blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a42227a53e0dfb62b537e0755bb28a18c9a0cf09 | [
"self.class_name = class_name\nself.klass = klass\nif not filter_models_classes(klass):\n raise NameError('Incompatible module for Models class: {0}'.format(klass.__module__))\nself.module_full_name = klass.__module__.replace('kubernetes.', 'kubernetes_typed.')\nself.module_name = klass.__module__.rpartition('.'... | <|body_start_0|>
self.class_name = class_name
self.klass = klass
if not filter_models_classes(klass):
raise NameError('Incompatible module for Models class: {0}'.format(klass.__module__))
self.module_full_name = klass.__module__.replace('kubernetes.', 'kubernetes_typed.')
... | Represents parsed state of kubernetes client model. | Model | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
"""Represents parsed state of kubernetes client model."""
def __init__(self, class_name: str, klass: object) -> None:
"""Parse model parameters."""
<|body_0|>
def uniq_imports(self, import_type: str) -> List[str]:
"""Get uniq import for the model."""
... | stack_v2_sparse_classes_75kplus_train_070400 | 6,267 | permissive | [
{
"docstring": "Parse model parameters.",
"name": "__init__",
"signature": "def __init__(self, class_name: str, klass: object) -> None"
},
{
"docstring": "Get uniq import for the model.",
"name": "uniq_imports",
"signature": "def uniq_imports(self, import_type: str) -> List[str]"
}
] | 2 | stack_v2_sparse_classes_30k_train_016193 | Implement the Python class `Model` described below.
Class description:
Represents parsed state of kubernetes client model.
Method signatures and docstrings:
- def __init__(self, class_name: str, klass: object) -> None: Parse model parameters.
- def uniq_imports(self, import_type: str) -> List[str]: Get uniq import fo... | Implement the Python class `Model` described below.
Class description:
Represents parsed state of kubernetes client model.
Method signatures and docstrings:
- def __init__(self, class_name: str, klass: object) -> None: Parse model parameters.
- def uniq_imports(self, import_type: str) -> List[str]: Get uniq import fo... | 82995b008daf551a4fe11660018d9c08c69f9e6e | <|skeleton|>
class Model:
"""Represents parsed state of kubernetes client model."""
def __init__(self, class_name: str, klass: object) -> None:
"""Parse model parameters."""
<|body_0|>
def uniq_imports(self, import_type: str) -> List[str]:
"""Get uniq import for the model."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Model:
"""Represents parsed state of kubernetes client model."""
def __init__(self, class_name: str, klass: object) -> None:
"""Parse model parameters."""
self.class_name = class_name
self.klass = klass
if not filter_models_classes(klass):
raise NameError('Inco... | the_stack_v2_python_sparse | scripts/typeddictgen.py | gordonbondon/kubernetes-typed | train | 24 |
183e355df6fd630d0c65ef9fac58ef286556ee20 | [
"self.k_heap = []\nself.k = k\nfor i, x in enumerate(nums):\n if i < k:\n heapq.heappush(self.k_heap, x)\n elif self.k_heap[0] < x:\n heapq.heappop(self.k_heap)\n heapq.heappush(self.k_heap, x)",
"if len(self.k_heap) < self.k:\n heapq.heappush(self.k_heap, val)\n return self.k_hea... | <|body_start_0|>
self.k_heap = []
self.k = k
for i, x in enumerate(nums):
if i < k:
heapq.heappush(self.k_heap, x)
elif self.k_heap[0] < x:
heapq.heappop(self.k_heap)
heapq.heappush(self.k_heap, x)
<|end_body_0|>
<|body_sta... | KthLargest | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k_heap = []
self.k = k
for i, x in en... | stack_v2_sparse_classes_75kplus_train_070401 | 932 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021495 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 1c273eadfbf4bef9323a0f386717ac8e7ad2ba71 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k_heap = []
self.k = k
for i, x in enumerate(nums):
if i < k:
heapq.heappush(self.k_heap, x)
elif self.k_heap[0] < x:
heapq.heappop(sel... | the_stack_v2_python_sparse | Algorithm/streamKlagest.py | jackwang816/python_practice | train | 0 | |
be8f9a119f4c07da8b6740acf01ef6da2b68d8ab | [
"super().__init__(*args, **kwargs)\nself.input_sample_rate = input_sample_rate\nself.n_mfcc = n_mfcc\nself.n_fft_length = n_fft_length\nself.hop_length = hop_length",
"from librosa.feature import mfcc\nembeds = []\nfor chunk_data in data:\n mfccs = mfcc(y=chunk_data, sr=self.input_sample_rate, n_mfcc=self.n_mf... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.input_sample_rate = input_sample_rate
self.n_mfcc = n_mfcc
self.n_fft_length = n_fft_length
self.hop_length = hop_length
<|end_body_0|>
<|body_start_1|>
from librosa.feature import mfcc
embeds = []
f... | :class:`MFCCTimbreEncoder` is based on Mel-Frequency Cepstral Coefficients (MFCCs) which represent timbral features. :class:`MFCCTimbreEncoder` encodes an audio signal from a `Batch x Signal Length` ndarray into a `Batch x Concatenated Features` ndarray. | MFCCTimbreEncoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MFCCTimbreEncoder:
""":class:`MFCCTimbreEncoder` is based on Mel-Frequency Cepstral Coefficients (MFCCs) which represent timbral features. :class:`MFCCTimbreEncoder` encodes an audio signal from a `Batch x Signal Length` ndarray into a `Batch x Concatenated Features` ndarray."""
def __init__... | stack_v2_sparse_classes_75kplus_train_070402 | 4,047 | permissive | [
{
"docstring": ":class:`MFCCTimbreEncoder` extracts from an audio signal a `n_mfcc`-dimensional feature vector for each MFCC frame. :param input_sample_rate: input sampling rate in Hz (22050 by default) :param n_mfcc: the number of coefficients (20 by default) :param n_fft: length of the FFT window (2048 by def... | 2 | stack_v2_sparse_classes_30k_train_042477 | Implement the Python class `MFCCTimbreEncoder` described below.
Class description:
:class:`MFCCTimbreEncoder` is based on Mel-Frequency Cepstral Coefficients (MFCCs) which represent timbral features. :class:`MFCCTimbreEncoder` encodes an audio signal from a `Batch x Signal Length` ndarray into a `Batch x Concatenated ... | Implement the Python class `MFCCTimbreEncoder` described below.
Class description:
:class:`MFCCTimbreEncoder` is based on Mel-Frequency Cepstral Coefficients (MFCCs) which represent timbral features. :class:`MFCCTimbreEncoder` encodes an audio signal from a `Batch x Signal Length` ndarray into a `Batch x Concatenated ... | e30a8827d1b10b691ab7e18ea70c25b22166afc5 | <|skeleton|>
class MFCCTimbreEncoder:
""":class:`MFCCTimbreEncoder` is based on Mel-Frequency Cepstral Coefficients (MFCCs) which represent timbral features. :class:`MFCCTimbreEncoder` encodes an audio signal from a `Batch x Signal Length` ndarray into a `Batch x Concatenated Features` ndarray."""
def __init__... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MFCCTimbreEncoder:
""":class:`MFCCTimbreEncoder` is based on Mel-Frequency Cepstral Coefficients (MFCCs) which represent timbral features. :class:`MFCCTimbreEncoder` encodes an audio signal from a `Batch x Signal Length` ndarray into a `Batch x Concatenated Features` ndarray."""
def __init__(self, input_... | the_stack_v2_python_sparse | jina/executors/encoders/audio/spectral.py | alexcg1/jina | train | 1 |
fe9888a500d0fa9e6015e4b0100295450d364f85 | [
"self.debug = debug\nself._spi = spi\nself._ss = ss\nsuper().__init__(debug=debug, reset=reset)",
"if self._reset_pin:\n self._reset_pin.value(1)\n time.sleep(0.01)\nself.low_power = False\nself._ss(0)\nself._spi.write(b'UU\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00')\nself._... | <|body_start_0|>
self.debug = debug
self._spi = spi
self._ss = ss
super().__init__(debug=debug, reset=reset)
<|end_body_0|>
<|body_start_1|>
if self._reset_pin:
self._reset_pin.value(1)
time.sleep(0.01)
self.low_power = False
self._ss(0)
... | Driver for the PN532 connected over SPI | PN532_SPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PN532_SPI:
"""Driver for the PN532 connected over SPI"""
def __init__(self, spi, ss, *, reset=None, debug=False):
"""Create an instance of the PN532 class using Serial connection. Optional reset pin and debugging output."""
<|body_0|>
def _wakeup(self):
"""Send a... | stack_v2_sparse_classes_75kplus_train_070403 | 3,392 | no_license | [
{
"docstring": "Create an instance of the PN532 class using Serial connection. Optional reset pin and debugging output.",
"name": "__init__",
"signature": "def __init__(self, spi, ss, *, reset=None, debug=False)"
},
{
"docstring": "Send any special commands/data to wake up PN532",
"name": "_... | 5 | null | Implement the Python class `PN532_SPI` described below.
Class description:
Driver for the PN532 connected over SPI
Method signatures and docstrings:
- def __init__(self, spi, ss, *, reset=None, debug=False): Create an instance of the PN532 class using Serial connection. Optional reset pin and debugging output.
- def ... | Implement the Python class `PN532_SPI` described below.
Class description:
Driver for the PN532 connected over SPI
Method signatures and docstrings:
- def __init__(self, spi, ss, *, reset=None, debug=False): Create an instance of the PN532 class using Serial connection. Optional reset pin and debugging output.
- def ... | 6941424ade1e5c2563290fb32cf39034a55968f6 | <|skeleton|>
class PN532_SPI:
"""Driver for the PN532 connected over SPI"""
def __init__(self, spi, ss, *, reset=None, debug=False):
"""Create an instance of the PN532 class using Serial connection. Optional reset pin and debugging output."""
<|body_0|>
def _wakeup(self):
"""Send a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PN532_SPI:
"""Driver for the PN532 connected over SPI"""
def __init__(self, spi, ss, *, reset=None, debug=False):
"""Create an instance of the PN532 class using Serial connection. Optional reset pin and debugging output."""
self.debug = debug
self._spi = spi
self._ss = ss
... | the_stack_v2_python_sparse | esp32-micropython/components/rfid/spi.py | octopusengine/octopuslab | train | 32 |
082ce4e73277ac6949606ff297b343c648964a5f | [
"self.smp = smp\nself.nangles = nangles\nself.angles = np.linspace(0, np.pi, nangles, endpoint=False)",
"smp = self.smp\nangles = self.angles\nsmp.compCov(y)\nspec = np.zeros(angles.shape)\nfor i in range(self.nangles):\n spec[i] = smp.compSpecSample(angles[i])\nangle = angles[np.argmax(spec)]\nif retspec:\n ... | <|body_start_0|>
self.smp = smp
self.nangles = nangles
self.angles = np.linspace(0, np.pi, nangles, endpoint=False)
<|end_body_0|>
<|body_start_1|>
smp = self.smp
angles = self.angles
smp.compCov(y)
spec = np.zeros(angles.shape)
for i in range(self.nangle... | DOA tracker without any filtering. It always computes the full spectrum. Attributes ---------- angles : (nangles,) ndarray Vector of angles to be sampled in a spatial spectrum. It is sampled in a linear space. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle filtering for acoustic source... | NaiveTracker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NaiveTracker:
"""DOA tracker without any filtering. It always computes the full spectrum. Attributes ---------- angles : (nangles,) ndarray Vector of angles to be sampled in a spatial spectrum. It is sampled in a linear space. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S.,... | stack_v2_sparse_classes_75kplus_train_070404 | 2,209 | no_license | [
{
"docstring": "Parameters ---------- smp : SpectrumSampler Sampler of spatial spectrum. nangles : int Number of angle samples in a spatial spectrum. The angles will be sampled as a linear space in [0, pi).",
"name": "__init__",
"signature": "def __init__(self, smp, nangles)"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_011820 | Implement the Python class `NaiveTracker` described below.
Class description:
DOA tracker without any filtering. It always computes the full spectrum. Attributes ---------- angles : (nangles,) ndarray Vector of angles to be sampled in a spatial spectrum. It is sampled in a linear space. Reference --------- Zhong, X., ... | Implement the Python class `NaiveTracker` described below.
Class description:
DOA tracker without any filtering. It always computes the full spectrum. Attributes ---------- angles : (nangles,) ndarray Vector of angles to be sampled in a spatial spectrum. It is sampled in a linear space. Reference --------- Zhong, X., ... | 4cbb2eba87c6ffd79e474014584ee31c893ade13 | <|skeleton|>
class NaiveTracker:
"""DOA tracker without any filtering. It always computes the full spectrum. Attributes ---------- angles : (nangles,) ndarray Vector of angles to be sampled in a spatial spectrum. It is sampled in a linear space. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S.,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NaiveTracker:
"""DOA tracker without any filtering. It always computes the full spectrum. Attributes ---------- angles : (nangles,) ndarray Vector of angles to be sampled in a spatial spectrum. It is sampled in a linear space. Reference --------- Zhong, X., Prekumar, A. B., and Madhukumar, A. S., "Particle fi... | the_stack_v2_python_sparse | naivetracker.py | qrqiuren/particle | train | 5 |
0c9a5d0bd1bbd05e0aa18eb21561ed92812b1db7 | [
"sign = 1 if x >= 0 else -1\nx = abs(x)\nres = 0\nwhile x > 0:\n res = 10 * res + x % 10\n x /= 10\nreturn sign * res if -2 ** 31 <= sign * res <= 2 ** 31 - 1 else 0",
"sign = 1 if x >= 0 else -1\nres = int(str(abs(x))[::-1])\nreturn sign * res if -2 ** 31 <= sign * res <= 2 ** 31 - 1 else 0"
] | <|body_start_0|>
sign = 1 if x >= 0 else -1
x = abs(x)
res = 0
while x > 0:
res = 10 * res + x % 10
x /= 10
return sign * res if -2 ** 31 <= sign * res <= 2 ** 31 - 1 else 0
<|end_body_0|>
<|body_start_1|>
sign = 1 if x >= 0 else -1
res = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse2(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sign = 1 if x >= 0 else -1
x = abs(x)
res = 0
while ... | stack_v2_sparse_classes_75kplus_train_070405 | 669 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "reverse",
"signature": "def reverse(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse2",
"signature": "def reverse2(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001790 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def reverse2(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def reverse2(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int ... | 31b2b4dc1e5c3b1c53b333fe30b98ed04b0bdacc | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse2(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
sign = 1 if x >= 0 else -1
x = abs(x)
res = 0
while x > 0:
res = 10 * res + x % 10
x /= 10
return sign * res if -2 ** 31 <= sign * res <= 2 ** 31 - 1 else 0
def reverse2(... | the_stack_v2_python_sparse | prob007_reverseinteger.py | Hu-Wenchao/leetcode | train | 0 | |
7bf5c66ff540902d733abd5d076f8e5109085f44 | [
"assert eta > 0, 'Efficiency of electrical heater should not be ' + 'equal to or below zero. Check your inputs.'\nassert eta <= 1, 'Efficiency of electrical heater should not' + ' exceed 1. Check your inputs.'\nsuper(ElectricalHeaterExtended, self).__init__(environment=environment, qNominal=q_nominal, tMax=t_max, l... | <|body_start_0|>
assert eta > 0, 'Efficiency of electrical heater should not be ' + 'equal to or below zero. Check your inputs.'
assert eta <= 1, 'Efficiency of electrical heater should not' + ' exceed 1. Check your inputs.'
super(ElectricalHeaterExtended, self).__init__(environment=environment,... | electricalHeaterExtended class (inheritance from electricalHeater Boiler class) self.totalPConsumption self.totalQOutput | ElectricalHeaterExtended | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElectricalHeaterExtended:
"""electricalHeaterExtended class (inheritance from electricalHeater Boiler class) self.totalPConsumption self.totalQOutput"""
def __init__(self, environment, q_nominal, eta=1, t_max=85, lower_activation_limit=0):
"""Parameters ---------- environment : Exten... | stack_v2_sparse_classes_75kplus_train_070406 | 5,481 | permissive | [
{
"docstring": "Parameters ---------- environment : Extended environment object Common to all other objects. Includes time and weather instances q_nominal : float nominal heat production in W eta : float, optional nominal efficiency (without unit) (default: 1) t_max : float maximum provided temperature in °C (d... | 4 | stack_v2_sparse_classes_30k_train_026467 | Implement the Python class `ElectricalHeaterExtended` described below.
Class description:
electricalHeaterExtended class (inheritance from electricalHeater Boiler class) self.totalPConsumption self.totalQOutput
Method signatures and docstrings:
- def __init__(self, environment, q_nominal, eta=1, t_max=85, lower_activ... | Implement the Python class `ElectricalHeaterExtended` described below.
Class description:
electricalHeaterExtended class (inheritance from electricalHeater Boiler class) self.totalPConsumption self.totalQOutput
Method signatures and docstrings:
- def __init__(self, environment, q_nominal, eta=1, t_max=85, lower_activ... | 99fd0dab7f9a9030fd84ba4715753364662927ec | <|skeleton|>
class ElectricalHeaterExtended:
"""electricalHeaterExtended class (inheritance from electricalHeater Boiler class) self.totalPConsumption self.totalQOutput"""
def __init__(self, environment, q_nominal, eta=1, t_max=85, lower_activation_limit=0):
"""Parameters ---------- environment : Exten... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ElectricalHeaterExtended:
"""electricalHeaterExtended class (inheritance from electricalHeater Boiler class) self.totalPConsumption self.totalQOutput"""
def __init__(self, environment, q_nominal, eta=1, t_max=85, lower_activation_limit=0):
"""Parameters ---------- environment : Extended environme... | the_stack_v2_python_sparse | pycity_calc/energysystems/electricalHeater.py | RWTH-EBC/pyCity_calc | train | 4 |
89a228e893e87b20035e03a43537bcf5d1fcf929 | [
"super(RNNEnc, self).__init__()\nself._input_dim = input_dim\nself._con_len = context_length\nself.gru_enc = GRU(input_size=self._input_dim, hidden_size=self._input_dim, num_layers=1, bias=True, batch_first=True, bidirectional=True)\nself.initialize_encoder()",
"xavier_normal_(self.gru_enc.weight_ih_l0)\northogon... | <|body_start_0|>
super(RNNEnc, self).__init__()
self._input_dim = input_dim
self._con_len = context_length
self.gru_enc = GRU(input_size=self._input_dim, hidden_size=self._input_dim, num_layers=1, bias=True, batch_first=True, bidirectional=True)
self.initialize_encoder()
<|end_bo... | RNNEnc | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNEnc:
def __init__(self, input_dim, context_length):
"""The RNN encoder of the Masker. :param input_dim: The input dimensionality. :type input_dim: int :param context_length: The context length. :type context_length: int"""
<|body_0|>
def initialize_encoder(self):
... | stack_v2_sparse_classes_75kplus_train_070407 | 16,858 | no_license | [
{
"docstring": "The RNN encoder of the Masker. :param input_dim: The input dimensionality. :type input_dim: int :param context_length: The context length. :type context_length: int",
"name": "__init__",
"signature": "def __init__(self, input_dim, context_length)"
},
{
"docstring": "Manual weight... | 3 | stack_v2_sparse_classes_30k_test_001658 | Implement the Python class `RNNEnc` described below.
Class description:
Implement the RNNEnc class.
Method signatures and docstrings:
- def __init__(self, input_dim, context_length): The RNN encoder of the Masker. :param input_dim: The input dimensionality. :type input_dim: int :param context_length: The context leng... | Implement the Python class `RNNEnc` described below.
Class description:
Implement the RNNEnc class.
Method signatures and docstrings:
- def __init__(self, input_dim, context_length): The RNN encoder of the Masker. :param input_dim: The input dimensionality. :type input_dim: int :param context_length: The context leng... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class RNNEnc:
def __init__(self, input_dim, context_length):
"""The RNN encoder of the Masker. :param input_dim: The input dimensionality. :type input_dim: int :param context_length: The context length. :type context_length: int"""
<|body_0|>
def initialize_encoder(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RNNEnc:
def __init__(self, input_dim, context_length):
"""The RNN encoder of the Masker. :param input_dim: The input dimensionality. :type input_dim: int :param context_length: The context length. :type context_length: int"""
super(RNNEnc, self).__init__()
self._input_dim = input_dim
... | the_stack_v2_python_sparse | generated/test_dr_costas_mad_twinnet.py | jansel/pytorch-jit-paritybench | train | 35 | |
884edb9980e306a8d6f68572fe9097146125fe89 | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=self.normalize_email(email), name=name)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email, password=password, name=name)\nuser.is_active = True\nuser.is_superuser =... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email), name=name)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.c... | UserProfileManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfileManager:
def create_user(self, email, name, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, name, password):
"""Creates and saves a superuser with the given email... | stack_v2_sparse_classes_75kplus_train_070408 | 10,239 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, email, name, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name": "c... | 2 | stack_v2_sparse_classes_30k_train_023445 | Implement the Python class `UserProfileManager` described below.
Class description:
Implement the UserProfileManager class.
Method signatures and docstrings:
- def create_user(self, email, name, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, ema... | Implement the Python class `UserProfileManager` described below.
Class description:
Implement the UserProfileManager class.
Method signatures and docstrings:
- def create_user(self, email, name, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, ema... | c7a03e6c39fa97881455a5b073c4d0e9a5b6075e | <|skeleton|>
class UserProfileManager:
def create_user(self, email, name, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, name, password):
"""Creates and saves a superuser with the given email... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserProfileManager:
def create_user(self, email, name, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email), na... | the_stack_v2_python_sparse | web/models.py | myAlike/SunEye | train | 0 | |
4184af7a9550194a650379a96a557656b4750b63 | [
"if not email:\n raise ValueError('The Email must be set')\nemail = self.normalize_email(email)\nif not check_ncsu_email(email):\n raise ValueError('Please use NCSU Email Id!')\nuser = self.model(email=email, **extra_fields)\nuser.set_password(password)\nuser.save()\nreturn user",
"extra_fields.setdefault('... | <|body_start_0|>
if not email:
raise ValueError('The Email must be set')
email = self.normalize_email(email)
if not check_ncsu_email(email):
raise ValueError('Please use NCSU Email Id!')
user = self.model(email=email, **extra_fields)
user.set_password(pass... | Custom user model manager where email is the unique identifiers for authentication instead of usernames. | CustomUserManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUserManager:
"""Custom user model manager where email is the unique identifiers for authentication instead of usernames."""
def create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def create... | stack_v2_sparse_classes_75kplus_train_070409 | 2,595 | permissive | [
{
"docstring": "Create and save a User with the given email and password.",
"name": "create_user",
"signature": "def create_user(self, email, password, **extra_fields)"
},
{
"docstring": "Create and save a SuperUser with the given email and password.",
"name": "create_superuser",
"signat... | 2 | stack_v2_sparse_classes_30k_train_003265 | Implement the Python class `CustomUserManager` described below.
Class description:
Custom user model manager where email is the unique identifiers for authentication instead of usernames.
Method signatures and docstrings:
- def create_user(self, email, password, **extra_fields): Create and save a User with the given ... | Implement the Python class `CustomUserManager` described below.
Class description:
Custom user model manager where email is the unique identifiers for authentication instead of usernames.
Method signatures and docstrings:
- def create_user(self, email, password, **extra_fields): Create and save a User with the given ... | c40b5f642577926e01dbc5d95d4abdf2a08bdbb5 | <|skeleton|>
class CustomUserManager:
"""Custom user model manager where email is the unique identifiers for authentication instead of usernames."""
def create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def create... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomUserManager:
"""Custom user model manager where email is the unique identifiers for authentication instead of usernames."""
def create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
if not email:
raise ValueEr... | the_stack_v2_python_sparse | src/base/managers.py | Nikhil1912/FindMyRoomie_2.0 | train | 1 |
c219375c1f52bcbbf41de7510397aaa2565f6a8f | [
"print('BASE CONVERTER')\nprint('Numbers entered must be below ten quintillion threshold.\\n')\nnum1 = input('Please enter number to convert: ')\nnum2 = int(input('Please enter the base of the number: '))\nif num2 == 1 or num2 == 0:\n print('A base of 0 or 1 will not work.')\nelif num2 == 10:\n print('The num... | <|body_start_0|>
print('BASE CONVERTER')
print('Numbers entered must be below ten quintillion threshold.\n')
num1 = input('Please enter number to convert: ')
num2 = int(input('Please enter the base of the number: '))
if num2 == 1 or num2 == 0:
print('A base of 0 or 1 ... | Base | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
def convert_ten(self):
"""Description: This method converts any number from its base to base 10. Args: None. Returns: num1, total"""
<|body_0|>
def convert_base(self, num1, total):
"""Description: This method converts any number from base 10 to the users chosen... | stack_v2_sparse_classes_75kplus_train_070410 | 3,231 | permissive | [
{
"docstring": "Description: This method converts any number from its base to base 10. Args: None. Returns: num1, total",
"name": "convert_ten",
"signature": "def convert_ten(self)"
},
{
"docstring": "Description: This method converts any number from base 10 to the users chosen base. Args: num1,... | 2 | stack_v2_sparse_classes_30k_test_001292 | Implement the Python class `Base` described below.
Class description:
Implement the Base class.
Method signatures and docstrings:
- def convert_ten(self): Description: This method converts any number from its base to base 10. Args: None. Returns: num1, total
- def convert_base(self, num1, total): Description: This me... | Implement the Python class `Base` described below.
Class description:
Implement the Base class.
Method signatures and docstrings:
- def convert_ten(self): Description: This method converts any number from its base to base 10. Args: None. Returns: num1, total
- def convert_base(self, num1, total): Description: This me... | df46c8bb8e4c8ba6d34898cd13cdb0348eb4e74d | <|skeleton|>
class Base:
def convert_ten(self):
"""Description: This method converts any number from its base to base 10. Args: None. Returns: num1, total"""
<|body_0|>
def convert_base(self, num1, total):
"""Description: This method converts any number from base 10 to the users chosen... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Base:
def convert_ten(self):
"""Description: This method converts any number from its base to base 10. Args: None. Returns: num1, total"""
print('BASE CONVERTER')
print('Numbers entered must be below ten quintillion threshold.\n')
num1 = input('Please enter number to convert: '... | the_stack_v2_python_sparse | base_converter.py | tangowithfoxtrot/beginner_project_solutions | train | 0 | |
a43818e2155633354f9a3d4ae1b25104d32ffb58 | [
"super().__init__(**kwargs)\nself.reader = profile_reader\nself.standardiser = profile_standardiser\nself.taxonomy = taxonomy_service",
"if name is None:\n name = profile.stem\ntry:\n result = self.standardiser.transform(self.reader.read(profile))\nexcept SchemaErrors as errors:\n raise StandardisationEr... | <|body_start_0|>
super().__init__(**kwargs)
self.reader = profile_reader
self.standardiser = profile_standardiser
self.taxonomy = taxonomy_service
<|end_body_0|>
<|body_start_1|>
if name is None:
name = profile.stem
try:
result = self.standardiser... | Define the sample ETL application. | SampleETLApplication | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleETLApplication:
"""Define the sample ETL application."""
def __init__(self, *, profile_reader: Type[ProfileReader], profile_standardiser: Type[ProfileStandardisationService], taxonomy_service: Optional[TaxonomyService]=None, **kwargs: dict):
"""Initialize the application for a ... | stack_v2_sparse_classes_75kplus_train_070411 | 3,774 | permissive | [
{
"docstring": "Initialize the application for a particular taxonomic profiler. Args: profile_reader: A profile reader for a specific taxonomic profile format. profile_standardiser: A profile standardisation service for a specific taxonomic profile format. taxonomy_service: A taxonomy service instance. It is as... | 2 | stack_v2_sparse_classes_30k_train_042396 | Implement the Python class `SampleETLApplication` described below.
Class description:
Define the sample ETL application.
Method signatures and docstrings:
- def __init__(self, *, profile_reader: Type[ProfileReader], profile_standardiser: Type[ProfileStandardisationService], taxonomy_service: Optional[TaxonomyService]... | Implement the Python class `SampleETLApplication` described below.
Class description:
Define the sample ETL application.
Method signatures and docstrings:
- def __init__(self, *, profile_reader: Type[ProfileReader], profile_standardiser: Type[ProfileStandardisationService], taxonomy_service: Optional[TaxonomyService]... | 98713deaeec2e92b2f020860d264bccc9a25dbd1 | <|skeleton|>
class SampleETLApplication:
"""Define the sample ETL application."""
def __init__(self, *, profile_reader: Type[ProfileReader], profile_standardiser: Type[ProfileStandardisationService], taxonomy_service: Optional[TaxonomyService]=None, **kwargs: dict):
"""Initialize the application for a ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SampleETLApplication:
"""Define the sample ETL application."""
def __init__(self, *, profile_reader: Type[ProfileReader], profile_standardiser: Type[ProfileStandardisationService], taxonomy_service: Optional[TaxonomyService]=None, **kwargs: dict):
"""Initialize the application for a particular ta... | the_stack_v2_python_sparse | src/taxpasta/infrastructure/application/sample_etl_application.py | taxprofiler/taxpasta | train | 21 |
7c8eb00d7016fd0f84cca169f382c73cd6eab64c | [
"self._libros = []\narchivos = os.listdir(path='libros')\nfor n in archivos:\n if '.txt' in n:\n archivo = open('libros/' + n, 'r', encoding='utf-8')\n linea1 = archivo.readline()\n linea2 = archivo.readline()\n autor = (linea1 if linea1.find('autor') != -1 else linea2).replace('autor... | <|body_start_0|>
self._libros = []
archivos = os.listdir(path='libros')
for n in archivos:
if '.txt' in n:
archivo = open('libros/' + n, 'r', encoding='utf-8')
linea1 = archivo.readline()
linea2 = archivo.readline()
auto... | Representa un lector de libros eléctronicos | EReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EReader:
"""Representa un lector de libros eléctronicos"""
def __init__(self):
"""Se debe leer la lista de libros que están en el directorio 'libros'. Las dos primeras líneas de cada archivo contienen el autor y el título de cada libro, esta información no forma parte del contenido d... | stack_v2_sparse_classes_75kplus_train_070412 | 1,656 | no_license | [
{
"docstring": "Se debe leer la lista de libros que están en el directorio 'libros'. Las dos primeras líneas de cada archivo contienen el autor y el título de cada libro, esta información no forma parte del contenido del libro. Los nombres de los archivos terminan con la extensión .txt",
"name": "__init__",... | 2 | null | Implement the Python class `EReader` described below.
Class description:
Representa un lector de libros eléctronicos
Method signatures and docstrings:
- def __init__(self): Se debe leer la lista de libros que están en el directorio 'libros'. Las dos primeras líneas de cada archivo contienen el autor y el título de ca... | Implement the Python class `EReader` described below.
Class description:
Representa un lector de libros eléctronicos
Method signatures and docstrings:
- def __init__(self): Se debe leer la lista de libros que están en el directorio 'libros'. Las dos primeras líneas de cada archivo contienen el autor y el título de ca... | ec6b69ccf995041a086ccf14e57cbc7886622ed5 | <|skeleton|>
class EReader:
"""Representa un lector de libros eléctronicos"""
def __init__(self):
"""Se debe leer la lista de libros que están en el directorio 'libros'. Las dos primeras líneas de cada archivo contienen el autor y el título de cada libro, esta información no forma parte del contenido d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EReader:
"""Representa un lector de libros eléctronicos"""
def __init__(self):
"""Se debe leer la lista de libros que están en el directorio 'libros'. Las dos primeras líneas de cada archivo contienen el autor y el título de cada libro, esta información no forma parte del contenido del libro. Los... | the_stack_v2_python_sparse | ejercicio1/angel/ereader.py | jazt9513/IA | train | 0 |
774f871c6924b3adc5cee488b2beb7128509d8eb | [
"Thread.__init__(self)\nself.name = name\nself.url = url",
"handle = urllib.request.urlopen(self.url)\nfname = os.path.basename(self.url)\nwith open(fname, 'wb') as f_handler:\n while True:\n chunk = handle.read(1024)\n if not chunk:\n break\n f_handler.write(chunk)\nmsg = '%s h... | <|body_start_0|>
Thread.__init__(self)
self.name = name
self.url = url
<|end_body_0|>
<|body_start_1|>
handle = urllib.request.urlopen(self.url)
fname = os.path.basename(self.url)
with open(fname, 'wb') as f_handler:
while True:
chunk = handle... | A threading example that can download a file | DownloadThread | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DownloadThread:
"""A threading example that can download a file"""
def __init__(self, url, name):
"""Initialize the thread"""
<|body_0|>
def run(self):
"""Run the thread"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Thread.__init__(self)
... | stack_v2_sparse_classes_75kplus_train_070413 | 3,234 | no_license | [
{
"docstring": "Initialize the thread",
"name": "__init__",
"signature": "def __init__(self, url, name)"
},
{
"docstring": "Run the thread",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_051520 | Implement the Python class `DownloadThread` described below.
