blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
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value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
5399b121ec372865fd963a3fbe863b425e656ae2 | [
"if data is None:\n if lambtha <= 0:\n raise ValueError('lambtha must be a positive value')\n self.lambtha = float(lambtha)\nelse:\n if not isinstance(data, list):\n raise TypeError('data must be a list')\n if len(data) < 2:\n raise ValueError('data must contain multiple values')\n ... | <|body_start_0|>
if data is None:
if lambtha <= 0:
raise ValueError('lambtha must be a positive value')
self.lambtha = float(lambtha)
else:
if not isinstance(data, list):
raise TypeError('data must be a list')
if len(data) <... | Poisson | Poisson | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Poisson:
"""Poisson"""
def __init__(self, data=None, lambtha=1.0):
"""Constructor"""
<|body_0|>
def pmf(self, k):
"""Calculates PMF"""
<|body_1|>
def cdf(self, k):
"""calculate CDF"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_000500 | 1,184 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, data=None, lambtha=1.0)"
},
{
"docstring": "Calculates PMF",
"name": "pmf",
"signature": "def pmf(self, k)"
},
{
"docstring": "calculate CDF",
"name": "cdf",
"signature": "def cdf(self, k)"... | 3 | null | Implement the Python class `Poisson` described below.
Class description:
Poisson
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Constructor
- def pmf(self, k): Calculates PMF
- def cdf(self, k): calculate CDF | Implement the Python class `Poisson` described below.
Class description:
Poisson
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Constructor
- def pmf(self, k): Calculates PMF
- def cdf(self, k): calculate CDF
<|skeleton|>
class Poisson:
"""Poisson"""
def __init__(self, data=... | ff1af62484620b599cc3813068770db03b37036d | <|skeleton|>
class Poisson:
"""Poisson"""
def __init__(self, data=None, lambtha=1.0):
"""Constructor"""
<|body_0|>
def pmf(self, k):
"""Calculates PMF"""
<|body_1|>
def cdf(self, k):
"""calculate CDF"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Poisson:
"""Poisson"""
def __init__(self, data=None, lambtha=1.0):
"""Constructor"""
if data is None:
if lambtha <= 0:
raise ValueError('lambtha must be a positive value')
self.lambtha = float(lambtha)
else:
if not isinstance(dat... | the_stack_v2_python_sparse | math/0x03-probability/poisson.py | paurbano/holbertonschool-machine_learning | train | 0 |
13b9428e0f046efdfffb52c2e296efe195138dba | [
"for rule_cls in self.rules:\n rule = rule_cls()\n logging.info(f'Running: {rule}')\n for result in rule.evaluate(oi):\n yield result",
"rule_dict = {rule.__name__: rule for rule in RULES}\nself.rules = [rule_dict[name] for name in rule_names]\nlogging.info(f'Set rules: {self.rules}')"
] | <|body_start_0|>
for rule_cls in self.rules:
rule = rule_cls()
logging.info(f'Running: {rule}')
for result in rule.evaluate(oi):
yield result
<|end_body_0|>
<|body_start_1|>
rule_dict = {rule.__name__: rule for rule in RULES}
self.rules = [rul... | RuleRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RuleRunner:
def run(self, oi: BasicOntologyInterface) -> Iterable[ValidationResult]:
"""Run all rules :param oi: :return:"""
<|body_0|>
def set_rules(self, rule_names: Iterable[str]) -> None:
"""Set the rules to run :param rules: :return:"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_000501 | 1,313 | permissive | [
{
"docstring": "Run all rules :param oi: :return:",
"name": "run",
"signature": "def run(self, oi: BasicOntologyInterface) -> Iterable[ValidationResult]"
},
{
"docstring": "Set the rules to run :param rules: :return:",
"name": "set_rules",
"signature": "def set_rules(self, rule_names: It... | 2 | null | Implement the Python class `RuleRunner` described below.
Class description:
Implement the RuleRunner class.
Method signatures and docstrings:
- def run(self, oi: BasicOntologyInterface) -> Iterable[ValidationResult]: Run all rules :param oi: :return:
- def set_rules(self, rule_names: Iterable[str]) -> None: Set the r... | Implement the Python class `RuleRunner` described below.
Class description:
Implement the RuleRunner class.
Method signatures and docstrings:
- def run(self, oi: BasicOntologyInterface) -> Iterable[ValidationResult]: Run all rules :param oi: :return:
- def set_rules(self, rule_names: Iterable[str]) -> None: Set the r... | 8d2a124f7af66fe2e796f9e0ece55585438796a5 | <|skeleton|>
class RuleRunner:
def run(self, oi: BasicOntologyInterface) -> Iterable[ValidationResult]:
"""Run all rules :param oi: :return:"""
<|body_0|>
def set_rules(self, rule_names: Iterable[str]) -> None:
"""Set the rules to run :param rules: :return:"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RuleRunner:
def run(self, oi: BasicOntologyInterface) -> Iterable[ValidationResult]:
"""Run all rules :param oi: :return:"""
for rule_cls in self.rules:
rule = rule_cls()
logging.info(f'Running: {rule}')
for result in rule.evaluate(oi):
yield... | the_stack_v2_python_sparse | src/oaklib/utilities/validation/rule_runner.py | INCATools/ontology-access-kit | train | 67 | |
6ddbd8d7ed307d91d245ff2505927accb29986a4 | [
"result = []\nself.restore(s, 4, '', result)\nreturn result",
"if seg_no == 1:\n if int(s) > 255 or (s[0] == '0' and len(s) > 1):\n return None\n else:\n cur_ip += '.' + s\n ip_list.append(cur_ip[1:])\n return s\nfor i in range(0, len(s) - seg_no + 1):\n ip_seg = s[0:i + 1]\n ... | <|body_start_0|>
result = []
self.restore(s, 4, '', result)
return result
<|end_body_0|>
<|body_start_1|>
if seg_no == 1:
if int(s) > 255 or (s[0] == '0' and len(s) > 1):
return None
else:
cur_ip += '.' + s
ip_list.... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def restoreIpAddresses(self, s):
"""使用递归：每次递归确定第n个地址段的所有可能，在第4个地址段结束递归 :type s: str :rtype: List[str]"""
<|body_0|>
def restore(self, s, seg_no, cur_ip, ip_list):
"""递归主体 :param s: 字符串 :param seg_no: 当前ip片段的idx :param cur_ip: 当前ip，用于传递当前以及restore好的ip :param... | stack_v2_sparse_classes_36k_train_000502 | 1,787 | no_license | [
{
"docstring": "使用递归：每次递归确定第n个地址段的所有可能，在第4个地址段结束递归 :type s: str :rtype: List[str]",
"name": "restoreIpAddresses",
"signature": "def restoreIpAddresses(self, s)"
},
{
"docstring": "递归主体 :param s: 字符串 :param seg_no: 当前ip片段的idx :param cur_ip: 当前ip，用于传递当前以及restore好的ip :param ip_list: 最终结果存放列表 :retur... | 2 | stack_v2_sparse_classes_30k_train_002267 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def restoreIpAddresses(self, s): 使用递归：每次递归确定第n个地址段的所有可能，在第4个地址段结束递归 :type s: str :rtype: List[str]
- def restore(self, s, seg_no, cur_ip, ip_list): 递归主体 :param s: 字符串 :param seg_... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def restoreIpAddresses(self, s): 使用递归：每次递归确定第n个地址段的所有可能，在第4个地址段结束递归 :type s: str :rtype: List[str]
- def restore(self, s, seg_no, cur_ip, ip_list): 递归主体 :param s: 字符串 :param seg_... | 68a09a1ea2fb5083d62d8188c7ef213b2cc315cd | <|skeleton|>
class Solution:
def restoreIpAddresses(self, s):
"""使用递归：每次递归确定第n个地址段的所有可能，在第4个地址段结束递归 :type s: str :rtype: List[str]"""
<|body_0|>
def restore(self, s, seg_no, cur_ip, ip_list):
"""递归主体 :param s: 字符串 :param seg_no: 当前ip片段的idx :param cur_ip: 当前ip，用于传递当前以及restore好的ip :param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def restoreIpAddresses(self, s):
"""使用递归：每次递归确定第n个地址段的所有可能，在第4个地址段结束递归 :type s: str :rtype: List[str]"""
result = []
self.restore(s, 4, '', result)
return result
def restore(self, s, seg_no, cur_ip, ip_list):
"""递归主体 :param s: 字符串 :param seg_no: 当前ip片段的id... | the_stack_v2_python_sparse | leetcode081-100/leetcode93-restore-ip-addresses.py | linshuang/code4fun | train | 0 | |
7c60bf82e61a98ea3d96b025467db0fa5af6974b | [
"for frame in g.app.windowList:\n if frame.c != c:\n frame.c.close()",
"result: list[str] = []\nif not getattr(g.app.gui, 'frameFactory', None):\n return result\nmf = getattr(g.app.gui.frameFactory, 'masterFrame', None)\nif mf:\n outlines = [mf.widget(i).leo_c for i in range(mf.count())]\nelse:\n ... | <|body_start_0|>
for frame in g.app.windowList:
if frame.c != c:
frame.c.close()
<|end_body_0|>
<|body_start_1|>
result: list[str] = []
if not getattr(g.app.gui, 'frameFactory', None):
return result
mf = getattr(g.app.gui.frameFactory, 'masterFram... | A class managing session data and related commands. | SessionManager | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionManager:
"""A class managing session data and related commands."""
def clear_session(self, c: Cmdr) -> None:
"""Close all tabs except the presently selected tab."""
<|body_0|>
def get_session(self) -> list[str]:
"""Return a list of UNLs for open tabs."""
... | stack_v2_sparse_classes_36k_train_000503 | 6,641 | permissive | [
{
"docstring": "Close all tabs except the presently selected tab.",
"name": "clear_session",
"signature": "def clear_session(self, c: Cmdr) -> None"
},
{
"docstring": "Return a list of UNLs for open tabs.",
"name": "get_session",
"signature": "def get_session(self) -> list[str]"
},
{... | 6 | null | Implement the Python class `SessionManager` described below.
Class description:
A class managing session data and related commands.
Method signatures and docstrings:
- def clear_session(self, c: Cmdr) -> None: Close all tabs except the presently selected tab.
- def get_session(self) -> list[str]: Return a list of UNL... | Implement the Python class `SessionManager` described below.
Class description:
A class managing session data and related commands.
Method signatures and docstrings:
- def clear_session(self, c: Cmdr) -> None: Close all tabs except the presently selected tab.
- def get_session(self) -> list[str]: Return a list of UNL... | a3f6c3ebda805dc40cd93123948f153a26eccee5 | <|skeleton|>
class SessionManager:
"""A class managing session data and related commands."""
def clear_session(self, c: Cmdr) -> None:
"""Close all tabs except the presently selected tab."""
<|body_0|>
def get_session(self) -> list[str]:
"""Return a list of UNLs for open tabs."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SessionManager:
"""A class managing session data and related commands."""
def clear_session(self, c: Cmdr) -> None:
"""Close all tabs except the presently selected tab."""
for frame in g.app.windowList:
if frame.c != c:
frame.c.close()
def get_session(self... | the_stack_v2_python_sparse | leo/core/leoSessions.py | leo-editor/leo-editor | train | 1,671 |
28f1c2035d5bd40880fc34bf9ced71900512d0f4 | [
"filterInputValue = request.GET.get('filterInputValue', '')\nfilterDbType = request.GET.get('filterDbType[]', '')\nfilterDbType = json.loads(filterDbType) if len(filterDbType) > 2 else None\nobj = DataSourceConfig.objects.filter()\nif filterInputValue:\n obj = obj.filter(host__contains=filterInputValue)\nif filt... | <|body_start_0|>
filterInputValue = request.GET.get('filterInputValue', '')
filterDbType = request.GET.get('filterDbType[]', '')
filterDbType = json.loads(filterDbType) if len(filterDbType) > 2 else None
obj = DataSourceConfig.objects.filter()
if filterInputValue:
obj... | DataSourceConfigList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSourceConfigList:
def get(self, request, *args, **kwargs):
"""数据源列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑数据源"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建数据源"""
<|body_2|>
def delete(self, r... | stack_v2_sparse_classes_36k_train_000504 | 9,325 | no_license | [
{
"docstring": "数据源列表",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "编辑数据源",
"name": "put",
"signature": "def put(self, request, *args, **kwargs)"
},
{
"docstring": "创建数据源",
"name": "post",
"signature": "def post(self, request, ... | 4 | stack_v2_sparse_classes_30k_val_000568 | Implement the Python class `DataSourceConfigList` described below.
Class description:
Implement the DataSourceConfigList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 数据源列表
- def put(self, request, *args, **kwargs): 编辑数据源
- def post(self, request, *args, **kwargs): 创建数据源
- def de... | Implement the Python class `DataSourceConfigList` described below.
Class description:
Implement the DataSourceConfigList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 数据源列表
- def put(self, request, *args, **kwargs): 编辑数据源
- def post(self, request, *args, **kwargs): 创建数据源
- def de... | f2523d6e51cde1b53ac6f453f8066b4b90c523b9 | <|skeleton|>
class DataSourceConfigList:
def get(self, request, *args, **kwargs):
"""数据源列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑数据源"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建数据源"""
<|body_2|>
def delete(self, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataSourceConfigList:
def get(self, request, *args, **kwargs):
"""数据源列表"""
filterInputValue = request.GET.get('filterInputValue', '')
filterDbType = request.GET.get('filterDbType[]', '')
filterDbType = json.loads(filterDbType) if len(filterDbType) > 2 else None
obj = Da... | the_stack_v2_python_sparse | api/db/rest/dataSourceConfig.py | zhuzhanhao1/backend | train | 0 | |
fb4049d8db8793c5d605768946086fd310732a59 | [
"permutations = set([('K', 'K', 'R'), ('K', 'R', 'K'), ('R', 'K', 'K')])\nresult = board.possible_ordered_sequences({'K': 2, 'Q': 0, 'R': 1, 'B': 0, 'N': 0})\nself.assertEqual(permutations, set(result))",
"matrix = [[0] * 3 for _ in itertools.repeat(None, 3)]\ncorner_uleft_boundaries = [1, 2, 5]\nresult = board.p... | <|body_start_0|>
permutations = set([('K', 'K', 'R'), ('K', 'R', 'K'), ('R', 'K', 'K')])
result = board.possible_ordered_sequences({'K': 2, 'Q': 0, 'R': 1, 'B': 0, 'N': 0})
self.assertEqual(permutations, set(result))
<|end_body_0|>
<|body_start_1|>
matrix = [[0] * 3 for _ in itertools.r... | Class of chess main application - board module testing | BoardApplicationTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoardApplicationTest:
"""Class of chess main application - board module testing"""
def test_permutations(self):
"""Tests possible ordered sequences in permutation"""
<|body_0|>
def test_boundaries(self):
"""Tests boundaries checking"""
<|body_1|>
def... | stack_v2_sparse_classes_36k_train_000505 | 6,418 | permissive | [
{
"docstring": "Tests possible ordered sequences in permutation",
"name": "test_permutations",
"signature": "def test_permutations(self)"
},
{
"docstring": "Tests boundaries checking",
"name": "test_boundaries",
"signature": "def test_boundaries(self)"
},
{
"docstring": "Tests ch... | 5 | stack_v2_sparse_classes_30k_val_000332 | Implement the Python class `BoardApplicationTest` described below.
Class description:
Class of chess main application - board module testing
Method signatures and docstrings:
- def test_permutations(self): Tests possible ordered sequences in permutation
- def test_boundaries(self): Tests boundaries checking
- def tes... | Implement the Python class `BoardApplicationTest` described below.
Class description:
Class of chess main application - board module testing
Method signatures and docstrings:
- def test_permutations(self): Tests possible ordered sequences in permutation
- def test_boundaries(self): Tests boundaries checking
- def tes... | 7470479e352bf6fa28215e745af8c42dc20d7a1f | <|skeleton|>
class BoardApplicationTest:
"""Class of chess main application - board module testing"""
def test_permutations(self):
"""Tests possible ordered sequences in permutation"""
<|body_0|>
def test_boundaries(self):
"""Tests boundaries checking"""
<|body_1|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BoardApplicationTest:
"""Class of chess main application - board module testing"""
def test_permutations(self):
"""Tests possible ordered sequences in permutation"""
permutations = set([('K', 'K', 'R'), ('K', 'R', 'K'), ('R', 'K', 'K')])
result = board.possible_ordered_sequences({... | the_stack_v2_python_sparse | challenges/chess/tests.py | williamlagos/python-coding | train | 0 |
46372296cede8dc8ccb262e21bf6c4d0dab8ad95 | [
"self.f = f\nself.gp = GP(X_init, Y_init, l, sigma_f)\nb_min, b_max = bounds\nself.X_s = np.linspace(b_min, b_max, num=ac_samples).reshape(-1, 1)\nself.xsi = xsi\nself.minimize = minimize",
"mu, sigma = self.gp.predict(self.X_s)\nif self.minimize is True:\n f_plus = np.amin(self.gp.Y)\n imp = f_plus - mu - ... | <|body_start_0|>
self.f = f
self.gp = GP(X_init, Y_init, l, sigma_f)
b_min, b_max = bounds
self.X_s = np.linspace(b_min, b_max, num=ac_samples).reshape(-1, 1)
self.xsi = xsi
self.minimize = minimize
<|end_body_0|>
<|body_start_1|>
mu, sigma = self.gp.predict(self... | Bayesian optimization on a noiseless 1D Gaussian process: | BayesianOptimization | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BayesianOptimization:
"""Bayesian optimization on a noiseless 1D Gaussian process:"""
def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True):
"""- f is the black-box function to be optimized - X_init is a numpy.ndarray of shape (t, 1) repre... | stack_v2_sparse_classes_36k_train_000506 | 4,224 | no_license | [
{
"docstring": "- f is the black-box function to be optimized - X_init is a numpy.ndarray of shape (t, 1) representing the inputs already sampled with the black-box function - Y_init is a numpy.ndarray of shape (t, 1) representing the outputs of the black-box function for each input in X_init - t is the number ... | 3 | null | Implement the Python class `BayesianOptimization` described below.
Class description:
Bayesian optimization on a noiseless 1D Gaussian process:
Method signatures and docstrings:
- def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True): - f is the black-box function to be op... | Implement the Python class `BayesianOptimization` described below.
Class description:
Bayesian optimization on a noiseless 1D Gaussian process:
Method signatures and docstrings:
- def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True): - f is the black-box function to be op... | e10b4e9b6f3fa00639e6e9e5b35f0cdb43a339a3 | <|skeleton|>
class BayesianOptimization:
"""Bayesian optimization on a noiseless 1D Gaussian process:"""
def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True):
"""- f is the black-box function to be optimized - X_init is a numpy.ndarray of shape (t, 1) repre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BayesianOptimization:
"""Bayesian optimization on a noiseless 1D Gaussian process:"""
def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True):
"""- f is the black-box function to be optimized - X_init is a numpy.ndarray of shape (t, 1) representing the i... | the_stack_v2_python_sparse | unsupervised_learning/0x03-hyperparameter_tuning/5-bayes_opt.py | HeimerR/holbertonschool-machine_learning | train | 0 |
4bc8f0bfb6cdb80d47c3f0545e559fbf01850196 | [
"self.coef_ = None\nself.intercept_ = None\nself._theta = None",
"assert X_train.shape[0] == y_train.shape[0], 'The size of X_train must be equal to the size of y_train'\nX_b = np.vstack([np.ones((len(X_train), 1)), X_train])\nself._theta = np.linalg.inv(X_b.T.dot(X_b)).dot(X_b.T).dot(y_train)\nself.coef_ = self.... | <|body_start_0|>
self.coef_ = None
self.intercept_ = None
self._theta = None
<|end_body_0|>
<|body_start_1|>
assert X_train.shape[0] == y_train.shape[0], 'The size of X_train must be equal to the size of y_train'
X_b = np.vstack([np.ones((len(X_train), 1)), X_train])
sel... | LinearRegression | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearRegression:
def __int__(self):
"""构造方法"""
<|body_0|>
def fit_nomal(self, X_train, y_train):
"""根据训练数据集X_train, y_train训练Linear Regression模型"""
<|body_1|>
def predict(self, X_predict):
"""给定待预测数据集X_predict，返回表示X_predict的结果向量"""
<|bod... | stack_v2_sparse_classes_36k_train_000507 | 1,092 | no_license | [
{
"docstring": "构造方法",
"name": "__int__",
"signature": "def __int__(self)"
},
{
"docstring": "根据训练数据集X_train, y_train训练Linear Regression模型",
"name": "fit_nomal",
"signature": "def fit_nomal(self, X_train, y_train)"
},
{
"docstring": "给定待预测数据集X_predict，返回表示X_predict的结果向量",
"na... | 3 | stack_v2_sparse_classes_30k_train_004580 | Implement the Python class `LinearRegression` described below.
Class description:
Implement the LinearRegression class.
Method signatures and docstrings:
- def __int__(self): 构造方法
- def fit_nomal(self, X_train, y_train): 根据训练数据集X_train, y_train训练Linear Regression模型
- def predict(self, X_predict): 给定待预测数据集X_predict，返回... | Implement the Python class `LinearRegression` described below.
Class description:
Implement the LinearRegression class.
Method signatures and docstrings:
- def __int__(self): 构造方法
- def fit_nomal(self, X_train, y_train): 根据训练数据集X_train, y_train训练Linear Regression模型
- def predict(self, X_predict): 给定待预测数据集X_predict，返回... | 517ac7b7992a686fa5370b6fda8b62663735853c | <|skeleton|>
class LinearRegression:
def __int__(self):
"""构造方法"""
<|body_0|>
def fit_nomal(self, X_train, y_train):
"""根据训练数据集X_train, y_train训练Linear Regression模型"""
<|body_1|>
def predict(self, X_predict):
"""给定待预测数据集X_predict，返回表示X_predict的结果向量"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearRegression:
def __int__(self):
"""构造方法"""
self.coef_ = None
self.intercept_ = None
self._theta = None
def fit_nomal(self, X_train, y_train):
"""根据训练数据集X_train, y_train训练Linear Regression模型"""
assert X_train.shape[0] == y_train.shape[0], 'The size of X... | the_stack_v2_python_sparse | MachineLearning/PlayML/LinearRegression.py | CharlesBird/Resources | train | 1 | |
83a70ed2d61353c68c47156f851f49936d5fc15c | [
"self.job_id = job_id\nself.num_machines_failed = num_machines_failed\nself.num_machines_passed = num_machines_passed\nself.num_machines_total = num_machines_total\nself.registering_app = registering_app\nself.state = state",
"if dictionary is None:\n return None\njob_id = dictionary.get('jobId')\nnum_machines... | <|body_start_0|>
self.job_id = job_id
self.num_machines_failed = num_machines_failed
self.num_machines_passed = num_machines_passed
self.num_machines_total = num_machines_total
self.registering_app = registering_app
self.state = state
<|end_body_0|>
<|body_start_1|>
... | Implementation of the 'BulkInstallAppTaskInfo' model. Parameters for a bulk install app task. Attributes: job_id (string): Job id of the task. num_machines_failed (int): Number of machines on which task is started. num_machines_passed (int): Number of machines on which task is started. num_machines_total (int): Number ... | BulkInstallAppTaskInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BulkInstallAppTaskInfo:
"""Implementation of the 'BulkInstallAppTaskInfo' model. Parameters for a bulk install app task. Attributes: job_id (string): Job id of the task. num_machines_failed (int): Number of machines on which task is started. num_machines_passed (int): Number of machines on which ... | stack_v2_sparse_classes_36k_train_000508 | 3,321 | permissive | [
{
"docstring": "Constructor for the BulkInstallAppTaskInfo class",
"name": "__init__",
"signature": "def __init__(self, job_id=None, num_machines_failed=None, num_machines_passed=None, num_machines_total=None, registering_app=None, state=None)"
},
{
"docstring": "Creates an instance of this mode... | 2 | stack_v2_sparse_classes_30k_train_007332 | Implement the Python class `BulkInstallAppTaskInfo` described below.
Class description:
Implementation of the 'BulkInstallAppTaskInfo' model. Parameters for a bulk install app task. Attributes: job_id (string): Job id of the task. num_machines_failed (int): Number of machines on which task is started. num_machines_pas... | Implement the Python class `BulkInstallAppTaskInfo` described below.
Class description:
Implementation of the 'BulkInstallAppTaskInfo' model. Parameters for a bulk install app task. Attributes: job_id (string): Job id of the task. num_machines_failed (int): Number of machines on which task is started. num_machines_pas... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class BulkInstallAppTaskInfo:
"""Implementation of the 'BulkInstallAppTaskInfo' model. Parameters for a bulk install app task. Attributes: job_id (string): Job id of the task. num_machines_failed (int): Number of machines on which task is started. num_machines_passed (int): Number of machines on which ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BulkInstallAppTaskInfo:
"""Implementation of the 'BulkInstallAppTaskInfo' model. Parameters for a bulk install app task. Attributes: job_id (string): Job id of the task. num_machines_failed (int): Number of machines on which task is started. num_machines_passed (int): Number of machines on which task is start... | the_stack_v2_python_sparse | cohesity_management_sdk/models/bulk_install_app_task_info.py | cohesity/management-sdk-python | train | 24 |
2c1ce9b33fc0b7ac96c0e683692982322e64f2ae | [
"q = quantity.Inertia(1.0, 'kg*m^2')\nself.assertAlmostEqual(q.value, 1.0, 6)\nself.assertAlmostEqual(q.value_si, 1.0, delta=1e-06)\nself.assertEqual(q.units, 'kg*m^2')",
"q = quantity.Inertia(1.0, 'amu*angstrom^2')\nself.assertAlmostEqual(q.value, 1.0, 6)\nself.assertAlmostEqual(q.value_si * constants.Na * 1e+23... | <|body_start_0|>
q = quantity.Inertia(1.0, 'kg*m^2')
self.assertAlmostEqual(q.value, 1.0, 6)
self.assertAlmostEqual(q.value_si, 1.0, delta=1e-06)
self.assertEqual(q.units, 'kg*m^2')
<|end_body_0|>
<|body_start_1|>
q = quantity.Inertia(1.0, 'amu*angstrom^2')
self.assertAl... | Contains unit tests of the Inertia unit type object. | TestInertia | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestInertia:
"""Contains unit tests of the Inertia unit type object."""
def test_kg_m2(self):
"""Test the creation of a moment of inertia quantity with units of kg*m^2."""
<|body_0|>
def test_amu_angstrom2(self):
"""Test the creation of a moment of inertia quanti... | stack_v2_sparse_classes_36k_train_000509 | 33,010 | permissive | [
{
"docstring": "Test the creation of a moment of inertia quantity with units of kg*m^2.",
"name": "test_kg_m2",
"signature": "def test_kg_m2(self)"
},
{
"docstring": "Test the creation of a moment of inertia quantity with units of amu*angstrom^2.",
"name": "test_amu_angstrom2",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_009005 | Implement the Python class `TestInertia` described below.
Class description:
Contains unit tests of the Inertia unit type object.
Method signatures and docstrings:
- def test_kg_m2(self): Test the creation of a moment of inertia quantity with units of kg*m^2.
- def test_amu_angstrom2(self): Test the creation of a mom... | Implement the Python class `TestInertia` described below.
Class description:
Contains unit tests of the Inertia unit type object.
Method signatures and docstrings:
- def test_kg_m2(self): Test the creation of a moment of inertia quantity with units of kg*m^2.
- def test_amu_angstrom2(self): Test the creation of a mom... | 0937b2e0a955dcf21b79674a4e89f43941c0dd85 | <|skeleton|>
class TestInertia:
"""Contains unit tests of the Inertia unit type object."""
def test_kg_m2(self):
"""Test the creation of a moment of inertia quantity with units of kg*m^2."""
<|body_0|>
def test_amu_angstrom2(self):
"""Test the creation of a moment of inertia quanti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestInertia:
"""Contains unit tests of the Inertia unit type object."""
def test_kg_m2(self):
"""Test the creation of a moment of inertia quantity with units of kg*m^2."""
q = quantity.Inertia(1.0, 'kg*m^2')
self.assertAlmostEqual(q.value, 1.0, 6)
self.assertAlmostEqual(q.... | the_stack_v2_python_sparse | rmgpy/quantityTest.py | vrlambert/RMG-Py | train | 1 |
699dada0f6978149a95a3e76b18be7ba86887adb | [
"loss = self.compute_loss(data)\nloss['total'] = loss['total'].item()\nreturn loss",
"\"\"\"load input and ground-truth data\"\"\"\ndata = self.to_device(data)\n'network forwarding'\nest_data = self.net(data)\n'computer losses'\nloss = self.net.loss(est_data, data[1])\nreturn loss"
] | <|body_start_0|>
loss = self.compute_loss(data)
loss['total'] = loss['total'].item()
return loss
<|end_body_0|>
<|body_start_1|>
"""load input and ground-truth data"""
data = self.to_device(data)
'network forwarding'
est_data = self.net(data)
'computer lo... | Trainer object for pano3d. | Trainer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trainer:
"""Trainer object for pano3d."""
def eval_step(self, data):
"""performs a step in evaluation :param data (dict): data dictionary :return:"""
<|body_0|>
def compute_loss(self, data):
"""compute the overall loss. :param data (dict): data dictionary :return... | stack_v2_sparse_classes_36k_train_000510 | 778 | permissive | [
{
"docstring": "performs a step in evaluation :param data (dict): data dictionary :return:",
"name": "eval_step",
"signature": "def eval_step(self, data)"
},
{
"docstring": "compute the overall loss. :param data (dict): data dictionary :return:",
"name": "compute_loss",
"signature": "def... | 2 | null | Implement the Python class `Trainer` described below.
Class description:
Trainer object for pano3d.
Method signatures and docstrings:
- def eval_step(self, data): performs a step in evaluation :param data (dict): data dictionary :return:
- def compute_loss(self, data): compute the overall loss. :param data (dict): da... | Implement the Python class `Trainer` described below.
Class description:
Trainer object for pano3d.
Method signatures and docstrings:
- def eval_step(self, data): performs a step in evaluation :param data (dict): data dictionary :return:
- def compute_loss(self, data): compute the overall loss. :param data (dict): da... | 8628c19b8113a64d529def5447a207a77143f916 | <|skeleton|>
class Trainer:
"""Trainer object for pano3d."""
def eval_step(self, data):
"""performs a step in evaluation :param data (dict): data dictionary :return:"""
<|body_0|>
def compute_loss(self, data):
"""compute the overall loss. :param data (dict): data dictionary :return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trainer:
"""Trainer object for pano3d."""
def eval_step(self, data):
"""performs a step in evaluation :param data (dict): data dictionary :return:"""
loss = self.compute_loss(data)
loss['total'] = loss['total'].item()
return loss
def compute_loss(self, data):
... | the_stack_v2_python_sparse | models/pano3d/training.py | TrendingTechnology/DeepPanoContext | train | 0 |
a639412340c7c976da22e0ae2f1cb875ddf94df8 | [
"r = Round.query.get(round_id)\nif r is not None:\n return r.reports_data()\nabort(404, 'Unknown round_id')",
"r = Round.query.get(round_id)\nif r is not None:\n r.heat_list_published = not r.heat_list_published\n db.session.commit()\n return OK\nabort(404, 'Unknown round_id')",
"r = Round.query.get... | <|body_start_0|>
r = Round.query.get(round_id)
if r is not None:
return r.reports_data()
abort(404, 'Unknown round_id')
<|end_body_0|>
<|body_start_1|>
r = Round.query.get(round_id)
if r is not None:
r.heat_list_published = not r.heat_list_published
... | RoundAPIReports | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoundAPIReports:
def get(self, round_id):
"""Get reports data"""
<|body_0|>
def patch(self, round_id):
"""Publishes or hides the heat list"""
<|body_1|>
def post(self, round_id):
"""Returns data to print reports"""
<|body_2|>
<|end_skele... | stack_v2_sparse_classes_36k_train_000511 | 25,303 | no_license | [
{
"docstring": "Get reports data",
"name": "get",
"signature": "def get(self, round_id)"
},
{
"docstring": "Publishes or hides the heat list",
"name": "patch",
"signature": "def patch(self, round_id)"
},
{
"docstring": "Returns data to print reports",
"name": "post",
"sig... | 3 | null | Implement the Python class `RoundAPIReports` described below.
