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Merge pull request #195 from collerek/excludes_in_dict

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Excludes in dict
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collerek
2021-05-17 17:43:37 +02:00
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parent e564acbb45 b9a38be5c6
commit 2a84a8b93d
27 changed files with 1263 additions and 159 deletions
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17
README.md
View File

@ -35,6 +35,10 @@ Ormar - apart form obvious ORM in name - get it's name from ormar in swedish whi
And what's a better name for python ORM than snakes cabinet :)
**If you like ormar remember to star the repository in [github](https://github.com/collerek/ormar)!**
The bigger community we build, the easier it will be to catch bugs and attract contributors ;)
### Documentation
Check out the [documentation][documentation] for details.
@ -68,7 +72,16 @@ Ormar is built with:
* [`pydantic`][pydantic] for data validation.
* `typing_extensions` for python 3.6 - 3.7
### Migrating from `sqlalchemy`
### License
`ormar` is built as an open-sorce software and remain completely free (MIT license).
As I write open-source code to solve everyday problems in my work or to promote and build strong python
community you can say thank you and buy me a coffee or sponsor me with a monthly amount to help ensure my work remains free and maintained.
<iframe src="https://github.com/sponsors/collerek/button" title="Sponsor collerek" height="35" width="116" style="border: 0;"></iframe>
### Migrating from `sqlalchemy` and existing databases
If you currently use `sqlalchemy` and would like to switch to `ormar` check out the auto-translation
tool that can help you with translating existing sqlalchemy orm models so you do not have to do it manually.
@ -76,6 +89,8 @@ tool that can help you with translating existing sqlalchemy orm models so you do
**Beta** versions available at github: [`sqlalchemy-to-ormar`](https://github.com/collerek/sqlalchemy-to-ormar)
or simply `pip install sqlalchemy-to-ormar`
`sqlalchemy-to-ormar` can be used in pair with `sqlacodegen` to auto-map/ generate `ormar` models from existing database, even if you don't use the `sqlalchemy` for your project.
### Migrations & Database creation
Because ormar is built on SQLAlchemy core, you can use [`alembic`][alembic] to provide

29
docs/fields/field-types.md
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@ -138,6 +138,35 @@ LargeBinary length is used in some backend (i.e. mysql) to determine the size of
in other backends it's simply ignored yet in ormar it's always required. It should be max
size of the file/bytes in bytes.
`LargeBinary` has also optional `represent_as_base64_str: bool = False` flag.
When set to `True` `ormar` will auto-convert bytes value to base64 decoded string,
you can also set value by passing a base64 encoded string.
That way you can i.e. set the value by API, even if value is not `utf-8` compatible and would otherwise fail during json conversion.
```python
import base64
... # other imports skipped for brevity
class LargeBinaryStr(ormar.Model):
class Meta:
tablename = "my_str_blobs"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
test_binary: str = ormar.LargeBinary(
max_length=100000, represent_as_base64_str=True
)
# set non utf-8 compliant value - note this can be passed by api (i.e. fastapi) in json
item = LargeBinaryStr(test_binary=base64.b64encode(b"\xc3\x28").decode())
assert item.test_binary == base64.b64encode(b"\xc3\x28").decode()
# technical note that underlying value is still bytes and will be saved as so
assert item.__dict__["test_binary"] == b"\xc3\x28"
```
### UUID
`UUID(uuid_format: str = 'hex')` has no required parameters.

17
docs/index.md
View File

@ -35,6 +35,10 @@ Ormar - apart form obvious ORM in name - get it's name from ormar in swedish whi
And what's a better name for python ORM than snakes cabinet :)
**If you like ormar remember to star the repository in [github](https://github.com/collerek/ormar)!**
The bigger community we build, the easier it will be to catch bugs and attract contributors ;)
### Documentation
Check out the [documentation][documentation] for details.
@ -68,7 +72,16 @@ Ormar is built with:
* [`pydantic`][pydantic] for data validation.
* `typing_extensions` for python 3.6 - 3.7
### Migrating from `sqlalchemy`
### License
`ormar` is built as an open-sorce software and remain completely free (MIT license).
As I write open-source code to solve everyday problems in my work or to promote and build strong python
community you can say thank you and buy me a coffee or sponsor me with a monthly amount to help ensure my work remains free and maintained.
<iframe src="https://github.com/sponsors/collerek/button" title="Sponsor collerek" height="35" width="116" style="border: 0;"></iframe>
### Migrating from `sqlalchemy` and existing databases
If you currently use `sqlalchemy` and would like to switch to `ormar` check out the auto-translation
tool that can help you with translating existing sqlalchemy orm models so you do not have to do it manually.
@ -76,6 +89,8 @@ tool that can help you with translating existing sqlalchemy orm models so you do
**Beta** versions available at github: [`sqlalchemy-to-ormar`](https://github.com/collerek/sqlalchemy-to-ormar)
or simply `pip install sqlalchemy-to-ormar`
`sqlalchemy-to-ormar` can be used in pair with `sqlacodegen` to auto-map/ generate `ormar` models from existing database, even if you don't use the `sqlalchemy` for your project.
### Migrations & Database creation
Because ormar is built on SQLAlchemy core, you can use [`alembic`][alembic] to provide