Class description:
A threading example that can download a file
Method signatures and docstrings:
- def __init__(self, url, name): Initialize the thread
- def run(self): Run the thread | Implement the Python class `DownloadThread` described below.
Class description:
A threading example that can download a file
Method signatures and docstrings:
- def __init__(self, url, name): Initialize the thread
- def run(self): Run the thread
<|skeleton|>
class DownloadThread:
"""A threading example that can ... | 8ea0871c3d7ca86327424562e1b04daca6d54054 | <|skeleton|>
class DownloadThread:
"""A threading example that can download a file"""
def __init__(self, url, name):
"""Initialize the thread"""
<|body_0|>
def run(self):
"""Run the thread"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DownloadThread:
"""A threading example that can download a file"""
def __init__(self, url, name):
"""Initialize the thread"""
Thread.__init__(self)
self.name = name
self.url = url
def run(self):
"""Run the thread"""
handle = urllib.request.urlopen(self... | the_stack_v2_python_sparse | metaverse/utils/scheduler_example.py | CyberChad/Metaverse | train | 3 |
3610fa11406aab74feba6b034e76e404bb00c387 | [
"self._params = Parameters()\nfor path, param in network.get_variables().items():\n self._params.add(path + '_velocity', numpy.zeros_like(param.get_value()))\nif 'momentum' not in optimization_options:\n raise ValueError('Momentum is not given in optimization options.')\nself._momentum = optimization_options[... | <|body_start_0|>
self._params = Parameters()
for path, param in network.get_variables().items():
self._params.add(path + '_velocity', numpy.zeros_like(param.get_value()))
if 'momentum' not in optimization_options:
raise ValueError('Momentum is not given in optimization op... | Nesterov Momentum Optimization Method Normally Nesterov momentum is implemented by first taking a step towards the previous update direction, calculating gradient at that position, using the gradient to obtain the new update direction, and finally updating the parameters. We use an alternative formulation that requires... | NesterovOptimizer | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NesterovOptimizer:
"""Nesterov Momentum Optimization Method Normally Nesterov momentum is implemented by first taking a step towards the previous update direction, calculating gradient at that position, using the gradient to obtain the new update direction, and finally updating the parameters. We... | stack_v2_sparse_classes_75kplus_train_070414 | 2,905 | permissive | [
{
"docstring": "Creates a Nesterov momentum optimizer. Nesterov momentum optimizer does not use additional parameters. :type optimization_options: dict :param optimization_options: a dictionary of optimization options :type network: Network :param network: the neural network object",
"name": "__init__",
... | 2 | stack_v2_sparse_classes_30k_train_017734 | Implement the Python class `NesterovOptimizer` described below.
Class description:
Nesterov Momentum Optimization Method Normally Nesterov momentum is implemented by first taking a step towards the previous update direction, calculating gradient at that position, using the gradient to obtain the new update direction, ... | Implement the Python class `NesterovOptimizer` described below.
Class description:
Nesterov Momentum Optimization Method Normally Nesterov momentum is implemented by first taking a step towards the previous update direction, calculating gradient at that position, using the gradient to obtain the new update direction, ... | 9904faec19ad5718470f21927229aad2656e5686 | <|skeleton|>
class NesterovOptimizer:
"""Nesterov Momentum Optimization Method Normally Nesterov momentum is implemented by first taking a step towards the previous update direction, calculating gradient at that position, using the gradient to obtain the new update direction, and finally updating the parameters. We... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NesterovOptimizer:
"""Nesterov Momentum Optimization Method Normally Nesterov momentum is implemented by first taking a step towards the previous update direction, calculating gradient at that position, using the gradient to obtain the new update direction, and finally updating the parameters. We use an alter... | the_stack_v2_python_sparse | theanolm/training/nesterovoptimizer.py | senarvi/theanolm | train | 95 |
4284535d2c74a3c15e86ff792b59ea2f5ce103c5 | [
"losses = dict()\nif self.pixel_loss:\n losses['loss_pix'] = self.pixel_loss(batch_outputs, batch_gt_data)\nif self.perceptual_loss:\n loss_percep, loss_style = self.perceptual_loss(batch_outputs, batch_gt_data)\n if loss_percep is not None:\n losses['loss_perceptual'] = loss_percep\n if loss_sty... | <|body_start_0|>
losses = dict()
if self.pixel_loss:
losses['loss_pix'] = self.pixel_loss(batch_outputs, batch_gt_data)
if self.perceptual_loss:
loss_percep, loss_style = self.perceptual_loss(batch_outputs, batch_gt_data)
if loss_percep is not None:
... | Enhanced SRGAN model for single image super-resolution. Ref: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. It uses RaGAN for GAN updates: The relativistic discriminator: a key element missing from standard GAN. Args: generator (dict): Config for the generator. discriminator (dict): Config for the d... | ESRGAN | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ESRGAN:
"""Enhanced SRGAN model for single image super-resolution. Ref: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. It uses RaGAN for GAN updates: The relativistic discriminator: a key element missing from standard GAN. Args: generator (dict): Config for the generator. disc... | stack_v2_sparse_classes_75kplus_train_070415 | 4,262 | permissive | [
{
"docstring": "G step of GAN: Calculate losses of generator. Args: batch_outputs (Tensor): Batch output of generator. batch_gt_data (Tensor): Batch GT data. Returns: dict: Dict of losses.",
"name": "g_step",
"signature": "def g_step(self, batch_outputs: torch.Tensor, batch_gt_data: torch.Tensor)"
},
... | 3 | stack_v2_sparse_classes_30k_train_023562 | Implement the Python class `ESRGAN` described below.
Class description:
Enhanced SRGAN model for single image super-resolution. Ref: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. It uses RaGAN for GAN updates: The relativistic discriminator: a key element missing from standard GAN. Args: generator... | Implement the Python class `ESRGAN` described below.
Class description:
Enhanced SRGAN model for single image super-resolution. Ref: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. It uses RaGAN for GAN updates: The relativistic discriminator: a key element missing from standard GAN. Args: generator... | a382f143c0fd20d227e1e5524831ba26a568190d | <|skeleton|>
class ESRGAN:
"""Enhanced SRGAN model for single image super-resolution. Ref: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. It uses RaGAN for GAN updates: The relativistic discriminator: a key element missing from standard GAN. Args: generator (dict): Config for the generator. disc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ESRGAN:
"""Enhanced SRGAN model for single image super-resolution. Ref: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. It uses RaGAN for GAN updates: The relativistic discriminator: a key element missing from standard GAN. Args: generator (dict): Config for the generator. discriminator (di... | the_stack_v2_python_sparse | mmagic/models/editors/esrgan/esrgan.py | open-mmlab/mmagic | train | 1,370 |
12880601eb056ffcd27fedc77b3964e1d4a6f5d2 | [
"if m == 1 or n == 1:\n return 1\ndp = [[0] * n for _ in range(m)]\ndp[0] = [1] * n\nfor i in range(m):\n dp[i][0] = 1\nfor i in range(1, m):\n for j in range(1, n):\n dp[i][j] = dp[i][j - 1] + dp[i - 1][j]\nreturn dp[m - 1][n - 1]",
"if m == 1 or n == 1:\n return 1\ndp = [1] * n\nfor _ in rang... | <|body_start_0|>
if m == 1 or n == 1:
return 1
dp = [[0] * n for _ in range(m)]
dp[0] = [1] * n
for i in range(m):
dp[i][0] = 1
for i in range(1, m):
for j in range(1, n):
dp[i][j] = dp[i][j - 1] + dp[i - 1][j]
return dp... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def unique_path(self, m: int, n: int) -> int:
"""O(n*m) space"""
<|body_0|>
def unique_path_less_space(self, m: int, n: int) -> int:
"""Instead of using m rows in the dp matrix, we only need to maintain one row. O(n) sapce"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus_train_070416 | 864 | no_license | [
{
"docstring": "O(n*m) space",
"name": "unique_path",
"signature": "def unique_path(self, m: int, n: int) -> int"
},
{
"docstring": "Instead of using m rows in the dp matrix, we only need to maintain one row. O(n) sapce",
"name": "unique_path_less_space",
"signature": "def unique_path_le... | 2 | stack_v2_sparse_classes_30k_train_014833 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def unique_path(self, m: int, n: int) -> int: O(n*m) space
- def unique_path_less_space(self, m: int, n: int) -> int: Instead of using m rows in the dp matrix, we only need to ma... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def unique_path(self, m: int, n: int) -> int: O(n*m) space
- def unique_path_less_space(self, m: int, n: int) -> int: Instead of using m rows in the dp matrix, we only need to ma... | 5625e6396b746255f3343253c75447ead95879c7 | <|skeleton|>
class Solution:
def unique_path(self, m: int, n: int) -> int:
"""O(n*m) space"""
<|body_0|>
def unique_path_less_space(self, m: int, n: int) -> int:
"""Instead of using m rows in the dp matrix, we only need to maintain one row. O(n) sapce"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def unique_path(self, m: int, n: int) -> int:
"""O(n*m) space"""
if m == 1 or n == 1:
return 1
dp = [[0] * n for _ in range(m)]
dp[0] = [1] * n
for i in range(m):
dp[i][0] = 1
for i in range(1, m):
for j in range(1, ... | the_stack_v2_python_sparse | 62_unique_path/solution.py | FluffyFu/Leetcode | train | 0 | |
29eba9e0c27314ff329dcb653fff6c43de0edf03 | [
"\"\"\"Logging server requires some default data for easy searching.\"\"\"\nusername = os.environ.get('BUILD_USER_ID', None)\nif username is None:\n username = os.environ.get('USER', '')\nself.default_data = {'type': 'qcatest', 'subtype': subtype, 'hostname': socket.gethostname(), 'user': username, 'build_url': ... | <|body_start_0|>
"""Logging server requires some default data for easy searching."""
username = os.environ.get('BUILD_USER_ID', None)
if username is None:
username = os.environ.get('USER', '')
self.default_data = {'type': 'qcatest', 'subtype': subtype, 'hostname': socket.geth... | Write data to remote logging server. | RemoteLogger | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteLogger:
"""Write data to remote logging server."""
def __init__(self, server, subtype='demo'):
"""Constructor used to remote server logging :param server: remote server to log :type server: string :param subtype: subtype to be used, defaults to 'demo' :type subtype: string"""
... | stack_v2_sparse_classes_75kplus_train_070417 | 2,116 | permissive | [
{
"docstring": "Constructor used to remote server logging :param server: remote server to log :type server: string :param subtype: subtype to be used, defaults to 'demo' :type subtype: string",
"name": "__init__",
"signature": "def __init__(self, server, subtype='demo')"
},
{
"docstring": "Logs ... | 2 | null | Implement the Python class `RemoteLogger` described below.
Class description:
Write data to remote logging server.
Method signatures and docstrings:
- def __init__(self, server, subtype='demo'): Constructor used to remote server logging :param server: remote server to log :type server: string :param subtype: subtype ... | Implement the Python class `RemoteLogger` described below.
Class description:
Write data to remote logging server.
Method signatures and docstrings:
- def __init__(self, server, subtype='demo'): Constructor used to remote server logging :param server: remote server to log :type server: string :param subtype: subtype ... | 100521fde1fb67536682cafecc2f91a6e2e8a6f8 | <|skeleton|>
class RemoteLogger:
"""Write data to remote logging server."""
def __init__(self, server, subtype='demo'):
"""Constructor used to remote server logging :param server: remote server to log :type server: string :param subtype: subtype to be used, defaults to 'demo' :type subtype: string"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RemoteLogger:
"""Write data to remote logging server."""
def __init__(self, server, subtype='demo'):
"""Constructor used to remote server logging :param server: remote server to log :type server: string :param subtype: subtype to be used, defaults to 'demo' :type subtype: string"""
"""Log... | the_stack_v2_python_sparse | boardfarm/dbclients/logstash.py | mattsm/boardfarm | train | 45 |
7980cac317f328fd6387eab10ef8309b30a155e7 | [
"self.pool = heapq.nlargest(k, nums)\nheapq.heapify(self.pool)\nself.k = k",
"if len(self.pool) < self.k:\n heapq.heappush(self.pool, val)\nelse:\n heapq.heappushpop(self.pool, val)\nreturn self.pool[0]"
] | <|body_start_0|>
self.pool = heapq.nlargest(k, nums)
heapq.heapify(self.pool)
self.k = k
<|end_body_0|>
<|body_start_1|>
if len(self.pool) < self.k:
heapq.heappush(self.pool, val)
else:
heapq.heappushpop(self.pool, val)
return self.pool[0]
<|end_b... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.pool = heapq.nlargest(k, nums)
heapq.heapify(... | stack_v2_sparse_classes_75kplus_train_070418 | 822 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011854 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | bf900574ebec530f4af4494f81c84b31d36c9933 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.pool = heapq.nlargest(k, nums)
heapq.heapify(self.pool)
self.k = k
def add(self, val):
""":type val: int :rtype: int"""
if len(self.pool) < self.k:
heapq.heap... | the_stack_v2_python_sparse | easy/kth_largest_element_in_a_stream.py | luozhiping/leetcode | train | 5 | |
97121c708408294e0bb9804efec9e695d6907591 | [
"location = self._parse_location(response)\nmeeting_map = {}\nfor item in response.css('.layoutArea li'):\n start = self._parse_start(item)\n if not start:\n continue\n meeting = Meeting(title='State Street Commission', description='', classification=COMMISSION, start=start, end=None, time_notes='',... | <|body_start_0|>
location = self._parse_location(response)
meeting_map = {}
for item in response.css('.layoutArea li'):
start = self._parse_start(item)
if not start:
continue
meeting = Meeting(title='State Street Commission', description='', cl... | ChiSsa1Spider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChiSsa1Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, item):
"""Parse start date and time."""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_070419 | 2,987 | permissive | [
{
"docstring": "`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Parse start date and time.",
"name": "_parse_start",
"signature":... | 4 | stack_v2_sparse_classes_30k_test_001398 | Implement the Python class `ChiSsa1Spider` described below.
Class description:
Implement the ChiSsa1Spider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- def _parse_... | Implement the Python class `ChiSsa1Spider` described below.
Class description:
Implement the ChiSsa1Spider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- def _parse_... | 611fce6a2705446e25a2fc33e32090a571eb35d1 | <|skeleton|>
class ChiSsa1Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, item):
"""Parse start date and time."""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChiSsa1Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
location = self._parse_location(response)
meeting_map = {}
for item in response.css('.layoutArea li'):... | the_stack_v2_python_sparse | city_scrapers/spiders/chi_ssa_1.py | City-Bureau/city-scrapers | train | 308 | |
aeede243f60600e080ec9bee7e0cd54734f9cfb0 | [
"if v is not None:\n if not v.get('eapType'):\n raise ValueError('eapType must be defined')\n try:\n wifi.eap_check_config(v)\n except wifi.ConfigureArgsError as e:\n raise ValueError(str(e))\nreturn v",
"security_type = values.get('securityType')\npsk = values.get('psk')\neapconfig ... | <|body_start_0|>
if v is not None:
if not v.get('eapType'):
raise ValueError('eapType must be defined')
try:
wifi.eap_check_config(v)
except wifi.ConfigureArgsError as e:
raise ValueError(str(e))
return v
<|end_body_0|>
... | WifiConfiguration | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WifiConfiguration:
def eap_config_validate(cls, v):
"""Custom validator for the eapConfig field"""
<|body_0|>
def validate_configuration(cls, values):
"""Validate the configuration"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if v is not None:
... | stack_v2_sparse_classes_75kplus_train_070420 | 13,352 | permissive | [
{
"docstring": "Custom validator for the eapConfig field",
"name": "eap_config_validate",
"signature": "def eap_config_validate(cls, v)"
},
{
"docstring": "Validate the configuration",
"name": "validate_configuration",
"signature": "def validate_configuration(cls, values)"
}
] | 2 | stack_v2_sparse_classes_30k_test_002956 | Implement the Python class `WifiConfiguration` described below.
Class description:
Implement the WifiConfiguration class.
Method signatures and docstrings:
- def eap_config_validate(cls, v): Custom validator for the eapConfig field
- def validate_configuration(cls, values): Validate the configuration | Implement the Python class `WifiConfiguration` described below.
Class description:
Implement the WifiConfiguration class.
Method signatures and docstrings:
- def eap_config_validate(cls, v): Custom validator for the eapConfig field
- def validate_configuration(cls, values): Validate the configuration
<|skeleton|>
cl... | 026b523c8c9e5d45910c490efb89194d72595be9 | <|skeleton|>
class WifiConfiguration:
def eap_config_validate(cls, v):
"""Custom validator for the eapConfig field"""
<|body_0|>
def validate_configuration(cls, values):
"""Validate the configuration"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WifiConfiguration:
def eap_config_validate(cls, v):
"""Custom validator for the eapConfig field"""
if v is not None:
if not v.get('eapType'):
raise ValueError('eapType must be defined')
try:
wifi.eap_check_config(v)
except wif... | the_stack_v2_python_sparse | robot-server/robot_server/service/legacy/models/networking.py | Opentrons/opentrons | train | 326 | |
da793730ffbc2d0521a106fc0cc5d003484e5f8e | [
"super(ReinforceWithBaseline, self).__init__()\nself.num_actions = num_actions\nself.hidden_size = 64\nself.dense1 = tf.keras.layers.Dense(self.hidden_size, activation='relu')\nself.dense2 = tf.keras.layers.Dense(self.num_actions, activation='softmax')\nself.critic1 = tf.keras.layers.Dense(self.hidden_size, activat... | <|body_start_0|>
super(ReinforceWithBaseline, self).__init__()
self.num_actions = num_actions
self.hidden_size = 64
self.dense1 = tf.keras.layers.Dense(self.hidden_size, activation='relu')
self.dense2 = tf.keras.layers.Dense(self.num_actions, activation='softmax')
self.cr... | ReinforceWithBaseline | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReinforceWithBaseline:
def __init__(self, state_size, num_actions):
"""The ReinforceWithBaseline class that inherits from tf.keras.Model. The forward pass calculates the policy for the agent given a batch of states. During training, ReinforceWithBaseLine estimates the value of each state... | stack_v2_sparse_classes_75kplus_train_070421 | 5,091 | no_license | [
{
"docstring": "The ReinforceWithBaseline class that inherits from tf.keras.Model. The forward pass calculates the policy for the agent given a batch of states. During training, ReinforceWithBaseLine estimates the value of each state to be used as a baseline to compare the policy's performance with. :param stat... | 4 | null | Implement the Python class `ReinforceWithBaseline` described below.
Class description:
Implement the ReinforceWithBaseline class.
Method signatures and docstrings:
- def __init__(self, state_size, num_actions): The ReinforceWithBaseline class that inherits from tf.keras.Model. The forward pass calculates the policy f... | Implement the Python class `ReinforceWithBaseline` described below.
Class description:
Implement the ReinforceWithBaseline class.
Method signatures and docstrings:
- def __init__(self, state_size, num_actions): The ReinforceWithBaseline class that inherits from tf.keras.Model. The forward pass calculates the policy f... | 8f0ed6982ae6aba938cbf39af0e2a6259478db1c | <|skeleton|>
class ReinforceWithBaseline:
def __init__(self, state_size, num_actions):
"""The ReinforceWithBaseline class that inherits from tf.keras.Model. The forward pass calculates the policy for the agent given a batch of states. During training, ReinforceWithBaseLine estimates the value of each state... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReinforceWithBaseline:
def __init__(self, state_size, num_actions):
"""The ReinforceWithBaseline class that inherits from tf.keras.Model. The forward pass calculates the policy for the agent given a batch of states. During training, ReinforceWithBaseLine estimates the value of each state to be used as... | the_stack_v2_python_sparse | hw6_REINFORCE/reinforce_with_baseline.py | YingSun0314/DeepLearningProjects | train | 0 | |
13a9eec5b9e72d3a869a196d6472043bc6b9036d | [
"problem = api.problem.get_problem(problem_id)\nif not problem:\n raise PicoException('Problem not found', status_code=404)\ncurr_user = api.user.get_user()\nproblem['solves'] = api.stats.get_problem_solves(problem['pid'])\nproblem['unlocked'] = problem['pid'] in api.problem.get_unlocked_pids(curr_user['tid'])\n... | <|body_start_0|>
problem = api.problem.get_problem(problem_id)
if not problem:
raise PicoException('Problem not found', status_code=404)
curr_user = api.user.get_user()
problem['solves'] = api.stats.get_problem_solves(problem['pid'])
problem['unlocked'] = problem['pid... | Get or update the availability of a specific problem. | Problem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Problem:
"""Get or update the availability of a specific problem."""
def get(self, problem_id):
"""Retrieve a specific problem."""
<|body_0|>
def patch(self, problem_id):
"""Update a specific problem. The only valid field for this method is "disabled". Other fiel... | stack_v2_sparse_classes_75kplus_train_070422 | 11,388 | permissive | [
{
"docstring": "Retrieve a specific problem.",
"name": "get",
"signature": "def get(self, problem_id)"
},
{
"docstring": "Update a specific problem. The only valid field for this method is \"disabled\". Other fields are pulled from the shell server, and can be updated via the PATCH /problems end... | 2 | null | Implement the Python class `Problem` described below.
Class description:
Get or update the availability of a specific problem.
Method signatures and docstrings:
- def get(self, problem_id): Retrieve a specific problem.
- def patch(self, problem_id): Update a specific problem. The only valid field for this method is "... | Implement the Python class `Problem` described below.
Class description:
Get or update the availability of a specific problem.
Method signatures and docstrings:
- def get(self, problem_id): Retrieve a specific problem.
- def patch(self, problem_id): Update a specific problem. The only valid field for this method is "... | 468035038afe00c6e7842b7e68ec45355ee1a224 | <|skeleton|>
class Problem:
"""Get or update the availability of a specific problem."""
def get(self, problem_id):
"""Retrieve a specific problem."""
<|body_0|>
def patch(self, problem_id):
"""Update a specific problem. The only valid field for this method is "disabled". Other fiel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Problem:
"""Get or update the availability of a specific problem."""
def get(self, problem_id):
"""Retrieve a specific problem."""
problem = api.problem.get_problem(problem_id)
if not problem:
raise PicoException('Problem not found', status_code=404)
curr_user ... | the_stack_v2_python_sparse | picoCTF-web/api/apps/v1/problems.py | zxc135781/picoCTF | train | 1 |
32078d034f26582cec3511d5a3b8b0354d65863d | [
"super().__init__(input_name=input_name, output_names=[output_name])\nself.crop_proportion = crop_proportion\nself.crop_shape = crop_shape",
"with tf.name_scope('CenterCropWithResize'):\n input = input[self.input_name]\n shape = tf.shape(input)\n image_height = shape[0]\n image_width = shape[1]\n h... | <|body_start_0|>
super().__init__(input_name=input_name, output_names=[output_name])
self.crop_proportion = crop_proportion
self.crop_shape = crop_shape
<|end_body_0|>
<|body_start_1|>
with tf.name_scope('CenterCropWithResize'):
input = input[self.input_name]
sha... | The CenterCropWithResize crops (and resizes) the given (image) input at the center. :Attributes: crop_proportion: (Float) Proportion of image to retain along the less-cropped side. 0.875 by default. crop_shape: (Array) The shape to crop. [1, 32, 32, 3] by default. | CenterCropWithResize | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CenterCropWithResize:
"""The CenterCropWithResize crops (and resizes) the given (image) input at the center. :Attributes: crop_proportion: (Float) Proportion of image to retain along the less-cropped side. 0.875 by default. crop_shape: (Array) The shape to crop. [1, 32, 32, 3] by default."""
... | stack_v2_sparse_classes_75kplus_train_070423 | 4,169 | permissive | [
{
"docstring": "Constructor, initialize member variables. :param crop_proportion: (Float) Proportion of image to retain along the less-cropped side. 0.875 by default. :param crop_shape: (Array) The shape to crop. [1, 32, 32, 3] by default. :param input_name: (String) The name of the input to apply this operatio... | 3 | stack_v2_sparse_classes_30k_train_007149 | Implement the Python class `CenterCropWithResize` described below.
Class description:
The CenterCropWithResize crops (and resizes) the given (image) input at the center. :Attributes: crop_proportion: (Float) Proportion of image to retain along the less-cropped side. 0.875 by default. crop_shape: (Array) The shape to c... | Implement the Python class `CenterCropWithResize` described below.
Class description:
The CenterCropWithResize crops (and resizes) the given (image) input at the center. :Attributes: crop_proportion: (Float) Proportion of image to retain along the less-cropped side. 0.875 by default. crop_shape: (Array) The shape to c... | 6907ae5781765f56a8492bfba594bfb3b9987f29 | <|skeleton|>
class CenterCropWithResize:
"""The CenterCropWithResize crops (and resizes) the given (image) input at the center. :Attributes: crop_proportion: (Float) Proportion of image to retain along the less-cropped side. 0.875 by default. crop_shape: (Array) The shape to crop. [1, 32, 32, 3] by default."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CenterCropWithResize:
"""The CenterCropWithResize crops (and resizes) the given (image) input at the center. :Attributes: crop_proportion: (Float) Proportion of image to retain along the less-cropped side. 0.875 by default. crop_shape: (Array) The shape to crop. [1, 32, 32, 3] by default."""
def __init__... | the_stack_v2_python_sparse | Preprocessing_Component/Preprocessing/CenterCropWithResize.py | BonifazStuhr/OFM | train | 0 |
453df5d56509724e346bede1f95801d911a90861 | [
"if not root:\n return\nl = self.invertTree(root.left)\nr = self.invertTree(root.right)\nroot.left = r\nroot.right = l\nreturn root",
"if root:\n self.invertTree(root.left)\n self.invertTree(root.right)\n root.left, root.right = (root.right, root.left)\nreturn root"
] | <|body_start_0|>
if not root:
return
l = self.invertTree(root.left)
r = self.invertTree(root.right)
root.left = r
root.right = l
return root
<|end_body_0|>
<|body_start_1|>
if root:
self.invertTree(root.left)
self.invertTree(ro... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Nov 05, 2021 13:16"""
<|body_0|>
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Mar 20, 2023 23:41"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_070424 | 1,710 | no_license | [
{
"docstring": "Nov 05, 2021 13:16",
"name": "invertTree",
"signature": "def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]"
},
{
"docstring": "Mar 20, 2023 23:41",
"name": "invertTree",
"signature": "def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]"... | 2 | stack_v2_sparse_classes_30k_train_038590 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Nov 05, 2021 13:16
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Mar 20, 2023 23:4... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Nov 05, 2021 13:16
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Mar 20, 2023 23:4... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Nov 05, 2021 13:16"""
<|body_0|>
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Mar 20, 2023 23:41"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Nov 05, 2021 13:16"""
if not root:
return
l = self.invertTree(root.left)
r = self.invertTree(root.right)
root.left = r
root.right = l
return root
def inve... | the_stack_v2_python_sparse | leetcode/solved/226_Invert_Binary_Tree/solution.py | sungminoh/algorithms | train | 0 | |
98db034bcef575d979fd1bcbf9d53896af0819c0 | [
"super().__init__(channel)\nconfig = get_config()\nself.LOGGER = logging.getLogger('fm.device.service.messages')\nself.exchange_name = config.RABBITMQ_MESSAGES_EXCHANGE_NAME\nself.exchange_type = config.RABBITMQ_MESSAGES_EXCHANGE_TYPE\nself.routing_key = '_internal'\nself.setup_exchange(self.exchange_name)",
"pay... | <|body_start_0|>
super().__init__(channel)
config = get_config()
self.LOGGER = logging.getLogger('fm.device.service.messages')
self.exchange_name = config.RABBITMQ_MESSAGES_EXCHANGE_NAME
self.exchange_type = config.RABBITMQ_MESSAGES_EXCHANGE_TYPE
self.routing_key = '_inte... | Receive and respond to internal message requests. | DeviceMessage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceMessage:
"""Receive and respond to internal message requests."""
def __init__(self, channel):
"""Override the __init__ method from Message class. Create the logger instance, and set the required config info. Call the setup_exchange function to start the communication"""
... | stack_v2_sparse_classes_75kplus_train_070425 | 9,633 | permissive | [
{
"docstring": "Override the __init__ method from Message class. Create the logger instance, and set the required config info. Call the setup_exchange function to start the communication",
"name": "__init__",
"signature": "def __init__(self, channel)"
},
{
"docstring": "Invoked by pika when a me... | 2 | stack_v2_sparse_classes_30k_val_000608 | Implement the Python class `DeviceMessage` described below.
Class description:
Receive and respond to internal message requests.
Method signatures and docstrings:
- def __init__(self, channel): Override the __init__ method from Message class. Create the logger instance, and set the required config info. Call the setu... | Implement the Python class `DeviceMessage` described below.
Class description:
Receive and respond to internal message requests.
Method signatures and docstrings:
- def __init__(self, channel): Override the __init__ method from Message class. Create the logger instance, and set the required config info. Call the setu... | 7d37690a8c42091a5892aa45518bfe6003728a18 | <|skeleton|>
class DeviceMessage:
"""Receive and respond to internal message requests."""
def __init__(self, channel):
"""Override the __init__ method from Message class. Create the logger instance, and set the required config info. Call the setup_exchange function to start the communication"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeviceMessage:
"""Receive and respond to internal message requests."""
def __init__(self, channel):
"""Override the __init__ method from Message class. Create the logger instance, and set the required config info. Call the setup_exchange function to start the communication"""
super().__in... | the_stack_v2_python_sparse | server/fm_server/device/service.py | nstoik/farm_monitor | train | 0 |
e049b6f78f5ce65cb884b5fb1437243f559f512a | [
"super().__init__(coordinator)\nself.entity_description = description\nself._remote = remote\nself._attr_unique_id = f'{coordinator.mac_address}-{description.key}'\nself._attr_device_info = DeviceInfo(connections={(dr.CONNECTION_NETWORK_MAC, coordinator.mac_address)})",
"response: SwitcherBaseResponse = None\nerr... | <|body_start_0|>
super().__init__(coordinator)
self.entity_description = description
self._remote = remote
self._attr_unique_id = f'{coordinator.mac_address}-{description.key}'
self._attr_device_info = DeviceInfo(connections={(dr.CONNECTION_NETWORK_MAC, coordinator.mac_address)})... | Representation of a Switcher climate entity. | SwitcherThermostatButtonEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SwitcherThermostatButtonEntity:
"""Representation of a Switcher climate entity."""
def __init__(self, coordinator: SwitcherDataUpdateCoordinator, description: SwitcherThermostatButtonEntityDescription, remote: SwitcherBreezeRemote) -> None:
"""Initialize the entity."""
<|body... | stack_v2_sparse_classes_75kplus_train_070426 | 5,671 | permissive | [
{
"docstring": "Initialize the entity.",
"name": "__init__",
"signature": "def __init__(self, coordinator: SwitcherDataUpdateCoordinator, description: SwitcherThermostatButtonEntityDescription, remote: SwitcherBreezeRemote) -> None"
},
{
"docstring": "Press the button.",
"name": "async_press... | 2 | stack_v2_sparse_classes_30k_train_021821 | Implement the Python class `SwitcherThermostatButtonEntity` described below.
Class description:
Representation of a Switcher climate entity.
Method signatures and docstrings:
- def __init__(self, coordinator: SwitcherDataUpdateCoordinator, description: SwitcherThermostatButtonEntityDescription, remote: SwitcherBreeze... | Implement the Python class `SwitcherThermostatButtonEntity` described below.
Class description:
Representation of a Switcher climate entity.
