Merge pull request #183 from collerek/large_binary
Add large binary, support for native pydantic fields, examples in openapi
This commit is contained in:
1
.github/FUNDING.yml
vendored
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1
.github/FUNDING.yml
vendored
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@ -0,0 +1 @@
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github: collerek
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12
Makefile
12
Makefile
@ -17,3 +17,15 @@ test_mysql:
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test_sqlite:
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bash scripts/test.sh -svv
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test:
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pytest
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coverage:
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pytest --cov=ormar --cov=tests --cov-fail-under=100 --cov-report=term-missing
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black:
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black ormar tests
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mypy:
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mypy ormar tests
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13
README.md
13
README.md
@ -452,6 +452,16 @@ async def aggregations():
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# visit: https://collerek.github.io/ormar/queries/aggregations/
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async def with_connect(function):
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# note that for any other backend than sqlite you actually need to
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# connect to the database to perform db operations
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async with database:
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await function()
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# note that if you use framework like `fastapi` you shouldn't connect
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# in your endpoints but have a global connection pool
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# check https://collerek.github.io/ormar/fastapi/ and section with db connection
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# gather and execute all functions
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# note - normally import should be at the beginning of the file
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import asyncio
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@ -462,7 +472,7 @@ for func in [create, read, update, delete, joins,
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filter_and_sort, subset_of_columns,
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pagination, aggregations]:
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print(f"Executing: {func.__name__}")
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asyncio.run(func())
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asyncio.run(with_connect(func))
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# drop the database tables
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metadata.drop_all(engine)
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@ -521,6 +531,7 @@ Available Model Fields (with required args - optional ones in docs):
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* `BigInteger()`
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* `Decimal(scale, precision)`
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* `UUID()`
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* `LargeBinary(max_length)`
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* `EnumField` - by passing `choices` to any other Field type
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* `EncryptedString` - by passing `encrypt_secret` and `encrypt_backend`
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* `ForeignKey(to)`
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@ -98,7 +98,11 @@ Sets the unique constraint on a table's column.
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Used in sql only.
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## pydantic_only
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## pydantic_only (**DEPRECATED**)
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**This parameter is deprecated and will be removed in one of next releases!**
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**To check how to declare pydantic only fields that are not saved into database see [pydantic fields section](pydantic-fields.md)**
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`pydantic_only`: `bool` = `False`
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@ -127,6 +127,17 @@ You can use either `length` and `precision` parameters or `max_digits` and `deci
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* Sqlalchemy column: `sqlalchemy.JSON`
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* Type (used for pydantic): `pydantic.Json`
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### LargeBinary
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`LargeBinary(max_length)` has a required `max_length` parameter.
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* Sqlalchemy column: `sqlalchemy.LargeBinary`
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* Type (used for pydantic): `bytes`
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LargeBinary length is used in some backend (i.e. mysql) to determine the size of the field,
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in other backends it's simply ignored yet in ormar it's always required. It should be max
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size of the file/bytes in bytes.
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### UUID
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`UUID(uuid_format: str = 'hex')` has no required parameters.
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195
docs/fields/pydantic-fields.md
Normal file
195
docs/fields/pydantic-fields.md
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@ -0,0 +1,195 @@
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# Pydantic only fields
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Ormar allows you to declare normal `pydantic` fields in its model, so you have access to
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all basic and custom pydantic fields like `str`, `int`, `HttpUrl`, `PaymentCardNumber` etc.
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You can even declare fields leading to nested pydantic only Models, not only single fields.
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Since those fields are not stored in database (that's the whole point of those fields),
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you have to provide a meaningful value for them, either by setting a default one or
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providing one during model initialization.
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If `ormar` cannot resolve the value for pydantic field it will fail during loading data from the database,
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with missing required value for declared pydantic field.
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Options to provide a value are described below.
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Of course you can combine few or all of them in one model.
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## Optional field
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If you set a field as `Optional`, it defaults to `None` if not provided and that's
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exactly what's going to happen during loading from database.
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```python
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database = databases.Database(DATABASE_URL)
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metadata = sqlalchemy.MetaData()
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class BaseMeta(ormar.ModelMeta):
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metadata = metadata
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database = database
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class ModelTest(ormar.Model):
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class Meta(BaseMeta):
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pass
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=200)
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number: Optional[PaymentCardNumber]
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test = ModelTest(name="Test")
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assert test.name == "Test"
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assert test.number is None
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test.number = "123456789015"
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await test.save()
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test_check = await ModelTest.objects.get()
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assert test_check.name == "Test"
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# after load it's back to None
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assert test_check.number is None
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```
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## Field with default value
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By setting a default value, this value will be set on initialization and database load.
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Note that setting a default to `None` is the same as setting the field to `Optional`.
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```python
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database = databases.Database(DATABASE_URL)
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metadata = sqlalchemy.MetaData()
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class BaseMeta(ormar.ModelMeta):
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metadata = metadata
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database = database
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class ModelTest(ormar.Model):
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class Meta(BaseMeta):
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pass
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=200)
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url: HttpUrl = "https://www.example.com"
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test = ModelTest(name="Test")
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assert test.name == "Test"
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assert test.url == "https://www.example.com"
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test.url = "https://www.sdta.ada.pt"
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assert test.url == "https://www.sdta.ada.pt"
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await test.save()
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test_check = await ModelTest.objects.get()
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assert test_check.name == "Test"
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# after load it's back to default
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assert test_check.url == "https://www.example.com"
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```
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## Default factory function
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By setting a `default_factory` function, this result of the function call will be set
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on initialization and each database load.
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```python
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from pydantic import Field, PaymentCardNumber
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# ...
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database = databases.Database(DATABASE_URL)
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metadata = sqlalchemy.MetaData()
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class BaseMeta(ormar.ModelMeta):
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metadata = metadata
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database = database
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CARD_NUMBERS = [
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"123456789007",
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"123456789015",
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"123456789023",
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"123456789031",
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"123456789049",
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]
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def get_number():
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return random.choice(CARD_NUMBERS)
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class ModelTest2(ormar.Model):
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class Meta(BaseMeta):
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pass
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=200)
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# note that you do not call the function, just pass reference
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number: PaymentCardNumber = Field(default_factory=get_number)
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# note that you still CAN provide a value
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test = ModelTest2(name="Test2", number="4000000000000002")
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assert test.name == "Test2"
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assert test.number == "4000000000000002"
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await test.save()
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test_check = await ModelTest2.objects.get()
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assert test_check.name == "Test2"
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# after load value is set to be one of the CARD_NUMBERS
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assert test_check.number in CARD_NUMBERS
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assert test_check.number != test.number
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```
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## Custom setup in `__init__`
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You can provide a value for the field in your `__init__()` method before calling a `super()` init method.
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```python
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from pydantic import BaseModel
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# ...
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database = databases.Database(DATABASE_URL)
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metadata = sqlalchemy.MetaData()
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class BaseMeta(ormar.ModelMeta):
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metadata = metadata
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database = database
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class PydanticTest(BaseModel):
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aa: str
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bb: int
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class ModelTest3(ormar.Model):
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class Meta(BaseMeta):
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pass
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# provide your custom init function
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def __init__(self, **kwargs):
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# add value for required field without default value
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kwargs["pydantic_test"] = PydanticTest(aa="random", bb=42)
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# remember to call ormar.Model init!
