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prefect.server.database.query_componentsClasses FlowRunGraphV2Node BaseQueryComponents Abstract base class used to inject dialect-specific SQL operations into Prefect.
Methods: build_json_object build_json_object( self , * args: Union[ str , sa.ColumnElement[Any]]) -> sa.ColumnElement[Any]
builds a JSON object from sequential key-value pairs
cast_to_json cast_to_json( self , json_obj: sa.ColumnElement[T]) -> sa.ColumnElement[T]
casts to JSON object if necessary
clear_configuration_value_cache_for_key clear_configuration_value_cache_for_key( self , key: str ) -> None
Removes a configuration key from the cache.
flow_run_graph_v2 flow_run_graph_v2( self , db: PrefectDBInterface, session: AsyncSession, flow_run_id: UUID , since: DateTime, max_nodes: int , max_artifacts: int ) -> Graph
Returns the query that selects all of the nodes and edges for a flow run graph (version 2).
get_scheduled_flow_runs_from_work_pool get_scheduled_flow_runs_from_work_pool( self , db: PrefectDBInterface, session: AsyncSession, limit: Optional[ int ] = None , worker_limit: Optional[ int ] = None , queue_limit: Optional[ int ] = None , work_pool_ids: Optional[list[ UUID ]] = None , work_queue_ids: Optional[list[ UUID ]] = None , scheduled_before: Optional[DateTime] = None , scheduled_after: Optional[DateTime] = None , respect_queue_priorities: bool = False ) -> list[schemas.responses.WorkerFlowRunResponse]
get_scheduled_flow_runs_from_work_queues get_scheduled_flow_runs_from_work_queues( self , db: PrefectDBInterface, limit_per_queue: Optional[ int ] = None , work_queue_ids: Optional[list[ UUID ]] = None , scheduled_before: Optional[DateTime] = None ) -> sa.Select[tuple[orm_models.FlowRun, UUID ]]
Returns all scheduled runs in work queues, subject to provided parameters.
This query returns a (orm_models.FlowRun, orm_models.WorkQueue.id) pair; calling
result.all() will return both; calling result.scalars().unique().all()
will return only the flow run because it grabs the first result.
insert insert( self , obj: type[orm_models.Base]) -> Union[postgresql.Insert, sqlite.Insert]
dialect-specific insert statement
json_arr_agg json_arr_agg( self , json_array: sa.ColumnElement[Any]) -> sa.ColumnElement[Any]
aggregates a JSON array
make_timestamp_intervals make_timestamp_intervals( self , start_time: datetime.datetime, end_time: datetime.datetime, interval: datetime.timedelta) -> sa.Select[tuple[datetime.datetime, datetime.datetime]]
read_configuration_value read_configuration_value( self , db: PrefectDBInterface, session: AsyncSession, key: str ) -> Optional[dict[ str , Any]]
Read a configuration value by key.
Configuration values should not be changed at run time, so retrieved
values are cached in memory.
The main use of configurations is encrypting blocks, this speeds up nested
block document queries.
set_state_id_on_inserted_flow_runs_statement set_state_id_on_inserted_flow_runs_statement( self , inserted_flow_run_ids: Sequence[ UUID ], insert_flow_run_states: Iterable[dict[ str , Any]]) -> sa.Update
unique_key unique_key( self ) -> tuple[Hashable, ... ]
Returns a key used to determine whether to instantiate a new DB interface.
uses_json_strings uses_json_strings( self ) -> bool
specifies whether the configured dialect returns JSON as strings
AsyncPostgresQueryComponents Methods: build_json_object build_json_object( self , * args: Union[ str , sa.ColumnElement[Any]]) -> sa.ColumnElement[Any]
build_json_object build_json_object( self , * args: Union[ str , sa.ColumnElement[Any]]) -> sa.ColumnElement[Any]
builds a JSON object from sequential key-value pairs
cast_to_json cast_to_json( self , json_obj: sa.ColumnElement[T]) -> sa.ColumnElement[T]
cast_to_json cast_to_json( self , json_obj: sa.ColumnElement[T]) -> sa.ColumnElement[T]
casts to JSON object if necessary
clear_configuration_value_cache_for_key clear_configuration_value_cache_for_key( self , key: str ) -> None
Removes a configuration key from the cache.
