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14,924 | ipyleaflet.leaflet | SearchControl | SearchControl class, with Control as parent class.
Attributes
----------
url: string, default ""
The url used for the search queries.
layer: default None
The LayerGroup used for search queries.
zoom: int, default None
The zoom level after moving to searched location, by default zoom level will not change.
marker: default Marker()
The marker used by the control.
found_style: default {‘fillColor’: ‘#3f0’, ‘color’: ‘#0f0’}
Style for searched feature when searching in LayerGroup.
| class SearchControl(Control):
"""SearchControl class, with Control as parent class.
Attributes
----------
url: string, default ""
The url used for the search queries.
layer: default None
The LayerGroup used for search queries.
zoom: int, default None
The zoom level after moving to searched location, by default zoom level will not change.
marker: default Marker()
The marker used by the control.
found_style: default {‘fillColor’: ‘#3f0’, ‘color’: ‘#0f0’}
Style for searched feature when searching in LayerGroup.
"""
_view_name = Unicode("LeafletSearchControlView").tag(sync=True)
_model_name = Unicode("LeafletSearchControlModel").tag(sync=True)
url = Unicode().tag(sync=True, o=True)
zoom = Int(default_value=None, allow_none=True).tag(sync=True, o=True)
property_name = Unicode("display_name").tag(sync=True, o=True)
property_loc = List(["lat", "lon"]).tag(sync=True, o=True)
jsonp_param = Unicode("json_callback").tag(sync=True, o=True)
auto_type = Bool(False).tag(sync=True, o=True)
auto_collapse = Bool(False).tag(sync=True, o=True)
animate_location = Bool(False).tag(sync=True, o=True)
found_style = Dict(default_value={"fillColor": "#3f0", "color": "#0f0"}).tag(
sync=True, o=True
)
marker = Instance(Marker, allow_none=True, default_value=None).tag(
sync=True, **widget_serialization
)
layer = Instance(LayerGroup, allow_none=True, default_value=None).tag(
sync=True, **widget_serialization
)
_location_found_callbacks = Instance(CallbackDispatcher, ())
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.on_msg(self._handle_leaflet_event)
def _handle_leaflet_event(self, _, content, buffers):
if content.get("event", "") == "locationfound":
self._location_found_callbacks(**content)
def on_feature_found(self, callback, remove=False):
"""Add a found feature event listener for searching in GeoJSON layer.
Parameters
----------
callback : callable
Callback function that will be called on found event when searching in GeoJSON layer.
remove: boolean
Whether to remove this callback or not. Defaults to False.
"""
self._location_found_callbacks.register_callback(callback, remove=remove)
def on_location_found(self, callback, remove=False):
"""Add a found location event listener. The callback will be called when a search result has been found.
Parameters
----------
callback : callable
Callback function that will be called on location found event.
remove: boolean
Whether to remove this callback or not. Defaults to False.
"""
self._location_found_callbacks.register_callback(callback, remove=remove)
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14,929 | ipyleaflet.leaflet | __init__ | null | def __init__(self, **kwargs):
super().__init__(**kwargs)
self.on_msg(self._handle_leaflet_event)
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14,940 | ipyleaflet.leaflet | _handle_leaflet_event | null | def _handle_leaflet_event(self, _, content, buffers):
if content.get("event", "") == "locationfound":
self._location_found_callbacks(**content)
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14,965 | ipyleaflet.leaflet | on_feature_found | Add a found feature event listener for searching in GeoJSON layer.
Parameters
----------
callback : callable
Callback function that will be called on found event when searching in GeoJSON layer.
remove: boolean
Whether to remove this callback or not. Defaults to False.
| def on_feature_found(self, callback, remove=False):
"""Add a found feature event listener for searching in GeoJSON layer.
Parameters
----------
callback : callable
Callback function that will be called on found event when searching in GeoJSON layer.
remove: boolean
Whether to remove this callback or not. Defaults to False.
"""
self._location_found_callbacks.register_callback(callback, remove=remove)
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14,966 | ipyleaflet.leaflet | on_location_found | Add a found location event listener. The callback will be called when a search result has been found.
Parameters
----------
callback : callable
Callback function that will be called on location found event.
remove: boolean
Whether to remove this callback or not. Defaults to False.
| def on_location_found(self, callback, remove=False):
"""Add a found location event listener. The callback will be called when a search result has been found.
Parameters
----------
callback : callable
Callback function that will be called on location found event.
remove: boolean
Whether to remove this callback or not. Defaults to False.
"""
self._location_found_callbacks.register_callback(callback, remove=remove)
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14,984 | ipyleaflet.leaflet | SplitMapControl | SplitMapControl class, with Control as parent class.
A control which allows comparing layers by splitting the map in two.
Attributes
----------
left_layer: Layer or list of Layers
The left layer(s) for comparison.
right_layer: Layer or list of Layers
The right layer(s) for comparison.
| class SplitMapControl(Control):
"""SplitMapControl class, with Control as parent class.
A control which allows comparing layers by splitting the map in two.
Attributes
----------
left_layer: Layer or list of Layers
The left layer(s) for comparison.
right_layer: Layer or list of Layers
The right layer(s) for comparison.
"""
_view_name = Unicode("LeafletSplitMapControlView").tag(sync=True)
_model_name = Unicode("LeafletSplitMapControlModel").tag(sync=True)
left_layer = Union((Instance(Layer), List(Instance(Layer)))).tag(
sync=True, **widget_serialization
)
right_layer = Union((Instance(Layer), List(Instance(Layer)))).tag(
sync=True, **widget_serialization
)
@default("left_layer")
def _default_left_layer(self):
# TODO: Shouldn't this be None?
return TileLayer()
@default("right_layer")
def _default_right_layer(self):
# TODO: Shouldn't this be None?
return TileLayer()
def __init__(self, **kwargs):
super(SplitMapControl, self).__init__(**kwargs)
self.on_msg(self._handle_leaflet_event)
def _handle_leaflet_event(self, _, content, buffers):
if content.get("event", "") == "dividermove":
event = content.get("event")
# TODO: Add x trait?
self.x = event.x
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14,989 | ipyleaflet.leaflet | __init__ | null | def __init__(self, **kwargs):
super(SplitMapControl, self).__init__(**kwargs)
self.on_msg(self._handle_leaflet_event)
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15,000 | ipyleaflet.leaflet | _handle_leaflet_event | null | def _handle_leaflet_event(self, _, content, buffers):
if content.get("event", "") == "dividermove":
event = content.get("event")
# TODO: Add x trait?
self.x = event.x
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15,042 | ipywidgets.widgets.widget_style | Style | Style specification | class Style(Widget):
"""Style specification"""
_model_name = Unicode('StyleModel').tag(sync=True)
_view_name = Unicode('StyleView').tag(sync=True)
_view_module = Unicode('@jupyter-widgets/base').tag(sync=True)
_view_module_version = Unicode(__jupyter_widgets_base_version__).tag(sync=True)
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15,099 | ipyleaflet.leaflet | TileLayer | TileLayer class.
Tile service layer.
Attributes
----------
url: string, default "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png"
Url to the tiles service.
min_zoom: int, default 0
The minimum zoom level down to which this layer will be displayed (inclusive).
max_zoom: int, default 18
The maximum zoom level up to which this layer will be displayed (inclusive).
min_native_zoom: int, default None
Minimum zoom number the tile source has available. If it is specified, the tiles on all zoom levels lower than min_native_zoom will be loaded from min_native_zoom level and auto-scaled.
max_native_zoom: int, default None
Maximum zoom number the tile source has available. If it is specified, the tiles on all zoom levels higher than max_native_zoom will be loaded from max_native_zoom level and auto-scaled.
bounds: list or None, default None
List of SW and NE location tuples. e.g. [(50, 75), (75, 120)].
tile_size: int, default 256
Tile sizes for this tile service.
attribution: string, default None.
Tiles service attribution.
no_wrap: boolean, default False
Whether the layer is wrapped around the antimeridian.
tms: boolean, default False
If true, inverses Y axis numbering for tiles (turn this on for TMS services).
zoom_offset: int, default 0
The zoom number used in tile URLs will be offset with this value.
show_loading: boolean, default False
Whether to show a spinner when tiles are loading.
loading: boolean, default False (dynamically updated)
Whether the tiles are currently loading.
detect_retina: boolean, default False
opacity: float, default 1.0
visible: boolean, default True
| class TileLayer(RasterLayer):
"""TileLayer class.
Tile service layer.
Attributes
----------
url: string, default "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png"
Url to the tiles service.
min_zoom: int, default 0
The minimum zoom level down to which this layer will be displayed (inclusive).
max_zoom: int, default 18
The maximum zoom level up to which this layer will be displayed (inclusive).
min_native_zoom: int, default None
Minimum zoom number the tile source has available. If it is specified, the tiles on all zoom levels lower than min_native_zoom will be loaded from min_native_zoom level and auto-scaled.
max_native_zoom: int, default None
Maximum zoom number the tile source has available. If it is specified, the tiles on all zoom levels higher than max_native_zoom will be loaded from max_native_zoom level and auto-scaled.
bounds: list or None, default None
List of SW and NE location tuples. e.g. [(50, 75), (75, 120)].
tile_size: int, default 256
Tile sizes for this tile service.
attribution: string, default None.
Tiles service attribution.
no_wrap: boolean, default False
Whether the layer is wrapped around the antimeridian.
tms: boolean, default False
If true, inverses Y axis numbering for tiles (turn this on for TMS services).
zoom_offset: int, default 0
The zoom number used in tile URLs will be offset with this value.
show_loading: boolean, default False
Whether to show a spinner when tiles are loading.
loading: boolean, default False (dynamically updated)
Whether the tiles are currently loading.
detect_retina: boolean, default False
opacity: float, default 1.0
visible: boolean, default True
"""
_view_name = Unicode("LeafletTileLayerView").tag(sync=True)
_model_name = Unicode("LeafletTileLayerModel").tag(sync=True)
bottom = Bool(True).tag(sync=True)
url = Unicode("https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png").tag(sync=True)
min_zoom = Int(0).tag(sync=True, o=True)
max_zoom = Int(18).tag(sync=True, o=True)
min_native_zoom = Int(default_value=None, allow_none=True).tag(sync=True, o=True)
max_native_zoom = Int(default_value=None, allow_none=True).tag(sync=True, o=True)
bounds = List(
default_value=None, allow_none=True, help="list of SW and NE location tuples"
).tag(sync=True, o=True)
tile_size = Int(256).tag(sync=True, o=True)
attribution = Unicode(default_value=None, allow_none=True).tag(sync=True, o=True)
detect_retina = Bool(False).tag(sync=True, o=True)
no_wrap = Bool(False).tag(sync=True, o=True)
tms = Bool(False).tag(sync=True, o=True)
zoom_offset = Int(0).tag(sync=True, o=True)
show_loading = Bool(False).tag(sync=True)
loading = Bool(False, read_only=True).tag(sync=True)
_load_callbacks = Instance(CallbackDispatcher, ())
def __init__(self, **kwargs):
super(TileLayer, self).__init__(**kwargs)
self.on_msg(self._handle_leaflet_event)
def _handle_leaflet_event(self, _, content, buffers):
if content.get("event", "") == "load":
self._load_callbacks(**content)
def on_load(self, callback, remove=False):
"""Add a load event listener.
Parameters
----------
callback : callable
Callback function that will be called when the tiles have finished loading.
remove: boolean
Whether to remove this callback or not. Defaults to False.
"""
self._load_callbacks.register_callback(callback, remove=remove)
def redraw(self):
"""Force redrawing the tiles.
This is especially useful when you are sure the server updated the tiles and you
need to refresh the layer.
"""
self.send({"msg": "redraw"})
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15,167 | traitlets.traitlets | TraitError | null | class TraitError(Exception):
pass
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15,168 | traitlets.traitlets | Tuple | An instance of a Python tuple. | class Tuple(Container[t.Tuple[t.Any, ...]]):
"""An instance of a Python tuple."""
klass = tuple
_cast_types = (list,)
def __init__(self, *traits: t.Any, **kwargs: t.Any) -> None:
"""Create a tuple from a list, set, or tuple.
Create a fixed-type tuple with Traits:
``t = Tuple(Int(), Str(), CStr())``
would be length 3, with Int,Str,CStr for each element.
If only one arg is given and it is not a Trait, it is taken as
default_value:
``t = Tuple((1, 2, 3))``
Otherwise, ``default_value`` *must* be specified by keyword.
Parameters
----------
*traits : TraitTypes [ optional ]
the types for restricting the contents of the Tuple. If unspecified,
types are not checked. If specified, then each positional argument
corresponds to an element of the tuple. Tuples defined with traits
are of fixed length.
default_value : SequenceType [ optional ]
The default value for the Tuple. Must be list/tuple/set, and
will be cast to a tuple. If ``traits`` are specified,
``default_value`` must conform to the shape and type they specify.
**kwargs
Other kwargs passed to `Container`
"""
default_value = kwargs.pop("default_value", Undefined)
# allow Tuple((values,)):
if len(traits) == 1 and default_value is Undefined and not is_trait(traits[0]):
default_value = traits[0]
traits = ()
if default_value is None and not kwargs.get("allow_none", False):
# improve backward-compatibility for possible subclasses
# specifying default_value=None as default,
# keeping 'unspecified' behavior (i.e. empty container)
warn(
f"Specifying {self.__class__.__name__}(default_value=None)"
" for no default is deprecated in traitlets 5.0.5."
" Use default_value=Undefined",
DeprecationWarning,
stacklevel=2,
)
default_value = Undefined
if default_value is Undefined:
args: t.Any = ()
elif default_value is None:
# default_value back on kwargs for super() to handle
args = ()
kwargs["default_value"] = None
elif isinstance(default_value, self._valid_defaults):
args = (default_value,)
else:
raise TypeError(f"default value of {self.__class__.__name__} was {default_value}")
self._traits = []
for trait in traits:
if isinstance(trait, type):
warn(
"Traits should be given as instances, not types (for example, `Int()`, not `Int`)"
" Passing types is deprecated in traitlets 4.1.",
DeprecationWarning,
stacklevel=2,
)
trait = trait()
self._traits.append(trait)
if self._traits and (default_value is None or default_value is Undefined):
# don't allow default to be an empty container if length is specified
args = None
super(Container, self).__init__(klass=self.klass, args=args, **kwargs)
def item_from_string(self, s: str, index: int) -> t.Any: # type:ignore[override]
"""Cast a single item from a string
Evaluated when parsing CLI configuration from a string
"""
if not self._traits or index >= len(self._traits):
# return s instead of raising index error
# length errors will be raised later on validation
return s
return self._traits[index].from_string(s)
def validate_elements(self, obj: t.Any, value: t.Any) -> t.Any:
if not self._traits:
# nothing to validate
return value
if len(value) != len(self._traits):
e = (
"The '%s' trait of %s instance requires %i elements, but a value of %s was specified."
% (self.name, class_of(obj), len(self._traits), repr_type(value))
)
raise TraitError(e)
validated = []
for trait, v in zip(self._traits, value):
try:
v = trait._validate(obj, v)
except TraitError as error:
self.error(obj, v, error)
else:
validated.append(v)
return tuple(validated)
def class_init(self, cls: type[t.Any], name: str | None) -> None:
for trait in self._traits:
if isinstance(trait, TraitType):
trait.class_init(cls, None)
super(Container, self).class_init(cls, name)
def subclass_init(self, cls: type[t.Any]) -> None:
for trait in self._traits:
if isinstance(trait, TraitType):
trait.subclass_init(cls)
# explicitly not calling super().subclass_init(cls)
# to opt out of instance_init
| (*traits: 't.Any', **kwargs: 't.Any') -> 'None' | [
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] |
15,170 | traitlets.traitlets | __init__ | Create a tuple from a list, set, or tuple.
Create a fixed-type tuple with Traits:
``t = Tuple(Int(), Str(), CStr())``
would be length 3, with Int,Str,CStr for each element.
If only one arg is given and it is not a Trait, it is taken as
default_value:
``t = Tuple((1, 2, 3))``
Otherwise, ``default_value`` *must* be specified by keyword.
Parameters
----------
*traits : TraitTypes [ optional ]
the types for restricting the contents of the Tuple. If unspecified,
types are not checked. If specified, then each positional argument
corresponds to an element of the tuple. Tuples defined with traits
are of fixed length.
default_value : SequenceType [ optional ]
The default value for the Tuple. Must be list/tuple/set, and
will be cast to a tuple. If ``traits`` are specified,
``default_value`` must conform to the shape and type they specify.
**kwargs
Other kwargs passed to `Container`
| def __init__(self, *traits: t.Any, **kwargs: t.Any) -> None:
"""Create a tuple from a list, set, or tuple.
