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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation.Hidden
class Hidden: """Class encapsulating a constraint not meant to be exposed to the user. Parameters ---------- constraint : str or _Constraint instance The constraint to be used internally. """ def __init__(self, constraint): self.constraint = constraint
class Hidden: '''Class encapsulating a constraint not meant to be exposed to the user. Parameters ---------- constraint : str or _Constraint instance The constraint to be used internally. ''' def __init__(self, constraint): pass
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sklearn.utils._param_validation.Interval
from numbers import Integral, Real import operator import numpy as np class Interval(_Constraint): """Constraint representing a typed interval. Parameters ---------- type : {numbers.Integral, numbers.Real, RealNotInt} The set of numbers in which to set the interval. If RealNotInt, onl...
class Interval(_Constraint): '''Constraint representing a typed interval. Parameters ---------- type : {numbers.Integral, numbers.Real, RealNotInt} The set of numbers in which to set the interval. If RealNotInt, only reals that don't have the integer type are allowed. For exampl...
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sklearn.utils._param_validation.InvalidParameterError
class InvalidParameterError(ValueError, TypeError): """Custom exception to be raised when the parameter of a class/method/function does not have a valid type or value. """
class InvalidParameterError(ValueError, TypeError): '''Custom exception to be raised when the parameter of a class/method/function does not have a valid type or value. ''' pass
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sklearn.utils._param_validation.MissingValues
from numbers import Integral, Real class MissingValues(_Constraint): """Helper constraint for the `missing_values` parameters. Convenience for [ Integral, Interval(Real, None, None, closed="both"), str, # when numeric_only is False None, # when numeric_only is False ...
class MissingValues(_Constraint): '''Helper constraint for the `missing_values` parameters. Convenience for [ Integral, Interval(Real, None, None, closed="both"), str, # when numeric_only is False None, # when numeric_only is False _NanConstraint(), _Panda...
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sklearn.utils._param_validation.Options
class Options(_Constraint): """Constraint representing a finite set of instances of a given type. Parameters ---------- type : type options : set The set of valid scalars. deprecated : set or None, default=None A subset of the `options` to mark as deprecated in the string ...
class Options(_Constraint): '''Constraint representing a finite set of instances of a given type. Parameters ---------- type : type options : set The set of valid scalars. deprecated : set or None, default=None A subset of the `options` to mark as deprecated in the string ...
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sklearn.utils._param_validation.RealNotInt
from numbers import Integral, Real class RealNotInt(Real): """A type that represents reals that are not instances of int. Behaves like float, but also works with values extracted from numpy arrays. isintance(1, RealNotInt) -> False isinstance(1.0, RealNotInt) -> True """
class RealNotInt(Real): '''A type that represents reals that are not instances of int. Behaves like float, but also works with values extracted from numpy arrays. isintance(1, RealNotInt) -> False isinstance(1.0, RealNotInt) -> True ''' pass
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sklearn.utils._param_validation.StrOptions
class StrOptions(Options): """Constraint representing a finite set of strings. Parameters ---------- options : set of str The set of valid strings. deprecated : set of str or None, default=None A subset of the `options` to mark as deprecated in the string representation of ...
class StrOptions(Options): '''Constraint representing a finite set of strings. Parameters ---------- options : set of str The set of valid strings. deprecated : set of str or None, default=None A subset of the `options` to mark as deprecated in the string representation of th...
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sklearn.utils._param_validation._ArrayLikes
from .validation import _is_arraylike_not_scalar class _ArrayLikes(_Constraint): """Constraint representing array-likes""" def is_satisfied_by(self, val): return _is_arraylike_not_scalar(val) def __str__(self): return 'an array-like'
class _ArrayLikes(_Constraint): '''Constraint representing array-likes''' def is_satisfied_by(self, val): pass def __str__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._Booleans
import numpy as np class _Booleans(_Constraint): """Constraint representing boolean likes. Convenience class for [bool, np.bool_] """ def __init__(self): super().__init__() self._constraints = [_InstancesOf(bool), _InstancesOf(np.bool_)] def is_satisfied_by(self, val): ...
class _Booleans(_Constraint): '''Constraint representing boolean likes. Convenience class for [bool, np.bool_] ''' def __init__(self): pass def is_satisfied_by(self, val): pass def __str__(self): pass
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sklearn.utils._param_validation._CVObjects
from numbers import Integral, Real class _CVObjects(_Constraint): """Constraint representing cv objects. Convenient class for [ Interval(Integral, 2, None, closed="left"), HasMethods(["split", "get_n_splits"]), _IterablesNotString(), None, ] """ def __init__(se...
class _CVObjects(_Constraint): '''Constraint representing cv objects. Convenient class for [ Interval(Integral, 2, None, closed="left"), HasMethods(["split", "get_n_splits"]), _IterablesNotString(), None, ] ''' def __init__(self): pass def is_satisf...
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sklearn.utils._param_validation._Callables
class _Callables(_Constraint): """Constraint representing callables.""" def is_satisfied_by(self, val): return callable(val) def __str__(self): return 'a callable'
class _Callables(_Constraint): '''Constraint representing callables.''' def is_satisfied_by(self, val): pass def __str__(self): pass
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sklearn.utils._param_validation._Constraint
from abc import ABC, abstractmethod class _Constraint(ABC): """Base class for the constraint objects.""" def __init__(self): self.hidden = False @abstractmethod def is_satisfied_by(self, val): """Whether or not a value satisfies the constraint. Parameters ---------- ...
class _Constraint(ABC): '''Base class for the constraint objects.''' def __init__(self): pass @abstractmethod def is_satisfied_by(self, val): '''Whether or not a value satisfies the constraint. Parameters ---------- val : object The value to check. ...
