---
title: "QuerySet API リファレンス"
version: 4.1
locale: ja
source: https://docs.djangoproject.com/ja/4.1/ref/models/querysets/
canonical: https://djangodocs.dev/ja/4.1/ref/models/querysets/
---
# `QuerySet` API リファレンス

このドキュメントでは、`QuerySet` API の詳細を説明しています。[モデル](/ja/4.1/topics/db/models/) と [データベースクエリ](/ja/4.1/topics/db/queries/) ガイドにある説明を前提としていますので、このドキュメントを読む前にこの 2 つを読んでおいた方がよいでしょう。

このリファレンスでは、 [データベースクエリガイド](/ja/4.1/topics/db/queries/) で提供された [Blogモデルの例](/ja/4.1/topics/db/queries/#queryset-model-example) を使用します。

## When `QuerySet`s are evaluated

内部的に、 `QuerySet` は実際にデータベースにアクセスすることなく、構築、フィルタ、スライス、そして基本的に他に渡されます。あなたがクエリセットを評価するために何かしない限り、実際のデータベースへのアクセスは発生しません。

あなたは次のような方法で `QuerySet` を評価することができます:

- **イテレーション。** `QuerySet` はイテラブルで、初めてイテレートした時にデータベースのクエリを実行します。たとえば、これはデータベースにある全エントリのヘッドラインを出力するプログラムです:

  ```
  for e in Entry.objects.all():
      print(e.headline)
  ```

  メモ: 単に1つ以上の結果が存在するかどうかを決定したいだけなら、これを使わないでください。 [`exists()`](#django.db.models.query.QuerySet.exists) を使う方がより効率的です。
- **非同期イテレーション** 。`QuerySet` は `async for` を使うことによっても反復処理することができます:

  ```
  async for e in Entry.objects.all():
    results.append(e)
  ```

  クエリセットの同期的・非同期的イテレータは、同じキャッシュを共有します。

  > **Changed in Django 4.1**
  >
  > 非同期イテレーションのサポートが追加されました。
- **スライス。** [QuerySet の要素数を制限する](/ja/4.1/topics/db/queries/#limiting-querysets) で説明されているとおり、 `QuerySet` はPythonのリストスライスを用いてスライス可能です。未評価の `QuerySet` をスライスすると、通常は新たな未評価の `QuerySet` が返されます。しかし、スライスの "step" パラメータを使用した場合、Djangoはデータベースクエリを実行し、リストを返します。評価された `QuerySet` をスライスした場合も同様にリストが返されます。

  未評価の `QuerySet` をスライスして別の未評価の `QuerySet` が返されても、それをさらに変更すること(たとえば、さらにフィルタを追加したり、順序を変更したりすること)は許されていないことに気を付けてください。これは、その操作がSQLに正しく変換されず、明確な意味を持たないためです。
- **Pickle 化/キャッシュ化。**  詳細については、後述の [pickling QuerySets](#pickling-querysets) を参照してください。結果がデータベースから読み出されることが、このセクションの目的として重要なことです。
- **repr()。**  `QuerySet` は `repr()` が呼び出された時点で評価されます。これはPythonの対話型インタプリタでの利便性を図るためで、APIを対話的に使用する際にクエリの結果をすぐに確認することができます。
- **len()。** `QuerySet` は `len()` を呼び出した時点で評価されます。想像される通り、この操作は結果のリストの長さを返します。

  メモ: セット内のレコード数を決定したいだけであれば(そして実際のオブジェクトが必要ないのであれば)、SQLの `SELECT COUNT(*)` を使ってデータベースレベルでハンドルする方がより効率的です。Djangoはまさにこの理由から [`count()`](#django.db.models.query.QuerySet.count) メソッドを提供しています。
- **list()。** `list()` を呼び出すことで、 `QuerySet` の評価を強制します。たとえば:

  ```
  entry_list = list(Entry.objects.all())
  ```
- **bool()。** `bool()`, `or`, `and` または `if` 文を使用してブール値として `QuerySet` をテストすると、クエリが実行されます。 `QuerySet` も少なくとも1つ以上の結果が含まれれば `True` となり、そうでなければ `False` になります。例えば:

  ```
  if Entry.objects.filter(headline="Test"):
     print("There is at least one Entry with the headline Test")
  ```

  注意: もしクエリの結果が少なくとも1つ存在するかどうかを確認したいだけであれば(そして実際のオブジェクトを必要としないのであれば)、 [`exists()`](#django.db.models.query.QuerySet.exists) を使うべきです。

### Pickling `QuerySet`s

`QuerySet` を [`pickle`](https://docs.python.org/3/library/pickle.html#module-pickle) 化するとき、pickle化の前にすべての結果がメモリにロードされるように強制されます。キャッシュされたクエリセットがリロードされた時、結果がすでに存在し、使用できる状態になっていることが望ましいからです(データベースからの読み込みには時間がかかるので、キャッシュとしての目的を達成できません)。つまり、 `QuerySet` のpickle化を解除すると、解除した時点でデータベースにある結果ではなく、pickle化した時点での結果が出力されることになります。

もし、後でデータベースから `QuerySet` を再生成するために必要な情報だけを取り出したい場合は、 `QuerySet` の `query` を属性を取り出してください。そうすることで、以下のようなコードで本来の `QuerySet` (結果を読み込む前の状態)を再現することができます:

```
>>> import pickle
>>> query = pickle.loads(s)     # Assuming 's' is the pickled string.
>>> qs = MyModel.objects.all()
>>> qs.query = query            # Restore the original 'query'.
```

`query` 属性は不透明なオブジェクトです。これは内側でのクエリ構築を表すもので、公開APIの一部ではありません。しかし、ここで説明しているように、この属性の内容のpickle化・pickle化の解除は安全に行うことができます(完全にサポートもされています)。

> **QuerySet.values_list() における制限**
>
> `query` 属性をpickle化して [`QuerySet.values_list()`](#django.db.models.query.QuerySet.values_list) を再生成すると、 [`QuerySet.values()`](#django.db.models.query.QuerySet.values) に変換されます:
>
> ```
> >>> import pickle
> >>> qs = Blog.objects.values_list('id', 'name')
> >>> qs
> <QuerySet [(1, 'Beatles Blog')]>
> >>> reloaded_qs = Blog.objects.all()
> >>> reloaded_qs.query = pickle.loads(pickle.dumps(qs.query))
> >>> reloaded_qs
> <QuerySet [{'id': 1, 'name': 'Beatles Blog'}]>
> ```

> **バージョン間でpickle化されたデータを共有することはできません**
>
> `QuerySets` をpickle化したデータは、生成したDjangoの同一バージョンでのみ有効です。DjangoのバージョンNで生成したデータをバージョンN+1でも正常に読み込める保証はありません。Pickle化は長期的なアーカイブ戦略の手段として用いるべきではありません。
>
> pickle の互換性エラーは、静的に衝突したオブジェクトのように判定が難しいことがあるので、モデルをpickle化したデータを別のバージョンで復元しようとすると `RuntimeWarning` が送出されます。

## `QuerySet` API

これが `QuerySet` の正式な宣言です:

#### `class QuerySet(model=None, query=None, using=None, hints=None)`

通常、 `QuerySet` を操作する際には [chaining filters](/ja/4.1/topics/db/queries/#chaining-filters) を使用します。これを実現するために、ほとんどの `QuerySet` のメソッドは新たなクエリセットを返します。これらのメソッドについては、このセクションで後ほど詳しく説明します。

`QuerySet` クラスは、イントロスペクションのために以下のパブリックな属性を持っています:

#### `ordered`

`QuerySet` が [`order_by()`](#django.db.models.query.QuerySet.order_by) やモデルのデフォルトの順序指定によって並び替えられた場合に `True` となります。それ以外のときは `False` になります。

#### `db`

このクエリが実行されるデータベースを示します。

> **Note**
>
> [`QuerySet`](#django.db.models.query.QuerySet) の `query` パラメータは、特殊なクエリのサブクラスが内部のクエリ状態を再構築できるようにするために存在します。このパラメータの値はクエリの状態の不透明な表現であり、パブリックAPIの一部ではありません。

### 新しい `QuerySet`s を返すメソッド

`QuerySet` が返す結果の種類や、SQLクエリの実行方法を変更するための、さまざまな `QuerySet` の改良メソッドをDjangoは提供します。

> **Note**
>
> これらのメソッドはデータベースクエリを実行しないので、非同期コードで実行しても **安全** であり、非同期処理専用のメソッドは存在しません。

#### `filter()`

#### `filter(*args, **kwargs)`

与えられた検索パラメータにマッチする新しい `QuerySet` を返します。

検索パラメータ (`**kwargs`) は以下の [Field lookups](#id4) で説明されているフォーマットに従わなければなりません。複数のパラメータは、元となるSQLステートメントでは `AND` によって結合されます。

より複雑なクエリを実行したい場合(たとえば  `OR` ステートメントを含むクエリ)は、  [`Q objects`](#django.db.models.Q) (`*args`) を使用してください。

#### `exclude()`

#### `exclude(*args, **kwargs)`

与えられた検索パラメータにマッチ *しない* 新しい `QuerySet` を返します。

検索パラメータ (`**kwargs`) は以下の [Field lookups](#id4) で説明されているフォーマットに従わなければなりません。複数のパラメータは、元となるSQLステートメントでは `AND` によって結合され、全体が `NOT()` によって囲まれます。

この例では `pub_date` が 2005-1-3より新しく、 `headline` が "Hello" であるようなエントリーを除外しています:

```
Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3), headline='Hello')
```

SQL文では、次のように評価されます:

```sql
SELECT ...
WHERE NOT (pub_date > '2005-1-3' AND headline = 'Hello')
```

この例では `pub_date` が 2005-1-3より新しいか、 `headline` が "Hello" であるようなエントリーを除外しています:

```
Entry.objects.exclude(pub_date__gt=datetime.date(2005, 1, 3)).exclude(headline='Hello')
```

SQL文では、次のように評価されます:

```sql
SELECT ...
WHERE NOT pub_date > '2005-1-3'
AND NOT headline = 'Hello'
```

2つ目の例の方が、制約がより強いことに留意してください。

より複雑なクエリを実行したい場合(たとえば  `OR` ステートメントを含むクエリ)は、  [`Q objects`](#django.db.models.Q) (`*args`) を使用してください。

#### `annotate()`

#### `annotate(*args, **kwargs)`

[query expressions](/ja/4.1/ref/models/expressions/) で提供されるリストに従い、 `QuerySet` の各オブジェクトに集計情報を付加します。式としては、シンプルな値、モデル(または関連モデル)のフィールド参照、あるいは `QuerySet` 内のオブジェクトに関連するオブジェクトに対して計算された集計式(平均、合計など)が含まれます。