Class description:
Implement the RoundAPIReports class.
Method signatures and docstrings:
- def get(self, round_id): Get reports data
- def patch(self, round_id): Publishes or hides the heat list
- def post(self, round_id): Returns data to print reports | Implement the Python class `RoundAPIReports` described below.
Class description:
Implement the RoundAPIReports class.
Method signatures and docstrings:
- def get(self, round_id): Get reports data
- def patch(self, round_id): Publishes or hides the heat list
- def post(self, round_id): Returns data to print reports
<... | 079b109fd13683a31d1d632faa5ab72cf0e78ddf | <|skeleton|>
class RoundAPIReports:
def get(self, round_id):
"""Get reports data"""
<|body_0|>
def patch(self, round_id):
"""Publishes or hides the heat list"""
<|body_1|>
def post(self, round_id):
"""Returns data to print reports"""
<|body_2|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoundAPIReports:
def get(self, round_id):
"""Get reports data"""
r = Round.query.get(round_id)
if r is not None:
return r.reports_data()
abort(404, 'Unknown round_id')
def patch(self, round_id):
"""Publishes or hides the heat list"""
r = Round.q... | the_stack_v2_python_sparse | backend/apis/round/apis.py | AlenAlic/DANCE | train | 0 | |
ed407e708913b85db248b3493889e67babb38946 | [
"self.lsa_components = lsa_components\nself.tfidf_parameters = tfidf_parameters\nself._tfv = TfidfVectorizer(**self.tfidf_parameters)\nself._svd = TruncatedSVD(self.lsa_components)",
"X.fillna('NA', inplace=True)\ntfidf_output_csr = self._tfv.fit_transform(X, y)\nself._svd.fit(tfidf_output_csr)\nprint('LSA explai... | <|body_start_0|>
self.lsa_components = lsa_components
self.tfidf_parameters = tfidf_parameters
self._tfv = TfidfVectorizer(**self.tfidf_parameters)
self._svd = TruncatedSVD(self.lsa_components)
<|end_body_0|>
<|body_start_1|>
X.fillna('NA', inplace=True)
tfidf_output_csr... | This class defines a Scikit-Learn transformer that implements a Latent Semantic Analysis. | LSAVectorizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSAVectorizer:
"""This class defines a Scikit-Learn transformer that implements a Latent Semantic Analysis."""
def __init__(self, lsa_components, tfidf_parameters={'analyzer': 'word', 'ngram_range': (1, 1), 'min_df': 10}):
"""This is the class' constructor. Parameters ---------- lsa_... | stack_v2_sparse_classes_36k_train_000512 | 14,227 | no_license | [
{
"docstring": "This is the class' constructor. Parameters ---------- lsa_components : positive integer Number of components we want to keep. tfidf_parameters : dict (default = {\"analyzer\": \"word\", \"ngram_range\": (1, 1), \"min_df\": 10}) Dict containing parameters of TfidfVectorizer used in this class. Ea... | 3 | stack_v2_sparse_classes_30k_train_005892 | Implement the Python class `LSAVectorizer` described below.
Class description:
This class defines a Scikit-Learn transformer that implements a Latent Semantic Analysis.
Method signatures and docstrings:
- def __init__(self, lsa_components, tfidf_parameters={'analyzer': 'word', 'ngram_range': (1, 1), 'min_df': 10}): T... | Implement the Python class `LSAVectorizer` described below.
Class description:
This class defines a Scikit-Learn transformer that implements a Latent Semantic Analysis.
Method signatures and docstrings:
- def __init__(self, lsa_components, tfidf_parameters={'analyzer': 'word', 'ngram_range': (1, 1), 'min_df': 10}): T... | ba9a7a15a3ae8b65cb09044489ee1d907a702909 | <|skeleton|>
class LSAVectorizer:
"""This class defines a Scikit-Learn transformer that implements a Latent Semantic Analysis."""
def __init__(self, lsa_components, tfidf_parameters={'analyzer': 'word', 'ngram_range': (1, 1), 'min_df': 10}):
"""This is the class' constructor. Parameters ---------- lsa_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LSAVectorizer:
"""This class defines a Scikit-Learn transformer that implements a Latent Semantic Analysis."""
def __init__(self, lsa_components, tfidf_parameters={'analyzer': 'word', 'ngram_range': (1, 1), 'min_df': 10}):
"""This is the class' constructor. Parameters ---------- lsa_components : ... | the_stack_v2_python_sparse | python_code/M5_Forecasting_Accuracy/m5_forecasting_accuracy/preprocessing/text_encoders.py | ThomasSELECK/src | train | 0 |
07cc42e856cb84f94e6c47e852905cb2d90d0d75 | [
"class EntryCount:\n\n def __init__(self):\n self.value = 0\n\n def add_function(self, items):\n items = list(items)\n for _ in items:\n self.value += 1\n return items\n\n def remove_function(self, items):\n items = list(items)\n for _ in items:\n ... | <|body_start_0|>
class EntryCount:
def __init__(self):
self.value = 0
def add_function(self, items):
items = list(items)
for _ in items:
self.value += 1
return items
def remove_function(sel... | Hierarchical directory. An extension of python `dict` allowing N hierarchically-ordered key types to be used to organize and access a set of values. Contains enforcement hooks that call functions whenever items are added/overwritten/removed. | EnforcerHidirSpec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnforcerHidirSpec:
"""Hierarchical directory. An extension of python `dict` allowing N hierarchically-ordered key types to be used to organize and access a set of values. Contains enforcement hooks that call functions whenever items are added/overwritten/removed."""
def ENFORCER_HIDIR(Enforc... | stack_v2_sparse_classes_36k_train_000513 | 5,334 | no_license | [
{
"docstring": "Build a hierarchical directory. `add_function(added)` is a function that is called whenever a new (or replacement) key:value pair is added, and it should expect `added` to be a `iterable<tuple<key1, key2, ..., value>>` as an argument. The return of `add_function(added)` should be an `iterable<tu... | 6 | stack_v2_sparse_classes_30k_train_015464 | Implement the Python class `EnforcerHidirSpec` described below.
Class description:
Hierarchical directory. An extension of python `dict` allowing N hierarchically-ordered key types to be used to organize and access a set of values. Contains enforcement hooks that call functions whenever items are added/overwritten/rem... | Implement the Python class `EnforcerHidirSpec` described below.
Class description:
Hierarchical directory. An extension of python `dict` allowing N hierarchically-ordered key types to be used to organize and access a set of values. Contains enforcement hooks that call functions whenever items are added/overwritten/rem... | 47c1512bc2d593dd33ac55ec6137d035fff2e2a9 | <|skeleton|>
class EnforcerHidirSpec:
"""Hierarchical directory. An extension of python `dict` allowing N hierarchically-ordered key types to be used to organize and access a set of values. Contains enforcement hooks that call functions whenever items are added/overwritten/removed."""
def ENFORCER_HIDIR(Enforc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnforcerHidirSpec:
"""Hierarchical directory. An extension of python `dict` allowing N hierarchically-ordered key types to be used to organize and access a set of values. Contains enforcement hooks that call functions whenever items are added/overwritten/removed."""
def ENFORCER_HIDIR(EnforcerHidir, dict... | the_stack_v2_python_sparse | structpy/collection/enforcer/enforcer_hidir_spec.py | jdfinch/structpy | train | 0 |
40a96bfe0a1328d123da5121b4fac09389faa053 | [
"self._client_creator = client_creator\nself._sso_region = sso_region\nself._role_name = role_name\nself._account_id = account_id\nself._start_url = start_url\nself._token_loader = token_loader\nsuper().__init__(cache, expiry_window_seconds)",
"args = {'startUrl': self._start_url, 'roleName': self._role_name, 'ac... | <|body_start_0|>
self._client_creator = client_creator
self._sso_region = sso_region
self._role_name = role_name
self._account_id = account_id
self._start_url = start_url
self._token_loader = token_loader
super().__init__(cache, expiry_window_seconds)
<|end_body_0... | AWS SSO credential fetcher. | SSOCredentialFetcher | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSOCredentialFetcher:
"""AWS SSO credential fetcher."""
def __init__(self, start_url, sso_region, role_name, account_id, client_creator, token_loader=None, cache=None, expiry_window_seconds=None):
"""Instantiate class."""
<|body_0|>
def _create_cache_key(self):
"... | stack_v2_sparse_classes_36k_train_000514 | 11,021 | permissive | [
{
"docstring": "Instantiate class.",
"name": "__init__",
"signature": "def __init__(self, start_url, sso_region, role_name, account_id, client_creator, token_loader=None, cache=None, expiry_window_seconds=None)"
},
{
"docstring": "Create a predictable cache key for the current configuration. The... | 4 | stack_v2_sparse_classes_30k_train_012195 | Implement the Python class `SSOCredentialFetcher` described below.
Class description:
AWS SSO credential fetcher.
Method signatures and docstrings:
- def __init__(self, start_url, sso_region, role_name, account_id, client_creator, token_loader=None, cache=None, expiry_window_seconds=None): Instantiate class.
- def _c... | Implement the Python class `SSOCredentialFetcher` described below.
Class description:
AWS SSO credential fetcher.
Method signatures and docstrings:
- def __init__(self, start_url, sso_region, role_name, account_id, client_creator, token_loader=None, cache=None, expiry_window_seconds=None): Instantiate class.
- def _c... | 0763b06aee07d2cf3f037a49ca0cb81a048c5deb | <|skeleton|>
class SSOCredentialFetcher:
"""AWS SSO credential fetcher."""
def __init__(self, start_url, sso_region, role_name, account_id, client_creator, token_loader=None, cache=None, expiry_window_seconds=None):
"""Instantiate class."""
<|body_0|>
def _create_cache_key(self):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SSOCredentialFetcher:
"""AWS SSO credential fetcher."""
def __init__(self, start_url, sso_region, role_name, account_id, client_creator, token_loader=None, cache=None, expiry_window_seconds=None):
"""Instantiate class."""
self._client_creator = client_creator
self._sso_region = ss... | the_stack_v2_python_sparse | runway/aws_sso_botocore/credentials.py | onicagroup/runway | train | 156 |
5d24e7300c299defa3e0714caaca629c734027bc | [
"ret, queue = ([], [root])\nfor node in queue:\n if node is None:\n ret.append('null')\n else:\n ret.append(str(node.val))\n queue += [node.left, node.right]\nreturn ','.join(ret)",
"vals = data.split(',')\nif len(vals) == 0 or vals[0] == 'null':\n return None\ndummy = root = TreeNod... | <|body_start_0|>
ret, queue = ([], [root])
for node in queue:
if node is None:
ret.append('null')
else:
ret.append(str(node.val))
queue += [node.left, node.right]
return ','.join(ret)
<|end_body_0|>
<|body_start_1|>
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_000515 | 1,378 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_019944 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 1a0dbcabb0f454a4fdcc31af9b919f5d30664335 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
ret, queue = ([], [root])
for node in queue:
if node is None:
ret.append('null')
else:
ret.append(str(node.val))
... | the_stack_v2_python_sparse | 297. Serialize and Deserialize Binary Tree.py | haomingchan0811/Leetcode | train | 0 | |
65363130424ad565487f772538a11a377156418c | [
"self.head = MyLinkedListNode()\nself.tail = MyLinkedListNode()\nself.head.next = self.tail\nself.tail.prev = self.head\nself.size = 0",
"def getFromHead(m):\n p = self.head\n while m > 0:\n m -= 1\n p = p.next\n return p.next.val\n\ndef getFromTail(m):\n p = self.tail\n while m > 0:\... | <|body_start_0|>
self.head = MyLinkedListNode()
self.tail = MyLinkedListNode()
self.head.next = self.tail
self.tail.prev = self.head
self.size = 0
<|end_body_0|>
<|body_start_1|>
def getFromHead(m):
p = self.head
while m > 0:
m -= ... | MyLinkedList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here. Running Time: O(1)"""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1. Running Time: O(size of list)"""... | stack_v2_sparse_classes_36k_train_000516 | 3,989 | permissive | [
{
"docstring": "Initialize your data structure here. Running Time: O(1)",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get the value of the index-th node in the linked list. If the index is invalid, return -1. Running Time: O(size of list)",
"name": "get",
"si... | 6 | stack_v2_sparse_classes_30k_train_012347 | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here. Running Time: O(1)
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If ... | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here. Running Time: O(1)
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If ... | 4a508a982b125a3a90ea893ae70863df7c99cc70 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here. Running Time: O(1)"""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -1. Running Time: O(size of list)"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyLinkedList:
def __init__(self):
"""Initialize your data structure here. Running Time: O(1)"""
self.head = MyLinkedListNode()
self.tail = MyLinkedListNode()
self.head.next = self.tail
self.tail.prev = self.head
self.size = 0
def get(self, index: int) -> in... | the_stack_v2_python_sparse | solutions/707_design_linked_list.py | YiqunPeng/leetcode_pro | train | 0 | |
4fd718677ac2b8cab8337a38a0288803db112ef7 | [
"self.name: str = name\nif isinstance(yaml, dict):\n path = yaml.get('path', None)\n self.path: Optional[Path] = None if path is None else Path(path)\n self.groups: Optional[List[str]] = yaml.get('groups', None)\n defaults = yaml.get('defaults', None)\n self.defaults: Optional[Defaults] = None if def... | <|body_start_0|>
self.name: str = name
if isinstance(yaml, dict):
path = yaml.get('path', None)
self.path: Optional[Path] = None if path is None else Path(path)
self.groups: Optional[List[str]] = yaml.get('groups', None)
defaults = yaml.get('defaults', Non... | clowder yaml Section model class :ivar str name: Section name :ivar Optional[Path] path: Section path prefix :ivar Optional[List[str]] groups: Group names :ivar Optional[Defaults] defaults: Group defaults :ivar List[Project] projects: Group projects :ivar bool _has_projects_key: Whether the projects were listed under t... | Section | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Section:
"""clowder yaml Section model class :ivar str name: Section name :ivar Optional[Path] path: Section path prefix :ivar Optional[List[str]] groups: Group names :ivar Optional[Defaults] defaults: Group defaults :ivar List[Project] projects: Group projects :ivar bool _has_projects_key: Wheth... | stack_v2_sparse_classes_36k_train_000517 | 2,522 | permissive | [
{
"docstring": "Group __init__ :param str name: Section name :param Union[dict, List[Project]] yaml: Parsed YAML python object for group :raise UnknownTypeError:",
"name": "__init__",
"signature": "def __init__(self, name: str, yaml: Union[dict, List[Project]])"
},
{
"docstring": "Return python ... | 2 | stack_v2_sparse_classes_30k_train_002449 | Implement the Python class `Section` described below.
Class description:
clowder yaml Section model class :ivar str name: Section name :ivar Optional[Path] path: Section path prefix :ivar Optional[List[str]] groups: Group names :ivar Optional[Defaults] defaults: Group defaults :ivar List[Project] projects: Group proje... | Implement the Python class `Section` described below.
Class description:
clowder yaml Section model class :ivar str name: Section name :ivar Optional[Path] path: Section path prefix :ivar Optional[List[str]] groups: Group names :ivar Optional[Defaults] defaults: Group defaults :ivar List[Project] projects: Group proje... | 1438fc8b1bb7379de66142ffcb0e20b459b59159 | <|skeleton|>
class Section:
"""clowder yaml Section model class :ivar str name: Section name :ivar Optional[Path] path: Section path prefix :ivar Optional[List[str]] groups: Group names :ivar Optional[Defaults] defaults: Group defaults :ivar List[Project] projects: Group projects :ivar bool _has_projects_key: Wheth... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Section:
"""clowder yaml Section model class :ivar str name: Section name :ivar Optional[Path] path: Section path prefix :ivar Optional[List[str]] groups: Group names :ivar Optional[Defaults] defaults: Group defaults :ivar List[Project] projects: Group projects :ivar bool _has_projects_key: Whether the projec... | the_stack_v2_python_sparse | clowder/model/section.py | JrGoodle/clowder | train | 17 |
fc0a960b86f0d98bf58a4f1720137d78acd42a85 | [
"self.end_time_usecs = end_time_usecs\nself.error = error\nself.indexing_task_end_time_usecs = indexing_task_end_time_usecs\nself.indexing_task_start_time_usecs = indexing_task_start_time_usecs\nself.indexing_task_status = indexing_task_status\nself.indexing_task_uid = indexing_task_uid\nself.latest_expiry_time_use... | <|body_start_0|>
self.end_time_usecs = end_time_usecs
self.error = error
self.indexing_task_end_time_usecs = indexing_task_end_time_usecs
self.indexing_task_start_time_usecs = indexing_task_start_time_usecs
self.indexing_task_status = indexing_task_status
self.indexing_ta... | Implementation of the 'RemoteRestoreIndexingStatus' model. Specifies the status of an indexing task. Attributes: end_time_usecs (long|int): Specifies the end time of the time range that is being indexed. The indexing task is creating an index of the Job Runs that occurred between the startTimeUsecs and this endTimeUsec... | RemoteRestoreIndexingStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteRestoreIndexingStatus:
"""Implementation of the 'RemoteRestoreIndexingStatus' model. Specifies the status of an indexing task. Attributes: end_time_usecs (long|int): Specifies the end time of the time range that is being indexed. The indexing task is creating an index of the Job Runs that o... | stack_v2_sparse_classes_36k_train_000518 | 5,666 | permissive | [
{
"docstring": "Constructor for the RemoteRestoreIndexingStatus class",
"name": "__init__",
"signature": "def __init__(self, end_time_usecs=None, error=None, indexing_task_end_time_usecs=None, indexing_task_start_time_usecs=None, indexing_task_status=None, indexing_task_uid=None, latest_expiry_time_usec... | 2 | stack_v2_sparse_classes_30k_train_014543 | Implement the Python class `RemoteRestoreIndexingStatus` described below.
Class description:
Implementation of the 'RemoteRestoreIndexingStatus' model. Specifies the status of an indexing task. Attributes: end_time_usecs (long|int): Specifies the end time of the time range that is being indexed. The indexing task is c... | Implement the Python class `RemoteRestoreIndexingStatus` described below.
Class description:
Implementation of the 'RemoteRestoreIndexingStatus' model. Specifies the status of an indexing task. Attributes: end_time_usecs (long|int): Specifies the end time of the time range that is being indexed. The indexing task is c... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RemoteRestoreIndexingStatus:
"""Implementation of the 'RemoteRestoreIndexingStatus' model. Specifies the status of an indexing task. Attributes: end_time_usecs (long|int): Specifies the end time of the time range that is being indexed. The indexing task is creating an index of the Job Runs that o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RemoteRestoreIndexingStatus:
"""Implementation of the 'RemoteRestoreIndexingStatus' model. Specifies the status of an indexing task. Attributes: end_time_usecs (long|int): Specifies the end time of the time range that is being indexed. The indexing task is creating an index of the Job Runs that occurred betwe... | the_stack_v2_python_sparse | cohesity_management_sdk/models/remote_restore_indexing_status.py | cohesity/management-sdk-python | train | 24 |
4eeb5f3a039348c101787a022a52a2da53770be0 | [
"super(AuViSubNet, self).__init__()\nself.rnn = nn.LSTM(in_size, hidden_size, num_layers=num_layers, dropout=dropout, bidirectional=bidirectional, batch_first=True)\nself.dropout = nn.Dropout(dropout)\nself.linear_1 = nn.Linear(hidden_size, out_size)",
"_, final_states = self.rnn(x)\nh = self.dropout(final_states... | <|body_start_0|>
super(AuViSubNet, self).__init__()
self.rnn = nn.LSTM(in_size, hidden_size, num_layers=num_layers, dropout=dropout, bidirectional=bidirectional, batch_first=True)
self.dropout = nn.Dropout(dropout)
self.linear_1 = nn.Linear(hidden_size, out_size)
<|end_body_0|>
<|body_s... | AuViSubNet | [
"GPL-1.0-or-later",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuViSubNet:
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usa... | stack_v2_sparse_classes_36k_train_000519 | 7,016 | permissive | [
{
"docstring": "Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usage of bidirectional LSTM Output: (return value in forward) a tensor of shape (batch_size, out_size)",
"name": "__init__... | 2 | null | Implement the Python class `AuViSubNet` described below.
Class description:
Implement the AuViSubNet class.
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False): Args: in_size: input dimension hidden_size: hidden layer dimension num_lay... | Implement the Python class `AuViSubNet` described below.
Class description:
Implement the AuViSubNet class.
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False): Args: in_size: input dimension hidden_size: hidden layer dimension num_lay... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class AuViSubNet:
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuViSubNet:
def __init__(self, in_size, hidden_size, out_size, num_layers=1, dropout=0.2, bidirectional=False):
"""Args: in_size: input dimension hidden_size: hidden layer dimension num_layers: specify the number of layers of LSTMs. dropout: dropout probability bidirectional: specify usage of bidirect... | the_stack_v2_python_sparse | PyTorch/contrib/others/MMSA_ID2979_for_PyTorch/models/multiTask/SELF_MM.py | Ascend/ModelZoo-PyTorch | train | 23 | |
f20f0af2f9ca6055ceea9018f6b906a10c7a6fb9 | [
"self.sign_request = sign_request\nself.reminder = reminder\nself.signature_receipt = signature_receipt\nself.final_receipt = final_receipt\nself.canceled_receipt = canceled_receipt\nself.expired_receipt = expired_receipt\nself.additional_properties = additional_properties",
"if dictionary is None:\n return No... | <|body_start_0|>
self.sign_request = sign_request
self.reminder = reminder
self.signature_receipt = signature_receipt
self.final_receipt = final_receipt
self.canceled_receipt = canceled_receipt
self.expired_receipt = expired_receipt
self.additional_properties = ad... | Implementation of the 'Notification' model. Setup your own notification texts, and specify specail settings. Info: you also has to setup notifications on the signers you want to notify. Attributes: sign_request (SignatureSignRequest): Here you can setup email/sms notifications notifying the signer that they have a new ... | Notification | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Notification:
"""Implementation of the 'Notification' model. Setup your own notification texts, and specify specail settings. Info: you also has to setup notifications on the signers you want to notify. Attributes: sign_request (SignatureSignRequest): Here you can setup email/sms notifications no... | stack_v2_sparse_classes_36k_train_000520 | 5,007 | permissive | [
{
"docstring": "Constructor for the Notification class",
"name": "__init__",
"signature": "def __init__(self, sign_request=None, reminder=None, signature_receipt=None, final_receipt=None, canceled_receipt=None, expired_receipt=None, additional_properties={})"
},
{
"docstring": "Creates an instan... | 2 | null | Implement the Python class `Notification` described below.
Class description:
Implementation of the 'Notification' model. Setup your own notification texts, and specify specail settings. Info: you also has to setup notifications on the signers you want to notify. Attributes: sign_request (SignatureSignRequest): Here y... | Implement the Python class `Notification` described below.
Class description:
Implementation of the 'Notification' model. Setup your own notification texts, and specify specail settings. Info: you also has to setup notifications on the signers you want to notify. Attributes: sign_request (SignatureSignRequest): Here y... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class Notification:
"""Implementation of the 'Notification' model. Setup your own notification texts, and specify specail settings. Info: you also has to setup notifications on the signers you want to notify. Attributes: sign_request (SignatureSignRequest): Here you can setup email/sms notifications no... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Notification:
"""Implementation of the 'Notification' model. Setup your own notification texts, and specify specail settings. Info: you also has to setup notifications on the signers you want to notify. Attributes: sign_request (SignatureSignRequest): Here you can setup email/sms notifications notifying the s... | the_stack_v2_python_sparse | idfy_rest_client/models/notification.py | dealflowteam/Idfy | train | 0 |
dc9944f1b1b3472fa50b0dc82455fb8e8d0c7f07 | [
"self.small = []\nself.large = []\nself.size = 0",
"heappush(self.small, -1 * heappushpop(self.large, num))\nself.size += 1\nwhile len(self.large) < len(self.small):\n heappush(self.large, -1 * heappop(self.small))",
"if self.size % 2:\n return float(self.large[0])\nelse:\n return float(self.large[0] +... | <|body_start_0|>
self.small = []
self.large = []
self.size = 0
<|end_body_0|>
<|body_start_1|>
heappush(self.small, -1 * heappushpop(self.large, num))
self.size += 1
while len(self.large) < len(self.small):
heappush(self.large, -1 * heappop(self.small))
<|end... | MedianFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def addNum(self, num):
"""Adds a num into the data structure. :type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
"""Returns the median of current... | stack_v2_sparse_classes_36k_train_000521 | 1,833 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Adds a num into the data structure. :type num: int :rtype: void",
"name": "addNum",
"signature": "def addNum(self, num)"
},
{
"docstring": "Returns the ... | 3 | stack_v2_sparse_classes_30k_train_008004 | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def addNum(self, num): Adds a num into the data structure. :type num: int :rtype: void
- def findMedian(self): ... | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def addNum(self, num): Adds a num into the data structure. :type num: int :rtype: void
- def findMedian(self): ... | b4da922c4e8406c486760639b71e3ec50283ca43 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def addNum(self, num):
"""Adds a num into the data structure. :type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
"""Returns the median of current... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedianFinder:
def __init__(self):
"""Initialize your data structure here."""
self.small = []
self.large = []
self.size = 0
def addNum(self, num):
"""Adds a num into the data structure. :type num: int :rtype: void"""
heappush(self.small, -1 * heappushpop(sel... | the_stack_v2_python_sparse | old_session/session_1/_295/_295_find_median_from_data_stream.py | YJL33/LeetCode | train | 3 | |
02235ddd5cedb1ef5fdb9338c3e95e5f26785162 | [
"self.buffer_capacity = max_size\nself.num_states = num_states\nself.num_actions = num_actions\nself.clear()",
"index = self.size % self.buffer_capacity\nself.state_buffer[index] = obs_tuple[0]\nself.action_buffer[index] = obs_tuple[1]\nself.next_state_buffer[index] = obs_tuple[2]\nself.reward_buffer[index] = obs... | <|body_start_0|>
self.buffer_capacity = max_size
self.num_states = num_states
self.num_actions = num_actions
self.clear()
<|end_body_0|>
<|body_start_1|>
index = self.size % self.buffer_capacity
self.state_buffer[index] = obs_tuple[0]
self.action_buffer[index] = ... | Replay buffer class to store experiences for a reinforcement learning agent. | ReplayBuffer | [
"MIT",
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReplayBuffer:
"""Replay buffer class to store experiences for a reinforcement learning agent."""
def __init__(self, max_size, num_states, num_actions):
"""Replay buffer class to store experiences for a reinforcement learning agent. Parameters ---------- max_size: int maximum number o... | stack_v2_sparse_classes_36k_train_000522 | 3,252 | permissive | [
{
"docstring": "Replay buffer class to store experiences for a reinforcement learning agent. Parameters ---------- max_size: int maximum number of experiences to store in the repleay buffer. When adding experiences beyond this limit, the first entry is deleted. num_state: int the dimension of the state space nu... | 4 | stack_v2_sparse_classes_30k_train_014608 | Implement the Python class `ReplayBuffer` described below.
Class description:
Replay buffer class to store experiences for a reinforcement learning agent.
Method signatures and docstrings:
- def __init__(self, max_size, num_states, num_actions): Replay buffer class to store experiences for a reinforcement learning ag... | Implement the Python class `ReplayBuffer` described below.
Class description:
Replay buffer class to store experiences for a reinforcement learning agent.
Method signatures and docstrings:
- def __init__(self, max_size, num_states, num_actions): Replay buffer class to store experiences for a reinforcement learning ag... | 2dab162a3a7bd33632fd36924b2bfb289249ffa3 | <|skeleton|>
class ReplayBuffer:
"""Replay buffer class to store experiences for a reinforcement learning agent."""
def __init__(self, max_size, num_states, num_actions):
"""Replay buffer class to store experiences for a reinforcement learning agent. Parameters ---------- max_size: int maximum number o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReplayBuffer:
"""Replay buffer class to store experiences for a reinforcement learning agent."""
def __init__(self, max_size, num_states, num_actions):
"""Replay buffer class to store experiences for a reinforcement learning agent. Parameters ---------- max_size: int maximum number of experiences... | the_stack_v2_python_sparse | software/python/simple_pendulum/reinforcement_learning/ddpg/replay_buffer.py | dfki-ric-underactuated-lab/torque_limited_simple_pendulum | train | 37 |
db7182ba59e04cfd998c29f48c614622a6c75a89 | [
"auth_string = self.get_auth_string(url)\nif not auth_string:\n return {}\nb64_auth = base64.b64encode(auth_string.encode('utf-8')).decode('utf-8')\nreturn {'Authorization': 'Basic %s' % b64_auth}",
"username, password = self.get_username_password(url)\nif username and password:\n return '%s:%s' % (username... | <|body_start_0|>
auth_string = self.get_auth_string(url)
if not auth_string:
return {}
b64_auth = base64.b64encode(auth_string.encode('utf-8')).decode('utf-8')
return {'Authorization': 'Basic %s' % b64_auth}
<|end_body_0|>
<|body_start_1|>
username, password = self.g... | A base for downloaders to add an HTTP basic auth header | BasicAuthDownloader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicAuthDownloader:
"""A base for downloaders to add an HTTP basic auth header"""
def build_auth_header(self, url):
"""Constructs an HTTP basic auth header for a URL, if present in settings :param url: A unicode string of the URL being downloaded :return: A dict with an HTTP header ... | stack_v2_sparse_classes_36k_train_000523 | 2,100 | permissive | [
{
"docstring": "Constructs an HTTP basic auth header for a URL, if present in settings :param url: A unicode string of the URL being downloaded :return: A dict with an HTTP header name as the key and the value as the value. Both are unicode strings.",
"name": "build_auth_header",
"signature": "def build... | 3 | stack_v2_sparse_classes_30k_train_005319 | Implement the Python class `BasicAuthDownloader` described below.
Class description:
A base for downloaders to add an HTTP basic auth header
Method signatures and docstrings:
- def build_auth_header(self, url): Constructs an HTTP basic auth header for a URL, if present in settings :param url: A unicode string of the ... | Implement the Python class `BasicAuthDownloader` described below.
