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collerek
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docs/queries.md
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@ -130,6 +130,45 @@ assert len(all_books) == 3
`update_or_create(**kwargs) -> Model`
Updates the model, or in case there is no match in database creates a new one.
```python hl_lines="24-30"
import databases
import ormar
import sqlalchemy
database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()
class Book(ormar.Model):
class Meta:
tablename = "books"
metadata = metadata
database = database
id: ormar.Integer(primary_key=True)
title: ormar.String(max_length=200)
author: ormar.String(max_length=100)
genre: ormar.String(max_length=100, default='Fiction', choices=['Fiction', 'Adventure', 'Historic', 'Fantasy'])
await Book.objects.create(title='Tom Sawyer', author="Twain, Mark", genre='Adventure')
await Book.objects.create(title='War and Peace', author="Tolstoy, Leo", genre='Fiction')
await Book.objects.create(title='Anna Karenina', author="Tolstoy, Leo", genre='Fiction')
# if not exist the instance will be persisted in db
vol2 = await Book.objects.update_or_create(title="Volume II", author='Anonymous', genre='Fiction')
assert await Book.objects.count() == 1
# if pk or pkname passed in kwargs (like id here) the object will be updated
assert await Book.objects.update_or_create(id=vol2.id, genre='Historic')
assert await Book.objects.count() == 1
```
!!!note
Note that if you want to create a new object you either have to pass pk column value or pk column has to be set as autoincrement
### bulk_create
`bulk_create(objects: List["Model"]) -> None`
@ -238,15 +277,27 @@ assert len(all_books) == 2
### all
Returns all rows from a database for given model
`all(self, **kwargs) -> List[Optional["Model"]]`
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()`.
If there are no rows meeting the criteria an empty list is returned.
```python
tracks = await Track.objects.select_related("album").all()
# will return a list of all Tracks
tracks = await Track.objects.select_related("album").all(title='Sample')
# will return a list of all Tracks with title Sample
tracks = await Track.objects.all()
# will return a list of all Tracks in database
```
### filter
`filter(**kwargs) -> QuerySet`
Allows you to filter by any `Model` attribute/field
as well as to fetch instances, with a filter across an FK relationship.
@ -269,16 +320,40 @@ You can use special filter suffix to change the filter operands:
* gte - like `position__gte=3` (sql >=)
* lt - like `position__lt=3` (sql <)
* lte - like `position__lte=3` (sql <=)
* startswith - like `album__name__startswith='Mal'` (exact start match)
* istartswith - like `album__name__istartswith='mal'` (exact start match case insensitive)
* endswith - like `album__name__endswith='ibu'` (exact end match)
* iendswith - like `album__name__iendswith='IBU'` (exact end match case insensitive)
!!!note
`filter()`, `select_related()`, `limit()` and `offset()` returns a QueySet instance so you can chain them together.
All methods that do not return the rows explicitly returns a QueySet instance so you can chain them together
So operations like `filter()`, `select_related()`, `limit()` and `offset()` etc. can be chained.
Something like `Track.object.select_related("album").filter(album__name="Malibu").offset(1).limit(1).all()`
### exclude
`exclude(**kwargs) -> QuerySet`
Works exactly the same as filter and all modifiers (suffixes) are the same, but returns a not condition.
So if you use `filter(name='John')` which equals to `where name = 'John'` in SQL,
the `exclude(name='John')` equals to `where name <> 'John'`
Note that all conditions are joined so if you pass multiple values it becomes a union of conditions.
`exclude(name='John', age>=35)` will become `where not (name='John' and age>=35)`
```python
notes = await Track.objects.exclude(position_gt=3).all()
# returns all tracks with position < 3
```
### select_related
`select_related(related: Union[List, str]) -> QuerySet`
Allows to prefetch related models.
To fetch related model use `ForeignKey` names.
