Documentation Index Fetch the complete documentation index at: https://docs.prefect.io/llms.txt
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prefect.server.database.orm_modelsClasses Base Base SQLAlchemy model that automatically infers the table name
and provides ID, created, and updated columns
Flow SQLAlchemy mixin of a flow.
FlowRunState SQLAlchemy mixin of a flow run state.
Methods: as_state as_state( self ) -> schemas.states.State
data data( self ) -> Optional[Any]
TaskRunState SQLAlchemy model of a task run state.
Methods: as_state as_state( self ) -> schemas.states.State
data data( self ) -> Optional[Any]
Artifact SQLAlchemy model of artifacts.
ArtifactCollection TaskRunStateCache SQLAlchemy model of a task run state cache.
Run Common columns and logic for FlowRun and TaskRun models
Methods: estimated_run_time estimated_run_time( self ) -> datetime.timedelta
Total run time is incremented in the database whenever a RUNNING
state is exited. To give up-to-date estimates, we estimate incremental
run time for any runs currently in a RUNNING state.
estimated_start_time_delta estimated_start_time_delta( self ) -> datetime.timedelta
The delta to the expected start time (or “lateness”) is computed as
the difference between the actual start time and expected start time. To
give up-to-date estimates, we estimate lateness for any runs that don’t
have a start time and are not in a final state and were expected to
start already.
FlowRun SQLAlchemy model of a flow run.
Methods: estimated_run_time estimated_run_time( self ) -> datetime.timedelta
Total run time is incremented in the database whenever a RUNNING
state is exited. To give up-to-date estimates, we estimate incremental
run time for any runs currently in a RUNNING state.
estimated_start_time_delta estimated_start_time_delta( self ) -> datetime.timedelta
The delta to the expected start time (or “lateness”) is computed as
the difference between the actual start time and expected start time. To
give up-to-date estimates, we estimate lateness for any runs that don’t
have a start time and are not in a final state and were expected to
start already.
set_state set_state( self , state: Optional[FlowRunState]) -> None
If a state is assigned to this run, populate its run id.
This would normally be handled by the back-populated SQLAlchemy
relationship, but because this is a one-to-one pointer to a
one-to-many relationship, SQLAlchemy can’t figure it out.
state state( self ) -> Optional[FlowRunState]
TaskRun SQLAlchemy model of a task run.
Methods: estimated_run_time estimated_run_time( self ) -> datetime.timedelta
Total run time is incremented in the database whenever a RUNNING
state is exited. To give up-to-date estimates, we estimate incremental
run time for any runs currently in a RUNNING state.
estimated_start_time_delta estimated_start_time_delta( self ) -> datetime.timedelta
The delta to the expected start time (or “lateness”) is computed as
the difference between the actual start time and expected start time. To
give up-to-date estimates, we estimate lateness for any runs that don’t
have a start time and are not in a final state and were expected to
start already.
set_state set_state( self , state: Optional[TaskRunState]) -> None
If a state is assigned to this run, populate its run id.
This would normally be handled by the back-populated SQLAlchemy
relationship, but because this is a one-to-one pointer to a
one-to-many relationship, SQLAlchemy can’t figure it out.
state state( self ) -> Optional[TaskRunState]
DeploymentSchedule Deployment SQLAlchemy model of a deployment.
Methods: job_variables job_variables( self ) -> Mapped[dict[ str , Any]]
Log SQLAlchemy model of a logging statement.
ConcurrencyLimit ConcurrencyLimitV2 BlockType BlockSchema BlockSchemaReference BlockDocument Methods: decrypt_data decrypt_data( self , session: AsyncSession) -> dict[ str , Any]
Retrieve decrypted data from the ORM model.
Note: will only succeed if the caller has sufficient permission.
encrypt_data encrypt_data( self , session: AsyncSession, data: dict[ str , Any]) -> None
Store encrypted data on the ORM model
Note: will only succeed if the caller has sufficient permission.
BlockDocumentReference Configuration SavedSearch SQLAlchemy model of a saved search.
WorkQueue SQLAlchemy model of a work queue
WorkPool SQLAlchemy model of an worker
Worker SQLAlchemy model of an worker
Agent SQLAlchemy model of an agent
Variable CsrfToken Automation Methods: sort_expression sort_expression( cls , value: AutomationSort) -> sa.ColumnExpressionArgument[Any]
Return an expression used to sort Automations
AutomationBucket CompositeTriggerChildFiring AutomationEventFollower Event EventResource BaseORMConfiguration Abstract base class used to inject database-specific ORM configuration into Prefect.
Modifications to core Prefect REST API data structures can have unintended consequences.
Use with caution.
Methods: artifact_collection_unique_upsert_columns artifact_collection_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting an ArtifactCollection
block_document_unique_upsert_columns block_document_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockDocument
block_schema_unique_upsert_columns block_schema_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockSchema
block_type_unique_upsert_columns block_type_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockType
concurrency_limit_unique_upsert_columns concurrency_limit_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a ConcurrencyLimit
deployment_unique_upsert_columns deployment_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a Deployment
flow_run_unique_upsert_columns flow_run_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a FlowRun
flow_unique_upsert_columns flow_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a Flow
saved_search_unique_upsert_columns saved_search_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a SavedSearch
task_run_unique_upsert_columns task_run_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a TaskRun
unique_key unique_key( self ) -> tuple[Hashable, ... ]
Returns a key used to determine whether to instantiate a new DB interface.
versions_dir versions_dir( self ) -> Path
Directory containing migrations
AsyncPostgresORMConfiguration Postgres specific orm configuration
Methods: artifact_collection_unique_upsert_columns artifact_collection_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting an ArtifactCollection
block_document_unique_upsert_columns block_document_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockDocument
block_schema_unique_upsert_columns block_schema_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockSchema
block_type_unique_upsert_columns block_type_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockType
concurrency_limit_unique_upsert_columns concurrency_limit_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a ConcurrencyLimit
deployment_unique_upsert_columns deployment_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a Deployment
flow_run_unique_upsert_columns flow_run_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a FlowRun
flow_unique_upsert_columns flow_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a Flow
saved_search_unique_upsert_columns saved_search_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a SavedSearch
task_run_unique_upsert_columns task_run_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a TaskRun
unique_key unique_key( self ) -> tuple[Hashable, ... ]
Returns a key used to determine whether to instantiate a new DB interface.
versions_dir versions_dir( self ) -> Path
Directory containing migrations
versions_dir versions_dir( self ) -> Path
Directory containing migrations
AioSqliteORMConfiguration SQLite specific orm configuration
Methods: artifact_collection_unique_upsert_columns artifact_collection_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting an ArtifactCollection
block_document_unique_upsert_columns block_document_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockDocument
block_schema_unique_upsert_columns block_schema_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockSchema
block_type_unique_upsert_columns block_type_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a BlockType
concurrency_limit_unique_upsert_columns concurrency_limit_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a ConcurrencyLimit
deployment_unique_upsert_columns deployment_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a Deployment
flow_run_unique_upsert_columns flow_run_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a FlowRun
flow_unique_upsert_columns flow_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a Flow
saved_search_unique_upsert_columns saved_search_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a SavedSearch
task_run_unique_upsert_columns task_run_unique_upsert_columns( self ) -> _UpsertColumns
Unique columns for upserting a TaskRun
unique_key unique_key( self ) -> tuple[Hashable, ... ]
Returns a key used to determine whether to instantiate a new DB interface.
versions_dir versions_dir( self ) -> Path
Directory containing migrations
versions_dir versions_dir( self ) -> Path
Directory containing migrations 
