-
Notifications
You must be signed in to change notification settings - Fork 167
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Support pickling dynamic classes subclassing typing.Generic
instances on 3.7+
#351
Conversation
Codecov Report
@@ Coverage Diff @@
## master #351 +/- ##
==========================================
+ Coverage 93.28% 93.32% +0.04%
==========================================
Files 2 2
Lines 759 764 +5
Branches 154 156 +2
==========================================
+ Hits 708 713 +5
Misses 26 26
Partials 25 25
Continue to review full report at Codecov.
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I don't think the scope of this PR is respected, please see comment below.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Now that this is rebased, here are some comments. You also need a new entry in the changelog.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
LGTM. This also need a dedicated changelog entry.
Here are a few nitpicking suggestions:
It's weird that my new test passes with Python 3.8 but does not work with Python 3.7. I thought that the built-in pickle memoization would ensure that the type definition would make the physical equality check work: https://github.com/cloudpipe/cloudpickle/pull/351/checks?check_run_id=508124864 |
I have added a simpler failing test (under py37, but not py38) to debug the memoization problem in Any idea? |
I think we miss a Good catch @ogrisel, apologies for missing that. |
Thanks for the comments, I addressed all the easy ones for now.
I didn't commit the |
Why? |
By the way I think we should also enable the definition tracking (currently only used for dynamic classes and enums) for dynamic typevars. But this can be done in a dedicated PR. |
I pushed the memoization fix to see if the full CI will pass. |
tests/cloudpickle_test.py
Outdated
"Pickling type hints not supported below py37") | ||
def test_locally_defined_class_with_type_hints(self): | ||
with subprocess_worker(protocol=self.protocol) as worker: | ||
for type_ in _generic_objects_to_test(): |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I would be in favor of using this test to check not only generic types, but all kinds of type annotations, including simple literals from the typing module as was done before.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Trying to understand here: why would you want the pickling of these constructs to be tested in the same, single test (and not in test_pickling_stlib_typing_module_globals
or something like that)? The pickling process and branches traversed to pickle C
(which is the only purpose of this PR) is not the same as when pickling globals defined in the typing
module. To the best of my knowledge, there is no reason for why pickling these two different constructs should be tested in a single unit-test.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
All type annotations should be preserved, dynamic or non-dynamic.
We could have additional tests for things that are specific to dynamic ones but we should check that we do not break the pickling of annotations with non-dynamic types too, no?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I agree. I simply want [my/your/any-cloudpickle-contributor/maintainer] future-self to be able to quickly understand why a specific line/commit exists, and this through atomic unit tests (we can also have composite ones, but to me atomic ones are necessary), related to the exact feature we decided to introduce in the said line/commit. In our case, this PR introduces support for pickling classes subclassing typing.Generic
constructs. I think we should have an atomic unit test for this feature.
- If we are missing tests testing the pickling of
typing.Generic
constructs only, let's add another test. - If we are missing tests testing the pickling of the
globals
of thetyping
module, let's add another test. - If we are missing tests testing the pickling what's inside a dynamic class/function
__annotations__
(be itGeneric
construct or othertyping
constructs), let's add another test. - If we want to test any combination of the 4 situations above (the first one being subclassing
typing.Generic
), then let's add another test.
But why mixing everything up in one single test? The test suite of cloudpickle
stills run pretty fast (<1 minute against CPython
), not sure there is a need for optimization on this end yet.
Two final remarks:
- I hope I don't sound like I'm bikeshedding -- I just want to make sure every one is on the same line when hitting
merge
. - If this message, along with the other ones I wrote about this topic, did not convince you, then I'll withdraw. I can also write a PR by myself once we merge this PR and Pickling of generic annotations/types in 3.5+ #318 if we don't want to spend too much time reviewing these PRs.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
+1 for an atomic test for public Generic type subclasses alone (without the subprocess thing). But I like to also have a big integration test that test dynamic classes annotated with all the possible kinds of types (literal, typevars, generic and generic subclasses).
# The type annotation syntax causes a SyntaxError on Python 3.5 | ||
code = textwrap.dedent("""\ | ||
class MyClass: | ||
attribute: type_ |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
To make things clear: pickling Generic
constructs works fine on master right now. The only thing this PR introduces is supporting the pickling of dynamic classes defined using the
class A(typing.Generic[T]):
...
semantic. the type hint used in attribute
as well as in method
is correctly pickled (for Python 3.7+
) in cloudpickle
master as of now. I think adding such type hints in this tests generates more confusion that it helps.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
To make things clear: pickling Generic constructs works fine on master right now.
Maybe, but it was not properly tested. So better take the opportunity to increase the test coverage in general, not just the specific fix from this PR.
|
||
@unittest.skipIf(sys.version_info < (3, 7), | ||
"Pickling type hints not supported below py37") | ||
def test_locally_defined_class_with_type_hints(self): |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
The name used in this test is a little bit confusing: are we testing classes inheriting from Generic
constructs, or the pickling of Generic
type hints? It seems like we are testing both, and I am not sure why we should test both things in the same tests. See my comments below for additional remarks.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I my initial commit, this test was testing for all kinds of type annotations, both simple literal types and more complex custom types based on generics and their subclasses.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
LGTM once the discussion going on about the tests is resolved.
typing.Generic
instances on 3.7+
Co-Authored-By: Pierre Glaser <[email protected]>
I pushed the new tests to take @pierreglaser comments into account. Everything looks good. Let's merge. I will also merge #353 after that. Thank you very much @valtron! |
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
This PR depends on #350. Only the last commit should be reviewed. When #350 is merged I'll rebase this.This involved using
types.new_class
. I checked and the new tests fail without it.