Merge pull request #203 from collerek/check_defaults

Bug fixes

docs/releases.md

@@ -1,3 +1,12 @@
+# 0.10.8
+
+## 🐛 Fixes
+
+* Fix populating default values in pk_only child models [#202](https://github.com/collerek/ormar/issues/202)
+* Fix mypy for LargeBinary fields with base64 str representation [#199](https://github.com/collerek/ormar/issues/199)
+* Fix OpenAPI schema format for LargeBinary fields with base64 str representation [#199](https://github.com/collerek/ormar/issues/199)
+* Fix OpenAPI choices encoding for LargeBinary fields with base64 str representation
+
 # 0.10.7
 
 ## ✨ Features

ormar/__init__.py

@@ -76,7 +76,7 @@ class UndefinedType:  # pragma no cover
 
 Undefined = UndefinedType()
 
-__version__ = "0.10.7"
+__version__ = "0.10.8"
 __all__ = [
     "Integer",
     "BigInteger",

ormar/fields/model_fields.py

@@ -1,7 +1,7 @@
 import datetime
 import decimal
 import uuid
-from typing import Any, Optional, TYPE_CHECKING
+from typing import Any, Optional, TYPE_CHECKING, Union, overload
 
 import pydantic
 import sqlalchemy
@@ -11,6 +11,11 @@ from ormar.fields import sqlalchemy_uuid
 from ormar.fields.base import BaseField  # noqa I101
 from ormar.fields.sqlalchemy_encrypted import EncryptBackends
 
+try:
+    from typing import Literal
+except ImportError:  # pragma: no cover
+    from typing_extensions import Literal  # type: ignore
+
 
 def is_field_nullable(
     nullable: Optional[bool],
@@ -426,16 +431,49 @@ class JSON(ModelFieldFactory, pydantic.Json):
         return sqlalchemy.JSON()
 
 
-class LargeBinary(ModelFieldFactory, bytes):
+if TYPE_CHECKING:  # pragma: nocover # noqa: C901
+
+    @overload
+    def LargeBinary(
+        max_length: int, *, represent_as_base64_str: Literal[True], **kwargs: Any
+    ) -> str:
+        ...
+
+    @overload
+    def LargeBinary(
+        max_length: int, *, represent_as_base64_str: Literal[False], **kwargs: Any
+    ) -> bytes:
+        ...
+
+    @overload
+    def LargeBinary(
+        max_length: int, represent_as_base64_str: Literal[False] = ..., **kwargs: Any
+    ) -> bytes:
+        ...
+
+    def LargeBinary(
+        max_length: int, represent_as_base64_str: bool = False, **kwargs: Any
+    ) -> Union[str, bytes]:
+        pass
+
+
+else:
+
+    class LargeBinary(ModelFieldFactory, bytes):
         """
-    LargeBinary field factory that construct Field classes and populated their values.
+        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, represent_as_base64_str: bool = False, **kwargs: Any
+            cls,
+            *,
+            max_length: int,
+            represent_as_base64_str: bool = False,
+            **kwargs: Any
         ) -> BaseField:  # type: ignore
             kwargs = {
                 **kwargs,

ormar/models/helpers/validation.py

@@ -142,7 +142,8 @@ def generate_model_example(model: Type["Model"], relation_map: Dict = None) -> D
     )
     for name, field in model.Meta.model_fields.items():
         if not field.is_relation:
-            example[name] = field.__sample__
+            is_bytes_str = field.__type__ == bytes and field.represent_as_base64_str
+            example[name] = field.__sample__ if not is_bytes_str else "string"
         elif isinstance(relation_map, dict) and name in relation_map:
             example[name] = get_nested_model_example(
                 name=name, field=field, relation_map=relation_map
@@ -217,6 +218,44 @@ def get_pydantic_example_repr(type_: Any) -> Any:
         return "string"
 
 
+def overwrite_example_and_description(
+    schema: Dict[str, Any], model: Type["Model"]
+) -> None:
+    """
+    Overwrites the example with properly nested children models.
+    Overwrites the description if it's taken from ormar.Model.
+
+    :param schema: schema of current model
+    :type schema: Dict[str, Any]
+    :param model: model class
+    :type model: Type["Model"]
+    """
+    schema["example"] = generate_model_example(model=model)
+    if "Main base class of ormar Model." in schema.get("description", ""):
+        schema["description"] = f"{model.__name__}"
+
+
+def overwrite_binary_format(schema: Dict[str, Any], model: Type["Model"]) -> None:
+    """
+    Overwrites format of the field if it's a LargeBinary field with
+    a flag to represent the field as base64 encoded string.
+
+    :param schema: schema of current model
+    :type schema: Dict[str, Any]
+    :param model: model class
+    :type model: Type["Model"]
+    """
+    for field_id, prop in schema.get("properties", {}).items():
+        if (
+            field_id in model._bytes_fields
+            and model.Meta.model_fields[field_id].represent_as_base64_str
+        ):
+            prop["format"] = "base64"
+            prop["enum"] = [
+                base64.b64encode(choice).decode() for choice in prop["enum"]
+            ]
+
+
 def construct_modify_schema_function(fields_with_choices: List) -> SchemaExtraCallable:
     """
     Modifies the schema to include fields with choices validator.
@@ -237,9 +276,8 @@ 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__}"
+        overwrite_example_and_description(schema=schema, model=model)
+        overwrite_binary_format(schema=schema, model=model)
 
     return staticmethod(schema_extra)  # type: ignore
 
@@ -256,9 +294,8 @@ def construct_schema_function_without_choices() -> SchemaExtraCallable:
     """
 
