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import asyncio
from abc import ABC, abstractmethod
from collections import defaultdict
import asyncio
from abc import ABC, abstractmethod
from collections import defaultdict
-from concurrent.futures import Executor, ProcessPoolExecutor
+from concurrent.futures import Executor, ThreadPoolExecutor, ProcessPoolExecutor
from contextlib import contextmanager
from datetime import datetime
from enum import Enum
from contextlib import contextmanager
from datetime import datetime
from enum import Enum
sources: Set[Path], fast: bool, write_back: WriteBack, mode: Mode, report: "Report"
) -> None:
"""Reformat multiple files using a ProcessPoolExecutor."""
sources: Set[Path], fast: bool, write_back: WriteBack, mode: Mode, report: "Report"
) -> None:
"""Reformat multiple files using a ProcessPoolExecutor."""
loop = asyncio.get_event_loop()
worker_count = os.cpu_count()
if sys.platform == "win32":
loop = asyncio.get_event_loop()
worker_count = os.cpu_count()
if sys.platform == "win32":
executor = ProcessPoolExecutor(max_workers=worker_count)
except OSError:
# we arrive here if the underlying system does not support multi-processing
executor = ProcessPoolExecutor(max_workers=worker_count)
except OSError:
# we arrive here if the underlying system does not support multi-processing
- # like in AWS Lambda, in which case we gracefully fallback to the default
- # mono-process Executor by using None
- executor = None
+ # like in AWS Lambda, in which case we gracefully fallback to
+ # a ThreadPollExecutor with just a single worker (more workers would not do us
+ # any good due to the Global Interpreter Lock)
+ executor = ThreadPoolExecutor(max_workers=1)
try:
loop.run_until_complete(
try:
loop.run_until_complete(
mode: Mode,
report: "Report",
loop: asyncio.AbstractEventLoop,
mode: Mode,
report: "Report",
loop: asyncio.AbstractEventLoop,
- executor: Optional[Executor] ,
) -> None:
"""Run formatting of `sources` in parallel using the provided `executor`.
) -> None:
"""Run formatting of `sources` in parallel using the provided `executor`.