Method signatures and docstrings:
- def __init__(self, coordinator: SwitcherDataUpdateCoordinator, description: SwitcherThermostatButtonEntityDescription, remote: SwitcherBreeze... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SwitcherThermostatButtonEntity:
"""Representation of a Switcher climate entity."""
def __init__(self, coordinator: SwitcherDataUpdateCoordinator, description: SwitcherThermostatButtonEntityDescription, remote: SwitcherBreezeRemote) -> None:
"""Initialize the entity."""
<|body... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SwitcherThermostatButtonEntity:
"""Representation of a Switcher climate entity."""
def __init__(self, coordinator: SwitcherDataUpdateCoordinator, description: SwitcherThermostatButtonEntityDescription, remote: SwitcherBreezeRemote) -> None:
"""Initialize the entity."""
super().__init__(co... | the_stack_v2_python_sparse | homeassistant/components/switcher_kis/button.py | home-assistant/core | train | 35,501 |
c307b1a541a8541710c5cfa34e4a57b40733e25c | [
"self.params = {}\n'\\n 我们用标准差为weight_scale的高斯分布初始化参数W,\\n 偏置B的初始化都为0：\\n (其中randn函数是基于零均值和标准差的一个高斯分布)\\n '\nself.params['W1'] = weight_scale * np.random.randn(input_dims, hidden_dims)\nself.params['b1'] = np.zeros((hidden_dims,))\nself.params['W2'] = weight_scale * np.random.randn(hidde... | <|body_start_0|>
self.params = {}
'\n 我们用标准差为weight_scale的高斯分布初始化参数W,\n 偏置B的初始化都为0：\n (其中randn函数是基于零均值和标准差的一个高斯分布)\n '
self.params['W1'] = weight_scale * np.random.randn(input_dims, hidden_dims)
self.params['b1'] = np.zeros((hidden_dims,))
self.params[... | 首先，先初始化我们的神经网络。 毕竟，数据从输入层第一次流入到神经网络里，参数(W,B)不能为空，(w,b)是 一层的参数；(W,B)是所有层参数的统一。参数初始化也不能太大或太小，因此 (W,B)的初始化时很重要的，对整个神经网络的训练影响巨大，但如何proper 的初始化参数还没定论。 | TwoLayerNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoLayerNet:
"""首先，先初始化我们的神经网络。 毕竟，数据从输入层第一次流入到神经网络里，参数(W,B)不能为空，(w,b)是 一层的参数；(W,B)是所有层参数的统一。参数初始化也不能太大或太小，因此 (W,B)的初始化时很重要的，对整个神经网络的训练影响巨大，但如何proper 的初始化参数还没定论。"""
def __init__(self, input_dims=32 * 32 * 3, hidden_dims=100, num_classes=10, weight_scale=0.001):
"""我们把需要学习的参数(W,B)都存在s... | stack_v2_sparse_classes_75kplus_train_070427 | 36,287 | no_license | [
{
"docstring": "我们把需要学习的参数(W,B)都存在self.params字典中， 其中每个元素都是numpy array:",
"name": "__init__",
"signature": "def __init__(self, input_dims=32 * 32 * 3, hidden_dims=100, num_classes=10, weight_scale=0.001)"
},
{
"docstring": "首先，输入的数据X是一个多维的array,shape为(样本图片的个数N * 32*32*3), y是与输入数据X对应的正确标签，shape为(N... | 2 | stack_v2_sparse_classes_30k_test_002663 | Implement the Python class `TwoLayerNet` described below.
Class description:
首先，先初始化我们的神经网络。 毕竟，数据从输入层第一次流入到神经网络里，参数(W,B)不能为空，(w,b)是 一层的参数；(W,B)是所有层参数的统一。参数初始化也不能太大或太小，因此 (W,B)的初始化时很重要的，对整个神经网络的训练影响巨大，但如何proper 的初始化参数还没定论。
Method signatures and docstrings:
- def __init__(self, input_dims=32 * 32 * 3, hidden_dims=100,... | Implement the Python class `TwoLayerNet` described below.
Class description:
首先，先初始化我们的神经网络。 毕竟，数据从输入层第一次流入到神经网络里，参数(W,B)不能为空，(w,b)是 一层的参数；(W,B)是所有层参数的统一。参数初始化也不能太大或太小，因此 (W,B)的初始化时很重要的，对整个神经网络的训练影响巨大，但如何proper 的初始化参数还没定论。
Method signatures and docstrings:
- def __init__(self, input_dims=32 * 32 * 3, hidden_dims=100,... | e82d9577d8a7f4ce9950bc7e5a950592dff34bbd | <|skeleton|>
class TwoLayerNet:
"""首先，先初始化我们的神经网络。 毕竟，数据从输入层第一次流入到神经网络里，参数(W,B)不能为空，(w,b)是 一层的参数；(W,B)是所有层参数的统一。参数初始化也不能太大或太小，因此 (W,B)的初始化时很重要的，对整个神经网络的训练影响巨大，但如何proper 的初始化参数还没定论。"""
def __init__(self, input_dims=32 * 32 * 3, hidden_dims=100, num_classes=10, weight_scale=0.001):
"""我们把需要学习的参数(W,B)都存在s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TwoLayerNet:
"""首先，先初始化我们的神经网络。 毕竟，数据从输入层第一次流入到神经网络里，参数(W,B)不能为空，(w,b)是 一层的参数；(W,B)是所有层参数的统一。参数初始化也不能太大或太小，因此 (W,B)的初始化时很重要的，对整个神经网络的训练影响巨大，但如何proper 的初始化参数还没定论。"""
def __init__(self, input_dims=32 * 32 * 3, hidden_dims=100, num_classes=10, weight_scale=0.001):
"""我们把需要学习的参数(W,B)都存在self.params字典中... | the_stack_v2_python_sparse | assigment2/full_connect.py | hduyuanfu/SHUQI_SHIYAN | train | 0 |
4543fe908c8f40c729c61d69fbff56f825d7bfc6 | [
"host = get_live_server_host()\nport = get_live_server_port()\nasync with websockets.serve(self.handler, host, port):\n await self.bus.run()",
"channel_id = path.split('/')[-2]\nchannel_name = make_channel_group_name(channel_id)\nawait self.bus.subscribe(channel_name, websocket)\ntry:\n await websocket.wait... | <|body_start_0|>
host = get_live_server_host()
port = get_live_server_port()
async with websockets.serve(self.handler, host, port):
await self.bus.run()
<|end_body_0|>
<|body_start_1|>
channel_id = path.split('/')[-2]
channel_name = make_channel_group_name(channel_id... | WebsocketsPublisherApp | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebsocketsPublisherApp:
async def __call__(self):
"""Called once per session."""
<|body_0|>
async def handler(self, websocket, path):
"""Called once per new connection. Adds/removes the websocket connection to/from the channel group corresponding to the channel id fo... | stack_v2_sparse_classes_75kplus_train_070428 | 1,271 | permissive | [
{
"docstring": "Called once per session.",
"name": "__call__",
"signature": "async def __call__(self)"
},
{
"docstring": "Called once per new connection. Adds/removes the websocket connection to/from the channel group corresponding to the channel id found in the request's path.",
"name": "ha... | 2 | stack_v2_sparse_classes_30k_train_037475 | Implement the Python class `WebsocketsPublisherApp` described below.
Class description:
Implement the WebsocketsPublisherApp class.
Method signatures and docstrings:
- async def __call__(self): Called once per session.
- async def handler(self, websocket, path): Called once per new connection. Adds/removes the websoc... | Implement the Python class `WebsocketsPublisherApp` described below.
Class description:
Implement the WebsocketsPublisherApp class.
Method signatures and docstrings:
- async def __call__(self): Called once per session.
- async def handler(self, websocket, path): Called once per new connection. Adds/removes the websoc... | dd769be089d457cf36db2506520028bc5f506ac3 | <|skeleton|>
class WebsocketsPublisherApp:
async def __call__(self):
"""Called once per session."""
<|body_0|>
async def handler(self, websocket, path):
"""Called once per new connection. Adds/removes the websocket connection to/from the channel group corresponding to the channel id fo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WebsocketsPublisherApp:
async def __call__(self):
"""Called once per session."""
host = get_live_server_host()
port = get_live_server_port()
async with websockets.serve(self.handler, host, port):
await self.bus.run()
async def handler(self, websocket, path):
... | the_stack_v2_python_sparse | src/wagtail_live/publishers/websockets/app.py | 7saikat7/wagtail-live | train | 0 | |
0c39f494f433581204a4332e0c75c1b0d76975f7 | [
"if db_field.name == 'name':\n kwargs['widget'] = VerboseNameShowTextWidget()\nreturn super(ResourceReqAdminInline, self).formfield_for_dbfield(db_field, **kwargs)",
"ro_fields = super(ResourceReqAdminInline, self).get_readonly_fields(request, obj=obj)\nif 'name' in ro_fields:\n ro_fields.remove('name')\nre... | <|body_start_0|>
if db_field.name == 'name':
kwargs['widget'] = VerboseNameShowTextWidget()
return super(ResourceReqAdminInline, self).formfield_for_dbfield(db_field, **kwargs)
<|end_body_0|>
<|body_start_1|>
ro_fields = super(ResourceReqAdminInline, self).get_readonly_fields(reques... | ResourceReqAdminInline | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceReqAdminInline:
def formfield_for_dbfield(self, db_field, **kwargs):
"""Readonly resource name but form input still hidden"""
<|body_0|>
def get_readonly_fields(self, request, obj=None):
"""Remove 'name' from readonly fields because its value is required to c... | stack_v2_sparse_classes_75kplus_train_070429 | 2,533 | no_license | [
{
"docstring": "Readonly resource name but form input still hidden",
"name": "formfield_for_dbfield",
"signature": "def formfield_for_dbfield(self, db_field, **kwargs)"
},
{
"docstring": "Remove 'name' from readonly fields because its value is required to call properly Resource.get ResourceReqFo... | 2 | stack_v2_sparse_classes_30k_train_039918 | Implement the Python class `ResourceReqAdminInline` described below.
Class description:
Implement the ResourceReqAdminInline class.
Method signatures and docstrings:
- def formfield_for_dbfield(self, db_field, **kwargs): Readonly resource name but form input still hidden
- def get_readonly_fields(self, request, obj=N... | Implement the Python class `ResourceReqAdminInline` described below.
Class description:
Implement the ResourceReqAdminInline class.
Method signatures and docstrings:
- def formfield_for_dbfield(self, db_field, **kwargs): Readonly resource name but form input still hidden
- def get_readonly_fields(self, request, obj=N... | dd798dc9bd3321b17007ff131e7b1288a2cd3c36 | <|skeleton|>
class ResourceReqAdminInline:
def formfield_for_dbfield(self, db_field, **kwargs):
"""Readonly resource name but form input still hidden"""
<|body_0|>
def get_readonly_fields(self, request, obj=None):
"""Remove 'name' from readonly fields because its value is required to c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResourceReqAdminInline:
def formfield_for_dbfield(self, db_field, **kwargs):
"""Readonly resource name but form input still hidden"""
if db_field.name == 'name':
kwargs['widget'] = VerboseNameShowTextWidget()
return super(ResourceReqAdminInline, self).formfield_for_dbfield(... | the_stack_v2_python_sparse | controller/apps/resources/admin.py | m00dy/vct-controller | train | 2 | |
fde840e940baa324acb334122c1d4602dbb0bb74 | [
"try:\n if dataframe is not None:\n df = dataframe\n else:\n df = self.df\n if df is None:\n self.warning('Dataframe is empty: nothing to show')\n return\n num = len(df.columns.values)\nexcept Exception as e:\n self.err(e, self.show, 'Can not show dataframe')\n return\n... | <|body_start_0|>
try:
if dataframe is not None:
df = dataframe
else:
df = self.df
if df is None:
self.warning('Dataframe is empty: nothing to show')
return
num = len(df.columns.values)
except ... | Class to view the data | View | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class View:
"""Class to view the data"""
def show(self, rows: int=5, dataframe: pd.DataFrame=None) -> pd.DataFrame:
"""Display info about the dataframe :param rows: number of rows to show, defaults to 5 :param rows: int, optional :param dataframe: a pandas dataframe, defaults to None :para... | stack_v2_sparse_classes_75kplus_train_070430 | 3,823 | permissive | [
{
"docstring": "Display info about the dataframe :param rows: number of rows to show, defaults to 5 :param rows: int, optional :param dataframe: a pandas dataframe, defaults to None :param dataframe: pd.DataFrame, optional :return: a pandas dataframe :rtype: pd.DataFrame :example: ``ds.show()``",
"name": "s... | 6 | null | Implement the Python class `View` described below.
Class description:
Class to view the data
Method signatures and docstrings:
- def show(self, rows: int=5, dataframe: pd.DataFrame=None) -> pd.DataFrame: Display info about the dataframe :param rows: number of rows to show, defaults to 5 :param rows: int, optional :pa... | Implement the Python class `View` described below.
Class description:
Class to view the data
Method signatures and docstrings:
- def show(self, rows: int=5, dataframe: pd.DataFrame=None) -> pd.DataFrame: Display info about the dataframe :param rows: number of rows to show, defaults to 5 :param rows: int, optional :pa... | ea33a114cea6af046d50839a88ea1b2f3b8f895b | <|skeleton|>
class View:
"""Class to view the data"""
def show(self, rows: int=5, dataframe: pd.DataFrame=None) -> pd.DataFrame:
"""Display info about the dataframe :param rows: number of rows to show, defaults to 5 :param rows: int, optional :param dataframe: a pandas dataframe, defaults to None :para... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class View:
"""Class to view the data"""
def show(self, rows: int=5, dataframe: pd.DataFrame=None) -> pd.DataFrame:
"""Display info about the dataframe :param rows: number of rows to show, defaults to 5 :param rows: int, optional :param dataframe: a pandas dataframe, defaults to None :param dataframe: ... | the_stack_v2_python_sparse | dataswim/data/views.py | synw/dataswim | train | 11 |
15297ba52e6b0e0daecf1743890059a7c2088174 | [
"assert isinstance(name, str), 'Invalid name %s' % name\nassert isinstance(description, str), 'Invalid description %s' % description\nself.name = name.strip()\nself.description = description.strip()\nself._rights = {}\nself._defaults = []",
"if isinstance(names, str):\n names = (names,)\nassert isinstance(name... | <|body_start_0|>
assert isinstance(name, str), 'Invalid name %s' % name
assert isinstance(description, str), 'Invalid description %s' % description
self.name = name.strip()
self.description = description.strip()
self._rights = {}
self._defaults = []
<|end_body_0|>
<|body... | The ACL type model. | TypeAcl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TypeAcl:
"""The ACL type model."""
def __init__(self, name, description):
"""Construct the type model. @param name: string The type name. @param description: string The description for the type."""
<|body_0|>
def rightsFor(self, names):
"""Provides the rights for... | stack_v2_sparse_classes_75kplus_train_070431 | 5,791 | no_license | [
{
"docstring": "Construct the type model. @param name: string The type name. @param description: string The description for the type.",
"name": "__init__",
"signature": "def __init__(self, name, description)"
},
{
"docstring": "Provides the rights for the provided name(s). @param names: string|I... | 4 | stack_v2_sparse_classes_30k_val_002849 | Implement the Python class `TypeAcl` described below.
Class description:
The ACL type model.
Method signatures and docstrings:
- def __init__(self, name, description): Construct the type model. @param name: string The type name. @param description: string The description for the type.
- def rightsFor(self, names): Pr... | Implement the Python class `TypeAcl` described below.
Class description:
The ACL type model.
Method signatures and docstrings:
- def __init__(self, name, description): Construct the type model. @param name: string The type name. @param description: string The description for the type.
- def rightsFor(self, names): Pr... | a10cb774c8cbc5010950eed9342413846734fea7 | <|skeleton|>
class TypeAcl:
"""The ACL type model."""
def __init__(self, name, description):
"""Construct the type model. @param name: string The type name. @param description: string The description for the type."""
<|body_0|>
def rightsFor(self, names):
"""Provides the rights for... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TypeAcl:
"""The ACL type model."""
def __init__(self, name, description):
"""Construct the type model. @param name: string The type name. @param description: string The description for the type."""
assert isinstance(name, str), 'Invalid name %s' % name
assert isinstance(descriptio... | the_stack_v2_python_sparse | plugins/support-acl/acl/spec.py | bonomali/Ally-Py | train | 0 |
ae94392bc08cf338d3b9447e38e958d49144632e | [
"cnt = 0\nfor i in range(len(A)):\n p, q = (0, i)\n while p < len(A) and q < len(B):\n while p < len(A) and q < len(B) and (A[p] != B[q]):\n p += 1\n q += 1\n t = 0\n while p < len(A) and q < len(B) and (A[p] == B[q]):\n p += 1\n q += 1\n ... | <|body_start_0|>
cnt = 0
for i in range(len(A)):
p, q = (0, i)
while p < len(A) and q < len(B):
while p < len(A) and q < len(B) and (A[p] != B[q]):
p += 1
q += 1
t = 0
while p < len(A) and q <... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findLength(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_0|>
def findLength1(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cnt = 0
... | stack_v2_sparse_classes_75kplus_train_070432 | 1,625 | no_license | [
{
"docstring": ":type A: List[int] :type B: List[int] :rtype: int",
"name": "findLength",
"signature": "def findLength(self, A, B)"
},
{
"docstring": ":type A: List[int] :type B: List[int] :rtype: int",
"name": "findLength1",
"signature": "def findLength1(self, A, B)"
}
] | 2 | stack_v2_sparse_classes_30k_train_038165 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLength(self, A, B): :type A: List[int] :type B: List[int] :rtype: int
- def findLength1(self, A, B): :type A: List[int] :type B: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLength(self, A, B): :type A: List[int] :type B: List[int] :rtype: int
- def findLength1(self, A, B): :type A: List[int] :type B: List[int] :rtype: int
<|skeleton|>
class... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def findLength(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_0|>
def findLength1(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findLength(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: int"""
cnt = 0
for i in range(len(A)):
p, q = (0, i)
while p < len(A) and q < len(B):
while p < len(A) and q < len(B) and (A[p] != B[q]):
p... | the_stack_v2_python_sparse | py/leetcode/718.py | wfeng1991/learnpy | train | 0 | |
9e9f4b553b7151b0c0db0cdc26ceb86dd82f278a | [
"if not root:\n return 0\n\ndef recur(node: TreeNode, min_ancestor: int, max_ancestor: int) -> int:\n max_diff = max(abs(node.val - min_ancestor), abs(node.val - max_ancestor))\n min_ancestor = min(min_ancestor, node.val)\n max_ancestor = max(max_ancestor, node.val)\n if node.left:\n max_diff ... | <|body_start_0|>
if not root:
return 0
def recur(node: TreeNode, min_ancestor: int, max_ancestor: int) -> int:
max_diff = max(abs(node.val - min_ancestor), abs(node.val - max_ancestor))
min_ancestor = min(min_ancestor, node.val)
max_ancestor = max(max_anc... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxAncestorDiff(self, root: TreeNode) -> int:
"""When going down the descendants: - keep the minimum value of ancestor - keep the maximum value of ancestor => Allows to do the diff When going up (end of recursion): - look at the max difference on left and right - take the m... | stack_v2_sparse_classes_75kplus_train_070433 | 2,439 | no_license | [
{
"docstring": "When going down the descendants: - keep the minimum value of ancestor - keep the maximum value of ancestor => Allows to do the diff When going up (end of recursion): - look at the max difference on left and right - take the max with own difference with above Complexity is O(N)",
"name": "max... | 2 | stack_v2_sparse_classes_30k_train_024884 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxAncestorDiff(self, root: TreeNode) -> int: When going down the descendants: - keep the minimum value of ancestor - keep the maximum value of ancestor => Allows to do the d... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxAncestorDiff(self, root: TreeNode) -> int: When going down the descendants: - keep the minimum value of ancestor - keep the maximum value of ancestor => Allows to do the d... | 3ffcfee5cedf421d5de6d0dec4ba53b0eecbbff8 | <|skeleton|>
class Solution:
def maxAncestorDiff(self, root: TreeNode) -> int:
"""When going down the descendants: - keep the minimum value of ancestor - keep the maximum value of ancestor => Allows to do the diff When going up (end of recursion): - look at the max difference on left and right - take the m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxAncestorDiff(self, root: TreeNode) -> int:
"""When going down the descendants: - keep the minimum value of ancestor - keep the maximum value of ancestor => Allows to do the diff When going up (end of recursion): - look at the max difference on left and right - take the max with own di... | the_stack_v2_python_sparse | binary_tree/MaxDifferenceBetweenNodeAndAncestor.py | QuentinDuval/PythonExperiments | train | 3 | |
c94385fb8c043eaf9d6c19c652fe808cad1639d0 | [
"app_id, handler_name, action = (int(app_id), handler_name, action)\nhandler = None\nprint(app_id, handler_name, action)\nself._app_id = app_id\nhandlers = platform_defines.get_platform_by_id(app_id)\nif handler_name in handlers:\n handler = handlers[handler_name]()\n print(handler)\nelse:\n print('handler... | <|body_start_0|>
app_id, handler_name, action = (int(app_id), handler_name, action)
handler = None
print(app_id, handler_name, action)
self._app_id = app_id
handlers = platform_defines.get_platform_by_id(app_id)
if handler_name in handlers:
handler = handlers[... | HandlerMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HandlerMixin:
def handle_request_with_process(self, app_id, handler_name, action):
"""处理app_id, action,寻找相对于的模块"""
<|body_0|>
def collect_params(self, keys):
"""从请求中获取参数"""
<|body_1|>
def on_find_handler(self, handler):
"""分发到各自的类中执行各自的方法"""
... | stack_v2_sparse_classes_75kplus_train_070434 | 2,344 | no_license | [
{
"docstring": "处理app_id, action,寻找相对于的模块",
"name": "handle_request_with_process",
"signature": "def handle_request_with_process(self, app_id, handler_name, action)"
},
{
"docstring": "从请求中获取参数",
"name": "collect_params",
"signature": "def collect_params(self, keys)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_006461 | Implement the Python class `HandlerMixin` described below.
Class description:
Implement the HandlerMixin class.
Method signatures and docstrings:
- def handle_request_with_process(self, app_id, handler_name, action): 处理app_id, action,寻找相对于的模块
- def collect_params(self, keys): 从请求中获取参数
- def on_find_handler(self, hand... | Implement the Python class `HandlerMixin` described below.
Class description:
Implement the HandlerMixin class.
Method signatures and docstrings:
- def handle_request_with_process(self, app_id, handler_name, action): 处理app_id, action,寻找相对于的模块
- def collect_params(self, keys): 从请求中获取参数
- def on_find_handler(self, hand... | 8b78411413aae01e7ade0eec36f37746d0e54cd4 | <|skeleton|>
class HandlerMixin:
def handle_request_with_process(self, app_id, handler_name, action):
"""处理app_id, action,寻找相对于的模块"""
<|body_0|>
def collect_params(self, keys):
"""从请求中获取参数"""
<|body_1|>
def on_find_handler(self, handler):
"""分发到各自的类中执行各自的方法"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HandlerMixin:
def handle_request_with_process(self, app_id, handler_name, action):
"""处理app_id, action,寻找相对于的模块"""
app_id, handler_name, action = (int(app_id), handler_name, action)
handler = None
print(app_id, handler_name, action)
self._app_id = app_id
handler... | the_stack_v2_python_sparse | tornado_SDK/utils/handler_mixn.py | du-debug/tornado_SDK | train | 0 | |
e8716122b3b4a7e66fe8292e3cda19c83803a370 | [
"tmp, ans = (x, 0)\nif x < 0:\n return False\nwhile tmp > 0:\n ans = ans * 10 + tmp % 10\n tmp = tmp // 10\nreturn True if x == ans else False",
"if x < 0:\n return False\nx = str(x)\nreturn True if x == x[::-1] else False"
] | <|body_start_0|>
tmp, ans = (x, 0)
if x < 0:
return False
while tmp > 0:
ans = ans * 10 + tmp % 10
tmp = tmp // 10
return True if x == ans else False
<|end_body_0|>
<|body_start_1|>
if x < 0:
return False
x = str(x)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome2(self, x: int) -> bool:
"""time complexity : O(log10(N)) space complexity : O(1)"""
<|body_0|>
def isPalindrome1(self, x: int) -> bool:
"""time complexity :O(N) space complexity : O(1)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_75kplus_train_070435 | 689 | no_license | [
{
"docstring": "time complexity : O(log10(N)) space complexity : O(1)",
"name": "isPalindrome2",
"signature": "def isPalindrome2(self, x: int) -> bool"
},
{
"docstring": "time complexity :O(N) space complexity : O(1)",
"name": "isPalindrome1",
"signature": "def isPalindrome1(self, x: int... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome2(self, x: int) -> bool: time complexity : O(log10(N)) space complexity : O(1)
- def isPalindrome1(self, x: int) -> bool: time complexity :O(N) space complexity :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome2(self, x: int) -> bool: time complexity : O(log10(N)) space complexity : O(1)
- def isPalindrome1(self, x: int) -> bool: time complexity :O(N) space complexity :... | 29cb49a166a1dfd19c39613a0e9895c545a6bfe9 | <|skeleton|>
class Solution:
def isPalindrome2(self, x: int) -> bool:
"""time complexity : O(log10(N)) space complexity : O(1)"""
<|body_0|>
def isPalindrome1(self, x: int) -> bool:
"""time complexity :O(N) space complexity : O(1)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isPalindrome2(self, x: int) -> bool:
"""time complexity : O(log10(N)) space complexity : O(1)"""
tmp, ans = (x, 0)
if x < 0:
return False
while tmp > 0:
ans = ans * 10 + tmp % 10
tmp = tmp // 10
return True if x == ans e... | the_stack_v2_python_sparse | 08.Math/PalindromeNum.py | mjmingd/study_algorithm | train | 0 | |
2b21ef1c80899255fdce4476aa5fdea9999f2482 | [
"parityBitOdd = Parity.Field('odd')\nparityBitOdd.setData(0)\nself.assertEqual(parityBitOdd.pack(), 1 << 31, 'Parity Not Calculated Properly')\nparityBitEven = Parity.Field('even')\nparityBitEven.setData(0)\nself.assertEqual(parityBitEven.pack(), 0, 'Parity Not Calculated Properly')",
"parityBitOdd = Parity.Field... | <|body_start_0|>
parityBitOdd = Parity.Field('odd')
parityBitOdd.setData(0)
self.assertEqual(parityBitOdd.pack(), 1 << 31, 'Parity Not Calculated Properly')
parityBitEven = Parity.Field('even')
parityBitEven.setData(0)
self.assertEqual(parityBitEven.pack(), 0, 'Parity Not... | Test Parity Pack/Unpack Algorithm | testParity | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class testParity:
"""Test Parity Pack/Unpack Algorithm"""
def testEmptyMessage(self):
"""Verify Case of no bit set in message"""
<|body_0|>
def testFullMessage(self):
"""Verify Case of all bits set in message"""
<|body_1|>
def testAFewCases(self):
... | stack_v2_sparse_classes_75kplus_train_070436 | 5,073 | permissive | [
{
"docstring": "Verify Case of no bit set in message",
"name": "testEmptyMessage",
"signature": "def testEmptyMessage(self)"
},
{
"docstring": "Verify Case of all bits set in message",
"name": "testFullMessage",
"signature": "def testFullMessage(self)"
},
{
"docstring": "Further ... | 5 | stack_v2_sparse_classes_30k_train_050777 | Implement the Python class `testParity` described below.
Class description:
Test Parity Pack/Unpack Algorithm
Method signatures and docstrings:
- def testEmptyMessage(self): Verify Case of no bit set in message
- def testFullMessage(self): Verify Case of all bits set in message
- def testAFewCases(self): Further test... | Implement the Python class `testParity` described below.
Class description:
Test Parity Pack/Unpack Algorithm
Method signatures and docstrings:
- def testEmptyMessage(self): Verify Case of no bit set in message
- def testFullMessage(self): Verify Case of all bits set in message
- def testAFewCases(self): Further test... | 077c979c7eb2aae206f6052c2a67e68ecc5b35a8 | <|skeleton|>
class testParity:
"""Test Parity Pack/Unpack Algorithm"""
def testEmptyMessage(self):
"""Verify Case of no bit set in message"""
<|body_0|>
def testFullMessage(self):
"""Verify Case of all bits set in message"""
<|body_1|>
def testAFewCases(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class testParity:
"""Test Parity Pack/Unpack Algorithm"""
def testEmptyMessage(self):
"""Verify Case of no bit set in message"""
parityBitOdd = Parity.Field('odd')
parityBitOdd.setData(0)
self.assertEqual(parityBitOdd.pack(), 1 << 31, 'Parity Not Calculated Properly')
pa... | the_stack_v2_python_sparse | ARINC429/UnitTests/ParityTest.py | superliujian/Py429 | train | 1 |
ca30922a8c09f3288b753e6eca7bd1dea1e0f174 | [
"new_contact = Contact()\nnew_contact.first_name = request.data['first_name']\nnew_contact.last_name = request.data['last_name']\nnew_contact.address = request.data['address']\nnew_contact.email = request.data['email']\nnew_contact.phone_number = request.data['phone_number']\ncustom_user = CustomUser.objects.get(us... | <|body_start_0|>
new_contact = Contact()
new_contact.first_name = request.data['first_name']
new_contact.last_name = request.data['last_name']
new_contact.address = request.data['address']
new_contact.email = request.data['email']
new_contact.phone_number = request.data['... | Contacts for helloDanh | Contacts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Contacts:
"""Contacts for helloDanh"""
def create(self, request):
"""Handle POST operations Returns: Response -- JSON serialized Contact instance"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Handle GET requests for single contact Returns: Response -- JS... | stack_v2_sparse_classes_75kplus_train_070437 | 3,739 | no_license | [
{
"docstring": "Handle POST operations Returns: Response -- JSON serialized Contact instance",
"name": "create",
"signature": "def create(self, request)"
},
{
"docstring": "Handle GET requests for single contact Returns: Response -- JSON serialized contact instance",
"name": "retrieve",
... | 5 | stack_v2_sparse_classes_30k_train_005144 | Implement the Python class `Contacts` described below.
Class description:
Contacts for helloDanh
Method signatures and docstrings:
- def create(self, request): Handle POST operations Returns: Response -- JSON serialized Contact instance
- def retrieve(self, request, pk=None): Handle GET requests for single contact Re... | Implement the Python class `Contacts` described below.
Class description:
Contacts for helloDanh
Method signatures and docstrings:
- def create(self, request): Handle POST operations Returns: Response -- JSON serialized Contact instance
- def retrieve(self, request, pk=None): Handle GET requests for single contact Re... | 678cecfa51bac3211752ef0967b7668cde4c2ab4 | <|skeleton|>
class Contacts:
"""Contacts for helloDanh"""
def create(self, request):
"""Handle POST operations Returns: Response -- JSON serialized Contact instance"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Handle GET requests for single contact Returns: Response -- JS... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Contacts:
"""Contacts for helloDanh"""
def create(self, request):
"""Handle POST operations Returns: Response -- JSON serialized Contact instance"""
new_contact = Contact()
new_contact.first_name = request.data['first_name']
new_contact.last_name = request.data['last_name'... | the_stack_v2_python_sparse | helloDanhApi/views/contact.py | KrystalGates/helloDanhApi | train | 0 |
94e5b5b259903c80ac81bb5243c42457bc6fc59e | [
"record = self.shopware_record\nfor sw_category in record['categories']:\n self._import_dependency(sw_category['id'], 'shopware.product.category')",
"record = self.shopware_record\nproduct_model = 'shopware.product.product'\nsw_main_detail_id = record['mainDetail']['id']\nimport_record(self.session, product_mo... | <|body_start_0|>
record = self.shopware_record
for sw_category in record['categories']:
self._import_dependency(sw_category['id'], 'shopware.product.category')
<|end_body_0|>
<|body_start_1|>
record = self.shopware_record
product_model = 'shopware.product.product'
sw... | ArticleImporter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArticleImporter:
def _import_dependencies(self):
"""Import the dependencies for the record"""
<|body_0|>
def _after_import(self, binding):
"""Hook called at the end of the import"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
record = self.shopware... | stack_v2_sparse_classes_75kplus_train_070438 | 23,991 | no_license | [
{
"docstring": "Import the dependencies for the record",
"name": "_import_dependencies",
"signature": "def _import_dependencies(self)"
},
{
"docstring": "Hook called at the end of the import",
"name": "_after_import",
"signature": "def _after_import(self, binding)"
}
] | 2 | stack_v2_sparse_classes_30k_train_051853 | Implement the Python class `ArticleImporter` described below.
