Skip to content

output

output

Attribute dataclass

Bases: BaseInterface

An attribute belonging to a feature. The aim here is to drill down to simple types which can be used in consuming applications without further handling. This does not include the geometry attribute!

Attributes:

  • name (str) –

    The name of the attribute. Has to match with the name used for exported fields with Field class.

  • value (int | float | str | bool | bytes | None) –

    Value as simple as possible. It has to be pickleable

Source code in src/qgis_server_light/interface/job/feature/output.py 
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
@dataclass(repr=False)
class Attribute(BaseInterface):
    """An attribute belonging to a feature. The aim here is to
    drill down to simple types which can be used in consuming
    applications without further handling. This does not include
    the geometry attribute!

    Attributes:
        name: The name of the attribute. Has to match with the
            name used for exported fields with `Field` class.
        value: Value as simple as possible. It has to be
            [pickleable](https://docs.python.org/3/library/pickle.html#what-can-be-pickled-and-unpickled)

    """

    name: str = field(metadata={"type": "Element"})
    value: int | float | str | bool | bytes | None = field(
        metadata={"type": "Element", "format": "base64"}
    )

name: str = field(metadata={'type': 'Element'}) class-attribute instance-attribute

value: int | float | str | bool | bytes | None = field(metadata={'type': 'Element', 'format': 'base64'}) class-attribute instance-attribute

__init__(name: str, value: int | float | str | bool | bytes | None) -> None

Feature dataclass

Bases: BaseInterface

Feature to hold information of extracted QgsFeature.

Attributes:

Source code in src/qgis_server_light/interface/job/feature/output.py 
39
40
41
42
43
44
45
46
47
48
49
50
51
52
@dataclass(repr=False)
class Feature(BaseInterface):
    """Feature to hold information of extracted QgsFeature.

    Attributes:
        geometry: The geometry representing the feature.
        attributes: List of attributes defined in this feature.
    """

    geometry: Geometry | None = field(default=None, metadata={"type": "Element"})
    attributes: list[Attribute] = field(
        default_factory=list,
        metadata={"type": "Element"},
    )

attributes: list[Attribute] = field(default_factory=list, metadata={'type': 'Element'}) class-attribute instance-attribute

geometry: Geometry | None = field(default=None, metadata={'type': 'Element'}) class-attribute instance-attribute

__init__(geometry: Geometry | None = None, attributes: list[Attribute] = list()) -> None

FeatureCollection dataclass

Bases: BaseInterface

This construction is used to abstract the content of extracted features for pickelable transportation from QSL to the queue. This way we ensure how things are constructed and transported.

Attributes:

  • name (str) –

    The name of the feature collection. This is the key to match it to requested layers.

  • features (list[Feature]) –

    The features belonging to the feature collection.

Source code in src/qgis_server_light/interface/job/feature/output.py 
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
@dataclass(repr=False)
class FeatureCollection(BaseInterface):
    """This construction is used to abstract the content of extracted
    features for pickelable transportation from QSL to the queue.
    This way we ensure how things are constructed and transported.

    Attributes:
        name: The name of the feature collection. This is the key to
            match it to requested layers.
        features: The features belonging to the feature collection.
    """

    name: str = field(metadata={"type": "Element"})
    features: list[Feature] = field(
        default_factory=list,
        metadata={"type": "Element"},
    )

features: list[Feature] = field(default_factory=list, metadata={'type': 'Element'}) class-attribute instance-attribute

name: str = field(metadata={'type': 'Element'}) class-attribute instance-attribute

__init__(name: str, features: list[Feature] = list()) -> None

Geometry dataclass

Bases: Attribute

Source code in src/qgis_server_light/interface/job/feature/output.py 
27
28
29
30
31
32
33
34
35
36
@dataclass(repr=False)
class Geometry(Attribute):
    name: str = field(default="geometry", metadata={"type": "Element"})
    value: bytes | None = field(
        default=None, metadata={"type": "Element", "format": "base64"}
    )

    @property
    def shortened_fields(self) -> set:
        return {"value"}

name: str = field(default='geometry', metadata={'type': 'Element'}) class-attribute instance-attribute

shortened_fields: set property

value: bytes | None = field(default=None, metadata={'type': 'Element', 'format': 'base64'}) class-attribute instance-attribute

__init__(name: str = 'geometry', value: bytes | None = None) -> None

QueryCollection dataclass

Bases: BaseInterface

Holds all feature collections which are bound to the passed queries. The order in the list has to be not changed, so that consuming applications can map the response to the passed queries.

Attributes:

Source code in src/qgis_server_light/interface/job/feature/output.py 
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
@dataclass(repr=False)
class QueryCollection(BaseInterface):
    """Holds all feature collections which are bound to the
    passed queries. The order in the list has to be not changed,
    so that consuming applications can map the response to the
    passed queries.

    Attributes:
        numbers_matched: Information about how many matches are fund for the executed query.
        feature_collections: The feature collections belonging to the passed queries.
    """

    numbers_matched: str | int = field(
        default="unknown",
        metadata={"type": "Element"},
    )
    feature_collections: list[FeatureCollection] = field(
        default_factory=list,
        metadata={"type": "Element"},
    )

feature_collections: list[FeatureCollection] = field(default_factory=list, metadata={'type': 'Element'}) class-attribute instance-attribute

numbers_matched: str | int = field(default='unknown', metadata={'type': 'Element'}) class-attribute instance-attribute

__init__(numbers_matched: str | int = 'unknown', feature_collections: list[FeatureCollection] = list()) -> None