Class description:
A base for downloaders to add an HTTP basic auth header
Method signatures and docstrings:
- def build_auth_header(self, url): Constructs an HTTP basic auth header for a URL, if present in settings :param url: A unicode string of the ... | 9f5eb7e3392e6bc2ad979ad32d3dd27ef9c00b20 | <|skeleton|>
class BasicAuthDownloader:
"""A base for downloaders to add an HTTP basic auth header"""
def build_auth_header(self, url):
"""Constructs an HTTP basic auth header for a URL, if present in settings :param url: A unicode string of the URL being downloaded :return: A dict with an HTTP header ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicAuthDownloader:
"""A base for downloaders to add an HTTP basic auth header"""
def build_auth_header(self, url):
"""Constructs an HTTP basic auth header for a URL, if present in settings :param url: A unicode string of the URL being downloaded :return: A dict with an HTTP header name as the k... | the_stack_v2_python_sparse | app/lib/package_control/downloaders/basic_auth_downloader.py | june07/packagecontrol.io | train | 1 |
b3b36ac73791afcdd0a65a650e929c9fad049b48 | [
"tz_info = timezone.get_default_timezone()\narr_date_from = datetime.strptime(str_date, '%Y-%m-%d').replace(tzinfo=tz_info)\narr_date_to = arr_date_from + timedelta(days=settings.BOOKING_DATE_RANGE_GAP)\nqueryset['departure_date__gte'] = arr_date_from\nqueryset['departure_date__lte'] = arr_date_to",
"queryset = {... | <|body_start_0|>
tz_info = timezone.get_default_timezone()
arr_date_from = datetime.strptime(str_date, '%Y-%m-%d').replace(tzinfo=tz_info)
arr_date_to = arr_date_from + timedelta(days=settings.BOOKING_DATE_RANGE_GAP)
queryset['departure_date__gte'] = arr_date_from
queryset['depar... | Booking ship select form - filter queryset based on data from directions and dates which user provided - check if schedules vessel can carry cargo or passenger | BookingShipSelectForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookingShipSelectForm:
"""Booking ship select form - filter queryset based on data from directions and dates which user provided - check if schedules vessel can carry cargo or passenger"""
def get_departure_date_query(self, queryset, str_date):
"""Departure date filter - timezne awar... | stack_v2_sparse_classes_36k_train_000524 | 13,644 | no_license | [
{
"docstring": "Departure date filter - timezne aware datetime object - time gap which defined beforehand in settings",
"name": "get_departure_date_query",
"signature": "def get_departure_date_query(self, queryset, str_date)"
},
{
"docstring": "Dynamically create queryset for schedule field",
... | 2 | stack_v2_sparse_classes_30k_train_003082 | Implement the Python class `BookingShipSelectForm` described below.
Class description:
Booking ship select form - filter queryset based on data from directions and dates which user provided - check if schedules vessel can carry cargo or passenger
Method signatures and docstrings:
- def get_departure_date_query(self, ... | Implement the Python class `BookingShipSelectForm` described below.
Class description:
Booking ship select form - filter queryset based on data from directions and dates which user provided - check if schedules vessel can carry cargo or passenger
Method signatures and docstrings:
- def get_departure_date_query(self, ... | e01ac10772f484e83209c47484a2af2ad595e7f1 | <|skeleton|>
class BookingShipSelectForm:
"""Booking ship select form - filter queryset based on data from directions and dates which user provided - check if schedules vessel can carry cargo or passenger"""
def get_departure_date_query(self, queryset, str_date):
"""Departure date filter - timezne awar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BookingShipSelectForm:
"""Booking ship select form - filter queryset based on data from directions and dates which user provided - check if schedules vessel can carry cargo or passenger"""
def get_departure_date_query(self, queryset, str_date):
"""Departure date filter - timezne aware datetime ob... | the_stack_v2_python_sparse | port_app/booking/forms.py | vugarrahim/vugarrahim.github.io | train | 0 |
0eeaeedb2129fc779778f6a1118801a8342b47ac | [
"n = len(nums)\nl = r = 1\noutput = [1] * n\nfor i in range(n):\n output[i] *= l\n l *= nums[i]\nfor i in range(n - 1, -1, -1):\n output[i] *= r\n r *= nums[i]\nreturn output",
"result = [1] * len(nums)\nfor i, n in enumerate(nums):\n for j in range(len(result)):\n if i != j:\n re... | <|body_start_0|>
n = len(nums)
l = r = 1
output = [1] * n
for i in range(n):
output[i] *= l
l *= nums[i]
for i in range(n - 1, -1, -1):
output[i] *= r
r *= nums[i]
return output
<|end_body_0|>
<|body_start_1|>
resul... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
"""This is so cool. :type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelfSlow(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_000525 | 909 | no_license | [
{
"docstring": "This is so cool. :type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelfSlow",
"signature": "def productExceptSelfSlow(s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): This is so cool. :type nums: List[int] :rtype: List[int]
- def productExceptSelfSlow(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): This is so cool. :type nums: List[int] :rtype: List[int]
- def productExceptSelfSlow(self, nums): :type nums: List[int] :rtype: List[int]
<|sk... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
"""This is so cool. :type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelfSlow(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelf(self, nums):
"""This is so cool. :type nums: List[int] :rtype: List[int]"""
n = len(nums)
l = r = 1
output = [1] * n
for i in range(n):
output[i] *= l
l *= nums[i]
for i in range(n - 1, -1, -1):
... | the_stack_v2_python_sparse | random/product_of_array_except_self.py | hwc1824/LeetCodeSolution | train | 0 | |
4d3407e399f277451b0f08880eb9c75e5689f085 | [
"super(TrainableInitialState, self).__init__(name=name)\nwarnings.simplefilter('always', DeprecationWarning)\nwarnings.warn('Use the trainable flag in initial_state instead.', DeprecationWarning, stacklevel=2)\nif mask is not None:\n flat_mask = nest.flatten(mask)\n if not all([isinstance(m, bool) for m in fl... | <|body_start_0|>
super(TrainableInitialState, self).__init__(name=name)
warnings.simplefilter('always', DeprecationWarning)
warnings.warn('Use the trainable flag in initial_state instead.', DeprecationWarning, stacklevel=2)
if mask is not None:
flat_mask = nest.flatten(mask)
... | Helper Module that creates a learnable initial state for an RNNCore. This class receives an example (possibly nested) initial state of an RNNCore, and returns a state that has the same shape, structure, and values, but is trainable. Additionally, the user may specify a boolean mask that indicates which parts of the ini... | TrainableInitialState | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainableInitialState:
"""Helper Module that creates a learnable initial state for an RNNCore. This class receives an example (possibly nested) initial state of an RNNCore, and returns a state that has the same shape, structure, and values, but is trainable. Additionally, the user may specify a b... | stack_v2_sparse_classes_36k_train_000526 | 14,770 | permissive | [
{
"docstring": "Constructs the Module that introduces a trainable state in the graph. It receives an initial state that will be used as the initial values for the trainable variables that the module contains, and optionally a mask that indicates the parts of the initial state that should be learnable. Args: ini... | 2 | stack_v2_sparse_classes_30k_train_004122 | Implement the Python class `TrainableInitialState` described below.
Class description:
Helper Module that creates a learnable initial state for an RNNCore. This class receives an example (possibly nested) initial state of an RNNCore, and returns a state that has the same shape, structure, and values, but is trainable.... | Implement the Python class `TrainableInitialState` described below.
Class description:
Helper Module that creates a learnable initial state for an RNNCore. This class receives an example (possibly nested) initial state of an RNNCore, and returns a state that has the same shape, structure, and values, but is trainable.... | 4e28fdf2ffd0eaefc0d23049106609421c9290b0 | <|skeleton|>
class TrainableInitialState:
"""Helper Module that creates a learnable initial state for an RNNCore. This class receives an example (possibly nested) initial state of an RNNCore, and returns a state that has the same shape, structure, and values, but is trainable. Additionally, the user may specify a b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainableInitialState:
"""Helper Module that creates a learnable initial state for an RNNCore. This class receives an example (possibly nested) initial state of an RNNCore, and returns a state that has the same shape, structure, and values, but is trainable. Additionally, the user may specify a boolean mask t... | the_stack_v2_python_sparse | sunset/sunset/python/modules/rnn_core.py | SynthAI/SynthAI | train | 3 |
8850ed7fa96daf7095108fc25b586e7021bb3b2f | [
"if not nums:\n return\nsize = len(nums)\nk = k % size\nif not k:\n return\nremain = size - k\nfor i in range(remain // 2):\n nums[i], nums[remain - 1 - i] = (nums[remain - 1 - i], nums[i])\nfor i in range(k // 2):\n nums[i + remain], nums[size - 1 - i] = (nums[size - 1 - i], nums[i + remain])\nfor i in... | <|body_start_0|>
if not nums:
return
size = len(nums)
k = k % size
if not k:
return
remain = size - k
for i in range(remain // 2):
nums[i], nums[remain - 1 - i] = (nums[remain - 1 - i], nums[i])
for i in range(k // 2):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate1(self, nums: List[int], k: int) -> None:
"""Reverse solution. Reverse the first n-k and remaining k elements separately, then reverse the whole array. Time: O(n) Space: O(1)"""
<|body_0|>
def rotate2(self, nums: List[int], k: int) -> None:
"""Cac... | stack_v2_sparse_classes_36k_train_000527 | 1,450 | no_license | [
{
"docstring": "Reverse solution. Reverse the first n-k and remaining k elements separately, then reverse the whole array. Time: O(n) Space: O(1)",
"name": "rotate1",
"signature": "def rotate1(self, nums: List[int], k: int) -> None"
},
{
"docstring": "Cache the first size - k numbers and replace... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate1(self, nums: List[int], k: int) -> None: Reverse solution. Reverse the first n-k and remaining k elements separately, then reverse the whole array. Time: O(n) Space: O... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate1(self, nums: List[int], k: int) -> None: Reverse solution. Reverse the first n-k and remaining k elements separately, then reverse the whole array. Time: O(n) Space: O... | c14d8829c95f61ff6691816e8c0de76b9319f389 | <|skeleton|>
class Solution:
def rotate1(self, nums: List[int], k: int) -> None:
"""Reverse solution. Reverse the first n-k and remaining k elements separately, then reverse the whole array. Time: O(n) Space: O(1)"""
<|body_0|>
def rotate2(self, nums: List[int], k: int) -> None:
"""Cac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate1(self, nums: List[int], k: int) -> None:
"""Reverse solution. Reverse the first n-k and remaining k elements separately, then reverse the whole array. Time: O(n) Space: O(1)"""
if not nums:
return
size = len(nums)
k = k % size
if not k:
... | the_stack_v2_python_sparse | easy/rotate-array/solution.py | hsuanhauliu/leetcode-solutions | train | 0 | |
46ff90bfd962e82e37c05f3d42574d4675c1dde3 | [
"cnst = mdl_const()\nret_list = []\nret_srate = 0\nfiletype_arg = [('CSV/MAT (*.csv, *.mat)', '*.csv *.mat')]\nf_name = filedialog.askopenfilename(initialdir=cnst.fout_dflt_dir, title='Open data file: ', filetypes=filetype_arg)\ncsv_pat = re.compile('^(.)+(.csv)$')\nmat_pat = re.compile('^(.)+(.mat)$')\nif csv_pat.... | <|body_start_0|>
cnst = mdl_const()
ret_list = []
ret_srate = 0
filetype_arg = [('CSV/MAT (*.csv, *.mat)', '*.csv *.mat')]
f_name = filedialog.askopenfilename(initialdir=cnst.fout_dflt_dir, title='Open data file: ', filetypes=filetype_arg)
csv_pat = re.compile('^(.)+(.csv... | This class defines control logic for file output and input functions. of the front end. @author: sdmay18-31 | ctrl_fileio | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ctrl_fileio:
"""This class defines control logic for file output and input functions. of the front end. @author: sdmay18-31"""
def parse_data_file():
"""Generate a data list and sampling rate based on a opened MAT or CSV file. Prompts the user for a file to open. Args: None Returns: ... | stack_v2_sparse_classes_36k_train_000528 | 4,838 | no_license | [
{
"docstring": "Generate a data list and sampling rate based on a opened MAT or CSV file. Prompts the user for a file to open. Args: None Returns: data_list: List of data samples data_srate: Sampling rate of data file",
"name": "parse_data_file",
"signature": "def parse_data_file()"
},
{
"docstr... | 5 | stack_v2_sparse_classes_30k_train_000684 | Implement the Python class `ctrl_fileio` described below.
Class description:
This class defines control logic for file output and input functions. of the front end. @author: sdmay18-31
Method signatures and docstrings:
- def parse_data_file(): Generate a data list and sampling rate based on a opened MAT or CSV file. ... | Implement the Python class `ctrl_fileio` described below.
Class description:
This class defines control logic for file output and input functions. of the front end. @author: sdmay18-31
Method signatures and docstrings:
- def parse_data_file(): Generate a data list and sampling rate based on a opened MAT or CSV file. ... | 30ac8bb8ad1a6dbfa7c2181949f468213a6ae717 | <|skeleton|>
class ctrl_fileio:
"""This class defines control logic for file output and input functions. of the front end. @author: sdmay18-31"""
def parse_data_file():
"""Generate a data list and sampling rate based on a opened MAT or CSV file. Prompts the user for a file to open. Args: None Returns: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ctrl_fileio:
"""This class defines control logic for file output and input functions. of the front end. @author: sdmay18-31"""
def parse_data_file():
"""Generate a data list and sampling rate based on a opened MAT or CSV file. Prompts the user for a file to open. Args: None Returns: data_list: Li... | the_stack_v2_python_sparse | src/front_end/ctrl_fileio.py | tdemps/CyDAQ | train | 0 |
e2eb4a37cd3c8df8707e807565c967bec31a68db | [
"self.min_num = min_num\nself.max_num = max_num\nself.choice = choice\nself.target = random.randint(min_num, max_num)",
"choice = self.choice\nwhile choice > 0:\n try:\n num = int(input('请输入猜测数字：'))\n except ValueError as e:\n print('请输入有效数字')\n continue\n choice -= 1\n if self.ta... | <|body_start_0|>
self.min_num = min_num
self.max_num = max_num
self.choice = choice
self.target = random.randint(min_num, max_num)
<|end_body_0|>
<|body_start_1|>
choice = self.choice
while choice > 0:
try:
num = int(input('请输入猜测数字：'))
... | GuessNumGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GuessNumGame:
def __init__(self, min_num, max_num, choice):
""":param min_num: 最小值 :param max_num: 最大值 :param choice: 猜测次数"""
<|body_0|>
def guess(self):
"""猜字方法 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.min_num = min_num
... | stack_v2_sparse_classes_36k_train_000529 | 1,573 | no_license | [
{
"docstring": ":param min_num: 最小值 :param max_num: 最大值 :param choice: 猜测次数",
"name": "__init__",
"signature": "def __init__(self, min_num, max_num, choice)"
},
{
"docstring": "猜字方法 :return:",
"name": "guess",
"signature": "def guess(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019080 | Implement the Python class `GuessNumGame` described below.
Class description:
Implement the GuessNumGame class.
Method signatures and docstrings:
- def __init__(self, min_num, max_num, choice): :param min_num: 最小值 :param max_num: 最大值 :param choice: 猜测次数
- def guess(self): 猜字方法 :return: | Implement the Python class `GuessNumGame` described below.
Class description:
Implement the GuessNumGame class.
Method signatures and docstrings:
- def __init__(self, min_num, max_num, choice): :param min_num: 最小值 :param max_num: 最大值 :param choice: 猜测次数
- def guess(self): 猜字方法 :return:
<|skeleton|>
class GuessNumGam... | dbc54dd1017cdeacc79bc8d0856d17bb7033b11f | <|skeleton|>
class GuessNumGame:
def __init__(self, min_num, max_num, choice):
""":param min_num: 最小值 :param max_num: 最大值 :param choice: 猜测次数"""
<|body_0|>
def guess(self):
"""猜字方法 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GuessNumGame:
def __init__(self, min_num, max_num, choice):
""":param min_num: 最小值 :param max_num: 最大值 :param choice: 猜测次数"""
self.min_num = min_num
self.max_num = max_num
self.choice = choice
self.target = random.randint(min_num, max_num)
def guess(self):
... | the_stack_v2_python_sparse | code/exercises/guess_number_game.py | Glepooek/python-learning-notes | train | 2 | |
84ce86af7df9dbf15895ab7178cd2b9880c9f3bf | [
"if graph.is_directed():\n raise ValueError('the graph is directed')\nif not is_connected(graph):\n raise ValueError('the graph is not connected')\nself.graph = graph\nself.color = dict(((node, None) for node in self.graph.iternodes()))\nself._color_list = [False] * self.graph.v()",
"try:\n algorithm = B... | <|body_start_0|>
if graph.is_directed():
raise ValueError('the graph is directed')
if not is_connected(graph):
raise ValueError('the graph is not connected')
self.graph = graph
self.color = dict(((node, None) for node in self.graph.iternodes()))
self._colo... | Find sp-graph node coloring. | SPNodeColoring | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SPNodeColoring:
"""Find sp-graph node coloring."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self):
"""Executable pseudocode."""
<|body_1|>
def _greedy_color(self, source):
"""Give node the smallest pos... | stack_v2_sparse_classes_36k_train_000530 | 1,800 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Give node the smallest possible color.",
"name": "_greedy_co... | 3 | stack_v2_sparse_classes_30k_val_000504 | Implement the Python class `SPNodeColoring` described below.
Class description:
Find sp-graph node coloring.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self): Executable pseudocode.
- def _greedy_color(self, source): Give node the smallest possible color. | Implement the Python class `SPNodeColoring` described below.
Class description:
Find sp-graph node coloring.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self): Executable pseudocode.
- def _greedy_color(self, source): Give node the smallest possible color.
<... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class SPNodeColoring:
"""Find sp-graph node coloring."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self):
"""Executable pseudocode."""
<|body_1|>
def _greedy_color(self, source):
"""Give node the smallest pos... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SPNodeColoring:
"""Find sp-graph node coloring."""
def __init__(self, graph):
"""The algorithm initialization."""
if graph.is_directed():
raise ValueError('the graph is directed')
if not is_connected(graph):
raise ValueError('the graph is not connected')
... | the_stack_v2_python_sparse | graphtheory/seriesparallel/spnodecolor.py | kgashok/graphs-dict | train | 0 |
c1067a5fc296d1851e30c9e59564f53ebcfa0ac8 | [
"input_file = self.get_data(self.test_dir, 'jw00001001001_01101_00001_MIRIMAGE_jump.fits')\nresult = RampFitStep.call(input_file, save_opt=True, opt_name='rampfit1_opt_out.fits')\noutput_file = result[0].save(path=result[0].meta.filename.replace('jump', 'rampfit'))\nint_output = result[1].save(path=result[1].meta.f... | <|body_start_0|>
input_file = self.get_data(self.test_dir, 'jw00001001001_01101_00001_MIRIMAGE_jump.fits')
result = RampFitStep.call(input_file, save_opt=True, opt_name='rampfit1_opt_out.fits')
output_file = result[0].save(path=result[0].meta.filename.replace('jump', 'rampfit'))
int_outp... | TestMIRIRampFit | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMIRIRampFit:
def test_ramp_fit_miri1(self):
"""Regression test of ramp_fit step performed on MIRI data."""
<|body_0|>
def test_ramp_fit_miri2(self):
"""Regression test of ramp_fit step performed on MIRI data."""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_000531 | 20,238 | permissive | [
{
"docstring": "Regression test of ramp_fit step performed on MIRI data.",
"name": "test_ramp_fit_miri1",
"signature": "def test_ramp_fit_miri1(self)"
},
{
"docstring": "Regression test of ramp_fit step performed on MIRI data.",
"name": "test_ramp_fit_miri2",
"signature": "def test_ramp_... | 2 | stack_v2_sparse_classes_30k_train_011204 | Implement the Python class `TestMIRIRampFit` described below.
Class description:
Implement the TestMIRIRampFit class.
Method signatures and docstrings:
- def test_ramp_fit_miri1(self): Regression test of ramp_fit step performed on MIRI data.
- def test_ramp_fit_miri2(self): Regression test of ramp_fit step performed ... | Implement the Python class `TestMIRIRampFit` described below.
Class description:
Implement the TestMIRIRampFit class.
Method signatures and docstrings:
- def test_ramp_fit_miri1(self): Regression test of ramp_fit step performed on MIRI data.
- def test_ramp_fit_miri2(self): Regression test of ramp_fit step performed ... | e3a5b2d8bb50d92ccca46cd3bbd6585d5238000a | <|skeleton|>
class TestMIRIRampFit:
def test_ramp_fit_miri1(self):
"""Regression test of ramp_fit step performed on MIRI data."""
<|body_0|>
def test_ramp_fit_miri2(self):
"""Regression test of ramp_fit step performed on MIRI data."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestMIRIRampFit:
def test_ramp_fit_miri1(self):
"""Regression test of ramp_fit step performed on MIRI data."""
input_file = self.get_data(self.test_dir, 'jw00001001001_01101_00001_MIRIMAGE_jump.fits')
result = RampFitStep.call(input_file, save_opt=True, opt_name='rampfit1_opt_out.fits'... | the_stack_v2_python_sparse | jwst/tests_nightly/general/miri/test_miri_steps_single.py | mperrin/jwst | train | 0 | |
918261500212eee0d6652e9ecd3db267f8bf8eea | [
"self.logger = logger.SecureTeaLogger(__name__, debug=debug)\nself.ap_dict = dict()\nself._THRESHOLD = 3",
"if pkt.haslayer(scapy.Dot11) and pkt.haslayer(scapy.Dot11Beacon):\n if int(pkt[scapy.Dot11].subtype) == 8:\n bssid = pkt[scapy.Dot11].addr2\n time_stamp = pkt[scapy.Dot11Beacon].timestamp\n... | <|body_start_0|>
self.logger = logger.SecureTeaLogger(__name__, debug=debug)
self.ap_dict = dict()
self._THRESHOLD = 3
<|end_body_0|>
<|body_start_1|>
if pkt.haslayer(scapy.Dot11) and pkt.haslayer(scapy.Dot11Beacon):
if int(pkt[scapy.Dot11].subtype) == 8:
bss... | FakeAccessPoint class. | FakeAccessPoint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FakeAccessPoint:
"""FakeAccessPoint class."""
def __init__(self, debug=False):
"""Initialize FakeAccessPoint class. Args: debug (bool): Log on terminal or not Raises: None Returns: None"""
<|body_0|>
def detect_fake_ap(self, pkt):
"""Detect fake access point by o... | stack_v2_sparse_classes_36k_train_000532 | 2,870 | permissive | [
{
"docstring": "Initialize FakeAccessPoint class. Args: debug (bool): Log on terminal or not Raises: None Returns: None",
"name": "__init__",
"signature": "def __init__(self, debug=False)"
},
{
"docstring": "Detect fake access point by observing their time stamps. A genuine access point broadcas... | 2 | null | Implement the Python class `FakeAccessPoint` described below.
Class description:
FakeAccessPoint class.
Method signatures and docstrings:
- def __init__(self, debug=False): Initialize FakeAccessPoint class. Args: debug (bool): Log on terminal or not Raises: None Returns: None
- def detect_fake_ap(self, pkt): Detect f... | Implement the Python class `FakeAccessPoint` described below.
Class description:
FakeAccessPoint class.
Method signatures and docstrings:
- def __init__(self, debug=False): Initialize FakeAccessPoint class. Args: debug (bool): Log on terminal or not Raises: None Returns: None
- def detect_fake_ap(self, pkt): Detect f... | 43dec187e5848b9ced8a6b4957b6e9028d4d43cd | <|skeleton|>
class FakeAccessPoint:
"""FakeAccessPoint class."""
def __init__(self, debug=False):
"""Initialize FakeAccessPoint class. Args: debug (bool): Log on terminal or not Raises: None Returns: None"""
<|body_0|>
def detect_fake_ap(self, pkt):
"""Detect fake access point by o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FakeAccessPoint:
"""FakeAccessPoint class."""
def __init__(self, debug=False):
"""Initialize FakeAccessPoint class. Args: debug (bool): Log on terminal or not Raises: None Returns: None"""
self.logger = logger.SecureTeaLogger(__name__, debug=debug)
self.ap_dict = dict()
se... | the_stack_v2_python_sparse | securetea/lib/ids/r2l_rules/wireless/fake_access.py | rejahrehim/SecureTea-Project | train | 1 |
d6947ba6ed412b7d17be54151f4d96c1a409169b | [
"if df is None:\n return False\ndf.to_csv(filename, float_format='%f')\nreturn True",
"df = pd.read_csv(filename, index_col=0)\ntimestamps = df[info.colname_timestamps]\ndf.drop(info.colname_timestamps, axis=1)\nreturn (timestamps, df)"
] | <|body_start_0|>
if df is None:
return False
df.to_csv(filename, float_format='%f')
return True
<|end_body_0|>
<|body_start_1|>
df = pd.read_csv(filename, index_col=0)
timestamps = df[info.colname_timestamps]
df.drop(info.colname_timestamps, axis=1)
r... | Handle feeling files. | FeelFileHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeelFileHandler:
"""Handle feeling files."""
def save_data(cls, filename, df):
"""Save a feelings dataframe to a .csv"""
<|body_0|>
def load_data(cls, filename):
"""Read the feelings from csv."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if d... | stack_v2_sparse_classes_36k_train_000533 | 950 | no_license | [
{
"docstring": "Save a feelings dataframe to a .csv",
"name": "save_data",
"signature": "def save_data(cls, filename, df)"
},
{
"docstring": "Read the feelings from csv.",
"name": "load_data",
"signature": "def load_data(cls, filename)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008164 | Implement the Python class `FeelFileHandler` described below.
Class description:
Handle feeling files.
Method signatures and docstrings:
- def save_data(cls, filename, df): Save a feelings dataframe to a .csv
- def load_data(cls, filename): Read the feelings from csv. | Implement the Python class `FeelFileHandler` described below.
Class description:
Handle feeling files.
Method signatures and docstrings:
- def save_data(cls, filename, df): Save a feelings dataframe to a .csv
- def load_data(cls, filename): Read the feelings from csv.
<|skeleton|>
class FeelFileHandler:
"""Handl... | 38cbb8d55cec730a03899692a37273f0817875eb | <|skeleton|>
class FeelFileHandler:
"""Handle feeling files."""
def save_data(cls, filename, df):
"""Save a feelings dataframe to a .csv"""
<|body_0|>
def load_data(cls, filename):
"""Read the feelings from csv."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeelFileHandler:
"""Handle feeling files."""
def save_data(cls, filename, df):
"""Save a feelings dataframe to a .csv"""
if df is None:
return False
df.to_csv(filename, float_format='%f')
return True
def load_data(cls, filename):
"""Read the feelin... | the_stack_v2_python_sparse | backend/filesystem/feel.py | pdpino/muse-player | train | 0 |
d48cfdcf7c832d7ab459c0a1e9f7d98a1398e882 | [
"super(AtributoItemCadenaForm, self).__init__(*args, **kwargs)\nself.plantilla = plantilla\nself.nombre = 'valor_' + str(counter)\nself.fields[self.nombre] = forms.CharField()\nself.fields[self.nombre].label = self.plantilla.nombre\nself.fields[self.nombre].required = self.plantilla.requerido",
"valor = self.clea... | <|body_start_0|>
super(AtributoItemCadenaForm, self).__init__(*args, **kwargs)
self.plantilla = plantilla
self.nombre = 'valor_' + str(counter)
self.fields[self.nombre] = forms.CharField()
self.fields[self.nombre].label = self.plantilla.nombre
self.fields[self.nombre].req... | Form que permite crear y editar atributos dinamicos del tipo 'Cadena'. Validaciones: - La longitud del texto no debe superar la especificada en la plantilla del atributo. Campos: - str | AtributoItemCadenaForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AtributoItemCadenaForm:
"""Form que permite crear y editar atributos dinamicos del tipo 'Cadena'. Validaciones: - La longitud del texto no debe superar la especificada en la plantilla del atributo. Campos: - str"""
def __init__(self, *args, plantilla=None, counter=None, **kwargs):
""... | stack_v2_sparse_classes_36k_train_000534 | 12,403 | no_license | [
{
"docstring": "Constructor del form AtributoItemCadenaForm. Argumentos: - plantilla: AtributoCadena",
"name": "__init__",
"signature": "def __init__(self, *args, plantilla=None, counter=None, **kwargs)"
},
{
"docstring": "Método que valida que la longitud de la cadena no supere la especificada ... | 2 | null | Implement the Python class `AtributoItemCadenaForm` described below.
Class description:
Form que permite crear y editar atributos dinamicos del tipo 'Cadena'. Validaciones: - La longitud del texto no debe superar la especificada en la plantilla del atributo. Campos: - str
Method signatures and docstrings:
- def __ini... | Implement the Python class `AtributoItemCadenaForm` described below.
Class description:
Form que permite crear y editar atributos dinamicos del tipo 'Cadena'. Validaciones: - La longitud del texto no debe superar la especificada en la plantilla del atributo. Campos: - str
Method signatures and docstrings:
- def __ini... | 423e79d437b8666f9508b4b0eeb2be67533b8b2d | <|skeleton|>
class AtributoItemCadenaForm:
"""Form que permite crear y editar atributos dinamicos del tipo 'Cadena'. Validaciones: - La longitud del texto no debe superar la especificada en la plantilla del atributo. Campos: - str"""
def __init__(self, *args, plantilla=None, counter=None, **kwargs):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AtributoItemCadenaForm:
"""Form que permite crear y editar atributos dinamicos del tipo 'Cadena'. Validaciones: - La longitud del texto no debe superar la especificada en la plantilla del atributo. Campos: - str"""
def __init__(self, *args, plantilla=None, counter=None, **kwargs):
"""Constructor ... | the_stack_v2_python_sparse | gestion_de_item/forms.py | jbust97/proyecto_is2 | train | 0 |
25c6377bf1a7101a2c8440f6ea06152f0e8bb476 | [
"if not root:\n return []\nqueue = [(root, 0)]\nvalues = defaultdict(list)\nwhile queue:\n cur, height = queue.pop(0)\n values[height].append(cur.val)\n if cur.left:\n queue.append((cur.left, height + 1))\n if cur.right:\n queue.append((cur.right, height + 1))\nres = []\niter = True\nfo... | <|body_start_0|>
if not root:
return []
queue = [(root, 0)]
values = defaultdict(list)
while queue:
cur, height = queue.pop(0)
values[height].append(cur.val)
if cur.left:
queue.append((cur.left, height + 1))
if c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def zigzagLevelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def zigzagLevelOrder2(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:... | stack_v2_sparse_classes_36k_train_000535 | 2,087 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "zigzagLevelOrder",
"signature": "def zigzagLevelOrder(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "zigzagLevelOrder2",
"signature": "def zigzagLevelOrder2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010986 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def zigzagLevelOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def zigzagLevelOrder2(self, root): :type root: TreeNode :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def zigzagLevelOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def zigzagLevelOrder2(self, root): :type root: TreeNode :rtype: List[List[int]]
<|skeleton|>
cla... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def zigzagLevelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def zigzagLevelOrder2(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def zigzagLevelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
if not root:
return []
queue = [(root, 0)]
values = defaultdict(list)
while queue:
cur, height = queue.pop(0)
values[height].append(cur.val... | the_stack_v2_python_sparse | 103. Binary Tree Zigzag Level Order Traversal/zigzag.py | Macielyoung/LeetCode | train | 1 | |
d8e7010bbe6d8e80e80cfc2e9c932ab339a73f27 | [
"if file_:\n source = ImageFile(file_)\nelse:\n return None\nfor key, value in list(self.default_options.items()):\n options.setdefault(key, value)\nname = self._get_thumbnail_filename(source, geometry_string, options)\nthumbnail = ImageFile(name, default.storage)\nreturn thumbnail",
"base_url = 'thumbs'... | <|body_start_0|>
if file_:
source = ImageFile(file_)
else:
return None
for key, value in list(self.default_options.items()):
options.setdefault(key, value)
name = self._get_thumbnail_filename(source, geometry_string, options)
thumbnail = ImageF... | S3Backend | [
"MIT",
"CC-BY-SA-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3Backend:
def get_thumbnail(self, file_, geometry_string, **options):
"""Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us."""
... | stack_v2_sparse_classes_36k_train_000536 | 1,764 | permissive | [
{
"docstring": "Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us.",
"name": "get_thumbnail",
"signature": "def get_thumbnail(self, file_, geometry_st... | 2 | stack_v2_sparse_classes_30k_train_009516 | Implement the Python class `S3Backend` described below.
