deepcopy doesn't copy instance methods

[mlvanbie]

BPO	1515
Nosy	@gvanrossum, @warsaw, @pitrou, @tiran, @rbtcollins, @cool-RR
Files	issue1515.patch: Patch to add InstanceMethod copying. issue1515.patch: Updated patch

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = None
closed_at = <Date 2009-11-28.15:59:33.453>
created_at = <Date 2007-11-29.00:41:00.076>
labels = ['type-bug', 'library']
title = "deepcopy doesn't copy instance methods"
updated_at = <Date 2009-11-28.15:59:33.451>
user = 'https://bugs.python.org/mlvanbie'

bugs.python.org fields:

activity = <Date 2009-11-28.15:59:33.451>
actor = 'pitrou'
assignee = 'none'
closed = True
closed_date = <Date 2009-11-28.15:59:33.453>
closer = 'pitrou'
components = ['Library (Lib)']
creation = <Date 2007-11-29.00:41:00.076>
creator = 'mlvanbie'
dependencies = []
files = ['15405', '15406']
hgrepos = []
issue_num = 1515
keywords = ['patch']
message_count = 24.0
messages = ['57923', '58839', '58851', '58854', '59508', '61893', '61900', '61901', '61909', '61921', '61922', '61938', '61941', '95716', '95760', '95761', '95766', '95767', '95776', '95777', '95778', '95779', '95790', '95791']
nosy_count = 8.0
nosy_names = ['gvanrossum', 'barry', 'pitrou', 'christian.heimes', 'rbcollins', 'mlvanbie', 'Dmitrey', 'cool-RR']
pr_nums = []
priority = 'normal'
resolution = 'fixed'
stage = 'resolved'
status = 'closed'
superseder = None
type = 'behavior'
url = 'https://bugs.python.org/issue1515'
versions = ['Python 2.7', 'Python 3.2']

[mlvanbie]

Currently, using deepcopy on instance methods causes an exception to be
thrown. This can be fixed by adding one line to copy.py:

d[types.MethodType] = _deepcopy_atomic

This will not make duplicate copies of mutable values referenced within
the instance method (such as its associated instance), but it will be
the same as the handling of other function types (which have the same
problem).

[gvanrossum]

I disagree that this would be harmless; this was excluded intentionally.
A (bound) method contains an instance which definitely represents state
and calling the method can easily mutate that state.

This is different from classes (which could contain state) or modules
(which almost certainly contain state) or functions (which could mutate
global state) -- in all those cases, we're talking about singleton
state, for which it makes sense not to create a clone. But for methods,
we're talking about instances, of which there could be many, and I
believe those should be properly copied or refused, rather than creating
accidental state sharing between the original and its deep copy.

I suppose you have a specific use case in mind. Can't you solve that by
adding a __deepcopy__ method to some object?

[mlvanbie]

I am implementing a library that makes extensive use of delayed
executions represented by functions. Copying objects both with and
without shared state referenced by the functions is important. There is
one entry point where I would expect functions to go. On the other
hand, I can't prevent users from taking an instance method and wrapping
it inside of a callable object that lacks an appropriate __deepcopy__
method (this would be a sensible thing to do, in fact).

I don't mind whether instance methods have shallow or deep copies as
long as I can document the result. Neither invasive use of __deepcopy__
nor throwing an exception is suitable for my use. For reference, the
exception is

TypeError: instancemethod expected at least 2 arguments, got 0

Ideally, deepcopy() and pickle() would copy the internals of all
function types and I could implement shared mutable state by using
__deepcopy__ in a single class. I assume that this is unreasonable to
implement.

No matter the implementation, I think that there should be some way of
running deepcopy() on all primitive types without throwing exceptions.
I can see use cases where throwing exceptions for all types that can't
be deeply copied would be useful and disabling __deepcopy__ might be
important.

[gvanrossum]

I'll take this off line.

[mlvanbie]

Guido pointed out a common use case where people use bound methods in a
way that would be poorly served by my change. An alternate
implementation with a deeper copy will cause less surprise:

def _deepcopy_method(x, memo):
    return type(x)(x.im_func, deepcopy(x.im_self, memo), x.im_class)
d[types.MethodType] = _deepcopy_method

The function and class are still shallow-copied but the bound object is
deep-copied. I use type(x)() instead of types.MethodType() because
types will be unbound when the function runs.

[Dmitrey]

Hallo, I' developer of the OpenOpt, free Python-based numerical
optimization framework.

Please don't you mind me to increase Severity of the bug to major. This
bug is driving me mad, as well as some of OO users, and makes OO usage
much less convenient and obvious.

http://openopt.blogspot.com/2008/01/about-prob-structure-redefinition.html

[tiran]

I've read your blog. You don't have to modify the Python core:

import copy
import types

def _deepcopy_method(x, memo):
    return type(x)(x.im_func, deepcopy(x.im_self, memo), x.im_class)
copy._deepcopy_dispatch[types.MethodType] = _deepcopy_method

I still wonder why you have to use deepcopy in your app.

