Model Catalog Endpoints¶

class graphdatascience.procedure_surface.api.model.ModelCatalogEndpoints¶

abstract delete(model_name: str, fail_if_missing: bool = False) → ModelDeleteResult | None¶

Delete a persisted model from storage.

Parameters:

model_name (str) – The model to delete.
fail_if_missing (bool) – If True, a missing model will cause an error. If False, returns None when missing.

Returns:

The delete result.

Return type:

ModelDeleteResult

abstract drop(model_name: str, *, fail_if_missing: bool = False) → ModelDetails | None¶

Drop a model from the in-memory catalog.

Parameters:

model_name (str) – The model to drop.
fail_if_missing (bool) – If True, a missing model will cause an error. If False, returns None when missing.

Returns:

The model details after the drop operation when applicable.

Return type:

ModelDetails

abstract exists(model_name: str) → ModelExistsResult | None¶

Check whether a model exists.

Parameters:: model_name (str) – The name of the model to check.
Returns:: A result object when the model exists; otherwise None.
Return type:: ModelExistsResult | None

abstract get(model_name: str) → ModelDetails¶

Get a model catalog entry by name.

Parameters:: model_name (str) – The model name to resolve.
Returns:: The model details.
Return type:: ModelDetails

abstract list() → list[ModelDetails]¶

List all models in the model catalog.

Returns:: List of model catalog entries.
Return type:: list[ModelDetails]

abstract load(model_name: str) → ModelLoadResult¶

Load a persisted model into the session/catalog.

Parameters:: model_name (str) – The model to load.
Returns:: The load result.
Return type:: ModelLoadResult

abstract store(model_name: str, *, fail_if_unsupported: bool = False) → ModelStoreResult¶

Persist/store a model.

Parameters:

model_name (str) – The model to store.
fail_if_unsupported (bool) – If True, unsupported models cause an error.

Returns:

The store result.

Return type:

ModelStoreResult

pydantic model graphdatascience.procedure_surface.api.model.ModelDeleteResult¶

field delete_millis: int¶

field model_name: str¶

pydantic model graphdatascience.procedure_surface.api.model.ModelExistsResult¶

field exists: bool¶

field model_name: str¶

field model_type: str¶

pydantic model graphdatascience.procedure_surface.api.model.ModelLoadResult¶

field load_millis: int¶

field model_name: str¶

pydantic model graphdatascience.procedure_surface.api.model.ModelStoreResult¶

field model_name: str¶

field store_millis: int¶

class graphdatascience.model.v2.model_details.ModelDetails¶

model_config: ClassVar[ConfigDict] = {'alias_generator': <function to_camel>}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].