Create a fixed-type tuple with Traits:
``t = Tuple(Int(), Str(), CStr())``
would be length 3, with Int,Str,CStr for each element.
If only one arg is given and it is not a Trait, it is taken as
default_value:
``t = Tuple((1, 2, 3))``
Otherwise, ``default_value`` *must* be specified by keyword.
Parameters
----------
*traits : TraitTypes [ optional ]
the types for restricting the contents of the Tuple. If unspecified,
types are not checked. If specified, then each positional argument
corresponds to an element of the tuple. Tuples defined with traits
are of fixed length.
default_value : SequenceType [ optional ]
The default value for the Tuple. Must be list/tuple/set, and
will be cast to a tuple. If ``traits`` are specified,
``default_value`` must conform to the shape and type they specify.
**kwargs
Other kwargs passed to `Container`
"""
default_value = kwargs.pop("default_value", Undefined)
# allow Tuple((values,)):
if len(traits) == 1 and default_value is Undefined and not is_trait(traits[0]):
default_value = traits[0]
traits = ()
if default_value is None and not kwargs.get("allow_none", False):
# improve backward-compatibility for possible subclasses
# specifying default_value=None as default,
# keeping 'unspecified' behavior (i.e. empty container)
warn(
f"Specifying {self.__class__.__name__}(default_value=None)"
" for no default is deprecated in traitlets 5.0.5."
" Use default_value=Undefined",
DeprecationWarning,
stacklevel=2,
)
default_value = Undefined
if default_value is Undefined:
args: t.Any = ()
elif default_value is None:
# default_value back on kwargs for super() to handle
args = ()
kwargs["default_value"] = None
elif isinstance(default_value, self._valid_defaults):
args = (default_value,)
else:
raise TypeError(f"default value of {self.__class__.__name__} was {default_value}")
self._traits = []
for trait in traits:
if isinstance(trait, type):
warn(
"Traits should be given as instances, not types (for example, `Int()`, not `Int`)"
" Passing types is deprecated in traitlets 4.1.",
DeprecationWarning,
stacklevel=2,
)
trait = trait()
self._traits.append(trait)
if self._traits and (default_value is None or default_value is Undefined):
# don't allow default to be an empty container if length is specified
args = None
super(Container, self).__init__(klass=self.klass, args=args, **kwargs)
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15,177 | traitlets.traitlets | class_init | null | def class_init(self, cls: type[t.Any], name: str | None) -> None:
for trait in self._traits:
if isinstance(trait, TraitType):
trait.class_init(cls, None)
super(Container, self).class_init(cls, name)
| (self, cls: type[typing.Any], name: str | None) -> NoneType | [
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] |
15,189 | traitlets.traitlets | item_from_string | Cast a single item from a string
Evaluated when parsing CLI configuration from a string
| def item_from_string(self, s: str, index: int) -> t.Any: # type:ignore[override]
"""Cast a single item from a string
Evaluated when parsing CLI configuration from a string
"""
if not self._traits or index >= len(self._traits):
# return s instead of raising index error
# length errors will be raised later on validation
return s
return self._traits[index].from_string(s)
| (self, s: str, index: int) -> Any | [
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15,193 | traitlets.traitlets | subclass_init | null | def subclass_init(self, cls: type[t.Any]) -> None:
for trait in self._traits:
if isinstance(trait, TraitType):
trait.subclass_init(cls)
# explicitly not calling super().subclass_init(cls)
# to opt out of instance_init
| (self, cls: type[typing.Any]) -> NoneType | [
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] |
15,196 | traitlets.traitlets | validate_elements | null | def validate_elements(self, obj: t.Any, value: t.Any) -> t.Any:
if not self._traits:
# nothing to validate
return value
if len(value) != len(self._traits):
e = (
"The '%s' trait of %s instance requires %i elements, but a value of %s was specified."
% (self.name, class_of(obj), len(self._traits), repr_type(value))
)
raise TraitError(e)
validated = []
for trait, v in zip(self._traits, value):
try:
v = trait._validate(obj, v)
except TraitError as error:
self.error(obj, v, error)
else:
validated.append(v)
return tuple(validated)
| (self, obj: Any, value: Any) -> Any | [
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15,197 | ipyleaflet.leaflet | UILayer | Abstract UILayer class. | class UILayer(Layer):
"""Abstract UILayer class."""
_view_name = Unicode("LeafletUILayerView").tag(sync=True)
_model_name = Unicode("LeafletUILayerModel").tag(sync=True)
| (*args: 't.Any', **kwargs: 't.Any') -> 't.Any' | [
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15,262 | traitlets.traitlets | Unicode | A trait for unicode strings. | class Unicode(TraitType[G, S]):
"""A trait for unicode strings."""
default_value = ""
info_text = "a unicode string"
if t.TYPE_CHECKING:
@t.overload
def __init__(
self: Unicode[str, str | bytes],
default_value: str | Sentinel = ...,
allow_none: Literal[False] = ...,
read_only: bool | None = ...,
help: str | None = ...,
config: t.Any = ...,
**kwargs: t.Any,
) -> None:
...
@t.overload
def __init__(
self: Unicode[str | None, str | bytes | None],
default_value: str | Sentinel | None = ...,
allow_none: Literal[True] = ...,
read_only: bool | None = ...,
help: str | None = ...,
config: t.Any = ...,
**kwargs: t.Any,
) -> None:
...
def __init__(
self: Unicode[str | None, str | bytes | None],
default_value: str | Sentinel | None = ...,
allow_none: bool = ...,
read_only: bool | None = ...,
help: str | None = ...,
config: t.Any = ...,
**kwargs: t.Any,
) -> None:
...
def validate(self, obj: t.Any, value: t.Any) -> G:
if isinstance(value, str):
return t.cast(G, value)
if isinstance(value, bytes):
try:
return t.cast(G, value.decode("ascii", "strict"))
except UnicodeDecodeError as e:
msg = "Could not decode {!r} for unicode trait '{}' of {} instance."
raise TraitError(msg.format(value, self.name, class_of(obj))) from e
self.error(obj, value)
def from_string(self, s: str) -> G:
if self.allow_none and s == "None":
return t.cast(G, None)
s = os.path.expanduser(s)
if len(s) >= 2:
# handle deprecated "1"
for c in ('"', "'"):
if s[0] == s[-1] == c:
old_s = s
s = s[1:-1]
warn(
"Supporting extra quotes around strings is deprecated in traitlets 5.0. "
f"You can use {s!r} instead of {old_s!r} if you require traitlets >=5.",
DeprecationWarning,
stacklevel=2,
)
return t.cast(G, s)
def subclass_init(self, cls: type[t.Any]) -> None:
pass # fully opt out of instance_init
| (default_value: Any = traitlets.Undefined, allow_none: bool = False, read_only: bool = None, help: 'str | None' = None, config: 't.Any' = None, **kwargs: 't.Any') -> 'None' | [
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] |
15,284 | traitlets.traitlets | validate | null | def validate(self, obj: t.Any, value: t.Any) -> G:
if isinstance(value, str):
return t.cast(G, value)
if isinstance(value, bytes):
try:
return t.cast(G, value.decode("ascii", "strict"))
except UnicodeDecodeError as e:
msg = "Could not decode {!r} for unicode trait '{}' of {} instance."
raise TraitError(msg.format(value, self.name, class_of(obj))) from e
self.error(obj, value)
| (self, obj: Any, value: Any) -> ~G | [
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] |
15,285 | traitlets.traitlets | Union | A trait type representing a Union type. | class Union(TraitType[t.Any, t.Any]):
"""A trait type representing a Union type."""
def __init__(self, trait_types: t.Any, **kwargs: t.Any) -> None:
"""Construct a Union trait.
This trait allows values that are allowed by at least one of the
specified trait types. A Union traitlet cannot have metadata on
its own, besides the metadata of the listed types.
Parameters
----------
trait_types : sequence
The list of trait types of length at least 1.
**kwargs
Extra kwargs passed to `TraitType`
Notes
-----
Union([Float(), Bool(), Int()]) attempts to validate the provided values
with the validation function of Float, then Bool, and finally Int.
Parsing from string is ambiguous for container types which accept other
collection-like literals (e.g. List accepting both `[]` and `()`
precludes Union from ever parsing ``Union([List(), Tuple()])`` as a tuple;
you can modify behaviour of too permissive container traits by overriding
``_literal_from_string_pairs`` in subclasses.
Similarly, parsing unions of numeric types is only unambiguous if
types are provided in order of increasing permissiveness, e.g.
``Union([Int(), Float()])`` (since floats accept integer-looking values).
"""
self.trait_types = list(trait_types)
self.info_text = " or ".join([tt.info() for tt in self.trait_types])
super().__init__(**kwargs)
def default(self, obj: t.Any = None) -> t.Any:
default = super().default(obj)
for trait in self.trait_types:
if default is Undefined:
default = trait.default(obj)
else:
break
return default
def class_init(self, cls: type[HasTraits], name: str | None) -> None:
for trait_type in reversed(self.trait_types):
trait_type.class_init(cls, None)
super().class_init(cls, name)
def subclass_init(self, cls: type[t.Any]) -> None:
for trait_type in reversed(self.trait_types):
trait_type.subclass_init(cls)
# explicitly not calling super().subclass_init(cls)
# to opt out of instance_init
def validate(self, obj: t.Any, value: t.Any) -> t.Any:
with obj.cross_validation_lock:
for trait_type in self.trait_types:
try:
v = trait_type._validate(obj, value)
# In the case of an element trait, the name is None
if self.name is not None:
setattr(obj, "_" + self.name + "_metadata", trait_type.metadata)
return v
except TraitError:
continue
self.error(obj, value)
def __or__(self, other: t.Any) -> Union:
if isinstance(other, Union):
return Union(self.trait_types + other.trait_types)
else:
return Union([*self.trait_types, other])
def from_string(self, s: str) -> t.Any:
for trait_type in self.trait_types:
try:
v = trait_type.from_string(s)
return trait_type.validate(None, v)
except (TraitError, ValueError):
continue
return super().from_string(s)
| (trait_types: 't.Any', **kwargs: 't.Any') -> 'None' | [
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15,287 | traitlets.traitlets | __init__ | Construct a Union trait.
This trait allows values that are allowed by at least one of the
specified trait types. A Union traitlet cannot have metadata on
its own, besides the metadata of the listed types.
Parameters
----------
trait_types : sequence
The list of trait types of length at least 1.
**kwargs
Extra kwargs passed to `TraitType`
Notes
-----
Union([Float(), Bool(), Int()]) attempts to validate the provided values
with the validation function of Float, then Bool, and finally Int.
Parsing from string is ambiguous for container types which accept other
collection-like literals (e.g. List accepting both `[]` and `()`
precludes Union from ever parsing ``Union([List(), Tuple()])`` as a tuple;
you can modify behaviour of too permissive container traits by overriding
``_literal_from_string_pairs`` in subclasses.
Similarly, parsing unions of numeric types is only unambiguous if
types are provided in order of increasing permissiveness, e.g.
``Union([Int(), Float()])`` (since floats accept integer-looking values).
| def __init__(self, trait_types: t.Any, **kwargs: t.Any) -> None:
"""Construct a Union trait.
This trait allows values that are allowed by at least one of the
specified trait types. A Union traitlet cannot have metadata on
its own, besides the metadata of the listed types.
Parameters
----------
trait_types : sequence
The list of trait types of length at least 1.
**kwargs
Extra kwargs passed to `TraitType`
Notes
-----
Union([Float(), Bool(), Int()]) attempts to validate the provided values
with the validation function of Float, then Bool, and finally Int.
Parsing from string is ambiguous for container types which accept other
collection-like literals (e.g. List accepting both `[]` and `()`
precludes Union from ever parsing ``Union([List(), Tuple()])`` as a tuple;
you can modify behaviour of too permissive container traits by overriding
``_literal_from_string_pairs`` in subclasses.
Similarly, parsing unions of numeric types is only unambiguous if
types are provided in order of increasing permissiveness, e.g.
``Union([Int(), Float()])`` (since floats accept integer-looking values).
"""
self.trait_types = list(trait_types)
self.info_text = " or ".join([tt.info() for tt in self.trait_types])
super().__init__(**kwargs)
| (self, trait_types: Any, **kwargs: Any) -> NoneType | [
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15,288 | traitlets.traitlets | __or__ | null | def __or__(self, other: t.Any) -> Union:
if isinstance(other, Union):
return Union(self.trait_types + other.trait_types)
else:
return Union([*self.trait_types, other])
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15,292 | traitlets.traitlets | class_init | null | def class_init(self, cls: type[HasTraits], name: str | None) -> None:
for trait_type in reversed(self.trait_types):
trait_type.class_init(cls, None)
super().class_init(cls, name)
| (self, cls: type[traitlets.traitlets.HasTraits], name: str | None) -> NoneType | [
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15,293 | traitlets.traitlets | default | null | def default(self, obj: t.Any = None) -> t.Any:
default = super().default(obj)
for trait in self.trait_types:
if default is Undefined:
default = trait.default(obj)
else:
break
return default
| (self, obj: Optional[Any] = None) -> Any | [
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15,296 | traitlets.traitlets | from_string | null | def from_string(self, s: str) -> t.Any:
for trait_type in self.trait_types:
try:
v = trait_type.from_string(s)
return trait_type.validate(None, v)
except (TraitError, ValueError):
continue
return super().from_string(s)
| (self, s: str) -> Any | [
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15,305 | traitlets.traitlets | subclass_init | null | def subclass_init(self, cls: type[t.Any]) -> None:
for trait_type in reversed(self.trait_types):
trait_type.subclass_init(cls)
# explicitly not calling super().subclass_init(cls)
# to opt out of instance_init
| (self, cls: type[typing.Any]) -> NoneType | [
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] |
15,307 | traitlets.traitlets | validate | null | def validate(self, obj: t.Any, value: t.Any) -> t.Any:
with obj.cross_validation_lock:
for trait_type in self.trait_types:
try:
v = trait_type._validate(obj, value)
# In the case of an element trait, the name is None
if self.name is not None:
setattr(obj, "_" + self.name + "_metadata", trait_type.metadata)
return v
except TraitError:
continue
self.error(obj, value)
| (self, obj: Any, value: Any) -> Any | [
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15,308 | ipyleaflet.leaflet | VectorLayer | VectorLayer abstract class. | class VectorLayer(Layer):
"""VectorLayer abstract class."""
_view_name = Unicode("LeafletVectorLayerView").tag(sync=True)
_model_name = Unicode("LeafletVectorLayerModel").tag(sync=True)
| (*args: 't.Any', **kwargs: 't.Any') -> 't.Any' | [
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15,373 | ipyleaflet.leaflet | VectorTileLayer | VectorTileLayer class, with Layer as parent class.
Vector tile layer.
Attributes
----------
url: string, default ""
Url to the vector tile service.
attribution: string, default ""
Vector tile service attribution.
vector_tile_layer_styles: dict, default {}
CSS Styles to apply to the vector data.
| class VectorTileLayer(Layer):
"""VectorTileLayer class, with Layer as parent class.
Vector tile layer.
Attributes
----------
url: string, default ""
Url to the vector tile service.
attribution: string, default ""
Vector tile service attribution.
vector_tile_layer_styles: dict, default {}
CSS Styles to apply to the vector data.
"""
_view_name = Unicode("LeafletVectorTileLayerView").tag(sync=True)
_model_name = Unicode("LeafletVectorTileLayerModel").tag(sync=True)
url = Unicode().tag(sync=True, o=True)
attribution = Unicode().tag(sync=True, o=True)
vector_tile_layer_styles = Dict().tag(sync=True, o=True)
def redraw(self):
"""Force redrawing the tiles.
This is especially useful when you are sure the server updated the tiles and you
need to refresh the layer.
"""
self.send({"msg": "redraw"})
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15,439 | ipyleaflet.leaflet | VideoOverlay | VideoOverlay class.
Video layer from a local or remote video file.
Attributes
----------
url: string, default ""
Url to the local or remote video file.
bounds: list, default [0., 0]
SW and NE corners of the video.
attribution: string, default ""
Video attribution.
| class VideoOverlay(RasterLayer):
"""VideoOverlay class.
Video layer from a local or remote video file.
Attributes
----------
url: string, default ""
Url to the local or remote video file.
bounds: list, default [0., 0]
SW and NE corners of the video.
attribution: string, default ""
Video attribution.
"""
_view_name = Unicode("LeafletVideoOverlayView").tag(sync=True)
_model_name = Unicode("LeafletVideoOverlayModel").tag(sync=True)
url = Unicode().tag(sync=True)
bounds = List([def_loc, def_loc], help="SW and NE corners of the image").tag(
sync=True
)
# Options
attribution = Unicode().tag(sync=True, o=True)
| (*args: 't.Any', **kwargs: 't.Any') -> 't.Any' | [
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15,504 | ipyleaflet.leaflet | WKTLayer | WKTLayer class.
