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Title:
Instances share objects after copy or created from unpacking a dict · Issue #249 · pydantic/pydantic
Description:
This is related to #154 and I'm using pydantic v0.12.1 Here is a simple example to show what I mean. >>> class Model(pydantic.BaseModel): ... my_dict: dict ... >>> model1 = Mo...
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Keywords {🔍}
model, copy, mydictmylist, samuelcolvin, dict, issue, gangefors, commented, pydantic, data, add, sign, share, created, modelmydict, create, deepcopy, member, case, dont, method, test, objects, unpacking, mydict, mylist, modelmydictmylist, basemodeldict, user, make, agree, deep, cases, contributor, author, navigation, issues, pull, requests, actions, security, instances, closed, class, modelcopy, dictionary, copies, correctly, true, support,
Topics {✒️}
async def my_view comment metadata assignees gangefors mentioned deep=false argument samuelcolvin closed add keyword arguments verified 895ddb0 sign class method model base data model support deepcopy operations create copies correctly issues user created classes objects terms docs referenced issue deep copy pydantic v0 share work correctly shallow copies base data {'my_list' significantly slower roughtly aiohttp web framework raise badrequesterror markdown link initial problem add support assigned labels labels type type projects projects milestone milestone relationships my_dict {'my_dict' my_dict input data true copy unpacked dictionary await request unit test test emptied github make sense converting dict model1 nuanced case
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Questions {❓}
- Already have an account?
- Do you want to change the way copy() works or should we add a deepcopy() method to seperate the two?
- Does that make sense?
Schema {🗺️}
DiscussionForumPosting:
context:https://schema.org
headline:Instances share objects after copy or created from unpacking a dict
articleBody:This is related to #154 and I'm using pydantic v0.12.1
Here is a simple example to show what I mean.
```python
>>> class Model(pydantic.BaseModel):
... my_dict: dict
...
>>> model1 = Model(**{'my_dict': {'my_list': [1,2,3]}})
>>> model1
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2 = model1.copy()
>>> model2
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2.my_dict['my_list'] = []
>>> model2
<Model my_dict={'my_list': []}>
>>> model1
<Model my_dict={'my_list': []}>
```
Another example when created by unpacking a dictionary.
```python
>>> my_dict = {'my_dict': {'my_list': [1,2,3]}}
>>> model1 = Model(**my_dict)
>>> model1
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2 = Model(**my_dict)
>>> model2
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2.my_dict['my_list'] = []
>>> model1
<Model my_dict={'my_list': []}>
>>> model2
<Model my_dict={'my_list': []}>
```
BaseModel.dict() seems to create copies correctly and can be used instead of .copy() to create a new object as seen with model3 in this example.
```python
>>> model1 = Model(**{'my_dict': {'my_list': [1,2,3]}})
>>> model1
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2 = model1.copy()
>>> model2
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model3 = Model(**model1.dict())
>>> model3
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2.my_dict['my_list'] = []
>>> model1
<Model my_dict={'my_list': []}>
>>> model2
<Model my_dict={'my_list': []}>
>>> model3
<Model my_dict={'my_list': [1, 2, 3]}>
```
I think this is quite serious since you can't know if you are working with a true copy of a model or not.
I see two things that need to be fixed.
.copy() should create a deepcopy that doesn't share any objects with the model it was copied from. User created classes have to support deepcopy operations to work correctly.
BaseModel(**dict) need to make sure that all items in the dict are deepcopied from the unpacked dictionary.
author:
url:https://github.com/gangefors
type:Person
name:gangefors
datePublished:2018-08-25T12:42:51.000Z
interactionStatistic:
type:InteractionCounter
interactionType:https://schema.org/CommentAction
userInteractionCount:7
url:https://github.com/249/pydantic/issues/249
context:https://schema.org
headline:Instances share objects after copy or created from unpacking a dict
articleBody:This is related to #154 and I'm using pydantic v0.12.1
Here is a simple example to show what I mean.
```python
>>> class Model(pydantic.BaseModel):
... my_dict: dict
...
>>> model1 = Model(**{'my_dict': {'my_list': [1,2,3]}})
>>> model1
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2 = model1.copy()
>>> model2
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2.my_dict['my_list'] = []
>>> model2
<Model my_dict={'my_list': []}>
>>> model1
<Model my_dict={'my_list': []}>
```
Another example when created by unpacking a dictionary.
```python
>>> my_dict = {'my_dict': {'my_list': [1,2,3]}}
>>> model1 = Model(**my_dict)
>>> model1
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2 = Model(**my_dict)
>>> model2
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2.my_dict['my_list'] = []
>>> model1
<Model my_dict={'my_list': []}>
>>> model2
<Model my_dict={'my_list': []}>
```
BaseModel.dict() seems to create copies correctly and can be used instead of .copy() to create a new object as seen with model3 in this example.
```python
>>> model1 = Model(**{'my_dict': {'my_list': [1,2,3]}})
>>> model1
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2 = model1.copy()
>>> model2
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model3 = Model(**model1.dict())
>>> model3
<Model my_dict={'my_list': [1, 2, 3]}>
>>> model2.my_dict['my_list'] = []
>>> model1
<Model my_dict={'my_list': []}>
>>> model2
<Model my_dict={'my_list': []}>
>>> model3
<Model my_dict={'my_list': [1, 2, 3]}>
```
I think this is quite serious since you can't know if you are working with a true copy of a model or not.
I see two things that need to be fixed.
.copy() should create a deepcopy that doesn't share any objects with the model it was copied from. User created classes have to support deepcopy operations to work correctly.
BaseModel(**dict) need to make sure that all items in the dict are deepcopied from the unpacked dictionary.
author:
url:https://github.com/gangefors
type:Person
name:gangefors
datePublished:2018-08-25T12:42:51.000Z
interactionStatistic:
type:InteractionCounter
interactionType:https://schema.org/CommentAction
userInteractionCount:7
url:https://github.com/249/pydantic/issues/249
Person:
url:https://github.com/gangefors
name:gangefors
url:https://github.com/gangefors
name:gangefors
InteractionCounter:
interactionType:https://schema.org/CommentAction
userInteractionCount:7
interactionType:https://schema.org/CommentAction
userInteractionCount:7
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