flow_run_graph_v2 flow_run_graph_v2( self , db: PrefectDBInterface, session: AsyncSession, flow_run_id: UUID , since: DateTime, max_nodes: int , max_artifacts: int ) -> Graph
Returns the query that selects all of the nodes and edges for a flow run graph (version 2).
get_scheduled_flow_runs_from_work_pool get_scheduled_flow_runs_from_work_pool( self , db: PrefectDBInterface, session: AsyncSession, limit: Optional[ int ] = None , worker_limit: Optional[ int ] = None , queue_limit: Optional[ int ] = None , work_pool_ids: Optional[list[ UUID ]] = None , work_queue_ids: Optional[list[ UUID ]] = None , scheduled_before: Optional[DateTime] = None , scheduled_after: Optional[DateTime] = None , respect_queue_priorities: bool = False ) -> list[schemas.responses.WorkerFlowRunResponse]
get_scheduled_flow_runs_from_work_queues get_scheduled_flow_runs_from_work_queues( self , db: PrefectDBInterface, limit_per_queue: Optional[ int ] = None , work_queue_ids: Optional[list[ UUID ]] = None , scheduled_before: Optional[DateTime] = None ) -> sa.Select[tuple[orm_models.FlowRun, UUID ]]
Returns all scheduled runs in work queues, subject to provided parameters.
This query returns a (orm_models.FlowRun, orm_models.WorkQueue.id) pair; calling
result.all() will return both; calling result.scalars().unique().all()
will return only the flow run because it grabs the first result.
insert insert( self , obj: type[orm_models.Base]) -> postgresql.Insert
insert insert( self , obj: type[orm_models.Base]) -> Union[postgresql.Insert, sqlite.Insert]
dialect-specific insert statement
json_arr_agg json_arr_agg( self , json_array: sa.ColumnElement[Any]) -> sa.ColumnElement[Any]
json_arr_agg json_arr_agg( self , json_array: sa.ColumnElement[Any]) -> sa.ColumnElement[Any]
aggregates a JSON array
make_timestamp_intervals make_timestamp_intervals( self , start_time: datetime.datetime, end_time: datetime.datetime, interval: datetime.timedelta) -> sa.Select[tuple[datetime.datetime, datetime.datetime]]
make_timestamp_intervals make_timestamp_intervals( self , start_time: datetime.datetime, end_time: datetime.datetime, interval: datetime.timedelta) -> sa.Select[tuple[datetime.datetime, datetime.datetime]]
read_configuration_value read_configuration_value( self , db: PrefectDBInterface, session: AsyncSession, key: str ) -> Optional[dict[ str , Any]]
Read a configuration value by key.
Configuration values should not be changed at run time, so retrieved
values are cached in memory.
The main use of configurations is encrypting blocks, this speeds up nested
block document queries.
set_state_id_on_inserted_flow_runs_statement set_state_id_on_inserted_flow_runs_statement( self , db: PrefectDBInterface, inserted_flow_run_ids: Sequence[ UUID ], insert_flow_run_states: Iterable[dict[ str , Any]]) -> sa.Update
Given a list of flow run ids and associated states, set the state_id
to the appropriate state for all flow runs
set_state_id_on_inserted_flow_runs_statement set_state_id_on_inserted_flow_runs_statement( self , inserted_flow_run_ids: Sequence[ UUID ], insert_flow_run_states: Iterable[dict[ str , Any]]) -> sa.Update
unique_key unique_key( self ) -> tuple[Hashable, ... ]
Returns a key used to determine whether to instantiate a new DB interface.
uses_json_strings uses_json_strings( self ) -> bool
uses_json_strings uses_json_strings( self ) -> bool
specifies whether the configured dialect returns JSON as strings
UUIDList Map a JSON list of strings back to a list of UUIDs at the result loading stage
Methods: process_result_value process_result_value( self , value: Optional[list[Union[ str , UUID ]]], dialect: sa.Dialect) -> Optional[list[ UUID ]]
AioSqliteQueryComponents Methods: build_json_object build_json_object( self , * args: Union[ str , sa.ColumnElement[Any]]) -> sa.ColumnElement[Any]
build_json_object build_json_object( self , * args: Union[ str , sa.ColumnElement[Any]]) -> sa.ColumnElement[Any]
builds a JSON object from sequential key-value pairs
cast_to_json cast_to_json( self , json_obj: sa.ColumnElement[T]) -> sa.ColumnElement[T]
cast_to_json cast_to_json( self , json_obj: sa.ColumnElement[T]) -> sa.ColumnElement[T]
casts to JSON object if necessary
clear_configuration_value_cache_for_key clear_configuration_value_cache_for_key( self , key: str ) -> None
Removes a configuration key from the cache.
