keychron_qmk_firmware/lib/python/qmk/util.py
2024-11-08 04:57:22 +00:00

99 lines
2.9 KiB
Python

"""Utility functions.
"""
import contextlib
import multiprocessing
import sys
from milc import cli
maybe_exit_should_exit = True
maybe_exit_reraise = False
# Controls whether or not early `exit()` calls should be made
def maybe_exit(rc):
if maybe_exit_should_exit:
sys.exit(rc)
if maybe_exit_reraise:
e = sys.exc_info()[1]
if e:
raise e
def maybe_exit_config(should_exit: bool = True, should_reraise: bool = False):
global maybe_exit_should_exit
global maybe_exit_reraise
maybe_exit_should_exit = should_exit
maybe_exit_reraise = should_reraise
def truthy(value, value_if_unknown=False):
"""Returns True if the value is truthy, False otherwise.
Deals with:
True: 1, true, t, yes, y, on
False: 0, false, f, no, n, off
"""
if value in {False, True}:
return bool(value)
test_value = str(value).strip().lower()
if test_value in {"1", "true", "t", "yes", "y", "on"}:
return True
if test_value in {"0", "false", "f", "no", "n", "off"}:
return False
return value_if_unknown
@contextlib.contextmanager
def parallelize():
"""Returns a function that can be used in place of a map() call.
Attempts to use `mpire`, falling back to `multiprocessing` if it's not
available. If parallelization is not requested, returns the original map()
function.
"""
# Work out if we've already got a config value for parallel searching
if cli.config.user.parallel_search is None:
parallel_search = True
else:
parallel_search = cli.config.user.parallel_search
# Non-parallel searches use `map()`
if not parallel_search:
yield map
return
# Prefer mpire's `WorkerPool` if it's available
with contextlib.suppress(ImportError):
from mpire import WorkerPool
from mpire.utils import make_single_arguments
with WorkerPool() as pool:
def _worker(func, *args):
# Ensure we don't unpack tuples -- mpire's `WorkerPool` tries to do so normally so we tell it not to.
for r in pool.imap_unordered(func, make_single_arguments(*args, generator=False), progress_bar=True):
yield r
yield _worker
return
# Otherwise fall back to multiprocessing's `Pool`
with multiprocessing.Pool() as pool:
yield pool.imap_unordered
def parallel_map(*args, **kwargs):
"""Effectively runs `map()` but executes it in parallel if necessary.
"""
with parallelize() as map_fn:
# This needs to be enclosed in a `list()` as some implementations return
# a generator function, which means the scope of the pool is closed off
# before the results are returned. Returning a list ensures results are
# materialised before any worker pool is shut down.
return list(map_fn(*args, **kwargs))