from __future__ import annotations import logging from dask.core import validate_key from distributed.client import Future, futures_of, wait from distributed.protocol.serialize import ToPickle from distributed.utils import sync logger = logging.getLogger(__name__) class ReplayTaskScheduler: """A plugin for the scheduler to recreate tasks locally This adds the following routes to the scheduler * get_runspec * get_error_cause """ def __init__(self, scheduler): self.scheduler = scheduler self.scheduler.handlers["get_runspec"] = self.get_runspec self.scheduler.handlers["get_error_cause"] = self.get_error_cause def _process_key(self, key): if isinstance(key, list): key = tuple(key) # ensure not a list from msgpack return key def get_error_cause(self, *args, keys=(), **kwargs): for key in keys: key = self._process_key(key) ts = self.scheduler.tasks.get(key) if ts is not None and ts.exception_blame is not None: return ts.exception_blame.key def get_runspec(self, *args, key=None, **kwargs): key = self._process_key(key) ts = self.scheduler.tasks[key] return ToPickle(ts.run_spec) class ReplayTaskClient: """ A plugin for the client allowing replay of remote tasks locally Adds the following methods to the given client: - ``recreate_error_locally``: main user method for replaying failed tasks - ``recreate_task_locally``: main user method for replaying any task """ def __init__(self, client): self.client = client self.client.extensions["replay-tasks"] = self # monkey patch self.client._get_raw_components_from_future = self._get_task_runspec self.client._prepare_raw_components = self._get_dependencies self.client._get_components_from_future = self._get_components_from_future self.client._get_errored_future = self._get_errored_future self.client.recreate_task_locally = self.recreate_task_locally self.client.recreate_error_locally = self.recreate_error_locally @property def scheduler(self): return self.client.scheduler async def _get_task_runspec(self, future): """ For a given future return the func, args and kwargs and future deps that would be executed remotely. """ if isinstance(future, Future): await wait(future) key = future.key else: validate_key(future) key = future run_spec = await self.scheduler.get_runspec(key=key) return run_spec async def _get_dependencies(self, dependencies): """ Take raw components and resolve future dependencies. """ futures = self.client._graph_to_futures({}, dependencies, span_metadata={}) data = await self.client._gather(futures) return data async def _get_components_from_future(self, future): """ For a given future return the func, args and kwargs that would be executed remotely. Any args/kwargs that are themselves futures will be resolved to the return value of those futures. """ runspec = await self._get_task_runspec(future) return runspec, await self._get_dependencies(runspec.dependencies) def recreate_task_locally(self, future): """ For any calculation, whether it succeeded or failed, perform the task locally for debugging. This operation should be performed after a future (result of ``gather``, ``compute``, etc) comes back with a status other than "pending". Cases where you might want to debug a successfully completed future could include a calculation that returns an unexpected results. A common debugging process might include running the task locally in debug mode, with `pdb.runcall`. Examples -------- >>> import pdb # doctest: +SKIP >>> future = c.submit(div, 1, 1) # doctest: +SKIP >>> future.status # doctest: +SKIP 'finished' >>> pdb.runcall(c.recreate_task_locally, future) # doctest: +SKIP Parameters ---------- future : future The same thing as was given to ``gather``. Returns ------- Any; will return the result of the task future. """ runspec, dependencies = sync( self.client.loop, self._get_components_from_future, future ) return runspec(dependencies) async def _get_errored_future(self, future): """ For a given future collection, return the first future that raised an error. """ await wait(future) futures = [f.key for f in futures_of(future) if f.status == "error"] if not futures: raise ValueError("No errored futures passed") cause_key = await self.scheduler.get_error_cause(keys=futures) return cause_key def recreate_error_locally(self, future): """ For a failed calculation, perform the blamed task locally for debugging. This operation should be performed after a future (result of ``gather``, ``compute``, etc) comes back with a status of "error", if the stack- trace is not informative enough to diagnose the problem. The specific task (part of the graph pointing to the future) responsible for the error will be fetched from the scheduler, together with the values of its inputs. The function will then be executed, so that ``pdb`` can be used for debugging. Examples -------- >>> future = c.submit(div, 1, 0) # doctest: +SKIP >>> future.status # doctest: +SKIP 'error' >>> c.recreate_error_locally(future) # doctest: +SKIP ZeroDivisionError: division by zero If you're in IPython you might take this opportunity to use pdb >>> %pdb # doctest: +SKIP Automatic pdb calling has been turned ON >>> c.recreate_error_locally(future) # doctest: +SKIP ZeroDivisionError: division by zero 1 def div(x, y): ----> 2 return x / y ipdb> Parameters ---------- future : future or collection that failed The same thing as was given to ``gather``, but came back with an exception/stack-trace. Can also be a (persisted) dask collection containing any errored futures. Returns ------- Nothing; the function runs and should raise an exception, allowing the debugger to run. """ errored_future_key = sync(self.client.loop, self._get_errored_future, future) return self.recreate_task_locally(errored_future_key)