1: :param nums2: :return:"""
<... | stack_v2_sparse_classes_36k_train_027861 | 3,283 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: float",
"name": "findMedianSortedArrays",
"signature": "def findMedianSortedArrays(self, nums1, nums2)"
},
{
"docstring": "O(log(min(m, n))) :param nums1: :param nums2: :return:",
"name": "findMedianSortedArrays_binary_sea... | 2 | stack_v2_sparse_classes_30k_train_020545 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def findMedianSortedArrays_binary_search(self, nums1, nums2): O(log(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def findMedianSortedArrays_binary_search(self, nums1, nums2): O(log(... | f2c4f727689567e00ee06560132fca55a6fd9286 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def findMedianSortedArrays_binary_search(self, nums1, nums2):
"""O(log(min(m, n))) :param nums1: :param nums2: :return:"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
m, n = (len(nums1), len(nums2))
ans = []
i, j = (0, 0)
while i < m and j < n:
if nums1[i] <= nums2[j]:
ans.append(nums... | the_stack_v2_python_sparse | leetcode/4_median_of_two_sorted_arrays.py | JianxiangWang/python-journey | train | 1 | |
12492e47e30ceeb472638c84bc3c17c54aa0f22e | [
"opts = setup_options()\nopt_file = tempfile.NamedTemporaryFile(suffix='.ini', mode='w', delete=False)\nopts.write_to_stream(opt_file)\nopt_file.close()\nproblem = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, 'mock_problems', 'default_parsers'))\nrun([problem], options_file=opt_file.name, debu... | <|body_start_0|>
opts = setup_options()
opt_file = tempfile.NamedTemporaryFile(suffix='.ini', mode='w', delete=False)
opts.write_to_stream(opt_file)
opt_file.close()
problem = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, 'mock_problems', 'default_parsers'))
... | Regression tests for the Fitbenchmarking software with all default fitting software packages | TestRegressionDefault | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestRegressionDefault:
"""Regression tests for the Fitbenchmarking software with all default fitting software packages"""
def setUpClass(cls):
"""Create an options file, run it, and get the results."""
<|body_0|>
def test_results_consistent(self):
"""Regression t... | stack_v2_sparse_classes_36k_train_027862 | 8,084 | permissive | [
{
"docstring": "Create an options file, run it, and get the results.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Regression testing that the results of fitting a set of problems containing all problem types against a single minimizer from each of the supported s... | 2 | stack_v2_sparse_classes_30k_train_008511 | Implement the Python class `TestRegressionDefault` described below.
Class description:
Regression tests for the Fitbenchmarking software with all default fitting software packages
Method signatures and docstrings:
- def setUpClass(cls): Create an options file, run it, and get the results.
- def test_results_consisten... | Implement the Python class `TestRegressionDefault` described below.
Class description:
Regression tests for the Fitbenchmarking software with all default fitting software packages
Method signatures and docstrings:
- def setUpClass(cls): Create an options file, run it, and get the results.
- def test_results_consisten... | edae46c0361568bc537de2425d603e7b271eabe7 | <|skeleton|>
class TestRegressionDefault:
"""Regression tests for the Fitbenchmarking software with all default fitting software packages"""
def setUpClass(cls):
"""Create an options file, run it, and get the results."""
<|body_0|>
def test_results_consistent(self):
"""Regression t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestRegressionDefault:
"""Regression tests for the Fitbenchmarking software with all default fitting software packages"""
def setUpClass(cls):
"""Create an options file, run it, and get the results."""
opts = setup_options()
opt_file = tempfile.NamedTemporaryFile(suffix='.ini', mo... | the_stack_v2_python_sparse | fitbenchmarking/systests/test_regression.py | dsotiropoulos/fitbenchmarking | train | 0 |
b8c4f459b40784f9a2b2da2b9dedf7cc2b5e4c92 | [
"try:\n current_subscription = self.get_current_subscription()\n serializer = SubscriptionSerializer(current_subscription)\n print(serializer.data)\n return Response(serializer.data, status=status.HTTP_200_0K)\nexcept:\n return Response(status=status.HTTP_204_NO_CONTENT)",
"serializer = CreateSubsc... | <|body_start_0|>
try:
current_subscription = self.get_current_subscription()
serializer = SubscriptionSerializer(current_subscription)
print(serializer.data)
return Response(serializer.data, status=status.HTTP_200_0K)
except:
return Response(st... | A REST API for Stripes implementation in the backend. Shows account details including customer and subscription details. | SubscribeView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubscribeView:
"""A REST API for Stripes implementation in the backend. Shows account details including customer and subscription details."""
def get(self, request, *args, **kwargs):
"""Return the users current subscription. Returns with status code 200."""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_027863 | 12,846 | no_license | [
{
"docstring": "Return the users current subscription. Returns with status code 200.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Create a new current subscription for the user. Returns with status code 201.",
"name": "post",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_012221 | Implement the Python class `SubscribeView` described below.
Class description:
A REST API for Stripes implementation in the backend. Shows account details including customer and subscription details.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Return the users current subscription. Re... | Implement the Python class `SubscribeView` described below.
Class description:
A REST API for Stripes implementation in the backend. Shows account details including customer and subscription details.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Return the users current subscription. Re... | f38ea1ff9283416f4b4b1a9eb134344a566856a4 | <|skeleton|>
class SubscribeView:
"""A REST API for Stripes implementation in the backend. Shows account details including customer and subscription details."""
def get(self, request, *args, **kwargs):
"""Return the users current subscription. Returns with status code 200."""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubscribeView:
"""A REST API for Stripes implementation in the backend. Shows account details including customer and subscription details."""
def get(self, request, *args, **kwargs):
"""Return the users current subscription. Returns with status code 200."""
try:
current_subscr... | the_stack_v2_python_sparse | djstripe/views.py | meanwise-eng/meanwise-server | train | 0 |
9a6725bd20276f39603cd18c6db3f3f3f1e2f8fc | [
"logg = logging.getLogger(f'c.{__class__.__name__}.init')\nlogg.info(f'Start init')\nself.dod_map = dod_map\nself.map_shape = dod_map.mappa.shape\nself.bias = bias\nself.scale = scale\nself.step_len = step_len\nself.num_steps = 3\npad = 10\nif x is None:\n self.x = 50\nelse:\n self.x = x\nif y is None:\n s... | <|body_start_0|>
logg = logging.getLogger(f'c.{__class__.__name__}.init')
logg.info(f'Start init')
self.dod_map = dod_map
self.map_shape = dod_map.mappa.shape
self.bias = bias
self.scale = scale
self.step_len = step_len
self.num_steps = 3
pad = 10
... | Agent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Agent:
def __init__(self, dod_map, bias, scale, step_len, x=None, y=None, d=None):
"""Create a doodling agent, that will draw on dod_map bias controls the tightness of the curvature step_len is the length of a step specific position and direction can be provided"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_027864 | 2,152 | no_license | [
{
"docstring": "Create a doodling agent, that will draw on dod_map bias controls the tightness of the curvature step_len is the length of a step specific position and direction can be provided",
"name": "__init__",
"signature": "def __init__(self, dod_map, bias, scale, step_len, x=None, y=None, d=None)"... | 2 | null | Implement the Python class `Agent` described below.
Class description:
Implement the Agent class.
Method signatures and docstrings:
- def __init__(self, dod_map, bias, scale, step_len, x=None, y=None, d=None): Create a doodling agent, that will draw on dod_map bias controls the tightness of the curvature step_len is ... | Implement the Python class `Agent` described below.
Class description:
Implement the Agent class.
Method signatures and docstrings:
- def __init__(self, dod_map, bias, scale, step_len, x=None, y=None, d=None): Create a doodling agent, that will draw on dod_map bias controls the tightness of the curvature step_len is ... | 1d7e5657014b00612cde87b78d5506a9e8b6adfc | <|skeleton|>
class Agent:
def __init__(self, dod_map, bias, scale, step_len, x=None, y=None, d=None):
"""Create a doodling agent, that will draw on dod_map bias controls the tightness of the curvature step_len is the length of a step specific position and direction can be provided"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Agent:
def __init__(self, dod_map, bias, scale, step_len, x=None, y=None, d=None):
"""Create a doodling agent, that will draw on dod_map bias controls the tightness of the curvature step_len is the length of a step specific position and direction can be provided"""
logg = logging.getLogger(f'c... | the_stack_v2_python_sparse | python/proc-generation/doodles/doodle_agent.py | Pitrified/snippet | train | 2 | |
823ff152610a1f07d0dbd0253c7125d1a92e4077 | [
"self.data = {}\ncancer_ann_file = os.path.join(data_dir, sample_name + 'T.ann')\nnormal_ann_file = os.path.join(data_dir, sample_name + 'N.ann')\ncancer_consensus_qualities = get_consensus_qualities(cancer_ann_file)\nnormal_consensus_qualities = get_consensus_qualities(normal_ann_file)\nconsensus_qualities = {}\nc... | <|body_start_0|>
self.data = {}
cancer_ann_file = os.path.join(data_dir, sample_name + 'T.ann')
normal_ann_file = os.path.join(data_dir, sample_name + 'N.ann')
cancer_consensus_qualities = get_consensus_qualities(cancer_ann_file)
normal_consensus_qualities = get_consensus_qualiti... | Simple class for data parsed from data/all_non_ref_hg19/yuaker folder, or other samples | calls | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class calls:
"""Simple class for data parsed from data/all_non_ref_hg19/yuaker folder, or other samples"""
def __init__(self, data_dir, sample_name):
"""Parses exome and ann files in data_dir for this sample to make {} of paired tumor/normal call data"""
<|body_0|>
def get_inh... | stack_v2_sparse_classes_36k_train_027865 | 12,376 | no_license | [
{
"docstring": "Parses exome and ann files in data_dir for this sample to make {} of paired tumor/normal call data",
"name": "__init__",
"signature": "def __init__(self, data_dir, sample_name)"
},
{
"docstring": "Return chrpos and ref, normal, cancer alleles for in inherited and somatic {}",
... | 4 | stack_v2_sparse_classes_30k_train_001964 | Implement the Python class `calls` described below.
Class description:
Simple class for data parsed from data/all_non_ref_hg19/yuaker folder, or other samples
Method signatures and docstrings:
- def __init__(self, data_dir, sample_name): Parses exome and ann files in data_dir for this sample to make {} of paired tumo... | Implement the Python class `calls` described below.
Class description:
Simple class for data parsed from data/all_non_ref_hg19/yuaker folder, or other samples
Method signatures and docstrings:
- def __init__(self, data_dir, sample_name): Parses exome and ann files in data_dir for this sample to make {} of paired tumo... | 6565975357bb944f7a4b3d1b2e502ca3cf9d2312 | <|skeleton|>
class calls:
"""Simple class for data parsed from data/all_non_ref_hg19/yuaker folder, or other samples"""
def __init__(self, data_dir, sample_name):
"""Parses exome and ann files in data_dir for this sample to make {} of paired tumor/normal call data"""
<|body_0|>
def get_inh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class calls:
"""Simple class for data parsed from data/all_non_ref_hg19/yuaker folder, or other samples"""
def __init__(self, data_dir, sample_name):
"""Parses exome and ann files in data_dir for this sample to make {} of paired tumor/normal call data"""
self.data = {}
cancer_ann_file =... | the_stack_v2_python_sparse | call_class.py | samesense/loh | train | 0 |
d13d087464b40df9ee5d4fc05ab47f609ff1c1c8 | [
"super(LockedDictionary, self).__init__()\nfor k, v in template.items():\n super(LockedDictionary, self).__setitem__(k, v)",
"if self.has_key(key):\n super(LockedDictionary, self).__setitem__(key, value)\nelse:\n msg = 'Can not ad key to LockedDictionary: %s' % key\n raise KeyError(msg)"
] | <|body_start_0|>
super(LockedDictionary, self).__init__()
for k, v in template.items():
super(LockedDictionary, self).__setitem__(k, v)
<|end_body_0|>
<|body_start_1|>
if self.has_key(key):
super(LockedDictionary, self).__setitem__(key, value)
else:
m... | Defines a dictionary subclass with a pre-determined set of keys. It is not possible to add new keys after construction. | LockedDictionary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LockedDictionary:
"""Defines a dictionary subclass with a pre-determined set of keys. It is not possible to add new keys after construction."""
def __init__(self, template):
"""Construct new LockedDictionary. ARGS: template - dictionary which defined allowed keys and initial values."... | stack_v2_sparse_classes_36k_train_027866 | 1,021 | no_license | [
{
"docstring": "Construct new LockedDictionary. ARGS: template - dictionary which defined allowed keys and initial values.",
"name": "__init__",
"signature": "def __init__(self, template)"
},
{
"docstring": "Sets dictionary value. Raises KeyError for invalid key.",
"name": "__setitem__",
... | 2 | stack_v2_sparse_classes_30k_test_001091 | Implement the Python class `LockedDictionary` described below.
