gh-107006: Move threading.local docstring to docs (#131840)

Co-authored-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com>
This commit is contained in:
Lysandros Nikolaou 2025-05-05 14:00:15 +02:00 committed by GitHub
parent 8467026ed6
commit b97328ef5d
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
3 changed files with 120 additions and 131 deletions

View file

@ -260,23 +260,132 @@ All of the methods described below are executed atomically.
Thread-Local Data
-----------------
Thread-local data is data whose values are thread specific. To manage
thread-local data, just create an instance of :class:`local` (or a
subclass) and store attributes on it::
Thread-local data is data whose values are thread specific. If you
have data that you want to be local to a thread, create a
:class:`local` object and use its attributes::
mydata = threading.local()
mydata.x = 1
>>> mydata = local()
>>> mydata.number = 42
>>> mydata.number
42
The instance's values will be different for separate threads.
You can also access the :class:`local`-object's dictionary::
>>> mydata.__dict__
{'number': 42}
>>> mydata.__dict__.setdefault('widgets', [])
[]
>>> mydata.widgets
[]
If we access the data in a different thread::
>>> log = []
>>> def f():
... items = sorted(mydata.__dict__.items())
... log.append(items)
... mydata.number = 11
... log.append(mydata.number)
>>> import threading
>>> thread = threading.Thread(target=f)
>>> thread.start()
>>> thread.join()
>>> log
[[], 11]
we get different data. Furthermore, changes made in the other thread
don't affect data seen in this thread::
>>> mydata.number
42
Of course, values you get from a :class:`local` object, including their
:attr:`~object.__dict__` attribute, are for whatever thread was current
at the time the attribute was read. For that reason, you generally
don't want to save these values across threads, as they apply only to
the thread they came from.
You can create custom :class:`local` objects by subclassing the
:class:`local` class::
>>> class MyLocal(local):
... number = 2
... def __init__(self, /, **kw):
... self.__dict__.update(kw)
... def squared(self):
... return self.number ** 2
This can be useful to support default values, methods and
initialization. Note that if you define an :py:meth:`~object.__init__`
method, it will be called each time the :class:`local` object is used
in a separate thread. This is necessary to initialize each thread's
dictionary.
Now if we create a :class:`local` object::
>>> mydata = MyLocal(color='red')
we have a default number::
>>> mydata.number
2
an initial color::
>>> mydata.color
'red'
>>> del mydata.color
And a method that operates on the data::
>>> mydata.squared()
4
As before, we can access the data in a separate thread::
>>> log = []
>>> thread = threading.Thread(target=f)
>>> thread.start()
>>> thread.join()
>>> log
[[('color', 'red')], 11]
without affecting this thread's data::
>>> mydata.number
2
>>> mydata.color
Traceback (most recent call last):
...
AttributeError: 'MyLocal' object has no attribute 'color'
Note that subclasses can define :term:`__slots__`, but they are not
thread local. They are shared across threads::
>>> class MyLocal(local):
... __slots__ = 'number'
>>> mydata = MyLocal()
>>> mydata.number = 42
>>> mydata.color = 'red'
So, the separate thread::
>>> thread = threading.Thread(target=f)
>>> thread.start()
>>> thread.join()
affects what we see::
>>> mydata.number
11
.. class:: local()
A class that represents thread-local data.
For more details and extensive examples, see the documentation string of the
:mod:`!_threading_local` module: :source:`Lib/_threading_local.py`.
.. _thread-objects: