VectorSourceConfig#
Note
All Configs are derived from rastervision.pipeline.config.Config, which itself is a pydantic Model.
- pydantic model VectorSourceConfig[source]#
Configure a
VectorSource.Show JSON schema
{ "title": "VectorSourceConfig", "description": "Configure a :class:`.VectorSource`.", "type": "object", "properties": { "transformers": { "default": [], "description": "List of VectorTransformers.", "items": { "$ref": "#/$defs/VectorTransformerConfig" }, "title": "Transformers", "type": "array" }, "type_hint": { "const": "vector_source", "default": "vector_source", "title": "Type Hint", "type": "string" } }, "$defs": { "VectorTransformerConfig": { "additionalProperties": false, "description": "Configure a :class:`.VectorTransformer`.", "properties": { "type_hint": { "const": "vector_transformer", "default": "vector_transformer", "title": "Type Hint", "type": "string" } }, "title": "VectorTransformerConfig", "type": "object" } }, "additionalProperties": false }
- Config
extra: str = forbid
validate_assignment: bool = True
- Fields
- field transformers: list[VectorTransformerConfig] = []#
List of VectorTransformers.
- abstract build(class_config: ClassConfig, crs_transformer: CRSTransformer) VectorSource[source]#
Build an instance of the corresponding type of object using this config.
For example, BackendConfig will build a Backend object. The arguments to this method will vary depending on the type of Config.
- Parameters
class_config (ClassConfig) –
crs_transformer (CRSTransformer) –
- Return type
- classmethod deserialize(inp: str | dict | Config) Self#
Deserialize Config from a JSON file or dict, upgrading if possible.
If
inpis already aConfig, it is returned as is.
- classmethod from_dict(cfg_dict: dict) Self#
Deserialize Config from a dict.
- Parameters
cfg_dict (dict) – Dict to deserialize.
- Return type
Self
- classmethod from_file(uri: str) Self#
Deserialize Config from a JSON file, upgrading if possible.
- Parameters
uri (str) – URI to load from.
- Return type
Self
- recursive_validate_config()#
Recursively validate hierarchies of Configs.
This uses reflection to call validate_config on a hierarchy of Configs using a depth-first pre-order traversal.
- revalidate()#
Re-validate an instantiated Config.
Runs all Pydantic validators plus self.validate_config().
- to_file(uri: str, with_rv_metadata: bool = True) None#
Save a Config to a JSON file, optionally with RV metadata.
- update(pipeline: RVPipelineConfig | None = None, scene: SceneConfig | None = None) None[source]#
Update any fields before validation.
Subclasses should override this to provide complex default behavior, for example, setting default values as a function of the values of other fields. The arguments to this method will vary depending on the type of Config.
- Parameters
pipeline (RVPipelineConfig | None) –
scene (SceneConfig | None) –
- Return type
None
- validate_config()#
Validate fields that should be checked after update is called.
This is to complement the builtin validation that Pydantic performs at the time of object construction.