Layer created from a local WKT file or WKT string input.
Attributes
----------
path: string, default ""
file path of local WKT file.
wkt_string: string, default ""
WKT string.
| class WKTLayer(GeoJSON):
"""WKTLayer class.
Layer created from a local WKT file or WKT string input.
Attributes
----------
path: string, default ""
file path of local WKT file.
wkt_string: string, default ""
WKT string.
"""
path = Unicode("")
wkt_string = Unicode("")
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.data = self._get_data()
@observe("path", "wkt_string", "style", "style_callback")
def _update_data(self, change):
self.data = self._get_data()
def _get_data(self):
try:
from shapely import geometry, wkt
except ImportError:
raise RuntimeError(
"The WKTLayer needs shapely to be installed, please run `pip install shapely`"
)
if self.path:
with open(self.path) as f:
parsed_wkt = wkt.load(f)
elif self.wkt_string:
parsed_wkt = wkt.loads(self.wkt_string)
else:
raise ValueError("Please provide either WKT file path or WKT string")
geo = geometry.mapping(parsed_wkt)
if geo["type"] == "GeometryCollection":
features = [
{"geometry": g, "properties": {}, "type": "Feature"}
for g in geo["geometries"]
]
feature_collection = {"type": "FeatureCollection", "features": features}
return feature_collection
else:
feature = {"geometry": geo, "properties": {}, "type": "Feature"}
return feature
| (**kwargs) | [
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15,509 | ipyleaflet.leaflet | __init__ | null | def __init__(self, **kwargs):
super().__init__(**kwargs)
self.data = self._get_data()
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15,518 | ipyleaflet.leaflet | _get_data | null | def _get_data(self):
try:
from shapely import geometry, wkt
except ImportError:
raise RuntimeError(
"The WKTLayer needs shapely to be installed, please run `pip install shapely`"
)
if self.path:
with open(self.path) as f:
parsed_wkt = wkt.load(f)
elif self.wkt_string:
parsed_wkt = wkt.loads(self.wkt_string)
else:
raise ValueError("Please provide either WKT file path or WKT string")
geo = geometry.mapping(parsed_wkt)
if geo["type"] == "GeometryCollection":
features = [
{"geometry": g, "properties": {}, "type": "Feature"}
for g in geo["geometries"]
]
feature_collection = {"type": "FeatureCollection", "features": features}
return feature_collection
else:
feature = {"geometry": geo, "properties": {}, "type": "Feature"}
return feature
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15,580 | ipyleaflet.leaflet | WMSLayer | WMSLayer class, with TileLayer as a parent class.
Attributes
----------
layers: string, default ""
Comma-separated list of WMS layers to show.
styles: string, default ""
Comma-separated list of WMS styles
format: string, default "image/jpeg"
WMS image format (use `'image/png'` for layers with transparency).
transparent: boolean, default False
If true, the WMS service will return images with transparency.
crs: dict, default ipyleaflet.projections.EPSG3857
Projection used for this WMS service.
| class WMSLayer(TileLayer):
"""WMSLayer class, with TileLayer as a parent class.
Attributes
----------
layers: string, default ""
Comma-separated list of WMS layers to show.
styles: string, default ""
Comma-separated list of WMS styles
format: string, default "image/jpeg"
WMS image format (use `'image/png'` for layers with transparency).
transparent: boolean, default False
If true, the WMS service will return images with transparency.
crs: dict, default ipyleaflet.projections.EPSG3857
Projection used for this WMS service.
"""
_view_name = Unicode("LeafletWMSLayerView").tag(sync=True)
_model_name = Unicode("LeafletWMSLayerModel").tag(sync=True)
# Options
layers = Unicode().tag(sync=True, o=True)
styles = Unicode().tag(sync=True, o=True)
format = Unicode("image/jpeg").tag(sync=True, o=True)
transparent = Bool(False).tag(sync=True, o=True)
crs = Dict(default_value=projections.EPSG3857).tag(sync=True)
uppercase = Bool(False).tag(sync=True, o=True)
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] |
15,648 | ipywidgets.widgets.widget | Widget | null | class Widget(LoggingHasTraits):
#-------------------------------------------------------------------------
# Class attributes
#-------------------------------------------------------------------------
_widget_construction_callback = None
_control_comm = None
@_staticproperty
def widgets():
# Because this is a static attribute, it will be accessed when initializing this class. In that case, since a user
# did not explicitly try to use this attribute, we do not want to throw a deprecation warning.
# So we check if the thing calling this static property is one of the known initialization functions in traitlets.
frame = _get_frame(2)
if not (frame.f_code.co_filename == TRAITLETS_FILE and (frame.f_code.co_name in ('getmembers', 'setup_instance', 'setup_class'))):
deprecation("Widget.widgets is deprecated.")
return _instances
@_staticproperty
def _active_widgets():
# Because this is a static attribute, it will be accessed when initializing this class. In that case, since a user
# did not explicitly try to use this attribute, we do not want to throw a deprecation warning.
# So we check if the thing calling this static property is one of the known initialization functions in traitlets.
frame = _get_frame(2)
if not (frame.f_code.co_filename == TRAITLETS_FILE and (frame.f_code.co_name in ('getmembers', 'setup_instance', 'setup_class'))):
deprecation("Widget._active_widgets is deprecated.")
return _instances
@_staticproperty
def _widget_types():
# Because this is a static attribute, it will be accessed when initializing this class. In that case, since a user
# did not explicitly try to use this attribute, we do not want to throw a deprecation warning.
# So we check if the thing calling this static property is one of the known initialization functions in traitlets.
frame = _get_frame(2)
if not (frame.f_code.co_filename == TRAITLETS_FILE and (frame.f_code.co_name in ('getmembers', 'setup_instance', 'setup_class'))):
deprecation("Widget._widget_types is deprecated.")
return _registry
@_staticproperty
def widget_types():
# Because this is a static attribute, it will be accessed when initializing this class. In that case, since a user
# did not explicitly try to use this attribute, we do not want to throw a deprecation warning.
# So we check if the thing calling this static property is one of the known initialization functions in traitlets.
frame = _get_frame(2)
if not (frame.f_code.co_filename == TRAITLETS_FILE and (frame.f_code.co_name in ('getmembers', 'setup_instance', 'setup_class'))):
deprecation("Widget.widget_types is deprecated.")
return _registry
@classmethod
def close_all(cls):
for widget in list(_instances.values()):
widget.close()
@staticmethod
def on_widget_constructed(callback):
"""Registers a callback to be called when a widget is constructed.
The callback must have the following signature:
callback(widget)"""
Widget._widget_construction_callback = callback
@staticmethod
def _call_widget_constructed(widget):
"""Static method, called when a widget is constructed."""
if Widget._widget_construction_callback is not None and callable(Widget._widget_construction_callback):
Widget._widget_construction_callback(widget)
@classmethod
def handle_control_comm_opened(cls, comm, msg):
"""
Class method, called when the comm-open message on the
"jupyter.widget.control" comm channel is received
"""
version = msg.get('metadata', {}).get('version', '')
if version.split('.')[0] != CONTROL_PROTOCOL_VERSION_MAJOR:
raise ValueError("Incompatible widget control protocol versions: received version %r, expected version %r"%(version, __control_protocol_version__))
cls._control_comm = comm
cls._control_comm.on_msg(cls._handle_control_comm_msg)
@classmethod
def _handle_control_comm_msg(cls, msg):
# This shouldn't happen unless someone calls this method manually
if cls._control_comm is None:
raise RuntimeError('Control comm has not been properly opened')
data = msg['content']['data']
method = data['method']
if method == 'request_states':
# Send back the full widgets state
cls.get_manager_state()
widgets = _instances.values()
full_state = {}
drop_defaults = False
for widget in widgets:
full_state[widget.model_id] = {
'model_name': widget._model_name,
'model_module': widget._model_module,
'model_module_version': widget._model_module_version,
'state': widget.get_state(drop_defaults=drop_defaults),
}
full_state, buffer_paths, buffers = _remove_buffers(full_state)
cls._control_comm.send(dict(
method='update_states',
states=full_state,
buffer_paths=buffer_paths
), buffers=buffers)
else:
raise RuntimeError('Unknown front-end to back-end widget control msg with method "%s"' % method)
@staticmethod
def handle_comm_opened(comm, msg):
"""Static method, called when a widget is constructed."""
version = msg.get('metadata', {}).get('version', '')
if version.split('.')[0] != PROTOCOL_VERSION_MAJOR:
raise ValueError("Incompatible widget protocol versions: received version %r, expected version %r"%(version, __protocol_version__))
data = msg['content']['data']
state = data['state']
# Find the widget class to instantiate in the registered widgets
widget_class = _registry.get(state['_model_module'],
state['_model_module_version'],
state['_model_name'],
state['_view_module'],
state['_view_module_version'],
state['_view_name'])
widget = widget_class(comm=comm)
if 'buffer_paths' in data:
_put_buffers(state, data['buffer_paths'], msg['buffers'])
widget.set_state(state)
@staticmethod
def get_manager_state(drop_defaults=False, widgets=None):
"""Returns the full state for a widget manager for embedding
:param drop_defaults: when True, it will not include default value
:param widgets: list with widgets to include in the state (or all widgets when None)
:return:
"""
state = {}
if widgets is None:
widgets = _instances.values()
for widget in widgets:
state[widget.model_id] = widget._get_embed_state(drop_defaults=drop_defaults)
return {'version_major': 2, 'version_minor': 0, 'state': state}
def _get_embed_state(self, drop_defaults=False):
state = {
'model_name': self._model_name,
'model_module': self._model_module,
'model_module_version': self._model_module_version
}
model_state, buffer_paths, buffers = _remove_buffers(self.get_state(drop_defaults=drop_defaults))
state['state'] = model_state
if len(buffers) > 0:
state['buffers'] = [{'encoding': 'base64',
'path': p,
'data': standard_b64encode(d).decode('ascii')}
for p, d in zip(buffer_paths, buffers)]
return state
def get_view_spec(self):
return dict(version_major=2, version_minor=0, model_id=self._model_id)
#-------------------------------------------------------------------------
# Traits
#----------------------------------------------------------------- | (**kwargs) | [
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15,705 | ipyleaflet.leaflet | WidgetControl | WidgetControl class, with Control as parent class.
A control that contains any DOMWidget instance.
Attributes
----------
widget: DOMWidget
The widget to put inside of the control. It can be any widget, even coming from
a third-party library like bqplot.
| class WidgetControl(Control):
"""WidgetControl class, with Control as parent class.
A control that contains any DOMWidget instance.
Attributes
----------
widget: DOMWidget
The widget to put inside of the control. It can be any widget, even coming from
a third-party library like bqplot.
"""
_view_name = Unicode("LeafletWidgetControlView").tag(sync=True)
_model_name = Unicode("LeafletWidgetControlModel").tag(sync=True)
widget = Instance(DOMWidget).tag(sync=True, **widget_serialization)
max_width = Int(default_value=None, allow_none=True).tag(sync=True)
min_width = Int(default_value=None, allow_none=True).tag(sync=True)
max_height = Int(default_value=None, allow_none=True).tag(sync=True)
min_height = Int(default_value=None, allow_none=True).tag(sync=True)
transparent_bg = Bool(False).tag(sync=True, o=True)
| (*args: 't.Any', **kwargs: 't.Any') -> 't.Any' | [
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15,762 | ipyleaflet.leaflet | ZoomControl | ZoomControl class, with Control as parent class.
A control which contains buttons for zooming in/out the Map.
Attributes
----------
zoom_in_text: str, default '+'
Text to put in the zoom-in button.
zoom_in_title: str, default 'Zoom in'
Title to put in the zoom-in button, this is shown when the mouse
is over the button.
zoom_out_text: str, default '-'
Text to put in the zoom-out button.
zoom_out_title: str, default 'Zoom out'
Title to put in the zoom-out button, this is shown when the mouse
is over the button.
| class ZoomControl(Control):
"""ZoomControl class, with Control as parent class.
A control which contains buttons for zooming in/out the Map.
Attributes
----------
zoom_in_text: str, default '+'
Text to put in the zoom-in button.
zoom_in_title: str, default 'Zoom in'
Title to put in the zoom-in button, this is shown when the mouse
is over the button.
zoom_out_text: str, default '-'
Text to put in the zoom-out button.
zoom_out_title: str, default 'Zoom out'
Title to put in the zoom-out button, this is shown when the mouse
is over the button.
"""
_view_name = Unicode("LeafletZoomControlView").tag(sync=True)
_model_name = Unicode("LeafletZoomControlModel").tag(sync=True)
zoom_in_text = Unicode("+").tag(sync=True, o=True)
zoom_in_title = Unicode("Zoom in").tag(sync=True, o=True)
zoom_out_text = Unicode("-").tag(sync=True, o=True)
zoom_out_title = Unicode("Zoom out").tag(sync=True, o=True)
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] |
15,821 | ipyleaflet.leaflet | basemap_to_tiles | Turn a basemap into a TileLayer object.
Parameters
----------
basemap : class:`xyzservices.lib.TileProvider` or Dict
Basemap description coming from ipyleaflet.basemaps.
day: string
If relevant for the chosen basemap, you can specify the day for
the tiles in the "%Y-%m-%d" format. Defaults to yesterday's date.
kwargs: key-word arguments
Extra key-word arguments to pass to the TileLayer constructor.
| def basemap_to_tiles(basemap, day=yesterday, **kwargs):
"""Turn a basemap into a TileLayer object.
Parameters
----------
basemap : class:`xyzservices.lib.TileProvider` or Dict
Basemap description coming from ipyleaflet.basemaps.
day: string
If relevant for the chosen basemap, you can specify the day for
the tiles in the "%Y-%m-%d" format. Defaults to yesterday's date.
kwargs: key-word arguments
Extra key-word arguments to pass to the TileLayer constructor.
"""
if isinstance(basemap, xyzservices.lib.TileProvider):
url = basemap.build_url(time=day)
elif isinstance(basemap, dict):
url = basemap.get("url", "")
else:
raise ValueError("Invalid basemap type")
return TileLayer(
url=url,
max_zoom=basemap.get("max_zoom", 18),
min_zoom=basemap.get("min_zoom", 1),
attribution=basemap.get("html_attribution", "")
or basemap.get("attribution", ""),
name=basemap.get("name", ""),
**kwargs,
)
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15,824 | traitlets.traitlets | default | A decorator which assigns a dynamic default for a Trait on a HasTraits object.
Parameters
----------
name
The str name of the Trait on the object whose default should be generated.
Notes
-----
Unlike observers and validators which are properties of the HasTraits
instance, default value generators are class-level properties.
Besides, default generators are only invoked if they are registered in
subclasses of `this_type`.
::
class A(HasTraits):
bar = Int()
@default('bar')
def get_bar_default(self):
return 11
class B(A):
bar = Float() # This trait ignores the default generator defined in
# the base class A
class C(B):
@default('bar')
def some_other_default(self): # This default generator should not be
return 3.0 # ignored since it is defined in a
# class derived from B.a.this_class.
| def default(name: str) -> DefaultHandler:
"""A decorator which assigns a dynamic default for a Trait on a HasTraits object.
Parameters
----------
name
The str name of the Trait on the object whose default should be generated.
Notes
-----
Unlike observers and validators which are properties of the HasTraits
instance, default value generators are class-level properties.
Besides, default generators are only invoked if they are registered in
subclasses of `this_type`.
::
class A(HasTraits):
bar = Int()
@default('bar')
def get_bar_default(self):
return 11
class B(A):
bar = Float() # This trait ignores the default generator defined in
# the base class A
class C(B):
@default('bar')
def some_other_default(self): # This default generator should not be
return 3.0 # ignored since it is defined in a
# class derived from B.a.this_class.
"""
if not isinstance(name, str):
raise TypeError("Trait name must be a string or All, not %r" % name)
return DefaultHandler(name)
| (name: str) -> traitlets.traitlets.DefaultHandler | [
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15,825 | IPython.core.display_functions | display | Display a Python object in all frontends.
By default all representations will be computed and sent to the frontends.
Frontends can decide which representation is used and how.
In terminal IPython this will be similar to using :func:`print`, for use in richer
frontends see Jupyter notebook examples with rich display logic.