@ -299,17 +374,24 @@ classes = await SchoolClass.objects.select_related(
# as well as classes students
```
Exactly the same behavior is for Many2Many fields, where you put the names of Many2Many fields and the final `Models` are fetched for you.
!!!warning
If you set `ForeignKey` field as not nullable (so required) during
all queries the not nullable `Models` will be auto prefetched, even if you do not include them in select_related.
!!!note
`filter()`, `select_related()`, `limit()` and `offset()` returns a QueySet instance so you can chain them together.
All methods that do not return the rows explicitly returns a QueySet instance so you can chain them together
So operations like `filter()`, `select_related()`, `limit()` and `offset()` etc. can be chained.
Something like `Track.object.select_related("album").filter(album__name="Malibu").offset(1).limit(1).all()`
### limit
`limit(limit_count: int) -> QuerySet`
You can limit the results to desired number of rows.
```python
@ -318,12 +400,16 @@ tracks = await Track.objects.limit(1).all()
```
!!!note
`filter()`, `select_related()`, `limit()` and `offset()` returns a QueySet instance so you can chain them together.
All methods that do not return the rows explicitly returns a QueySet instance so you can chain them together
So operations like `filter()`, `select_related()`, `limit()` and `offset()` etc. can be chained.
Something like `Track.object.select_related("album").filter(album__name="Malibu").offset(1).limit(1).all()`
### offset
`offset(offset: int) -> QuerySet`
You can also offset the results by desired number of rows.
```python
@ -331,18 +417,126 @@ tracks = await Track.objects.offset(1).limit(1).all()
# will return just one Track, but this time the second one
```
!!!note
All methods that do not return the rows explicitly returns a QueySet instance so you can chain them together
So operations like `filter()`, `select_related()`, `limit()` and `offset()` etc. can be chained.
Something like `Track.object.select_related("album").filter(album__name="Malibu").offset(1).limit(1).all()`
### count
`count() -> int`
Returns number of rows matching the given criteria (applied with `filter` and `exclude`)
```python
# returns count of rows in db
no_of_books = await Book.objects.count()
```
### exists
`exists() -> bool`
Returns a bool value to confirm if there are rows matching the given criteria (applied with `filter` and `exclude`)
```python
# returns a boolean value if given row exists
has_sample = await Book.objects.filter(title='Sample').exists()
```
### fields
`fields(columns: Union[List, str]) -> QuerySet`
With `fields()` you can select subset of model columns to limit the data load.
```python hl_lines="48 60 61 67"
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: ormar.Integer(primary_key=True)
name: ormar.String(max_length=100)
founded: ormar.Integer(nullable=True)
class Car(ormar.Model):
class Meta:
tablename = "cars"
metadata = metadata
database = database
id: ormar.Integer(primary_key=True)
manufacturer: ormar.ForeignKey(Company)
name: ormar.String(max_length=100)
year: ormar.Integer(nullable=True)
gearbox_type: ormar.String(max_length=20, nullable=True)
gears: ormar.Integer(nullable=True)
aircon_type: 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').fields(['id', 'name', 'company__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'])
# 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
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').fields('id').fields(
['name']).all()
# all fiels 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
await Car.objects.select_related('manufacturer').fields(['id', 'name', 'company__founded']).all()
# will raise pydantic ValidationError as company.name is required
```
!!!warning
Mandatory fields cannot be excluded as it will raise `ValidationError`, to exclude a field it has to be nullable.
!!!tip
Pk column cannot be excluded - it's always auto added even if not explicitly included.
!!!note
`filter()`, `select_related()`, `limit()` and `offset()` returns a QueySet instance so you can chain them together.
All methods that do not return the rows explicitly returns a QueySet instance so you can chain them together
So operations like `filter()`, `select_related()`, `limit()` and `offset()` etc. can be chained.
Something like `Track.object.select_related("album").filter(album__name="Malibu").offset(1).limit(1).all()`
[models]: ./models.md