# Queries

## QuerySet

Each Model is auto registered with a QuerySet that represents the underlaying query and it's options.

Most of the methods are also available through many to many relation interface.

Given the Models like this

```Python 
--8<-- "../docs_src/queries/docs001.py"
```

we can demonstrate available methods to fetch and save the data into the database.


### create

`create(**kwargs): -> Model` 

Creates the model instance, saves it in a database and returns the updates model 
(with pk populated if not passed and autoincrement is set).

The allowed kwargs are `Model` fields names and proper value types. 

```python
malibu = await Album.objects.create(name="Malibu")
await Track.objects.create(album=malibu, title="The Bird", position=1)
```

The alternative is a split creation and persistence of the `Model`.
```python
malibu = Album(name="Malibu")
await malibu.save()
```

!!!tip
    Check other `Model` methods in [models][models]

### get

`get(**kwargs): -> Model` 

Get's the first row from the db meeting the criteria set by kwargs.

If no criteria set it will return the first row in db.

Passing a criteria is actually calling filter(**kwargs) method described below.

```python
track = await Track.objects.get(name='The Bird')
# note that above is equivalent to await Track.objects.filter(name='The Bird').get()
track2 = track = await Track.objects.get()
track == track2 # True since it's the only row in db in our example
```

!!!warning
    If no row meets the criteria `NoMatch` exception is raised.
    
    If there are multiple rows meeting the criteria the `MultipleMatches` exception is raised.

### get_or_create

`get_or_create(**kwargs) -> Model`

Combination of create and get methods.

Tries to get a row meeting the criteria and if `NoMatch` exception is raised it creates a new one with given kwargs.

```python
album = await Album.objects.get_or_create(name='The Cat')
# object is created as it does not exist
album2 = await Album.objects.get_or_create(name='The Cat')
assert album == album2
# return True as the same db row is returned
```

!!!warning
    Despite being a equivalent row from database the `album` and `album2` in example above are 2 different python objects!
    Updating one of them will not refresh the second one until you excplicitly load() the fresh data from db.

!!!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

### update

`update(each: bool = False, **kwargs) -> int`

QuerySet level update is used to update multiple records with the same value at once.

You either have to filter the QuerySet first or provide a `each=True` flag to update whole table.

If you do not provide this flag or a filter a `QueryDefinitionError` will be raised.

Return number of rows updated.

```python hl_lines="24-28"
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')


# queryset needs to be filtered before deleting to prevent accidental overwrite
# to update whole database table each=True needs to be provided as a safety switch
await Book.objects.update(each=True, genre='Fiction')
all_books = await Book.objects.filter(genre='Fiction').all()
assert len(all_books) == 3
```

### update_or_create

`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`

Allows you to create multiple objects at once.

A valid list of `Model` objects needs to be passed.

```python hl_lines="20-26"
import databases
import ormar
import sqlalchemy

database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()


class ToDo(ormar.Model):
    class Meta:
        tablename = "todos"
        metadata = metadata
        database = database

    id: ormar.Integer(primary_key=True)
    text: ormar.String(max_length=500)
    completed: ormar.Boolean(default=False)

# create multiple instances at once with bulk_create
await ToDo.objects.bulk_create(
            [
                ToDo(text="Buy the groceries."),
                ToDo(text="Call Mum.", completed=True),
                ToDo(text="Send invoices.", completed=True),
            ]
        )

todoes = await ToDo.objects.all()
assert len(todoes) == 3
```

### bulk_update

`bulk_update(objects: List["Model"], columns: List[str] = None) -> None`

Allows to update multiple instance at once.

All `Models` passed need to have primary key column populated.

You can also select which fields to update by passing `columns` list as a list of string names.

```python hl_lines="8"
# continuing the example from bulk_create
# update objects
for todo in todoes:
    todo.completed = False

# perform update of all objects at once
# objects need to have pk column set, otherwise exception is raised
await ToDo.objects.bulk_update(todoes)

completed = await ToDo.objects.filter(completed=False).all()
assert len(completed) == 3
```

### delete

`delete(each: bool = False, **kwargs) -> int`

QuerySet level delete is used to delete multiple records at once.

You either have to filter the QuerySet first or provide a `each=True` flag to delete whole table.

If you do not provide this flag or a filter a `QueryDefinitionError` will be raised.

Return number of rows deleted.

```python hl_lines="23-27"
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 in Space', author="Tolstoy, Leo", genre='Fantasy')
await Book.objects.create(title='Anna Karenina', author="Tolstoy, Leo", genre='Fiction')

# delete accepts kwargs that will be used in filter
# acting in same way as queryset.filter(**kwargs).delete()
await Book.objects.delete(genre='Fantasy') # delete all fantasy books
all_books = await Book.objects.all()
assert len(all_books) == 2
```

### all

`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(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.

```python
track = Track.objects.filter(name="The Bird").get()
# will return a track with name equal to 'The Bird'
 
tracks = Track.objects.filter(album__name="Fantasies").all()
# will return all tracks where the columns album name = 'Fantasies'
```

You can use special filter suffix to change the filter operands:

*  exact - like `album__name__exact='Malibu'` (exact match)
*  iexact - like `album__name__iexact='malibu'` (exact match case insensitive)
*  contains - like `album__name__conatins='Mal'` (sql like)
*  icontains - like `album__name__icontains='mal'` (sql like case insensitive)
*  in - like `album__name__in=['Malibu', 'Barclay']` (sql in)
*  gt - like `position__gt=3` (sql >)
*  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
    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.

To chain related `Models` relation use double underscore.

```python
album = await Album.objects.select_related("tracks").all()
# will return album will all columns tracks
```

You can provide a string or a list of strings

```python
classes = await SchoolClass.objects.select_related(
["teachers__category", "students"]).all()
# will return classes with teachers and teachers categories
# 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
    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
tracks = await Track.objects.limit(1).all()
# will return just one Track
```

!!!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()`

### offset

`offset(offset: int) -> QuerySet`

You can also offset the results by desired number of rows.

```python
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
    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