Class description:
Implement the ArticleImporter class.
Method signatures and docstrings:
- def _import_dependencies(self): Import the dependencies for the record
- def _after_import(self, binding): Hook called at the end of the import | Implement the Python class `ArticleImporter` described below.
Class description:
Implement the ArticleImporter class.
Method signatures and docstrings:
- def _import_dependencies(self): Import the dependencies for the record
- def _after_import(self, binding): Hook called at the end of the import
<|skeleton|>
class ... | b7463b0e3b2069a7980d1b5bc38f658fe6637f67 | <|skeleton|>
class ArticleImporter:
def _import_dependencies(self):
"""Import the dependencies for the record"""
<|body_0|>
def _after_import(self, binding):
"""Hook called at the end of the import"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ArticleImporter:
def _import_dependencies(self):
"""Import the dependencies for the record"""
record = self.shopware_record
for sw_category in record['categories']:
self._import_dependency(sw_category['id'], 'shopware.product.category')
def _after_import(self, binding)... | the_stack_v2_python_sparse | shopwareerpconnect/product.py | antorajjacob/Shopware-Odoo-Connector | train | 0 | |
5782fa1e86da2e3c2f79ac7665a462530197d269 | [
"if isinstance(value, int) or isinstance(value, float):\n return Sync.sync_value(value=value, device=device, op=op)\nelif isinstance(value, Tensor):\n return Sync.sync_tensor(value=value, device=device, op=op)\nelif isinstance(value, Dict):\n return Sync.sync_tensor_dict(value=value, device=device, op=op)\... | <|body_start_0|>
if isinstance(value, int) or isinstance(value, float):
return Sync.sync_value(value=value, device=device, op=op)
elif isinstance(value, Tensor):
return Sync.sync_tensor(value=value, device=device, op=op)
elif isinstance(value, Dict):
return Sy... | 同步数据 | Sync | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sync:
"""同步数据"""
def sync(value: Union[Tensor, int, float, Dict[str, Tensor]], device: torch.device, op: ReduceOp=ReduceOp.SUM) -> Union[Tensor, int, float, Dict[str, Tensor]]:
"""同步数据, in place 操作 :param value: 需要同步的数据 :param device: 当前 device :param op: op :return: 同步后的数据"""
... | stack_v2_sparse_classes_75kplus_train_070439 | 3,778 | permissive | [
{
"docstring": "同步数据, in place 操作 :param value: 需要同步的数据 :param device: 当前 device :param op: op :return: 同步后的数据",
"name": "sync",
"signature": "def sync(value: Union[Tensor, int, float, Dict[str, Tensor]], device: torch.device, op: ReduceOp=ReduceOp.SUM) -> Union[Tensor, int, float, Dict[str, Tensor]]"
... | 4 | null | Implement the Python class `Sync` described below.
Class description:
同步数据
Method signatures and docstrings:
- def sync(value: Union[Tensor, int, float, Dict[str, Tensor]], device: torch.device, op: ReduceOp=ReduceOp.SUM) -> Union[Tensor, int, float, Dict[str, Tensor]]: 同步数据, in place 操作 :param value: 需要同步的数据 :param ... | Implement the Python class `Sync` described below.
Class description:
同步数据
Method signatures and docstrings:
- def sync(value: Union[Tensor, int, float, Dict[str, Tensor]], device: torch.device, op: ReduceOp=ReduceOp.SUM) -> Union[Tensor, int, float, Dict[str, Tensor]]: 同步数据, in place 操作 :param value: 需要同步的数据 :param ... | ef83261a366bd8d7c259aa112da14f3fa7cdf918 | <|skeleton|>
class Sync:
"""同步数据"""
def sync(value: Union[Tensor, int, float, Dict[str, Tensor]], device: torch.device, op: ReduceOp=ReduceOp.SUM) -> Union[Tensor, int, float, Dict[str, Tensor]]:
"""同步数据, in place 操作 :param value: 需要同步的数据 :param device: 当前 device :param op: op :return: 同步后的数据"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Sync:
"""同步数据"""
def sync(value: Union[Tensor, int, float, Dict[str, Tensor]], device: torch.device, op: ReduceOp=ReduceOp.SUM) -> Union[Tensor, int, float, Dict[str, Tensor]]:
"""同步数据, in place 操作 :param value: 需要同步的数据 :param device: 当前 device :param op: op :return: 同步后的数据"""
if isinstan... | the_stack_v2_python_sparse | easytext/utils/distributed/sync_util.py | freedomkite/easytext | train | 0 |
6371c480a582a25d00d420323b00f120d925f1bc | [
"try:\n if name is None or size is None:\n raise Exception('Cannot create logical volume without specified name and size')\n if uuid_str is None:\n uuid_str = str(uuid.uuid4())\n data = {'name': name, 'uuid': uuid_str, 'size': size}\n self.logger.debug('Creating logical volume %s in VG %s ... | <|body_start_0|>
try:
if name is None or size is None:
raise Exception('Cannot create logical volume without specified name and size')
if uuid_str is None:
uuid_str = str(uuid.uuid4())
data = {'name': name, 'uuid': uuid_str, 'size': size}
... | VolumeGroup | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeGroup:
def create_lv(self, name=None, uuid_str=None, size=None):
"""Create a logical volume in this volume group. :param name: Name of the logical volume :param uuid_str: A UUID4-format string specifying the LV uuid. Will be generated if left as None :param size: The size of the lo... | stack_v2_sparse_classes_75kplus_train_070440 | 5,626 | permissive | [
{
"docstring": "Create a logical volume in this volume group. :param name: Name of the logical volume :param uuid_str: A UUID4-format string specifying the LV uuid. Will be generated if left as None :param size: The size of the logical volume",
"name": "create_lv",
"signature": "def create_lv(self, name... | 4 | stack_v2_sparse_classes_30k_train_032207 | Implement the Python class `VolumeGroup` described below.
Class description:
Implement the VolumeGroup class.
Method signatures and docstrings:
- def create_lv(self, name=None, uuid_str=None, size=None): Create a logical volume in this volume group. :param name: Name of the logical volume :param uuid_str: A UUID4-for... | Implement the Python class `VolumeGroup` described below.
Class description:
Implement the VolumeGroup class.
Method signatures and docstrings:
- def create_lv(self, name=None, uuid_str=None, size=None): Create a logical volume in this volume group. :param name: Name of the logical volume :param uuid_str: A UUID4-for... | f99abfa4337f8cbb591513aac404b11208d4187c | <|skeleton|>
class VolumeGroup:
def create_lv(self, name=None, uuid_str=None, size=None):
"""Create a logical volume in this volume group. :param name: Name of the logical volume :param uuid_str: A UUID4-format string specifying the LV uuid. Will be generated if left as None :param size: The size of the lo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VolumeGroup:
def create_lv(self, name=None, uuid_str=None, size=None):
"""Create a logical volume in this volume group. :param name: Name of the logical volume :param uuid_str: A UUID4-format string specifying the LV uuid. Will be generated if left as None :param size: The size of the logical volume""... | the_stack_v2_python_sparse | python/drydock_provisioner/drivers/node/maasdriver/models/volumegroup.py | airshipit/drydock | train | 13 | |
aa431b9798c5148574f25fee0ee21204fef0165f | [
"instructions = {}\nif flatten:\n obj, unflatten_kwargs = cls._flatten_dataframe(dataframe=obj)\n instructions['unflatten_kwargs'] = unflatten_kwargs\nobj.to_html(buf=file_path, **to_kwargs)\nreturn instructions",
"obj = pd.read_html(io=file_path, **read_kwargs)[0]\nif unflatten_kwargs is not None:\n if ... | <|body_start_0|>
instructions = {}
if flatten:
obj, unflatten_kwargs = cls._flatten_dataframe(dataframe=obj)
instructions['unflatten_kwargs'] = unflatten_kwargs
obj.to_html(buf=file_path, **to_kwargs)
return instructions
<|end_body_0|>
<|body_start_1|>
ob... | A static class for managing pandas html files. | _HTMLFormatter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _HTMLFormatter:
"""A static class for managing pandas html files."""
def to(cls, obj: pd.DataFrame, file_path: str, flatten: bool=True, **to_kwargs) -> dict:
"""Save the given dataframe to the html file path given. :param obj: The dataframe to save. :param file_path: The file to save... | stack_v2_sparse_classes_75kplus_train_070441 | 35,951 | permissive | [
{
"docstring": "Save the given dataframe to the html file path given. :param obj: The dataframe to save. :param file_path: The file to save to. :param flatten: Whether to flatten the dataframe before saving. For some formats it is mandatory to enable flattening, otherwise saving and loading the dataframe will c... | 2 | stack_v2_sparse_classes_30k_train_005559 | Implement the Python class `_HTMLFormatter` described below.
Class description:
A static class for managing pandas html files.
Method signatures and docstrings:
- def to(cls, obj: pd.DataFrame, file_path: str, flatten: bool=True, **to_kwargs) -> dict: Save the given dataframe to the html file path given. :param obj: ... | Implement the Python class `_HTMLFormatter` described below.
Class description:
A static class for managing pandas html files.
Method signatures and docstrings:
- def to(cls, obj: pd.DataFrame, file_path: str, flatten: bool=True, **to_kwargs) -> dict: Save the given dataframe to the html file path given. :param obj: ... | b5fe0c05ae7f5818a4a5a5a40245c851ff9b2c77 | <|skeleton|>
class _HTMLFormatter:
"""A static class for managing pandas html files."""
def to(cls, obj: pd.DataFrame, file_path: str, flatten: bool=True, **to_kwargs) -> dict:
"""Save the given dataframe to the html file path given. :param obj: The dataframe to save. :param file_path: The file to save... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _HTMLFormatter:
"""A static class for managing pandas html files."""
def to(cls, obj: pd.DataFrame, file_path: str, flatten: bool=True, **to_kwargs) -> dict:
"""Save the given dataframe to the html file path given. :param obj: The dataframe to save. :param file_path: The file to save to. :param f... | the_stack_v2_python_sparse | mlrun/package/packagers/pandas_packagers.py | mlrun/mlrun | train | 1,093 |
00c7c8479f5033857464096bc1842f54a7c4694b | [
"if not self.logical_drives:\n msg = 'No logical drives found on the controller %(controller)s' % {'controller': str(self.controller_id)}\n LOG.debug(msg)\n raise exception.IloLogicalDriveNotFoundError(msg)\nlds = [{'Actions': [{'Action': 'LogicalDriveDelete'}], 'VolumeUniqueIdentifier': logical_drive.volu... | <|body_start_0|>
if not self.logical_drives:
msg = 'No logical drives found on the controller %(controller)s' % {'controller': str(self.controller_id)}
LOG.debug(msg)
raise exception.IloLogicalDriveNotFoundError(msg)
lds = [{'Actions': [{'Action': 'LogicalDriveDelete'... | Class that defines the functionality for SmartSorageConfig Resources. | HPESmartStorageConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HPESmartStorageConfig:
"""Class that defines the functionality for SmartSorageConfig Resources."""
def delete_raid(self):
"""Clears the RAID configuration from the system."""
<|body_0|>
def create_raid(self, raid_config):
"""Create the raid configuration on the h... | stack_v2_sparse_classes_75kplus_train_070442 | 4,150 | permissive | [
{
"docstring": "Clears the RAID configuration from the system.",
"name": "delete_raid",
"signature": "def delete_raid(self)"
},
{
"docstring": "Create the raid configuration on the hardware. :param raid_config: A dictionary containing target raid configuration data. This data stucture should be ... | 2 | stack_v2_sparse_classes_30k_test_002080 | Implement the Python class `HPESmartStorageConfig` described below.
Class description:
Class that defines the functionality for SmartSorageConfig Resources.
Method signatures and docstrings:
- def delete_raid(self): Clears the RAID configuration from the system.
- def create_raid(self, raid_config): Create the raid c... | Implement the Python class `HPESmartStorageConfig` described below.
Class description:
Class that defines the functionality for SmartSorageConfig Resources.
Method signatures and docstrings:
- def delete_raid(self): Clears the RAID configuration from the system.
- def create_raid(self, raid_config): Create the raid c... | 35c711e391b839bbb93c24880e08e4ac7554dae6 | <|skeleton|>
class HPESmartStorageConfig:
"""Class that defines the functionality for SmartSorageConfig Resources."""
def delete_raid(self):
"""Clears the RAID configuration from the system."""
<|body_0|>
def create_raid(self, raid_config):
"""Create the raid configuration on the h... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HPESmartStorageConfig:
"""Class that defines the functionality for SmartSorageConfig Resources."""
def delete_raid(self):
"""Clears the RAID configuration from the system."""
if not self.logical_drives:
msg = 'No logical drives found on the controller %(controller)s' % {'contr... | the_stack_v2_python_sparse | proliantutils/redfish/resources/system/smart_storage_config.py | anta-nok/proliantutils | train | 0 |
0debc914d1f3b8a5aeecca1493d036788133d8df | [
"res = []\nnums.sort()\nfor i in range(len(nums) - 2):\n if i > 0 and nums[i] == nums[i - 1]:\n continue\n l, r = (i + 1, len(nums) - 1)\n while l < r:\n s = nums[i] + nums[l] + nums[r]\n if s < 0:\n l += 1\n elif s > 0:\n r -= 1\n else:\n ... | <|body_start_0|>
res = []
nums.sort()
for i in range(len(nums) - 2):
if i > 0 and nums[i] == nums[i - 1]:
continue
l, r = (i + 1, len(nums) - 1)
while l < r:
s = nums[i] + nums[l] + nums[r]
if s < 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def threeSum_myfirst(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
nu... | stack_v2_sparse_classes_75kplus_train_070443 | 1,959 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum",
"signature": "def threeSum(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum_myfirst",
"signature": "def threeSum_myfirst(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001387 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSum_myfirst(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSum_myfirst(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class Solu... | f0d9070fa292ca36971a465a805faddb12025482 | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def threeSum_myfirst(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
res = []
nums.sort()
for i in range(len(nums) - 2):
if i > 0 and nums[i] == nums[i - 1]:
continue
l, r = (i + 1, len(nums) - 1)
while l < ... | the_stack_v2_python_sparse | 15.3Sum.py | JerryRoc/leetcode | train | 0 | |
1948aad05d7e89cd1b82015c8ab045a67269b214 | [
"dict = Counter(nums)\nfor key, value in dict.items():\n if value > 1:\n return key",
"tortoise = nums[0]\nhare = nums[0]\nwhile True:\n tortoise = nums[tortoise]\n hare = nums[nums[hare]]\n if tortoise == hare:\n break\nptr1 = nums[0]\nptr2 = tortoise\nwhile ptr1 != ptr2:\n ptr1 = nu... | <|body_start_0|>
dict = Counter(nums)
for key, value in dict.items():
if value > 1:
return key
<|end_body_0|>
<|body_start_1|>
tortoise = nums[0]
hare = nums[0]
while True:
tortoise = nums[tortoise]
hare = nums[nums[hare]]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dict = Counter(nums)
for key, va... | stack_v2_sparse_classes_75kplus_train_070444 | 1,088 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findDuplicate2",
"signature": "def findDuplicate2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014328 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def findDu... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
dict = Counter(nums)
for key, value in dict.items():
if value > 1:
return key
def findDuplicate2(self, nums):
""":type nums: List[int] :rtype: int"""
tortoi... | the_stack_v2_python_sparse | 287. Find the Duplicate Number/duplicate.py | Macielyoung/LeetCode | train | 1 | |
ba2b7612c34aae146eb61ca807ca15fb5e52c70b | [
"self.__status = False\nrospy.Subscriber(override_topic, std_msgs.msg.Bool, callback=self.__update)\nself.__status_lock = threading.Lock()",
"self.__status_lock.acquire()\nstatus_equality = self.__status == other_status\nself.__status_lock.release()\nreturn status_equality",
"self.__status_lock.acquire()\nself.... | <|body_start_0|>
self.__status = False
rospy.Subscriber(override_topic, std_msgs.msg.Bool, callback=self.__update)
self.__status_lock = threading.Lock()
<|end_body_0|>
<|body_start_1|>
self.__status_lock.acquire()
status_equality = self.__status == other_status
self.__st... | Automatically maintain an override status. | OverrideStatus | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OverrideStatus:
"""Automatically maintain an override status."""
def __init__(self, override_topic):
"""Initialize this override status with a subscriber. This class possibly doesn't need the lock, but I left it just in case."""
<|body_0|>
def __eq__(self, other_status):... | stack_v2_sparse_classes_75kplus_train_070445 | 3,766 | no_license | [
{
"docstring": "Initialize this override status with a subscriber. This class possibly doesn't need the lock, but I left it just in case.",
"name": "__init__",
"signature": "def __init__(self, override_topic)"
},
{
"docstring": "Allow easy comparisons of this override status with a boolean.",
... | 3 | null | Implement the Python class `OverrideStatus` described below.
Class description:
Automatically maintain an override status.
Method signatures and docstrings:
- def __init__(self, override_topic): Initialize this override status with a subscriber. This class possibly doesn't need the lock, but I left it just in case.
-... | Implement the Python class `OverrideStatus` described below.
Class description:
Automatically maintain an override status.
Method signatures and docstrings:
- def __init__(self, override_topic): Initialize this override status with a subscriber. This class possibly doesn't need the lock, but I left it just in case.
-... | 0c5911b59dda4fa4439f6a96a66dab435436204e | <|skeleton|>
class OverrideStatus:
"""Automatically maintain an override status."""
def __init__(self, override_topic):
"""Initialize this override status with a subscriber. This class possibly doesn't need the lock, but I left it just in case."""
<|body_0|>
def __eq__(self, other_status):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OverrideStatus:
"""Automatically maintain an override status."""
def __init__(self, override_topic):
"""Initialize this override status with a subscriber. This class possibly doesn't need the lock, but I left it just in case."""
self.__status = False
rospy.Subscriber(override_topi... | the_stack_v2_python_sparse | packages/communication/ezrassor_topic_switch/source/ezrassor_topic_switch/topic_switch.py | FlaSpaceInst/EZ-RASSOR | train | 49 |
1045cff0cce963fa728dd835717731fa7d764b9d | [
"new_list = []\nfor i in matrix:\n for j in i:\n new_list.append(j)\nprint(new_list)\nnew_list.sort()\nreturn new_list[k - 1]",
"n = len(matrix)\n\ndef check(mid):\n i, j = (n - 1, 0)\n num = 0\n while j < n and i >= 0:\n if matrix[i][j] <= mid:\n num += i + 1\n j +... | <|body_start_0|>
new_list = []
for i in matrix:
for j in i:
new_list.append(j)
print(new_list)
new_list.sort()
return new_list[k - 1]
<|end_body_0|>
<|body_start_1|>
n = len(matrix)
def check(mid):
i, j = (n - 1, 0)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kthSmallest(self, matrix: List[List[int]], k: int) -> int:
"""将二维矩阵变成一维矩阵之后，从小到大排序好 取第k-1即可。 :param matrix: :param k: :return:"""
<|body_0|>
def kthSmallest2(self, matrix: List[List[int]], k: int) -> int:
"""二分法 完全利用有序矩阵的两个特性 :param matrix: :param k: :r... | stack_v2_sparse_classes_75kplus_train_070446 | 2,021 | no_license | [
{
"docstring": "将二维矩阵变成一维矩阵之后，从小到大排序好 取第k-1即可。 :param matrix: :param k: :return:",
"name": "kthSmallest",
"signature": "def kthSmallest(self, matrix: List[List[int]], k: int) -> int"
},
{
"docstring": "二分法 完全利用有序矩阵的两个特性 :param matrix: :param k: :return:",
"name": "kthSmallest2",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_005047 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, matrix: List[List[int]], k: int) -> int: 将二维矩阵变成一维矩阵之后，从小到大排序好 取第k-1即可。 :param matrix: :param k: :return:
- def kthSmallest2(self, matrix: List[List[int]], ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, matrix: List[List[int]], k: int) -> int: 将二维矩阵变成一维矩阵之后，从小到大排序好 取第k-1即可。 :param matrix: :param k: :return:
- def kthSmallest2(self, matrix: List[List[int]], ... | 578cacff5851c5c2522981693c34e3c318002d30 | <|skeleton|>
class Solution:
def kthSmallest(self, matrix: List[List[int]], k: int) -> int:
"""将二维矩阵变成一维矩阵之后，从小到大排序好 取第k-1即可。 :param matrix: :param k: :return:"""
<|body_0|>
def kthSmallest2(self, matrix: List[List[int]], k: int) -> int:
"""二分法 完全利用有序矩阵的两个特性 :param matrix: :param k: :r... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def kthSmallest(self, matrix: List[List[int]], k: int) -> int:
"""将二维矩阵变成一维矩阵之后，从小到大排序好 取第k-1即可。 :param matrix: :param k: :return:"""
new_list = []
for i in matrix:
for j in i:
new_list.append(j)
print(new_list)
new_list.sort()
... | the_stack_v2_python_sparse | 有序矩阵中第K小的元素.py | cjrzs/MyLeetCode | train | 8 | |
07f7a01edb1cbeaf1f87abf2cef5fd1eede01a72 | [
"with codecs.open(Json_File, 'r', 'utf-8-sig') as f:\n predict_data = json.load(f)\nself.Four_officials_report = predict_data['four_officials_report']\nself.action_data = predict_data['data']\nself.action_index = 0\nself.len = len(self.action_data)\nself.stack_action_index = []\nself.Team_Roster = {'Home': None,... | <|body_start_0|>
with codecs.open(Json_File, 'r', 'utf-8-sig') as f:
predict_data = json.load(f)
self.Four_officials_report = predict_data['four_officials_report']
self.action_data = predict_data['data']
self.action_index = 0
self.len = len(self.action_data)
s... | 这个纠正器，用来根据四官报告来对算饭检测出来的号码进行更正。 | Number_Rectifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Number_Rectifier:
"""这个纠正器，用来根据四官报告来对算饭检测出来的号码进行更正。"""
def __init__(self, Json_File):
"""载入基本信息 Json_File : 算法运行完成后的写入的Json file"""
<|body_0|>
def generate_number_list(self, players):
"""生成号码列表,和球员号码字典"""
<|body_1|>
def rectify(self):
"""开始根据... | stack_v2_sparse_classes_75kplus_train_070447 | 5,657 | permissive | [
{
"docstring": "载入基本信息 Json_File : 算法运行完成后的写入的Json file",
"name": "__init__",
"signature": "def __init__(self, Json_File)"
},
{
"docstring": "生成号码列表,和球员号码字典",
"name": "generate_number_list",
"signature": "def generate_number_list(self, players)"
},
{
"docstring": "开始根据四官来纠正号码",
... | 6 | null | Implement the Python class `Number_Rectifier` described below.
Class description:
这个纠正器，用来根据四官报告来对算饭检测出来的号码进行更正。
Method signatures and docstrings:
- def __init__(self, Json_File): 载入基本信息 Json_File : 算法运行完成后的写入的Json file
- def generate_number_list(self, players): 生成号码列表,和球员号码字典
- def rectify(self): 开始根据四官来纠正号码
- def n... | Implement the Python class `Number_Rectifier` described below.
Class description:
这个纠正器，用来根据四官报告来对算饭检测出来的号码进行更正。
Method signatures and docstrings:
- def __init__(self, Json_File): 载入基本信息 Json_File : 算法运行完成后的写入的Json file
- def generate_number_list(self, players): 生成号码列表,和球员号码字典
- def rectify(self): 开始根据四官来纠正号码
- def n... | c496e911a89870a9b6988d93f80e680d01ee8afc | <|skeleton|>
class Number_Rectifier:
"""这个纠正器，用来根据四官报告来对算饭检测出来的号码进行更正。"""
def __init__(self, Json_File):
"""载入基本信息 Json_File : 算法运行完成后的写入的Json file"""
<|body_0|>
def generate_number_list(self, players):
"""生成号码列表,和球员号码字典"""
<|body_1|>
def rectify(self):
"""开始根据... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Number_Rectifier:
"""这个纠正器，用来根据四官报告来对算饭检测出来的号码进行更正。"""
def __init__(self, Json_File):
"""载入基本信息 Json_File : 算法运行完成后的写入的Json file"""
with codecs.open(Json_File, 'r', 'utf-8-sig') as f:
predict_data = json.load(f)
self.Four_officials_report = predict_data['four_officials... | the_stack_v2_python_sparse | utils_BINGO/Number_Rectifier.py | IMBINGO95/FairMOT | train | 0 |
399be71da9d7bff67258e5c72d0c686168a5ba73 | [
"self.count = 0\nself.batch = batch\nself.atomistic = atomistic",
"if not self.batch and (not self.atomistic):\n self._add_sample(sample_value)\nelif not self.batch and self.atomistic:\n n_atoms = sample_value.size(0)\n for i in range(n_atoms):\n self._add_sample(sample_value[i, :])\nelif self.bat... | <|body_start_0|>
self.count = 0
self.batch = batch
self.atomistic = atomistic
<|end_body_0|>
<|body_start_1|>
if not self.batch and (not self.atomistic):
self._add_sample(sample_value)
elif not self.batch and self.atomistic:
n_atoms = sample_value.size(0)... | StatisticsAccumulator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StatisticsAccumulator:
def __init__(self, batch=False, atomistic=False):
"""Use the incremental Welford algorithm described in [1]_ to accumulate the mean and standard deviation over a set of samples. Args: batch: If set to true, assumes sample is batch and uses leading dimension as batc... | stack_v2_sparse_classes_75kplus_train_070448 | 22,927 | permissive | [
{
"docstring": "Use the incremental Welford algorithm described in [1]_ to accumulate the mean and standard deviation over a set of samples. Args: batch: If set to true, assumes sample is batch and uses leading dimension as batch size atomistic: If set to true, average over atom dimension References: ----------... | 4 | null | Implement the Python class `StatisticsAccumulator` described below.
Class description:
Implement the StatisticsAccumulator class.
Method signatures and docstrings:
- def __init__(self, batch=False, atomistic=False): Use the incremental Welford algorithm described in [1]_ to accumulate the mean and standard deviation ... | Implement the Python class `StatisticsAccumulator` described below.
Class description:
Implement the StatisticsAccumulator class.
Method signatures and docstrings:
- def __init__(self, batch=False, atomistic=False): Use the incremental Welford algorithm described in [1]_ to accumulate the mean and standard deviation ... | 9ca068d1f43ee4aff5bc2b6b0d5714c3ac484470 | <|skeleton|>
class StatisticsAccumulator:
def __init__(self, batch=False, atomistic=False):
"""Use the incremental Welford algorithm described in [1]_ to accumulate the mean and standard deviation over a set of samples. Args: batch: If set to true, assumes sample is batch and uses leading dimension as batc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StatisticsAccumulator:
def __init__(self, batch=False, atomistic=False):
"""Use the incremental Welford algorithm described in [1]_ to accumulate the mean and standard deviation over a set of samples. Args: batch: If set to true, assumes sample is batch and uses leading dimension as batch size atomist... | the_stack_v2_python_sparse | custom/datasqlite.py | MichaelSluydts/schnetpack | train | 0 | |
11b9c027c8420358bcd243fbcd4663e49156abdd | [
"super().__init__(dev_id)\nself._attr_device_class = device_class\nself.which = -1\nself.onoff = -1\nself._attr_unique_id = f'{combine_hex(dev_id)}-{device_class}'\nself._attr_name = dev_name",
"pushed = None\nif packet.data[6] == 48:\n pushed = 1\nelif packet.data[6] == 32:\n pushed = 0\nself.schedule_upda... | <|body_start_0|>
super().__init__(dev_id)
self._attr_device_class = device_class
self.which = -1
self.onoff = -1
self._attr_unique_id = f'{combine_hex(dev_id)}-{device_class}'
self._attr_name = dev_name
<|end_body_0|>
<|body_start_1|>
pushed = None
if pac... | Representation of EnOcean binary sensors such as wall switches. Supported EEPs (EnOcean Equipment Profiles): - F6-02-01 (Light and Blind Control - Application Style 2) - F6-02-02 (Light and Blind Control - Application Style 1) | EnOceanBinarySensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnOceanBinarySensor:
"""Representation of EnOcean binary sensors such as wall switches. Supported EEPs (EnOcean Equipment Profiles): - F6-02-01 (Light and Blind Control - Application Style 2) - F6-02-02 (Light and Blind Control - Application Style 1)"""
def __init__(self, dev_id: list[int], ... | stack_v2_sparse_classes_75kplus_train_070449 | 3,643 | permissive | [
{
"docstring": "Initialize the EnOcean binary sensor.",
"name": "__init__",
"signature": "def __init__(self, dev_id: list[int], dev_name: str, device_class: BinarySensorDeviceClass | None) -> None"
},
{
"docstring": "Fire an event with the data that have changed. This method is called when there... | 2 | stack_v2_sparse_classes_30k_train_051662 | Implement the Python class `EnOceanBinarySensor` described below.
Class description:
Representation of EnOcean binary sensors such as wall switches. Supported EEPs (EnOcean Equipment Profiles): - F6-02-01 (Light and Blind Control - Application Style 2) - F6-02-02 (Light and Blind Control - Application Style 1)
Method... | Implement the Python class `EnOceanBinarySensor` described below.
Class description:
Representation of EnOcean binary sensors such as wall switches. Supported EEPs (EnOcean Equipment Profiles): - F6-02-01 (Light and Blind Control - Application Style 2) - F6-02-02 (Light and Blind Control - Application Style 1)
Method... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class EnOceanBinarySensor:
"""Representation of EnOcean binary sensors such as wall switches. Supported EEPs (EnOcean Equipment Profiles): - F6-02-01 (Light and Blind Control - Application Style 2) - F6-02-02 (Light and Blind Control - Application Style 1)"""
def __init__(self, dev_id: list[int], ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EnOceanBinarySensor:
"""Representation of EnOcean binary sensors such as wall switches. Supported EEPs (EnOcean Equipment Profiles): - F6-02-01 (Light and Blind Control - Application Style 2) - F6-02-02 (Light and Blind Control - Application Style 1)"""
def __init__(self, dev_id: list[int], dev_name: str... | the_stack_v2_python_sparse | homeassistant/components/enocean/binary_sensor.py | home-assistant/core | train | 35,501 |
695330fe4c0bdacde5878f17c044e709e0aa0276 | [
"self._update_interval = update_interval\nself._fps = 0\nself._tick_count = 0\nself._last_time_updated = time.time()",
"self._tick_count += 1\ncurrent_time = time.time()\nif current_time - self._last_time_updated > self._update_interval:\n self._fps = int(round(self._tick_count / (current_time - self._last_tim... | <|body_start_0|>
self._update_interval = update_interval
self._fps = 0
self._tick_count = 0
self._last_time_updated = time.time()
<|end_body_0|>
<|body_start_1|>
self._tick_count += 1
current_time = time.time()
if current_time - self._last_time_updated > self._up... | The counter for calculating the FPS Invoke `get_FPS()` at each frame. The counter will count how many calls within a specified updating interval. Within a updating interval, the returned FPS value won't be updated until the starting of next updating interval. | FPSCounter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FPSCounter:
"""The counter for calculating the FPS Invoke `get_FPS()` at each frame. The counter will count how many calls within a specified updating interval. Within a updating interval, the returned FPS value won't be updated until the starting of next updating interval."""
def __init__(s... | stack_v2_sparse_classes_75kplus_train_070450 | 2,603 | no_license | [
{
"docstring": "Constructor @param update_interval The time interval in seconds for updating the FPS value",
"name": "__init__",
"signature": "def __init__(self, update_interval=1.0)"
},
{
"docstring": "Update and get the calculated FPS",
"name": "get_FPS",
"signature": "def get_FPS(self... | 2 | stack_v2_sparse_classes_30k_train_041012 | Implement the Python class `FPSCounter` described below.
Class description:
The counter for calculating the FPS Invoke `get_FPS()` at each frame. The counter will count how many calls within a specified updating interval. Within a updating interval, the returned FPS value won't be updated until the starting of next up... | Implement the Python class `FPSCounter` described below.