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super().__init__(**kwargs)
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=200)
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pydantic_test: PydanticTest
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test = ModelTest3(name="Test3")
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assert test.name == "Test3"
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assert test.pydantic_test.bb == 42
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test.pydantic.aa = "new value"
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assert test.pydantic.aa == "new value"
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await test.save()
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test_check = await ModelTest3.objects.get()
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assert test_check.name == "Test3"
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# after load it's back to value provided in init
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assert test_check.pydantic_test.aa == "random"
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```
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!!!warning
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If you do not provide a value in one of the above ways `ValidationError` will be raised on load from database.
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@ -452,6 +452,16 @@ async def aggregations():
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# visit: https://collerek.github.io/ormar/queries/aggregations/
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|
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async def with_connect(function):
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# note that for any other backend than sqlite you actually need to
|
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# connect to the database to perform db operations
|
||||
async with database:
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await function()
|
||||
|
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# note that if you use framework like `fastapi` you shouldn't connect
|
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# in your endpoints but have a global connection pool
|
||||
# check https://collerek.github.io/ormar/fastapi/ and section with db connection
|
||||
|
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# gather and execute all functions
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# note - normally import should be at the beginning of the file
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import asyncio
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@ -462,7 +472,7 @@ for func in [create, read, update, delete, joins,
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filter_and_sort, subset_of_columns,
|
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pagination, aggregations]:
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print(f"Executing: {func.__name__}")
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asyncio.run(func())
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asyncio.run(with_connect(func))
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# drop the database tables
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metadata.drop_all(engine)
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@ -521,6 +531,7 @@ Available Model Fields (with required args - optional ones in docs):
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* `BigInteger()`
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* `Decimal(scale, precision)`
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* `UUID()`
|
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* `LargeBinary(max_length)`
|
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* `EnumField` - by passing `choices` to any other Field type
|
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* `EncryptedString` - by passing `encrypt_secret` and `encrypt_backend`
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* `ForeignKey(to)`
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@ -1,3 +1,38 @@
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# 0.10.6
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## ✨ Features
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* Add `LargeBinary(max_length)` field type [#166](https://github.com/collerek/ormar/issues/166)
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* Add support for normal pydantic fields (including Models) instead of `pydantic_only`
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attribute which is now deprecated [#160](https://github.com/collerek/ormar/issues/160).
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Pydantic fields should be declared normally as in pydantic model next to ormar fields,
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note that (obviously) `ormar` does not save and load the value for this field in
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database that mean that **ONE** of the following has to be true:
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* pydantic field declared on ormar model has to be `Optional` (defaults to None)
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* pydantic field has to have a default value set
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* pydantic field has `default_factory` function set
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* ormar.Model with pydantic field has to overwrite `__init__()` and provide the value there
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If none of the above `ormar` (or rather pydantic) will fail during loading data from the database,
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with missing required value for declared pydantic field.
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* Ormar provides now a meaningful examples in openapi schema, including nested models.
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The same algorithm is used to iterate related models without looks
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as with `dict()` and `select/load_all`. Examples appear also in `fastapi`. [#157](https://github.com/collerek/ormar/issues/157)
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## 🐛 Fixes
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* By default `pydantic` is not validating fields during assignment,
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which is not a desirable setting for an ORM, now all `ormar.Models`
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have validation turned-on during assignment (like `model.column = 'value'`)
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## 💬 Other
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* Add connecting to the database in QuickStart in readme [#180](https://github.com/collerek/ormar/issues/180)
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* OpenAPI schema does no longer include `ormar.Model` docstring as description,
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instead just model name is provided if you do not provide your own docstring.
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* Some performance improvements.
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# 0.10.5
|
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|
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## 🐛 Fixes
|
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|
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Binary file not shown.