Parameters
----------
*objs : object
The Python objects to display.
raw : bool, optional
Are the objects to be displayed already mimetype-keyed dicts of raw display data,
or Python objects that need to be formatted before display? [default: False]
include : list, tuple or set, optional
A list of format type strings (MIME types) to include in the
format data dict. If this is set *only* the format types included
in this list will be computed.
exclude : list, tuple or set, optional
A list of format type strings (MIME types) to exclude in the format
data dict. If this is set all format types will be computed,
except for those included in this argument.
metadata : dict, optional
A dictionary of metadata to associate with the output.
mime-type keys in this dictionary will be associated with the individual
representation formats, if they exist.
transient : dict, optional
A dictionary of transient data to associate with the output.
Data in this dict should not be persisted to files (e.g. notebooks).
display_id : str, bool optional
Set an id for the display.
This id can be used for updating this display area later via update_display.
If given as `True`, generate a new `display_id`
clear : bool, optional
Should the output area be cleared before displaying anything? If True,
this will wait for additional output before clearing. [default: False]
**kwargs : additional keyword-args, optional
Additional keyword-arguments are passed through to the display publisher.
Returns
-------
handle: DisplayHandle
Returns a handle on updatable displays for use with :func:`update_display`,
if `display_id` is given. Returns :any:`None` if no `display_id` is given
(default).
Examples
--------
>>> class Json(object):
... def __init__(self, json):
... self.json = json
... def _repr_pretty_(self, pp, cycle):
... import json
... pp.text(json.dumps(self.json, indent=2))
... def __repr__(self):
... return str(self.json)
...
>>> d = Json({1:2, 3: {4:5}})
>>> print(d)
{1: 2, 3: {4: 5}}
>>> display(d)
{
"1": 2,
"3": {
"4": 5
}
}
>>> def int_formatter(integer, pp, cycle):
... pp.text('I'*integer)
>>> plain = get_ipython().display_formatter.formatters['text/plain']
>>> plain.for_type(int, int_formatter)
<function _repr_pprint at 0x...>
>>> display(7-5)
II
>>> del plain.type_printers[int]
>>> display(7-5)
2
See Also
--------
:func:`update_display`
Notes
-----
In Python, objects can declare their textual representation using the
`__repr__` method. IPython expands on this idea and allows objects to declare
other, rich representations including:
- HTML
- JSON
- PNG
- JPEG
- SVG
- LaTeX
A single object can declare some or all of these representations; all are
handled by IPython's display system.
The main idea of the first approach is that you have to implement special
display methods when you define your class, one for each representation you
want to use. Here is a list of the names of the special methods and the
values they must return:
- `_repr_html_`: return raw HTML as a string, or a tuple (see below).
- `_repr_json_`: return a JSONable dict, or a tuple (see below).
- `_repr_jpeg_`: return raw JPEG data, or a tuple (see below).
- `_repr_png_`: return raw PNG data, or a tuple (see below).
- `_repr_svg_`: return raw SVG data as a string, or a tuple (see below).
- `_repr_latex_`: return LaTeX commands in a string surrounded by "$",
or a tuple (see below).
- `_repr_mimebundle_`: return a full mimebundle containing the mapping
from all mimetypes to data.
Use this for any mime-type not listed above.
The above functions may also return the object's metadata alonside the
data. If the metadata is available, the functions will return a tuple
containing the data and metadata, in that order. If there is no metadata
available, then the functions will return the data only.
When you are directly writing your own classes, you can adapt them for
display in IPython by following the above approach. But in practice, you
often need to work with existing classes that you can't easily modify.
You can refer to the documentation on integrating with the display system in
order to register custom formatters for already existing types
(:ref:`integrating_rich_display`).
.. versionadded:: 5.4 display available without import
.. versionadded:: 6.1 display available without import
Since IPython 5.4 and 6.1 :func:`display` is automatically made available to
the user without import. If you are using display in a document that might
be used in a pure python context or with older version of IPython, use the
following import at the top of your file::
from IPython.display import display
| def display(
*objs,
include=None,
exclude=None,
metadata=None,
transient=None,
display_id=None,
raw=False,
clear=False,
**kwargs,
):
"""Display a Python object in all frontends.
By default all representations will be computed and sent to the frontends.
Frontends can decide which representation is used and how.
In terminal IPython this will be similar to using :func:`print`, for use in richer
frontends see Jupyter notebook examples with rich display logic.
Parameters
----------
*objs : object
The Python objects to display.
raw : bool, optional
Are the objects to be displayed already mimetype-keyed dicts of raw display data,
or Python objects that need to be formatted before display? [default: False]
include : list, tuple or set, optional
A list of format type strings (MIME types) to include in the
format data dict. If this is set *only* the format types included
in this list will be computed.
exclude : list, tuple or set, optional
A list of format type strings (MIME types) to exclude in the format
data dict. If this is set all format types will be computed,
except for those included in this argument.
metadata : dict, optional
A dictionary of metadata to associate with the output.
mime-type keys in this dictionary will be associated with the individual
representation formats, if they exist.
transient : dict, optional
A dictionary of transient data to associate with the output.
Data in this dict should not be persisted to files (e.g. notebooks).
display_id : str, bool optional
Set an id for the display.
This id can be used for updating this display area later via update_display.
If given as `True`, generate a new `display_id`
clear : bool, optional
Should the output area be cleared before displaying anything? If True,
this will wait for additional output before clearing. [default: False]
**kwargs : additional keyword-args, optional
Additional keyword-arguments are passed through to the display publisher.
Returns
-------
handle: DisplayHandle
Returns a handle on updatable displays for use with :func:`update_display`,
if `display_id` is given. Returns :any:`None` if no `display_id` is given
(default).
Examples
--------
>>> class Json(object):
... def __init__(self, json):
... self.json = json
... def _repr_pretty_(self, pp, cycle):
... import json
... pp.text(json.dumps(self.json, indent=2))
... def __repr__(self):
... return str(self.json)
...
>>> d = Json({1:2, 3: {4:5}})
>>> print(d)
{1: 2, 3: {4: 5}}
>>> display(d)
{
"1": 2,
"3": {
"4": 5
}
}
>>> def int_formatter(integer, pp, cycle):
... pp.text('I'*integer)
>>> plain = get_ipython().display_formatter.formatters['text/plain']
>>> plain.for_type(int, int_formatter)
<function _repr_pprint at 0x...>
>>> display(7-5)
II
>>> del plain.type_printers[int]
>>> display(7-5)
2
See Also
--------
:func:`update_display`
Notes
-----
In Python, objects can declare their textual representation using the
`__repr__` method. IPython expands on this idea and allows objects to declare
other, rich representations including:
- HTML
- JSON
- PNG
- JPEG
- SVG
- LaTeX
A single object can declare some or all of these representations; all are
handled by IPython's display system.
The main idea of the first approach is that you have to implement special
display methods when you define your class, one for each representation you
want to use. Here is a list of the names of the special methods and the
values they must return:
- `_repr_html_`: return raw HTML as a string, or a tuple (see below).
- `_repr_json_`: return a JSONable dict, or a tuple (see below).
- `_repr_jpeg_`: return raw JPEG data, or a tuple (see below).
- `_repr_png_`: return raw PNG data, or a tuple (see below).
- `_repr_svg_`: return raw SVG data as a string, or a tuple (see below).
- `_repr_latex_`: return LaTeX commands in a string surrounded by "$",
or a tuple (see below).
- `_repr_mimebundle_`: return a full mimebundle containing the mapping
from all mimetypes to data.
Use this for any mime-type not listed above.
The above functions may also return the object's metadata alonside the
data. If the metadata is available, the functions will return a tuple
containing the data and metadata, in that order. If there is no metadata
available, then the functions will return the data only.
When you are directly writing your own classes, you can adapt them for
display in IPython by following the above approach. But in practice, you
often need to work with existing classes that you can't easily modify.
You can refer to the documentation on integrating with the display system in
order to register custom formatters for already existing types
(:ref:`integrating_rich_display`).
.. versionadded:: 5.4 display available without import
.. versionadded:: 6.1 display available without import
Since IPython 5.4 and 6.1 :func:`display` is automatically made available to
the user without import. If you are using display in a document that might
be used in a pure python context or with older version of IPython, use the
following import at the top of your file::
from IPython.display import display
"""
from IPython.core.interactiveshell import InteractiveShell
if not InteractiveShell.initialized():
# Directly print objects.
print(*objs)
return
if transient is None:
transient = {}
if metadata is None:
metadata={}
if display_id:
if display_id is True:
display_id = _new_id()
transient['display_id'] = display_id
if kwargs.get('update') and 'display_id' not in transient:
raise TypeError('display_id required for update_display')
if transient:
kwargs['transient'] = transient
if not objs and display_id:
# if given no objects, but still a request for a display_id,
# we assume the user wants to insert an empty output that
# can be updated later
objs = [{}]
raw = True
if not raw:
format = InteractiveShell.instance().display_formatter.format
if clear:
clear_output(wait=True)
for obj in objs:
if raw:
publish_display_data(data=obj, metadata=metadata, **kwargs)
else:
format_dict, md_dict = format(obj, include=include, exclude=exclude)
if not format_dict:
# nothing to display (e.g. _ipython_display_ took over)
continue
if metadata:
# kwarg-specified metadata gets precedence
_merge(md_dict, metadata)
publish_display_data(data=format_dict, metadata=md_dict, **kwargs)
if display_id:
return DisplayHandle(display_id)
| (*objs, include=None, exclude=None, metadata=None, transient=None, display_id=None, raw=False, clear=False, **kwargs) | [
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15,826 | ipywidgets.embed | embed_minimal_html | Write a minimal HTML file with widget views embedded.
Parameters
----------
fp: filename or file-like object
The file to write the HTML output to.
views: widget or collection of widgets or None
The widgets to include views for. If None, all DOMWidgets are
included (not just the displayed ones).
title: title of the html page.
template: Template in which to embed the widget state.
This should be a Python string with placeholders
`{title}` and `{snippet}`. The `{snippet}` placeholder
will be replaced by all the widgets.
drop_defaults: boolean
Whether to drop default values from the widget states.
state: dict or None (default)
The state to include. When set to None, the state of all widgets
know to the widget manager is included. Otherwise it uses the
passed state directly. This allows for end users to include a
smaller state, under the responsibility that this state is
sufficient to reconstruct the embedded views.
indent: integer, string or None
The indent to use for the JSON state dump. See `json.dumps` for
full description.
embed_url: string or None
Allows for overriding the URL used to fetch the widget manager
for the embedded code. This defaults (None) to a `jsDelivr` CDN url.
requirejs: boolean (True)
Enables the requirejs-based embedding, which allows for custom widgets.
If True, the embed_url should point to an AMD module.
cors: boolean (True)
If True avoids sending user credentials while requesting the scripts.
When opening an HTML file from disk, some browsers may refuse to load
the scripts.
| @doc_subst(_doc_snippets)
def embed_minimal_html(fp, views, title='IPyWidget export', template=None, **kwargs):
"""Write a minimal HTML file with widget views embedded.
Parameters
----------
fp: filename or file-like object
The file to write the HTML output to.
{views_attribute}
title: title of the html page.
template: Template in which to embed the widget state.
This should be a Python string with placeholders
`{{title}}` and `{{snippet}}`. The `{{snippet}}` placeholder
will be replaced by all the widgets.
{embed_kwargs}
"""
snippet = embed_snippet(views, **kwargs)
values = {
'title': title,
'snippet': snippet,
}
if template is None:
template = html_template
html_code = template.format(**values)
# Check if fp is writable:
if hasattr(fp, 'write'):
fp.write(html_code)
else:
# Assume fp is a filename:
with open(fp, "w") as f:
f.write(html_code)
| (fp, views, title='IPyWidget export', template=None, **kwargs) | [
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15,827 | ipywidgets.widgets.interaction | interactive |
A VBox container containing a group of interactive widgets tied to a
function.
Parameters
----------
__interact_f : function
The function to which the interactive widgets are tied. The `**kwargs`
should match the function signature.
__options : dict
A dict of options. Currently, the only supported keys are
``"manual"`` (defaults to ``False``), ``"manual_name"`` (defaults
to ``"Run Interact"``) and ``"auto_display"`` (defaults to ``False``).
**kwargs : various, optional
An interactive widget is created for each keyword argument that is a
valid widget abbreviation.
Note that the first two parameters intentionally start with a double
underscore to avoid being mixed up with keyword arguments passed by
``**kwargs``.
| class interactive(VBox):
"""
A VBox container containing a group of interactive widgets tied to a
function.
Parameters
----------
__interact_f : function
The function to which the interactive widgets are tied. The `**kwargs`
should match the function signature.
__options : dict
A dict of options. Currently, the only supported keys are
``"manual"`` (defaults to ``False``), ``"manual_name"`` (defaults
to ``"Run Interact"``) and ``"auto_display"`` (defaults to ``False``).
**kwargs : various, optional
An interactive widget is created for each keyword argument that is a
valid widget abbreviation.
Note that the first two parameters intentionally start with a double
underscore to avoid being mixed up with keyword arguments passed by
``**kwargs``.
"""
def __init__(self, __interact_f, __options={}, **kwargs):
VBox.__init__(self, _dom_classes=['widget-interact'])
self.result = None
self.args = []
self.kwargs = {}
self.f = f = __interact_f
self.clear_output = kwargs.pop('clear_output', True)
self.manual = __options.get("manual", False)
self.manual_name = __options.get("manual_name", "Run Interact")
self.auto_display = __options.get("auto_display", False)
new_kwargs = self.find_abbreviations(kwargs)
# Before we proceed, let's make sure that the user has passed a set of args+kwargs
# that will lead to a valid call of the function. This protects against unspecified
# and doubly-specified arguments.
try:
check_argspec(f)
except TypeError:
# if we can't inspect, we can't validate
pass
else:
getcallargs(f, **{n:v for n,v,_ in new_kwargs})
# Now build the widgets from the abbreviations.
self.kwargs_widgets = self.widgets_from_abbreviations(new_kwargs)
# This has to be done as an assignment, not using self.children.append,
# so that traitlets notices the update. We skip any objects (such as fixed) that
# are not DOMWidgets.
c = [w for w in self.kwargs_widgets if isinstance(w, DOMWidget)]
# If we are only to run the function on demand, add a button to request this.
if self.manual:
self.manual_button = Button(description=self.manual_name)
c.append(self.manual_button)
self.out = Output()
c.append(self.out)
self.children = c
# Wire up the widgets
# If we are doing manual running, the callback is only triggered by the button
# Otherwise, it is triggered for every trait change received
# On-demand running also suppresses running the function with the initial parameters
if self.manual:
self.manual_button.on_click(self.update)
# Also register input handlers on text areas, so the user can hit return to
# invoke execution.
for w in self.kwargs_widgets:
if isinstance(w, Text):
w.continuous_update = False
w.observe(self.update, names='value')
else:
for widget in self.kwargs_widgets:
widget.observe(self.update, names='value')
self.update()
# Callback function
def update(self, *args):
"""
Call the interact function and update the output widget with
the result of the function call.
Parameters
----------
*args : ignored
Required for this method to be used as traitlets callback.
"""
self.kwargs = {}
if self.manual:
self.manual_button.disabled = True
try:
show_inline_matplotlib_plots()
with self.out:
if self.clear_output:
clear_output(wait=True)
for widget in self.kwargs_widgets:
value = widget.get_interact_value()
self.kwargs[widget._kwarg] = value
self.result = self.f(**self.kwargs)
show_inline_matplotlib_plots()
if self.auto_display and self.result is not None:
display(self.result)
except Exception as e:
ip = get_ipython()
if ip is None:
self.log.warning("Exception in interact callback: %s", e, exc_info=True)
else:
ip.showtraceback()
finally:
if self.manual:
self.manual_button.disabled = False
# Find abbreviations
def signature(self):
return signature(self.f)
def find_abbreviations(self, kwargs):
"""Find the abbreviations for the given function and kwargs.
Return (name, abbrev, default) tuples.