267
docs/models/methods.md
View File

@ -17,6 +17,273 @@ especially `dict()` and `json()` methods that can also accept `exclude`, `includ
To read more check [pydantic][pydantic] documentation
## dict
`dict` is a method inherited from `pydantic`, yet `ormar` adds its own parameters and has some nuances when working with default values,
therefore it's listed here for clarity.
`dict` as the name suggests export data from model tree to dictionary.
Explanation of dict parameters:
### include (`ormar` modifed)
`include: Union[Set, Dict] = None`
Set or dictionary of field names to include in returned dictionary.
Note that `pydantic` has an uncommon pattern of including/ excluding fields in lists (so also nested models) by an index.
And if you want to exclude the field in all children you need to pass a `__all__` key to dictionary.
You cannot exclude nested models in `Set`s in `pydantic` but you can in `ormar`
(by adding double underscore on relation name i.e. to exclude name of category for a book you cen use `exclude={"book__category__name"}`)
`ormar` does not support by index exclusion/ inclusions and accepts a simplified and more user-friendly notation.
To check how you can include/exclude fields, including nested fields check out [fields](../queries/select-columns.md#fields) section that has an explanation and a lot of samples.
!!!note
The fact that in `ormar` you can exclude nested models in sets, you can exclude from a whole model tree in `response_model_exclude` and `response_model_include` in fastapi!
### exclude (`ormar` modified)
`exclude: Union[Set, Dict] = None`
Set or dictionary of field names to exclude in returned dictionary.
Note that `pydantic` has an uncommon pattern of including/ excluding fields in lists (so also nested models) by an index.
And if you want to exclude the field in all children you need to pass a `__all__` key to dictionary.
You cannot exclude nested models in `Set`s in `pydantic` but you can in `ormar`
(by adding double underscore on relation name i.e. to exclude name of category for a book you cen use `exclude={"book__category__name"}`)
`ormar` does not support by index exclusion/ inclusions and accepts a simplified and more user-friendly notation.
To check how you can include/exclude fields, including nested fields check out [fields](../queries/select-columns.md#fields) section that has an explanation and a lot of samples.
!!!note
The fact that in `ormar` you can exclude nested models in sets, you can exclude from a whole model tree in `response_model_exclude` and `response_model_include` in fastapi!
### exclude_unset
`exclude_unset: bool = False`
Flag indicates whether fields which were not explicitly set when creating the model should be excluded from the returned dictionary.
!!!warning
Note that after you save data into database each field has its own value -> either provided by you, default, or `None`.
That means that when you load the data from database, **all** fields are set, and this flag basically stop working!
```python
class Category(ormar.Model):
class Meta:
tablename = "categories"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100, default="Test")
visibility: bool = ormar.Boolean(default=True)
class Item(ormar.Model):
class Meta:
tablename = "items"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
price: float = ormar.Float(default=9.99)
categories: List[Category] = ormar.ManyToMany(Category)
category = Category(name="Test 2")
assert category.dict() == {'id': None, 'items': [], 'name': 'Test 2',
'visibility': True}
assert category.dict(exclude_unset=True) == {'items': [], 'name': 'Test 2'}
await category.save()
category2 = await Category.objects.get()
assert category2.dict() == {'id': 1, 'items': [], 'name': 'Test 2',
'visibility': True}
# NOTE how after loading from db all fields are set explicitly
# as this is what happens when you populate a model from db
assert category2.dict(exclude_unset=True) == {'id': 1, 'items': [],
'name': 'Test 2', 'visibility': True}
```
### exclude_defaults
`exclude_defaults: bool = False`
Flag indicates are equal to their default values (whether set or otherwise) should be excluded from the returned dictionary
```python
class Category(ormar.Model):
class Meta:
tablename = "categories"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100, default="Test")
visibility: bool = ormar.Boolean(default=True)
class Item(ormar.Model):
class Meta:
tablename = "items"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
price: float = ormar.Float(default=9.99)
categories: List[Category] = ormar.ManyToMany(Category)
category = Category()
# note that Integer pk is by default autoincrement so optional
assert category.dict() == {'id': None, 'items': [], 'name': 'Test', 'visibility': True}
assert category.dict(exclude_defaults=True) == {'items': []}
# save and reload the data
await category.save()
category2 = await Category.objects.get()
assert category2.dict() == {'id': 1, 'items': [], 'name': 'Test', 'visibility': True}
assert category2.dict(exclude_defaults=True) == {'id': 1, 'items': []}
```
### exclude_none
`exclude_none: bool = False`
Flag indicates whether fields which are equal to `None` should be excluded from the returned dictionary.
```python
class Category(ormar.Model):
class Meta:
tablename = "categories"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100, default="Test", nullable=True)
visibility: bool = ormar.Boolean(default=True)
class Item(ormar.Model):
class Meta:
tablename = "items"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
price: float = ormar.Float(default=9.99)
categories: List[Category] = ormar.ManyToMany(Category)
category = Category(name=None)
assert category.dict() == {'id': None, 'items': [], 'name': None,
'visibility': True}
# note the id is not set yet so None and excluded
assert category.dict(exclude_none=True) == {'items': [], 'visibility': True}
await category.save()
category2 = await Category.objects.get()
assert category2.dict() == {'id': 1, 'items': [], 'name': None,
'visibility': True}
assert category2.dict(exclude_none=True) == {'id': 1, 'items': [],
'visibility': True}
```
### exclude_primary_keys (`ormar` only)
`exclude_primary_keys: bool = False`
Setting flag to `True` will exclude all primary key columns in a tree, including nested models.
```python
class Item(ormar.Model):
class Meta:
tablename = "items"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
item1 = Item(id=1, name="Test Item")
assert item1.dict() == {"id": 1, "name": "Test Item"}
assert item1.dict(exclude_primary_keys=True) == {"name": "Test Item"}
```
### exclude_through_models (`ormar` only)
`exclude_through_models: bool = False`
`Through` models are auto added for every `ManyToMany` relation, and they hold additional parameters on linking model/table.
Setting the `exclude_through_models=True` will exclude all through models, including Through models of submodels.
```python
class Category(ormar.Model):
class Meta:
tablename = "categories"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
class Item(ormar.Model):
class Meta:
tablename = "items"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
categories: List[Category] = ormar.ManyToMany(Category)
# tree defining the models
item_dict = {
"name": "test",
"categories": [{"name": "test cat"}, {"name": "test cat2"}],
}
# save whole tree
await Item(**item_dict).save_related(follow=True, save_all=True)
# get the saved values
item = await Item.objects.select_related("categories").get()
# by default you can see the through models (itemcategory)
assert item.dict() == {'id': 1, 'name': 'test',
'categories': [
{'id': 1, 'name': 'test cat',
'itemcategory': {'id': 1, 'category': None, 'item': None}},
{'id': 2, 'name': 'test cat2',
'itemcategory': {'id': 2, 'category': None, 'item': None}}
]}
# you can exclude those fields/ models
assert item.dict(exclude_through_models=True) == {
'id': 1, 'name': 'test',
'categories': [
{'id': 1, 'name': 'test cat'},
{'id': 2, 'name': 'test cat2'}
]}
```
## json
`json()` has exactly the same parameters as `dict()` so check above.
Of course the end result is a string with json representation and not a dictionary.
## load
By default when you query a table without prefetching related models, the ormar will still construct

20
docs/releases.md
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@ -1,3 +1,23 @@
# 0.10.7
## ✨ Features
* Add `exclude_primary_keys: bool = False` flag to `dict()` method that allows to exclude all primary key columns in the resulting dictionaru. [#164](https://github.com/collerek/ormar/issues/164)
* Add `exclude_through_models: bool = False` flag to `dict()` that allows excluding all through models from `ManyToMany` relations [#164](https://github.com/collerek/ormar/issues/164)
* Add `represent_as_base64_str: bool = False` parameter that allows conversion of bytes `LargeBinary` field to base64 encoded string. String is returned in `dict()`,
on access to attribute and string is converted to bytes on setting. Data in database is stored as bytes. [#187](https://github.com/collerek/ormar/issues/187)
* Add `pk` alias to allow field access by `Model.pk` in filters and order by clauses (python style)
## 🐛 Fixes
* Remove default `None` option for `max_length` for `LargeBinary` field [#186](https://github.com/collerek/ormar/issues/186)
* Remove default `None` option for `max_length` for `String` field
## 💬 Other
* Provide a guide and samples of `dict()` parameters in the [docs](https://collerek.github.io/ormar/models/methods/)
* Major refactor of getting/setting attributes from magic methods into descriptors -> noticeable performance improvement
# 0.10.6
## ✨ Features

2
ormar/__init__.py
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@ -76,7 +76,7 @@ class UndefinedType: # pragma no cover
Undefined = UndefinedType()
__version__ = "0.10.6"
__version__ = "0.10.7"
__all__ = [
"Integer",
"BigInteger",

4
ormar/fields/base.py
View File

@ -95,6 +95,10 @@ class BaseField(FieldInfo):
self.ormar_default: Any = kwargs.pop("default", None)
self.server_default: Any = kwargs.pop("server_default", None)
self.represent_as_base64_str: bool = kwargs.pop(
"represent_as_base64_str", False
)
for name, value in kwargs.items():
setattr(self, name, value)

