8000 modify behaviour of the construct method (#898) · ag-python/pydantic@677677e · GitHub
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modify behaviour of the construct method (pydantic#898)
* modify behaviour of the construct method * change construct signature * Add example for construct function (pydantic#907) * add example for construct * edit exporting_models * typo * add changes file * code review changes * fix bad copy paste * extend example in docs * use __field_defaults__ in construct
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‎changes/898-samuelcolvin.md

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Change the signature of `Model.construct()` to be more user-friendly, document `construct()` usage.

‎changes/907-ashears.md

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Add example for the `construct()` method

‎docs/examples/ex_construct.py

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from pydantic import BaseModel
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class User(BaseModel):
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id: int
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age: int
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name: str = 'John Doe'
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original_user = User(id=123, age=32)
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user_data = original_user.dict()
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print(user_data)
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fields_set = original_user.__fields_set__
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print(fields_set)
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# ...
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# pass user_data and fields_set to RPC or save to the database etc.
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# ...
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# you can then create a new instance of User without
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# re-running validation which would be unnecessary at this point:
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new_user = User.construct(_fields_set=fields_set, **user_data)
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print(repr(new_user))
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print(new_user.__fields_set__)
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# construct can be dangerous, only use it with validated data!:
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bad_user = User.construct(id='dog')
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print(repr(bad_user))

‎docs/usage/models.md

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@@ -92,6 +92,10 @@ Models possess the following methods and attributes:
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`schema_json()`
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: returns a JSON string representation of `schema()`; cf. [Schema](schema.md)
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`construct()`
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: a class method for creating models without running validation;
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cf. [Creating models without validation](#creating-models-without-validation)
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`__fields_set__`
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: Set of names of fields which were set when the model instance was initialised
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!!! info
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Because it can result in arbitrary code execution, as a security measure, you need
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to explicitly pass `allow_pickle` to the parsing function in order to load `pickle` data.
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### Creating models without validation
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*pydantic* also provides the `construct()` method which allows models to be created **without validation** this
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can be useful when data has already been validated or comes from a trusted source and you want to create a model
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as efficiently as possible (`construct()` is generally around 30x faster than creating a model with full validation).
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!!! warning
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`construct()` does not do any validation, meaning it can create models which are invalid. **You should only
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ever use the `construct()` method with data which has already been validated, or you trust.**
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```py
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{!.tmp_examples/ex_construct.py!}
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```
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_(This script is complete, it should run "as is")_
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The `_fields_set` keyword argument to `construct()` is optional, but allows you to be more precise about
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which fields were originally set and which weren't. If it's omitted `__fields_set__` will just be the keys
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of the data provided.
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For example, in the example above, if `_fields_set` was not provided,
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`new_user.__fields_set__` would be `{'id', 'age', 'name'}`.
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## Generic Models
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‎pydantic/main.py

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@@ -439,14 +439,16 @@ def from_orm(cls: Type['Model'], obj: Any) -> 'Model':
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return m
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@classmethod
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def construct(cls: Type['Model'], values: 'DictAny', fields_set: 'SetStr') -> 'Model':
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def construct(cls: Type['Model'], _fields_set: Optional['SetStr'] = None, **values: Any) -> 'Model':
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"""
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Creates a new model and set __dict__ without any validation, thus values should already be trusted.
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Chances are you don't want to use this method directly.
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Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
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Default values are respected, but no other validation is performed.
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"""
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m = cls.__new__(cls)
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object.__setattr__(m, '__dict__', values)
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object.__setattr__(m, '__fields_set__', fields_set)
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object.__setattr__(m, '__dict__', {**deepcopy(cls.__field_defaults__), **values})
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if _fields_set is None:
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_fields_set = set(values.keys())
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object.__setattr__(m, '__fields_set__', _fields_set)
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return m
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def copy(
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if deep:
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v = deepcopy(v)
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m = self.__class__.construct(v, self.__fields_set__.copy())
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cls = self.__class__
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m = cls.__new__(cls)
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object.__setattr__(m, '__dict__', v)
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object.__setattr__(m, '__fields_set__', self.__fields_set__.copy())
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return m
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@classmethod

‎tests/test_construction.py

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def test_simple_construct():
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m = Model.construct(dict(a=40, b=10), {'a', 'b'})
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assert m.a == 40
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m = Model.construct(a=3.14)
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assert m.a == 3.14
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assert m.b == 10
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assert m.__fields_set__ == {'a'}
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assert m.dict() == {'a': 3.14, 'b': 10}
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def test_construct_missing():
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m = Model.construct(dict(a='not a float'), {'a'})
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assert m.a == 'not a float'
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with pytest.raises(AttributeError) as exc_info:
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print(m.b)
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def test_construct_misuse():
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m = Model.construct(b='foobar')
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assert m.b == 'foobar'
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assert m.dict() == {'b': 'foobar'}
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with pytest.raises(AttributeError, match="'Model' object has no attribute 'a'"):
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print(m.a)
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assert "'Model' object has no attribute 'b'" in exc_info.value.args[0]
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def test_construct_fields_set():
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m = Model.construct(a=3.0, b=-1, _fields_set={'a'})
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assert m.a == 3
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assert m.b == -1
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assert m.__fields_set__ == {'a'}
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assert m.dict() == {'a': 3, 'b': -1}
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def test_large_any_str():

‎tests/test_edge_cases.py

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assert Model(a=1, field_set=2).dict() == {'a': 1, 'field_set': 2, 'b': 3}
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assert Model(a=1, field_set=2).dict(exclude_unset=True) == {'a': 1, 'field_set': 2}
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assert Model.construct(dict(a=1, field_set=3), {'a', 'field_set'}).dict() == {'a': 1, 'field_set': 3}
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assert Model.construct(a=1, field_set=3).dict() == {'a': 1, 'field_set': 3, 'b': 3}
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def test_values_order():

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