core.execution_state

Execution state management for parallel and batch execution.

class ExecutionState(completed=<factory>, in_progress=<factory>, pending=<factory>, results=<factory>, results_lock=<factory>, success_count=0, failed_count=0, skipped_count=0, aborted_count=0, results_by_name=<factory>, current_name='', aborted=False)[source]

Bases: object

Tracks state during parallel execution with thread-safe operations.

Parameters:

completed (set[int])
in_progress (set[int])
pending (dict[int, PromptNode])
results (list[dict[str, Any]])
results_lock (allocate_lock)
success_count (int)
failed_count (int)
skipped_count (int)
aborted_count (int)
results_by_name (dict[str, dict[str, Any]])
current_name (str)
aborted (bool)

completed

Set of completed sequence numbers.

Type:: set[int]

in_progress

Set of currently executing sequence numbers.

Type:: set[int]

pending

Dict of pending PromptNodes by sequence number.

Type:: dict[int, ffai.core.prompt_node.PromptNode]

results

List of execution results.

Type:: list[dict[str, Any]]

results_lock

Thread lock for result access.

Type:: _thread.allocate_lock

success_count

Number of successful executions.

Type:: int

failed_count

Number of failed executions.

Type:: int

skipped_count

Number of skipped executions.

Type:: int

aborted_count

Number of aborted executions.

Type:: int

results_by_name

Results indexed by prompt name.

Type:: dict[str, dict[str, Any]]

current_name

Name of currently executing prompt.

Type:: str

aborted

Whether execution has been aborted.

Type:: bool

completed: set[int]

in_progress: set[int]

pending: dict[int, PromptNode]

results: list[dict[str, Any]]

results_lock: allocate_lock

success_count: int = 0

failed_count: int = 0

skipped_count: int = 0

aborted_count: int = 0

results_by_name: dict[str, dict[str, Any]]

current_name: str = ''

aborted: bool = False

Classes