[tiran]

I'm bumping up the version number to 2.6. Python 2.5 is in maintenance
mode and the behavior of deepcopy for instance methods won't be changed.

[gvanrossum]

I'm fine with applying Michael's suggestion to 2.6.

I're reverting the priority change though; using deepcopy is not OO and
IMO usually indicates that there's something wrong with your app.

[tiran]

Since Guido accepted the proposal can you please provide a patch with at
least one unit test?

[Dmitrey]

I don't know did you mean it to me (as I've noticed from address) or no.
I can hardly provide any help for fixing the bug, I'm not skilled enough
in Python core files. Here's results of the proposition mentioned:

import copy
import types

def _deepcopy_method(x, memo):
    return type(x)(x.im_func, deepcopy(x.im_self, memo), x.im_class)
copy._deepcopy_dispatch[types.MethodType] = _deepcopy_method

from scikits.openopt import NLP
p = NLP(lambda x: x**2, 1)
p3 = _deepcopy_method(p, None)

Traceback (most recent call last):
  File "test_deepcopy.py", line 10, in <module>
    p3 = _deepcopy_method(p, None)
  File "test_deepcopy.py", line 5, in _deepcopy_method
    return type(x)(x.im_func, deepcopy(x.im_self, memo), x.im_class)
AttributeError: NLP instance has no attribute 'im_func'

as for copy.py from Python core, it seems like the file has no
"_deepcopy_method" function.

Users want to run r = p.solve(solverName) for several different solvers and same p instance. So it needs each time using
for sn in [solverName1, solverName2, ..., solverNameN]:
p = NLP(dozens of params)
p.somefiled.paramN+1 =valN+1
p.somefiled.paramN+2 =valN+2
...
r{i} = p.solve(sn)
while in my previous MATLAB version of the toolbox it looks just like:

(assign prob only once)
p = ooAssign(params)
for sn in [solverName1, solverName2, ..., solverNameN]
r{i} = p.solve(sn)
end

Christian Heimes wrote:

Christian Heimes added the comment:

Since Guido accepted the proposal can you please provide a patch with at
least one unit test?

----------
resolution: -> accepted

---

Tracker <report@bugs.python.org>
<http://bugs.python.org/issue1515\>

---

[mlvanbie]

Dmitrey: You can't call _deepcopy_method() on anything other than
something with type types.MethodType. It is a function in a
type-dispatch table, so it will always be called safely.
copy._deepcopy_dispatch is that table; if you assign _deepcopy_method to
copy._deepcopy_dispatch[types.MethodType] then copy.deepcopy() will
understand what to do with method types. See my unit test below for the
semantics.

Christian Heimes, this is my unit test:

# This test would fail due to an exception during deepcopy in version 2.5.1

class C(object):
  def __init__(self, n):
    self.n = n

  def GetN(self):
    return self.n

orig_obj = C(42)
copy_list = copy.deepcopy([orig_obj, orig_obj.GetN])
if copy_list[1]() != 42:
  print 'Error: Instance method lost object?'
orig_obj.n = 43
if copy_list[1]() != 42:
  print 'Error: Instance method assoc with orig object'
copy_list[0].n = 44
if copy_list[1]() != 44:
  print 'Error: Instance method should assoc with new object copy'
if not type(copy_list[1]) is type(orig_obj.GetN):
  print 'Error: Deepcopy changed type of instance method'

Why do people want to use copy and deepcopy? I think that the issue is
that Python is an imperative language that passes and copies references.
If a library function doesn't treat its arguments as const, horrible
things could happen. Compounding this, several standard operations
(such as sort) operate in place, so if you want to use them then you
need to make shallow copies at the very least. When non-scalar types
nest, the whole structure can be deepcopied or copy can be used
repeatedly in a selective manner (with a high chance of bugs). Perl
deals with this issue by using standard copy semantics (but
call-by-reference) and a copy-on-write implementation. Most operations
operate out-of-place. Pure languages can use reference-based copy
semantics because you can't modify anything, forcing users to create the
copy-on-write implementation when mutating structures.

[gvanrossum]

On Jan 31, 2008 2:54 PM, Michael Van Biesbrouck wrote:

Why do people want to use copy and deepcopy? I think that the issue is
that Python is an imperative language that passes and copies references.
If a library function doesn't treat its arguments as const, horrible
things could happen. Compounding this, several standard operations
(such as sort) operate in place, so if you want to use them then you
need to make shallow copies at the very least.

I see the point for shallow copies. I just don't see the point for deep copies.

When non-scalar types
nest, the whole structure can be deepcopied or copy can be used
repeatedly in a selective manner (with a high chance of bugs).

I don't understand the use case. I still think this comes primarily
from a lack of familiarity with how Python is typically used.