@ -319,6 +319,16 @@ async def aggregations():
|
||||
# visit: https://collerek.github.io/ormar/queries/aggregations/
|
||||
|
||||
|
||||
async def with_connect(function):
|
||||
# note that for any other backend than sqlite you actually need to
|
||||
# connect to the database to perform db operations
|
||||
async with database:
|
||||
await function()
|
||||
|
||||
# note that if you use framework like `fastapi` you shouldn't connect
|
||||
# in your endpoints but have a global connection pool
|
||||
# check https://collerek.github.io/ormar/fastapi/ and section with db connection
|
||||
|
||||
# gather and execute all functions
|
||||
# note - normally import should be at the beginning of the file
|
||||
import asyncio
|
||||
@ -329,7 +339,7 @@ for func in [create, read, update, delete, joins,
|
||||
filter_and_sort, subset_of_columns,
|
||||
pagination, aggregations]:
|
||||
print(f"Executing: {func.__name__}")
|
||||
asyncio.run(func())
|
||||
asyncio.run(with_connect(func))
|
||||
|
||||
# drop the database tables
|
||||
metadata.drop_all(engine)
|
||||
@ -12,6 +12,7 @@ nav:
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- Fields:
|
||||
- Common parameters: fields/common-parameters.md
|
||||
- Fields types: fields/field-types.md
|
||||
- Pydantic only fields: fields/pydantic-fields.md
|
||||
- Fields encryption: fields/encryption.md
|
||||
- Relations:
|
||||
- relations/index.md
|
||||
|
||||
@ -53,6 +53,7 @@ from ormar.fields import (
|
||||
ForeignKeyField,
|
||||
Integer,
|
||||
JSON,
|
||||
LargeBinary,
|
||||
ManyToMany,
|
||||
ManyToManyField,
|
||||
String,
|
||||
@ -75,7 +76,7 @@ class UndefinedType: # pragma no cover
|
||||
|
||||
Undefined = UndefinedType()
|
||||
|
||||
__version__ = "0.10.5"
|
||||
__version__ = "0.10.6"
|
||||
__all__ = [
|
||||
"Integer",
|
||||
"BigInteger",
|
||||
@ -124,4 +125,5 @@ __all__ = [
|
||||
"EncryptBackends",
|
||||
"ENCODERS_MAP",
|
||||
"DECODERS_MAP",
|
||||
"LargeBinary",
|
||||
]
|
||||
|
||||
@ -16,6 +16,7 @@ from ormar.fields.model_fields import (
|
||||
Float,
|
||||
Integer,
|
||||
JSON,
|
||||
LargeBinary,
|
||||
String,
|
||||
Text,
|
||||
Time,
|
||||
@ -50,4 +51,5 @@ __all__ = [
|
||||
"EncryptBackend",
|
||||
"DECODERS_MAP",
|
||||
"ENCODERS_MAP",
|
||||
"LargeBinary",
|
||||
]
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
import warnings
|
||||
from typing import Any, Dict, List, Optional, TYPE_CHECKING, Type, Union
|
||||
|
||||
import sqlalchemy
|
||||
@ -30,6 +31,7 @@ class BaseField(FieldInfo):
|
||||
|
||||
def __init__(self, **kwargs: Any) -> None:
|
||||
self.__type__: type = kwargs.pop("__type__", None)
|
||||
self.__sample__: type = kwargs.pop("__sample__", None)
|
||||
self.related_name = kwargs.pop("related_name", None)
|
||||
|
||||
self.column_type: sqlalchemy.Column = kwargs.pop("column_type", None)
|
||||
@ -43,6 +45,14 @@ class BaseField(FieldInfo):
|
||||
self.index: bool = kwargs.pop("index", False)
|
||||
self.unique: bool = kwargs.pop("unique", False)
|
||||
self.pydantic_only: bool = kwargs.pop("pydantic_only", False)
|
||||
if self.pydantic_only:
|
||||
warnings.warn(
|
||||
"Parameter `pydantic_only` is deprecated and will "
|
||||
"be removed in one of the next releases.\n You can declare "
|
||||
"pydantic fields in a normal way. \n Check documentation: "
|
||||
"https://collerek.github.io/ormar/fields/pydantic-fields",
|
||||
DeprecationWarning,
|
||||
)
|
||||
self.choices: typing.Sequence = kwargs.pop("choices", False)
|
||||
|
||||
self.virtual: bool = kwargs.pop(
|
||||
|
||||
@ -80,7 +80,7 @@ def create_dummy_model(
|
||||
:rtype: pydantic.BaseModel
|
||||
"""
|
||||
alias = (
|
||||
"".join(choices(string.ascii_uppercase, k=2)) + uuid.uuid4().hex[:4]
|
||||
"".join(choices(string.ascii_uppercase, k=6)) # + uuid.uuid4().hex[:4]
|
||||
).lower()
|
||||
fields = {f"{pk_field.name}": (pk_field.__type__, None)}
|
||||
|
||||
|
||||
@ -62,6 +62,7 @@ class ModelFieldFactory:
|
||||
|
||||
_bases: Any = (BaseField,)
|
||||
_type: Any = None
|
||||
_sample: Any = None
|
||||
|
||||
def __new__(cls, *args: Any, **kwargs: Any) -> BaseField: # type: ignore
|
||||
cls.validate(**kwargs)
|
||||
@ -80,6 +81,7 @@ class ModelFieldFactory:
|
||||
|
||||
namespace = dict(
|
||||
__type__=cls._type,
|
||||
__sample__=cls._sample,
|
||||
alias=kwargs.pop("name", None),
|
||||
name=None,
|
||||
primary_key=primary_key,
|
||||
@ -129,6 +131,7 @@ class String(ModelFieldFactory, str):
|
||||
"""
|
||||
|
||||
_type = str
|
||||
_sample = "string"
|
||||
|
||||
def __new__( # type: ignore # noqa CFQ002
|
||||
cls,
|
||||
@ -185,6 +188,7 @@ class Integer(ModelFieldFactory, int):
|
||||
"""
|
||||
|
||||
_type = int
|
||||
_sample = 0
|
||||
|
||||
def __new__( # type: ignore
|
||||
cls,
|
||||
@ -232,6 +236,7 @@ class Text(ModelFieldFactory, str):
|
||||
"""
|
||||
|
||||
_type = str
|
||||
_sample = "text"
|
||||
|
||||
def __new__( # type: ignore
|
||||
cls, *, allow_blank: bool = True, strip_whitespace: bool = False, **kwargs: Any
|
||||
@ -267,6 +272,7 @@ class Float(ModelFieldFactory, float):
|
||||
"""
|
||||
|
||||
_type = float
|
||||
_sample = 0.0
|
||||
|
||||
def __new__( # type: ignore
|
||||
cls,
|
||||
@ -316,6 +322,7 @@ else:
|
||||
"""
|
||||
|
||||
_type = bool
|
||||
_sample = True
|
||||
|
||||
@classmethod
|
||||
def get_column_type(cls, **kwargs: Any) -> Any:
|
||||
@ -337,6 +344,7 @@ class DateTime(ModelFieldFactory, datetime.datetime):
|
||||
"""
|
||||
|
||||
_type = datetime.datetime
|
||||
_sample = "datetime"
|
||||
|
||||
@classmethod
|
||||
def get_column_type(cls, **kwargs: Any) -> Any:
|
||||
@ -358,6 +366,7 @@ class Date(ModelFieldFactory, datetime.date):
|
||||
"""
|
||||
|
||||
_type = datetime.date
|
||||
_sample = "date"
|
||||
|
||||
@classmethod
|
||||
def get_column_type(cls, **kwargs: Any) -> Any:
|
||||
@ -379,6 +388,7 @@ class Time(ModelFieldFactory, datetime.time):
|
||||
"""
|
||||
|
||||
_type = datetime.time
|
||||
_sample = "time"
|
||||
|
||||
@classmethod
|
||||
def get_column_type(cls, **kwargs: Any) -> Any:
|
||||
@ -400,6 +410,7 @@ class JSON(ModelFieldFactory, pydantic.Json):
|
||||
"""
|
||||
|
||||
_type = pydantic.Json
|
||||
_sample = '{"json": "json"}'
|
||||
|
||||
@classmethod
|
||||
def get_column_type(cls, **kwargs: Any) -> Any:
|
||||
@ -415,12 +426,61 @@ class JSON(ModelFieldFactory, pydantic.Json):
|
||||
return sqlalchemy.JSON()
|
||||
|
||||
|
||||
class LargeBinary(ModelFieldFactory, bytes):
|
||||
"""
|
||||
LargeBinary field factory that construct Field classes and populated their values.
|
||||
"""
|
||||
|
||||
_type = bytes
|
||||
_sample = "bytes"
|
||||
|
||||
def __new__( # type: ignore # noqa CFQ002
|
||||
cls, *, max_length: int = None, **kwargs: Any
|
||||
) -> BaseField: # type: ignore
|
||||
kwargs = {
|
||||
**kwargs,
|
||||
**{
|
||||
k: v
|
||||
for k, v in locals().items()
|
||||
if k not in ["cls", "__class__", "kwargs"]
|
||||
},
|
||||
}
|
||||
return super().__new__(cls, **kwargs)
|
||||
|
||||
@classmethod
|
||||
def get_column_type(cls, **kwargs: Any) -> Any:
|
||||
"""
|
||||
Return proper type of db column for given field type.
|
||||
Accepts required and optional parameters that each column type accepts.
|
||||
|
||||
:param kwargs: key, value pairs of sqlalchemy options
|
||||
:type kwargs: Any
|
||||
:return: initialized column with proper options
|
||||
:rtype: sqlalchemy Column
|
||||
"""
|
||||
return sqlalchemy.LargeBinary(length=kwargs.get("max_length"))
|
||||
|
||||
@classmethod
|
||||
def validate(cls, **kwargs: Any) -> None:
|
||||
"""
|
||||
Used to validate if all required parameters on a given field type are set.
