hybrid-diff-ar/stack-v2-sparse-classes-36k

dea8d6f747138b93eb4c7f9a135e45c5146a4551

[ "if self._return_code != 0:\n return None\nreturn self._body.get(IPROTO_VERSION)", "if self._return_code != 0:\n return []\nreturn self._body.get(IPROTO_FEATURES)", "if self._return_code != 0:\n return None\nreturn to_unicode(self._body.get(IPROTO_AUTH_TYPE))" ]

Represents an ID request response: information about server protocol version and features it supports.

ResponseProtocolVersion

[ "BSD-3-Clause", "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ResponseProtocolVersion: """Represents an ID request response: information about server protocol version and features it supports.""" def protocol_version(self): """Server protocol version. :rtype: :obj:`int` or :obj:`None`""" <|body_0|> def features(self): """Se...

stack_v2_sparse_classes_36k_train_008300

10,967

permissive

[ { "docstring": "Server protocol version. :rtype: :obj:`int` or :obj:`None`", "name": "protocol_version", "signature": "def protocol_version(self)" }, { "docstring": "Server supported features. :rtype: :obj:`list`", "name": "features", "signature": "def features(self)" }, { "docst...

3

stack_v2_sparse_classes_30k_train_021549

Implement the Python class `ResponseProtocolVersion` described below. Class description: Represents an ID request response: information about server protocol version and features it supports. Method signatures and docstrings: - def protocol_version(self): Server protocol version. :rtype: :obj:`int` or :obj:`None` - d...

66e53bca472fec0efacd690ebe6c54c33a7df3f9

<|skeleton|> class ResponseProtocolVersion: """Represents an ID request response: information about server protocol version and features it supports.""" def protocol_version(self): """Server protocol version. :rtype: :obj:`int` or :obj:`None`""" <|body_0|> def features(self): """Se...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ResponseProtocolVersion: """Represents an ID request response: information about server protocol version and features it supports.""" def protocol_version(self): """Server protocol version. :rtype: :obj:`int` or :obj:`None`""" if self._return_code != 0: return None ret...

the_stack_v2_python_sparse

tarantool/response.py

tarantool/tarantool-python

train

80

3e9a70f2bb3186f5131a38c2b73f67a7b582a5f0

[ "super(Recorder, self).__init__()\nself.symbols = symbols\nself.timer_frequency = SNAPSHOT_RATE\nself.workers = dict()\nself.current_time = dt.now()\nself.daemon = False", "coinbase, bitfinex = self.symbols\nself.workers[coinbase] = CoinbaseClient(sym=coinbase)\nself.workers[bitfinex] = BitfinexClient(sym=bitfine...

Recorder

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Recorder: def __init__(self, symbols): """Constructor of Recorder. :param symbols: basket of securities to record... Example: symbols = [('BTC-USD, 'tBTCUSD')]""" <|body_0|> def run(self) -> None: """New process created to instantiate limit order books for (1) Coinba...

stack_v2_sparse_classes_36k_train_008301

4,752

no_license

[ { "docstring": "Constructor of Recorder. :param symbols: basket of securities to record... Example: symbols = [('BTC-USD, 'tBTCUSD')]", "name": "__init__", "signature": "def __init__(self, symbols)" }, { "docstring": "New process created to instantiate limit order books for (1) Coinbase Pro, and...

3

stack_v2_sparse_classes_30k_val_001052

Implement the Python class `Recorder` described below. Class description: Implement the Recorder class. Method signatures and docstrings: - def __init__(self, symbols): Constructor of Recorder. :param symbols: basket of securities to record... Example: symbols = [('BTC-USD, 'tBTCUSD')] - def run(self) -> None: New pr...

078081e5715cadeae9c798a3d759c9d59d2041bc

<|skeleton|> class Recorder: def __init__(self, symbols): """Constructor of Recorder. :param symbols: basket of securities to record... Example: symbols = [('BTC-USD, 'tBTCUSD')]""" <|body_0|> def run(self) -> None: """New process created to instantiate limit order books for (1) Coinba...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Recorder: def __init__(self, symbols): """Constructor of Recorder. :param symbols: basket of securities to record... Example: symbols = [('BTC-USD, 'tBTCUSD')]""" super(Recorder, self).__init__() self.symbols = symbols self.timer_frequency = SNAPSHOT_RATE self.workers =...

the_stack_v2_python_sparse

recorder.py

sadighian/crypto-rl

train

676

54dcc8891439a5350d8ec44525b64eda8554423c

[ "n = len(s)\nm = len(t)\ndp = [[0] * (m + 1) for _ in range(n + 1)]\ni = 0\nwhile i <= n:\n j = 0\n while j <= m:\n if i == j == 0:\n dp[i][j] = 0\n elif s[i - 1] == t[j - 1]:\n dp[i][j] = dp[i - 1][j - 1]\n else:\n dp[i][j] = min([dp[i - 1][j - 1] + 1, dp...

<|body_start_0|> n = len(s) m = len(t) dp = [[0] * (m + 1) for _ in range(n + 1)] i = 0 while i <= n: j = 0 while j <= m: if i == j == 0: dp[i][j] = 0 elif s[i - 1] == t[j - 1]: dp[i][...

@param s: a string @param t: a string @return: true if they are both one edit distance apart or false

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: """@param s: a string @param t: a string @return: true if they are both one edit distance apart or false""" def isOneEditDistance(self, s, t): """Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/soluti...

stack_v2_sparse_classes_36k_train_008302

1,840

no_license

[ { "docstring": "Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/solution/edit-distance-by-ikaruga/", "name": "isOneEditDistance", "signature": "def isOneEditDistance(self, s, t)" }, { "docstring": "O(n) runtime, O(1) space...

2

stack_v2_sparse_classes_30k_test_000318

Implement the Python class `Solution` described below. Class description: @param s: a string @param t: a string @return: true if they are both one edit distance apart or false Method signatures and docstrings: - def isOneEditDistance(self, s, t): Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) sp...

3ea03cd8b1fa507553ebee4fd765c4cc4b5814b6

<|skeleton|> class Solution: """@param s: a string @param t: a string @return: true if they are both one edit distance apart or false""" def isOneEditDistance(self, s, t): """Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/soluti...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: """@param s: a string @param t: a string @return: true if they are both one edit distance apart or false""" def isOneEditDistance(self, s, t): """Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/solution/edit-dista...

the_stack_v2_python_sparse

One_Edit_Distance_14.py

jay6413682/Leetcode

train

0

8fe70f778074ee2ce032fe11375889317f383c57

[ "super(HyperOptNoTraining, self).__init__(params, data)\nself.objective = None\nself.trial_losses = None\nself.best_trial = None\nself.trial_list = None", "self.trial_list = trial_list\nif self.trial_list is None:\n raise Exception('Sorry, Hyperparameter optimization without training currently only works if a ...

Hyperparameter optimizer that does not require training networks. Networks are analysed using the Jacobian.

HyperOptNoTraining

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class HyperOptNoTraining: """Hyperparameter optimizer that does not require training networks. Networks are analysed using the Jacobian.""" def __init__(self, params, data): """Create a HyperOptNoTraining object. Parameters ---------- params : mala.common.parametes.Parameters Parameters us...

stack_v2_sparse_classes_36k_train_008303

2,999

permissive

[ { "docstring": "Create a HyperOptNoTraining object. Parameters ---------- params : mala.common.parametes.Parameters Parameters used to create this hyperparameter optimizer. data : mala.datahandling.data_handler.DataHandler DataHandler holding the data for the hyperparameter optimization.", "name": "__init__...

3

stack_v2_sparse_classes_30k_train_014278

Implement the Python class `HyperOptNoTraining` described below. Class description: Hyperparameter optimizer that does not require training networks. Networks are analysed using the Jacobian. Method signatures and docstrings: - def __init__(self, params, data): Create a HyperOptNoTraining object. Parameters ---------...

9cc771b0cdc4178c7f66fd717684658abbb0d95c

<|skeleton|> class HyperOptNoTraining: """Hyperparameter optimizer that does not require training networks. Networks are analysed using the Jacobian.""" def __init__(self, params, data): """Create a HyperOptNoTraining object. Parameters ---------- params : mala.common.parametes.Parameters Parameters us...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class HyperOptNoTraining: """Hyperparameter optimizer that does not require training networks. Networks are analysed using the Jacobian.""" def __init__(self, params, data): """Create a HyperOptNoTraining object. Parameters ---------- params : mala.common.parametes.Parameters Parameters used to create ...

the_stack_v2_python_sparse

mala/network/hyper_opt_notraining.py

icamps/mala

train

0

dbf09a5b896f7769485c6dda3dfbdac6006e7531

[ "self.subject = subject\nself.condition = condition\nself.effect = effect\nself.singleUse = singleUse\nself.parent = None", "context = self.getTriggerContext(event)\nif self.condition is None or self.condition.evaluate(context):\n if self.singleUse:\n context.owner.unregisterTrigger(self)\n coroutine...

Represents a Triggerable Effect

Trigger

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008304

1,219

no_license

[ { "docstring": "Initialize the Trigger", "name": "__init__", "signature": "def __init__(self, subject, effect, condition=None, singleUse=False)" }, { "docstring": "Receive the event", "name": "receive", "signature": "def receive(self, event)" }, { "docstring": "Return the modifie...

3

stack_v2_sparse_classes_30k_train_011938

Implement the Python class `Trigger` described below. Class description: Represents a Triggerable Effect Method signatures and docstrings: - def __init__(self, subject, effect, condition=None, singleUse=False): Initialize the Trigger - def receive(self, event): Receive the event - def getTriggerContext(self, event): ...

0b5a7573a3cf33430fe61e4ff8a8a7a0ae20b258

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Trigger: """Represents a Triggerable Effect""" def __init__(self, subject, effect, condition=None, singleUse=False): """Initialize the Trigger""" self.subject = subject self.condition = condition self.effect = effect self.singleUse = singleUse self.parent =...

the_stack_v2_python_sparse

src/Game/Effects/Triggers/trigger.py

dfwarden/DeckBuilding

train

0

95a471991bc9e5dd14f77180b6e002b3a149a142

[ "self.t = self.ctx.convert(t)\nif 'degree' in kwargs:\n self.degree = kwargs['degree']\n self.dps_goal = int(1.5 * self.degree)\nelse:\n self.dps_goal = int(self.ctx.dps * 1.74)\n self.degree = max(22, int(1.31 * self.dps_goal))\nM = self.degree + 1\nself.dps_orig = self.ctx.dps\nself.ctx.dps = self.dps...

<|body_start_0|> self.t = self.ctx.convert(t) if 'degree' in kwargs: self.degree = kwargs['degree'] self.dps_goal = int(1.5 * self.degree) else: self.dps_goal = int(self.ctx.dps * 1.74) self.degree = max(22, int(1.31 * self.dps_goal)) M = s...

Cohen

[ "Apache-2.0", "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Cohen: def calc_laplace_parameter(self, t, **kwargs): """The Cohen algorithm accelerates the convergence of the nearly alternating series resulting from the application of the trapezoidal rule to the Bromwich contour inversion integral. .. math :: p_k = \\frac{\\gamma}{2 t} + \\frac{\\pi...

stack_v2_sparse_classes_36k_train_008305

36,056

permissive

[ { "docstring": "The Cohen algorithm accelerates the convergence of the nearly alternating series resulting from the application of the trapezoidal rule to the Bromwich contour inversion integral. .. math :: p_k = \\\\frac{\\\\gamma}{2 t} + \\\\frac{\\\\pi i k}{t} \\\\qquad 0 \\\\le k < M where .. math :: \\\\ga...

2

null

Implement the Python class `Cohen` described below. Class description: Implement the Cohen class. Method signatures and docstrings: - def calc_laplace_parameter(self, t, **kwargs): The Cohen algorithm accelerates the convergence of the nearly alternating series resulting from the application of the trapezoidal rule t...

f5042e35b945aded77b23470ead62d7eacefde92

<|skeleton|> class Cohen: def calc_laplace_parameter(self, t, **kwargs): """The Cohen algorithm accelerates the convergence of the nearly alternating series resulting from the application of the trapezoidal rule to the Bromwich contour inversion integral. .. math :: p_k = \\frac{\\gamma}{2 t} + \\frac{\\pi...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Cohen: def calc_laplace_parameter(self, t, **kwargs): """The Cohen algorithm accelerates the convergence of the nearly alternating series resulting from the application of the trapezoidal rule to the Bromwich contour inversion integral. .. math :: p_k = \\frac{\\gamma}{2 t} + \\frac{\\pi i k}{t} \\qqu...

the_stack_v2_python_sparse

contrib/python/mpmath/mpmath/calculus/inverselaplace.py

catboost/catboost

train

8,012

dec36a6ffecd6e3f8acf8aaa6191d412003c8a58

[ "files = self._find(topdir)\ntags = self._read(files)\nreturn tags", "matches = []\nfor root, dirnames, filenames in os.walk(topdir):\n for filename in fnmatch.filter(filenames, '*.mp3'):\n matches.append(os.path.join(root, filename))\nreturn matches", "metadata = []\nfor mp3 in musicfiles:\n filed...

A TagReader reads metadata from .mp3 files and returns it in a list of dictionaries. The only method used outside this file will be readtags().

TagReader

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TagReader: """A TagReader reads metadata from .mp3 files and returns it in a list of dictionaries. The only method used outside this file will be readtags().""" def readtags(self, topdir): """Searches through the given directory for .mp3 files, reads the files' metadata, and returns ...

stack_v2_sparse_classes_36k_train_008306

2,103

no_license

[ { "docstring": "Searches through the given directory for .mp3 files, reads the files' metadata, and returns it in a list of dictionaries.", "name": "readtags", "signature": "def readtags(self, topdir)" }, { "docstring": "Searches through the given music directory for .mp3 files and returns an ar...

3

stack_v2_sparse_classes_30k_train_000097

Implement the Python class `TagReader` described below. Class description: A TagReader reads metadata from .mp3 files and returns it in a list of dictionaries. The only method used outside this file will be readtags(). Method signatures and docstrings: - def readtags(self, topdir): Searches through the given director...

d903ea36887221032342349c90478ce331321e65

<|skeleton|> class TagReader: """A TagReader reads metadata from .mp3 files and returns it in a list of dictionaries. The only method used outside this file will be readtags().""" def readtags(self, topdir): """Searches through the given directory for .mp3 files, reads the files' metadata, and returns ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class TagReader: """A TagReader reads metadata from .mp3 files and returns it in a list of dictionaries. The only method used outside this file will be readtags().""" def readtags(self, topdir): """Searches through the given directory for .mp3 files, reads the files' metadata, and returns it in a list ...

the_stack_v2_python_sparse

project/tagreader.py

paperbackdragon/python-300

train

0

023d378c23d28f319c553c0e7587769e9a768a9d

[ "dummy = tail = ListNode(None)\nwhile head1 and head2:\n if head1.val <= head2.val:\n tail.next = head1\n head1 = head1.next\n else:\n tail.next = head2\n head2 = head2.next\n tail = tail.next\nif head1:\n tail.next = head1\nelif head2:\n tail.next = head2\nreturn dummy.ne...

<|body_start_0|> dummy = tail = ListNode(None) while head1 and head2: if head1.val <= head2.val: tail.next = head1 head1 = head1.next else: tail.next = head2 head2 = head2.next tail = tail.next if...

SolutionDivideAndConquer

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SolutionDivideAndConquer: def merge(self, head1, head2): """Merges two sorted linked lists and returns head of a new list. Time complexity: O(m + n). Space complexity: O(1), m, n are lengths of linked lists.""" <|body_0|> def mergeKLists(self, lists): """Merges sorte...

stack_v2_sparse_classes_36k_train_008307

5,297

no_license

[ { "docstring": "Merges two sorted linked lists and returns head of a new list. Time complexity: O(m + n). Space complexity: O(1), m, n are lengths of linked lists.", "name": "merge", "signature": "def merge(self, head1, head2)" }, { "docstring": "Merges sorted linked lists from array lists into ...

2

null

Implement the Python class `SolutionDivideAndConquer` described below. Class description: Implement the SolutionDivideAndConquer class. Method signatures and docstrings: - def merge(self, head1, head2): Merges two sorted linked lists and returns head of a new list. Time complexity: O(m + n). Space complexity: O(1), m...

71b722ddfe8da04572e527b055cf8723d5c87bbf

<|skeleton|> class SolutionDivideAndConquer: def merge(self, head1, head2): """Merges two sorted linked lists and returns head of a new list. Time complexity: O(m + n). Space complexity: O(1), m, n are lengths of linked lists.""" <|body_0|> def mergeKLists(self, lists): """Merges sorte...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class SolutionDivideAndConquer: def merge(self, head1, head2): """Merges two sorted linked lists and returns head of a new list. Time complexity: O(m + n). Space complexity: O(1), m, n are lengths of linked lists.""" dummy = tail = ListNode(None) while head1 and head2: if head1.v...

the_stack_v2_python_sparse

Linked_Lists/merge_k_sorted_lists.py

vladn90/Algorithms

train

0

a05cc41300b4ea6a33d01bec34f0b3d538212c46

[ "self.arr = arr\ntotal = 0\nself.runningSum = [total]\nfor i in arr:\n total += i\n self.runningSum.append(total)", "if i < 0 or len(self.arr) < j or j <= i:\n return None\nreturn self.runningSum[j] - self.runningSum[i]" ]

Optimized sub list.

SubListSum

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008308

1,070

no_license

[ { "docstring": "Init.", "name": "__init__", "signature": "def __init__(self, arr)" }, { "docstring": "Sum the sublist of arr from i (inc ) to j ( exc ).", "name": "sum", "signature": "def sum(self, i, j)" } ]

2

null

Implement the Python class `SubListSum` described below. Class description: Optimized sub list. Method signatures and docstrings: - def __init__(self, arr): Init. - def sum(self, i, j): Sum the sublist of arr from i (inc ) to j ( exc ).

Implement the Python class `SubListSum` described below. Class description: Optimized sub list. Method signatures and docstrings: - def __init__(self, arr): Init. - def sum(self, i, j): Sum the sublist of arr from i (inc ) to j ( exc ). <|skeleton|> class SubListSum: """Optimized sub list.""" def __init__(s...

d3e1a6ab102c7af1eea4ab6b1282e4d44e5b80ba

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class SubListSum: """Optimized sub list.""" def __init__(self, arr): """Init.""" self.arr = arr total = 0 self.runningSum = [total] for i in arr: total += i self.runningSum.append(total) def sum(self, i, j): """Sum the sublist of arr ...

the_stack_v2_python_sparse

149-sum-sublist.py

ericgarig/daily-coding-problem

train

0

7c330d055d112f38e9faf2031180f17fa572f58c

[ "self.qname = qname\nself.attrs = attrs\nself.text = text or ''\nself.tail = None\nself.child_elements = []", "elt = Element(qname, attrs, text)\nself.child_elements.append(elt)\nreturn elt", "prefix, _ = split_qname(self.qname)\nif prefix:\n prefixes.add(prefix)\nelif '' in prefix_namespaces:\n prefixes....

One element in a document.

Element

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Element: """One element in a document.""" def __init__(self, qname, attrs=None, text=None): """Create instance with this QName and attrs.""" <|body_0|> def add_child(self, qname, attrs=None, text=None): """Create a new element and make it a child of this one.""" ...

stack_v2_sparse_classes_36k_train_008309

4,900

no_license

[ { "docstring": "Create instance with this QName and attrs.", "name": "__init__", "signature": "def __init__(self, qname, attrs=None, text=None)" }, { "docstring": "Create a new element and make it a child of this one.", "name": "add_child", "signature": "def add_child(self, qname, attrs=...

4

null

Implement the Python class `Element` described below. Class description: One element in a document. Method signatures and docstrings: - def __init__(self, qname, attrs=None, text=None): Create instance with this QName and attrs. - def add_child(self, qname, attrs=None, text=None): Create a new element and make it a c...

0075ea457f764cbb67acecb584e927bf58d2e7a8

<|skeleton|> class Element: """One element in a document.""" def __init__(self, qname, attrs=None, text=None): """Create instance with this QName and attrs.""" <|body_0|> def add_child(self, qname, attrs=None, text=None): """Create a new element and make it a child of this one.""" ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Element: """One element in a document.""" def __init__(self, qname, attrs=None, text=None): """Create instance with this QName and attrs.""" self.qname = qname self.attrs = attrs self.text = text or '' self.tail = None self.child_elements = [] def add_...

the_stack_v2_python_sparse

linotak/xml_writer.py

pdc/linotak

train

0

ec2890a4d572bf8a26aade406687be280217d540

[ "if frequency == icdtyp.Frequency.Minutely:\n df = cls._transform_minutely_df(df, trade_symbol_id)\nelif frequency == icdtyp.Frequency.Daily:\n df = cls._transform_daily_df(df, trade_symbol_id)\nelif frequency == icdtyp.Frequency.Tick:\n df = cls._transform_tick_df(df, trade_symbol_id)\nelse:\n dbg.dfat...

<|body_start_0|> if frequency == icdtyp.Frequency.Minutely: df = cls._transform_minutely_df(df, trade_symbol_id) elif frequency == icdtyp.Frequency.Daily: df = cls._transform_daily_df(df, trade_symbol_id) elif frequency == icdtyp.Frequency.Tick: df = cls._tran...

IbS3ToSqlTransformer

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class IbS3ToSqlTransformer: def transform(cls, df: pd.DataFrame, trade_symbol_id: int, frequency: icdtyp.Frequency) -> pd.DataFrame: """Transform IB data loaded from S3 to load to SQL. :param df: dataframe with data from S3 :param trade_symbol_id: symbol id in SQL database :param frequency: da...

stack_v2_sparse_classes_36k_train_008310

3,028

permissive

[ { "docstring": "Transform IB data loaded from S3 to load to SQL. :param df: dataframe with data from S3 :param trade_symbol_id: symbol id in SQL database :param frequency: dataframe frequency :return: processed dataframe", "name": "transform", "signature": "def transform(cls, df: pd.DataFrame, trade_sym...

4

null

Implement the Python class `IbS3ToSqlTransformer` described below. Class description: Implement the IbS3ToSqlTransformer class. Method signatures and docstrings: - def transform(cls, df: pd.DataFrame, trade_symbol_id: int, frequency: icdtyp.Frequency) -> pd.DataFrame: Transform IB data loaded from S3 to load to SQL. ...

363c59fa29df2ba2719cbad2f8a19ae12cc54a92

<|skeleton|> class IbS3ToSqlTransformer: def transform(cls, df: pd.DataFrame, trade_symbol_id: int, frequency: icdtyp.Frequency) -> pd.DataFrame: """Transform IB data loaded from S3 to load to SQL. :param df: dataframe with data from S3 :param trade_symbol_id: symbol id in SQL database :param frequency: da...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class IbS3ToSqlTransformer: def transform(cls, df: pd.DataFrame, trade_symbol_id: int, frequency: icdtyp.Frequency) -> pd.DataFrame: """Transform IB data loaded from S3 to load to SQL. :param df: dataframe with data from S3 :param trade_symbol_id: symbol id in SQL database :param frequency: dataframe freque...

the_stack_v2_python_sparse

im/ib/data/transform/ib_s3_to_sql_transformer.py

srlindemann/amp

train

0

0c80ba8767cc2ef9b8f37ae1ed5c296550bfd226

[ "GenBank.__init__(self, email, api_key, **kwargs)\nself.accessions = accessions\nself.directory = directory\nself.outputfile = outputfile", "for i in range(0, len(self.accessions), self.number_of_requests):\n if self.verbose:\n sys.stderr.write(f'{color.PINK}Chunk {i}-{i + self.number_of_requests}{color...

A genbank download object. This has a directory to store the results and a list of accessions to retrieve.

GenBankDownload

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GenBankDownload: """A genbank download object. This has a directory to store the results and a list of accessions to retrieve.""" def __init__(self, email, api_key, outputfile='sequences.gb', directory='.', accessions=[], **kwargs): """Initialize the object.""" <|body_0|> ...

stack_v2_sparse_classes_36k_train_008311

2,093

permissive

[ { "docstring": "Initialize the object.", "name": "__init__", "signature": "def __init__(self, email, api_key, outputfile='sequences.gb', directory='.', accessions=[], **kwargs)" }, { "docstring": "Split the list into the number of elements to request", "name": "chunk_accessions", "signat...

3

stack_v2_sparse_classes_30k_train_000269

Implement the Python class `GenBankDownload` described below. Class description: A genbank download object. This has a directory to store the results and a list of accessions to retrieve. Method signatures and docstrings: - def __init__(self, email, api_key, outputfile='sequences.gb', directory='.', accessions=[], **...

42575fa93e8a1c53012bbfe292514d95b48fbd9d

<|skeleton|> class GenBankDownload: """A genbank download object. This has a directory to store the results and a list of accessions to retrieve.""" def __init__(self, email, api_key, outputfile='sequences.gb', directory='.', accessions=[], **kwargs): """Initialize the object.""" <|body_0|> ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class GenBankDownload: """A genbank download object. This has a directory to store the results and a list of accessions to retrieve.""" def __init__(self, email, api_key, outputfile='sequences.gb', directory='.', accessions=[], **kwargs): """Initialize the object.""" GenBank.__init__(self, emai...

the_stack_v2_python_sparse

pppf_lib/genbank_download.py

linsalrob/PPPF

train

2

86cdffad3925e3a9e31b6de81edd58eed1fadb92

[ "self.lookup = collections.defaultdict(set)\nfor word in dictionary:\n if len(word) > 2:\n new_word = '{0}{1}{2}'.format(word[0], len(word) - 2, word[-1])\n else:\n new_word = word\n self.lookup[new_word].add(word)", "if len(word) > 2:\n new_word = '{0}{1}{2}'.format(word[0], len(word) -...