Class description:
The counter for calculating the FPS Invoke `get_FPS()` at each frame. The counter will count how many calls within a specified updating interval. Within a updating interval, the returned FPS value won't be updated until the starting of next up... | f82cd74cdb711dcb4710a4fdf25dfc52666f4898 | <|skeleton|>
class FPSCounter:
"""The counter for calculating the FPS Invoke `get_FPS()` at each frame. The counter will count how many calls within a specified updating interval. Within a updating interval, the returned FPS value won't be updated until the starting of next updating interval."""
def __init__(s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FPSCounter:
"""The counter for calculating the FPS Invoke `get_FPS()` at each frame. The counter will count how many calls within a specified updating interval. Within a updating interval, the returned FPS value won't be updated until the starting of next updating interval."""
def __init__(self, update_i... | the_stack_v2_python_sparse | mlgame/gamedev/generic.py | leooel97895750/Python_Game_ML | train | 1 |
58f1d956630e8d14dcec3fb01728b365981353dd | [
"if dialect.name == 'postgresql':\n return dialect.type_descriptor(UUID())\nelse:\n return dialect.type_descriptor(CHAR(32))",
"if value is None:\n return value\nelif dialect.name == 'postgresql':\n return str(value)\nelif not isinstance(value, uuid.UUID):\n return '{0:.32x}'.format(uuid.UUID(value... | <|body_start_0|>
if dialect.name == 'postgresql':
return dialect.type_descriptor(UUID())
else:
return dialect.type_descriptor(CHAR(32))
<|end_body_0|>
<|body_start_1|>
if value is None:
return value
elif dialect.name == 'postgresql':
retur... | Platform-independent GUID type. Uses Postgresql's UUID type, otherwise uses CHAR(32), storing as stringified hex values. Taken from http://docs.sqlalchemy.org/en/latest/core/custom_types.html ?highlight=guid#backend-agnostic-guid-type Does not work if you simply do the following: id = Column(UUID(as_uuid=True), primary... | GUID | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GUID:
"""Platform-independent GUID type. Uses Postgresql's UUID type, otherwise uses CHAR(32), storing as stringified hex values. Taken from http://docs.sqlalchemy.org/en/latest/core/custom_types.html ?highlight=guid#backend-agnostic-guid-type Does not work if you simply do the following: id = Co... | stack_v2_sparse_classes_75kplus_train_070451 | 8,387 | permissive | [
{
"docstring": "Load the native type for the database type being used :param dialect: database type being used :return: native type of the database",
"name": "load_dialect_impl",
"signature": "def load_dialect_impl(dialect)"
},
{
"docstring": "Format the value for insertion in to the database :p... | 4 | null | Implement the Python class `GUID` described below.
Class description:
Platform-independent GUID type. Uses Postgresql's UUID type, otherwise uses CHAR(32), storing as stringified hex values. Taken from http://docs.sqlalchemy.org/en/latest/core/custom_types.html ?highlight=guid#backend-agnostic-guid-type Does not work ... | Implement the Python class `GUID` described below.
Class description:
Platform-independent GUID type. Uses Postgresql's UUID type, otherwise uses CHAR(32), storing as stringified hex values. Taken from http://docs.sqlalchemy.org/en/latest/core/custom_types.html ?highlight=guid#backend-agnostic-guid-type Does not work ... | c49134e6e2edee39bebe4a08b6b0f9b83c309588 | <|skeleton|>
class GUID:
"""Platform-independent GUID type. Uses Postgresql's UUID type, otherwise uses CHAR(32), storing as stringified hex values. Taken from http://docs.sqlalchemy.org/en/latest/core/custom_types.html ?highlight=guid#backend-agnostic-guid-type Does not work if you simply do the following: id = Co... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GUID:
"""Platform-independent GUID type. Uses Postgresql's UUID type, otherwise uses CHAR(32), storing as stringified hex values. Taken from http://docs.sqlalchemy.org/en/latest/core/custom_types.html ?highlight=guid#backend-agnostic-guid-type Does not work if you simply do the following: id = Column(UUID(as_... | the_stack_v2_python_sparse | biblib/models.py | adsabs/biblib-service | train | 5 |
e41e961429193a8788cb53e87991122266fbaf9b | [
"super(HeaderUnit, self).__init__(**kwargs)\nself._unit_type = HeaderUnit.UNIT_TYPE\nself._unit_category = HeaderUnit.UNIT_CATEGORY\nself._name = 'header'\nself.head_data = {'name': HeadDataItem('', '', 0, 0, dtype=dt.STRING), 'revision': HeadDataItem('#REVISION#1', '{:>10}', 1, 0, dtype=dt.STRING), 'node_count': H... | <|body_start_0|>
super(HeaderUnit, self).__init__(**kwargs)
self._unit_type = HeaderUnit.UNIT_TYPE
self._unit_category = HeaderUnit.UNIT_CATEGORY
self._name = 'header'
self.head_data = {'name': HeadDataItem('', '', 0, 0, dtype=dt.STRING), 'revision': HeadDataItem('#REVISION#1', '... | This class deals with the data file values at the top of the file. These contain the global variables for the model such as water temperature, key matrix coefficients and the total number of nodes. There is only ever one of these units in every dat file - at the very top - so it seems convenient to put it in this modul... | HeaderUnit | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HeaderUnit:
"""This class deals with the data file values at the top of the file. These contain the global variables for the model such as water temperature, key matrix coefficients and the total number of nodes. There is only ever one of these units in every dat file - at the very top - so it se... | stack_v2_sparse_classes_75kplus_train_070452 | 23,622 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Reads the given data into the object. Args: unit_data (list): The raw file data to be processed.",
"name": "readUnitData",
"signature": "def readUnitData(self, unit_data, fil... | 3 | null | Implement the Python class `HeaderUnit` described below.
Class description:
This class deals with the data file values at the top of the file. These contain the global variables for the model such as water temperature, key matrix coefficients and the total number of nodes. There is only ever one of these units in ever... | Implement the Python class `HeaderUnit` described below.
Class description:
This class deals with the data file values at the top of the file. These contain the global variables for the model such as water temperature, key matrix coefficients and the total number of nodes. There is only ever one of these units in ever... | e8e7249a511d52b29d34be0951d6a05f346b836c | <|skeleton|>
class HeaderUnit:
"""This class deals with the data file values at the top of the file. These contain the global variables for the model such as water temperature, key matrix coefficients and the total number of nodes. There is only ever one of these units in every dat file - at the very top - so it se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HeaderUnit:
"""This class deals with the data file values at the top of the file. These contain the global variables for the model such as water temperature, key matrix coefficients and the total number of nodes. There is only ever one of these units in every dat file - at the very top - so it seems convenien... | the_stack_v2_python_sparse | ship/fmp/datunits/isisunit.py | duncan-r/SHIP | train | 6 |
d723c19cae370055641529ebaeaa219f49371327 | [
"if self.cluster_id is None:\n raise SkipTest('The cluster_id is not specified, can not run ostf')\nself.fuel_web.run_ostf(cluster_id=self.cluster_id, should_fail=getattr(self, 'ostf_tests_should_failed', 0), failed_test_name=getattr(self, 'failed_test_name', None))",
"if self.cluster_id is None:\n raise Sk... | <|body_start_0|>
if self.cluster_id is None:
raise SkipTest('The cluster_id is not specified, can not run ostf')
self.fuel_web.run_ostf(cluster_id=self.cluster_id, should_fail=getattr(self, 'ostf_tests_should_failed', 0), failed_test_name=getattr(self, 'failed_test_name', None))
<|end_body_0... | Basic actions for OSTF tests health_check - run sanity and smoke OSTF tests health_check_sanity_smoke_ha - run sanity, smoke and ha OSTF tests health_check_ha - run ha OSTF tests | HealthCheckActions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HealthCheckActions:
"""Basic actions for OSTF tests health_check - run sanity and smoke OSTF tests health_check_sanity_smoke_ha - run sanity, smoke and ha OSTF tests health_check_ha - run ha OSTF tests"""
def health_check(self):
"""Run health checker Skip action if cluster doesn't ex... | stack_v2_sparse_classes_75kplus_train_070453 | 3,407 | no_license | [
{
"docstring": "Run health checker Skip action if cluster doesn't exist",
"name": "health_check",
"signature": "def health_check(self)"
},
{
"docstring": "Run health checker Sanity, Smoke and HA Skip action if cluster doesn't exist",
"name": "health_check_sanity_smoke_ha",
"signature": "... | 4 | stack_v2_sparse_classes_30k_train_053066 | Implement the Python class `HealthCheckActions` described below.
Class description:
Basic actions for OSTF tests health_check - run sanity and smoke OSTF tests health_check_sanity_smoke_ha - run sanity, smoke and ha OSTF tests health_check_ha - run ha OSTF tests
Method signatures and docstrings:
- def health_check(se... | Implement the Python class `HealthCheckActions` described below.
Class description:
Basic actions for OSTF tests health_check - run sanity and smoke OSTF tests health_check_sanity_smoke_ha - run sanity, smoke and ha OSTF tests health_check_ha - run ha OSTF tests
Method signatures and docstrings:
- def health_check(se... | e825c2f0483ab2030ddc47c8a2bdc85a80e5da02 | <|skeleton|>
class HealthCheckActions:
"""Basic actions for OSTF tests health_check - run sanity and smoke OSTF tests health_check_sanity_smoke_ha - run sanity, smoke and ha OSTF tests health_check_ha - run ha OSTF tests"""
def health_check(self):
"""Run health checker Skip action if cluster doesn't ex... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HealthCheckActions:
"""Basic actions for OSTF tests health_check - run sanity and smoke OSTF tests health_check_sanity_smoke_ha - run sanity, smoke and ha OSTF tests health_check_ha - run ha OSTF tests"""
def health_check(self):
"""Run health checker Skip action if cluster doesn't exist"""
... | the_stack_v2_python_sparse | system_test/actions/ostf_actions.py | rkhozinov/fuel-qa | train | 1 |
cf20cee78c5ead87ddbd400a598df5ff96dcde24 | [
"sample_atom = atoms[-1]\nself.atoms = []\nself.name = sample_atom.res_name\nself.chain_id = sample_atom.chain_id\nself.res_seq = sample_atom.res_seq\nself.ins_code = sample_atom.ins_code\nself.fixed = 0\nself.ffname = 'WAT'\nself.map = {}\nself.reference = ref\nself.is_n_term = 0\nself.is_c_term = 0\nfor atom_ in ... | <|body_start_0|>
sample_atom = atoms[-1]
self.atoms = []
self.name = sample_atom.res_name
self.chain_id = sample_atom.chain_id
self.res_seq = sample_atom.res_seq
self.ins_code = sample_atom.ins_code
self.fixed = 0
self.ffname = 'WAT'
self.map = {}
... | Generic ligand class. | LIG | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LIG:
"""Generic ligand class."""
def __init__(self, atoms, ref):
"""Initialize this object. .. todo:: why is the force field name "WAT" for this? :param atoms: A list of :class:`Atom` objects to be stored in this object :type atoms: [Atom] :param ref: The reference object for the res... | stack_v2_sparse_classes_75kplus_train_070454 | 32,726 | no_license | [
{
"docstring": "Initialize this object. .. todo:: why is the force field name \"WAT\" for this? :param atoms: A list of :class:`Atom` objects to be stored in this object :type atoms: [Atom] :param ref: The reference object for the residue. Used to convert from the alternate naming scheme to the main naming sche... | 3 | stack_v2_sparse_classes_30k_val_001276 | Implement the Python class `LIG` described below.
Class description:
Generic ligand class.
Method signatures and docstrings:
- def __init__(self, atoms, ref): Initialize this object. .. todo:: why is the force field name "WAT" for this? :param atoms: A list of :class:`Atom` objects to be stored in this object :type a... | Implement the Python class `LIG` described below.
Class description:
Generic ligand class.
Method signatures and docstrings:
- def __init__(self, atoms, ref): Initialize this object. .. todo:: why is the force field name "WAT" for this? :param atoms: A list of :class:`Atom` objects to be stored in this object :type a... | 53cbe6d320048508710b3bad8581b69d3a358ab9 | <|skeleton|>
class LIG:
"""Generic ligand class."""
def __init__(self, atoms, ref):
"""Initialize this object. .. todo:: why is the force field name "WAT" for this? :param atoms: A list of :class:`Atom` objects to be stored in this object :type atoms: [Atom] :param ref: The reference object for the res... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LIG:
"""Generic ligand class."""
def __init__(self, atoms, ref):
"""Initialize this object. .. todo:: why is the force field name "WAT" for this? :param atoms: A list of :class:`Atom` objects to be stored in this object :type atoms: [Atom] :param ref: The reference object for the residue. Used to... | the_stack_v2_python_sparse | pdb2pqr/aa.py | rkretsch/pdb2pqr | train | 0 |
a65f02194031714c7b4552ed9b80c6a8a925e451 | [
"client_info = self.get_client_info()\ntheir_signature = self.request.headers.get('DCI-Auth-Signature')\nidentity = self.get_identity(client_info['type'], client_info['id'])\nif identity is None:\n raise dci_exc.DCIException('Client %(type)s/%(id)s does not exist' % client_info, status_code=401)\nself.identity =... | <|body_start_0|>
client_info = self.get_client_info()
their_signature = self.request.headers.get('DCI-Auth-Signature')
identity = self.get_identity(client_info['type'], client_info['id'])
if identity is None:
raise dci_exc.DCIException('Client %(type)s/%(id)s does not exist' ... | SignatureAuthMechanism | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignatureAuthMechanism:
def authenticate(self):
"""Tries to authenticate a request using a signature as authentication mechanism. Sets self.identity to the authenticated entity for later use."""
<|body_0|>
def get_identity(self, client_type, client_id):
"""Get an ide... | stack_v2_sparse_classes_75kplus_train_070455 | 12,001 | permissive | [
{
"docstring": "Tries to authenticate a request using a signature as authentication mechanism. Sets self.identity to the authenticated entity for later use.",
"name": "authenticate",
"signature": "def authenticate(self)"
},
{
"docstring": "Get an identity including its API secret",
"name": "... | 4 | stack_v2_sparse_classes_30k_train_032346 | Implement the Python class `SignatureAuthMechanism` described below.
Class description:
Implement the SignatureAuthMechanism class.
Method signatures and docstrings:
- def authenticate(self): Tries to authenticate a request using a signature as authentication mechanism. Sets self.identity to the authenticated entity ... | Implement the Python class `SignatureAuthMechanism` described below.
Class description:
Implement the SignatureAuthMechanism class.
Method signatures and docstrings:
- def authenticate(self): Tries to authenticate a request using a signature as authentication mechanism. Sets self.identity to the authenticated entity ... | 016592c133d12f6a980a335112eca13a07a0f273 | <|skeleton|>
class SignatureAuthMechanism:
def authenticate(self):
"""Tries to authenticate a request using a signature as authentication mechanism. Sets self.identity to the authenticated entity for later use."""
<|body_0|>
def get_identity(self, client_type, client_id):
"""Get an ide... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SignatureAuthMechanism:
def authenticate(self):
"""Tries to authenticate a request using a signature as authentication mechanism. Sets self.identity to the authenticated entity for later use."""
client_info = self.get_client_info()
their_signature = self.request.headers.get('DCI-Auth-S... | the_stack_v2_python_sparse | dci/auth_mechanism.py | AlexxNica/dci-control-server | train | 0 | |
083cfb130feea19f4fc5372c8aa2a79f8b4507b1 | [
"super(SecureResource, self).__init__()\nself.__session = session\nself.__auth = AWS4Auth(self.__session.credentials.key_id, self.__session.credentials.secret_key, ApiConfig.aws_region(), ApiConfig.aws_api_gw_service_name(), session_token=self.__session.credentials.session_token)",
"url = self._build_url('secure'... | <|body_start_0|>
super(SecureResource, self).__init__()
self.__session = session
self.__auth = AWS4Auth(self.__session.credentials.key_id, self.__session.credentials.secret_key, ApiConfig.aws_region(), ApiConfig.aws_api_gw_service_name(), session_token=self.__session.credentials.session_token)
<... | SecureResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecureResource:
def __init__(self, session):
""":param session: chikyu_sdk.resource.session.Session"""
<|body_0|>
def invoke(self, path, data):
""":param path: APIのパス :param data: APIに渡すデータ(リクエストのプロパティである「data」に入るもの) :rtype: dict :return:"""
<|body_1|>
<|end... | stack_v2_sparse_classes_75kplus_train_070456 | 1,518 | no_license | [
{
"docstring": ":param session: chikyu_sdk.resource.session.Session",
"name": "__init__",
"signature": "def __init__(self, session)"
},
{
"docstring": ":param path: APIのパス :param data: APIに渡すデータ(リクエストのプロパティである「data」に入るもの) :rtype: dict :return:",
"name": "invoke",
"signature": "def invoke... | 2 | stack_v2_sparse_classes_30k_test_002165 | Implement the Python class `SecureResource` described below.
Class description:
Implement the SecureResource class.
Method signatures and docstrings:
- def __init__(self, session): :param session: chikyu_sdk.resource.session.Session
- def invoke(self, path, data): :param path: APIのパス :param data: APIに渡すデータ(リクエストのプロパテ... | Implement the Python class `SecureResource` described below.
Class description:
Implement the SecureResource class.
Method signatures and docstrings:
- def __init__(self, session): :param session: chikyu_sdk.resource.session.Session
- def invoke(self, path, data): :param path: APIのパス :param data: APIに渡すデータ(リクエストのプロパテ... | 03c0724d7dc31dae85a1d10472cafd83efbcc46b | <|skeleton|>
class SecureResource:
def __init__(self, session):
""":param session: chikyu_sdk.resource.session.Session"""
<|body_0|>
def invoke(self, path, data):
""":param path: APIのパス :param data: APIに渡すデータ(リクエストのプロパティである「data」に入るもの) :rtype: dict :return:"""
<|body_1|>
<|end... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SecureResource:
def __init__(self, session):
""":param session: chikyu_sdk.resource.session.Session"""
super(SecureResource, self).__init__()
self.__session = session
self.__auth = AWS4Auth(self.__session.credentials.key_id, self.__session.credentials.secret_key, ApiConfig.aws_... | the_stack_v2_python_sparse | src/chikyu_sdk/secure_resource.py | chikyuinc/chikyu-sdk-python | train | 0 | |
57079aded9db70048585b9f3b509c2f89e3e9e11 | [
"send_url = self.get_peizhi_(name='shiming', yaml_ming='yilou_fangdong.yaml')\nsend_url = send_url['bindIdentity']\nlogging.info('url is %s' % send_url)\nsend_dict = {'realName': realName, 'idCard': idCard}\nresponse = self.request_post(base_url=send_url, dict_data=send_dict)\nreturn response",
"send_url = self.g... | <|body_start_0|>
send_url = self.get_peizhi_(name='shiming', yaml_ming='yilou_fangdong.yaml')
send_url = send_url['bindIdentity']
logging.info('url is %s' % send_url)
send_dict = {'realName': realName, 'idCard': idCard}
response = self.request_post(base_url=send_url, dict_data=se... | ShiMing | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShiMing:
def bindIdentity(self, realName, idCard):
"""提交实名认证 :return:"""
<|body_0|>
def getSupportBankList(self):
"""#86、获取支持银行列表 :return:"""
<|body_1|>
def getCardBin(self, bankCardNo):
"""#87、获取银行卡开户行 :return:"""
<|body_2|>
def rea... | stack_v2_sparse_classes_75kplus_train_070457 | 2,689 | no_license | [
{
"docstring": "提交实名认证 :return:",
"name": "bindIdentity",
"signature": "def bindIdentity(self, realName, idCard)"
},
{
"docstring": "#86、获取支持银行列表 :return:",
"name": "getSupportBankList",
"signature": "def getSupportBankList(self)"
},
{
"docstring": "#87、获取银行卡开户行 :return:",
"n... | 4 | stack_v2_sparse_classes_30k_train_042584 | Implement the Python class `ShiMing` described below.
Class description:
Implement the ShiMing class.
Method signatures and docstrings:
- def bindIdentity(self, realName, idCard): 提交实名认证 :return:
- def getSupportBankList(self): #86、获取支持银行列表 :return:
- def getCardBin(self, bankCardNo): #87、获取银行卡开户行 :return:
- def real... | Implement the Python class `ShiMing` described below.
Class description:
Implement the ShiMing class.
Method signatures and docstrings:
- def bindIdentity(self, realName, idCard): 提交实名认证 :return:
- def getSupportBankList(self): #86、获取支持银行列表 :return:
- def getCardBin(self, bankCardNo): #87、获取银行卡开户行 :return:
- def real... | e173d4e535ac22b72b67371b8a2524ee425cdcbf | <|skeleton|>
class ShiMing:
def bindIdentity(self, realName, idCard):
"""提交实名认证 :return:"""
<|body_0|>
def getSupportBankList(self):
"""#86、获取支持银行列表 :return:"""
<|body_1|>
def getCardBin(self, bankCardNo):
"""#87、获取银行卡开户行 :return:"""
<|body_2|>
def rea... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ShiMing:
def bindIdentity(self, realName, idCard):
"""提交实名认证 :return:"""
send_url = self.get_peizhi_(name='shiming', yaml_ming='yilou_fangdong.yaml')
send_url = send_url['bindIdentity']
logging.info('url is %s' % send_url)
send_dict = {'realName': realName, 'idCard': id... | the_stack_v2_python_sparse | public/aYiLou_fangdong/yilou_fangdong_business/yilou_fangdong_shiMing.py | GSIL-Monitor/mrbao_python | train | 0 | |
d9f9b43c28929b8edbeb869a00ce48acfd26d4be | [
"p = pHead\nwhile p:\n pClone = RandomListNode(p.label)\n pClone.next = p.next\n pClone.random = None\n p.next = pClone\n p = pClone.next\npHead = self.ConnectRandomNodes(pHead)\npHead = self.ReconnectNodes(pHead)\nreturn pHead",
"p = pHead\nwhile p:\n pClone = p.next\n if p.random != None:\n... | <|body_start_0|>
p = pHead
while p:
pClone = RandomListNode(p.label)
pClone.next = p.next
pClone.random = None
p.next = pClone
p = pClone.next
pHead = self.ConnectRandomNodes(pHead)
pHead = self.ReconnectNodes(pHead)
ret... | 复制复杂链表 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""复制复杂链表"""
def Clone(self, pHead):
"""复制原始链表，(p1,p2,p3)->(p1,p11,p2,p22,p3,p33)"""
<|body_0|>
def ConnectRandomNodes(self, pHead):
"""连接含random的节点，如果原始链表中的N的random指向S，则对应的复制节点N'对应S'"""
<|body_1|>
def ReconnectNodes(self, pHead):
"... | stack_v2_sparse_classes_75kplus_train_070458 | 3,242 | no_license | [
{
"docstring": "复制原始链表，(p1,p2,p3)->(p1,p11,p2,p22,p3,p33)",
"name": "Clone",
"signature": "def Clone(self, pHead)"
},
{
"docstring": "连接含random的节点，如果原始链表中的N的random指向S，则对应的复制节点N'对应S'",
"name": "ConnectRandomNodes",
"signature": "def ConnectRandomNodes(self, pHead)"
},
{
"docstring... | 3 | null | Implement the Python class `Solution` described below.
Class description:
复制复杂链表
Method signatures and docstrings:
- def Clone(self, pHead): 复制原始链表，(p1,p2,p3)->(p1,p11,p2,p22,p3,p33)
- def ConnectRandomNodes(self, pHead): 连接含random的节点，如果原始链表中的N的random指向S，则对应的复制节点N'对应S'
- def ReconnectNodes(self, pHead): 将链表拆分为两个链表，奇数... | Implement the Python class `Solution` described below.
Class description:
复制复杂链表
Method signatures and docstrings:
- def Clone(self, pHead): 复制原始链表，(p1,p2,p3)->(p1,p11,p2,p22,p3,p33)
- def ConnectRandomNodes(self, pHead): 连接含random的节点，如果原始链表中的N的random指向S，则对应的复制节点N'对应S'
- def ReconnectNodes(self, pHead): 将链表拆分为两个链表，奇数... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class Solution:
"""复制复杂链表"""
def Clone(self, pHead):
"""复制原始链表，(p1,p2,p3)->(p1,p11,p2,p22,p3,p33)"""
<|body_0|>
def ConnectRandomNodes(self, pHead):
"""连接含random的节点，如果原始链表中的N的random指向S，则对应的复制节点N'对应S'"""
<|body_1|>
def ReconnectNodes(self, pHead):
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""复制复杂链表"""
def Clone(self, pHead):
"""复制原始链表，(p1,p2,p3)->(p1,p11,p2,p22,p3,p33)"""
p = pHead
while p:
pClone = RandomListNode(p.label)
pClone.next = p.next
pClone.random = None
p.next = pClone
p = pClone.next
... | the_stack_v2_python_sparse | 剑指offer/25.复杂链表的复制.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 |
df5be540ac69cca4a7b4617e13b9ae3d3c9a4950 | [
"if show_columns is not None:\n self.all_extra_data_columns = show_columns['extra_data']\nelse:\n self.all_extra_data_columns = all_extra_data_columns\nsuper().__init__(instance=instance, data=data, **kwargs)\nif show_columns is not None:\n for field_name in set(self.fields) - set(show_columns['fields']):\... | <|body_start_0|>
if show_columns is not None:
self.all_extra_data_columns = show_columns['extra_data']
else:
self.all_extra_data_columns = all_extra_data_columns
super().__init__(instance=instance, data=data, **kwargs)
if show_columns is not None:
for ... | PropertyStateSerializer | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropertyStateSerializer:
def __init__(self, instance=None, data=empty, all_extra_data_columns=None, show_columns=None, **kwargs):
"""If show_columns is passed, then all_extra_data_columns is not needed since the extra_data columns are embedded in the show_columns. TODO: remove the use of... | stack_v2_sparse_classes_75kplus_train_070459 | 26,431 | permissive | [
{
"docstring": "If show_columns is passed, then all_extra_data_columns is not needed since the extra_data columns are embedded in the show_columns. TODO: remove the use of all_extra_data_columns. :param instance: instance to serialize :param data: initial data :param all_extra_data_columns: :param show_columns:... | 2 | stack_v2_sparse_classes_30k_val_002813 | Implement the Python class `PropertyStateSerializer` described below.
Class description:
Implement the PropertyStateSerializer class.
Method signatures and docstrings:
- def __init__(self, instance=None, data=empty, all_extra_data_columns=None, show_columns=None, **kwargs): If show_columns is passed, then all_extra_d... | Implement the Python class `PropertyStateSerializer` described below.
Class description:
Implement the PropertyStateSerializer class.
Method signatures and docstrings:
- def __init__(self, instance=None, data=empty, all_extra_data_columns=None, show_columns=None, **kwargs): If show_columns is passed, then all_extra_d... | 680b6a2b45f3c568d779d8ac86553a0b08c384c8 | <|skeleton|>
class PropertyStateSerializer:
def __init__(self, instance=None, data=empty, all_extra_data_columns=None, show_columns=None, **kwargs):
"""If show_columns is passed, then all_extra_data_columns is not needed since the extra_data columns are embedded in the show_columns. TODO: remove the use of... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PropertyStateSerializer:
def __init__(self, instance=None, data=empty, all_extra_data_columns=None, show_columns=None, **kwargs):
"""If show_columns is passed, then all_extra_data_columns is not needed since the extra_data columns are embedded in the show_columns. TODO: remove the use of all_extra_dat... | the_stack_v2_python_sparse | seed/serializers/properties.py | SEED-platform/seed | train | 108 | |
742da9a67f06192b7f0716ea788b6498591a8de7 | [
"B = A[::-1]\nfor i in range(1, len(A)):\n A[i] *= A[i - 1] or 1\n B[i] *= B[i - 1] or 1\nreturn max(A + B)",
"dp = [None] * len(nums)\ndp[0] = nums[0]\nfor i in range(1, len(nums)):\n dp[i] = max(dp[i - 1] + nums[i], nums[i])\nprint(dp)\nreturn max(dp)",
"dp = nums.copy()\nfor i in range(2, len(nums))... | <|body_start_0|>
B = A[::-1]
for i in range(1, len(A)):
A[i] *= A[i - 1] or 1
B[i] *= B[i - 1] or 1
return max(A + B)
<|end_body_0|>
<|body_start_1|>
dp = [None] * len(nums)
dp[0] = nums[0]
for i in range(1, len(nums)):
dp[i] = max(dp[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProduct(self, A):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus_train_070460 | 1,014 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxProduct",
"signature": "def maxProduct(self, A)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtyp... | 3 | stack_v2_sparse_classes_30k_train_023209 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, A): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :type nums: List[int] :rtype: i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, A): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :type nums: List[int] :rtype: i... | 7bcba42556475f56fad995b97a37b98f4981da8c | <|skeleton|>
class Solution:
def maxProduct(self, A):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProduct(self, A):
""":type nums: List[int] :rtype: int"""
B = A[::-1]
for i in range(1, len(A)):
A[i] *= A[i - 1] or 1
B[i] *= B[i - 1] or 1
return max(A + B)
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int... | the_stack_v2_python_sparse | Problems/152. Maximum Product Subarray.py | chendingyan/My-Leetcode | train | 0 | |
e12e303c35c0b77f3ad47300404d5b7acb48b5da | [
"time = timezone.now() + datetime.timedelta(days=30)\nfuture_question = Question(pub_date=time)\nself.assertEqual(future_question.was_published_recently(), False)",
"time = timezone.now() - datetime.timedelta(days=30)\nold_question = Question(pub_date=time)\nself.assertEqual(old_question.was_published_recently(),... | <|body_start_0|>
time = timezone.now() + datetime.timedelta(days=30)
future_question = Question(pub_date=time)
self.assertEqual(future_question.was_published_recently(), False)
<|end_body_0|>
<|body_start_1|>
time = timezone.now() - datetime.timedelta(days=30)
old_question = Que... | QuestionModelTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionModelTests:
def test_was_published_recently_with_future_question(self):
"""Should return False for Questions published in the future."""
<|body_0|>
def test_was_published_recently_with_old_question(self):
"""Should return False for questions whose published d... | stack_v2_sparse_classes_75kplus_train_070461 | 16,730 | no_license | [
{
"docstring": "Should return False for Questions published in the future.",
"name": "test_was_published_recently_with_future_question",
"signature": "def test_was_published_recently_with_future_question(self)"
},
{
"docstring": "Should return False for questions whose published date is older th... | 3 | stack_v2_sparse_classes_30k_train_008668 | Implement the Python class `QuestionModelTests` described below.
Class description:
Implement the QuestionModelTests class.
Method signatures and docstrings:
- def test_was_published_recently_with_future_question(self): Should return False for Questions published in the future.
- def test_was_published_recently_with_... | Implement the Python class `QuestionModelTests` described below.
Class description:
Implement the QuestionModelTests class.
Method signatures and docstrings:
- def test_was_published_recently_with_future_question(self): Should return False for Questions published in the future.
- def test_was_published_recently_with_... | 0adc16d8f291e7c670eb56c612597c30d0bdbd95 | <|skeleton|>
class QuestionModelTests:
def test_was_published_recently_with_future_question(self):
"""Should return False for Questions published in the future."""
<|body_0|>
def test_was_published_recently_with_old_question(self):
"""Should return False for questions whose published d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuestionModelTests:
def test_was_published_recently_with_future_question(self):
"""Should return False for Questions published in the future."""
time = timezone.now() + datetime.timedelta(days=30)
future_question = Question(pub_date=time)
self.assertEqual(future_question.was_pu... | the_stack_v2_python_sparse | polls/tests.py | ajmejia/LearningDjango | train | 0 | |
50d04a0f29f71b60bdc83d787514d08152365234 | [
"user = kwargs.get('user')\napp = kwargs.get('application')\nmessages = SentItem.get(user_id=user.id, application_id=app.id if app else None)\nreturn response(messages)",
"user = kwargs.get('user')\napp = kwargs.get('application')\nSentItem.remove(uuid=sentitem, user_id=user.id, application_id=app.id if app else ... | <|body_start_0|>
user = kwargs.get('user')
app = kwargs.get('application')
messages = SentItem.get(user_id=user.id, application_id=app.id if app else None)
return response(messages)
<|end_body_0|>
<|body_start_1|>
user = kwargs.get('user')
app = kwargs.get('application')... | Sent endpoints | SentResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentResource:
"""Sent endpoints"""
def index(self, **kwargs):
"""Returning list of sent items"""
<|body_0|>
def delete(self, sentitem, **kwargs):
"""Delete sent message"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = kwargs.get('user')
... | stack_v2_sparse_classes_75kplus_train_070462 | 1,591 | permissive | [
{
"docstring": "Returning list of sent items",
"name": "index",
"signature": "def index(self, **kwargs)"
},
{
"docstring": "Delete sent message",
"name": "delete",
"signature": "def delete(self, sentitem, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026812 | Implement the Python class `SentResource` described below.