|
||||
:param kwargs: all params passed during construction
|
||||
:type kwargs: Any
|
||||
"""
|
||||
max_length = kwargs.get("max_length", None)
|
||||
if max_length is None or max_length <= 0:
|
||||
raise ModelDefinitionError(
|
||||
"Parameter max_length is required for field LargeBinary"
|
||||
)
|
||||
|
||||
|
||||
class BigInteger(Integer, int):
|
||||
"""
|
||||
BigInteger field factory that construct Field classes and populated their values.
|
||||
"""
|
||||
|
||||
_type = int
|
||||
_sample = 0
|
||||
|
||||
def __new__( # type: ignore
|
||||
cls,
|
||||
@ -468,6 +528,7 @@ class Decimal(ModelFieldFactory, decimal.Decimal):
|
||||
"""
|
||||
|
||||
_type = decimal.Decimal
|
||||
_sample = 0.0
|
||||
|
||||
def __new__( # type: ignore # noqa CFQ002
|
||||
cls,
|
||||
@ -540,6 +601,7 @@ class UUID(ModelFieldFactory, uuid.UUID):
|
||||
"""
|
||||
|
||||
_type = uuid.UUID
|
||||
_sample = "uuid"
|
||||
|
||||
def __new__( # type: ignore # noqa CFQ002
|
||||
cls, *, uuid_format: str = "hex", **kwargs: Any
|
||||
|
||||
@ -3,6 +3,7 @@ import itertools
|
||||
import sqlite3
|
||||
from typing import Any, Dict, List, TYPE_CHECKING, Tuple, Type
|
||||
|
||||
import pydantic
|
||||
from pydantic.typing import ForwardRef
|
||||
import ormar # noqa: I100
|
||||
from ormar.models.helpers.pydantic import populate_pydantic_default_values
|
||||
@ -61,6 +62,12 @@ def populate_default_options_values(
|
||||
else:
|
||||
new_model.Meta.requires_ref_update = False
|
||||
|
||||
new_model._json_fields = {
|
||||
name
|
||||
for name, field in new_model.Meta.model_fields.items()
|
||||
if field.__type__ == pydantic.Json
|
||||
}
|
||||
|
||||
|
||||
class Connection(sqlite3.Connection):
|
||||
def __init__(self, *args: Any, **kwargs: Any) -> None: # pragma: no cover
|
||||
|
||||
@ -98,6 +98,7 @@ def get_pydantic_base_orm_config() -> Type[pydantic.BaseConfig]:
|
||||
|
||||
class Config(pydantic.BaseConfig):
|
||||
orm_mode = True
|
||||
validate_assignment = True
|
||||
|
||||
return Config
|
||||
|
||||
|
||||
@ -1,8 +1,9 @@
|
||||
import datetime
|
||||
import decimal
|
||||
import numbers
|
||||
import uuid
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, TYPE_CHECKING, Tuple, Type
|
||||
from typing import Any, Dict, List, Set, TYPE_CHECKING, Tuple, Type, Union
|
||||
|
||||
try:
|
||||
import orjson as json
|
||||
@ -10,11 +11,13 @@ except ImportError: # pragma: no cover
|
||||
import json # type: ignore
|
||||
|
||||
import pydantic
|
||||
from pydantic.fields import SHAPE_LIST
|
||||
from pydantic.main import SchemaExtraCallable
|
||||
|
||||
import ormar # noqa: I100, I202
|
||||
from ormar.fields import BaseField
|
||||
from ormar.models.helpers.models import meta_field_not_set
|
||||
from ormar.queryset.utils import translate_list_to_dict
|
||||
|
||||
if TYPE_CHECKING: # pragma no cover
|
||||
from ormar import Model
|
||||
@ -73,6 +76,8 @@ def convert_choices_if_needed( # noqa: CCR001
|
||||
else value
|
||||
)
|
||||
choices = [round(float(o), precision) for o in choices]
|
||||
elif field.__type__ == bytes:
|
||||
value = value if isinstance(value, bytes) else value.encode("utf-8")
|
||||
|
||||
return value, choices
|
||||
|
||||
@ -114,12 +119,109 @@ def choices_validator(cls: Type["Model"], values: Dict[str, Any]) -> Dict[str, A
|
||||
return values
|
||||
|
||||
|
||||
def generate_model_example(model: Type["Model"], relation_map: Dict = None) -> Dict:
|
||||
"""
|
||||
Generates example to be included in schema in fastapi.
|
||||
|
||||
:param model: ormar.Model
|
||||
:type model: Type["Model"]
|
||||
:param relation_map: dict with relations to follow
|
||||
:type relation_map: Optional[Dict]
|
||||
:return:
|
||||
:rtype: Dict[str, int]
|
||||
"""
|
||||
example: Dict[str, Any] = dict()
|
||||
relation_map = (
|
||||
relation_map
|
||||
if relation_map is not None
|
||||
else translate_list_to_dict(model._iterate_related_models())
|
||||
)
|
||||
for name, field in model.Meta.model_fields.items():
|
||||
if not field.is_relation:
|
||||
example[name] = field.__sample__
|
||||
elif isinstance(relation_map, dict) and name in relation_map:
|
||||
example[name] = get_nested_model_example(
|
||||
name=name, field=field, relation_map=relation_map
|
||||
)
|
||||
to_exclude = {name for name in model.Meta.model_fields}
|
||||
pydantic_repr = generate_pydantic_example(pydantic_model=model, exclude=to_exclude)
|
||||
example.update(pydantic_repr)
|
||||
|
||||
return example
|
||||
|
||||
|
||||
def get_nested_model_example(
|
||||
name: str, field: "BaseField", relation_map: Dict
|
||||
) -> Union[List, Dict]:
|
||||
"""
|
||||
Gets representation of nested model.
|
||||
|
||||
:param name: name of the field to follow
|
||||
:type name: str
|
||||
:param field: ormar field
|
||||
:type field: BaseField
|
||||
:param relation_map: dict with relation map
|
||||
:type relation_map: Dict
|
||||
:return: nested model or list of nested model repr
|
||||
:rtype: Union[List, Dict]
|
||||
"""
|
||||
value = generate_model_example(field.to, relation_map=relation_map.get(name, {}))
|
||||
new_value: Union[List, Dict] = [value] if field.is_multi or field.virtual else value
|
||||
return new_value
|
||||
|
||||
|
||||
def generate_pydantic_example(
|
||||
pydantic_model: Type[pydantic.BaseModel], exclude: Set = None
|
||||
) -> Dict:
|
||||
"""
|
||||
Generates dict with example.
|
||||
|
||||
:param pydantic_model: model to parse
|
||||
:type pydantic_model: Type[pydantic.BaseModel]
|
||||
:param exclude: list of fields to exclude
|
||||
:type exclude: Optional[Set]
|
||||
:return: dict with fields and sample values
|
||||
:rtype: Dict
|
||||
"""
|
||||
example: Dict[str, Any] = dict()
|
||||
exclude = exclude or set()
|
||||
name_to_check = [name for name in pydantic_model.__fields__ if name not in exclude]
|
||||
for name in name_to_check:
|
||||
field = pydantic_model.__fields__[name]
|
||||
type_ = field.type_
|
||||
if field.shape == SHAPE_LIST:
|
||||
example[name] = [get_pydantic_example_repr(type_)]
|
||||
else:
|
||||
example[name] = get_pydantic_example_repr(type_)
|
||||
return example
|
||||
|
||||
|
||||
def get_pydantic_example_repr(type_: Any) -> Any:
|
||||
"""
|
||||
Gets sample representation of pydantic field for example dict.