<|body_start_0|> self.lookup = collections.defaultdict(set) for word in dictionary: if len(word) > 2: new_word = '{0}{1}{2}'.format(word[0], len(word) - 2, word[-1]) else: new_word = word self.lookup[new_word].add(word) <|end_body_0|> ...

ValidWordAbbr

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008312

819

no_license

[ { "docstring": "initialize your data structure here. :type dictionary: List[str]", "name": "__init__", "signature": "def __init__(self, dictionary)" }, { "docstring": "check if a word is unique. :type word: str :rtype: bool", "name": "isUnique", "signature": "def isUnique(self, word)" ...

2

null

Implement the Python class `ValidWordAbbr` described below. Class description: Implement the ValidWordAbbr class. Method signatures and docstrings: - def __init__(self, dictionary): initialize your data structure here. :type dictionary: List[str] - def isUnique(self, word): check if a word is unique. :type word: str ...

c33559dc5e0bf6879bb3462ab65a9446a66d19f6

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ValidWordAbbr: def __init__(self, dictionary): """initialize your data structure here. :type dictionary: List[str]""" self.lookup = collections.defaultdict(set) for word in dictionary: if len(word) > 2: new_word = '{0}{1}{2}'.format(word[0], len(word) - 2, w...

the_stack_v2_python_sparse

288.py

htl1126/leetcode

train

7

45d301b7c70130ef1f17df94957b9eb7a6298ac5

[ "author_data = validated_data.pop('author', None)\nvalidated_data['author'] = get_author(author_data.get('uuid'), author_data.get('node'))\nreturn super(CommentSerializer, self).create(validated_data)", "author_data = validated_data.pop('author', None)\npubDate = validated_data.get('pubDate', None)\nif pubDate an...

A Serializer for the Comment Model

CommentSerializer

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CommentSerializer: """A Serializer for the Comment Model""" def create(self, validated_data): """Creates and return a new `Comment` instance, given the validated data.""" <|body_0|> def update(self, instance, validated_data): """Updates and returns an instance of...

stack_v2_sparse_classes_36k_train_008313

1,729

permissive

[ { "docstring": "Creates and return a new `Comment` instance, given the validated data.", "name": "create", "signature": "def create(self, validated_data)" }, { "docstring": "Updates and returns an instance of the `Comment` Model with validated data", "name": "update", "signature": "def u...

2

stack_v2_sparse_classes_30k_train_008677

Implement the Python class `CommentSerializer` described below. Class description: A Serializer for the Comment Model Method signatures and docstrings: - def create(self, validated_data): Creates and return a new `Comment` instance, given the validated data. - def update(self, instance, validated_data): Updates and r...

a05a5161c415b546084bbe98b00e0671860c9bc6

<|skeleton|> class CommentSerializer: """A Serializer for the Comment Model""" def create(self, validated_data): """Creates and return a new `Comment` instance, given the validated data.""" <|body_0|> def update(self, instance, validated_data): """Updates and returns an instance of...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class CommentSerializer: """A Serializer for the Comment Model""" def create(self, validated_data): """Creates and return a new `Comment` instance, given the validated data.""" author_data = validated_data.pop('author', None) validated_data['author'] = get_author(author_data.get('uuid')...

the_stack_v2_python_sparse

DistributedSocialNetworking/api/serializers/comment_serializer.py

Roshack/cmput410-project

train

0

9a2afa68e12538797ee347b0851e7fc7e6d09114

[ "def partition(left: int, right: int, pivot_index: int) -> int:\n pivot = nums[pivot_index]\n nums[pivot_index], nums[right] = (nums[right], nums[pivot_index])\n store_index = left\n for i in range(left, right):\n if nums[i] < pivot:\n nums[store_index], nums[i] = (nums[i], nums[store_...

<|body_start_0|> def partition(left: int, right: int, pivot_index: int) -> int: pivot = nums[pivot_index] nums[pivot_index], nums[right] = (nums[right], nums[pivot_index]) store_index = left for i in range(left, right): if nums[i] < pivot: ...

Array

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Array: def kth_largest_element_(self, nums: List[int], k: int) -> int: """Approach: Partition Algortihm Time Complexity: O(N) Worst Case: O(N^2) Space Complexity: O(1) :param nums: :param k: :return:""" <|body_0|> def kth_largest_element(self, nums: List[int], k: int) -> int...

stack_v2_sparse_classes_36k_train_008314

2,568

no_license

[ { "docstring": "Approach: Partition Algortihm Time Complexity: O(N) Worst Case: O(N^2) Space Complexity: O(1) :param nums: :param k: :return:", "name": "kth_largest_element_", "signature": "def kth_largest_element_(self, nums: List[int], k: int) -> int" }, { "docstring": "Approach: Heap Time Com...

2

null

Implement the Python class `Array` described below. Class description: Implement the Array class. Method signatures and docstrings: - def kth_largest_element_(self, nums: List[int], k: int) -> int: Approach: Partition Algortihm Time Complexity: O(N) Worst Case: O(N^2) Space Complexity: O(1) :param nums: :param k: :re...

65cc78b5afa0db064f9fe8f06597e3e120f7363d

<|skeleton|> class Array: def kth_largest_element_(self, nums: List[int], k: int) -> int: """Approach: Partition Algortihm Time Complexity: O(N) Worst Case: O(N^2) Space Complexity: O(1) :param nums: :param k: :return:""" <|body_0|> def kth_largest_element(self, nums: List[int], k: int) -> int...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Array: def kth_largest_element_(self, nums: List[int], k: int) -> int: """Approach: Partition Algortihm Time Complexity: O(N) Worst Case: O(N^2) Space Complexity: O(1) :param nums: :param k: :return:""" def partition(left: int, right: int, pivot_index: int) -> int: pivot = nums[piv...

the_stack_v2_python_sparse

amazon/heap/kth_largest_element.py

Shiv2157k/leet_code

train

1

22e4d9702a840cce0e1551289c50561225b4f268

[ "if (image_folder is None) == (image_files is None):\n raise ValueError('One of image_folder and image_files should be provided')\ndataset, preproc_transform = _load_dataset(image_folder, image_files)\nsuper().__init__(dataset, batchsize_per_replica, shuffle, transform, num_samples)\nif preproc_transform is not ...

<|body_start_0|> if (image_folder is None) == (image_files is None): raise ValueError('One of image_folder and image_files should be provided') dataset, preproc_transform = _load_dataset(image_folder, image_files) super().__init__(dataset, batchsize_per_replica, shuffle, transform, n...

Dataset which reads images from a local filesystem. Implements ClassyDataset.

ImagePathDataset

[ "MIT", "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ImagePathDataset: """Dataset which reads images from a local filesystem. Implements ClassyDataset.""" def __init__(self, batchsize_per_replica: int, shuffle: bool, transform: Optional[Union[ClassyTransform, Callable]]=None, num_samples: Optional[int]=None, image_folder: Optional[str]=None, i...

stack_v2_sparse_classes_36k_train_008315

4,706

permissive

[ { "docstring": "Constructor for ImagePathDataset. Only one of image_folder or image_files should be passed to specify the images. Args: batchsize_per_replica: Positive integer indicating batch size for each replica shuffle: Whether we should shuffle between epochs transform: Transform to be applied to each samp...

2

stack_v2_sparse_classes_30k_train_002258

Implement the Python class `ImagePathDataset` described below. Class description: Dataset which reads images from a local filesystem. Implements ClassyDataset. Method signatures and docstrings: - def __init__(self, batchsize_per_replica: int, shuffle: bool, transform: Optional[Union[ClassyTransform, Callable]]=None, ...

08a82e88fcfa143933832994ace2424c03dd43b8

<|skeleton|> class ImagePathDataset: """Dataset which reads images from a local filesystem. Implements ClassyDataset.""" def __init__(self, batchsize_per_replica: int, shuffle: bool, transform: Optional[Union[ClassyTransform, Callable]]=None, num_samples: Optional[int]=None, image_folder: Optional[str]=None, i...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ImagePathDataset: """Dataset which reads images from a local filesystem. Implements ClassyDataset.""" def __init__(self, batchsize_per_replica: int, shuffle: bool, transform: Optional[Union[ClassyTransform, Callable]]=None, num_samples: Optional[int]=None, image_folder: Optional[str]=None, image_files: O...

the_stack_v2_python_sparse

classy_vision/dataset/image_path_dataset.py

facebookresearch/ClassyVision

train

1,673

90f01c7dc72e7a2462fc064b137cf49c22de6ea1

[ "row, col = (len(matrix), len(matrix[0]))\nif matrix[row_index][col_index] == '0':\n return 0\nlength = 1\nmax_size = min(row - row_index, col - col_index)\nfor size in range(1, max_size):\n for i in range(row_index, row_index + size + 1):\n new_col = col_index + size\n if matrix[i][new_col] == ...

<|body_start_0|> row, col = (len(matrix), len(matrix[0])) if matrix[row_index][col_index] == '0': return 0 length = 1 max_size = min(row - row_index, col - col_index) for size in range(1, max_size): for i in range(row_index, row_index + size + 1): ...

Solution

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def get_max(self, matrix: List[List[int]], row_index: int, col_index: int) -> int: """获取最大值 Args: matrix: 二维数组 row_index: 行下标 col_index: 列下标 Returns: 最大长度数量""" <|body_0|> def maximal_square(self, matrix: List[List[chr]]) -> int: """获取最大正方形 Args: matrix: 输入二...

stack_v2_sparse_classes_36k_train_008316

3,418

permissive

[ { "docstring": "获取最大值 Args: matrix: 二维数组 row_index: 行下标 col_index: 列下标 Returns: 最大长度数量", "name": "get_max", "signature": "def get_max(self, matrix: List[List[int]], row_index: int, col_index: int) -> int" }, { "docstring": "获取最大正方形 Args: matrix: 输入二维数组 Returns: 最大正方形数量", "name": "maximal_squ...

3

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def get_max(self, matrix: List[List[int]], row_index: int, col_index: int) -> int: 获取最大值 Args: matrix: 二维数组 row_index: 行下标 col_index: 列下标 Returns: 最大长度数量 - def maximal_square(sel...

50f35eef6a0ad63173efed10df3c835b1dceaa3f

<|skeleton|> class Solution: def get_max(self, matrix: List[List[int]], row_index: int, col_index: int) -> int: """获取最大值 Args: matrix: 二维数组 row_index: 行下标 col_index: 列下标 Returns: 最大长度数量""" <|body_0|> def maximal_square(self, matrix: List[List[chr]]) -> int: """获取最大正方形 Args: matrix: 输入二...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def get_max(self, matrix: List[List[int]], row_index: int, col_index: int) -> int: """获取最大值 Args: matrix: 二维数组 row_index: 行下标 col_index: 列下标 Returns: 最大长度数量""" row, col = (len(matrix), len(matrix[0])) if matrix[row_index][col_index] == '0': return 0 length...

the_stack_v2_python_sparse

src/leetcodepython/array/maximal_square_221.py

zhangyu345293721/leetcode

train

101

7557e2b426cb44ab37acc747abe296de70974d86

[ "Thread.__init__(self)\nself.predict = predict\nself.name = name\nself.faceCascade = faceCascade\nself.is_running = False", "self.is_running = True\nimage_processor = image_processing(frame, self.faceCascade)\nimage_processor.img_prep(face)\nself.name = self.predict.predict_face(image_processor.img)\nif self.name...

A class used to parallelize calculations in order to use the model in realtime Attributes ---------- predict : prediction.predict prediction object use to get the identity of a people on a frame name : string people name faceCascade : cv2.CascadeClassifier cascade object use to localize faces on an image is_running : b...

Name

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Name: """A class used to parallelize calculations in order to use the model in realtime Attributes ---------- predict : prediction.predict prediction object use to get the identity of a people on a frame name : string people name faceCascade : cv2.CascadeClassifier cascade object use to localize ...

stack_v2_sparse_classes_36k_train_008317

2,084

no_license

[ { "docstring": "Parameters ---------- predict : prediction.predict prediction object use to get the identity of a people on a frame name : string identity name faceCascade : cv2.CascadeClassifier cascade object use to localize faces on an image is_running : bool boolean variable that indicates whether the calcu...

2

stack_v2_sparse_classes_30k_train_003802

Implement the Python class `Name` described below. Class description: A class used to parallelize calculations in order to use the model in realtime Attributes ---------- predict : prediction.predict prediction object use to get the identity of a people on a frame name : string people name faceCascade : cv2.CascadeCla...

d1ba87ff5b0f2b58c98f02519073b335cdc55c58

<|skeleton|> class Name: """A class used to parallelize calculations in order to use the model in realtime Attributes ---------- predict : prediction.predict prediction object use to get the identity of a people on a frame name : string people name faceCascade : cv2.CascadeClassifier cascade object use to localize ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Name: """A class used to parallelize calculations in order to use the model in realtime Attributes ---------- predict : prediction.predict prediction object use to get the identity of a people on a frame name : string people name faceCascade : cv2.CascadeClassifier cascade object use to localize faces on an i...

the_stack_v2_python_sparse

AI/face_recognition/thread_pred.py

cemot/DaVinciBot-InMoov-2020-2021

train

0

29ee016a4f20be96d35e962054f723be2bffada2

[ "self.internreferanse_field = internreferanse_field\nself.fodt_dato_field = APIHelper.RFC3339DateTime(fodt_dato_field) if fodt_dato_field else None\nself.fodt_dato_field_specified = fodt_dato_field_specified\nself.navn_field = navn_field\nself.adresse_field = adresse_field\nself.postnr_field = postnr_field\nself.po...

<|body_start_0|> self.internreferanse_field = internreferanse_field self.fodt_dato_field = APIHelper.RFC3339DateTime(fodt_dato_field) if fodt_dato_field else None self.fodt_dato_field_specified = fodt_dato_field_specified self.navn_field = navn_field self.adresse_field = adresse_...

Implementation of the 'Rettighetshavere' model. TODO: type model description here. Attributes: internreferanse_field (long|int): TODO: type description here. fodt_dato_field (datetime): TODO: type description here. fodt_dato_field_specified (bool): TODO: type description here. navn_field (string): TODO: type descriptio...

Rettighetshavere

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Rettighetshavere: """Implementation of the 'Rettighetshavere' model. TODO: type model description here. Attributes: internreferanse_field (long|int): TODO: type description here. fodt_dato_field (datetime): TODO: type description here. fodt_dato_field_specified (bool): TODO: type description here...

stack_v2_sparse_classes_36k_train_008318

4,475

permissive

[ { "docstring": "Constructor for the Rettighetshavere class", "name": "__init__", "signature": "def __init__(self, internreferanse_field=None, fodt_dato_field=None, fodt_dato_field_specified=None, navn_field=None, adresse_field=None, postnr_field=None, poststed_field=None, andel_field=None, indirekte_eie...

2

null

Implement the Python class `Rettighetshavere` described below. Class description: Implementation of the 'Rettighetshavere' model. TODO: type model description here. Attributes: internreferanse_field (long|int): TODO: type description here. fodt_dato_field (datetime): TODO: type description here. fodt_dato_field_specif...

fa3918a6c54ea0eedb9146578645b7eb1755b642

<|skeleton|> class Rettighetshavere: """Implementation of the 'Rettighetshavere' model. TODO: type model description here. Attributes: internreferanse_field (long|int): TODO: type description here. fodt_dato_field (datetime): TODO: type description here. fodt_dato_field_specified (bool): TODO: type description here...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Rettighetshavere: """Implementation of the 'Rettighetshavere' model. TODO: type model description here. Attributes: internreferanse_field (long|int): TODO: type description here. fodt_dato_field (datetime): TODO: type description here. fodt_dato_field_specified (bool): TODO: type description here. navn_field ...

the_stack_v2_python_sparse

idfy_rest_client/models/rettighetshavere.py

dealflowteam/Idfy

train

0

eb4c5fc86dff7c664005e51d55409b6086e660bf

[ "is_in_time_interval.return_value = (False, datetime(2019, 1, 1, 8, 0, 0))\nsend_message(None)\nretry.assert_called_once_with(eta=datetime(2019, 1, 1, 8, 0, 0))", "is_in_time_interval.return_value = (True, datetime(2019, 1, 1, 8, 0, 0))\nsend_message(None)\nretry.assert_not_called()" ]

SendMessageTests

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SendMessageTests: def test_retry_outside_of_safe_time(self, is_in_time_interval, retry): """If we are outside of the safe sending time, then we should retry""" <|body_0|> def test_no_retry_inside_of_safe_time(self, is_in_time_interval, retry): """If we are inside the...

stack_v2_sparse_classes_36k_train_008319

1,224

permissive

[ { "docstring": "If we are outside of the safe sending time, then we should retry", "name": "test_retry_outside_of_safe_time", "signature": "def test_retry_outside_of_safe_time(self, is_in_time_interval, retry)" }, { "docstring": "If we are inside the safe sending time, then we should send the me...

2

stack_v2_sparse_classes_30k_test_000213

Implement the Python class `SendMessageTests` described below. Class description: Implement the SendMessageTests class. Method signatures and docstrings: - def test_retry_outside_of_safe_time(self, is_in_time_interval, retry): If we are outside of the safe sending time, then we should retry - def test_no_retry_inside...

d90ef4dc9fa248df97ca97f07569c6c70afcd1bd

<|skeleton|> class SendMessageTests: def test_retry_outside_of_safe_time(self, is_in_time_interval, retry): """If we are outside of the safe sending time, then we should retry""" <|body_0|> def test_no_retry_inside_of_safe_time(self, is_in_time_interval, retry): """If we are inside the...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class SendMessageTests: def test_retry_outside_of_safe_time(self, is_in_time_interval, retry): """If we are outside of the safe sending time, then we should retry""" is_in_time_interval.return_value = (False, datetime(2019, 1, 1, 8, 0, 0)) send_message(None) retry.assert_called_once_...

the_stack_v2_python_sparse

message_sender/test_tasks.py

praekeltfoundation/seed-message-sender

train

0

e2a24c4e7c8e369d2f4267652c1940486e416620

[ "if len(nums) == 0:\n return None\nself.sums = [0 for _ in range(len(nums))]\nself.sums[0] = nums[0]\nfor i in range(1, len(nums)):\n self.sums[i] = self.sums[i - 1] + nums[i]", "if i > 0 and j > 0:\n return self.sums[j] - self.sums[i - 1]\nelse:\n return self.sums[j]" ]

NumArray

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008320

1,117

no_license

[ { "docstring": ":type nums: List[int]", "name": "__init__", "signature": "def __init__(self, nums)" }, { "docstring": ":type i: int :type j: int :rtype: int", "name": "sumRange", "signature": "def sumRange(self, i, j)" } ]

2

stack_v2_sparse_classes_30k_train_020474

Implement the Python class `NumArray` described below. Class description: Implement the NumArray class. Method signatures and docstrings: - def __init__(self, nums): :type nums: List[int] - def sumRange(self, i, j): :type i: int :type j: int :rtype: int

Implement the Python class `NumArray` described below. Class description: Implement the NumArray class. Method signatures and docstrings: - def __init__(self, nums): :type nums: List[int] - def sumRange(self, i, j): :type i: int :type j: int :rtype: int <|skeleton|> class NumArray: def __init__(self, nums): ...

7fa160362ebb58e7286b490012542baa2d51e5c9

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class NumArray: def __init__(self, nums): """:type nums: List[int]""" if len(nums) == 0: return None self.sums = [0 for _ in range(len(nums))] self.sums[0] = nums[0] for i in range(1, len(nums)): self.sums[i] = self.sums[i - 1] + nums[i] def sumRa...

the_stack_v2_python_sparse

sum/range_sum_query.py

gerrycfchang/leetcode-python

train

2

1302e58baa08a2603260d5c737a9804ae140fa9a

[ "current_node = self.head\nwhile current_node is not None:\n if current_node.value[0] == key:\n return current_node.value[1]\n current_node = current_node.next_value\nreturn None", "if self.head is not None:\n current_node = self.head\n idx = 0\n while current_node is not None:\n if c...

This class describes nodes for Hash Table

HashNodeList

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008321

2,293

no_license

[ { "docstring": "This method checks node exist in Hash Table", "name": "check_node_exist", "signature": "def check_node_exist(self, key)" }, { "docstring": "This method removes node of Hash Table by key", "name": "delete_node", "signature": "def delete_node(self, key)" } ]

2

stack_v2_sparse_classes_30k_train_011256

Implement the Python class `HashNodeList` described below. Class description: This class describes nodes for Hash Table Method signatures and docstrings: - def check_node_exist(self, key): This method checks node exist in Hash Table - def delete_node(self, key): This method removes node of Hash Table by key

Implement the Python class `HashNodeList` described below. Class description: This class describes nodes for Hash Table Method signatures and docstrings: - def check_node_exist(self, key): This method checks node exist in Hash Table - def delete_node(self, key): This method removes node of Hash Table by key <|skelet...

9e9fd6583ef4f586c3b4d8cae06c23bdff89c35a

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class HashNodeList: """This class describes nodes for Hash Table""" def check_node_exist(self, key): """This method checks node exist in Hash Table""" current_node = self.head while current_node is not None: if current_node.value[0] == key: return current_nod...

the_stack_v2_python_sparse

data_structures/basic_data_structure/hash_table.py

Mariia-Kosorotykova/python-education

train

0

3e5f1255c2276781a1a4f553bef9fa53919a388e

[ "beta = parameters['beta'].value\ngamma = parameters['gamma'].value\nsigma = parameters['sigma'].value\neta = parameters['eta'].value\nT_quarantine = parameters['T'].value\nK = parameters['K'].value\nassert len(y) == 6 * K, f'Error: SEIRCM states not organized into {K} age groups!'\ndydt = [0] * len(y)\n\ndef epsil...

<|body_start_0|> beta = parameters['beta'].value gamma = parameters['gamma'].value sigma = parameters['sigma'].value eta = parameters['eta'].value T_quarantine = parameters['T'].value K = parameters['K'].value assert len(y) == 6 * K, f'Error: SEIRCM states not org...

Age-structured SEIRCM Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf

SEIRCMAgeStratified

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SEIRCMAgeStratified: """Age-structured SEIRCM Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf""" def calibrate(cls, y: list, t: float, parameters: Parameters) -> list: """SEIR model derivatives at t. :param y: variables that we are solving for i.e. [...

stack_v2_sparse_classes_36k_train_008322

29,649

permissive

[ { "docstring": "SEIR model derivatives at t. :param y: variables that we are solving for i.e. [S]usceptible, [E]xposed, [I]nfected, [R]emoved, [C]ases, [M]ortality :param t: time parameter :param parameters: parameters of the model (not including initial conditions) i.e. beta, gamma, sigma, eta, epsilon :return...

2

null

Implement the Python class `SEIRCMAgeStratified` described below. Class description: Age-structured SEIRCM Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf Method signatures and docstrings: - def calibrate(cls, y: list, t: float, parameters: Parameters) -> list: SEIR model derivatives...

4cf8ec75c4d85b16ec08371c46cc1a9ede9d72a2

<|skeleton|> class SEIRCMAgeStratified: """Age-structured SEIRCM Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf""" def calibrate(cls, y: list, t: float, parameters: Parameters) -> list: """SEIR model derivatives at t. :param y: variables that we are solving for i.e. [...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class SEIRCMAgeStratified: """Age-structured SEIRCM Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf""" def calibrate(cls, y: list, t: float, parameters: Parameters) -> list: """SEIR model derivatives at t. :param y: variables that we are solving for i.e. [S]usceptible,...

the_stack_v2_python_sparse

gs_quant/models/epidemiology.py

goldmansachs/gs-quant

train

2,088

933c17fa7a81e3805b9e3c86a4cc5973c6159718

[ "try:\n return json_encode(packet.get_dict())\nexcept Exception as e:\n logger.debug('can not serialize packet to text: %s' % e)\n return None", "if 'code' not in data or not data['code']:\n raise Exception('packet data must contain non-empty \"code\" field')\nif len(data['code'].split(':')) != 2:\n ...

Класс сериализации/десериализации сообщений.

Converter

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Converter: """Класс сериализации/десериализации сообщений.""" def serialize(cls, packet): """Превращает пакет в текст. @param message: dmgame.packets.outcoming.OutcomingPacket @return: string""" <|body_0|> def _check_packet_data(cls, data): """Проверяет корректно...

stack_v2_sparse_classes_36k_train_008323

2,353

no_license

[ { "docstring": "Превращает пакет в текст. @param message: dmgame.packets.outcoming.OutcomingPacket @return: string", "name": "serialize", "signature": "def serialize(cls, packet)" }, { "docstring": "Проверяет корректность данных пакета. @param data: dict", "name": "_check_packet_data", "...

4

stack_v2_sparse_classes_30k_train_002945

Implement the Python class `Converter` described below. Class description: Класс сериализации/десериализации сообщений. Method signatures and docstrings: - def serialize(cls, packet): Превращает пакет в текст. @param message: dmgame.packets.outcoming.OutcomingPacket @return: string - def _check_packet_data(cls, data)...

c1d6f129ce321b9bfa448442a33ac89eb0ccd3ee

<|skeleton|> class Converter: """Класс сериализации/десериализации сообщений.""" def serialize(cls, packet): """Превращает пакет в текст. @param message: dmgame.packets.outcoming.OutcomingPacket @return: string""" <|body_0|> def _check_packet_data(cls, data): """Проверяет корректно...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Converter: """Класс сериализации/десериализации сообщений.""" def serialize(cls, packet): """Превращает пакет в текст. @param message: dmgame.packets.outcoming.OutcomingPacket @return: string""" try: return json_encode(packet.get_dict()) except Exception as e: ...

the_stack_v2_python_sparse

dmgame/servers/ws/converter.py

micdm/dmgame-server

train

0

4ac5f763bfd8ded430ed0e586212cbe7aeb70ce0

[ "decorator_name = ''.join(('@', Reduction.__name__.lower()))\nself.decorator_name = decorator_name\nself.args = args\nself.kwargs = kwargs\nself.scope = CONTEXT.in_pycompss()\nself.core_element = None\nself.core_element_configured = False\nif self.scope:\n check_arguments(MANDATORY_ARGUMENTS, DEPRECATED_ARGUMENT...

