PipelineConfig#

Note

All Configs are derived from rastervision.pipeline.config.Config, which itself is a pydantic Model.

pydantic model PipelineConfig[source]#

Base class for configuring Pipelines.

This should be subclassed to configure new Pipelines.

Show JSON schema

{
   "title": "PipelineConfig",
   "description": "Base class for configuring :class:`Pipelines <.Pipeline>`.\n\nThis should be subclassed to configure new Pipelines.",
   "type": "object",
   "properties": {
      "root_uri": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The root URI for output generated by the pipeline",
         "title": "Root Uri"
      },
      "rv_config": {
         "anyOf": [
            {
               "type": "object"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Used to store serialized RVConfig so pipeline can run in remote environment with the local RVConfig. This should not be set explicitly by users -- it is only used by the runner when running a remote pipeline.",
         "title": "Rv Config"
      },
      "plugin_versions": {
         "anyOf": [
            {
               "additionalProperties": {
                  "type": "integer"
               },
               "type": "object"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Used to store a mapping of plugin module paths to the latest version number. This should not be set explicitly by users -- it is set automatically when serializing and saving the config to disk.",
         "title": "Plugin Versions"
      },
      "type_hint": {
         "const": "pipeline",
         "default": "pipeline",
         "enum": [
            "pipeline"
         ],
         "title": "Type Hint",
         "type": "string"
      }
   },
   "additionalProperties": false
}

Config:

extra: str = forbid
validate_assignment: bool = True

Fields:

plugin_versions (dict[str, int] | None)
root_uri (str | None)
rv_config (dict | None)
type_hint (Literal['pipeline'])

field plugin_versions: dict[str, int] | None = None#: Used to store a mapping of plugin module paths to the latest version number. This should not be set explicitly by users – it is set automatically when serializing and saving the config to disk.

field root_uri: str | None = None#: The root URI for output generated by the pipeline

field rv_config: dict | None = None#: Used to store serialized RVConfig so pipeline can run in remote environment with the local RVConfig. This should not be set explicitly by users – it is only used by the runner when running a remote pipeline.

field type_hint: Literal['pipeline'] = 'pipeline'#

build(tmp_dir: str) → Pipeline[source]#

Return a pipeline based on this configuration.

Subclasses should override this to return an instance of the corresponding subclass of Pipeline.

Parameters:: tmp_dir (str) – root of any temporary directory to pass to pipeline
Return type:: Pipeline

classmethod deserialize(inp: str | dict | Config) → Self#

Deserialize Config from a JSON file or dict, upgrading if possible.

If inp is already a Config, it is returned as is.

Parameters:: inp (str | dict | Config) – a URI to a JSON file or a dict.
Return type:: Self

classmethod from_dict(cfg_dict: dict) → Self[source]#

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

get_config_uri() → str[source]#

Get URI of serialized version of this PipelineConfig.

Return type:: str

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.

Parameters:

uri (str) – URI to save to.
with_rv_metadata (bool) – If True, inject Raster Vision metadata such as plugin_versions, so that the config can be upgraded when loaded.

Return type:

None

update(*args, **kwargs)#

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.

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.

validate_list(field: str, valid_options: list[str])#

Validate a list field.

Parameters:

field (str) – name of field to validate
valid_options (list[str]) – values that field is allowed to take

Raises:

ConfigError – if field is invalid