Class description:
Defines a dictionary subclass with a pre-determined set of keys. It is not possible to add new keys after construction.
Method signatures and docstrings:
- def __init__(self, template): Construct new LockedDictionary. ARGS: template - d... | Implement the Python class `LockedDictionary` described below.
Class description:
Defines a dictionary subclass with a pre-determined set of keys. It is not possible to add new keys after construction.
Method signatures and docstrings:
- def __init__(self, template): Construct new LockedDictionary. ARGS: template - d... | 97f530ff0841b9604f0d9575e7e1f0e3c0660be0 | <|skeleton|>
class LockedDictionary:
"""Defines a dictionary subclass with a pre-determined set of keys. It is not possible to add new keys after construction."""
def __init__(self, template):
"""Construct new LockedDictionary. ARGS: template - dictionary which defined allowed keys and initial values."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LockedDictionary:
"""Defines a dictionary subclass with a pre-determined set of keys. It is not possible to add new keys after construction."""
def __init__(self, template):
"""Construct new LockedDictionary. ARGS: template - dictionary which defined allowed keys and initial values."""
su... | the_stack_v2_python_sparse | llia/locked_dictionary.py | plewto/Llia | train | 17 |
b5bde1bbb7a01917e6ab445423edff96e6742c2e | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | DeliverServicer | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeliverServicer:
"""Missing associated documentation comment in .proto file."""
def Deliver(self, request_iterator, context):
"""Deliver first requires an Envelope of type ab.DELIVER_SEEK_INFO with Payload data as a marshaled orderer.SeekInfo message, then a stream of block replies i... | stack_v2_sparse_classes_36k_train_027867 | 6,614 | permissive | [
{
"docstring": "Deliver first requires an Envelope of type ab.DELIVER_SEEK_INFO with Payload data as a marshaled orderer.SeekInfo message, then a stream of block replies is received",
"name": "Deliver",
"signature": "def Deliver(self, request_iterator, context)"
},
{
"docstring": "DeliverFiltere... | 3 | stack_v2_sparse_classes_30k_train_003618 | Implement the Python class `DeliverServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def Deliver(self, request_iterator, context): Deliver first requires an Envelope of type ab.DELIVER_SEEK_INFO with Payload data as a marshaled o... | Implement the Python class `DeliverServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def Deliver(self, request_iterator, context): Deliver first requires an Envelope of type ab.DELIVER_SEEK_INFO with Payload data as a marshaled o... | 0ca510569229217f81fb093682c38e1b4a0cd7c6 | <|skeleton|>
class DeliverServicer:
"""Missing associated documentation comment in .proto file."""
def Deliver(self, request_iterator, context):
"""Deliver first requires an Envelope of type ab.DELIVER_SEEK_INFO with Payload data as a marshaled orderer.SeekInfo message, then a stream of block replies i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeliverServicer:
"""Missing associated documentation comment in .proto file."""
def Deliver(self, request_iterator, context):
"""Deliver first requires an Envelope of type ab.DELIVER_SEEK_INFO with Payload data as a marshaled orderer.SeekInfo message, then a stream of block replies is received"""... | the_stack_v2_python_sparse | hfc/protos/peer/events_pb2_grpc.py | hyperledger/fabric-sdk-py | train | 439 |
80c37cd98ec568cab060ce699f8620c4409dcaa2 | [
"self.x = x\nself.y = y\nself.height = 25\nself.width = 50\nself.health = health",
"if self.health == 1:\n pygame.draw.rect(screen, GREY, (self.x, self.y, self.width, self.height))\nif self.health == 2:\n pygame.draw.rect(screen, RED, (self.x, self.y, self.width, self.height))\nif self.health == 3:\n pyg... | <|body_start_0|>
self.x = x
self.y = y
self.height = 25
self.width = 50
self.health = health
<|end_body_0|>
<|body_start_1|>
if self.health == 1:
pygame.draw.rect(screen, GREY, (self.x, self.y, self.width, self.height))
if self.health == 2:
... | This class contains the structure of the bricks objects to be destroyed by the player | Bricks | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bricks:
"""This class contains the structure of the bricks objects to be destroyed by the player"""
def __init__(self, x, y, health=1):
"""self.x is the x position on the screen self.y is the y position on the screen self.height is the height of the rectangle self.width is the width ... | stack_v2_sparse_classes_36k_train_027868 | 4,153 | no_license | [
{
"docstring": "self.x is the x position on the screen self.y is the y position on the screen self.height is the height of the rectangle self.width is the width of the rectangle self.health is the health of the bricks which defines how many hits needed to destroy the bricks",
"name": "__init__",
"signat... | 2 | stack_v2_sparse_classes_30k_train_016556 | Implement the Python class `Bricks` described below.
Class description:
This class contains the structure of the bricks objects to be destroyed by the player
Method signatures and docstrings:
- def __init__(self, x, y, health=1): self.x is the x position on the screen self.y is the y position on the screen self.heigh... | Implement the Python class `Bricks` described below.
Class description:
This class contains the structure of the bricks objects to be destroyed by the player
Method signatures and docstrings:
- def __init__(self, x, y, health=1): self.x is the x position on the screen self.y is the y position on the screen self.heigh... | 14a140aac32397ae4b412e276488a83b730cc7b5 | <|skeleton|>
class Bricks:
"""This class contains the structure of the bricks objects to be destroyed by the player"""
def __init__(self, x, y, health=1):
"""self.x is the x position on the screen self.y is the y position on the screen self.height is the height of the rectangle self.width is the width ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bricks:
"""This class contains the structure of the bricks objects to be destroyed by the player"""
def __init__(self, x, y, health=1):
"""self.x is the x position on the screen self.y is the y position on the screen self.height is the height of the rectangle self.width is the width of the rectan... | the_stack_v2_python_sparse | Objektorientert INF-1400/oblig1/Files/Objects.py | MartinRovang/UniversityPhysics | train | 3 |
da577011b4bad29f3cbda1e044ee544f6bcce846 | [
"if not os.path.exists(path):\n return\nif os.path.isfile(path) or os.path.islink(path):\n os.unlink(path)\nelse:\n shutil.rmtree(path)",
"if os.path.exists(dstname):\n if os.path.abspath(linkto) == os.path.abspath(dstname):\n return\n os.unlink(dstname)\nos.symlink(linkto, dstname)",
"try... | <|body_start_0|>
if not os.path.exists(path):
return
if os.path.isfile(path) or os.path.islink(path):
os.unlink(path)
else:
shutil.rmtree(path)
<|end_body_0|>
<|body_start_1|>
if os.path.exists(dstname):
if os.path.abspath(linkto) == os.pa... | FileUtils | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileUtils:
def rm_rf(path):
"""Util to delete path"""
<|body_0|>
def symlink(linkto, dstname):
"""Util to symlink path"""
<|body_1|>
def mkdir_p(start_path):
"""Util to make path"""
<|body_2|>
def dir_size(start_path):
"""Uti... | stack_v2_sparse_classes_36k_train_027869 | 1,591 | no_license | [
{
"docstring": "Util to delete path",
"name": "rm_rf",
"signature": "def rm_rf(path)"
},
{
"docstring": "Util to symlink path",
"name": "symlink",
"signature": "def symlink(linkto, dstname)"
},
{
"docstring": "Util to make path",
"name": "mkdir_p",
"signature": "def mkdir... | 4 | stack_v2_sparse_classes_30k_train_013852 | Implement the Python class `FileUtils` described below.
Class description:
Implement the FileUtils class.
Method signatures and docstrings:
- def rm_rf(path): Util to delete path
- def symlink(linkto, dstname): Util to symlink path
- def mkdir_p(start_path): Util to make path
- def dir_size(start_path): Util to get t... | Implement the Python class `FileUtils` described below.
Class description:
Implement the FileUtils class.
Method signatures and docstrings:
- def rm_rf(path): Util to delete path
- def symlink(linkto, dstname): Util to symlink path
- def mkdir_p(start_path): Util to make path
- def dir_size(start_path): Util to get t... | 3962b3c7bab9d26bf871d257e15dd39c45ffaddd | <|skeleton|>
class FileUtils:
def rm_rf(path):
"""Util to delete path"""
<|body_0|>
def symlink(linkto, dstname):
"""Util to symlink path"""
<|body_1|>
def mkdir_p(start_path):
"""Util to make path"""
<|body_2|>
def dir_size(start_path):
"""Uti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileUtils:
def rm_rf(path):
"""Util to delete path"""
if not os.path.exists(path):
return
if os.path.isfile(path) or os.path.islink(path):
os.unlink(path)
else:
shutil.rmtree(path)
def symlink(linkto, dstname):
"""Util to symlink... | the_stack_v2_python_sparse | tools/files/file_utils.py | zigvu/samosa | train | 0 | |
9d6fe2626314c5bd7708fc9b7c689a0624374f97 | [
"self._values = args[::2]\nself._times = args[1::2]\nassert len(self._values) == len(self._times) + 1\nassert all((isinstance(dt, datetime.datetime) for dt in self._times))",
"left = 0\nright = len(self._times)\nif now is None:\n now = datetime.datetime.utcnow()\nwhile left != right:\n mid = (left + right) ... | <|body_start_0|>
self._values = args[::2]
self._times = args[1::2]
assert len(self._values) == len(self._times) + 1
assert all((isinstance(dt, datetime.datetime) for dt in self._times))
<|end_body_0|>
<|body_start_1|>
left = 0
right = len(self._times)
if now is N... | Config helper class to handle config values changing at set times. | Until | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Until:
"""Config helper class to handle config values changing at set times."""
def __init__(self, *args):
"""Initialise class. Args should be an alternating sequence of values and sequential datetimes."""
<|body_0|>
def get(self, now=None):
"""Return the appropr... | stack_v2_sparse_classes_36k_train_027870 | 1,978 | no_license | [
{
"docstring": "Initialise class. Args should be an alternating sequence of values and sequential datetimes.",
"name": "__init__",
"signature": "def __init__(self, *args)"
},
{
"docstring": "Return the appropriate value based on the current time.",
"name": "get",
"signature": "def get(se... | 2 | stack_v2_sparse_classes_30k_test_000912 | Implement the Python class `Until` described below.
Class description:
Config helper class to handle config values changing at set times.
Method signatures and docstrings:
- def __init__(self, *args): Initialise class. Args should be an alternating sequence of values and sequential datetimes.
- def get(self, now=None... | Implement the Python class `Until` described below.
Class description:
Config helper class to handle config values changing at set times.
Method signatures and docstrings:
- def __init__(self, *args): Initialise class. Args should be an alternating sequence of values and sequential datetimes.
- def get(self, now=None... | 1115fe316f7c1ee1407017a60a054b1f7291f331 | <|skeleton|>
class Until:
"""Config helper class to handle config values changing at set times."""
def __init__(self, *args):
"""Initialise class. Args should be an alternating sequence of values and sequential datetimes."""
<|body_0|>
def get(self, now=None):
"""Return the appropr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Until:
"""Config helper class to handle config values changing at set times."""
def __init__(self, *args):
"""Initialise class. Args should be an alternating sequence of values and sequential datetimes."""
self._values = args[::2]
self._times = args[1::2]
assert len(self._... | the_stack_v2_python_sparse | eisitirio/helpers/timed_config.py | gwynethbradbury/ouss_ball | train | 1 |
bccc353a6d7056da6e489c1144a242fbd5af02ae | [
"self.schemas = Collection()\nself.collector = collector\nif self.collector is None:\n paths = os.environ.get('HARMONY_SCHEMA_PATH', self.DEFAULT_SCHEMA_PATH).split(os.pathsep)\n self.collector = FilesystemCollector(paths)\nself.validator_class = validator_class\nif self.validator_class is None:\n self.val... | <|body_start_0|>
self.schemas = Collection()
self.collector = collector
if self.collector is None:
paths = os.environ.get('HARMONY_SCHEMA_PATH', self.DEFAULT_SCHEMA_PATH).split(os.pathsep)
self.collector = FilesystemCollector(paths)
self.validator_class = validato... | A configuration of the various components in a standard way. | Session | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Session:
"""A configuration of the various components in a standard way."""
def __init__(self, collector=None, processors=None, validator_class=None):
"""Initialise session. *collector* is used to collect schemas for use in the session and should conform to the :py:class:`~harmony.sc... | stack_v2_sparse_classes_36k_train_027871 | 5,833 | permissive | [
{
"docstring": "Initialise session. *collector* is used to collect schemas for use in the session and should conform to the :py:class:`~harmony.schema.collector.Collector` interface. Defaults to a :py:class:`~harmony.schema.collector.FileSystemCollector` using the environment variable :envvar:`HARMONY_SCHEMA_PA... | 6 | stack_v2_sparse_classes_30k_train_009959 | Implement the Python class `Session` described below.
Class description:
A configuration of the various components in a standard way.
Method signatures and docstrings:
- def __init__(self, collector=None, processors=None, validator_class=None): Initialise session. *collector* is used to collect schemas for use in the... | Implement the Python class `Session` described below.
Class description:
A configuration of the various components in a standard way.
Method signatures and docstrings:
- def __init__(self, collector=None, processors=None, validator_class=None): Initialise session. *collector* is used to collect schemas for use in the... | 41039cea452860649f717358fd57a99e73202579 | <|skeleton|>
class Session:
"""A configuration of the various components in a standard way."""
def __init__(self, collector=None, processors=None, validator_class=None):
"""Initialise session. *collector* is used to collect schemas for use in the session and should conform to the :py:class:`~harmony.sc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Session:
"""A configuration of the various components in a standard way."""
def __init__(self, collector=None, processors=None, validator_class=None):
"""Initialise session. *collector* is used to collect schemas for use in the session and should conform to the :py:class:`~harmony.schema.collecto... | the_stack_v2_python_sparse | source/harmony/session.py | 4degrees/harmony | train | 4 |
6be2f838c3901f986b9013e96c70fecff9544420 | [
"body = pickle.dumps(item)\nheader = struct.pack(self.packing, len(body))\nmessage = header + body\nreturn channel.write(bstr=message)",
"header = channel.read(maxlen=self.headerSize)\nlength, = struct.unpack(self.packing, header)\nbody = channel.read(minlen=length)\nreturn pickle.loads(body)"
] | <|body_start_0|>
body = pickle.dumps(item)
header = struct.pack(self.packing, len(body))
message = header + body
return channel.write(bstr=message)
<|end_body_0|>
<|body_start_1|>
header = channel.read(maxlen=self.headerSize)
length, = struct.unpack(self.packing, header)... | A marshaler that uses the native python services in {pickle} to serialize python objects for transmission to other processes. The {send} protocol pickles an object into the payload byte stream, and builds a header with the length of the payload. Similarly, {recv} first extracts the length of the byte string and uses th... | Pickler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pickler:
"""A marshaler that uses the native python services in {pickle} to serialize python objects for transmission to other processes. The {send} protocol pickles an object into the payload byte stream, and builds a header with the length of the payload. Similarly, {recv} first extracts the le... | stack_v2_sparse_classes_36k_train_027872 | 1,854 | permissive | [
{
"docstring": "Pack and ship {item} over {channel}",
"name": "send",
"signature": "def send(self, item, channel)"
},
{
"docstring": "Extract and return a single item from {channel}",
"name": "recv",
"signature": "def recv(self, channel)"
}
] | 2 | null | Implement the Python class `Pickler` described below.
Class description:
A marshaler that uses the native python services in {pickle} to serialize python objects for transmission to other processes. The {send} protocol pickles an object into the payload byte stream, and builds a header with the length of the payload. ... | Implement the Python class `Pickler` described below.
Class description:
A marshaler that uses the native python services in {pickle} to serialize python objects for transmission to other processes. The {send} protocol pickles an object into the payload byte stream, and builds a header with the length of the payload. ... | d741c44ffb3e9e1f726bf492202ac8738bb4aa1c | <|skeleton|>
class Pickler:
"""A marshaler that uses the native python services in {pickle} to serialize python objects for transmission to other processes. The {send} protocol pickles an object into the payload byte stream, and builds a header with the length of the payload. Similarly, {recv} first extracts the le... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pickler:
"""A marshaler that uses the native python services in {pickle} to serialize python objects for transmission to other processes. The {send} protocol pickles an object into the payload byte stream, and builds a header with the length of the payload. Similarly, {recv} first extracts the length of the b... | the_stack_v2_python_sparse | packages/pyre/ipc/Pickler.py | pyre/pyre | train | 27 |
7cef87f8d560167381388303cafd5f843102d9bd | [
"url = host + '/api/mart/list'\ndata = {'size': 10, 'page': 1}\nr = requests.post(url=url, data=data).json()\nout_format('砍价列表:', r)\ns = len(r['data'])\nif s == 0:\n print('data is null')\nelse:\n p_id = r['data'][5]['id']\n return p_id",
"url = host + '/api/trophy/list'\ndata = {'size': 10, 'page': 1}\... | <|body_start_0|>
url = host + '/api/mart/list'
data = {'size': 10, 'page': 1}
r = requests.post(url=url, data=data).json()
out_format('砍价列表:', r)
s = len(r['data'])
if s == 0:
print('data is null')
else:
p_id = r['data'][5]['id']
... | 定义一个双十一活动的公共测试类 | double_elev | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class double_elev:
"""定义一个双十一活动的公共测试类"""
def test_mart_list(self):
"""砍价列表"""
<|body_0|>
def test_past(self):
"""往期开奖 :param:size:单页记录数 :param:page:页码"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
url = host + '/api/mart/list'
data = {'size'... | stack_v2_sparse_classes_36k_train_027873 | 1,327 | no_license | [
{
"docstring": "砍价列表",
"name": "test_mart_list",
"signature": "def test_mart_list(self)"
},
{
"docstring": "往期开奖 :param:size:单页记录数 :param:page:页码",
"name": "test_past",
"signature": "def test_past(self)"
}
] | 2 | null | Implement the Python class `double_elev` described below.
Class description:
定义一个双十一活动的公共测试类
Method signatures and docstrings:
- def test_mart_list(self): 砍价列表
- def test_past(self): 往期开奖 :param:size:单页记录数 :param:page:页码 | Implement the Python class `double_elev` described below.
Class description:
定义一个双十一活动的公共测试类
Method signatures and docstrings:
- def test_mart_list(self): 砍价列表
- def test_past(self): 往期开奖 :param:size:单页记录数 :param:page:页码
<|skeleton|>
class double_elev:
"""定义一个双十一活动的公共测试类"""
def test_mart_list(self):
... | 0ebaae335de2f1633e31c4fc3f60e556220a8bfb | <|skeleton|>
class double_elev:
"""定义一个双十一活动的公共测试类"""
def test_mart_list(self):
"""砍价列表"""
<|body_0|>
def test_past(self):
"""往期开奖 :param:size:单页记录数 :param:page:页码"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class double_elev:
"""定义一个双十一活动的公共测试类"""
def test_mart_list(self):
"""砍价列表"""
url = host + '/api/mart/list'
data = {'size': 10, 'page': 1}
r = requests.post(url=url, data=data).json()
out_format('砍价列表:', r)
s = len(r['data'])
if s == 0:
print(... | the_stack_v2_python_sparse | Atle/interface/framework/common/pubilc_act.py | shiqi0128/My_scripts | train | 0 |
3cbdab37c7968553f96e904dbaeb6a2c6660f74c | [
"self.kl_low = kl_low\nself.kl_high = kl_high\nself.n_epochs = n_epochs\nself.start_epoch = start_epoch\nself.kl = (self.kl_high - self.kl_low) / (self.n_epochs - self.start_epoch)",
"k = epoch - self.start_epoch if epoch >= self.start_epoch else 0\nbeta = self.kl_low + k * self.kl\nif beta > self.kl_high:\n b... | <|body_start_0|>
self.kl_low = kl_low
self.kl_high = kl_high
self.n_epochs = n_epochs
self.start_epoch = start_epoch
self.kl = (self.kl_high - self.kl_low) / (self.n_epochs - self.start_epoch)
<|end_body_0|>
<|body_start_1|>
k = epoch - self.start_epoch if epoch >= self.... | Annealer scaling KL weights (beta) linearly according to the number of epochs. | KLAnnealer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KLAnnealer:
"""Annealer scaling KL weights (beta) linearly according to the number of epochs."""
def __init__(self, kl_low: float, kl_high: float, n_epochs: int, start_epoch: int) -> None:
"""Construct KLAnnealer. Args: kl_low: low KL weight. kl_high: high KL weight. n_epochs: number... | stack_v2_sparse_classes_36k_train_027874 | 2,172 | permissive | [
{
"docstring": "Construct KLAnnealer. Args: kl_low: low KL weight. kl_high: high KL weight. n_epochs: number of epochs. start_epoch: starting epoch.",
"name": "__init__",
"signature": "def __init__(self, kl_low: float, kl_high: float, n_epochs: int, start_epoch: int) -> None"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_007908 | Implement the Python class `KLAnnealer` described below.
Class description:
Annealer scaling KL weights (beta) linearly according to the number of epochs.
Method signatures and docstrings:
- def __init__(self, kl_low: float, kl_high: float, n_epochs: int, start_epoch: int) -> None: Construct KLAnnealer. Args: kl_low:... | Implement the Python class `KLAnnealer` described below.
Class description:
Annealer scaling KL weights (beta) linearly according to the number of epochs.
Method signatures and docstrings:
- def __init__(self, kl_low: float, kl_high: float, n_epochs: int, start_epoch: int) -> None: Construct KLAnnealer. Args: kl_low:... | 0b69b7d5b261f2f9af3984793c1295b9b80cd01a | <|skeleton|>
class KLAnnealer:
"""Annealer scaling KL weights (beta) linearly according to the number of epochs."""
def __init__(self, kl_low: float, kl_high: float, n_epochs: int, start_epoch: int) -> None:
"""Construct KLAnnealer. Args: kl_low: low KL weight. kl_high: high KL weight. n_epochs: number... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KLAnnealer:
"""Annealer scaling KL weights (beta) linearly according to the number of epochs."""
def __init__(self, kl_low: float, kl_high: float, n_epochs: int, start_epoch: int) -> None:
"""Construct KLAnnealer. Args: kl_low: low KL weight. kl_high: high KL weight. n_epochs: number of epochs. s... | the_stack_v2_python_sparse | src/gt4sd/frameworks/granular/ml/models/utils.py | GT4SD/gt4sd-core | train | 239 |
10ccbd8041655ad4bbbcac7d6dfe62cfc2bfa94f | [
"it = iter(test_inputs.split('\\n')) if test_inputs else None\n\ndef uinput():\n return next(it) if it else sys.stdin.readline().rstrip()\n[self.p, self.k] = map(int, uinput().split())\nself.M = 10 ** 9 + 7",
"result = 0\nbp = Binominals(mod=self.p)\nmm = 1\nfor m in range(1, self.p):\n mm = bp.mul(mm, self... | <|body_start_0|>
it = iter(test_inputs.split('\n')) if test_inputs else None
def uinput():
return next(it) if it else sys.stdin.readline().rstrip()
[self.p, self.k] = map(int, uinput().split())
self.M = 10 ** 9 + 7
<|end_body_0|>
<|body_start_1|>
result = 0
... | Modular representation | Modular | [
"Unlicense",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Modular:
"""Modular representation"""
def __init__(self, test_inputs=None):
"""Default constructor"""
<|body_0|>
def calculate(self):
"""Main calcualtion function of the class"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
it = iter(test_inputs... | stack_v2_sparse_classes_36k_train_027875 | 3,558 | permissive | [
{
"docstring": "Default constructor",
"name": "__init__",
"signature": "def __init__(self, test_inputs=None)"
},
{
"docstring": "Main calcualtion function of the class",
"name": "calculate",
"signature": "def calculate(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008476 | Implement the Python class `Modular` described below.
Class description:
Modular representation
Method signatures and docstrings:
- def __init__(self, test_inputs=None): Default constructor
- def calculate(self): Main calcualtion function of the class | Implement the Python class `Modular` described below.