8
ormar/fields/model_fields.py
View File

@ -136,10 +136,10 @@ class String(ModelFieldFactory, str):
def __new__( # type: ignore # noqa CFQ002
cls,
*,
max_length: int,
allow_blank: bool = True,
strip_whitespace: bool = False,
min_length: int = None,
max_length: int = None,
curtail_length: int = None,
regex: str = None,
**kwargs: Any
@ -176,7 +176,7 @@ class String(ModelFieldFactory, str):
:type kwargs: Any
"""
max_length = kwargs.get("max_length", None)
if max_length is None or max_length <= 0:
if max_length <= 0:
raise ModelDefinitionError(
"Parameter max_length is required for field String"
)
@ -435,7 +435,7 @@ class LargeBinary(ModelFieldFactory, bytes):
_sample = "bytes"
def __new__( # type: ignore # noqa CFQ002
cls, *, max_length: int = None, **kwargs: Any
cls, *, max_length: int, represent_as_base64_str: bool = False, **kwargs: Any
) -> BaseField: # type: ignore
kwargs = {
**kwargs,
@ -468,7 +468,7 @@ class LargeBinary(ModelFieldFactory, bytes):
:type kwargs: Any
"""
max_length = kwargs.get("max_length", None)
if max_length is None or max_length <= 0:
if max_length <= 0:
raise ModelDefinitionError(
"Parameter max_length is required for field LargeBinary"
)

17
ormar/models/descriptors/__init__.py Normal file
View File

@ -0,0 +1,17 @@
from ormar.models.descriptors.descriptors import (
BytesDescriptor,
JsonDescriptor,
PkDescriptor,
PropertyDescriptor,
PydanticDescriptor,
RelationDescriptor,
)
__all__ = [
"PydanticDescriptor",
"RelationDescriptor",
"PropertyDescriptor",
"PkDescriptor",
"JsonDescriptor",
"BytesDescriptor",
]

143
ormar/models/descriptors/descriptors.py Normal file
View File

@ -0,0 +1,143 @@
import base64
from typing import Any, TYPE_CHECKING, Type
try:
import orjson as json
except ImportError: # pragma: no cover
import json # type: ignore
if TYPE_CHECKING: # pragma: no cover
from ormar import Model
class PydanticDescriptor:
"""
Pydantic descriptor simply delegates everything to pydantic model
"""
def __init__(self, name: str) -> None:
self.name = name
def __get__(self, instance: "Model", owner: Type["Model"]) -> Any:
value = instance.__dict__.get(self.name, None)
return value
def __set__(self, instance: "Model", value: Any) -> None:
instance._internal_set(self.name, value)
instance.set_save_status(False)
class JsonDescriptor:
"""
Json descriptor dumps/loads strings to actual data on write/read
"""
def __init__(self, name: str) -> None:
self.name = name
def __get__(self, instance: "Model", owner: Type["Model"]) -> Any:
value = instance.__dict__.get(self.name, None)
return value
def __set__(self, instance: "Model", value: Any) -> None:
if not isinstance(value, str):
value = json.dumps(value)
value = value.decode("utf-8") if isinstance(value, bytes) else value
instance._internal_set(self.name, value)
instance.set_save_status(False)
class BytesDescriptor:
"""
Bytes descriptor converts strings to bytes on write and converts bytes to str
if represent_as_base64_str flag is set, so the value can be dumped to json
"""
def __init__(self, name: str) -> None:
self.name = name
def __get__(self, instance: "Model", owner: Type["Model"]) -> Any:
value = instance.__dict__.get(self.name, None)
field = instance.Meta.model_fields[self.name]
if field.represent_as_base64_str and not isinstance(value, str):
value = base64.b64encode(value).decode()
return value
def __set__(self, instance: "Model", value: Any) -> None:
field = instance.Meta.model_fields[self.name]
if isinstance(value, str):
if field.represent_as_base64_str:
value = base64.b64decode(value)
else:
value = value.encode("utf-8")
instance._internal_set(self.name, value)
instance.set_save_status(False)
class PkDescriptor:
"""
As of now it's basically a copy of PydanticDescriptor but that will
change in the future with multi column primary keys
"""
def __init__(self, name: str) -> None:
self.name = name
def __get__(self, instance: "Model", owner: Type["Model"]) -> Any:
value = instance.__dict__.get(self.name, None)
return value
def __set__(self, instance: "Model", value: Any) -> None:
instance._internal_set(self.name, value)
instance.set_save_status(False)
class RelationDescriptor:
"""
Relation descriptor expands the relation to initialize the related model
before setting it to __dict__. Note that expanding also registers the
related model in RelationManager.
"""
def __init__(self, name: str) -> None:
self.name = name
def __get__(self, instance: "Model", owner: Type["Model"]) -> Any:
if self.name in instance._orm:
return instance._orm.get(self.name) # type: ignore
return None # pragma no cover
def __set__(self, instance: "Model", value: Any) -> None:
model = instance.Meta.model_fields[self.name].expand_relationship(
value=value, child=instance
)
if isinstance(instance.__dict__.get(self.name), list):
# virtual foreign key or many to many
# TODO: Fix double items in dict, no effect on real action just ugly repr
instance.__dict__[self.name].append(model)
else:
# foreign key relation
instance.__dict__[self.name] = model
instance.set_save_status(False)
class PropertyDescriptor:
"""
Property descriptor handles methods decorated with @property_field decorator.
They are read only.
"""
def __init__(self, name: str, function: Any) -> None:
self.name = name
self.function = function
def __get__(self, instance: "Model", owner: Type["Model"]) -> Any:
if instance is None:
return self
if instance is not None and self.function is not None:
bound = self.function.__get__(instance, instance.__class__)
return bound() if callable(bound) else bound
def __set__(self, instance: "Model", value: Any) -> None: # pragma: no cover
# kept here so it's a data-descriptor and precedes __dict__ lookup
pass

5
ormar/models/helpers/models.py
View File

@ -67,6 +67,11 @@ def populate_default_options_values(
for name, field in new_model.Meta.model_fields.items()
if field.__type__ == pydantic.Json
}
new_model._bytes_fields = {
name
for name, field in new_model.Meta.model_fields.items()
if field.__type__ == bytes
}
class Connection(sqlite3.Connection):

5
ormar/models/helpers/relations.py
View File

@ -3,6 +3,7 @@ from typing import TYPE_CHECKING, Type, cast
import ormar
from ormar import ForeignKey, ManyToMany
from ormar.fields import Through
from ormar.models.descriptors import RelationDescriptor
from ormar.models.helpers.sqlalchemy import adjust_through_many_to_many_model
from ormar.relations import AliasManager
@ -130,6 +131,8 @@ def register_reverse_model_fields(model_field: "ForeignKeyField") -> None:
orders_by=model_field.related_orders_by,
skip_field=model_field.skip_reverse,
)
if not model_field.skip_reverse:
setattr(model_field.to, related_name, RelationDescriptor(name=related_name))
def register_through_shortcut_fields(model_field: "ManyToManyField") -> None:
@ -160,6 +163,8 @@ def register_through_shortcut_fields(model_field: "ManyToManyField") -> None:
owner=model_field.to,
nullable=True,
)
setattr(model_field.owner, through_name, RelationDescriptor(name=through_name))
setattr(model_field.to, through_name, RelationDescriptor(name=through_name))
def register_relation_in_alias_manager(field: "ForeignKeyField") -> None:

