client
Kitaru client for execution and artifact management.
KitaruClient provides a programmatic API for inspecting and managing
executions outside flow bodies.
Example::
from kitaru import KitaruClient
client = KitaruClient() execution = client.executions.get("exec-123") print(execution.status)
func_temporary_active_stack(stack_name_or_id) -> Iterator[None]Temporarily activate a stack while running an operation.
paramstack_name_or_idstr | NoneReturns
collections.abc.Iterator[None]func_snapshot_source_parts(run) -> tuple[str, str | None]Return (module, attribute) from a run snapshot source.
paramrunPipelineRunResponseReturns
tuple[str, str | None]func_import_module_for_replay(module_name, run_id) -> AnyImport a module by name, falling back to sys.modules search.
ZenML records the pipeline source module relative to the archived source
root (e.g. replay_with_overrides), but in the running process the
module may be loaded under a different path. Three fallback strategies:
- Direct
importlib.import_module(exact match). - Search
sys.modulesfor a suffix match (e.g. the module is loaded asexamples.replay.replay_with_overrides). - Return
__main__— when invoked viapython -m pkg.mod, the module is loaded as__main__and won't appear under its dotted name insys.modules.
parammodule_namestrparamrun_idstr | AnyReturns
typing.Anyfunc_resolve_flow_for_replay(run) -> _ReplayFlowLikeResolve the original flow wrapper object for a replay source run.
paramrunPipelineRunResponseReturns
kitaru.client._ReplayFlowLikefunc_resolve_pipeline_for_replay(run) -> AnyResolve the underlying pipeline object for replay fallback.
paramrunPipelineRunResponseReturns
typing.Anyfunc_restart_run_from_snapshot(*, run, client, operation_name) -> NoneRestart an execution from its stored snapshot metadata.
paramrunPipelineRunResponseparamclientKitaruClientparamoperation_namestrReturns
None