[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[Eric V. Smith]

Eric V. Smith  added the comment:

Thanks, Raymond. I agree that this request is too specialized to add to 
dataclasses. Any proposal here or that I've been able to think of complicate 
the API for the much more common use case of not needing asdict() 
specialization.

To the original poster: I suggest you just implement the functionality you need 
in a custom version of asdict() yourself. As noted, all of the information 
needed for a custom asdict() are publicly available.

--
resolution:  -> rejected
stage:  -> resolved
status: open -> closed

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com

[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[Raymond Hettinger]

Raymond Hettinger  added the comment:

I recommend passing on this feature request as being too specialized and beyond 
the scope of what data classes are intended to do.  

FWIW, the information needed by a user to write their own customized iteration 
patterns is publicly available.  One of the reasons for having a general 
purpose programming language is to enable users to write customizations that 
best fit their particular use cases.

--
nosy: +rhettinger

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com

[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[mkurnikov]

mkurnikov  added the comment:

Cleanest thing I could think of is:

1. Extract dataclass_to_dict function from _asdict_inner as:

def dataclass_asdict(obj, dict_factory):
result = []
for f in fields(obj):
value = _asdict_inner(getattr(obj, f.name), dict_factory)
result.append((f.name, value))
return dict_factory(result)

2. Add "asdict" parameter to the dataclass decorator (with default value of 
dataclass_to_dict function)

@dataclass(asdict=specific_dcls_dict_factory)
class MyDataclass:
pass

3. Change check to 

def _asdict_inner(obj, dict_factory):
if _is_dataclass_instance(obj):
return getattr(obj, _PARAMS).asdict(obj) 

# ... other code


Other solution could be to add parameter "directly_serializable"(smth like 
that), add check for this parameter

def _asdict_inner(obj, dict_factory):
if _is_dataclass_instance(obj):
if getattr(obj, _PARAMS).directly_serializable: 
return dict_factory(obj)

# ... other code

and force user to process everything in dict_factory function.

--

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com

[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[Eric V. Smith]

Eric V. Smith  added the comment:

I've been thinking about this, but I don't have a suggestion on how to improve 
the API. Maybe some sort of visitor pattern? I'm open to concrete ideas.

--

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com

[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[mkurnikov]

mkurnikov  added the comment:

from pprint import pprint
from typing import List, Any, Dict

import dataclasses
from dataclasses import field


def service_interface_dict_factory(obj: Any) -> Dict[str, Any]:
print(type(obj)) # <- type(obj) here is a list, but there's no way to 
understand whether it's a ServiceInterface or
# InputVar except for looking for the presence of certain keys which is not 
very convenient
return dict(obj)


@dataclasses.dataclass
class InputVar(object):
name: str
required: bool = False
options: Dict[str, Any] = field(default_factory=dict)


@dataclasses.dataclass
class ServiceInterface(object):
input: List[InputVar] = field(default_factory=list)


if __name__ == '__main__':
inputvar_inst = InputVar(name='myinput',
 required=False,
 options={'default': 'mytext'})
interface = ServiceInterface(input=[inputvar_inst])

outdict = dataclasses.asdict(interface, 
dict_factory=service_interface_dict_factory)
print('outdict', end=' ')
pprint(outdict)

# prints:
# outdict {'input': [{'name': 'myinput',
# 'options': {'default': 'mytext'},
# 'required': False}]}

# desirable output
# {'input': [{
# 'name': 'myinput',
# 'required': False,
# 'default': 'mytext'
# }]}
# "default" key moved to the root of the dictionary (inside list)

--

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com

[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[Eric V. Smith]

Change by Eric V. Smith :


--
assignee:  -> eric.smith

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com

[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[Eric V. Smith]

Eric V. Smith  added the comment:

Could you show some example dataclass instances? Also, show the output you get 
with asdict(), and show what output you'd like to get instead.

I'm not sure I understand it correctly from the description you've given.

Thanks!

--
nosy: +eric.smith
versions: +Python 3.7 -Python 3.6

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com

[issue34409] Add a way to customize iteration over fields in asdict() for the nested dataclasses

[mkurnikov]

New submission from mkurnikov :

Suppose I have two dataclasses:

@dataclass
class NestedDataclass(object):
name: str
options: Dict[str, Any] = field(default_factory=dict)

@dataclass
class RootDataclass(object):
nested_list: List[NestedDataclass]

I want a dict under the key "options" to be merged in the NestedDataclass dict 
in the dataclasses.asdict(root_dcls_instance). 

For that, according to docs, I need to specify dict_factory= for 
dataclasses.asdict() function. 

The problem is that, according to the implementation, when this function 
"meets" dataclass, there's no way to customize how result dict will be built. 
Dataclass itself is never passed to the function. 

if _is_dataclass_instance(obj):
result = []
for f in fields(obj):
value = _asdict_inner(getattr(obj, f.name), dict_factory)
result.append((f.name, value))
return dict_factory(result)

Yes, I can catch "result" obj (what I did in the end):

def root_dataclass_dict_factory(obj):
if isinstance(obj, list):
dataclass_dict = dict(obj)
if 'options' in dataclass_dict:
dataclass_dict.update(dataclass_dict.pop('options'))

return dict(obj)

The problem is that type of the dataclass is lost for the list, and if by any 
chance later I'll have "options" key in the RootDataclass, there's no way for 
me to distinguish between them cleanly. 

Other solution is to iterate over the RootDataclass dictionary, follow the path 
to the NestedDataclass and change dictionary there, but it even uglier. 

Would be nice to be able to somehow hook into the field traversal of the 
dataclass instance.

--
components: Library (Lib)
messages: 323542
nosy: mkurnikov
priority: normal
severity: normal
status: open
title: Add a way to customize iteration over fields in asdict() for the nested 
dataclasses
type: enhancement
versions: Python 3.6

___
Python tracker 

___
___
Python-bugs-list mailing list
Unsubscribe: 
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com