Files
ormar/docs/queries/raw-data.md
collerek 500625f0ec WIP - Pydantic v2 support (#1238)
* 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>
2024-03-23 19:28:28 +01:00

12 KiB

Return raw data

Following methods allow you to execute a query but instead of returning ormar models those will return list of dicts or tuples.

  • values(fields = None, exclude_through = False) -> List[Dict]

  • values_list(fields = None, exclude_through = False, flatten = False) -> List

  • QuerysetProxy

    • QuerysetProxy.values(fields = None, exclude_through = False) method
    • QuerysetProxy.values_list(fields = None, exclude_through= False, flatten = False) method

!!!danger Note that values and values_list skips parsing the result to ormar models so skips also the validation of the result!

!!!warning Note that each entry in a result list is one to one reflection of a query result row. Since rows are not parsed if you have one-to-many or many-to-many relation expect duplicated columns values in result entries if one parent row have multiple related rows.

values

values(fields: Union[List, str, Set, Dict] = None, exclude_through: bool = False) -> List[Dict]

Return a list of dictionaries representing the values of the columns coming from the database.

You can select a subset of fields with fields parameter, that accepts the same set of parameters as fields() method.

Note that passing fields to values(fields) is actually a shortcut for calling fields(fields).values().

!!!tip To read more about what you can pass to fields and how to select nested models fields read selecting columns docs

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.

Example:

# declared models

class Category(ormar.Model):
    ormar_config = base_ormar_config.copy(tablename="categories")

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=40)
    sort_order: int = ormar.Integer(nullable=True)


class Post(ormar.Model):
    ormar_config = base_ormar_config.copy()

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=200)
    category: Optional[Category] = ormar.ForeignKey(Category)

# sample data
news = await Category(name="News", sort_order=0).save()
await Post(name="Ormar strikes again!", category=news).save()
await Post(name="Why don't you use ormar yet?", category=news).save()
await Post(name="Check this out, ormar now for free", category=news).save()

Access Post models:

posts = await Post.objects.values()
assert posts == [
    {"id": 1, "name": "Ormar strikes again!", "category": 1},
    {"id": 2, "name": "Why don't you use ormar yet?", "category": 1},
    {"id": 3, "name": "Check this out, ormar now for free", "category": 1},
]

To select also related models use select_related or prefetch_related.

Note how nested models columns will be prefixed with full relation path coming from the main model (the one used in a query).

# declare models

class User(ormar.Model):
    ormar_config = base_ormar_config.copy()

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=100)


class Role(ormar.Model):
    ormar_config = base_ormar_config.copy()

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=100)
    users: List[User] = ormar.ManyToMany(User)

# sample data
creator = await User(name="Anonymous").save()
admin = await Role(name="admin").save()
editor = await Role(name="editor").save()
await creator.roles.add(admin)
await creator.roles.add(editor)

Select user with roles

user = await User.objects.select_related("roles").values()
# note nested prefixes: roleuser and roles
assert user == [
    {
        "id": 1,
        "name": "Anonymous",
        "roleuser__id": 1,
        "roleuser__role": 1,
        "roleuser__user": 1,
        "roles__id": 1,
        "roles__name": "admin",
    },
    {
        "id": 1,
        "name": "Anonymous",
        "roleuser__id": 2,
        "roleuser__role": 2,
        "roleuser__user": 1,
        "roles__id": 2,
        "roles__name": "editor",
    },
]

!!!note Note how role to users relation is a ManyToMany relation so by default you also get through model columns.

Combine select related and fields to select only 3 fields.

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).

!!!note Note that in contrary to other queryset methods here you can exclude the in-between models but keep the end columns, which does not make sense when parsing the raw data into models.

So in relation category -> category_x_post -> post -> user you can exclude
category_x_post and post models but can keep the user one. (in ormar model
context that is not possible as if you would exclude through and post model
there would be no way to reach user model from category model).
user = (
        await Role.objects.select_related("users__categories")
        .filter(name="admin")
        .fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
        .exclude_fields("roleuser")
        .values()
    )
assert user == [
    {
        "name": "admin",
        "users__name": "Anonymous",
        "users__categories__name": "News",
    }
]

If you have multiple ManyToMany models in your query you would have to exclude each through model manually.

To avoid this burden ormar provides you with exclude_through=False parameter. If you set this flag to True all through models will be fully excluded.

