163 lines
5.8 KiB
Plaintext
163 lines
5.8 KiB
Plaintext
PEP: 412
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Title: Key-Sharing Dictionary
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Version: $Revision$
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Last-Modified: $Date$
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Author: Mark Shannon <mark@hotpy.org>
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Status: Draft
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Type: Standards Track
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Content-Type: text/x-rst
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Created: 08-Feb-2012
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Python-Version: 3.3 or 3.4
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Post-History: 08-Feb-2012
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Abstract
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========
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This PEP proposes a change in the implementation of the builtin dictionary
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type ``dict``. The new implementation allows dictionaries which are used as
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attribute dictionaries (the ``__dict__`` attribute of an object) to share
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keys with other attribute dictionaries of instances of the same class.
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Motivation
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==========
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The current dictionary implementation uses more memory than is necessary
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when used as a container for object attributes as the keys are
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replicated for each instance rather than being shared across many instances
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of the same class.
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Despite this, the current dictionary implementation is finely tuned and
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performs very well as a general-purpose mapping object.
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By separating the keys (and hashes) from the values it is possible to share
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the keys between multiple dictionaries and improve memory use.
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By ensuring that keys are separated from the values only when beneficial,
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it is possible to retain the high-performance of the current dictionary
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implementation when used as a general-purpose mapping object.
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Behaviour
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=========
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The new dictionary behaves in the same way as the old implementation.
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It fully conforms to the Python API, the C API and the ABI.
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Performance
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===========
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Memory Usage
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------------
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Reduction in memory use is directly related to the number of dictionaries
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with shared keys in existence at any time. These dictionaries are typically
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half the size of the current dictionary implementation.
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Benchmarking shows that memory use is reduced by 10% to 20% for
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object-oriented programs with no significant change in memory use
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for other programs.
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Speed
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-----
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The performance of the new implementation is dominated by memory locality
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effects. When keys are not shared (for example in module dictionaries
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and dictionary explicitly created by dict() or {} ) then performance is
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unchanged (within a percent or two) from the current implementation.
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For the shared keys case, the new implementation tends to separate keys
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from values, but reduces total memory usage. This will improve performance
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in many cases as the effects of reduced memory usage outweigh the loss of
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locality, but some programs may show a small slow down.
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Benchmarking shows no significant change of speed for most benchmarks.
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Object-oriented benchmarks show small speed ups when they create large
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numbers of objects of the same class (the gcbench benchmark shows a 10%
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speed up; this is likely to be an upper limit).
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Implementation
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==============
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Both the old and new dictionaries consist of a fixed-sized dict struct and
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a re-sizeable table.
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In the new dictionary the table can be further split into a keys table and
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values array.
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The keys table holds the keys and hashes and (for non-split tables) the
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values as well. It differs only from the original implementation in that it
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contains a number of fields that were previously in the dict struct.
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If a table is split the values in the keys table are ignored, instead the
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values are held in a separate array.
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Split-Table dictionaries
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------------------------
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When dictionaries are created to fill the __dict__ slot of an object, they are
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created in split form. The keys table is cached in the type, potentially
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allowing all attribute dictionaries of instances of one class to share keys.
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In the event of the keys of these dictionaries starting to diverge,
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individual dictionaries will lazily convert to the combined-table form.
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This ensures good memory use in the common case, and correctness in all cases.
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When resizing a split dictionary it is converted to a combined table.
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If resizing is as a result of storing an instance attribute, and there is
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only instance of a class, then the dictionary will be re-split immediately.
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Since most OO code will set attributes in the __init__ method, all attributes
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will be set before a second instance is created and no more resizing will be
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necessary as all further instance dictionaries will have the correct size.
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For more complex use patterns, it is impossible to know what is the best
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approach, so the implementation allows extra insertions up to the point
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of a resize when it reverts to the combined table (non-shared keys).
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A deletion from a split dictionary does not change the keys table, it simply
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removes the value from the values array.
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Combined-Table dictionaries
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---------------------------
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Explicit dictionaries (dict() or {}), module dictionaries and most other
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dictionaries are created as combined-table dictionaries.
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A combined-table dictionary never becomes a split-table dictionary.
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Combined tables are laid out in much the same way as the tables in the old
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dictionary, resulting in very similar performance.
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Implementation
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==============
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The new dictionary implementation is available at [1]_.
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Pros and Cons
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=============
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Pros
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----
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Significant memory savings for object-oriented applications.
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Small improvement to speed for programs which create lots of similar objects.
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Cons
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----
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Change to data structures:
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Third party modules which meddle with the internals of the dictionary
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implementation will break.
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Changes to repr() output and iteration order:
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For most cases, this will be unchanged.
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However for some split-table dictionaries the iteration order will
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change.
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Neither of these cons should be a problem.
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Modules which meddle with the internals of the dictionary
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implementation are already broken and should be fixed to use the API.
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The iteration order of dictionaries was never defined and has always been
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arbitrary; it is different for Jython and PyPy.
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References
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==========
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.. [1] Reference Implementation:
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https://bitbucket.org/markshannon/cpython_new_dict
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Copyright
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=========
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This document has been placed in the public domain.
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