[Python-Dev] PEP 509: Add a private version to dict (version 3)
Victor Stinner
victor.stinner at gmail.com
Tue Apr 19 06:27:38 EDT 2016
Hi,
Below if the third version of my PEP 509 (dict version).
Changes since the version 2:
* __setitem__() and update() now always increases the version: remove
the micro-optimization on "dict[key] is new_value". Exception: version
is not changed with dict.update() is called without argument.
* be more explict on version++: explain that the operation must be
atomic, and that dict methods are already atomic thanks to the GIL
* Usage of the dict version: add Cython
* "Guard against changing dict during iteration": don't guess if the
new dict version can be used or not. Let's discuss that later.
* rephrase/complete some sections
* add links to new threads on python-dev
I hope that I addressed all Jim's concerns about the version 2.
Note: I also updated the implementation. The implementation now
contains more tests for identical values and more tests on equal
values.
HTML version:
https://www.python.org/dev/peps/pep-0509/
PEP: 509
Title: Add a private version to dict
Version: $Revision$
Last-Modified: $Date$
Author: Victor Stinner <victor.stinner at gmail.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 4-January-2016
Python-Version: 3.6
Abstract
========
Add a new private version to the builtin ``dict`` type, incremented at
each dictionary creation and at each dictionary change, to implement
fast guards on namespaces.
Rationale
=========
In Python, the builtin ``dict`` type is used by many instructions. For
example, the ``LOAD_GLOBAL`` instruction looks up a variable in the
global namespace, or in the builtins namespace (two dict lookups).
Python uses ``dict`` for the builtins namespace, globals namespace, type
namespaces, instance namespaces, etc. The local namespace (function
namespace) is usually optimized to an array, but it can be a dict too.
Python is hard to optimize because almost everything is mutable: builtin
functions, function code, global variables, local variables, ... can be
modified at runtime. Implementing optimizations respecting the Python
semantics requires to detect when "something changes": we will call
these checks "guards".
The speedup of optimizations depends on the speed of guard checks. This
PEP proposes to add a private version to dictionaries to implement fast
guards on namespaces.
Dictionary lookups can be skipped if the version does not change which
is the common case for most namespaces. The version is globally unique,
so checking the version is also enough to check if the namespace
dictionary was not replaced with a new dictionary.
When the dictionary version does not change, the performance of a guard
does not depend on the number of watched dictionary entries: the
complexity is O(1).
Example of optimization: copy the value of a global variable to function
constants. This optimization requires a guard on the global variable to
check if it was modified. If the global variable is not modified, the
function uses the cached copy. If the global variable is modified, the
function uses a regular lookup, and maybe also deoptimize the function
(to remove the overhead of the guard check for next function calls).
See the `PEP 510 -- Specialized functions with guards
<https://www.python.org/dev/peps/pep-0510/>`_ for the concrete usage of
guards to specialize functions and for a more general rationale on
Python static optimizers.
Guard example
=============
Pseudo-code of an fast guard to check if a dictionary entry was modified
(created, updated or deleted) using an hypothetical
``dict_get_version(dict)`` function::
UNSET = object()
class GuardDictKey:
def __init__(self, dict, key):
self.dict = dict
self.key = key
self.value = dict.get(key, UNSET)
self.version = dict_get_version(dict)
def check(self):
"""Return True if the dictionary entry did not change
and the dictionary was not replaced."""
# read the version of the dictionary
version = dict_get_version(self.dict)
if version == self.version:
# Fast-path: dictionary lookup avoided
return True
# lookup in the dictionary
value = self.dict.get(self.key, UNSET)
if value is self.value:
# another key was modified:
# cache the new dictionary version
self.version = version
return True
# the key was modified
return False
Usage of the dict version
=========================
Speedup method calls
--------------------
Yury Selivanov wrote a `patch to optimize method calls
<https://bugs.python.org/issue26110>`_. The patch depends on the
`"implement per-opcode cache in ceval"
<https://bugs.python.org/issue26219>`_ patch which requires dictionary
versions to invalidate the cache if the globals dictionary or the
builtins dictionary has been modified.
The cache also requires that the dictionary version is globally unique.
It is possible to define a function in a namespace and call it in a
different namespace, using ``exec()`` with the *globals* parameter for
example. In this case, the globals dictionary was replaced and the cache
must also be invalidated.
Specialized functions using guards
----------------------------------
The `PEP 510 -- Specialized functions with guards
<https://www.python.org/dev/peps/pep-0510/>`_ proposes an API to support
specialized functions with guards. It allows to implement static
optimizers for Python without breaking the Python semantics.