"""
new_kwargs = []
try:
sig = self.signature()
except (ValueError, TypeError):
# can't inspect, no info from function; only use kwargs
return [ (key, value, value) for key, value in kwargs.items() ]
for param in sig.parameters.values():
for name, value, default in _yield_abbreviations_for_parameter(param, kwargs):
if value is empty:
raise ValueError('cannot find widget or abbreviation for argument: {!r}'.format(name))
new_kwargs.append((name, value, default))
return new_kwargs
# Abbreviations to widgets
def widgets_from_abbreviations(self, seq):
"""Given a sequence of (name, abbrev, default) tuples, return a sequence of Widgets."""
result = []
for name, abbrev, default in seq:
if isinstance(abbrev, Widget) and (not isinstance(abbrev, ValueWidget)):
raise TypeError("{!r} is not a ValueWidget".format(abbrev))
widget = self.widget_from_abbrev(abbrev, default)
if widget is None:
raise ValueError("{!r} cannot be transformed to a widget".format(abbrev))
if not hasattr(widget, "description") or not widget.description:
widget.description = name
widget._kwarg = name
result.append(widget)
return result
@classmethod
def widget_from_abbrev(cls, abbrev, default=empty):
"""Build a ValueWidget instance given an abbreviation or Widget."""
if isinstance(abbrev, ValueWidget) or isinstance(abbrev, fixed):
return abbrev
if isinstance(abbrev, tuple):
widget = cls.widget_from_tuple(abbrev)
if default is not empty:
try:
widget.value = default
except Exception:
# ignore failure to set default
pass
return widget
# Try single value
widget = cls.widget_from_single_value(abbrev)
if widget is not None:
return widget
# Something iterable (list, dict, generator, ...). Note that str and
# tuple should be handled before, that is why we check this case last.
if isinstance(abbrev, Iterable):
widget = cls.widget_from_iterable(abbrev)
if default is not empty:
try:
widget.value = default
except Exception:
# ignore failure to set default
pass
return widget
# No idea...
return None
@staticmethod
def widget_from_single_value(o):
"""Make widgets from single values, which can be used as parameter defaults."""
if isinstance(o, str):
return Text(value=str(o))
elif isinstance(o, bool):
return Checkbox(value=o)
elif isinstance(o, Integral):
min, max, value = _get_min_max_value(None, None, o)
return IntSlider(value=o, min=min, max=max)
elif isinstance(o, Real):
min, max, value = _get_min_max_value(None, None, o)
return FloatSlider(value=o, min=min, max=max)
else:
return None
@stat | (_interactive__interact_f, _interactive__options={}, **kwargs) | [
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15,832 | ipywidgets.widgets.interaction | __init__ | null | def __init__(self, __interact_f, __options={}, **kwargs):
VBox.__init__(self, _dom_classes=['widget-interact'])
self.result = None
self.args = []
self.kwargs = {}
self.f = f = __interact_f
self.clear_output = kwargs.pop('clear_output', True)
self.manual = __options.get("manual", False)
self.manual_name = __options.get("manual_name", "Run Interact")
self.auto_display = __options.get("auto_display", False)
new_kwargs = self.find_abbreviations(kwargs)
# Before we proceed, let's make sure that the user has passed a set of args+kwargs
# that will lead to a valid call of the function. This protects against unspecified
# and doubly-specified arguments.
try:
check_argspec(f)
except TypeError:
# if we can't inspect, we can't validate
pass
else:
getcallargs(f, **{n:v for n,v,_ in new_kwargs})
# Now build the widgets from the abbreviations.
self.kwargs_widgets = self.widgets_from_abbreviations(new_kwargs)
# This has to be done as an assignment, not using self.children.append,
# so that traitlets notices the update. We skip any objects (such as fixed) that
# are not DOMWidgets.
c = [w for w in self.kwargs_widgets if isinstance(w, DOMWidget)]
# If we are only to run the function on demand, add a button to request this.
if self.manual:
self.manual_button = Button(description=self.manual_name)
c.append(self.manual_button)
self.out = Output()
c.append(self.out)
self.children = c
# Wire up the widgets
# If we are doing manual running, the callback is only triggered by the button
# Otherwise, it is triggered for every trait change received
# On-demand running also suppresses running the function with the initial parameters
if self.manual:
self.manual_button.on_click(self.update)
# Also register input handlers on text areas, so the user can hit return to
# invoke execution.
for w in self.kwargs_widgets:
if isinstance(w, Text):
w.continuous_update = False
w.observe(self.update, names='value')
else:
for widget in self.kwargs_widgets:
widget.observe(self.update, names='value')
self.update()
| (self, _interactive__interact_f, _interactive__options={}, **kwargs) | [
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15,860 | ipywidgets.widgets.interaction | find_abbreviations | Find the abbreviations for the given function and kwargs.
Return (name, abbrev, default) tuples.
| def find_abbreviations(self, kwargs):
"""Find the abbreviations for the given function and kwargs.
Return (name, abbrev, default) tuples.
"""
new_kwargs = []
try:
sig = self.signature()
except (ValueError, TypeError):
# can't inspect, no info from function; only use kwargs
return [ (key, value, value) for key, value in kwargs.items() ]
for param in sig.parameters.values():
for name, value, default in _yield_abbreviations_for_parameter(param, kwargs):
if value is empty:
raise ValueError('cannot find widget or abbreviation for argument: {!r}'.format(name))
new_kwargs.append((name, value, default))
return new_kwargs
| (self, kwargs) | [
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15,881 | ipywidgets.widgets.interaction | signature | null | def signature(self):
return signature(self.f)
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] |
15,890 | ipywidgets.widgets.interaction | update |
Call the interact function and update the output widget with
the result of the function call.
Parameters
----------
*args : ignored
Required for this method to be used as traitlets callback.
| def update(self, *args):
"""
Call the interact function and update the output widget with
the result of the function call.
Parameters
----------
*args : ignored
Required for this method to be used as traitlets callback.
"""
self.kwargs = {}
if self.manual:
self.manual_button.disabled = True
try:
show_inline_matplotlib_plots()
with self.out:
if self.clear_output:
clear_output(wait=True)
for widget in self.kwargs_widgets:
value = widget.get_interact_value()
self.kwargs[widget._kwarg] = value
self.result = self.f(**self.kwargs)
show_inline_matplotlib_plots()
if self.auto_display and self.result is not None:
display(self.result)
except Exception as e:
ip = get_ipython()
if ip is None:
self.log.warning("Exception in interact callback: %s", e, exc_info=True)
else:
ip.showtraceback()
finally:
if self.manual:
self.manual_button.disabled = False
| (self, *args) | [
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] |
15,891 | ipywidgets.widgets.interaction | widget_from_iterable | Make widgets from an iterable. This should not be done for
a string or tuple. | @staticmethod
def widget_from_iterable(o):
"""Make widgets from an iterable. This should not be done for
a string or tuple."""
# Dropdown expects a dict or list, so we convert an arbitrary
# iterable to either of those.
if isinstance(o, (list, dict)):
return Dropdown(options=o)
elif isinstance(o, Mapping):
return Dropdown(options=list(o.items()))
else:
return Dropdown(options=list(o))
| (o) | [
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15,892 | ipywidgets.widgets.interaction | widget_from_single_value | Make widgets from single values, which can be used as parameter defaults. | @staticmethod
def widget_from_single_value(o):
"""Make widgets from single values, which can be used as parameter defaults."""
if isinstance(o, str):
return Text(value=str(o))
elif isinstance(o, bool):
return Checkbox(value=o)
elif isinstance(o, Integral):
min, max, value = _get_min_max_value(None, None, o)
return IntSlider(value=o, min=min, max=max)
elif isinstance(o, Real):
min, max, value = _get_min_max_value(None, None, o)
return FloatSlider(value=o, min=min, max=max)
else:
return None
| (o) | [
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15,893 | ipywidgets.widgets.interaction | widget_from_tuple | Make widgets from a tuple abbreviation. | @staticmethod
def widget_from_tuple(o):
"""Make widgets from a tuple abbreviation."""
if _matches(o, (Real, Real)):
min, max, value = _get_min_max_value(o[0], o[1])
if all(isinstance(_, Integral) for _ in o):
cls = IntSlider
else:
cls = FloatSlider
return cls(value=value, min=min, max=max)
elif _matches(o, (Real, Real, Real)):
step = o[2]
if step <= 0:
raise ValueError("step must be >= 0, not %r" % step)
min, max, value = _get_min_max_value(o[0], o[1], step=step)
if all(isinstance(_, Integral) for _ in o):
cls = IntSlider
else:
cls = FloatSlider
return cls(value=value, min=min, max=max, step=step)
| (o) | [
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15,894 | ipywidgets.widgets.interaction | widgets_from_abbreviations | Given a sequence of (name, abbrev, default) tuples, return a sequence of Widgets. | def widgets_from_abbreviations(self, seq):
"""Given a sequence of (name, abbrev, default) tuples, return a sequence of Widgets."""
result = []
for name, abbrev, default in seq:
if isinstance(abbrev, Widget) and (not isinstance(abbrev, ValueWidget)):
raise TypeError("{!r} is not a ValueWidget".format(abbrev))
widget = self.widget_from_abbrev(abbrev, default)
if widget is None:
raise ValueError("{!r} cannot be transformed to a widget".format(abbrev))
if not hasattr(widget, "description") or not widget.description:
widget.description = name
widget._kwarg = name
result.append(widget)
return result
| (self, seq) | [
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] |
15,897 | traitlets.traitlets | link | Link traits from different objects together so they remain in sync.
Parameters
----------
source : (object / attribute name) pair
target : (object / attribute name) pair
transform: iterable with two callables (optional)
Data transformation between source and target and target and source.
Examples
--------
>>> class X(HasTraits):
... value = Int()
>>> src = X(value=1)
>>> tgt = X(value=42)
>>> c = link((src, "value"), (tgt, "value"))
Setting source updates target objects:
>>> src.value = 5
>>> tgt.value
5
| class link:
"""Link traits from different objects together so they remain in sync.
Parameters
----------
source : (object / attribute name) pair
target : (object / attribute name) pair
transform: iterable with two callables (optional)
Data transformation between source and target and target and source.
Examples
--------
>>> class X(HasTraits):
... value = Int()
>>> src = X(value=1)
>>> tgt = X(value=42)
>>> c = link((src, "value"), (tgt, "value"))
Setting source updates target objects:
>>> src.value = 5
>>> tgt.value
5
"""
updating = False
def __init__(self, source: t.Any, target: t.Any, transform: t.Any = None) -> None:
_validate_link(source, target)
self.source, self.target = source, target
self._transform, self._transform_inv = transform if transform else (lambda x: x,) * 2
self.link()
def link(self) -> None:
try:
setattr(
self.target[0],
self.target[1],
self._transform(getattr(self.source[0], self.source[1])),
)
finally:
self.source[0].observe(self._update_target, names=self.source[1])
self.target[0].observe(self._update_source, names=self.target[1])
@contextlib.contextmanager
def _busy_updating(self) -> t.Any:
self.updating = True
try:
yield
finally:
self.updating = False
def _update_target(self, change: t.Any) -> None:
if self.updating:
return
with self._busy_updating():
setattr(self.target[0], self.target[1], self._transform(change.new))
if getattr(self.source[0], self.source[1]) != change.new:
raise TraitError(
f"Broken link {self}: the source value changed while updating " "the target."
)
def _update_source(self, change: t.Any) -> None:
if self.updating:
return
with self._busy_updating():
setattr(self.source[0], self.source[1], self._transform_inv(change.new))
if getattr(self.target[0], self.target[1]) != change.new:
raise TraitError(
f"Broken link {self}: the target value changed while updating " "the source."
)
def unlink(self) -> None:
self.source[0].unobserve(self._update_target, names=self.source[1])
self.target[0].unobserve(self._update_source, names=self.target[1])
| (source: 't.Any', target: 't.Any', transform: 't.Any' = None) -> 'None' | [
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15,898 | traitlets.traitlets | __init__ | null | def __init__(self, source: t.Any, target: t.Any, transform: t.Any = None) -> None:
_validate_link(source, target)
self.source, self.target = source, target
self._transform, self._transform_inv = transform if transform else (lambda x: x,) * 2
self.link()
| (self, source: Any, target: Any, transform: Optional[Any] = None) -> NoneType | [
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15,899 | traitlets.traitlets | _busy_updating | null | def _validate_link(*tuples: t.Any) -> None:
"""Validate arguments for traitlet link functions"""
for tup in tuples:
if not len(tup) == 2:
raise TypeError(
"Each linked traitlet must be specified as (HasTraits, 'trait_name'), not %r" % t
)
obj, trait_name = tup
if not isinstance(obj, HasTraits):
raise TypeError("Each object must be HasTraits, not %r" % type(obj))
if trait_name not in obj.traits():
raise TypeError(f"{obj!r} has no trait {trait_name!r}")
| (self) -> Any | [
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15,900 | traitlets.traitlets | _update_source | null | def _update_source(self, change: t.Any) -> None:
if self.updating:
return
with self._busy_updating():
setattr(self.source[0], self.source[1], self._transform_inv(change.new))
if getattr(self.target[0], self.target[1]) != change.new:
raise TraitError(
f"Broken link {self}: the target value changed while updating " "the source."
)
| (self, change: Any) -> NoneType | [
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15,901 | traitlets.traitlets | _update_target | null | def _update_target(self, change: t.Any) -> None:
if self.updating:
return
with self._busy_updating():
setattr(self.target[0], self.target[1], self._transform(change.new))
if getattr(self.source[0], self.source[1]) != change.new:
raise TraitError(
f"Broken link {self}: the source value changed while updating " "the target."
)
| (self, change: Any) -> NoneType | [
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] |
15,902 | traitlets.traitlets | link | null | def link(self) -> None:
try:
setattr(
self.target[0],
self.target[1],
self._transform(getattr(self.source[0], self.source[1])),
)
finally:
self.source[0].observe(self._update_target, names=self.source[1])
self.target[0].observe(self._update_source, names=self.target[1])
| (self) -> NoneType | [
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15,903 | traitlets.traitlets | unlink | null | def unlink(self) -> None:
self.source[0].unobserve(self._update_target, names=self.source[1])
self.target[0].unobserve(self._update_source, names=self.target[1])
| (self) -> NoneType | [
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15,904 | traitlets.traitlets | observe | A decorator which can be used to observe Traits on a class.
The handler passed to the decorator will be called with one ``change``
dict argument. The change dictionary at least holds a 'type' key and a
'name' key, corresponding respectively to the type of notification and the
name of the attribute that triggered the notification.
Other keys may be passed depending on the value of 'type'. In the case
where type is 'change', we also have the following keys:
* ``owner`` : the HasTraits instance
* ``old`` : the old value of the modified trait attribute
* ``new`` : the new value of the modified trait attribute
* ``name`` : the name of the modified trait attribute.
Parameters
----------
*names
The str names of the Traits to observe on the object.
type : str, kwarg-only
The type of event to observe (e.g. 'change')
| def observe(*names: Sentinel | str, type: str = "change") -> ObserveHandler:
"""A decorator which can be used to observe Traits on a class.
The handler passed to the decorator will be called with one ``change``
dict argument. The change dictionary at least holds a 'type' key and a
'name' key, corresponding respectively to the type of notification and the
name of the attribute that triggered the notification.
Other keys may be passed depending on the value of 'type'. In the case
where type is 'change', we also have the following keys:
* ``owner`` : the HasTraits instance
* ``old`` : the old value of the modified trait attribute
* ``new`` : the new value of the modified trait attribute
* ``name`` : the name of the modified trait attribute.
Parameters
----------
*names
The str names of the Traits to observe on the object.
type : str, kwarg-only
The type of event to observe (e.g. 'change')
"""
if not names:
raise TypeError("Please specify at least one trait name to observe.")
for name in names:
if name is not All and not isinstance(name, str):
raise TypeError("trait names to observe must be strings or All, not %r" % name)
return ObserveHandler(names, type=type)
| (*names: traitlets.utils.sentinel.Sentinel | str, type: str = 'change') -> traitlets.traitlets.ObserveHandler | [
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15,907 | traitlets.traitlets | validate | A decorator to register cross validator of HasTraits object's state
when a Trait is set.
The handler passed to the decorator must have one ``proposal`` dict argument.
The proposal dictionary must hold the following keys:
* ``owner`` : the HasTraits instance
* ``value`` : the proposed value for the modified trait attribute
* ``trait`` : the TraitType instance associated with the attribute
Parameters
----------
*names
The str names of the Traits to validate.
Notes
-----
Since the owner has access to the ``HasTraits`` instance via the 'owner' key,
the registered cross validator could potentially make changes to attributes
of the ``HasTraits`` instance. However, we recommend not to do so. The reason
is that the cross-validation of attributes may run in arbitrary order when
exiting the ``hold_trait_notifications`` context, and such changes may not
commute.
| def validate(*names: Sentinel | str) -> ValidateHandler:
"""A decorator to register cross validator of HasTraits object's state
when a Trait is set.
The handler passed to the decorator must have one ``proposal`` dict argument.
The proposal dictionary must hold the following keys:
* ``owner`` : the HasTraits instance
* ``value`` : the proposed value for the modified trait attribute
* ``trait`` : the TraitType instance associated with the attribute
Parameters
----------
*names
The str names of the Traits to validate.
Notes
-----
Since the owner has access to the ``HasTraits`` instance via the 'owner' key,
the registered cross validator could potentially make changes to attributes
of the ``HasTraits`` instance. However, we recommend not to do so. The reason
is that the cross-validation of attributes may run in arbitrary order when
exiting the ``hold_trait_notifications`` context, and such changes may not
commute.