Class description:
Modular representation
Method signatures and docstrings:
- def __init__(self, test_inputs=None): Default constructor
- def calculate(self): Main calcualtion function of the class
<|skeleton|>
class Modular:
"""Modular representation"""
... | ae02ea872ca91ef98630cc172a844b82cc56f621 | <|skeleton|>
class Modular:
"""Modular representation"""
def __init__(self, test_inputs=None):
"""Default constructor"""
<|body_0|>
def calculate(self):
"""Main calcualtion function of the class"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Modular:
"""Modular representation"""
def __init__(self, test_inputs=None):
"""Default constructor"""
it = iter(test_inputs.split('\n')) if test_inputs else None
def uinput():
return next(it) if it else sys.stdin.readline().rstrip()
[self.p, self.k] = map(int,... | the_stack_v2_python_sparse | codeforces/604D_modular.py | snsokolov/contests | train | 1 |
9015a6981f4388cb8fd6788addf1c6447f0c876a | [
"result = cls(group=operation, data_type=data_type)\nlatency_unit = 'ms'\nfor _, name, val in lines:\n name = name.strip()\n val = val.strip()\n if name.startswith('>'):\n name = name[1:]\n val = float(val) if '.' in val or 'nan' in val.lower() else int(val)\n if name.isdigit():\n if va... | <|body_start_0|>
result = cls(group=operation, data_type=data_type)
latency_unit = 'ms'
for _, name, val in lines:
name = name.strip()
val = val.strip()
if name.startswith('>'):
name = name[1:]
val = float(val) if '.' in val or 'nan... | Individual results for a single operation. YCSB results are either aggregated per operation (read/update) at the end of the run or output on a per-interval (i.e. second) basis during the run. Attributes: group: group name (e.g. update, insert, overall) statistics: dict mapping from statistic name to value (e.g. {'Count... | _OpResult | [
"Classpath-exception-2.0",
"BSD-3-Clause",
"AGPL-3.0-only",
"MIT",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _OpResult:
"""Individual results for a single operation. YCSB results are either aggregated per operation (read/update) at the end of the run or output on a per-interval (i.e. second) basis during the run. Attributes: group: group name (e.g. update, insert, overall) statistics: dict mapping from ... | stack_v2_sparse_classes_36k_train_027876 | 37,650 | permissive | [
{
"docstring": "Returns an _OpResult parsed from YCSB summary lines. Example format: [UPDATE], Operations, 2468054 [UPDATE], AverageLatency(us), 2218.8513395574005 [UPDATE], MinLatency(us), 554 [UPDATE], MaxLatency(us), 352634 [UPDATE], 95thPercentileLatency(ms), 4 [UPDATE], 99thPercentileLatency(ms), 7 [UPDATE... | 2 | stack_v2_sparse_classes_30k_train_019415 | Implement the Python class `_OpResult` described below.
Class description:
Individual results for a single operation. YCSB results are either aggregated per operation (read/update) at the end of the run or output on a per-interval (i.e. second) basis during the run. Attributes: group: group name (e.g. update, insert, ... | Implement the Python class `_OpResult` described below.
Class description:
Individual results for a single operation. YCSB results are either aggregated per operation (read/update) at the end of the run or output on a per-interval (i.e. second) basis during the run. Attributes: group: group name (e.g. update, insert, ... | d0699f32998898757b036704fba39e5471641f01 | <|skeleton|>
class _OpResult:
"""Individual results for a single operation. YCSB results are either aggregated per operation (read/update) at the end of the run or output on a per-interval (i.e. second) basis during the run. Attributes: group: group name (e.g. update, insert, overall) statistics: dict mapping from ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _OpResult:
"""Individual results for a single operation. YCSB results are either aggregated per operation (read/update) at the end of the run or output on a per-interval (i.e. second) basis during the run. Attributes: group: group name (e.g. update, insert, overall) statistics: dict mapping from statistic nam... | the_stack_v2_python_sparse | perfkitbenchmarker/linux_packages/ycsb_stats.py | GoogleCloudPlatform/PerfKitBenchmarker | train | 1,923 |
9b8eeb5c92964259eaa481abfbb71b7808653243 | [
"self.w = w\nfor i in range(1, len(self.w)):\n self.w[i] += self.w[i - 1]",
"index = randint(1, self.w[-1])\nstart = 0\nend = len(self.w) - 1\nif index < self.w[0]:\n return 0\nwhile start < end:\n mid = (start + end) // 2\n if index > self.w[mid]:\n start = mid + 1\n else:\n end = mi... | <|body_start_0|>
self.w = w
for i in range(1, len(self.w)):
self.w[i] += self.w[i - 1]
<|end_body_0|>
<|body_start_1|>
index = randint(1, self.w[-1])
start = 0
end = len(self.w) - 1
if index < self.w[0]:
return 0
while start < end:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.w = w
for i in range(1, len(self.w)):
self.w[i] += self.w[i - 1]
<|end_... | stack_v2_sparse_classes_36k_train_027877 | 650 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | 16e8a7935811fa71ce71998da8549e29ba68f847 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.w = w
for i in range(1, len(self.w)):
self.w[i] += self.w[i - 1]
def pickIndex(self):
""":rtype: int"""
index = randint(1, self.w[-1])
start = 0
end = len(self.w) - 1
... | the_stack_v2_python_sparse | leetcode6/pickIndex.py | lizyang95/leetcode | train | 0 | |
b2c651ca1856de05b4edc60d44e18493e3cc29c9 | [
"new_users = []\nseen = set()\nfor user_dict in validated_data:\n if user_dict['id'] in seen:\n raise ValidationError({'id': [f\"User with ID {user_dict['id']} given multiple times.\"]})\n seen.add(user_dict['id'])\n new_users.append(User(**user_dict))\nUser.objects.bulk_create(new_users, ignore_con... | <|body_start_0|>
new_users = []
seen = set()
for user_dict in validated_data:
if user_dict['id'] in seen:
raise ValidationError({'id': [f"User with ID {user_dict['id']} given multiple times."]})
seen.add(user_dict['id'])
new_users.append(User(*... | List serializer for User model to handle bulk updates. | UserListSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserListSerializer:
"""List serializer for User model to handle bulk updates."""
def create(self, validated_data: list) -> list:
"""Override create method to optimize django queries."""
<|body_0|>
def update(self, queryset: QuerySet, validated_data: list) -> list:
... | stack_v2_sparse_classes_36k_train_027878 | 23,871 | permissive | [
{
"docstring": "Override create method to optimize django queries.",
"name": "create",
"signature": "def create(self, validated_data: list) -> list"
},
{
"docstring": "Override update method to support bulk updates. ref:https://www.django-rest-framework.org/api-guide/serializers/#customizing-mul... | 2 | null | Implement the Python class `UserListSerializer` described below.
Class description:
List serializer for User model to handle bulk updates.
Method signatures and docstrings:
- def create(self, validated_data: list) -> list: Override create method to optimize django queries.
- def update(self, queryset: QuerySet, valid... | Implement the Python class `UserListSerializer` described below.
Class description:
List serializer for User model to handle bulk updates.
Method signatures and docstrings:
- def create(self, validated_data: list) -> list: Override create method to optimize django queries.
- def update(self, queryset: QuerySet, valid... | cb6326cabee6570a5725702cb2893ae39f752279 | <|skeleton|>
class UserListSerializer:
"""List serializer for User model to handle bulk updates."""
def create(self, validated_data: list) -> list:
"""Override create method to optimize django queries."""
<|body_0|>
def update(self, queryset: QuerySet, validated_data: list) -> list:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserListSerializer:
"""List serializer for User model to handle bulk updates."""
def create(self, validated_data: list) -> list:
"""Override create method to optimize django queries."""
new_users = []
seen = set()
for user_dict in validated_data:
if user_dict['... | the_stack_v2_python_sparse | pydis_site/apps/api/serializers.py | python-discord/site | train | 746 |
e489f1bc1d7aa773665187aa5c276fb97cd92c25 | [
"if self.state_model.op_state in [DevState.UNKNOWN, DevState.DISABLE]:\n log_msg = f'ObsReset() is not allowed in {self.state_model.op_state}'\n tango.Except.throw_exception(log_msg, 'Failed to invoke ObsReset command on CspSubarrayLeafNode.', 'cspsubarrayleafnode.ObsReset()', tango.ErrSeverity.ERR)\nthis_ser... | <|body_start_0|>
if self.state_model.op_state in [DevState.UNKNOWN, DevState.DISABLE]:
log_msg = f'ObsReset() is not allowed in {self.state_model.op_state}'
tango.Except.throw_exception(log_msg, 'Failed to invoke ObsReset command on CspSubarrayLeafNode.', 'cspsubarrayleafnode.ObsReset()'... | A class for CSPSubarrayLeafNode's ObsReset() command. ObsReset command is inherited from BaseCommand. Command to reset the Csp Subarray and bring it to its RESETTING state. | ObsResetCommand | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObsResetCommand:
"""A class for CSPSubarrayLeafNode's ObsReset() command. ObsReset command is inherited from BaseCommand. Command to reset the Csp Subarray and bring it to its RESETTING state."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current ... | stack_v2_sparse_classes_36k_train_027879 | 4,780 | permissive | [
{
"docstring": "Checks whether this command is allowed to be run in current device state :return: True if this command is allowed to be run in current device state :rtype: boolean :raises: DevFailed if this command is not allowed to be run in current device state",
"name": "check_allowed",
"signature": ... | 3 | stack_v2_sparse_classes_30k_train_000913 | Implement the Python class `ObsResetCommand` described below.
Class description:
A class for CSPSubarrayLeafNode's ObsReset() command. ObsReset command is inherited from BaseCommand. Command to reset the Csp Subarray and bring it to its RESETTING state.
Method signatures and docstrings:
- def check_allowed(self): Che... | Implement the Python class `ObsResetCommand` described below.
Class description:
A class for CSPSubarrayLeafNode's ObsReset() command. ObsReset command is inherited from BaseCommand. Command to reset the Csp Subarray and bring it to its RESETTING state.
Method signatures and docstrings:
- def check_allowed(self): Che... | 7ee65a9c8dada9b28893144b372a398bd0646195 | <|skeleton|>
class ObsResetCommand:
"""A class for CSPSubarrayLeafNode's ObsReset() command. ObsReset command is inherited from BaseCommand. Command to reset the Csp Subarray and bring it to its RESETTING state."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObsResetCommand:
"""A class for CSPSubarrayLeafNode's ObsReset() command. ObsReset command is inherited from BaseCommand. Command to reset the Csp Subarray and bring it to its RESETTING state."""
def check_allowed(self):
"""Checks whether this command is allowed to be run in current device state ... | the_stack_v2_python_sparse | temp_src/ska_tmc_cspsubarrayleafnode_mid/obsreset_command.py | ska-telescope/tmc-prototype | train | 4 |
a9fa36ae5eab3868b96042f88178ed764c70450a | [
"body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A', 'startTime': '20181010' + '06000000', 'endTime': '20181023' + '06000000'}\na = api_v1_analysis_pre_security_passrate(body_1)\ndict_data = json.loads(a)\nself.assertNotEqual(dict_data['results'][0]['num'], 0)",
"body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A'... | <|body_start_0|>
body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A', 'startTime': '20181010' + '06000000', 'endTime': '20181023' + '06000000'}
a = api_v1_analysis_pre_security_passrate(body_1)
dict_data = json.loads(a)
self.assertNotEqual(dict_data['results'][0]['num'], 0)
<|end_body_0|>... | 预安检通过率接口测试回归 | TestApiAnalysisPreSecurityPassRate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestApiAnalysisPreSecurityPassRate:
"""预安检通过率接口测试回归"""
def test_01(self):
"""查询通过率"""
<|body_0|>
def test_02(self):
"""不在当前时间不能查出来"""
<|body_1|>
def test_03(self):
"""区域通道不存在时不能查询相关信息"""
<|body_2|>
def test_04(self):
"""验... | stack_v2_sparse_classes_36k_train_027880 | 2,178 | no_license | [
{
"docstring": "查询通过率",
"name": "test_01",
"signature": "def test_01(self)"
},
{
"docstring": "不在当前时间不能查出来",
"name": "test_02",
"signature": "def test_02(self)"
},
{
"docstring": "区域通道不存在时不能查询相关信息",
"name": "test_03",
"signature": "def test_03(self)"
},
{
"docstri... | 4 | stack_v2_sparse_classes_30k_train_000767 | Implement the Python class `TestApiAnalysisPreSecurityPassRate` described below.
Class description:
预安检通过率接口测试回归
Method signatures and docstrings:
- def test_01(self): 查询通过率
- def test_02(self): 不在当前时间不能查出来
- def test_03(self): 区域通道不存在时不能查询相关信息
- def test_04(self): 验证服务器响应时间小于1S | Implement the Python class `TestApiAnalysisPreSecurityPassRate` described below.
