tessl/pypi-google-cloud-aiplatform
Comprehensive Python client library for Google Cloud Vertex AI, offering machine learning tools, generative AI models, and MLOps capabilities
—
Pending
feature-store.mddocs/
Feature Store
Enterprise feature management with online and offline serving, feature versioning, and monitoring.
Capabilities
Featurestore Management
Centralized feature repository with versioning and access control.
class Featurestore:
@classmethod
def create(
cls,
featurestore_id: str,
online_store_fixed_node_count: Optional[int] = None,
online_store_scaling: Optional[Dict] = None,
labels: Optional[Dict[str, str]] = None,
encryption_spec_key_name: Optional[str] = None,
**kwargs
) -> 'Featurestore': ...
def create_entity_type(
self,
entity_type_id: str,
description: Optional[str] = None,
labels: Optional[Dict[str, str]] = None,
monitoring_config: Optional[Dict] = None,
offline_storage_ttl_days: Optional[int] = None,
**kwargs
) -> 'EntityType': ...
def list_entity_types(self, **kwargs) -> List['EntityType']: ...Entity Types and Features
Manage feature schemas and metadata with type safety and validation.
class EntityType:
def create_feature(
self,
feature_id: str,
value_type: str,
description: Optional[str] = None,
labels: Optional[Dict[str, str]] = None,
monitoring_config: Optional[Dict] = None,
**kwargs
) -> 'Feature': ...
def batch_create_features(
self,
feature_configs: List[Dict[str, Any]],
**kwargs
) -> List['Feature']: ...
class Feature:
@classmethod
def create(
cls,
feature_id: str,
value_type: str,
entity_type: EntityType,
description: Optional[str] = None,
labels: Optional[Dict[str, str]] = None,
**kwargs
) -> 'Feature': ...
def ingest_from_gcs(
self,
feature_ids: List[str],
gcs_source_uris: List[str],
entity_id_field: str,
feature_time_field: str,
worker_count: int = 1,
**kwargs
) -> FeatureValueImportJob: ...Install with Tessl CLI
npx tessl i tessl/pypi-google-cloud-aiplatform