235 lines
8.3 KiB
Plaintext
235 lines
8.3 KiB
Plaintext
PEP: 213
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Title: Attribute Access Handlers
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Version: $Revision$
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Author: paul@prescod.net (Paul Prescod)
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Status: Draft
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Type: Standards Track
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Python-Version: 2.1
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Created: 21-Jul-2000
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Post-History:
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Introduction
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It is possible (and even relatively common) in Python code and
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in extension modules to "trap" when an instance's client code
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attempts to set an attribute and execute code instead. In other
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words it is possible to allow users to use attribute assignment/
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retrieval/deletion syntax even though the underlying implementation
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is doing some computation rather than directly modifying a
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binding.
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This PEP describes a feature that makes it easier, more efficient
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and safer to implement these handlers for Python instances.
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Justification
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cenario 1:
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You have a deployed class that works on an attribute named
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"stdout". After a while, you think it would be better to
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check that stdout is really an object with a "write" method
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at the moment of assignment. Rather than change to a
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setstdout method (which would be incompatible with deployed
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code) you would rather trap the assignment and check the
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object's type.
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Scenario 2:
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You want to be as compatible as possible with an object
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model that has a concept of attribute assignment. It could
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be the W3C Document Object Model or a particular COM
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interface (e.g. the PowerPoint interface). In that case
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you may well want attributes in the model to show up as
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attributes in the Python interface, even though the
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underlying implementation may not use attributes at all.
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Scenario 3:
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A user wants to make an attribute read-only.
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In short, this feature allows programmers to separate the
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interface of their module from the underlying implementation
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for whatever purpose. Again, this is not a new feature but
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merely a new syntax for an existing convention.
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Current Solution
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To make some attributes read-only:
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class foo:
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def __setattr__( self, name, val ):
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if name=="readonlyattr":
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raise TypeError
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elif name=="readonlyattr2":
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raise TypeError
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...
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else:
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self.__dict__["name"]=val
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This has the following problems:
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1. The creator of the method must be intimately aware of whether
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somewhere else in the class hiearchy __setattr__ has also been
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trapped for any particular purpose. If so, she must specifically
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call that method rather than assigning to the dictionary. There
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are many different reasons to overload __setattr__ so there is a
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decent potential for clashes. For instance object database
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implementations often overload setattr for an entirely unrelated
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purpose.
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2. The string-based switch statement forces all attribute handlers
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to be specified in one place in the code. They may then dispatch
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to task-specific methods (for modularity) but this could cause
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performance problems.
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3. Logic for the setting, getting and deleting must live in
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__getattr__, __setattr__ and __delattr__. Once again, this can be
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mitigated through an extra level of method call but this is
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inefficient.
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Proposed Syntax
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Special methods should declare themselves with declarations of the
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following form:
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class x:
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def __attr_XXX__(self, op, val ):
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if op=="get":
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return someComputedValue(self.internal)
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elif op=="set":
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self.internal=someComputedValue(val)
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elif op=="del":
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del self.internal
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Client code looks like this:
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fooval=x.foo
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x.foo=fooval+5
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del x.foo
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Semantics
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Attribute references of all three kinds should call the method.
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The op parameter can be "get"/"set"/"del". Of course this string
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will be interned so the actual checks for the string will be
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very fast.
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It is disallowed to actually have an attribute named XXX in the
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same instance as a method named __attr_XXX__.
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An implementation of __attr_XXX__ takes precedence over an
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implementation of __getattr__ based on the principle that
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__getattr__ is supposed to be invoked only after finding an
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appropriate attribute has failed.
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An implementation of __attr_XXX__ takes precedence over an
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implementation of __setattr__ in order to be consistent. The
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opposite choice seems fairly feasible also, however. The same
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goes for __del_y__.
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Proposed Implementation
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There is a new object type called an attribute access handler.
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Objects of this type have the following attributes:
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name (e.g. XXX, not __attr__XXX__
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method (pointer to a method object
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In PyClass_New, methods of the appropriate form will be detected and
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converted into objects (just like unbound method objects). These are
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stored in the class __dict__ under the name XXX. The original method
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is stored as an unbound method under its original name.
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If there are any attribute access handlers in an instance at all,
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a flag is set. Let's call it "I_have_computed_attributes" for
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now. Derived classes inherit the flag from base classes. Instances
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inherit the flag from classes.
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A get proceeds as usual until just before the object is returned.
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In addition to the current check whether the returned object is a
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method it would also check whether a returned object is an access
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handler. If so, it would invoke the getter method and return
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the value. To remove an attribute access handler you could directly
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fiddle with the dictionary.
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A set proceeds by checking the "I_have_computed_attributes" flag. If
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it is not set, everything proceeds as it does today. If it is set
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then we must do a dictionary get on the requested object name. If it
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returns an attribute access handler then we call the setter function
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with the value. If it returns any other object then we discard the
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result and continue as we do today. Note that having an attribute
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access handler will mildly affect attribute "setting" performance for
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all sets on a particular instance, but no more so than today, using
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__setattr__. Gets are more efficient than they are today with
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__getattr__.
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The I_have_computed_attributes flag is intended to eliminate the
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performance degradation of an extra "get" per "set" for objects not
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using this feature. Checking this flag should have miniscule
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performance implications for all objects.
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The implementation of delete is analogous to the implementation
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of set.
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Caveats
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1. You might note that I have not proposed any logic to keep
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the I_have_computed_attributes flag up to date as attributes
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are added and removed from the instance's dictionary. This is
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consistent with current Python. If you add a __setattr__ method
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to an object after it is in use, that method will not behave as
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it would if it were available at "compile" time. The dynamism is
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arguably not worth the extra implementation effort. This snippet
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demonstrates the current behavior:
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>>> def prn(*args):print args
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>>> class a:
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... __setattr__=prn
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>>> a().foo=5
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(<__main__.a instance at 882890>, 'foo', 5)
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>>> class b: pass
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>>> bi=b()
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>>> bi.__setattr__=prn
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>>> b.foo=5
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2. Assignment to __dict__["XXX"] can overwrite the attribute
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access handler for __attr_XXX__. Typically the access handlers will
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store information away in private __XXX variables
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3. An attribute access handler that attempts to call setattr or getattr
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on the object itself can cause an infinite loop (as with __getattr__)
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Once again, the solution is to use a special (typically private)
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variable such as __XXX.
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Note
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The descriptor mechanism described in PEP 252 is powerful enough
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to support this more directly. A 'getset' constructor may be
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added to the language making this possible:
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class C:
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def get_x(self):
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return self.__x
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def set_x(self, v):
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self.__x = v
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x = getset(get_x, set_x)
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Additional syntactic sugar might be added, or a naming convention
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could be recognized.
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Local Variables:
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mode: indented-text
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indent-tabs-mode: nil
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End:
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