`annotate()` の引数は、それぞれが返り値となる `QuerySet` 内の各オブジェクトに追加される集計情報となります。

Djangoが提供する集計関数については、 [Aggregation Functions](#id6) で説明されています。

キーワード引数を用いて集計情報を定義した場合、キーワードが集計情報のエイリアスとして用いられます。位置引数を用いた場合、使用した集計関数と集計されるモデルフィールドの名前に基づいてエイリアスが生成されます。単一のフィールドを参照する集計式であれば位置引数を利用できます。それ以外のすべての集計式は、キーワード引数を用いなくてはなりません。

たとえば、ブログのリストを操作しているときに、ブログごとのエントリー数を決定したいとします:

```
>>> from django.db.models import Count
>>> q = Blog.objects.annotate(Count('entry'))
# The name of the first blog
>>> q[0].name
'Blogasaurus'
# The number of entries on the first blog
>>> q[0].entry__count
42
```

`Blog` モデル自体は `entry__count` 属性を定義しませんが、集計式を指定したキーワード引数を用いることで、集計情報の名前を制御できます:

```
>>> q = Blog.objects.annotate(number_of_entries=Count('entry'))
# The number of entries on the first blog, using the name provided
>>> q[0].number_of_entries
42
```

集計処理についての深い議論については、 [the topic guide on Aggregation](/ja/4.1/topics/db/aggregation/) を確認してください。

#### `alias()`

#### `alias(*args, **kwargs)`

[`annotate()`](#django.db.models.query.QuerySet.annotate) と同じですが、 `QuerySet` にオブジェクトをアノテーションするかわりに、後で他の `QuerySet` メソッドで再利用できるように式を保存します。これは式の結果自体は必要ないが、フィルタリングやソート、あるいは複雑な式の一部として利用する場合に便利です。未使用の値を選択しないことで、データベースで冗長な処理を行わずに済み、結果的にパフォーマンスを向上させることができます。

For example, if you want to find blogs with more than 5 entries, but are not
interested in the exact number of entries, you could do this:

```
>>> from django.db.models import Count
>>> blogs = Blog.objects.alias(entries=Count('entry')).filter(entries__gt=5)
```

`alias()` は [`annotate()`](#django.db.models.query.QuerySet.annotate), [`exclude()`](#django.db.models.query.QuerySet.exclude), [`filter()`](#django.db.models.query.QuerySet.filter), [`order_by()`](#django.db.models.query.QuerySet.order_by), [`update()`](#django.db.models.query.QuerySet.update) と組み合わせて使用することができます。エイリアス式をその他のメソッド([`aggregate()`](#django.db.models.query.QuerySet.aggregate) など)と組み合わせるためには、アノテーションを用いる必要があります

```
Blog.objects.alias(entries=Count('entry')).annotate(
    entries=F('entries'),
).aggregate(Sum('entries'))
```

[`filter()`](#django.db.models.query.QuerySet.filter) と [`order_by()`](#django.db.models.query.QuerySet.order_by) は式を直接受け取ることができますが、式の構築と評価は同じ場所では行われないことが多いです(例えば、 `QuerySet` メソッドは式を作成し、後からビューを表示するときに使用されるため)。 `alias()` は、複数のメソッドやモジュールにまたがる複雑な式を段階的に構築することができ、式の部分をエイリアスで参照し、さいしゅうけっかにたいしてのみ [`annotate()`](#django.db.models.query.QuerySet.annotate) を使用する、といった使い方ができます。

#### `order_by()`

#### `order_by(*fields)`

デフォルトでは、 `QuerySet` の返り値はモデルの `Meta` 内の `ordering` オプションで指定されたタプルに基づいて並び替えられます。 `order_by` メソッドを使うことで、 `QuerySet` ごとにこれをオーバーライドすることができます。

実装例:

```
Entry.objects.filter(pub_date__year=2005).order_by('-pub_date', 'headline')
```

上のコードの結果は `pub_date` の降順、次に `headline` の昇順で並び替えられます。 `"-pub_date"` のように、前にマイナス符号をつけることで降順を表現します。昇順は暗黙的に表現されます。ランダムに並び替えたい場合、次のように `"?"` を使います:

```
Entry.objects.order_by('?')
```

メモ: `order_by('?')` クエリは、使用するデータベースバックエンドによっては高負荷で遅くなる可能性があります。

異なるモデルのフィールドで並び替えたい場合、モデル間を横断して参照するクエリを発行するときと同じ構文を使用します。すなわち、フィールド名の後にダブルアンダースコア(`__`)を続けて、その後に新たなモデルのフィールド名を続けます。そして、それを結合したいモデルの数だけ繰り返します。例えば:

```
Entry.objects.order_by('blog__name', 'headline')
```

異なるモデルを参照するフィールドで並び替えるとき、Djangoは参照先のモデルのデフォルトの順序を用いますが、 [`Meta.ordering`](/ja/4.1/ref/models/options/#django.db.models.Options.ordering) が設定されていなければ参照先のモデルのプライマリーキーで並び替えます。たとえば、 `Blog` モデルにはデフォルトで設定された順序がないとき:

```
Entry.objects.order_by('blog')
```

...は以下と同じです:

```
Entry.objects.order_by('blog__id')
```

`Blog` が `ordering = ['name']` を保持している場合、最初のクエリセットは以下と同じになります:

```
Entry.objects.order_by('blog__name')
```

[`asc()`](/ja/4.1/ref/models/expressions/#django.db.models.Expression.asc) か [`desc()`](/ja/4.1/ref/models/expressions/#django.db.models.Expression.desc) を式中で呼び出すことで、 [query expressions](/ja/4.1/ref/models/expressions/) を使うこともできます:

```
Entry.objects.order_by(Coalesce('summary', 'headline').desc())
```

[`asc()`](/ja/4.1/ref/models/expressions/#django.db.models.Expression.asc) と [`desc()`](/ja/4.1/ref/models/expressions/#django.db.models.Expression.desc) は、null値をどのようにソートするかを制御する引数 (`nulls_first` と `nulls_last`)をとります。

モデル参照フィールドによる並び替えと同時に [`distinct()`](#django.db.models.query.QuerySet.distinct) を使用する際は注意してください。参照先のモデルの順序によって、期待される結果がどのように変化するかについては、 [`distinct()`](#django.db.models.query.QuerySet.distinct)  の注記を確認してください。

> **Note**
>
> 複数の値をとりうるフィールドを指定し、結果を並び替えることは許されています(たとえば、 [`ManyToManyField`](/ja/4.1/ref/models/fields/#django.db.models.ManyToManyField) フィールド、もしくは [`ForeignKey`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey) フィールドの逆参照など)。
>
> このケースを考えます:
>
> ```
> class Event(Model):
>    parent = models.ForeignKey(
>        'self',
>        on_delete=models.CASCADE,
>        related_name='children',
>    )
>    date = models.DateField()
>
> Event.objects.order_by('children__date')
> ```
>
> ここで、それぞれの `Event` に対して、複数の並べ替えデータが存在する可能性があります; 複数の `children` を伴う `Event` は、`order_by()` が作る新たな `QuerySet` においてそれぞれ複数回返されることになります。言い換えれば、 `QuerySet` で `order_by()` を使うことで、もともと作業していたよりも多くの項目を返してしまう可能性があります。これはおそらく予期されることはなく、有用でもないでしょう。
>
> 従って、複数の値をとりうるフィールドを結果の並び替えに用いる際は気を付けてください。 **もし仮に** 並び替える項目ごとに1つのデータしか存在しないのであれば、この方法でも問題はないでしょう。そうでなければ、結果が期待通りになることを確認してください。

大文字と小文字を区別して並べ替えるかどうかを指定することはできません。Djangoは使用するデータベースバックエンドが通常このCase-sensitiveをどのように扱うかに従って結果を並び替えます。

[`Lower`](/ja/4.1/ref/models/database-functions/#django.db.models.functions.Lower) によって小文字に変換したフィールドで並び替えることで、一貫したルールでの並び替えを実現できます:

```
Entry.objects.order_by(Lower('headline').desc())
```

クエリに対し、デフォルトの順序付けも含めて並び替えを適用したくない場合、パラメータを指定せずに [`order_by()`](#django.db.models.query.QuerySet.order_by) を呼び出してください。

クエリに並び替えが適用されたかどうかは、 [`QuerySet.ordered`](#django.db.models.query.QuerySet.ordered) 属性を確認することで知ることができます。 `QuerySet` がなんらかの方法で並び替えられれば、この属性の値は `True` となります。

`order_by()` の呼び出しごとに、過去の並び替えは解除されます。たとえば、以下のクエリでは並び替えに `pub_date` が使われ、 `headline` は使われません:

```
Entry.objects.order_by('headline').order_by('pub_date')
```

> **Warning**
>
> 並べ替えは自由な操作ではありません。並べ替えの条件にフィールドを指定するたびに、データベースへのコストが発生します。指定した外部キーは、すべてのデフォルトの並べ替え条件を暗黙のうちに含んでいます。
>
> クエリに順序の指定が含まれていなければ、順序が指定されない状態の結果がデータベースから返されます。特定の順序が保証されるのは、結果内の各オブジェクトを、一意に識別するフィールドの組み合わせで順序を指定した場合のみです。例えば、 `name` フィールドが一意でない場合、そのフィールドで順序を決めても、同じ名前を持つオブジェクトが常に同じ順序で表示されることは保証されません。

#### `reverse()`

#### `reverse()`

`reverse()` メソッドを使用すると、クエリセットの要素を返す順序を逆にすることができます。再度 `reverse()` を呼び出すと、順序が元に戻ります。

クエリセットの「最後の」5つの項目を取り出すには、次のようにします:

```
my_queryset.reverse()[:5]
```

この処理がPythonでシーケンスの最後からスライスするのとは全く違うことに注意してください。上記の例では、まず最後の項目が返され、次に最後から5番目の項目が返されます。Python のシーケンスに対して `seq[-5:]` を参照すると、最後の 5 番目の項目が最初に表示されるはずです。そのようなアクセスモード (末尾からのスライス) は、SQL で効率的に行うことができないため、Django ではサポートされていません。

また、一般的に `reverse()` は、順序が定義されている `QuerySet` に対してのみ呼び出すべきであることに注意してください(例えば、デフォルトの順序を定義しているモデルに対するクエリや、 ```order_by() `を使用する場合など)。もし、ある ``QuerySet`()``` に対してそのような順序が定義されていない場合、 `reverse()` を呼び出しても何の効果もありません(順序は `reverse()` を呼び出す前から未定義であり、その後も未定義のままです)。