"""
if not names:
raise TypeError("Please specify at least one trait name to validate.")
for name in names:
if name is not All and not isinstance(name, str):
raise TypeError("trait names to validate must be strings or All, not %r" % name)
return ValidateHandler(names)
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15,908 | ipyleaflet.leaflet | wait_for_change | null | def wait_for_change(widget, value):
future = asyncio.Future()
def get_value(change):
future.set_result(change.new)
widget.unobserve(get_value, value)
widget.observe(get_value, value)
return future
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15,911 | hypothesis.core | given | A decorator for turning a test function that accepts arguments into a
randomized test.
This is the main entry point to Hypothesis.
| def given(
*_given_arguments: Union[SearchStrategy[Any], EllipsisType],
**_given_kwargs: Union[SearchStrategy[Any], EllipsisType],
) -> Callable[
[Callable[..., Optional[Coroutine[Any, Any, None]]]], Callable[..., None]
]:
"""A decorator for turning a test function that accepts arguments into a
randomized test.
This is the main entry point to Hypothesis.
"""
def run_test_as_given(test):
if inspect.isclass(test):
# Provide a meaningful error to users, instead of exceptions from
# internals that assume we're dealing with a function.
raise InvalidArgument("@given cannot be applied to a class.")
given_arguments = tuple(_given_arguments)
given_kwargs = dict(_given_kwargs)
original_sig = get_signature(test)
if given_arguments == (Ellipsis,) and not given_kwargs:
# user indicated that they want to infer all arguments
given_kwargs = {
p.name: Ellipsis
for p in original_sig.parameters.values()
if p.kind in (p.POSITIONAL_OR_KEYWORD, p.KEYWORD_ONLY)
}
given_arguments = ()
check_invalid = is_invalid_test(
test, original_sig, given_arguments, given_kwargs
)
# If the argument check found problems, return a dummy test function
# that will raise an error if it is actually called.
if check_invalid is not None:
return check_invalid
# Because the argument check succeeded, we can convert @given's
# positional arguments into keyword arguments for simplicity.
if given_arguments:
assert not given_kwargs
posargs = [
p.name
for p in original_sig.parameters.values()
if p.kind is p.POSITIONAL_OR_KEYWORD
]
given_kwargs = dict(list(zip(posargs[::-1], given_arguments[::-1]))[::-1])
# These have been converted, so delete them to prevent accidental use.
del given_arguments
new_signature = new_given_signature(original_sig, given_kwargs)
# Use type information to convert "infer" arguments into appropriate strategies.
if ... in given_kwargs.values():
hints = get_type_hints(test)
for name in [name for name, value in given_kwargs.items() if value is ...]:
if name not in hints:
return _invalid(
f"passed {name}=... for {test.__name__}, but {name} has "
"no type annotation",
test=test,
given_kwargs=given_kwargs,
)
given_kwargs[name] = st.from_type(hints[name])
prev_self = Unset = object()
@impersonate(test)
@define_function_signature(test.__name__, test.__doc__, new_signature)
def wrapped_test(*arguments, **kwargs):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
test = wrapped_test.hypothesis.inner_test
if getattr(test, "is_hypothesis_test", False):
raise InvalidArgument(
f"You have applied @given to the test {test.__name__} more than "
"once, which wraps the test several times and is extremely slow. "
"A similar effect can be gained by combining the arguments "
"of the two calls to given. For example, instead of "
"@given(booleans()) @given(integers()), you could write "
"@given(booleans(), integers())"
)
settings = wrapped_test._hypothesis_internal_use_settings
random = get_random_for_wrapped_test(test, wrapped_test)
arguments, kwargs, stuff = process_arguments_to_given(
wrapped_test, arguments, kwargs, given_kwargs, new_signature.parameters
)
if (
inspect.iscoroutinefunction(test)
and get_executor(stuff.selfy) is default_executor
):
# See https://github.com/HypothesisWorks/hypothesis/issues/3054
# If our custom executor doesn't handle coroutines, or we return an
# awaitable from a non-async-def function, we just rely on the
# return_value health check. This catches most user errors though.
raise InvalidArgument(
"Hypothesis doesn't know how to run async test functions like "
f"{test.__name__}. You'll need to write a custom executor, "
"or use a library like pytest-asyncio or pytest-trio which can "
"handle the translation for you.\n See https://hypothesis."
"readthedocs.io/en/latest/details.html#custom-function-execution"
)
runner = stuff.selfy
if isinstance(stuff.selfy, TestCase) and test.__name__ in dir(TestCase):
msg = (
f"You have applied @given to the method {test.__name__}, which is "
"used by the unittest runner but is not itself a test."
" This is not useful in any way."
)
fail_health_check(settings, msg, HealthCheck.not_a_test_method)
if bad_django_TestCase(runner): # pragma: no cover
# Covered by the Django tests, but not the pytest coverage task
raise InvalidArgument(
"You have applied @given to a method on "
f"{type(runner).__qualname__}, but this "
"class does not inherit from the supported versions in "
"`hypothesis.extra.django`. Use the Hypothesis variants "
"to ensure that each example is run in a separate "
"database transaction."
)
if settings.database is not None:
nonlocal prev_self
# Check selfy really is self (not e.g. a mock) before we health-check
cur_self = (
stuff.selfy
if getattr(type(stuff.selfy), test.__name__, None) is wrapped_test
else None
)
if prev_self is Unset:
prev_self = cur_self
elif cur_self is not prev_self:
msg = (
f"The method {test.__qualname__} was called from multiple "
"different executors. This may lead to flaky tests and "
"nonreproducible errors when replaying from database."
)
fail_health_check(settings, msg, HealthCheck.differing_executors)
state = StateForActualGivenExecution(
stuff, test, settings, random, wrapped_test
)
reproduce_failure = wrapped_test._hypothesis_internal_use_reproduce_failure
# If there was a @reproduce_failure decorator, use it to reproduce
# the error (or complain that we couldn't). Either way, this will
# always raise some kind of error.
if reproduce_failure is not None:
expected_version, failure = reproduce_failure
if expected_version != __version__:
raise InvalidArgument(
"Attempting to reproduce a failure from a different "
"version of Hypothesis. This failure is from %s, but "
"you are currently running %r. Please change your "
"Hypothesis version to a matching one."
% (expected_version, __version__)
)
try:
state.execute_once(
ConjectureData.for_buffer(decode_failure(failure)),
print_example=True,
is_final=True,
)
raise DidNotReproduce(
"Exp | (*_given_arguments: Union[hypothesis.strategies.SearchStrategy[Any], ellipsis], **_given_kwargs: Union[hypothesis.strategies.SearchStrategy[Any], ellipsis]) -> Callable[[Callable[..., Optional[Coroutine[Any, Any, NoneType]]]], Callable[..., NoneType]] | [
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15,912 | d8s_hypothesis.hypothesis_wrapper | hypothesis_get_strategy_results | Return the given n of results from the given hypothesis strategy.
For a list of hypothesis strategies, see: https://hypothesis.readthedocs.io/en/latest/data.html.
| def hypothesis_get_strategy_results(strategy, *args, n: int = 10, **kwargs):
"""Return the given n of results from the given hypothesis strategy.
For a list of hypothesis strategies, see: https://hypothesis.readthedocs.io/en/latest/data.html.
"""
class A: # pylint: disable=R0903
def __init__(self):
self.l = [] # noqa:E741
@given(strategy(*args))
@settings(max_examples=n, **kwargs)
def a(self, value):
"""."""
self.l.append(value)
obj = A()
obj.a() # pylint: disable=E1120
return obj.l
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15,914 | hypothesis | settings | A settings object configures options including verbosity, runtime controls,
persistence, determinism, and more.
Default values are picked up from the settings.default object and
changes made there will be picked up in newly created settings.
| from hypothesis import settings
| (parent: Optional[ForwardRef('settings')] = None, *, max_examples: int = not_set, derandomize: bool = not_set, database: Optional[ForwardRef('ExampleDatabase')] = not_set, verbosity: 'Verbosity' = not_set, phases: Collection[ForwardRef('Phase')] = not_set, stateful_step_count: int = not_set, report_multiple_bugs: bool = not_set, suppress_health_check: Collection[ForwardRef('HealthCheck')] = not_set, deadline: Union[int, float, datetime.timedelta, NoneType] = not_set, print_blob: bool = not_set, backend: str = not_set) -> None | [
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] |
15,915 | hypothesis._settings | __call__ | Make the settings object (self) an attribute of the test.
The settings are later discovered by looking them up on the test itself.
| def __call__(self, test: T) -> T:
"""Make the settings object (self) an attribute of the test.
The settings are later discovered by looking them up on the test itself.
"""
# Aliasing as Any avoids mypy errors (attr-defined) when accessing and
# setting custom attributes on the decorated function or class.
_test: Any = test
# Using the alias here avoids a mypy error (return-value) later when
# ``test`` is returned, because this check results in type refinement.
if not callable(_test):
raise InvalidArgument(
"settings objects can be called as a decorator with @given, "
f"but decorated {test=} is not callable."
)
if inspect.isclass(test):
from hypothesis.stateful import RuleBasedStateMachine
if issubclass(_test, RuleBasedStateMachine):
attr_name = "_hypothesis_internal_settings_applied"
if getattr(test, attr_name, False):
raise InvalidArgument(
"Applying the @settings decorator twice would "
"overwrite the first version; merge their arguments "
"instead."
)
setattr(test, attr_name, True)
_test.TestCase.settings = self
return test # type: ignore
else:
raise InvalidArgument(
"@settings(...) can only be used as a decorator on "
"functions, or on subclasses of RuleBasedStateMachine."
)
if hasattr(_test, "_hypothesis_internal_settings_applied"):
# Can't use _hypothesis_internal_use_settings as an indicator that
# @settings was applied, because @given also assigns that attribute.
descr = get_pretty_function_description(test)
raise InvalidArgument(
f"{descr} has already been decorated with a settings object.\n"
f" Previous: {_test._hypothesis_internal_use_settings!r}\n"
f" This: {self!r}"
)
_test._hypothesis_internal_use_settings = self
_test._hypothesis_internal_settings_applied = True
return test
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15,916 | hypothesis._settings | __getattr__ | null | def __getattr__(self, name):
if name in all_settings:
return all_settings[name].default
else:
raise AttributeError(f"settings has no attribute {name}")
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] |
15,917 | hypothesis._settings | __init__ | null | def __init__(
self,
parent: Optional["settings"] = None,
*,
# This looks pretty strange, but there's good reason: we want Mypy to detect
# bad calls downstream, but not to freak out about the `= not_set` part even
# though it's not semantically valid to pass that as an argument value.
# The intended use is "like **kwargs, but more tractable for tooling".
max_examples: int = not_set, # type: ignore
derandomize: bool = not_set, # type: ignore
database: Optional["ExampleDatabase"] = not_set, # type: ignore
verbosity: "Verbosity" = not_set, # type: ignore
phases: Collection["Phase"] = not_set, # type: ignore
stateful_step_count: int = not_set, # type: ignore
report_multiple_bugs: bool = not_set, # type: ignore
suppress_health_check: Collection["HealthCheck"] = not_set, # type: ignore
deadline: Union[int, float, datetime.timedelta, None] = not_set, # type: ignore
print_blob: bool = not_set, # type: ignore
backend: str = not_set, # type: ignore
) -> None:
if parent is not None:
check_type(settings, parent, "parent")
if derandomize not in (not_set, False):
if database not in (not_set, None): # type: ignore
raise InvalidArgument(
"derandomize=True implies database=None, so passing "
f"{database=} too is invalid."
)
database = None
defaults = parent or settings.default
if defaults is not None:
for setting in all_settings.values():
value = locals()[setting.name]
if value is not_set:
object.__setattr__(
self, setting.name, getattr(defaults, setting.name)
)
else:
object.__setattr__(self, setting.name, setting.validator(value))
| (self, parent: Optional[ForwardRef('settings')] = None, *, max_examples: int = not_set, derandomize: bool = not_set, database: Optional[ForwardRef('ExampleDatabase')] = not_set, verbosity: 'Verbosity' = not_set, phases: Collection[ForwardRef('Phase')] = not_set, stateful_step_count: int = not_set, report_multiple_bugs: bool = not_set, suppress_health_check: Collection[ForwardRef('HealthCheck')] = not_set, deadline: Union[int, float, datetime.timedelta, NoneType] = not_set, print_blob: bool = not_set, backend: str = not_set) -> None | [
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15,918 | hypothesis._settings | __repr__ | null | def __repr__(self):
from hypothesis.internal.conjecture.data import AVAILABLE_PROVIDERS
bits = sorted(
f"{name}={getattr(self, name)!r}"
for name in all_settings
if (name != "backend" or len(AVAILABLE_PROVIDERS) > 1) # experimental
)
return "settings({})".format(", ".join(bits))
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15,919 | hypothesis._settings | __setattr__ | null | def __setattr__(self, name, value):
raise AttributeError("settings objects are immutable")
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15,920 | hypothesis._settings | get_profile | Return the profile with the given name. | @staticmethod
def get_profile(name: str) -> "settings":
"""Return the profile with the given name."""
check_type(str, name, "name")
try:
return settings._profiles[name]
except KeyError:
raise InvalidArgument(f"Profile {name!r} is not registered") from None
| (name: str) -> hypothesis.settings | [
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] |
15,921 | hypothesis._settings | load_profile | Loads in the settings defined in the profile provided.
If the profile does not exist, InvalidArgument will be raised.
Any setting not defined in the profile will be the library
defined default for that setting.
| @staticmethod
def load_profile(name: str) -> None:
"""Loads in the settings defined in the profile provided.
If the profile does not exist, InvalidArgument will be raised.
Any setting not defined in the profile will be the library
defined default for that setting.
"""
check_type(str, name, "name")
settings._current_profile = name
settings._assign_default_internal(settings.get_profile(name))
| (name: str) -> NoneType | [
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] |
15,922 | hypothesis._settings | register_profile | Registers a collection of values to be used as a settings profile.
Settings profiles can be loaded by name - for example, you might
create a 'fast' profile which runs fewer examples, keep the 'default'
profile, and create a 'ci' profile that increases the number of
examples and uses a different database to store failures.
The arguments to this method are exactly as for
:class:`~hypothesis.settings`: optional ``parent`` settings, and
keyword arguments for each setting that will be set differently to
parent (or settings.default, if parent is None).
| @staticmethod
def register_profile(
name: str,
parent: Optional["settings"] = None,
**kwargs: Any,
) -> None:
"""Registers a collection of values to be used as a settings profile.
Settings profiles can be loaded by name - for example, you might
create a 'fast' profile which runs fewer examples, keep the 'default'
profile, and create a 'ci' profile that increases the number of
examples and uses a different database to store failures.
The arguments to this method are exactly as for
:class:`~hypothesis.settings`: optional ``parent`` settings, and
keyword arguments for each setting that will be set differently to
parent (or settings.default, if parent is None).
"""
check_type(str, name, "name")
settings._profiles[name] = settings(parent=parent, **kwargs)
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15,923 | hypothesis._settings | show_changed | null | def show_changed(self):
bits = []
for name, setting in all_settings.items():
value = getattr(self, name)
if value != setting.default:
bits.append(f"{name}={value!r}")
return ", ".join(sorted(bits, key=len))
| (self) | [
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] |
15,927 | netapp_ontap.host_connection | HostConnection | The HostConnection allows the client application to store their credentials
and reuse them for each operation. There are three ways to use a connection
object:
* The first is to use the connection object as a context manager. Any operations
on a resource that are called within the scope of the block will use that
connection.
* The second is to call set_connection() on a resource object. This
will then be the connection used for all actions for that object only.
* The third way is to call netapp_ontap.config.CONNECTION = connection. This
connection instance will now be used for all actions on all resource
objects (that do not otherwise set their own connection). This reduces
the need to pass the connection around the application.
Connections will be searched for in this order when executing an action.
| class HostConnection: # pylint: disable=too-many-instance-attributes
"""The HostConnection allows the client application to store their credentials
and reuse them for each operation. There are three ways to use a connection
object:
* The first is to use the connection object as a context manager. Any operations
on a resource that are called within the scope of the block will use that
connection.
* The second is to call set_connection() on a resource object. This
will then be the connection used for all actions for that object only.
* The third way is to call netapp_ontap.config.CONNECTION = connection. This
connection instance will now be used for all actions on all resource
objects (that do not otherwise set their own connection). This reduces
the need to pass the connection around the application.
Connections will be searched for in this order when executing an action.
"""
# pylint: disable=bad-continuation,too-many-arguments
def __init__(
self,
host,
username: str = None,
password: str = None,
cert: str = None,
key: str = None,
verify: bool = True,
poll_timeout: int = 30,
poll_interval: int = 5,
headers: dict = None,
port: int = 443,
):
"""Store information needed to contact the API host
Either username and password must be provided or certificate and key must
be provided or the 'Authorization' must be provided in the headers.
