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Raw output: local.c
+001: # cython: auto_pickle=False,embedsignature=True,always_allow_keywords=False
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002: """
003: Greenlet-local objects.
004:
005: This module is based on `_threading_local.py`__ from the standard
006: library of Python 3.4.
007:
008: __ https://github.com/python/cpython/blob/3.4/Lib/_threading_local.py
009:
010: Greenlet-local objects support the management of greenlet-local data.
011: If you have data that you want to be local to a greenlet, simply create
012: a greenlet-local object and use its attributes:
013:
014: >>> mydata = local()
015: >>> mydata.number = 42
016: >>> mydata.number
017: 42
018:
019: You can also access the local-object's dictionary:
020:
021: >>> mydata.__dict__
022: {'number': 42}
023: >>> mydata.__dict__.setdefault('widgets', [])
024: []
025: >>> mydata.widgets
026: []
027:
028: What's important about greenlet-local objects is that their data are
029: local to a greenlet. If we access the data in a different greenlet:
030:
031: >>> log = []
032: >>> def f():
033: ... items = list(mydata.__dict__.items())
034: ... items.sort()
035: ... log.append(items)
036: ... mydata.number = 11
037: ... log.append(mydata.number)
038: >>> greenlet = gevent.spawn(f)
039: >>> greenlet.join()
040: >>> log
041: [[], 11]
042:
043: we get different data. Furthermore, changes made in the other greenlet
044: don't affect data seen in this greenlet:
045:
046: >>> mydata.number
047: 42
048:
049: Of course, values you get from a local object, including a __dict__
050: attribute, are for whatever greenlet was current at the time the
051: attribute was read. For that reason, you generally don't want to save
052: these values across greenlets, as they apply only to the greenlet they
053: came from.
054:
055: You can create custom local objects by subclassing the local class:
056:
057: >>> class MyLocal(local):
058: ... number = 2
059: ... initialized = False
060: ... def __init__(self, **kw):
061: ... if self.initialized:
062: ... raise SystemError('__init__ called too many times')
063: ... self.initialized = True
064: ... self.__dict__.update(kw)
065: ... def squared(self):
066: ... return self.number ** 2
067:
068: This can be useful to support default values, methods and
069: initialization. Note that if you define an __init__ method, it will be
070: called each time the local object is used in a separate greenlet. This
071: is necessary to initialize each greenlet's dictionary.
072:
073: Now if we create a local object:
074:
075: >>> mydata = MyLocal(color='red')
076:
077: Now we have a default number:
078:
079: >>> mydata.number
080: 2
081:
082: an initial color:
083:
084: >>> mydata.color
085: 'red'
086: >>> del mydata.color
087:
088: And a method that operates on the data:
089:
090: >>> mydata.squared()
091: 4
092:
093: As before, we can access the data in a separate greenlet:
094:
095: >>> log = []
096: >>> greenlet = gevent.spawn(f)
097: >>> greenlet.join()
098: >>> log
099: [[('color', 'red'), ('initialized', True)], 11]
100:
101: without affecting this greenlet's data:
102:
103: >>> mydata.number
104: 2
105: >>> mydata.color
106: Traceback (most recent call last):
107: ...
108: AttributeError: 'MyLocal' object has no attribute 'color'
109:
110: Note that subclasses can define slots, but they are not greenlet
111: local. They are shared across greenlets::
112:
113: >>> class MyLocal(local):
114: ... __slots__ = 'number'
115:
116: >>> mydata = MyLocal()
117: >>> mydata.number = 42
118: >>> mydata.color = 'red'
119:
120: So, the separate greenlet:
121:
122: >>> greenlet = gevent.spawn(f)
123: >>> greenlet.join()
124:
125: affects what we see:
126:
127: >>> mydata.number
128: 11
129:
130: >>> del mydata
131:
132: .. versionchanged:: 1.1a2
133: Update the implementation to match Python 3.4 instead of Python 2.5.
134: This results in locals being eligible for garbage collection as soon
135: as their greenlet exits.
136:
137: .. versionchanged:: 1.2.3
138: Use a weak-reference to clear the greenlet link we establish in case
139: the local object dies before the greenlet does.
140:
141: .. versionchanged:: 1.3a1
142: Implement the methods for attribute access directly, handling
143: descriptors directly here. This allows removing the use of a lock
144: and facilitates greatly improved performance.
145:
146: .. versionchanged:: 1.3a1
147: The ``__init__`` method of subclasses of ``local`` is no longer
148: called with a lock held. CPython does not use such a lock in its
149: native implementation. This could potentially show as a difference
150: if code that uses multiple dependent attributes in ``__slots__``
151: (which are shared across all greenlets) switches during ``__init__``.
152:
153: """
154: from __future__ import print_function
155:
+156: from copy import copy
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158:
159:
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164: "local",
165: ]
166:
167: # The key used in the Thread objects' attribute dicts.
168: # We keep it a string for speed but make it unlikely to clash with
169: # a "real" attribute.
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172: # The overall structure is as follows:
173: # For each local() object:
174: # greenlet.__dict__[key_prefix + str(id(local))]
175: # => _localimpl.dicts[id(greenlet)] => (ref(greenlet), {})
176:
177: # That final tuple is actually a localimpl_dict_entry object.
178:
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185: is the type and id of the local object and the second object is its
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187:
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