# equivalent to query above, note lack of exclude_fields call
user = (
    await Role.objects.select_related("users__categories")
    .filter(name="admin")
    .fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
    .values(exclude_through=True)
)
assert user == [
    {
        "name": "admin",
        "users__name": "Anonymous",
        "users__categories__name": "News",
    }
]

values_list

values_list(fields: Union[List, str, Set, Dict] = None, flatten: bool = False, exclude_through: bool = False) -> List

Return a list of tuples representing the values of the columns coming from the database.

You can select a subset of fields with fields parameter, that accepts the same set of parameters as fields() method.

Note that passing fields to values_list(fields) is actually a shortcut for calling fields(fields).values_list().

!!!tip To read more about what you can pass to fields and how to select nested models fields read selecting columns docs

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.

!!!warning Setting flatten=True if more than one (or none which means all) fields are selected will raise QueryDefinitionError exception.

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.

Example:

# declared models

class Category(ormar.Model):
    ormar_config = base_ormar_config.copy(tablename="categories")

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=40)
    sort_order: int = ormar.Integer(nullable=True)


class Post(ormar.Model):
    ormar_config = base_ormar_config.copy()

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=200)
    category: Optional[Category] = ormar.ForeignKey(Category)

# sample data
news = await Category(name="News", sort_order=0).save()
await Post(name="Ormar strikes again!", category=news).save()
await Post(name="Why don't you use ormar yet?", category=news).save()
await Post(name="Check this out, ormar now for free", category=news).save()

Access Post models:

posts = await Post.objects.values_list()
# note how columns refer to id, name and category (fk)
assert posts == [
    (1, "Ormar strikes again!", 1),
    (2, "Why don't you use ormar yet?", 1),
    (3, "Check this out, ormar now for free", 1),
]

To select also related models use select_related or prefetch_related.

Let's complicate the relation and modify the previously mentioned Category model to refer to User model.

class Category(ormar.Model):
    ormar_config = base_ormar_config.copy(tablename="categories")

    id: int = ormar.Integer(primary_key=True)
    name: str = ormar.String(max_length=40)
    sort_order: int = ormar.Integer(nullable=True)
    # new column below
    created_by: Optional[User] = ormar.ForeignKey(User, related_name="categories")

Now create the sample data with link to user.

creator = await User(name="Anonymous").save()
admin = await Role(name="admin").save()
editor = await Role(name="editor").save()
await creator.roles.add(admin)
await creator.roles.add(editor)
news = await Category(name="News", sort_order=0, created_by=creator).save()

Combine select related and fields to select only 3 fields.

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).

!!!note Note that in contrary to other queryset methods here you can exclude the in-between models but keep the end columns, which does not make sense when parsing the raw data into models.

So in relation category -> category_x_post -> post -> user you can exclude
category_x_post and post models but can keep the user one. (in ormar model
context that is not possible as if you would exclude through and post model
there would be no way to reach user model from category model).
user = (
        await Role.objects.select_related("users__categories")
        .filter(name="admin")
        .fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
        .exclude_fields("roleuser")
        .values_list()
    )
assert user == [("admin", "Anonymous", "News")]

If you have multiple ManyToMany models in your query you would have to exclude each through model manually.

To avoid this burden ormar provides you with exclude_through=False parameter. If you set this flag to True all through models will be fully excluded.

# equivalent to query above, note lack of exclude_fields call
user = (
        await Role.objects.select_related("users__categories")
        .filter(name="admin")
        .fields({"name": ..., "users": {"name": ..., "categories": {"name"}}})
        .values_list(exclude_through=True)
    )
assert user == [("admin", "Anonymous", "News")]

Use flatten to get list of values.

# using flatten with more than one field will raise exception!
await Role.objects.fields({"name", "id"}).values_list(flatten=True)

# proper usage
roles = await Role.objects.fields("name").values_list(flatten=True)
assert roles == ["admin", "editor"]

QuerysetProxy methods

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.

!!!warning 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!

values

Works exactly the same as values function above but allows you to fetch related objects from other side of the relation.

!!!tip To read more about QuerysetProxy visit querysetproxy section

values_list

Works exactly the same as values_list function above but allows you to query or create related objects from other side of the relation.

!!!tip To read more about QuerysetProxy visit querysetproxy section