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Raw output: local.c

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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:   >>> import gevent
 015:   >>> from gevent.local import local
 016:   >>> mydata = local()
 017:   >>> mydata.number = 42
 018:   >>> mydata.number
 019:   42
 020: 
 021: You can also access the local-object's dictionary:
 022: 
 023:   >>> mydata.__dict__
 024:   {'number': 42}
 025:   >>> mydata.__dict__.setdefault('widgets', [])
 026:   []
 027:   >>> mydata.widgets
 028:   []
 029: 
 030: What's important about greenlet-local objects is that their data are
 031: local to a greenlet. If we access the data in a different greenlet:
 032: 
 033:   >>> log = []
 034:   >>> def f():
 035:   ...     items = list(mydata.__dict__.items())
 036:   ...     items.sort()
 037:   ...     log.append(items)
 038:   ...     mydata.number = 11
 039:   ...     log.append(mydata.number)
 040:   >>> greenlet = gevent.spawn(f)
 041:   >>> greenlet.join()
 042:   >>> log
 043:   [[], 11]
 044: 
 045: we get different data.  Furthermore, changes made in the other greenlet
 046: don't affect data seen in this greenlet:
 047: 
 048:   >>> mydata.number
 049:   42
 050: 
 051: Of course, values you get from a local object, including a __dict__
 052: attribute, are for whatever greenlet was current at the time the
 053: attribute was read.  For that reason, you generally don't want to save
 054: these values across greenlets, as they apply only to the greenlet they
 055: came from.
 056: 
 057: You can create custom local objects by subclassing the local class:
 058: 
 059:   >>> class MyLocal(local):
 060:   ...     number = 2
 061:   ...     initialized = False
 062:   ...     def __init__(self, **kw):
 063:   ...         if self.initialized:
 064:   ...             raise SystemError('__init__ called too many times')
 065:   ...         self.initialized = True
 066:   ...         self.__dict__.update(kw)
 067:   ...     def squared(self):
 068:   ...         return self.number ** 2
 069: 
 070: This can be useful to support default values, methods and
 071: initialization.  Note that if you define an __init__ method, it will be
 072: called each time the local object is used in a separate greenlet.  This
 073: is necessary to initialize each greenlet's dictionary.
 074: 
 075: Now if we create a local object:
 076: 
 077:   >>> mydata = MyLocal(color='red')
 078: 
 079: Now we have a default number:
 080: 
 081:   >>> mydata.number
 082:   2
 083: 
 084: an initial color:
 085: 
 086:   >>> mydata.color
 087:   'red'
 088:   >>> del mydata.color
 089: 
 090: And a method that operates on the data:
 091: 
 092:   >>> mydata.squared()
 093:   4
 094: 
 095: As before, we can access the data in a separate greenlet:
 096: 
 097:   >>> log = []
 098:   >>> greenlet = gevent.spawn(f)
 099:   >>> greenlet.join()
 100:   >>> log
 101:   [[('color', 'red'), ('initialized', True)], 11]
 102: 
 103: without affecting this greenlet's data:
 104: 
 105:   >>> mydata.number
 106:   2
 107:   >>> mydata.color
 108:   Traceback (most recent call last):
 109:   ...
 110:   AttributeError: 'MyLocal' object has no attribute 'color'
 111: 
 112: Note that subclasses can define slots, but they are not greenlet
 113: local. They are shared across greenlets::
 114: 
 115:   >>> class MyLocal(local):
 116:   ...     __slots__ = 'number'
 117: 
 118:   >>> mydata = MyLocal()
 119:   >>> mydata.number = 42
 120:   >>> mydata.color = 'red'
 121: 
 122: So, the separate greenlet:
 123: 
 124:   >>> greenlet = gevent.spawn(f)
 125:   >>> greenlet.join()
 126: 
 127: affects what we see:
 128: 
 129:   >>> mydata.number
 130:   11
 131: 
 132: >>> del mydata
 133: 
 134: .. versionchanged:: 1.1a2
 135:    Update the implementation to match Python 3.4 instead of Python 2.5.
 136:    This results in locals being eligible for garbage collection as soon
 137:    as their greenlet exits.
 138: 
 139: .. versionchanged:: 1.2.3
 140:    Use a weak-reference to clear the greenlet link we establish in case
 141:    the local object dies before the greenlet does.
 142: 
 143: .. versionchanged:: 1.3a1
 144:    Implement the methods for attribute access directly, handling
 145:    descriptors directly here. This allows removing the use of a lock
 146:    and facilitates greatly improved performance.
 147: 
 148: .. versionchanged:: 1.3a1
 149:    The ``__init__`` method of subclasses of ``local`` is no longer
 150:    called with a lock held. CPython does not use such a lock in its
 151:    native implementation. This could potentially show as a difference
 152:    if code that uses multiple dependent attributes in ``__slots__``
 153:    (which are shared across all greenlets) switches during ``__init__``.
 154: 
 155: """
 156: from __future__ import print_function
 157: 
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 161: 
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 166:     "local",
 167: ]
 168: 
 169: # The key used in the Thread objects' attribute dicts.
 170: # We keep it a string for speed but make it unlikely to clash with
 171: # a "real" attribute.
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 174: # The overall structure is as follows:
 175: # For each local() object:
 176: # greenlet.__dict__[key_prefix + str(id(local))]
 177: #    => _localimpl.dicts[id(greenlet)] => (ref(greenlet), {})
 178: 
 179: # That final tuple is actually a localimpl_dict_entry object.
 180: 
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 183:     Internal debug helper for getting the local values associated
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 185: 
 186:     :return: A list of ((type, id), {}) pairs, where the first element
 187:       is the type and id of the local object and the second object is its
 188:       instance dictionary, as seen from this greenlet.
 189: 
 190:     .. versionadded:: 1.3a2
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