<|body_start_0|> decorator_name = ''.join(('@', Reduction.__name__.lower())) self.decorator_name = decorator_name self.args = args self.kwargs = kwargs self.scope = CONTEXT.in_pycompss() self.core_element = None self.core_element_configured = False if self...

Reduction decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on Reduction task creation.

Reduction

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Reduction: """Reduction decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on Reduction task creation.""" def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None: """Store arguments passed to the decorator. s...

stack_v2_sparse_classes_36k_train_008324

7,263

permissive

[ { "docstring": "Store arguments passed to the decorator. self = itself. args = not used. kwargs = dictionary with the given Reduce parameters :param args: Arguments :param kwargs: Keyword arguments", "name": "__init__", "signature": "def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None" ...

4

null

Implement the Python class `Reduction` described below. Class description: Reduction decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on Reduction task creation. Method signatures and docstrings: - def __init__(self, *args: typing.Any, **kwargs: typing...

5f7a31436d0e6f5acbeb66fa36ab8aad18dc4092

<|skeleton|> class Reduction: """Reduction decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on Reduction task creation.""" def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None: """Store arguments passed to the decorator. s...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Reduction: """Reduction decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on Reduction task creation.""" def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None: """Store arguments passed to the decorator. self = itself....

the_stack_v2_python_sparse

compss/programming_model/bindings/python/src/pycompss/api/reduction.py

bsc-wdc/compss

train

39

7eb323ed5105d95a645bbb42cf8da571db09bbac

[ "super().__init__(list_of_modules_to_winnow, reshape, in_place, verbose)\ndebug_level = logger.getEffectiveLevel()\nlogger.debug('Current log level: %s', debug_level)\nself._conn_graph = ConnectedGraph(sess.graph, input_op_names, output_op_names)\nself._modules_by_name = None\nself._mask_propagator = MaskPropagator...

<|body_start_0|> super().__init__(list_of_modules_to_winnow, reshape, in_place, verbose) debug_level = logger.getEffectiveLevel() logger.debug('Current log level: %s', debug_level) self._conn_graph = ConnectedGraph(sess.graph, input_op_names, output_op_names) self._modules_by_nam...

The MaskPropagationWinnower class implements winnowing based on propagating masks corresponding to each module's input channels identified to be winnowed.

MaskPropagationWinnower

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MaskPropagationWinnower: """The MaskPropagationWinnower class implements winnowing based on propagating masks corresponding to each module's input channels identified to be winnowed.""" def __init__(self, sess: tf.compat.v1.Session, input_op_names: List[str], output_op_names: List[str], list...

stack_v2_sparse_classes_36k_train_008325

9,289

permissive

[ { "docstring": "MaskPropagationWinnower object initialization. :param sess: The model to be winnowed. :param input_op_names: Input operations to the model. :param output_op_names: List of output op names of the model, used to help ConnectedGraph determine valid ops (to ignore training ops for example). :param l...

5

null

Implement the Python class `MaskPropagationWinnower` described below. Class description: The MaskPropagationWinnower class implements winnowing based on propagating masks corresponding to each module's input channels identified to be winnowed. Method signatures and docstrings: - def __init__(self, sess: tf.compat.v1....

5a406e657082b6a4f6e4bf48f0e46e085cb1e351

<|skeleton|> class MaskPropagationWinnower: """The MaskPropagationWinnower class implements winnowing based on propagating masks corresponding to each module's input channels identified to be winnowed.""" def __init__(self, sess: tf.compat.v1.Session, input_op_names: List[str], output_op_names: List[str], list...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class MaskPropagationWinnower: """The MaskPropagationWinnower class implements winnowing based on propagating masks corresponding to each module's input channels identified to be winnowed.""" def __init__(self, sess: tf.compat.v1.Session, input_op_names: List[str], output_op_names: List[str], list_of_modules_t...

the_stack_v2_python_sparse

TrainingExtensions/tensorflow/src/python/aimet_tensorflow/winnow/mask_propagation_winnower.py

quic/aimet

train

1,676

2535decd5c6f5ff9e24e08b2da00da8d1d2ddd97

[ "self.__neighbours = NearestNeighbors(n_neighbors=1)\nself.__neighbours.fit(mapping.colours)\nself.minerals = list(mapping.minerals)\nself.fields = fields or {}", "data = image.convert('RGB').tobytes()\narray = np.frombuffer(data, dtype=np.uint8).reshape(-1, 3)\ndistances, indices = self.__neighbours.kneighbors(a...

<|body_start_0|> self.__neighbours = NearestNeighbors(n_neighbors=1) self.__neighbours.fit(mapping.colours) self.minerals = list(mapping.minerals) self.fields = fields or {} <|end_body_0|> <|body_start_1|> data = image.convert('RGB').tobytes() array = np.frombuffer(data,...

The ImageDataExtractor class combines tools to extract data from images via transformations

ImageDataExtractor

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ImageDataExtractor: """The ImageDataExtractor class combines tools to extract data from images via transformations""" def __init__(self, mapping: ColourMapping, fields: Optional[Dict[str, Field]]=None): """Construct the extractor using a colour mapping appropriate to the images to be...

stack_v2_sparse_classes_36k_train_008326

3,069

permissive

[ { "docstring": "Construct the extractor using a colour mapping appropriate to the images to be supplied. The mapping should assign a mineral name to each colour in the image. Parameters ---------- mapping : A mapping between minerals and colours", "name": "__init__", "signature": "def __init__(self, map...

3

stack_v2_sparse_classes_30k_train_008655

Implement the Python class `ImageDataExtractor` described below. Class description: The ImageDataExtractor class combines tools to extract data from images via transformations Method signatures and docstrings: - def __init__(self, mapping: ColourMapping, fields: Optional[Dict[str, Field]]=None): Construct the extract...

7343e352cecfabb0e19c0ce97d02cd7d9ddf0631

<|skeleton|> class ImageDataExtractor: """The ImageDataExtractor class combines tools to extract data from images via transformations""" def __init__(self, mapping: ColourMapping, fields: Optional[Dict[str, Field]]=None): """Construct the extractor using a colour mapping appropriate to the images to be...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ImageDataExtractor: """The ImageDataExtractor class combines tools to extract data from images via transformations""" def __init__(self, mapping: ColourMapping, fields: Optional[Dict[str, Field]]=None): """Construct the extractor using a colour mapping appropriate to the images to be supplied. Th...

the_stack_v2_python_sparse

steinbit/core/imagedataextractor.py

rocktype/steinbit

train

0

73d5a2f05e89ae64a530c141d9d9ec3c4a6eefe0

[ "self.filename = filename\nself.bias_polarisation = bias_polarisation\nwith open(self.filename, 'rb') as input:\n self.exec_path, self.tmax, self.nc, self.nRuns, self.initSim, self.sValues, self.seed, self.seeds, self.N, self.lp, self.phi, self._tau, self.dt, self.tSCGF, self.activeWork, self.activeWorkForce, se...

<|body_start_0|> self.filename = filename self.bias_polarisation = bias_polarisation with open(self.filename, 'rb') as input: self.exec_path, self.tmax, self.nc, self.nRuns, self.initSim, self.sValues, self.seed, self.seeds, self.N, self.lp, self.phi, self._tau, self.dt, self.tSCGF, ...

Read and analyse aggregated data from cloning simulations launched with active_work.cloning.

CloningOutput

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CloningOutput: """Read and analyse aggregated data from cloning simulations launched with active_work.cloning.""" def __init__(self, filename, bias_polarisation=False): """Get data. Parameters ---------- filename : string Path to data file. bias_polarisation : bool Cloning data corre...

stack_v2_sparse_classes_36k_train_008327

26,002

permissive

[ { "docstring": "Get data. Parameters ---------- filename : string Path to data file. bias_polarisation : bool Cloning data corresponds to simulation biased with respect to the polarisation. (default: False)", "name": "__init__", "signature": "def __init__(self, filename, bias_polarisation=False)" }, ...

2

stack_v2_sparse_classes_30k_train_006348

Implement the Python class `CloningOutput` described below. Class description: Read and analyse aggregated data from cloning simulations launched with active_work.cloning. Method signatures and docstrings: - def __init__(self, filename, bias_polarisation=False): Get data. Parameters ---------- filename : string Path ...

99107a0d4935296b673f67469c1e2bd258954b9b

<|skeleton|> class CloningOutput: """Read and analyse aggregated data from cloning simulations launched with active_work.cloning.""" def __init__(self, filename, bias_polarisation=False): """Get data. Parameters ---------- filename : string Path to data file. bias_polarisation : bool Cloning data corre...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class CloningOutput: """Read and analyse aggregated data from cloning simulations launched with active_work.cloning.""" def __init__(self, filename, bias_polarisation=False): """Get data. Parameters ---------- filename : string Path to data file. bias_polarisation : bool Cloning data corresponds to sim...

the_stack_v2_python_sparse

cloning.py

yketa/active_work

train

1

ab25c9316ecac532f9d7e71bf23c412ca504a29d

[ "self.__screen = screen\nself.__msg = TextboxReflowed(40, 'The system configuration is completed. Exit from the configuration tool and log into the system.')\nself.__buttonsBar = ButtonBar(self.__screen, [('Exit', 'exit')])\nself.__grid = GridForm(self.__screen, 'IBM zKVM', 1, 2)\nself.__grid.add(self.__msg, 0, 0)\...

<|body_start_0|> self.__screen = screen self.__msg = TextboxReflowed(40, 'The system configuration is completed. Exit from the configuration tool and log into the system.') self.__buttonsBar = ButtonBar(self.__screen, [('Exit', 'exit')]) self.__grid = GridForm(self.__screen, 'IBM zKVM', ...

Last screen for the configuration application

ConfigCompleted

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ConfigCompleted: """Last screen for the configuration application""" def __init__(self, screen): """Constructor @type screen: SnackScreen @param screen: SnackScreen instance""" <|body_0|> def run(self): """Draws the screen @rtype: integer @returns: sucess status"...

stack_v2_sparse_classes_36k_train_008328

996

no_license

[ { "docstring": "Constructor @type screen: SnackScreen @param screen: SnackScreen instance", "name": "__init__", "signature": "def __init__(self, screen)" }, { "docstring": "Draws the screen @rtype: integer @returns: sucess status", "name": "run", "signature": "def run(self)" } ]

2

stack_v2_sparse_classes_30k_train_019666

Implement the Python class `ConfigCompleted` described below. Class description: Last screen for the configuration application Method signatures and docstrings: - def __init__(self, screen): Constructor @type screen: SnackScreen @param screen: SnackScreen instance - def run(self): Draws the screen @rtype: integer @re...

1c738fd5e6ee3f8fd4f47acf2207038f20868212

<|skeleton|> class ConfigCompleted: """Last screen for the configuration application""" def __init__(self, screen): """Constructor @type screen: SnackScreen @param screen: SnackScreen instance""" <|body_0|> def run(self): """Draws the screen @rtype: integer @returns: sucess status"...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ConfigCompleted: """Last screen for the configuration application""" def __init__(self, screen): """Constructor @type screen: SnackScreen @param screen: SnackScreen instance""" self.__screen = screen self.__msg = TextboxReflowed(40, 'The system configuration is completed. Exit fro...

the_stack_v2_python_sparse

zfrobisher-installer/src/ui/systemconfig/configcompleted.py

fedosu85nce/work

train

2

ca53850649ed3c3cbf06f49f91cc804519fdbf37

[ "super(Application, self).__init__(master)\nself.grid()\nself.create_widgets()", "Label(self, text='Choose your favorite movie types').grid(row=0, column=0, sticky=W)\nLabel(self, text='Select all that apply').grid(row=1, column=0, sticky=W)\nself.favorite = StringVar()\nself.favorite.set(None)\nRadiobutton(self,...

GUI Application for favorite movie types.

Application

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008329

2,164

no_license

[ { "docstring": "Initialiaze the frame.", "name": "__init__", "signature": "def __init__(self, master)" }, { "docstring": "Create widgets for movie type choices", "name": "create_widgets", "signature": "def create_widgets(self)" }, { "docstring": "Update the text area and dispaly ...

3

stack_v2_sparse_classes_30k_train_019548

Implement the Python class `Application` described below. Class description: GUI Application for favorite movie types. Method signatures and docstrings: - def __init__(self, master): Initialiaze the frame. - def create_widgets(self): Create widgets for movie type choices - def update_text(self): Update the text area ...

2e96474567d31988944a865aad35dc8ae63a990a

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Application: """GUI Application for favorite movie types.""" def __init__(self, master): """Initialiaze the frame.""" super(Application, self).__init__(master) self.grid() self.create_widgets() def create_widgets(self): """Create widgets for movie type choices...

the_stack_v2_python_sparse

Chapter 10/movie_chooser2.py

dguzman96/Python-Practice

train

0

af788f1b33b24a6c2c3e80cb974c69b73c94106a

[ "try:\n login_options = OrgService.get_login_options_for_org(org_id, allowed_roles=ALL_ALLOWED_ROLES)\n response, status = (jsonify({'loginOption': login_options.login_source if login_options else None}), http_status.HTTP_200_OK)\nexcept BusinessException as exception:\n response, status = ({'code': except...

<|body_start_0|> try: login_options = OrgService.get_login_options_for_org(org_id, allowed_roles=ALL_ALLOWED_ROLES) response, status = (jsonify({'loginOption': login_options.login_source if login_options else None}), http_status.HTTP_200_OK) except BusinessException as exception:...

Resource for managing org login options.

OrgLoginOptions

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008330

30,185

permissive

[ { "docstring": "Retrieve the set of payment settings associated with the specified org.", "name": "get", "signature": "def get(org_id)" }, { "docstring": "Create a new login type for the specified org.", "name": "post", "signature": "def post(org_id)" }, { "docstring": "Update a ...

3

stack_v2_sparse_classes_30k_train_012711

Implement the Python class `OrgLoginOptions` described below. Class description: Resource for managing org login options. Method signatures and docstrings: - def get(org_id): Retrieve the set of payment settings associated with the specified org. - def post(org_id): Create a new login type for the specified org. - de...

923cb8a3ee88dcbaf0fe800ca70022b3c13c1d01

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class OrgLoginOptions: """Resource for managing org login options.""" def get(org_id): """Retrieve the set of payment settings associated with the specified org.""" try: login_options = OrgService.get_login_options_for_org(org_id, allowed_roles=ALL_ALLOWED_ROLES) respons...

the_stack_v2_python_sparse

auth-api/src/auth_api/resources/org.py

bcgov/sbc-auth

train

13

53fc07946786b13849ac4b77ff5a580876c24102

[ "self.request = requests.Session()\nself.headers = dict()\nif user_agent is None:\n self.headers['User-Agent'] = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36'\nelse:\n self.headers['User-Agent'] = user_agent\nself.query_string_param...

<|body_start_0|> self.request = requests.Session() self.headers = dict() if user_agent is None: self.headers['User-Agent'] = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36' else: self.head...

Stock

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Stock: def __init__(self, user_agent: str=None): """请求参数初始化 :type user_agent: str :param:浏览器""" <|body_0|> def get_real_time_a_stock(self, page: int, block: int=2, number: int=50) -> list: """获取泸深A股实时数据 :rtype: iterable[dict] :param page: 第几页,范围为1-43 :param block: 请求...

stack_v2_sparse_classes_36k_train_008331

5,700

no_license

[ { "docstring": "请求参数初始化 :type user_agent: str :param:浏览器", "name": "__init__", "signature": "def __init__(self, user_agent: str=None)" }, { "docstring": "获取泸深A股实时数据 :rtype: iterable[dict] :param page: 第几页,范围为1-43 :param block: 请求类型，默认2，暂且支持2 :param number: 一次请求返回多少条数据，建议默认值50 :return:iterable[{\...

3

stack_v2_sparse_classes_30k_train_003995

Implement the Python class `Stock` described below. Class description: Implement the Stock class. Method signatures and docstrings: - def __init__(self, user_agent: str=None): 请求参数初始化 :type user_agent: str :param:浏览器 - def get_real_time_a_stock(self, page: int, block: int=2, number: int=50) -> list: 获取泸深A股实时数据 :rtype...

5e34873cd13950dd3b5dc6341aad144522af0eae

<|skeleton|> class Stock: def __init__(self, user_agent: str=None): """请求参数初始化 :type user_agent: str :param:浏览器""" <|body_0|> def get_real_time_a_stock(self, page: int, block: int=2, number: int=50) -> list: """获取泸深A股实时数据 :rtype: iterable[dict] :param page: 第几页,范围为1-43 :param block: 请求...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Stock: def __init__(self, user_agent: str=None): """请求参数初始化 :type user_agent: str :param:浏览器""" self.request = requests.Session() self.headers = dict() if user_agent is None: self.headers['User-Agent'] = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/5...

the_stack_v2_python_sparse

spyderpro/data_requests/financialmodel/stockmarket.py

LianZS/spyderpro

train

8

c6f53d340217b112e5658222d402cac5ca3b1a8d

[ "get_user = request.user\ndata = get_profile_data(get_user)\nresponse_data = success_response(data=data)\nreturn Response(response_data, status=response_data['code'])", "serializer_data = self.serializer_class(request.user, data=request.data)\nif serializer_data.is_valid():\n user_obj = serializer_data.save()\...

UserProfileView

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008332

12,263

no_license

[ { "docstring": "for Retrieve profile data", "name": "get", "signature": "def get(self, request)" }, { "docstring": "for Update profile data", "name": "post", "signature": "def post(self, request)" } ]

2

stack_v2_sparse_classes_30k_train_014306

Implement the Python class `UserProfileView` described below. Class description: Implement the UserProfileView class. Method signatures and docstrings: - def get(self, request): for Retrieve profile data - def post(self, request): for Update profile data

Implement the Python class `UserProfileView` described below. Class description: Implement the UserProfileView class. Method signatures and docstrings: - def get(self, request): for Retrieve profile data - def post(self, request): for Update profile data <|skeleton|> class UserProfileView: def get(self, request...

41b019e11e2106f57875fc00f85ea6b49d535d86

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class UserProfileView: def get(self, request): """for Retrieve profile data""" get_user = request.user data = get_profile_data(get_user) response_data = success_response(data=data) return Response(response_data, status=response_data['code']) def post(self, request): ...

the_stack_v2_python_sparse

auth/views.py

SimranSingh11/new-fisher-python

train

0

f4729bcec08c3bf70a8b3093e70d4b0dc76e2b04

[ "cumsum = [0]\nfor i in range(len(nums)):\n if i == 0:\n cumsum.append(nums[i])\n else:\n cumsum.append(nums[i] + cumsum[-1])\nfor i in range(len(nums)):\n for j in range(i + 1, len(nums)):\n s = cumsum[j + 1] - cumsum[i]\n if k == 0:\n if s == 0:\n ret...

<|body_start_0|> cumsum = [0] for i in range(len(nums)): if i == 0: cumsum.append(nums[i]) else: cumsum.append(nums[i] + cumsum[-1]) for i in range(len(nums)): for j in range(i + 1, len(nums)): s = cumsum[j + 1] ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008333

3,007

no_license

[ { "docstring": "05/31/2020 17:30", "name": "checkSubarraySum", "signature": "def checkSubarraySum(self, nums: List[int], k: int) -> bool" }, { "docstring": "05/31/2020 17:39", "name": "checkSubarraySum", "signature": "def checkSubarraySum(self, nums: List[int], k: int) -> bool" }, { ...

3

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def checkSubarraySum(self, nums: List[int], k: int) -> bool: 05/31/2020 17:30 - def checkSubarraySum(self, nums: List[int], k: int) -> bool: 05/31/2020 17:39 - def checkSubarrayS...

1389a009a02e90e8700a7a00e0b7f797c129cdf4

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def checkSubarraySum(self, nums: List[int], k: int) -> bool: """05/31/2020 17:30""" cumsum = [0] for i in range(len(nums)): if i == 0: cumsum.append(nums[i]) else: cumsum.append(nums[i] + cumsum[-1]) for i in ran...

the_stack_v2_python_sparse

leetcode/solved/523_Continuous_Subarray_Sum/solution.py

sungminoh/algorithms

train

0

bea7481e77508a599f97dd9d8adb87ef46071178

[ "self.cap = capacity\nself.lookup = {}\nself.tail = None\nself.head = None\nself.counter = 0", "if self.lookup.get(key):\n node = self.lookup[key]\n prev_node = node.prev\n next_node = node.next\n if prev_node:\n prev_node.next = next_node\n else:\n self.head = next_node\n self.tai...

<|body_start_0|> self.cap = capacity self.lookup = {} self.tail = None self.head = None self.counter = 0 <|end_body_0|> <|body_start_1|> if self.lookup.get(key): node = self.lookup[key] prev_node = node.prev next_node = node.next ...

LRUCache

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008334

2,374

no_license

[ { "docstring": ":type capacity: int", "name": "__init__", "signature": "def __init__(self, capacity)" }, { "docstring": ":type key: int :rtype: int", "name": "get", "signature": "def get(self, key)" }, { "docstring": ":type key: int :type value: int :rtype: void", "name": "pu...

3

null

Implement the Python class `LRUCache` described below. Class description: Implement the LRUCache class. Method signatures and docstrings: - def __init__(self, capacity): :type capacity: int - def get(self, key): :type key: int :rtype: int - def put(self, key, value): :type key: int :type value: int :rtype: void

Implement the Python class `LRUCache` described below. Class description: Implement the LRUCache class. Method signatures and docstrings: - def __init__(self, capacity): :type capacity: int - def get(self, key): :type key: int :rtype: int - def put(self, key, value): :type key: int :type value: int :rtype: void <|sk...

5fed58c0cbbaf7dfa6b27282e4914b691f9e0759

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class LRUCache: def __init__(self, capacity): """:type capacity: int""" self.cap = capacity self.lookup = {} self.tail = None self.head = None self.counter = 0 def get(self, key): """:type key: int :rtype: int""" if self.lookup.get(key): ...

the_stack_v2_python_sparse

design/146_lru.py

misa5555/py

train

0

9b5064a672d0fe14038bbd1040b23d0c2811e769

[ "self.size = 10\nself.times = [0 for _ in range(self.size)]\nself.d = collections.defaultdict(set)", "t = timestamp % self.size\nif timestamp != self.times[t]:\n self.d[t] = set()\n self.times[t] = timestamp\nfor i in range(self.size):\n if self.times[i] + 10 > timestamp and message in self.d[i]:\n ...

Logger

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Logger: def __init__(self): """Initialize your data structure here.""" <|body_0|> def shouldPrintMessage(self, timestamp: int, message: str) -> bool: """Returns true if the message should be printed in the given timestamp, otherwise returns false. If this method retu...

stack_v2_sparse_classes_36k_train_008335

2,846

no_license

[ { "docstring": "Initialize your data structure here.", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "Returns true if the message should be printed in the given timestamp, otherwise returns false. If this method returns false, the message will not be printed. The timest...

2

null

Implement the Python class `Logger` described below. Class description: Implement the Logger class. Method signatures and docstrings: - def __init__(self): Initialize your data structure here. - def shouldPrintMessage(self, timestamp: int, message: str) -> bool: Returns true if the message should be printed in the gi...

4c1288c99f78823c7c3bac0ceedd532e64af1258

<|skeleton|> class Logger: def __init__(self): """Initialize your data structure here.""" <|body_0|> def shouldPrintMessage(self, timestamp: int, message: str) -> bool: """Returns true if the message should be printed in the given timestamp, otherwise returns false. If this method retu...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Logger: def __init__(self): """Initialize your data structure here.""" self.size = 10 self.times = [0 for _ in range(self.size)] self.d = collections.defaultdict(set) def shouldPrintMessage(self, timestamp: int, message: str) -> bool: """Returns true if the message...

the_stack_v2_python_sparse

Algorithms/0359 Logger Rate Limiter.py

cravo123/LeetCode

train

6

4170dd059797402dbda541b33d7d8be187e3ee41

[ "self.data_struct = defaultdict()\nself.counter_struct = defaultdict(set)\nself.max_count = 0\nself.min_count = 0", "old_count = 0\nif self.data_struct.get(key):\n old_count = self.data_struct[key]\n new_count = old_count + 1\n self.counter_struct[old_count] -= {key}\n self.data_struct[key] += 1\nelse...

AllOne

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008336

3,617

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. :type key: str :rtype: void", "name": "inc", "signature": "def inc(self, key)" }, ...

5

stack_v2_sparse_classes_30k_train_008868

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): Inserts a new key <Key> with value 1. Or increments an existing key by 1. :type key: str :rtype: void -...

009484a2bb80fed61970558a72670d66d9b71b6b

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class AllOne: def __init__(self): """Initialize your data structure here.""" self.data_struct = defaultdict() self.counter_struct = defaultdict(set) self.max_count = 0 self.min_count = 0 def inc(self, key): """Inserts a new key <Key> with value 1. Or increments a...

the_stack_v2_python_sparse

design_O_1_.py

at3103/Leetcode

train

0

c5005fe514407501cdd06f3d98b7a81109e975e0

[ "super(ScaledDotProductAttention, self).__init__()\nself.scaling = 1 / sqrt(size)\nself.dropout = nn.Dropout(p)", "batch_size, query_len, _ = q.size()\nattention = t.bmm(q, k.transpose(1, 2)) * self.scaling\n'\\n In order to prevent contribution of padding symbols in attention lockup, \\n it is nece...

ScaledDotProductAttention

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ScaledDotProductAttention: def __init__(self, size, p=0.1): """:param size: float number that is necessary for estimation scaling factor :param m_size: int number of size of the window that performing local-m attention. None corresponds to global attention mechanism :param p: drop prob""...

stack_v2_sparse_classes_36k_train_008337

1,623

permissive

[ { "docstring": ":param size: float number that is necessary for estimation scaling factor :param m_size: int number of size of the window that performing local-m attention. None corresponds to global attention mechanism :param p: drop prob", "name": "__init__", "signature": "def __init__(self, size, p=0...

