Prodream/ormar
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

WIP - Pydantic v2 support (#1238)

Browse Source 
* WIP

* WIP - make test_model_definition tests pass

* WIP - make test_model_methods pass

* WIP - make whole test suit at least run - failing 49/443 tests

* WIP fix part of the getting pydantic tests as types of fields are now kept in core schema and not on fieldsinfo

* WIP fix validation in update by creating individual fields validators, failing 36/443

* WIP fix __pydantic_extra__ in intializing model, fix test related to pydantic config checks, failing 32/442

* WIP - fix enum schema in model_json_schema, failing 31/442

* WIP - fix copying through model, fix setting pydantic fields on through, fix default config and inheriting from it, failing 26/442

* WIP fix tests checking pydantic schema, fix excluding parent fields, failing 21/442

* WIP some missed files

* WIP - fix validators inheritance and fix validators in generated pydantic, failing 17/442

* WIP - fix through models setting - only on reverse side of relation, but always on reverse side, failing 15/442

* WIP - fix through models setting - only on reverse side of relation, but always on reverse side, failing 15/442

* WIP - working on proper populating __dict__ for relations for new schema dumping, some work on openapi docs, failing 13/442

* WIP - remove property fields as pydantic has now computed_field on its own, failing 9/442

* WIP - fixes in docs, failing 8/442

* WIP - fix tests for largebinary schema, wrapped bytes fields fail in pydantic, will be fixed in pydantic-core, remaining is circural schema for related models, failing 6/442

* WIP - fix to pk only models in schemas

* Getting test suites to pass (#1249)

* wip, fixing tests

* iteration, fixing some more tests

* iteration, fixing some more tests

* adhere to comments

* adhere to comments

* remove unnecessary dict call, re-add getattribute for testing

* todo for reverse relationship

* adhere to comments, remove prints

* solve circular refs

* all tests pass 🎉

* remove 3.7 from tests

* add lint and type check jobs

* reforat with ruff, fix jobs

* rename jobs

* fix imports

* fix evaluate in py3.8

* partially fix coverage

* fix coverage, add more tests

* fix test ids

* fix test ids

* fix lint, fix docs, make docs fully working scripts, add test docs job

* fix pyproject

* pin py ver in test docs

* change dir in test docs

* fix pydantic warning hack

* rm poetry call in test_docs

* switch to pathlib in test docs

* remove coverage req test docs

* fix type check tests, fix part of types

* fix/skip next part of types

* fix next part of types

* fix next part of types

* fix coverage

* fix coverage

* fix type (bit dirty 🤷)

* fix some code smells

* change pre-commit

* tweak workflows

* remove no root from tests

* switch to full python path by passing sys.executable

* some small refactor in new base model, one sample test, change makefile

* small refactors to reduce complexity of methods

* temp add tests for prs against pydantic_v2

* remove all references to __fields__

* remove all references to construct, deprecate the method and update model_construct to be in line with pydantic

* deprecate dict and add model_dump, todo switch to model_dict in calls

* fix tests

* change to union

* change to union

* change to model_dump and model_dump_json from dict and json deprecated methods, deprecate them in ormar too

* finish switching dict() -> model_dump()

* finish switching json() -> model_dump_json()

* remove fully pydantic_only

* switch to extra for payment card, change missed json calls

* fix coverage - no more warnings internal

* fix coverage - no more warnings internal - part 2

* split model_construct into own and pydantic parts

* split determine pydantic field type

* change to new field validators

* fix benchmarks, add codspeed instead of pytest-benchmark, add action and gh workflow

* restore pytest-benchmark

* remove codspeed

* pin pydantic version, restore codspeed

* change on push to pydantic_v2 to trigger first one

* Use lifespan function instead of event (#1259)

* check return types

* fix imports order, set warnings=False on json that passes the dict, fix unnecessary loop in one of the test

* remove references to model's meta as it's now ormar config, rename related methods too

* filter out pydantic serializer warnings

* remove choices leftovers

* remove leftovers after property_fields, keep only enough to exclude them in initialization

* add migration guide

* fix meta references

* downgrade databases for now

* Change line numbers in documentation (#1265)

* proofread and fix the docs, part 1

* proofread and fix the docs for models

* proofread and fix the docs for fields

* proofread and fix the docs for relations

* proofread and fix rest of the docs, add release notes for 0.20

* create tables in new docs src

* cleanup old deps, uncomment docs publish on tag

* fix import reorder

---------

Co-authored-by: TouwaStar <30479449+TouwaStar@users.noreply.github.com>
Co-authored-by: Goran Mekić <meka@tilda.center>
This commit is contained in:
collerek
2024-03-23 19:28:28 +01:00
committed by GitHub
parent 3a206dd8dc
commit 500625f0ec
294 changed files with 8132 additions and 9311 deletions
Download Patch File Download Diff File Expand all files Collapse all files

