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import logging
from typing import Callable, Optional, TypeVar, Tuple, ParamSpec, Dict, Any, List
from concurrent.futures import ThreadPoolExecutor, as_completed
from functools import reduce
P = ParamSpec("P")
T = TypeVar("T")
R = TypeVar("R")
def is_some(
callable: Callable[P, Optional[T]], *args: P.args, **kwargs: P.kwargs
) -> Tuple[bool, Optional[T]]:
result = callable(*args, **kwargs)
return result is not None, result
def merge_dicts(*dicts: Dict[str, Any]) -> Dict[str, Any]:
def merge(a: Dict[str, Any], b: Dict[str, Any]) -> Dict[str, Any]:
out = dict(a)
for k, v in b.items():
if k in out and isinstance(out[k], dict) and isinstance(v, dict):
out[k] = merge(out[k], v)
else:
out[k] = v
return out
return reduce(merge, dicts, {})
def parallelize(
worker: Callable[[T], R],
items: List[T],
logger: logging.Logger,
executor: Optional[ThreadPoolExecutor] = None,
) -> List[R]:
if executor is None:
from dots_manager.config import Constants
executor = ThreadPoolExecutor(max_workers=Constants.max_workers)
with executor as exec:
futures = [exec.submit(worker, item) for item in items]
logger.info(f"submitted {len(futures)} tasks to executor <_mood.excited>")
return [f.result() for f in as_completed(futures)]
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