2

stack_v2_sparse_classes_30k_train_007271

Implement the Python class `ScaledDotProductAttention` described below. Class description: Implement the ScaledDotProductAttention class. Method signatures and docstrings: - def __init__(self, size, p=0.1): :param size: float number that is necessary for estimation scaling factor :param m_size: int number of size of ...

6dcca5743ea8750a740c569181ec6998352ef784

<|skeleton|> class ScaledDotProductAttention: def __init__(self, size, p=0.1): """:param size: float number that is necessary for estimation scaling factor :param m_size: int number of size of the window that performing local-m attention. None corresponds to global attention mechanism :param p: drop prob""...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ScaledDotProductAttention: def __init__(self, size, p=0.1): """:param size: float number that is necessary for estimation scaling factor :param m_size: int number of size of the window that performing local-m attention. None corresponds to global attention mechanism :param p: drop prob""" supe...

the_stack_v2_python_sparse

nn/attention/scaled_dot_product.py

kefirski/amt

train

28

268d2ebcc2d4b134ad720e109c366fe9adac7eea

[ "self.ControlDAO = UserDao(controldatabase_name, controldatabase_address)\nself.SISAControlCollectionName = 'Control'\nself.SISAControlLastDateString = 'lastDate'\nself.SISAInformationCollectionName = 'Info'\ndefault_initial_date = '2015-01-01 12:00:00'\nself.numberOfItemsToBatchProcess = 50\nself.SensingDAO = Sens...

<|body_start_0|> self.ControlDAO = UserDao(controldatabase_name, controldatabase_address) self.SISAControlCollectionName = 'Control' self.SISAControlLastDateString = 'lastDate' self.SISAInformationCollectionName = 'Info' default_initial_date = '2015-01-01 12:00:00' self.n...

DataBaseExtractor

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class DataBaseExtractor: def __init__(self, queue, controldatabase_name, controldatabase_address, SensingDAO): """Queue used for working thread send data collected form DB to processing method This class fetches data from sensing database and put on a queue for analysis processing plugin This ...

stack_v2_sparse_classes_36k_train_008338

6,753

permissive

[ { "docstring": "Queue used for working thread send data collected form DB to processing method This class fetches data from sensing database and put on a queue for analysis processing plugin This class mantains a control database to identify the sensig data already processed/analysed This class starts a thread ...

2

stack_v2_sparse_classes_30k_train_020950

Implement the Python class `DataBaseExtractor` described below. Class description: Implement the DataBaseExtractor class. Method signatures and docstrings: - def __init__(self, queue, controldatabase_name, controldatabase_address, SensingDAO): Queue used for working thread send data collected form DB to processing me...

a2d71916b0f1bd79d0f5b444865279530eb6b836

<|skeleton|> class DataBaseExtractor: def __init__(self, queue, controldatabase_name, controldatabase_address, SensingDAO): """Queue used for working thread send data collected form DB to processing method This class fetches data from sensing database and put on a queue for analysis processing plugin This ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class DataBaseExtractor: def __init__(self, queue, controldatabase_name, controldatabase_address, SensingDAO): """Queue used for working thread send data collected form DB to processing method This class fetches data from sensing database and put on a queue for analysis processing plugin This class mantains...

the_stack_v2_python_sparse

sisa/src/informationanalysis/databaseprocessing.py

dmazzer/CogRIoT

train

1

fee352831935669d24c68eafbc5df41218c493d3

[ "self.file_path = file_path\nself.current_row = 0\nself.workbook = ''\nself.sheet = ''\nself.load_workbook()", "if os.path.exists(self.file_path):\n temp_workbook = xlrd.open_workbook(self.file_path)\n self.workbook = copy(temp_workbook)\nelse:\n self.workbook = xlwt.Workbook(encoding='utf-8')", "try:\...

It is for printer discovery tests

Excel

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008339

4,409

no_license

[ { "docstring": "Initialize workbook instance with sheet instance :param file_path: path of Excel file", "name": "__init__", "signature": "def __init__(self, file_path)" }, { "docstring": "Load a workbook :return:", "name": "load_workbook", "signature": "def load_workbook(self)" }, { ...

6

stack_v2_sparse_classes_30k_train_011846

Implement the Python class `Excel` described below. Class description: It is for printer discovery tests Method signatures and docstrings: - def __init__(self, file_path): Initialize workbook instance with sheet instance :param file_path: path of Excel file - def load_workbook(self): Load a workbook :return: - def lo...

b5230c51d3bc7bb04b3448d1a1fe5a076d8898d5

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Excel: """It is for printer discovery tests""" def __init__(self, file_path): """Initialize workbook instance with sheet instance :param file_path: path of Excel file""" self.file_path = file_path self.current_row = 0 self.workbook = '' self.sheet = '' self...

the_stack_v2_python_sparse

MobileApps/libs/ma_misc/excel.py

Amal548/QAMA

train

0

cf5ef9679cd1ec863b2ee1a29df0912ac42c1207

[ "if new_server_name:\n srv_dyn.stop()\n srv_dyn = self.get_server(new_server_name)\n srv_dyn.start()\nclient = self.get_client('client')\nif isinstance(client, Wrk):\n client.duration = self.min_duration\nelse:\n client.options[0] += f' --duration {self.min_duration}'\nclient.start()\nself.wait_while...

<|body_start_0|> if new_server_name: srv_dyn.stop() srv_dyn = self.get_server(new_server_name) srv_dyn.start() client = self.get_client('client') if isinstance(client, Wrk): client.duration = self.min_duration else: client.optio...

Check that server weight is re-calculated based on it's performance.

RatioDynamic

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class RatioDynamic: """Check that server weight is re-calculated based on it's performance.""" def run_test(self, srv_const, srv_dyn, new_server_name=None): """Run wrk and get performance statistics from backends and Tempesta. If 'new_server_name' of 'srv_dyn' is set, first reload its conf...

stack_v2_sparse_classes_36k_train_008340

8,514

no_license

[ { "docstring": "Run wrk and get performance statistics from backends and Tempesta. If 'new_server_name' of 'srv_dyn' is set, first reload its configuration.", "name": "run_test", "signature": "def run_test(self, srv_const, srv_dyn, new_server_name=None)" }, { "docstring": "Calculate weights of s...

3

stack_v2_sparse_classes_30k_test_000817

Implement the Python class `RatioDynamic` described below. Class description: Check that server weight is re-calculated based on it's performance. Method signatures and docstrings: - def run_test(self, srv_const, srv_dyn, new_server_name=None): Run wrk and get performance statistics from backends and Tempesta. If 'ne...

d56358ea653dbb367624937197ce5e489abf0b00

<|skeleton|> class RatioDynamic: """Check that server weight is re-calculated based on it's performance.""" def run_test(self, srv_const, srv_dyn, new_server_name=None): """Run wrk and get performance statistics from backends and Tempesta. If 'new_server_name' of 'srv_dyn' is set, first reload its conf...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class RatioDynamic: """Check that server weight is re-calculated based on it's performance.""" def run_test(self, srv_const, srv_dyn, new_server_name=None): """Run wrk and get performance statistics from backends and Tempesta. If 'new_server_name' of 'srv_dyn' is set, first reload its configuration."""...

the_stack_v2_python_sparse

t_sched/test_ratio_dynamic_recalc.py

tempesta-tech/tempesta-test

train

13

0293f65a4aaa91f7b3cf7565b473eb955d2eec61

[ "self.capacity = capacity\nself.cache = {}\nself.recent = 0", "if key in self.cache:\n self.recent += 1\n self.cache[key][1] = self.recent\n return self.cache[key][0]\nelse:\n return -1", "if key in self.cache:\n self.cache[key][0] = value\nelse:\n if len(self.cache) == self.capacity:\n ...

<|body_start_0|> self.capacity = capacity self.cache = {} self.recent = 0 <|end_body_0|> <|body_start_1|> if key in self.cache: self.recent += 1 self.cache[key][1] = self.recent return self.cache[key][0] else: return -1 <|end_body_...

LRUCache

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008341

3,359

no_license

[ { "docstring": ":type capacity: int", "name": "__init__", "signature": "def __init__(self, capacity)" }, { "docstring": ":type key: int :rtype: int", "name": "get", "signature": "def get(self, key)" }, { "docstring": ":type key: int :type value: int :rtype: void", "name": "pu...

3

null

Implement the Python class `LRUCache` described below. Class description: Implement the LRUCache class. Method signatures and docstrings: - def __init__(self, capacity): :type capacity: int - def get(self, key): :type key: int :rtype: int - def put(self, key, value): :type key: int :type value: int :rtype: void

Implement the Python class `LRUCache` described below. Class description: Implement the LRUCache class. Method signatures and docstrings: - def __init__(self, capacity): :type capacity: int - def get(self, key): :type key: int :rtype: int - def put(self, key, value): :type key: int :type value: int :rtype: void <|sk...

aac41ddd2ec5f6e5c0f46659696ed5b67769bde2

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class LRUCache: def __init__(self, capacity): """:type capacity: int""" self.capacity = capacity self.cache = {} self.recent = 0 def get(self, key): """:type key: int :rtype: int""" if key in self.cache: self.recent += 1 self.cache[key][1]...

the_stack_v2_python_sparse

lru_cache.py

aroraakshit/coding_prep

train

8

0f146d3e5232a742fadb963e253b3a9e1772d28b

[ "if root is None:\n return 0\nres = 0\nif root.val == sum:\n res += 1\nres += self.containNode(root.left, sum - root.val)\nres += self.containNode(root.right, sum - root.val)\nreturn res", "if root is None:\n return 0\nres = self.containNode(root, sum)\nres += self.pathSum(root.left, sum)\nres += self.pa...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008342

1,068

no_license

[ { "docstring": "calcuate how many path is valid from root, that sums up to the given value", "name": "containNode", "signature": "def containNode(self, root, sum)" }, { "docstring": ":type root: TreeNode :type sum: int :rtype: int", "name": "pathSum", "signature": "def pathSum(self, root...

2

stack_v2_sparse_classes_30k_train_017199

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def containNode(self, root, sum): calcuate how many path is valid from root, that sums up to the given value - def pathSum(self, root, sum): :type root: TreeNode :type sum: int :...

f8b35179b980e55f61bbcd2631fa3a9bf30c40ec

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def containNode(self, root, sum): """calcuate how many path is valid from root, that sums up to the given value""" if root is None: return 0 res = 0 if root.val == sum: res += 1 res += self.containNode(root.left, sum - root.val) ...

the_stack_v2_python_sparse

Python Solutions/437 Path Sum III.py

Sue9/Leetcode

train

0

700bd9de354e9003dd116be0ed618626b1a1e6ab

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.incomingCallOptions'.casefold():\n from ...

<|body_start_0|> if not parse_node: raise TypeError('parse_node cannot be null.') try: mapping_value = parse_node.get_child_node('@odata.type').get_str_value() except AttributeError: mapping_value = None if mapping_value and mapping_value.casefold() ==...

CallOptions

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CallOptions: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Ca...

stack_v2_sparse_classes_36k_train_008343

3,943

permissive

[ { "docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: CallOptions", "name": "create_from_discriminator_value", "signature": "def create_from_discriminator_value(p...

3

null

Implement the Python class `CallOptions` described below. Class description: Implement the CallOptions class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: Creates a new instance of the appropriate class based on discriminator value Args:...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class CallOptions: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Ca...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class CallOptions: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CallOptions: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: CallOptions""" ...

the_stack_v2_python_sparse

msgraph/generated/models/call_options.py

microsoftgraph/msgraph-sdk-python

train

135

8b50a8804e58a0b95aac9e05e870fe0678a42afd

[ "if stanza_type is None:\n if element is None:\n raise ValueError('Missing iq type')\nelif stanza_type not in IQ_TYPES:\n raise ValueError('Bad iq type')\nif element is None and stanza_id is None and (stanza_type in ('get', 'set')):\n stanza_id = self.gen_id()\nif element is None:\n element = 'iq...

<|body_start_0|> if stanza_type is None: if element is None: raise ValueError('Missing iq type') elif stanza_type not in IQ_TYPES: raise ValueError('Bad iq type') if element is None and stanza_id is None and (stanza_type in ('get', 'set')): sta...

<message /> stanza class.

Iq

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Iq: """<message /> stanza class.""" def __init__(self, element=None, from_jid=None, to_jid=None, stanza_type=None, stanza_id=None, error=None, error_cond=None, return_path=None, language=None): """Initialize an `Iq` object. :Parameters: - `element`: XML element of this stanza. - `fro...

stack_v2_sparse_classes_36k_train_008344

6,218

permissive

[ { "docstring": "Initialize an `Iq` object. :Parameters: - `element`: XML element of this stanza. - `from_jid`: sender JID. - `to_jid`: recipient JID. - `stanza_type`: staza type: one of: \"get\", \"set\", \"response\" or \"error\". - `stanza_id`: stanza id -- value of stanza's \"id\" attribute. If not given, th...

5

stack_v2_sparse_classes_30k_train_009053

Implement the Python class `Iq` described below. Class description: <message /> stanza class. Method signatures and docstrings: - def __init__(self, element=None, from_jid=None, to_jid=None, stanza_type=None, stanza_id=None, error=None, error_cond=None, return_path=None, language=None): Initialize an `Iq` object. :Pa...

26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891

<|skeleton|> class Iq: """<message /> stanza class.""" def __init__(self, element=None, from_jid=None, to_jid=None, stanza_type=None, stanza_id=None, error=None, error_cond=None, return_path=None, language=None): """Initialize an `Iq` object. :Parameters: - `element`: XML element of this stanza. - `fro...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Iq: """<message /> stanza class.""" def __init__(self, element=None, from_jid=None, to_jid=None, stanza_type=None, stanza_id=None, error=None, error_cond=None, return_path=None, language=None): """Initialize an `Iq` object. :Parameters: - `element`: XML element of this stanza. - `from_jid`: sende...

the_stack_v2_python_sparse

python3-alpha/python-libs/pyxmpp2/iq.py

kuri65536/python-for-android

train

280

1d3585de4df8a057b0e453aa89670e3fa937d938

[ "FeatureExtractor.__init__(self)\nself.width = 40\nself.height = 40\nself.channels = 3\nself.load_model(model_path)", "with tf.variable_scope('placeholder'):\n Img = tf.placeholder('float', [None, self.width, self.height, self.channels])\n Dropout = tf.placeholder(tf.float32)\n Is_Training = tf.placehold...

MiniFacenet特征提取器 es 2018-11-06

MiniFacenetFeatureExtractor

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008345

3,122

no_license

[ { "docstring": "初始化", "name": "__init__", "signature": "def __init__(self, model_path)" }, { "docstring": "加载预先已训练的模型", "name": "load_model", "signature": "def load_model(self, model_path)" }, { "docstring": "图像预处理", "name": "preprocess", "signature": "def preprocess(self...

4

stack_v2_sparse_classes_30k_train_009510

Implement the Python class `MiniFacenetFeatureExtractor` described below. Class description: MiniFacenet特征提取器 es 2018-11-06 Method signatures and docstrings: - def __init__(self, model_path): 初始化 - def load_model(self, model_path): 加载预先已训练的模型 - def preprocess(self, imgs): 图像预处理 - def extract_features(self, imgs, batc...

3c756d00c83cd0a8dd745fd32a074c9121977ab8

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class MiniFacenetFeatureExtractor: """MiniFacenet特征提取器 es 2018-11-06""" def __init__(self, model_path): """初始化""" FeatureExtractor.__init__(self) self.width = 40 self.height = 40 self.channels = 3 self.load_model(model_path) def load_model(self, model_path):...

the_stack_v2_python_sparse

feature/mini_facenet_feature_extractor.py

esfamely/es_face_server

train

0

e957317869ae26b95af468292c2668d038fe9347

[ "N = len(nums)\nW = sum(nums) // 2\nif sum(nums) % 2 == 1:\n return False\nif N * W == 0:\n return False\ndp = [[False] * (W + 1) for _ in range(N + 1)]\nfor i in range(N + 1):\n dp[i][0] = True\nfor i in range(1, N + 1):\n for j in range(1, W + 1):\n if j >= nums[i - 1]:\n dp[i][j] = ...

<|body_start_0|> N = len(nums) W = sum(nums) // 2 if sum(nums) % 2 == 1: return False if N * W == 0: return False dp = [[False] * (W + 1) for _ in range(N + 1)] for i in range(N + 1): dp[i][0] = True for i in range(1, N + 1): ...

Solution

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def canPartition(self, nums: List[int]) -> bool: """状态转移方程： 0-1背包：dp[i][j] = max(dp[i−1][j], dp[i−1][j−w[i]]+v[i]) // j >= w[i] 完全背包：dp[i][j] = max(dp[i−1][j], dp[i][j−w[i]]+v[i]) // j >= w[i] dp[i][j] = dp[i - 1][j] or dp[i - 1][j - nums[i]] dp[i][j] = x 表示，对于前i个物品，当前背包的容量为j时，...

stack_v2_sparse_classes_36k_train_008346

3,325

permissive

[ { "docstring": "状态转移方程： 0-1背包：dp[i][j] = max(dp[i−1][j], dp[i−1][j−w[i]]+v[i]) // j >= w[i] 完全背包：dp[i][j] = max(dp[i−1][j], dp[i][j−w[i]]+v[i]) // j >= w[i] dp[i][j] = dp[i - 1][j] or dp[i - 1][j - nums[i]] dp[i][j] = x 表示，对于前i个物品，当前背包的容量为j时，若x为true，则说明可以恰好将背包装满，若x为false，则说明不能恰好将背包装满。", "name": "canPartitio...

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def canPartition(self, nums: List[int]) -> bool: 状态转移方程： 0-1背包：dp[i][j] = max(dp[i−1][j], dp[i−1][j−w[i]]+v[i]) // j >= w[i] 完全背包：dp[i][j] = max(dp[i−1][j], dp[i][j−w[i]]+v[i]) /...

e8a1c6cae6547cbcb6e8494be6df685f3e7c837c

<|skeleton|> class Solution: def canPartition(self, nums: List[int]) -> bool: """状态转移方程： 0-1背包：dp[i][j] = max(dp[i−1][j], dp[i−1][j−w[i]]+v[i]) // j >= w[i] 完全背包：dp[i][j] = max(dp[i−1][j], dp[i][j−w[i]]+v[i]) // j >= w[i] dp[i][j] = dp[i - 1][j] or dp[i - 1][j - nums[i]] dp[i][j] = x 表示，对于前i个物品，当前背包的容量为j时，...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def canPartition(self, nums: List[int]) -> bool: """状态转移方程： 0-1背包：dp[i][j] = max(dp[i−1][j], dp[i−1][j−w[i]]+v[i]) // j >= w[i] 完全背包：dp[i][j] = max(dp[i−1][j], dp[i][j−w[i]]+v[i]) // j >= w[i] dp[i][j] = dp[i - 1][j] or dp[i - 1][j - nums[i]] dp[i][j] = x 表示，对于前i个物品，当前背包的容量为j时，若x为true，则说明可以恰...

the_stack_v2_python_sparse

416-partition-equal-subset-sum.py

yuenliou/leetcode

train

0

94ca94e2d08034f8675f0f9b6cafad0eda68ddb6

[ "n = len(p) - 1\nm = [[0] * (n + 1) for _ in range(n + 1)]\ns = [[0] * (n + 1) for _ in range(n)]\nfor l in range(2, n + 1):\n for i in range(1, n - l + 2):\n j = i + l - 1\n m[i][j] = float('inf')\n for k in range(i, j):\n q = m[i][k] + m[k + 1][j] + p[i - 1] * p[k] * p[j]\n ...

<|body_start_0|> n = len(p) - 1 m = [[0] * (n + 1) for _ in range(n + 1)] s = [[0] * (n + 1) for _ in range(n)] for l in range(2, n + 1): for i in range(1, n - l + 2): j = i + l - 1 m[i][j] = float('inf') for k in range(i, j): ...

Solution1

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008347

3,066

no_license

[ { "docstring": "动态规划", "name": "matrix_chain_order", "signature": "def matrix_chain_order(p)" }, { "docstring": "生成矩阵链最优括号化方案", "name": "print_optimal_parens", "signature": "def print_optimal_parens(self, s, i, j)" }, { "docstring": "15.2-2：实现矩阵链最优代价乘法计算", "name": "matrix_cha...

3

null

Implement the Python class `Solution1` described below. Class description: Implement the Solution1 class. Method signatures and docstrings: - def matrix_chain_order(p): 动态规划 - def print_optimal_parens(self, s, i, j): 生成矩阵链最优括号化方案 - def matrix_chain_multiply(self, A, s, i, j): 15.2-2：实现矩阵链最优代价乘法计算

Implement the Python class `Solution1` described below. Class description: Implement the Solution1 class. Method signatures and docstrings: - def matrix_chain_order(p): 动态规划 - def print_optimal_parens(self, s, i, j): 生成矩阵链最优括号化方案 - def matrix_chain_multiply(self, A, s, i, j): 15.2-2：实现矩阵链最优代价乘法计算 <|skeleton|> class ...

9fdc4b1a2b59b7aed22ddfe92aade487b4c19b71

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution1: def matrix_chain_order(p): """动态规划""" n = len(p) - 1 m = [[0] * (n + 1) for _ in range(n + 1)] s = [[0] * (n + 1) for _ in range(n)] for l in range(2, n + 1): for i in range(1, n - l + 2): j = i + l - 1 m[i][j] = fl...

the_stack_v2_python_sparse

introduction_to_algorithms/15.2_matrix_chain_order.py

MemoryForSky/Data-Structures-and-Algorithms

train

0

c652428851eb81eab8ea3fa740d3fb1f52b51bfc

[ "super(topic_embedding, self).__init__()\nassert n_topics < embedding_dim\ntopic_vectors = ortho_group.rvs(embedding_dim)\ntopic_vectors = topic_vectors[0:n_topics]\ntopic_vectors = torch.FloatTensor(topic_vectors)\nself.topic_vectors = nn.Parameter(topic_vectors)\nself.n_topics = n_topics", "doc_probs = F.softma...

<|body_start_0|> super(topic_embedding, self).__init__() assert n_topics < embedding_dim topic_vectors = ortho_group.rvs(embedding_dim) topic_vectors = topic_vectors[0:n_topics] topic_vectors = torch.FloatTensor(topic_vectors) self.topic_vectors = nn.Parameter(topic_vecto...

topic_embedding

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class topic_embedding: def __init__(self, n_topics, embedding_dim): """Arguments: embedding_dim: An integer. n_topics: An integer.""" <|body_0|> def forward(self, doc_weights): """Embed a batch of documents. Arguments: doc_weights: A float tensor of shape [batch_size, n_to...

stack_v2_sparse_classes_36k_train_008348

29,814

no_license

[ { "docstring": "Arguments: embedding_dim: An integer. n_topics: An integer.", "name": "__init__", "signature": "def __init__(self, n_topics, embedding_dim)" }, { "docstring": "Embed a batch of documents. Arguments: doc_weights: A float tensor of shape [batch_size, n_topics], document distributio...

2

stack_v2_sparse_classes_30k_train_007799

Implement the Python class `topic_embedding` described below. Class description: Implement the topic_embedding class. Method signatures and docstrings: - def __init__(self, n_topics, embedding_dim): Arguments: embedding_dim: An integer. n_topics: An integer. - def forward(self, doc_weights): Embed a batch of document...

82d3e9808073f2145b039ccf464c526cb85274e3

<|skeleton|> class topic_embedding: def __init__(self, n_topics, embedding_dim): """Arguments: embedding_dim: An integer. n_topics: An integer.""" <|body_0|> def forward(self, doc_weights): """Embed a batch of documents. Arguments: doc_weights: A float tensor of shape [batch_size, n_to...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class topic_embedding: def __init__(self, n_topics, embedding_dim): """Arguments: embedding_dim: An integer. n_topics: An integer.""" super(topic_embedding, self).__init__() assert n_topics < embedding_dim topic_vectors = ortho_group.rvs(embedding_dim) topic_vectors = topic_v...

the_stack_v2_python_sparse

business/p201908/3507_750/lda2vec_model.py

Alvin2580du/alvin_py

train

12

44c583f750ad5c040bdd9e1e413b57fc1571ef16

[ "article_dict = list()\nfor key in ['课程名称', '任教老师', '人数限制', '课程描述']:\n a = input(f'请输入{key}')\n article_dict.append(a)\ncurriculum = Course(*article_dict)\ncurriculum.save()\ninput('课程增加成功，按任意键打印增加课程的信息')\nprint(curriculum)\ninput('按任意键返回')\nmin()", "for i in Data.article_dict.values():\n print(i)\ninput...

<|body_start_0|> article_dict = list() for key in ['课程名称', '任教老师', '人数限制', '课程描述']: a = input(f'请输入{key}') article_dict.append(a) curriculum = Course(*article_dict) curriculum.save() input('课程增加成功，按任意键打印增加课程的信息') print(curriculum) input('按任...