If verify is set to False, urllib3's InsecureRequestWarnings will also be
silenced in the logs.
Args:
host: The API host that the library should talk to
username: The user identifier known to the host
password: The secret for the user
cert: The file path to the users public certificate. The common
name in the certificate must match the account name.
key: A private key in PEM format
verify: If an SSL connection is made to the host, this parameter
controls how the validity of the trust chain of the certificate
is handled. See the documentation for the requests library for more information:
https://2.python-requests.org/en/master/user/advanced/#ssl-cert-verification
poll_timeout: Time in seconds to poll on a job. This setting applies to all polling
that uses this connection unless overridden as a parameter to poll(). Defaults
to 30 seconds.
poll_interval: Time in seconds to wait between polls on a job. This setting applies
to all polling that uses this connection unless overridden as a parameter to
poll(). Defaults to 5 seconds.
headers: Any custom headers to be passed to each request using this connection object.
port: The port that the library should talk to
"""
authentication_methods = 0
if username and password is not None:
authentication_methods += 1
if cert and key:
authentication_methods += 1
elif headers and 'Authorization' in headers:
authentication_methods += 1
if authentication_methods != 1:
from netapp_ontap.error import NetAppRestError # pylint: disable=cyclic-import
raise NetAppRestError(
"There must be only one authentication method provided. The following four"
" methods are the only types of authentication methods currently accepted."
" 1. Username and password. 2. Cert and key. 3. An 'Authorization' header."
" 4. An 'Authorization' header and a cert and key"
)
self.scheme = "https"
self.host = host
self.port = port
self.username = username
self.password = password
self.cert = cert
self.key = key
self.verify = verify
self.poll_timeout = poll_timeout
self.poll_interval = poll_interval
self.headers = headers
self.protocol_timeouts = None
self._old_context = None # type: Optional[HostConnection]
self._request_session = None # type: Optional[requests.Session]
if not self.verify:
import urllib3 # type: ignore
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
@staticmethod
def get_host_context() -> "Optional[HostConnection]":
"""Get the current host context, if any.
Returns:
A HostConnection object or None if not in a host connection context.
"""
return _HOST_CONTEXT
@property
def basic_auth(self) -> Optional[Tuple[str, str]]:
"""Pulls the credentials out of the connection object.
Returns:
A tuple of username and password sufficient for passing to the requests library. Returns None if this connection is not configured for basic auth with a username and password.
"""
if self.username and self.password is not None:
return (self.username, self.password)
return None
@property
def cert_auth(self) -> Optional[Tuple[str, str]]:
"""Pulls the certificate details out of the connection object.
Returns:
A tuple of cert and key sufficient for passing to the requests library. Returns None if this connection is not configured for cert auth with a cert and key.
"""
if self.cert and self.key:
return (self.cert, self.key)
return None
@property
def bearer_auth(self) -> Optional[Tuple[str, str]]:
"""Pulls the header name and token out of the connection object.
Returns:
A tuple of the header name and token for passing to the requests library. Returns None if this connection is not configured for oauth2 yet
"""
if not self.headers or self.headers.get('Authorization', '').split()[0] != 'Bearer':
return None
# Right now NetApp only supports 3 IDP (keycloak, auth0, adfs) which all use the JWT format
# The following code checks to make sure that the token generally follows the JWT format before returning the tuple
# The steps are taken from https://www.rfc-editor.org/rfc/rfc7519#section-7.2
token = self.headers['Authorization'].split()[1]
#1 Verify that the JWT contains at least one period ('.') character.
if '.' not in token:
return None
#2 Let the Encoded JOSE Header be the portion of the JWT before the first period ('.') character.
header = token.split(".")[0]
message = token.split(".")[1]
#3~9 Base64url decode the Encoded JOSE Header and Message following the restriction that no line breaks, whitespace, or other additional characters have been used.
if ' ' in header or '\n' in header or ' ' in message or '\n' in message:
return None
try:
for b64 in (header, message):
b64 += "=" * ((4 - len(b64) % 4) % 4) #add padding as required to properly encode and decode with base64
if base64.b64encode(base64.b64decode(b64)) != bytes(b64, "utf-8"):
return None
except (ValueError, TypeError, binascii.Error):
return None
# Success! The our tuple is most likely a valid JWT
return (self.headers['Authorization'].split()[0], self.headers['Authorization'].split()[1])
@property
def origin(self) -> str:
"""The beginning of any REST endpoint.
Returns:
The origin part of the URL. For example, `http://1.2.3.4:8080`.
"""
return f"{self.scheme}://{self.host}:{self.port}"
@property
def request_headers(self) -> Optional[dict]:
"""Retrieves the headers set out of the connection object
Returns:
A dictionary consisting of header names and values for passing to the requests library. Returns None if no headers are configured.
"""
if self.headers:
| (host, username: str = None, password: str = None, cert: str = None, key: str = None, verify: bool = True, poll_timeout: int = 30, poll_interval: int = 5, headers: dict = None, port: int = 443) | [
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15,928 | netapp_ontap.host_connection | __enter__ | null | def __enter__(self):
global _HOST_CONTEXT # pylint: disable=global-statement
self._old_context = _HOST_CONTEXT
_HOST_CONTEXT = self
return self
| (self) | [
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15,929 | netapp_ontap.host_connection | __exit__ | null | def __exit__(self, exception_type, exception_value, traceback):
global _HOST_CONTEXT # pylint: disable=global-statement
_HOST_CONTEXT = self._old_context
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15,930 | netapp_ontap.host_connection | __init__ | Store information needed to contact the API host
Either username and password must be provided or certificate and key must
be provided or the 'Authorization' must be provided in the headers.
If verify is set to False, urllib3's InsecureRequestWarnings will also be
silenced in the logs.
Args:
host: The API host that the library should talk to
username: The user identifier known to the host
password: The secret for the user
cert: The file path to the users public certificate. The common
name in the certificate must match the account name.
key: A private key in PEM format
verify: If an SSL connection is made to the host, this parameter
controls how the validity of the trust chain of the certificate
is handled. See the documentation for the requests library for more information:
https://2.python-requests.org/en/master/user/advanced/#ssl-cert-verification
poll_timeout: Time in seconds to poll on a job. This setting applies to all polling
that uses this connection unless overridden as a parameter to poll(). Defaults
to 30 seconds.
poll_interval: Time in seconds to wait between polls on a job. This setting applies
to all polling that uses this connection unless overridden as a parameter to
poll(). Defaults to 5 seconds.
headers: Any custom headers to be passed to each request using this connection object.
port: The port that the library should talk to
| def __init__(
self,
host,
username: str = None,
password: str = None,
cert: str = None,
key: str = None,
verify: bool = True,
poll_timeout: int = 30,
poll_interval: int = 5,
headers: dict = None,
port: int = 443,
):
"""Store information needed to contact the API host
Either username and password must be provided or certificate and key must
be provided or the 'Authorization' must be provided in the headers.
If verify is set to False, urllib3's InsecureRequestWarnings will also be
silenced in the logs.
Args:
host: The API host that the library should talk to
username: The user identifier known to the host
password: The secret for the user
cert: The file path to the users public certificate. The common
name in the certificate must match the account name.
key: A private key in PEM format
verify: If an SSL connection is made to the host, this parameter
controls how the validity of the trust chain of the certificate
is handled. See the documentation for the requests library for more information:
https://2.python-requests.org/en/master/user/advanced/#ssl-cert-verification
poll_timeout: Time in seconds to poll on a job. This setting applies to all polling
that uses this connection unless overridden as a parameter to poll(). Defaults
to 30 seconds.
poll_interval: Time in seconds to wait between polls on a job. This setting applies
to all polling that uses this connection unless overridden as a parameter to
poll(). Defaults to 5 seconds.
headers: Any custom headers to be passed to each request using this connection object.
port: The port that the library should talk to
"""
authentication_methods = 0
if username and password is not None:
authentication_methods += 1
if cert and key:
authentication_methods += 1
elif headers and 'Authorization' in headers:
authentication_methods += 1
if authentication_methods != 1:
from netapp_ontap.error import NetAppRestError # pylint: disable=cyclic-import
raise NetAppRestError(
"There must be only one authentication method provided. The following four"
" methods are the only types of authentication methods currently accepted."
" 1. Username and password. 2. Cert and key. 3. An 'Authorization' header."
" 4. An 'Authorization' header and a cert and key"
)
self.scheme = "https"
self.host = host
self.port = port
self.username = username
self.password = password
self.cert = cert
self.key = key
self.verify = verify
self.poll_timeout = poll_timeout
self.poll_interval = poll_interval
self.headers = headers
self.protocol_timeouts = None
self._old_context = None # type: Optional[HostConnection]
self._request_session = None # type: Optional[requests.Session]
if not self.verify:
import urllib3 # type: ignore
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
| (self, host, username: Optional[str] = None, password: Optional[str] = None, cert: Optional[str] = None, key: Optional[str] = None, verify: bool = True, poll_timeout: int = 30, poll_interval: int = 5, headers: Optional[dict] = None, port: int = 443) | [
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15,931 | netapp_ontap.host_connection | get_host_context | Get the current host context, if any.
Returns:
A HostConnection object or None if not in a host connection context.
| @staticmethod
def get_host_context() -> "Optional[HostConnection]":
"""Get the current host context, if any.
Returns:
A HostConnection object or None if not in a host connection context.
"""
return _HOST_CONTEXT
| () -> Optional[netapp_ontap.host_connection.HostConnection] | [
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] |
15,932 | netapp_ontap.host_connection | with_headers | Manually set the headers field of the connection object | @property
def session(self) -> requests.Session:
"""A `requests.Session` object which is used for all API calls.
This session is reused for each API call made with this connection. Multiple
requests may therefore be sent through the same TCP connection assuming
the host supports keep-alive.
Returns:
A `requests.Session` object which is used for all API calls.
"""
current_session = getattr(self, "_request_session", None)
if not current_session:
current_session = WrappedSession()
if self.origin not in current_session.adapters:
from netapp_ontap import config
if config.RETRY_API_ON_ERROR:
retry_strategy = LoggingRetry(
total=config.RETRY_API_ATTEMPTS,
status_forcelist=config.RETRY_API_ERROR_CODES,
allowed_methods=config.RETRY_API_HTTP_METHODS,
backoff_factor=config.RETRY_API_BACKOFF_FACTOR,
)
else:
retry_strategy = LoggingRetry.from_int(5)
current_session.mount(
self.origin,
LoggingAdapter(self, max_retries=retry_strategy, timeout=self.protocol_timeouts)
)
if self.basic_auth:
current_session.auth = self.basic_auth
else:
current_session.cert = self.cert_auth
if self.request_headers:
current_session.headers.update(self.request_headers)
current_session.verify = self.verify
import netapp_ontap # pylint: disable=cyclic-import
current_session.headers.update(
{"X-Dot-Client-App": f"netapp-ontap-python-{netapp_ontap.__version__}"}
)
self._request_session = current_session
return current_session
| (self, headers: dict) -> Generator[netapp_ontap.host_connection.HostConnection, NoneType, NoneType] | [
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] |
15,933 | netapp_ontap.response | NetAppResponse | Contains the HTTP response received by a client from a server
for a specific action. The object allows all responses to be examined
in a consistent way. For example, is this an error or is an ongoing job?
| class NetAppResponse:
"""Contains the HTTP response received by a client from a server
for a specific action. The object allows all responses to be examined
in a consistent way. For example, is this an error or is an ongoing job?
"""
def __init__(self, http_response: requests.Response, connection: HostConnection = None) -> None:
"""Create and initialize a NetAppResponse object based on the result of an API call.
Args:
http_response: The API response to wrap
"""
self.http_response = http_response
self.connection = connection
@property
def is_job(self) -> bool:
"""Examine to determine if the response is a job.
Returns:
True if the HTTP status code returned was 202, else it will return False.
"""
try:
job_link = self.http_response.json()["job"]["_links"]["self"]["href"]
return job_link is not None
except: # pylint: disable=bare-except
return False
@property
def is_err(self) -> bool:
"""Examine to determine if the response is an error.
Returns:
True if the HTTP status code was 400 or greater, else it will return False.
"""
return self.http_response.status_code > 399
def poll(
self, connection: HostConnection = None, timeout: int = None, interval: int = None
) -> "NetAppResponse":
"""Wait for the job associated with the response to complete.
Calls 'utils.poll' with the response object and blocks until the job
completes (that is reaches a terminal state).
Args:
connection: The host containing the job to connect to.
timeout: Seconds to wait before timing out of a poll request. If set,
the value overrides the timeout set in connection. Otherwise, the
timeout set in the connection is used.
interval: Seconds to wait between making REST API calls to check the
the job status. If set, the value overrides the interval set in the
connection object. Otherwise, the interval set in connection object
is used.
Returns:
The response received after the job completes. This is normally a success or failure indication for the job.
"""
from netapp_ontap import utils # pylint: disable=cyclic-import
my_connection = connection if connection is not None else self.connection
return utils.poll(
self.http_response,
connection=my_connection,
timeout=timeout,
interval=interval
)
| (http_response: requests.models.Response, connection: netapp_ontap.host_connection.HostConnection = None) -> None | [
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15,934 | netapp_ontap.response | __init__ | Create and initialize a NetAppResponse object based on the result of an API call.
Args:
http_response: The API response to wrap
| def __init__(self, http_response: requests.Response, connection: HostConnection = None) -> None:
"""Create and initialize a NetAppResponse object based on the result of an API call.
Args:
http_response: The API response to wrap
"""
self.http_response = http_response
self.connection = connection
| (self, http_response: requests.models.Response, connection: Optional[netapp_ontap.host_connection.HostConnection] = None) -> NoneType | [
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] |
15,935 | netapp_ontap.response | poll | Wait for the job associated with the response to complete.
Calls 'utils.poll' with the response object and blocks until the job
completes (that is reaches a terminal state).
Args:
connection: The host containing the job to connect to.
timeout: Seconds to wait before timing out of a poll request. If set,
the value overrides the timeout set in connection. Otherwise, the
timeout set in the connection is used.
interval: Seconds to wait between making REST API calls to check the
the job status. If set, the value overrides the interval set in the
connection object. Otherwise, the interval set in connection object
is used.
Returns:
The response received after the job completes. This is normally a success or failure indication for the job.
| def poll(
self, connection: HostConnection = None, timeout: int = None, interval: int = None
) -> "NetAppResponse":
"""Wait for the job associated with the response to complete.
Calls 'utils.poll' with the response object and blocks until the job
completes (that is reaches a terminal state).
Args:
connection: The host containing the job to connect to.
timeout: Seconds to wait before timing out of a poll request. If set,
the value overrides the timeout set in connection. Otherwise, the
timeout set in the connection is used.
interval: Seconds to wait between making REST API calls to check the
the job status. If set, the value overrides the interval set in the
connection object. Otherwise, the interval set in connection object
is used.
Returns:
The response received after the job completes. This is normally a success or failure indication for the job.
"""
from netapp_ontap import utils # pylint: disable=cyclic-import
my_connection = connection if connection is not None else self.connection
return utils.poll(
self.http_response,
connection=my_connection,
timeout=timeout,
interval=interval
)
| (self, connection: Optional[netapp_ontap.host_connection.HostConnection] = None, timeout: Optional[int] = None, interval: Optional[int] = None) -> netapp_ontap.response.NetAppResponse | [
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] |
15,936 | netapp_ontap.error | NetAppRestError | Common base class for all exceptions raised by the library functions. All
custom exceptions are derived from this type.
| class NetAppRestError(Exception):
"""Common base class for all exceptions raised by the library functions. All
custom exceptions are derived from this type.
"""
def __init__(self, message: str = None, cause: Exception = None) -> None:
"""Initalize the error object.
Optionally accepts a custom message and cause. If provided, the cause is
the exception object that was handled when this exception is created.
Args:
message: A human readable message that explains the error.
cause: An exception object that caused this exception to be raised.
"""
msg = message if message else ""
if cause:
self.cause = cause
msg += f" Caused by {cause!r}"
if getattr(cause, "response", None) is not None:
try:
self._response = NetAppResponse(cause.response) # type: ignore
err_msg = cause.response.json().get("error", {}).get("message") # type: ignore
if err_msg:
msg += f": {err_msg}"
except Exception: # pylint: disable=broad-except
# the error response wasn't json so there's nothing additional
# we will add
pass
super().__init__(msg.strip())
@property
def http_err_response(self) -> Optional[NetAppResponse]:
"""Describes a response to an API request that contains an error.