Class description:
Implement the S3Backend class.
Method signatures and docstrings:
- def get_thumbnail(self, file_, geometry_string, **options): Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation... | Implement the Python class `S3Backend` described below.
Class description:
Implement the S3Backend class.
Method signatures and docstrings:
- def get_thumbnail(self, file_, geometry_string, **options): Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation... | db3f037c356a586b0eb6b9d5430ce12aa1ea7119 | <|skeleton|>
class S3Backend:
def get_thumbnail(self, file_, geometry_string, **options):
"""Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class S3Backend:
def get_thumbnail(self, file_, geometry_string, **options):
"""Returns thumbnail as an ImageFile instance for file with geometry and options given. All of the thumbnail generation logic is short-circuited as we know that CloudFront will generate the thumbnail for us."""
if file_:
... | the_stack_v2_python_sparse | electionleaflets/apps/core/s3_thumbnail_store.py | DemocracyClub/electionleaflets | train | 9 | |
e92b53172eb81cfbab8f376daba44ae22013ce8b | [
"self.list = []\nself.window = size\nself.sum = 0",
"if len(self.list) == self.window:\n self.sum -= self.list.pop(0)\nself.sum += val\nself.list.append(val)\nreturn self.sum / len(self.list)"
] | <|body_start_0|>
self.list = []
self.window = size
self.sum = 0
<|end_body_0|>
<|body_start_1|>
if len(self.list) == self.window:
self.sum -= self.list.pop(0)
self.sum += val
self.list.append(val)
return self.sum / len(self.list)
<|end_body_1|>
| MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.list = []
self.window = ... | stack_v2_sparse_classes_36k_train_000537 | 725 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | null | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | baa6927a137765e4d7fe2d020863bca6988a1cf7 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.list = []
self.window = size
self.sum = 0
def next(self, val):
""":type val: int :rtype: float"""
if len(self.list) == self.window:
self.sum... | the_stack_v2_python_sparse | 346. Moving Average from Data Stream.py | Jingwei4CMU/Leetcode | train | 0 | |
710fea9c8cb9ca215d255f212994b7883675edf2 | [
"self.__logger = get_logger(__name__)\nself.__logger.info('Creating decorator ')\nself.__topics_receive__ = []\nself.__topics_send__ = []\nself.__connection__ = None\nself.cls = None",
"self.__logger.info('Adding host')\nparent = self\n\ndef inner(cls):\n parent.__logger.info(f'Creating class: {cls}')\n\n c... | <|body_start_0|>
self.__logger = get_logger(__name__)
self.__logger.info('Creating decorator ')
self.__topics_receive__ = []
self.__topics_send__ = []
self.__connection__ = None
self.cls = None
<|end_body_0|>
<|body_start_1|>
self.__logger.info('Adding host')
... | Wrap pykafka functions. Define the decorators and hold the comunication data | KafkaDecorator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KafkaDecorator:
"""Wrap pykafka functions. Define the decorators and hold the comunication data"""
def __init__(self):
"""Create a KafkaDecorator."""
<|body_0|>
def host(self, *args, **kargs):
"""Set the conenction data. Create a new version of the decorated clas... | stack_v2_sparse_classes_36k_train_000538 | 5,207 | permissive | [
{
"docstring": "Create a KafkaDecorator.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Set the conenction data. Create a new version of the decorated class that inherits from kafka_client_decorators.client.Client class Parameters ---------- *args A list of arguments ... | 5 | stack_v2_sparse_classes_30k_train_009288 | Implement the Python class `KafkaDecorator` described below.
Class description:
Wrap pykafka functions. Define the decorators and hold the comunication data
Method signatures and docstrings:
- def __init__(self): Create a KafkaDecorator.
- def host(self, *args, **kargs): Set the conenction data. Create a new version ... | Implement the Python class `KafkaDecorator` described below.
Class description:
Wrap pykafka functions. Define the decorators and hold the comunication data
Method signatures and docstrings:
- def __init__(self): Create a KafkaDecorator.
- def host(self, *args, **kargs): Set the conenction data. Create a new version ... | f2c958df88c5698148aae4c5314dd39e31e995c3 | <|skeleton|>
class KafkaDecorator:
"""Wrap pykafka functions. Define the decorators and hold the comunication data"""
def __init__(self):
"""Create a KafkaDecorator."""
<|body_0|>
def host(self, *args, **kargs):
"""Set the conenction data. Create a new version of the decorated clas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KafkaDecorator:
"""Wrap pykafka functions. Define the decorators and hold the comunication data"""
def __init__(self):
"""Create a KafkaDecorator."""
self.__logger = get_logger(__name__)
self.__logger.info('Creating decorator ')
self.__topics_receive__ = []
self.__... | the_stack_v2_python_sparse | kafka_client_decorators/decorators.py | cdsedson/kafka-decorator | train | 1 |
9de96cdb4557ff0680805d7ceb2086485f2e0b52 | [
"self.fasta = fasta\nself.output = output\nself.window_size = window_size\nself.max_bp_span = max_bp_span\nself.avg_bp_prob_cutoff = avg_bp_prob_cutoff\nself.complexity = complexity\nself.nbits = nbits\nself.njobs = njobs\nself.verbose = verbose",
"if self.verbose:\n print('Folding sequences using RNAplfold -W... | <|body_start_0|>
self.fasta = fasta
self.output = output
self.window_size = window_size
self.max_bp_span = max_bp_span
self.avg_bp_prob_cutoff = avg_bp_prob_cutoff
self.complexity = complexity
self.nbits = nbits
self.njobs = njobs
self.verbose = ve... | Compute the RNA features. | RNAVectorizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNAVectorizer:
"""Compute the RNA features."""
def __init__(self, fasta, output, window_size=150, max_bp_span=40, avg_bp_prob_cutoff=0.4, complexity=2, nbits=10, njobs=-1, verbose=True):
"""Constructor. Parameters ---------- fasta : str Fasta file containing the RNA sequences. output... | stack_v2_sparse_classes_36k_train_000539 | 6,638 | permissive | [
{
"docstring": "Constructor. Parameters ---------- fasta : str Fasta file containing the RNA sequences. output : str Name of the output file. The output file is an HDF5 containing a pandas DataFrame, in which the columns are the RNA names and the rows are the EDeN features. window_size : int (default : 150) Win... | 4 | stack_v2_sparse_classes_30k_train_008628 | Implement the Python class `RNAVectorizer` described below.
Class description:
Compute the RNA features.
Method signatures and docstrings:
- def __init__(self, fasta, output, window_size=150, max_bp_span=40, avg_bp_prob_cutoff=0.4, complexity=2, nbits=10, njobs=-1, verbose=True): Constructor. Parameters ---------- fa... | Implement the Python class `RNAVectorizer` described below.
Class description:
Compute the RNA features.
Method signatures and docstrings:
- def __init__(self, fasta, output, window_size=150, max_bp_span=40, avg_bp_prob_cutoff=0.4, complexity=2, nbits=10, njobs=-1, verbose=True): Constructor. Parameters ---------- fa... | 840007ae9da2bb89ba5a60769e3bc885579c0a39 | <|skeleton|>
class RNAVectorizer:
"""Compute the RNA features."""
def __init__(self, fasta, output, window_size=150, max_bp_span=40, avg_bp_prob_cutoff=0.4, complexity=2, nbits=10, njobs=-1, verbose=True):
"""Constructor. Parameters ---------- fasta : str Fasta file containing the RNA sequences. output... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNAVectorizer:
"""Compute the RNA features."""
def __init__(self, fasta, output, window_size=150, max_bp_span=40, avg_bp_prob_cutoff=0.4, complexity=2, nbits=10, njobs=-1, verbose=True):
"""Constructor. Parameters ---------- fasta : str Fasta file containing the RNA sequences. output : str Name o... | the_stack_v2_python_sparse | rnacommender/rnafeatures.py | xflicsu/RNAcommender | train | 0 |
e8d632942b51977f54ed57e3b3dbe11fa8b4f67c | [
"def input_fn():\n return ({'age': tf.constant([1]), 'language': tf.SparseTensor(values=['english'], indices=[[0, 0]], shape=[1, 1])}, tf.constant([[1]]))\nlanguage = tf.contrib.layers.sparse_column_with_hash_bucket('language', 100)\nage = tf.contrib.layers.real_valued_column('age')\ntarget_column = layers.multi... | <|body_start_0|>
def input_fn():
return ({'age': tf.constant([1]), 'language': tf.SparseTensor(values=['english'], indices=[[0, 0]], shape=[1, 1])}, tf.constant([[1]]))
language = tf.contrib.layers.sparse_column_with_hash_bucket('language', 100)
age = tf.contrib.layers.real_valued_co... | ComposableModelTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComposableModelTest:
def testLinearModel(self):
"""Tests that loss goes down with training."""
<|body_0|>
def testDNNModel(self):
"""Tests multi-class classification using matrix data as input."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def inp... | stack_v2_sparse_classes_36k_train_000540 | 4,936 | permissive | [
{
"docstring": "Tests that loss goes down with training.",
"name": "testLinearModel",
"signature": "def testLinearModel(self)"
},
{
"docstring": "Tests multi-class classification using matrix data as input.",
"name": "testDNNModel",
"signature": "def testDNNModel(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012610 | Implement the Python class `ComposableModelTest` described below.
Class description:
Implement the ComposableModelTest class.
Method signatures and docstrings:
- def testLinearModel(self): Tests that loss goes down with training.
- def testDNNModel(self): Tests multi-class classification using matrix data as input. | Implement the Python class `ComposableModelTest` described below.
Class description:
Implement the ComposableModelTest class.
Method signatures and docstrings:
- def testLinearModel(self): Tests that loss goes down with training.
- def testDNNModel(self): Tests multi-class classification using matrix data as input.
... | 6d39eeb66c63a6f0f7895befc588c9eb1dd105f9 | <|skeleton|>
class ComposableModelTest:
def testLinearModel(self):
"""Tests that loss goes down with training."""
<|body_0|>
def testDNNModel(self):
"""Tests multi-class classification using matrix data as input."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComposableModelTest:
def testLinearModel(self):
"""Tests that loss goes down with training."""
def input_fn():
return ({'age': tf.constant([1]), 'language': tf.SparseTensor(values=['english'], indices=[[0, 0]], shape=[1, 1])}, tf.constant([[1]]))
language = tf.contrib.layer... | the_stack_v2_python_sparse | jni-build/jni/include/tensorflow/contrib/learn/python/learn/estimators/composable_model_test.py | Lab603/PicEncyclopedias | train | 6 | |
d3d0fa5a5fb275115480ca085ef2a4ca5c824bfb | [
"lines = read_file('globalbss.info')\n\ndef mapper(l):\n items = l.strip().split()\n return (items[0][1:].upper(), items[1])\nreturn map(mapper, lines)",
"u_fl = filter(lambda f: not f.is_lib, fl)\nif docfg:\n _cg = cg()\n _cg.set_funcs(fl)\n il = _cg.visit(il)\nil = re.adjust_loclabel(il)\nre.reas... | <|body_start_0|>
lines = read_file('globalbss.info')
def mapper(l):
items = l.strip().split()
return (items[0][1:].upper(), items[1])
return map(mapper, lines)
<|end_body_0|>
<|body_start_1|>
u_fl = filter(lambda f: not f.is_lib, fl)
if docfg:
... | Code analysis skeleton | Analysis | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Analysis:
"""Code analysis skeleton"""
def global_bss():
"""Load external bss variable information"""
<|body_0|>
def analyze(il, fl, re, docfg=False):
"""Analyze code :param il: instruction list :param fl: function list :param re: symbol reconstruction object :pa... | stack_v2_sparse_classes_36k_train_000541 | 1,907 | no_license | [
{
"docstring": "Load external bss variable information",
"name": "global_bss",
"signature": "def global_bss()"
},
{
"docstring": "Analyze code :param il: instruction list :param fl: function list :param re: symbol reconstruction object :param docfg: True to evaluate call graph and cfg :return: [... | 3 | stack_v2_sparse_classes_30k_train_016310 | Implement the Python class `Analysis` described below.
Class description:
Code analysis skeleton
Method signatures and docstrings:
- def global_bss(): Load external bss variable information
- def analyze(il, fl, re, docfg=False): Analyze code :param il: instruction list :param fl: function list :param re: symbol reco... | Implement the Python class `Analysis` described below.
Class description:
Code analysis skeleton
Method signatures and docstrings:
- def global_bss(): Load external bss variable information
- def analyze(il, fl, re, docfg=False): Analyze code :param il: instruction list :param fl: function list :param re: symbol reco... | aff27a9f7281e76e935a5b085160038767363eed | <|skeleton|>
class Analysis:
"""Code analysis skeleton"""
def global_bss():
"""Load external bss variable information"""
<|body_0|>
def analyze(il, fl, re, docfg=False):
"""Analyze code :param il: instruction list :param fl: function list :param re: symbol reconstruction object :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Analysis:
"""Code analysis skeleton"""
def global_bss():
"""Load external bss variable information"""
lines = read_file('globalbss.info')
def mapper(l):
items = l.strip().split()
return (items[0][1:].upper(), items[1])
return map(mapper, lines)
... | the_stack_v2_python_sparse | src/analysis/analysis_process.py | jimwangzx/adversarial-example----GNN-malware-Uroboros-ELF- | train | 0 |
96c6d3bdf363067247f1825a28e290fb28febc1f | [
"self.maxDiff = None\nuser = User.objects.create(username='cristina@gmail.com', email='cristina@gmail.com', password='password')\nresponse = self.client.post(path=f'/api/v1/user/{user.id}/address/', data=json.dumps({'first_name': 'first_name', 'last_name': 'last_name', 'street_address': 'street_address', 'apt_nr': ... | <|body_start_0|>
self.maxDiff = None
user = User.objects.create(username='cristina@gmail.com', email='cristina@gmail.com', password='password')
response = self.client.post(path=f'/api/v1/user/{user.id}/address/', data=json.dumps({'first_name': 'first_name', 'last_name': 'last_name', 'street_addr... | AddressCreationTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddressCreationTest:
def test_create_address(self):
"""tests that the address information is saved to the database."""
<|body_0|>
def test_create_unique_address(self):
"""tests that if the address already exists 200 status code is returned and the address is not adde... | stack_v2_sparse_classes_36k_train_000542 | 7,789 | no_license | [
{
"docstring": "tests that the address information is saved to the database.",
"name": "test_create_address",
"signature": "def test_create_address(self)"
},
{
"docstring": "tests that if the address already exists 200 status code is returned and the address is not added to the database.",
"... | 2 | null | Implement the Python class `AddressCreationTest` described below.
Class description:
Implement the AddressCreationTest class.
Method signatures and docstrings:
- def test_create_address(self): tests that the address information is saved to the database.
- def test_create_unique_address(self): tests that if the addres... | Implement the Python class `AddressCreationTest` described below.
Class description:
Implement the AddressCreationTest class.
Method signatures and docstrings:
- def test_create_address(self): tests that the address information is saved to the database.
- def test_create_unique_address(self): tests that if the addres... | d84bdedc9ed011dc009cd1b6d42eed1925ccc977 | <|skeleton|>
class AddressCreationTest:
def test_create_address(self):
"""tests that the address information is saved to the database."""
<|body_0|>
def test_create_unique_address(self):
"""tests that if the address already exists 200 status code is returned and the address is not adde... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddressCreationTest:
def test_create_address(self):
"""tests that the address information is saved to the database."""
self.maxDiff = None
user = User.objects.create(username='cristina@gmail.com', email='cristina@gmail.com', password='password')
response = self.client.post(path... | the_stack_v2_python_sparse | backend/user/tests.py | Code-Institute-Submissions/vintage-earrings | train | 0 | |
b235ca9b860ca7079725ddb4aab103380ac70aaf | [
"Questionnaire.__init__(self, df)\nself.names = ['stai_state', 'stai_trait']\nself.labels = ['STAI anxiety questionnaire - state', 'STAI anxiety questionnaire - trait']\nself.values = {'stai_state': {}, 'stai_trait': {}}\nself.code_dic = stai\nself.new_df = pd.DataFrame(0, index=self.df.index, columns=self.names)",... | <|body_start_0|>
Questionnaire.__init__(self, df)
self.names = ['stai_state', 'stai_trait']
self.labels = ['STAI anxiety questionnaire - state', 'STAI anxiety questionnaire - trait']
self.values = {'stai_state': {}, 'stai_trait': {}}
self.code_dic = stai
self.new_df = pd.... | A class used to represent an the Spielberg Anxiety Questionnaire Attributes ---------- df : DataFrame a Pandas data frame with the specific columns for the questionnaire Methods ------- grade() calculates the grading of the questionnaire state_trait_calc() helper funtion for calculating the STATE/TRAIT score | Stai | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Stai:
"""A class used to represent an the Spielberg Anxiety Questionnaire Attributes ---------- df : DataFrame a Pandas data frame with the specific columns for the questionnaire Methods ------- grade() calculates the grading of the questionnaire state_trait_calc() helper funtion for calculating... | stack_v2_sparse_classes_36k_train_000543 | 2,702 | no_license | [
{
"docstring": "Init the following arguments: names = the new columns' names (after grading) labels = labels for the columns to be written in the SPSS output file values = explanation for the value for SPSS columns - empty for this questionaire code_dic = a dictionary from each pharse to a number Parameters ---... | 3 | stack_v2_sparse_classes_30k_train_014059 | Implement the Python class `Stai` described below.
Class description:
A class used to represent an the Spielberg Anxiety Questionnaire Attributes ---------- df : DataFrame a Pandas data frame with the specific columns for the questionnaire Methods ------- grade() calculates the grading of the questionnaire state_trai... | Implement the Python class `Stai` described below.
Class description:
A class used to represent an the Spielberg Anxiety Questionnaire Attributes ---------- df : DataFrame a Pandas data frame with the specific columns for the questionnaire Methods ------- grade() calculates the grading of the questionnaire state_trai... | 26b8a2847d7202b61e67e2cd0074278a46a9f8f3 | <|skeleton|>
class Stai:
"""A class used to represent an the Spielberg Anxiety Questionnaire Attributes ---------- df : DataFrame a Pandas data frame with the specific columns for the questionnaire Methods ------- grade() calculates the grading of the questionnaire state_trait_calc() helper funtion for calculating... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Stai:
"""A class used to represent an the Spielberg Anxiety Questionnaire Attributes ---------- df : DataFrame a Pandas data frame with the specific columns for the questionnaire Methods ------- grade() calculates the grading of the questionnaire state_trait_calc() helper funtion for calculating the STATE/TR... | the_stack_v2_python_sparse | Questionnaires/Stai.py | TechnionENIC/ENIC_scoring_program | train | 0 |
77d8723cd663e9ab9e74c203ccad8ad6582ab89d | [
"if not s:\n return True\ns = s.lower()\nnum = len(s)\ni = 0\nj = num - 1\nwhile j - i >= 1:\n if not (s[i] >= 'a' and s[i] <= 'z' or (s[i] >= 'A' and s[i] <= 'Z') or (s[i] >= '0' and s[i] <= '9')):\n i += 1\n continue\n if not (s[j] >= 'a' and s[j] <= 'z' or (s[j] >= 'A' and s[j] <= 'Z') or ... | <|body_start_0|>
if not s:
return True
s = s.lower()
num = len(s)
i = 0
j = num - 1
while j - i >= 1:
if not (s[i] >= 'a' and s[i] <= 'z' or (s[i] >= 'A' and s[i] <= 'Z') or (s[i] >= '0' and s[i] <= '9')):
i += 1
con... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isPalindrome2(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not s:
return True
s = s.lower()
... | stack_v2_sparse_classes_36k_train_000544 | 1,152 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "isPalindrome2",
"signature": "def isPalindrome2(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015157 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, s): :type s: str :rtype: bool
- def isPalindrome2(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, s): :type s: str :rtype: bool
- def isPalindrome2(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def isPalindrome(self, s):
... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def isPalindrome2(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
if not s:
return True
s = s.lower()
num = len(s)
i = 0
j = num - 1
while j - i >= 1:
if not (s[i] >= 'a' and s[i] <= 'z' or (s[i] >= 'A' and s[i] <= 'Z') or (s[i... | the_stack_v2_python_sparse | 125. Valid Palindrome/palindrome.py | Macielyoung/LeetCode | train | 1 | |
39d736d0fed6ec7343728649d5e8fb31174cdbb6 | [
"if isinstance(symbol, (SymbolAtom,)):\n return True\nelif containsAnonymousList(symbol):\n return False\nelif containsOr(symbol):\n return False\nelse:\n return True",
"if isinstance(symbol, (SymbolAtom,)):\n return False\nelif isinstance(symbol, (SymbolList,)):\n return True\nelse:\n while ... | <|body_start_0|>
if isinstance(symbol, (SymbolAtom,)):
return True
elif containsAnonymousList(symbol):
return False
elif containsOr(symbol):
return False
else:
return True
<|end_body_0|>
<|body_start_1|>
if isinstance(symbol, (Symb... | generated source for class GdlValidator | GdlValidator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GdlValidator:
"""generated source for class GdlValidator"""
def validate(self, symbol):
"""generated source for method validate"""
<|body_0|>
def containsAnonymousList(self, symbol):
"""generated source for method containsAnonymousList"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_000545 | 3,334 | permissive | [
{
"docstring": "generated source for method validate",
"name": "validate",
"signature": "def validate(self, symbol)"
},
{
"docstring": "generated source for method containsAnonymousList",
"name": "containsAnonymousList",
"signature": "def containsAnonymousList(self, symbol)"
},
{
... | 3 | null | Implement the Python class `GdlValidator` described below.
Class description:
generated source for class GdlValidator
Method signatures and docstrings:
- def validate(self, symbol): generated source for method validate
- def containsAnonymousList(self, symbol): generated source for method containsAnonymousList
- def ... | Implement the Python class `GdlValidator` described below.
Class description:
generated source for class GdlValidator
Method signatures and docstrings:
- def validate(self, symbol): generated source for method validate
- def containsAnonymousList(self, symbol): generated source for method containsAnonymousList
- def ... | 4e6e6e876c3a4294cd711647051da2d9c1836b60 | <|skeleton|>
class GdlValidator:
"""generated source for class GdlValidator"""
def validate(self, symbol):
"""generated source for method validate"""
<|body_0|>
def containsAnonymousList(self, symbol):
"""generated source for method containsAnonymousList"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GdlValidator:
"""generated source for class GdlValidator"""
def validate(self, symbol):
"""generated source for method validate"""
if isinstance(symbol, (SymbolAtom,)):
return True
elif containsAnonymousList(symbol):
return False
elif containsOr(sym... | the_stack_v2_python_sparse | ggpy/cruft/autocode/GdlValidator.py | hobson/ggpy | train | 1 |
fe04cfdc4e7d304ec81da5b2f41c3572dca0f4d3 | [
"options = super()._default_run_options()\noptions.meas_level = MeasLevel.KERNELED\noptions.meas_return = MeasReturnType.SINGLE\nreturn options",
"options = super()._default_experiment_options()\noptions.n_states = 2\noptions.schedules = None\nreturn options",
"super().__init__(physical_qubits, analysis=MultiSt... | <|body_start_0|>
options = super()._default_run_options()
options.meas_level = MeasLevel.KERNELED
options.meas_return = MeasReturnType.SINGLE
return options
<|end_body_0|>
<|body_start_1|>
options = super()._default_experiment_options()
options.n_states = 2
optio... | An experiment that discriminates between the first :math:`n` energy states. # section: overview The experiment creates :math:`n` circuits that prepare, respectively, the energy states :math:`|0\\rangle,\\cdots,|n-1\\rangle`. For, e.g., :math:`n=4` the circuits are of the form .. parsed-literal:: Circuit preparing :math... | MultiStateDiscrimination | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiStateDiscrimination:
"""An experiment that discriminates between the first :math:`n` energy states. # section: overview The experiment creates :math:`n` circuits that prepare, respectively, the energy states :math:`|0\\rangle,\\cdots,|n-1\\rangle`. For, e.g., :math:`n=4` the circuits are of ... | stack_v2_sparse_classes_36k_train_000546 | 5,401 | permissive | [
{
"docstring": "Default option values for the experiment :meth:`run` method.",
"name": "_default_run_options",
"signature": "def _default_run_options(cls) -> Options"
},
{
"docstring": "Default values for the number of states if none is given. Experiment Options: n_states (int): The number of st... | 4 | null | Implement the Python class `MultiStateDiscrimination` described below.
Class description:
An experiment that discriminates between the first :math:`n` energy states. # section: overview The experiment creates :math:`n` circuits that prepare, respectively, the energy states :math:`|0\\rangle,\\cdots,|n-1\\rangle`. For,... | Implement the Python class `MultiStateDiscrimination` described below.
Class description:
An experiment that discriminates between the first :math:`n` energy states. # section: overview The experiment creates :math:`n` circuits that prepare, respectively, the energy states :math:`|0\\rangle,\\cdots,|n-1\\rangle`. For,... | a387675a3fe817cef05b968bbf3e05799a09aaae | <|skeleton|>
class MultiStateDiscrimination:
"""An experiment that discriminates between the first :math:`n` energy states. # section: overview The experiment creates :math:`n` circuits that prepare, respectively, the energy states :math:`|0\\rangle,\\cdots,|n-1\\rangle`. For, e.g., :math:`n=4` the circuits are of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiStateDiscrimination:
"""An experiment that discriminates between the first :math:`n` energy states. # section: overview The experiment creates :math:`n` circuits that prepare, respectively, the energy states :math:`|0\\rangle,\\cdots,|n-1\\rangle`. For, e.g., :math:`n=4` the circuits are of the form .. p... | the_stack_v2_python_sparse | qiskit_experiments/library/characterization/multi_state_discrimination.py | oliverdial/qiskit-experiments | train | 0 |
68edf807f129b92d99d60602870d197e2db17fb0 | [
"try:\n user = User.objects.get(pk=pk)\n serializer = UserSerializer(user, context={'request': request})\n return Response(serializer.data)\nexcept Exception as ex:\n return HttpResponseServerError(ex)",
"users = User.objects.all().order_by('-is_staff')\nserializer = UserSerializer(users, many=True, c... | <|body_start_0|>
try:
user = User.objects.get(pk=pk)
serializer = UserSerializer(user, context={'request': request})
return Response(serializer.data)
except Exception as ex:
return HttpResponseServerError(ex)
<|end_body_0|>
<|body_start_1|>
users ... | UserViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserViewSet:
def retrieve(self, request, pk=None):
"""Handle GET requests for single user returns: Response -- JSON serialized user"""
<|body_0|>
def list(self, request):
"""Handle GET requests to get all users Returns: Response -- JSON serialized list of users"""
... | stack_v2_sparse_classes_36k_train_000547 | 1,271 | no_license | [
{
"docstring": "Handle GET requests for single user returns: Response -- JSON serialized user",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
},
{
"docstring": "Handle GET requests to get all users Returns: Response -- JSON serialized list of users",
"name": "list",... | 2 | stack_v2_sparse_classes_30k_train_021049 | Implement the Python class `UserViewSet` described below.
Class description:
Implement the UserViewSet class.
Method signatures and docstrings:
- def retrieve(self, request, pk=None): Handle GET requests for single user returns: Response -- JSON serialized user
- def list(self, request): Handle GET requests to get al... | Implement the Python class `UserViewSet` described below.
Class description:
Implement the UserViewSet class.
Method signatures and docstrings:
- def retrieve(self, request, pk=None): Handle GET requests for single user returns: Response -- JSON serialized user
- def list(self, request): Handle GET requests to get al... | bd996853f6bd9a95d15115248300e6d801c0dc47 | <|skeleton|>
class UserViewSet:
def retrieve(self, request, pk=None):
"""Handle GET requests for single user returns: Response -- JSON serialized user"""
<|body_0|>
def list(self, request):
"""Handle GET requests to get all users Returns: Response -- JSON serialized list of users"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserViewSet:
def retrieve(self, request, pk=None):
"""Handle GET requests for single user returns: Response -- JSON serialized user"""
try:
user = User.objects.get(pk=pk)
serializer = UserSerializer(user, context={'request': request})
return Response(seriali... | the_stack_v2_python_sparse | capstoneapi/views/user.py | jeaninebeckle/backend-capstone-api | train | 0 | |
17d6169090f2bcd7b73f08bb21894e3c940a14ee | [
"nodes_gpu = max(1, int(ceil(ngpus / cls.gpus_per_node)))\nnodes_cpu = max(1, int(ceil(ncpus / cls.cores_per_node)))\nif nodes_gpu >= nodes_cpu:\n check_utilization(nodes_gpu, ngpus, cls.gpus_per_node, threshold, 'compute')\n return nodes_gpu\ncheck_utilization(nodes_cpu, ncpus, cls.cores_per_node, threshold,... | <|body_start_0|>
nodes_gpu = max(1, int(ceil(ngpus / cls.gpus_per_node)))
nodes_cpu = max(1, int(ceil(ncpus / cls.cores_per_node)))
if nodes_gpu >= nodes_cpu:
check_utilization(nodes_gpu, ngpus, cls.gpus_per_node, threshold, 'compute')
return nodes_gpu
check_utili... | Environment profile for the Frontier supercomputer. https://docs.olcf.ornl.gov/systems/frontier_user_guide.html | FrontierEnvironment | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrontierEnvironment:
"""Environment profile for the Frontier supercomputer. https://docs.olcf.ornl.gov/systems/frontier_user_guide.html"""
def calc_num_nodes(cls, ngpus, ncpus, threshold):
"""Compute the number of nodes needed to meet the resource request. Also raise an error when th... | stack_v2_sparse_classes_36k_train_000548 | 10,994 | permissive | [
{
"docstring": "Compute the number of nodes needed to meet the resource request. Also raise an error when the requested resource do not come close to saturating the asked for nodes.",
"name": "calc_num_nodes",
"signature": "def calc_num_nodes(cls, ngpus, ncpus, threshold)"
},
{
"docstring": "Get... | 2 | stack_v2_sparse_classes_30k_train_007621 | Implement the Python class `FrontierEnvironment` described below.
Class description:
Environment profile for the Frontier supercomputer. https://docs.olcf.ornl.gov/systems/frontier_user_guide.html
Method signatures and docstrings:
- def calc_num_nodes(cls, ngpus, ncpus, threshold): Compute the number of nodes needed ... | Implement the Python class `FrontierEnvironment` described below.