Class description:
Sent endpoints
Method signatures and docstrings:
- def index(self, **kwargs): Returning list of sent items
- def delete(self, sentitem, **kwargs): Delete sent message | Implement the Python class `SentResource` described below.
Class description:
Sent endpoints
Method signatures and docstrings:
- def index(self, **kwargs): Returning list of sent items
- def delete(self, sentitem, **kwargs): Delete sent message
<|skeleton|>
class SentResource:
"""Sent endpoints"""
def index... | 37a3be814fc32ad87eb2a0ecfd93aa46ef46e68d | <|skeleton|>
class SentResource:
"""Sent endpoints"""
def index(self, **kwargs):
"""Returning list of sent items"""
<|body_0|>
def delete(self, sentitem, **kwargs):
"""Delete sent message"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SentResource:
"""Sent endpoints"""
def index(self, **kwargs):
"""Returning list of sent items"""
user = kwargs.get('user')
app = kwargs.get('application')
messages = SentItem.get(user_id=user.id, application_id=app.id if app else None)
return response(messages)
... | the_stack_v2_python_sparse | smsgw/resources/sent/api.py | jajonsraviation/smsgw | train | 0 |
0ca44ce02b0706ccdc523abe6eb0cef31a720582 | [
"first = second = third = float('-inf')\nfor n in nums:\n if n > first:\n first, second, third = (n, first, third)\n elif first > n > second:\n second, third = (n, second)\n elif second > n > third:\n third = n\n print(first, second, third)\nreturn third if third > float('-inf') els... | <|body_start_0|>
first = second = third = float('-inf')
for n in nums:
if n > first:
first, second, third = (n, first, third)
elif first > n > second:
second, third = (n, second)
elif second > n > third:
third = n
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def thirdMax(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def thirdMax_refer(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
first = second = third = float('-inf')
... | stack_v2_sparse_classes_75kplus_train_070463 | 1,879 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "thirdMax",
"signature": "def thirdMax(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "thirdMax_refer",
"signature": "def thirdMax_refer(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026585 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def thirdMax(self, nums): :type nums: List[int] :rtype: int
- def thirdMax_refer(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def thirdMax(self, nums): :type nums: List[int] :rtype: int
- def thirdMax_refer(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def thirdMax(se... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def thirdMax(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def thirdMax_refer(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def thirdMax(self, nums):
""":type nums: List[int] :rtype: int"""
first = second = third = float('-inf')
for n in nums:
if n > first:
first, second, third = (n, first, third)
elif first > n > second:
second, third = (n, ... | the_stack_v2_python_sparse | 414_thirdMax.py | jennyChing/leetCode | train | 2 | |
793dc852a1128d3a11be4b305f63a7e7d303057b | [
"self.summary_file = []\nself.path_params = []\nif release in ['DR17', 'MPL-11']:\n files = ['GZD_auto', 'gzUKIDSS', 'gz']\n version_DR17 = {'GZD_auto': 'v1_0_1', 'gzUKIDSS': 'v1_0_1', 'gz': 'v2_0_1'}\n for file in files:\n params = {'file': file, 'ver': version_DR17[file]}\n self.path_params... | <|body_start_0|>
self.summary_file = []
self.path_params = []
if release in ['DR17', 'MPL-11']:
files = ['GZD_auto', 'gzUKIDSS', 'gz']
version_DR17 = {'GZD_auto': 'v1_0_1', 'gzUKIDSS': 'v1_0_1', 'gz': 'v2_0_1'}
for file in files:
params = {'fil... | Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (GZ) data for SDSS galaxies has bee... | GZVAC | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GZVAC:
"""Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (G... | stack_v2_sparse_classes_75kplus_train_070464 | 5,257 | permissive | [
{
"docstring": "Sets the path to the GalaxyZoo summary file. Sets the paths to the GalaxyZoom summary file(s). For DR15 this is a single summary file, while for DR17, this has been split into three files, so ``self.summary_file`` and ``self.path_params`` return lists for DR17.",
"name": "set_summary_file",
... | 2 | stack_v2_sparse_classes_30k_train_029170 | Implement the Python class `GZVAC` described below.
Class description:
Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morpholog... | Implement the Python class `GZVAC` described below.
Class description:
Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morpholog... | db4c536a65fb2f16fee05a4f34996a7fd35f0527 | <|skeleton|>
class GZVAC:
"""Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (G... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GZVAC:
"""Provides access to the MaNGA Galaxy Zoo Morphology VAC. VAC name: MaNGA Morphologies from Galaxy Zoo URL: https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=manga-morphologies-from-galaxy-zoo Description Returns Galaxy Zoo morphology for MaNGA galaxies. The Galaxy Zoo (GZ) data for S... | the_stack_v2_python_sparse | python/marvin/contrib/vacs/galaxyzoo.py | sdss/marvin | train | 56 |
c4398c7da68c924363f44d82aac41e541b90f522 | [
"if 'xml' not in self.mimetype:\n raise AttributeError('Not a XML response (Content-Type: %s)' % self.mimetype)\nfor module in ['xml.etree.ElementTree', 'ElementTree', 'elementtree.ElementTree']:\n etree = import_string(module, silent=True)\n if etree is not None:\n return etree.XML(self.body)\nrais... | <|body_start_0|>
if 'xml' not in self.mimetype:
raise AttributeError('Not a XML response (Content-Type: %s)' % self.mimetype)
for module in ['xml.etree.ElementTree', 'ElementTree', 'elementtree.ElementTree']:
etree = import_string(module, silent=True)
if etree is not ... | A mixin class for response objects that provides a couple of useful accessors for unittesting. | ContentAccessors | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContentAccessors:
"""A mixin class for response objects that provides a couple of useful accessors for unittesting."""
def xml(self):
"""Get an etree if possible."""
<|body_0|>
def lxml(self):
"""Get an lxml etree if possible."""
<|body_1|>
def json(... | stack_v2_sparse_classes_75kplus_train_070465 | 2,453 | permissive | [
{
"docstring": "Get an etree if possible.",
"name": "xml",
"signature": "def xml(self)"
},
{
"docstring": "Get an lxml etree if possible.",
"name": "lxml",
"signature": "def lxml(self)"
},
{
"docstring": "Get the result of simplejson.loads if possible.",
"name": "json",
"... | 3 | stack_v2_sparse_classes_30k_train_054138 | Implement the Python class `ContentAccessors` described below.
Class description:
A mixin class for response objects that provides a couple of useful accessors for unittesting.
Method signatures and docstrings:
- def xml(self): Get an etree if possible.
- def lxml(self): Get an lxml etree if possible.
- def json(self... | Implement the Python class `ContentAccessors` described below.
Class description:
A mixin class for response objects that provides a couple of useful accessors for unittesting.
Method signatures and docstrings:
- def xml(self): Get an etree if possible.
- def lxml(self): Get an lxml etree if possible.
- def json(self... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class ContentAccessors:
"""A mixin class for response objects that provides a couple of useful accessors for unittesting."""
def xml(self):
"""Get an etree if possible."""
<|body_0|>
def lxml(self):
"""Get an lxml etree if possible."""
<|body_1|>
def json(... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ContentAccessors:
"""A mixin class for response objects that provides a couple of useful accessors for unittesting."""
def xml(self):
"""Get an etree if possible."""
if 'xml' not in self.mimetype:
raise AttributeError('Not a XML response (Content-Type: %s)' % self.mimetype)
... | the_stack_v2_python_sparse | Keras_tensorflow_nightly/source2.7/werkzeug/contrib/testtools.py | ryfeus/lambda-packs | train | 1,283 |
62da06083352717cd06395d00985dd6dcf9b2836 | [
"pg.ModellingBase.__init__(self, verbose)\nself.nlay_ = nlay\nself.FOP_ = pg.FDEM1dModelling(nlay + 1, frequencies, coilspacing, 0.0)\nself.mesh_ = pg.createMesh1D(nlay, 2)\nself.mesh_.cell(0).setMarker(2)\nself.setMesh(self.mesh_)",
"thk = model(0, self.nlay)\nres = model(self.nlay - 1, self.nlay * 2)\nres[0] = ... | <|body_start_0|>
pg.ModellingBase.__init__(self, verbose)
self.nlay_ = nlay
self.FOP_ = pg.FDEM1dModelling(nlay + 1, frequencies, coilspacing, 0.0)
self.mesh_ = pg.createMesh1D(nlay, 2)
self.mesh_.cell(0).setMarker(2)
self.setMesh(self.mesh_)
<|end_body_0|>
<|body_start_... | Airborne FDEM modelling including variable bird height. | HEM1dWithElevation | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HEM1dWithElevation:
"""Airborne FDEM modelling including variable bird height."""
def __init__(self, frequencies, coilspacing, nlay=2, verbose=False):
"""Set up class by frequencies and geometries."""
<|body_0|>
def response(self, model):
"""Return forward respon... | stack_v2_sparse_classes_75kplus_train_070466 | 27,181 | permissive | [
{
"docstring": "Set up class by frequencies and geometries.",
"name": "__init__",
"signature": "def __init__(self, frequencies, coilspacing, nlay=2, verbose=False)"
},
{
"docstring": "Return forward response for a given model.",
"name": "response",
"signature": "def response(self, model)... | 2 | stack_v2_sparse_classes_30k_train_035370 | Implement the Python class `HEM1dWithElevation` described below.
Class description:
Airborne FDEM modelling including variable bird height.
Method signatures and docstrings:
- def __init__(self, frequencies, coilspacing, nlay=2, verbose=False): Set up class by frequencies and geometries.
- def response(self, model): ... | Implement the Python class `HEM1dWithElevation` described below.
Class description:
Airborne FDEM modelling including variable bird height.
Method signatures and docstrings:
- def __init__(self, frequencies, coilspacing, nlay=2, verbose=False): Set up class by frequencies and geometries.
- def response(self, model): ... | 9962fe882fad284e52858ba3aa5e87b2395d791d | <|skeleton|>
class HEM1dWithElevation:
"""Airborne FDEM modelling including variable bird height."""
def __init__(self, frequencies, coilspacing, nlay=2, verbose=False):
"""Set up class by frequencies and geometries."""
<|body_0|>
def response(self, model):
"""Return forward respon... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HEM1dWithElevation:
"""Airborne FDEM modelling including variable bird height."""
def __init__(self, frequencies, coilspacing, nlay=2, verbose=False):
"""Set up class by frequencies and geometries."""
pg.ModellingBase.__init__(self, verbose)
self.nlay_ = nlay
self.FOP_ = p... | the_stack_v2_python_sparse | python/pygimli/physics/em/fdem.py | Geophysics-OpenSource/gimli | train | 0 |
494a8e60f5b213a8ce84e74bafcc9fa45ac16fd8 | [
"self.x = x\nself.y = y\nself.width = width\nself.height = height",
"dx = x - self.x\ndy = y - self.y\nreturn 0 <= dx < self.width and 0 <= dy < self.height"
] | <|body_start_0|>
self.x = x
self.y = y
self.width = width
self.height = height
<|end_body_0|>
<|body_start_1|>
dx = x - self.x
dy = y - self.y
return 0 <= dx < self.width and 0 <= dy < self.height
<|end_body_1|>
| Represents a single task as a rectangular region. | Task | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Task:
"""Represents a single task as a rectangular region."""
def __init__(self, x, y, width, height):
"""Initializes the task. :param x: the x coordinate of the top left corner of the goal region :param y: the y coordinate of the top left corner of the goal region :param width: the ... | stack_v2_sparse_classes_75kplus_train_070467 | 5,418 | no_license | [
{
"docstring": "Initializes the task. :param x: the x coordinate of the top left corner of the goal region :param y: the y coordinate of the top left corner of the goal region :param width: the width of the goal region :param height: the height of the goal region",
"name": "__init__",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_001967 | Implement the Python class `Task` described below.
Class description:
Represents a single task as a rectangular region.
Method signatures and docstrings:
- def __init__(self, x, y, width, height): Initializes the task. :param x: the x coordinate of the top left corner of the goal region :param y: the y coordinate of ... | Implement the Python class `Task` described below.
Class description:
Represents a single task as a rectangular region.
Method signatures and docstrings:
- def __init__(self, x, y, width, height): Initializes the task. :param x: the x coordinate of the top left corner of the goal region :param y: the y coordinate of ... | 381c019a3c930d943672a65ae651e5a4f52686f8 | <|skeleton|>
class Task:
"""Represents a single task as a rectangular region."""
def __init__(self, x, y, width, height):
"""Initializes the task. :param x: the x coordinate of the top left corner of the goal region :param y: the y coordinate of the top left corner of the goal region :param width: the ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Task:
"""Represents a single task as a rectangular region."""
def __init__(self, x, y, width, height):
"""Initializes the task. :param x: the x coordinate of the top left corner of the goal region :param y: the y coordinate of the top left corner of the goal region :param width: the width of the ... | the_stack_v2_python_sparse | domains/navigation/environment.py | rtloftin/HAL | train | 0 |
9ba46b93a94feb252896217120877ff6eb7a2bd1 | [
"try:\n book = BookInfo.objects.get(pk=pk)\nexcept BookInfo.DoesNotExist:\n return HttpResponse(status=404)\nreturn JsonResponse({'id': book.id, 'title': book.title, 'pub_date': book.pub_date, 'read': book.read, 'comment': book.comment, 'image': book.image.url if book.image else ''})",
"try:\n book = Boo... | <|body_start_0|>
try:
book = BookInfo.objects.get(pk=pk)
except BookInfo.DoesNotExist:
return HttpResponse(status=404)
return JsonResponse({'id': book.id, 'title': book.title, 'pub_date': book.pub_date, 'read': book.read, 'comment': book.comment, 'image': book.image.url i... | BookAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookAPIView:
def get(self, request, pk):
"""获取单个图书信息 路由： GET /books/<pk>/"""
<|body_0|>
def put(self, request, pk):
"""修改图书信息 路由： PUT /books/<pk>"""
<|body_1|>
def delete(self, request, pk):
"""删除图书 路由： DELETE /books/<pk>/"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus_train_070468 | 5,895 | no_license | [
{
"docstring": "获取单个图书信息 路由： GET /books/<pk>/",
"name": "get",
"signature": "def get(self, request, pk)"
},
{
"docstring": "修改图书信息 路由： PUT /books/<pk>",
"name": "put",
"signature": "def put(self, request, pk)"
},
{
"docstring": "删除图书 路由： DELETE /books/<pk>/",
"name": "delete"... | 3 | stack_v2_sparse_classes_30k_train_053554 | Implement the Python class `BookAPIView` described below.
Class description:
Implement the BookAPIView class.
Method signatures and docstrings:
- def get(self, request, pk): 获取单个图书信息 路由： GET /books/<pk>/
- def put(self, request, pk): 修改图书信息 路由： PUT /books/<pk>
- def delete(self, request, pk): 删除图书 路由： DELETE /books/<... | Implement the Python class `BookAPIView` described below.
Class description:
Implement the BookAPIView class.
Method signatures and docstrings:
- def get(self, request, pk): 获取单个图书信息 路由： GET /books/<pk>/
- def put(self, request, pk): 修改图书信息 路由： PUT /books/<pk>
- def delete(self, request, pk): 删除图书 路由： DELETE /books/<... | 0f123a99856238af5f1aab0b555f6501e635fc52 | <|skeleton|>
class BookAPIView:
def get(self, request, pk):
"""获取单个图书信息 路由： GET /books/<pk>/"""
<|body_0|>
def put(self, request, pk):
"""修改图书信息 路由： PUT /books/<pk>"""
<|body_1|>
def delete(self, request, pk):
"""删除图书 路由： DELETE /books/<pk>/"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BookAPIView:
def get(self, request, pk):
"""获取单个图书信息 路由： GET /books/<pk>/"""
try:
book = BookInfo.objects.get(pk=pk)
except BookInfo.DoesNotExist:
return HttpResponse(status=404)
return JsonResponse({'id': book.id, 'title': book.title, 'pub_date': book.p... | the_stack_v2_python_sparse | DRF_Tutorial/app/views.py | YDongY/PythonCode | train | 1 | |
e28391d7c4b82a0a3918dd79eef43426b5a34cf0 | [
"layers = [state_dim + action_dim] + hidden_layers + [state_dim]\nsuper(EnvironmentModel, self).__init__(layers, activations)\nself.predicts_delta = predicts_delta\nself.probabilistic = False",
"input = torch.cat((state, action), dim=-1)\noutput = self.forward(input)\nif self.predicts_delta:\n output = state +... | <|body_start_0|>
layers = [state_dim + action_dim] + hidden_layers + [state_dim]
super(EnvironmentModel, self).__init__(layers, activations)
self.predicts_delta = predicts_delta
self.probabilistic = False
<|end_body_0|>
<|body_start_1|>
input = torch.cat((state, action), dim=-1)... | EnvironmentModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvironmentModel:
def __init__(self, state_dim, action_dim, hidden_layers, activations, batch_norm=True, predicts_delta=True):
"""A neural network parameterized to model an OpenAI Gym environments state transition. :param state_dim: dimension of the environments state space :param action... | stack_v2_sparse_classes_75kplus_train_070469 | 21,063 | no_license | [
{
"docstring": "A neural network parameterized to model an OpenAI Gym environments state transition. :param state_dim: dimension of the environments state space :param action_dim: dimension of the environments action space :param hidden_layers: hidden_layers is a list defining the number of hidden nodes per lay... | 2 | null | Implement the Python class `EnvironmentModel` described below.
Class description:
Implement the EnvironmentModel class.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim, hidden_layers, activations, batch_norm=True, predicts_delta=True): A neural network parameterized to model an OpenAI Gym... | Implement the Python class `EnvironmentModel` described below.
Class description:
Implement the EnvironmentModel class.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim, hidden_layers, activations, batch_norm=True, predicts_delta=True): A neural network parameterized to model an OpenAI Gym... | ceeb196bde01592f9ec15f9e24d008a9395c65ea | <|skeleton|>
class EnvironmentModel:
def __init__(self, state_dim, action_dim, hidden_layers, activations, batch_norm=True, predicts_delta=True):
"""A neural network parameterized to model an OpenAI Gym environments state transition. :param state_dim: dimension of the environments state space :param action... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EnvironmentModel:
def __init__(self, state_dim, action_dim, hidden_layers, activations, batch_norm=True, predicts_delta=True):
"""A neural network parameterized to model an OpenAI Gym environments state transition. :param state_dim: dimension of the environments state space :param action_dim: dimensio... | the_stack_v2_python_sparse | src/algorithm/MPC/model.py | al91liwo/pytorch-rl-lab | train | 3 | |
2b1c7d624611b984a54b48cd73df8f6a47828819 | [
"self.source_plate = source_plate\nself.s_cells = source_cells\nself.d_cells = dest_cells\nself.dilution_factor = dilution_factor\nself.mapping = {}\nself._populate_mapping()",
"s_shape, s_width, s_height = self.s_cells.shape()\nd_shape, d_width, d_height = self.d_cells.shape()\nif s_shape == RowColIntersections.... | <|body_start_0|>
self.source_plate = source_plate
self.s_cells = source_cells
self.d_cells = dest_cells
self.dilution_factor = dilution_factor
self.mapping = {}
self._populate_mapping()
<|end_body_0|>
<|body_start_1|>
s_shape, s_width, s_height = self.s_cells.sha... | A transfer rule specifies rows and columns on an upstream *source* plate, and on a downstream *destination* plate. It refers to these rows and columns by holding a RowColIntersection object for the source and for the destination respectively. It also holds a dilution factor for the transfer. The shape made by the rows ... | TransferRule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransferRule:
"""A transfer rule specifies rows and columns on an upstream *source* plate, and on a downstream *destination* plate. It refers to these rows and columns by holding a RowColIntersection object for the source and for the destination respectively. It also holds a dilution factor for t... | stack_v2_sparse_classes_75kplus_train_070470 | 6,521 | permissive | [
{
"docstring": "Provide the source and destination cells using one RowColIntersections object respectively. The constructor will raise an IncompatibleTransferError when the combination is incompatible.",
"name": "__init__",
"signature": "def __init__(self, source_plate, source_cells, dest_cells, dilutio... | 6 | stack_v2_sparse_classes_30k_train_029658 | Implement the Python class `TransferRule` described below.
Class description:
A transfer rule specifies rows and columns on an upstream *source* plate, and on a downstream *destination* plate. It refers to these rows and columns by holding a RowColIntersection object for the source and for the destination respectively... | Implement the Python class `TransferRule` described below.
Class description:
A transfer rule specifies rows and columns on an upstream *source* plate, and on a downstream *destination* plate. It refers to these rows and columns by holding a RowColIntersection object for the source and for the destination respectively... | b67f65694fe058dbdb7001f7b30f3cdbc08c686f | <|skeleton|>
class TransferRule:
"""A transfer rule specifies rows and columns on an upstream *source* plate, and on a downstream *destination* plate. It refers to these rows and columns by holding a RowColIntersection object for the source and for the destination respectively. It also holds a dilution factor for t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TransferRule:
"""A transfer rule specifies rows and columns on an upstream *source* plate, and on a downstream *destination* plate. It refers to these rows and columns by holding a RowColIntersection object for the source and for the destination respectively. It also holds a dilution factor for the transfer. ... | the_stack_v2_python_sparse | app/rules_engine/transfer_rule.py | pete-dnae/assay-screening-proj | train | 1 |
865a4ed482eecfb7ccb3f284f7e6bd97bc2a6972 | [
"super().__init__()\nself.requires_grad = False\nself._r = 2",
"batch, in_channel, in_height, in_width = x.size()\nout_channel, out_height, out_width = (int(in_channel / self._r ** 2), self._r * in_height, self._r * in_width)\nx1 = x[:, 0:out_channel, :, :] / 2\nx2 = x[:, out_channel:out_channel * 2, :, :] / 2\nx... | <|body_start_0|>
super().__init__()
self.requires_grad = False
self._r = 2
<|end_body_0|>
<|body_start_1|>
batch, in_channel, in_height, in_width = x.size()
out_channel, out_height, out_width = (int(in_channel / self._r ** 2), self._r * in_height, self._r * in_width)
x1 ... | 2D Inverse Wavelet Transform as implemented in [1]_. References ---------- .. [1] Liu, Pengju, et al. “Multi-Level Wavelet-CNN for Image Restoration.” ArXiv:1805.07071 [Cs], May 2018. arXiv.org, http://arxiv.org/abs/1805.07071. | IWT | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IWT:
"""2D Inverse Wavelet Transform as implemented in [1]_. References ---------- .. [1] Liu, Pengju, et al. “Multi-Level Wavelet-CNN for Image Restoration.” ArXiv:1805.07071 [Cs], May 2018. arXiv.org, http://arxiv.org/abs/1805.07071."""
def __init__(self):
"""Inits :class:`IWT`."""... | stack_v2_sparse_classes_75kplus_train_070471 | 14,137 | permissive | [
{
"docstring": "Inits :class:`IWT`.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Computes IWT(`x`) given tensor `x`. Parameters ---------- x: torch.Tensor Input tensor. Returns ------- h: torch.Tensor IWT of `x`.",
"name": "forward",
"signature": "def forwar... | 2 | stack_v2_sparse_classes_30k_train_025330 | Implement the Python class `IWT` described below.
Class description:
2D Inverse Wavelet Transform as implemented in [1]_. References ---------- .. [1] Liu, Pengju, et al. “Multi-Level Wavelet-CNN for Image Restoration.” ArXiv:1805.07071 [Cs], May 2018. arXiv.org, http://arxiv.org/abs/1805.07071.
Method signatures and... | Implement the Python class `IWT` described below.
Class description:
2D Inverse Wavelet Transform as implemented in [1]_. References ---------- .. [1] Liu, Pengju, et al. “Multi-Level Wavelet-CNN for Image Restoration.” ArXiv:1805.07071 [Cs], May 2018. arXiv.org, http://arxiv.org/abs/1805.07071.
Method signatures and... | 2a4c29342bc52a404aae097bc2654fb4323e1ac8 | <|skeleton|>
class IWT:
"""2D Inverse Wavelet Transform as implemented in [1]_. References ---------- .. [1] Liu, Pengju, et al. “Multi-Level Wavelet-CNN for Image Restoration.” ArXiv:1805.07071 [Cs], May 2018. arXiv.org, http://arxiv.org/abs/1805.07071."""
def __init__(self):
"""Inits :class:`IWT`."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IWT:
"""2D Inverse Wavelet Transform as implemented in [1]_. References ---------- .. [1] Liu, Pengju, et al. “Multi-Level Wavelet-CNN for Image Restoration.” ArXiv:1805.07071 [Cs], May 2018. arXiv.org, http://arxiv.org/abs/1805.07071."""
def __init__(self):
"""Inits :class:`IWT`."""
supe... | the_stack_v2_python_sparse | direct/nn/mwcnn/mwcnn.py | NKI-AI/direct | train | 151 |
e6dd2414161976f95ad77ee4c69f0414e8c0c3f1 | [
"iterable = [1, 2, 3, 4, 5]\nfirst_matching = first_matching_item(iterable, lambda item: item == 1)\nsecond_matching = first_matching_item(iterable, lambda item: item == 5)\nthird_matching = first_matching_item(iterable, lambda item: item == 10)\nassert first_matching == 1\nassert second_matching == 5\nassert third... | <|body_start_0|>
iterable = [1, 2, 3, 4, 5]
first_matching = first_matching_item(iterable, lambda item: item == 1)
second_matching = first_matching_item(iterable, lambda item: item == 5)
third_matching = first_matching_item(iterable, lambda item: item == 10)
assert first_matching... | Tests for assorted utility functions | UtilTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UtilTests:
"""Tests for assorted utility functions"""
def test_first_matching_item(self):
"""Tests that first_matching_item returns a matching item in an iterable, or None"""
<|body_0|>
def test_is_subset_dict(self):
"""Tests that is_subset_dict properly determin... | stack_v2_sparse_classes_75kplus_train_070472 | 7,529 | no_license | [
{
"docstring": "Tests that first_matching_item returns a matching item in an iterable, or None",
"name": "test_first_matching_item",
"signature": "def test_first_matching_item(self)"
},
{
"docstring": "Tests that is_subset_dict properly determines whether or not a dict is a subset of another dic... | 3 | stack_v2_sparse_classes_30k_train_021467 | Implement the Python class `UtilTests` described below.
Class description:
Tests for assorted utility functions
Method signatures and docstrings:
- def test_first_matching_item(self): Tests that first_matching_item returns a matching item in an iterable, or None
- def test_is_subset_dict(self): Tests that is_subset_d... | Implement the Python class `UtilTests` described below.
Class description:
Tests for assorted utility functions
Method signatures and docstrings:
- def test_first_matching_item(self): Tests that first_matching_item returns a matching item in an iterable, or None
- def test_is_subset_dict(self): Tests that is_subset_d... | 3c166bc52dfe8d7aa04f922134f4f6deeff49eb6 | <|skeleton|>
class UtilTests:
"""Tests for assorted utility functions"""
def test_first_matching_item(self):
"""Tests that first_matching_item returns a matching item in an iterable, or None"""
<|body_0|>
def test_is_subset_dict(self):
"""Tests that is_subset_dict properly determin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UtilTests:
"""Tests for assorted utility functions"""
def test_first_matching_item(self):
"""Tests that first_matching_item returns a matching item in an iterable, or None"""
iterable = [1, 2, 3, 4, 5]
first_matching = first_matching_item(iterable, lambda item: item == 1)
... | the_stack_v2_python_sparse | micromasters/utils_test.py | avontd2868/micromasters | train | 0 |
d1f3e56e7a29765d6b4e6079e9b5d7e2df4555de | [
"try:\n self.send(self.get_collection_endpoint(), http_method='POST', **client_params)\nexcept Exception as e:\n raise CartoException(e)",
"if self.get_resource_endpoint() is None:\n raise CartoException('Async job needs to be run or retrieved first!')\nsuper(AsyncResourc... | <|body_start_0|>
try:
self.send(self.get_collection_endpoint(), http_method='POST', **client_params)
except Exception as e:
raise CartoException(e)
<|end_body_0|>
<|body_start_1|>
if self.get_resource_endpoint() is None:
raise CartoException('Async job needs ... | AsyncResource | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsyncResource:
def run(self, **client_params):
"""Actually creates the async job on the CARTO server :param client_params: To be send to the CARTO API. See CARTO's documentation depending on the subclass you are using :type client_params: kwargs :return: :raise: CartoException"""
... | stack_v2_sparse_classes_75kplus_train_070473 | 3,366 | permissive | [
{
"docstring": "Actually creates the async job on the CARTO server :param client_params: To be send to the CARTO API. See CARTO's documentation depending on the subclass you are using :type client_params: kwargs :return: :raise: CartoException",
"name": "run",
"signature": "def run(self, **client_params... | 2 | stack_v2_sparse_classes_30k_train_018024 | Implement the Python class `AsyncResource` described below.
Class description:
Implement the AsyncResource class.
Method signatures and docstrings:
- def run(self, **client_params): Actually creates the async job on the CARTO server :param client_params: To be send to the CARTO API. See CARTO's documentation dependin... | Implement the Python class `AsyncResource` described below.
Class description:
Implement the AsyncResource class.
Method signatures and docstrings:
- def run(self, **client_params): Actually creates the async job on the CARTO server :param client_params: To be send to the CARTO API. See CARTO's documentation dependin... | 631b018f065960baa35473e2087ce598560b9e17 | <|skeleton|>
class AsyncResource:
def run(self, **client_params):
"""Actually creates the async job on the CARTO server :param client_params: To be send to the CARTO API. See CARTO's documentation depending on the subclass you are using :type client_params: kwargs :return: :raise: CartoException"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AsyncResource:
def run(self, **client_params):
"""Actually creates the async job on the CARTO server :param client_params: To be send to the CARTO API. See CARTO's documentation depending on the subclass you are using :type client_params: kwargs :return: :raise: CartoException"""
try:
... | the_stack_v2_python_sparse | carto/resources.py | danicarrion/carto-python | train | 0 | |
c913584b014d9d0fbe036dd30c3411fb96501422 | [
"anagrams_list = defaultdict(list)\nfor string in strings:\n count = [0] * 26\n for char in string:\n count[ord(char) - ord('a')] += 1\n anagrams_list[tuple(count)].append(string)\nreturn anagrams_list.values()",
"anagrams_list = defaultdict(list)\nfor string in strings:\n anagrams_list[tuple(s... | <|body_start_0|>
anagrams_list = defaultdict(list)
for string in strings:
count = [0] * 26
for char in string:
count[ord(char) - ord('a')] += 1
anagrams_list[tuple(count)].append(string)
return anagrams_list.values()
<|end_body_0|>
<|body_star... | Anagrams | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Anagrams:
def group_(self, strings: List[str]) -> List[List[str]]:
"""Approach: Categorize by Count. N - length of strings. K - max length of strings. Time Complexity: O(NK) Space Complexity: :param strings: :return:"""
<|body_0|>
def group(self, strings: List[str]) -> List[... | stack_v2_sparse_classes_75kplus_train_070474 | 1,320 | no_license | [
{
"docstring": "Approach: Categorize by Count. N - length of strings. K - max length of strings. Time Complexity: O(NK) Space Complexity: :param strings: :return:",
"name": "group_",
"signature": "def group_(self, strings: List[str]) -> List[List[str]]"
},
{
"docstring": "Approach: Categorize by... | 2 | null | Implement the Python class `Anagrams` described below.
Class description:
Implement the Anagrams class.
Method signatures and docstrings:
- def group_(self, strings: List[str]) -> List[List[str]]: Approach: Categorize by Count. N - length of strings. K - max length of strings. Time Complexity: O(NK) Space Complexity:... | Implement the Python class `Anagrams` described below.