5
ormar/models/helpers/sqlalchemy.py
View File

@ -4,6 +4,7 @@ from typing import Dict, List, Optional, TYPE_CHECKING, Tuple, Type, Union
import sqlalchemy
import ormar # noqa: I100, I202
from ormar.models.descriptors import RelationDescriptor
from ormar.models.helpers.pydantic import create_pydantic_field
from ormar.models.helpers.related_names_validation import (
validate_related_names_in_relations,
@ -33,6 +34,7 @@ def adjust_through_many_to_many_model(model_field: "ManyToManyField") -> None:
ondelete="CASCADE",
owner=model_field.through,
)
model_fields[child_name] = ormar.ForeignKey( # type: ignore
model_field.owner,
real_name=child_name,
@ -50,6 +52,9 @@ def adjust_through_many_to_many_model(model_field: "ManyToManyField") -> None:
create_pydantic_field(parent_name, model_field.to, model_field)
create_pydantic_field(child_name, model_field.owner, model_field)
setattr(model_field.through, parent_name, RelationDescriptor(name=parent_name))
setattr(model_field.through, child_name, RelationDescriptor(name=child_name))
def create_and_append_m2m_fk(
model: Type["Model"], model_field: "ManyToManyField", field_name: str

4
ormar/models/helpers/validation.py
View File

@ -1,3 +1,4 @@
import base64
import datetime
import decimal
import numbers
@ -77,6 +78,9 @@ def convert_choices_if_needed( # noqa: CCR001
)
choices = [round(float(o), precision) for o in choices]
elif field.__type__ == bytes:
if field.represent_as_base64_str:
value = value if isinstance(value, bytes) else base64.b64decode(value)
else:
value = value if isinstance(value, bytes) else value.encode("utf-8")
return value, choices

58
ormar/models/metaclass.py
View File

@ -22,6 +22,14 @@ from ormar.exceptions import ModelError
from ormar.fields import BaseField
from ormar.fields.foreign_key import ForeignKeyField
from ormar.fields.many_to_many import ManyToManyField
from ormar.models.descriptors import (
JsonDescriptor,
PkDescriptor,
PropertyDescriptor,
PydanticDescriptor,
RelationDescriptor,
)
from ormar.models.descriptors.descriptors import BytesDescriptor
from ormar.models.helpers import (
alias_manager,
check_required_meta_parameters,
@ -95,6 +103,7 @@ def add_cached_properties(new_model: Type["Model"]) -> None:
new_model._pydantic_fields = {name for name in new_model.__fields__}
new_model._choices_fields = set()
new_model._json_fields = set()
new_model._bytes_fields = set()
def add_property_fields(new_model: Type["Model"], attrs: Dict) -> None: # noqa: CCR001
@ -477,6 +486,31 @@ def update_attrs_and_fields(
return updated_model_fields
def add_field_descriptor(
name: str, field: "BaseField", new_model: Type["Model"]
) -> None:
"""
Sets appropriate descriptor for each model field.
There are 5 main types of descriptors, for bytes, json, pure pydantic fields,
and 2 ormar ones - one for relation and one for pk shortcut
:param name: name of the field
:type name: str
:param field: model field to add descriptor for
:type field: BaseField
:param new_model: model with fields
:type new_model: Type["Model]
"""
if field.is_relation:
setattr(new_model, name, RelationDescriptor(name=name))
elif field.__type__ == pydantic.Json:
setattr(new_model, name, JsonDescriptor(name=name))
elif field.__type__ == bytes:
setattr(new_model, name, BytesDescriptor(name=name))
else:
setattr(new_model, name, PydanticDescriptor(name=name))
class ModelMetaclass(pydantic.main.ModelMetaclass):
def __new__( # type: ignore # noqa: CCR001
mcs: "ModelMetaclass", name: str, bases: Any, attrs: dict
@ -539,8 +573,9 @@ class ModelMetaclass(pydantic.main.ModelMetaclass):
populate_meta_sqlalchemy_table_if_required(new_model.Meta)
expand_reverse_relationships(new_model)
# TODO: iterate only related fields
for field in new_model.Meta.model_fields.values():
for name, field in new_model.Meta.model_fields.items():
register_relation_in_alias_manager(field=field)
add_field_descriptor(name=name, field=field, new_model=new_model)
if new_model.Meta.pkname not in attrs["__annotations__"]:
field_name = new_model.Meta.pkname
@ -551,6 +586,16 @@ class ModelMetaclass(pydantic.main.ModelMetaclass):
)
new_model.Meta.alias_manager = alias_manager
for item in new_model.Meta.property_fields:
function = getattr(new_model, item)
setattr(
new_model,
item,
PropertyDescriptor(name=item, function=function),
)
new_model.pk = PkDescriptor(name=new_model.Meta.pkname)
return new_model
@property
@ -564,6 +609,17 @@ class ModelMetaclass(pydantic.main.ModelMetaclass):
return QuerySet(model_cls=cls)
def __getattr__(self, item: str) -> Any:
"""
Returns FieldAccessors on access to model fields from a class,
that way it can be used in python style filters and order_by.
:param item: name of the field
:type item: str
:return: FieldAccessor for given field
:rtype: FieldAccessor
"""
if item == "pk":
item = self.Meta.pkname
if item in object.__getattribute__(self, "Meta").model_fields:
field = self.Meta.model_fields.get(item)
if field.is_relation:

22
ormar/models/mixins/excludable_mixin.py
View File

@ -151,7 +151,7 @@ class ExcludableMixin(RelationMixin):
:return: set or dict with excluded fields added.
:rtype: Union[Set, Dict]
"""
exclude = exclude or {}
exclude = exclude or set()
related_set = cls.extract_related_names()
if isinstance(exclude, set):
exclude = {s for s in exclude}
@ -162,6 +162,26 @@ class ExcludableMixin(RelationMixin):
exclude = exclude.union(related_set)
return exclude
@classmethod
def _update_excluded_with_pks_and_through(
cls, exclude: Set, exclude_primary_keys: bool, exclude_through_models: bool
) -> Set:
"""
Updates excluded names with name of pk column if exclude flag is set.
:param exclude: set of names to exclude
:type exclude: Set
:param exclude_primary_keys: flag if the primary keys should be excluded
:type exclude_primary_keys: bool
:return: set updated with pk if flag is set
:rtype: Set
"""
if exclude_primary_keys:
exclude.add(cls.Meta.pkname)
if exclude_through_models:
exclude = exclude.union(cls.extract_through_names())
return exclude
@classmethod
def get_names_to_exclude(cls, excludable: ExcludableItems, alias: str) -> Set:
"""