|
||||
|
||||
:param type_: type of pydantic field
|
||||
:type type_: Any
|
||||
:return: representation to include in example
|
||||
:rtype: Any
|
||||
"""
|
||||
if issubclass(type_, (numbers.Number, decimal.Decimal)):
|
||||
return 0
|
||||
elif issubclass(type_, pydantic.BaseModel):
|
||||
return generate_pydantic_example(pydantic_model=type_)
|
||||
else:
|
||||
return "string"
|
||||
|
||||
|
||||
def construct_modify_schema_function(fields_with_choices: List) -> SchemaExtraCallable:
|
||||
"""
|
||||
Modifies the schema to include fields with choices validator.
|
||||
Those fields will be displayed in schema as Enum types with available choices
|
||||
values listed next to them.
|
||||
|
||||
Note that schema extra has to be a function, otherwise it's called to soon
|
||||
before all the relations are expanded.
|
||||
|
||||
:param fields_with_choices: list of fields with choices validation
|
||||
:type fields_with_choices: List
|
||||
:return: callable that will be run by pydantic to modify the schema
|
||||
@ -131,6 +233,28 @@ def construct_modify_schema_function(fields_with_choices: List) -> SchemaExtraCa
|
||||
if field_id in fields_with_choices:
|
||||
prop["enum"] = list(model.Meta.model_fields[field_id].choices)
|
||||
prop["description"] = prop.get("description", "") + "An enumeration."
|
||||
schema["example"] = generate_model_example(model=model)
|
||||
if "Main base class of ormar Model." in schema.get("description", ""):
|
||||
schema["description"] = f"{model.__name__}"
|
||||
|
||||
return staticmethod(schema_extra) # type: ignore
|
||||
|
||||
|
||||
def construct_schema_function_without_choices() -> SchemaExtraCallable:
|
||||
"""
|
||||
Modifies model example and description if needed.
|
||||
|
||||
Note that schema extra has to be a function, otherwise it's called to soon
|
||||
before all the relations are expanded.
|
||||
|
||||
:return: callable that will be run by pydantic to modify the schema
|
||||
:rtype: Callable
|
||||
"""
|
||||
|
||||
def schema_extra(schema: Dict[str, Any], model: Type["Model"]) -> None:
|
||||
schema["example"] = generate_model_example(model=model)
|
||||
if "Main base class of ormar Model." in schema.get("description", ""):
|
||||
schema["description"] = f"{model.__name__}"
|
||||
|
||||
return staticmethod(schema_extra) # type: ignore
|
||||
|
||||
@ -160,3 +284,5 @@ def populate_choices_validators(model: Type["Model"]) -> None: # noqa CCR001
|
||||
model.Config.schema_extra = construct_modify_schema_function(
|
||||
fields_with_choices=fields_with_choices
|
||||
)
|
||||
else:
|
||||
model.Config.schema_extra = construct_schema_function_without_choices()
|
||||
|
||||
@ -94,6 +94,7 @@ def add_cached_properties(new_model: Type["Model"]) -> None:
|
||||
new_model._related_fields = None
|
||||
new_model._pydantic_fields = {name for name in new_model.__fields__}
|
||||
new_model._choices_fields = set()
|
||||
new_model._json_fields = set()
|
||||
|
||||
|
||||
def add_property_fields(new_model: Type["Model"], attrs: Dict) -> None: # noqa: CCR001
|
||||
|
||||
@ -48,7 +48,7 @@ class RelationMixin:
|
||||
:return: list of related fields
|
||||
:rtype: List
|
||||
"""
|
||||
if isinstance(cls._related_fields, List):
|
||||
if cls._related_fields is not None:
|
||||
return cls._related_fields
|
||||
|
||||
related_fields = []
|
||||
@ -66,7 +66,7 @@ class RelationMixin:
|
||||
:return: set of related through fields names
|
||||
:rtype: Set
|
||||
"""
|
||||
if isinstance(cls._through_names, Set):
|
||||
if cls._through_names is not None:
|
||||
return cls._through_names
|
||||
|
||||
related_names = set()
|
||||
@ -86,7 +86,7 @@ class RelationMixin:
|
||||
:return: set of related fields names
|
||||
:rtype: Set
|
||||
"""
|
||||
if isinstance(cls._related_names, Set):
|
||||
if cls._related_names is not None:
|
||||
return cls._related_names
|
||||
|
||||
related_names = set()
|
||||
|
||||
@ -275,12 +275,12 @@ class SavePrepareMixin(RelationMixin, AliasMixin):
|
||||
:rtype: int
|
||||
"""
|
||||
for field in fields_list:
|
||||
value = getattr(self, field.name) or []
|
||||
if not isinstance(value, list):
|
||||
value = [value]
|
||||
for val in value:
|
||||
values = getattr(self, field.name) or []
|
||||
if not isinstance(values, list):
|
||||
values = [values]
|
||||
for value in values:
|
||||
if follow:
|
||||
update_count = await val.save_related(
|
||||
update_count = await value.save_related(
|
||||
follow=follow,
|
||||
save_all=save_all,
|
||||
relation_map=self._skip_ellipsis( # type: ignore
|
||||
@ -291,8 +291,8 @@ class SavePrepareMixin(RelationMixin, AliasMixin):
|
||||
relation_field=field,
|
||||
)
|
||||
else:
|
||||
update_count = await val._upsert_model(
|
||||
instance=val,
|
||||
update_count = await value._upsert_model(
|
||||
instance=value,
|
||||
save_all=save_all,
|
||||
previous_model=self,
|
||||
relation_field=field,
|
||||
|
||||
@ -1,5 +1,4 @@
|
||||
import sys
|
||||
import uuid
|
||||
from typing import (
|
||||
AbstractSet,
|
||||
Any,
|
||||
@ -12,6 +11,7 @@ from typing import (
|
||||
Sequence,
|
||||
Set,
|
||||
TYPE_CHECKING,
|
||||
Tuple,
|
||||
Type,
|
||||
Union,
|
||||
cast,
|
||||
@ -86,6 +86,7 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
_choices_fields: Optional[Set]
|
||||
_pydantic_fields: Set
|
||||
_quick_access_fields: Set
|
||||
_json_fields: Set
|
||||
Meta: ModelMeta
|
||||
|
||||
# noinspection PyMissingConstructor
|
||||
@ -123,53 +124,12 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
:type kwargs: Any
|
||||
"""
|
||||
self._verify_model_can_be_initialized()
|
||||
object.__setattr__(self, "_orm_id", uuid.uuid4().hex)
|
||||
object.__setattr__(self, "_orm_saved", False)
|
||||
object.__setattr__(self, "_pk_column", None)
|
||||
object.__setattr__(
|
||||
self,
|
||||
"_orm",
|
||||
RelationsManager(
|
||||
related_fields=self.extract_related_fields(), owner=cast("Model", self),
|
||||
),
|
||||
)
|
||||
self._initialize_internal_attributes()
|
||||
|
||||
pk_only = kwargs.pop("__pk_only__", False)
|
||||
object.__setattr__(self, "__pk_only__", pk_only)
|
||||
|
||||
excluded: Set[str] = kwargs.pop("__excluded__", set())
|
||||
|
||||
if "pk" in kwargs:
|
||||
kwargs[self.Meta.pkname] = kwargs.pop("pk")
|
||||
|
||||
# build the models to set them and validate but don't register
|
