filelock

This package contains a single module, which implements a platform independent file lock in Python, which provides a simple way of inter-process communication:

from filelock import Timeout, FileLock

lock = FileLock("high_ground.txt.lock")
with lock:
    with open("high_ground.txt", "a") as f:
        f.write("You were the chosen one.")

Don’t use a FileLock to lock the file you want to write to, instead create a separate .lock file as shown above.

Similar libraries

Perhaps you are looking for something like:

• the pid 3rd party library,

• for Windows the msvcrt module in the standard library,

• for UNIX the fcntl module in the standard library,

• the flufl.lock 3rd party library.

Installation

filelock is available via PyPI, so you can pip install it:

python -m pip install filelock

Tutorial

A FileLock is used to indicate another process of your application that a resource or working directory is currently used. To do so, create a FileLock first:

from filelock import Timeout, FileLock

file_path = "high_ground.txt"
lock_path = "high_ground.txt.lock"

lock = FileLock(lock_path, timeout=1)

The lock object supports multiple ways for acquiring the lock, including the ones used to acquire standard Python thread locks:

with lock:
    with open(file_path, "a") as f:
        f.write("Hello there!")

lock.acquire()
try:
    with open(file_path, "a") as f:
        f.write("General Kenobi!")
finally:
    lock.release()


@lock
def decorated():
    print("You're a decorated Jedi!")


decorated()

The acquire method accepts also a timeout parameter. If the lock cannot be acquired within timeout seconds, a Timeout exception is raised:

try:
    with lock.acquire(timeout=10):
        with open(file_path, "a") as f:
            f.write("I have a bad feeling about this.")
except Timeout:
    print("Another instance of this application currently holds the lock.")

The lock objects are recursive locks, which means that once acquired, they will not block on successive lock requests:

def cite1():
    with lock:
        with open(file_path, "a") as f:
            f.write("I hate it when he does that.")


def cite2():
    with lock:
        with open(file_path, "a") as f:
            f.write("You don't want to sell me death sticks.")


# The lock is acquired here.
with lock:
    cite1()
    cite2()
# And released here.

Logging

All log messages by this library are made using the DEBUG_ level, under the filelock name. On how to control displaying/hiding that please consult the logging documentation of the standard library. E.g. to hide these messages you can use:

logging.getLogger("filelock").setLevel(logging.INFO)

FileLock vs SoftFileLock

The FileLock is platform dependent while the SoftFileLock is not. Use the FileLock if all instances of your application are running on the same platform and a SoftFileLock otherwise.

The SoftFileLock only watches the existence of the lock file. This makes it ultra portable, but also more prone to dead locks if the application crashes. You can simply delete the lock file in such cases.

Asyncio support

This library currently does not support asyncio. We’d recommend adding an asyncio variant though if someone can make a pull request for it, see here.

FileLocks and threads

By default the FileLock internally uses threading.local to ensure that the lock is thread-local. If you have a use case where you’d like an instance of FileLock to be shared across threads, you can set the thread_local parameter to False when creating a lock. For example:

lock = FileLock("test.lock", thread_local=False)
# lock will be re-entrant across threads

# The same behavior would also work with other instances of BaseFileLock like SoftFileLock:
soft_lock = SoftFileLock("soft_test.lock", thread_local=False)
# soft_lock will be re-entrant across threads.

Behavior where FileLock is thread-local started in version 3.11.0. Previous versions, were not thread-local by default.

Note: If disabling thread-local, be sure to remember that locks are re-entrant: You will be able to acquire the same lock multiple times across multiple threads.

Contributions and issues

Contributions are always welcome, please make sure they pass all tests before creating a pull request. This module is hosted on GitHub. If you have any questions or suggestions, don’t hesitate to open a new issue 😊. There’s no bad question, just a missed opportunity to learn more.