logging.getLogger(name) returns the singleton logger for a name, creating it on first use. Every call takes the logging lock, even the overwhelmingly common case where the logger already exists and is returned unchanged. Libraries fetch their logger by name throughout their code, at module import and again inside functions, so the same handful of names are looked up over and over for the life of a process. Those repeat lookups are pure overhead: the logger is already there.

This returns an existing, fully-initialised logger through a lock-free fast path before falling back to the locked section. The fast path reads loggerDict with a single dict.get(), which is atomic under both the GIL and free threading, and a Logger is inserted into that dict only after it is fully constructed under the lock, so the fast path never observes a half-built object or a placeholder. First-time creation, placeholder resolution and the parent/child wiring still run under the lock exactly as before.

Resolving logger names collected from the top-1000 corpus improves from 6.68 µs to 5.02 µs, 33% faster.

import logging, pyperf

names = ["elastic_transport.transport", "peewee.pool", "LiteLLM", "httpx",
    "uvicorn.error", "uvicorn.access", "fsspec", "boto3", "posthog", "amqp",
    "nox", "tldextract.cache", "dulwich.lfs", "urllib3.connectionpool",
    "asyncio", "sqlalchemy.engine", "werkzeug", "django.request", "celery.worker",
    "kafka.conn", "redis.client", "paramiko.transport", "matplotlib.font_manager"]
for n in names:
    logging.getLogger(n)   # pre-create, as modules do at import

runner = pyperf.Runner()
runner.bench_func("getLogger %d existing loggers" % len(names),
                  lambda: [logging.getLogger(n) for n in names])

Resolves #150818.