#### `distinct()`

#### `distinct(*fields)`

SQL クエリで `SELECT DISTINCT` を使用した新しい `QuerySet` を返します。これにより、クエリ結果から重複した行を取り除くことができます。

デフォルトでは、 `QuerySet` は重複した行を削除しません。なぜなら、 `Blog.objects.all()` のような単純なクエリでは、結果の行が重複する可能性はないからです。しかし、クエリが複数のテーブルにまたがっている場合、 `QuerySet` が評価されたときに重複した結果を得る可能性があります。このような場合は `distinct()` を使用します。

> **Note**
>
> meth:order\_by の呼び出しで使用されるフィールドはすべて、SQL の `SELECT` 列に含まれます。これは `distinct()` と組み合わせて使用すると、時に予期せぬ結果をもたらすことがあります。関連するモデルのフィールドでソートした場合、それらのフィールドが `SELECT` の対象に追加され、重複した行が重複していないように出力されるかもしれません。余分なカラムは返される結果には現れないので (カラムは順序付けをサポートするためだけに存在するため)、重複した結果が返されているように見えることがあります。
>
> 同様に、 [`values()`](#django.db.models.query.QuerySet.values) クエリを使用して選択するカラムを制限した場合、 [`order_by()`](#django.db.models.query.QuerySet.order_by) （またはデフォルトのモデルの順序付け）で使用したカラムが残存し、結果の一意性に影響する可能性があります。
>
> この問題の解決策は、distinct() を使用する場合、関連するモデルによる順序付けに注意することです。同様に、distinct() と ``values() `()`` を一緒に使う場合、 ``values() `()`` の呼び出しに含まれないフィールドによる順序付けに注意する必要があります。

PostgreSQL のみ、位置引数 (`*fields`) を渡して、 `DISTINCT` を適用するフィールドの名前を指定することができます。これは `SELECT DISTINCT ON` というSQLクエリに相当します。通常の `distinct()` 呼び出しでは、データベースはどの行が区別されるかを判断する際に、各行の *each* フィールドを比較しますが、フィールド名を指定した `distinct()` の呼び出しでは、データベースは指定されたフィールド名のみを比較することができます。

> **Note**
>
> フィールド名を指定する場合、`QuerySet` に `order_by()` を指定する必要があり、 `order_by()` のフィールドは `distinct()` のフィールドと同じ順序で始まる必要があります。
>
> 例えば、`SELECT DISTINCT ON (a)` とすると、列 `a` の各値の最初の行が得られます。もし順序を指定しなければ、任意の行を得ることができます。

例を示します(1行目以外はPostgreSQLでのみ動作します)

```
>>> Author.objects.distinct()
[...]

>>> Entry.objects.order_by('pub_date').distinct('pub_date')
[...]

>>> Entry.objects.order_by('blog').distinct('blog')
[...]

>>> Entry.objects.order_by('author', 'pub_date').distinct('author', 'pub_date')
[...]

>>> Entry.objects.order_by('blog__name', 'mod_date').distinct('blog__name', 'mod_date')
[...]

>>> Entry.objects.order_by('author', 'pub_date').distinct('author')
[...]
```

> **Note**
>
> meth:order\_by は、定義されている既定の関連モデルの順序を使用することに留意してください。ORDER BY\`\` 節の先頭にある `DISTINCT ON` 式が一致するように、明示的に `_id` や参照するフィールドで順序付けする必要があるかもしれません。例えば、 `Blog` モデルが [`ordering`](/ja/4.1/ref/models/options/#django.db.models.Options.ordering) を `name`: と定義していた場合:
>
> ```
> Entry.objects.order_by('blog').distinct('blog')
> ```
>
> というのは、クエリが `blog__name` によって順序付けされるため、`DISTINCT ON` 式と不一致になって正しい結果を得られないでしょう。両方の式が一致するように、リレーションの `_id` フィールド（この場合は `blog_id` ）または参照されるフィールド（ `blog__pk` ）によって明示的に順序付けする必要があります。

#### `values()`

#### `values(*fields, **expressions)`

イテラブルオブジェクトとして使用するとき、モデルインスタンスではなく辞書を返す `QuerySet` を返します。

これらの辞書はそれぞれオブジェクトを表し、キーはモデルオブジェクトの属性名に対応しています。

この例では、`values()` によって得られる辞書と通常のモデルのオブジェクトを比較しています:

```
# This list contains a Blog object.
>>> Blog.objects.filter(name__startswith='Beatles')
<QuerySet [<Blog: Beatles Blog>]>

# This list contains a dictionary.
>>> Blog.objects.filter(name__startswith='Beatles').values()
<QuerySet [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}]>
```

values()\`\` メソッドはオプションの位置引数 `*fields` を取り、 `SELECT` で絞り込むフィールド名を指定します。フィールドを指定した場合、それぞれの辞書は指定したフィールドのキー/値のみを保有します。フィールドを指定しない場合、各ディクショナリは、データベーステーブルのすべてのフィールドのキーと値を保有します。

実装例:

```
>>> Blog.objects.values()
<QuerySet [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}]>
>>> Blog.objects.values('id', 'name')
<QuerySet [{'id': 1, 'name': 'Beatles Blog'}]>
```

```values() ``メソッドはオプションでキーワード引数 ``**expressions``` を受け取り、 [`annotate()`](#django.db.models.query.QuerySet.annotate): に渡すこともできます:

```
>>> from django.db.models.functions import Lower
>>> Blog.objects.values(lower_name=Lower('name'))
<QuerySet [{'lower_name': 'beatles blog'}]>
```

ソートには、ビルトインのルックアップまたは :doc:カスタムルックアップ \</howto/custom-lookups\> \` を使用することができます。例えば、次のようになります：

```
>>> from django.db.models import CharField
>>> from django.db.models.functions import Lower
>>> CharField.register_lookup(Lower)
>>> Blog.objects.values('name__lower')
<QuerySet [{'name__lower': 'beatles blog'}]>
```

An aggregate within a `values()` clause is applied before other arguments
within the same `values()` clause. If you need to group by another value,
add it to an earlier `values()` clause instead. For example:

```
>>> from django.db.models import Count
>>> Blog.objects.values('entry__authors', entries=Count('entry'))
<QuerySet [{'entry__authors': 1, 'entries': 20}, {'entry__authors': 1, 'entries': 13}]>
>>> Blog.objects.values('entry__authors').annotate(entries=Count('entry'))
<QuerySet [{'entry__authors': 1, 'entries': 33}]>
```

A few subtleties that are worth mentioning:

- If you have a field called `foo` that is a
  [`ForeignKey`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey), the default `values()` call
  will return a dictionary key called `foo_id`, since this is the name
  of the hidden model attribute that stores the actual value (the `foo`
  attribute refers to the related model). When you are calling
  `values()` and passing in field names, you can pass in either `foo`
  or `foo_id` and you will get back the same thing (the dictionary key
  will match the field name you passed in).

  例:

  ```
  >>> Entry.objects.values()
  <QuerySet [{'blog_id': 1, 'headline': 'First Entry', ...}, ...]>

  >>> Entry.objects.values('blog')
  <QuerySet [{'blog': 1}, ...]>

  >>> Entry.objects.values('blog_id')
  <QuerySet [{'blog_id': 1}, ...]>
  ```
- When using `values()` together with [`distinct()`](#django.db.models.query.QuerySet.distinct), be aware that
  ordering can affect the results. See the note in [`distinct()`](#django.db.models.query.QuerySet.distinct) for
  details.
- If you use a `values()` clause after an [`extra()`](#django.db.models.query.QuerySet.extra) call,
  any fields defined by a `select` argument in the [`extra()`](#django.db.models.query.QuerySet.extra) must
  be explicitly included in the `values()` call. Any [`extra()`](#django.db.models.query.QuerySet.extra) call
  made after a `values()` call will have its extra selected fields
  ignored.
- Calling [`only()`](#django.db.models.query.QuerySet.only) and [`defer()`](#django.db.models.query.QuerySet.defer) after `values()` doesn't make
  sense, so doing so will raise a `TypeError`.
- Combining transforms and aggregates requires the use of two [`annotate()`](#django.db.models.query.QuerySet.annotate)
  calls, either explicitly or as keyword arguments to [`values()`](#django.db.models.query.QuerySet.values). As above,
  if the transform has been registered on the relevant field type the first
  [`annotate()`](#django.db.models.query.QuerySet.annotate) can be omitted, thus the following examples are equivalent:

  ```
  >>> from django.db.models import CharField, Count
  >>> from django.db.models.functions import Lower
  >>> CharField.register_lookup(Lower)
  >>> Blog.objects.values('entry__authors__name__lower').annotate(entries=Count('entry'))
  <QuerySet [{'entry__authors__name__lower': 'test author', 'entries': 33}]>
  >>> Blog.objects.values(
  ...     entry__authors__name__lower=Lower('entry__authors__name')
  ... ).annotate(entries=Count('entry'))
  <QuerySet [{'entry__authors__name__lower': 'test author', 'entries': 33}]>
  >>> Blog.objects.annotate(
  ...     entry__authors__name__lower=Lower('entry__authors__name')
  ... ).values('entry__authors__name__lower').annotate(entries=Count('entry'))
  <QuerySet [{'entry__authors__name__lower': 'test author', 'entries': 33}]>
  ```

It is useful when you know you're only going to need values from a small number
of the available fields and you won't need the functionality of a model
instance object. It's more efficient to select only the fields you need to use.

Finally, note that you can call `filter()`, `order_by()`, etc. after the
`values()` call, that means that these two calls are identical:

```
Blog.objects.values().order_by('id')
Blog.objects.order_by('id').values()
```

The people who made Django prefer to put all the SQL-affecting methods first,
followed (optionally) by any output-affecting methods (such as `values()`),
but it doesn't really matter. This is your chance to really flaunt your
individualism.

You can also refer to fields on related models with reverse relations through
`OneToOneField`, `ForeignKey` and `ManyToManyField` attributes:

