# pydantic-collections
[](https://github.com/romis2012/pydantic-collections/actions/workflows/ci.yml)
[](https://codecov.io/gh/romis2012/pydantic-collections)
[](https://pypi.python.org/pypi/pydantic-collections)
The `pydantic-collections` package provides `BaseCollectionModel` class that allows you
to manipulate collections of [pydantic](https://github.com/samuelcolvin/pydantic) models
(and any other types supported by pydantic).
## Requirements
- Python>=3.7
- pydantic>=1.8.2,<3.0
## Installation
```
pip install pydantic-collections
```
## Usage
#### Basic usage
```python
from datetime import datetime
from pydantic import BaseModel
from pydantic_collections import BaseCollectionModel
class User(BaseModel):
id: int
name: str
birth_date: datetime
class UserCollection(BaseCollectionModel[User]):
pass
user_data = [
{'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'},
{'id': 2, 'name': 'Balaganov', 'birth_date': '2020-04-01T12:59:59'},
]
users = UserCollection(user_data)
print(users)
#> UserCollection([User(id=1, name='Bender', birth_date=datetime.datetime(2010, 4, 1, 12, 59, 59)), User(id=2, name='Balaganov', birth_date=datetime.datetime(2020, 4, 1, 12, 59, 59))])
print(users.dict()) # pydantic v1.x
print(users.model_dump()) # pydantic v2.x
#> [{'id': 1, 'name': 'Bender', 'birth_date': datetime.datetime(2010, 4, 1, 12, 59, 59)}, {'id': 2, 'name': 'Balaganov', 'birth_date': datetime.datetime(2020, 4, 1, 12, 59, 59)}]
print(users.json()) # pydantic v1.x
print(users.model_dump_json()) # pydantic v2.x
#> [{"id": 1, "name": "Bender", "birth_date": "2010-04-01T12:59:59"}, {"id": 2, "name": "Balaganov", "birth_date": "2020-04-01T12:59:59"}]
```
#### Strict assignment validation
By default `BaseCollectionModel` has a strict assignment check
```python
...
users = UserCollection()
users.append(User(id=1, name='Bender', birth_date=datetime.utcnow())) # OK
users.append({'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'})
#> pydantic.error_wrappers.ValidationError: 1 validation error for UserCollection
#> __root__ -> 2
#> instance of User expected (type=type_error.arbitrary_type; expected_arbitrary_type=User)
```
This behavior can be changed via Model Config
Pydantic v1.x
```python
from pydantic_collections import BaseCollectionModel
...
class UserCollection(BaseCollectionModel[User]):
class Config:
validate_assignment_strict = False
```
Pydantic v2.x
```python
from pydantic_collections import BaseCollectionModel, CollectionModelConfig
...
class UserCollection(BaseCollectionModel[User]):
model_config = CollectionModelConfig(validate_assignment_strict=False)
```
```python
users = UserCollection()
users.append({'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'}) # OK
assert users[0].__class__ is User
assert users[0].id == 1
```
#### Using as a model field
`BaseCollectionModel` is a subclass of `BaseModel`, so you can use it as a model field
```python
...
class UserContainer(BaseModel):
users: UserCollection = []
data = {
'users': [
{'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'},
{'id': 2, 'name': 'Balaganov', 'birth_date': '2020-04-01T12:59:59'},
]
}
container = UserContainer(**data)
container.users.append(User(...))
...
```
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"description": "# pydantic-collections\n\n[](https://github.com/romis2012/pydantic-collections/actions/workflows/ci.yml)\n[](https://codecov.io/gh/romis2012/pydantic-collections)\n[](https://pypi.python.org/pypi/pydantic-collections)\n\nThe `pydantic-collections` package provides `BaseCollectionModel` class that allows you \nto manipulate collections of [pydantic](https://github.com/samuelcolvin/pydantic) models \n(and any other types supported by pydantic).\n\n\n## Requirements\n- Python>=3.7\n- pydantic>=1.8.2,<3.0\n\n\n## Installation\n\n```\npip install pydantic-collections\n```\n\n## Usage\n\n#### Basic usage\n```python\n\nfrom datetime import datetime\n\nfrom pydantic import BaseModel\nfrom pydantic_collections import BaseCollectionModel\n\n\nclass User(BaseModel):\n id: int\n name: str\n birth_date: datetime\n\n\nclass UserCollection(BaseCollectionModel[User]):\n pass\n\n\n user_data = [\n {'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'},\n {'id': 2, 'name': 'Balaganov', 'birth_date': '2020-04-01T12:59:59'},\n ]\n\nusers = UserCollection(user_data)\n\nprint(users)\n#> UserCollection([User(id=1, name='Bender', birth_date=datetime.datetime(2010, 4, 1, 12, 59, 59)), User(id=2, name='Balaganov', birth_date=datetime.datetime(2020, 4, 1, 12, 59, 59))])\n\nprint(users.dict()) # pydantic v1.x\nprint(users.model_dump()) # pydantic v2.x\n#> [{'id': 1, 'name': 'Bender', 'birth_date': datetime.datetime(2010, 4, 1, 12, 59, 59)}, {'id': 2, 'name': 'Balaganov', 'birth_date': datetime.datetime(2020, 4, 1, 12, 59, 59)}]\n\nprint(users.json()) # pydantic v1.x\nprint(users.model_dump_json()) # pydantic v2.x\n#> [{\"id\": 1, \"name\": \"Bender\", \"birth_date\": \"2010-04-01T12:59:59\"}, {\"id\": 2, \"name\": \"Balaganov\", \"birth_date\": \"2020-04-01T12:59:59\"}]\n```\n\n#### Strict assignment validation\n\nBy default `BaseCollectionModel` has a strict assignment check\n```python\n...\nusers = UserCollection()\nusers.append(User(id=1, name='Bender', birth_date=datetime.utcnow())) # OK\nusers.append({'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'})\n#> pydantic.error_wrappers.ValidationError: 1 validation error for UserCollection\n#> __root__ -> 2\n#> instance of User expected (type=type_error.arbitrary_type; expected_arbitrary_type=User)\n```\n\nThis behavior can be changed via Model Config\n\nPydantic v1.x\n```python\nfrom pydantic_collections import BaseCollectionModel\n...\nclass UserCollection(BaseCollectionModel[User]):\n class Config:\n validate_assignment_strict = False\n```\n\nPydantic v2.x\n```python\nfrom pydantic_collections import BaseCollectionModel, CollectionModelConfig\n...\nclass UserCollection(BaseCollectionModel[User]):\n model_config = CollectionModelConfig(validate_assignment_strict=False)\n```\n\n```python\nusers = UserCollection()\nusers.append({'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'}) # OK\nassert users[0].__class__ is User\nassert users[0].id == 1\n```\n\n#### Using as a model field\n\n`BaseCollectionModel` is a subclass of `BaseModel`, so you can use it as a model field\n```python\n...\nclass UserContainer(BaseModel):\n users: UserCollection = []\n \ndata = {\n 'users': [\n {'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'},\n {'id': 2, 'name': 'Balaganov', 'birth_date': '2020-04-01T12:59:59'},\n ]\n}\n\ncontainer = UserContainer(**data)\ncontainer.users.append(User(...))\n...\n```\n",
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