管理员类

Admin

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008349

4,552

no_license

[ { "docstring": "添加课程", "name": "add_course", "signature": "def add_course(self)" }, { "docstring": "查看课程", "name": "check_course", "signature": "def check_course(cls, *args, **kwargs)" } ]

2

stack_v2_sparse_classes_30k_train_009969

Implement the Python class `Admin` described below. Class description: 管理员类 Method signatures and docstrings: - def add_course(self): 添加课程 - def check_course(cls, *args, **kwargs): 查看课程

Implement the Python class `Admin` described below. Class description: 管理员类 Method signatures and docstrings: - def add_course(self): 添加课程 - def check_course(cls, *args, **kwargs): 查看课程 <|skeleton|> class Admin: """管理员类""" def add_course(self): """添加课程""" <|body_0|> def check_course(cls...

e11f5fcb10f37a0f0663e4c746ca862b076f9aee

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Admin: """管理员类""" def add_course(self): """添加课程""" article_dict = list() for key in ['课程名称', '任教老师', '人数限制', '课程描述']: a = input(f'请输入{key}') article_dict.append(a) curriculum = Course(*article_dict) curriculum.save() input('课程增加成功，按任...

the_stack_v2_python_sparse

作业/5-11作业.py

liujiang9/python0421

train

1

bf09854c0c1f0c26af9941a158dfad534f5c984e

[ "if isinstance(exceptions, type):\n exceptions = [exceptions]\nself.exceptions = exceptions\nself.exceptions_dict = dict(((e.code, e) for e in self.exceptions))", "code, message, data = err\ntry:\n exp = self.exceptions_dict[code]\n return exp(exp.code, message, data)\nexcept KeyError:\n return TRexEx...

CExceptionHandler is responsible for generating TRex API related exceptions in client side.

CExceptionHandler

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CExceptionHandler: """CExceptionHandler is responsible for generating TRex API related exceptions in client side.""" def __init__(self, exceptions): """Instatiate a CExceptionHandler object :parameters: exceptions : list a list of all TRex acceptable exception objects. default list: ...

stack_v2_sparse_classes_36k_train_008350

5,237

permissive

[ { "docstring": "Instatiate a CExceptionHandler object :parameters: exceptions : list a list of all TRex acceptable exception objects. default list: - :exc:`trex_exceptions.TRexException` - :exc:`trex_exceptions.TRexError` - :exc:`trex_exceptions.TRexWarning` - :exc:`trex_exceptions.TRexInUseError` - :exc:`trex_...

2

null

Implement the Python class `CExceptionHandler` described below. Class description: CExceptionHandler is responsible for generating TRex API related exceptions in client side. Method signatures and docstrings: - def __init__(self, exceptions): Instatiate a CExceptionHandler object :parameters: exceptions : list a list...

e30f5af03aaaad518b5def6e1804c3741dd5d0c6

<|skeleton|> class CExceptionHandler: """CExceptionHandler is responsible for generating TRex API related exceptions in client side.""" def __init__(self, exceptions): """Instatiate a CExceptionHandler object :parameters: exceptions : list a list of all TRex acceptable exception objects. default list: ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class CExceptionHandler: """CExceptionHandler is responsible for generating TRex API related exceptions in client side.""" def __init__(self, exceptions): """Instatiate a CExceptionHandler object :parameters: exceptions : list a list of all TRex acceptable exception objects. default list: - :exc:`trex_...

the_stack_v2_python_sparse

trex_client/stf/trex_stf_lib/trex_exceptions.py

alwye/trex-http-proxy

train

4

e315b8ddd4b1c9ae0575dc9f95e0702e500a2f05

[ "detail = ''\nif detailed:\n detail = '/detail'\nif response_key:\n return self._get('/os-hypervisors%s' % detail, 'hypervisors', **kwargs)\nelse:\n return self._get('/os-hypervisors%s' % detail, **kwargs)", "target = 'servers' if servers else 'search'\nurl = '/os-hypervisors/%s/%s' % (parse.quote(hyperv...

<|body_start_0|> detail = '' if detailed: detail = '/detail' if response_key: return self._get('/os-hypervisors%s' % detail, 'hypervisors', **kwargs) else: return self._get('/os-hypervisors%s' % detail, **kwargs) <|end_body_0|> <|body_start_1|> ...

HypervisorManager

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class HypervisorManager: def list(self, detailed=True, response_key=True, **kwargs): """Get a list of hypervisors.""" <|body_0|> def search(self, hypervisor_match, servers=False, response_key=True, **kwargs): """Get a list of matching hypervisors. :param servers: If True, ...

stack_v2_sparse_classes_36k_train_008351

2,287

no_license

[ { "docstring": "Get a list of hypervisors.", "name": "list", "signature": "def list(self, detailed=True, response_key=True, **kwargs)" }, { "docstring": "Get a list of matching hypervisors. :param servers: If True, server information is also retrieved.", "name": "search", "signature": "d...

5

null

Implement the Python class `HypervisorManager` described below. Class description: Implement the HypervisorManager class. Method signatures and docstrings: - def list(self, detailed=True, response_key=True, **kwargs): Get a list of hypervisors. - def search(self, hypervisor_match, servers=False, response_key=True, **...

42f9197ba26ffb6b9dd336a524639ecbbf194365

<|skeleton|> class HypervisorManager: def list(self, detailed=True, response_key=True, **kwargs): """Get a list of hypervisors.""" <|body_0|> def search(self, hypervisor_match, servers=False, response_key=True, **kwargs): """Get a list of matching hypervisors. :param servers: If True, ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class HypervisorManager: def list(self, detailed=True, response_key=True, **kwargs): """Get a list of hypervisors.""" detail = '' if detailed: detail = '/detail' if response_key: return self._get('/os-hypervisors%s' % detail, 'hypervisors', **kwargs) e...

the_stack_v2_python_sparse

ops_client/project/nova/hypervisors.py

tokuzfunpi/ops_client

train

0

26f2162ea2709a5275a8780d7415161efc420589

[ "super(GRRHuntOsqueryCollector, self).__init__(state, name=name, critical=critical)\nself.timeout_millis = self.DEFAULT_OSQUERY_TIMEOUT_MILLIS\nself.ignore_stderr_errors = True", "self.GrrSetUp(reason, grr_server_url, grr_username, grr_password, approvers=approvers, verify=verify, message_callback=self.PublishMes...

Osquery collector for a GRR Hunt. Attributes: timeout_millis (int): the number of milliseconds before osquery timeouts. ignore_stderr_errors (bool): ignore stderr errors from osquery.

GRRHuntOsqueryCollector

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GRRHuntOsqueryCollector: """Osquery collector for a GRR Hunt. Attributes: timeout_millis (int): the number of milliseconds before osquery timeouts. ignore_stderr_errors (bool): ignore stderr errors from osquery.""" def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical...

stack_v2_sparse_classes_36k_train_008352

27,645

permissive

[ { "docstring": "Initializes a GRR file collector hunt. Args: state (DFTimewolfState): recipe state. name (Optional[str]): The module's runtime name. critical (bool): True if the module is critical, which causes the entire recipe to fail if the module encounters an error.", "name": "__init__", "signature...

3

null

Implement the Python class `GRRHuntOsqueryCollector` described below. Class description: Osquery collector for a GRR Hunt. Attributes: timeout_millis (int): the number of milliseconds before osquery timeouts. ignore_stderr_errors (bool): ignore stderr errors from osquery. Method signatures and docstrings: - def __ini...

bcea85b1ce7a0feb2aa28b5be4fc6ae124e8ca3c

<|skeleton|> class GRRHuntOsqueryCollector: """Osquery collector for a GRR Hunt. Attributes: timeout_millis (int): the number of milliseconds before osquery timeouts. ignore_stderr_errors (bool): ignore stderr errors from osquery.""" def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class GRRHuntOsqueryCollector: """Osquery collector for a GRR Hunt. Attributes: timeout_millis (int): the number of milliseconds before osquery timeouts. ignore_stderr_errors (bool): ignore stderr errors from osquery.""" def __init__(self, state: DFTimewolfState, name: Optional[str]=None, critical: bool=False)...

the_stack_v2_python_sparse

dftimewolf/lib/collectors/grr_hunt.py

log2timeline/dftimewolf

train

248

8f540844ba35df23b5dd0188d3d9d7fd9f0228b4

[ "self.timeout = timeout\ntry:\n self.pre_snap = self.mapping.learn_ops(device=uut, abstract=abstract, steps=steps, timeout=self.timeout)\nexcept Exception as e:\n self.skipped('Cannot learn the feature', from_exception=e, goto=['next_tc'])\nfor stp in steps.details:\n if stp.result.name == 'skipped':\n ...

<|body_start_0|> self.timeout = timeout try: self.pre_snap = self.mapping.learn_ops(device=uut, abstract=abstract, steps=steps, timeout=self.timeout) except Exception as e: self.skipped('Cannot learn the feature', from_exception=e, goto=['next_tc']) for stp in ste...

Trigger class for Reload action

TriggerReload

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TriggerReload: """Trigger class for Reload action""" def verify_prerequisite(self, uut, abstract, steps, timeout): """Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstract (`obj`...

stack_v2_sparse_classes_36k_train_008353

20,969

permissive

[ { "docstring": "Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstract (`obj`): Abstract object. steps (`step obj`): aetest step object timeout (`timeout obj`): Timeout Object Returns: None Raises: pyATS Res...

4

null

Implement the Python class `TriggerReload` described below. Class description: Trigger class for Reload action Method signatures and docstrings: - def verify_prerequisite(self, uut, abstract, steps, timeout): Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next te...

e42e51475cddcb10f5c7814d0fe892ac865742ba

<|skeleton|> class TriggerReload: """Trigger class for Reload action""" def verify_prerequisite(self, uut, abstract, steps, timeout): """Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstract (`obj`...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class TriggerReload: """Trigger class for Reload action""" def verify_prerequisite(self, uut, abstract, steps, timeout): """Learn Ops object and verify the requirements. If the requirements are not satisfied, then skip to the next testcase. Args: uut (`obj`): Device object. abstract (`obj`): Abstract o...

the_stack_v2_python_sparse

pkgs/sdk-pkg/src/genie/libs/sdk/triggers/ha/ha.py

CiscoTestAutomation/genielibs

train

109

f38465223d99757ea736fb0d78f652b766861804

[ "self.radius = np.abs(np.atleast_1d(radius))\nif len(self.radius) == 1:\n self.radius = np.abs(np.array([radius, radius, radius]))\nif len(self.radius) != 3 or (self.radius <= 0).any():\n self.error('non positive radius defined for ellipsoid object')\n self.empty = True\n return self\ntry:\n self.cen...

<|body_start_0|> self.radius = np.abs(np.atleast_1d(radius)) if len(self.radius) == 1: self.radius = np.abs(np.array([radius, radius, radius])) if len(self.radius) != 3 or (self.radius <= 0).any(): self.error('non positive radius defined for ellipsoid object') ...

PyRatEllipsoid: A PyRat object P. Lewis 30/6/2012 For an ellipsoid or sphere

PyRatEllipsoid

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class PyRatEllipsoid: """PyRatEllipsoid: A PyRat object P. Lewis 30/6/2012 For an ellipsoid or sphere""" def __init__(self, base, radius, contents=None, material=None, info=None): """Load the object: base : vector that define the ellipsoid base (N.B. not centre) radius : vector (for ellips...

stack_v2_sparse_classes_36k_train_008354

4,469

no_license

[ { "docstring": "Load the object: base : vector that define the ellipsoid base (N.B. not centre) radius : vector (for ellipsoid) or scalar for sphere OPTIONAL: info['coords']: 3 x 2 vectors that define a coordinate for each vertex Options: contents : a list that may contain other objects or None material : a dic...

4

stack_v2_sparse_classes_30k_train_020275

Implement the Python class `PyRatEllipsoid` described below. Class description: PyRatEllipsoid: A PyRat object P. Lewis 30/6/2012 For an ellipsoid or sphere Method signatures and docstrings: - def __init__(self, base, radius, contents=None, material=None, info=None): Load the object: base : vector that define the ell...

031db80c597947cf089b72fbdc1a1e167b308bda

<|skeleton|> class PyRatEllipsoid: """PyRatEllipsoid: A PyRat object P. Lewis 30/6/2012 For an ellipsoid or sphere""" def __init__(self, base, radius, contents=None, material=None, info=None): """Load the object: base : vector that define the ellipsoid base (N.B. not centre) radius : vector (for ellips...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class PyRatEllipsoid: """PyRatEllipsoid: A PyRat object P. Lewis 30/6/2012 For an ellipsoid or sphere""" def __init__(self, base, radius, contents=None, material=None, info=None): """Load the object: base : vector that define the ellipsoid base (N.B. not centre) radius : vector (for ellipsoid) or scala...

the_stack_v2_python_sparse

PyRat/PyRatEllipsoid.py

profLewis/PyRat

train

2

e9eadedcbc1992bce435b1d3120e3e81bc3f46f3

[ "for element in brain.getObject().objectValues():\n info = {'title': element.title or ''}\n if element.portal_type == 'PSCFileLink':\n info['url'] = element.externalURL\n else:\n info['url'] = element.absolute_url()\n yield info", "sc = self.context\ncatalog = getToolByName(self.context,...

<|body_start_0|> for element in brain.getObject().objectValues(): info = {'title': element.title or ''} if element.portal_type == 'PSCFileLink': info['url'] = element.externalURL else: info['url'] = element.absolute_url() yield info...

view used for the main index page

PyPISimpleView

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008355

1,303

no_license

[ { "docstring": "returns url and title", "name": "get_urls_and_titles", "signature": "def get_urls_and_titles(self, brain)" }, { "docstring": "provides the simple view over the projects with links to the published files", "name": "get_files", "signature": "def get_files(self)" } ]

2

stack_v2_sparse_classes_30k_train_018166

Implement the Python class `PyPISimpleView` described below. Class description: view used for the main index page Method signatures and docstrings: - def get_urls_and_titles(self, brain): returns url and title - def get_files(self): provides the simple view over the projects with links to the published files

Implement the Python class `PyPISimpleView` described below. Class description: view used for the main index page Method signatures and docstrings: - def get_urls_and_titles(self, brain): returns url and title - def get_files(self): provides the simple view over the projects with links to the published files <|skele...

8a7bdbdb98c3f9fc1073c6061cd2d3a0ec80caf5

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class PyPISimpleView: """view used for the main index page""" def get_urls_and_titles(self, brain): """returns url and title""" for element in brain.getObject().objectValues(): info = {'title': element.title or ''} if element.portal_type == 'PSCFileLink': ...

the_stack_v2_python_sparse

buildout-cache/eggs/Products.PloneSoftwareCenter-1.5-py2.7.egg/Products/PloneSoftwareCenter/browser/pypisimple.py

renansfs/Plone_SP

train

0

edb58aedc46522ecb607c7cf4e6bac811ca0b5ea

[ "date_list = []\nstrstring = str(strstring)\nif strstring.find('-'):\n date_list = strstring.split('-')\nelif strstring.find(':'):\n date_list = strstring.split(':')\nelse:\n date_list[0], date_list[1], date_list[2] = (strstring[:4], strstring[4:6], strstring[6:])\nself.year, self.month, self.day = (date_l...

<|body_start_0|> date_list = [] strstring = str(strstring) if strstring.find('-'): date_list = strstring.split('-') elif strstring.find(':'): date_list = strstring.split(':') else: date_list[0], date_list[1], date_list[2] = (strstring[:4], strs...

Datadis

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008356

1,861

no_license

[ { "docstring": "读取字符串时间 :param strstring: 2020-1-9 or 2020:1:9 or 20200109 :return:", "name": "set_strdate", "signature": "def set_strdate(self, strstring)" }, { "docstring": "获取月天数 :return:", "name": "get_int_md", "signature": "def get_int_md(self)" }, { "docstring": "获取时间段内的双休日...

3

stack_v2_sparse_classes_30k_train_010627

Implement the Python class `Datadis` described below. Class description: Implement the Datadis class. Method signatures and docstrings: - def set_strdate(self, strstring): 读取字符串时间 :param strstring: 2020-1-9 or 2020:1:9 or 20200109 :return: - def get_int_md(self): 获取月天数 :return: - def get_interval_vacation(self, start...

88705807df697dc86a5ed8a648505b3fb895872b

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Datadis: def set_strdate(self, strstring): """读取字符串时间 :param strstring: 2020-1-9 or 2020:1:9 or 20200109 :return:""" date_list = [] strstring = str(strstring) if strstring.find('-'): date_list = strstring.split('-') elif strstring.find(':'): date...

the_stack_v2_python_sparse

main/src/general/date_G.py

wangwuli/XLauto

train

1

d8f15ef7655b1a4ae4efdccf688635d326e085f0

[ "self.name = name\nself.money = 20\ntry:\n soldiers, archers, cavalries = self._verifyInput(soldiers, archers, cavalries)\nexcept (ValueError, AssertionError):\n raise\ntry:\n self.money -= self.calculateMoney(soldiers, archers, cavalries)\nexcept AssertionError:\n raise\nself.createQueue(soldiers, arch...

<|body_start_0|> self.name = name self.money = 20 try: soldiers, archers, cavalries = self._verifyInput(soldiers, archers, cavalries) except (ValueError, AssertionError): raise try: self.money -= self.calculateMoney(soldiers, archers, cavalries...

Army

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Army: def __init__(self, name, soldiers, archers, cavalries): """creates an Army class that uses Linked Queue @ param name: string for the Army's name @ param soldiers: integer, positive @ param archers: integer, positive @ param cavalries: integer, positive @ post: Army class created @ ...

stack_v2_sparse_classes_36k_train_008357

8,892

no_license

[ { "docstring": "creates an Army class that uses Linked Queue @ param name: string for the Army's name @ param soldiers: integer, positive @ param archers: integer, positive @ param cavalries: integer, positive @ post: Army class created @ return: Army class @ complexity: O(1) -> because soldiers, archers, caval...

4

null

Implement the Python class `Army` described below. Class description: Implement the Army class. Method signatures and docstrings: - def __init__(self, name, soldiers, archers, cavalries): creates an Army class that uses Linked Queue @ param name: string for the Army's name @ param soldiers: integer, positive @ param ...

a6d7ce18d377aa975c29f2ec441e91d1480903e6

<|skeleton|> class Army: def __init__(self, name, soldiers, archers, cavalries): """creates an Army class that uses Linked Queue @ param name: string for the Army's name @ param soldiers: integer, positive @ param archers: integer, positive @ param cavalries: integer, positive @ post: Army class created @ ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Army: def __init__(self, name, soldiers, archers, cavalries): """creates an Army class that uses Linked Queue @ param name: string for the Army's name @ param soldiers: integer, positive @ param archers: integer, positive @ param cavalries: integer, positive @ post: Army class created @ return: Army c...

the_stack_v2_python_sparse

intro to comp science/python functions/fairer_army.py

gabimelo/AnDS-examples-python

train

0

c4eb1efc82cd72ca759782f138304b8f35ac80d5

[ "self.nums = nums\nfor i in range(1, len(nums)):\n self.nums[i] += self.nums[i - 1]", "if i > j:\n return None\nif j >= len(self.nums):\n return None\nsum = 0\nfor m in range(i, j + 1, 1):\n sum += self.nums[m]\nreturn self.nums[j] - (self.nums[i - 1] if i > 0 else 0)" ]

NumArray

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008358

696

no_license

[ { "docstring": ":type nums: List[int]", "name": "__init__", "signature": "def __init__(self, nums)" }, { "docstring": ":type i: int :type j: int :rtype: int", "name": "sumRange", "signature": "def sumRange(self, i, j)" } ]

2

null

Implement the Python class `NumArray` described below. Class description: Implement the NumArray class. Method signatures and docstrings: - def __init__(self, nums): :type nums: List[int] - def sumRange(self, i, j): :type i: int :type j: int :rtype: int

Implement the Python class `NumArray` described below. Class description: Implement the NumArray class. Method signatures and docstrings: - def __init__(self, nums): :type nums: List[int] - def sumRange(self, i, j): :type i: int :type j: int :rtype: int <|skeleton|> class NumArray: def __init__(self, nums): ...

d87acd5481a2dbfad7288b73750e6e086650a17d

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class NumArray: def __init__(self, nums): """:type nums: List[int]""" self.nums = nums for i in range(1, len(nums)): self.nums[i] += self.nums[i - 1] def sumRange(self, i, j): """:type i: int :type j: int :rtype: int""" if i > j: return None ...

the_stack_v2_python_sparse

303. Range Sum Query - Immutable/303. Range Sum Query - Immutable(AC).py

BohaoLiGithub/Leetcode

train

0

34bbd6cf700d5e47042556623c46e7ee002800d2

[ "yield Request(url=response.url, callback=self.parse_details, dont_filter=True)\nnext_page = response.css('.next::attr(href)').extract_first('')\nif next_page:\n yield Request(url=parse.urljoin(response.url, next_page), callback=self.parse)", "for i in range(len(response.css('.mod-bd .comment-item'))):\n it...

<|body_start_0|> yield Request(url=response.url, callback=self.parse_details, dont_filter=True) next_page = response.css('.next::attr(href)').extract_first('') if next_page: yield Request(url=parse.urljoin(response.url, next_page), callback=self.parse) <|end_body_0|> <|body_start_1|...

DoubanSpider

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008359

2,310

no_license

[ { "docstring": "交给parse_details 进行处理", "name": "parse", "signature": "def parse(self, response)" }, { "docstring": "解析爱情公寓具体短评论", "name": "parse_details", "signature": "def parse_details(self, response)" } ]

2

stack_v2_sparse_classes_30k_train_011111

Implement the Python class `DoubanSpider` described below. Class description: Implement the DoubanSpider class. Method signatures and docstrings: - def parse(self, response): 交给parse_details 进行处理 - def parse_details(self, response): 解析爱情公寓具体短评论

Implement the Python class `DoubanSpider` described below. Class description: Implement the DoubanSpider class. Method signatures and docstrings: - def parse(self, response): 交给parse_details 进行处理 - def parse_details(self, response): 解析爱情公寓具体短评论 <|skeleton|> class DoubanSpider: def parse(self, response): ...

5e84bb83d46454b06ab65b819fd0f962b4d40421

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class DoubanSpider: def parse(self, response): """交给parse_details 进行处理""" yield Request(url=response.url, callback=self.parse_details, dont_filter=True) next_page = response.css('.next::attr(href)').extract_first('') if next_page: yield Request(url=parse.urljoin(response....

the_stack_v2_python_sparse

爬虫新scrape/爬虫新scrape/scrapy_learn_bole-master/scrapy_learn_bole-master/ArticleSpider/spiders/douban.py

xzbuku/16219111133-qimo-work

train

1

624da4dcc8c6a8ae5c6a0d01e5663e0216d964ca

[ "super(LogmelFilterBank, self).__init__()\nself.is_log = is_log\nself.ref = ref\nself.amin = amin\nself.top_db = top_db\nself.melW = librosa.filters.mel(sr=sr, n_fft=n_fft, n_mels=n_mels, fmin=fmin, fmax=fmax).T\nself.melW = nn.Parameter(torch.Tensor(self.melW))\nif freeze_parameters:\n for param in self.paramet...

<|body_start_0|> super(LogmelFilterBank, self).__init__() self.is_log = is_log self.ref = ref self.amin = amin self.top_db = top_db self.melW = librosa.filters.mel(sr=sr, n_fft=n_fft, n_mels=n_mels, fmin=fmin, fmax=fmax).T self.melW = nn.Parameter(torch.Tensor(sel...

LogmelFilterBank

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class LogmelFilterBank: def __init__(self, sr=32000, n_fft=2048, n_mels=64, fmin=50, fmax=14000, is_log=True, ref=1.0, amin=1e-10, top_db=80.0, freeze_parameters=True): """Calculate logmel spectrogram using pytorch. The mel filter bank is the pytorch implementation of as librosa.filters.mel"""...

stack_v2_sparse_classes_36k_train_008360

25,139

no_license

[ { "docstring": "Calculate logmel spectrogram using pytorch. The mel filter bank is the pytorch implementation of as librosa.filters.mel", "name": "__init__", "signature": "def __init__(self, sr=32000, n_fft=2048, n_mels=64, fmin=50, fmax=14000, is_log=True, ref=1.0, amin=1e-10, top_db=80.0, freeze_param...

3

stack_v2_sparse_classes_30k_train_020536

Implement the Python class `LogmelFilterBank` described below. Class description: Implement the LogmelFilterBank class. Method signatures and docstrings: - def __init__(self, sr=32000, n_fft=2048, n_mels=64, fmin=50, fmax=14000, is_log=True, ref=1.0, amin=1e-10, top_db=80.0, freeze_parameters=True): Calculate logmel ...

7ab627aefa56525735684b6671918d7c7db1cc07

<|skeleton|> class LogmelFilterBank: def __init__(self, sr=32000, n_fft=2048, n_mels=64, fmin=50, fmax=14000, is_log=True, ref=1.0, amin=1e-10, top_db=80.0, freeze_parameters=True): """Calculate logmel spectrogram using pytorch. The mel filter bank is the pytorch implementation of as librosa.filters.mel"""...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class LogmelFilterBank: def __init__(self, sr=32000, n_fft=2048, n_mels=64, fmin=50, fmax=14000, is_log=True, ref=1.0, amin=1e-10, top_db=80.0, freeze_parameters=True): """Calculate logmel spectrogram using pytorch. The mel filter bank is the pytorch implementation of as librosa.filters.mel""" super...

the_stack_v2_python_sparse

easy_gold/pann_utils.py

wdy06/kaggle-birdsong-recognition

train

1

3f07fc82aa1f55354352bdcba5273053e9e9129d

[ "if attributeData:\n attrData = array(attributeData)\n leafData = array(leafData, object_)\n self.root = Node(attrData, leafData, sepVal)\nelse:\n self.root = None", "if not self.root:\n return []\nreturn _searchNode(self.root, target, window * window, [zero] * len(target), zero)", "if not self.r...

Define an 'adaptive k-d tree' as per "The Design and Analysis of Spatial Data Structures" pp. 70-71. Basically, given a set of k-dimensional points (each dimension referred to as an "attribute") with associated data, they are partitioned into leaf nodes. Each leaf nodes hold lists of associated data whose corresponding...