282
ormar/models/newbasemodel.py
View File

@ -1,4 +1,6 @@
import base64
import sys
import warnings
from typing import (
AbstractSet,
Any,
@ -8,7 +10,6 @@ from typing import (
Mapping,
MutableSequence,
Optional,
Sequence,
Set,
TYPE_CHECKING,
Tuple,
@ -37,7 +38,6 @@ from ormar.models.helpers.sqlalchemy import (
populate_meta_sqlalchemy_table_if_required,
update_column_definition,
)
from ormar.models.helpers.validation import validate_choices
from ormar.models.metaclass import ModelMeta, ModelMetaclass
from ormar.models.modelproxy import ModelTableProxy
from ormar.queryset.utils import translate_list_to_dict
@ -87,6 +87,7 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
_pydantic_fields: Set
_quick_access_fields: Set
_json_fields: Set
_bytes_fields: Set
Meta: ModelMeta
# noinspection PyMissingConstructor
@ -155,23 +156,7 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
def __setattr__(self, name: str, value: Any) -> None: # noqa CCR001
"""
Overwrites setattr in object to allow for special behaviour of certain params.
Parameter "pk" is translated into actual primary key field name.
Relations are expanded (child model constructed if needed) and registered on
both ends of the relation. The related models are handled by RelationshipManager
exposed at _orm param.
Json fields converted if needed.
Setting pk, foreign key value or any other field value sets Model save status
to False. Setting a reverse relation or many to many relation does not as it
does not modify the state of the model (but related model or through model).
To short circuit all checks and expansions the set of attribute names present
on each model is gathered into _quick_access_fields that is looked first and
if field is in this set the object setattr is called directly.
Overwrites setattr in pydantic parent as otherwise descriptors are not called.
:param name: name of the attribute to set
:type name: str
@ -180,84 +165,35 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
:return: None
:rtype: None
"""
if name in object.__getattribute__(self, "_quick_access_fields"):
if hasattr(self, name):
object.__setattr__(self, name, value)
elif name == "pk":
object.__setattr__(self, self.Meta.pkname, value)
self.set_save_status(False)
elif name in object.__getattribute__(self, "_orm"):
model = (
object.__getattribute__(self, "Meta")
.model_fields[name]
.expand_relationship(value=value, child=self)
)
if isinstance(object.__getattribute__(self, "__dict__").get(name), list):
# virtual foreign key or many to many
# TODO: Fix double items in dict, no effect on real action ugly repr
# if model.pk not in [x.pk for x in related_list]:
object.__getattribute__(self, "__dict__")[name].append(model)
else:
# foreign key relation
object.__getattribute__(self, "__dict__")[name] = model
self.set_save_status(False)
else:
if name in object.__getattribute__(self, "_choices_fields"):
validate_choices(field=self.Meta.model_fields[name], value=value)
super().__setattr__(name, self._convert_json(name, value, op="dumps"))
self.set_save_status(False)
# let pydantic handle errors for unknown fields
super().__setattr__(name, value)
def __getattribute__(self, item: str) -> Any: # noqa: CCR001
def __getattr__(self, item: str) -> Any:
"""
Because we need to overwrite getting the attribute by ormar instead of pydantic
as well as returning related models and not the value stored on the model the
__getattribute__ needs to be used not __getattr__.
Used only to silence mypy errors for Through models and reverse relations.
Not used in real life as in practice calls are intercepted
by RelationDescriptors
It's used to access all attributes so it can be a big overhead that's why a
number of short circuits is used.
To short circuit all checks and expansions the set of attribute names present
on each model is gathered into _quick_access_fields that is looked first and
if field is in this set the object setattr is called directly.
To avoid recursion object's getattribute is used to actually get the attribute
value from the model after the checks.
Even the function calls are constructed with objects functions.
Parameter "pk" is translated into actual primary key field name.
Relations are returned so the actual related model is returned and not current
model's field. The related models are handled by RelationshipManager exposed
at _orm param.
Json fields are converted if needed.
:param item: name of the attribute to retrieve
:param item: name of attribute
:type item: str
:return: value of the attribute
:return: Any
:rtype: Any
"""
if item in object.__getattribute__(self, "_quick_access_fields"):
return object.__getattribute__(self, item)
if item == "pk":
return object.__getattribute__(self, "__dict__").get(self.Meta.pkname, None)
if item in object.__getattribute__(self, "extract_related_names")():
return object.__getattribute__(
self, "_extract_related_model_instead_of_field"
)(item)
if item in object.__getattribute__(self, "extract_through_names")():
return object.__getattribute__(
self, "_extract_related_model_instead_of_field"
)(item)
if item in object.__getattribute__(self, "Meta").property_fields:
value = object.__getattribute__(self, item)
return value() if callable(value) else value
if item in object.__getattribute__(self, "_pydantic_fields"):
value = object.__getattribute__(self, "__dict__").get(item, None)
value = object.__getattribute__(self, "_convert_json")(item, value, "loads")
return value
return super().__getattribute__(item)
return object.__getattribute__(self, item) # pragma: no cover
def _internal_set(self, name: str, value: Any) -> None:
"""
Delegates call to pydantic.
:param name: name of param
:type name: str
:param value: value to set
:type value: Any
"""
super().__setattr__(name, value)
def _verify_model_can_be_initialized(self) -> None:
"""
@ -266,9 +202,9 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
:return: None
:rtype: None
"""
if object.__getattribute__(self, "Meta").abstract:
if self.Meta.abstract:
raise ModelError(f"You cannot initialize abstract model {self.get_name()}")
if object.__getattribute__(self, "Meta").requires_ref_update:
if self.Meta.requires_ref_update:
raise ModelError(
f"Model {self.get_name()} has not updated "
f"ForwardRefs. \nBefore using the model you "
@ -292,10 +228,9 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
: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__")
property_fields = self.Meta.property_fields
model_fields = self.Meta.model_fields
pydantic_fields = set(self.__fields__.keys())
# remove property fields
for prop_filed in property_fields:
@ -303,7 +238,7 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
excluded: Set[str] = kwargs.pop("__excluded__", set())
if "pk" in kwargs:
kwargs[meta.pkname] = kwargs.pop("pk")
kwargs[self.Meta.pkname] = kwargs.pop("pk")
# extract through fields
through_tmp_dict = dict()
@ -312,12 +247,14 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
try:
new_kwargs: Dict[str, Any] = {
k: self._convert_json(
k: self._convert_to_bytes(
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()
}
@ -349,21 +286,6 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
),
)
def _extract_related_model_instead_of_field(
self, item: str
) -> Optional[Union["Model", Sequence["Model"]]]:
"""
Retrieves the related model/models from RelationshipManager.
:param item: name of the relation
:type item: str
:return: related model, list of related models or None
:rtype: Optional[Union[Model, List[Model]]]
"""
if item in self._orm:
return self._orm.get(item) # type: ignore
return None # pragma no cover
def __eq__(self, other: object) -> bool:
"""
Compares other model to this model. when == is called.
@ -562,6 +484,8 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
models: MutableSequence,
include: Union[Set, Dict, None],
exclude: Union[Set, Dict, None],
exclude_primary_keys: bool,
exclude_through_models: bool,
) -> List:
"""
Converts list of models into list of dictionaries.
@ -580,7 +504,11 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
try:
result.append(
model.dict(
relation_map=relation_map, include=include, exclude=exclude,
relation_map=relation_map,
include=include,
exclude=exclude,
exclude_primary_keys=exclude_primary_keys,
exclude_through_models=exclude_through_models,
)
)
except ReferenceError: # pragma no cover
@ -623,6 +551,8 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
dict_instance: Dict,
include: Optional[Dict],
exclude: Optional[Dict],
exclude_primary_keys: bool,
exclude_through_models: bool,
) -> Dict:
"""
Traverse nested models and converts them into dictionaries.
@ -655,6 +585,8 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
models=nested_model,
include=self._convert_all(self._skip_ellipsis(include, field)),
exclude=self._convert_all(self._skip_ellipsis(exclude, field)),
exclude_primary_keys=exclude_primary_keys,
exclude_through_models=exclude_through_models,
)
elif nested_model is not None:
@ -664,6 +596,8 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
),
include=self._convert_all(self._skip_ellipsis(include, field)),
exclude=self._convert_all(self._skip_ellipsis(exclude, field)),
exclude_primary_keys=exclude_primary_keys,
exclude_through_models=exclude_through_models,
)
else:
dict_instance[field] = None
@ -681,6 +615,8 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
exclude_primary_keys: bool = False,
exclude_through_models: bool = False,
relation_map: Dict = None,
) -> "DictStrAny": # noqa: A003'
"""
@ -692,6 +628,10 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
Additionally fields decorated with @property_field are also added.
:param exclude_through_models: flag to exclude through models from dict
:type exclude_through_models: bool
:param exclude_primary_keys: flag to exclude primary keys from dict
:type exclude_primary_keys: bool
:param include: fields to include
:type include: Union[Set, Dict, None]
:param exclude: fields to exclude
@ -711,9 +651,15 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
:return:
:rtype:
"""
pydantic_exclude = self._update_excluded_with_related(exclude)
pydantic_exclude = self._update_excluded_with_pks_and_through(
exclude=pydantic_exclude,
exclude_primary_keys=exclude_primary_keys,
exclude_through_models=exclude_through_models,
)
dict_instance = super().dict(
include=include,
exclude=self._update_excluded_with_related(exclude),
exclude=pydantic_exclude,
by_alias=by_alias,
skip_defaults=skip_defaults,
exclude_unset=exclude_unset,
@ -721,6 +667,11 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
exclude_none=exclude_none,
)
dict_instance = {
k: self._convert_bytes_to_str(column_name=k, value=v)
for k, v in dict_instance.items()
}
if include and isinstance(include, Set):
include = translate_list_to_dict(include)
if exclude and isinstance(exclude, Set):
@ -738,6 +689,8 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
dict_instance=dict_instance,
include=include, # type: ignore
exclude=exclude, # type: ignore
exclude_primary_keys=exclude_primary_keys,
exclude_through_models=exclude_through_models,
)
# include model properties as fields in dict
@ -748,6 +701,50 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
return dict_instance
def json( # type: ignore # noqa A003
self,
*,
include: Union[Set, Dict] = None,
exclude: Union[Set, Dict] = None,
by_alias: bool = False,
skip_defaults: bool = None,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
encoder: Optional[Callable[[Any], Any]] = None,
exclude_primary_keys: bool = False,
exclude_through_models: bool = False,
**dumps_kwargs: Any,
) -> str:
"""
Generate a JSON representation of the model, `include` and `exclude`
arguments as per `dict()`.
`encoder` is an optional function to supply as `default` to json.dumps(),
other arguments as per `json.dumps()`.
"""
if skip_defaults is not None: # pragma: no cover
warnings.warn(
f'{self.__class__.__name__}.json(): "skip_defaults" is deprecated '
f'and replaced by "exclude_unset"',
DeprecationWarning,
)
exclude_unset = skip_defaults
encoder = cast(Callable[[Any], Any], encoder or self.__json_encoder__)
data = self.dict(
include=include,
exclude=exclude,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
exclude_primary_keys=exclude_primary_keys,
exclude_through_models=exclude_through_models,
)
if self.__custom_root_type__: # pragma: no cover
data = data["__root__"]
return self.__config__.json_dumps(data, default=encoder, **dumps_kwargs)
def update_from_dict(self, value_dict: Dict) -> "NewBaseModel":
"""
Updates self with values of fields passed in the dictionary.
@ -761,7 +758,46 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
setattr(self, key, value)
return self
def _convert_json(self, column_name: str, value: Any, op: str) -> Union[str, Dict]:
def _convert_to_bytes(self, column_name: str, value: Any) -> Union[str, Dict]:
"""
Converts value to bytes from string
:param column_name: name of the field
:type column_name: str
:param value: value fo the field
:type value: Any
:return: converted value if needed, else original value
:rtype: Any
"""
if column_name not in self._bytes_fields:
return value
field = self.Meta.model_fields[column_name]
if not isinstance(value, bytes):
if field.represent_as_base64_str:
value = base64.b64decode(value)
else:
value = value.encode("utf-8")
return value
def _convert_bytes_to_str(self, column_name: str, value: Any) -> Union[str, Dict]:
"""
Converts value to str from bytes for represent_as_base64_str columns.
:param column_name: name of the field
:type column_name: str
:param value: value fo the field
:type value: Any
:return: converted value if needed, else original value
:rtype: Any
"""
if column_name not in self._bytes_fields:
return value
field = self.Meta.model_fields[column_name]
if not isinstance(value, str) and field.represent_as_base64_str:
return base64.b64encode(value).decode()
return value
def _convert_json(self, column_name: str, value: Any) -> Union[str, Dict]:
"""
Converts value to/from json if needed (for Json columns).
@ -769,24 +805,14 @@ class NewBaseModel(pydantic.BaseModel, ModelTableProxy, metaclass=ModelMetaclass
:type column_name: str
:param value: value fo the field
:type value: Any
:param op: operator on json
:type op: str
:return: converted value if needed, else original value
:rtype: Any
"""
if column_name not in object.__getattribute__(self, "_json_fields"):
if column_name not in self._json_fields:
return value
condition = (
isinstance(value, str) if op == "loads" else not isinstance(value, str)
)
operand: Callable[[Any], Any] = (
json.loads if op == "loads" else json.dumps # type: ignore
)
if condition:
if not isinstance(value, str):
try:
value = operand(value)
value = json.dumps(value)
except TypeError: # pragma no cover
pass
return value.decode("utf-8") if isinstance(value, bytes) else value

