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m Z d S ) a% Thread-local objects.
(Note that this module provides a Python version of the threading.local
class. Depending on the version of Python you're using, there may be a
faster one available. You should always import the `local` class from
`threading`.)
Thread-local objects support the management of thread-local data.
If you have data that you want to be local to a thread, simply create
a thread-local object and use its attributes:
>>> mydata = local()
>>> mydata.number = 42
>>> mydata.number
42
You can also access the local-object's dictionary:
>>> mydata.__dict__
{'number': 42}
>>> mydata.__dict__.setdefault('widgets', [])
[]
>>> mydata.widgets
[]
What's important about thread-local objects is that their data are
local to a thread. 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 local object, including a __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 local objects by subclassing the 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 __init__ method, it will be
called each time the local object is used in a separate thread. This
is necessary to initialize each thread's dictionary.
Now if we create a local object:
>>> mydata = MyLocal(color='red')
Now 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 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
>>> del mydata
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