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._InstancesOf
class _InstancesOf(_Constraint): """Constraint representing instances of a given type. Parameters ---------- type : type The valid type. """ def __init__(self, type): super().__init__() self.type = type def is_satisfied_by(self, val): return isinstance(val,...
class _InstancesOf(_Constraint): '''Constraint representing instances of a given type. Parameters ---------- type : type The valid type. ''' def __init__(self, type): pass def is_satisfied_by(self, val): pass def __str__(self): pass
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sklearn.utils._param_validation._IterablesNotString
from collections.abc import Iterable class _IterablesNotString(_Constraint): """Constraint representing iterables that are not strings.""" def is_satisfied_by(self, val): return isinstance(val, Iterable) and (not isinstance(val, str)) def __str__(self): return 'an iterable'
class _IterablesNotString(_Constraint): '''Constraint representing iterables that are not strings.''' def is_satisfied_by(self, val): pass def __str__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._NanConstraint
from numbers import Integral, Real import math class _NanConstraint(_Constraint): """Constraint representing the indicator `np.nan`.""" def is_satisfied_by(self, val): return not isinstance(val, Integral) and isinstance(val, Real) and math.isnan(val) def __str__(self): return 'numpy.nan'
class _NanConstraint(_Constraint): '''Constraint representing the indicator `np.nan`.''' def is_satisfied_by(self, val): pass def __str__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._NoneConstraint
class _NoneConstraint(_Constraint): """Constraint representing the None singleton.""" def is_satisfied_by(self, val): return val is None def __str__(self): return 'None'
class _NoneConstraint(_Constraint): '''Constraint representing the None singleton.''' def is_satisfied_by(self, val): pass def __str__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._PandasNAConstraint
class _PandasNAConstraint(_Constraint): """Constraint representing the indicator `pd.NA`.""" def is_satisfied_by(self, val): try: import pandas as pd return isinstance(val, type(pd.NA)) and pd.isna(val) except ImportError: return False def __str__(self):...
class _PandasNAConstraint(_Constraint): '''Constraint representing the indicator `pd.NA`.''' def is_satisfied_by(self, val): pass def __str__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._RandomStates
import numpy as np from numbers import Integral, Real class _RandomStates(_Constraint): """Constraint representing random states. Convenience class for [Interval(Integral, 0, 2**32 - 1, closed="both"), np.random.RandomState, None] """ def __init__(self): super().__init__() self._c...
class _RandomStates(_Constraint): '''Constraint representing random states. Convenience class for [Interval(Integral, 0, 2**32 - 1, closed="both"), np.random.RandomState, None] ''' def __init__(self): pass def is_satisfied_by(self, val): pass def __str__(self): pa...
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._SparseMatrices
from scipy.sparse import csr_matrix, issparse class _SparseMatrices(_Constraint): """Constraint representing sparse matrices.""" def is_satisfied_by(self, val): return issparse(val) def __str__(self): return 'a sparse matrix'
class _SparseMatrices(_Constraint): '''Constraint representing sparse matrices.''' def is_satisfied_by(self, val): pass def __str__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._param_validation._VerboseHelper
from numbers import Integral, Real import numpy as np class _VerboseHelper(_Constraint): """Helper constraint for the verbose parameter. Convenience class for [Interval(Integral, 0, None, closed="left"), bool, numpy.bool_] """ def __init__(self): super().__init__() self._constrain...
class _VerboseHelper(_Constraint): '''Helper constraint for the verbose parameter. Convenience class for [Interval(Integral, 0, None, closed="left"), bool, numpy.bool_] ''' def __init__(self): pass def is_satisfied_by(self, val): pass def __str__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._plotting._BinaryClassifierCurveDisplayMixin
from ._optional_dependencies import check_matplotlib_support import warnings from .validation import _check_pos_label_consistency, _num_samples from collections.abc import Mapping from .multiclass import type_of_target from . import check_consistent_length from ._response import _get_response_values_binary class _Bina...
class _BinaryClassifierCurveDisplayMixin: '''Mixin class to be used in Displays requiring a binary classifier. The aim of this class is to centralize some validations regarding the estimator and the target and gather the response of the estimator. ''' def _validate_plot_params(self, *, ax=None, na...
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etsi-ai/etsi-watchdog
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sklearn.utils._pprint.KeyValTuple
class KeyValTuple(tuple): """Dummy class for correctly rendering key-value tuples from dicts.""" def __repr__(self): return super().__repr__()
class KeyValTuple(tuple): '''Dummy class for correctly rendering key-value tuples from dicts.''' def __repr__(self): pass
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etsi-ai/etsi-watchdog
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sklearn.utils._pprint.KeyValTupleParam
class KeyValTupleParam(KeyValTuple): """Dummy class for correctly rendering key-value tuples from parameters.""" pass
class KeyValTupleParam(KeyValTuple): '''Dummy class for correctly rendering key-value tuples from parameters.''' pass
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sklearn.utils._pprint._EstimatorPrettyPrinter
from .._config import get_config import pprint from ..base import BaseEstimator class _EstimatorPrettyPrinter(pprint.PrettyPrinter): """Pretty Printer class for estimator objects. This extends the pprint.PrettyPrinter class, because: - we need estimators to be printed with their parameters, e.g. Est...
class _EstimatorPrettyPrinter(pprint.PrettyPrinter): '''Pretty Printer class for estimator objects. This extends the pprint.PrettyPrinter class, because: - we need estimators to be printed with their parameters, e.g. Estimator(param1=value1, ...) which is not supported by default. - the 'compact'...
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/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_repr_html/base.py
sklearn.utils._repr_html.base.ReprHTMLMixin
from ..._config import get_config class ReprHTMLMixin: """Mixin to handle consistently the HTML representation. When inheriting from this class, you need to define an attribute `_html_repr` which is a callable that returns the HTML representation to be shown. """ @property def _repr_html_(sel...
class ReprHTMLMixin: '''Mixin to handle consistently the HTML representation. When inheriting from this class, you need to define an attribute `_html_repr` which is a callable that returns the HTML representation to be shown. ''' @property def _repr_html_(self): '''HTML representation o...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_repr_html/base.py
sklearn.utils._repr_html.base._HTMLDocumentationLinkMixin
import itertools from ..fixes import parse_version from ... import __version__ class _HTMLDocumentationLinkMixin: """Mixin class allowing to generate a link to the API documentation. This mixin relies on three attributes: - `_doc_link_module`: it corresponds to the root module (e.g. `sklearn`). Using this...
class _HTMLDocumentationLinkMixin: '''Mixin class allowing to generate a link to the API documentation. This mixin relies on three attributes: - `_doc_link_module`: it corresponds to the root module (e.g. `sklearn`). Using this mixin, the default value is `sklearn`. - `_doc_link_template`: it cor...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_repr_html/estimator.py
sklearn.utils._repr_html.estimator._IDCounter
class _IDCounter: """Generate sequential ids with a prefix.""" def __init__(self, prefix): self.prefix = prefix self.count = 0 def get_id(self): self.count += 1 return f'{self.prefix}-{self.count}'
class _IDCounter: '''Generate sequential ids with a prefix.''' def __init__(self, prefix): pass def get_id(self): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_repr_html/estimator.py
sklearn.utils._repr_html.estimator._VisualBlock
class _VisualBlock: """HTML Representation of Estimator Parameters ---------- kind : {'serial', 'parallel', 'single'} kind of HTML block estimators : list of estimators or `_VisualBlock`s or a single estimator If kind != 'single', then `estimators` is a list of estimators. ...
class _VisualBlock: '''HTML Representation of Estimator Parameters ---------- kind : {'serial', 'parallel', 'single'} kind of HTML block estimators : list of estimators or `_VisualBlock`s or a single estimator If kind != 'single', then `estimators` is a list of estimators. ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_repr_html/params.py
sklearn.utils._repr_html.params.ParamsDict
from collections import UserDict from sklearn.utils._repr_html.base import ReprHTMLMixin class ParamsDict(ReprHTMLMixin, UserDict): """Dictionary-like class to store and provide an HTML representation. It builds an HTML structure to be used with Jupyter notebooks or similar environments. It allows storing...
class ParamsDict(ReprHTMLMixin, UserDict): '''Dictionary-like class to store and provide an HTML representation. It builds an HTML structure to be used with Jupyter notebooks or similar environments. It allows storing metadata to track non-default parameters. Parameters ---------- params : dict...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_set_output.py
sklearn.utils._set_output.ContainerAdapterProtocol
from typing import Protocol, runtime_checkable @runtime_checkable class ContainerAdapterProtocol(Protocol): container_lib: str def create_container(self, X_output, X_original, columns, inplace=False): """Create container from `X_output` with additional metadata. Parameters ---------- ...
@runtime_checkable class ContainerAdapterProtocol(Protocol): def create_container(self, X_output, X_original, columns, inplace=False): '''Create container from `X_output` with additional metadata. Parameters ---------- X_output : {ndarray, dataframe} Data to wrap. ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_set_output.py
sklearn.utils._set_output.ContainerAdaptersManager
class ContainerAdaptersManager: def __init__(self): self.adapters = {} @property def supported_outputs(self): return {'default'} | set(self.adapters) def register(self, adapter): self.adapters[adapter.container_lib] = adapter
class ContainerAdaptersManager: def __init__(self): pass @property def supported_outputs(self): pass def register(self, adapter): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_set_output.py
sklearn.utils._set_output.PandasAdapter
class PandasAdapter: container_lib = 'pandas' def create_container(self, X_output, X_original, columns, inplace=True): pd = check_library_installed('pandas') columns = get_columns(columns) if not inplace or not isinstance(X_output, pd.DataFrame): if isinstance(X_output, pd.D...
class PandasAdapter: def create_container(self, X_output, X_original, columns, inplace=True): pass def is_supported_container(self, X): pass def rename_columns(self, X, columns): pass def hstack(self, Xs): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_set_output.py
sklearn.utils._set_output.PolarsAdapter
import numpy as np class PolarsAdapter: container_lib = 'polars' def create_container(self, X_output, X_original, columns, inplace=True): pl = check_library_installed('polars') columns = get_columns(columns) columns = columns.tolist() if isinstance(columns, np.ndarray) else columns ...
class PolarsAdapter: def create_container(self, X_output, X_original, columns, inplace=True): pass def is_supported_container(self, X): pass def rename_columns(self, X, columns): pass def hstack(self, Xs): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_set_output.py
sklearn.utils._set_output._SetOutputMixin
from ._available_if import available_if class _SetOutputMixin: """Mixin that dynamically wraps methods to return container based on config. Currently `_SetOutputMixin` wraps `transform` and `fit_transform` and configures it based on `set_output` of the global configuration. `set_output` is only defin...
class _SetOutputMixin: '''Mixin that dynamically wraps methods to return container based on config. Currently `_SetOutputMixin` wraps `transform` and `fit_transform` and configures it based on `set_output` of the global configuration. `set_output` is only defined if `get_feature_names_out` is defined a...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_tags.py
sklearn.utils._tags.ClassifierTags
from dataclasses import dataclass, field @dataclass(slots=True) class ClassifierTags: """Tags for the classifier. Parameters ---------- poor_score : bool, default=False Whether the estimator fails to provide a "reasonable" test-set score, which currently for classification is an accura...
@dataclass(slots=True) class ClassifierTags: '''Tags for the classifier. Parameters ---------- poor_score : bool, default=False Whether the estimator fails to provide a "reasonable" test-set score, which currently for classification is an accuracy of 0.83 on ``make_blobs(n_sample...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_tags.py
sklearn.utils._tags.InputTags
from dataclasses import dataclass, field @dataclass(slots=True) class InputTags: """Tags for the input data. Parameters ---------- one_d_array : bool, default=False Whether the input can be a 1D array. two_d_array : bool, default=True Whether the input can be a 2D array. Note that...
@dataclass(slots=True) class InputTags: '''Tags for the input data. Parameters ---------- one_d_array : bool, default=False Whether the input can be a 1D array. two_d_array : bool, default=True Whether the input can be a 2D array. Note that most common tests currently run onl...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_tags.py
sklearn.utils._tags.RegressorTags
from dataclasses import dataclass, field @dataclass(slots=True) class RegressorTags: """Tags for the regressor. Parameters ---------- poor_score : bool, default=False Whether the estimator fails to provide a "reasonable" test-set score, which currently for regression is an R2 of 0.5 on...
@dataclass(slots=True) class RegressorTags: '''Tags for the regressor. Parameters ---------- poor_score : bool, default=False Whether the estimator fails to provide a "reasonable" test-set score, which currently for regression is an R2 of 0.5 on ``make_regression(n_samples=200, n...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_tags.py
sklearn.utils._tags.Tags
from dataclasses import dataclass, field @dataclass(slots=True) class Tags: """Tags for the estimator. See :ref:`estimator_tags` for more information. Parameters ---------- estimator_type : str or None The type of the estimator. Can be one of: - "classifier" - "regressor" ...
@dataclass(slots=True) class Tags: '''Tags for the estimator. See :ref:`estimator_tags` for more information. Parameters ---------- estimator_type : str or None The type of the estimator. Can be one of: - "classifier" - "regressor" - "transformer" - "clusterer...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_tags.py
sklearn.utils._tags.TargetTags
from dataclasses import dataclass, field @dataclass(slots=True) class TargetTags: """Tags for the target data. Parameters ---------- required : bool Whether the estimator requires y to be passed to `fit`, `fit_predict` or `fit_transform` methods. The tag is ``True`` for estimat...
