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Implement dynamic class provenance tracking to fix isinstance semantics and add support for dynamically defined enums #246

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merged 31 commits into from May 13, 2019

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ogrisel
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@ogrisel ogrisel commented Feb 9, 2019

This is a fix for #244 (and #101) to add support for dynamically defined Enum subclasses.

Properly adding support for dynamic Enums required to more broadly fix the isinstance semantics as initially requested in #195.

The proposed solution involves tracking the provenance of pickled dynamic class definitions with a pair of weakref.WeakKeyDictionary / weakref.WeakValueDictionary protected by a threading.Lock.

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codecov-io commented Feb 9, 2019

Codecov Report

Merging #246 into master will increase coverage by 0.93%.
The diff coverage is 96.42%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master     #246      +/-   ##
==========================================
+ Coverage   88.22%   89.15%   +0.93%     
==========================================
  Files           1        1              
  Lines         552      627      +75     
  Branches      112      129      +17     
==========================================
+ Hits          487      559      +72     
- Misses         42       44       +2     
- Partials       23       24       +1
Impacted Files Coverage Δ
cloudpickle/cloudpickle.py 89.15% <96.42%> (+0.93%) ⬆️

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ogrisel commented Feb 9, 2019

@pitrou @pierreglaser if you have any suggestions / comments on this solution, please let me know.

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ogrisel commented Feb 14, 2019

I had forgotten about #105 which implemented similar support for Enum classes in __main__ as first requested in #101.

However I also think this is a dangerous feature in its current implementation. I think we need to better think trough when an how to reconcile dynamic types (including enums for also other dynamically defined types) on a cluster with some explicit scoping mechanism.

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ogrisel commented Feb 14, 2019

Here is another valid use case that cannot be support by this PR:

from enum import Enum
from dask.distributed import Client


class Color(Enum):
    RED = 1
    GREEN = 2


client = Client()
data_futures = client.scatter([Color.RED, Color.GREEN])


def is_red(x):
    return x is Color.RED


for f in client.map(is_red, data_futures):
     print(f.result())

data_futures and is_red are pickled each by their own CloudPickler instances with their own memoizer and global_ref namespaces. The reconstructed Color classes on the worker are therefore independent and is_red can never return True under those conditions.

@ogrisel ogrisel mentioned this pull request Feb 14, 2019
@ogrisel ogrisel changed the title Add support for dynamically defined enums [WIP] Add support for dynamically defined enums Feb 14, 2019
@ogrisel ogrisel changed the title [WIP] Add support for dynamically defined enums Implement dynamic class provenance tracking to fix isinstance semantics and add support for dynamically defined enums Feb 16, 2019
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ogrisel commented Feb 16, 2019

@mrocklin you might be interested in this PR. Basically it makes it possible to properly support enums in dask and fix the isinstance semantics for objects passed as futures.

@pitrou @mrocklin I would also love to get your feedback on the solution I used to tackle this issue that involves a WeakKeyDictionary / WeakValueDictionary pair protected by a lock. Maybe there is a better way to achieve a similar result.

@pcmoritz @HyukjinKwon I would love it if you could test this PR with Ray and Spark to check that it does not introduce any regression.

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ogrisel commented Feb 16, 2019

@mrocklin when launching the dask-distributed tests against this PR, test_prometheus fails:

https://travis-ci.org/cloudpipe/cloudpickle/jobs/494254377

It does not seem to be related to the change of this PR but I am not 100% sure and it seems deterministic.

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Resolved here: dask/distributed#2533

ogrisel pushed a commit to dask/distributed that referenced this pull request Feb 17, 2019
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ogrisel commented Feb 17, 2019

Alright: all downstream CI tests pass (dask, loky, joblib). I removed the hard dependency to the enum module so that it should fix a broken test on Py 2.7 on Ray. Waiting for more feedback.

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ogrisel commented Feb 22, 2019

@llllllllll @ssanderson I would also love to get your input on this PR.

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From the Ray side, this PR passes the test suite, so looking forward to seeing it merged!

Thanks for all the hard work :)

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Sorry it took so long for me to look at this. I will try to be more responsive here in the future.