Class description:
Environment profile for the Frontier supercomputer. https://docs.olcf.ornl.gov/systems/frontier_user_guide.html
Method signatures and docstrings:
- def calc_num_nodes(cls, ngpus, ncpus, threshold): Compute the number of nodes needed ... | 845865c5f34135243ac21800495c46c915662c64 | <|skeleton|>
class FrontierEnvironment:
"""Environment profile for the Frontier supercomputer. https://docs.olcf.ornl.gov/systems/frontier_user_guide.html"""
def calc_num_nodes(cls, ngpus, ncpus, threshold):
"""Compute the number of nodes needed to meet the resource request. Also raise an error when th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FrontierEnvironment:
"""Environment profile for the Frontier supercomputer. https://docs.olcf.ornl.gov/systems/frontier_user_guide.html"""
def calc_num_nodes(cls, ngpus, ncpus, threshold):
"""Compute the number of nodes needed to meet the resource request. Also raise an error when the requested r... | the_stack_v2_python_sparse | flow/environments/incite.py | glotzerlab/signac-flow | train | 54 |
5bb00eab175218c14123f30ae3f02272492d26f3 | [
"self.username = username\npassword = password.encode('utf8')\nself.password = md5(password).hexdigest()\nself.soft_id = soft_id\nself.base_params = {'user': self.username, 'pass2': self.password, 'softid': self.soft_id}\nself.headers = {'Accept-Encoding': 'gzip, deflate, sdch', 'Accept-Language': 'en-US,en;q=0.8',... | <|body_start_0|>
self.username = username
password = password.encode('utf8')
self.password = md5(password).hexdigest()
self.soft_id = soft_id
self.base_params = {'user': self.username, 'pass2': self.password, 'softid': self.soft_id}
self.headers = {'Accept-Encoding': 'gzi... | Chaojiying | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chaojiying:
def __init__(self, username, password, soft_id):
""":param username: :param password: :param soft_id:"""
<|body_0|>
def PostPic(self, im, codetype):
""":param im: 图片字节 :param codetype: 题目类型 参考 http://www.chaojiying.com/price.html :return:"""
<|bod... | stack_v2_sparse_classes_36k_train_000549 | 7,494 | no_license | [
{
"docstring": ":param username: :param password: :param soft_id:",
"name": "__init__",
"signature": "def __init__(self, username, password, soft_id)"
},
{
"docstring": ":param im: 图片字节 :param codetype: 题目类型 参考 http://www.chaojiying.com/price.html :return:",
"name": "PostPic",
"signature... | 3 | stack_v2_sparse_classes_30k_train_013176 | Implement the Python class `Chaojiying` described below.
Class description:
Implement the Chaojiying class.
Method signatures and docstrings:
- def __init__(self, username, password, soft_id): :param username: :param password: :param soft_id:
- def PostPic(self, im, codetype): :param im: 图片字节 :param codetype: 题目类型 参考... | Implement the Python class `Chaojiying` described below.
Class description:
Implement the Chaojiying class.
Method signatures and docstrings:
- def __init__(self, username, password, soft_id): :param username: :param password: :param soft_id:
- def PostPic(self, im, codetype): :param im: 图片字节 :param codetype: 题目类型 参考... | a9705ebc3a6f95160ad9571d48675bc59876bd32 | <|skeleton|>
class Chaojiying:
def __init__(self, username, password, soft_id):
""":param username: :param password: :param soft_id:"""
<|body_0|>
def PostPic(self, im, codetype):
""":param im: 图片字节 :param codetype: 题目类型 参考 http://www.chaojiying.com/price.html :return:"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Chaojiying:
def __init__(self, username, password, soft_id):
""":param username: :param password: :param soft_id:"""
self.username = username
password = password.encode('utf8')
self.password = md5(password).hexdigest()
self.soft_id = soft_id
self.base_params = {... | the_stack_v2_python_sparse | codes/Module_4/lecture_23/lecture_23_1.py | Gedanke/Reptile_study_notes | train | 5 | |
b0097f8c7c50f1f2c852f612e3ad08f171c752af | [
"app.config['TESTING'] = True\nself.client = app.test_client()\nconnect_to_db(app, 'postgresql:///testdb')\ndb.drop_all()\ndb.create_all()\ncreate_test_data()",
"db.session.remove()\ndb.drop_all()\ndb.engine.dispose()",
"result = self.client.get('/')\nself.assertIn(b'IM_Melon', result.data)\nself.assertEqual(re... | <|body_start_0|>
app.config['TESTING'] = True
self.client = app.test_client()
connect_to_db(app, 'postgresql:///testdb')
db.drop_all()
db.create_all()
create_test_data()
<|end_body_0|>
<|body_start_1|>
db.session.remove()
db.drop_all()
db.engine.d... | Flask tests. | FlaskTestBasic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlaskTestBasic:
"""Flask tests."""
def setUp(self):
"""Run code before every test"""
<|body_0|>
def tearDown(self):
"""Run this at the end of every test."""
<|body_1|>
def test_index(self):
"""Test homepage"""
<|body_2|>
def test... | stack_v2_sparse_classes_36k_train_000550 | 4,379 | no_license | [
{
"docstring": "Run code before every test",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Run this at the end of every test.",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "Test homepage",
"name": "test_index",
"signature":... | 4 | stack_v2_sparse_classes_30k_train_011683 | Implement the Python class `FlaskTestBasic` described below.
Class description:
Flask tests.
Method signatures and docstrings:
- def setUp(self): Run code before every test
- def tearDown(self): Run this at the end of every test.
- def test_index(self): Test homepage
- def test_addnewmelon(self): Test add new melon p... | Implement the Python class `FlaskTestBasic` described below.
Class description:
Flask tests.
Method signatures and docstrings:
- def setUp(self): Run code before every test
- def tearDown(self): Run this at the end of every test.
- def test_index(self): Test homepage
- def test_addnewmelon(self): Test add new melon p... | 81f76323e660a97e46b479099ab02591be6ce4e4 | <|skeleton|>
class FlaskTestBasic:
"""Flask tests."""
def setUp(self):
"""Run code before every test"""
<|body_0|>
def tearDown(self):
"""Run this at the end of every test."""
<|body_1|>
def test_index(self):
"""Test homepage"""
<|body_2|>
def test... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlaskTestBasic:
"""Flask tests."""
def setUp(self):
"""Run code before every test"""
app.config['TESTING'] = True
self.client = app.test_client()
connect_to_db(app, 'postgresql:///testdb')
db.drop_all()
db.create_all()
create_test_data()
def te... | the_stack_v2_python_sparse | test.py | kioshi87/IM_Melon | train | 6 |
010a5eda3d42169112042145140e28c0d5d19a12 | [
"try:\n userDetail = {'realname': request.user.detail.realname, 'idCard': request.user.detail.idCard, 'gender': request.user.detail.gender}\nexcept AttributeError as e:\n detailForm = DetailForm()\nelse:\n detailForm = DetailForm(userDetail)\nreturn render(request, 'usermgr/user/userdetail.html', locals())... | <|body_start_0|>
try:
userDetail = {'realname': request.user.detail.realname, 'idCard': request.user.detail.idCard, 'gender': request.user.detail.gender}
except AttributeError as e:
detailForm = DetailForm()
else:
detailForm = DetailForm(userDetail)
re... | 处理用户信息相关请求 | UserDetail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserDetail:
"""处理用户信息相关请求"""
def get(self, request):
"""处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理页面"""
<|body_0|>
def post(self, request):
"""处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理结果"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_000551 | 12,349 | no_license | [
{
"docstring": "处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理页面",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理结果",
"name": "post",
"signature": "def post(self, request)"... | 3 | stack_v2_sparse_classes_30k_train_013263 | Implement the Python class `UserDetail` described below.
Class description:
处理用户信息相关请求
Method signatures and docstrings:
- def get(self, request): 处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理页面
- def post(self, request): 处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理结果
- ... | Implement the Python class `UserDetail` described below.
Class description:
处理用户信息相关请求
Method signatures and docstrings:
- def get(self, request): 处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理页面
- def post(self, request): 处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理结果
- ... | 26c49e8f525ca57dca27f8de53d15bcab24d00e4 | <|skeleton|>
class UserDetail:
"""处理用户信息相关请求"""
def get(self, request):
"""处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理页面"""
<|body_0|>
def post(self, request):
"""处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理结果"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserDetail:
"""处理用户信息相关请求"""
def get(self, request):
"""处理用户信息相关请求 :param request: django路由响应默认携带request对象 :return: 返回用户信息处理页面"""
try:
userDetail = {'realname': request.user.detail.realname, 'idCard': request.user.detail.idCard, 'gender': request.user.detail.gender}
ex... | the_stack_v2_python_sparse | iframe_api/views.py | A35-Zhou/Rental-House-Manager | train | 0 |
f461c7d0144dcee17906fbafed05a10af8fb7723 | [
"self.interpreter = interpreter\nassert os.path.isfile(interpreter) and os.path.exists(interpreter), \"'%s' is not a valid interpreter path\" % interpreter\nself.paths = paths\nself.flags = flags\nself.environ = environ",
"rt_env = self._runtime_environment(self.paths)\narg_string = ''\nif len(args):\n arg_str... | <|body_start_0|>
self.interpreter = interpreter
assert os.path.isfile(interpreter) and os.path.exists(interpreter), "'%s' is not a valid interpreter path" % interpreter
self.paths = paths
self.flags = flags
self.environ = environ
<|end_body_0|>
<|body_start_1|>
rt_env = ... | For running a maya python interpreter* under controlled conditions: - Override default paths - Overrides environment variables - Disable userSetup.py * Technically this _should_ work for any Python installation, although non-maya versions may not be able to find their standard libraries if these are installed in non-st... | MayaPyManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MayaPyManager:
"""For running a maya python interpreter* under controlled conditions: - Override default paths - Overrides environment variables - Disable userSetup.py * Technically this _should_ work for any Python installation, although non-maya versions may not be able to find their standard l... | stack_v2_sparse_classes_36k_train_000552 | 9,665 | permissive | [
{
"docstring": "Create a MayaPyManager for ths supplied interpreter and paths Arguments: - intepreter is a disk path to a maya python interpreter - environ is a dictionary of environment variables. If no dictionary is provided, intepreter will use os.environ. - paths is an array of strings. It will completely r... | 6 | null | Implement the Python class `MayaPyManager` described below.
Class description:
For running a maya python interpreter* under controlled conditions: - Override default paths - Overrides environment variables - Disable userSetup.py * Technically this _should_ work for any Python installation, although non-maya versions m... | Implement the Python class `MayaPyManager` described below.
Class description:
For running a maya python interpreter* under controlled conditions: - Override default paths - Overrides environment variables - Disable userSetup.py * Technically this _should_ work for any Python installation, although non-maya versions m... | 665d39a2bd82543d5196555f0801ef8fd4a3ee48 | <|skeleton|>
class MayaPyManager:
"""For running a maya python interpreter* under controlled conditions: - Override default paths - Overrides environment variables - Disable userSetup.py * Technically this _should_ work for any Python installation, although non-maya versions may not be able to find their standard l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MayaPyManager:
"""For running a maya python interpreter* under controlled conditions: - Override default paths - Overrides environment variables - Disable userSetup.py * Technically this _should_ work for any Python installation, although non-maya versions may not be able to find their standard libraries if t... | the_stack_v2_python_sparse | dockerized-gists/2c712a91155c7e1c4c15/snippet.py | gistable/gistable | train | 76 |
1ca63ad43b40cf7cde85bc1e26fb8a38c12bc5aa | [
"if not persno:\n from cdb import auth\n persno = auth.persno\nif not Subscription.ByKeys(object_id, persno):\n fields = clss.MakeChangeControlAttributes()\n fields['channel_cdb_object_id'] = object_id\n fields['personalnummer'] = persno\n Subscription.Create(**fields)",
"if not persno:\n fro... | <|body_start_0|>
if not persno:
from cdb import auth
persno = auth.persno
if not Subscription.ByKeys(object_id, persno):
fields = clss.MakeChangeControlAttributes()
fields['channel_cdb_object_id'] = object_id
fields['personalnummer'] = persno
... | Subscription | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Subscription:
def subscribeToChannel(clss, object_id, persno=''):
"""Checks whether there is a subscription entry for the user identified by `persno` or the active user if `persno` is ``None``. If not the entry will be generated."""
<|body_0|>
def unsubscribeFromChannel(clss... | stack_v2_sparse_classes_36k_train_000553 | 19,136 | no_license | [
{
"docstring": "Checks whether there is a subscription entry for the user identified by `persno` or the active user if `persno` is ``None``. If not the entry will be generated.",
"name": "subscribeToChannel",
"signature": "def subscribeToChannel(clss, object_id, persno='')"
},
{
"docstring": "Ch... | 3 | null | Implement the Python class `Subscription` described below.
Class description:
Implement the Subscription class.
Method signatures and docstrings:
- def subscribeToChannel(clss, object_id, persno=''): Checks whether there is a subscription entry for the user identified by `persno` or the active user if `persno` is ``N... | Implement the Python class `Subscription` described below.
Class description:
Implement the Subscription class.
Method signatures and docstrings:
- def subscribeToChannel(clss, object_id, persno=''): Checks whether there is a subscription entry for the user identified by `persno` or the active user if `persno` is ``N... | 6bc932c67bc8d93b873838ae6d9fb8d33c72234d | <|skeleton|>
class Subscription:
def subscribeToChannel(clss, object_id, persno=''):
"""Checks whether there is a subscription entry for the user identified by `persno` or the active user if `persno` is ``None``. If not the entry will be generated."""
<|body_0|>
def unsubscribeFromChannel(clss... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Subscription:
def subscribeToChannel(clss, object_id, persno=''):
"""Checks whether there is a subscription entry for the user identified by `persno` or the active user if `persno` is ``None``. If not the entry will be generated."""
if not persno:
from cdb import auth
p... | the_stack_v2_python_sparse | site-packages/cs.activitystream-15.3.1.4-py2.7.egg/cs/activitystream/objects.py | prachipainuly-rbei/devops-poc | train | 0 | |
447f5b04de5b3b0eb3204f9c86f10d609ea98244 | [
"dummy = ListNode(0)\ndummy.next = head\nfirst = head\nlength = 0\nwhile first:\n first = first.next\n length += 1\nlength -= n\nfirst = dummy\nwhile length:\n length -= 1\n first = first.next\nfirst.next = first.next.next\nreturn dummy.next",
"first = head\nsecond = first\nwhile n:\n n -= 1\n f... | <|body_start_0|>
dummy = ListNode(0)
dummy.next = head
first = head
length = 0
while first:
first = first.next
length += 1
length -= n
first = dummy
while length:
length -= 1
first = first.next
first.... | LinkedList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkedList:
def remove_nth_node_(self, head: 'ListNode', n: int) -> 'ListNode':
"""Approach: Two Pass Time Complexity: O(N) Space Complexity: O(1) :param head: :param n: :return:"""
<|body_0|>
def remove_nth_node(self, head: 'ListNode', n: int) -> 'ListNode':
"""Appr... | stack_v2_sparse_classes_36k_train_000554 | 1,555 | no_license | [
{
"docstring": "Approach: Two Pass Time Complexity: O(N) Space Complexity: O(1) :param head: :param n: :return:",
"name": "remove_nth_node_",
"signature": "def remove_nth_node_(self, head: 'ListNode', n: int) -> 'ListNode'"
},
{
"docstring": "Approach: Single Pass Time Complexity: O(N) Space Com... | 2 | null | Implement the Python class `LinkedList` described below.
Class description:
Implement the LinkedList class.
Method signatures and docstrings:
- def remove_nth_node_(self, head: 'ListNode', n: int) -> 'ListNode': Approach: Two Pass Time Complexity: O(N) Space Complexity: O(1) :param head: :param n: :return:
- def remo... | Implement the Python class `LinkedList` described below.
Class description:
Implement the LinkedList class.
Method signatures and docstrings:
- def remove_nth_node_(self, head: 'ListNode', n: int) -> 'ListNode': Approach: Two Pass Time Complexity: O(N) Space Complexity: O(1) :param head: :param n: :return:
- def remo... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class LinkedList:
def remove_nth_node_(self, head: 'ListNode', n: int) -> 'ListNode':
"""Approach: Two Pass Time Complexity: O(N) Space Complexity: O(1) :param head: :param n: :return:"""
<|body_0|>
def remove_nth_node(self, head: 'ListNode', n: int) -> 'ListNode':
"""Appr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkedList:
def remove_nth_node_(self, head: 'ListNode', n: int) -> 'ListNode':
"""Approach: Two Pass Time Complexity: O(N) Space Complexity: O(1) :param head: :param n: :return:"""
dummy = ListNode(0)
dummy.next = head
first = head
length = 0
while first:
... | the_stack_v2_python_sparse | revisited__2021/linked_list/remove_nth_node_from_end_of_list.py | Shiv2157k/leet_code | train | 1 | |
970f76aece79528ddec4777e1ca655789b89319e | [
"if not prices:\n return 0\nminPirce = prices[0]\nmaxProfit = 0\nfor price in prices[1:]:\n maxProfit = max(maxProfit, price - minPirce)\n minPirce = min(minPirce, price)\nreturn maxProfit",
"if not prices:\n return 0\nsold, hold = (0, -prices[0])\nfor price in prices:\n prev_sold = sold\n prev_... | <|body_start_0|>
if not prices:
return 0
minPirce = prices[0]
maxProfit = 0
for price in prices[1:]:
maxProfit = max(maxProfit, price - minPirce)
minPirce = min(minPirce, price)
return maxProfit
<|end_body_0|>
<|body_start_1|>
if not p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit_121(self, prices: List[int]) -> int:
"""https://leetcode-cn.com/problems/best-time-to-buy-and-sell-stock 给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。 你只能选择 某一天 买入这只股票，并选择在 未来的某一个不同的日子 卖出该股票。设计一个算法来计算你所能获取的最大利润。 返回你可以从这笔交易中获取的最大利润。如果你不能获取任何利润，返回 0 *****解题思路... | stack_v2_sparse_classes_36k_train_000555 | 4,200 | no_license | [
{
"docstring": "https://leetcode-cn.com/problems/best-time-to-buy-and-sell-stock 给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。 你只能选择 某一天 买入这只股票，并选择在 未来的某一个不同的日子 卖出该股票。设计一个算法来计算你所能获取的最大利润。 返回你可以从这笔交易中获取的最大利润。如果你不能获取任何利润，返回 0 *****解题思路****** 假设当前在第 i 天，令 minPrice 表示前 i-1 天的最低价格；令 maxProfit 表示前 i-1 天的最大收益。 ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_121(self, prices: List[int]) -> int: https://leetcode-cn.com/problems/best-time-to-buy-and-sell-stock 给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。 你只能选择 某一天... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_121(self, prices: List[int]) -> int: https://leetcode-cn.com/problems/best-time-to-buy-and-sell-stock 给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。 你只能选择 某一天... | 42fc5de91fa724c901243b1e6bcf5641e03c2791 | <|skeleton|>
class Solution:
def maxProfit_121(self, prices: List[int]) -> int:
"""https://leetcode-cn.com/problems/best-time-to-buy-and-sell-stock 给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。 你只能选择 某一天 买入这只股票，并选择在 未来的某一个不同的日子 卖出该股票。设计一个算法来计算你所能获取的最大利润。 返回你可以从这笔交易中获取的最大利润。如果你不能获取任何利润，返回 0 *****解题思路... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit_121(self, prices: List[int]) -> int:
"""https://leetcode-cn.com/problems/best-time-to-buy-and-sell-stock 给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。 你只能选择 某一天 买入这只股票，并选择在 未来的某一个不同的日子 卖出该股票。设计一个算法来计算你所能获取的最大利润。 返回你可以从这笔交易中获取的最大利润。如果你不能获取任何利润，返回 0 *****解题思路****** 假设当前在第 ... | the_stack_v2_python_sparse | buy_sell_stock/stock_problems.py | tianyunzqs/LeetCodePractise | train | 1 | |
a8d17d8474c2cd59bb8f179790019c23345cd4e9 | [
"map_table = {}\nfor i in range(len(s)):\n a = s[i]\n b = t[i]\n if not map_table.keys().__contains__(a):\n if map_table.values().__contains__(b):\n return False\n map_table[a] = b\n elif map_table[a] != b:\n return False\nprint(map_table)\nreturn True",
"m1 = [0] * 256... | <|body_start_0|>
map_table = {}
for i in range(len(s)):
a = s[i]
b = t[i]
if not map_table.keys().__contains__(a):
if map_table.values().__contains__(b):
return False
map_table[a] = b
elif map_table[a] !=... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isIsomorphic1(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_0|>
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
map_table = {}
for i in ... | stack_v2_sparse_classes_36k_train_000556 | 1,064 | no_license | [
{
"docstring": ":type s: str :type t: str :rtype: bool",
"name": "isIsomorphic1",
"signature": "def isIsomorphic1(self, s, t)"
},
{
"docstring": ":type s: str :type t: str :rtype: bool",
"name": "isIsomorphic",
"signature": "def isIsomorphic(self, s, t)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001043 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isIsomorphic1(self, s, t): :type s: str :type t: str :rtype: bool
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isIsomorphic1(self, s, t): :type s: str :type t: str :rtype: bool
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool
<|skeleton|>
class Solution:
de... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def isIsomorphic1(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_0|>
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isIsomorphic1(self, s, t):
""":type s: str :type t: str :rtype: bool"""
map_table = {}
for i in range(len(s)):
a = s[i]
b = t[i]
if not map_table.keys().__contains__(a):
if map_table.values().__contains__(b):
... | the_stack_v2_python_sparse | python/leetcode/205_Isomorphic_Strings.py | bobcaoge/my-code | train | 0 | |
3bc09cf9ba1759b2ce86e0ec6614c0821f9f04c4 | [
"base_mapping = {1000: 'M', 500: 'D', 100: 'C', 50: 'L', 10: 'X', 5: 'V', 1: 'I'}\nbase = [1000, 500, 100, 50, 10, 5, 1]\nroman = ''\nn = len(base)\nfor i, b in enumerate(base):\n result = num // b\n if result > 0:\n roman += base_mapping[b] * result\n num = num % b\n if num == 0:\n break\... | <|body_start_0|>
base_mapping = {1000: 'M', 500: 'D', 100: 'C', 50: 'L', 10: 'X', 5: 'V', 1: 'I'}
base = [1000, 500, 100, 50, 10, 5, 1]
roman = ''
n = len(base)
for i, b in enumerate(base):
result = num // b
if result > 0:
roman += base_map... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intToRoman(self, num):
""":type num: int :rtype: str"""
<|body_0|>
def intToRoman_opt(self, num):
""":type num: int :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
base_mapping = {1000: 'M', 500: 'D', 100: 'C', 50: 'L', 10:... | stack_v2_sparse_classes_36k_train_000557 | 1,314 | no_license | [
{
"docstring": ":type num: int :rtype: str",
"name": "intToRoman",
"signature": "def intToRoman(self, num)"
},
{
"docstring": ":type num: int :rtype: str",
"name": "intToRoman_opt",
"signature": "def intToRoman_opt(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012257 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intToRoman(self, num): :type num: int :rtype: str
- def intToRoman_opt(self, num): :type num: int :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intToRoman(self, num): :type num: int :rtype: str
- def intToRoman_opt(self, num): :type num: int :rtype: str
<|skeleton|>
class Solution:
def intToRoman(self, num):
... | 84c81fd17c652141d3d194da3481a7241c2accf6 | <|skeleton|>
class Solution:
def intToRoman(self, num):
""":type num: int :rtype: str"""
<|body_0|>
def intToRoman_opt(self, num):
""":type num: int :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def intToRoman(self, num):
""":type num: int :rtype: str"""
base_mapping = {1000: 'M', 500: 'D', 100: 'C', 50: 'L', 10: 'X', 5: 'V', 1: 'I'}
base = [1000, 500, 100, 50, 10, 5, 1]
roman = ''
n = len(base)
for i, b in enumerate(base):
result ... | the_stack_v2_python_sparse | leetcode/12-integer to roman.py | harvey103565/OI-Algorithm-wareh | train | 0 | |
b89cc1a4b7aee8abf2c5c25ddf4889d97bb242cc | [
"mobile = attrs.get('mobile')\nif not re.match('1[3-9]\\\\d{9}$', mobile):\n raise serializers.ValidationError('手机号不合法。')\nif attrs.get('password') != attrs.get('password2'):\n raise serializers.ValidationError('两次输入密码不一致。')\nredis_conn = get_redis_connection('default')\nreal_sms_code = redis_conn.get('sms_%s... | <|body_start_0|>
mobile = attrs.get('mobile')
if not re.match('1[3-9]\\d{9}$', mobile):
raise serializers.ValidationError('手机号不合法。')
if attrs.get('password') != attrs.get('password2'):
raise serializers.ValidationError('两次输入密码不一致。')
redis_conn = get_redis_connecti... | 用户注册序列化器 | UserRegisterSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRegisterSerializer:
"""用户注册序列化器"""
def validate(self, attrs):
"""验证数据 :param attrs: :return:"""
<|body_0|>
def create(self, validated_data):
"""重写父类create方法 :param validated_data: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
mobi... | stack_v2_sparse_classes_36k_train_000558 | 3,402 | no_license | [
{
"docstring": "验证数据 :param attrs: :return:",
"name": "validate",
"signature": "def validate(self, attrs)"
},
{
"docstring": "重写父类create方法 :param validated_data: :return:",
"name": "create",
"signature": "def create(self, validated_data)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000142 | Implement the Python class `UserRegisterSerializer` described below.
Class description:
用户注册序列化器
Method signatures and docstrings:
- def validate(self, attrs): 验证数据 :param attrs: :return:
- def create(self, validated_data): 重写父类create方法 :param validated_data: :return: | Implement the Python class `UserRegisterSerializer` described below.
Class description:
用户注册序列化器
Method signatures and docstrings:
- def validate(self, attrs): 验证数据 :param attrs: :return:
- def create(self, validated_data): 重写父类create方法 :param validated_data: :return:
<|skeleton|>
class UserRegisterSerializer:
"... | c7a57b6ac23885a6db682899d9360017708d084a | <|skeleton|>
class UserRegisterSerializer:
"""用户注册序列化器"""
def validate(self, attrs):
"""验证数据 :param attrs: :return:"""
<|body_0|>
def create(self, validated_data):
"""重写父类create方法 :param validated_data: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserRegisterSerializer:
"""用户注册序列化器"""
def validate(self, attrs):
"""验证数据 :param attrs: :return:"""
mobile = attrs.get('mobile')
if not re.match('1[3-9]\\d{9}$', mobile):
raise serializers.ValidationError('手机号不合法。')
if attrs.get('password') != attrs.get('passwo... | the_stack_v2_python_sparse | backend/backend/apps/users/serializers.py | chenya1123236324/AutomationTestPlat | train | 1 |
707da0130932e982e2f8b26796b7c38235ff10d3 | [
"Thread.__init__(self)\nself.server = server\nself.width = os.get_terminal_size().columns\nself.terminal_size = shutil.get_terminal_size(fallback=(120, 50))",
"while True:\n connection_socket, addr = self.server.server_socket.accept()\n connection_socket.send(('\\n' + PrettyPrint.pretty_print('CONCORD'.cent... | <|body_start_0|>
Thread.__init__(self)
self.server = server
self.width = os.get_terminal_size().columns
self.terminal_size = shutil.get_terminal_size(fallback=(120, 50))
<|end_body_0|>
<|body_start_1|>
while True:
connection_socket, addr = self.server.server_socket.a... | Class of thread responsible for handling incoming users | ControllerConnections | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ControllerConnections:
"""Class of thread responsible for handling incoming users"""
def __init__(self, server) -> None:
"""Initializes the ControllerConnections class instance's attributes :param server: server obj :returns: None"""
<|body_0|>
def run(self) -> None:
... | stack_v2_sparse_classes_36k_train_000559 | 1,771 | permissive | [
{
"docstring": "Initializes the ControllerConnections class instance's attributes :param server: server obj :returns: None",
"name": "__init__",
"signature": "def __init__(self, server) -> None"
},
{
"docstring": "Responsible for running the thread :returns: None",
"name": "run",
"signat... | 2 | null | Implement the Python class `ControllerConnections` described below.
Class description:
Class of thread responsible for handling incoming users
Method signatures and docstrings:
- def __init__(self, server) -> None: Initializes the ControllerConnections class instance's attributes :param server: server obj :returns: N... | Implement the Python class `ControllerConnections` described below.
Class description:
Class of thread responsible for handling incoming users
Method signatures and docstrings:
- def __init__(self, server) -> None: Initializes the ControllerConnections class instance's attributes :param server: server obj :returns: N... | 6720d1789a366bfd7943b81c7c84cb0941c66e80 | <|skeleton|>
class ControllerConnections:
"""Class of thread responsible for handling incoming users"""
def __init__(self, server) -> None:
"""Initializes the ControllerConnections class instance's attributes :param server: server obj :returns: None"""
<|body_0|>
def run(self) -> None:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ControllerConnections:
"""Class of thread responsible for handling incoming users"""
def __init__(self, server) -> None:
"""Initializes the ControllerConnections class instance's attributes :param server: server obj :returns: None"""
Thread.__init__(self)
self.server = server
... | the_stack_v2_python_sparse | src/controllers/controller_connections.py | WebisD/chat-irc-protocol | train | 0 |
07c9fd457e74a8c5c769b629ec0a457a7a27efed | [
"if numRows == 0:\n return []\n\ndef recurse(rows, triangle):\n if rows == 0:\n return triangle\n triangle.append(self.calculate(triangle[-1]))\n return recurse(rows - 1, triangle)\nreturn recurse(numRows - 1, [[1]])",
"if numRows == 0:\n return []\noutput = [[1]]\nfor i in range(numRows - 1... | <|body_start_0|>
if numRows == 0:
return []
def recurse(rows, triangle):
if rows == 0:
return triangle
triangle.append(self.calculate(triangle[-1]))
return recurse(rows - 1, triangle)
return recurse(numRows - 1, [[1]])
<|end_body_0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""Recursive solution"""
<|body_0|>
def generate_iterative(self, numRows: int) -> List[List[int]]:
"""Iterative for-loop solution; O(n) linear time complexity,"""
<|body_1|>
def calculate(sel... | stack_v2_sparse_classes_36k_train_000560 | 1,594 | no_license | [
{
"docstring": "Recursive solution",
"name": "generate",
"signature": "def generate(self, numRows: int) -> List[List[int]]"
},
{
"docstring": "Iterative for-loop solution; O(n) linear time complexity,",
"name": "generate_iterative",
"signature": "def generate_iterative(self, numRows: int... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate(self, numRows: int) -> List[List[int]]: Recursive solution
- def generate_iterative(self, numRows: int) -> List[List[int]]: Iterative for-loop solution; O(n) linear ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate(self, numRows: int) -> List[List[int]]: Recursive solution
- def generate_iterative(self, numRows: int) -> List[List[int]]: Iterative for-loop solution; O(n) linear ... | 286677fc7be84f8f8a8754c785a39d07a2c5604a | <|skeleton|>
class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""Recursive solution"""
<|body_0|>
def generate_iterative(self, numRows: int) -> List[List[int]]:
"""Iterative for-loop solution; O(n) linear time complexity,"""
<|body_1|>
def calculate(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generate(self, numRows: int) -> List[List[int]]:
"""Recursive solution"""
if numRows == 0:
return []
def recurse(rows, triangle):
if rows == 0:
return triangle
triangle.append(self.calculate(triangle[-1]))
r... | the_stack_v2_python_sparse | arrays/pascals-triangle/pascals_triangle.py | mich-chen/code-challenges | train | 3 | |
faa69b4d569abd0831d5c39cc203e7352f3ff2eb | [
"super(RequeueJobsBulk, self).__init__('requeue_jobs_bulk')\nself.current_job_id = None\nself.started = None\nself.ended = None\nself.error_categories = None\nself.error_ids = None\nself.job_ids = None\nself.job_type_ids = None\nself.priority = None\nself.status = None\nself.job_type_names = None\nself.batch_ids = ... | <|body_start_0|>
super(RequeueJobsBulk, self).__init__('requeue_jobs_bulk')
self.current_job_id = None
self.started = None
self.ended = None
self.error_categories = None
self.error_ids = None
self.job_ids = None
self.job_type_ids = None
self.priori... | Command message that performs a bulk re-queue operation | RequeueJobsBulk | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequeueJobsBulk:
"""Command message that performs a bulk re-queue operation"""
def __init__(self):
"""Constructor"""
<|body_0|>
def to_json(self):
"""See :meth:`messaging.messages.message.CommandMessage.to_json`"""
<|body_1|>
def from_json(json_dict)... | stack_v2_sparse_classes_36k_train_000561 | 8,523 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "See :meth:`messaging.messages.message.CommandMessage.to_json`",
"name": "to_json",
"signature": "def to_json(self)"
},
{
"docstring": "See :meth:`messaging.messages.message.Comm... | 4 | null | Implement the Python class `RequeueJobsBulk` described below.