12
ormar/relations/querysetproxy.py
View File

@ -282,6 +282,9 @@ class QuerysetProxy(Generic[T]):
Actual call delegated to QuerySet.
Passing args and/or kwargs is a shortcut and equals to calling
`filter(*args, **kwargs).first()`.
List of related models is cleared before the call.
:param kwargs:
@ -300,7 +303,8 @@ class QuerysetProxy(Generic[T]):
If no criteria set it will return the last row in db sorted by pk.
Passing a criteria is actually calling filter(**kwargs) method described below.
Passing args and/or kwargs is a shortcut and equals to calling
`filter(*args, **kwargs).get_or_none()`.
If not match is found None will be returned.
@ -324,7 +328,8 @@ class QuerysetProxy(Generic[T]):
If no criteria set it will return the last row in db sorted by pk.
Passing a criteria is actually calling filter(**kwargs) method described below.
Passing args and/or kwargs is a shortcut and equals to calling
`filter(*args, **kwargs).get()`.
Actual call delegated to QuerySet.
@ -346,7 +351,8 @@ class QuerysetProxy(Generic[T]):
"""
Returns all rows from a database for given model for set filter options.
Passing kwargs is a shortcut and equals to calling `filter(**kwrags).all()`.
Passing args and/or kwargs is a shortcut and equals to calling
`filter(*args, **kwargs).all()`.
If there are no rows meeting the criteria an empty list is returned.