AdaptiveTree

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class AdaptiveTree: """Define an 'adaptive k-d tree' as per "The Design and Analysis of Spatial Data Structures" pp. 70-71. Basically, given a set of k-dimensional points (each dimension referred to as an "attribute") with associated data, they are partitioned into leaf nodes. Each leaf nodes hold list...

stack_v2_sparse_classes_36k_train_008361

7,623

no_license

[ { "docstring": "attributeData is a sequence of sequences. Each individual sequence is attribute data. For example, in a 3D space partitioning, the attribute data is x, y, and z values. leafData ia a sequence of the same length as attributeData. Each item is what is to put into leaf nodes after tree partitioning...

3

null

Implement the Python class `AdaptiveTree` described below. Class description: Define an 'adaptive k-d tree' as per "The Design and Analysis of Spatial Data Structures" pp. 70-71. Basically, given a set of k-dimensional points (each dimension referred to as an "attribute") with associated data, they are partitioned int...

024890dba56c3e82ea2cf8c773965117f8cda339

<|skeleton|> class AdaptiveTree: """Define an 'adaptive k-d tree' as per "The Design and Analysis of Spatial Data Structures" pp. 70-71. Basically, given a set of k-dimensional points (each dimension referred to as an "attribute") with associated data, they are partitioned into leaf nodes. Each leaf nodes hold list...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class AdaptiveTree: """Define an 'adaptive k-d tree' as per "The Design and Analysis of Spatial Data Structures" pp. 70-71. Basically, given a set of k-dimensional points (each dimension referred to as an "attribute") with associated data, they are partitioned into leaf nodes. Each leaf nodes hold lists of associat...

the_stack_v2_python_sparse

tools/MolSurfGenService/MolSurfaceGen32/chimera/share/CGLutil/AdaptiveTree.py

project-renard-survey/semanticscience

train

0

c70a497fa0a9db39e3f4546fd96775912458e71d

[ "i = 0\nwhile i < len(nums):\n if nums[i] == val:\n del nums[i]\n else:\n i += 1\nreturn len(nums)", "tmp = list(filter(lambda x: x != val, nums))\nnums[:len(tmp)] = tmp\ndel nums[len(tmp):]\nreturn len(nums)" ]

Solution

[ "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008362

1,988

permissive

[ { "docstring": "direct solution", "name": "removeElement", "signature": "def removeElement(self, nums, val)" }, { "docstring": "use filter", "name": "removeElement2", "signature": "def removeElement2(self, nums, val)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def removeElement(self, nums, val): direct solution - def removeElement2(self, nums, val): use filter

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def removeElement(self, nums, val): direct solution - def removeElement2(self, nums, val): use filter <|skeleton|> class Solution: def removeElement(self, nums, val): ...

49a0b03c55d8a702785888d473ef96539265ce9c

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def removeElement(self, nums, val): """direct solution""" i = 0 while i < len(nums): if nums[i] == val: del nums[i] else: i += 1 return len(nums) def removeElement2(self, nums, val): """use filter"""...

the_stack_v2_python_sparse

leetcode/0027_remove_element.py

chaosWsF/Python-Practice

train

1

6e63aabc3519f11574e7148e7766628800719288

[ "self.seed = seed\nself.digits = digits\nself.base = len(self.digits)", "result = ''\npower = len(self.seed)\nseedidx = 0\nwhile power > 0:\n digit = 0\n number = self.base ** (power - 1)\n while tbc >= number:\n digit += 1\n tbc -= number\n seedchar = self.seed[seedidx]\n pos = self....

Class to Generate a new ID

IdGenerator

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class IdGenerator: """Class to Generate a new ID""" def __init__(self, seed, digits): """initialse the seed for encoding the number""" <|body_0|> def dec2Encoded(self, tbc): """the function works by converting the sequence to a base 48 number represented by the digit s...

stack_v2_sparse_classes_36k_train_008363

3,805

no_license

[ { "docstring": "initialse the seed for encoding the number", "name": "__init__", "signature": "def __init__(self, seed, digits)" }, { "docstring": "the function works by converting the sequence to a base 48 number represented by the digit set above. It is then encoded by add the corresponding di...

2

null

Implement the Python class `IdGenerator` described below. Class description: Class to Generate a new ID Method signatures and docstrings: - def __init__(self, seed, digits): initialse the seed for encoding the number - def dec2Encoded(self, tbc): the function works by converting the sequence to a base 48 number repre...

e6c967c5e70bca099657655db62e3a33593a1a58

<|skeleton|> class IdGenerator: """Class to Generate a new ID""" def __init__(self, seed, digits): """initialse the seed for encoding the number""" <|body_0|> def dec2Encoded(self, tbc): """the function works by converting the sequence to a base 48 number represented by the digit s...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class IdGenerator: """Class to Generate a new ID""" def __init__(self, seed, digits): """initialse the seed for encoding the number""" self.seed = seed self.digits = digits self.base = len(self.digits) def dec2Encoded(self, tbc): """the function works by converting ...

the_stack_v2_python_sparse

site/controllers/generator.py

mikejmets/polokelo-bookings

train

0

69c790f2feb2571758d6d99f6b0221f6a61443a3

[ "while obj:\n yield obj\n for opChild in IESMetaSaverHelper.HierarchyIterator(obj.GetDown()):\n yield opChild\n obj = obj.GetNext()", "if not isinstance(op, c4d.BaseObject):\n raise TypeError('Expected a BaseObject or derived class got {0}'.format(op.__class__.__name__))\ntemp = op.GetDeformCac...

IESMetaSaverHelper

[ "LicenseRef-scancode-unknown-license-reference", "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class IESMetaSaverHelper: def HierarchyIterator(obj): """A Generator to iterate over the Hierarchy. Args: obj: The starting object of the generator (will be the first result) Returns: All objects under and next of the `obj`""" <|body_0|> def CacheIterator(op): """A Python ...

stack_v2_sparse_classes_36k_train_008364

8,297

permissive

[ { "docstring": "A Generator to iterate over the Hierarchy. Args: obj: The starting object of the generator (will be the first result) Returns: All objects under and next of the `obj`", "name": "HierarchyIterator", "signature": "def HierarchyIterator(obj)" }, { "docstring": "A Python Generator to...

2

stack_v2_sparse_classes_30k_train_008420

Implement the Python class `IESMetaSaverHelper` described below. Class description: Implement the IESMetaSaverHelper class. Method signatures and docstrings: - def HierarchyIterator(obj): A Generator to iterate over the Hierarchy. Args: obj: The starting object of the generator (will be the first result) Returns: All...

b1ea3fce533df34094bc3d0bd6460dfb84306e53

<|skeleton|> class IESMetaSaverHelper: def HierarchyIterator(obj): """A Generator to iterate over the Hierarchy. Args: obj: The starting object of the generator (will be the first result) Returns: All objects under and next of the `obj`""" <|body_0|> def CacheIterator(op): """A Python ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class IESMetaSaverHelper: def HierarchyIterator(obj): """A Generator to iterate over the Hierarchy. Args: obj: The starting object of the generator (will be the first result) Returns: All objects under and next of the `obj`""" while obj: yield obj for opChild in IESMetaSaverH...

the_stack_v2_python_sparse

plugins/py-ies_meta_r12/py-ies_meta_r12.pyp

PluginCafe/cinema4d_py_sdk_extended

train

112

5093d43f88877843c5f6da9a33bb9ec148ef253d

[ "if k <= 1:\n return head\np = head\nlength = 0\nwhile p is not None:\n length += 1\n p = p.next\ncnt = 0\ncur_node = head\nwhile cur_node is not None:\n if cnt + k <= length:\n if cnt == 0:\n head = self.reverse_k(cur_node, k)\n cnt += k\n else:\n next_nod...

<|body_start_0|> if k <= 1: return head p = head length = 0 while p is not None: length += 1 p = p.next cnt = 0 cur_node = head while cur_node is not None: if cnt + k <= length: if cnt == 0: ...

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def reverse_k_group(self, head, k): """leetcode 25. K 个一组翻转链表 :param head: ListNode 链表的表头 :param k: 每个翻转的个数 :return: 翻转后链表的表头""" <|body_0|> def reverse_k(self, head, k): """对以head为表头的链表进行翻转k个节点返回翻转后表头 :param head: 链表表头 :param k: k个节点 :return: 翻转后的表头""" ...

stack_v2_sparse_classes_36k_train_008365

2,790

no_license

[ { "docstring": "leetcode 25. K 个一组翻转链表 :param head: ListNode 链表的表头 :param k: 每个翻转的个数 :return: 翻转后链表的表头", "name": "reverse_k_group", "signature": "def reverse_k_group(self, head, k)" }, { "docstring": "对以head为表头的链表进行翻转k个节点返回翻转后表头 :param head: 链表表头 :param k: k个节点 :return: 翻转后的表头", "name": "re...

3

stack_v2_sparse_classes_30k_train_016314

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def reverse_k_group(self, head, k): leetcode 25. K 个一组翻转链表 :param head: ListNode 链表的表头 :param k: 每个翻转的个数 :return: 翻转后链表的表头 - def reverse_k(self, head, k): 对以head为表头的链表进行翻转k个节点返回...

6479c0ad862a18d1021f35493e5e7d18d1ced5e4

<|skeleton|> class Solution: def reverse_k_group(self, head, k): """leetcode 25. K 个一组翻转链表 :param head: ListNode 链表的表头 :param k: 每个翻转的个数 :return: 翻转后链表的表头""" <|body_0|> def reverse_k(self, head, k): """对以head为表头的链表进行翻转k个节点返回翻转后表头 :param head: 链表表头 :param k: k个节点 :return: 翻转后的表头""" ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def reverse_k_group(self, head, k): """leetcode 25. K 个一组翻转链表 :param head: ListNode 链表的表头 :param k: 每个翻转的个数 :return: 翻转后链表的表头""" if k <= 1: return head p = head length = 0 while p is not None: length += 1 p = p.next ...

the_stack_v2_python_sparse

linkedlist_relate/ReverseKGroup.py

Batman001/leetcode_in_python

train

3

146c8ecf92f9cb293b69a3285616d43a12c205a2

[ "if degree < 0:\n raise ValueError('Polynomial degree must be non-negative')\nself.degree = degree\nself.params = None", "rows, *remaining = data.shape\nif remaining:\n raise ValueError('Data must have dimensions N x 1')\nreturn np.vander(data, N=degree + 1, increasing=True)", "X = PolynomialRegression._d...

PolynomialRegression

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class PolynomialRegression: def __init__(self, degree: int) -> None: """@raises ValueError: if the polynomial degree is negative""" <|body_0|> def _design_matrix(data: np.ndarray, degree: int) -> np.ndarray: """Constructs a polynomial regression design matrix for the given...

stack_v2_sparse_classes_36k_train_008366

7,827

permissive

[ { "docstring": "@raises ValueError: if the polynomial degree is negative", "name": "__init__", "signature": "def __init__(self, degree: int) -> None" }, { "docstring": "Constructs a polynomial regression design matrix for the given input data. For input data x = (x₁, x₂, ..., xₙ) and polynomial ...

4

null

Implement the Python class `PolynomialRegression` described below. Class description: Implement the PolynomialRegression class. Method signatures and docstrings: - def __init__(self, degree: int) -> None: @raises ValueError: if the polynomial degree is negative - def _design_matrix(data: np.ndarray, degree: int) -> n...

421ace81edb0d9af3a173f4ca7e66cc900078c1d

<|skeleton|> class PolynomialRegression: def __init__(self, degree: int) -> None: """@raises ValueError: if the polynomial degree is negative""" <|body_0|> def _design_matrix(data: np.ndarray, degree: int) -> np.ndarray: """Constructs a polynomial regression design matrix for the given...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class PolynomialRegression: def __init__(self, degree: int) -> None: """@raises ValueError: if the polynomial degree is negative""" if degree < 0: raise ValueError('Polynomial degree must be non-negative') self.degree = degree self.params = None def _design_matrix(da...

the_stack_v2_python_sparse

machine_learning/polynomial_regression.py

TheAlgorithms/Python

train

184,217

6085c3fc8b08f9cc24ecae36b7d32f8b26182e3c

[ "roman_symbols = ['M', 'D', 'C', 'L', 'X', 'V', 'I']\nnumbers = [1000, 500, 100, 50, 10, 5, 1]\nroman = []\nfor idx, n in enumerate(numbers):\n i, num = (num / n, num % n)\n if i > 3:\n last = roman.pop()\n if last == '':\n li = [roman_symbols[idx], roman_symbols[idx - 1]]\n el...

<|body_start_0|> roman_symbols = ['M', 'D', 'C', 'L', 'X', 'V', 'I'] numbers = [1000, 500, 100, 50, 10, 5, 1] roman = [] for idx, n in enumerate(numbers): i, num = (num / n, num % n) if i > 3: last = roman.pop() if last == '': ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008367

2,501

no_license

[ { "docstring": "http://en.wikipedia.org/wiki/Roman_numerals", "name": "intToRoman", "signature": "def intToRoman(self, num)" }, { "docstring": "little bit improvement", "name": "intToRoman2", "signature": "def intToRoman2(self, num)" }, { "docstring": "recursive version", "na...

3

stack_v2_sparse_classes_30k_train_013550

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def intToRoman(self, num): http://en.wikipedia.org/wiki/Roman_numerals - def intToRoman2(self, num): little bit improvement - def intToRoman3(self, num): recursive version

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def intToRoman(self, num): http://en.wikipedia.org/wiki/Roman_numerals - def intToRoman2(self, num): little bit improvement - def intToRoman3(self, num): recursive version <|ske...

c10ed7710cfbb74fd068e5c5d05d45564ad22194

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def intToRoman(self, num): """http://en.wikipedia.org/wiki/Roman_numerals""" roman_symbols = ['M', 'D', 'C', 'L', 'X', 'V', 'I'] numbers = [1000, 500, 100, 50, 10, 5, 1] roman = [] for idx, n in enumerate(numbers): i, num = (num / n, num % n) ...

the_stack_v2_python_sparse

leetcode/python/integer-to-roman.py

deepgully/codes

train

1

35d0dd01e2df73117f2db3b9bc922efdd9da0aa6

[ "logging.info('=============测试登录16312345678=============')\nl = LoginView(self.driver)\ndata = l.get_csv_data(self.csv_file, 2)\nl.login_action(data[0], data[1])\nself.assertTrue(l.check_loginStatus())", "logging.info('=============测试登录16212345678=============')\nl = LoginView(self.driver)\ndata = l.get_csv_data(...

TestLogin

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008368

2,618

no_license

[ { "docstring": "测试登录账号16312345678 :return:", "name": "test_login_1", "signature": "def test_login_1(self)" }, { "docstring": "测试登录账号16212345678 :return:", "name": "test_login_2", "signature": "def test_login_2(self)" }, { "docstring": "测试登录账号16512345678 :return:", "name": "te...

5

stack_v2_sparse_classes_30k_train_014925

Implement the Python class `TestLogin` described below. Class description: Implement the TestLogin class. Method signatures and docstrings: - def test_login_1(self): 测试登录账号16312345678 :return: - def test_login_2(self): 测试登录账号16212345678 :return: - def test_login_3(self): 测试登录账号16512345678 :return: - def test_login_4(...

d2b7819fd3687e0a011988fefab3e6fd70bb014a

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class TestLogin: def test_login_1(self): """测试登录账号16312345678 :return:""" logging.info('=============测试登录16312345678=============') l = LoginView(self.driver) data = l.get_csv_data(self.csv_file, 2) l.login_action(data[0], data[1]) self.assertTrue(l.check_loginStatus(...

the_stack_v2_python_sparse

care_doctor/test_case/test_login.py

vothin/code

train

0

c5c07fdb87f04aaeb008e3d02771d17ac3c3e1c0

[ "message = MIMEMultipart('alternative')\nmessage['Subject'] = self.message_subject\nmessage['From'] = self.mail_from_header\nmessage['To'] = self.mail_to_header\nmessage['Reply-To'] = self.message_reply_to\nif self.html_content:\n message.attach(MIMEText(self.html_content, 'html'))\nif self.text_content:\n me...

<|body_start_0|> message = MIMEMultipart('alternative') message['Subject'] = self.message_subject message['From'] = self.mail_from_header message['To'] = self.mail_to_header message['Reply-To'] = self.message_reply_to if self.html_content: message.attach(MIMET...

Mail smtp driver.

MailSmtpDriver

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MailSmtpDriver: """Mail smtp driver.""" def message(self): """Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart""" <|body_0|> def send(self, message=None, message_contents=None): """Send the message through SMTP. Keyw...

stack_v2_sparse_classes_36k_train_008369

3,884

permissive

[ { "docstring": "Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart", "name": "message", "signature": "def message(self)" }, { "docstring": "Send the message through SMTP. Keyword Arguments: message {string} -- The HTML message to be sent to SMTP. (def...

4

stack_v2_sparse_classes_30k_train_004516

Implement the Python class `MailSmtpDriver` described below. Class description: Mail smtp driver. Method signatures and docstrings: - def message(self): Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart - def send(self, message=None, message_contents=None): Send the messa...

66a6b1480a5771bbd1056ba59cec4014beb63fa8

<|skeleton|> class MailSmtpDriver: """Mail smtp driver.""" def message(self): """Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart""" <|body_0|> def send(self, message=None, message_contents=None): """Send the message through SMTP. Keyw...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class MailSmtpDriver: """Mail smtp driver.""" def message(self): """Creates a message object for the underlying driver. Returns: email.mime.multipart.MIMEMultipart""" message = MIMEMultipart('alternative') message['Subject'] = self.message_subject message['From'] = self.mail_fro...

the_stack_v2_python_sparse

src/masonite/drivers/mail/MailSmtpDriver.py

angrycaptain19/masonite

train

0

547b08ebe69e3d8856c45267560203d6c1a0deed

[ "if root is None:\n return True\nreturn self.isMirror(root.left, root.right)", "if root1 is None and root2 is None:\n return True\nelif root1 is None and root2 is not None or (root1 is not None and root2 is None):\n return False\nreturn root1.val == root2.val and self.isMirror(root1.left, root2.right) an...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008370

3,665

no_license

[ { "docstring": ":type root: TreeNode :rtype: bool", "name": "isSymmetric", "signature": "def isSymmetric(self, root)" }, { "docstring": "Checks if root1 is mirror image of root2 (and vice versa.) i.e. flip(root1) == root2 and flip(root2) == root1", "name": "isMirror", "signature": "def i...

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def isSymmetric(self, root): :type root: TreeNode :rtype: bool - def isMirror(self, root1, root2): Checks if root1 is mirror image of root2 (and vice versa.) i.e. flip(root1) == ...

69a960dd8f39e9c8435a3678852071e1085fcb72

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def isSymmetric(self, root): """:type root: TreeNode :rtype: bool""" if root is None: return True return self.isMirror(root.left, root.right) def isMirror(self, root1, root2): """Checks if root1 is mirror image of root2 (and vice versa.) i.e. flip(roo...

the_stack_v2_python_sparse

python/tree/lc101.py

chao-ji/LeetCode

train

1

9aac65469721ac4a9b0e984797a283f08f320604

[ "self.device = device\nself.conn_cmd = conn_cmd\nself.device.conn_cmd = conn_cmd", "try:\n bft_pexpect_helper.spawn.__init__(self.device, command='/bin/bash', args=['-c', self.conn_cmd])\n self.device.expect(pexpect.TIMEOUT, timeout=5)\nexcept pexpect.EOF:\n raise boardfarm.exceptions.ConnectionRefused('...

This class is meant to be used to connect to a device using a custom Linux command instead of telnet/SSH. Sets connection_type to local_cmd, ignores all output for now

LocalCmd

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class LocalCmd: """This class is meant to be used to connect to a device using a custom Linux command instead of telnet/SSH. Sets connection_type to local_cmd, ignores all output for now""" def __init__(self, device=None, conn_cmd=None, **kwargs): """Initializes instance of LocalCmd class ...

stack_v2_sparse_classes_36k_train_008371

1,895

permissive

[ { "docstring": "Initializes instance of LocalCmd class :param device: the device on which the command is to be executed, defaults to None :type device: object :param conn_cmd: the command to be used to connect to the device, defaults to None :type conn_cmd: string :param **kwargs: extra args to be used if any :...

3

stack_v2_sparse_classes_30k_train_001576

Implement the Python class `LocalCmd` described below. Class description: This class is meant to be used to connect to a device using a custom Linux command instead of telnet/SSH. Sets connection_type to local_cmd, ignores all output for now Method signatures and docstrings: - def __init__(self, device=None, conn_cmd...

100521fde1fb67536682cafecc2f91a6e2e8a6f8

<|skeleton|> class LocalCmd: """This class is meant to be used to connect to a device using a custom Linux command instead of telnet/SSH. Sets connection_type to local_cmd, ignores all output for now""" def __init__(self, device=None, conn_cmd=None, **kwargs): """Initializes instance of LocalCmd class ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class LocalCmd: """This class is meant to be used to connect to a device using a custom Linux command instead of telnet/SSH. Sets connection_type to local_cmd, ignores all output for now""" def __init__(self, device=None, conn_cmd=None, **kwargs): """Initializes instance of LocalCmd class :param device...

the_stack_v2_python_sparse

boardfarm/devices/local_cmd.py

mattsm/boardfarm

train

45

9e5d16824ad827209f0aeb0c66e0b869a9761eaf

[ "self.min = np.array([0.0, 0.0])\nself.value = 0.0\nself.domain = np.array([[-100.0, 100.0], [-100.0, 100.0]])\nself.n = 2\nself.smooth = False\nself.info = [True, False, False]\nself.latex_name = 'Schaffer No. 4 Function'\nself.latex_type = 'Many Local Minima'\nself.latex_cost = '\\\\[ f(\\\\mathbf{x}) = 0.5 + \\\...

<|body_start_0|> self.min = np.array([0.0, 0.0]) self.value = 0.0 self.domain = np.array([[-100.0, 100.0], [-100.0, 100.0]]) self.n = 2 self.smooth = False self.info = [True, False, False] self.latex_name = 'Schaffer No. 4 Function' self.latex_type = 'Many...

Schaffer No. 4 Function.

Schaffer4

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008372

1,054

no_license

[ { "docstring": "Constructor.", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "Cost function.", "name": "cost", "signature": "def cost(self, x)" } ]

2

stack_v2_sparse_classes_30k_train_001642

Implement the Python class `Schaffer4` described below. Class description: Schaffer No. 4 Function. Method signatures and docstrings: - def __init__(self): Constructor. - def cost(self, x): Cost function.

Implement the Python class `Schaffer4` described below. Class description: Schaffer No. 4 Function. Method signatures and docstrings: - def __init__(self): Constructor. - def cost(self, x): Cost function. <|skeleton|> class Schaffer4: """Schaffer No. 4 Function.""" def __init__(self): """Constructor...

f2a74df3ab01ac35ea8d80569da909ffa1e86af3

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Schaffer4: """Schaffer No. 4 Function.""" def __init__(self): """Constructor.""" self.min = np.array([0.0, 0.0]) self.value = 0.0 self.domain = np.array([[-100.0, 100.0], [-100.0, 100.0]]) self.n = 2 self.smooth = False self.info = [True, False, Fal...

the_stack_v2_python_sparse

ctf/functions2d/schaffer_4.py

cntaylor/ctf

train

1

40873b9e0ffaadb6451f553b15a061d4381f80da

[ "if not isinstance(filePath, str):\n raise Exceptions.IncorrectTypeException(filePath, 'path', (str,))\nsuper().__init__(currentVersion, hostNamespace=hostNamespace)\nself.FilePath = filePath", "operationSuccess = True\npersistentDataContainerString = '{}'\nif os.path.exists(self.FilePath):\n try:\n ...

A class for handling persistent data. This version will read and write the data to a file through the load and save methods.

PersistentBranchedFile

[ "CC-BY-4.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class PersistentBranchedFile: """A class for handling persistent data. This version will read and write the data to a file through the load and save methods.""" def __init__(self, filePath: str, currentVersion: Version.Version, hostNamespace: str=This.Mod.Namespace): """:param filePath: Th...

stack_v2_sparse_classes_36k_train_008373

34,547

permissive

[ { "docstring": ":param filePath: The file path this persistence object will be written to and read from. :type filePath: str :param currentVersion: The current version of what ever will be controlling this persistence object. This value can allow you to correct outdated persistent data. :type currentVersion: Ve...

3

stack_v2_sparse_classes_30k_train_017978

Implement the Python class `PersistentBranchedFile` described below. Class description: A class for handling persistent data. This version will read and write the data to a file through the load and save methods. Method signatures and docstrings: - def __init__(self, filePath: str, currentVersion: Version.Version, ho...

2d85e6d4428f01294d2d34f1807287b753f7490c

<|skeleton|> class PersistentBranchedFile: """A class for handling persistent data. This version will read and write the data to a file through the load and save methods.""" def __init__(self, filePath: str, currentVersion: Version.Version, hostNamespace: str=This.Mod.Namespace): """:param filePath: Th...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class PersistentBranchedFile: """A class for handling persistent data. This version will read and write the data to a file through the load and save methods.""" def __init__(self, filePath: str, currentVersion: Version.Version, hostNamespace: str=This.Mod.Namespace): """:param filePath: The file path t...

the_stack_v2_python_sparse

Python/NeonOcean.S4.Main/NeonOcean/S4/Main/Data/PersistenceBranched.py

NeonOcean/S4.Main

train

1

46e1b6040e5c41d9cd5760ec9902fce4a5acda80

[ "self.client = aff4.FACTORY.Open(self.client_id, token=self.token)\nself.system = str(self.client.Get(self.client.Schema.SYSTEM))\nself.os_version = str(self.client.Get(self.client.Schema.OS_VERSION))\nself.os_major_version = self.os_version.split('.')[0]\nif self.use_tsk:\n self.path_type = rdfvalue.PathSpec.Pa...

<|body_start_0|> self.client = aff4.FACTORY.Open(self.client_id, token=self.token) self.system = str(self.client.Get(self.client.Schema.SYSTEM)) self.os_version = str(self.client.Get(self.client.Schema.OS_VERSION)) self.os_major_version = self.os_version.split('.')[0] if self.use...