Class description:
Command message that performs a bulk re-queue operation
Method signatures and docstrings:
- def __init__(self): Constructor
- def to_json(self): See :meth:`messaging.messages.message.CommandMessage.to_json`
- def from_json(json_dict): Se... | Implement the Python class `RequeueJobsBulk` described below.
Class description:
Command message that performs a bulk re-queue operation
Method signatures and docstrings:
- def __init__(self): Constructor
- def to_json(self): See :meth:`messaging.messages.message.CommandMessage.to_json`
- def from_json(json_dict): Se... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class RequeueJobsBulk:
"""Command message that performs a bulk re-queue operation"""
def __init__(self):
"""Constructor"""
<|body_0|>
def to_json(self):
"""See :meth:`messaging.messages.message.CommandMessage.to_json`"""
<|body_1|>
def from_json(json_dict)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequeueJobsBulk:
"""Command message that performs a bulk re-queue operation"""
def __init__(self):
"""Constructor"""
super(RequeueJobsBulk, self).__init__('requeue_jobs_bulk')
self.current_job_id = None
self.started = None
self.ended = None
self.error_categ... | the_stack_v2_python_sparse | scale/queue/messages/requeue_jobs_bulk.py | kfconsultant/scale | train | 0 |
26902aa755d009427e4904aaa1f93905bf2e2470 | [
"height = 0\nwhile root:\n height += 1\n root = root.left\nreturn height",
"if not root:\n return 0\nl_h = self.height(root.left)\nr_h = self.height(root.right)\nnodes = 0\nif l_h == r_h:\n nodes = 2 ** l_h - 1 + 1 + self.countNodes(root.right)\nelse:\n nodes = 2 ** r_h - 1 + 1 + self.countNodes(ro... | <|body_start_0|>
height = 0
while root:
height += 1
root = root.left
return height
<|end_body_0|>
<|body_start_1|>
if not root:
return 0
l_h = self.height(root.left)
r_h = self.height(root.right)
nodes = 0
if l_h == r_h... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def height(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
height = 0
while root:
height += ... | stack_v2_sparse_classes_36k_train_000562 | 862 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "height",
"signature": "def height(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "countNodes",
"signature": "def countNodes(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def height(self, root): :type root: TreeNode :rtype: int
- def countNodes(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def height(self, root): :type root: TreeNode :rtype: int
- def countNodes(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def height(self, root):... | 9bd2d706f014ce84356ba38fc7801da0285a91d3 | <|skeleton|>
class Solution:
def height(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def height(self, root):
""":type root: TreeNode :rtype: int"""
height = 0
while root:
height += 1
root = root.left
return height
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
if not root:
re... | the_stack_v2_python_sparse | leetcode/countNodes-222.py | pittcat/Algorithm_Practice | train | 0 | |
4bccc69ad21ca874c6040662089e9b4790183327 | [
"self.bnet = bnet\nself.do_print = do_print\nself.is_quantum = is_quantum",
"story_line = ''\nfor node in annotated_story.keys():\n story_line += node.name + '='\n story_line += str(annotated_story[node]) + ', '\nprint(story_line[:-2])"
] | <|body_start_0|>
self.bnet = bnet
self.do_print = do_print
self.is_quantum = is_quantum
<|end_body_0|>
<|body_start_1|>
story_line = ''
for node in annotated_story.keys():
story_line += node.name + '='
story_line += str(annotated_story[node]) + ', '
... | This is the parent class of all inference engines. Attributes ---------- bnet : BayesNet do_print : bool is_quantum : bool | InferenceEngine | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InferenceEngine:
"""This is the parent class of all inference engines. Attributes ---------- bnet : BayesNet do_print : bool is_quantum : bool"""
def __init__(self, bnet, do_print=False, is_quantum=False):
"""Constructor Parameters ---------- bnet : BayesNet do_print : bool is_quantu... | stack_v2_sparse_classes_36k_train_000563 | 1,264 | permissive | [
{
"docstring": "Constructor Parameters ---------- bnet : BayesNet do_print : bool is_quantum : bool Returns -------",
"name": "__init__",
"signature": "def __init__(self, bnet, do_print=False, is_quantum=False)"
},
{
"docstring": "Prints in a pretty way an annotated story, which is a dictionary ... | 2 | stack_v2_sparse_classes_30k_val_001094 | Implement the Python class `InferenceEngine` described below.
Class description:
This is the parent class of all inference engines. Attributes ---------- bnet : BayesNet do_print : bool is_quantum : bool
Method signatures and docstrings:
- def __init__(self, bnet, do_print=False, is_quantum=False): Constructor Parame... | Implement the Python class `InferenceEngine` described below.
Class description:
This is the parent class of all inference engines. Attributes ---------- bnet : BayesNet do_print : bool is_quantum : bool
Method signatures and docstrings:
- def __init__(self, bnet, do_print=False, is_quantum=False): Constructor Parame... | 92e1d2a38de92422642545623341ecd9cfb7a39f | <|skeleton|>
class InferenceEngine:
"""This is the parent class of all inference engines. Attributes ---------- bnet : BayesNet do_print : bool is_quantum : bool"""
def __init__(self, bnet, do_print=False, is_quantum=False):
"""Constructor Parameters ---------- bnet : BayesNet do_print : bool is_quantu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InferenceEngine:
"""This is the parent class of all inference engines. Attributes ---------- bnet : BayesNet do_print : bool is_quantum : bool"""
def __init__(self, bnet, do_print=False, is_quantum=False):
"""Constructor Parameters ---------- bnet : BayesNet do_print : bool is_quantum : bool Retu... | the_stack_v2_python_sparse | inference/InferenceEngine.py | Statici/quantum-fog | train | 2 |
c40b0c63acda4376adc692aefdcf5468ef603442 | [
"progress_bar = ProgressBar(spinnman_constants.MAX_TAG_ID, 'Clearing tags')\nfor tag_id in range(spinnman_constants.MAX_TAG_ID):\n transceiver.clear_ip_tag(tag_id)\n progress_bar.update()\nprogress_bar.end()\nprogress_bar = None\nif tags is not None:\n progress_bar = ProgressBar(len(list(tags.ip_tags)) + l... | <|body_start_0|>
progress_bar = ProgressBar(spinnman_constants.MAX_TAG_ID, 'Clearing tags')
for tag_id in range(spinnman_constants.MAX_TAG_ID):
transceiver.clear_ip_tag(tag_id)
progress_bar.update()
progress_bar.end()
progress_bar = None
if tags is not Non... | Loads tags onto the machine | FrontEndCommonTagsLoader | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrontEndCommonTagsLoader:
"""Loads tags onto the machine"""
def __call__(self, transceiver, tags=None, iptags=None, reverse_iptags=None):
""":param tags: the tags object which contains ip and reverse ip tags. could be none if these are being given in separate lists :param iptags: a l... | stack_v2_sparse_classes_36k_train_000564 | 2,725 | permissive | [
{
"docstring": ":param tags: the tags object which contains ip and reverse ip tags. could be none if these are being given in separate lists :param iptags: a list of iptags, given when tags is none :param reverse_iptags: a list of reverse iptags when tags is none. :param transceiver: the transceiver object :ret... | 3 | stack_v2_sparse_classes_30k_train_004424 | Implement the Python class `FrontEndCommonTagsLoader` described below.
Class description:
Loads tags onto the machine
Method signatures and docstrings:
- def __call__(self, transceiver, tags=None, iptags=None, reverse_iptags=None): :param tags: the tags object which contains ip and reverse ip tags. could be none if t... | Implement the Python class `FrontEndCommonTagsLoader` described below.
Class description:
Loads tags onto the machine
Method signatures and docstrings:
- def __call__(self, transceiver, tags=None, iptags=None, reverse_iptags=None): :param tags: the tags object which contains ip and reverse ip tags. could be none if t... | 04fa1eaf78778edea3ba3afa4c527d20c491718e | <|skeleton|>
class FrontEndCommonTagsLoader:
"""Loads tags onto the machine"""
def __call__(self, transceiver, tags=None, iptags=None, reverse_iptags=None):
""":param tags: the tags object which contains ip and reverse ip tags. could be none if these are being given in separate lists :param iptags: a l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FrontEndCommonTagsLoader:
"""Loads tags onto the machine"""
def __call__(self, transceiver, tags=None, iptags=None, reverse_iptags=None):
""":param tags: the tags object which contains ip and reverse ip tags. could be none if these are being given in separate lists :param iptags: a list of iptags... | the_stack_v2_python_sparse | src/spinnaker_ros_lsm/venv/lib/python2.7/site-packages/spinn_front_end_common/interface/interface_functions/front_end_common_tags_loader.py | Roboy/LSM_SpiNNaker_MyoArm | train | 2 |
f8357c6e6d0b5a278efeee7f08179a117e68be88 | [
"self.big = big\nself.medium = medium\nself.small = small",
"if carType == 1:\n self.big = self.big - 1\n if self.big >= 0:\n return True\n else:\n return False\nelif carType == 2:\n self.medium = self.medium - 1\n if self.medium >= 0:\n return True\n else:\n return F... | <|body_start_0|>
self.big = big
self.medium = medium
self.small = small
<|end_body_0|>
<|body_start_1|>
if carType == 1:
self.big = self.big - 1
if self.big >= 0:
return True
else:
return False
elif carType == 2... | ParkingSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
<|body_0|>
def addCar(self, carType):
""":type carType: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.big = big
... | stack_v2_sparse_classes_36k_train_000565 | 1,839 | no_license | [
{
"docstring": ":type big: int :type medium: int :type small: int",
"name": "__init__",
"signature": "def __init__(self, big, medium, small)"
},
{
"docstring": ":type carType: int :rtype: bool",
"name": "addCar",
"signature": "def addCar(self, carType)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000504 | Implement the Python class `ParkingSystem` described below.
Class description:
Implement the ParkingSystem class.
Method signatures and docstrings:
- def __init__(self, big, medium, small): :type big: int :type medium: int :type small: int
- def addCar(self, carType): :type carType: int :rtype: bool | Implement the Python class `ParkingSystem` described below.
Class description:
Implement the ParkingSystem class.
Method signatures and docstrings:
- def __init__(self, big, medium, small): :type big: int :type medium: int :type small: int
- def addCar(self, carType): :type carType: int :rtype: bool
<|skeleton|>
cla... | 6d6afba93d20665d033fe542c97e3eb50368bd3c | <|skeleton|>
class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
<|body_0|>
def addCar(self, carType):
""":type carType: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
self.big = big
self.medium = medium
self.small = small
def addCar(self, carType):
""":type carType: int :rtype: bool"""
if carType == 1:
... | the_stack_v2_python_sparse | design_parking_system.py | naomi397liu/AlgorithmPactice | train | 1 | |
ef9af024a00c829bfb773d16dea0cd6cbb8fd4ee | [
"course_keys = value\nfor course in course_keys:\n try:\n CourseKey.from_string(course)\n except InvalidKeyError:\n raise serializers.ValidationError(f'Course key not valid: {course}')\nreturn value",
"if attrs.get('cohorts'):\n if attrs['action'] != 'enroll':\n raise serializers.Val... | <|body_start_0|>
course_keys = value
for course in course_keys:
try:
CourseKey.from_string(course)
except InvalidKeyError:
raise serializers.ValidationError(f'Course key not valid: {course}')
return value
<|end_body_0|>
<|body_start_1|>
... | Serializes enrollment information for a collection of students/emails. This is mainly useful for implementing validation when performing bulk enrollment operations. | BulkEnrollmentSerializer | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BulkEnrollmentSerializer:
"""Serializes enrollment information for a collection of students/emails. This is mainly useful for implementing validation when performing bulk enrollment operations."""
def validate_courses(self, value):
"""Check that each course key in list is valid."""
... | stack_v2_sparse_classes_36k_train_000566 | 2,612 | permissive | [
{
"docstring": "Check that each course key in list is valid.",
"name": "validate_courses",
"signature": "def validate_courses(self, value)"
},
{
"docstring": "Check that the cohorts list is the same size as the courses list.",
"name": "validate",
"signature": "def validate(self, attrs)"
... | 2 | stack_v2_sparse_classes_30k_train_003975 | Implement the Python class `BulkEnrollmentSerializer` described below.
Class description:
Serializes enrollment information for a collection of students/emails. This is mainly useful for implementing validation when performing bulk enrollment operations.
Method signatures and docstrings:
- def validate_courses(self, ... | Implement the Python class `BulkEnrollmentSerializer` described below.
Class description:
Serializes enrollment information for a collection of students/emails. This is mainly useful for implementing validation when performing bulk enrollment operations.
Method signatures and docstrings:
- def validate_courses(self, ... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class BulkEnrollmentSerializer:
"""Serializes enrollment information for a collection of students/emails. This is mainly useful for implementing validation when performing bulk enrollment operations."""
def validate_courses(self, value):
"""Check that each course key in list is valid."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BulkEnrollmentSerializer:
"""Serializes enrollment information for a collection of students/emails. This is mainly useful for implementing validation when performing bulk enrollment operations."""
def validate_courses(self, value):
"""Check that each course key in list is valid."""
course... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/lms/djangoapps/bulk_enroll/serializers.py | luque/better-ways-of-thinking-about-software | train | 3 |
39db05e5f8928b1e9f0f42edcd2e27b1fcd61565 | [
"new_ml_model = Project()\nnew_ml_model.create(dto)\nif dto.users:\n ProjectAccess.list_update(new_ml_model.id, [], dto.users)\nreturn new_ml_model.id",
"ml_model = Project.get(model_id)\nif ml_model:\n ml_model.delete()\nelse:\n raise NotFound('Model does not exist')",
"ml_model = Project.get(model_id... | <|body_start_0|>
new_ml_model = Project()
new_ml_model.create(dto)
if dto.users:
ProjectAccess.list_update(new_ml_model.id, [], dto.users)
return new_ml_model.id
<|end_body_0|>
<|body_start_1|>
ml_model = Project.get(model_id)
if ml_model:
ml_mode... | ProjectService | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectService:
def subscribe_ml_model(dto: ProjectDTO) -> int:
"""Subscribes an ML Model by saving it in the database :params dto :raises DataError :returns ID of the ml model"""
<|body_0|>
def delete_ml_model(model_id: int):
"""Deletes ML model and associated predi... | stack_v2_sparse_classes_36k_train_000567 | 2,737 | permissive | [
{
"docstring": "Subscribes an ML Model by saving it in the database :params dto :raises DataError :returns ID of the ml model",
"name": "subscribe_ml_model",
"signature": "def subscribe_ml_model(dto: ProjectDTO) -> int"
},
{
"docstring": "Deletes ML model and associated predictions :params model... | 5 | null | Implement the Python class `ProjectService` described below.
Class description:
Implement the ProjectService class.
Method signatures and docstrings:
- def subscribe_ml_model(dto: ProjectDTO) -> int: Subscribes an ML Model by saving it in the database :params dto :raises DataError :returns ID of the ml model
- def de... | Implement the Python class `ProjectService` described below.
Class description:
Implement the ProjectService class.
Method signatures and docstrings:
- def subscribe_ml_model(dto: ProjectDTO) -> int: Subscribes an ML Model by saving it in the database :params dto :raises DataError :returns ID of the ml model
- def de... | cff1b5955c6f110e64489427dfb8902d442a0e62 | <|skeleton|>
class ProjectService:
def subscribe_ml_model(dto: ProjectDTO) -> int:
"""Subscribes an ML Model by saving it in the database :params dto :raises DataError :returns ID of the ml model"""
<|body_0|>
def delete_ml_model(model_id: int):
"""Deletes ML model and associated predi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectService:
def subscribe_ml_model(dto: ProjectDTO) -> int:
"""Subscribes an ML Model by saving it in the database :params dto :raises DataError :returns ID of the ml model"""
new_ml_model = Project()
new_ml_model.create(dto)
if dto.users:
ProjectAccess.list_upd... | the_stack_v2_python_sparse | ml_enabler/services/project_service.py | rustyb/ml-enabler | train | 0 | |
aee5f921b197272216abd6db0f4c73ae10077b7f | [
"for j in range(len(nums)):\n for k in range(j + 1, len(nums)):\n if nums[j] + nums[k] == target:\n return (j, k)",
"memo = {}\nfor i in range(len(nums)):\n if nums[i] in memo:\n return (memo[nums[i]], i)\n elif target - nums[i] not in memo:\n memo[target - nums[i]] = i"
] | <|body_start_0|>
for j in range(len(nums)):
for k in range(j + 1, len(nums)):
if nums[j] + nums[k] == target:
return (j, k)
<|end_body_0|>
<|body_start_1|>
memo = {}
for i in range(len(nums)):
if nums[i] in memo:
return... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_000568 | 1,211 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum2",
"signature": "def twoSum2(self, nums, target)"
}... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSum2(self, nums, target): :type nums: List[int] :type target: int :rtype: List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSum2(self, nums, target): :type nums: List[int] :type target: int :rtype: List[... | af3b19adefb31ea17fa8096eb03a77634795a807 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
for j in range(len(nums)):
for k in range(j + 1, len(nums)):
if nums[j] + nums[k] == target:
return (j, k)
def twoSum2(self, nums, targ... | the_stack_v2_python_sparse | ib/5.Hashing/LC001. Two Sum.py | qq279585876/algorithm | train | 0 | |
75fb30c209f4171b12406183cba2682d00fa0e56 | [
"origin_country_id = self._context.get('origin_country_ept', False)\nif not origin_country_id:\n return super(AccountFiscalPosition, self)._get_fpos_by_region(country_id=country_id, state_id=state_id, zipcode=zipcode, vat_required=vat_required)\nreturn self.search_fiscal_position_based_on_origin_country(origin_c... | <|body_start_0|>
origin_country_id = self._context.get('origin_country_ept', False)
if not origin_country_id:
return super(AccountFiscalPosition, self)._get_fpos_by_region(country_id=country_id, state_id=state_id, zipcode=zipcode, vat_required=vat_required)
return self.search_fiscal_... | AccountFiscalPosition | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountFiscalPosition:
def _get_fpos_by_region(self, country_id=False, state_id=False, zipcode=False, vat_required=False):
"""Inherited this method for selecting fiscal position based on warehouse (origin country). @param country_id: @param state_id: @param zipcode: @param vat_required: ... | stack_v2_sparse_classes_36k_train_000569 | 2,584 | no_license | [
{
"docstring": "Inherited this method for selecting fiscal position based on warehouse (origin country). @param country_id: @param state_id: @param zipcode: @param vat_required: @return:",
"name": "_get_fpos_by_region",
"signature": "def _get_fpos_by_region(self, country_id=False, state_id=False, zipcod... | 2 | stack_v2_sparse_classes_30k_train_000180 | Implement the Python class `AccountFiscalPosition` described below.
Class description:
Implement the AccountFiscalPosition class.
Method signatures and docstrings:
- def _get_fpos_by_region(self, country_id=False, state_id=False, zipcode=False, vat_required=False): Inherited this method for selecting fiscal position ... | Implement the Python class `AccountFiscalPosition` described below.
Class description:
Implement the AccountFiscalPosition class.
Method signatures and docstrings:
- def _get_fpos_by_region(self, country_id=False, state_id=False, zipcode=False, vat_required=False): Inherited this method for selecting fiscal position ... | 581b23342122c0568407c1c42efd4b2085719335 | <|skeleton|>
class AccountFiscalPosition:
def _get_fpos_by_region(self, country_id=False, state_id=False, zipcode=False, vat_required=False):
"""Inherited this method for selecting fiscal position based on warehouse (origin country). @param country_id: @param state_id: @param zipcode: @param vat_required: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountFiscalPosition:
def _get_fpos_by_region(self, country_id=False, state_id=False, zipcode=False, vat_required=False):
"""Inherited this method for selecting fiscal position based on warehouse (origin country). @param country_id: @param state_id: @param zipcode: @param vat_required: @return:"""
... | the_stack_v2_python_sparse | modules/common_connector_library/models/account_fiscal_position.py | yspcn/odoo14-import | train | 0 | |
da870b8b761d45d90f2b88d06d0fd53082368f15 | [
"assert alpha >= 0\nsuper(PrioritizedReplayBuffer, self).__init__(size, batch_size, n_step, gamma)\nself.max_priority, self.tree_ptr = (1.0, 0)\nself.alpha = alpha\ntree_capacity = 1\nwhile tree_capacity < self.max_size:\n tree_capacity *= 2\nself.sum_tree = SumSegmentTree(tree_capacity)\nself.min_tree = MinSegm... | <|body_start_0|>
assert alpha >= 0
super(PrioritizedReplayBuffer, self).__init__(size, batch_size, n_step, gamma)
self.max_priority, self.tree_ptr = (1.0, 0)
self.alpha = alpha
tree_capacity = 1
while tree_capacity < self.max_size:
tree_capacity *= 2
s... | Prioritized Replay buffer. Attributes: max_priority (float): max priority tree_ptr (int): next index of tree alpha (float): alpha parameter for prioritized replay buffer sum_tree (SumSegmentTree): sum tree for prior min_tree (MinSegmentTree): min tree for min prior to get max weight | PrioritizedReplayBuffer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrioritizedReplayBuffer:
"""Prioritized Replay buffer. Attributes: max_priority (float): max priority tree_ptr (int): next index of tree alpha (float): alpha parameter for prioritized replay buffer sum_tree (SumSegmentTree): sum tree for prior min_tree (MinSegmentTree): min tree for min prior to ... | stack_v2_sparse_classes_36k_train_000570 | 26,535 | no_license | [
{
"docstring": "Initialization.",
"name": "__init__",
"signature": "def __init__(self, size: int, batch_size: int=32, alpha: float=0.6, n_step: int=1, gamma: float=0.99)"
},
{
"docstring": "Store experience and priority.",
"name": "store",
"signature": "def store(self, obs: OdinsynthEnvS... | 6 | stack_v2_sparse_classes_30k_train_003501 | Implement the Python class `PrioritizedReplayBuffer` described below.
Class description:
Prioritized Replay buffer. Attributes: max_priority (float): max priority tree_ptr (int): next index of tree alpha (float): alpha parameter for prioritized replay buffer sum_tree (SumSegmentTree): sum tree for prior min_tree (MinS... | Implement the Python class `PrioritizedReplayBuffer` described below.
Class description:
Prioritized Replay buffer. Attributes: max_priority (float): max priority tree_ptr (int): next index of tree alpha (float): alpha parameter for prioritized replay buffer sum_tree (SumSegmentTree): sum tree for prior min_tree (MinS... | 60e0c3389724460b5b32ba35c89d8838da4d51c9 | <|skeleton|>
class PrioritizedReplayBuffer:
"""Prioritized Replay buffer. Attributes: max_priority (float): max priority tree_ptr (int): next index of tree alpha (float): alpha parameter for prioritized replay buffer sum_tree (SumSegmentTree): sum tree for prior min_tree (MinSegmentTree): min tree for min prior to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrioritizedReplayBuffer:
"""Prioritized Replay buffer. Attributes: max_priority (float): max priority tree_ptr (int): next index of tree alpha (float): alpha parameter for prioritized replay buffer sum_tree (SumSegmentTree): sum tree for prior min_tree (MinSegmentTree): min tree for min prior to get max weigh... | the_stack_v2_python_sparse | lrec2022-odinsynth/python/rl_rainbow_implementation.py | clulab/releases | train | 29 |
6c7ddd7f616d26e75fa33a900a13ca836a3416ad | [
"end_date = dateutil.get_today()\nstart_date = dateutil.get_previous_date(end_date, 6)\nc = RequestContext(request, {'first_nav_name': FIRST_NAV, 'app_name': 'stats', 'second_navs': export.get_stats_second_navs(request), 'second_nav_name': export.STATS_SALES_SECOND_NAV, 'third_nav_name': export.SALES_ORDER_SUMMARY_... | <|body_start_0|>
end_date = dateutil.get_today()
start_date = dateutil.get_previous_date(end_date, 6)
c = RequestContext(request, {'first_nav_name': FIRST_NAV, 'app_name': 'stats', 'second_navs': export.get_stats_second_navs(request), 'second_nav_name': export.STATS_SALES_SECOND_NAV, 'third_nav_... | 订单概况 | OrderSummary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderSummary:
"""订单概况"""
def get(request):
"""显示订单概况"""
<|body_0|>
def api_get(request):
"""获取订单概况数据"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
end_date = dateutil.get_today()
start_date = dateutil.get_previous_date(end_date, 6)
... | stack_v2_sparse_classes_36k_train_000571 | 19,458 | no_license | [
{
"docstring": "显示订单概况",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "获取订单概况数据",
"name": "api_get",
"signature": "def api_get(request)"
}
] | 2 | null | Implement the Python class `OrderSummary` described below.
Class description:
订单概况
Method signatures and docstrings:
- def get(request): 显示订单概况
- def api_get(request): 获取订单概况数据 | Implement the Python class `OrderSummary` described below.
Class description:
订单概况
Method signatures and docstrings:
- def get(request): 显示订单概况
- def api_get(request): 获取订单概况数据
<|skeleton|>
class OrderSummary:
"""订单概况"""
def get(request):
"""显示订单概况"""
<|body_0|>
def api_get(request):
... | 8b2f7befe92841bcc35e0e60cac5958ef3f3af54 | <|skeleton|>
class OrderSummary:
"""订单概况"""
def get(request):
"""显示订单概况"""
<|body_0|>
def api_get(request):
"""获取订单概况数据"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderSummary:
"""订单概况"""
def get(request):
"""显示订单概况"""
end_date = dateutil.get_today()
start_date = dateutil.get_previous_date(end_date, 6)
c = RequestContext(request, {'first_nav_name': FIRST_NAV, 'app_name': 'stats', 'second_navs': export.get_stats_second_navs(request),... | the_stack_v2_python_sparse | weapp/stats/sales/order_summary.py | chengdg/weizoom | train | 1 |
ef89d1ecbeef51897ed5c1ad374848730ec3d2eb | [
"data_course = request.data\nauth_token = request.headers['Authorization'][6:]\nuser = YouYodaUser.objects.get(auth_token=auth_token)\ncourse = Courses.objects.get(id=data_course['course_id'])\ndata_course['participant_id'] = user.id\ndata_course['course_id'] = course.id\ncourse_add = CoursesSubscribers.objects.fil... | <|body_start_0|>
data_course = request.data
auth_token = request.headers['Authorization'][6:]
user = YouYodaUser.objects.get(auth_token=auth_token)
course = Courses.objects.get(id=data_course['course_id'])
data_course['participant_id'] = user.id
data_course['course_id'] =... | Takes data from CoursesSubscribersPostSerializator for add user to course | UserSubscribeToCourse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSubscribeToCourse:
"""Takes data from CoursesSubscribersPostSerializator for add user to course"""
def post(self, request):
"""Push user, course to db with CoursesSubscribersPostSerializator"""
<|body_0|>
def get(self, request):
"""Receives and transmits user... | stack_v2_sparse_classes_36k_train_000572 | 5,378 | no_license | [
{
"docstring": "Push user, course to db with CoursesSubscribersPostSerializator",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "Receives and transmits user course data and schedule data about these courses",
"name": "get",
"signature": "def get(self, request)"... | 4 | stack_v2_sparse_classes_30k_train_009956 | Implement the Python class `UserSubscribeToCourse` described below.
Class description:
Takes data from CoursesSubscribersPostSerializator for add user to course
Method signatures and docstrings:
- def post(self, request): Push user, course to db with CoursesSubscribersPostSerializator
- def get(self, request): Receiv... | Implement the Python class `UserSubscribeToCourse` described below.
Class description:
Takes data from CoursesSubscribersPostSerializator for add user to course
Method signatures and docstrings:
- def post(self, request): Push user, course to db with CoursesSubscribersPostSerializator
- def get(self, request): Receiv... | 62b4f1cc79b4c71cc44bb741fb20af066c7023a5 | <|skeleton|>
class UserSubscribeToCourse:
"""Takes data from CoursesSubscribersPostSerializator for add user to course"""
def post(self, request):
"""Push user, course to db with CoursesSubscribersPostSerializator"""
<|body_0|>
def get(self, request):
"""Receives and transmits user... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserSubscribeToCourse:
"""Takes data from CoursesSubscribersPostSerializator for add user to course"""
def post(self, request):
"""Push user, course to db with CoursesSubscribersPostSerializator"""
data_course = request.data
auth_token = request.headers['Authorization'][6:]
... | the_stack_v2_python_sparse | backend/appsrc/views/user_subscribe_to_course.py | OleksandrHavrylchyk/YouYoda | train | 0 |
ce37bfb51b8ee9a419a980b6ebf21d6be9122366 | [
"vowels = 'aeiouAEIOU'\nli = list(a)\ni = 0\nj = len(li) - 1\nwhile i < j:\n if li[i] in vowels and li[j] in vowels:\n li[i], li[j] = (li[j], li[i])\n i += 1\n j -= 1\n elif li[i] in vowels and li[j] not in vowels:\n j -= 1\n else:\n i += 1\nreturn ''.join(li)",
"li = '... | <|body_start_0|>
vowels = 'aeiouAEIOU'
li = list(a)
i = 0
j = len(li) - 1
while i < j:
if li[i] in vowels and li[j] in vowels:
li[i], li[j] = (li[j], li[i])
i += 1
j -= 1
elif li[i] in vowels and li[j] not in... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseVowels(self, a):
""":type s: str :rtype: str"""
<|body_0|>
def reverseVowels(self, a):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
vowels = 'aeiouAEIOU'
li = list(a)
i = 0
... | stack_v2_sparse_classes_36k_train_000573 | 1,503 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "reverseVowels",
"signature": "def reverseVowels(self, a)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "reverseVowels",
"signature": "def reverseVowels(self, a)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseVowels(self, a): :type s: str :rtype: str
- def reverseVowels(self, a): :type s: str :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseVowels(self, a): :type s: str :rtype: str
- def reverseVowels(self, a): :type s: str :rtype: str
<|skeleton|>
class Solution:
def reverseVowels(self, a):
... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def reverseVowels(self, a):
""":type s: str :rtype: str"""
<|body_0|>
def reverseVowels(self, a):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseVowels(self, a):
""":type s: str :rtype: str"""
vowels = 'aeiouAEIOU'
li = list(a)
i = 0
j = len(li) - 1
while i < j:
if li[i] in vowels and li[j] in vowels:
li[i], li[j] = (li[j], li[i])
i += 1
... | the_stack_v2_python_sparse | 0345_Reverse_Vowels_of_a_String.py | bingli8802/leetcode | train | 0 | |
672074117f60aa2cf181251521ec8d928efb1360 | [
"heap = [-t for t in target]\nheapify(heap)\ns = sum(target)\nwhile len(heap) > 0:\n t = -heap[0]\n if t == 1:\n break\n old = t - (s - t)\n s -= t - old\n if old < 1:\n return False\n heapreplace(heap, -old)\nreturn True",
"s = len(target) - 1\nv = set()\nfor t in target:\n if ... | <|body_start_0|>
heap = [-t for t in target]
heapify(heap)
s = sum(target)
while len(heap) > 0:
t = -heap[0]
if t == 1:
break
old = t - (s - t)
s -= t - old
if old < 1:
return False
he... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPossible(self, target: [int]) -> bool:
"""To construct a list of all 1's, we need to find the max elements `m`, and replace it with `m-(sum-m)`. We can use heap to speed up this process."""