```
>>> Blog.objects.values('name', 'entry__headline')
<QuerySet [{'name': 'My blog', 'entry__headline': 'An entry'},
     {'name': 'My blog', 'entry__headline': 'Another entry'}, ...]>
```

> **Warning**
>
> Because [`ManyToManyField`](/ja/4.1/ref/models/fields/#django.db.models.ManyToManyField) attributes and reverse
> relations can have multiple related rows, including these can have a
> multiplier effect on the size of your result set. This will be especially
> pronounced if you include multiple such fields in your `values()` query,
> in which case all possible combinations will be returned.

> **Special values for JSONField on SQLite**
>
> Due to the way the `JSON_EXTRACT` and `JSON_TYPE` SQL functions are
> implemented on SQLite, and lack of the `BOOLEAN` data type,
> `values()` will return `True`, `False`, and `None` instead of
> `"true"`, `"false"`, and `"null"` strings for
> [`JSONField`](/ja/4.1/ref/models/fields/#django.db.models.JSONField) key transforms.

#### `values_list()`

#### `values_list(*fields, flat=False, named=False)`

This is similar to `values()` except that instead of returning dictionaries,
it returns tuples when iterated over. Each tuple contains the value from the
respective field or expression passed into the `values_list()` call — so the
first item is the first field, etc. For example:

```
>>> Entry.objects.values_list('id', 'headline')
<QuerySet [(1, 'First entry'), ...]>
>>> from django.db.models.functions import Lower
>>> Entry.objects.values_list('id', Lower('headline'))
<QuerySet [(1, 'first entry'), ...]>
```

If you only pass in a single field, you can also pass in the `flat`
parameter. If `True`, this will mean the returned results are single values,
rather than one-tuples. An example should make the difference clearer:

```
>>> Entry.objects.values_list('id').order_by('id')
<QuerySet[(1,), (2,), (3,), ...]>

>>> Entry.objects.values_list('id', flat=True).order_by('id')
<QuerySet [1, 2, 3, ...]>
```

It is an error to pass in `flat` when there is more than one field.

You can pass `named=True` to get results as a
[`namedtuple()`](https://docs.python.org/3/library/collections.html#collections.namedtuple):

```
>>> Entry.objects.values_list('id', 'headline', named=True)
<QuerySet [Row(id=1, headline='First entry'), ...]>
```

Using a named tuple may make use of the results more readable, at the expense
of a small performance penalty for transforming the results into a named tuple.

If you don't pass any values to `values_list()`, it will return all the
fields in the model, in the order they were declared.

A common need is to get a specific field value of a certain model instance. To
achieve that, use `values_list()` followed by a `get()` call:

```
>>> Entry.objects.values_list('headline', flat=True).get(pk=1)
'First entry'
```

`values()` and `values_list()` are both intended as optimizations for a
specific use case: retrieving a subset of data without the overhead of creating
a model instance. This metaphor falls apart when dealing with many-to-many and
other multivalued relations (such as the one-to-many relation of a reverse
foreign key) because the "one row, one object" assumption doesn't hold.

For example, notice the behavior when querying across a
[`ManyToManyField`](/ja/4.1/ref/models/fields/#django.db.models.ManyToManyField):

```
>>> Author.objects.values_list('name', 'entry__headline')
<QuerySet [('Noam Chomsky', 'Impressions of Gaza'),
 ('George Orwell', 'Why Socialists Do Not Believe in Fun'),
 ('George Orwell', 'In Defence of English Cooking'),
 ('Don Quixote', None)]>
```

Authors with multiple entries appear multiple times and authors without any
entries have `None` for the entry headline.

Similarly, when querying a reverse foreign key, `None` appears for entries
not having any author:

```
>>> Entry.objects.values_list('authors')
<QuerySet [('Noam Chomsky',), ('George Orwell',), (None,)]>
```

> **Special values for JSONField on SQLite**
>
> Due to the way the `JSON_EXTRACT` and `JSON_TYPE` SQL functions are
> implemented on SQLite, and lack of the `BOOLEAN` data type,
> `values_list()` will return `True`, `False`, and `None` instead of
> `"true"`, `"false"`, and `"null"` strings for
> [`JSONField`](/ja/4.1/ref/models/fields/#django.db.models.JSONField) key transforms.

#### `dates()`

#### `dates(field, kind, order='ASC')`

Returns a `QuerySet` that evaluates to a list of [`datetime.date`](https://docs.python.org/3/library/datetime.html#datetime.date)
objects representing all available dates of a particular kind within the
contents of the `QuerySet`.

`field` should be the name of a `DateField` of your model.
`kind` should be either `"year"`, `"month"`, `"week"`, or `"day"`.
Each [`datetime.date`](https://docs.python.org/3/library/datetime.html#datetime.date) object in the result list is "truncated" to the
given `type`.

- `"year"` returns a list of all distinct year values for the field.
- `"month"` returns a list of all distinct year/month values for the
  field.
- `"week"` returns a list of all distinct year/week values for the field. All
  dates will be a Monday.
- `"day"` returns a list of all distinct year/month/day values for the
  field.

`order`, which defaults to `'ASC'`, should be either `'ASC'` or
`'DESC'`. This specifies how to order the results.

例:

```
>>> Entry.objects.dates('pub_date', 'year')
[datetime.date(2005, 1, 1)]
>>> Entry.objects.dates('pub_date', 'month')
[datetime.date(2005, 2, 1), datetime.date(2005, 3, 1)]
>>> Entry.objects.dates('pub_date', 'week')
[datetime.date(2005, 2, 14), datetime.date(2005, 3, 14)]
>>> Entry.objects.dates('pub_date', 'day')
[datetime.date(2005, 2, 20), datetime.date(2005, 3, 20)]
>>> Entry.objects.dates('pub_date', 'day', order='DESC')
[datetime.date(2005, 3, 20), datetime.date(2005, 2, 20)]
>>> Entry.objects.filter(headline__contains='Lennon').dates('pub_date', 'day')
[datetime.date(2005, 3, 20)]
```

#### `datetimes()`

#### `datetimes(field_name, kind, order='ASC', tzinfo=None, is_dst=None)`

Returns a `QuerySet` that evaluates to a list of [`datetime.datetime`](https://docs.python.org/3/library/datetime.html#datetime.datetime)
objects representing all available dates of a particular kind within the
contents of the `QuerySet`.

`field_name` should be the name of a `DateTimeField` of your model.

`kind` should be either `"year"`, `"month"`, `"week"`, `"day"`,
`"hour"`, `"minute"`, or `"second"`. Each [`datetime.datetime`](https://docs.python.org/3/library/datetime.html#datetime.datetime)
object in the result list is "truncated" to the given `type`.

`order`, which defaults to `'ASC'`, should be either `'ASC'` or
`'DESC'`. This specifies how to order the results.

`tzinfo` defines the time zone to which datetimes are converted prior to
truncation. Indeed, a given datetime has different representations depending
on the time zone in use. This parameter must be a [`datetime.tzinfo`](https://docs.python.org/3/library/datetime.html#datetime.tzinfo)
object. If it's `None`, Django uses the [current time zone](/ja/4.1/topics/i18n/timezones/#default-current-time-zone). It has no effect when [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is
`False`.

`is_dst` indicates whether or not `pytz` should interpret nonexistent and
ambiguous datetimes in daylight saving time. By default (when `is_dst=None`),
`pytz` raises an exception for such datetimes.

> **Deprecated since Django 4.0**
>
> バージョン 4.0 で非推奨: The `is_dst` parameter is deprecated and will be removed in Django 5.0.

> **Note**
>
> This function performs time zone conversions directly in the database.
> As a consequence, your database must be able to interpret the value of
> `tzinfo.tzname(None)`. This translates into the following requirements:
>
> - SQLite: no requirements. Conversions are performed in Python.
> - PostgreSQL: no requirements (see [Time Zones](https://www.postgresql.org/docs/current/datatype-datetime.html#DATATYPE-TIMEZONES)).
> - Oracle: no requirements (see [Choosing a Time Zone File](https://docs.oracle.com/en/database/oracle/oracle-database/18/nlspg/datetime-data-types-and-time-zone-support.html#GUID-805AB986-DE12-4FEA-AF56-5AABCD2132DF)).
> - MySQL: load the time zone tables with [mysql\_tzinfo\_to\_sql](https://dev.mysql.com/doc/refman/en/mysql-tzinfo-to-sql.html).

#### `none()`

#### `none()`

Calling `none()` will create a queryset that never returns any objects and no
query will be executed when accessing the results. A `qs.none()` queryset
is an instance of `EmptyQuerySet`.

例:

```
>>> Entry.objects.none()
<QuerySet []>
>>> from django.db.models.query import EmptyQuerySet
>>> isinstance(Entry.objects.none(), EmptyQuerySet)
True
```

#### `all()`

#### `all()`

Returns a *copy* of the current `QuerySet` (or `QuerySet` subclass).  This
can be useful in situations where you might want to pass in either a model
manager or a `QuerySet` and do further filtering on the result. After calling
`all()` on either object, you'll definitely have a `QuerySet` to work with.

`QuerySet` が [評価される](#when-querysets-are-evaluated) とき、通常その結果はキャッシュされます。もし `QuerySet` が評価された後にデータベースのデータが更新された場合、以前に評価された  `QuerySet` に対して\`\`all()\`\` を呼び出すことで、同じクエリの最新の結果を取得することができます。

#### `union()`

#### `union(*other_qs, all=False)`

Uses SQL's `UNION` operator to combine the results of two or more
`QuerySet`s. For example:

```
>>> qs1.union(qs2, qs3)
```

The `UNION` operator selects only distinct values by default. To allow
duplicate values, use the `all=True` argument.

`union()`, `intersection()`, and `difference()` return model instances
of the type of the first `QuerySet` even if the arguments are `QuerySet`s
of other models. Passing different models works as long as the `SELECT` list
is the same in all `QuerySet`s (at least the types, the names don't matter
as long as the types are in the same order). In such cases, you must use the
column names from the first `QuerySet` in `QuerySet` methods applied to the
resulting `QuerySet`. For example:

```
>>> qs1 = Author.objects.values_list('name')
>>> qs2 = Entry.objects.values_list('headline')
>>> qs1.union(qs2).order_by('name')
```

In addition, only `LIMIT`, `OFFSET`, `COUNT(*)`, `ORDER BY`, and
specifying columns (i.e. slicing, [`count()`](#django.db.models.query.QuerySet.count), [`exists()`](#django.db.models.query.QuerySet.exists),
[`order_by()`](#django.db.models.query.QuerySet.order_by), and [`values()`](#django.db.models.query.QuerySet.values)/[`values_list()`](#django.db.models.query.QuerySet.values_list)) are allowed
on the resulting `QuerySet`. Further, databases place restrictions on
what operations are allowed in the combined queries. For example, most
databases don't allow `LIMIT` or `OFFSET` in the combined queries.

#### `intersection()`

#### `intersection(*other_qs)`

Uses SQL's `INTERSECT` operator to return the shared elements of two or more
`QuerySet`s. For example:

```
>>> qs1.intersection(qs2, qs3)
```

See [`union()`](#django.db.models.query.QuerySet.union) for some restrictions.

#### `difference()`

#### `difference(*other_qs)`

Uses SQL's `EXCEPT` operator to keep only elements present in the
`QuerySet` but not in some other `QuerySet`s. For example:

