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ENH: derive from C-pickler for fast serialization #253
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Thank you for putting this PR together. Also any plans for making this change backwards compatible < 3.8 or even 2.7 ? |
It will all depend on whether
This is still an open question: doing this would mean including the new |
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Another option (for Python 3.6+ only) would be to include the change in the |
If a Pickler instance already has methods in its dispatch table, do not override them. This bug showed up in cloudpipe/cloudpickle#253, where the Cloudpickler instances derives from the C Pickler, and most custom saving methods are inside dispatch_table, not dispatch.
If a Pickler instance already has methods in its dispatch table, do not override them. This bug showed up in cloudpipe/cloudpickle#253, where the Cloudpickler instances derives from the C Pickler, and most custom saving methods are inside dispatch_table, not dispatch.
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I think all the new helpers functions and reducers should be made private (with a leading _
in their name so as to make it explicit that this is not part of the public API and can change without a deprecation notice).
Furthermore I find this PR a bit hard to review because some the helpers are duplicates from existing helpers in cloudpickle.cloudpickle
and it's hard to know if they are exactly the same or not. Hence I suggest the following:
@pierreglaser I'm sorry about my bad memory, but did you post a PR and/or a Python issue about your changes? I don't remember. If a change is needed in pickle protocol 5, you'd better tell me also (and/or post a thread on python-dev to gather feedback). |
That would be theoretically ok with me. Whether I concretely agree or not depends on how harder it makes to maintain the backport (right now it works with simple diff scripts and bit a manual work whenever there's a conflict). |
@pitrou there is an issue in the bug tracker, with patches. I was waiting for feedback before submitting a PR.
There is no change to the pickle protocol (no new opcode) itself, however I extended the |
Nowadays PRs are easier to read than raw patches, so I'd rather have that. |
It seems that this PR needs to be updated to take the merge of #254 into account. |
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A small batch of comments:
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Here is a first review. Overall this looks good to me.
Have you tried to run some of the downstream test suites? I guess we have to do that manually because of the need to run against a patched python master.
The more I think about it, the less I am convinced about the need for |
We don't want to accumulate objects in a global datastructure. This can be considered a memory leak (although there would be only empty dicts there if I am correct). I much prefer to avoid global variables if there is a natural way not have any (as in the current code). |
@ogrisel will (the CI breaks because |
I think it would be a good idea to ensure forward compatibility for the pure Python Pickler implementation if it's not to complicated to get. |
I merged #246 which will impact this PR significantly unfortunately. |
@pierreglaser would it be easier for your to redo this PR only once #262 is merged? In which case I would put the priority on reviewing it. |
This comment #253 (comment) does not seem to be addressed. |
There was a race condition with your comment and my last commit :) I'll cherry-pick in a separate PR. |
Haha, as you wish. Please add an entry to the changelog so that we can merge this PR :) |
I changed my mind I'll leave it as is, as this is part of the refactoring of this PR to change this helper. I'll add an entry to the changelog and make a last pass. |
@ogrisel this LGTM as well! |
Merged! Thank you very much @pierreglaser! |
