* 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>
9.8 KiB
QuerySetProxy
When access directly the related ManyToMany field as well as ReverseForeignKey returns the list of related models.
But at the same time it exposes subset of QuerySet API, so you can filter, create, select related etc related models directly from parent model.
!!!note
By default exposed QuerySet is already filtered to return only Models related to parent Model.
So if you issue `post.categories.all()` you will get all categories related to that post, not all in table.
!!!note
Note that when accessing QuerySet API methods through QuerysetProxy you don't
need to use objects attribute like in normal queries.
So note that it's `post.categories.all()` and **not** `post.categories.objects.all()`.
To learn more about available QuerySet methods visit [queries][queries]
!!!warning Querying related models from ManyToMany cleans list of related models loaded on parent model:
Example: `post.categories.first()` will set post.categories to list of 1 related model -> the one returned by first()
Example 2: if post has 4 categories so `len(post.categories) == 4` calling `post.categories.limit(2).all()`
-> will load only 2 children and now `assert len(post.categories) == 2`
This happens for all QuerysetProxy methods returning data: `get`, `all` and `first` and in `get_or_create` if model already exists.
Note that value returned by `create` or created in `get_or_create` and `update_or_create`
if model does not exist will be added to relation list (not clearing it).
Read data from database
get
get(**kwargs): -> Model
To grab just one of related models filtered by name you can use get(**kwargs) method.
# grab one category
assert news == await post.categories.get(name="News")
# note that method returns the category so you can grab this value
# but it also modifies list of related models in place
# so regardless of what was previously loaded on parent model
# now it has only one value -> just loaded with get() call
assert len(post.categories) == 1
assert post.categories[0] == news
!!!tip Read more in queries documentation get
get_or_create
get_or_create(_defaults: Optional[Dict[str, Any]] = None, **kwargs) -> Tuple[Model, bool]
Tries to get a row meeting the criteria and if NoMatch exception is raised it creates a new one with given kwargs and _defaults.
!!!tip Read more in queries documentation get_or_create
all
all(**kwargs) -> List[Optional["Model"]]
To get a list of related models use all() method.
Note that you can filter the queryset, select related, exclude fields etc. like in normal query.
# with all Queryset methods - filtering, selecting columns, counting etc.
await news.posts.filter(title__contains="M2M").all()
await Category.objects.filter(posts__author=guido).get()
# columns models of many to many relation can be prefetched
news_posts = await news.posts.select_related("author").all()
assert news_posts[0].author == guido
!!!tip Read more in queries documentation all
iterate
iterate(**kwargs) -> AsyncGenerator["Model"]
To iterate on related models use iterate() method.
Note that you can filter the queryset, select related, exclude fields etc. like in normal query.
# iterate on categories of this post with an async generator
async for category in post.categories.iterate():
print(category.name)
!!!tip Read more in queries documentation iterate
Insert/ update data into database
create
create(**kwargs): -> Model
Create related Model directly from parent Model.
The link table is automatically populated, as well as relation ids in the database.
# Creating columns object from instance:
await post.categories.create(name="Tips")
assert len(await post.categories.all()) == 2
# newly created instance already have relation persisted in the database
!!!tip Read more in queries documentation create
For ManyToMany relations there is an additional functionality of passing parameters
that will be used to create a through model if you declared additional fields on explicitly
provided Through model.
Given sample like this:
--8<-- "../docs_src/relations/docs004.py"
You can populate fields on through model in the create() call in a following way:
post = await Post(title="Test post").save()
await post.categories.create(
name="Test category1",
# in arguments pass a dictionary with name of the through field and keys
# corresponding to through model fields
postcategory={"sort_order": 1, "param_name": "volume"},
)
get_or_create
get_or_create(_defaults: Optional[Dict[str, Any]] = None, **kwargs) -> Tuple[Model, bool]
Tries to get a row meeting the criteria and if NoMatch exception is raised it creates a new one with given kwargs.
!!!tip Read more in queries documentation get_or_create
update_or_create
update_or_create(**kwargs) -> Model
Updates the model, or in case there is no match in database creates a new one.
!!!tip Read more in queries documentation update_or_create
update
update(**kwargs, each:bool = False) -> int
Updates the related model with provided keyword arguments, return number of updated rows.
!!!tip Read more in queries documentation update
Note that for ManyToMany relations update can also accept an argument with through field
name and a dictionary of fields.
--8<-- "../docs_src/relations/docs004.py"
In example above you can update attributes of postcategory in a following call:
await post.categories.filter(name="Test category3").update(
postcategory={"sort_order": 4}
)
Filtering and sorting
filter
filter(*args, **kwargs) -> QuerySet
Allows you to filter by any Model attribute/field as well as to fetch instances, with a filter across an FK relationship.
!!!tip Read more in queries documentation filter
exclude
exclude(*args, **kwargs) -> QuerySet
Works exactly the same as filter and all modifiers (suffixes) are the same, but returns a not condition.
!!!tip Read more in queries documentation exclude
order_by
order_by(columns:Union[List, str]) -> QuerySet
With order_by() you can order the results from database based on your choice of fields.
!!!tip Read more in queries documentation order_by
Joins and subqueries
select_related
select_related(related: Union[List, str]) -> QuerySet
Allows to prefetch related models during the same query.
With select_related always only one query is run against the database, meaning that one (sometimes complicated) join is generated and later nested models are processed in python.
!!!tip Read more in queries documentation select_related
prefetch_related
prefetch_related(related: Union[List, str]) -> QuerySet
Allows to prefetch related models during query - but opposite to select_related each subsequent model is fetched in a separate database query.
With prefetch_related always one query per Model is run against the database, meaning that you will have multiple queries executed one after another.
!!!tip Read more in queries documentation prefetch_related
Pagination and rows number
paginate
paginate(page: int, page_size: int = 20) -> QuerySet
Combines the offset and limit methods based on page number and size.
!!!tip Read more in queries documentation paginate
limit
limit(limit_count: int) -> QuerySet
You can limit the results to desired number of parent models.
!!!tip Read more in queries documentation limit
offset
offset(offset: int) -> QuerySet
You can offset the results by desired number of main models.
!!!tip Read more in queries documentation offset
Selecting subset of columns
fields
fields(columns: Union[List, str, set, dict]) -> QuerySet
With fields() you can select subset of model columns to limit the data load.
!!!tip Read more in queries documentation fields
exclude_fields
exclude_fields(columns: Union[List, str, set, dict]) -> QuerySet
With exclude_fields() you can select subset of model columns that will be excluded to limit the data load.
!!!tip Read more in queries documentation exclude_fields
Aggregated functions
count
count(distinct: bool = True) -> int
Returns number of rows matching the given criteria (i.e. applied with filter and exclude)
!!!tip Read more in queries documentation count
exists
exists() -> bool
Returns a bool value to confirm if there are rows matching the given criteria (applied with filter and exclude)
!!!tip Read more in queries documentation exists