The `fatoptimizer <http://fatoptimizer.readthedocs.org/>`_ of the `FAT
Python <http://faster-cpython.readthedocs.org/fat_python.html>`_ project
is an example of a static Python optimizer. It implements many
optimizations which require guards on namespaces:
* Call pure builtins: to replace ``len("abc")`` with ``3``, guards on
``builtins.__dict__['len']`` and ``globals()['len']`` are required
* Loop unrolling: to unroll the loop ``for i in range(...): ...``,
guards on ``builtins.__dict__['range']`` and ``globals()['range']``
are required
* etc.
Pyjion
------
According of Brett Cannon, one of the two main developers of Pyjion,
Pyjion can benefit from dictionary version to implement optimizations.
`Pyjion <https://github.com/Microsoft/Pyjion>`_ is a JIT compiler for
Python based upon CoreCLR (Microsoft .NET Core runtime).
Cython
------
Cython can benefit from dictionary version to implement optimizations.
`Cython <http://cython.org/>`_ is an optimising static compiler for both
the Python programming language and the extended Cython programming
language.
Unladen Swallow
---------------
Even if dictionary version was not explicitly mentioned, optimizing
globals and builtins lookup was part of the Unladen Swallow plan:
"Implement one of the several proposed schemes for speeding lookups of
globals and builtins." (source: `Unladen Swallow ProjectPlan
<https://code.google.com/p/unladen-swallow/wiki/ProjectPlan>`_).
Unladen Swallow is a fork of CPython 2.6.1 adding a JIT compiler
implemented with LLVM. The project stopped in 2011: `Unladen Swallow
Retrospective
<http://qinsb.blogspot.com.au/2011/03/unladen-swallow-retrospective.html>`_.
Changes
=======
Add a ``ma_version_tag`` field to the ``PyDictObject`` structure with
the C type ``PY_UINT64_T``, 64-bit unsigned integer. Add also a global
dictionary version. Each time a dictionary is created, the global
version is incremented and the dictionary version is initialized to the
global version. The global version is also incremented and copied to the
dictionary version at each dictionary change:
* ``clear()`` if the dict is non-empty
* ``pop(key)`` if the key exists
* ``popitem()`` if the dict is non-empty
* ``setdefault(key, value)`` if the key does not exist
* ``__delitem__(key)`` if the key exists
* ``__setitem__(key, value)`` always increases the version
* ``update(...)`` if called with arguments
The version increase must be atomic. In CPython, the Global Interpreter
Lock (GIL) already protects ``dict`` methods to make them atomic.
Example using an hypothetical ``dict_get_version(dict)`` function::
>>> d = {}
>>> dict_get_version(d)
100
>>> d['key'] = 'value'
>>> dict_get_version(d)
101
>>> d['key'] = 'new value'
>>> dict_get_version(d)
102
>>> del d['key']
>>> dict_get_version(d)
103
``dict.__setitem__(key, value)`` and ``dict.update(...)`` always
increases the version, even if the new value is identical or is equal to
the current value (even if ``(dict[key] is value) or (dict[key] ==
value)``).
The field is called ``ma_version_tag``, rather than ``ma_version``, to
suggest to compare it using ``version_tag == old_version_tag``, rather
than ``version <= old_version`` which is wrong most of the time after an
integer overflow.
Backwards Compatibility
=======================
Since the ``PyDictObject`` structure is not part of the stable ABI and
the new dictionary version not exposed at the Python scope, changes are
backward compatible.
Implementation and Performance
==============================
The `issue #26058: PEP 509: Add ma_version_tag to PyDictObject
<https://bugs.python.org/issue26058>`_ contains a patch implementing
this PEP.
On pybench and timeit microbenchmarks, the patch does not seem to add
any overhead on dictionary operations. For example, the following timeit
micro-benchmarks takes 318 nanoseconds before and after the change::
python3.6 -m timeit 'd={1: 0}; d[2]=0; d[3]=0; d[4]=0; del d[1];
del d[2]; d.clear()'
When the version does not change, ``PyDict_GetItem()`` takes 14.8 ns for
a dictionary lookup, whereas a guard check only takes 3.8 ns. Moreover,
a guard can watch for multiple keys. For example, for an optimization
using 10 global variables in a function, 10 dictionary lookups costs 148
ns, whereas the guard still only costs 3.8 ns when the version does not
change (39x as fast).
The `fat module
<http://fatoptimizer.readthedocs.org/en/latest/fat.html>`_ implements
such guards: ``fat.GuardDict`` is based on the dictionary version.
Integer overflow
================
The implementation uses the C type ``PY_UINT64_T`` to store the version:
a 64 bits unsigned integer. The C code uses ``version++``. On integer
overflow, the version is wrapped to ``0`` (and then continue to be
incremented) according to the C standard.