2.0.0 ===== - Python 3.5 is no longer supported. - Support for registering modules to be serialised by value. This allows code defined in local modules to be serialised and executed remotely without those local modules installed on the remote machine. ([PR #417](cloudpipe/cloudpickle#417)) - Fix a side effect altering dynamic modules at pickling time. ([PR #426](cloudpipe/cloudpickle#426)) - Support for pickling type annotations on Python 3.10 as per [PEP 563]( https://www.python.org/dev/peps/pep-0563/) ([PR #400](cloudpipe/cloudpickle#400)) - Stricter parametrized type detection heuristics in _is_parametrized_type_hint to limit false positives. ([PR #409](cloudpipe/cloudpickle#409)) - Support pickling / depickling of OrderedDict KeysView, ValuesView, and ItemsView, following similar strategy for vanilla Python dictionaries. ([PR #423](cloudpipe/cloudpickle#423)) - Suppressed a source of non-determinism when pickling dynamically defined functions and handles the deprecation of co_lnotab in Python 3.10+. ([PR #428](cloudpipe/cloudpickle#428)) 1.6.0 ===== - `cloudpickle`'s pickle.Pickler subclass (currently defined as `cloudpickle.cloudpickle_fast.CloudPickler`) can and should now be accessed as `cloudpickle.Pickler`. This is the only officially supported way of accessing it. ([issue #366](cloudpipe/cloudpickle#366)) - `cloudpickle` now supports pickling `dict_keys`, `dict_items` and `dict_values`. ([PR #384](cloudpipe/cloudpickle#384)) 1.5.0 ===== - Fix a bug causing cloudpickle to crash when pickling dynamically created, importable modules. ([issue #360](cloudpipe/cloudpickle#354)) - Add optional dependency on `pickle5` to get improved performance on Python 3.6 and 3.7. ([PR #370](cloudpipe/cloudpickle#370)) - Internal refactoring to ease the use of `pickle5` in cloudpickle for Python 3.6 and 3.7. ([PR #368](cloudpipe/cloudpickle#368)) 1.4.1 ===== - Fix incompatibilities between cloudpickle 1.4.0 and Python 3.5.0/1/2 introduced by the new support of cloudpickle for pickling typing constructs. ([issue #360](cloudpipe/cloudpickle#360)) - Restore compat with loading dynamic classes pickled with cloudpickle version 1.2.1 that would reference the `types.ClassType` attribute. ([PR #359](cloudpipe/cloudpickle#359)) 1.4.0 ===== **This version requires Python 3.5 or later** - cloudpickle can now all pickle all constructs from the ``typing`` module and the ``typing_extensions`` library in Python 3.5+ ([PR #318](cloudpipe/cloudpickle#318)) - Stop pickling the annotations of a dynamic class for Python < 3.6 (follow up on #276) ([issue #347](cloudpipe/cloudpickle#347)) - Fix a bug affecting the pickling of dynamic `TypeVar` instances on Python 3.7+, and expand the support for pickling `TypeVar` instances (dynamic or non-dynamic) to Python 3.5-3.6 ([PR #350](cloudpipe/cloudpickle#350)) - Add support for pickling dynamic classes subclassing `typing.Generic` instances on Python 3.7+ ([PR #351](cloudpipe/cloudpickle#351)) 1.3.0 ===== - Fix a bug affecting dynamic modules occuring with modified builtins ([issue #316](cloudpipe/cloudpickle#316)) - Fix a bug affecting cloudpickle when non-modules objects are added into sys.modules ([PR #326](cloudpipe/cloudpickle#326)). - Fix a regression in cloudpickle and python3.8 causing an error when trying to pickle property objects. ([PR #329](cloudpipe/cloudpickle#329)). - Fix a bug when a thread imports a module while cloudpickle iterates over the module list ([PR #322](cloudpipe/cloudpickle#322)). - Add support for out-of-band pickling (Python 3.8 and later). https://docs.python.org/3/library/pickle.html#example ([issue #308](cloudpipe/cloudpickle#308)) - Fix a side effect that would redefine `types.ClassTypes` as `type` when importing cloudpickle. ([issue #337](cloudpipe/cloudpickle#337)) - Fix a bug affecting subclasses of slotted classes. ([issue #311](cloudpipe/cloudpickle#311)) - Dont pickle the abc cache of dynamically defined classes for Python 3.6- (This was already the case for python3.7+) ([issue #302](cloudpipe/cloudpickle#302)) 1.2.2 ===== - Revert the change introduced in ([issue #276](cloudpipe/cloudpickle#276)) attempting to pickle functions annotations for Python 3.4 to 3.6. It is not possible to pickle complex typing constructs for those versions (see [issue #193]( cloudpipe/cloudpickle#193)) - Fix a bug affecting bound classmethod saving on Python 2. ([issue #288](cloudpipe/cloudpickle#288)) - Add support for pickling "getset" descriptors ([issue #290](cloudpipe/cloudpickle#290)) 1.2.1 ===== - Restore (partial) support for Python 3.4 for downstream projects that have LTS versions that would benefit from cloudpickle bug fixes. 