```
>>> qs1.difference(qs2, qs3)
```

See [`union()`](#django.db.models.query.QuerySet.union) for some restrictions.

#### `select_related()`

#### `select_related(*fields)`

Returns a `QuerySet` that will "follow" foreign-key relationships, selecting
additional related-object data when it executes its query. This is a
performance booster which results in a single more complex query but means
later use of foreign-key relationships won't require database queries.

The following examples illustrate the difference between plain lookups and
`select_related()` lookups. Here's standard lookup:

```
# Hits the database.
e = Entry.objects.get(id=5)

# Hits the database again to get the related Blog object.
b = e.blog
```

And here's `select_related` lookup:

```
# Hits the database.
e = Entry.objects.select_related('blog').get(id=5)

# Doesn't hit the database, because e.blog has been prepopulated
# in the previous query.
b = e.blog
```

You can use `select_related()` with any queryset of objects:

```
from django.utils import timezone

# Find all the blogs with entries scheduled to be published in the future.
blogs = set()

for e in Entry.objects.filter(pub_date__gt=timezone.now()).select_related('blog'):
    # Without select_related(), this would make a database query for each
    # loop iteration in order to fetch the related blog for each entry.
    blogs.add(e.blog)
```

The order of `filter()` and `select_related()` chaining isn't important.
These querysets are equivalent:

```
Entry.objects.filter(pub_date__gt=timezone.now()).select_related('blog')
Entry.objects.select_related('blog').filter(pub_date__gt=timezone.now())
```

You can follow foreign keys in a similar way to querying them. If you have the
following models:

```
from django.db import models

class City(models.Model):
    # ...
    pass

class Person(models.Model):
    # ...
    hometown = models.ForeignKey(
        City,
        on_delete=models.SET_NULL,
        blank=True,
        null=True,
    )

class Book(models.Model):
    # ...
    author = models.ForeignKey(Person, on_delete=models.CASCADE)
```

... then a call to `Book.objects.select_related('author__hometown').get(id=4)`
will cache the related `Person` *and* the related `City`:

```
# Hits the database with joins to the author and hometown tables.
b = Book.objects.select_related('author__hometown').get(id=4)
p = b.author         # Doesn't hit the database.
c = p.hometown       # Doesn't hit the database.

# Without select_related()...
b = Book.objects.get(id=4)  # Hits the database.
p = b.author         # Hits the database.
c = p.hometown       # Hits the database.
```

You can refer to any [`ForeignKey`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey) or
[`OneToOneField`](/ja/4.1/ref/models/fields/#django.db.models.OneToOneField) relation in the list of fields
passed to `select_related()`.

You can also refer to the reverse direction of a
[`OneToOneField`](/ja/4.1/ref/models/fields/#django.db.models.OneToOneField) in the list of fields passed to
`select_related` — that is, you can traverse a
[`OneToOneField`](/ja/4.1/ref/models/fields/#django.db.models.OneToOneField) back to the object on which the field
is defined. Instead of specifying the field name, use the [`related_name`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey.related_name) for the field on the related object.

There may be some situations where you wish to call `select_related()` with a
lot of related objects, or where you don't know all of the relations. In these
cases it is possible to call `select_related()` with no arguments. This will
follow all non-null foreign keys it can find - nullable foreign keys must be
specified. This is not recommended in most cases as it is likely to make the
underlying query more complex, and return more data, than is actually needed.

If you need to clear the list of related fields added by past calls of
`select_related` on a `QuerySet`, you can pass `None` as a parameter:

```
>>> without_relations = queryset.select_related(None)
```

Chaining `select_related` calls works in a similar way to other methods -
that is that `select_related('foo', 'bar')` is equivalent to
`select_related('foo').select_related('bar')`.

#### `prefetch_related()`

#### `prefetch_related(*lookups)`

`QuerySet` を返し、単一のバッチで、指定した検索それぞれに対して関連するオブジェクトを自動的に取り出します。

目的は `select_related` と似ていて、関連オブジェクトにアクセスすることで多量のデータベースクエリが発生してしまうのを防ぐために作られていますが、その手段が異なります。

`select_related` は、SQL の結合を生成して `SELECT` 句に関連オブジェクトを含むことでクエリ発行を抑制します。このため、`select_related` は同一のデータベースクエリ内で関連オブジェクトを取得します。しかしながら、'多量の' リレーションシップを結合することで非常に大きな結果になってしまうのを防ぐため、`select_related` は単一値のリレーションシップ - つまり外部キーと一対一 - のみに制限されています。

`prefetch_related` はこれとは異なり、各リレーションシップに対して別々に検索を行い、Python で '結合’ を行います。これにより、`select_related` で可能な外部キーおよび一対一のリレーションシップだけでなく、多対多および多対一のオブジェクトも事前に読み込んでおけるようになります。また、[`GenericRelation`](/ja/4.1/ref/contrib/contenttypes/#django.contrib.contenttypes.fields.GenericRelation) や [`GenericForeignKey`](/ja/4.1/ref/contrib/contenttypes/#django.contrib.contenttypes.fields.GenericForeignKey) の事前読み込みも可能となりますが、使用できるのは結果が同種の場合に限ります。例えば、`GenericForeignKey` が参照するオブジェクトの事前読み込みは、クエリが 1 つの `ContentType` に制限されている場合のみ可能です。

例えば、以下のようなモデルがあると考えます:

```
from django.db import models

class Topping(models.Model):
    name = models.CharField(max_length=30)

class Pizza(models.Model):
    name = models.CharField(max_length=50)
    toppings = models.ManyToManyField(Topping)

    def __str__(self):
        return "%s (%s)" % (
            self.name,
            ", ".join(topping.name for topping in self.toppings.all()),
        )
```

そして以下を実行します:

```
>>> Pizza.objects.all()
["Hawaiian (ham, pineapple)", "Seafood (prawns, smoked salmon)"...
```

上記の問題点は、`Pizza.__str__()` が `self.toppings.all()` を要求するたびデータベースにクエリを発行する必要があるので、`Pizza.objects.all()` は Toppings テーブルで **すべての** Pizza `QuerySet` アイテムに対してクエリを実行することです。

`prefetch_related` を使えばわすか 2 つのクエリに削減することができます:

```
>>> Pizza.objects.prefetch_related('toppings')
```

上記は、それぞれの `Pizza` に対する `self.toppings.all()` を暗示しています; `self.toppings.all()` を呼び出すとき、アイテム取得のためいちいちデータベースに行かず、単一クエリ内で事前読み込みされた `QuerySet` キャッシュを利用します。

つまり、すべての関連するトッピングが単一のクエリで取り出され、関連する結果の事前読み込みキャッシュを持つ `QuerySet` の生成に使われます。この `QuerySet` は `self.toppings.all()` の呼び出しで使用されます。

`prefetch_related()` 内の追加クエリは `QuerySet` の評価が開始され、主クエリが実行されたときに実行されます。

モデルインスタンスのイテラブルを保持する場合は、 [`prefetch_related_objects()`](#django.db.models.prefetch_related_objects) 関数を使ってこれらインスタンスに関連する属性を事前読み込みしておくことができます。

主 `QuerySet` の結果のキャッシュと指定されたすべての関連オブジェクトは、メモリ上に完全にロードされます。これにより、クエリがデータベースで実行された後であっても必要になるまでオブジェクトをメモリに呼び出さないという一般的な `QuerySet` の動作が変わる点に注意してください。

> **Note**
>
> いつもの `QuerySet` と同じく、異なるデータベースクエリを意味するチェーンメソッドは、読み込み済みのキャッシュを無視して新たなデータベースクエリを発行します。従って、以下のように書いた場合:
>
> ```
> >>> pizzas = Pizza.objects.prefetch_related('toppings')
> >>> [list(pizza.toppings.filter(spicy=True)) for pizza in pizzas]
> ```
>
> ... `pizza.toppings.all()` が事前読み込みされたことは役に立たないことになります。`prefetch_related('toppings')` は `pizza.toppings.all()` を意味しますが、`pizza.toppings.filter()` は新しくまた異なるクエリなのです。事前読み込みキャッシュはここでは役立ちません; 実際は不要なデータベースクエリを発行することでパフォーマンス低下の原因にさえなります。なので、この機能は注意深く使用してください！
>
> また、[`related managers`](/ja/4.1/ref/models/relations/#django.db.models.fields.related.RelatedManager) で [`add()`](/ja/4.1/ref/models/relations/#django.db.models.fields.related.RelatedManager.add)、[`remove()`](/ja/4.1/ref/models/relations/#django.db.models.fields.related.RelatedManager.remove)、[`clear()`](/ja/4.1/ref/models/relations/#django.db.models.fields.related.RelatedManager.clear)、[`set()`](/ja/4.1/ref/models/relations/#django.db.models.fields.related.RelatedManager.set) といったデータベース互換のメソッドを呼び出した場合、リレーション用の事前呼び出しキャッシュはすべてクリアされます。

通常の結合構文を使って、関連フィールドの関連フィールドを行うこともできます。上記の例二以下のモデルを追加したと考えましょう:

```
class Restaurant(models.Model):
    pizzas = models.ManyToManyField(Pizza, related_name='restaurants')
    best_pizza = models.ForeignKey(Pizza, related_name='championed_by', on_delete=models.CASCADE)
```

以下は適切です:

```
>>> Restaurant.objects.prefetch_related('pizzas__toppings')
```

これはレストランに所属するすべてのピザと、これらのピザに所属するすべてのトッピングを事前読み込みします。これにより、3 つのデータベースクエリが発行されます - 一つはレストランのため、一つはピザのため、そしてもう一つはトッピングのためです。

```
>>> Restaurant.objects.prefetch_related('best_pizza__toppings')
```

これは、ベストなピザと、各レストランに対するベストなピザに対するすべてのトッピングを取得します。これは 3 つのデータベースクエリで実行されます - 一つはレストランのため、一つは 'ベストなピザ' のため、おっして一つはトッピングのためです。

The `best_pizza` relationship could also be fetched using `select_related`
to reduce the query count to 2:

```
>>> Restaurant.objects.select_related('best_pizza').prefetch_related('best_pizza__toppings')
```

事前読み込みは主クエリ (```select_related``が必要とする結合を含みます) の後に実行されるので ``best_pizza``` がすでに読み込み済みかを検査することが可能で、再度読み込まないよう処理を飛ばします。

`prefetch_related` をチェーンで呼び出すと、事前読み込みの検索を蓄積します。すべての `prefetch_related` 動作をクリアするには `None` パラメータを渡してください。

```
>>> non_prefetched = qs.prefetch_related(None)
```

`prefetch_related` を使う際の違いの一つは、一つのクエリで生成されたオブジェクトは関連した異なるオブジェクト間で共有できることです。例えば、単一の Python モデルインスタンスは、返されたオブジェクトのツリー内で複数現れることができます。これは通常、外部キーで発生します。通常、この動作は問題とはならず、むしろメモリと CPU の両方を節約します。

`prefetch_related` は `GenericForeignKey` リレーションシップの事前読み込みをサポートしますが、クエリ数はデータに依存します。`GenericForeignKey` は複数のテーブルでデータを参照できるので、すべてのアイテムに対する単一のクエリではなく各テーブルを参照するクエリが必要となります。関連する行がまだ取得されていない場合、`ContentType` テーブルで追加的なクエリが必要となります。

多くの場合 `prefetch_related` は 'IN' オペラータを使用する単一の SQL クエリを意味します。これは、大きな `QuerySet` に対して大きな 'IN' 節が生成され、データベースによってはSQL クエリの解析および実行の際にパフォーマンスの問題の原因となり得ます。利用状況に合わせて使用するよう心がけてください！

> **Changed in Django 4.1**
>
> If you use `iterator()` to run the query, `prefetch_related()`
> calls will only be observed if a value for `chunk_size` is provided.

[`Prefetch`](#django.db.models.Prefetch) オブジェクトを使って、事前呼び出しの操作をより細かくコントロールできます。

`Prefetch` の最もシンプルな形では、従来の文字列ベースの検索と同等になります:

```
>>> from django.db.models import Prefetch
>>> Restaurant.objects.prefetch_related(Prefetch('pizzas__toppings'))
```

オプションの `queryset` 引数を使って、独自のクエリセットを指定することができます。これは、クエリセットのデフォルトの並び順を変更するために使用できます:

```
>>> Restaurant.objects.prefetch_related(
...     Prefetch('pizzas__toppings', queryset=Toppings.objects.order_by('name')))
```

もしくは、さらにクエリ数を減らすために、可能なときは [`select_related()`](#django.db.models.query.QuerySet.select_related) を呼び出します:

```
>>> Pizza.objects.prefetch_related(
...     Prefetch('restaurants', queryset=Restaurant.objects.select_related('best_pizza')))
```

また、オプションの `to_attr` で、事前読み込みの結果を独自の属性に割り当てることもできます。結果はリストに直接格納されます。

これにより、異なる `QuerySet` で同じリレーションを複数回事前読み込みできるようになります; 例えば:

```
>>> vegetarian_pizzas = Pizza.objects.filter(vegetarian=True)
>>> Restaurant.objects.prefetch_related(
...     Prefetch('pizzas', to_attr='menu'),
...     Prefetch('pizzas', queryset=vegetarian_pizzas, to_attr='vegetarian_menu'))
```

独自の `to_attr` で生成した検索はいつも通り他の検索でも使用可能です:

```
>>> vegetarian_pizzas = Pizza.objects.filter(vegetarian=True)
>>> Restaurant.objects.prefetch_related(
...     Prefetch('pizzas', queryset=vegetarian_pizzas, to_attr='vegetarian_menu'),
...     'vegetarian_menu__toppings')
```

`to_attr` の使用は、関係するマネージャのキャッシュにフィルタした結果を格納するよりも明確になるよう、事前読み込みした結果をフィルタする際に推奨されます:

```
>>> queryset = Pizza.objects.filter(vegetarian=True)
>>>
>>> # Recommended:
>>> restaurants = Restaurant.objects.prefetch_related(
...     Prefetch('pizzas', queryset=queryset, to_attr='vegetarian_pizzas'))
>>> vegetarian_pizzas = restaurants[0].vegetarian_pizzas
>>>
>>> # Not recommended:
>>> restaurants = Restaurant.objects.prefetch_related(
...     Prefetch('pizzas', queryset=queryset))
>>> vegetarian_pizzas = restaurants[0].pizzas.all()
```

独自の事前読み込みは、`ForeignKey` や `OneToOneField` のような単一の関連リレーションでも機能します。一般的にはこういう場合 [`select_related()`](#django.db.models.query.QuerySet.select_related) を使いたくなるでしょうが、`QuerySet` が役立つ場面も多くあります:

- 関連モデルに対してさらに事前読み込みを行う `QuerySet` を使用したい。
- 関連オブジェクトのサブセットのみを事前読み込みしたい。
- You want to use performance optimization techniques like
  [`deferred fields`](#django.db.models.query.QuerySet.defer):

  ```
  >>> queryset = Pizza.objects.only('name')
  >>>
  >>> restaurants = Restaurant.objects.prefetch_related(
  ...     Prefetch('best_pizza', queryset=queryset))
  ```

When using multiple databases, `Prefetch` will respect your choice of
database. If the inner query does not specify a database, it will use the
database selected by the outer query. All of the following are valid:

```
>>> # Both inner and outer queries will use the 'replica' database
>>> Restaurant.objects.prefetch_related('pizzas__toppings').using('replica')
>>> Restaurant.objects.prefetch_related(
...     Prefetch('pizzas__toppings'),
... ).using('replica')
>>>
>>> # Inner will use the 'replica' database; outer will use 'default' database
>>> Restaurant.objects.prefetch_related(
...     Prefetch('pizzas__toppings', queryset=Toppings.objects.using('replica')),
... )
>>>
>>> # Inner will use 'replica' database; outer will use 'cold-storage' database
>>> Restaurant.objects.prefetch_related(
...     Prefetch('pizzas__toppings', queryset=Toppings.objects.using('replica')),
... ).using('cold-storage')
```

> **Note**
>
> 検索の順番は重要です。
>
> 以下の例を見てみましょう:
>
> ```
> >>> prefetch_related('pizzas__toppings', 'pizzas')
> ```
>
> `'pizzas__toppings'` がすでに必要な情報を含んでいるので、並び替えしていないにもかかわらずこれは機能します。したがって 2 番目の引数 `'pizzas'` は実際には不要です。
>
> ```
> >>> prefetch_related('pizzas__toppings', Prefetch('pizzas', queryset=Pizza.objects.all()))
> ```
>
> 事前に見た検索クエリを再定義しようとしているため、これは `ValueError` を発生させます。 `'pizzas'` を横切るために\`\`'pizzas\_\_toppings'\`\` の一部として暗黙的なクエリセットが生成される点に留意してください。
>
> ```
> >>> prefetch_related('pizza_list__toppings', Prefetch('pizzas', to_attr='pizza_list'))
> ```
>
> `'pizza_list__toppings'` が実行される際にまだ `'pizza_list'` が存在していないため、これは\`\`AttributeError\`\` を引き起こします。
>
> この考慮事項は、`Prefetch` の使用に限りません。高度なテクニックのいくつかでは、余計なクエリの生成を防止するため、特定の順序で検索を実施する必要があるかもしれません; したがって、`prefetch_related` の引数には常に注意を払うことを推奨します。

#### `extra()`

#### `extra(select=None, where=None, params=None, tables=None, order_by=None, select_params=None)`

Sometimes, the Django query syntax by itself can't easily express a complex
`WHERE` clause. For these edge cases, Django provides the `extra()`
`QuerySet` modifier — a hook for injecting specific clauses into the SQL
generated by a `QuerySet`.

> **Use this method as a last resort**
>
> This is an old API that we aim to deprecate at some point in the future.
> Use it only if you cannot express your query using other queryset methods.
> If you do need to use it, please [file a ticket](https://code.djangoproject.com/newticket) using the [QuerySet.extra
> keyword](https://code.djangoproject.com/query?status=assigned&status=new&keywords=~QuerySet.extra)
> with your use case (please check the list of existing tickets first) so
> that we can enhance the QuerySet API to allow removing `extra()`. We are
> no longer improving or fixing bugs for this method.
>
> For example, this use of `extra()`:
>
> ```
> >>> qs.extra(
> ...     select={'val': "select col from sometable where othercol = %s"},
> ...     select_params=(someparam,),
> ... )
> ```
>
> これは以下と同じです:
>
> ```
> >>> qs.annotate(val=RawSQL("select col from sometable where othercol = %s", (someparam,)))
> ```
>
> The main benefit of using [`RawSQL`](/ja/4.1/ref/models/expressions/#django.db.models.expressions.RawSQL) is
> that you can set `output_field` if needed. The main downside is that if
> you refer to some table alias of the queryset in the raw SQL, then it is
> possible that Django might change that alias (for example, when the
> queryset is used as a subquery in yet another query).

> **Warning**
>
> You should be very careful whenever you use `extra()`. Every time you use
> it, you should escape any parameters that the user can control by using
> `params` in order to protect against SQL injection attacks.
>
> You also must not quote placeholders in the SQL string. This example is
> vulnerable to SQL injection because of the quotes around `%s`:
>
> ```sql
> SELECT col FROM sometable WHERE othercol = '%s'  # unsafe!
> ```
>
> You can read more about how Django's [SQL injection protection](/ja/4.1/topics/security/#sql-injection-protection) works.

By definition, these extra lookups may not be portable to different database
engines (because you're explicitly writing SQL code) and violate the DRY
principle, so you should avoid them if possible.

Specify one or more of `params`, `select`, `where` or `tables`. None
of the arguments is required, but you should use at least one of them.

- `select`

  The `select` argument lets you put extra fields in the `SELECT`
  clause.  It should be a dictionary mapping attribute names to SQL
  clauses to use to calculate that attribute.

  実装例:

  ```
  Entry.objects.extra(select={'is_recent': "pub_date > '2006-01-01'"})
  ```

  As a result, each `Entry` object will have an extra attribute,
  `is_recent`, a boolean representing whether the entry's `pub_date`
  is greater than Jan. 1, 2006.

  Django inserts the given SQL snippet directly into the `SELECT`
  statement, so the resulting SQL of the above example would be something like:

  ```sql
  SELECT blog_entry.*, (pub_date > '2006-01-01') AS is_recent
  FROM blog_entry;
  ```

  The next example is more advanced; it does a subquery to give each
  resulting `Blog` object an `entry_count` attribute, an integer count
  of associated `Entry` objects:

  ```
  Blog.objects.extra(
      select={
          'entry_count': 'SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id'
      },
  )
  ```

  In this particular case, we're exploiting the fact that the query will
  already contain the `blog_blog` table in its `FROM` clause.

  The resulting SQL of the above example would be:

  ```sql
  SELECT blog_blog.*, (SELECT COUNT(*) FROM blog_entry WHERE blog_entry.blog_id = blog_blog.id) AS entry_count
  FROM blog_blog;
  ```

  Note that the parentheses required by most database engines around
  subqueries are not required in Django's `select` clauses. Also note
  that some database backends, such as some MySQL versions, don't support
  subqueries.

  In some rare cases, you might wish to pass parameters to the SQL
  fragments in `extra(select=...)`. For this purpose, use the
  `select_params` parameter.

  This will work, for example:

  ```
  Blog.objects.extra(
      select={'a': '%s', 'b': '%s'},
      select_params=('one', 'two'),
  )
  ```

  If you need to use a literal `%s` inside your select string, use
  the sequence `%%s`.
- `where` / `tables`

  You can define explicit SQL `WHERE` clauses — perhaps to perform
  non-explicit joins — by using `where`. You can manually add tables to
  the SQL `FROM` clause by using `tables`.

  `where` and `tables` both take a list of strings. All `where`
  parameters are "AND"ed to any other search criteria.

  実装例:

  ```
  Entry.objects.extra(where=["foo='a' OR bar = 'a'", "baz = 'a'"])
  ```

  ...translates (roughly) into the following SQL:

  ```sql
  SELECT * FROM blog_entry WHERE (foo='a' OR bar='a') AND (baz='a')
  ```

  Be careful when using the `tables` parameter if you're specifying
  tables that are already used in the query. When you add extra tables
  via the `tables` parameter, Django assumes you want that table
  included an extra time, if it is already included. That creates a
  problem, since the table name will then be given an alias. If a table
  appears multiple times in an SQL statement, the second and subsequent
  occurrences must use aliases so the database can tell them apart. If
  you're referring to the extra table you added in the extra `where`
  parameter this is going to cause errors.

  Normally you'll only be adding extra tables that don't already appear
  in the query. However, if the case outlined above does occur, there are
  a few solutions. First, see if you can get by without including the
  extra table and use the one already in the query. If that isn't
  possible, put your `extra()` call at the front of the queryset
  construction so that your table is the first use of that table.
  Finally, if all else fails, look at the query produced and rewrite your
  `where` addition to use the alias given to your extra table. The
  alias will be the same each time you construct the queryset in the same
  way, so you can rely upon the alias name to not change.
- `order_by`

  If you need to order the resulting queryset using some of the new
  fields or tables you have included via `extra()` use the `order_by`
  parameter to `extra()` and pass in a sequence of strings. These
  strings should either be model fields (as in the normal
  [`order_by()`](#django.db.models.query.QuerySet.order_by) method on querysets), of the form
  `table_name.column_name` or an alias for a column that you specified
  in the `select` parameter to `extra()`.

  例:

  ```
  q = Entry.objects.extra(select={'is_recent': "pub_date > '2006-01-01'"})
  q = q.extra(order_by = ['-is_recent'])
  ```

  This would sort all the items for which `is_recent` is true to the
  front of the result set (`True` sorts before `False` in a
  descending ordering).

  This shows, by the way, that you can make multiple calls to `extra()`
  and it will behave as you expect (adding new constraints each time).
- `params`

  The `where` parameter described above may use standard Python
  database string placeholders — `'%s'` to indicate parameters the
  database engine should automatically quote. The `params` argument is
  a list of any extra parameters to be substituted.

  実装例:

  ```
  Entry.objects.extra(where=['headline=%s'], params=['Lennon'])
  ```

  Always use `params` instead of embedding values directly into
  `where` because `params` will ensure values are quoted correctly
  according to your particular backend. For example, quotes will be
  escaped correctly.

  Bad:

  ```
  Entry.objects.extra(where=["headline='Lennon'"])
  ```

  Good:

  ```
  Entry.objects.extra(where=['headline=%s'], params=['Lennon'])
  ```

> **Warning**
>
> もしあなたが MySQL でクエリを処理する場合は、複数の型を扱う際に MySQL の暗黙的な型変換が予期しない結果をもたらす場合がある事に注意してください。もし文字列型で定義したカラムに対し、数値型の値で問い合わせた場合、MySQL は比較処理を行う前にテーブル上の全ての値の型を数値型に変換します。例えば `'abc'`、 `'def'` といった値が含まれているテーブルに対して `WHERE mycolumn=0` という条件での問い合わせを行うと、両方の行がマッチします。これを防ぐため、クエリの値を利用する前に適切な型キャストを行ってください。

#### `defer()`

#### `defer(*fields)`

In some complex data-modeling situations, your models might contain a lot of
fields, some of which could contain a lot of data (for example, text fields),
or require expensive processing to convert them to Python objects. If you are
using the results of a queryset in some situation where you don't know
if you need those particular fields when you initially fetch the data, you can
tell Django not to retrieve them from the database.

This is done by passing the names of the fields to not load to `defer()`:

```
Entry.objects.defer("headline", "body")
```

A queryset that has deferred fields will still return model instances. Each
deferred field will be retrieved from the database if you access that field
(one at a time, not all the deferred fields at once).

> **Note**
>
> Deferred fields will not lazy-load like this from asynchronous code.
> Instead, you will get a `SynchronousOnlyOperation` exception. If you are
> writing asynchronous code, you should not try to access any fields that you
> `defer()`.

You can make multiple calls to `defer()`. Each call adds new fields to the
deferred set:

```
# Defers both the body and headline fields.
Entry.objects.defer("body").filter(rating=5).defer("headline")
```

The order in which fields are added to the deferred set does not matter.
Calling `defer()` with a field name that has already been deferred is
harmless (the field will still be deferred).

You can defer loading of fields in related models (if the related models are
loading via [`select_related()`](#django.db.models.query.QuerySet.select_related)) by using the standard double-underscore
notation to separate related fields:

```
Blog.objects.select_related().defer("entry__headline", "entry__body")
```

If you want to clear the set of deferred fields, pass `None` as a parameter
to `defer()`:

```
# Load all fields immediately.
my_queryset.defer(None)
```

Some fields in a model won't be deferred, even if you ask for them. You can
never defer the loading of the primary key. If you are using
[`select_related()`](#django.db.models.query.QuerySet.select_related) to retrieve related models, you shouldn't defer the
loading of the field that connects from the primary model to the related
one, doing so will result in an error.

> **Note**
>
> The `defer()` method (and its cousin, [`only()`](#django.db.models.query.QuerySet.only), below) are only for
> advanced use-cases. They provide an optimization for when you have analyzed
> your queries closely and understand *exactly* what information you need and
> have measured that the difference between returning the fields you need and
> the full set of fields for the model will be significant.
>
> Even if you think you are in the advanced use-case situation, **only use**
> `defer()` **when you cannot, at queryset load time, determine if you will
> need the extra fields or not**. If you are frequently loading and using a
> particular subset of your data, the best choice you can make is to
> normalize your models and put the non-loaded data into a separate model
> (and database table). If the columns *must* stay in the one table for some
> reason, create a model with `Meta.managed = False` (see the
> [`managed attribute`](/ja/4.1/ref/models/options/#django.db.models.Options.managed) documentation)
> containing just the fields you normally need to load and use that where you
> might otherwise call `defer()`. This makes your code more explicit to the
> reader, is slightly faster and consumes a little less memory in the Python
> process.
>
> For example, both of these models use the same underlying database table:
>
> ```
> class CommonlyUsedModel(models.Model):
>     f1 = models.CharField(max_length=10)
>
>     class Meta:
>         managed = False
>         db_table = 'app_largetable'
>
> class ManagedModel(models.Model):
>     f1 = models.CharField(max_length=10)
>     f2 = models.CharField(max_length=10)
>
>     class Meta:
>         db_table = 'app_largetable'
>
> # Two equivalent QuerySets:
> CommonlyUsedModel.objects.all()
> ManagedModel.objects.defer('f2')
> ```
>
> If many fields need to be duplicated in the unmanaged model, it may be best
> to create an abstract model with the shared fields and then have the
> unmanaged and managed models inherit from the abstract model.

> **Note**
>
> When calling [`save()`](/ja/4.1/ref/models/instances/#django.db.models.Model.save) for instances with
> deferred fields, only the loaded fields will be saved. See
> [`save()`](/ja/4.1/ref/models/instances/#django.db.models.Model.save) for more details.

#### `only()`

#### `only(*fields)`

The `only()` method is essentially the opposite of [`defer()`](#django.db.models.query.QuerySet.defer). Only the
fields passed into this method and that are *not* already specified as deferred
are loaded immediately when the queryset is evaluated.

If you have a model where almost all the fields need to be deferred, using
`only()` to specify the complementary set of fields can result in simpler
code.

Suppose you have a model with fields `name`, `age` and `biography`. The
following two querysets are the same, in terms of deferred fields:

```
Person.objects.defer("age", "biography")
Person.objects.only("name")
```

Whenever you call `only()` it *replaces* the set of fields to load
immediately. The method's name is mnemonic: **only** those fields are loaded
immediately; the remainder are deferred. Thus, successive calls to `only()`
result in only the final fields being considered:

```
# This will defer all fields except the headline.
Entry.objects.only("body", "rating").only("headline")
```

Since `defer()` acts incrementally (adding fields to the deferred list), you
can combine calls to `only()` and `defer()` and things will behave
logically:

```
# Final result is that everything except "headline" is deferred.
Entry.objects.only("headline", "body").defer("body")

# Final result loads headline immediately.
Entry.objects.defer("body").only("headline", "body")
```

All of the cautions in the note for the [`defer()`](#django.db.models.query.QuerySet.defer) documentation apply to
`only()` as well. Use it cautiously and only after exhausting your other
options.

Using [`only()`](#django.db.models.query.QuerySet.only) and omitting a field requested using [`select_related()`](#django.db.models.query.QuerySet.select_related)
is an error as well.

As with `defer()`, you cannot access the non-loaded fields from asynchronous
code and expect them to load. Instead, you will get a
`SynchronousOnlyOperation` exception. Ensure that all fields you might access
are in your `only()` call.

> **Note**
>
> When calling [`save()`](/ja/4.1/ref/models/instances/#django.db.models.Model.save) for instances with
> deferred fields, only the loaded fields will be saved. See
> [`save()`](/ja/4.1/ref/models/instances/#django.db.models.Model.save) for more details.

> **Note**
>
> When using [`defer()`](#django.db.models.query.QuerySet.defer) after `only()` the fields in [`defer()`](#django.db.models.query.QuerySet.defer) will
> override `only()` for fields that are listed in both.

#### `using()`

#### `using(alias)`

This method is for controlling which database the `QuerySet` will be
evaluated against if you are using more than one database.  The only argument
this method takes is the alias of a database, as defined in
[`DATABASES`](/ja/4.1/ref/settings/#std-setting-DATABASES).

例:

```
# queries the database with the 'default' alias.
>>> Entry.objects.all()