After an integer overflow, a guard can succeed whereas the watched
dictionary key was modified. The bug only occurs at a guard check if
there are exaclty ``2 ** 64`` dictionary creations or modifications
since the previous guard check.
If a dictionary is modified every nanosecond, ``2 ** 64`` modifications
takes longer than 584 years. Using a 32-bit version, it only takes 4
seconds. That's why a 64-bit unsigned type is also used on 32-bit
systems. A dictionary lookup at the C level takes 14.8 ns.
A risk of a bug every 584 years is acceptable.
Alternatives
============
Expose the version at Python level as a read-only __version__ property
----------------------------------------------------------------------
The first version of the PEP proposed to expose the dictionary version
as a read-only ``__version__`` property at Python level, and also to add
the property to ``collections.UserDict`` (since this type must mimick
the ``dict`` API).
There are multiple issues:
* To be consistent and avoid bad surprises, the version must be added to
all mapping types. Implementing a new mapping type would require extra
work for no benefit, since the version is only required on the
``dict`` type in practice.
* All Python implementations would have to implement this new property,
it gives more work to other implementations, whereas they may not use
the dictionary version at all.
* Exposing the dictionary version at the Python level can lead the
false assumption on performances. Checking ``dict.__version__`` at
the Python level is not faster than a dictionary lookup. A dictionary
lookup in Python has a cost of 48.7 ns and checking the version has a
cost of 47.5 ns, the difference is only 1.2 ns (3%)::
$ python3.6 -m timeit -s 'd = {str(i):i for i in range(100)}'
'd["33"] == 33'
10000000 loops, best of 3: 0.0487 usec per loop
$ python3.6 -m timeit -s 'd = {str(i):i for i in range(100)}'
'd.__version__ == 100'
10000000 loops, best of 3: 0.0475 usec per loop
* The ``__version__`` can be wrapped on integer overflow. It is error
prone: using ``dict.__version__ <= guard_version`` is wrong,
``dict.__version__ == guard_version`` must be used instead to reduce
the risk of bug on integer overflow (even if the integer overflow is
unlikely in practice).
Mandatory bikeshedding on the property name:
* ``__cache_token__``: name proposed by Nick Coghlan, name coming from
`abc.get_cache_token()
<https://docs.python.org/3/library/abc.html#abc.get_cache_token>`_.
* ``__version__``
* ``__version_tag__``
* ``__timestamp__``
Add a version to each dict entry
--------------------------------
A single version per dictionary requires to keep a strong reference to
the value which can keep the value alive longer than expected. If we add
also a version per dictionary entry, the guard can only store the entry
version (a simple integer) to avoid the strong reference to the value:
only strong references to the dictionary and to the key are needed.
Changes: add a ``me_version_tag`` field to the ``PyDictKeyEntry``
structure, the field has the C type ``PY_UINT64_T``. When a key is
created or modified, the entry version is set to the dictionary version
which is incremented at any change (create, modify, delete).
Pseudo-code of an fast guard to check if a dictionary key was modified
using hypothetical ``dict_get_version(dict)`` and
``dict_get_entry_version(dict)`` functions::
UNSET = object()
class GuardDictKey:
def __init__(self, dict, key):
self.dict = dict
self.key = key
self.dict_version = dict_get_version(dict)
self.entry_version = dict_get_entry_version(dict, key)
def check(self):
"""Return True if the dictionary entry did not change
and the dictionary was not replaced."""
# read the version of the dictionary
dict_version = dict_get_version(self.dict)
if dict_version == self.version:
# Fast-path: dictionary lookup avoided
return True
# lookup in the dictionary to read the entry version
entry_version = get_dict_key_version(dict, key)
if entry_version == self.entry_version:
# another key was modified:
# cache the new dictionary version
self.dict_version = dict_version
self.entry_version = entry_version
return True
# the key was modified
return False
The main drawback of this option is the impact on the memory footprint.
It increases the size of each dictionary entry, so the overhead depends
on the number of buckets (dictionary entries, used or not used). For
example, it increases the size of each dictionary entry by 8 bytes on
64-bit system.
In Python, the memory footprint matters and the trend is to reduce it.
Examples:
* `PEP 393 -- Flexible String Representation
<https://www.python.org/dev/peps/pep-0393/>`_
* `PEP 412 -- Key-Sharing Dictionary
<https://www.python.org/dev/peps/pep-0412/>`_
Add a new dict subtype
----------------------
Add a new ``verdict`` type, subtype of ``dict``. When guards are needed,
use the ``verdict`` for namespaces (module namespace, type namespace,
instance namespace, etc.) instead of ``dict``.
Leave the ``dict`` type unchanged to not add any overhead (CPU, memory
footprint) when guards are not used.