@dataclass(slots=True) class TargetTags: '''Tags for the target data. Parameters ---------- required : bool Whether the estimator requires y to be passed to `fit`, `fit_predict` or `fit_transform` methods. The tag is ``True`` for estimators inheriting from `~sklearn.base.Regresso...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_tags.py
sklearn.utils._tags.TransformerTags
from dataclasses import dataclass, field @dataclass(slots=True) class TransformerTags: """Tags for the transformer. Parameters ---------- preserves_dtype : list[str], default=["float64"] Applies only on transformers. It corresponds to the data types which will be preserved such that `X...
@dataclass(slots=True) class TransformerTags: '''Tags for the transformer. Parameters ---------- preserves_dtype : list[str], default=["float64"] Applies only on transformers. It corresponds to the data types which will be preserved such that `X_trans.dtype` is the same as `X.dty...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_testing.py
sklearn.utils._testing.MinimalClassifier
from sklearn.utils.validation import check_array, check_is_fitted, check_X_y import numpy as np from sklearn.utils import ClassifierTags, RegressorTags, Tags, TargetTags, TransformerTags from sklearn.utils.multiclass import check_classification_targets class MinimalClassifier: """Minimal classifier implementation ...
class MinimalClassifier: '''Minimal classifier implementation without inheriting from BaseEstimator. This estimator should be tested with: * `check_estimator` in `test_estimator_checks.py`; * within a `Pipeline` in `test_pipeline.py`; * within a `SearchCV` in `test_search.py`. ''' def __in...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_testing.py
sklearn.utils._testing.MinimalRegressor
from sklearn.utils import ClassifierTags, RegressorTags, Tags, TargetTags, TransformerTags from sklearn.utils.validation import check_array, check_is_fitted, check_X_y import numpy as np class MinimalRegressor: """Minimal regressor implementation without inheriting from BaseEstimator. This estimator should be...
class MinimalRegressor: '''Minimal regressor implementation without inheriting from BaseEstimator. This estimator should be tested with: * `check_estimator` in `test_estimator_checks.py`; * within a `Pipeline` in `test_pipeline.py`; * within a `SearchCV` in `test_search.py`. ''' def __init...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_testing.py
sklearn.utils._testing.MinimalTransformer
from sklearn.utils.validation import check_array, check_is_fitted, check_X_y from sklearn.utils import ClassifierTags, RegressorTags, Tags, TargetTags, TransformerTags class MinimalTransformer: """Minimal transformer implementation without inheriting from BaseEstimator. This estimator should be tested wit...
class MinimalTransformer: '''Minimal transformer implementation without inheriting from BaseEstimator. This estimator should be tested with: * `check_estimator` in `test_estimator_checks.py`; * within a `Pipeline` in `test_pipeline.py`; * within a `SearchCV` in `test_search.py`. ''' de...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_testing.py
sklearn.utils._testing.TempMemmap
class TempMemmap: """ Parameters ---------- data mmap_mode : str, default='r' """ def __init__(self, data, mmap_mode='r'): self.mmap_mode = mmap_mode self.data = data def __enter__(self): data_read_only, self.temp_folder = create_memmap_backed_data(self.data, mm...
class TempMemmap: ''' Parameters ---------- data mmap_mode : str, default='r' ''' def __init__(self, data, mmap_mode='r'): pass def __enter__(self): pass def __exit__(self, exc_type, exc_val, exc_tb): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_testing.py
sklearn.utils._testing._IgnoreWarnings
import warnings from functools import wraps import sys class _IgnoreWarnings: """Improved and simplified Python warnings context manager and decorator. This class allows the user to ignore the warnings raised by a function. Copied from Python 2.7.5 and modified as required. Parameters ---------- ...
class _IgnoreWarnings: '''Improved and simplified Python warnings context manager and decorator. This class allows the user to ignore the warnings raised by a function. Copied from Python 2.7.5 and modified as required. Parameters ---------- category : tuple of warning class, default=Warning ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/_testing.py
sklearn.utils._testing._Raises
from collections.abc import Iterable import contextlib import re class _Raises(contextlib.AbstractContextManager): def __init__(self, expected_exc_type, match, may_pass, err_msg): self.expected_exc_types = expected_exc_type if isinstance(expected_exc_type, Iterable) else [expected_exc_type] self.m...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/deprecation.py
sklearn.utils.deprecation.deprecated
import functools import warnings from inspect import signature class deprecated: """Decorator to mark a function or class as deprecated. Issue a warning when the function is called/the class is instantiated and adds a warning to the docstring. The optional extra argument will be appended to the depre...
class deprecated: '''Decorator to mark a function or class as deprecated. Issue a warning when the function is called/the class is instantiated and adds a warning to the docstring. The optional extra argument will be appended to the deprecation message and the docstring. Note: to use this with the ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/estimator_checks.py
sklearn.utils.estimator_checks._NotAnArray
import numpy as np class _NotAnArray: """An object that is convertible to an array. Parameters ---------- data : array-like The data. """ def __init__(self, data): self.data = np.asarray(data) def __array__(self, dtype=None, copy=None): return self.data def _...
class _NotAnArray: '''An object that is convertible to an array. Parameters ---------- data : array-like The data. ''' def __init__(self, data): pass def __array__(self, dtype=None, copy=None): pass def __array_function__(self, func, types, args, kwargs): ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/metaestimators.py
sklearn.utils.metaestimators._BaseComposition
from typing import Any, List from abc import ABCMeta, abstractmethod from contextlib import suppress from ..base import BaseEstimator class _BaseComposition(BaseEstimator, metaclass=ABCMeta): """Handles parameter management for classifiers composed of named estimators.""" steps: List[Any] @abstractmethod ...
class _BaseComposition(BaseEstimator, metaclass=ABCMeta): '''Handles parameter management for classifiers composed of named estimators.''' @abstractmethod def __init__(self): pass def _get_params(self, attr, deep=True): pass def _set_params(self, attr, **params): pass ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/optimize.py
sklearn.utils.optimize._LineSearchError
class _LineSearchError(RuntimeError): pass
class _LineSearchError(RuntimeError): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/parallel.py
sklearn.utils.parallel.Parallel
from .._config import config_context, get_config import joblib import warnings class Parallel(joblib.Parallel): """Tweak of :class:`joblib.Parallel` that propagates the scikit-learn configuration. This subclass of :class:`joblib.Parallel` ensures that the active configuration (thread-local) of scikit-lear...