flow_run_graph_v2 flow_run_graph_v2( self , db: PrefectDBInterface, session: AsyncSession, flow_run_id: UUID , since: DateTime, max_nodes: int , max_artifacts: int ) -> Graph
Returns the query that selects all of the nodes and edges for a flow run graph (version 2).
get_scheduled_flow_runs_from_work_pool get_scheduled_flow_runs_from_work_pool( self , db: PrefectDBInterface, session: AsyncSession, limit: Optional[ int ] = None , worker_limit: Optional[ int ] = None , queue_limit: Optional[ int ] = None , work_pool_ids: Optional[list[ UUID ]] = None , work_queue_ids: Optional[list[ UUID ]] = None , scheduled_before: Optional[DateTime] = None , scheduled_after: Optional[DateTime] = None , respect_queue_priorities: bool = False ) -> list[schemas.responses.WorkerFlowRunResponse]
get_scheduled_flow_runs_from_work_queues get_scheduled_flow_runs_from_work_queues( self , db: PrefectDBInterface, limit_per_queue: Optional[ int ] = None , work_queue_ids: Optional[list[ UUID ]] = None , scheduled_before: Optional[DateTime] = None ) -> sa.Select[tuple[orm_models.FlowRun, UUID ]]
Returns all scheduled runs in work queues, subject to provided parameters.
This query returns a (orm_models.FlowRun, orm_models.WorkQueue.id) pair; calling
result.all() will return both; calling result.scalars().unique().all()
will return only the flow run because it grabs the first result.
insert insert( self , obj: type[orm_models.Base]) -> sqlite.Insert
insert insert( self , obj: type[orm_models.Base]) -> Union[postgresql.Insert, sqlite.Insert]
dialect-specific insert statement
json_arr_agg json_arr_agg( self , json_array: sa.ColumnElement[Any]) -> sa.ColumnElement[Any]
json_arr_agg json_arr_agg( self , json_array: sa.ColumnElement[Any]) -> sa.ColumnElement[Any]
aggregates a JSON array
make_timestamp_intervals make_timestamp_intervals( self , start_time: datetime.datetime, end_time: datetime.datetime, interval: datetime.timedelta) -> sa.Select[tuple[datetime.datetime, datetime.datetime]]
make_timestamp_intervals make_timestamp_intervals( self , start_time: datetime.datetime, end_time: datetime.datetime, interval: datetime.timedelta) -> sa.Select[tuple[datetime.datetime, datetime.datetime]]
read_configuration_value read_configuration_value( self , db: PrefectDBInterface, session: AsyncSession, key: str ) -> Optional[dict[ str , Any]]
Read a configuration value by key.
Configuration values should not be changed at run time, so retrieved
values are cached in memory.
The main use of configurations is encrypting blocks, this speeds up nested
block document queries.
set_state_id_on_inserted_flow_runs_statement set_state_id_on_inserted_flow_runs_statement( self , db: PrefectDBInterface, inserted_flow_run_ids: Sequence[ UUID ], insert_flow_run_states: Iterable[dict[ str , Any]]) -> sa.Update
Given a list of flow run ids and associated states, set the state_id
to the appropriate state for all flow runs
set_state_id_on_inserted_flow_runs_statement set_state_id_on_inserted_flow_runs_statement( self , inserted_flow_run_ids: Sequence[ UUID ], insert_flow_run_states: Iterable[dict[ str , Any]]) -> sa.Update
unique_key unique_key( self ) -> tuple[Hashable, ... ]
Returns a key used to determine whether to instantiate a new DB interface.
uses_json_strings uses_json_strings( self ) -> bool
uses_json_strings uses_json_strings( self ) -> bool
specifies whether the configured dialect returns JSON as strings 