Class description:
预安检通过率接口测试回归
Method signatures and docstrings:
- def test_01(self): 查询通过率
- def test_02(self): 不在当前时间不能查出来
- def test_03(self): 区域通道不存在时不能查询相关信息
- def test_04(self): 验证服务器响应时间小于1S
<|skeleton|>
class TestApiAnalysisPre... | aa0749f4a237ee76a61579dc5984635a7127a631 | <|skeleton|>
class TestApiAnalysisPreSecurityPassRate:
"""预安检通过率接口测试回归"""
def test_01(self):
"""查询通过率"""
<|body_0|>
def test_02(self):
"""不在当前时间不能查出来"""
<|body_1|>
def test_03(self):
"""区域通道不存在时不能查询相关信息"""
<|body_2|>
def test_04(self):
"""验... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestApiAnalysisPreSecurityPassRate:
"""预安检通过率接口测试回归"""
def test_01(self):
"""查询通过率"""
body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A', 'startTime': '20181010' + '06000000', 'endTime': '20181023' + '06000000'}
a = api_v1_analysis_pre_security_passrate(body_1)
dict_data =... | the_stack_v2_python_sparse | Airport/Auto_return/TestCase/test_data_platform_082.py | jingshiyue/zhongkeyuan_workspace | train | 0 |
8918786f098a26e9888ecc5be3afe37bf6bffb34 | [
"self.app_id = 'my-app'\nos.environ['APPLICATION_ID'] = self.app_id\nself.datastore_stub = datastore_file_stub.DatastoreFileStub(self.app_id, None)\nself.ResetApiProxyStubMap()\napiproxy_stub_map.apiproxy.RegisterStub('datastore_v3', self.datastore_stub)",
"if self.__apiproxy_initialized:\n return\nself.__apip... | <|body_start_0|>
self.app_id = 'my-app'
os.environ['APPLICATION_ID'] = self.app_id
self.datastore_stub = datastore_file_stub.DatastoreFileStub(self.app_id, None)
self.ResetApiProxyStubMap()
apiproxy_stub_map.apiproxy.RegisterStub('datastore_v3', self.datastore_stub)
<|end_body_0|... | Base class for tests that require datastore. | DatastoreTest | [
"BSD-3-Clause",
"Apache-2.0",
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatastoreTest:
"""Base class for tests that require datastore."""
def setUp(self):
"""Set up the datastore."""
<|body_0|>
def ResetApiProxyStubMap(self):
"""Reset the proxy stub-map. Args: force: When True, always reset the stubs regardless of their status. Must ... | stack_v2_sparse_classes_36k_train_027881 | 2,277 | permissive | [
{
"docstring": "Set up the datastore.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Reset the proxy stub-map. Args: force: When True, always reset the stubs regardless of their status. Must be called before stubs can be configured. Every time a new test is created, it is n... | 2 | stack_v2_sparse_classes_30k_train_005243 | Implement the Python class `DatastoreTest` described below.
Class description:
Base class for tests that require datastore.
Method signatures and docstrings:
- def setUp(self): Set up the datastore.
- def ResetApiProxyStubMap(self): Reset the proxy stub-map. Args: force: When True, always reset the stubs regardless o... | Implement the Python class `DatastoreTest` described below.
Class description:
Base class for tests that require datastore.
Method signatures and docstrings:
- def setUp(self): Set up the datastore.
- def ResetApiProxyStubMap(self): Reset the proxy stub-map. Args: force: When True, always reset the stubs regardless o... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class DatastoreTest:
"""Base class for tests that require datastore."""
def setUp(self):
"""Set up the datastore."""
<|body_0|>
def ResetApiProxyStubMap(self):
"""Reset the proxy stub-map. Args: force: When True, always reset the stubs regardless of their status. Must ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatastoreTest:
"""Base class for tests that require datastore."""
def setUp(self):
"""Set up the datastore."""
self.app_id = 'my-app'
os.environ['APPLICATION_ID'] = self.app_id
self.datastore_stub = datastore_file_stub.DatastoreFileStub(self.app_id, None)
self.Rese... | the_stack_v2_python_sparse | third_party/catapult/third_party/gsutil/third_party/protorpc/demos/tunes_db/server/datastore_test_util.py | metux/chromium-suckless | train | 5 |
fb1200c85ac9ab4177dbb59360d3939337dfb76d | [
"row_num = len(array)\nfor i in range(row_num):\n col_num = len(array[i])\n for j in range(col_num):\n if array[i][j] == target:\n return True\nreturn False",
"row_num = 0\ncol_num = len(array[0]) - 1\nrow_count = len(array)\nwhile row_num < row_count and col_num >= 0:\n val = array[row... | <|body_start_0|>
row_num = len(array)
for i in range(row_num):
col_num = len(array[i])
for j in range(col_num):
if array[i][j] == target:
return True
return False
<|end_body_0|>
<|body_start_1|>
row_num = 0
col_num = le... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def Find_1(self, target, array):
"""方法一：常规扫描整个二维数组。时间复杂度为O(n*m) 行数*列数，可视为O(n^2) 没有用到 每行从左到右递增、每列从上到下递增 的特性"""
<|body_0|>
def Find_2(self, target, array):
"""方法二：利用 每行从左到右递增、每列从上到下递增 的特性，减少扫描、比较次数。时间复杂度为O(n)"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_027882 | 1,457 | no_license | [
{
"docstring": "方法一：常规扫描整个二维数组。时间复杂度为O(n*m) 行数*列数，可视为O(n^2) 没有用到 每行从左到右递增、每列从上到下递增 的特性",
"name": "Find_1",
"signature": "def Find_1(self, target, array)"
},
{
"docstring": "方法二：利用 每行从左到右递增、每列从上到下递增 的特性，减少扫描、比较次数。时间复杂度为O(n)",
"name": "Find_2",
"signature": "def Find_2(self, target, array)... | 2 | stack_v2_sparse_classes_30k_train_020830 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def Find_1(self, target, array): 方法一：常规扫描整个二维数组。时间复杂度为O(n*m) 行数*列数，可视为O(n^2) 没有用到 每行从左到右递增、每列从上到下递增 的特性
- def Find_2(self, target, array): 方法二：利用 每行从左到右递增、每列从上到下递增 的特性，减少扫描、比较次数。... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def Find_1(self, target, array): 方法一：常规扫描整个二维数组。时间复杂度为O(n*m) 行数*列数，可视为O(n^2) 没有用到 每行从左到右递增、每列从上到下递增 的特性
- def Find_2(self, target, array): 方法二：利用 每行从左到右递增、每列从上到下递增 的特性，减少扫描、比较次数。... | 6ee455019ae2d9adeea9fc3876f5da4297320715 | <|skeleton|>
class Solution:
def Find_1(self, target, array):
"""方法一：常规扫描整个二维数组。时间复杂度为O(n*m) 行数*列数，可视为O(n^2) 没有用到 每行从左到右递增、每列从上到下递增 的特性"""
<|body_0|>
def Find_2(self, target, array):
"""方法二：利用 每行从左到右递增、每列从上到下递增 的特性，减少扫描、比较次数。时间复杂度为O(n)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def Find_1(self, target, array):
"""方法一：常规扫描整个二维数组。时间复杂度为O(n*m) 行数*列数，可视为O(n^2) 没有用到 每行从左到右递增、每列从上到下递增 的特性"""
row_num = len(array)
for i in range(row_num):
col_num = len(array[i])
for j in range(col_num):
if array[i][j] == target:
... | the_stack_v2_python_sparse | p1_array/a1_Find.py | atm1992/nowcoder_offer_in_Python27 | train | 0 | |
9a2e3ec46e565c30ec121349ae78b06f15b3e245 | [
"key = ndb.Key(models.InstanceGroupManager, 'fake-key')\ninstance_group_managers.delete(key)\nself.failIf(key.get())",
"def json_request(url, *_args, **_kwargs):\n return {'targetLink': url}\nself.mock(instance_group_managers.net, 'json_request', json_request)\nkey = models.InstanceGroupManager(key=instance_gr... | <|body_start_0|>
key = ndb.Key(models.InstanceGroupManager, 'fake-key')
instance_group_managers.delete(key)
self.failIf(key.get())
<|end_body_0|>
<|body_start_1|>
def json_request(url, *_args, **_kwargs):
return {'targetLink': url}
self.mock(instance_group_managers.n... | Tests for instance_group_managers.delete. | DeleteTest | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeleteTest:
"""Tests for instance_group_managers.delete."""
def test_entity_doesnt_exist(self):
"""Ensures nothing happens when the entity doesn't exist."""
<|body_0|>
def test_deletes(self):
"""Ensures an instance group manager is deleted."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_027883 | 34,211 | permissive | [
{
"docstring": "Ensures nothing happens when the entity doesn't exist.",
"name": "test_entity_doesnt_exist",
"signature": "def test_entity_doesnt_exist(self)"
},
{
"docstring": "Ensures an instance group manager is deleted.",
"name": "test_deletes",
"signature": "def test_deletes(self)"
... | 6 | null | Implement the Python class `DeleteTest` described below.
Class description:
Tests for instance_group_managers.delete.
Method signatures and docstrings:
- def test_entity_doesnt_exist(self): Ensures nothing happens when the entity doesn't exist.
- def test_deletes(self): Ensures an instance group manager is deleted.
-... | Implement the Python class `DeleteTest` described below.
Class description:
Tests for instance_group_managers.delete.
Method signatures and docstrings:
- def test_entity_doesnt_exist(self): Ensures nothing happens when the entity doesn't exist.
- def test_deletes(self): Ensures an instance group manager is deleted.
-... | 0a4fdfc25f89833026be6a8b29c0a27b8f3c5fc4 | <|skeleton|>
class DeleteTest:
"""Tests for instance_group_managers.delete."""
def test_entity_doesnt_exist(self):
"""Ensures nothing happens when the entity doesn't exist."""
<|body_0|>
def test_deletes(self):
"""Ensures an instance group manager is deleted."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeleteTest:
"""Tests for instance_group_managers.delete."""
def test_entity_doesnt_exist(self):
"""Ensures nothing happens when the entity doesn't exist."""
key = ndb.Key(models.InstanceGroupManager, 'fake-key')
instance_group_managers.delete(key)
self.failIf(key.get())
... | the_stack_v2_python_sparse | appengine/gce-backend/instance_group_managers_test.py | Swift1313/luci-py | train | 0 |
a3f827b6e43308c94dad6a568ed8c7c6376a1f09 | [
"processedString = []\nfor c in s:\n if c.isalnum():\n processedString.append(c.lower())\nl = len(processedString)\nfor i in range(0, l // 2):\n if processedString[i] != processedString[l - 1 - i]:\n return False\nreturn True",
"import re\ns = s.lower()\ns1 = re.findall('[a-z0-9]', s)\ns2 = ''... | <|body_start_0|>
processedString = []
for c in s:
if c.isalnum():
processedString.append(c.lower())
l = len(processedString)
for i in range(0, l // 2):
if processedString[i] != processedString[l - 1 - i]:
return False
return... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isPalindrome2(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
processedString = []
for c in s:
if c.isalnu... | stack_v2_sparse_classes_36k_train_027884 | 902 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "isPalindrome2",
"signature": "def isPalindrome2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, s): :type s: str :rtype: bool
- def isPalindrome2(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, s): :type s: str :rtype: bool
- def isPalindrome2(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def isPalindrome(self, s):
... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isPalindrome2(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
processedString = []
for c in s:
if c.isalnum():
processedString.append(c.lower())
l = len(processedString)
for i in range(0, l // 2):
if processedString[i] != p... | the_stack_v2_python_sparse | code/125#Valid Palindrome.py | EachenKuang/LeetCode | train | 28 | |
e027a9183c2c149dd94aeeaa48900e5a483960bd | [
"super().__init__()\nself._img_size = config.get('img_size')\nself._input_channel = config.get('input_channel')\nself._filter_sizes = config.get('filter_size')\nself._kernel_size = config.get('kernel_size')\nself._padding = padding\nself._stride = stride\nself._dilation = dilation\nself._encoder_maxpool_count = con... | <|body_start_0|>
super().__init__()
self._img_size = config.get('img_size')
self._input_channel = config.get('input_channel')
self._filter_sizes = config.get('filter_size')
self._kernel_size = config.get('kernel_size')
self._padding = padding
self._stride = stride... | Deterministic_Conv_Encoder | Deterministic_Conv_Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Deterministic_Conv_Encoder:
"""Deterministic_Conv_Encoder"""
def __init__(self, config, padding=0, stride=2, dilation=1):
"""NP"""
<|body_0|>
def forward(self, inputs):
"""Args: input : imamges (num_tasks, n_way, k_shot, filter_size img_size, img_size) Return: ou... | stack_v2_sparse_classes_36k_train_027885 | 18,202 | no_license | [
{
"docstring": "NP",
"name": "__init__",
"signature": "def __init__(self, config, padding=0, stride=2, dilation=1)"
},
{
"docstring": "Args: input : imamges (num_tasks, n_way, k_shot, filter_size img_size, img_size) Return: output :",
"name": "forward",
"signature": "def forward(self, in... | 2 | stack_v2_sparse_classes_30k_train_017083 | Implement the Python class `Deterministic_Conv_Encoder` described below.