I really like the type class tracking work, this seems super useful and fixes hard to explain isinstance bugs. I think there are a few cases that we still don't support with the enum serialization. It's pretty late right now so I am not sure yet what the correct fix is. I posted some tests in the comments below that show the behavior I am talking about. Tomorrow I can PR those tests against this branch and then look into making them pass.

cloudpickle/cloudpickle.py Outdated Show resolved Hide resolved
class_tracker_id, extra):
"""Build dynamic class with an empty __dict__ to be filled once memoized

If class_tracker_id is not None, try to lookup an existing class definition
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how can this be None if we are always passing in _ensure_tracking(obj) on line 590. The enum case also appears to pass this as a non-None value.

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It used to be the case in a former version of this PR. However I wonder if it's not a good idea to make it possible to disable tracking by passing None for forward compatibility.

I am not sure. Would this be a YAGNI?

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Hmm, this seems fine given that it is already implemented.

cloudpickle/cloudpickle.py Outdated Show resolved Hide resolved
@@ -468,6 +527,9 @@ def save_dynamic_class(self, obj):
functions, or that otherwise can't be serialized as attribute lookups
from global modules.
"""
if Enum is not None and issubclass(obj, Enum):
return self._save_dynamic_enum(obj)
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There is currently a case that we don't support, which we may want to consider. Currently the enum module has code that adds a failing reduce to the enum subclass if the mixed in type isn't (default) picklable.

        # If a custom type is mixed into the Enum, and it does not know how
        # to pickle itself, pickle.dumps will succeed but pickle.loads will
        # fail.  Rather than have the error show up later and possibly far
        # from the source, sabotage the pickle protocol for this class so
        # that pickle.dumps also fails.
        #
        # However, if the new class implements its own __reduce_ex__, do not
        # sabotage -- it's on them to make sure it works correctly.  We use
        # __reduce_ex__ instead of any of the others as it is preferred by
        # pickle over __reduce__, and it handles all pickle protocols.
        if '__reduce_ex__' not in classdict:
            if member_type is not object:
                methods = ('__getnewargs_ex__', '__getnewargs__',
                        '__reduce_ex__', '__reduce__')
                if not any(m in member_type.__dict__ for m in methods):
                    _make_class_unpicklable(enum_class)

This means I get the following error:

In [18]: class A:
    ...:     def a(self): return 'a'
    ...:     
    ...:     

In [19]: class AEnum(A, enum.Enum):
    ...:     value = 1
    ...:     
    ...:     

In [20]: cp.loads(cp.dumps(AEnum.value))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-20-24ee7c65848f> in <module>()
----> 1 cp.loads(cp.dumps(AEnum.value))

~/projects/python/cloudpickle/cloudpickle/cloudpickle.py in dumps(obj, protocol)
   1015     try:
   1016         cp = CloudPickler(file, protocol=protocol)
-> 1017         cp.dump(obj)
   1018         return file.getvalue()
   1019     finally:

~/projects/python/cloudpickle/cloudpickle/cloudpickle.py in dump(self, obj)
    297         self.inject_addons()
    298         try:
--> 299             return Pickler.dump(self, obj)
    300         except RuntimeError as e:
    301             if 'recursion' in e.args[0]:

/usr/lib64/python3.6/pickle.py in dump(self, obj)
    407         if self.proto >= 4:
    408             self.framer.start_framing()
--> 409         self.save(obj)
    410         self.write(STOP)
    411         self.framer.end_framing()

/usr/lib64/python3.6/pickle.py in save(self, obj, save_persistent_id)
    494             reduce = getattr(obj, "__reduce_ex__", None)
    495             if reduce is not None:
--> 496                 rv = reduce(self.proto)
    497             else:
    498                 reduce = getattr(obj, "__reduce__", None)

~/.virtualenvs/cloudpickle/lib/python3.6/enum.py in _break_on_call_reduce(self, proto)
     44     """Make the given class un-picklable."""
     45     def _break_on_call_reduce(self, proto):
---> 46         raise TypeError('%r cannot be pickled' % self)
     47     cls.__reduce_ex__ = _break_on_call_reduce
     48     cls.__module__ = '<unknown>'

TypeError: <AEnum.value: 1> cannot be pickled

However, I am able to pickle A objects just fine with cloudpickle. I am not sure if we can fix this because it looks a lot like an explicit __reduce_ex__

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Maybe that's what the type argument is for. I forgot to address @pierreglaser's comments above.