5
pydoc-markdown.yml
View File

@ -76,6 +76,11 @@ renderer:
- title: Save Prepare Mixin
contents:
- models.mixins.save_mixin.*
- title: Descriptors
children:
- title: descriptors
contents:
- models.descriptors.descriptors.*
- title: Fields
children:
- title: Base Field

68
tests/test_exclude_include_dict/test_dumping_model_to_dict.py
View File

@ -1,4 +1,4 @@
from typing import Optional
from typing import List, Optional
import databases
import pytest
@ -11,16 +11,28 @@ metadata = sqlalchemy.MetaData()
database = databases.Database(DATABASE_URL, force_rollback=True)
class User(ormar.Model):
class Meta:
tablename: str = "users"
class MainMeta(ormar.ModelMeta):
metadata = metadata
database = database
class Role(ormar.Model):
class Meta(MainMeta):
pass
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=255, nullable=False)
class User(ormar.Model):
class Meta(MainMeta):
tablename: str = "users"
id: int = ormar.Integer(primary_key=True)
email: str = ormar.String(max_length=255, nullable=False)
password: str = ormar.String(max_length=255, nullable=True)
first_name: str = ormar.String(max_length=255, nullable=False)
roles: List[Role] = ormar.ManyToMany(Role)
class Tier(ormar.Model):
@ -58,12 +70,20 @@ class Item(ormar.Model):
@pytest.fixture(autouse=True, scope="module")
def sample_data():
user = User(email="test@test.com", password="ijacids7^*&", first_name="Anna")
tier = Tier(name="Tier I")
category1 = Category(name="Toys", tier=tier)
category2 = Category(name="Weapons", tier=tier)
item1 = Item(name="Teddy Bear", category=category1, created_by=user)
item2 = Item(name="M16", category=category2, created_by=user)
role = Role(name="User", id=1)
role2 = Role(name="Admin", id=2)
user = User(
id=1,
email="test@test.com",
password="ijacids7^*&",
first_name="Anna",
roles=[role, role2],
)
tier = Tier(id=1, name="Tier I")
category1 = Category(id=1, name="Toys", tier=tier)
category2 = Category(id=2, name="Weapons", tier=tier)
item1 = Item(id=1, name="Teddy Bear", category=category1, created_by=user)
item2 = Item(id=2, name="M16", category=category2, created_by=user)
return item1, item2
@ -139,4 +159,30 @@ def test_dumping_to_dict_exclude_and_include_nested_dict(sample_data):
assert dict2["category"]["name"] == "Toys"
assert "created_by" not in dict1
assert dict1["category"]["tier"].get("name") is None
assert dict1["category"]["tier"]["id"] is None
assert dict1["category"]["tier"]["id"] == 1
def test_dumping_dict_without_primary_keys(sample_data):
item1, item2 = sample_data
dict1 = item2.dict(exclude_primary_keys=True)
assert dict1 == {
"category": {"name": "Weapons", "tier": {"name": "Tier I"}},
"created_by": {
"email": "test@test.com",
"first_name": "Anna",
"password": "ijacids7^*&",
"roles": [{"name": "User"}, {"name": "Admin"}],
},
"name": "M16",
}
dict2 = item1.dict(exclude_primary_keys=True)
assert dict2 == {
"category": {"name": "Toys", "tier": {"name": "Tier I"}},
"created_by": {
"email": "test@test.com",
"first_name": "Anna",
"password": "ijacids7^*&",
"roles": [{"name": "User"}, {"name": "Admin"}],
},
"name": "Teddy Bear",
}

135
tests/test_exclude_include_dict/test_pydantic_dict_params.py Normal file
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@ -0,0 +1,135 @@
from typing import List
import databases
import pytest
import sqlalchemy
import ormar
from tests.settings import DATABASE_URL
metadata = sqlalchemy.MetaData()
database = databases.Database(DATABASE_URL, force_rollback=True)
class Category(ormar.Model):
class Meta:
tablename = "categories"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100, default="Test", nullable=True)
visibility: bool = ormar.Boolean(default=True)
class Item(ormar.Model):
class Meta:
tablename = "items"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
price: float = ormar.Float(default=9.99)
categories: List[Category] = ormar.ManyToMany(Category)
@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.mark.asyncio
async def test_exclude_default():
async with database:
category = Category()
assert category.dict() == {
"id": None,
"items": [],
"name": "Test",
"visibility": True,
}
assert category.dict(exclude_defaults=True) == {"items": []}
await category.save()
category2 = await Category.objects.get()
assert category2.dict() == {
"id": 1,
"items": [],
"name": "Test",
"visibility": True,
}
assert category2.dict(exclude_defaults=True) == {"id": 1, "items": []}
assert category2.json(exclude_defaults=True) == '{"id": 1, "items": []}'
@pytest.mark.asyncio
async def test_exclude_none():
async with database:
category = Category(id=2, name=None)
assert category.dict() == {
"id": 2,
"items": [],
"name": None,
"visibility": True,
}
assert category.dict(exclude_none=True) == {
"id": 2,
"items": [],
"visibility": True,
}
await category.save()
category2 = await Category.objects.get()
assert category2.dict() == {
"id": 2,
"items": [],
"name": None,
"visibility": True,
}
assert category2.dict(exclude_none=True) == {
"id": 2,
"items": [],
"visibility": True,
}
assert (
category2.json(exclude_none=True)
== '{"id": 2, "visibility": true, "items": []}'
)
@pytest.mark.asyncio
async def test_exclude_unset():
async with database:
category = Category(id=3, name="Test 2")
assert category.dict() == {
"id": 3,
"items": [],
"name": "Test 2",
"visibility": True,
}
assert category.dict(exclude_unset=True) == {
"id": 3,
"items": [],
"name": "Test 2",
}
await category.save()
category2 = await Category.objects.get()
assert category2.dict() == {
"id": 3,
"items": [],
"name": "Test 2",
"visibility": True,
}
# NOTE how after loading from db all fields are set explicitly
# as this is what happens when you populate a model from db
assert category2.dict(exclude_unset=True) == {
"id": 3,
"items": [],
"name": "Test 2",
"visibility": True,
}