Class description:
Deterministic_Conv_Encoder
Method signatures and docstrings:
- def __init__(self, config, padding=0, stride=2, dilation=1): NP
- def forward(self, inputs): Args: input : imamges (num_tasks, n_way, k_shot, filter_size img_size,... | Implement the Python class `Deterministic_Conv_Encoder` described below.
Class description:
Deterministic_Conv_Encoder
Method signatures and docstrings:
- def __init__(self, config, padding=0, stride=2, dilation=1): NP
- def forward(self, inputs): Args: input : imamges (num_tasks, n_way, k_shot, filter_size img_size,... | c7e1bfb49ebaec6937ed7b186689227f95a43e0f | <|skeleton|>
class Deterministic_Conv_Encoder:
"""Deterministic_Conv_Encoder"""
def __init__(self, config, padding=0, stride=2, dilation=1):
"""NP"""
<|body_0|>
def forward(self, inputs):
"""Args: input : imamges (num_tasks, n_way, k_shot, filter_size img_size, img_size) Return: ou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Deterministic_Conv_Encoder:
"""Deterministic_Conv_Encoder"""
def __init__(self, config, padding=0, stride=2, dilation=1):
"""NP"""
super().__init__()
self._img_size = config.get('img_size')
self._input_channel = config.get('input_channel')
self._filter_sizes = conf... | the_stack_v2_python_sparse | model/MAML/Part/encoder.py | MingyuKim87/MLwM | train | 0 |
6ba4c6b4610048c9b939a6634a75709bf7df7ca5 | [
"self.tfrecord_paths = tfrecord_paths\nself.num_shards = len(self.tfrecord_paths)\nself.tfrecord_paths_tensor = tf.constant(self.tfrecord_paths)\nself.image_width = image_width\nself.image_channels = image_channels\nif seperate_background_channel:\n mask_channels += 1\nself.mask_channels = mask_channels\nprint('... | <|body_start_0|>
self.tfrecord_paths = tfrecord_paths
self.num_shards = len(self.tfrecord_paths)
self.tfrecord_paths_tensor = tf.constant(self.tfrecord_paths)
self.image_width = image_width
self.image_channels = image_channels
if seperate_background_channel:
m... | TFRecordSegmentationDataset | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFRecordSegmentationDataset:
def __init__(self, tfrecord_paths: List[str], image_width: int, image_channels=3, mask_channels=1, seed=0, augmenter: Optional[Augmenter]=None, seperate_background_channel: bool=True):
"""Image segmentation tf.data.Dataset constructor for batching from tfreco... | stack_v2_sparse_classes_36k_train_027886 | 8,998 | permissive | [
{
"docstring": "Image segmentation tf.data.Dataset constructor for batching from tfrecords. Args: tfrecord_paths: list of paths to tfrecords image_width: side of images and masks (all images and masks assumed to be square and of the same size) image_channels: Int number of channels in the images. mask_channels:... | 3 | stack_v2_sparse_classes_30k_train_010231 | Implement the Python class `TFRecordSegmentationDataset` described below.
Class description:
Implement the TFRecordSegmentationDataset class.
Method signatures and docstrings:
- def __init__(self, tfrecord_paths: List[str], image_width: int, image_channels=3, mask_channels=1, seed=0, augmenter: Optional[Augmenter]=No... | Implement the Python class `TFRecordSegmentationDataset` described below.
Class description:
Implement the TFRecordSegmentationDataset class.
Method signatures and docstrings:
- def __init__(self, tfrecord_paths: List[str], image_width: int, image_channels=3, mask_channels=1, seed=0, augmenter: Optional[Augmenter]=No... | f40352e734f77609bcd5c4ad330ea73a897a217d | <|skeleton|>
class TFRecordSegmentationDataset:
def __init__(self, tfrecord_paths: List[str], image_width: int, image_channels=3, mask_channels=1, seed=0, augmenter: Optional[Augmenter]=None, seperate_background_channel: bool=True):
"""Image segmentation tf.data.Dataset constructor for batching from tfreco... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TFRecordSegmentationDataset:
def __init__(self, tfrecord_paths: List[str], image_width: int, image_channels=3, mask_channels=1, seed=0, augmenter: Optional[Augmenter]=None, seperate_background_channel: bool=True):
"""Image segmentation tf.data.Dataset constructor for batching from tfrecords. Args: tfr... | the_stack_v2_python_sparse | joint_train/data/input_fn.py | qilicun/mliis | train | 0 | |
e94f0719a87a3fea23ece170d9430681caaa266c | [
"if grid == []:\n return 0\nif len(grid) > 0:\n parent = [-1] * (len(grid) * len(grid[0]))\nchecks = {}\nfor row in range(len(grid)):\n for col in range(len(grid[row])):\n if grid[row][col] == 1:\n if row - 1 >= 0 and grid[row - 1][col] == 1:\n rParent = self.find(parent, (... | <|body_start_0|>
if grid == []:
return 0
if len(grid) > 0:
parent = [-1] * (len(grid) * len(grid[0]))
checks = {}
for row in range(len(grid)):
for col in range(len(grid[row])):
if grid[row][col] == 1:
if row - 1 >= 0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int if it is a one check all four neighbors and if it is a one then put in subset"""
<|body_0|>
def find(self, parent, node):
""":type parent: List[] :rtype: int"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_027887 | 2,057 | no_license | [
{
"docstring": ":type grid: List[List[str]] :rtype: int if it is a one check all four neighbors and if it is a one then put in subset",
"name": "numIslands",
"signature": "def numIslands(self, grid)"
},
{
"docstring": ":type parent: List[] :rtype: int",
"name": "find",
"signature": "def ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid): :type grid: List[List[str]] :rtype: int if it is a one check all four neighbors and if it is a one then put in subset
- def find(self, parent, node): ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid): :type grid: List[List[str]] :rtype: int if it is a one check all four neighbors and if it is a one then put in subset
- def find(self, parent, node): ... | d5b3c659e6617853464c57819c1f04828bb202ad | <|skeleton|>
class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int if it is a one check all four neighbors and if it is a one then put in subset"""
<|body_0|>
def find(self, parent, node):
""":type parent: List[] :rtype: int"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int if it is a one check all four neighbors and if it is a one then put in subset"""
if grid == []:
return 0
if len(grid) > 0:
parent = [-1] * (len(grid) * len(grid[0]))
checks ... | the_stack_v2_python_sparse | unionFind/numberOfIslands.py | davidyip50/WallBreakers | train | 0 | |
522e38d8d8e209522f73df52b27263cd65318ac0 | [
"for i in range(int(c ** 0.5) + 1):\n j = int((c - i * i) ** 0.5)\n if i * i + j * j == c:\n return True\nreturn False",
"i = 2\nwhile i * i <= c:\n if c % i == 0:\n cnt = 0\n while c % i == 0:\n c //= i\n cnt += 1\n if i % 4 == 3 and cnt % 2 != 0:\n ... | <|body_start_0|>
for i in range(int(c ** 0.5) + 1):
j = int((c - i * i) ** 0.5)
if i * i + j * j == c:
return True
return False
<|end_body_0|>
<|body_start_1|>
i = 2
while i * i <= c:
if c % i == 0:
cnt = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def judgeSquareSum_MK1(self, c: int) -> bool:
"""Time complexity: O(√clgc). Space complexity: O(1)."""
<|body_0|>
def judgeSquareSum_MK2(self, c: int) -> bool:
"""Fermat Theorem: Any positive number n is expressible as a sum of two squares if and only if th... | stack_v2_sparse_classes_36k_train_027888 | 985 | no_license | [
{
"docstring": "Time complexity: O(√clgc). Space complexity: O(1).",
"name": "judgeSquareSum_MK1",
"signature": "def judgeSquareSum_MK1(self, c: int) -> bool"
},
{
"docstring": "Fermat Theorem: Any positive number n is expressible as a sum of two squares if and only if the prime factorization of... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def judgeSquareSum_MK1(self, c: int) -> bool: Time complexity: O(√clgc). Space complexity: O(1).
- def judgeSquareSum_MK2(self, c: int) -> bool: Fermat Theorem: Any positive numb... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def judgeSquareSum_MK1(self, c: int) -> bool: Time complexity: O(√clgc). Space complexity: O(1).
- def judgeSquareSum_MK2(self, c: int) -> bool: Fermat Theorem: Any positive numb... | d7ba416d22becfa8f2a2ae4eee04c86617cd9332 | <|skeleton|>
class Solution:
def judgeSquareSum_MK1(self, c: int) -> bool:
"""Time complexity: O(√clgc). Space complexity: O(1)."""
<|body_0|>
def judgeSquareSum_MK2(self, c: int) -> bool:
"""Fermat Theorem: Any positive number n is expressible as a sum of two squares if and only if th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def judgeSquareSum_MK1(self, c: int) -> bool:
"""Time complexity: O(√clgc). Space complexity: O(1)."""
for i in range(int(c ** 0.5) + 1):
j = int((c - i * i) ** 0.5)
if i * i + j * j == c:
return True
return False
def judgeSquareSu... | the_stack_v2_python_sparse | 0633. Sum of Square Numbers/Solution.py | faterazer/LeetCode | train | 4 | |
2a793dad8a047ed5bf32b4ccfa5bc9dc0f6441e3 | [
"if not preorder or not inorder:\n return None\nval = preorder.pop(0)\nroot_node = TreeNode(val)\nroot_index = inorder.index(val)\nleft_pre = preorder[:root_index]\nleft_in = inorder[:root_index]\nright_pre = preorder[root_index:]\nright_in = inorder[root_index + 1:]\nroot_node.left = self.buildTree(left_pre, le... | <|body_start_0|>
if not preorder or not inorder:
return None
val = preorder.pop(0)
root_node = TreeNode(val)
root_index = inorder.index(val)
left_pre = preorder[:root_index]
left_in = inorder[:root_index]
right_pre = preorder[root_index:]
right... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
"""先确定根节点：根节点是前序遍历的第一个元素 再在中序遍历中确定左右子树的个数：根节点左边是左子树，根节点右边是右子树 递归这个过程 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree1(self, preorder, inorder):
"""力扣官方解法 :type preorder:... | stack_v2_sparse_classes_36k_train_027889 | 3,589 | no_license | [
{
"docstring": "先确定根节点：根节点是前序遍历的第一个元素 再在中序遍历中确定左右子树的个数：根节点左边是左子树，根节点右边是右子树 递归这个过程 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, preorder, inorder)"
},
{
"docstring": "力扣官方解法 :type preorder: List[int] :type inorder: Li... | 2 | stack_v2_sparse_classes_30k_train_003041 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): 先确定根节点：根节点是前序遍历的第一个元素 再在中序遍历中确定左右子树的个数：根节点左边是左子树，根节点右边是右子树 递归这个过程 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- de... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): 先确定根节点：根节点是前序遍历的第一个元素 再在中序遍历中确定左右子树的个数：根节点左边是左子树，根节点右边是右子树 递归这个过程 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- de... | a3a1556abc5adb9325de54d64f9814e64b96db0f | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
"""先确定根节点：根节点是前序遍历的第一个元素 再在中序遍历中确定左右子树的个数：根节点左边是左子树，根节点右边是右子树 递归这个过程 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree1(self, preorder, inorder):
"""力扣官方解法 :type preorder:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def buildTree(self, preorder, inorder):
"""先确定根节点：根节点是前序遍历的第一个元素 再在中序遍历中确定左右子树的个数：根节点左边是左子树，根节点右边是右子树 递归这个过程 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
if not preorder or not inorder:
return None
val = preorder.pop(0)
root_node ... | the_stack_v2_python_sparse | leetcode/tree/buildTree.py | BigerWANG/geek_algorithm | train | 0 | |
ed4febb5ee9c4cbb8787bbf48a3b01bed43c3ba1 | [
"if Config.instance is None:\n Config.instance = Config.__Config()\nreturn Config.instance",
"Config.instance = Config.__Config(path)\nif not os.path.exists(path + Config.CONFIG_NAME):\n print('No config file found in ' + path)\n exit(1)"
] | <|body_start_0|>
if Config.instance is None:
Config.instance = Config.__Config()
return Config.instance
<|end_body_0|>
<|body_start_1|>
Config.instance = Config.__Config(path)
if not os.path.exists(path + Config.CONFIG_NAME):
print('No config file found in ' + pa... | Config | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
def get_instance():
"""implementation of singleton design pattern"""
<|body_0|>
def set_instance(path):
"""implementation of singleton design pattern @param path String where config should be stored"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_027890 | 3,889 | permissive | [
{
"docstring": "implementation of singleton design pattern",
"name": "get_instance",
"signature": "def get_instance()"
},
{
"docstring": "implementation of singleton design pattern @param path String where config should be stored",
"name": "set_instance",
"signature": "def set_instance(p... | 2 | stack_v2_sparse_classes_30k_train_007003 | Implement the Python class `Config` described below.