<|body_0|>
def isPossible0(self, target: [int]) -> bool:
"""O... | stack_v2_sparse_classes_36k_train_000574 | 1,744 | permissive | [
{
"docstring": "To construct a list of all 1's, we need to find the max elements `m`, and replace it with `m-(sum-m)`. We can use heap to speed up this process.",
"name": "isPossible",
"signature": "def isPossible(self, target: [int]) -> bool"
},
{
"docstring": "Original solution We first check ... | 2 | stack_v2_sparse_classes_30k_train_000756 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPossible(self, target: [int]) -> bool: To construct a list of all 1's, we need to find the max elements `m`, and replace it with `m-(sum-m)`. We can use heap to speed up th... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPossible(self, target: [int]) -> bool: To construct a list of all 1's, we need to find the max elements `m`, and replace it with `m-(sum-m)`. We can use heap to speed up th... | 58974b6e661101686eeab357dcf6821cf7b51064 | <|skeleton|>
class Solution:
def isPossible(self, target: [int]) -> bool:
"""To construct a list of all 1's, we need to find the max elements `m`, and replace it with `m-(sum-m)`. We can use heap to speed up this process."""
<|body_0|>
def isPossible0(self, target: [int]) -> bool:
"""O... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPossible(self, target: [int]) -> bool:
"""To construct a list of all 1's, we need to find the max elements `m`, and replace it with `m-(sum-m)`. We can use heap to speed up this process."""
heap = [-t for t in target]
heapify(heap)
s = sum(target)
while ... | the_stack_v2_python_sparse | practice/weekly-contest-176/construct-target-array-with-multiple-sums.py | yangtau/algorithms-practice | train | 1 | |
9f63011c1fc6009bfef6603fc54d9d310ea9d3e5 | [
"super().__init__(default_factory)\nself.connection = connect(GUNGAME_DATA_PATH / 'winners.db')\nself.connection.text_factory = str\nself.cursor = self.connection.cursor()\nself.cursor.execute('CREATE TABLE IF NOT EXISTS gungame_winners(unique_id varchar(20), name varchar(31), wins varchar(10) DEFAULT 0, time_stamp... | <|body_start_0|>
super().__init__(default_factory)
self.connection = connect(GUNGAME_DATA_PATH / 'winners.db')
self.connection.text_factory = str
self.cursor = self.connection.cursor()
self.cursor.execute('CREATE TABLE IF NOT EXISTS gungame_winners(unique_id varchar(20), name var... | Database to store player wins. | _WinsDatabase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _WinsDatabase:
"""Database to store player wins."""
def __init__(self, default_factory):
"""Create the dictionary and gather any stored values."""
<|body_0|>
def load_database(self):
"""Fill the dictionary with the data from the stored database."""
<|body... | stack_v2_sparse_classes_36k_train_000575 | 5,149 | no_license | [
{
"docstring": "Create the dictionary and gather any stored values.",
"name": "__init__",
"signature": "def __init__(self, default_factory)"
},
{
"docstring": "Fill the dictionary with the data from the stored database.",
"name": "load_database",
"signature": "def load_database(self)"
... | 4 | stack_v2_sparse_classes_30k_train_001010 | Implement the Python class `_WinsDatabase` described below.
Class description:
Database to store player wins.
Method signatures and docstrings:
- def __init__(self, default_factory): Create the dictionary and gather any stored values.
- def load_database(self): Fill the dictionary with the data from the stored databa... | Implement the Python class `_WinsDatabase` described below.
Class description:
Database to store player wins.
Method signatures and docstrings:
- def __init__(self, default_factory): Create the dictionary and gather any stored values.
- def load_database(self): Fill the dictionary with the data from the stored databa... | dd76d1f581a1a8aff18c2194834665fa66a82aab | <|skeleton|>
class _WinsDatabase:
"""Database to store player wins."""
def __init__(self, default_factory):
"""Create the dictionary and gather any stored values."""
<|body_0|>
def load_database(self):
"""Fill the dictionary with the data from the stored database."""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _WinsDatabase:
"""Database to store player wins."""
def __init__(self, default_factory):
"""Create the dictionary and gather any stored values."""
super().__init__(default_factory)
self.connection = connect(GUNGAME_DATA_PATH / 'winners.db')
self.connection.text_factory = s... | the_stack_v2_python_sparse | addons/source-python/plugins/gungame/core/players/database.py | Hackmastr/GunGame-SP | train | 0 |
803ab85ac425511dcee71923e21499053c053a5d | [
"self.matrix = matrix\nself.prefix_sum = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]\nfor i in range(len(matrix)):\n for j in range(len(matrix[0])):\n if i == 0:\n self.prefix_sum[i][j] = matrix[i][j]\n else:\n self.prefix_sum[i][j] = matrix[i][j] + self.p... | <|body_start_0|>
self.matrix = matrix
self.prefix_sum = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]
for i in range(len(matrix)):
for j in range(len(matrix[0])):
if i == 0:
self.prefix_sum[i][j] = matrix[i][j]
el... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def update(self, row, col, val):
""":type row: int :type col: int :type val: int :rtype: void"""
<|body_1|>
def sumRegion(self, row1, col1, row2, col2):
""":typ... | stack_v2_sparse_classes_36k_train_000576 | 16,103 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row: int :type col: int :type val: int :rtype: void",
"name": "update",
"signature": "def update(self, row, col, val)"
},
{
"docstring": ":type r... | 3 | null | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def update(self, row, col, val): :type row: int :type col: int :type val: int :rtype: void
- def sumRegion(self, row... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def update(self, row, col, val): :type row: int :type col: int :type val: int :rtype: void
- def sumRegion(self, row... | fa3704af37d9e04ab6fd13b7b17cc83c239946f7 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def update(self, row, col, val):
""":type row: int :type col: int :type val: int :rtype: void"""
<|body_1|>
def sumRegion(self, row1, col1, row2, col2):
""":typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
self.matrix = matrix
self.prefix_sum = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]
for i in range(len(matrix)):
for j in range(len(matrix[0])):
if i == 0:... | the_stack_v2_python_sparse | lintcode/medium/817_range_sum_query_2d_mutable.py | simonfqy/SimonfqyGitHub | train | 2 | |
de852b6b8894290405d2c0c75fb2b6aec7fe09a0 | [
"self.model = model\nself.learning_rate = learning_rate\nself.momentum = momentum\nself.type = 'SGD'\nself.old_gradients = [[] for _ in range(len(self.model.layers))]",
"for i, l in enumerate(self.model.layers):\n if isinstance(l, TrainableModule):\n current_old_grad = [l.weights_gradient, l.bias_gradie... | <|body_start_0|>
self.model = model
self.learning_rate = learning_rate
self.momentum = momentum
self.type = 'SGD'
self.old_gradients = [[] for _ in range(len(self.model.layers))]
<|end_body_0|>
<|body_start_1|>
for i, l in enumerate(self.model.layers):
if isi... | A simple class to take care of the optimization process, i.e. learning, with stochastic gradient descent. | SGDOptimizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SGDOptimizer:
"""A simple class to take care of the optimization process, i.e. learning, with stochastic gradient descent."""
def __init__(self, model, learning_rate, momentum=0.0):
"""Initialization of the SGD optimizer :param model: a sequential model :param learning_rate: paramete... | stack_v2_sparse_classes_36k_train_000577 | 1,730 | no_license | [
{
"docstring": "Initialization of the SGD optimizer :param model: a sequential model :param learning_rate: parameter to train the model :param momentum: a parameter to specify how much of the old gradient to keep",
"name": "__init__",
"signature": "def __init__(self, model, learning_rate, momentum=0.0)"... | 2 | stack_v2_sparse_classes_30k_train_014902 | Implement the Python class `SGDOptimizer` described below.
Class description:
A simple class to take care of the optimization process, i.e. learning, with stochastic gradient descent.
Method signatures and docstrings:
- def __init__(self, model, learning_rate, momentum=0.0): Initialization of the SGD optimizer :param... | Implement the Python class `SGDOptimizer` described below.
Class description:
A simple class to take care of the optimization process, i.e. learning, with stochastic gradient descent.
Method signatures and docstrings:
- def __init__(self, model, learning_rate, momentum=0.0): Initialization of the SGD optimizer :param... | f716276d44d25bfb6ee4e2a76e3248b109127cc7 | <|skeleton|>
class SGDOptimizer:
"""A simple class to take care of the optimization process, i.e. learning, with stochastic gradient descent."""
def __init__(self, model, learning_rate, momentum=0.0):
"""Initialization of the SGD optimizer :param model: a sequential model :param learning_rate: paramete... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SGDOptimizer:
"""A simple class to take care of the optimization process, i.e. learning, with stochastic gradient descent."""
def __init__(self, model, learning_rate, momentum=0.0):
"""Initialization of the SGD optimizer :param model: a sequential model :param learning_rate: parameter to train th... | the_stack_v2_python_sparse | framework/optimizers/sgd_optimizer.py | AndreCI/DL_p2 | train | 0 |
71e0d620d501f1e639aff5f2664927fe7770653a | [
"src = request.GET.get('utm_source', None)\nif src == 'Email Newsletter':\n self.record_newsletter_interaction(request, response)\nreturn response",
"try:\n plus_one_month = datetime.today() + timedelta(weeks=4)\n timestamp = to_js_timestamp(plus_one_month)\n cookie = request.COOKIES['crimson.intersti... | <|body_start_0|>
src = request.GET.get('utm_source', None)
if src == 'Email Newsletter':
self.record_newsletter_interaction(request, response)
return response
<|end_body_0|>
<|body_start_1|>
try:
plus_one_month = datetime.today() + timedelta(weeks=4)
... | NewsletterSubscribeMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewsletterSubscribeMiddleware:
def process_response(self, request, response):
"""Hides the newlsetter interstitial if the link came from a newsletter."""
<|body_0|>
def record_newsletter_interaction(request, response):
"""Updates the subscribe cookie so that it won't... | stack_v2_sparse_classes_36k_train_000578 | 1,418 | no_license | [
{
"docstring": "Hides the newlsetter interstitial if the link came from a newsletter.",
"name": "process_response",
"signature": "def process_response(self, request, response)"
},
{
"docstring": "Updates the subscribe cookie so that it won't be shown for another month. This function is used by t... | 2 | null | Implement the Python class `NewsletterSubscribeMiddleware` described below.
Class description:
Implement the NewsletterSubscribeMiddleware class.
Method signatures and docstrings:
- def process_response(self, request, response): Hides the newlsetter interstitial if the link came from a newsletter.
- def record_newsle... | Implement the Python class `NewsletterSubscribeMiddleware` described below.
Class description:
Implement the NewsletterSubscribeMiddleware class.
Method signatures and docstrings:
- def process_response(self, request, response): Hides the newlsetter interstitial if the link came from a newsletter.
- def record_newsle... | a9045ea79c73c7b864a391039799c2f22234fed3 | <|skeleton|>
class NewsletterSubscribeMiddleware:
def process_response(self, request, response):
"""Hides the newlsetter interstitial if the link came from a newsletter."""
<|body_0|>
def record_newsletter_interaction(request, response):
"""Updates the subscribe cookie so that it won't... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewsletterSubscribeMiddleware:
def process_response(self, request, response):
"""Hides the newlsetter interstitial if the link came from a newsletter."""
src = request.GET.get('utm_source', None)
if src == 'Email Newsletter':
self.record_newsletter_interaction(request, resp... | the_stack_v2_python_sparse | crimtech_final_project/crimsononline/newsletter/middleware.py | cindyz8735/crimtechcomp | train | 0 | |
2ef4c427f2917abd541c462115bf1861aad919c5 | [
"res1 = res2 = 0\nfor n in num1:\n res1 = res1 * 10 + (ord(n) - ord('0'))\nfor n in num2:\n res2 = res2 * 10 + (ord(n) - ord('0'))\nreturn str(res1 * res2)",
"n1 = len(num1)\nn2 = len(num2)\ndigits = [0] * (n1 + n2)\nfor i in range(n1 - 1, -1, -1):\n for j in range(n2 - 1, -1, -1):\n idx = i + j\n... | <|body_start_0|>
res1 = res2 = 0
for n in num1:
res1 = res1 * 10 + (ord(n) - ord('0'))
for n in num2:
res2 = res2 * 10 + (ord(n) - ord('0'))
return str(res1 * res2)
<|end_body_0|>
<|body_start_1|>
n1 = len(num1)
n2 = len(num2)
digits = [0]... | Strings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Strings:
def multiply(self, num1: str, num2: str) -> str:
""":param num1: :param num2: :return:"""
<|body_0|>
def multiply_(self, num1: str, num2: str) -> str:
""":param num1: :param num2: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res... | stack_v2_sparse_classes_36k_train_000579 | 1,197 | no_license | [
{
"docstring": ":param num1: :param num2: :return:",
"name": "multiply",
"signature": "def multiply(self, num1: str, num2: str) -> str"
},
{
"docstring": ":param num1: :param num2: :return:",
"name": "multiply_",
"signature": "def multiply_(self, num1: str, num2: str) -> str"
}
] | 2 | null | Implement the Python class `Strings` described below.
Class description:
Implement the Strings class.
Method signatures and docstrings:
- def multiply(self, num1: str, num2: str) -> str: :param num1: :param num2: :return:
- def multiply_(self, num1: str, num2: str) -> str: :param num1: :param num2: :return: | Implement the Python class `Strings` described below.
Class description:
Implement the Strings class.
Method signatures and docstrings:
- def multiply(self, num1: str, num2: str) -> str: :param num1: :param num2: :return:
- def multiply_(self, num1: str, num2: str) -> str: :param num1: :param num2: :return:
<|skelet... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Strings:
def multiply(self, num1: str, num2: str) -> str:
""":param num1: :param num2: :return:"""
<|body_0|>
def multiply_(self, num1: str, num2: str) -> str:
""":param num1: :param num2: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Strings:
def multiply(self, num1: str, num2: str) -> str:
""":param num1: :param num2: :return:"""
res1 = res2 = 0
for n in num1:
res1 = res1 * 10 + (ord(n) - ord('0'))
for n in num2:
res2 = res2 * 10 + (ord(n) - ord('0'))
return str(res1 * res2)... | the_stack_v2_python_sparse | revisited_2021/math_and_string/multiply_strings.py | Shiv2157k/leet_code | train | 1 | |
b62da8b5e42d227bace30884e6ea35adb059f562 | [
"self.dict = {}\nself.min_val = float('inf')\nself.max_val = float('-inf')",
"if number not in self.dict:\n self.dict[number] = 1\nelse:\n self.dict[number] += 1\nself.min_val = min(number, self.min_val)\nself.max_val = max(number, self.max_val)",
"if self.min_val * 2 > value or self.max_val * 2 < value:\... | <|body_start_0|>
self.dict = {}
self.min_val = float('inf')
self.max_val = float('-inf')
<|end_body_0|>
<|body_start_1|>
if number not in self.dict:
self.dict[number] = 1
else:
self.dict[number] += 1
self.min_val = min(number, self.min_val)
... | TwoSum | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoSum:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def add(self, number):
"""Add the number to an internal data structure.. :type number: int :rtype: void"""
<|body_1|>
def find(self, value):
"""Find if there exists... | stack_v2_sparse_classes_36k_train_000580 | 5,501 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Add the number to an internal data structure.. :type number: int :rtype: void",
"name": "add",
"signature": "def add(self, number)"
},
{
"docstring": "F... | 3 | null | Implement the Python class `TwoSum` described below.
Class description:
Implement the TwoSum class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def add(self, number): Add the number to an internal data structure.. :type number: int :rtype: void
- def find(self, value... | Implement the Python class `TwoSum` described below.
Class description:
Implement the TwoSum class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def add(self, number): Add the number to an internal data structure.. :type number: int :rtype: void
- def find(self, value... | c34b55bb42dc44a9026a902f6afcc018b4154662 | <|skeleton|>
class TwoSum:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def add(self, number):
"""Add the number to an internal data structure.. :type number: int :rtype: void"""
<|body_1|>
def find(self, value):
"""Find if there exists... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TwoSum:
def __init__(self):
"""Initialize your data structure here."""
self.dict = {}
self.min_val = float('inf')
self.max_val = float('-inf')
def add(self, number):
"""Add the number to an internal data structure.. :type number: int :rtype: void"""
if numb... | the_stack_v2_python_sparse | Algorithm/Two Sum III - Data structure design.py | superpigBB/Happy-Coding | train | 0 | |
31edbf4054ca2a69e083dad074b0e7ad01713e02 | [
"self.parameter_dict = parameter_dict\nself.para_names = list(parameter_dict.keys())\nself.no_para = len(self.para_names)\nself.formula = FiniteDifferenceStep(formula)\nself.step = step\nself.store = store\nself.scenario_nominal = [parameter_dict[d] for d in self.para_names]\nself.generate_scenario()",
"eps_abs =... | <|body_start_0|>
self.parameter_dict = parameter_dict
self.para_names = list(parameter_dict.keys())
self.no_para = len(self.para_names)
self.formula = FiniteDifferenceStep(formula)
self.step = step
self.store = store
self.scenario_nominal = [parameter_dict[d] for ... | ScenarioGenerator | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScenarioGenerator:
def __init__(self, parameter_dict=None, formula='central', step=0.001, store=False):
"""Generate scenarios. DoE library first calls this function to generate scenarios. Parameters ----------- parameter_dict: a ``dict`` of parameter, keys are names of ''string'', values... | stack_v2_sparse_classes_36k_train_000581 | 6,574 | permissive | [
{
"docstring": "Generate scenarios. DoE library first calls this function to generate scenarios. Parameters ----------- parameter_dict: a ``dict`` of parameter, keys are names of ''string'', values are their nominal value of ''float''. for e.g., {'A1': 84.79, 'A2': 371.72, 'E1': 7.78, 'E2': 15.05} formula: choo... | 2 | null | Implement the Python class `ScenarioGenerator` described below.
Class description:
Implement the ScenarioGenerator class.
Method signatures and docstrings:
- def __init__(self, parameter_dict=None, formula='central', step=0.001, store=False): Generate scenarios. DoE library first calls this function to generate scena... | Implement the Python class `ScenarioGenerator` described below.
Class description:
Implement the ScenarioGenerator class.
Method signatures and docstrings:
- def __init__(self, parameter_dict=None, formula='central', step=0.001, store=False): Generate scenarios. DoE library first calls this function to generate scena... | 05ed25d76d244d983a3aee3ebc84545b276688a1 | <|skeleton|>
class ScenarioGenerator:
def __init__(self, parameter_dict=None, formula='central', step=0.001, store=False):
"""Generate scenarios. DoE library first calls this function to generate scenarios. Parameters ----------- parameter_dict: a ``dict`` of parameter, keys are names of ''string'', values... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScenarioGenerator:
def __init__(self, parameter_dict=None, formula='central', step=0.001, store=False):
"""Generate scenarios. DoE library first calls this function to generate scenarios. Parameters ----------- parameter_dict: a ``dict`` of parameter, keys are names of ''string'', values are their nom... | the_stack_v2_python_sparse | pyomo/contrib/doe/scenario.py | mrmundt/pyomo | train | 2 | |
258b25351b08bd4184886e76564ee8d23b1513e8 | [
"self.mobile_number = mobile_number\nself.date_of_birth = date_of_birth\nself.get_social_security_number = get_social_security_number\nself.external_reference = external_reference\nself.addonservices = addonservices\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nmo... | <|body_start_0|>
self.mobile_number = mobile_number
self.date_of_birth = date_of_birth
self.get_social_security_number = get_social_security_number
self.external_reference = external_reference
self.addonservices = addonservices
self.additional_properties = additional_prop... | Implementation of the 'CreateBankIDMobileRequest' model. Creates a BankID mobile identification process Attributes: mobile_number (string): Mobile number for the user that is to be identified date_of_birth (string): Date of birth for the user that is to be identified get_social_security_number (bool): Should the social... | CreateBankIDMobileRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateBankIDMobileRequest:
"""Implementation of the 'CreateBankIDMobileRequest' model. Creates a BankID mobile identification process Attributes: mobile_number (string): Mobile number for the user that is to be identified date_of_birth (string): Date of birth for the user that is to be identified... | stack_v2_sparse_classes_36k_train_000582 | 3,537 | permissive | [
{
"docstring": "Constructor for the CreateBankIDMobileRequest class",
"name": "__init__",
"signature": "def __init__(self, mobile_number=None, date_of_birth=None, get_social_security_number=None, external_reference=None, addonservices=None, additional_properties={})"
},
{
"docstring": "Creates a... | 2 | null | Implement the Python class `CreateBankIDMobileRequest` described below.
Class description:
Implementation of the 'CreateBankIDMobileRequest' model. Creates a BankID mobile identification process Attributes: mobile_number (string): Mobile number for the user that is to be identified date_of_birth (string): Date of birt... | Implement the Python class `CreateBankIDMobileRequest` described below.
Class description:
Implementation of the 'CreateBankIDMobileRequest' model. Creates a BankID mobile identification process Attributes: mobile_number (string): Mobile number for the user that is to be identified date_of_birth (string): Date of birt... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class CreateBankIDMobileRequest:
"""Implementation of the 'CreateBankIDMobileRequest' model. Creates a BankID mobile identification process Attributes: mobile_number (string): Mobile number for the user that is to be identified date_of_birth (string): Date of birth for the user that is to be identified... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateBankIDMobileRequest:
"""Implementation of the 'CreateBankIDMobileRequest' model. Creates a BankID mobile identification process Attributes: mobile_number (string): Mobile number for the user that is to be identified date_of_birth (string): Date of birth for the user that is to be identified get_social_s... | the_stack_v2_python_sparse | idfy_rest_client/models/create_bank_id_mobile_request.py | dealflowteam/Idfy | train | 0 |
013edbd8447129b361126f345c19579d4e313d93 | [
"log.debug('Getting bee record with ID')\nengine = database.get_engine()\nbee = database.beerecord\nif id == -1:\n query = sql.select([bee.c.bee_dict_id, bee.c.bee_name, bee.c.loc_info, bee.c.time])\nelse:\n query = sql.select([bee.c.beerecord_id, bee.c.user_id, bee.c.bee_dict_id, bee.c.bee_name, bee.c.colora... | <|body_start_0|>
log.debug('Getting bee record with ID')
engine = database.get_engine()
bee = database.beerecord
if id == -1:
query = sql.select([bee.c.bee_dict_id, bee.c.bee_name, bee.c.loc_info, bee.c.time])
else:
query = sql.select([bee.c.beerecord_id, ... | BeeRecord | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeeRecord:
def get(self, id: int, user=None):
"""Get a bee record by ID"""
<|body_0|>
def put(self, id: int, user=None):
"""Update a bee record by ID"""
<|body_1|>
def delete(self, id: int, user):
"""Delete a bee record by ID"""
<|body_2|... | stack_v2_sparse_classes_36k_train_000583 | 12,437 | no_license | [
{
"docstring": "Get a bee record by ID",
"name": "get",
"signature": "def get(self, id: int, user=None)"
},
{
"docstring": "Update a bee record by ID",
"name": "put",
"signature": "def put(self, id: int, user=None)"
},
{
"docstring": "Delete a bee record by ID",
"name": "dele... | 3 | stack_v2_sparse_classes_30k_train_002576 | Implement the Python class `BeeRecord` described below.
Class description:
Implement the BeeRecord class.
Method signatures and docstrings:
- def get(self, id: int, user=None): Get a bee record by ID
- def put(self, id: int, user=None): Update a bee record by ID
- def delete(self, id: int, user): Delete a bee record ... | Implement the Python class `BeeRecord` described below.
Class description:
Implement the BeeRecord class.
Method signatures and docstrings:
- def get(self, id: int, user=None): Get a bee record by ID
- def put(self, id: int, user=None): Update a bee record by ID
- def delete(self, id: int, user): Delete a bee record ... | ab45d78d207b957bb31381b0df12f4e318fb1e41 | <|skeleton|>
class BeeRecord:
def get(self, id: int, user=None):
"""Get a bee record by ID"""
<|body_0|>
def put(self, id: int, user=None):
"""Update a bee record by ID"""
<|body_1|>
def delete(self, id: int, user):
"""Delete a bee record by ID"""
<|body_2|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BeeRecord:
def get(self, id: int, user=None):
"""Get a bee record by ID"""
log.debug('Getting bee record with ID')
engine = database.get_engine()
bee = database.beerecord
if id == -1:
query = sql.select([bee.c.bee_dict_id, bee.c.bee_name, bee.c.loc_info, bee... | the_stack_v2_python_sparse | beecology_api/bee_data_api/endpoints/bee_record.py | C7C8/beecology-api-v7 | train | 0 | |
131063fe699912e27c33fe66b721f9866fc8fea6 | [
"if user_input is None:\n return self.async_show_form(step_id='user', data_schema=STEP_USER_DATA_SCHEMA)\nservice = await WyomingService.create(user_input[CONF_HOST], user_input[CONF_PORT])\nif service is None:\n return self.async_show_form(step_id='user', data_schema=STEP_USER_DATA_SCHEMA, errors={'base': 'c... | <|body_start_0|>
if user_input is None:
return self.async_show_form(step_id='user', data_schema=STEP_USER_DATA_SCHEMA)
service = await WyomingService.create(user_input[CONF_HOST], user_input[CONF_PORT])
if service is None:
return self.async_show_form(step_id='user', data_... | Handle a config flow for Wyoming integration. | ConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Wyoming integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle the initial step."""
<|body_0|>
async def async_step_hassio(self, discovery_info: HassioServiceInfo) -> FlowRe... | stack_v2_sparse_classes_36k_train_000584 | 3,831 | permissive | [
{
"docstring": "Handle the initial step.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult"
},
{
"docstring": "Handle Supervisor add-on discovery.",
"name": "async_step_hassio",
"signature": "async def async_s... | 3 | null | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Wyoming integration.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle the initial step.
- async def async_step_hassio(self, discovery_in... | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Wyoming integration.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle the initial step.
- async def async_step_hassio(self, discovery_in... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Wyoming integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle the initial step."""
<|body_0|>
async def async_step_hassio(self, discovery_info: HassioServiceInfo) -> FlowRe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigFlow:
"""Handle a config flow for Wyoming integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle the initial step."""
if user_input is None:
return self.async_show_form(step_id='user', data_schema=STEP_USER_DATA_S... | the_stack_v2_python_sparse | homeassistant/components/wyoming/config_flow.py | home-assistant/core | train | 35,501 |
571877102adc99457f378f1488928f7ed4640ae1 | [
"self.stack = []\nself.p = root\nwhile self.p:\n self.stack.append(self.p)\n self.p = self.p.left",
"if self.stack or self.p:\n while self.p:\n self.stack.append(self.p)\n self.p = self.p.left\n else:\n next_node = self.stack.pop()\n self.p = next_node.right\n return... | <|body_start_0|>
self.stack = []
self.p = root
while self.p:
self.stack.append(self.p)
self.p = self.p.left
<|end_body_0|>
<|body_start_1|>
if self.stack or self.p:
while self.p:
self.stack.append(self.p)
self.p = self.... | BSTIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
"""@return the next smallest number :rtype: int"""
<|body_1|>
def hasNext(self):
"""@return whether we have a next smallest number :rtype: bool"""
... | stack_v2_sparse_classes_36k_train_000585 | 1,183 | no_license | [
{
"docstring": ":type root: TreeNode",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": "@return the next smallest number :rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": "@return whether we have a next smallest number :rt... | 3 | stack_v2_sparse_classes_30k_train_012424 | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): @return the next smallest number :rtype: int
- def hasNext(self): @return whether we have a next smallest n... | Implement the Python class `BSTIterator` described below.
Class description:
Implement the BSTIterator class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): @return the next smallest number :rtype: int
- def hasNext(self): @return whether we have a next smallest n... | f234bd7b62cb7bc2150faa764bf05a9095e19192 | <|skeleton|>
class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
"""@return the next smallest number :rtype: int"""
<|body_1|>
def hasNext(self):
"""@return whether we have a next smallest number :rtype: bool"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BSTIterator:
def __init__(self, root):
""":type root: TreeNode"""
self.stack = []
self.p = root
while self.p:
self.stack.append(self.p)
self.p = self.p.left
def next(self):
"""@return the next smallest number :rtype: int"""
if self.s... | the_stack_v2_python_sparse | alg/binary_search_tree_iterator.py | nyannko/leetcode-python | train | 0 | |
c1fdd9913757d8d8db9ee8d67874c31371b81259 | [
"if s == s[::-1]:\n return 0\nfor i in range(1, len(s)):\n if s[:i] == s[:i][::-1] and s[i:] == s[i:][::-1]:\n return 1\ns_len = len(s)\nmem = [i for i in range(-1, s_len)]\nfor i in range(1, s_len + 1):\n for j in range(i):\n if s[j:i] == s[j:i][::-1]:\n mem[i] = min(mem[i], mem[j... | <|body_start_0|>
if s == s[::-1]:
return 0
for i in range(1, len(s)):
if s[:i] == s[:i][::-1] and s[i:] == s[i:][::-1]:
return 1
s_len = len(s)
mem = [i for i in range(-1, s_len)]
for i in range(1, s_len + 1):
for j in range(i):... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minCut(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def minCut2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if s == s[::-1]:
return 0
for i in range(1, len(s)):
... | stack_v2_sparse_classes_36k_train_000586 | 2,167 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "minCut",
"signature": "def minCut(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "minCut2",
"signature": "def minCut2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCut(self, s): :type s: str :rtype: int
- def minCut2(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCut(self, s): :type s: str :rtype: int
- def minCut2(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def minCut(self, s):
""":type s: str :rt... | db2d0b05020a1fcb9f0cfaf9386f79daeaad759e | <|skeleton|>
class Solution:
def minCut(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def minCut2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minCut(self, s):
""":type s: str :rtype: int"""
if s == s[::-1]:
return 0
for i in range(1, len(s)):
if s[:i] == s[:i][::-1] and s[i:] == s[i:][::-1]:
return 1
s_len = len(s)
mem = [i for i in range(-1, s_len)]
... | the_stack_v2_python_sparse | leetcode/dynamic_programming/132_min_cut.py | longgb246/MLlearn | train | 0 | |
7680e5fc945fd522179262f9a2402180856c8dac | [
"for i in range(len(array)):\n min_index = i\n for j in range(i + 1, len(array)):\n if array[j] < array[min_index]:\n min_index = j\n array[i], array[min_index] = (array[min_index], array[i])\n print(i, ': ', array)\nreturn array",
"for _ in range(len(array)):\n swapped = False\n ... | <|body_start_0|>
for i in range(len(array)):
min_index = i
for j in range(i + 1, len(array)):
if array[j] < array[min_index]:
min_index = j
array[i], array[min_index] = (array[min_index], array[i])
print(i, ': ', array)
... | Implements two sorting algorithms: selection sort and bubble sort | Sort | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sort:
"""Implements two sorting algorithms: selection sort and bubble sort"""
def selection_sort(array):
"""Sort a list of numbers using selection sort"""
<|body_0|>
def bubble_sort(array):
"""Sort a list of numbers using bubble sort"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_000587 | 1,699 | no_license | [
{
"docstring": "Sort a list of numbers using selection sort",
"name": "selection_sort",
"signature": "def selection_sort(array)"
},
{
"docstring": "Sort a list of numbers using bubble sort",
"name": "bubble_sort",
"signature": "def bubble_sort(array)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001933 | Implement the Python class `Sort` described below.
Class description:
Implements two sorting algorithms: selection sort and bubble sort
Method signatures and docstrings:
- def selection_sort(array): Sort a list of numbers using selection sort
- def bubble_sort(array): Sort a list of numbers using bubble sort | Implement the Python class `Sort` described below.