91
tests/test_fastapi/test_binary_fields.py Normal file
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@ -0,0 +1,91 @@
import base64
import json
import os
import uuid
from typing import List
import databases
import pydantic
import pytest
import sqlalchemy
from fastapi import FastAPI
from starlette.testclient import TestClient
import ormar
from tests.settings import DATABASE_URL
app = FastAPI()
database = databases.Database(DATABASE_URL, force_rollback=True)
metadata = sqlalchemy.MetaData()
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()
blob3 = b"\xc3\x28"
blob4 = b"\xf0\x28\x8c\x28"
blob5 = b"\xee"
blob6 = b"\xff"
class BaseMeta(ormar.ModelMeta):
metadata = metadata
database = database
class BinaryThing(ormar.Model):
class Meta(BaseMeta):
tablename = "things"
id: uuid.UUID = ormar.UUID(primary_key=True, default=uuid.uuid4)
name: str = ormar.Text(default="")
bt: bytes = ormar.LargeBinary(
max_length=1000,
choices=[blob3, blob4, blob5, blob6],
represent_as_base64_str=True,
)
@app.get("/things", response_model=List[BinaryThing])
async def read_things():
return await BinaryThing.objects.order_by("name").all()
@app.post("/things", response_model=BinaryThing)
async def create_things(thing: BinaryThing):
thing = await thing.save()
return thing
@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)
def test_read_main():
client = TestClient(app)
with client as client:
response = client.post(
"/things", data=json.dumps({"bt": base64.b64encode(blob3).decode()})
)
assert response.status_code == 200
response = client.get("/things")
assert response.json()[0]["bt"] == base64.b64encode(blob3).decode()
thing = BinaryThing(**response.json()[0])
assert thing.__dict__["bt"] == blob3

149
tests/test_fastapi/test_excluding_fields.py Normal file
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@ -0,0 +1,149 @@
from typing import List
import databases
import pytest
import sqlalchemy
from fastapi import FastAPI
from starlette.testclient import TestClient
import ormar
from tests.settings import DATABASE_URL
app = FastAPI()
metadata = sqlalchemy.MetaData()
database = databases.Database(DATABASE_URL, force_rollback=True)
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 Category(ormar.Model):
class Meta:
tablename = "categories"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
class Item(ormar.Model):
class Meta:
tablename = "items"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
categories: List[Category] = ormar.ManyToMany(Category)
@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)
@app.post("/items/", response_model=Item)
async def create_item(item: Item):
await item.save_related(follow=True, save_all=True)
return item
@app.get("/items/{item_id}")
async def get_item(item_id: int):
item = await Item.objects.select_related("categories").get(pk=item_id)
return item.dict(exclude_primary_keys=True, exclude_through_models=True)
@app.get("/categories/{category_id}")
async def get_category(category_id: int):
category = await Category.objects.select_related("items").get(pk=category_id)
return category.dict(exclude_primary_keys=True)
@app.get("/categories/nt/{category_id}")
async def get_category_no_through(category_id: int):
category = await Category.objects.select_related("items").get(pk=category_id)
return category.dict(exclude_through_models=True)
@app.get("/categories/ntp/{category_id}")
async def get_category_no_pk_through(category_id: int):
category = await Category.objects.select_related("items").get(pk=category_id)
return category.dict(exclude_through_models=True, exclude_primary_keys=True)
@app.get(
"/items/fex/{item_id}",
response_model=Item,
response_model_exclude={
"id",
"categories__id",
"categories__itemcategory",
"categories__items",
},
)
async def get_item_excl(item_id: int):
item = await Item.objects.select_all().get(pk=item_id)
return item
def test_all_endpoints():
client = TestClient(app)
with client as client:
item = {
"name": "test",
"categories": [{"name": "test cat"}, {"name": "test cat2"}],
}
response = client.post("/items/", json=item)
item_check = Item(**response.json())
assert item_check.id is not None
assert item_check.categories[0].id is not None
no_pk_item = client.get(f"/items/{item_check.id}", json=item).json()
assert no_pk_item == item
no_pk_item2 = client.get(f"/items/fex/{item_check.id}", json=item).json()
assert no_pk_item2 == item
no_pk_category = client.get(
f"/categories/{item_check.categories[0].id}", json=item
).json()
assert no_pk_category == {
"items": [
{
"itemcategory": {"category": None, "id": 1, "item": None},
"name": "test",
}
],
"name": "test cat",
}
no_through_category = client.get(
f"/categories/nt/{item_check.categories[0].id}", json=item
).json()
assert no_through_category == {
"id": 1,
"items": [{"id": 1, "name": "test"}],
"name": "test cat",
}
no_through_category = client.get(
f"/categories/ntp/{item_check.categories[0].id}", json=item
).json()
assert no_through_category == {"items": [{"name": "test"}], "name": "test cat"}

1
tests/test_model_definition/test_fields_access.py
View File

@ -55,6 +55,7 @@ def test_fields_access():
# basic access
assert Product.id._field == Product.Meta.model_fields["id"]
assert Product.id.id == Product.Meta.model_fields["id"]
assert Product.pk.id == Product.id.id
assert isinstance(Product.id._field, BaseField)
assert Product.id._access_chain == "id"
assert Product.id._source_model == Product

4
tests/test_model_definition/test_model_definition.py
View File

@ -228,7 +228,7 @@ def test_binary_error_without_length_model_definition():
database = database
metadata = metadata
test: bytes = ormar.LargeBinary(primary_key=True)
test: bytes = ormar.LargeBinary(primary_key=True, max_length=-1)
@typing.no_type_check
@ -241,7 +241,7 @@ def test_string_error_in_model_definition():
database = database
metadata = metadata
test: str = ormar.String(primary_key=True)
test: str = ormar.String(primary_key=True, max_length=0)
@typing.no_type_check

42
tests/test_model_definition/test_models.py
View File

@ -1,5 +1,7 @@
import asyncio
import base64
import datetime
import os
import uuid
from typing import List
@ -37,7 +39,23 @@ class LargeBinarySample(ormar.Model):
database = database
id: int = ormar.Integer(primary_key=True)
test_binary = ormar.LargeBinary(max_length=100000, choices=[blob, blob2])
test_binary: bytes = ormar.LargeBinary(max_length=100000, choices=[blob, blob2])
blob3 = os.urandom(64)
blob4 = os.urandom(100)
class LargeBinaryStr(ormar.Model):
class Meta:
tablename = "my_str_blobs"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
test_binary: str = ormar.LargeBinary(
max_length=100000, choices=[blob3, blob4], represent_as_base64_str=True
)
class UUIDSample(ormar.Model):
@ -157,6 +175,9 @@ async def test_json_column():
assert items[0].test_json == dict(aa=12)
assert items[1].test_json == dict(aa=12)
items[0].test_json = "[1, 2, 3]"
assert items[0].test_json == [1, 2, 3]
@pytest.mark.asyncio
async def test_binary_column():
@ -170,6 +191,25 @@ async def test_binary_column():
assert items[0].test_binary == blob
assert items[1].test_binary == blob2
items[0].test_binary = "test2icac89uc98"
assert items[0].test_binary == b"test2icac89uc98"
@pytest.mark.asyncio
async def test_binary_str_column():
async with database:
async with database.transaction(force_rollback=True):
await LargeBinaryStr.objects.create(test_binary=blob3)
await LargeBinaryStr.objects.create(test_binary=blob4)
items = await LargeBinaryStr.objects.all()
assert len(items) == 2
assert items[0].test_binary == base64.b64encode(blob3).decode()
items[0].test_binary = base64.b64encode(blob4).decode()
assert items[0].test_binary == base64.b64encode(blob4).decode()
assert items[1].test_binary == base64.b64encode(blob4).decode()
assert items[1].__dict__["test_binary"] == blob4
@pytest.mark.asyncio
async def test_uuid_column():