* 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>
355 lines
12 KiB
Markdown
355 lines
12 KiB
Markdown
# Return raw data
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Following methods allow you to execute a query but instead of returning ormar models those will return list of dicts or tuples.
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* `values(fields = None, exclude_through = False) -> List[Dict]`
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* `values_list(fields = None, exclude_through = False, flatten = False) -> List`
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* `QuerysetProxy`
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* `QuerysetProxy.values(fields = None, exclude_through = False)` method
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* `QuerysetProxy.values_list(fields = None, exclude_through= False, flatten = False)` method
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!!!danger
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Note that `values` and `values_list` skips parsing the result to ormar models so skips also the validation of the result!
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!!!warning
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Note that each entry in a result list is one to one reflection of a query result row.
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Since rows are not parsed if you have one-to-many or many-to-many relation expect
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duplicated columns values in result entries if one parent row have multiple related rows.
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## values
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`values(fields: Union[List, str, Set, Dict] = None, exclude_through: bool = False) -> List[Dict]`
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Return a list of dictionaries representing the values of the columns coming from the database.
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You can select a subset of fields with fields parameter, that accepts the same set of parameters as `fields()` method.
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Note that passing fields to `values(fields)` is actually a shortcut for calling `fields(fields).values()`.
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!!!tip
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To read more about what you can pass to fields and how to select nested models fields read [selecting columns](./select-columns.md#fields) docs
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You can limit the number of rows by providing conditions in `filter()` and `exclude()`, but note that even if only one row (or no rows!) match your criteria you will return a list in response.
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Example:
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```python
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# declared models
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class Category(ormar.Model):
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ormar_config = base_ormar_config.copy(tablename="categories")
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=40)
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sort_order: int = ormar.Integer(nullable=True)
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class Post(ormar.Model):
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ormar_config = base_ormar_config.copy()
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=200)
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category: Optional[Category] = ormar.ForeignKey(Category)
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# sample data
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news = await Category(name="News", sort_order=0).save()
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await Post(name="Ormar strikes again!", category=news).save()
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await Post(name="Why don't you use ormar yet?", category=news).save()
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await Post(name="Check this out, ormar now for free", category=news).save()
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```
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Access Post models:
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```python
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posts = await Post.objects.values()
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assert posts == [
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{"id": 1, "name": "Ormar strikes again!", "category": 1},
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{"id": 2, "name": "Why don't you use ormar yet?", "category": 1},
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{"id": 3, "name": "Check this out, ormar now for free", "category": 1},
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]
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```
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To select also related models use `select_related` or `prefetch_related`.
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Note how nested models columns will be prefixed with full relation path coming from the main model (the one used in a query).
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```python
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# declare models
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class User(ormar.Model):
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ormar_config = base_ormar_config.copy()
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=100)
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class Role(ormar.Model):
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ormar_config = base_ormar_config.copy()
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=100)
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users: List[User] = ormar.ManyToMany(User)
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# sample data
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creator = await User(name="Anonymous").save()
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admin = await Role(name="admin").save()
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editor = await Role(name="editor").save()
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await creator.roles.add(admin)
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await creator.roles.add(editor)
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```
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Select user with roles
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```python
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user = await User.objects.select_related("roles").values()
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# note nested prefixes: roleuser and roles
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assert user == [
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{
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"id": 1,
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"name": "Anonymous",
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"roleuser__id": 1,
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"roleuser__role": 1,
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"roleuser__user": 1,
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"roles__id": 1,
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"roles__name": "admin",
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},
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{
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"id": 1,
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"name": "Anonymous",
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"roleuser__id": 2,
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"roleuser__role": 2,
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"roleuser__user": 1,
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"roles__id": 2,
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"roles__name": "editor",
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},
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]
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```
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!!!note
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Note how role to users relation is a `ManyToMany` relation so by default you also get through model columns.
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Combine select related and fields to select only 3 fields.
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Note that we also exclude through model as by definition every model included in a join but without any reference in fields is assumed to be selected in full (all fields included).
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!!!note
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Note that in contrary to other queryset methods here you can exclude the
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in-between models but keep the end columns, which does not make sense
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when parsing the raw data into models.
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So in relation category -> category_x_post -> post -> user you can exclude
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category_x_post and post models but can keep the user one. (in ormar model
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context that is not possible as if you would exclude through and post model
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there would be no way to reach user model from category model).
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```python
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user = (
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await Role.objects.select_related("users__categories")
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.filter(name="admin")
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.fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
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.exclude_fields("roleuser")
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.values()
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)
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assert user == [
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{
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"name": "admin",
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"users__name": "Anonymous",
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"users__categories__name": "News",
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}
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]
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```
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If you have multiple ManyToMany models in your query you would have to exclude each through model manually.
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To avoid this burden `ormar` provides you with `exclude_through=False` parameter.
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If you set this flag to True **all through models will be fully excluded**.
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```python
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# equivalent to query above, note lack of exclude_fields call
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user = (
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await Role.objects.select_related("users__categories")
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.filter(name="admin")
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.fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
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.values(exclude_through=True)
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)
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assert user == [
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{
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"name": "admin",
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"users__name": "Anonymous",
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"users__categories__name": "News",
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}
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]
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```
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## values_list
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`values_list(fields: Union[List, str, Set, Dict] = None, flatten: bool = False, exclude_through: bool = False) -> List`
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Return a list of tuples representing the values of the columns coming from the database.