class Parallel(joblib.Parallel): '''Tweak of :class:`joblib.Parallel` that propagates the scikit-learn configuration. This subclass of :class:`joblib.Parallel` ensures that the active configuration (thread-local) of scikit-learn is propagated to the parallel workers for the duration of the execution of...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/utils/parallel.py
sklearn.utils.parallel._FuncWrapper
from .._config import config_context, get_config import warnings from functools import update_wrapper class _FuncWrapper: """Load the global configuration before calling the function.""" def __init__(self, function): self.function = function update_wrapper(self, self.function) def with_co...
class _FuncWrapper: '''Load the global configuration before calling the function.''' def __init__(self, function): pass def with_config_and_warning_filters(self, config, warning_filters): pass def __call__(self, *args, **kwargs): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.BLISController
import ctypes class BLISController(LibController): """Controller class for BLIS""" user_api = 'blas' internal_api = 'blis' filename_prefixes = ('libblis', 'libblas') check_symbols = ('bli_thread_get_num_threads', 'bli_thread_set_num_threads', 'bli_info_get_version_str', 'bli_info_get_enable_openmp'...
class BLISController(LibController): '''Controller class for BLIS''' def set_additional_attributes(self): pass def get_num_threads(self): pass def set_num_threads(self, num_threads): pass def get_version(self): pass def _get_threading_layer(self): ''...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.FlexiBLASController
import ctypes class FlexiBLASController(LibController): """Controller class for FlexiBLAS""" user_api = 'blas' internal_api = 'flexiblas' filename_prefixes = ('libflexiblas',) check_symbols = ('flexiblas_get_num_threads', 'flexiblas_set_num_threads', 'flexiblas_get_version', 'flexiblas_list', 'flex...
class FlexiBLASController(LibController): '''Controller class for FlexiBLAS''' @property def loaded_backends(self): pass @property def current_backend(self): pass def info(self): '''Return relevant info wrapped in a dict''' pass def set_additional_attribute...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.LibController
import ctypes from typing import final from abc import ABC, abstractmethod class LibController(ABC): """Abstract base class for the individual library controllers A library controller must expose the following class attributes: - user_api : str Usually the name of the library or generic sp...
class LibController(ABC): '''Abstract base class for the individual library controllers A library controller must expose the following class attributes: - user_api : str Usually the name of the library or generic specification the library implements, e.g. "blas" is a specificati...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.MKLController
import ctypes import re class MKLController(LibController): """Controller class for MKL""" user_api = 'blas' internal_api = 'mkl' filename_prefixes = ('libmkl_rt', 'mkl_rt', 'libblas') check_symbols = ('MKL_Get_Max_Threads', 'MKL_Set_Num_Threads', 'MKL_Get_Version_String', 'MKL_Set_Threading_Layer'...
class MKLController(LibController): '''Controller class for MKL''' def set_additional_attributes(self): pass def get_num_threads(self): pass def set_num_threads(self, num_threads): pass def get_version(self): pass def _get_threading_layer(self): '''R...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.OpenBLASController
import ctypes import itertools class OpenBLASController(LibController): """Controller class for OpenBLAS""" user_api = 'blas' internal_api = 'openblas' filename_prefixes = ('libopenblas', 'libblas', 'libscipy_openblas') _symbol_prefixes = ('', 'scipy_') _symbol_suffixes = ('', '64_', '_64') ...
class OpenBLASController(LibController): '''Controller class for OpenBLAS''' def _find_affixes(self): pass def set_additional_attributes(self): pass def get_num_threads(self): pass def set_num_threads(self, num_threads): pass def get_version(self): p...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.OpenMPController
class OpenMPController(LibController): """Controller class for OpenMP""" user_api = 'openmp' internal_api = 'openmp' filename_prefixes = ('libiomp', 'libgomp', 'libomp', 'vcomp') check_symbols = ('omp_get_max_threads', 'omp_get_num_threads') def get_num_threads(self): get_func = getattr...
class OpenMPController(LibController): '''Controller class for OpenMP''' def get_num_threads(self): pass def set_num_threads(self, num_threads): pass def get_version(self): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.ThreadpoolController
import warnings import sys from ctypes.util import find_library import ctypes import textwrap import os class ThreadpoolController: """Collection of LibController objects for all loaded supported libraries Attributes ---------- lib_controllers : list of `LibController` objects The list of libr...
class ThreadpoolController: '''Collection of LibController objects for all loaded supported libraries Attributes ---------- lib_controllers : list of `LibController` objects The list of library controllers of all loaded supported libraries. ''' def __init__(self): pass @cla...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl._ThreadpoolLimiter
import warnings class _ThreadpoolLimiter: """The guts of ThreadpoolController.limit Refer to the docstring of ThreadpoolController.limit for more details. It will only act on the library controllers held by the provided `controller`. Using the default constructor sets the limits right away such that ...
class _ThreadpoolLimiter: '''The guts of ThreadpoolController.limit Refer to the docstring of ThreadpoolController.limit for more details. It will only act on the library controllers held by the provided `controller`. Using the default constructor sets the limits right away such that it can be used as ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl._ThreadpoolLimiterDecorator
from contextlib import ContextDecorator class _ThreadpoolLimiterDecorator(_ThreadpoolLimiter, ContextDecorator): """Same as _ThreadpoolLimiter but to be used as a decorator""" def __init__(self, controller, *, limits=None, user_api=None): self._limits, self._user_api, self._prefixes = self._check_para...
class _ThreadpoolLimiterDecorator(_ThreadpoolLimiter, ContextDecorator): '''Same as _ThreadpoolLimiter but to be used as a decorator''' def __init__(self, controller, *, limits=None, user_api=None): pass def __enter__(self): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl._dl_phdr_info
import ctypes class _dl_phdr_info(ctypes.Structure): _fields_ = [('dlpi_addr', _SYSTEM_UINT), ('dlpi_name', ctypes.c_char_p), ('dlpi_phdr', ctypes.c_void_p), ('dlpi_phnum', _SYSTEM_UINT_HALF)]
class _dl_phdr_info(ctypes.Structure): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/threadpoolctl.py
threadpoolctl.threadpool_limits
@_format_docstring(USER_APIS=', '.join((f'"{api}"' for api in _ALL_USER_APIS)), BLAS_LIBS=', '.join(_ALL_BLAS_LIBRARIES), OPENMP_LIBS=', '.join(_ALL_OPENMP_LIBRARIES)) class threadpool_limits(_ThreadpoolLimiter): """Change the maximal number of threads that can be used in thread pools. This object can be used ...