||||
# also remove property fields values from validation
|
||||
try:
|
||||
new_kwargs: Dict[str, Any] = {
|
||||
k: self._convert_json(
|
||||
k,
|
||||
self.Meta.model_fields[k].expand_relationship(
|
||||
v, self, to_register=False,
|
||||
),
|
||||
"dumps",
|
||||
)
|
||||
for k, v in kwargs.items()
|
||||
if k not in object.__getattribute__(self, "Meta").property_fields
|
||||
}
|
||||
except KeyError as e:
|
||||
raise ModelError(
|
||||
f"Unknown field '{e.args[0]}' for model {self.get_name(lower=False)}"
|
||||
)
|
||||
|
||||
# explicitly set None to excluded fields
|
||||
# as pydantic populates them with default if set
|
||||
for field_to_nullify in excluded:
|
||||
new_kwargs[field_to_nullify] = None
|
||||
|
||||
# extract through fields
|
||||
through_tmp_dict = dict()
|
||||
for field_name in self.extract_through_names():
|
||||
through_tmp_dict[field_name] = new_kwargs.pop(field_name, None)
|
||||
new_kwargs, through_tmp_dict = self._process_kwargs(kwargs)
|
||||
|
||||
values, fields_set, validation_error = pydantic.validate_model(
|
||||
self, new_kwargs # type: ignore
|
||||
@ -182,10 +142,10 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
|
||||
# add back through fields
|
||||
new_kwargs.update(through_tmp_dict)
|
||||
|
||||
model_fields = object.__getattribute__(self, "Meta").model_fields
|
||||
# register the columns models after initialization
|
||||
for related in self.extract_related_names().union(self.extract_through_names()):
|
||||
self.Meta.model_fields[related].expand_relationship(
|
||||
model_fields[related].expand_relationship(
|
||||
new_kwargs.get(related), self, to_register=True,
|
||||
)
|
||||
|
||||
@ -243,7 +203,7 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
else:
|
||||
if name in object.__getattribute__(self, "_choices_fields"):
|
||||
validate_choices(field=self.Meta.model_fields[name], value=value)
|
||||
super().__setattr__(name, value)
|
||||
super().__setattr__(name, self._convert_json(name, value, op="dumps"))
|
||||
self.set_save_status(False)
|
||||
|
||||
def __getattribute__(self, item: str) -> Any: # noqa: CCR001
|
||||
@ -306,15 +266,89 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
:return: None
|
||||
:rtype: None
|
||||
"""
|
||||
if self.Meta.abstract:
|
||||
if object.__getattribute__(self, "Meta").abstract:
|
||||
raise ModelError(f"You cannot initialize abstract model {self.get_name()}")
|
||||
if self.Meta.requires_ref_update:
|
||||
if object.__getattribute__(self, "Meta").requires_ref_update:
|
||||
raise ModelError(
|
||||
f"Model {self.get_name()} has not updated "
|
||||
f"ForwardRefs. \nBefore using the model you "
|
||||
f"need to call update_forward_refs()."
|
||||
)
|
||||
|
||||
def _process_kwargs(self, kwargs: Dict) -> Tuple[Dict, Dict]:
|
||||
"""
|
||||
Initializes nested models.
|
||||
|
||||
Removes property_fields
|
||||
|
||||
Checks if field is in the model fields or pydatnic fields.
|
||||
|
||||
Nullifies fields that should be excluded.
|
||||
|
||||
Extracts through models from kwargs into temporary dict.
|
||||
|
||||
:param kwargs: passed to init keyword arguments
|
||||
:type kwargs: Dict
|
||||
:return: modified kwargs
|
||||
:rtype: Tuple[Dict, Dict]
|
||||
"""
|
||||
meta = object.__getattribute__(self, "Meta")
|
||||
property_fields = meta.property_fields
|
||||
model_fields = meta.model_fields
|
||||
pydantic_fields = object.__getattribute__(self, "__fields__")
|
||||
|
||||
# remove property fields
|
||||
for prop_filed in property_fields:
|
||||
kwargs.pop(prop_filed, None)
|
||||
|
||||
excluded: Set[str] = kwargs.pop("__excluded__", set())
|
||||
if "pk" in kwargs:
|
||||
kwargs[meta.pkname] = kwargs.pop("pk")
|
||||
|
||||
# extract through fields
|
||||
through_tmp_dict = dict()
|
||||
for field_name in self.extract_through_names():
|
||||
through_tmp_dict[field_name] = kwargs.pop(field_name, None)
|
||||
|
||||
try:
|
||||
new_kwargs: Dict[str, Any] = {
|
||||
k: self._convert_json(
|
||||
k,
|
||||
model_fields[k].expand_relationship(v, self, to_register=False,)
|
||||
if k in model_fields
|
||||
else (v if k in pydantic_fields else model_fields[k]),
|
||||
"dumps",
|
||||
)
|
||||
for k, v in kwargs.items()
|
||||
}
|
||||
except KeyError as e:
|
||||
raise ModelError(
|
||||
f"Unknown field '{e.args[0]}' for model {self.get_name(lower=False)}"
|
||||
)
|
||||
|
||||
# explicitly set None to excluded fields
|
||||
# as pydantic populates them with default if set
|
||||
for field_to_nullify in excluded:
|
||||
new_kwargs[field_to_nullify] = None
|
||||
|
||||
return new_kwargs, through_tmp_dict
|
||||
|
||||
def _initialize_internal_attributes(self) -> None:
|
||||
"""
|
||||
Initializes internal attributes during __init__()
|
||||
:rtype: None
|
||||
"""
|
||||
# object.__setattr__(self, "_orm_id", uuid.uuid4().hex)
|
||||
object.__setattr__(self, "_orm_saved", False)
|
||||
object.__setattr__(self, "_pk_column", None)
|
||||
object.__setattr__(
|
||||
self,
|
||||
"_orm",
|
||||
RelationsManager(
|
||||
related_fields=self.extract_related_fields(), owner=cast("Model", self),
|
||||
),
|
||||
)
|
||||
|
||||
def _extract_related_model_instead_of_field(
|
||||
self, item: str
|
||||
) -> Optional[Union["Model", Sequence["Model"]]]:
|
||||
@ -355,8 +389,8 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
:rtype: bool
|
||||
"""
|
||||
return (
|
||||
self._orm_id == other._orm_id
|
||||
or (self.pk == other.pk and self.pk is not None)
|
||||
# self._orm_id == other._orm_id
|
||||
(self.pk == other.pk and self.pk is not None)
|
||||
or (
|
||||
(self.pk is None and other.pk is None)
|
||||
and {
|
||||
@ -740,7 +774,7 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
:return: converted value if needed, else original value
|
||||
:rtype: Any
|
||||
"""
|
||||
if not self._is_conversion_to_json_needed(column_name):
|
||||
if column_name not in object.__getattribute__(self, "_json_fields"):
|
||||
return value
|
||||
|
||||
condition = (
|
||||
@ -757,20 +791,6 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
|
||||
pass
|
||||
return value.decode("utf-8") if isinstance(value, bytes) else value
|
||||
|
||||
def _is_conversion_to_json_needed(self, column_name: str) -> bool:
|
||||
"""
|
||||
Checks if given column name is related to JSON field.