     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__}"
+        overwrite_example_and_description(schema=schema, model=model)
+        overwrite_binary_format(schema=schema, model=model)
 
     return staticmethod(schema_extra)  # type: ignore
 

ormar/models/newbasemodel.py

@@ -132,11 +132,15 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
 
         new_kwargs, through_tmp_dict = self._process_kwargs(kwargs)
 
+        if not pk_only:
             values, fields_set, validation_error = pydantic.validate_model(
                 self, new_kwargs  # type: ignore
             )
-        if validation_error and not pk_only:
+            if validation_error:
                 raise validation_error
+        else:
+            fields_set = {self.Meta.pkname}
+            values = new_kwargs
 
         object.__setattr__(self, "__dict__", values)
         object.__setattr__(self, "__fields_set__", fields_set)

tests/test_fastapi/test_binary_fields.py

@@ -52,7 +52,7 @@ class BinaryThing(ormar.Model):
 
     id: uuid.UUID = ormar.UUID(primary_key=True, default=uuid.uuid4)
     name: str = ormar.Text(default="")
-    bt: bytes = ormar.LargeBinary(
+    bt: str = ormar.LargeBinary(
         max_length=1000,
         choices=[blob3, blob4, blob5, blob6],
         represent_as_base64_str=True,
@@ -89,3 +89,14 @@ def test_read_main():
         assert response.json()[0]["bt"] == base64.b64encode(blob3).decode()
         thing = BinaryThing(**response.json()[0])
         assert thing.__dict__["bt"] == blob3
+
+
+def test_schema():
+    schema = BinaryThing.schema()
+    assert schema["properties"]["bt"]["format"] == "base64"
+    converted_choices = ["7g==", "/w==", "8CiMKA==", "wyg="]
+    assert len(schema["properties"]["bt"]["enum"]) == 4
+    assert all(
+        choice in schema["properties"]["bt"]["enum"] for choice in converted_choices
+    )
+    assert schema["example"]["bt"] == "string"

tests/test_fastapi/test_relations_with_nested_defaults.py

@@ -0,0 +1,121 @@
+from typing import Optional
+
+import databases
+import pytest
+import sqlalchemy
+from fastapi import FastAPI
+from starlette.testclient import TestClient
+
+import ormar
+from tests.settings import DATABASE_URL
+
+database = databases.Database(DATABASE_URL)
+metadata = sqlalchemy.MetaData()
+
+app = FastAPI()
+app.state.database = database
+
+
+@app.on_event("startup")
+async def startup() -> None:
+    database_ = app.state.database
+    if not database_.is_connected:
+        await database_.connect()
+
+
+@app.on_event("shutdown")
+async def shutdown() -> None:
+    database_ = app.state.database
+    if database_.is_connected:
+        await database_.disconnect()
+
+
+class BaseMeta(ormar.ModelMeta):
+    metadata = metadata
+    database = database
+
+
+class Country(ormar.Model):
+    class Meta(BaseMeta):
+        tablename = "countries"
+
+    id: int = ormar.Integer(primary_key=True)
+    name: str = ormar.String(max_length=100, default="Poland")
+
+
+class Author(ormar.Model):
+    class Meta(BaseMeta):
+        tablename = "authors"
+
+    id: int = ormar.Integer(primary_key=True)
+    name: str = ormar.String(max_length=100)
+    rating: int = ormar.Integer(default=0)
+    country: Optional[Country] = ormar.ForeignKey(Country)
+
+
+class Book(ormar.Model):
+    class Meta(BaseMeta):
+        tablename = "books"
+
+    id: int = ormar.Integer(primary_key=True)
+    author: Optional[Author] = ormar.ForeignKey(Author)
+    title: str = ormar.String(max_length=100)
+    year: int = ormar.Integer(nullable=True)
+
+
+@pytest.fixture(autouse=True, scope="module")
+def create_test_database():
+    engine = sqlalchemy.create_engine(DATABASE_URL)
+    metadata.create_all(engine)
+    yield
+    metadata.drop_all(engine)
+
+
+@pytest.fixture()
+async def sample_data():
+    async with database:
+        country = await Country(id=1, name="USA").save()
+        author = await Author(id=1, name="bug", rating=5, country=country).save()
+        await Book(
+            id=1, author=author, title="Bug caused by default value", year=2021
+        ).save()
+
+
+@app.get("/books/{book_id}", response_model=Book)
+async def get_book_by_id(book_id: int):
+    book = await Book.objects.get(id=book_id)
+    return book
+
+
+@app.get("/books_with_author/{book_id}", response_model=Book)
+async def get_book_with_author_by_id(book_id: int):
+    book = await Book.objects.select_related("author").get(id=book_id)
+    return book
+
+
+def test_related_with_defaults(sample_data):
+    client = TestClient(app)
+    with client as client:
+        response = client.get("/books/1")
+        assert response.json() == {
+            "author": {"id": 1},
+            "id": 1,
+            "title": "Bug caused by default value",
+            "year": 2021,
+        }
+
+        response = client.get("/books_with_author/1")
+        assert response.json() == {
+            "author": {
+                "books": [
+                    {"id": 1, "title": "Bug caused by default value", "year": 2021}
+                ],
+                "country": {"id": 1},
+                "id": 1,
+                "name": "bug",
+                "rating": 5,
+            },
+            "id": 1,
+            "title": "Bug caused by default value",
+            "year": 2021,
+        }