@_format_docstring(USER_APIS=', '.join((f'"{api}"' for api in _ALL_USER_APIS)), BLAS_LIBS=', '.join(_ALL_BLAS_LIBRARIES), OPENMP_LIBS=', '.join(_ALL_OPENMP_LIBRARIES)) class threadpool_limits(_ThreadpoolLimiter): '''Change the maximal number of threads that can be used in thread pools. This object can be used e...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/Monitor.py
watchdog.Monitor.Monitor
from .slack_notifier import SlackNotifier from .drift_check import DriftCheck from .logger import log_drift from typing import Optional, Dict, Any import pandas as pd class Monitor: """ Monitor — Periodic/rolling drift monitoring with Slack alert integration. Example: >>> monitor = Monitor(reference_d...
class Monitor: ''' Monitor — Periodic/rolling drift monitoring with Slack alert integration. Example: >>> monitor = Monitor(reference_df) >>> monitor.enable_logging("logs/drift.csv") >>> monitor.enable_slack_alerts() # Uses environment variables >>> monitor.watch(live_df) ''' def ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/compare.py
watchdog.compare.DriftComparator
class DriftComparator: """ DriftComparator — Compare drift scores between two DriftCheck results. Example: >>> comp = DriftComparator(results_v1, results_v2) >>> deltas = comp.diff() """ def __init__(self, results1, results2): self.results1 = results1 self.results2 = result...
class DriftComparator: ''' DriftComparator — Compare drift scores between two DriftCheck results. Example: >>> comp = DriftComparator(results_v1, results_v2) >>> deltas = comp.diff() ''' def __init__(self, results1, results2): pass def diff(self): pass def report(s...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/config.py
watchdog.config.WatchdogConfig
import os from typing import Optional, Dict, Any from .slack_notifier import SlackNotifier class WatchdogConfig: """ Configuration helper for ETSI Watchdog with Slack integration. This class provides easy configuration management for the watchdog system, including Slack notifications, logging, and mon...
class WatchdogConfig: ''' Configuration helper for ETSI Watchdog with Slack integration. This class provides easy configuration management for the watchdog system, including Slack notifications, logging, and monitoring parameters. Example: >>> config = WatchdogConfig() >>> config.setup_slac...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/drift/base.py
watchdog.drift.base.DriftResult
from dataclasses import dataclass, asdict import matplotlib.pyplot as plt import json @dataclass class DriftResult: method: str score: float threshold: float details: dict sample_size: int @property def is_drifted(self) -> bool: return self.score > self.threshold def summary(s...
@dataclass class DriftResult: @property def is_drifted(self) -> bool: pass def summary(self) -> str: pass def plot(self): pass def to_json(self, path=None): pass
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/drift/sklearn_wrapper.py
watchdog.drift.sklearn_wrapper.SklearnDriftDetector
from .base import DriftResult from .factory import get_drift_function import numpy as np import pandas as pd from typing import Union, Optional, Dict, Any class SklearnDriftDetector: """ Scikit-learn compatible wrapper for drift detection functions. This class provides a unified interface for all drift de...
class SklearnDriftDetector: ''' Scikit-learn compatible wrapper for drift detection functions. This class provides a unified interface for all drift detection methods in the package, making them compatible with Scikit-learn's API. ''' def __init__(self, method: str='psi', threshold: float=0.2,...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/hooks.py
watchdog.hooks.DriftHook
from typing import Callable, List class DriftHook: """ A simple hook system to attach actions when drift is detected or logs are generated. Example use cases: - Send Slack alerts - Push metadata to MLflow - Save HTML/Markdown reports """ def __init__(self): self._on_drift...
class DriftHook: ''' A simple hook system to attach actions when drift is detected or logs are generated. Example use cases: - Send Slack alerts - Push metadata to MLflow - Save HTML/Markdown reports ''' def __init__(self): pass def register_on_drift(self, func: Call...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/monitor.py
watchdog.monitor.Monitor
import pandas as pd from .drift_check import DriftCheck from .logger import log_drift from .slack_notifier import SlackNotifier from typing import Optional, Dict, Any class Monitor: """ Monitor — Periodic/rolling drift monitoring with Slack alert integration. Example: >>> monitor = Monitor(reference_d...
class Monitor: ''' Monitor — Periodic/rolling drift monitoring with Slack alert integration. Example: >>> monitor = Monitor(reference_df) >>> monitor.enable_logging("logs/drift.csv") >>> monitor.enable_slack_alerts() # Uses environment variables >>> monitor.watch(live_df) ''' def ...
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etsi-ai/etsi-watchdog
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/etsi/watchdog/slack_notifier.py
watchdog.slack_notifier.SlackNotifier
from .drift.base import DriftResult from datetime import datetime import os from typing import Optional, Dict, Any from slack_sdk.errors import SlackApiError from slack_sdk import WebClient class SlackNotifier: """ SlackNotifier — Send drift detection alerts to Slack channels. This class handles sending n...
class SlackNotifier: ''' SlackNotifier — Send drift detection alerts to Slack channels. This class handles sending notifications to Slack when drift is detected or critical events occur in the watchdog monitoring system. Environment Variables: - SLACK_BOT_TOKEN: The Slack bot token for authenti...
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cbcoutinho/nextcloud-mcp-server
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/cbcoutinho_nextcloud-mcp-server/nextcloud_mcp_server/app.py
nextcloud_mcp_server.app.AppContext
from nextcloud_mcp_server.client import NextcloudClient from dataclasses import dataclass @dataclass class AppContext: client: NextcloudClient
@dataclass class AppContext: pass
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cbcoutinho/nextcloud-mcp-server
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/cbcoutinho_nextcloud-mcp-server/nextcloud_mcp_server/client/__init__.py
nextcloud_mcp_server.client.AsyncDisableCookieTransport
from httpx import AsyncClient, Auth, BasicAuth, Request, Response, AsyncBaseTransport, AsyncHTTPTransport class AsyncDisableCookieTransport(AsyncBaseTransport): """This Transport disable cookies from accumulating in the httpx AsyncClient Thanks to: https://github.com/encode/httpx/issues/2992#issuecomment-2133...
class AsyncDisableCookieTransport(AsyncBaseTransport): '''This Transport disable cookies from accumulating in the httpx AsyncClient Thanks to: https://github.com/encode/httpx/issues/2992#issuecomment-2133258994 ''' def __init__(self, transport: AsyncBaseTransport): pass async def handle_a...