|
||||
|
||||
:param column_name: name of the field
|
||||
:type column_name: str
|
||||
:return: result of the check
|
||||
:rtype: bool
|
||||
"""
|
||||
return (
|
||||
column_name in self.Meta.model_fields
|
||||
and self.Meta.model_fields[column_name].__type__ == pydantic.Json
|
||||
)
|
||||
|
||||
def _extract_own_model_fields(self) -> Dict:
|
||||
"""
|
||||
Returns a dictionary with field names and values for fields that are not
|
||||
|
||||
@ -1,6 +1,7 @@
|
||||
import datetime
|
||||
import decimal
|
||||
import uuid
|
||||
from base64 import b64encode
|
||||
from enum import Enum
|
||||
|
||||
import databases
|
||||
@ -22,6 +23,10 @@ uuid1 = uuid.uuid4()
|
||||
uuid2 = uuid.uuid4()
|
||||
|
||||
|
||||
blob = b"test"
|
||||
blob2 = b"test2icac89uc98"
|
||||
|
||||
|
||||
class EnumTest(Enum):
|
||||
val1 = "Val1"
|
||||
val2 = "Val2"
|
||||
@ -57,6 +62,7 @@ class Organisation(ormar.Model):
|
||||
random_json: pydantic.Json = ormar.JSON(choices=["aa", '{"aa":"bb"}'])
|
||||
random_uuid: uuid.UUID = ormar.UUID(choices=[uuid1, uuid2])
|
||||
enum_string: str = ormar.String(max_length=100, choices=list(EnumTest))
|
||||
blob_col: bytes = ormar.LargeBinary(max_length=100000, choices=[blob, blob2])
|
||||
|
||||
|
||||
@app.on_event("startup")
|
||||
@ -111,6 +117,7 @@ def test_all_endpoints():
|
||||
"random_json": '{"aa":"bb"}',
|
||||
"random_uuid": str(uuid1),
|
||||
"enum_string": EnumTest.val1.value,
|
||||
"blob_col": blob.decode("utf-8"),
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
@ -1,6 +1,8 @@
|
||||
from typing import List
|
||||
import datetime
|
||||
from typing import List, Optional
|
||||
|
||||
import databases
|
||||
import pydantic
|
||||
import pytest
|
||||
import sqlalchemy
|
||||
from fastapi import FastAPI
|
||||
@ -34,6 +36,17 @@ class LocalMeta:
|
||||
database = database
|
||||
|
||||
|
||||
class PTestA(pydantic.BaseModel):
|
||||
c: str
|
||||
d: bytes
|
||||
e: datetime.datetime
|
||||
|
||||
|
||||
class PTestP(pydantic.BaseModel):
|
||||
a: int
|
||||
b: Optional[PTestA]
|
||||
|
||||
|
||||
class Category(ormar.Model):
|
||||
class Meta(LocalMeta):
|
||||
tablename = "categories"
|
||||
@ -48,6 +61,8 @@ class Item(ormar.Model):
|
||||
|
||||
id: int = ormar.Integer(primary_key=True)
|
||||
name: str = ormar.String(max_length=100)
|
||||
pydantic_int: Optional[int]
|
||||
test_P: Optional[List[PTestP]]
|
||||
categories = ormar.ManyToMany(Category)
|
||||
|
||||
|
||||
@ -124,6 +139,29 @@ def test_schema_modification():
|
||||
x.get("type") == "array" for x in schema["properties"]["categories"]["anyOf"]
|
||||
)
|
||||
assert schema["properties"]["categories"]["title"] == "Categories"
|
||||
assert schema["example"] == {
|
||||
"categories": [{"id": 0, "name": "string"}],
|
||||
"id": 0,
|
||||
"name": "string",
|
||||
"pydantic_int": 0,
|
||||
"test_P": [{"a": 0, "b": {"c": "string", "d": "string", "e": "string"}}],
|
||||
}
|
||||
|
||||
schema = Category.schema()
|
||||
assert schema["example"] == {
|
||||
"id": 0,
|
||||
"name": "string",
|
||||
"items": [
|
||||
{
|
||||
"id": 0,
|
||||
"name": "string",
|
||||
"pydantic_int": 0,
|
||||
"test_P": [
|
||||
{"a": 0, "b": {"c": "string", "d": "string", "e": "string"}}
|
||||
],
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
def test_schema_gen():
|
||||
|
||||
@ -218,6 +218,19 @@ def test_decimal_error_in_model_definition():
|
||||
test: decimal.Decimal = ormar.Decimal(primary_key=True)
|
||||
|
||||
|
||||
@typing.no_type_check
|
||||
def test_binary_error_without_length_model_definition():
|
||||
with pytest.raises(ModelDefinitionError):
|
||||
|
||||
class ExampleModel2(Model):
|
||||
class Meta:
|
||||
tablename = "example6"
|
||||
database = database
|
||||
metadata = metadata
|
||||
|
||||
test: bytes = ormar.LargeBinary(primary_key=True)
|
||||
|
||||
|
||||
@typing.no_type_check
|
||||
def test_string_error_in_model_definition():
|
||||
with pytest.raises(ModelDefinitionError):
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
import asyncio
|
||||
import uuid
|
||||
import datetime
|
||||
import uuid
|
||||
from typing import List
|
||||
|
||||
import databases
|
||||
@ -9,7 +9,7 @@ import pytest
|
||||
import sqlalchemy
|
||||
|
||||
import ormar
|
||||
from ormar.exceptions import QueryDefinitionError, NoMatch, ModelError
|
||||
from ormar.exceptions import ModelError, NoMatch, QueryDefinitionError
|
||||
from tests.settings import DATABASE_URL
|
||||
|
||||
database = databases.Database(DATABASE_URL, force_rollback=True)
|
||||
@ -26,6 +26,20 @@ class JsonSample(ormar.Model):
|
||||
test_json = ormar.JSON(nullable=True)
|
||||
|
||||
|
||||
blob = b"test"
|
||||
blob2 = b"test2icac89uc98"
|
||||
|
||||
|
||||
class LargeBinarySample(ormar.Model):
|
||||
class Meta:
|
||||
tablename = "my_bolbs"
|
||||
metadata = metadata
|
||||
database = database
|
||||
|
||||
id: int = ormar.Integer(primary_key=True)
|
||||
test_binary = ormar.LargeBinary(max_length=100000, choices=[blob, blob2])
|
||||
|
||||
|
||||
class UUIDSample(ormar.Model):
|
||||
class Meta:
|
||||
tablename = "uuids"
|
||||
@ -102,15 +116,8 @@ class Country(ormar.Model):
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def event_loop():
|
||||
loop = asyncio.get_event_loop()
|
||||
yield loop
|
||||
loop.close()
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True, scope="module")
|
||||
async def create_test_database():
|
||||
def create_test_database():
|
||||
engine = sqlalchemy.create_engine(DATABASE_URL)
|
||||
metadata.drop_all(engine)
|
||||