261
docs/queries/select-columns.md
View File

@ -24,52 +24,7 @@ With `fields()` you can select subset of model columns to limit the data load.
Given a sample data like following:
```python
import databases
import sqlalchemy
import ormar
from tests.settings import DATABASE_URL
database = databases.Database(DATABASE_URL, force_rollback=True)
metadata = sqlalchemy.MetaData()
class Company(ormar.Model):
class Meta:
tablename = "companies"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
founded: int = ormar.Integer(nullable=True)
class Car(ormar.Model):
class Meta:
tablename = "cars"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
manufacturer = ormar.ForeignKey(Company)
name: str = ormar.String(max_length=100)
year: int = ormar.Integer(nullable=True)
gearbox_type: str = ormar.String(max_length=20, nullable=True)
gears: int = ormar.Integer(nullable=True)
aircon_type: str = ormar.String(max_length=20, nullable=True)
# build some sample data
toyota = await Company.objects.create(name="Toyota", founded=1937)
await Car.objects.create(manufacturer=toyota, name="Corolla", year=2020, gearbox_type='Manual', gears=5,
aircon_type='Manual')
await Car.objects.create(manufacturer=toyota, name="Yaris", year=2019, gearbox_type='Manual', gears=5,
aircon_type='Manual')
await Car.objects.create(manufacturer=toyota, name="Supreme", year=2020, gearbox_type='Auto', gears=6,
aircon_type='Auto')
--8<-- "../docs_src/select_columns/docs001.py"
```
You can select specified fields by passing a `str, List[str], Set[str] or dict` with
@ -78,8 +33,13 @@ nested definition.
To include related models use
notation `{related_name}__{column}[__{optional_next} etc.]`.
```python hl_lines="1"
all_cars = await Car.objects.select_related('manufacturer').fields(['id', 'name', 'manufacturer__name']).all()
```python hl_lines="1-6"
all_cars = await (
Car.objects
.select_related('manufacturer')
.fields(['id', 'name', 'manufacturer__name'])
.all()
)
for car in all_cars:
# excluded columns will yield None
assert all(getattr(car, x) is None for x in ['year', 'gearbox_type', 'gears', 'aircon_type'])
@ -97,9 +57,14 @@ for those models in fields
- implies a list of all fields for those nested models.
```python hl_lines="1"
all_cars = await Car.objects.select_related('manufacturer').fields('id').fields(
['name']).all()
```python hl_lines="1-7"
all_cars = await (
Car.objects
.select_related('manufacturer')
.fields('id')
.fields(['name'])
.all()
)
# all fields from company model are selected
assert all_cars[0].manufacturer.name == 'Toyota'
assert all_cars[0].manufacturer.founded == 1937
@ -115,8 +80,12 @@ assert all_cars[0].manufacturer.founded == 1937
You cannot exclude mandatory model columns - `manufacturer__name` in this example.
```python
await Car.objects.select_related('manufacturer').fields(
['id', 'name', 'manufacturer__founded']).all()
await (
Car.objects
.select_related('manufacturer')
.fields(['id', 'name', 'manufacturer__founded'])
.all()
)
# will raise pydantic ValidationError as company.name is required
```
@ -138,38 +107,71 @@ Below you can see examples that are equivalent:
```python
# 1. like in example above
await Car.objects.select_related('manufacturer').fields(['id', 'name', 'manufacturer__name']).all()
await (
Car.objects
.select_related('manufacturer')
.fields(['id', 'name', 'manufacturer__name'])
.all()
)
# 2. to mark a field as required use ellipsis
await Car.objects.select_related('manufacturer').fields({'id': ...,
'name': ...,
'manufacturer': {
'name': ...}
}).all()
await (
Car.objects
.select_related('manufacturer')
.fields({'id': ...,
'name': ...,
'manufacturer': {
'name': ...
}
})
.all()
)
# 3. to include whole nested model use ellipsis
await Car.objects.select_related('manufacturer').fields({'id': ...,
'name': ...,
'manufacturer': ...
}).all()
await (
Car.objects
.select_related('manufacturer')
.fields({'id': ...,
'name': ...,
'manufacturer': ...
})
.all()
)
# 4. to specify fields at last nesting level you can also use set - equivalent to 2. above
await Car.objects.select_related('manufacturer').fields({'id': ...,
'name': ...,
'manufacturer': {'name'}
}).all()
# 4. to specify fields at last nesting level
# you can also use set - equivalent to 2. above
await (
Car.objects
.select_related('manufacturer')
.fields({'id': ...,
'name': ...,
'manufacturer': {'name'}
})
.all()
)
# 5. of course set can have multiple fields
await Car.objects.select_related('manufacturer').fields({'id': ...,
'name': ...,
'manufacturer': {'name', 'founded'}
}).all()
await (
Car.objects
