diff --git a/cluster_tools/cluster_tools/__init__.py b/cluster_tools/cluster_tools/__init__.py index e698c9276..9c091f860 100644 --- a/cluster_tools/cluster_tools/__init__.py +++ b/cluster_tools/cluster_tools/__init__.py @@ -2,6 +2,7 @@ from typing_extensions import Literal +from cluster_tools.executors.dask import DaskExecutor from cluster_tools.executors.debug_sequential import DebugSequentialExecutor from cluster_tools.executors.multiprocessing_ import MultiprocessingExecutor from cluster_tools.executors.pickle_ import PickleExecutor @@ -70,6 +71,11 @@ def get_executor( ... +@overload +def get_executor(environment: Literal["dask"], **kwargs: Any) -> DaskExecutor: + ... + + @overload def get_executor( environment: Literal["multiprocessing"], **kwargs: Any @@ -105,6 +111,8 @@ def get_executor(environment: str, **kwargs: Any) -> "Executor": return PBSExecutor(**kwargs) elif environment == "kubernetes": return KubernetesExecutor(**kwargs) + elif environment == "dask": + return DaskExecutor(**kwargs) elif environment == "multiprocessing": global did_start_test_multiprocessing if not did_start_test_multiprocessing: @@ -121,4 +129,4 @@ def get_executor(environment: str, **kwargs: Any) -> "Executor": raise Exception("Unknown executor: {}".format(environment)) -Executor = Union[ClusterExecutor, MultiprocessingExecutor] +Executor = Union[ClusterExecutor, MultiprocessingExecutor, DaskExecutor] diff --git a/cluster_tools/cluster_tools/executors/dask.py b/cluster_tools/cluster_tools/executors/dask.py new file mode 100644 index 000000000..7aa66f152 --- /dev/null +++ b/cluster_tools/cluster_tools/executors/dask.py @@ -0,0 +1,103 @@ +import os +from concurrent import futures +from concurrent.futures import Future +from functools import partial +from typing import Any, Callable, Iterable, Iterator, List, Optional, TypeVar, cast + +from dask.distributed import Client, as_completed +from typing_extensions import ParamSpec + +from cluster_tools._utils.warning import enrich_future_with_uncaught_warning +from cluster_tools.executors.multiprocessing_ import CFutDict, MultiprocessingExecutor + +_T = TypeVar("_T") +_P = ParamSpec("_P") +_S = TypeVar("_S") + + +class DaskExecutor(futures.Executor): + client: Client + + def __init__( + self, + **kwargs: Any, + ) -> None: + self.client = Client(**kwargs) + + @classmethod + def as_completed(cls, futures: List[Future[_T]]) -> Iterator[Future[_T]]: + return as_completed(futures) + + def submit( # type: ignore[override] + self, + __fn: Callable[_P, _T], + *args: _P.args, + **kwargs: _P.kwargs, + ) -> "Future[_T]": + if "__cfut_options" in kwargs: + output_pickle_path = cast(CFutDict, kwargs["__cfut_options"])[ + "output_pickle_path" + ] + del kwargs["__cfut_options"] + + __fn = partial( + MultiprocessingExecutor._execute_and_persist_function, + output_pickle_path, + __fn, + ) + fut = self.client.submit(partial(__fn, *args, **kwargs)) + + enrich_future_with_uncaught_warning(fut) + return fut + + def map_unordered(self, fn: Callable[_P, _T], args: Any) -> Iterator[_T]: + futs: List["Future[_T]"] = self.map_to_futures(fn, args) + + # Return a separate generator to avoid that map_unordered + # is executed lazily (otherwise, jobs would be submitted + # lazily, as well). + def result_generator() -> Iterator: + for fut in as_completed(futs): + yield fut.result() + + return result_generator() + + def map_to_futures( + self, + fn: Callable[[_S], _T], + args: Iterable[_S], # TODO change: allow more than one arg per call + output_pickle_path_getter: Optional[Callable[[_S], os.PathLike]] = None, + ) -> List["Future[_T]"]: + if output_pickle_path_getter is not None: + futs = [ + self.submit( # type: ignore[call-arg] + fn, + arg, + __cfut_options={ + "output_pickle_path": output_pickle_path_getter(arg) + }, + ) + for arg in args + ] + else: + futs = [self.submit(fn, arg) for arg in args] + + return futs + + def map( + self, + fn: Callable[[_S], _T], + args: Iterable[_S], # TODO change: allow more than one arg per call, + timeout=None, + chunksize=1, + ): + return list(super().map(fn, args, timeout=timeout, chunksize=chunksize)) + + def forward_log(self, fut: "Future[_T]") -> _T: + return fut.result() + + def shutdown(self, wait: bool = True, *, cancel_futures: bool = False) -> None: + if wait: + self.client.close(timeout=60 * 60 * 24) + else: + self.client.close() diff --git a/cluster_tools/cluster_tools/executors/multiprocessing_.py b/cluster_tools/cluster_tools/executors/multiprocessing_.py index 4532c186a..d02e55d2c 100644 --- a/cluster_tools/cluster_tools/executors/multiprocessing_.py +++ b/cluster_tools/cluster_tools/executors/multiprocessing_.py @@ -85,6 +85,10 @@ def __init__( else: self._mp_logging_handler_pool = _MultiprocessingLoggingHandlerPool() + @classmethod + def as_completed(cls, futures: List[Future[_T]]) -> Iterator[Future[_T]]: + return futures.as_completed(futures) + def submit( # type: ignore[override] self, __fn: Callable[_P, _T], diff --git a/cluster_tools/cluster_tools/schedulers/cluster_executor.py b/cluster_tools/cluster_tools/schedulers/cluster_executor.py index e5945f142..662d438f4 100644 --- a/cluster_tools/cluster_tools/schedulers/cluster_executor.py +++ b/cluster_tools/cluster_tools/schedulers/cluster_executor.py @@ -140,6 +140,10 @@ def __init__( if "logging_setup_fn" in kwargs: self.meta_data["logging_setup_fn"] = kwargs["logging_setup_fn"] + @classmethod + def as_completed(cls, futures: List[Future[_T]]) -> Iterator[Future[_T]]: + return futures.as_completed(futures) + @classmethod @abstractmethod def executor_key(cls) -> str: diff --git a/cluster_tools/poetry.lock b/cluster_tools/poetry.lock index 2eaad71dc..15902bac9 100644 --- a/cluster_tools/poetry.lock +++ b/cluster_tools/poetry.lock @@ -156,6 +156,17 @@ files = [ colorama = {version = "*", markers = "platform_system == \"Windows\""} importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} +[[package]] +name = "cloudpickle" +version = "2.2.1" +description = "Extended pickling support for Python objects" +optional = false +python-versions = ">=3.6" +files = [ + {file = "cloudpickle-2.2.1-py3-none-any.whl", hash = "sha256:61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f"}, + {file = "cloudpickle-2.2.1.tar.gz", hash = "sha256:d89684b8de9e34a2a43b3460fbca07d09d6e25ce858df4d5a44240403b6178f5"}, +] + [[package]] name = "colorama" version = "0.4.6" @@ -167,6 +178,36 @@ files = [ {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, ] +[[package]] +name = "dask" +version = "2023.9.1" +description = "Parallel PyData with Task Scheduling" +optional = false +python-versions = ">=3.9" +files = [ + {file = "dask-2023.9.1-py3-none-any.whl", hash = "sha256:2b1085ef3a54cb8b96cb8651a803e644d77d992198bda2954715fd4fd6cb434c"}, + {file = "dask-2023.9.1.tar.gz", hash = "sha256:782825bbe52c23c5698166aa0cf95cfed02dcb9afa59b0814b69ae58e1bc9686"}, +] + 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b/cluster_tools/tests/test_all.py index 84962e757..f5ecfad8d 100644 --- a/cluster_tools/tests/test_all.py +++ b/cluster_tools/tests/test_all.py @@ -6,11 +6,13 @@ from enum import Enum from functools import partial from pathlib import Path -from typing import List +from typing import List, Optional import pytest +from dask.distributed import LocalCluster import cluster_tools +from cluster_tools.executors.dask import DaskExecutor # "Worker" functions. @@ -25,6 +27,8 @@ def sleep(duration: float) -> float: logging.basicConfig() +_dask_cluster: Optional[LocalCluster] = None + def raise_if(msg: str, _bool: bool) -> None: if _bool: @@ -32,9 +36,11 @@ def raise_if(msg: str, _bool: bool) -> None: def get_executors(with_debug_sequential: bool = False) -> List[cluster_tools.Executor]: + global _dask_cluster executor_keys = { "slurm", "kubernetes", + "dask", "multiprocessing", "sequential", "test_pickling", @@ -69,6 +75,10 @@ def get_executors(with_debug_sequential: bool = False) -> List[cluster_tools.Exe executors.append(cluster_tools.get_executor("multiprocessing", max_workers=5)) if "sequential" in executor_keys: executors.append(cluster_tools.get_executor("sequential")) + if "dask" in executor_keys: + if not _dask_cluster: + _dask_cluster = LocalCluster() + executors.append(cluster_tools.get_executor("dask", address=_dask_cluster)) if "test_pickling" in executor_keys: executors.append(cluster_tools.get_executor("test_pickling")) if "pbs" in executor_keys: @@ -199,9 +209,7 @@ def test_unordered_sleep() -> None: futures = [exc.submit(sleep, n) for n in durations] if not isinstance(exc, cluster_tools.SequentialExecutor): durations.sort() - for duration, future in zip( - durations, concurrent.futures.as_completed(futures) - ): + for duration, future in zip(durations, exc.as_completed(futures)): assert future.result() == duration @@ -226,7 +234,7 @@ def test_map_to_futures() -> None: futures = exc.map_to_futures(sleep, durations) results = [] - for i, duration in enumerate(concurrent.futures.as_completed(futures)): + for i, duration in enumerate(exc.as_completed(futures)): results.append(duration.result()) if not isinstance(exc, cluster_tools.SequentialExecutor): @@ -262,7 +270,7 @@ def test_map_to_futures_with_pickle_paths() -> None: ) results = [] - for i, duration in enumerate(concurrent.futures.as_completed(futures)): + for i, duration in enumerate(exc.as_completed(futures)): results.append(duration.result()) assert 2 in results