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cbcoutinho/nextcloud-mcp-server
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/cbcoutinho_nextcloud-mcp-server/nextcloud_mcp_server/client/__init__.py
nextcloud_mcp_server.client.NextcloudClient
from .contacts import ContactsClient from ..controllers.notes_search import NotesSearchController from .notes import NotesClient from .webdav import WebDAVClient from .tables import TablesClient import os from httpx import AsyncClient, Auth, BasicAuth, Request, Response, AsyncBaseTransport, AsyncHTTPTransport from .cal...
class NextcloudClient: '''Main Nextcloud client that orchestrates all app clients.''' def __init__(self, base_url: str, username: str, auth: Auth | None=None): pass @classmethod def from_env(cls): pass async def capabilities(self): pass async def notes_search_notes(se...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.client.base.BaseNextcloudClient
from httpx import HTTPStatusError, codes, RequestError, AsyncClient from abc import ABC class BaseNextcloudClient(ABC): """Base class for all Nextcloud app clients.""" def __init__(self, http_client: AsyncClient, username: str): """Initialize with shared HTTP client and username. Args: ...
class BaseNextcloudClient(ABC): '''Base class for all Nextcloud app clients.''' def __init__(self, http_client: AsyncClient, username: str): '''Initialize with shared HTTP client and username. Args: http_client: Authenticated AsyncClient instance username: Nextcloud use...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.client.calendar.CalendarClient
import xml.etree.ElementTree as ET from httpx import HTTPStatusError from icalendar import Event as ICalEvent import uuid from typing import Any, Dict, List, Optional, Tuple from icalendar import vRecur import datetime as dt from .base import BaseNextcloudClient from icalendar import Alarm, Calendar class CalendarClie...
class CalendarClient(BaseNextcloudClient): '''Client for NextCloud CalDAV calendar operations.''' def _get_caldav_base_path(self) -> str: '''Helper to get the base CalDAV path for calendars.''' pass def _get_principals_path(self) -> str: '''Helper to get the principals path for th...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.client.contacts.ContactsClient
from pythonvCard4.vcard import Contact from .base import BaseNextcloudClient import xml.etree.ElementTree as ET class ContactsClient(BaseNextcloudClient): """Client for NextCloud CardDAV contact operations.""" def _get_carddav_base_path(self) -> str: """Helper to get the base CardDAV path for contacts...
class ContactsClient(BaseNextcloudClient): '''Client for NextCloud CardDAV contact operations.''' def _get_carddav_base_path(self) -> str: '''Helper to get the base CardDAV path for contacts.''' pass async def list_addressbooks(self): '''List all available addressbooks for the use...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.client.notes.NotesClient
from typing import Any, Dict, List, Optional from .base import BaseNextcloudClient class NotesClient(BaseNextcloudClient): """Client for Nextcloud Notes app operations.""" async def get_settings(self) -> Dict[str, Any]: """Get Notes app settings.""" response = await self._make_request('GET', '...
class NotesClient(BaseNextcloudClient): '''Client for Nextcloud Notes app operations.''' async def get_settings(self) -> Dict[str, Any]: '''Get Notes app settings.''' pass async def get_all_notes(self) -> List[Dict[str, Any]]: '''Get all notes.''' pass async def get_note(self, note_i...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.client.tables.TablesClient
from .base import BaseNextcloudClient from typing import Any, Dict, List, Optional class TablesClient(BaseNextcloudClient): """Client for Nextcloud Tables app operations.""" async def list_tables(self) -> List[Dict[str, Any]]: """List all tables available to the user.""" response = await self....
class TablesClient(BaseNextcloudClient): '''Client for Nextcloud Tables app operations.''' async def list_tables(self) -> List[Dict[str, Any]]: '''List all tables available to the user.''' pass async def get_table_schema(self, table_id: int) -> Dict[str, Any]: '''Get the schema/structure of a...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.client.webdav.WebDAVClient
from .base import BaseNextcloudClient import mimetypes from httpx import HTTPStatusError from typing import Any, Dict, List, Optional, Tuple import xml.etree.ElementTree as ET class WebDAVClient(BaseNextcloudClient): """Client for Nextcloud WebDAV operations.""" async def delete_resource(self, path: str) -> D...
class WebDAVClient(BaseNextcloudClient): '''Client for Nextcloud WebDAV operations.''' async def delete_resource(self, path: str) -> Dict[str, Any]: '''Delete a resource (file or directory) via WebDAV DELETE.''' pass async def cleanup_old_attachment_directory(self, note_id: int, old_category: str...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.controllers.notes_search.NotesSearchController
from typing import Any, Dict, List class NotesSearchController: """Handles notes search logic and scoring.""" def search_notes(self, notes: List[Dict[str, Any]], query: str) -> List[Dict[str, Any]]: """ Search notes using token-based matching with relevance ranking. Returns notes sorte...
class NotesSearchController: '''Handles notes search logic and scoring.''' def search_notes(self, notes: List[Dict[str, Any]], query: str) -> List[Dict[str, Any]]: ''' Search notes using token-based matching with relevance ranking. Returns notes sorted by relevance score. ''' ...