Class description:
Implement the Config class.
Method signatures and docstrings:
- def get_instance(): implementation of singleton design pattern
- def set_instance(path): implementation of singleton design pattern @param path String where config should be stored | Implement the Python class `Config` described below.
Class description:
Implement the Config class.
Method signatures and docstrings:
- def get_instance(): implementation of singleton design pattern
- def set_instance(path): implementation of singleton design pattern @param path String where config should be stored
... | 701d935dd215bfd9a4810a4430973b33fecec257 | <|skeleton|>
class Config:
def get_instance():
"""implementation of singleton design pattern"""
<|body_0|>
def set_instance(path):
"""implementation of singleton design pattern @param path String where config should be stored"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Config:
def get_instance():
"""implementation of singleton design pattern"""
if Config.instance is None:
Config.instance = Config.__Config()
return Config.instance
def set_instance(path):
"""implementation of singleton design pattern @param path String where co... | the_stack_v2_python_sparse | Kaspa/config.py | karim-awad/kaspa | train | 0 | |
8b090c85807616328655677f860db8276c8c078e | [
"super().__init__(name=name)\nself._loss = loss if loss is not None else tf.keras.losses.BinaryCrossentropy()\nself._ranking_metrics = metrics or []\nself._prediction_metrics = prediction_metrics or []\nself._label_metrics = label_metrics or []\nself._loss_metrics = loss_metrics or []",
"loss = self._loss(y_true=... | <|body_start_0|>
super().__init__(name=name)
self._loss = loss if loss is not None else tf.keras.losses.BinaryCrossentropy()
self._ranking_metrics = metrics or []
self._prediction_metrics = prediction_metrics or []
self._label_metrics = label_metrics or []
self._loss_metr... | A ranking task. Recommender systems are often composed of two components: - a retrieval model, retrieving O(thousands) candidates from a corpus of O(millions) candidates. - a ranker model, scoring the candidates retrieved by the retrieval model to return a ranked shortlist of a few dozen candidates. This task helps wit... | Ranking | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ranking:
"""A ranking task. Recommender systems are often composed of two components: - a retrieval model, retrieving O(thousands) candidates from a corpus of O(millions) candidates. - a ranker model, scoring the candidates retrieved by the retrieval model to return a ranked shortlist of a few do... | stack_v2_sparse_classes_36k_train_027891 | 4,074 | permissive | [
{
"docstring": "Initializes the task. Args: loss: Loss function. Defaults to BinaryCrossentropy. metrics: List of Keras metrics to be evaluated. prediction_metrics: List of Keras metrics used to summarize the predictions. label_metrics: List of Keras metrics used to summarize the labels. loss_metrics: List of K... | 2 | stack_v2_sparse_classes_30k_train_009303 | Implement the Python class `Ranking` described below.
Class description:
A ranking task. Recommender systems are often composed of two components: - a retrieval model, retrieving O(thousands) candidates from a corpus of O(millions) candidates. - a ranker model, scoring the candidates retrieved by the retrieval model t... | Implement the Python class `Ranking` described below.
Class description:
A ranking task. Recommender systems are often composed of two components: - a retrieval model, retrieving O(thousands) candidates from a corpus of O(millions) candidates. - a ranker model, scoring the candidates retrieved by the retrieval model t... | f4f42c1a183a262539e21f5ab8d25f0dc3e5621d | <|skeleton|>
class Ranking:
"""A ranking task. Recommender systems are often composed of two components: - a retrieval model, retrieving O(thousands) candidates from a corpus of O(millions) candidates. - a ranker model, scoring the candidates retrieved by the retrieval model to return a ranked shortlist of a few do... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ranking:
"""A ranking task. Recommender systems are often composed of two components: - a retrieval model, retrieving O(thousands) candidates from a corpus of O(millions) candidates. - a ranker model, scoring the candidates retrieved by the retrieval model to return a ranked shortlist of a few dozen candidate... | the_stack_v2_python_sparse | tensorflow_recommenders/tasks/ranking.py | tensorflow/recommenders | train | 1,666 |
cefae31dd48354d56cbb8ece4e781e777e347f05 | [
"self.g = tf.Graph()\nwith self.g.as_default():\n self.session = tf.Session()\n model = load_cnn(self.session, modelname, run)\n self.params = model.params\n image_shape = [1] + model.params.image_dim\n optim = optimizer(lr)\n self.input_placeholder = tf.placeholder(tf.float32, shape=image_shape, ... | <|body_start_0|>
self.g = tf.Graph()
with self.g.as_default():
self.session = tf.Session()
model = load_cnn(self.session, modelname, run)
self.params = model.params
image_shape = [1] + model.params.image_dim
optim = optimizer(lr)
se... | Class for creating fooling images against a CNNClassifier model | FoolingModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FoolingModel:
"""Class for creating fooling images against a CNNClassifier model"""
def __init__(self, modelname, run=None, min_valid=0.0, max_valid=1.0, lr=0.0005, optimizer=tf.train.GradientDescentOptimizer):
"""Defines the operations for creating fooling images based on the input ... | stack_v2_sparse_classes_36k_train_027892 | 8,339 | permissive | [
{
"docstring": "Defines the operations for creating fooling images based on the input model. A 'fooling' variable-scope is used so that optimizers which create variables, such as Adam, can have those variables accessed and re-initialized separately from the main model. Inputs: - modelname: name used in the CNN ... | 3 | stack_v2_sparse_classes_30k_train_017720 | Implement the Python class `FoolingModel` described below.
Class description:
Class for creating fooling images against a CNNClassifier model
Method signatures and docstrings:
- def __init__(self, modelname, run=None, min_valid=0.0, max_valid=1.0, lr=0.0005, optimizer=tf.train.GradientDescentOptimizer): Defines the o... | Implement the Python class `FoolingModel` described below.
Class description:
Class for creating fooling images against a CNNClassifier model
Method signatures and docstrings:
- def __init__(self, modelname, run=None, min_valid=0.0, max_valid=1.0, lr=0.0005, optimizer=tf.train.GradientDescentOptimizer): Defines the o... | 24c354db961e5e620557c8f4d4d960bea05f3f7d | <|skeleton|>
class FoolingModel:
"""Class for creating fooling images against a CNNClassifier model"""
def __init__(self, modelname, run=None, min_valid=0.0, max_valid=1.0, lr=0.0005, optimizer=tf.train.GradientDescentOptimizer):
"""Defines the operations for creating fooling images based on the input ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FoolingModel:
"""Class for creating fooling images against a CNNClassifier model"""
def __init__(self, modelname, run=None, min_valid=0.0, max_valid=1.0, lr=0.0005, optimizer=tf.train.GradientDescentOptimizer):
"""Defines the operations for creating fooling images based on the input model. A 'foo... | the_stack_v2_python_sparse | fooling_images.py | vogelta/vogelta.github.io | train | 0 |
98d1d8a708a1b16ac650b4e544af3495781d7e19 | [
"tenant_id = self.request.user.tenant_id\nipsecsiteconnections = api.vpn.ipsecsiteconnection_list(request, tenant_id=tenant_id)\nreturn {'items': [u.to_dict() for u in ipsecsiteconnections]}",
"new_ipsecsiteconnection = api.vpn.ipsecsiteconnection_create(request, **request.DATA)\ni = api.vpn.ipsecsiteconnection_g... | <|body_start_0|>
tenant_id = self.request.user.tenant_id
ipsecsiteconnections = api.vpn.ipsecsiteconnection_list(request, tenant_id=tenant_id)
return {'items': [u.to_dict() for u in ipsecsiteconnections]}
<|end_body_0|>
<|body_start_1|>
new_ipsecsiteconnection = api.vpn.ipsecsiteconnect... | API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html | IPSecSiteConnections | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IPSecSiteConnections:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of ikepolicies for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_027893 | 11,907 | permissive | [
{
"docstring": "Get a list of ikepolicies for a project The listing result is an object with property \"items\". Each item is a network.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create IPSecSiteConnection :param request: request context :param name: name for IPSe... | 2 | stack_v2_sparse_classes_30k_train_017054 | Implement the Python class `IPSecSiteConnections` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of ikepolicies for a project The listing result is an object with property "it... | Implement the Python class `IPSecSiteConnections` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of ikepolicies for a project The listing result is an object with property "it... | 9524f1952461c83db485d5d1702c350b158d7ce0 | <|skeleton|>
class IPSecSiteConnections:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of ikepolicies for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IPSecSiteConnections:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of ikepolicies for a project The listing result is an object with property "items". Each item is a network."""
tenant_id = self.request.user... | the_stack_v2_python_sparse | easystack_dashboard/api/rest/vpn.py | oksbsb/horizon-acc | train | 0 |
5a9bc394abfec97c2ed61fdca423b0a26c146d42 | [
"threading.Thread.__init__(self)\nself.taskBuffer = taskBuffer\nif log_stream:\n self.log_stream = log_stream\nelse:\n self.log_stream = _logger\nif hasattr(panda_config, 'CRIC_URL_SCHEDCONFIG'):\n self.CRIC_URL_TAGS = panda_config.CRIC_URL_TAGS\nelse:\n self.CRIC_URL_TAGS = 'https://atlas-cric.cern.ch/... | <|body_start_0|>
threading.Thread.__init__(self)
self.taskBuffer = taskBuffer
if log_stream:
self.log_stream = log_stream
else:
self.log_stream = _logger
if hasattr(panda_config, 'CRIC_URL_SCHEDCONFIG'):
self.CRIC_URL_TAGS = panda_config.CRIC_U... | Downloads the CRIC tags dump, flattens it out and stores it in the DB, one row per queue | SWTagsDumper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SWTagsDumper:
"""Downloads the CRIC tags dump, flattens it out and stores it in the DB, one row per queue"""
def __init__(self, taskBuffer, log_stream=None):
"""Initialization and configuration"""
<|body_0|>
def run(self):
"""Principal function"""
<|body_... | stack_v2_sparse_classes_36k_train_027894 | 38,097 | permissive | [
{
"docstring": "Initialization and configuration",
"name": "__init__",
"signature": "def __init__(self, taskBuffer, log_stream=None)"
},
{
"docstring": "Principal function",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004128 | Implement the Python class `SWTagsDumper` described below.
Class description:
Downloads the CRIC tags dump, flattens it out and stores it in the DB, one row per queue
Method signatures and docstrings:
- def __init__(self, taskBuffer, log_stream=None): Initialization and configuration
- def run(self): Principal functi... | Implement the Python class `SWTagsDumper` described below.