.select_related('manufacturer')
.fields({'id': ...,
'name': ...,
'manufacturer': {'name', 'founded'}
})
.all()
)
# 6. you can include all nested fields but it will be equivalent of 3. above which is shorter
await Car.objects.select_related('manufacturer').fields({'id': ...,
'name': ...,
'manufacturer': {'id', 'name', 'founded'}
}).all()
# 6. you can include all nested fields,
# but it will be equivalent of 3. above which is shorter
await (
Car.objects
.select_related('manufacturer')
.fields({'id': ...,
'name': ...,
'manufacturer': {'id', 'name', 'founded'}
})
.all()
)
```
@ -201,74 +203,65 @@ exclude fields from whole hierarchy.
Below you can find few simple examples:
```python hl_lines="47 48 60 61 67"
import databases
import sqlalchemy
```python
--8<-- "../docs_src/select_columns/docs001.py"
```
import ormar
from tests.settings import DATABASE_URL
database = databases.Database(DATABASE_URL, force_rollback=True)
metadata = sqlalchemy.MetaData()
class Company(ormar.Model):
class Meta:
tablename = "companies"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
name: str = ormar.String(max_length=100)
founded: int = ormar.Integer(nullable=True)
class Car(ormar.Model):
class Meta:
tablename = "cars"
metadata = metadata
database = database
id: int = ormar.Integer(primary_key=True)
manufacturer = ormar.ForeignKey(Company)
name: str = ormar.String(max_length=100)
year: int = ormar.Integer(nullable=True)
gearbox_type: str = ormar.String(max_length=20, nullable=True)
gears: int = ormar.Integer(nullable=True)
aircon_type: str = ormar.String(max_length=20, nullable=True)
# build some sample data
toyota = await Company.objects.create(name="Toyota", founded=1937)
await Car.objects.create(manufacturer=toyota, name="Corolla", year=2020, gearbox_type='Manual', gears=5,
aircon_type='Manual')
await Car.objects.create(manufacturer=toyota, name="Yaris", year=2019, gearbox_type='Manual', gears=5,
aircon_type='Manual')
await Car.objects.create(manufacturer=toyota, name="Supreme", year=2020, gearbox_type='Auto', gears=6,
aircon_type='Auto')
# select manufacturer but only name - to include related models use notation {model_name}__{column}
all_cars = await Car.objects.select_related('manufacturer').exclude_fields(
['year', 'gearbox_type', 'gears', 'aircon_type', 'company__founded']).all()
```python
# select manufacturer but only name,
# to include related models use notation {model_name}__{column}
all_cars = await (
Car.objects
.select_related('manufacturer')
.exclude_fields([
'year',
'gearbox_type',
'gears',
'aircon_type',
'company__founded'
])
.all()
)
for car in all_cars:
# excluded columns will yield None
assert all(getattr(car, x) is None for x in ['year', 'gearbox_type', 'gears', 'aircon_type'])
# included column on related models will be available, pk column is always included
assert all(getattr(car, x) is None
for x in [
'year',
'gearbox_type',
'gears',
'aircon_type'
])
# included column on related models will be available,
# pk column is always included
# even if you do not include it in fields list
assert car.manufacturer.name == 'Toyota'
# also in the nested related models - you cannot exclude pk - it's always auto added
# also in the nested related models,
# you cannot exclude pk - it's always auto added
assert car.manufacturer.founded is None
# fields() can be called several times, building up the columns to select
# models selected in select_related but with no columns in fields list implies all fields
all_cars = await Car.objects.select_related('manufacturer').exclude_fields('year').exclude_fields(
['gear', 'gearbox_type']).all()
# fields() can be called several times,
# building up the columns to select
# models included in select_related
# but with no columns in fields list implies all fields
all_cars = await (
Car.objects
.select_related('manufacturer')
.exclude_fields('year')
.exclude_fields(['gear', 'gearbox_type'])
.all()
)
# all fields from company model are selected
assert all_cars[0].manufacturer.name == 'Toyota'
assert all_cars[0].manufacturer.founded == 1937
# cannot exclude mandatory model columns - company__name in this example - note usage of dict/set this time
await Car.objects.select_related('manufacturer').exclude_fields([{'company': {'name'}}]).all()
# cannot exclude mandatory model columns,
# company__name in this example - note usage of dict/set this time
await (
Car.objects
.select_related('manufacturer')
.exclude_fields([{'company': {'name'}}])
.all()
)
# will raise pydantic ValidationError as company.name is required
```