metadata.create_all(engine)
|
||||
@ -151,6 +158,19 @@ async def test_json_column():
|
||||
assert items[1].test_json == dict(aa=12)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_binary_column():
|
||||
async with database:
|
||||
async with database.transaction(force_rollback=True):
|
||||
await LargeBinarySample.objects.create(test_binary=blob)
|
||||
await LargeBinarySample.objects.create(test_binary=blob2)
|
||||
|
||||
items = await LargeBinarySample.objects.all()
|
||||
assert len(items) == 2
|
||||
assert items[0].test_binary == blob
|
||||
assert items[1].test_binary == blob2
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_uuid_column():
|
||||
async with database:
|
||||
|
||||
@ -1,9 +1,10 @@
|
||||
import random
|
||||
from typing import Optional
|
||||
|
||||
import databases
|
||||
import pytest
|
||||
import sqlalchemy
|
||||
from pydantic import HttpUrl
|
||||
from pydantic import BaseModel, Field, HttpUrl, PaymentCardNumber
|
||||
|
||||
import ormar
|
||||
from tests.settings import DATABASE_URL
|
||||
@ -17,19 +18,58 @@ class BaseMeta(ormar.ModelMeta):
|
||||
database = database
|
||||
|
||||
|
||||
class Test(ormar.Model):
|
||||
class ModelTest(ormar.Model):
|
||||
class Meta(BaseMeta):
|
||||
pass
|
||||
|
||||
id: int = ormar.Integer(primary_key=True)
|
||||
name: str = ormar.String(max_length=200)
|
||||
url: HttpUrl = "https://www.example.com"
|
||||
number: Optional[PaymentCardNumber]
|
||||
|
||||
|
||||
CARD_NUMBERS = [
|
||||
"123456789007",
|
||||
"123456789015",
|
||||
"123456789023",
|
||||
"123456789031",
|
||||
"123456789049",
|
||||
]
|
||||
|
||||
|
||||
def get_number():
|
||||
return random.choice(CARD_NUMBERS)
|
||||
|
||||
|
||||
class ModelTest2(ormar.Model):
|
||||
class Meta(BaseMeta):
|
||||
pass
|
||||
|
||||
id: int = ormar.Integer(primary_key=True)
|
||||
name: str = ormar.String(max_length=200)
|
||||
url: HttpUrl = "https://www.example2.com"
|
||||
number: PaymentCardNumber = Field(default_factory=get_number)
|
||||
|
||||
|
||||
class PydanticTest(BaseModel):
|
||||
aa: str
|
||||
bb: int
|
||||
|
||||
|
||||
class ModelTest3(ormar.Model):
|
||||
class Meta(BaseMeta):
|
||||
pass
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
# you need to pop non - db fields as ormar will complain that it's unknown field
|
||||
url = kwargs.pop("url", self.__fields__["url"].get_default())
|
||||
kwargs["number"] = get_number()
|
||||
kwargs["pydantic_test"] = PydanticTest(aa="random", bb=42)
|
||||
super().__init__(**kwargs)
|
||||
self.url = url
|
||||
|
||||
id: int = ormar.Integer(primary_key=True)
|
||||
name: str = ormar.String(max_length=200)
|
||||
url: HttpUrl = "www.example.com" # field with default
|
||||
url: HttpUrl = "https://www.example3.com"
|
||||
number: PaymentCardNumber
|
||||
pydantic_test: PydanticTest
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True, scope="module")
|
||||
@ -44,18 +84,58 @@ def create_test_database():
|
||||
@pytest.mark.asyncio
|
||||
async def test_working_with_pydantic_fields():
|
||||
async with database:
|
||||
test = Test(name="Test")
|
||||
test = ModelTest(name="Test")
|
||||
assert test.name == "Test"
|
||||
assert test.url == "www.example.com"
|
||||
assert test.url == "https://www.example.com"
|
||||
assert test.number is None
|
||||
test.number = "123456789015"
|
||||
|
||||
test.url = "www.sdta.ada.pt"
|
||||
assert test.url == "www.sdta.ada.pt"
|
||||
test.url = "https://www.sdta.ada.pt"
|
||||
assert test.url == "https://www.sdta.ada.pt"
|
||||
|
||||
await test.save()
|
||||
test_check = await Test.objects.get()
|
||||
test_check = await ModelTest.objects.get()
|
||||
|
||||
assert test_check.name == "Test"
|
||||
assert test_check.url == "www.example.com"
|
||||
assert test_check.url == "https://www.example.com"
|
||||
assert test_check.number is None
|
||||
|
||||
# TODO add validate assignment to pydantic config
|
||||
# test_check.email = 1
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_default_factory_for_pydantic_fields():
|
||||
async with database:
|
||||
test = ModelTest2(name="Test2", number="4000000000000002")
|
||||
assert test.name == "Test2"
|
||||
assert test.url == "https://www.example2.com"
|
||||
assert test.number == "4000000000000002"
|
||||
|
||||
test.url = "http://www.sdta.ada.pt"
|
||||
assert test.url == "http://www.sdta.ada.pt"
|
||||
|
||||
await test.save()
|
||||
test_check = await ModelTest2.objects.get()
|
||||
|
||||
assert test_check.name == "Test2"
|
||||
assert test_check.url == "https://www.example2.com"
|
||||
assert test_check.number in CARD_NUMBERS
|
||||
assert test_check.number != test.number
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_init_setting_for_pydantic_fields():
|
||||
async with database:
|
||||
test = ModelTest3(name="Test3")
|
||||
assert test.name == "Test3"
|
||||
assert test.url == "https://www.example3.com"
|
||||
assert test.pydantic_test.bb == 42
|
||||
|
||||
test.url = "http://www.sdta.ada.pt"
|
||||
assert test.url == "http://www.sdta.ada.pt"
|
||||
|
||||
await test.save()
|
||||
test_check = await ModelTest3.objects.get()
|
||||
|
||||
assert test_check.name == "Test3"
|
||||
assert test_check.url == "https://www.example3.com"
|
||||
assert test_check.number in CARD_NUMBERS
|
||||
assert test_check.pydantic_test.aa == "random"
|
||||
|
||||
@ -57,7 +57,7 @@ def create_test_database():
|
||||
|
||||
|
||||
def assert_type(book: Book):
|
||||
print(book)
|
||||
_ = str(book)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
|
||||
Reference in New Issue
Block a user