Returns:
Response object if the exception was raised because of an API failure (HTTP status code of 400 or higher). None if the exception was not related to an API error.
"""
return getattr(self, "_response", None)
@property
def status_code(self) -> Optional[int]:
"""Return the status code of the HTTP response if this error was generated
from a failed HTTP request. Otherwise, returns None
"""
if not getattr(self, "_response", None):
return None
return self._response.http_response.status_code
@property
def response_body(self) -> Optional[dict]:
"""Return the HTTP response body if this error was generated from a failed
HTTP request. The body will be in dictionary form. If this exception is
not from a failed request or the body cannot be parsed as JSON, returns None
"""
if not getattr(self, "_response", None):
return None
try:
return self._response.http_response.json()
except ValueError:
return None
@property
def response_text(self) -> Optional[str]:
"""Return the HTTP response body if this error was generated from a failed
HTTP request. This will be the raw text of the response body. This is useful
when the response body cannot be parsed as JSON.
"""
if not getattr(self, "_response", None):
return None
return self._response.http_response.text
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15,937 | netapp_ontap.error | __init__ | Initalize the error object.
Optionally accepts a custom message and cause. If provided, the cause is
the exception object that was handled when this exception is created.
Args:
message: A human readable message that explains the error.
cause: An exception object that caused this exception to be raised.
| def __init__(self, message: str = None, cause: Exception = None) -> None:
"""Initalize the error object.
Optionally accepts a custom message and cause. If provided, the cause is
the exception object that was handled when this exception is created.
Args:
message: A human readable message that explains the error.
cause: An exception object that caused this exception to be raised.
"""
msg = message if message else ""
if cause:
self.cause = cause
msg += f" Caused by {cause!r}"
if getattr(cause, "response", None) is not None:
try:
self._response = NetAppResponse(cause.response) # type: ignore
err_msg = cause.response.json().get("error", {}).get("message") # type: ignore
if err_msg:
msg += f": {err_msg}"
except Exception: # pylint: disable=broad-except
# the error response wasn't json so there's nothing additional
# we will add
pass
super().__init__(msg.strip())
| (self, message: Optional[str] = None, cause: Optional[Exception] = None) -> NoneType | [
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15,941 | sqlalchemy_utc.sqltypes | UtcDateTime | Almost equivalent to :class:`~sqlalchemy.types.DateTime` with
``timezone=True`` option, but it differs from that by:
- Never silently take naive :class:`~datetime.datetime`, instead it
always raise :exc:`ValueError` unless time zone aware value.
- :class:`~datetime.datetime` value's :attr:`~datetime.datetime.tzinfo`
is always converted to UTC.
- Unlike SQLAlchemy's built-in :class:`~sqlalchemy.types.DateTime`,
it never return naive :class:`~datetime.datetime`, but time zone
aware value, even with SQLite or MySQL.
| class UtcDateTime(TypeDecorator):
"""Almost equivalent to :class:`~sqlalchemy.types.DateTime` with
``timezone=True`` option, but it differs from that by:
- Never silently take naive :class:`~datetime.datetime`, instead it
always raise :exc:`ValueError` unless time zone aware value.
- :class:`~datetime.datetime` value's :attr:`~datetime.datetime.tzinfo`
is always converted to UTC.
- Unlike SQLAlchemy's built-in :class:`~sqlalchemy.types.DateTime`,
it never return naive :class:`~datetime.datetime`, but time zone
aware value, even with SQLite or MySQL.
"""
impl = DateTime(timezone=True)
cache_ok = True
def process_bind_param(self, value, dialect):
if value is not None:
if not isinstance(value, datetime.datetime):
raise TypeError('expected datetime.datetime, not ' +
repr(value))
elif value.tzinfo is None:
raise ValueError('naive datetime is disallowed')
return value.astimezone(utc)
def process_result_value(self, value, dialect):
if value is not None:
if value.tzinfo is None:
value = value.replace(tzinfo=utc)
else:
value = value.astimezone(utc)
return value
| (*args: 'Any', **kwargs: 'Any') | [
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15,942 | sqlalchemy.sql.type_api | __getattr__ | Proxy all other undefined accessors to the underlying
implementation. | def __getattr__(self, key: str) -> Any:
"""Proxy all other undefined accessors to the underlying
implementation."""
return getattr(self.impl_instance, key)
| (self, key: str) -> Any | [
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15,943 | sqlalchemy.sql.type_api | __init__ | Construct a :class:`.TypeDecorator`.
Arguments sent here are passed to the constructor
of the class assigned to the ``impl`` class level attribute,
assuming the ``impl`` is a callable, and the resulting
object is assigned to the ``self.impl`` instance attribute
(thus overriding the class attribute of the same name).
If the class level ``impl`` is not a callable (the unusual case),
it will be assigned to the same instance attribute 'as-is',
ignoring those arguments passed to the constructor.
Subclasses can override this to customize the generation
of ``self.impl`` entirely.
| def __init__(self, *args: Any, **kwargs: Any):
"""Construct a :class:`.TypeDecorator`.
Arguments sent here are passed to the constructor
of the class assigned to the ``impl`` class level attribute,
assuming the ``impl`` is a callable, and the resulting
object is assigned to the ``self.impl`` instance attribute
(thus overriding the class attribute of the same name).
If the class level ``impl`` is not a callable (the unusual case),
it will be assigned to the same instance attribute 'as-is',
ignoring those arguments passed to the constructor.
Subclasses can override this to customize the generation
of ``self.impl`` entirely.
"""
if not hasattr(self.__class__, "impl"):
raise AssertionError(
"TypeDecorator implementations "
"require a class-level variable "
"'impl' which refers to the class of "
"type being decorated"
)
self.impl = to_instance(self.__class__.impl, *args, **kwargs)
| (self, *args: Any, **kwargs: Any) | [
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15,944 | sqlalchemy.sql.type_api | __repr__ | null | def __repr__(self) -> str:
return util.generic_repr(self, to_inspect=self.impl_instance)
| (self) -> str | [
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15,945 | sqlalchemy.sql.type_api | __str__ | null | def __str__(self) -> str:
return str(self.compile())
| (self) -> str | [
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15,946 | sqlalchemy.sql.type_api | _cached_bind_processor | Return a dialect-specific bind processor for this type. | def _cached_bind_processor(
self, dialect: Dialect
) -> Optional[_BindProcessorType[_T]]:
"""Return a dialect-specific bind processor for this type."""
try:
return dialect._type_memos[self]["bind"]
except KeyError:
pass
# avoid KeyError context coming into bind_processor() function
# raises
d = self._dialect_info(dialect)
d["bind"] = bp = d["impl"].bind_processor(dialect)
return bp
| (self, dialect: 'Dialect') -> 'Optional[_BindProcessorType[_T]]' | [
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15,947 | sqlalchemy.sql.type_api | _cached_custom_processor | return a dialect-specific processing object for
custom purposes.
The cx_Oracle dialect uses this at the moment.
| def _cached_custom_processor(
self, dialect: Dialect, key: str, fn: Callable[[TypeEngine[_T]], _O]
) -> _O:
"""return a dialect-specific processing object for
custom purposes.
The cx_Oracle dialect uses this at the moment.
"""
try:
return cast(_O, dialect._type_memos[self]["custom"][key])
except KeyError:
pass
# avoid KeyError context coming into fn() function
# raises
d = self._dialect_info(dialect)
impl = d["impl"]
custom_dict = d.setdefault("custom", {})
custom_dict[key] = result = fn(impl)
return result
| (self, dialect: 'Dialect', key: 'str', fn: 'Callable[[TypeEngine[_T]], _O]') -> '_O' | [
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15,948 | sqlalchemy.sql.type_api | _cached_literal_processor | Return a dialect-specific literal processor for this type. | def _cached_literal_processor(
self, dialect: Dialect
) -> Optional[_LiteralProcessorType[_T]]:
"""Return a dialect-specific literal processor for this type."""
try:
return dialect._type_memos[self]["literal"]
except KeyError:
pass
# avoid KeyError context coming into literal_processor() function
# raises
d = self._dialect_info(dialect)
d["literal"] = lp = d["impl"].literal_processor(dialect)
return lp
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15,949 | sqlalchemy.sql.type_api | _cached_result_processor | Return a dialect-specific result processor for this type. | def _cached_result_processor(
self, dialect: Dialect, coltype: Any
) -> Optional[_ResultProcessorType[_T]]:
"""Return a dialect-specific result processor for this type."""
try:
return dialect._type_memos[self]["result"][coltype]
except KeyError:
pass
# avoid KeyError context coming into result_processor() function
# raises
d = self._dialect_info(dialect)
# key assumption: DBAPI type codes are
# constants. Else this dictionary would
# grow unbounded.
rp = d["impl"].result_processor(dialect, coltype)
d["result"][coltype] = rp
return rp
| (self, dialect: 'Dialect', coltype: 'Any') -> 'Optional[_ResultProcessorType[_T]]' | [
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15,950 | sqlalchemy.sql.type_api | _compare_type_affinity | null | def _compare_type_affinity(self, other: TypeEngine[Any]) -> bool:
return self._type_affinity is other._type_affinity
| (self, other: sqlalchemy.sql.type_api.TypeEngine) -> bool | [
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] |
15,951 | sqlalchemy.sql.visitors | _compiler_dispatch | Look for an attribute named "visit_<visit_name>" on the
visitor, and call it with the same kw params.
| @classmethod
def _generate_compiler_dispatch(cls) -> None:
visit_name = cls.__visit_name__
if "_compiler_dispatch" in cls.__dict__:
# class has a fixed _compiler_dispatch() method.
# copy it to "original" so that we can get it back if
# sqlalchemy.ext.compiles overrides it.
cls._original_compiler_dispatch = cls._compiler_dispatch
return
if not isinstance(visit_name, str):
raise exc.InvalidRequestError(
f"__visit_name__ on class {cls.__name__} must be a string "
"at the class level"
)
name = "visit_%s" % visit_name
getter = operator.attrgetter(name)
def _compiler_dispatch(
self: Visitable, visitor: Any, **kw: Any
) -> str:
"""Look for an attribute named "visit_<visit_name>" on the
visitor, and call it with the same kw params.
"""
try:
meth = getter(visitor)
except AttributeError as err:
return visitor.visit_unsupported_compilation(self, err, **kw) # type: ignore # noqa: E501
else:
return meth(self, **kw) # type: ignore # noqa: E501
cls._compiler_dispatch = ( # type: ignore
cls._original_compiler_dispatch
) = _compiler_dispatch
| (self: sqlalchemy.sql.visitors.Visitable, visitor: Any, **kw: Any) -> str | [
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15,952 | sqlalchemy.sql.type_api | _default_dialect | null | @util.preload_module("sqlalchemy.engine.default")
def _default_dialect(self) -> Dialect:
default = util.preloaded.engine_default
# dmypy / mypy seems to sporadically keep thinking this line is
# returning Any, which seems to be caused by the @deprecated_params
# decorator on the DefaultDialect constructor
return default.StrCompileDialect() # type: ignore
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15,953 | sqlalchemy.sql.type_api | _dialect_info | Return a dialect-specific registry which
caches a dialect-specific implementation, bind processing
function, and one or more result processing functions. | def _dialect_info(self, dialect: Dialect) -> _TypeMemoDict:
"""Return a dialect-specific registry which
caches a dialect-specific implementation, bind processing
function, and one or more result processing functions."""
if self in dialect._type_memos:
return dialect._type_memos[self]
else:
impl = self._gen_dialect_impl(dialect)
if impl is self:
impl = self.adapt(type(self))
# this can't be self, else we create a cycle
assert impl is not self
d: _TypeMemoDict = {"impl": impl, "result": {}}
dialect._type_memos[self] = d
return d
| (self, dialect: 'Dialect') -> '_TypeMemoDict' | [
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0.0032730952370911837,
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] |
15,954 | sqlalchemy.sql.type_api | _gen_dialect_impl | null | def _gen_dialect_impl(self, dialect: Dialect) -> TypeEngine[_T]:
if dialect.name in self._variant_mapping:
adapted = dialect.type_descriptor(
self._variant_mapping[dialect.name]
)
else:
adapted = dialect.type_descriptor(self)
if adapted is not self:
return adapted
# otherwise adapt the impl type, link
# to a copy of this TypeDecorator and return
# that.
typedesc = self.load_dialect_impl(dialect).dialect_impl(dialect)
tt = self.copy()
if not isinstance(tt, self.__class__):
raise AssertionError(
"Type object %s does not properly "
"implement the copy() method, it must "
"return an object of type %s" % (self, self.__class__)
)
tt.impl = tt.impl_instance = typedesc
return tt
| (self, dialect: 'Dialect') -> 'TypeEngine[_T]' | [
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15,956 | sqlalchemy.sql.type_api | _resolve_for_literal | adjust this type given a literal Python value that will be
stored in a bound parameter.
Used exclusively by _resolve_value_to_type().
.. versionadded:: 1.4.30 or 2.0
TODO: this should be part of public API
.. seealso::
:meth:`.TypeEngine._resolve_for_python_type`
| def _resolve_for_literal(self, value: Any) -> Self:
"""adjust this type given a literal Python value that will be
stored in a bound parameter.
Used exclusively by _resolve_value_to_type().
.. versionadded:: 1.4.30 or 2.0
TODO: this should be part of public API
.. seealso::
:meth:`.TypeEngine._resolve_for_python_type`
"""
return self
| (self, value: Any) -> typing_extensions.Self | [
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15,957 | sqlalchemy.sql.type_api | _resolve_for_python_type | given a Python type (e.g. ``int``, ``str``, etc. ) return an
instance of this :class:`.TypeEngine` that's appropriate for this type.
An additional argument ``matched_on`` is passed, which indicates an
entry from the ``__mro__`` of the given ``python_type`` that more
specifically matches how the caller located this :class:`.TypeEngine`
object. Such as, if a lookup of some kind links the ``int`` Python
type to the :class:`.Integer` SQL type, and the original object
was some custom subclass of ``int`` such as ``MyInt(int)``, the
arguments passed would be ``(MyInt, int)``.
If the given Python type does not correspond to this
:class:`.TypeEngine`, or the Python type is otherwise ambiguous, the
method should return None.
For simple cases, the method checks that the ``python_type``
and ``matched_on`` types are the same (i.e. not a subclass), and
returns self; for all other cases, it returns ``None``.
The initial use case here is for the ORM to link user-defined
Python standard library ``enum.Enum`` classes to the SQLAlchemy
:class:`.Enum` SQL type when constructing ORM Declarative mappings.
:param python_type: the Python type we want to use
:param matched_on: the Python type that led us to choose this
particular :class:`.TypeEngine` class, which would be a supertype
of ``python_type``. By default, the request is rejected if
``python_type`` doesn't match ``matched_on`` (None is returned).
.. versionadded:: 2.0.0b4
TODO: this should be part of public API
.. seealso::
:meth:`.TypeEngine._resolve_for_literal`
| def _resolve_for_python_type(
self,
python_type: Type[Any],
matched_on: _MatchedOnType,
matched_on_flattened: Type[Any],
) -> Optional[Self]:
"""given a Python type (e.g. ``int``, ``str``, etc. ) return an
instance of this :class:`.TypeEngine` that's appropriate for this type.
An additional argument ``matched_on`` is passed, which indicates an
entry from the ``__mro__`` of the given ``python_type`` that more
specifically matches how the caller located this :class:`.TypeEngine`
object. Such as, if a lookup of some kind links the ``int`` Python
type to the :class:`.Integer` SQL type, and the original object
was some custom subclass of ``int`` such as ``MyInt(int)``, the
arguments passed would be ``(MyInt, int)``.
If the given Python type does not correspond to this
:class:`.TypeEngine`, or the Python type is otherwise ambiguous, the
method should return None.
For simple cases, the method checks that the ``python_type``
and ``matched_on`` types are the same (i.e. not a subclass), and
returns self; for all other cases, it returns ``None``.
The initial use case here is for the ORM to link user-defined
Python standard library ``enum.Enum`` classes to the SQLAlchemy
:class:`.Enum` SQL type when constructing ORM Declarative mappings.
:param python_type: the Python type we want to use
:param matched_on: the Python type that led us to choose this
particular :class:`.TypeEngine` class, which would be a supertype
of ``python_type``. By default, the request is rejected if
``python_type`` doesn't match ``matched_on`` (None is returned).
.. versionadded:: 2.0.0b4
TODO: this should be part of public API
.. seealso::
:meth:`.TypeEngine._resolve_for_literal`
"""
if python_type is not matched_on_flattened:
return None
return self
| (self, python_type: 'Type[Any]', matched_on: '_MatchedOnType', matched_on_flattened: 'Type[Any]') -> 'Optional[Self]' | [
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