Do the initial work for a Linux system investigation. This encapsulates the different platform specific modules.

LinSystemActivityInvestigation

[ "Apache-2.0", "DOC" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class LinSystemActivityInvestigation: """Do the initial work for a Linux system investigation. This encapsulates the different platform specific modules.""" def Start(self): """Start.""" <|body_0|> def FinishFlow(self, responses): """Complete anything we need to do for...

stack_v2_sparse_classes_36k_train_008374

10,734

permissive

[ { "docstring": "Start.", "name": "Start", "signature": "def Start(self)" }, { "docstring": "Complete anything we need to do for each flow finishing.", "name": "FinishFlow", "signature": "def FinishFlow(self, responses)" } ]

2

stack_v2_sparse_classes_30k_train_016694

Implement the Python class `LinSystemActivityInvestigation` described below. Class description: Do the initial work for a Linux system investigation. This encapsulates the different platform specific modules. Method signatures and docstrings: - def Start(self): Start. - def FinishFlow(self, responses): Complete anyth...

ba1648b97a76f844ffb8e1891cc9e2680f9b1c6e

<|skeleton|> class LinSystemActivityInvestigation: """Do the initial work for a Linux system investigation. This encapsulates the different platform specific modules.""" def Start(self): """Start.""" <|body_0|> def FinishFlow(self, responses): """Complete anything we need to do for...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class LinSystemActivityInvestigation: """Do the initial work for a Linux system investigation. This encapsulates the different platform specific modules.""" def Start(self): """Start.""" self.client = aff4.FACTORY.Open(self.client_id, token=self.token) self.system = str(self.client.Get(...

the_stack_v2_python_sparse

lib/flows/general/automation.py

defaultnamehere/grr

train

3

a7e187abfd5943af19f545145d7b31c2ef09db95

[ "if not value:\n return None\nreturn ''.join([f'{int(i):02x}' for i in value.split(':')])", "if not value:\n return None\nvalue = value.lstrip('#')\nreturn ':'.join([str(int(value[i:i + 2], 16)) for i in range(0, len(value) - 1, 2)])" ]

<|body_start_0|> if not value: return None return ''.join([f'{int(i):02x}' for i in value.split(':')]) <|end_body_0|> <|body_start_1|> if not value: return None value = value.lstrip('#') return ':'.join([str(int(value[i:i + 2], 16)) for i in range(0, len(...

Utility field class for color values.

ColorField

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ColorField: """Utility field class for color values.""" def _serialize(self, value: str, *_, **__): """Convert a hex native color value (``ff0000``) to the format exposed by the SwitchBot API (``255:0:0``).""" <|body_0|> def _deserialize(self, value: str, *_, **__): ...

stack_v2_sparse_classes_36k_train_008375

8,416

permissive

[ { "docstring": "Convert a hex native color value (``ff0000``) to the format exposed by the SwitchBot API (``255:0:0``).", "name": "_serialize", "signature": "def _serialize(self, value: str, *_, **__)" }, { "docstring": "Convert a SwitchBot API color value (``255:0:0``) to the hex native format ...

2

stack_v2_sparse_classes_30k_train_017645

Implement the Python class `ColorField` described below. Class description: Utility field class for color values. Method signatures and docstrings: - def _serialize(self, value: str, *_, **__): Convert a hex native color value (``ff0000``) to the format exposed by the SwitchBot API (``255:0:0``). - def _deserialize(s...

446bc2f67493d3554c5422242ff91d5b5c76d78a

<|skeleton|> class ColorField: """Utility field class for color values.""" def _serialize(self, value: str, *_, **__): """Convert a hex native color value (``ff0000``) to the format exposed by the SwitchBot API (``255:0:0``).""" <|body_0|> def _deserialize(self, value: str, *_, **__): ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ColorField: """Utility field class for color values.""" def _serialize(self, value: str, *_, **__): """Convert a hex native color value (``ff0000``) to the format exposed by the SwitchBot API (``255:0:0``).""" if not value: return None return ''.join([f'{int(i):02x}' f...

the_stack_v2_python_sparse

platypush/schemas/switchbot.py

BlackLight/platypush

train

265

e7686e33272482ab49e219eb9c5dff7e8f89f422

[ "val = {}\nfor column in self.__table__.columns:\n val[column.key] = getattr(self, column.key)\nreturn val", "val = self.value\nif hasattr(self.__class__, '_expandedFields'):\n for field in self.__class__._expandedFields:\n val[field] = [item.expandedValue for item in getattr(self, field).all()]\nret...

<|body_start_0|> val = {} for column in self.__table__.columns: val[column.key] = getattr(self, column.key) return val <|end_body_0|> <|body_start_1|> val = self.value if hasattr(self.__class__, '_expandedFields'): for field in self.__class__._expandedFie...

Define the base functionality for the tables, including a simple primary key and method to convert into a simple (or extended) dictionary class, suitalble for JSON conversion.

TableBase

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TableBase: """Define the base functionality for the tables, including a simple primary key and method to convert into a simple (or extended) dictionary class, suitalble for JSON conversion.""" def value(self): """This extracts the values of the object into a simple dictionary, suitab...

stack_v2_sparse_classes_36k_train_008376

2,266

no_license

[ { "docstring": "This extracts the values of the object into a simple dictionary, suitable for passing to jsonify. Values are selected based on __table__ object, which is created & managed by SQLAlchemy", "name": "value", "signature": "def value(self)" }, { "docstring": "This injects additional i...

2

stack_v2_sparse_classes_30k_train_003271

Implement the Python class `TableBase` described below. Class description: Define the base functionality for the tables, including a simple primary key and method to convert into a simple (or extended) dictionary class, suitalble for JSON conversion. Method signatures and docstrings: - def value(self): This extracts ...

a9dfbf6dd68ebfe8de5f3a4df3c26a9c8ee9e9f0

<|skeleton|> class TableBase: """Define the base functionality for the tables, including a simple primary key and method to convert into a simple (or extended) dictionary class, suitalble for JSON conversion.""" def value(self): """This extracts the values of the object into a simple dictionary, suitab...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class TableBase: """Define the base functionality for the tables, including a simple primary key and method to convert into a simple (or extended) dictionary class, suitalble for JSON conversion.""" def value(self): """This extracts the values of the object into a simple dictionary, suitable for passin...

the_stack_v2_python_sparse

raw/table_base.py

divido/littlefinger

train

0

750d24eab80c9c45669671e6f463bfee0b0caa0b

[ "for _ in range(self.n_retries):\n try:\n r = requests.get(url)\n pathlib.Path(data_folder).mkdir(parents=True, exist_ok=True)\n open(os.path.join(data_folder, filename), 'wb').write(r.content)\n break\n except urllib.error.URLError:\n print(f'Download of {url} failed; wait ...

<|body_start_0|> for _ in range(self.n_retries): try: r = requests.get(url) pathlib.Path(data_folder).mkdir(parents=True, exist_ok=True) open(os.path.join(data_folder, filename), 'wb').write(r.content) break except urllib.er...

This task evaluates a set of metrics, mostly related to worst-class performance, as described in [1]. It is motivated by [2], where the authors note that using only accuracy as a metric is not enough to evaluate the performance of the classifier, as it must not be the same on all classes/groups.

WorstCase

[ "LicenseRef-scancode-proprietary-license", "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class WorstCase: """This task evaluates a set of metrics, mostly related to worst-class performance, as described in [1]. It is motivated by [2], where the authors note that using only accuracy as a metric is not enough to evaluate the performance of the classifier, as it must not be the same on all cl...

stack_v2_sparse_classes_36k_train_008377

7,265

permissive

[ { "docstring": "Method to download the data given its' url, and the desired folder to stor int", "name": "download", "signature": "def download(self, url, data_folder, filename, md5)" }, { "docstring": "Calls the download method to download the cleaned labels from [3], as well as superclasses us...

4

stack_v2_sparse_classes_30k_train_014397

Implement the Python class `WorstCase` described below. Class description: This task evaluates a set of metrics, mostly related to worst-class performance, as described in [1]. It is motivated by [2], where the authors note that using only accuracy as a metric is not enough to evaluate the performance of the classifie...

74b3cda69a2b90bcefed3848faca41a92ad0c9bf

<|skeleton|> class WorstCase: """This task evaluates a set of metrics, mostly related to worst-class performance, as described in [1]. It is motivated by [2], where the authors note that using only accuracy as a metric is not enough to evaluate the performance of the classifier, as it must not be the same on all cl...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class WorstCase: """This task evaluates a set of metrics, mostly related to worst-class performance, as described in [1]. It is motivated by [2], where the authors note that using only accuracy as a metric is not enough to evaluate the performance of the classifier, as it must not be the same on all classes/groups....

the_stack_v2_python_sparse

shifthappens/tasks/worst_case/worst_case.py

shift-happens-benchmark/icml-2022

train

39

fbfac0fbad35566d36233ffa5a0da74310e9f2f3

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ChecklistItem()", "from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'checkedDateTime': lambda n: setattr(self, 'checked_date_time', n.get_datetime_value()), 'createdDateTime': lambda n...

<|body_start_0|> if not parse_node: raise TypeError('parse_node cannot be null.') return ChecklistItem() <|end_body_0|> <|body_start_1|> from .entity import Entity from .entity import Entity fields: Dict[str, Callable[[Any], None]] = {'checkedDateTime': lambda n: set...

ChecklistItem

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ChecklistItem: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ChecklistItem: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns...

stack_v2_sparse_classes_36k_train_008378

2,843

permissive

[ { "docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: ChecklistItem", "name": "create_from_discriminator_value", "signature": "def create_from_discriminator_value...

3

null

Implement the Python class `ChecklistItem` described below. Class description: Implement the ChecklistItem class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ChecklistItem: Creates a new instance of the appropriate class based on discriminator value...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class ChecklistItem: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ChecklistItem: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class ChecklistItem: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ChecklistItem: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: ChecklistIte...

the_stack_v2_python_sparse

msgraph/generated/models/checklist_item.py

microsoftgraph/msgraph-sdk-python

train

135

5a66b20110b2947aefb4afa75292115957e03ecd

[ "try:\n return Member.objects.get(pk=pk)\nexcept Member.DoesNotExist:\n raise Http404", "if pk is not None:\n member = self.get_member(int(pk))\nelse:\n member = None\nself.check_object_permissions(request, member)\ntransactions = Savings.get_savings_transactions(member)\nserializer = SavingsTransacti...

SavingsTransactionsView

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008379

5,809

no_license

[ { "docstring": "Get a member.", "name": "get_member", "signature": "def get_member(self, pk)" }, { "docstring": "List Member's savings Deposits", "name": "get", "signature": "def get(self, request, pk, format=None)" } ]

2

stack_v2_sparse_classes_30k_train_003643

Implement the Python class `SavingsTransactionsView` described below. Class description: Implement the SavingsTransactionsView class. Method signatures and docstrings: - def get_member(self, pk): Get a member. - def get(self, request, pk, format=None): List Member's savings Deposits

Implement the Python class `SavingsTransactionsView` described below. Class description: Implement the SavingsTransactionsView class. Method signatures and docstrings: - def get_member(self, pk): Get a member. - def get(self, request, pk, format=None): List Member's savings Deposits <|skeleton|> class SavingsTransac...

c5ac11e40a628c93c3865363e97b4f255a104ca8

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class SavingsTransactionsView: def get_member(self, pk): """Get a member.""" try: return Member.objects.get(pk=pk) except Member.DoesNotExist: raise Http404 def get(self, request, pk, format=None): """List Member's savings Deposits""" if pk is not...

the_stack_v2_python_sparse

savings/views.py

lubegamark/gosacco

train

2

56c2838ab83515f2317a84ef97e45d0d3d338d13

[ "self.answers = answers\nself.gens = gens\nself.test = zip(answers, gens)\nreturn", "totalscore = 0\nfor answer, gen in self.test:\n score = sentence_bleu([answer], gen, smoothing_function=SmoothingFunction().method4, auto_reweigh=True)\n totalscore = totalscore + score\nreturn totalscore / len(self.gens)",...

TestUtils

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008380

1,704

permissive

[ { "docstring": "初始化，读入标准answers与生成的gens :param answers: 标准回答的list :param gens: 生成回答的list", "name": "__init__", "signature": "def __init__(self, answers, gens)" }, { "docstring": "根据answer与gen逐条对比计算bleu_score :return: bleu_score(float类型)", "name": "get_bleu_score", "signature": "def get_b...

3

stack_v2_sparse_classes_30k_train_004622

Implement the Python class `TestUtils` described below. Class description: Implement the TestUtils class. Method signatures and docstrings: - def __init__(self, answers, gens): 初始化，读入标准answers与生成的gens :param answers: 标准回答的list :param gens: 生成回答的list - def get_bleu_score(self): 根据answer与gen逐条对比计算bleu_score :return: bl...

f56796a86620accd487480e5c3bd992cf3dc7578

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class TestUtils: def __init__(self, answers, gens): """初始化，读入标准answers与生成的gens :param answers: 标准回答的list :param gens: 生成回答的list""" self.answers = answers self.gens = gens self.test = zip(answers, gens) return def get_bleu_score(self): """根据answer与gen逐条对比计算bleu_sc...

the_stack_v2_python_sparse

1.Metrics/metrics.py

imageslr/NLP

train

2

d4c2c99057c2e31c5ac851adc1151edfbb307a53

[ "self.indices = np.empty(shape[0], dtype='int')\nself.array = np.empty(shape)\nself.next = 0", "self.indices[self.next] = key\nself.array[self.next] = value\nself.next += 1", "if self.next != self.indices.shape[0]:\n raise Exception('SparseRows object has not been filled')\nother[self.indices] += self.array"...

Sparse rows

SparseRows

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SparseRows: """Sparse rows""" def __init__(self, shape): """Initialise a sparse numpy array with a given shape :param shape: tuple of integers, where the first index is the number of *non-zero* rows""" <|body_0|> def __setitem__(self, key, value): """Set the valu...

stack_v2_sparse_classes_36k_train_008381

9,083

permissive

[ { "docstring": "Initialise a sparse numpy array with a given shape :param shape: tuple of integers, where the first index is the number of *non-zero* rows", "name": "__init__", "signature": "def __init__(self, shape)" }, { "docstring": "Set the value of the next non-zero row :param key: index of...

3

null

Implement the Python class `SparseRows` described below. Class description: Sparse rows Method signatures and docstrings: - def __init__(self, shape): Initialise a sparse numpy array with a given shape :param shape: tuple of integers, where the first index is the number of *non-zero* rows - def __setitem__(self, key,...

6945d02bc204203a7fb43d70bbf8aa232646158a

<|skeleton|> class SparseRows: """Sparse rows""" def __init__(self, shape): """Initialise a sparse numpy array with a given shape :param shape: tuple of integers, where the first index is the number of *non-zero* rows""" <|body_0|> def __setitem__(self, key, value): """Set the valu...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class SparseRows: """Sparse rows""" def __init__(self, shape): """Initialise a sparse numpy array with a given shape :param shape: tuple of integers, where the first index is the number of *non-zero* rows""" self.indices = np.empty(shape[0], dtype='int') self.array = np.empty(shape) ...

the_stack_v2_python_sparse

src/core/utils.py

guyemerson/sem-func

train

4

d14e88a42aa4d1d53c01c1403d6692a8a5b6ef88

[ "if data is None and isinstance(lambtha, (float, int)):\n if lambtha <= 0:\n raise ValueError('lambtha must be a positive value')\n self.lambtha = float(lambtha)\nelif data is not None:\n if not isinstance(data, list):\n raise TypeError('data must be a list')\n if len(data) < 2:\n r...

<|body_start_0|> if data is None and isinstance(lambtha, (float, int)): if lambtha <= 0: raise ValueError('lambtha must be a positive value') self.lambtha = float(lambtha) elif data is not None: if not isinstance(data, list): raise Type...

define class

Poisson

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008382

1,678

no_license

[ { "docstring": "class constructor", "name": "__init__", "signature": "def __init__(self, data=None, lambtha=1.0)" }, { "docstring": "function that calculates the probability mass function for k successes", "name": "pmf", "signature": "def pmf(self, k)" }, { "docstring": "function...

4

stack_v2_sparse_classes_30k_train_018531

Implement the Python class `Poisson` described below. Class description: define class Method signatures and docstrings: - def __init__(self, data=None, lambtha=1.0): class constructor - def pmf(self, k): function that calculates the probability mass function for k successes - def fact(self, k): function that returns ...

7d3b348aec3b20da25b162b71f150c87c7c28d71

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Poisson: """define class""" def __init__(self, data=None, lambtha=1.0): """class constructor""" if data is None and isinstance(lambtha, (float, int)): if lambtha <= 0: raise ValueError('lambtha must be a positive value') self.lambtha = float(lambtha...

the_stack_v2_python_sparse

math/0x03-probability/poisson.py

dacastanogo/holbertonschool-machine_learning

train

0

9da2e5b13d4d669d3402defae75d2399f16b14f1

[ "e = 2.718281828459045\nctx.save_for_backward(x, l, u, g)\ny = l + (u - l) / (1 + e ** (-g * x))\nreturn y", "e = 2.718281828459045\nx, l, u, g = ctx.saved_tensors\ndzdx = dzdy * (g * (u - l) * e ** (-g * x) / (1 + e ** (-g * x)) ** 2)\ndzdl = dzdy * (1 / (e ** (g * x) + 1))\ndzdu = dzdy * (1 / (e ** (-g * x) + 1...

GeneralizedLogistic

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GeneralizedLogistic: def forward(ctx, x, l, u, g): """Computes the generalized logistic function Arguments --------- ctx: A PyTorch context object x: (Tensor) of size (T x n), the input features l, u, and g: (scalar tensors) representing the generalized logistic function parameters. Retu...

stack_v2_sparse_classes_36k_train_008383

1,489

no_license

[ { "docstring": "Computes the generalized logistic function Arguments --------- ctx: A PyTorch context object x: (Tensor) of size (T x n), the input features l, u, and g: (scalar tensors) representing the generalized logistic function parameters. Returns ------- y: (Tensor) of size (T x n), the outputs of the ge...

2

stack_v2_sparse_classes_30k_train_018910

Implement the Python class `GeneralizedLogistic` described below. Class description: Implement the GeneralizedLogistic class. Method signatures and docstrings: - def forward(ctx, x, l, u, g): Computes the generalized logistic function Arguments --------- ctx: A PyTorch context object x: (Tensor) of size (T x n), the ...

b6824c340272f65b8c5fd44fcea2a363a7e69f05

<|skeleton|> class GeneralizedLogistic: def forward(ctx, x, l, u, g): """Computes the generalized logistic function Arguments --------- ctx: A PyTorch context object x: (Tensor) of size (T x n), the input features l, u, and g: (scalar tensors) representing the generalized logistic function parameters. Retu...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class GeneralizedLogistic: def forward(ctx, x, l, u, g): """Computes the generalized logistic function Arguments --------- ctx: A PyTorch context object x: (Tensor) of size (T x n), the input features l, u, and g: (scalar tensors) representing the generalized logistic function parameters. Returns ------- y:...

the_stack_v2_python_sparse

homework/Kirsten_Ziman_HW1/generalized_logistic.py

KirstensGitHub/deep_learning

train

0

4e1ccd6f4a660ce2919ceeac94483ae8dd711e41

[ "res = [0]\nm = len(matrix)\nif m:\n n = len(matrix[0])\nelse:\n return 0\ndp = [[0 for _ in range(n + 1)] for _ in range(m + 1)]\nfor i in range(m):\n for j in range(n):\n if matrix[i][j] == '1':\n if dp[i][j] and dp[i + 1][j] and dp[i][j + 1]:\n dp[i + 1][j + 1] = min(dp[...

<|body_start_0|> res = [0] m = len(matrix) if m: n = len(matrix[0]) else: return 0 dp = [[0 for _ in range(n + 1)] for _ in range(m + 1)] for i in range(m): for j in range(n): if matrix[i][j] == '1': ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008384

1,273

no_license

[ { "docstring": ":type matrix: List[List[str]] :rtype: int", "name": "maximalSquare", "signature": "def maximalSquare(self, matrix)" }, { "docstring": ":type matrix: List[List[str]] :rtype: int", "name": "maximalSquare0", "signature": "def maximalSquare0(self, matrix)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def maximalSquare(self, matrix): :type matrix: List[List[str]] :rtype: int - def maximalSquare0(self, matrix): :type matrix: List[List[str]] :rtype: int

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def maximalSquare(self, matrix): :type matrix: List[List[str]] :rtype: int - def maximalSquare0(self, matrix): :type matrix: List[List[str]] :rtype: int <|skeleton|> class Solut...

9e49b2c6003b957276737005d4aaac276b44d251

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def maximalSquare(self, matrix): """:type matrix: List[List[str]] :rtype: int""" res = [0] m = len(matrix) if m: n = len(matrix[0]) else: return 0 dp = [[0 for _ in range(n + 1)] for _ in range(m + 1)] for i in range(m):...

the_stack_v2_python_sparse

PythonCode/src/0221_Maximal_Square.py

oneyuan/CodeforFun

train

0

23e1ca11a721f01b503928769d2cc82035a8f010

[ "self.nzbget = NZBGetAPI(config[CONF_HOST], config.get(CONF_USERNAME), config.get(CONF_PASSWORD), config[CONF_SSL], config[CONF_VERIFY_SSL], config[CONF_PORT])\nself._completed_downloads_init = False\nself._completed_downloads = set[tuple]()\nupdate_interval = timedelta(seconds=options[CONF_SCAN_INTERVAL])\nsuper()...

<|body_start_0|> self.nzbget = NZBGetAPI(config[CONF_HOST], config.get(CONF_USERNAME), config.get(CONF_PASSWORD), config[CONF_SSL], config[CONF_VERIFY_SSL], config[CONF_PORT]) self._completed_downloads_init = False self._completed_downloads = set[tuple]() update_interval = timedelta(seco...

Class to manage fetching NZBGet data.

NZBGetDataUpdateCoordinator

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class NZBGetDataUpdateCoordinator: """Class to manage fetching NZBGet data.""" def __init__(self, hass: HomeAssistant, *, config: Mapping[str, Any], options: Mapping[str, Any]) -> None: """Initialize global NZBGet data updater.""" <|body_0|> def _check_completed_downloads(self...

stack_v2_sparse_classes_36k_train_008385

3,030

permissive

[ { "docstring": "Initialize global NZBGet data updater.", "name": "__init__", "signature": "def __init__(self, hass: HomeAssistant, *, config: Mapping[str, Any], options: Mapping[str, Any]) -> None" }, { "docstring": "Check history for newly completed downloads.", "name": "_check_completed_do...

3

stack_v2_sparse_classes_30k_test_000119

Implement the Python class `NZBGetDataUpdateCoordinator` described below. Class description: Class to manage fetching NZBGet data. Method signatures and docstrings: - def __init__(self, hass: HomeAssistant, *, config: Mapping[str, Any], options: Mapping[str, Any]) -> None: Initialize global NZBGet data updater. - def...

80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743

<|skeleton|> class NZBGetDataUpdateCoordinator: """Class to manage fetching NZBGet data.""" def __init__(self, hass: HomeAssistant, *, config: Mapping[str, Any], options: Mapping[str, Any]) -> None: """Initialize global NZBGet data updater.""" <|body_0|> def _check_completed_downloads(self...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class NZBGetDataUpdateCoordinator: """Class to manage fetching NZBGet data.""" def __init__(self, hass: HomeAssistant, *, config: Mapping[str, Any], options: Mapping[str, Any]) -> None: """Initialize global NZBGet data updater.""" self.nzbget = NZBGetAPI(config[CONF_HOST], config.get(CONF_USERN...

the_stack_v2_python_sparse

homeassistant/components/nzbget/coordinator.py

home-assistant/core

train

35,501

1886a0e1996e1e4538c02e00aed4aa6f5ef99889

[ "super(Transformer, self).__init__()\nself.encoder = encoder\nself.decoder = decoder\nself.linear = tf.keras.layers.Dense(units=target_vocab, input_shape=([None], [None]))", "print('============================')\nprint(inputs)\nprint(target)\nprint('============================')\ndec_output = self.decoder.decod...

The Transformer model class

Transformer

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Transformer: """The Transformer model class""" def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, encoder, decoder, drop_rate=0.1): """init of transformer""" <|body_0|> def call(self, inputs, target, training, encoder_mask, loo...

stack_v2_sparse_classes_36k_train_008386

1,488

no_license

[ { "docstring": "init of transformer", "name": "__init__", "signature": "def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, encoder, decoder, drop_rate=0.1)" }, { "docstring": "Calls the transformer", "name": "call", "signature": "def call(self,...

2

null

Implement the Python class `Transformer` described below. Class description: The Transformer model class Method signatures and docstrings: - def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, encoder, decoder, drop_rate=0.1): init of transformer - def call(self, inputs, tar...

4200798bdbbe828db94e5585b62a595e3a96c3e6

<|skeleton|> class Transformer: """The Transformer model class""" def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, encoder, decoder, drop_rate=0.1): """init of transformer""" <|body_0|> def call(self, inputs, target, training, encoder_mask, loo...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Transformer: """The Transformer model class""" def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, encoder, decoder, drop_rate=0.1): """init of transformer""" super(Transformer, self).__init__() self.encoder = encoder self.decoder...

the_stack_v2_python_sparse

supervised_learning/0x12-transformer_apps/5-transformer.py

JohnCook17/holbertonschool-machine_learning

train

3

420fabc4c13777bf3a4a7a4796063b42e8a8e741

[ "self.num_elem = self.kwargs['num_elem']\nnum_pts = self.num_elem + 1\nind_pts = range(num_pts)\nself._declare_variable('Temp', size=num_pts, lower=0.001)\nself._declare_argument('h', indices=ind_pts)", "pvec = self.vec['p']\nuvec = self.vec['u']\nalt = pvec('h') * 1000.0\ntemp = uvec('Temp')\ntemp[:] = (288.16 -...

linear temperature model using the standard atmosphere

SysTempOld

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SysTempOld: """linear temperature model using the standard atmosphere""" def _declare(self): """owned variable: Temp (temperature) dependencies: h (altitude)""" <|body_0|> def apply_G(self): """temperature model extracted from linear portion of the standard atmos...

stack_v2_sparse_classes_36k_train_008387

17,488

no_license

[ { "docstring": "owned variable: Temp (temperature) dependencies: h (altitude)", "name": "_declare", "signature": "def _declare(self)" }, { "docstring": "temperature model extracted from linear portion of the standard atmosphere", "name": "apply_G", "signature": "def apply_G(self)" }, ...