Technical issue: a lot of C code in the wild, including CPython core,
expecting the exact ``dict`` type. Issues:
* ``exec()`` requires a ``dict`` for globals and locals. A lot of code
use ``globals={}``. It is not possible to cast the ``dict`` to a
``dict`` subtype because the caller expects the ``globals`` parameter
to be modified (``dict`` is mutable).
* C functions call directly ``PyDict_xxx()`` functions, instead of calling
``PyObject_xxx()`` if the object is a ``dict`` subtype
* ``PyDict_CheckExact()`` check fails on ``dict`` subtype, whereas some
functions require the exact ``dict`` type.
* ``Python/ceval.c`` does not completely supports dict subtypes for
namespaces
The ``exec()`` issue is a blocker issue.
Other issues:
* The garbage collector has a special code to "untrack" ``dict``
instances. If a ``dict`` subtype is used for namespaces, the garbage
collector can be unable to break some reference cycles.
* Some functions have a fast-path for ``dict`` which would not be taken
for ``dict`` subtypes, and so it would make Python a little bit
slower.
Prior Art
=========
Method cache and type version tag
---------------------------------
In 2007, Armin Rigo wrote a patch to to implement a cache of methods. It
was merged into Python 2.6. The patch adds a "type attribute cache
version tag" (``tp_version_tag``) and a "valid version tag" flag to
types (the ``PyTypeObject`` structure).
The type version tag is not exposed at the Python level.
The version tag has the C type ``unsigned int``. The cache is a global
hash table of 4096 entries, shared by all types. The cache is global to
"make it fast, have a deterministic and low memory footprint, and be
easy to invalidate". Each cache entry has a version tag. A global
version tag is used to create the next version tag, it also has the C
type ``unsigned int``.
By default, a type has its "valid version tag" flag cleared to indicate
that the version tag is invalid. When the first method of the type is
cached, the version tag and the "valid version tag" flag are set. When a
type is modified, the "valid version tag" flag of the type and its
subclasses is cleared. Later, when a cache entry of these types is used,
the entry is removed because its version tag is outdated.
On integer overflow, the whole cache is cleared and the global version
tag is reset to ``0``.
See `Method cache (issue #1685986)
<https://bugs.python.org/issue1685986>`_ and `Armin's method cache
optimization updated for Python 2.6 (issue #1700288)
<https://bugs.python.org/issue1700288>`_.
Globals / builtins cache
------------------------
In 2010, Antoine Pitrou proposed a `Globals / builtins cache (issue
#10401) <http://bugs.python.org/issue10401>`_ which adds a private
``ma_version`` field to the ``PyDictObject`` structure (``dict`` type),
the field has the C type ``Py_ssize_t``.
The patch adds a "global and builtin cache" to functions and frames, and
changes ``LOAD_GLOBAL`` and ``STORE_GLOBAL`` instructions to use the
cache.
The change on the ``PyDictObject`` structure is very similar to this
PEP.
Cached globals+builtins lookup
------------------------------
In 2006, Andrea Griffini proposed a patch implementing a `Cached
globals+builtins lookup optimization
<https://bugs.python.org/issue1616125>`_. The patch adds a private
``timestamp`` field to the ``PyDictObject`` structure (``dict`` type),
the field has the C type ``size_t``.
Thread on python-dev: `About dictionary lookup caching
<https://mail.python.org/pipermail/python-dev/2006-December/070348.html>`_
(December 2006).
Guard against changing dict during iteration
--------------------------------------------
In 2013, Serhiy Storchaka proposed `Guard against changing dict during
iteration (issue #19332) <https://bugs.python.org/issue19332>`_ which
adds a ``ma_count`` field to the ``PyDictObject`` structure (``dict``
type), the field has the C type ``size_t``. This field is incremented
when the dictionary is modified.
PySizer
-------
`PySizer <http://pysizer.8325.org/>`_: a memory profiler for Python,
Google Summer of Code 2005 project by Nick Smallbone.
This project has a patch for CPython 2.4 which adds ``key_time`` and
``value_time`` fields to dictionary entries. It uses a global
process-wide counter for dictionaries, incremented each time that a
dictionary is modified. The times are used to decide when child objects
first appeared in their parent objects.
Discussion
==========
Thread on the mailing lists:
* python-dev: `Updated PEP 509
<https://mail.python.org/pipermail/python-dev/2016-April/144250.html>`_
* python-dev: `RFC: PEP 509: Add a private version to dict
<https://mail.python.org/pipermail/python-dev/2016-April/144137.html>`_
* python-dev: `PEP 509: Add a private version to dict
<https://mail.python.org/pipermail/python-dev/2016-January/142685.html>`_
(january 2016)
* python-ideas: `RFC: PEP: Add dict.__version__
<https://mail.python.org/pipermail/python-ideas/2016-January/037702.html>`_
(january 2016)
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=========
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