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.base.BaseResponse
from pydantic import BaseModel, Field, field_serializer from datetime import datetime, timezone class BaseResponse(BaseModel): """Base response model for all MCP tool responses.""" success: bool = Field(default=True, description='Whether the operation was successful') timestamp: datetime = Field(default_fa...
class BaseResponse(BaseModel): '''Base response model for all MCP tool responses.''' @field_serializer('timestamp') def serialize_timestamp(self, timestamp: datetime) -> str: '''Serialize timestamp to RFC3339 format for MCP compliance.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.base.IdResponse
from typing import Optional, Union from pydantic import BaseModel, Field, field_serializer class IdResponse(BaseResponse): """Response model for operations that return a new ID.""" id: Union[int, str] = Field(description='ID of the created or affected resource')
class IdResponse(BaseResponse): '''Response model for operations that return a new ID.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.base.StatusResponse
from pydantic import BaseModel, Field, field_serializer from typing import Optional, Union class StatusResponse(BaseResponse): """Response model for operations that return just a status.""" status_code: Optional[int] = Field(None, description='HTTP status code') message: Optional[str] = Field(None, descrip...
class StatusResponse(BaseResponse): '''Response model for operations that return just a status.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.AvailabilitySlot
from pydantic import BaseModel, Field class AvailabilitySlot(BaseModel): """Model for an available time slot.""" start: str = Field(description='Slot start datetime (ISO format)') end: str = Field(description='Slot end datetime (ISO format)') duration_minutes: int = Field(description='Slot duration in ...
class AvailabilitySlot(BaseModel): '''Model for an available time slot.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.BulkOperationResponse
from pydantic import BaseModel, Field from .base import BaseResponse, StatusResponse class BulkOperationResponse(BaseResponse): """Response model for bulk operations.""" result: BulkOperationResult = Field(description='Bulk operation result')
class BulkOperationResponse(BaseResponse): '''Response model for bulk operations.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.BulkOperationResult
from typing import List, Optional from pydantic import BaseModel, Field class BulkOperationResult(BaseModel): """Model for bulk operation results.""" operation: str = Field(description='Operation performed (update, delete, move)') events_processed: int = Field(description='Number of events processed') ...
class BulkOperationResult(BaseModel): '''Model for bulk operation results.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.Calendar
from typing import List, Optional from pydantic import BaseModel, Field class Calendar(BaseModel): """Model for a Nextcloud calendar.""" name: str = Field(description='Calendar name/ID') display_name: str = Field(description='Calendar display name') description: Optional[str] = Field(None, description=...
class Calendar(BaseModel): '''Model for a Nextcloud calendar.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.CalendarEvent
from pydantic import BaseModel, Field from typing import List, Optional class CalendarEvent(CalendarEventSummary): """Model for a complete calendar event.""" created: Optional[str] = Field(None, description='Event creation datetime') last_modified: Optional[str] = Field(None, description='Last modification...
class CalendarEvent(CalendarEventSummary): '''Model for a complete calendar event.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.CalendarEventSummary
from typing import List, Optional from pydantic import BaseModel, Field class CalendarEventSummary(BaseModel): """Model for calendar event summary (for lists).""" uid: str = Field(description='Event UID') summary: str = Field(description='Event summary/title') start: str = Field(description='Event star...
class CalendarEventSummary(BaseModel): '''Model for calendar event summary (for lists).''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.CreateEventResponse
from pydantic import BaseModel, Field from .base import BaseResponse, StatusResponse class CreateEventResponse(BaseResponse): """Response model for event creation.""" event: CalendarEvent = Field(description='The created event') calendar_name: str = Field(description='Name of the calendar the event was cre...
class CreateEventResponse(BaseResponse): '''Response model for event creation.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.CreateMeetingResponse
class CreateMeetingResponse(CreateEventResponse): """Response model for meeting creation (same as event creation).""" pass
class CreateMeetingResponse(CreateEventResponse): '''Response model for meeting creation (same as event creation).''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.DeleteEventResponse
from .base import BaseResponse, StatusResponse from pydantic import BaseModel, Field class DeleteEventResponse(StatusResponse): """Response model for event deletion.""" deleted_uid: str = Field(description='UID of the deleted event') calendar_name: str = Field(description='Name of the calendar the event wa...
class DeleteEventResponse(StatusResponse): '''Response model for event deletion.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.FindAvailabilityResponse
from pydantic import BaseModel, Field from .base import BaseResponse, StatusResponse from typing import List, Optional class FindAvailabilityResponse(BaseResponse): """Response model for finding availability.""" available_slots: List[AvailabilitySlot] = Field(description='List of available time slots') dur...
class FindAvailabilityResponse(BaseResponse): '''Response model for finding availability.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.ListCalendarsResponse
from .base import BaseResponse, StatusResponse from typing import List, Optional from pydantic import BaseModel, Field class ListCalendarsResponse(BaseResponse): """Response model for listing calendars.""" calendars: List[Calendar] = Field(description='List of available calendars') total_count: int = Field...
class ListCalendarsResponse(BaseResponse): '''Response model for listing calendars.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.ListEventsResponse
from .base import BaseResponse, StatusResponse from pydantic import BaseModel, Field from typing import List, Optional class ListEventsResponse(BaseResponse): """Response model for listing events.""" events: List[CalendarEventSummary] = Field(description='List of events') calendar_name: Optional[str] = Fie...
class ListEventsResponse(BaseResponse): '''Response model for listing events.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.ManageCalendarResponse
from pydantic import BaseModel, Field from typing import List, Optional from .base import BaseResponse, StatusResponse class ManageCalendarResponse(BaseResponse): """Response model for calendar management operations.""" action: str = Field(description='Action performed (create, delete, update, list)') cale...
class ManageCalendarResponse(BaseResponse): '''Response model for calendar management operations.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.UpcomingEventsResponse
from typing import List, Optional from pydantic import BaseModel, Field from .base import BaseResponse, StatusResponse class UpcomingEventsResponse(BaseResponse): """Response model for upcoming events.""" events: List[CalendarEventSummary] = Field(description='List of upcoming events') days_ahead: int = Fi...
class UpcomingEventsResponse(BaseResponse): '''Response model for upcoming events.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.calendar.UpdateEventResponse
from .base import BaseResponse, StatusResponse from pydantic import BaseModel, Field class UpdateEventResponse(BaseResponse): """Response model for event updates.""" event: CalendarEvent = Field(description='The updated event') calendar_name: str = Field(description='Name of the calendar the event belongs ...
class UpdateEventResponse(BaseResponse): '''Response model for event updates.''' pass
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cbcoutinho/nextcloud-mcp-server
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nextcloud_mcp_server.models.contacts.AddressBook
from pydantic import BaseModel, Field from typing import Any, Dict, List, Optional class AddressBook(BaseModel): """Model for a Nextcloud address book.""" uri: str = Field(description='Address book URI') displayname: str = Field(description='Address book display name') description: Optional[str] = Fiel...
class AddressBook(BaseModel): '''Model for a Nextcloud address book.''' pass
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