Class description:
Downloads the CRIC tags dump, flattens it out and stores it in the DB, one row per queue
Method signatures and docstrings:
- def __init__(self, taskBuffer, log_stream=None): Initialization and configuration
- def run(self): Principal functi... | 365a9feb55d493b208e3052428f0b524e63e4178 | <|skeleton|>
class SWTagsDumper:
"""Downloads the CRIC tags dump, flattens it out and stores it in the DB, one row per queue"""
def __init__(self, taskBuffer, log_stream=None):
"""Initialization and configuration"""
<|body_0|>
def run(self):
"""Principal function"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SWTagsDumper:
"""Downloads the CRIC tags dump, flattens it out and stores it in the DB, one row per queue"""
def __init__(self, taskBuffer, log_stream=None):
"""Initialization and configuration"""
threading.Thread.__init__(self)
self.taskBuffer = taskBuffer
if log_stream:
... | the_stack_v2_python_sparse | pandaserver/configurator/Configurator.py | PanDAWMS/panda-server | train | 8 |
feaf07c7c3b3d32682df66b5a78281bf015e3829 | [
"def add(num: int) -> None:\n for i in range(32):\n if not num >> i & 1:\n counter[i] += 1\n\ndef remove(num: int) -> int:\n repay = 0\n for i in range(32):\n if not num >> i & 1:\n if counter[i] == 1:\n repay |= 1 << i\n counter[i] -= 1\n re... | <|body_start_0|>
def add(num: int) -> None:
for i in range(32):
if not num >> i & 1:
counter[i] += 1
def remove(num: int) -> int:
repay = 0
for i in range(32):
if not num >> i & 1:
if counter[i] ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestCombination2(self, candidates: List[int]) -> int:
"""返回按位与结果大于 0 的 最长子数组 利用与运算的单调性 O(n*logA)"""
<|body_0|>
def largestCombination3(self, candidates: List[int]) -> int:
"""返回按位与结果大于 0 的 最长子数组 标记下该位上一个是 0 的位置在哪里 按位分开处理 O(n*logA)"""
<|body_1... | stack_v2_sparse_classes_36k_train_027895 | 3,617 | no_license | [
{
"docstring": "返回按位与结果大于 0 的 最长子数组 利用与运算的单调性 O(n*logA)",
"name": "largestCombination2",
"signature": "def largestCombination2(self, candidates: List[int]) -> int"
},
{
"docstring": "返回按位与结果大于 0 的 最长子数组 标记下该位上一个是 0 的位置在哪里 按位分开处理 O(n*logA)",
"name": "largestCombination3",
"signature": "de... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestCombination2(self, candidates: List[int]) -> int: 返回按位与结果大于 0 的 最长子数组 利用与运算的单调性 O(n*logA)
- def largestCombination3(self, candidates: List[int]) -> int: 返回按位与结果大于 0 的 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestCombination2(self, candidates: List[int]) -> int: 返回按位与结果大于 0 的 最长子数组 利用与运算的单调性 O(n*logA)
- def largestCombination3(self, candidates: List[int]) -> int: 返回按位与结果大于 0 的 ... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def largestCombination2(self, candidates: List[int]) -> int:
"""返回按位与结果大于 0 的 最长子数组 利用与运算的单调性 O(n*logA)"""
<|body_0|>
def largestCombination3(self, candidates: List[int]) -> int:
"""返回按位与结果大于 0 的 最长子数组 标记下该位上一个是 0 的位置在哪里 按位分开处理 O(n*logA)"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largestCombination2(self, candidates: List[int]) -> int:
"""返回按位与结果大于 0 的 最长子数组 利用与运算的单调性 O(n*logA)"""
def add(num: int) -> None:
for i in range(32):
if not num >> i & 1:
counter[i] += 1
def remove(num: int) -> int:
... | the_stack_v2_python_sparse | 21_位运算/按位与/6065. 按位与结果大于零的最长子数组-按位统计.py | 981377660LMT/algorithm-study | train | 225 | |
db21a3b853c6dbd661a00bc2ee6a1ae9393adcb6 | [
"def dfs(n, k, memo):\n if n == 0:\n return 0\n if k == 1:\n return n\n if (n, k) not in memo:\n ans = float('inf')\n for x in range(1, n + 1):\n ans = min(ans, 1 + max(dfs(x - 1, k - 1, memo), dfs(n - x, k, memo)))\n memo[n, k] = ans\n return memo[n, k]\nre... | <|body_start_0|>
def dfs(n, k, memo):
if n == 0:
return 0
if k == 1:
return n
if (n, k) not in memo:
ans = float('inf')
for x in range(1, n + 1):
ans = min(ans, 1 + max(dfs(x - 1, k - 1, memo)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def superEggDrop(self, K: int, N: int) -> int:
"""Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)"""
<|body_0|>
def superEggDrop(self, K: int, N: int) -> int:
... | stack_v2_sparse_classes_36k_train_027896 | 5,857 | no_license | [
{
"docstring": "Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)",
"name": "superEggDrop",
"signature": "def superEggDrop(self, K: int, N: int) -> int"
},
{
"docstring": "The above algorithm got TL... | 5 | stack_v2_sparse_classes_30k_test_000662 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def superEggDrop(self, K: int, N: int) -> int: Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def superEggDrop(self, K: int, N: int) -> int: Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def superEggDrop(self, K: int, N: int) -> int:
"""Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)"""
<|body_0|>
def superEggDrop(self, K: int, N: int) -> int:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def superEggDrop(self, K: int, N: int) -> int:
"""Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)"""
def dfs(n, k, memo):
if n == 0:
return 0
if... | the_stack_v2_python_sparse | Leetcode 0887. Super Egg Drop.py | Chaoran-sjsu/leetcode | train | 0 | |
cd820f5feccd5cba37a2d9b0fdcca63a7cb2dcdb | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | StringFormatterServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringFormatterServicer:
def Upper(self, request, context):
"""makes all chars in string upper case"""
<|body_0|>
def Lower(self, request, context):
"""makes all chars in string lower case"""
<|body_1|>
def Proper(self, request, context):
"""make... | stack_v2_sparse_classes_36k_train_027897 | 2,935 | no_license | [
{
"docstring": "makes all chars in string upper case",
"name": "Upper",
"signature": "def Upper(self, request, context)"
},
{
"docstring": "makes all chars in string lower case",
"name": "Lower",
"signature": "def Lower(self, request, context)"
},
{
"docstring": "makes first char... | 3 | stack_v2_sparse_classes_30k_test_000866 | Implement the Python class `StringFormatterServicer` described below.
Class description:
Implement the StringFormatterServicer class.
Method signatures and docstrings:
- def Upper(self, request, context): makes all chars in string upper case
- def Lower(self, request, context): makes all chars in string lower case
- ... | Implement the Python class `StringFormatterServicer` described below.
Class description:
Implement the StringFormatterServicer class.
Method signatures and docstrings:
- def Upper(self, request, context): makes all chars in string upper case
- def Lower(self, request, context): makes all chars in string lower case
- ... | e08127c22b39cc7d87de1713ca42c98dc3855b7d | <|skeleton|>
class StringFormatterServicer:
def Upper(self, request, context):
"""makes all chars in string upper case"""
<|body_0|>
def Lower(self, request, context):
"""makes all chars in string lower case"""
<|body_1|>
def Proper(self, request, context):
"""make... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StringFormatterServicer:
def Upper(self, request, context):
"""makes all chars in string upper case"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def Lower(self, reques... | the_stack_v2_python_sparse | stringFormatter_grpc/stringFormatter_pb2_grpc.py | vzellmeister/ep_sistemas_distribuidos | train | 0 | |
3890bc3de624292f2203e9910ed70a1b0e1cdf3b | [
"super().__init__(*args, **kwargs)\nself.set_fields_from_dict(['dst_key', 'src_key', 'how_merge'])\nself.fields['how_merge'].required = False",
"form_data = super().clean()\nself.store_fields_in_dict([('dst_key', None), ('src_key', None), ('how_merge', None)])\nif self.workflow.has_data_frame:\n if not form_da... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.set_fields_from_dict(['dst_key', 'src_key', 'how_merge'])
self.fields['how_merge'].required = False
<|end_body_0|>
<|body_start_1|>
form_data = super().clean()
self.store_fields_in_dict([('dst_key', None), ('src_key', None)... | Form to request info for the SQL scheduled upload Three blocks of information are requested: Block 1: Name, description, start -- frequency -- stop times Block 2: Parameters for the SQL connection Block 3: Parameters for the merge: Left/Right column + merge method | ScheduleSQLUploadForm | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScheduleSQLUploadForm:
"""Form to request info for the SQL scheduled upload Three blocks of information are requested: Block 1: Name, description, start -- frequency -- stop times Block 2: Parameters for the SQL connection Block 3: Parameters for the merge: Left/Right column + merge method"""
... | stack_v2_sparse_classes_36k_train_027898 | 2,781 | permissive | [
{
"docstring": "Initialize all the fields",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Store the fields in the Form Payload",
"name": "clean",
"signature": "def clean(self) -> Dict"
}
] | 2 | stack_v2_sparse_classes_30k_train_012779 | Implement the Python class `ScheduleSQLUploadForm` described below.
Class description:
Form to request info for the SQL scheduled upload Three blocks of information are requested: Block 1: Name, description, start -- frequency -- stop times Block 2: Parameters for the SQL connection Block 3: Parameters for the merge: ... | Implement the Python class `ScheduleSQLUploadForm` described below.
Class description:
Form to request info for the SQL scheduled upload Three blocks of information are requested: Block 1: Name, description, start -- frequency -- stop times Block 2: Parameters for the SQL connection Block 3: Parameters for the merge: ... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class ScheduleSQLUploadForm:
"""Form to request info for the SQL scheduled upload Three blocks of information are requested: Block 1: Name, description, start -- frequency -- stop times Block 2: Parameters for the SQL connection Block 3: Parameters for the merge: Left/Right column + merge method"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScheduleSQLUploadForm:
"""Form to request info for the SQL scheduled upload Three blocks of information are requested: Block 1: Name, description, start -- frequency -- stop times Block 2: Parameters for the SQL connection Block 3: Parameters for the merge: Left/Right column + merge method"""
def __init_... | the_stack_v2_python_sparse | ontask/scheduler/forms/sql.py | abelardopardo/ontask_b | train | 43 |
204837e6365227f2b5c9259cee61720831530093 | [
"m = MultiFileInput()\nself.assertTrue(m.needs_multipart_form)\nself.assertFalse(m.is_hidden)",
"m = MultiFileInput({'count': 0})\nr = m.render(name='blah', value='bla', attrs={'id': 'test'})\nself.assert_('<input type=\"file\" name=\"blah[]\" id=\"test0\" />' in r)",
"m = MultiFileInput()\nr = m.render(name='b... | <|body_start_0|>
m = MultiFileInput()
self.assertTrue(m.needs_multipart_form)
self.assertFalse(m.is_hidden)
<|end_body_0|>
<|body_start_1|>
m = MultiFileInput({'count': 0})
r = m.render(name='blah', value='bla', attrs={'id': 'test'})
self.assert_('<input type="file" name... | Tests for the widget itself. | MultiFileInputTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiFileInputTest:
"""Tests for the widget itself."""
def testBasics(self):
"""Make sure the basics are correct (needs_multipart_form & is_hidden)."""
<|body_0|>
def testNoRender(self):
"""Makes sure we show a minimum of 1 input box."""
<|body_1|>
d... | stack_v2_sparse_classes_36k_train_027899 | 3,598 | no_license | [
{
"docstring": "Make sure the basics are correct (needs_multipart_form & is_hidden).",
"name": "testBasics",
"signature": "def testBasics(self)"
},
{
"docstring": "Makes sure we show a minimum of 1 input box.",
"name": "testNoRender",
"signature": "def testNoRender(self)"
},
{
"d... | 4 | stack_v2_sparse_classes_30k_train_010960 | Implement the Python class `MultiFileInputTest` described below.
Class description:
Tests for the widget itself.
Method signatures and docstrings:
- def testBasics(self): Make sure the basics are correct (needs_multipart_form & is_hidden).
- def testNoRender(self): Makes sure we show a minimum of 1 input box.
- def t... | Implement the Python class `MultiFileInputTest` described below.
Class description:
Tests for the widget itself.
Method signatures and docstrings:
- def testBasics(self): Make sure the basics are correct (needs_multipart_form & is_hidden).
- def testNoRender(self): Makes sure we show a minimum of 1 input box.
- def t... | 2791145f62a7e296be859a400499812b394249e9 | <|skeleton|>
class MultiFileInputTest:
"""Tests for the widget itself."""
def testBasics(self):
"""Make sure the basics are correct (needs_multipart_form & is_hidden)."""
<|body_0|>
def testNoRender(self):
"""Makes sure we show a minimum of 1 input box."""
<|body_1|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiFileInputTest:
"""Tests for the widget itself."""
def testBasics(self):
"""Make sure the basics are correct (needs_multipart_form & is_hidden)."""
m = MultiFileInput()
self.assertTrue(m.needs_multipart_form)
self.assertFalse(m.is_hidden)
def testNoRender(self):
... | the_stack_v2_python_sparse | combaragi/ccboard/tests.py | yonseics/yonseics | train | 1 |
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