CLN drop Cloudpickler's globals_ref attribute

[pierreglaser]

Not sure globals_ref is still needed, now that base_globals is simply the function's module name.

[codecov-io]

Codecov Report

Merging #229 into master will decrease coverage by 0.1%.
The diff coverage is 100%.

@@ Coverage Diff @@## master #229 +/- ##
==========================================
- Coverage 84.92% 84.81% -0.11% 
==========================================
Files 1 1 Lines 577 573 -4 Branches 114 113 -1 ==========================================
- Hits 490 486 -4 
Misses 63 63 Partials 24 24

Impacted Files	Coverage Δ
cloudpickle/cloudpickle.py	84.81% <100%> (-0.11%)	⬇️

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[ogrisel]

Hum, this is fishy. I wonder if we did not break something that was not tested in the past when doing this series of changes in the handling of base globals.

Maybe this is related to @suquark's comment #216 (comment) but I am not sure I understand.

[pierreglaser]

In summary:

• prior to the series of changes, it has a clear, but somewhat limited (if not broken) usage
• now, the only situation in which it has an influence is if modifying a function's __module__ attribute. But with a even more unstable behaviour.

Prior to the series of changes (i.e before commit 9a52ba3)

globals_ref allowed two functions sharing the same __globals__ attribute in a parent process to share it in the child process, but only if pickled in the same pickle string. Indeed, in this case, globals_ref would tell the CloudPickler to use its memo when pickling __globals__ instead of pickling each time a new dict.

My opinion is that globals_ref global variable sharing was not strong, since the memo is an attribute of a CloudPickler. Several calls to cloudpickle.dumps would have created several Cloudpickler, hence functions sharing the same global environment would have had separate global environment when depickled.

I made two tests that I ran using a version of CloudPickle, with HEAD at a249c44

deftest_global_variable_sharing_same_cloudpickler(self):
code_template=""" from cloudpickle import loads, dumps A_SHARED_GLOBAL = 1 def f(): global A_SHARED_GLOBAL A_SHARED_GLOBAL += 1 return A_SHARED_GLOBAL def g(): global A_SHARED_GLOBAL return A_SHARED_GLOBAL # the depickled functions share a global variable, as the the globals # dict will be shared in the cloudpickler's memo cloned_f, cloned_g = loads(dumps([f, g])) del A_SHARED_GLOBAL UNPICKLED_SHARED_GLOBAL = cloned_f() assert UNPICKLED_SHARED_GLOBAL == 2, UNPICKLED_SHARED_GLOBAL assert cloned_g() == UNPICKLED_SHARED_GLOBAL, cloned_g() """assert_run_python_script(textwrap.dedent(code_template))
deftest_global_variable_sharing_different_cloudpickler(self):
code_template=""" from cloudpickle import loads, dumps A_SHARED_GLOBAL = 1 def f(): global A_SHARED_GLOBAL A_SHARED_GLOBAL += 1 return A_SHARED_GLOBAL def g(): global A_SHARED_GLOBAL return A_SHARED_GLOBAL # here, the two functions do not share the global variables, as they # are picked in different pickle strings, so the memo is not use to # pickle the globals dictionnary cloned_f = loads(dumps(f)) cloned_g = loads(dumps(g)) del A_SHARED_GLOBAL UNPICKLED_SHARED_GLOBAL = cloned_f() assert UNPICKLED_SHARED_GLOBAL == 2, UNPICKLED_SHARED_GLOBAL # this fails, so the global variable is not shared assert cloned_g() == UNPICKLED_SHARED_GLOBAL, cloned_g() """assert_run_python_script(textwrap.dedent(code_template))

the first one pass, the second one fails.

If modifying the code by removing globals_ref:

@@ -260,7 +260,7 @@ class CloudPickler(Pickler):
# set of modules to unpickle
self.modules = set()
# map ids to dictionary. used to ensure that functions can share global env
- self.globals_ref = {}+ # self.globals_ref = {}
def dump(self, obj):
self.inject_addons()
@@ -632,8 +632,9 @@ class CloudPickler(Pickler):
# save the dict
dct = func.__dict__
- base_globals = self.globals_ref.get(id(func.__globals__), {})- self.globals_ref[id(func.__globals__)] = base_globals+ # base_globals = self.globals_ref.get(id(func.__globals__), {})+ # self.globals_ref[id(func.__globals__)] = base_globals+ base_globals = {}
return (code, f_globals, defaults, closure, dct, base_globals)

the two tests fail.

After the series of changes (i.e on master)

The situation has changed: globals_ref acts as a proxy before looking at a the function's __module__. There are edge cases where the presence or the absence of globals_ref therefore changes the globals handling behavior, but only if the function's __module__ attribute get mutated. But this looks like undefined behaviour anyway to me.

I think one of the key takeaways of my endeavours is that globals_ref's influence is limited to a Cloudpickler, i.e one call of cloudpickle.dumps. I am not sure we want this.

[TheButlah]

Perhaps this is related to my issues at #230?

[pierreglaser]

@TheButlah so far, all the code I posted here was ran on a Linux machine, so I cannot see a clear relation between this and #230. I did not investigate your issue though, and I am sadly not familiar with windows specificities.

[ogrisel]

I believe we actually want to preserve this. This is now being correctly tested as part of: #240.

Let's close this issue.