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You can select a subset of fields with fields parameter, that accepts the same set of parameters as `fields()` method.
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Note that passing fields to `values_list(fields)` is actually a shortcut for calling `fields(fields).values_list()`.
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!!!tip
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To read more about what you can pass to fields and how to select nested models fields read [selecting columns](./select-columns.md#fields) docs
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If you select only one column/field you can pass `flatten=True` which will return you a list of values instead of list of one element tuples.
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!!!warning
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Setting `flatten=True` if more than one (or none which means all) fields are selected will raise `QueryDefinitionError` exception.
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You can limit the number of rows by providing conditions in `filter()` and `exclude()`, but note that even if only one row (or no rows!) match your criteria you will return a list in response.
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Example:
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```python
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# declared models
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class Category(ormar.Model):
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ormar_config = base_ormar_config.copy(tablename="categories")
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=40)
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sort_order: int = ormar.Integer(nullable=True)
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class Post(ormar.Model):
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ormar_config = base_ormar_config.copy()
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=200)
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category: Optional[Category] = ormar.ForeignKey(Category)
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# sample data
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news = await Category(name="News", sort_order=0).save()
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await Post(name="Ormar strikes again!", category=news).save()
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await Post(name="Why don't you use ormar yet?", category=news).save()
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await Post(name="Check this out, ormar now for free", category=news).save()
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```
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Access Post models:
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```python
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posts = await Post.objects.values_list()
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# note how columns refer to id, name and category (fk)
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assert posts == [
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(1, "Ormar strikes again!", 1),
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(2, "Why don't you use ormar yet?", 1),
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(3, "Check this out, ormar now for free", 1),
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]
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```
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To select also related models use `select_related` or `prefetch_related`.
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Let's complicate the relation and modify the previously mentioned Category model to refer to User model.
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```python
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class Category(ormar.Model):
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ormar_config = base_ormar_config.copy(tablename="categories")
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id: int = ormar.Integer(primary_key=True)
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name: str = ormar.String(max_length=40)
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sort_order: int = ormar.Integer(nullable=True)
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# new column below
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created_by: Optional[User] = ormar.ForeignKey(User, related_name="categories")
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```
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Now create the sample data with link to user.
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```python
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creator = await User(name="Anonymous").save()
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admin = await Role(name="admin").save()
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editor = await Role(name="editor").save()
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await creator.roles.add(admin)
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await creator.roles.add(editor)
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news = await Category(name="News", sort_order=0, created_by=creator).save()
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```
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Combine select related and fields to select only 3 fields.
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Note that we also exclude through model as by definition every model included in a join but without any reference in fields is assumed to be selected in full (all fields included).
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!!!note
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Note that in contrary to other queryset methods here you can exclude the
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in-between models but keep the end columns, which does not make sense
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when parsing the raw data into models.
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So in relation category -> category_x_post -> post -> user you can exclude
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category_x_post and post models but can keep the user one. (in ormar model
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context that is not possible as if you would exclude through and post model
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there would be no way to reach user model from category model).
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```python
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user = (
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await Role.objects.select_related("users__categories")
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.filter(name="admin")
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.fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
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.exclude_fields("roleuser")
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.values_list()
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)
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assert user == [("admin", "Anonymous", "News")]
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```
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If you have multiple ManyToMany models in your query you would have to exclude each through model manually.
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To avoid this burden `ormar` provides you with `exclude_through=False` parameter.
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If you set this flag to True **all through models will be fully excluded**.
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```python
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# equivalent to query above, note lack of exclude_fields call
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user = (
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await Role.objects.select_related("users__categories")
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.filter(name="admin")
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.fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
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.values_list(exclude_through=True)
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)
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assert user == [("admin", "Anonymous", "News")]
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```
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Use flatten to get list of values.
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```python
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# using flatten with more than one field will raise exception!
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await Role.objects.fields({"name", "id"}).values_list(flatten=True)
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# proper usage
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roles = await Role.objects.fields("name").values_list(flatten=True)
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assert roles == ["admin", "editor"]
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```
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## QuerysetProxy methods
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When access directly the related `ManyToMany` field as well as `ReverseForeignKey`
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returns the list of related models.
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But at the same time it exposes subset of QuerySet API, so you can filter, create,
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select related etc related models directly from parent model.
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!!!warning
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Because using `values` and `values_list` skips parsing of the models and validation, in contrast to all other read methods in querysetproxy those 2 **does not clear currently loaded related models** and **does not overwrite the currently loaded models** with result of own call!
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### values
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Works exactly the same as [values](./#values) function above but allows you to fetch related
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objects from other side of the relation.
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!!!tip
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To read more about `QuerysetProxy` visit [querysetproxy][querysetproxy] section
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### values_list
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Works exactly the same as [values_list](./#values_list) function above but allows
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you to query or create related objects from other side of the relation.
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!!!tip
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To read more about `QuerysetProxy` visit [querysetproxy][querysetproxy] section
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[querysetproxy]: ../relations/queryset-proxy.md
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