Class description:
Implement the Anagrams class.
Method signatures and docstrings:
- def group_(self, strings: List[str]) -> List[List[str]]: Approach: Categorize by Count. N - length of strings. K - max length of strings. Time Complexity: O(NK) Space Complexity:... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Anagrams:
def group_(self, strings: List[str]) -> List[List[str]]:
"""Approach: Categorize by Count. N - length of strings. K - max length of strings. Time Complexity: O(NK) Space Complexity: :param strings: :return:"""
<|body_0|>
def group(self, strings: List[str]) -> List[... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Anagrams:
def group_(self, strings: List[str]) -> List[List[str]]:
"""Approach: Categorize by Count. N - length of strings. K - max length of strings. Time Complexity: O(NK) Space Complexity: :param strings: :return:"""
anagrams_list = defaultdict(list)
for string in strings:
... | the_stack_v2_python_sparse | revisited/math_and_strings/strings/group_anagrams.py | Shiv2157k/leet_code | train | 1 | |
32279fdbf0b9acbaa409088b3296fb52baea4baa | [
"res = ''\nfor strr in strs:\n res += str(len(strr)) + '$' + strr\nprint(res)\nreturn res",
"res = []\ni = 0\nwhile i < len(s):\n p = s.find('$', i)\n length = int(s[i:p])\n res.append(s[p + 1:p + 1 + length])\n i = p + 1 + length\nreturn res"
] | <|body_start_0|>
res = ''
for strr in strs:
res += str(len(strr)) + '$' + strr
print(res)
return res
<|end_body_0|>
<|body_start_1|>
res = []
i = 0
while i < len(s):
p = s.find('$', i)
length = int(s[i:p])
res.appen... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = ''
... | stack_v2_sparse_classes_75kplus_train_070475 | 561 | permissive | [
{
"docstring": "Encodes a list of strings to a single string.",
"name": "encode",
"signature": "def encode(self, strs: [str]) -> str"
},
{
"docstring": "Decodes a single string to a list of strings.",
"name": "decode",
"signature": "def decode(self, s: str) -> [str]"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings.
<|skeleton|>
cla... | 95ca845e40c7c9f8ba589a45332791d5bbf49bbf | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
res = ''
for strr in strs:
res += str(len(strr)) + '$' + strr
print(res)
return res
def decode(self, s: str) -> [str]:
"""Decodes a single string to... | the_stack_v2_python_sparse | String/Leetcode 271. Encode and Decode Strings.py | sriharsha004/LeetCode | train | 0 | |
55f19d3610a1f2d3da4f54aed0dd72169a6be3fa | [
"self.maxi = maxi\nself.p = self.__start_progress(maxi)()\nself.header_printed = False\nself.msg = msg\nself.size = size",
"if reset:\n self.__init__(self.maxi, self.size, self.msg)\nif not self.header_printed:\n self.__print_header()\nnext(self.p)",
"format_string = '\\n0%{: ^' + str(self.size - 6) + '}1... | <|body_start_0|>
self.maxi = maxi
self.p = self.__start_progress(maxi)()
self.header_printed = False
self.msg = msg
self.size = size
<|end_body_0|>
<|body_start_1|>
if reset:
self.__init__(self.maxi, self.size, self.msg)
if not self.header_printed:
... | Text mode progress bar. Usage: p = Progress(30) p.step() p.step() p.step(start=True) # to restart form 0% The progress bar displays a new header at each restart. | Progress | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Progress:
"""Text mode progress bar. Usage: p = Progress(30) p.step() p.step() p.step(start=True) # to restart form 0% The progress bar displays a new header at each restart."""
def __init__(self, maxi, size=100, msg=''):
"""Initialize class. Args: maxi: The number of steps required ... | stack_v2_sparse_classes_75kplus_train_070476 | 13,013 | permissive | [
{
"docstring": "Initialize class. Args: maxi: The number of steps required to reach 100%. size: The number of characters taken on the screen by the progress bar. msg: The message displayed in the header of the progress bar.",
"name": "__init__",
"signature": "def __init__(self, maxi, size=100, msg='')"
... | 4 | stack_v2_sparse_classes_30k_train_050785 | Implement the Python class `Progress` described below.
Class description:
Text mode progress bar. Usage: p = Progress(30) p.step() p.step() p.step(start=True) # to restart form 0% The progress bar displays a new header at each restart.
Method signatures and docstrings:
- def __init__(self, maxi, size=100, msg=''): In... | Implement the Python class `Progress` described below.
Class description:
Text mode progress bar. Usage: p = Progress(30) p.step() p.step() p.step(start=True) # to restart form 0% The progress bar displays a new header at each restart.
Method signatures and docstrings:
- def __init__(self, maxi, size=100, msg=''): In... | ba5086c9852a1ad2425126fa7a95c02213ddbab4 | <|skeleton|>
class Progress:
"""Text mode progress bar. Usage: p = Progress(30) p.step() p.step() p.step(start=True) # to restart form 0% The progress bar displays a new header at each restart."""
def __init__(self, maxi, size=100, msg=''):
"""Initialize class. Args: maxi: The number of steps required ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Progress:
"""Text mode progress bar. Usage: p = Progress(30) p.step() p.step() p.step(start=True) # to restart form 0% The progress bar displays a new header at each restart."""
def __init__(self, maxi, size=100, msg=''):
"""Initialize class. Args: maxi: The number of steps required to reach 100%... | the_stack_v2_python_sparse | src/python/bot/fuzzers/ml/rnn/utils.py | Google-Autofuzz/clusterfuzz | train | 4 |
e1bda30dca44604bc53daf7bd1fde62c7aa44321 | [
"try:\n user_id = request.GET.get('id')\n user = User.objects.get(id=user_id)\n data = simplejson.dumps(user.userprofile.notifications.all())\n return HttpResponse(data, mimetype='application/json')\nexcept:\n return HttpResponse('', mimetype='application/json')",
"id = request.POST.get('id')\nnoti... | <|body_start_0|>
try:
user_id = request.GET.get('id')
user = User.objects.get(id=user_id)
data = simplejson.dumps(user.userprofile.notifications.all())
return HttpResponse(data, mimetype='application/json')
except:
return HttpResponse('', mimet... | this class will generate a notification to the given user | NotificationsView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationsView:
"""this class will generate a notification to the given user"""
def get(self, request, *args, **kwargs):
"""This will get all the notifications for a given user"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""this will delete the not... | stack_v2_sparse_classes_75kplus_train_070477 | 3,219 | no_license | [
{
"docstring": "This will get all the notifications for a given user",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "this will delete the notification of the given id.",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}... | 2 | stack_v2_sparse_classes_30k_train_024114 | Implement the Python class `NotificationsView` described below.
Class description:
this class will generate a notification to the given user
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): This will get all the notifications for a given user
- def post(self, request, *args, **kwargs): thi... | Implement the Python class `NotificationsView` described below.
Class description:
this class will generate a notification to the given user
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): This will get all the notifications for a given user
- def post(self, request, *args, **kwargs): thi... | b7c6acdc1624c5feda4e76d4dea864f20ca6f9aa | <|skeleton|>
class NotificationsView:
"""this class will generate a notification to the given user"""
def get(self, request, *args, **kwargs):
"""This will get all the notifications for a given user"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""this will delete the not... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NotificationsView:
"""this class will generate a notification to the given user"""
def get(self, request, *args, **kwargs):
"""This will get all the notifications for a given user"""
try:
user_id = request.GET.get('id')
user = User.objects.get(id=user_id)
... | the_stack_v2_python_sparse | qurious_backend/qurious/sessions/views.py | abhiInCalif/qurious-ios | train | 0 |
fbca600a499299cbc19ccd7a6953bdd2faf0cf61 | [
"super().__init__(out_dims)\nself.dim = dim\nself.c_dim = c_dim\nself.net = []\nself.net.append(SineLayer(dim + c_dim, hidden_size, is_first=True, omega_0=first_omega_0))\nfor i in range(n_layers):\n self.net.append(SineLayer(hidden_size, hidden_size, is_first=False, omega_0=hidden_omega_0))\nif outermost_linear... | <|body_start_0|>
super().__init__(out_dims)
self.dim = dim
self.c_dim = c_dim
self.net = []
self.net.append(SineLayer(dim + c_dim, hidden_size, is_first=True, omega_0=first_omega_0))
for i in range(n_layers):
self.net.append(SineLayer(hidden_size, hidden_size,... | Siren | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Siren:
def __init__(self, dim: int, hidden_size: int=256, n_layers: int=3, out_dims: dict=OrderedDict(sdf=1), outermost_linear: bool=True, c_dim: int=256, first_omega_0: float=30, hidden_omega_0: float=30.0, activation: Optional[str]=None, **kwargs):
"""Args: dim: first input dimension h... | stack_v2_sparse_classes_75kplus_train_070478 | 19,841 | no_license | [
{
"docstring": "Args: dim: first input dimension hidden_size: intermediate feature dimension n_layers: number of hidden layers (total number of layers = n_layers + 2) out_dim: last output dimension outermost_linear: use linear layer as the last layer instead of sine layer activation: for the sdf value",
"na... | 2 | null | Implement the Python class `Siren` described below.
Class description:
Implement the Siren class.
Method signatures and docstrings:
- def __init__(self, dim: int, hidden_size: int=256, n_layers: int=3, out_dims: dict=OrderedDict(sdf=1), outermost_linear: bool=True, c_dim: int=256, first_omega_0: float=30, hidden_omeg... | Implement the Python class `Siren` described below.
Class description:
Implement the Siren class.
Method signatures and docstrings:
- def __init__(self, dim: int, hidden_size: int=256, n_layers: int=3, out_dims: dict=OrderedDict(sdf=1), outermost_linear: bool=True, c_dim: int=256, first_omega_0: float=30, hidden_omeg... | 8fd8d86593272a56305b13ec7d9b4bdd9d241ef9 | <|skeleton|>
class Siren:
def __init__(self, dim: int, hidden_size: int=256, n_layers: int=3, out_dims: dict=OrderedDict(sdf=1), outermost_linear: bool=True, c_dim: int=256, first_omega_0: float=30, hidden_omega_0: float=30.0, activation: Optional[str]=None, **kwargs):
"""Args: dim: first input dimension h... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Siren:
def __init__(self, dim: int, hidden_size: int=256, n_layers: int=3, out_dims: dict=OrderedDict(sdf=1), outermost_linear: bool=True, c_dim: int=256, first_omega_0: float=30, hidden_omega_0: float=30.0, activation: Optional[str]=None, **kwargs):
"""Args: dim: first input dimension hidden_size: in... | the_stack_v2_python_sparse | DSS/models/common.py | yifita/DSS | train | 305 | |
203ed0ec92045774e1d1905e0f4d64351c1f19e7 | [
"self._command = command\nself._terms = results.AllTerms()\nself._results = results\nself._found_commands_map = {}\nfor c in found_commands:\n path = _GetPathWithoutPrefix(c)\n self._found_commands_map.setdefault(path, []).append(c)",
"rating = 1.0\nrating *= self._RateForLocation()\nrating *= self._RateFor... | <|body_start_0|>
self._command = command
self._terms = results.AllTerms()
self._results = results
self._found_commands_map = {}
for c in found_commands:
path = _GetPathWithoutPrefix(c)
self._found_commands_map.setdefault(path, []).append(c)
<|end_body_0|>
... | A class to rate the results of searching a command. | CommandRater | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommandRater:
"""A class to rate the results of searching a command."""
def __init__(self, results, command, found_commands):
"""Create a CommandRater. Args: results: googlecloudsdk.command_lib.search_help.search_util .CommandSearchResult, class that holds results. command: dict, a j... | stack_v2_sparse_classes_75kplus_train_070479 | 6,273 | permissive | [
{
"docstring": "Create a CommandRater. Args: results: googlecloudsdk.command_lib.search_help.search_util .CommandSearchResult, class that holds results. command: dict, a json representation of a command. found_commands: [dict], a list of all commands that were found.",
"name": "__init__",
"signature": "... | 5 | null | Implement the Python class `CommandRater` described below.
Class description:
A class to rate the results of searching a command.
Method signatures and docstrings:
- def __init__(self, results, command, found_commands): Create a CommandRater. Args: results: googlecloudsdk.command_lib.search_help.search_util .CommandS... | Implement the Python class `CommandRater` described below.
Class description:
A class to rate the results of searching a command.
Method signatures and docstrings:
- def __init__(self, results, command, found_commands): Create a CommandRater. Args: results: googlecloudsdk.command_lib.search_help.search_util .CommandS... | 85bb264e273568b5a0408f733b403c56373e2508 | <|skeleton|>
class CommandRater:
"""A class to rate the results of searching a command."""
def __init__(self, results, command, found_commands):
"""Create a CommandRater. Args: results: googlecloudsdk.command_lib.search_help.search_util .CommandSearchResult, class that holds results. command: dict, a j... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommandRater:
"""A class to rate the results of searching a command."""
def __init__(self, results, command, found_commands):
"""Create a CommandRater. Args: results: googlecloudsdk.command_lib.search_help.search_util .CommandSearchResult, class that holds results. command: dict, a json represent... | the_stack_v2_python_sparse | google-cloud-sdk/lib/googlecloudsdk/command_lib/help_search/rater.py | bopopescu/socialliteapp | train | 0 |
9ee0df2ba14cf002aeec7b9c2ae16c6c565f43b2 | [
"auth_user = TokenAuthentication().authenticate(request)[0]\npayload = request.data\nowner_id = payload.get('owner', None)\noffer_amount = payload.get('amount', None)\nlisting_item = payload.get('listing_id', None)\nowner = account_models.User.objects.filter(id=owner_id)\nif owner.exists():\n offer = marketplace... | <|body_start_0|>
auth_user = TokenAuthentication().authenticate(request)[0]
payload = request.data
owner_id = payload.get('owner', None)
offer_amount = payload.get('amount', None)
listing_item = payload.get('listing_id', None)
owner = account_models.User.objects.filter(id... | API view set to handle Marketplace offers | MarketplaceOfferViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarketplaceOfferViewSet:
"""API view set to handle Marketplace offers"""
def post(self, request, **kwargs):
"""POST method to create MarketplaceOffer object :param request: HTTP request object :param kwargs: Additional keyword arguments from the url :return: HTTP response object"""
... | stack_v2_sparse_classes_75kplus_train_070480 | 8,477 | no_license | [
{
"docstring": "POST method to create MarketplaceOffer object :param request: HTTP request object :param kwargs: Additional keyword arguments from the url :return: HTTP response object",
"name": "post",
"signature": "def post(self, request, **kwargs)"
},
{
"docstring": "API Endpoint to retrieve ... | 2 | null | Implement the Python class `MarketplaceOfferViewSet` described below.
Class description:
API view set to handle Marketplace offers
Method signatures and docstrings:
- def post(self, request, **kwargs): POST method to create MarketplaceOffer object :param request: HTTP request object :param kwargs: Additional keyword ... | Implement the Python class `MarketplaceOfferViewSet` described below.
Class description:
API view set to handle Marketplace offers
Method signatures and docstrings:
- def post(self, request, **kwargs): POST method to create MarketplaceOffer object :param request: HTTP request object :param kwargs: Additional keyword ... | 38a09ce2fe68312338c8cb597a341853901eeaa3 | <|skeleton|>
class MarketplaceOfferViewSet:
"""API view set to handle Marketplace offers"""
def post(self, request, **kwargs):
"""POST method to create MarketplaceOffer object :param request: HTTP request object :param kwargs: Additional keyword arguments from the url :return: HTTP response object"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MarketplaceOfferViewSet:
"""API view set to handle Marketplace offers"""
def post(self, request, **kwargs):
"""POST method to create MarketplaceOffer object :param request: HTTP request object :param kwargs: Additional keyword arguments from the url :return: HTTP response object"""
auth_u... | the_stack_v2_python_sparse | apps/marketplace/views.py | AOV-Team/aov-py-backend | train | 0 |
11ca96c8a277e9cee7fea9f88a4d842010e1791a | [
"ref = db.child(table)\nkey = ref.generate_key()\nreturn ref.child(key).update(data)",
"table_name = 'body_parts'\nfor body_part in ALL_BODY_PARTS:\n Fire.create_child(table_name, body_part['data'])\nreturn make_response({}, 200)",
"table_name = 'workouts'\nfor workout in ALL_WORKOUTS:\n Fire.create_child... | <|body_start_0|>
ref = db.child(table)
key = ref.generate_key()
return ref.child(key).update(data)
<|end_body_0|>
<|body_start_1|>
table_name = 'body_parts'
for body_part in ALL_BODY_PARTS:
Fire.create_child(table_name, body_part['data'])
return make_response... | This class acts as the fire model for our database. It contains all the methods related to initalizing the firebase database. | Fire | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fire:
"""This class acts as the fire model for our database. It contains all the methods related to initalizing the firebase database."""
def create_child(cls, table, data):
"""Creates a specified child in the table with that key and data. Arguments: table {str} -> The table name to ... | stack_v2_sparse_classes_75kplus_train_070481 | 3,823 | no_license | [
{
"docstring": "Creates a specified child in the table with that key and data. Arguments: table {str} -> The table name to update name {str} -> The name of the child object data {dict} -> The data for the child object Returns: response object -> If valid call, returns the the updated data and a 200 status code.... | 6 | null | Implement the Python class `Fire` described below.
Class description:
This class acts as the fire model for our database. It contains all the methods related to initalizing the firebase database.
Method signatures and docstrings:
- def create_child(cls, table, data): Creates a specified child in the table with that k... | Implement the Python class `Fire` described below.
Class description:
This class acts as the fire model for our database. It contains all the methods related to initalizing the firebase database.
Method signatures and docstrings:
- def create_child(cls, table, data): Creates a specified child in the table with that k... | 98f72eff6408801d770c74125b702364aab14835 | <|skeleton|>
class Fire:
"""This class acts as the fire model for our database. It contains all the methods related to initalizing the firebase database."""
def create_child(cls, table, data):
"""Creates a specified child in the table with that key and data. Arguments: table {str} -> The table name to ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Fire:
"""This class acts as the fire model for our database. It contains all the methods related to initalizing the firebase database."""
def create_child(cls, table, data):
"""Creates a specified child in the table with that key and data. Arguments: table {str} -> The table name to update name {... | the_stack_v2_python_sparse | backend/app/src/models/fire.py | imranmatin23/BitFit | train | 0 |
94c6163d655cae48fd54687051333457a53dce42 | [
"l = len(rods)\nmemory = {}\n\ndef dfs(i, left, right):\n if i == l:\n return left if left == right else 0\n if (i, left, right) in memory:\n return memory[i, left, right]\n first = dfs(i + 1, left + rods[i], right)\n second = dfs(i + 1, left, right + rods[i])\n third = dfs(i + 1, left,... | <|body_start_0|>
l = len(rods)
memory = {}
def dfs(i, left, right):
if i == l:
return left if left == right else 0
if (i, left, right) in memory:
return memory[i, left, right]
first = dfs(i + 1, left + rods[i], right)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def tallestBillboard(self, rods):
""":type rods: List[int] :rtype: int"""
<|body_0|>
def tallestBillboard_1(self, rods):
""":type rods: List[int] :rtype: int 620 ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l = len(rods)
memo... | stack_v2_sparse_classes_75kplus_train_070482 | 3,463 | no_license | [
{
"docstring": ":type rods: List[int] :rtype: int",
"name": "tallestBillboard",
"signature": "def tallestBillboard(self, rods)"
},
{
"docstring": ":type rods: List[int] :rtype: int 620 ms",
"name": "tallestBillboard_1",
"signature": "def tallestBillboard_1(self, rods)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def tallestBillboard(self, rods): :type rods: List[int] :rtype: int
- def tallestBillboard_1(self, rods): :type rods: List[int] :rtype: int 620 ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def tallestBillboard(self, rods): :type rods: List[int] :rtype: int
- def tallestBillboard_1(self, rods): :type rods: List[int] :rtype: int 620 ms
<|skeleton|>
class Solution:
... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def tallestBillboard(self, rods):
""":type rods: List[int] :rtype: int"""
<|body_0|>
def tallestBillboard_1(self, rods):
""":type rods: List[int] :rtype: int 620 ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def tallestBillboard(self, rods):
""":type rods: List[int] :rtype: int"""
l = len(rods)
memory = {}
def dfs(i, left, right):
if i == l:
return left if left == right else 0
if (i, left, right) in memory:
return m... | the_stack_v2_python_sparse | TallestBillboard_HARD_956.py | 953250587/leetcode-python | train | 2 | |
9820628612a6ee1acf247a6d1c483b78e0ac111a | [
"self.dq = collections.deque()\nfor i in range(1, n + 1):\n self.dq.append(i)\nself.t = collections.deque()",
"if k == len(self.dq):\n return self.dq[-1]\nwhile k != 0:\n k -= 1\n self.t.append(self.dq.popleft())\nr = self.t[-1]\nself.dq.append(self.t.pop())\nwhile self.t:\n self.dq.appendleft(self... | <|body_start_0|>
self.dq = collections.deque()
for i in range(1, n + 1):
self.dq.append(i)
self.t = collections.deque()
<|end_body_0|>
<|body_start_1|>
if k == len(self.dq):
return self.dq[-1]
while k != 0:
k -= 1
self.t.append(sel... | MRUQueue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MRUQueue:
def __init__(self, n):
""":type n: int"""
<|body_0|>
def fetch(self, k):
""":type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.dq = collections.deque()
for i in range(1, n + 1):
self.dq.append... | stack_v2_sparse_classes_75kplus_train_070483 | 754 | no_license | [
{
"docstring": ":type n: int",
"name": "__init__",
"signature": "def __init__(self, n)"
},
{
"docstring": ":type k: int :rtype: int",
"name": "fetch",
"signature": "def fetch(self, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010417 | Implement the Python class `MRUQueue` described below.
Class description:
Implement the MRUQueue class.
Method signatures and docstrings:
- def __init__(self, n): :type n: int
- def fetch(self, k): :type k: int :rtype: int | Implement the Python class `MRUQueue` described below.
Class description:
Implement the MRUQueue class.
Method signatures and docstrings:
- def __init__(self, n): :type n: int
- def fetch(self, k): :type k: int :rtype: int
<|skeleton|>
class MRUQueue:
def __init__(self, n):
""":type n: int"""
<|... | 20623defecf65cbc35b194d8b60d8b211816ee4f | <|skeleton|>
class MRUQueue:
def __init__(self, n):
""":type n: int"""
<|body_0|>
def fetch(self, k):
""":type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MRUQueue:
def __init__(self, n):
""":type n: int"""
self.dq = collections.deque()
for i in range(1, n + 1):
self.dq.append(i)
self.t = collections.deque()
def fetch(self, k):
""":type k: int :rtype: int"""
if k == len(self.dq):
retur... | the_stack_v2_python_sparse | in_Python/1756 Design Most Recently Used Queue.py | YangLiyli131/Leetcode2020 | train | 0 | |
b62e676950067dc8c383022ea9fd0237b8438e61 | [
"court_order = {'courtName': self.court_name, 'courtRegistry': self.court_registry, 'fileNumber': self.file_number, 'orderDate': format_ts(self.order_date)}\nif self.effect_of_order:\n court_order['effectOfOrder'] = self.effect_of_order\nreturn court_order",
"expiry = None\nif court_order_id:\n expiry = cls... | <|body_start_0|>
court_order = {'courtName': self.court_name, 'courtRegistry': self.court_registry, 'fileNumber': self.file_number, 'orderDate': format_ts(self.order_date)}
if self.effect_of_order:
court_order['effectOfOrder'] = self.effect_of_order
return court_order
<|end_body_0|>
... | This class manages all of the amendment, renewal statement court order information. | CourtOrder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CourtOrder:
"""This class manages all of the amendment, renewal statement court order information."""
def json(self) -> dict:
"""Return the court_order as a json object."""
<|body_0|>
def find_by_id(cls, court_order_id: int=None):
"""Return an expiry object by ex... | stack_v2_sparse_classes_75kplus_train_070484 | 3,545 | permissive | [
{
"docstring": "Return the court_order as a json object.",
"name": "json",
"signature": "def json(self) -> dict"
},
{
"docstring": "Return an expiry object by expiry ID.",
"name": "find_by_id",
"signature": "def find_by_id(cls, court_order_id: int=None)"
},
{
"docstring": "Return... | 4 | stack_v2_sparse_classes_30k_train_047089 | Implement the Python class `CourtOrder` described below.
Class description:
This class manages all of the amendment, renewal statement court order information.
Method signatures and docstrings:
- def json(self) -> dict: Return the court_order as a json object.
- def find_by_id(cls, court_order_id: int=None): Return a... | Implement the Python class `CourtOrder` described below.
Class description:
This class manages all of the amendment, renewal statement court order information.
Method signatures and docstrings:
- def json(self) -> dict: Return the court_order as a json object.
- def find_by_id(cls, court_order_id: int=None): Return a... | af1a4458bb78c16ecca484514d4bd0d1d8c24b5d | <|skeleton|>
class CourtOrder:
"""This class manages all of the amendment, renewal statement court order information."""
def json(self) -> dict:
"""Return the court_order as a json object."""
<|body_0|>
def find_by_id(cls, court_order_id: int=None):
"""Return an expiry object by ex... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CourtOrder:
"""This class manages all of the amendment, renewal statement court order information."""
def json(self) -> dict:
"""Return the court_order as a json object."""
court_order = {'courtName': self.court_name, 'courtRegistry': self.court_registry, 'fileNumber': self.file_number, '... | the_stack_v2_python_sparse | ppr-api/src/ppr_api/models/court_order.py | bcgov/ppr | train | 4 |
3f3050d43bb64aa123d7b79d4b59dd09f593bf16 | [
"if __debug__:\n logger.debug('Creating Consumer...')\nif isinstance(topic, bytes):\n topic_fix = str(topic.decode('utf-8'))\nelse:\n topic_fix = str(topic)\nself.topic = topic_fix\nself.access_mode = access_mode\nfrom kafka import KafkaConsumer\nbootstrap_server_info = str(bootstrap_server).split(':')\nbo... | <|body_start_0|>
if __debug__:
logger.debug('Creating Consumer...')
if isinstance(topic, bytes):
topic_fix = str(topic.decode('utf-8'))
else:
topic_fix = str(topic)
self.topic = topic_fix
self.access_mode = access_mode
from kafka import... | ODS Consumer connector implementation. Attributes: - topic: Registered topic name on the Kafka backend + type: string - access_mode: Consumer access mode + type: string - kafka_consumer: KafkaConsumer instance + type: KafkaConsumer | ODSConsumer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ODSConsumer:
"""ODS Consumer connector implementation. Attributes: - topic: Registered topic name on the Kafka backend + type: string - access_mode: Consumer access mode + type: string - kafka_consumer: KafkaConsumer instance + type: KafkaConsumer"""
def __init__(self, bootstrap_server: str,... | stack_v2_sparse_classes_75kplus_train_070485 | 6,395 | permissive | [
{
"docstring": "Create a new ODSConsumer instance. :param bootstrap_server: Associated boostrap server. :param topic: Topic where to consume records. :param access_mode: Consumer access mode.",
"name": "__init__",
"signature": "def __init__(self, bootstrap_server: str, topic: str, access_mode: str) -> N... | 2 | stack_v2_sparse_classes_30k_train_003418 | Implement the Python class `ODSConsumer` described below.
Class description:
ODS Consumer connector implementation. Attributes: - topic: Registered topic name on the Kafka backend + type: string - access_mode: Consumer access mode + type: string - kafka_consumer: KafkaConsumer instance + type: KafkaConsumer
Method si... | Implement the Python class `ODSConsumer` described below.
Class description:
ODS Consumer connector implementation. Attributes: - topic: Registered topic name on the Kafka backend + type: string - access_mode: Consumer access mode + type: string - kafka_consumer: KafkaConsumer instance + type: KafkaConsumer
Method si... | 5f7a31436d0e6f5acbeb66fa36ab8aad18dc4092 | <|skeleton|>
class ODSConsumer:
"""ODS Consumer connector implementation. Attributes: - topic: Registered topic name on the Kafka backend + type: string - access_mode: Consumer access mode + type: string - kafka_consumer: KafkaConsumer instance + type: KafkaConsumer"""
def __init__(self, bootstrap_server: str,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ODSConsumer:
"""ODS Consumer connector implementation. Attributes: - topic: Registered topic name on the Kafka backend + type: string - access_mode: Consumer access mode + type: string - kafka_consumer: KafkaConsumer instance + type: KafkaConsumer"""
def __init__(self, bootstrap_server: str, topic: str, ... | the_stack_v2_python_sparse | compss/programming_model/bindings/python/src/pycompss/streams/components/objects/kafka_connectors.py | bsc-wdc/compss | train | 39 |
3521bc10d1058a01403545ad6d3a488e80d29253 | [
"super().__init__()\nself._attention_type = attention\nself.conv_1 = nn.Sequential(nn.Conv2d(256, 1024, 1), nn.ReLU(), nn.Conv2d(1024, 256, 1), nn.ReLU())\nself.conv_1b = nn.Sequential(nn.Conv2d(256, 1024, 1), nn.ReLU(), nn.Conv2d(1024, 256, 1), nn.ReLU())\nself.attention_layer = AttentionLayer(use_language and att... | <|body_start_0|>
super().__init__()
self._attention_type = attention
self.conv_1 = nn.Sequential(nn.Conv2d(256, 1024, 1), nn.ReLU(), nn.Conv2d(1024, 256, 1), nn.ReLU())
self.conv_1b = nn.Sequential(nn.Conv2d(256, 1024, 1), nn.ReLU(), nn.Conv2d(1024, 256, 1), nn.ReLU())
self.atten... | Predicate Branch. pred. features -> CONV -> RELU -> Att. Pool -> CONV1D -> RELU -> -> Att. Clsfr -> out attention: multihead, singlehead, None | PredicateBranch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PredicateBranch:
"""Predicate Branch. pred. features -> CONV -> RELU -> Att. Pool -> CONV1D -> RELU -> -> Att. Clsfr -> out attention: multihead, singlehead, None"""
def __init__(self, num_classes, attention='multi_head', use_language=True, use_spatial=True):
"""Initialize model."""
... | stack_v2_sparse_classes_75kplus_train_070486 | 13,005 | no_license | [
{
"docstring": "Initialize model.",
"name": "__init__",
"signature": "def __init__(self, num_classes, attention='multi_head', use_language=True, use_spatial=True)"
},
{
"docstring": "Forward pass.",
"name": "forward",
"signature": "def forward(self, pred_feats, deltas, masks, subj_embs, ... | 2 | null | Implement the Python class `PredicateBranch` described below.
Class description:
Predicate Branch. pred. features -> CONV -> RELU -> Att. Pool -> CONV1D -> RELU -> -> Att. Clsfr -> out attention: multihead, singlehead, None
Method signatures and docstrings:
- def __init__(self, num_classes, attention='multi_head', us... | Implement the Python class `PredicateBranch` described below.