3

stack_v2_sparse_classes_30k_train_009852

Implement the Python class `SysTempOld` described below. Class description: linear temperature model using the standard atmosphere Method signatures and docstrings: - def _declare(self): owned variable: Temp (temperature) dependencies: h (altitude) - def apply_G(self): temperature model extracted from linear portion ...

f5b1ce287c6692540b738a7e9ec85be645f4947a

<|skeleton|> class SysTempOld: """linear temperature model using the standard atmosphere""" def _declare(self): """owned variable: Temp (temperature) dependencies: h (altitude)""" <|body_0|> def apply_G(self): """temperature model extracted from linear portion of the standard atmos...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class SysTempOld: """linear temperature model using the standard atmosphere""" def _declare(self): """owned variable: Temp (temperature) dependencies: h (altitude)""" self.num_elem = self.kwargs['num_elem'] num_pts = self.num_elem + 1 ind_pts = range(num_pts) self._decla...

the_stack_v2_python_sparse

cmf_original_code/atmospherics.py

naylor-b/pyMission

train

0

5c53351570bfcd2c3247bc5f9fd70e3ce2d882b4

[ "if model._meta.app_label == 'data_source':\n return 'moodle'\nif model._meta.app_label == 'export':\n return 'cassandra'\nreturn None", "if model._meta.app_label == 'data_source':\n raise Exception('No writing to Moodle DB allowed.')\nif model._meta.app_label == 'export':\n return 'cassandra'\nreturn...

A router to control all database operations on models in the applications listed in route_app_labels.

Router

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Router: """A router to control all database operations on models in the applications listed in route_app_labels.""" def db_for_read(self, model, **hints): """db to use to read models listed in in apps route_app_labels.""" <|body_0|> def db_for_write(self, model, **hints)...

stack_v2_sparse_classes_36k_train_008388

1,669

permissive

[ { "docstring": "db to use to read models listed in in apps route_app_labels.", "name": "db_for_read", "signature": "def db_for_read(self, model, **hints)" }, { "docstring": "db to use to write models listed in in apps route_app_labels. Beware that save() and delete() are not supposed to happen",...

4

stack_v2_sparse_classes_30k_train_013654

Implement the Python class `Router` described below. Class description: A router to control all database operations on models in the applications listed in route_app_labels. Method signatures and docstrings: - def db_for_read(self, model, **hints): db to use to read models listed in in apps route_app_labels. - def db...

e2d3fa7eb65bc32345acbda28fc4c7fb775f65cb

<|skeleton|> class Router: """A router to control all database operations on models in the applications listed in route_app_labels.""" def db_for_read(self, model, **hints): """db to use to read models listed in in apps route_app_labels.""" <|body_0|> def db_for_write(self, model, **hints)...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Router: """A router to control all database operations on models in the applications listed in route_app_labels.""" def db_for_read(self, model, **hints): """db to use to read models listed in in apps route_app_labels.""" if model._meta.app_label == 'data_source': return 'mood...

the_stack_v2_python_sparse

assessment_ms/app/app/db.py

jakobschroeber/bachelor_thesis

train

0

3e703feef06773e70218659a7d05eddd42bacc99

[ "self.words = dict()\nfor i, w in enumerate(words):\n self.words[w] = self.words.get(w, []) + [i]", "result = float('inf')\nw1 = self.words.get(word1)\nw2 = self.words.get(word2)\ni1 = 0\ni2 = 0\nwhile i1 < len(w1) and i2 < len(w2):\n if w1[i1] < w2[i2]:\n result = min(result, w2[i2] - w1[i1])\n ...

WordDistance

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008389

1,033

no_license

[ { "docstring": ":type words: List[str]", "name": "__init__", "signature": "def __init__(self, words)" }, { "docstring": ":type word1: str :type word2: str :rtype: int", "name": "shortest", "signature": "def shortest(self, word1, word2)" } ]

2

null

Implement the Python class `WordDistance` described below. Class description: Implement the WordDistance class. Method signatures and docstrings: - def __init__(self, words): :type words: List[str] - def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int

Implement the Python class `WordDistance` described below. Class description: Implement the WordDistance class. Method signatures and docstrings: - def __init__(self, words): :type words: List[str] - def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int <|skeleton|> class WordDistance: ...

36cb33af758b1d01da35982481a8bbfbee5c2810

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class WordDistance: def __init__(self, words): """:type words: List[str]""" self.words = dict() for i, w in enumerate(words): self.words[w] = self.words.get(w, []) + [i] def shortest(self, word1, word2): """:type word1: str :type word2: str :rtype: int""" res...

the_stack_v2_python_sparse

LeetCode/shortestWordDistance2.py

dicao425/algorithmExercise

train

0

1dd8840793332f3881cebaa3f1442f2d61a55931

[ "self.TIDAL_CLIENT_VERSION = '1.9.1'\nself.TIDAL_API_BASE = 'https://api.tidalhifi.com/v1/'\nself.username = username\nself.token = token\nself.unique_id = str(uuid.uuid4()).replace('-', '')[16:]\nself.auth(password)\npassword = None", "postParams = {'username': self.username, 'password': password, 'token': self....

<|body_start_0|> self.TIDAL_CLIENT_VERSION = '1.9.1' self.TIDAL_API_BASE = 'https://api.tidalhifi.com/v1/' self.username = username self.token = token self.unique_id = str(uuid.uuid4()).replace('-', '')[16:] self.auth(password) password = None <|end_body_0|> <|bo...

Tidal session object which can be used to communicate with Tidal servers

TidalSession

[ "ISC" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TidalSession: """Tidal session object which can be used to communicate with Tidal servers""" def __init__(self, username, password, token='4zx46pyr9o8qZNRw'): """Initiate a new session""" <|body_0|> def auth(self, password): """Attempts to authorize and create a ...

stack_v2_sparse_classes_36k_train_008390

8,327

permissive

[ { "docstring": "Initiate a new session", "name": "__init__", "signature": "def __init__(self, username, password, token='4zx46pyr9o8qZNRw')" }, { "docstring": "Attempts to authorize and create a new valid session", "name": "auth", "signature": "def auth(self, password)" }, { "doc...

4

stack_v2_sparse_classes_30k_train_011504

Implement the Python class `TidalSession` described below. Class description: Tidal session object which can be used to communicate with Tidal servers Method signatures and docstrings: - def __init__(self, username, password, token='4zx46pyr9o8qZNRw'): Initiate a new session - def auth(self, password): Attempts to au...

2a7e339b97f173efa319abc5e4ec8fc9172f1505

<|skeleton|> class TidalSession: """Tidal session object which can be used to communicate with Tidal servers""" def __init__(self, username, password, token='4zx46pyr9o8qZNRw'): """Initiate a new session""" <|body_0|> def auth(self, password): """Attempts to authorize and create a ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class TidalSession: """Tidal session object which can be used to communicate with Tidal servers""" def __init__(self, username, password, token='4zx46pyr9o8qZNRw'): """Initiate a new session""" self.TIDAL_CLIENT_VERSION = '1.9.1' self.TIDAL_API_BASE = 'https://api.tidalhifi.com/v1/' ...

the_stack_v2_python_sparse

bin/redsea/tidal_api.py

SultanSGillani/dotfiles

train

7

cdc578138d2b4d7413dcd6cdffb9d7717708b746

[ "r = [str(len(strs))]\nfor s in strs:\n r.append(str(len(s)))\n r.append(s)\nreturn ' '.join(r)", "q = 0\np = s.find(' ')\np = p if p > 0 else len(s)\nlistlen = int(s[q:p])\nstrs = []\nfor _ in xrange(listlen):\n q = p + 1\n p = s.find(' ', q)\n strlen = int(s[q:p])\n q = p + 1\n p = q + strl...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008391

877

no_license

[ { "docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str", "name": "encode", "signature": "def encode(self, strs)" }, { "docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]", "name": "decode", "signature": "def ...

2

stack_v2_sparse_classes_30k_train_013635

Implement the Python class `Codec` described below. Class description: Implement the Codec class. Method signatures and docstrings: - def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str - def decode(self, s): Decodes a single string to a list of strings. :type s: st...

20580185c6f72f3c09a725168af48893156161f5

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Codec: def encode(self, strs): """Encodes a list of strings to a single string. :type strs: List[str] :rtype: str""" r = [str(len(strs))] for s in strs: r.append(str(len(s))) r.append(s) return ' '.join(r) def decode(self, s): """Decodes a s...

the_stack_v2_python_sparse

coding/00271-encode-decode-str/solution.py

misaka-10032/leetcode

train

3

973014ada78ac62a8b1c58f59d1ac5619de47fee

[ "import matplotlib.pyplot\nfrom mpl_toolkits.mplot3d import Axes3D\nfig = matplotlib.pyplot.figure()\naxs = fig.add_subplot(1, 1, 1, projection='3d')\naxs.plot_trisurf(V[:, 0], V[:, 1], V[:, 2], triangles=F)\naxs.set_xlabel('x')\naxs.set_ylabel('y')\naxs.set_zlabel('z')\naxs.axis('equal')\nmatplotlib.pyplot.show()\...

<|body_start_0|> import matplotlib.pyplot from mpl_toolkits.mplot3d import Axes3D fig = matplotlib.pyplot.figure() axs = fig.add_subplot(1, 1, 1, projection='3d') axs.plot_trisurf(V[:, 0], V[:, 1], V[:, 2], triangles=F) axs.set_xlabel('x') axs.set_ylabel('y') ...

Define all of my functions within a class to keep the global name space clean.

myfuncs

[ "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class myfuncs: """Define all of my functions within a class to keep the global name space clean.""" def qp(F, V): """Quickly plot a surface defined by a face and vertex list, F and V respectively. The faces are colored blue. This is simply a rewrite of Ken's qp in MATLAB. F : Nx3 NumPy arr...

stack_v2_sparse_classes_36k_train_008392

2,695

permissive

[ { "docstring": "Quickly plot a surface defined by a face and vertex list, F and V respectively. The faces are colored blue. This is simply a rewrite of Ken's qp in MATLAB. F : Nx3 NumPy array of faces (V1, V2, V3) V : Nx3 NumPy array of vertexes ( X, Y, Z)", "name": "qp", "signature": "def qp(F, V)" }...

2

stack_v2_sparse_classes_30k_train_015381

Implement the Python class `myfuncs` described below. Class description: Define all of my functions within a class to keep the global name space clean. Method signatures and docstrings: - def qp(F, V): Quickly plot a surface defined by a face and vertex list, F and V respectively. The faces are colored blue. This is ...

c4fbebe26b09dde93249293ce3db2e71936a894b

<|skeleton|> class myfuncs: """Define all of my functions within a class to keep the global name space clean.""" def qp(F, V): """Quickly plot a surface defined by a face and vertex list, F and V respectively. The faces are colored blue. This is simply a rewrite of Ken's qp in MATLAB. F : Nx3 NumPy arr...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class myfuncs: """Define all of my functions within a class to keep the global name space clean.""" def qp(F, V): """Quickly plot a surface defined by a face and vertex list, F and V respectively. The faces are colored blue. This is simply a rewrite of Ken's qp in MATLAB. F : Nx3 NumPy array of faces (...

the_stack_v2_python_sparse

ipython/profile_default/startup/50_myfuncs.py

kprussing/dotfiles

train

1

6092746b461e8423478ff35b1dc045f10190790a

[ "num_dic = {}\nfor i, num in enumerate(numbers):\n if num_dic.get(target - num) is not None:\n return [num_dic.get(target - num) + 1, i + 1]\n else:\n num_dic[num] = i\nreturn [-1, -1]", "left, right = (0, len(numbers) - 1)\nwhile left < right:\n sums = numbers[left] + numbers[right]\n i...

<|body_start_0|> num_dic = {} for i, num in enumerate(numbers): if num_dic.get(target - num) is not None: return [num_dic.get(target - num) + 1, i + 1] else: num_dic[num] = i return [-1, -1] <|end_body_0|> <|body_start_1|> left, ri...

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def twoSum(self, numbers, target): """字典边存边查看是否满足""" <|body_0|> def twoSum_(self, numbers, target): """双指针法：有效利用有序数组这个条件""" <|body_1|> <|end_skeleton|> <|body_start_0|> num_dic = {} for i, num in enumerate(numbers): if ...

stack_v2_sparse_classes_36k_train_008393

1,765

no_license

[ { "docstring": "字典边存边查看是否满足", "name": "twoSum", "signature": "def twoSum(self, numbers, target)" }, { "docstring": "双指针法：有效利用有序数组这个条件", "name": "twoSum_", "signature": "def twoSum_(self, numbers, target)" } ]

2

stack_v2_sparse_classes_30k_train_014817

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def twoSum(self, numbers, target): 字典边存边查看是否满足 - def twoSum_(self, numbers, target): 双指针法：有效利用有序数组这个条件

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def twoSum(self, numbers, target): 字典边存边查看是否满足 - def twoSum_(self, numbers, target): 双指针法：有效利用有序数组这个条件 <|skeleton|> class Solution: def twoSum(self, numbers, target): ...

2e81b871bf1db7ea7432d1ebf889c72066e64753

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def twoSum(self, numbers, target): """字典边存边查看是否满足""" num_dic = {} for i, num in enumerate(numbers): if num_dic.get(target - num) is not None: return [num_dic.get(target - num) + 1, i + 1] else: num_dic[num] = i r...

the_stack_v2_python_sparse

array/twoSum.py

NextNight/LeetCodeAndStructAndAlgorithm

train

0

852d747b43a63cccaedfd6a77a1248f772c33014

[ "len_n, right_most = (len(nums), 0)\nfor i in range(len_n):\n if i <= right_most:\n right_most = max(nums[i] + i, right_most)\n if right_most >= len_n - 1:\n return True\nreturn False", "len_n = len(nums)\ndp = [False] * len_n\ndp[0] = True\nfor i in range(len_n):\n if dp[i]:\n ...

<|body_start_0|> len_n, right_most = (len(nums), 0) for i in range(len_n): if i <= right_most: right_most = max(nums[i] + i, right_most) if right_most >= len_n - 1: return True return False <|end_body_0|> <|body_start_1|> l...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008394

4,093

no_license

[ { "docstring": "执行用时： 52 ms , 在所有 Python3 提交中击败了 52.08% 的用户内存消耗： 16 MB , 在所有 Python3 提交中击败了 73.49% 的用户", "name": "canJump", "signature": "def canJump(self, nums: List[int]) -> bool" }, { "docstring": "超时", "name": "canJump1", "signature": "def canJump1(self, nums: List[int]) -> bool" ...

4

stack_v2_sparse_classes_30k_train_011064

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def canJump(self, nums: List[int]) -> bool: 执行用时： 52 ms , 在所有 Python3 提交中击败了 52.08% 的用户内存消耗： 16 MB , 在所有 Python3 提交中击败了 73.49% 的用户 - def canJump1(self, nums: List[int]) -> bool:...

d613ed8a5a2c15ace7d513965b372d128845d66a

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def canJump(self, nums: List[int]) -> bool: """执行用时： 52 ms , 在所有 Python3 提交中击败了 52.08% 的用户内存消耗： 16 MB , 在所有 Python3 提交中击败了 73.49% 的用户""" len_n, right_most = (len(nums), 0) for i in range(len_n): if i <= right_most: right_most = max(nums[i] + i, ri...

the_stack_v2_python_sparse

跳跃游戏1&2.py

nomboy/leetcode

train

0

e4ff882ac432ed2ee43f9e7487b700100fccbea4

[ "super(QuickShift, self).__init__(paramlist)\nself.params['algorithm'] = 'QuickShift'\nself.params['alpha1'] = 0.5\nself.params['beta1'] = 0.5\nself.params['beta2'] = 0.5\nself.paramindexes = ['alpha1', 'beta1', 'beta2']\nself.set_params(paramlist)", "mindim = min(img.shape)\nratio = self.params['alpha1']\nkernel...

<|body_start_0|> super(QuickShift, self).__init__(paramlist) self.params['algorithm'] = 'QuickShift' self.params['alpha1'] = 0.5 self.params['beta1'] = 0.5 self.params['beta2'] = 0.5 self.paramindexes = ['alpha1', 'beta1', 'beta2'] self.set_params(paramlist) <|end...

Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher vals give more weight to color-space ...

QuickShift

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class QuickShift: """Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher...

stack_v2_sparse_classes_36k_train_008395

29,598

permissive

[ { "docstring": "Get parameters from parameter list that are used in segmentation algorithm. Assign default values to these parameters.", "name": "__init__", "signature": "def __init__(self, paramlist=None)" }, { "docstring": "Evaluate segmentation algorithm on training image. Keyword arguments: ...

2

stack_v2_sparse_classes_30k_test_000327

Implement the Python class `QuickShift` described below. Class description: Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space pr...

9246b8b20510d4c89357a6764ed96b919eb92d5a

<|skeleton|> class QuickShift: """Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class QuickShift: """Perform the Quick Shift segmentation algorithm. Segments images with quickshift clustering in Color (x,y) space. Returns ndarray segmentation mask of the labels. Parameters: image -- ndarray, input image ratio -- float, balances color-space proximity & image-space proximity. Higher vals give mo...

the_stack_v2_python_sparse

see/Segmentors.py

Deepak768/see-segment

train

0

03a5f5f33e6f3e79a050006d374c6dfd10a08ffc

[ "self.rects = rects\nself.sizes = list(map(lambda x: (x[2] - x[0] + 1) * (x[3] - x[1] + 1), rects))\nself.weights = list(accumulate(self.sizes))", "r = random.randrange(0, self.weights[-1])\nidx = bisect(self.weights, r)\noffset = self.sizes[idx] + r - self.weights[idx]\nwidth = self.rects[idx][2] - self.rects[id...

Solution

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008396

820

permissive

[ { "docstring": ":type rects: List[List[int]]", "name": "__init__", "signature": "def __init__(self, rects)" }, { "docstring": ":rtype: List[int]", "name": "pick", "signature": "def pick(self)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def __init__(self, rects): :type rects: List[List[int]] - def pick(self): :rtype: List[int]

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def __init__(self, rects): :type rects: List[List[int]] - def pick(self): :rtype: List[int] <|skeleton|> class Solution: def __init__(self, rects): """:type rects: ...

b07f7ba69f3d2a7e294f915934db302f43c0848f

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class Solution: def __init__(self, rects): """:type rects: List[List[int]]""" self.rects = rects self.sizes = list(map(lambda x: (x[2] - x[0] + 1) * (x[3] - x[1] + 1), rects)) self.weights = list(accumulate(self.sizes)) def pick(self): """:rtype: List[int]""" r =...

the_stack_v2_python_sparse

algorithms/python/497.py

viing937/leetcode

train

3

249603cafd61a4eee2a3a77fefbe57ad8b700bab

[ "user = cls._from_database('SELECT * FROM users WHERE google_id = %s', (google_id,))\nif user is not None:\n return user\nreturn User()", "user = cls._from_database('SELECT * FROM users WHERE email = %s', (email,))\nif user is not None:\n return user\nreturn User()", "if authorization_level in ['EDIT', 'O...

User

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_36k_train_008397

1,275

permissive

[ { "docstring": "Initialize a User by fetching them by their google id.", "name": "from_google_id", "signature": "def from_google_id(cls, google_id)" }, { "docstring": "Initialize a User by fetching them by their email.", "name": "from_email", "signature": "def from_email(cls, email)" }...

3

null

Implement the Python class `User` described below. Class description: Implement the User class. Method signatures and docstrings: - def from_google_id(cls, google_id): Initialize a User by fetching them by their google id. - def from_email(cls, email): Initialize a User by fetching them by their email. - def google_i...

71aa937a9b7db7289d69ac85587387070d2af851

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class User: def from_google_id(cls, google_id): """Initialize a User by fetching them by their google id.""" user = cls._from_database('SELECT * FROM users WHERE google_id = %s', (google_id,)) if user is not None: return user return User() def from_email(cls, email):...

the_stack_v2_python_sparse

opendc/models/user.py

atlarge-research/opendc-web-server

train

2

e1fb48ad6c99e4875eacb656070cdb520fe327f7

[ "template_values = {}\ntemplate_values['page_title'] = handler.format_title('Local Chapters')\ncontent = safe_dom.NodeList()\ncontent.append(safe_dom.Element('a', id='add_local_chapter', className='gcb-button gcb-pull-right', role='button', href='%s?action=add_local_chapter' % handler.LINK_URL).add_text('Add Local ...

<|body_start_0|> template_values = {} template_values['page_title'] = handler.format_title('Local Chapters') content = safe_dom.NodeList() content.append(safe_dom.Element('a', id='add_local_chapter', className='gcb-button gcb-pull-right', role='button', href='%s?action=add_local_chapter'...

LocalChapterBaseAdminHandler

[ "CC-BY-3.0", "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class LocalChapterBaseAdminHandler: def get_local_chapters(self, handler): """Shows a list of all local chapters available on this site.""" <|body_0|> def get_add_local_chapter(self, handler): """Handles 'get_add_local_chapter' action and renders new course entry editor.""...

stack_v2_sparse_classes_36k_train_008398

20,021

permissive

[ { "docstring": "Shows a list of all local chapters available on this site.", "name": "get_local_chapters", "signature": "def get_local_chapters(self, handler)" }, { "docstring": "Handles 'get_add_local_chapter' action and renders new course entry editor.", "name": "get_add_local_chapter", ...

4

null

Implement the Python class `LocalChapterBaseAdminHandler` described below. Class description: Implement the LocalChapterBaseAdminHandler class. Method signatures and docstrings: - def get_local_chapters(self, handler): Shows a list of all local chapters available on this site. - def get_add_local_chapter(self, handle...

2bca9d64499e160b2da9bed6e97fcda712feec72

<|skeleton|> class LocalChapterBaseAdminHandler: def get_local_chapters(self, handler): """Shows a list of all local chapters available on this site.""" <|body_0|> def get_add_local_chapter(self, handler): """Handles 'get_add_local_chapter' action and renders new course entry editor.""...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class LocalChapterBaseAdminHandler: def get_local_chapters(self, handler): """Shows a list of all local chapters available on this site.""" template_values = {} template_values['page_title'] = handler.format_title('Local Chapters') content = safe_dom.NodeList() content.append...

the_stack_v2_python_sparse

coursebuilder/modules/local_chapter/local_chapter.py

RavinderSinghPB/seek

train

0

9c0c3b64e469c154e4385b71e27e8bd3a22eebf6

[ "query = {'uuid': bundle_id}\nprojection = {'_id': False, 'files': False}\nlogging.debug(f'MONGO-START: db.Bundles.find_one(filter={query}, projection={projection})')\nret = await self.db.Bundles.find_one(filter=query, projection=projection)\nlogging.debug('MONGO-END: db.Bundles.find_one(filter, projection)')\nif...

<|body_start_0|> query = {'uuid': bundle_id} projection = {'_id': False, 'files': False} logging.debug(f'MONGO-START: db.Bundles.find_one(filter={query}, projection={projection})') ret = await self.db.Bundles.find_one(filter=query, projection=projection) logging.debug('MONGO-END:...

BundlesSingleHandler handles object level routes for Bundles.

BundlesSingleHandler

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class BundlesSingleHandler: """BundlesSingleHandler handles object level routes for Bundles.""" async def get(self, bundle_id: str) -> None: """Handle GET /Bundles/{uuid}.""" <|body_0|> async def patch(self, bundle_id: str) -> None: """Handle PATCH /Bundles/{uuid}.""" ...

stack_v2_sparse_classes_36k_train_008399

42,572

permissive

[ { "docstring": "Handle GET /Bundles/{uuid}.", "name": "get", "signature": "async def get(self, bundle_id: str) -> None" }, { "docstring": "Handle PATCH /Bundles/{uuid}.", "name": "patch", "signature": "async def patch(self, bundle_id: str) -> None" }, { "docstring": "Handle DELET...

3

stack_v2_sparse_classes_30k_train_000909

Implement the Python class `BundlesSingleHandler` described below. Class description: BundlesSingleHandler handles object level routes for Bundles. Method signatures and docstrings: - async def get(self, bundle_id: str) -> None: Handle GET /Bundles/{uuid}. - async def patch(self, bundle_id: str) -> None: Handle PATCH...

12719efa84be2281debe98a18c69bbe7a6d0f399

<|skeleton|> class BundlesSingleHandler: """BundlesSingleHandler handles object level routes for Bundles.""" async def get(self, bundle_id: str) -> None: """Handle GET /Bundles/{uuid}.""" <|body_0|> async def patch(self, bundle_id: str) -> None: """Handle PATCH /Bundles/{uuid}.""" ...

stack_v2_sparse_classes_36k

data/stack_v2_sparse_classes_30k

class BundlesSingleHandler: """BundlesSingleHandler handles object level routes for Bundles.""" async def get(self, bundle_id: str) -> None: """Handle GET /Bundles/{uuid}.""" query = {'uuid': bundle_id} projection = {'_id': False, 'files': False} logging.debug(f'MONGO-START: db....

the_stack_v2_python_sparse

lta/rest_server.py

blinkdog/lta

train

0