parsl.dataflow.taskrecord.TaskRecord

class parsl.dataflow.taskrecord.TaskRecord

This stores most information about a Parsl task

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)
clear()
copy()
fromkeys([value])	Create a new dictionary with keys from iterable and values set to value.
get(key[, default])	Return the value for key if key is in the dictionary, else default.
items()
keys()
pop(k[,d])	If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem()	Remove and return a (key, value) pair as a 2-tuple.
setdefault(key[, default])	Insert key with a value of default if key is not in the dictionary.
update([E, ]**F)	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()

Attributes

dfk	The DataFlowKernel which is managing this task.
func_name
status
depends
app_fu	The Future which was returned to the user when an app was invoked.
exec_fu	When a task has been launched on an executor, stores the Future returned by that executor.
executor	The name of the executor which this task will be/is being/was executed on.
retries_left
fail_count
fail_cost
fail_history
checkpoint	Should this task be checkpointed?
hashsum	The hash used for checkpointing and memoisation.
task_launch_lock	This lock is used to ensure that task launch only happens once.
func
fn_hash
args
kwargs
time_invoked
time_returned
try_time_launched
try_time_returned
memoize	Should this task be memoized?
ignore_for_cache
from_memo
id
try_id
resource_specification	Dictionary containing relevant info for a task execution.
join	Is this a join_app?
joins	If this is a join app and the python body has executed, then this contains the Future or list of Futures that the join app will join.
join_lock	Restricts access to end-of-join behavior to ensure that joins only complete once, even if several joining Futures complete close together in time.
span	Event tracing span for this task.

app_fu: AppFuture

The Future which was returned to the user when an app was invoked.

args: Sequence[Any]

checkpoint: bool

Should this task be checkpointed?

depends: List[Future]

dfk: dflow.DataFlowKernel

The DataFlowKernel which is managing this task.

exec_fu: Future | None

When a task has been launched on an executor, stores the Future returned by that executor.

executor: str

The name of the executor which this task will be/is being/was executed on.

fail_cost: float

fail_count: int

fail_history: List[str]

fn_hash: str

from_memo: bool | None

func: Callable

func_name: str

hashsum: str | None

The hash used for checkpointing and memoisation. This is not known until at least all relevant dependencies have completed, and will be None before that.

id: int

ignore_for_cache: Sequence[str]

join: bool

Is this a join_app?

join_lock: threading.Lock

Restricts access to end-of-join behavior to ensure that joins only complete once, even if several joining Futures complete close together in time.

joins: None | Future | List[Future]

If this is a join app and the python body has executed, then this contains the Future or list of Futures that the join app will join.

kwargs: Dict[str, Any]

memoize: bool

Should this task be memoized?

resource_specification: Dict[str, Any]

Dictionary containing relevant info for a task execution. Includes resources to allocate and execution mode as a given executor permits.

retries_left: int

span: Span

Event tracing span for this task.

status: States

task_launch_lock: threading.Lock

This lock is used to ensure that task launch only happens once. A task can be launched by dependencies completing from arbitrary threads, and a race condition would exist when dependencies complete in multiple threads very close together in time, which this lock prevents.

time_invoked: datetime.datetime | None

time_returned: datetime.datetime | None

try_id: int

try_time_launched: datetime.datetime | None

try_time_returned: datetime.datetime | None