1.2.0 ===== - Leverage the C-accelerated Pickler new subclassing API (available in Python 3.8) in cloudpickle. This allows cloudpickle to pickle Python objects up to 30 times faster. ([issue #253](cloudpipe/cloudpickle#253)) - Support pickling of classmethod and staticmethod objects in python2. arguments. ([issue #262](cloudpipe/cloudpickle#262)) - Add support to pickle type annotations for Python 3.5 and 3.6 (pickling type annotations was already supported for Python 3.7, Python 3.4 might also work but is no longer officially supported by cloudpickle) ([issue #276](cloudpipe/cloudpickle#276)) - Internal refactoring to proactively detect dynamic functions and classes when pickling them. This refactoring also yields small performance improvements when pickling dynamic classes (~10%) ([issue #273](cloudpipe/cloudpickle#273)) 1.1.1 ===== - Minor release to fix a packaging issue (Markdown formatting of the long description rendered on pypi.org). The code itself is the same as 1.1.0. 1.1.0 ===== - Support the pickling of interactively-defined functions with positional-only arguments. ([issue #266](cloudpipe/cloudpickle#266)) - Track the provenance of dynamic classes and enums so as to preseve the usual `isinstance` relationship between pickled objects and their original class defintions. ([issue #246](cloudpipe/cloudpickle#246)) 1.0.0 ===== - Fix a bug making functions with keyword-only arguments forget the default values of these arguments after being pickled. ([issue #264](cloudpipe/cloudpickle#264)) 0.8.1 ===== - Fix a bug (already present before 0.5.3 and re-introduced in 0.8.0) affecting relative import instructions inside depickled functions ([issue #254](cloudpipe/cloudpickle#254)) 0.8.0 ===== - Add support for pickling interactively defined dataclasses. ([issue #245](cloudpipe/cloudpickle#245)) - Global variables referenced by functions pickled by cloudpickle are now unpickled in a new and isolated namespace scoped by the CloudPickler instance. This restores the (previously untested) behavior of cloudpickle prior to changes done in 0.5.4 for functions defined in the `__main__` module, and 0.6.0/1 for other dynamic functions. 0.7.0 ===== - Correctly serialize dynamically defined classes that have a `__slots__` attribute. ([issue #225](cloudpipe/cloudpickle#225)) 0.6.1 ===== - Fix regression in 0.6.0 which breaks the pickling of local function defined in a module, making it impossible to access builtins. ([issue #211](cloudpipe/cloudpickle#211)) 0.6.0 ===== - Ensure that unpickling a function defined in a dynamic module several times sequentially does not reset the values of global variables. ([issue #187](cloudpipe/cloudpickle#205)) - Restrict the ability to pickle annotations to python3.7+ ([issue #193]( cloudpipe/cloudpickle#193) and [issue #196]( cloudpipe/cloudpickle#196)) - Stop using the deprecated `imp` module under Python 3. ([issue #207](cloudpipe/cloudpickle#207)) - Fixed pickling issue with singleton types `NoneType`, `type(...)` and `type(NotImplemented)` ([issue #209](cloudpipe/cloudpickle#209)) 0.5.6 ===== - Ensure that unpickling a locally defined function that accesses the global variables of a module does not reset the values of the global variables if they are already initialized. ([issue #187](cloudpipe/cloudpickle#187)) 0.5.5 ===== - Fixed inconsistent version in `cloudpickle.__version__`. 0.5.4 ===== - Fixed a pickling issue for ABC in python3.7+ ([issue #180]( cloudpipe/cloudpickle#180)). - Fixed a bug when pickling functions in `__main__` that access global variables ([issue #187]( cloudpipe/cloudpickle#187)). 0.5.3 ===== - Fixed a crash in Python 2 when serializing non-hashable instancemethods of built-in types ([issue #144](cloudpipe/cloudpickle#144)). - itertools objects can also pickled ([PR #156](cloudpipe/cloudpickle#156)). - `logging.RootLogger` can be also pickled ([PR #160](cloudpipe/cloudpickle#160)). 0.5.2 ===== - Fixed a regression: `AttributeError` when loading pickles that hold a reference to a dynamically defined class from the `__main__` module. ([issue #131]( cloudpipe/cloudpickle#131)). - Make it possible to pickle classes and functions defined in faulty modules that raise an exception when trying to look-up their attributes by name. 0.5.1 ===== - Fixed `cloudpickle.__version__`. 0.5.0 ===== - Use `pickle.HIGHEST_PROTOCOL` by default. 0.4.4 ===== - `logging.RootLogger` can be also pickled ([PR #160](cloudpipe/cloudpickle#160)). 0.4.3 ===== - Fixed a regression: `AttributeError` when loading pickles that hold a reference to a dynamically defined class from the `__main__` module. ([issue #131]( cloudpipe/cloudpickle#131)). - Fixed a crash in Python 2 when serializing non-hashable instancemethods of built-in types. ([issue #144](cloudpipe/cloudpickle#144)) 0.4.2 ===== - Restored compatibility with pickles from 0.4.0. - Handle the `func.