Class description:
Implements two sorting algorithms: selection sort and bubble sort
Method signatures and docstrings:
- def selection_sort(array): Sort a list of numbers using selection sort
- def bubble_sort(array): Sort a list of numbers using bubble sort
<|skele... | 51698ba8bfc2201639e6f4d358e0fc531780d2fc | <|skeleton|>
class Sort:
"""Implements two sorting algorithms: selection sort and bubble sort"""
def selection_sort(array):
"""Sort a list of numbers using selection sort"""
<|body_0|>
def bubble_sort(array):
"""Sort a list of numbers using bubble sort"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sort:
"""Implements two sorting algorithms: selection sort and bubble sort"""
def selection_sort(array):
"""Sort a list of numbers using selection sort"""
for i in range(len(array)):
min_index = i
for j in range(i + 1, len(array)):
if array[j] < arr... | the_stack_v2_python_sparse | Course_case/2018_11_27/sort.py | xiaohaiguicc/CS5001 | train | 0 |
5a866f7ed3243b014c36d9fffeec10b9cd2b94f3 | [
"if db_field.name == 'author':\n kwargs['initial'] = request.user.id\nreturn super().formfield_for_foreignkey(db_field, request, **kwargs)",
"try:\n profile = Profile.objects.get(user=request.user)\nexcept Profile.DoesNotExist:\n if request.user.is_superuser:\n return Mark.objects.all()\nif profil... | <|body_start_0|>
if db_field.name == 'author':
kwargs['initial'] = request.user.id
return super().formfield_for_foreignkey(db_field, request, **kwargs)
<|end_body_0|>
<|body_start_1|>
try:
profile = Profile.objects.get(user=request.user)
except Profile.DoesNotExi... | MarksAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarksAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Set default teacher"""
<|body_0|>
def get_queryset(self, request):
"""Get all marks for current profile"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if db_field.name ... | stack_v2_sparse_classes_36k_train_000588 | 2,628 | no_license | [
{
"docstring": "Set default teacher",
"name": "formfield_for_foreignkey",
"signature": "def formfield_for_foreignkey(self, db_field, request, **kwargs)"
},
{
"docstring": "Get all marks for current profile",
"name": "get_queryset",
"signature": "def get_queryset(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001949 | Implement the Python class `MarksAdmin` described below.
Class description:
Implement the MarksAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): Set default teacher
- def get_queryset(self, request): Get all marks for current profile | Implement the Python class `MarksAdmin` described below.
Class description:
Implement the MarksAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): Set default teacher
- def get_queryset(self, request): Get all marks for current profile
<|skeleton|>
class ... | 76c0df6f07f41f4baf7346acdbbf316b4dd13ee5 | <|skeleton|>
class MarksAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Set default teacher"""
<|body_0|>
def get_queryset(self, request):
"""Get all marks for current profile"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MarksAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""Set default teacher"""
if db_field.name == 'author':
kwargs['initial'] = request.user.id
return super().formfield_for_foreignkey(db_field, request, **kwargs)
def get_queryset(self, request)... | the_stack_v2_python_sparse | journal/admin.py | HallrizonX/api_chpk | train | 3 | |
6ba37f844aafe25216c328a80324aa8a695997fb | [
"if not hasattr(self, 'allEvents'):\n self.allEvents = Event.objects.filter(Q(instance_of=PublicEvent) | Q(instance_of=Series)).annotate(**self.get_annotations()).exclude(Q(status=Event.RegStatus.hidden) | Q(status=Event.RegStatus.regHidden) | Q(status=Event.RegStatus.linkOnly)).order_by(*self.get_ordering()).di... | <|body_start_0|>
if not hasattr(self, 'allEvents'):
self.allEvents = Event.objects.filter(Q(instance_of=PublicEvent) | Q(instance_of=Series)).annotate(**self.get_annotations()).exclude(Q(status=Event.RegStatus.hidden) | Q(status=Event.RegStatus.regHidden) | Q(status=Event.RegStatus.linkOnly)).order_... | RegisterView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterView:
def get_allEvents(self):
"""Exclude hidden and link-only events by default, as well as private events, etc. Additional restrictions are made on a per-plugin basis."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Add the event and series listing d... | stack_v2_sparse_classes_36k_train_000589 | 3,366 | permissive | [
{
"docstring": "Exclude hidden and link-only events by default, as well as private events, etc. Additional restrictions are made on a per-plugin basis.",
"name": "get_allEvents",
"signature": "def get_allEvents(self)"
},
{
"docstring": "Add the event and series listing data. If If \"today\" is s... | 2 | stack_v2_sparse_classes_30k_train_001337 | Implement the Python class `RegisterView` described below.
Class description:
Implement the RegisterView class.
Method signatures and docstrings:
- def get_allEvents(self): Exclude hidden and link-only events by default, as well as private events, etc. Additional restrictions are made on a per-plugin basis.
- def get... | Implement the Python class `RegisterView` described below.
Class description:
Implement the RegisterView class.
Method signatures and docstrings:
- def get_allEvents(self): Exclude hidden and link-only events by default, as well as private events, etc. Additional restrictions are made on a per-plugin basis.
- def get... | 19db3e83e76ea2002ee841989410d12d1e601023 | <|skeleton|>
class RegisterView:
def get_allEvents(self):
"""Exclude hidden and link-only events by default, as well as private events, etc. Additional restrictions are made on a per-plugin basis."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Add the event and series listing d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegisterView:
def get_allEvents(self):
"""Exclude hidden and link-only events by default, as well as private events, etc. Additional restrictions are made on a per-plugin basis."""
if not hasattr(self, 'allEvents'):
self.allEvents = Event.objects.filter(Q(instance_of=PublicEvent) |... | the_stack_v2_python_sparse | danceschool/register/views.py | django-danceschool/django-danceschool | train | 40 | |
3a76492557c51661b9afccd4bf42b8e54c737698 | [
"self.head = Node(0)\nself.tail = Node(0)\nself.head.next = self.tail\nself.tail.prev = self.head\nself.key2node = {}",
"if key in self.key2node:\n cur_node = self.key2node[key]\n cur_node.keys.remove(key)\nelse:\n cur_node = self.head\ncur_freq = cur_node.val\nif cur_freq + 1 != cur_node.next.val:\n ... | <|body_start_0|>
self.head = Node(0)
self.tail = Node(0)
self.head.next = self.tail
self.tail.prev = self.head
self.key2node = {}
<|end_body_0|>
<|body_start_1|>
if key in self.key2node:
cur_node = self.key2node[key]
cur_node.keys.remove(key)
... | AllOne | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllOne:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def inc(self, key: str) -> None:
"""Inserts a new key <Key> with value 1. Or increments an existing key by 1."""
<|body_1|>
def dec(self, key: str) -> None:
"""Decr... | stack_v2_sparse_classes_36k_train_000590 | 4,239 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inserts a new key <Key> with value 1. Or increments an existing key by 1.",
"name": "inc",
"signature": "def inc(self, key: str) -> None"
},
{
"docstrin... | 5 | null | Implement the Python class `AllOne` described below.
Class description:
Implement the AllOne class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def inc(self, key: str) -> None: Inserts a new key <Key> with value 1. Or increments an existing key by 1.
- def dec(self, ... | Implement the Python class `AllOne` described below.
Class description:
Implement the AllOne class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def inc(self, key: str) -> None: Inserts a new key <Key> with value 1. Or increments an existing key by 1.
- def dec(self, ... | e431ff831ddd5f26891e6ee4506a20d7972b4f02 | <|skeleton|>
class AllOne:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def inc(self, key: str) -> None:
"""Inserts a new key <Key> with value 1. Or increments an existing key by 1."""
<|body_1|>
def dec(self, key: str) -> None:
"""Decr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AllOne:
def __init__(self):
"""Initialize your data structure here."""
self.head = Node(0)
self.tail = Node(0)
self.head.next = self.tail
self.tail.prev = self.head
self.key2node = {}
def inc(self, key: str) -> None:
"""Inserts a new key <Key> with ... | the_stack_v2_python_sparse | leetcode_python/432.All_O`one_Data_Structure.py | zihuaweng/leetcode-solutions | train | 4 | |
f17060eb4fa78843e232aa8ae5e49612935cf8ac | [
"if USER_NOT_FOUND:\n return HttpResponseNotFound(USER_NOT_FOUND_MSG)\nreturn Response([{'ruleId': 0, 'ruleUser': user, 'ruleBlockedFrom': 'string', 'ruleBlockedTo': 'string', 'ruleReason': 'string'}])",
"if USER_NOT_FOUND:\n return HttpResponseNotFound(USER_NOT_FOUND_MSG)\nif len(request.data) != 2:\n r... | <|body_start_0|>
if USER_NOT_FOUND:
return HttpResponseNotFound(USER_NOT_FOUND_MSG)
return Response([{'ruleId': 0, 'ruleUser': user, 'ruleBlockedFrom': 'string', 'ruleBlockedTo': 'string', 'ruleReason': 'string'}])
<|end_body_0|>
<|body_start_1|>
if USER_NOT_FOUND:
retur... | [GET] /userBlock/{user} Get all rules with specified ruleAddress [PUT] /userBlock/{user} Change a reason and direction for all rules with the specified e-mail address [DELETE] /userBlock/{user} Delete all rules for specified e-mail address and direction (from or to) | UserBlockUser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserBlockUser:
"""[GET] /userBlock/{user} Get all rules with specified ruleAddress [PUT] /userBlock/{user} Change a reason and direction for all rules with the specified e-mail address [DELETE] /userBlock/{user} Delete all rules for specified e-mail address and direction (from or to)"""
def ... | stack_v2_sparse_classes_36k_train_000591 | 5,784 | permissive | [
{
"docstring": ":param user: any number of word characters",
"name": "get",
"signature": "def get(self, request, user, **kwargs)"
},
{
"docstring": ":param user: any number of word characters",
"name": "put",
"signature": "def put(self, request, user, **kwargs)"
},
{
"docstring":... | 3 | null | Implement the Python class `UserBlockUser` described below.
Class description:
[GET] /userBlock/{user} Get all rules with specified ruleAddress [PUT] /userBlock/{user} Change a reason and direction for all rules with the specified e-mail address [DELETE] /userBlock/{user} Delete all rules for specified e-mail address ... | Implement the Python class `UserBlockUser` described below.
Class description:
[GET] /userBlock/{user} Get all rules with specified ruleAddress [PUT] /userBlock/{user} Change a reason and direction for all rules with the specified e-mail address [DELETE] /userBlock/{user} Delete all rules for specified e-mail address ... | 73e4ac0ced6c3ac46d24ac5c3feb01a1e88bd36b | <|skeleton|>
class UserBlockUser:
"""[GET] /userBlock/{user} Get all rules with specified ruleAddress [PUT] /userBlock/{user} Change a reason and direction for all rules with the specified e-mail address [DELETE] /userBlock/{user} Delete all rules for specified e-mail address and direction (from or to)"""
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserBlockUser:
"""[GET] /userBlock/{user} Get all rules with specified ruleAddress [PUT] /userBlock/{user} Change a reason and direction for all rules with the specified e-mail address [DELETE] /userBlock/{user} Delete all rules for specified e-mail address and direction (from or to)"""
def get(self, req... | the_stack_v2_python_sparse | crusoe_act/act-component/userBlock-wrapper/userBlock_wrapper_project/views.py | wumingruiye/CRUSOE | train | 0 |
4ce8d150a417071ce7da500cb5f4777d9e9a28e6 | [
"baseSQL = 'SELECT count(*) FROM wmbs_job\\n WHERE location = (SELECT ID FROM wmbs_location WHERE site_name = :location)\\n AND state IN (SELECT ID FROM wmbs_job_state js WHERE js.name IN (\\n '\ntypeSQL = 'SELECT count(*) FROM wmbs_job\\n INNER JOIN wmbs_jobgr... | <|body_start_0|>
baseSQL = 'SELECT count(*) FROM wmbs_job\n WHERE location = (SELECT ID FROM wmbs_location WHERE site_name = :location)\n AND state IN (SELECT ID FROM wmbs_job_state js WHERE js.name IN (\n '
typeSQL = 'SELECT count(*) FROM wmbs_job\n ... | _GetLocation_ Retrieve all files that are associated with the given job from the database. | GetNumberOfJobsPerSite | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetNumberOfJobsPerSite:
"""_GetLocation_ Retrieve all files that are associated with the given job from the database."""
def buildSQL(self, states, type):
"""_buildSQL_ builds the sql statements; necessary for lists"""
<|body_0|>
def format(self, results):
"""_fo... | stack_v2_sparse_classes_36k_train_000592 | 2,859 | permissive | [
{
"docstring": "_buildSQL_ builds the sql statements; necessary for lists",
"name": "buildSQL",
"signature": "def buildSQL(self, states, type)"
},
{
"docstring": "_format_",
"name": "format",
"signature": "def format(self, results)"
},
{
"docstring": "_buildBinds_ Build a list of... | 4 | null | Implement the Python class `GetNumberOfJobsPerSite` described below.
Class description:
_GetLocation_ Retrieve all files that are associated with the given job from the database.
Method signatures and docstrings:
- def buildSQL(self, states, type): _buildSQL_ builds the sql statements; necessary for lists
- def forma... | Implement the Python class `GetNumberOfJobsPerSite` described below.
Class description:
_GetLocation_ Retrieve all files that are associated with the given job from the database.
Method signatures and docstrings:
- def buildSQL(self, states, type): _buildSQL_ builds the sql statements; necessary for lists
- def forma... | de110ccf6fc63ef5589b4e871ef4d51d5bce7a25 | <|skeleton|>
class GetNumberOfJobsPerSite:
"""_GetLocation_ Retrieve all files that are associated with the given job from the database."""
def buildSQL(self, states, type):
"""_buildSQL_ builds the sql statements; necessary for lists"""
<|body_0|>
def format(self, results):
"""_fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetNumberOfJobsPerSite:
"""_GetLocation_ Retrieve all files that are associated with the given job from the database."""
def buildSQL(self, states, type):
"""_buildSQL_ builds the sql statements; necessary for lists"""
baseSQL = 'SELECT count(*) FROM wmbs_job\n WHERE location... | the_stack_v2_python_sparse | src/python/WMCore/WMBS/MySQL/Jobs/GetNumberOfJobsPerSite.py | vkuznet/WMCore | train | 0 |
644e7f637bbae867f3b761e42a0ae599dbfdcae1 | [
"n = len(nums)\nif not n % 2:\n return True\ndp = [[-1 for _ in xrange(n)] for _ in xrange(n)]\nmaxSum = self.dfs(dp, 0, n - 1, nums)\nreturn 2 * maxSum >= sum(nums)",
"if i > j:\n return 0\nif dp[i][j] != -1:\n return dp[i][j]\na = nums[i] + min(self.dfs(dp, i + 1, j - 1, nums), self.dfs(dp, i + 2, j, n... | <|body_start_0|>
n = len(nums)
if not n % 2:
return True
dp = [[-1 for _ in xrange(n)] for _ in xrange(n)]
maxSum = self.dfs(dp, 0, n - 1, nums)
return 2 * maxSum >= sum(nums)
<|end_body_0|>
<|body_start_1|>
if i > j:
return 0
if dp[i][j] ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def PredictTheWinner(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def dfs(self, dp, i, j, nums):
""":dp: dp table :i: left index :j: right index"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
if n... | stack_v2_sparse_classes_36k_train_000593 | 802 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "PredictTheWinner",
"signature": "def PredictTheWinner(self, nums)"
},
{
"docstring": ":dp: dp table :i: left index :j: right index",
"name": "dfs",
"signature": "def dfs(self, dp, i, j, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def PredictTheWinner(self, nums): :type nums: List[int] :rtype: bool
- def dfs(self, dp, i, j, nums): :dp: dp table :i: left index :j: right index | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def PredictTheWinner(self, nums): :type nums: List[int] :rtype: bool
- def dfs(self, dp, i, j, nums): :dp: dp table :i: left index :j: right index
<|skeleton|>
class Solution:
... | 43bf3c594a71535a3f4ee9154cc72344b92b0608 | <|skeleton|>
class Solution:
def PredictTheWinner(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def dfs(self, dp, i, j, nums):
""":dp: dp table :i: left index :j: right index"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def PredictTheWinner(self, nums):
""":type nums: List[int] :rtype: bool"""
n = len(nums)
if not n % 2:
return True
dp = [[-1 for _ in xrange(n)] for _ in xrange(n)]
maxSum = self.dfs(dp, 0, n - 1, nums)
return 2 * maxSum >= sum(nums)
d... | the_stack_v2_python_sparse | python/predictthewinner.py | john15518513/leetcode | train | 0 | |
e65ec2b05344504d9f89662d5a2b0a9cbeda6b2a | [
"counters = []\nletters = set(words[0])\nfor word in words:\n counters.append(Counter(word))\n letters &= set(word)\nans = []\nfor letter in letters:\n count = float('inf')\n for counter in counters:\n count = min(count, counter.get(letter, 0))\n ans.extend([letter] * count)\nreturn ans",
"m... | <|body_start_0|>
counters = []
letters = set(words[0])
for word in words:
counters.append(Counter(word))
letters &= set(word)
ans = []
for letter in letters:
count = float('inf')
for counter in counters:
count = min(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def commonChars(self, words: List[str]) -> List[str]:
"""哈希表"""
<|body_0|>
def commonChars2(self, words: List[str]) -> List[str]:
"""官方答案"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
counters = []
letters = set(words[0])
... | stack_v2_sparse_classes_36k_train_000594 | 1,827 | no_license | [
{
"docstring": "哈希表",
"name": "commonChars",
"signature": "def commonChars(self, words: List[str]) -> List[str]"
},
{
"docstring": "官方答案",
"name": "commonChars2",
"signature": "def commonChars2(self, words: List[str]) -> List[str]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def commonChars(self, words: List[str]) -> List[str]: 哈希表
- def commonChars2(self, words: List[str]) -> List[str]: 官方答案 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def commonChars(self, words: List[str]) -> List[str]: 哈希表
- def commonChars2(self, words: List[str]) -> List[str]: 官方答案
<|skeleton|>
class Solution:
def commonChars(self, w... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def commonChars(self, words: List[str]) -> List[str]:
"""哈希表"""
<|body_0|>
def commonChars2(self, words: List[str]) -> List[str]:
"""官方答案"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def commonChars(self, words: List[str]) -> List[str]:
"""哈希表"""
counters = []
letters = set(words[0])
for word in words:
counters.append(Counter(word))
letters &= set(word)
ans = []
for letter in letters:
count = flo... | the_stack_v2_python_sparse | 1002.查找常用字符/solution.py | QtTao/daily_leetcode | train | 0 | |
4f591ff1b4d2662d55479682e1cee2f827db8fb2 | [
"flownames = ['EEin', 'Sigin', 'Watin', 'Watout']\nstates = {'eff': 1.0}\nself.delay = delay\nsuper().__init__(flownames, flows, states, timers={'timer'})\nself.failrate = 1e-05\nself.assoc_modes({'mech_break': [0.6, [0.1, 1.2, 0.1], 5000], 'short': [1.0, [1.5, 1.0, 1.0], 10000]})",
"if self.delay:\n if self.W... | <|body_start_0|>
flownames = ['EEin', 'Sigin', 'Watin', 'Watout']
states = {'eff': 1.0}
self.delay = delay
super().__init__(flownames, flows, states, timers={'timer'})
self.failrate = 1e-05
self.assoc_modes({'mech_break': [0.6, [0.1, 1.2, 0.1], 5000], 'short': [1.0, [1.5,... | Move Water is the pump itself. While one could decompose this further, one function is used for simplicity | MoveWat | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MoveWat:
"""Move Water is the pump itself. While one could decompose this further, one function is used for simplicity"""
def __init__(self, flows, delay):
"""In this function, more states are initialized than flows: - states (internal variables to be given to the function) states ar... | stack_v2_sparse_classes_36k_train_000595 | 13,659 | permissive | [
{
"docstring": "In this function, more states are initialized than flows: - states (internal variables to be given to the function) states are given as {'name':initval} - timers (objects that keep track of time), given as a set of timer names We also have a parameter `delay` which we use to change a design vari... | 3 | null | Implement the Python class `MoveWat` described below.
Class description:
Move Water is the pump itself. While one could decompose this further, one function is used for simplicity
Method signatures and docstrings:
- def __init__(self, flows, delay): In this function, more states are initialized than flows: - states (... | Implement the Python class `MoveWat` described below.
Class description:
Move Water is the pump itself. While one could decompose this further, one function is used for simplicity
Method signatures and docstrings:
- def __init__(self, flows, delay): In this function, more states are initialized than flows: - states (... | 2d87c415c036f44fe10310500788f5ab697e618d | <|skeleton|>
class MoveWat:
"""Move Water is the pump itself. While one could decompose this further, one function is used for simplicity"""
def __init__(self, flows, delay):
"""In this function, more states are initialized than flows: - states (internal variables to be given to the function) states ar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MoveWat:
"""Move Water is the pump itself. While one could decompose this further, one function is used for simplicity"""
def __init__(self, flows, delay):
"""In this function, more states are initialized than flows: - states (internal variables to be given to the function) states are given as {'... | the_stack_v2_python_sparse | pump example/ex_pump.py | DesignEngrLab/fmdtools | train | 10 |
c2db422cc7a9bb4ec61ea1f37c28c02e9da345ff | [
"try:\n with datastore_services.get_ndb_context():\n question_summary = question_services.get_question_summary_from_model(question_summary_model)\n question_summary.version = question_version\n question_summary.validate()\nexcept Exception as e:\n logging.exception(e)\n return result.Err((ques... | <|body_start_0|>
try:
with datastore_services.get_ndb_context():
question_summary = question_services.get_question_summary_from_model(question_summary_model)
question_summary.version = question_version
question_summary.validate()
except Exception as e:... | Job that audits PopulateQuestionSummaryVersionOneOffJob. | AuditPopulateQuestionSummaryVersionOneOffJob | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuditPopulateQuestionSummaryVersionOneOffJob:
"""Job that audits PopulateQuestionSummaryVersionOneOffJob."""
def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSummaryModel) -> result.Result[Tuple[str, question_models.QuestionSummary... | stack_v2_sparse_classes_36k_train_000596 | 12,101 | permissive | [
{
"docstring": "Transform question summary model into question summary object, add a version field and return the populated summary model. Args: question_version: int. The version number in the corresponding question domain object. question_summary_model: QuestionSummaryModel. The question summary model to migr... | 2 | stack_v2_sparse_classes_30k_train_007850 | Implement the Python class `AuditPopulateQuestionSummaryVersionOneOffJob` described below.
Class description:
Job that audits PopulateQuestionSummaryVersionOneOffJob.
Method signatures and docstrings:
- def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSumma... | Implement the Python class `AuditPopulateQuestionSummaryVersionOneOffJob` described below.
Class description:
Job that audits PopulateQuestionSummaryVersionOneOffJob.
Method signatures and docstrings:
- def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSumma... | d16fdf23d790eafd63812bd7239532256e30a21d | <|skeleton|>
class AuditPopulateQuestionSummaryVersionOneOffJob:
"""Job that audits PopulateQuestionSummaryVersionOneOffJob."""
def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSummaryModel) -> result.Result[Tuple[str, question_models.QuestionSummary... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuditPopulateQuestionSummaryVersionOneOffJob:
"""Job that audits PopulateQuestionSummaryVersionOneOffJob."""
def _update_and_validate_summary_model(question_version: int, question_summary_model: question_models.QuestionSummaryModel) -> result.Result[Tuple[str, question_models.QuestionSummaryModel], Tuple... | the_stack_v2_python_sparse | core/jobs/batch_jobs/question_migration_jobs.py | oppia/oppia | train | 6,172 |
8dc3ee7c3a0060d45db9487c320fd1ed381d8109 | [
"filenames = []\nfor attachment in self.attachments.entries:\n try:\n return filenames.append(attachment.upload.data.filename)\n except AttributeError:\n continue\nreturn filenames if len(filenames) > 0 else None",
"current_app.logger.info('CONDUCTOR EMAIL UPDATE | New update on stage \"{}\" f... | <|body_start_0|>
filenames = []
for attachment in self.attachments.entries:
try:
return filenames.append(attachment.upload.data.filename)
except AttributeError:
continue
return filenames if len(filenames) > 0 else None
<|end_body_0|>
<|bod... | Form to send an email update Attributes: send_to: Email or semicolon-delimited list of email addresses to send the update email to send_to_cc: Email or semicolon-delimited list of email addresses to cc on the update subject: The subject the update should have body: The body of the message the subject should have. This ... | SendUpdateForm | [
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SendUpdateForm:
"""Form to send an email update Attributes: send_to: Email or semicolon-delimited list of email addresses to send the update email to send_to_cc: Email or semicolon-delimited list of email addresses to cc on the update subject: The subject the update should have body: The body of ... | stack_v2_sparse_classes_36k_train_000597 | 21,451 | permissive | [
{
"docstring": "Return the names of all of the attached files or None",
"name": "get_attachment_filenames",
"signature": "def get_attachment_filenames(self)"
},
{
"docstring": "Send the email updates Arguments: action: A :py:class:`~purchasing.data.contract_stages.ContractStageActionItem` that n... | 2 | stack_v2_sparse_classes_30k_train_010232 | Implement the Python class `SendUpdateForm` described below.
Class description:
Form to send an email update Attributes: send_to: Email or semicolon-delimited list of email addresses to send the update email to send_to_cc: Email or semicolon-delimited list of email addresses to cc on the update subject: The subject th... | Implement the Python class `SendUpdateForm` described below.
Class description:
Form to send an email update Attributes: send_to: Email or semicolon-delimited list of email addresses to send the update email to send_to_cc: Email or semicolon-delimited list of email addresses to cc on the update subject: The subject th... | d676ed9c137e5aaa100992a798acd60ac464a2c1 | <|skeleton|>
class SendUpdateForm:
"""Form to send an email update Attributes: send_to: Email or semicolon-delimited list of email addresses to send the update email to send_to_cc: Email or semicolon-delimited list of email addresses to cc on the update subject: The subject the update should have body: The body of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SendUpdateForm:
"""Form to send an email update Attributes: send_to: Email or semicolon-delimited list of email addresses to send the update email to send_to_cc: Email or semicolon-delimited list of email addresses to cc on the update subject: The subject the update should have body: The body of the message t... | the_stack_v2_python_sparse | purchasing/conductor/forms.py | CityofPittsburgh/pittsburgh-purchasing-suite | train | 2 |
78db134fffac10f1e3c757a6506cbf1135214a5f | [
"rawline = self.file.readline()\nwhile rawline:\n rematch = self.line_re.match(rawline)\n if not rematch:\n rawline = self.file.readline()\n continue\n while rematch:\n rep = Replica()\n self.reps.append(rep)\n rep.index = [0 for i in range(self.numexchg)]\n rep.po... | <|body_start_0|>
rawline = self.file.readline()
while rawline:
rematch = self.line_re.match(rawline)
if not rematch:
rawline = self.file.readline()
continue
while rematch:
rep = Replica()
self.reps.append... | Replica exchange log file | TempRemLog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempRemLog:
"""Replica exchange log file"""
def _get_replicas(self):
"""Gets all of the replica information from the first block of repinfo"""
<|body_0|>
def _parse(self):
"""Parses the rem.log file and loads the data arrays"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_000598 | 12,296 | no_license | [
{
"docstring": "Gets all of the replica information from the first block of repinfo",
"name": "_get_replicas",
"signature": "def _get_replicas(self)"
},
{
"docstring": "Parses the rem.log file and loads the data arrays",
"name": "_parse",
"signature": "def _parse(self)"
}
] | 2 | null | Implement the Python class `TempRemLog` described below.
Class description:
Replica exchange log file
Method signatures and docstrings:
- def _get_replicas(self): Gets all of the replica information from the first block of repinfo
- def _parse(self): Parses the rem.log file and loads the data arrays | Implement the Python class `TempRemLog` described below.
Class description:
Replica exchange log file
Method signatures and docstrings:
- def _get_replicas(self): Gets all of the replica information from the first block of repinfo
- def _parse(self): Parses the rem.log file and loads the data arrays
<|skeleton|>
cla... | 5cec8112637be7a19c4aac893f612aa8c354b733 | <|skeleton|>
class TempRemLog:
"""Replica exchange log file"""
def _get_replicas(self):
"""Gets all of the replica information from the first block of repinfo"""
<|body_0|>
def _parse(self):
"""Parses the rem.log file and loads the data arrays"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TempRemLog:
"""Replica exchange log file"""
def _get_replicas(self):
"""Gets all of the replica information from the first block of repinfo"""
rawline = self.file.readline()
while rawline:
rematch = self.line_re.match(rawline)
if not rematch:
... | the_stack_v2_python_sparse | remd.py | jeff-wang/JmsScripts | train | 0 |
0c035d19991b348c7c10d98530763afb4cba642d | [
"self.encap = encap\nself.unidir_mode = unidir_mode\nself.mtu = mtu\nself.rx_bandwidth = rx_bandwidth\nself.tx_bandwidth = tx_bandwidth\nself.snmp_index = snmp_index\nself.islayer2 = islayer2\nself.display_name = display_name\nself.mac_address = mac_address\nself.description = description\nself.iphelper = []\nself.... | <|body_start_0|>
self.encap = encap
self.unidir_mode = unidir_mode
self.mtu = mtu
self.rx_bandwidth = rx_bandwidth
self.tx_bandwidth = tx_bandwidth
self.snmp_index = snmp_index
self.islayer2 = islayer2
self.display_name = display_name
self.mac_addr... | This class represents the configuration (software property) of the network interface. The configuration might be changed during the life of the session. Hence, it is refreshed if the last accessed time has aged out. @ivar islayer2: Indicates if this a Layer-2 Interface @type islayer2: C{bool} @ivar display_name: The na... | InterfaceConfig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterfaceConfig:
"""This class represents the configuration (software property) of the network interface. The configuration might be changed during the life of the session. Hence, it is refreshed if the last accessed time has aged out. @ivar islayer2: Indicates if this a Layer-2 Interface @type i... | stack_v2_sparse_classes_36k_train_000599 | 10,222 | no_license | [
{
"docstring": "Constructor of InterfaceConfig class.",
"name": "__init__",
"signature": "def __init__(self, encap, unidir_mode, mtu, rx_bandwidth, tx_bandwidth, snmp_index, islayer2, display_name, mac_address, description, ip_redirect, ip_unreachable, ip_proxy_arp, ip_unicast_reverse_path, vrf, speed=N... | 2 | stack_v2_sparse_classes_30k_train_013963 | Implement the Python class `InterfaceConfig` described below.
Class description:
This class represents the configuration (software property) of the network interface. The configuration might be changed during the life of the session. Hence, it is refreshed if the last accessed time has aged out. @ivar islayer2: Indica... | Implement the Python class `InterfaceConfig` described below.
Class description:
This class represents the configuration (software property) of the network interface. The configuration might be changed during the life of the session. Hence, it is refreshed if the last accessed time has aged out. @ivar islayer2: Indica... | 54bc49eaed14f7832aca45c4f52311a00282d862 | <|skeleton|>
class InterfaceConfig:
"""This class represents the configuration (software property) of the network interface. The configuration might be changed during the life of the session. Hence, it is refreshed if the last accessed time has aged out. @ivar islayer2: Indicates if this a Layer-2 Interface @type i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InterfaceConfig:
"""This class represents the configuration (software property) of the network interface. The configuration might be changed during the life of the session. Hence, it is refreshed if the last accessed time has aged out. @ivar islayer2: Indicates if this a Layer-2 Interface @type islayer2: C{bo... | the_stack_v2_python_sparse | onepk_without_pyc/build/lib.linux-x86_64-2.7/onep/interfaces/InterfaceConfig.py | neoyogi/onepk | train | 0 |
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