Class description:
Predicate Branch. pred. features -> CONV -> RELU -> Att. Pool -> CONV1D -> RELU -> -> Att. Clsfr -> out attention: multihead, singlehead, None
Method signatures and docstrings:
- def __init__(self, num_classes, attention='multi_head', us... | 810c79541a8584de3fe37943d244af366d361689 | <|skeleton|>
class PredicateBranch:
"""Predicate Branch. pred. features -> CONV -> RELU -> Att. Pool -> CONV1D -> RELU -> -> Att. Clsfr -> out attention: multihead, singlehead, None"""
def __init__(self, num_classes, attention='multi_head', use_language=True, use_spatial=True):
"""Initialize model."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PredicateBranch:
"""Predicate Branch. pred. features -> CONV -> RELU -> Att. Pool -> CONV1D -> RELU -> -> Att. Clsfr -> out attention: multihead, singlehead, None"""
def __init__(self, num_classes, attention='multi_head', use_language=True, use_spatial=True):
"""Initialize model."""
super... | the_stack_v2_python_sparse | common/models/sg_generator/atr_net.py | bgzu/zs-vrd-bmvc20 | train | 0 |
b8425396ab2dc40e7d85bbbf1ab1ee7569e184c6 | [
"self.bar = None\nself.onBar = onBar\nif bar_type == const.MARKET_TYPE_KLINE_5M:\n self.xmin = 5\nelif bar_type == const.MARKET_TYPE_KLINE_15M:\n self.xmin = 15\nself.bar_type = bar_type\nself.xminBar = None\nself.onXminBar = onXminBar",
"newMinute = False\nif not self.bar:\n self.bar = Kline()\n newM... | <|body_start_0|>
self.bar = None
self.onBar = onBar
if bar_type == const.MARKET_TYPE_KLINE_5M:
self.xmin = 5
elif bar_type == const.MARKET_TYPE_KLINE_15M:
self.xmin = 15
self.bar_type = bar_type
self.xminBar = None
self.onXminBar = onXminBa... | K线合成器，支持： 1. 基于trade合成1分钟K线 2. 基于1分钟K线合成X分钟K线 (X可以是5、15) | KlineGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KlineGenerator:
"""K线合成器，支持： 1. 基于trade合成1分钟K线 2. 基于1分钟K线合成X分钟K线 (X可以是5、15)"""
def __init__(self, onBar, bar_type=None, onXminBar=None):
"""Constructor"""
<|body_0|>
async def update_trade(self, trade):
"""逐笔成交更新"""
<|body_1|>
async def update_bar(se... | stack_v2_sparse_classes_75kplus_train_070487 | 3,675 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, onBar, bar_type=None, onXminBar=None)"
},
{
"docstring": "逐笔成交更新",
"name": "update_trade",
"signature": "async def update_trade(self, trade)"
},
{
"docstring": "1分钟K线更新",
"name": "update_bar",
... | 3 | stack_v2_sparse_classes_30k_train_030432 | Implement the Python class `KlineGenerator` described below.
Class description:
K线合成器，支持： 1. 基于trade合成1分钟K线 2. 基于1分钟K线合成X分钟K线 (X可以是5、15)
Method signatures and docstrings:
- def __init__(self, onBar, bar_type=None, onXminBar=None): Constructor
- async def update_trade(self, trade): 逐笔成交更新
- async def update_bar(self, ... | Implement the Python class `KlineGenerator` described below.
Class description:
K线合成器，支持： 1. 基于trade合成1分钟K线 2. 基于1分钟K线合成X分钟K线 (X可以是5、15)
Method signatures and docstrings:
- def __init__(self, onBar, bar_type=None, onXminBar=None): Constructor
- async def update_trade(self, trade): 逐笔成交更新
- async def update_bar(self, ... | 5f45dbd5f09354dd161606f7e740f8c8d8ae2772 | <|skeleton|>
class KlineGenerator:
"""K线合成器，支持： 1. 基于trade合成1分钟K线 2. 基于1分钟K线合成X分钟K线 (X可以是5、15)"""
def __init__(self, onBar, bar_type=None, onXminBar=None):
"""Constructor"""
<|body_0|>
async def update_trade(self, trade):
"""逐笔成交更新"""
<|body_1|>
async def update_bar(se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KlineGenerator:
"""K线合成器，支持： 1. 基于trade合成1分钟K线 2. 基于1分钟K线合成X分钟K线 (X可以是5、15)"""
def __init__(self, onBar, bar_type=None, onXminBar=None):
"""Constructor"""
self.bar = None
self.onBar = onBar
if bar_type == const.MARKET_TYPE_KLINE_5M:
self.xmin = 5
elif b... | the_stack_v2_python_sparse | quant/interface/kline_generator.py | lucali2014/alphahunter | train | 0 |
a9a861990602ac669150550c06c85c2bd602f217 | [
"logging.getLogger('tensorflow').setLevel(logging.ERROR)\nlogging.getLogger('batchglm').setLevel(logging.WARNING)\nlogging.getLogger('diffxpy').setLevel(logging.WARNING)\nnp.random.seed(1)\nreturn self._test_t_test_de(n_cells=n_cells, n_genes=n_genes)",
"logging.getLogger('tensorflow').setLevel(logging.ERROR)\nlo... | <|body_start_0|>
logging.getLogger('tensorflow').setLevel(logging.ERROR)
logging.getLogger('batchglm').setLevel(logging.WARNING)
logging.getLogger('diffxpy').setLevel(logging.WARNING)
np.random.seed(1)
return self._test_t_test_de(n_cells=n_cells, n_genes=n_genes)
<|end_body_0|>
... | Noise model-independent tests unit tests that tests false positive and false negative rates. | TestSingleDeStandard | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSingleDeStandard:
"""Noise model-independent tests unit tests that tests false positive and false negative rates."""
def test_ttest_de(self, n_cells: int=2000, n_genes: int=200):
""":param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Num... | stack_v2_sparse_classes_75kplus_train_070488 | 10,613 | permissive | [
{
"docstring": ":param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes to simulate (number of tests).",
"name": "test_ttest_de",
"signature": "def test_ttest_de(self, n_cells: int=2000, n_genes: int=200)"
},
{
"docstring": ":param n_cells: ... | 2 | stack_v2_sparse_classes_30k_train_030266 | Implement the Python class `TestSingleDeStandard` described below.
Class description:
Noise model-independent tests unit tests that tests false positive and false negative rates.
Method signatures and docstrings:
- def test_ttest_de(self, n_cells: int=2000, n_genes: int=200): :param n_cells: Number of cells to simula... | Implement the Python class `TestSingleDeStandard` described below.
Class description:
Noise model-independent tests unit tests that tests false positive and false negative rates.
Method signatures and docstrings:
- def test_ttest_de(self, n_cells: int=2000, n_genes: int=200): :param n_cells: Number of cells to simula... | 7609ea935936e3739fc4c71b75c8ee8ca57f51ea | <|skeleton|>
class TestSingleDeStandard:
"""Noise model-independent tests unit tests that tests false positive and false negative rates."""
def test_ttest_de(self, n_cells: int=2000, n_genes: int=200):
""":param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Num... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestSingleDeStandard:
"""Noise model-independent tests unit tests that tests false positive and false negative rates."""
def test_ttest_de(self, n_cells: int=2000, n_genes: int=200):
""":param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes ... | the_stack_v2_python_sparse | diffxpy/unit_test/test_single_de.py | theislab/diffxpy | train | 163 |
22e16b7044620e303415369fdf25b03a7db23921 | [
"super().__init__(coordinator=coordinator)\nself._service_key = service_key\nself.entity_id = f'{SENSOR_DOMAIN}.{service}_{description.key}'\nself.entity_description = description\nself._attr_unique_id = f'{coordinator.config_entry.entry_id}_{service_key}_{description.key}'\nself._attr_device_info = DeviceInfo(entr... | <|body_start_0|>
super().__init__(coordinator=coordinator)
self._service_key = service_key
self.entity_id = f'{SENSOR_DOMAIN}.{service}_{description.key}'
self.entity_description = description
self._attr_unique_id = f'{coordinator.config_entry.entry_id}_{service_key}_{description... | Defines an P1 Monitor sensor. | P1MonitorSensorEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class P1MonitorSensorEntity:
"""Defines an P1 Monitor sensor."""
def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None:
"""Initialize ... | stack_v2_sparse_classes_75kplus_train_070489 | 11,570 | permissive | [
{
"docstring": "Initialize P1 Monitor sensor.",
"name": "__init__",
"signature": "def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_034978 | Implement the Python class `P1MonitorSensorEntity` described below.
Class description:
Defines an P1 Monitor sensor.
Method signatures and docstrings:
- def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', '... | Implement the Python class `P1MonitorSensorEntity` described below.
Class description:
Defines an P1 Monitor sensor.
Method signatures and docstrings:
- def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', '... | 2e65b77b2b5c17919939481f327963abdfdc53f0 | <|skeleton|>
class P1MonitorSensorEntity:
"""Defines an P1 Monitor sensor."""
def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None:
"""Initialize ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class P1MonitorSensorEntity:
"""Defines an P1 Monitor sensor."""
def __init__(self, *, coordinator: P1MonitorDataUpdateCoordinator, description: SensorEntityDescription, service_key: Literal['smartmeter', 'watermeter', 'phases', 'settings'], name: str, service: str) -> None:
"""Initialize P1 Monitor se... | the_stack_v2_python_sparse | homeassistant/components/p1_monitor/sensor.py | konnected-io/home-assistant | train | 24 |
2a8420d3157a9d11ccc7dc1f6ce1768d8aa18e5d | [
"super().__init__()\nself.cost_is_referred = cost_is_referred\nself.cost_dice = cost_dice\nassert cost_is_referred != 0 or cost_dice != 0, 'all costs cant be 0'",
"t, bs, num_queries = outputs['pred_masks'].shape[:3]\nout_masks = outputs['pred_masks'].flatten(1, 2)\ntgt_masks = [[m for v in t_step_batch for m in ... | <|body_start_0|>
super().__init__()
self.cost_is_referred = cost_is_referred
self.cost_dice = cost_dice
assert cost_is_referred != 0 or cost_dice != 0, 'all costs cant be 0'
<|end_body_0|>
<|body_start_1|>
t, bs, num_queries = outputs['pred_masks'].shape[:3]
out_masks = ... | This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best predictions, while the others are un-matched (... | HungarianMatcher | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best pr... | stack_v2_sparse_classes_75kplus_train_070490 | 7,299 | permissive | [
{
"docstring": "Creates the matcher Params: cost_is_referred: This is the relative weight of the reference cost in the total matching cost cost_dice: This is the relative weight of the dice cost in the total matching cost",
"name": "__init__",
"signature": "def __init__(self, cost_is_referred: float=1, ... | 2 | stack_v2_sparse_classes_30k_train_003433 | Implement the Python class `HungarianMatcher` described below.
Class description:
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case,... | Implement the Python class `HungarianMatcher` described below.
Class description:
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case,... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best pr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best predictions, wh... | the_stack_v2_python_sparse | ai/modelscope/modelscope/models/cv/referring_video_object_segmentation/utils/matcher.py | alldatacenter/alldata | train | 774 |
01b1959a87e5d0745caeceb32d6188b53395ae79 | [
"print('Enter the values for filters you want to apply (Press enter to skip)')\nfor key in self.FILTERS:\n while True:\n value = SelectFiles.validate(input(self.FILTERS[key]['description']), key)\n if value == '':\n break\n elif not isinstance(value, bool):\n self.FILTE... | <|body_start_0|>
print('Enter the values for filters you want to apply (Press enter to skip)')
for key in self.FILTERS:
while True:
value = SelectFiles.validate(input(self.FILTERS[key]['description']), key)
if value == '':
break
... | Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered | SelectFiles | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectFiles:
"""Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered"""
def __init__(self):
"""Takes in arguments from the user for filtering files"""
<|body_0|>
def list_all_files(path):
... | stack_v2_sparse_classes_75kplus_train_070491 | 8,019 | permissive | [
{
"docstring": "Takes in arguments from the user for filtering files",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Returns a Dict object of all the files present at the path argument.",
"name": "list_all_files",
"signature": "def list_all_files(path)"
},
... | 5 | stack_v2_sparse_classes_30k_train_024215 | Implement the Python class `SelectFiles` described below.
Class description:
Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered
Method signatures and docstrings:
- def __init__(self): Takes in arguments from the user for filtering file... | Implement the Python class `SelectFiles` described below.
Class description:
Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered
Method signatures and docstrings:
- def __init__(self): Takes in arguments from the user for filtering file... | 31fd3fb1233f39ea2252a7a44160ff8a2140f7bd | <|skeleton|>
class SelectFiles:
"""Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered"""
def __init__(self):
"""Takes in arguments from the user for filtering files"""
<|body_0|>
def list_all_files(path):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SelectFiles:
"""Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered"""
def __init__(self):
"""Takes in arguments from the user for filtering files"""
print('Enter the values for filters you want to apply (Pr... | the_stack_v2_python_sparse | Python/Bulk_File_Renamer/utils.py | HarshCasper/Rotten-Scripts | train | 1,474 |
714bdd93d9df62640ebdf71d48ce8765db732485 | [
"self.table = table\nself.data = data or {}\nself.item_id = id",
"if col in self.table.template:\n if col in self.data.keys():\n return self.data[col]\n else:\n return None\nelse:\n raise KeyError()",
"if col in self.table.template:\n self.data[col] = val\nelse:\n raise KeyError()\n... | <|body_start_0|>
self.table = table
self.data = data or {}
self.item_id = id
<|end_body_0|>
<|body_start_1|>
if col in self.table.template:
if col in self.data.keys():
return self.data[col]
else:
return None
else:
... | Represents a database item. | db_item | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class db_item:
"""Represents a database item."""
def __init__(self, table, id, data):
"""Initialising a new item object."""
<|body_0|>
def get(self, col: str):
"""Gets a column from the record row."""
<|body_1|>
def set(self, col: str, val):
"""Set... | stack_v2_sparse_classes_75kplus_train_070492 | 4,747 | no_license | [
{
"docstring": "Initialising a new item object.",
"name": "__init__",
"signature": "def __init__(self, table, id, data)"
},
{
"docstring": "Gets a column from the record row.",
"name": "get",
"signature": "def get(self, col: str)"
},
{
"docstring": "Sets a column of the record ro... | 3 | stack_v2_sparse_classes_30k_train_017241 | Implement the Python class `db_item` described below.
Class description:
Represents a database item.
Method signatures and docstrings:
- def __init__(self, table, id, data): Initialising a new item object.
- def get(self, col: str): Gets a column from the record row.
- def set(self, col: str, val): Sets a column of t... | Implement the Python class `db_item` described below.
Class description:
Represents a database item.
Method signatures and docstrings:
- def __init__(self, table, id, data): Initialising a new item object.
- def get(self, col: str): Gets a column from the record row.
- def set(self, col: str, val): Sets a column of t... | 21261e3c9c4a7755b35dc9ae6e6fa4e453045f20 | <|skeleton|>
class db_item:
"""Represents a database item."""
def __init__(self, table, id, data):
"""Initialising a new item object."""
<|body_0|>
def get(self, col: str):
"""Gets a column from the record row."""
<|body_1|>
def set(self, col: str, val):
"""Set... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class db_item:
"""Represents a database item."""
def __init__(self, table, id, data):
"""Initialising a new item object."""
self.table = table
self.data = data or {}
self.item_id = id
def get(self, col: str):
"""Gets a column from the record row."""
if col i... | the_stack_v2_python_sparse | software/module/database/database.py | shaiTheKimhi/lab_control_panel | train | 0 |
3b79f1da407ce35df0781001c524bac20927a1d4 | [
"best_side = 'index_left'\nindex_left = 0\nindex_right = len(subHeight) - 1\nfor i in range(1, int(len(subHeight) / 2 - 1)):\n index_left += 1\n index_right -= 1\n if subHeight[index_left] < subHeight[index_right]:\n best_side = 'index_left'\n elif subHeight[index_left] > subHeight[index_right]:\... | <|body_start_0|>
best_side = 'index_left'
index_left = 0
index_right = len(subHeight) - 1
for i in range(1, int(len(subHeight) / 2 - 1)):
index_left += 1
index_right -= 1
if subHeight[index_left] < subHeight[index_right]:
best_side = 'i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def best_side(self, subHeight):
"""两边相同时，往内搜索，如果单边随机选有可能选不到最好的 :param subHeight: :return:"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
best_side = 'index_le... | stack_v2_sparse_classes_75kplus_train_070493 | 1,949 | no_license | [
{
"docstring": "两边相同时，往内搜索，如果单边随机选有可能选不到最好的 :param subHeight: :return:",
"name": "best_side",
"signature": "def best_side(self, subHeight)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013994 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def best_side(self, subHeight): 两边相同时，往内搜索，如果单边随机选有可能选不到最好的 :param subHeight: :return:
- def maxArea(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def best_side(self, subHeight): 两边相同时，往内搜索，如果单边随机选有可能选不到最好的 :param subHeight: :return:
- def maxArea(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class Soluti... | 17b22a7201de65cf9ac8807efee225f475d72ef3 | <|skeleton|>
class Solution:
def best_side(self, subHeight):
"""两边相同时，往内搜索，如果单边随机选有可能选不到最好的 :param subHeight: :return:"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def best_side(self, subHeight):
"""两边相同时，往内搜索，如果单边随机选有可能选不到最好的 :param subHeight: :return:"""
best_side = 'index_left'
index_left = 0
index_right = len(subHeight) - 1
for i in range(1, int(len(subHeight) / 2 - 1)):
index_left += 1
index_... | the_stack_v2_python_sparse | day5/code11.py | ohquai/LeetCode | train | 0 | |
d46907c83fb437396eddb57789990a73432e0a98 | [
"self.fixed_size = fixed_size\nself.classifier_pkl = classifier_pkl\nself.feature_method = feature_method\nself.feature_options = feature_options\nself.image_processing_options = image_processing_options\nself.raw_image_path = raw_image_path\nself.kernel = kernel\nself.gamma = gamma\nself.C = C\nself.data = None\ns... | <|body_start_0|>
self.fixed_size = fixed_size
self.classifier_pkl = classifier_pkl
self.feature_method = feature_method
self.feature_options = feature_options
self.image_processing_options = image_processing_options
self.raw_image_path = raw_image_path
self.kernel... | train_classifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class train_classifier:
def __init__(self, df_path, image_col_name, category_col_name, fixed_size, classifier_pkl, feature_method, feature_options, image_processing_options, raw_image_path, kernel='rbf', gamma='auto', C=1):
"""The class constructor :param df_path: full path to the input roi Da... | stack_v2_sparse_classes_75kplus_train_070494 | 6,767 | no_license | [
{
"docstring": "The class constructor :param df_path: full path to the input roi DataFrame file (e.g. ../data/roi/roidf.h5) :param image_col_name: column name for the image data column :param category_col_name: column name for the image category (negative or positive) column :param fixed_size: 2x1 matrix contai... | 3 | stack_v2_sparse_classes_30k_train_024632 | Implement the Python class `train_classifier` described below.
Class description:
Implement the train_classifier class.
Method signatures and docstrings:
- def __init__(self, df_path, image_col_name, category_col_name, fixed_size, classifier_pkl, feature_method, feature_options, image_processing_options, raw_image_pa... | Implement the Python class `train_classifier` described below.
Class description:
Implement the train_classifier class.
Method signatures and docstrings:
- def __init__(self, df_path, image_col_name, category_col_name, fixed_size, classifier_pkl, feature_method, feature_options, image_processing_options, raw_image_pa... | bbe858777fa043add1290adf56f213597bf7e44b | <|skeleton|>
class train_classifier:
def __init__(self, df_path, image_col_name, category_col_name, fixed_size, classifier_pkl, feature_method, feature_options, image_processing_options, raw_image_path, kernel='rbf', gamma='auto', C=1):
"""The class constructor :param df_path: full path to the input roi Da... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class train_classifier:
def __init__(self, df_path, image_col_name, category_col_name, fixed_size, classifier_pkl, feature_method, feature_options, image_processing_options, raw_image_path, kernel='rbf', gamma='auto', C=1):
"""The class constructor :param df_path: full path to the input roi DataFrame file (... | the_stack_v2_python_sparse | 2018_data_science_bowl/scripts/train_svm_classifier.py | laijasonk/kaggle | train | 1 | |
e316af4427639441ed2116da2deb81f2b19918eb | [
"data = self.get_json()\nname = data.get('galaxyName')\nif name is None:\n return self.error('galaxyName required to set object host')\nwith self.Session() as session:\n obj = session.scalars(Obj.select(session.user_or_token, mode='update').where(Obj.id == obj_id)).first()\n if obj is None:\n return... | <|body_start_0|>
data = self.get_json()
name = data.get('galaxyName')
if name is None:
return self.error('galaxyName required to set object host')
with self.Session() as session:
obj = session.scalars(Obj.select(session.user_or_token, mode='update').where(Obj.id =... | ObjHostHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjHostHandler:
def post(self, obj_id):
"""--- description: Set an object's host galaxy tags: - objs - galaxys parameters: - in: path name: obj_id required: true schema: type: string requestBody: content: application/json: schema: type: object properties: galaxyName: type: string descrip... | stack_v2_sparse_classes_75kplus_train_070495 | 41,985 | permissive | [
{
"docstring": "--- description: Set an object's host galaxy tags: - objs - galaxys parameters: - in: path name: obj_id required: true schema: type: string requestBody: content: application/json: schema: type: object properties: galaxyName: type: string description: | Name of the galaxy to associate with the ob... | 2 | stack_v2_sparse_classes_30k_train_019917 | Implement the Python class `ObjHostHandler` described below.
Class description:
Implement the ObjHostHandler class.
Method signatures and docstrings:
- def post(self, obj_id): --- description: Set an object's host galaxy tags: - objs - galaxys parameters: - in: path name: obj_id required: true schema: type: string re... | Implement the Python class `ObjHostHandler` described below.
Class description:
Implement the ObjHostHandler class.
Method signatures and docstrings:
- def post(self, obj_id): --- description: Set an object's host galaxy tags: - objs - galaxys parameters: - in: path name: obj_id required: true schema: type: string re... | 161d3532ba3ba059446addcdac58ca96f39e9636 | <|skeleton|>
class ObjHostHandler:
def post(self, obj_id):
"""--- description: Set an object's host galaxy tags: - objs - galaxys parameters: - in: path name: obj_id required: true schema: type: string requestBody: content: application/json: schema: type: object properties: galaxyName: type: string descrip... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ObjHostHandler:
def post(self, obj_id):
"""--- description: Set an object's host galaxy tags: - objs - galaxys parameters: - in: path name: obj_id required: true schema: type: string requestBody: content: application/json: schema: type: object properties: galaxyName: type: string description: | Name o... | the_stack_v2_python_sparse | skyportal/handlers/api/galaxy.py | skyportal/skyportal | train | 80 | |
a164b4fa59a69e1154a25238695a2d4c0fc69a16 | [
"self.__domain = domainName\nself.__kdcHost = serverIP\nself.__domainUsers = domainusers\nself.__sprayPassword = sprayPassword\nself.DomainUserRequest()",
"domain = '@' + self.__domain\nfor user in self.__domainUsers:\n targetuser = user + domain\n self.AttackToTarget(targetuser)",
"self.__sprayusers = []... | <|body_start_0|>
self.__domain = domainName
self.__kdcHost = serverIP
self.__domainUsers = domainusers
self.__sprayPassword = sprayPassword
self.DomainUserRequest()
<|end_body_0|>
<|body_start_1|>
domain = '@' + self.__domain
for user in self.__domainUsers:
... | PasswordSPRAY | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordSPRAY:
def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName):
"""Spray Attack Arguments"""
<|body_0|>
def DomainUserRequest(self):
"""Pars to Domain"""
<|body_1|>
def AttackToTarget(self, username):
"""Attack Part"""... | stack_v2_sparse_classes_75kplus_train_070496 | 1,067 | permissive | [
{
"docstring": "Spray Attack Arguments",
"name": "AttackArguments",
"signature": "def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName)"
},
{
"docstring": "Pars to Domain",
"name": "DomainUserRequest",
"signature": "def DomainUserRequest(self)"
},
{
"docstri... | 3 | stack_v2_sparse_classes_30k_train_035887 | Implement the Python class `PasswordSPRAY` described below.
Class description:
Implement the PasswordSPRAY class.
Method signatures and docstrings:
- def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName): Spray Attack Arguments
- def DomainUserRequest(self): Pars to Domain
- def AttackToTarget(s... | Implement the Python class `PasswordSPRAY` described below.
Class description:
Implement the PasswordSPRAY class.
Method signatures and docstrings:
- def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName): Spray Attack Arguments
- def DomainUserRequest(self): Pars to Domain
- def AttackToTarget(s... | 92263ea73bd2eaa2081fb277c76aa229103a1d54 | <|skeleton|>
class PasswordSPRAY:
def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName):
"""Spray Attack Arguments"""
<|body_0|>
def DomainUserRequest(self):
"""Pars to Domain"""
<|body_1|>
def AttackToTarget(self, username):
"""Attack Part"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PasswordSPRAY:
def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName):
"""Spray Attack Arguments"""
self.__domain = domainName
self.__kdcHost = serverIP
self.__domainUsers = domainusers
self.__sprayPassword = sprayPassword
self.DomainUserReq... | the_stack_v2_python_sparse | pentestui/pentest_api/enumeration/ldap/spray/sprayattack.py | mustgundogdu/PentestUI | train | 31 | |
a50be3966194211bd56a985baecdfdcfae6e9d99 | [
"try:\n object_list = persistent_query_example_api.get_all_by_user(request.user)\n serializer = self.serializer(object_list, many=True)\n return Response(serializer.data, status=status.HTTP_200_OK)\nexcept AccessControlError as exception:\n content = {'message': str(exception)}\n return Response(cont... | <|body_start_0|>
try:
object_list = persistent_query_example_api.get_all_by_user(request.user)
serializer = self.serializer(object_list, many=True)
return Response(serializer.data, status=status.HTTP_200_OK)
except AccessControlError as exception:
content ... | List all persistent query example or create one | PersistentQueryExampleList | [
"NIST-Software",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersistentQueryExampleList:
"""List all persistent query example or create one"""
def get(self, request):
"""Get all user persistent query example Args: request: HTTP request Returns: - code: 200 content: List of persistent query example - code: 403 content: Forbidden - code: 500 con... | stack_v2_sparse_classes_75kplus_train_070497 | 13,206 | permissive | [
{
"docstring": "Get all user persistent query example Args: request: HTTP request Returns: - code: 200 content: List of persistent query example - code: 403 content: Forbidden - code: 500 content: Internal server error",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Cre... | 2 | stack_v2_sparse_classes_30k_test_000259 | Implement the Python class `PersistentQueryExampleList` described below.
Class description:
List all persistent query example or create one
Method signatures and docstrings:
- def get(self, request): Get all user persistent query example Args: request: HTTP request Returns: - code: 200 content: List of persistent que... | Implement the Python class `PersistentQueryExampleList` described below.
Class description:
List all persistent query example or create one
Method signatures and docstrings:
- def get(self, request): Get all user persistent query example Args: request: HTTP request Returns: - code: 200 content: List of persistent que... | 2abebfd1c2319899d907ad0b650fedb955be7492 | <|skeleton|>
class PersistentQueryExampleList:
"""List all persistent query example or create one"""
def get(self, request):
"""Get all user persistent query example Args: request: HTTP request Returns: - code: 200 content: List of persistent query example - code: 403 content: Forbidden - code: 500 con... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PersistentQueryExampleList:
"""List all persistent query example or create one"""
def get(self, request):
"""Get all user persistent query example Args: request: HTTP request Returns: - code: 200 content: List of persistent query example - code: 403 content: Forbidden - code: 500 content: Interna... | the_stack_v2_python_sparse | core_explore_example_app/rest/persistent_query_example/views.py | usnistgov/core_explore_example_app | train | 0 |
a1bf59e97e61330f0ba7c69e348c15ff7727b4be | [
"def backtrack(start, track):\n if sum(track) == n and len(track) == k:\n return res.append(track[:])\n if sum(track) > n or len(track) > k:\n return\n for i in range(start, 10):\n track.append(i)\n backtrack(i + 1, track)\n track.pop()\nres = []\nif n <= 0 or k <= 0:\n ... | <|body_start_0|>
def backtrack(start, track):
if sum(track) == n and len(track) == k:
return res.append(track[:])
if sum(track) > n or len(track) > k:
return
for i in range(start, 10):
track.append(i)
backtrack(i... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum3(self, k: int, n: int) -> List[List[int]]:
"""k 限制了树的高度，n 限制了树的宽度。"""
<|body_0|>
def combinationSum3_1(self, k: int, n: int) -> List[List[int]]:
"""k 限制了树的高度，n 限制了树的宽度。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def... | stack_v2_sparse_classes_75kplus_train_070498 | 2,352 | permissive | [
{
"docstring": "k 限制了树的高度，n 限制了树的宽度。",
"name": "combinationSum3",
"signature": "def combinationSum3(self, k: int, n: int) -> List[List[int]]"
},
{
"docstring": "k 限制了树的高度，n 限制了树的宽度。",
"name": "combinationSum3_1",
"signature": "def combinationSum3_1(self, k: int, n: int) -> List[List[int]... | 2 | stack_v2_sparse_classes_30k_train_039760 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum3(self, k: int, n: int) -> List[List[int]]: k 限制了树的高度，n 限制了树的宽度。
- def combinationSum3_1(self, k: int, n: int) -> List[List[int]]: k 限制了树的高度，n 限制了树的宽度。 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum3(self, k: int, n: int) -> List[List[int]]: k 限制了树的高度，n 限制了树的宽度。
- def combinationSum3_1(self, k: int, n: int) -> List[List[int]]: k 限制了树的高度，n 限制了树的宽度。
<|skele... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def combinationSum3(self, k: int, n: int) -> List[List[int]]:
"""k 限制了树的高度，n 限制了树的宽度。"""
<|body_0|>
def combinationSum3_1(self, k: int, n: int) -> List[List[int]]:
"""k 限制了树的高度，n 限制了树的宽度。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def combinationSum3(self, k: int, n: int) -> List[List[int]]:
"""k 限制了树的高度，n 限制了树的宽度。"""
def backtrack(start, track):
if sum(track) == n and len(track) == k:
return res.append(track[:])
if sum(track) > n or len(track) > k:
retur... | the_stack_v2_python_sparse | 216-combination-sum-iii.py | yuenliou/leetcode | train | 0 | |
e6c7f349891e6fefbb3f91a45dc7b4737e5fb989 | [
"self.dataset = dataset[dataset['listingtype'] == 'sold']\nself.target_var = target_var\nself.cont_num_columns = cont_num_columns\nself.discrete_num_columns = discrete_num_columns\nself.nominal_cat_columns = nominal_cat_columns\nself.verbose_columns = verbose_columns\nself.verbose_threshold = verbose_threshold\nsel... | <|body_start_0|>
self.dataset = dataset[dataset['listingtype'] == 'sold']
self.target_var = target_var
self.cont_num_columns = cont_num_columns
self.discrete_num_columns = discrete_num_columns
self.nominal_cat_columns = nominal_cat_columns
self.verbose_columns = verbose_c... | ModelInputETL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelInputETL:
def __init__(self, dataset, target_var='', cont_num_columns=[], discrete_num_columns=[], nominal_cat_columns=[], verbose_columns=[], verbose_threshold=[], verbose_most_common=[], pca_columns=[], pca_expl_var=0.95, operation='model'):
"""Create Features from Raw Data."""
... | stack_v2_sparse_classes_75kplus_train_070499 | 2,994 | no_license | [
{
"docstring": "Create Features from Raw Data.",
"name": "__init__",
"signature": "def __init__(self, dataset, target_var='', cont_num_columns=[], discrete_num_columns=[], nominal_cat_columns=[], verbose_columns=[], verbose_threshold=[], verbose_most_common=[], pca_columns=[], pca_expl_var=0.95, operati... | 2 | stack_v2_sparse_classes_30k_train_053903 | Implement the Python class `ModelInputETL` described below.
Class description:
Implement the ModelInputETL class.
Method signatures and docstrings:
- def __init__(self, dataset, target_var='', cont_num_columns=[], discrete_num_columns=[], nominal_cat_columns=[], verbose_columns=[], verbose_threshold=[], verbose_most_... | Implement the Python class `ModelInputETL` described below.
Class description:
Implement the ModelInputETL class.
Method signatures and docstrings:
- def __init__(self, dataset, target_var='', cont_num_columns=[], discrete_num_columns=[], nominal_cat_columns=[], verbose_columns=[], verbose_threshold=[], verbose_most_... | 721e1a2fca36c378206462a36cecc9f403d11c86 | <|skeleton|>
class ModelInputETL:
def __init__(self, dataset, target_var='', cont_num_columns=[], discrete_num_columns=[], nominal_cat_columns=[], verbose_columns=[], verbose_threshold=[], verbose_most_common=[], pca_columns=[], pca_expl_var=0.95, operation='model'):
"""Create Features from Raw Data."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModelInputETL:
def __init__(self, dataset, target_var='', cont_num_columns=[], discrete_num_columns=[], nominal_cat_columns=[], verbose_columns=[], verbose_threshold=[], verbose_most_common=[], pca_columns=[], pca_expl_var=0.95, operation='model'):
"""Create Features from Raw Data."""
self.dat... | the_stack_v2_python_sparse | DeepREI/Model/src/preprocessing/ModelInputETL.py | dangoML/Project-Portfolio | train | 5 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.