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I had a deeper look with @pierreglaser and it seems that this is a fundamental limitation of enums that inherit from another Python class: this problem is already present for enums defined statically in importable modules. I therefore believe this cannot be fixed in cloudpickle but should be fixed upstream in Python's pickle or enum modules themselves.

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To be more specific:

In [6]: cat mymodule.py
from enum import Enum


class A:
    def method_a(self):
        return "a"


class E(A, Enum):
    x = 1
    y = 2



In [7]: from mymodule import E

In [8]: import pickle

In [9]: pickle.dumps(E.x)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-9-5c82fc8d827e> in <module>()
----> 1 pickle.dumps(E.x)

/opt/python3.7/lib/python3.7/enum.py in _break_on_call_reduce(self, proto)
     42     """Make the given class un-picklable."""
     43     def _break_on_call_reduce(self, proto):
---> 44         raise TypeError('%r cannot be pickled' % self)
     45     cls.__reduce_ex__ = _break_on_call_reduce
     46     cls.__module__ = '<unknown>'

TypeError: <E.x: 1> cannot be pickled

The class A can be imported from mymodule so maybe it's actually a bug in Python itself.

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I think somehow this is not the case anymore in recent python versions (3.7.1 and later):

Python 3.7.1 (tags/v3.7.1:260ec2c36a, Jan 24 2019, 18:18:14)                                                                                                                                                       
Type 'copyright', 'credits' or 'license' for more information                                                                                                                                                      
IPython 7.5.0 -- An enhanced Interactive Python. Type '?' for help.                                                                                                                                                
                                                                                                                                                                                                                   
In [1]: class A:                                                                                                                                                                                                   
   ...:     def a(self): return "a"                                                                                                                                                                                
   ...: import enum                                                                                                                                                                                                
   ...: class AEnum(A, enum.Enum):                                                                                                                                                                                 
   ...:     value = 1                                                                                                                                                                                              
   ...: import pickle                                                                                                                                                                                              
   ...: pickle.dumps(AEnum.value)                                                                                                                                                                                  
Out[1]: b'\x80\x03c__main__\nAEnum\nq\x00K\x01\x85q\x01Rq\x02.'     

See: Enum: mixin classes don't mix well with already mixed Enums

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ogrisel commented Mar 6, 2019

@llllllllll thanks for the review. I think I addressed your comments.

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ogrisel commented Mar 7, 2019

It seems that my latest commits have broken some dask tests although I am not 100% sure because there is no output for 10min and travis kills the job without letting pytest report the failures. Will have to do that manually but I won't have time soon enough. If someone else wants to have a look don't hesitate.

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ogrisel commented Mar 20, 2019

@llllllllll I have rebased this PR to check that the downstream tests of dask distributed, ray, loky and joblib pass.

I now pass all the bases as you suggested so and also added support for methods defined directly on the enum class itself.

@ogrisel ogrisel mentioned this pull request Apr 9, 2019
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Sorry for nagging here, but is there anything which blocks this PR? The fix would be pretty useful for my team.

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ogrisel commented May 6, 2019

I think we might want to release cloudpickle 1.0 without this change and 1.1 with this PR merged so that we have a pretty uncontroversial 1.0 release for cloudpickle as @mrocklin recently asked.

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ogrisel commented May 10, 2019

@llllllllll I would like to merge this but I would really appreciate it if you could confirm that I took your comments into account as intended.

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Sorry about that again. I just got back from C++now and did another pass. All of my comments have been addressed.

Thanks for working on this feature, this is really amazing work!

class_tracker_id, extra):
"""Build dynamic class with an empty __dict__ to be filled once memoized

If class_tracker_id is not None, try to lookup an existing class definition
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Hmm, this seems fine given that it is already implemented.

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ogrisel commented May 13, 2019

Thanks you @llllllllll for your review. I am merging.

@ogrisel ogrisel merged commit a11b718 into cloudpipe:master May 13, 2019
@ogrisel ogrisel deleted the dynamic-enum-class branch May 13, 2019 09:12
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ogrisel commented May 15, 2019

@philippotto cloudpickle 1.1.0 is out with this fix included.

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Awesome, thank you!

wip-sync pushed a commit to NetBSD/pkgsrc-wip that referenced this pull request Apr 4, 2022
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
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