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Optionally use pickle5 (Redux) #370
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Codecov Report
@@ Coverage Diff @@
## master #370 +/- ##
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+ Coverage 91.25% 91.40% +0.15%
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Files 2 3 +1
Lines 629 640 +11
Branches 132 134 +2
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+ Hits 574 585 +11
Misses 34 34
Partials 21 21
Continue to review full report at Codecov.
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We probably need the fix in PR ( pitrou/pickle5-backport#16 ). Asking about a patch release with that change in issue ( pitrou/pickle5-backport#17 ). Edit: This has been released as |
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Tries to use `pickle5` for `pickle` if available on older Python versions.
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Alright I think I've cleared the out-of-band related errors and have managed to get Python 3.7 to pass. 🎉 There still seem to be some other errors for earlier Python versions. The errors seem to be things like pickling |
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Has a fix for the module name `PickleBuffer` is in.
As NumPy 1.18.5 supports `pickle5` on Python 3.5 and we require that NumPy version for testing, include this out-of-band buffers test on Python 3.5 as well.
@pierreglaser, do you know what we need to do to run downstream CI tests here? Tried adding the label and restarting, but maybe something else is needed? |
pushing an empty commit should do the trick :) |
This reverts commit 8178a2c.
@@ -521,7 +521,7 @@ def test_module_locals_behavior(self): | |||
pickled_func_path = os.path.join(self.tmpdir, 'local_func_g.pkl') | |||
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child_process_script = ''' | |||
import pickle | |||
from cloudpickle.compat import pickle |
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using cloudpickle.compat.pickle
or pickle
should be equivalent in the load
case right?
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LGTM.
A small benchmark with and without pickle5
:
(cloudpickle_py37) ~/repos/cloudpickle (opt_use_pickle5_redux)❯_ pip show pickle5
WARNING: Package(s) not found: pickle5
(cloudpickle_py37) ~/repos/cloudpickle (opt_use_pickle5_redux)❯_ python -m timeit 'import cloudpickle; _ = cloudpickle.dumps(list(range(int(1e6))))'
1 loop, best of 5: 1.21 sec per loop
(cloudpickle_py37) ~/repos/cloudpickle (opt_use_pickle5_redux)❯_ pip install pickle5
Processing /home/pierreglaser/.cache/pip/wheels/7e/6a/00/67136a90d6aca437d806d1d3cedf98106e840c97a3e5188198/pickle5-0.0.11-cp37-cp37m-linux_x86_64.whl
Installing collected packages: pickle5
Successfully installed pickle5-0.0.11
WARNING: You are using pip version 20.0.2; however, version 20.1.1 is available.
You should consider upgrading via the '/home/pierreglaser/.virtualenvs/cloudpickle_py37/bin/python3.7 -m pip install --upgrade pip' command.
(cloudpickle_py37) ~/repos/cloudpickle (opt_use_pickle5_redux)❯_ python -m timeit 'import cloudpickle; _ = cloudpickle.dumps(list(range(int(1e6))))'
5 loops, best of 5: 46.7 msec per loop
# To be able to test tornado coroutines | ||
tornado | ||
# To be able to test numpy specific things | ||
# but do not build numpy from source on Python nightly | ||
numpy; python_version <= '3.8' | ||
numpy >=1.18.5; python_version <= '3.8' |
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so we don't have to skip numpy
+ Python 3.5
after all? nice :)
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Indeed :) PR ( numpy/numpy#16439 ) added Python 3.5 support
@@ -1008,7 +1008,8 @@ def example(): | |||
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# choose "subprocess" rather than "multiprocessing" because the latter | |||
# library uses fork to preserve the parent environment. | |||
command = ("import pickle, base64; " | |||
command = ("import base64; " | |||
"from cloudpickle.compat import pickle; " |
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ditto: cloudpickle.compat.pickle
and pickle
are interchangeable in this situation right?
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In both of these test cases, we are using the highest supported protocol with cloudpickle
, which is protocol 5
, to produce the pickled data. So we wound up needing to change these since we are trying to load the pickled data and then need to use pickle5
when pickle
doesn't have protocol 5
support. We could alternatively skip the test, restrict the protocol based on pickle.HIGHEST_PROTOCOL
, or something else. We could also leave as-is. Some options to consider 🙂
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In this case I agree. Thanks.
Co-authored-by: Pierre Glaser <[email protected]>
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LGTM.
@jakirkham I'm going to release now, feel free to voice any concern/remarks :) |
Awesome! Thank you both 😀 No concerns from me. Was thinking the same thing in fact 😉 |
Just as an FYI, @suquark this is in |
I encountered a failing dask test which I suppose is related to this: dask/dask#6374. It happens when you have |
Duplicating my comment from dask/dask#6374: The reason why this test is failing is that Although this is a breaking change:
But I'd be glad to hear your concerns. |
@jakirkham thanks for notifying me about the release! |
Of course! 😄 Also the Dask test failure should be fixed with PR ( dask/dask#6379 ). |
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
Fixes #179
Thanks to @pierreglaser's work in PR ( #368 ), this is a rebased/simplified version of PR ( #364 ). Otherwise is the same in that it tries to use
pickle5
on older Python versions to support out-of-band buffers.