__qualname__` attribute. 0.4.1 ===== - Fixed a crash when pickling dynamic classes whose `__dict__` attribute was defined as a [`property`](https://docs.python.org/3/library/functions.html#property). Most notably, this affected dynamic [namedtuples](https://docs.python.org/2/library/collections.html#namedtuple-factory-function-for-tuples-with-named-fields) in Python 2. (cloudpipe/cloudpickle#113) - Cloudpickle now preserves the `__module__` attribute of functions (cloudpipe/cloudpickle#118). - Fixed a crash when pickling modules that don't have a `__package__` attribute (cloudpipe/cloudpickle#116). 0.4.0 ===== * Fix functions with empty cells * Allow pickling Logger objects * Fix crash when pickling dynamic class cycles * Ignore "None" mdoules added to sys.modules * Support WeakSets and ABCMeta instances * Remove non-standard `__transient__` support * Catch exception from `pickle.whichmodule()` 0.3.1 ===== * Fix version information and ship a changelog 0.3.0 ===== * Import submodules accessed by pickled functions * Support recursive functions inside closures * Fix `ResourceWarnings` and `DeprecationWarnings` * Assume modules with `__file__` attribute are not dynamic 0.2.2 ===== * Support Python 3.6 * Support Tornado Coroutines * Support builtin methods
Summary:
This PR proposes a new
Cloudpickler
class, that inherits from the C_pickle.Pickler
instead of the pythonpickle._Pickler
, allowing 10x+speedups for the serialization of large builtin objects such as dicts, lists..
Disclaimer: a new start
Moving from the python to the c
Pickler
requires a fair amount of changes.For this reason, instead of simply adapting the current code to respect the new
constraints, I started back from scratch. This allows a new, clean API and
structure, that will be hopefully easier to understand for everyone.
I made a lot of comments, (sometimes overly verbose), to ease the review
process of this PR. Eventually, I hope the information they contain can be
transfered to a proper project documentation.
Implementation:
Changes to python
As opposed to the python pickler, The CPickler does not expose the
save_*
family of functions, as well as low level isntructions such as
write
. Thesemethods can can neither be patched, or called, and the only customization
option we had initially was the dispatch table, that is called for all types
BUT a few special cases, including classes and functions, the two principal
use-cases of cloudpickle.
As this makes it simply impossible to modify pickling behavior for such types,
we patched the C pickler for it to allow a user defined reduction callback for
functions and classes. This idea was suggested by @pitrou.
The direct consequence is that functions and classes now have to follow the
save_reduce
-load_build
pickling/depickling process. Unfortunaltely,this API is not well suited for custom
builtin
-type saving: in particular,the state setting part of
load_build
(function that reconstructs an object froma reduce value) assumes all attributes of an object are writeable, which is not
the case for C types (especially
function.__globals__
andfunction.__closure__
)For this reason, we also changed the API of
save_reduce
, allowing to add acustom
state_setter
, that will be called at unpickling time.You can view the totals changes in this diff
Individual PRs to CPython:
reducer_override
)state_setter
insave_reduce
)Changes to cloudpickle
Functions and classes are the two main types affected by this PR. The main
challenge was to make the saving process fit into the
save_reduce
API.Outside of these types, the actuall reduction process remains intact.
However, now that any customization must return a tuple, I decided to adopt a
new naming, hopefully clearer naming style for functions. You will see by
yourselves.
How to build this version locally
Until the final release of
Python 3.8
, you need to build python from upstream's master branchgit clone git@github.com:python/cpython.git cd cpython ./configure make
To be able to use external modules you need a virtual environment, using for
example the
venv
module:Clone and install
cloudpickle
and its dependenciesFinally, rum the tests:
Bechmarks:
loky
can be foundhere. To run the benchmarks, you also need the master version of loky.