# queries the database with the 'backup' alias
>>> Entry.objects.using('backup')
```

#### `select_for_update()`

#### `select_for_update(nowait=False, skip_locked=False, of=(), no_key=False)`

Returns a queryset that will lock rows until the end of the transaction,
generating a `SELECT ... FOR UPDATE` SQL statement on supported databases.

例:

```
from django.db import transaction

entries = Entry.objects.select_for_update().filter(author=request.user)
with transaction.atomic():
    for entry in entries:
        ...
```

When the queryset is evaluated (`for entry in entries` in this case), all
matched entries will be locked until the end of the transaction block, meaning
that other transactions will be prevented from changing or acquiring locks on
them.

通常、選択された行の1つに対して他のトランザクションが既にロックを取得している場合、ロックが解除されるまでクエリはブロックされます。このような動作が望ましくない場合は、  `select_for_update(nowait=True)` を呼び出してください。これにより、呼び出しがノンブロッキングになります。競合するロックが既に他のトランザクションによって取得されている場合は、クエリセットが評価される際に [`DatabaseError`](/ja/4.1/ref/exceptions/#django.db.DatabaseError) が発生します。代わりに `select_for_update(skip_locked=True)` を使用すれば、ロックされた行を無視することもできます。 `nowait` と ```skip_locked``は互いに排他的であり、両方のオプションを有効にして ``select_for_update()``` を呼び出そうとすると [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError) が発生します。

By default, `select_for_update()` locks all rows that are selected by the
query. For example, rows of related objects specified in [`select_related()`](#django.db.models.query.QuerySet.select_related)
are locked in addition to rows of the queryset's model. If this isn't desired,
specify the related objects you want to lock in `select_for_update(of=(...))`
using the same fields syntax as [`select_related()`](#django.db.models.query.QuerySet.select_related). Use the value `'self'`
to refer to the queryset's model.

> **Lock parents models in select_for_update(of=(...))**
>
> If you want to lock parents models when using [multi-table inheritance](/ja/4.1/topics/db/models/#multi-table-inheritance), you must specify parent link fields (by default
> `<parent_model_name>_ptr`) in the `of` argument. For example:
>
> ```
> Restaurant.objects.select_for_update(of=('self', 'place_ptr'))
> ```

> **Using select_for_update(of=(...)) with specified fields**
>
> If you want to lock models and specify selected fields, e.g. using
> [`values()`](#django.db.models.query.QuerySet.values), you must select at least one field from each model in the
> `of` argument. Models without selected fields will not be locked.

On PostgreSQL only, you can pass `no_key=True` in order to acquire a weaker
lock, that still allows creating rows that merely reference locked rows
(through a foreign key, for example) while the lock is in place. The
PostgreSQL documentation has more details about [row-level lock modes](https://www.postgresql.org/docs/current/explicit-locking.html#LOCKING-ROWS).

You can't use `select_for_update()` on nullable relations:

```
>>> Person.objects.select_related('hometown').select_for_update()
Traceback (most recent call last):
...
django.db.utils.NotSupportedError: FOR UPDATE cannot be applied to the nullable side of an outer join
```

To avoid that restriction, you can exclude null objects if you don't care about
them:

```
>>> Person.objects.select_related('hometown').select_for_update().exclude(hometown=None)
<QuerySet [<Person: ...)>, ...]>
```

The `postgresql`, `oracle`, and `mysql` database backends support
`select_for_update()`. However, MariaDB only supports the `nowait`
argument, MariaDB 10.6+ also supports the `skip_locked` argument, and MySQL
8.0.1+ supports the `nowait`, `skip_locked`, and `of` arguments. The
`no_key` argument is only supported on PostgreSQL.

Passing `nowait=True`, `skip_locked=True`, `no_key=True`, or `of` to
`select_for_update()` using database backends that do not support these
options, such as MySQL, raises a [`NotSupportedError`](/ja/4.1/ref/exceptions/#django.db.NotSupportedError). This
prevents code from unexpectedly blocking.

Evaluating a queryset with `select_for_update()` in autocommit mode on
backends which support `SELECT ... FOR UPDATE` is a
[`TransactionManagementError`](/ja/4.1/ref/exceptions/#django.db.transaction.TransactionManagementError) error because the
rows are not locked in that case. If allowed, this would facilitate data
corruption and could easily be caused by calling code that expects to be run in
a transaction outside of one.

Using `select_for_update()` on backends which do not support
`SELECT ... FOR UPDATE` (such as SQLite) will have no effect.
`SELECT ... FOR UPDATE` will not be added to the query, and an error isn't
raised if `select_for_update()` is used in autocommit mode.

> **Warning**
>
> Although `select_for_update()` normally fails in autocommit mode, since
> [`TestCase`](/ja/4.1/topics/testing/tools/#django.test.TestCase) automatically wraps each test in a
> transaction, calling `select_for_update()` in a `TestCase` even outside
> an [`atomic()`](/ja/4.1/topics/db/transactions/#django.db.transaction.atomic) block will (perhaps unexpectedly)
> pass without raising a `TransactionManagementError`. To properly test
> `select_for_update()` you should use
> [`TransactionTestCase`](/ja/4.1/topics/testing/tools/#django.test.TransactionTestCase).

> **Certain expressions may not be supported**
>
> PostgreSQL doesn't support `select_for_update()` with
> [`Window`](/ja/4.1/ref/models/expressions/#django.db.models.expressions.Window) expressions.

> **Changed in Django 4.0**
>
> The `skip_locked` argument was allowed on MariaDB 10.6+.

#### `raw()`

#### `raw(raw_query, params=(), translations=None, using=None)`

Takes a raw SQL query, executes it, and returns a
`django.db.models.query.RawQuerySet` instance. This `RawQuerySet` instance
can be iterated over just like a normal `QuerySet` to provide object
instances.

See the [素の SQL 文の実行](/ja/4.1/topics/db/sql/) for more information.

> **Warning**
>
> `raw()` always triggers a new query and doesn't account for previous
> filtering. As such, it should generally be called from the `Manager` or
> from a fresh `QuerySet` instance.

### Operators that return new `QuerySet`s

Combined querysets must use the same model.

#### AND (`&`)

Combines two `QuerySet`s using the SQL `AND` operator.

The following are equivalent:

```
Model.objects.filter(x=1) & Model.objects.filter(y=2)
Model.objects.filter(x=1, y=2)
from django.db.models import Q
Model.objects.filter(Q(x=1) & Q(y=2))
```

SQL equivalent:

```sql
SELECT ... WHERE x=1 AND y=2
```

#### OR (`|`)

Combines two `QuerySet`s using the SQL `OR` operator.

The following are equivalent:

```
Model.objects.filter(x=1) | Model.objects.filter(y=2)
from django.db.models import Q
Model.objects.filter(Q(x=1) | Q(y=2))
```

SQL equivalent:

```sql
SELECT ... WHERE x=1 OR y=2
```

`|` is not a commutative operation, as different (though equivalent) queries
may be generated.

#### XOR (`^`)

> **New in Django 4.1**

Combines two `QuerySet`s using the SQL `XOR` operator.

The following are equivalent:

```
Model.objects.filter(x=1) ^ Model.objects.filter(y=2)
from django.db.models import Q
Model.objects.filter(Q(x=1) ^ Q(y=2))
```

SQL equivalent:

```sql
SELECT ... WHERE x=1 XOR y=2
```

> **Note**
>
> `XOR` is natively supported on MariaDB and MySQL. On other databases,
> `x ^ y ^ ... ^ z` is converted to an equivalent:
>
> ```sql
> (x OR y OR ... OR z) AND
> 1=(
>     (CASE WHEN x THEN 1 ELSE 0 END) +
>     (CASE WHEN y THEN 1 ELSE 0 END) +
>     ...
>     (CASE WHEN z THEN 1 ELSE 0 END) +
> )
> ```

### Methods that do not return `QuerySet`s

The following `QuerySet` methods evaluate the `QuerySet` and return
something *other than* a `QuerySet`.

These methods do not use a cache (see [キャッシングと QuerySet](/ja/4.1/topics/db/queries/#caching-and-querysets)). Rather,
they query the database each time they're called.

Because these methods evaluate the QuerySet, they are blocking calls, and so
their main (synchronous) versions cannot be called from asynchronous code. For
this reason, each has a corresponding asynchronous version with an `a` prefix
\- for example, rather than `get(…)` you can `await aget(…)`.

There is usually no difference in behavior apart from their asynchronous
nature, but any differences are noted below next to each method.

> **Changed in Django 4.1**
>
> The asynchronous versions of each method, prefixed with `a` was added.

#### `get()`

#### `get(*args, **kwargs)`

#### `aget(*args, **kwargs)`

*Asynchronous version*: `aget()`

Returns the object matching the given lookup parameters, which should be in
the format described in [Field lookups](#id4). You should use lookups that are
guaranteed unique, such as the primary key or fields in a unique constraint.
For example:

```
Entry.objects.get(id=1)
Entry.objects.get(Q(blog=blog) & Q(entry_number=1))
```

If you expect a queryset to already return one row, you can use `get()`
without any arguments to return the object for that row:

```
Entry.objects.filter(pk=1).get()
```

If `get()` doesn't find any object, it raises a [`Model.DoesNotExist`](/ja/4.1/ref/models/class/#django.db.models.Model.DoesNotExist) exception:

```
Entry.objects.get(id=-999) # raises Entry.DoesNotExist
```

If `get()` finds more than one object, it raises a
[`Model.MultipleObjectsReturned`](/ja/4.1/ref/models/class/#django.db.models.Model.MultipleObjectsReturned) exception:

```
Entry.objects.get(name='A Duplicated Name') # raises Entry.MultipleObjectsReturned
```

Both these exception classes are attributes of the model class, and specific to
that model. If you want to handle such exceptions from several `get()` calls
for different models, you can use their generic base classes. For example, you
can use [`django.core.exceptions.ObjectDoesNotExist`](/ja/4.1/ref/exceptions/#django.core.exceptions.ObjectDoesNotExist)  to handle
[`DoesNotExist`](/ja/4.1/ref/models/class/#django.db.models.Model.DoesNotExist) exceptions from multiple models:

```
from django.core.exceptions import ObjectDoesNotExist

try:
    blog = Blog.objects.get(id=1)
    entry = Entry.objects.get(blog=blog, entry_number=1)
except ObjectDoesNotExist:
    print("Either the blog or entry doesn't exist.")
```

> **Changed in Django 4.1**
>
> `aget()` method was added.

#### `create()`

#### `create(**kwargs)`

#### `acreate(*args, **kwargs)`

*Asynchronous version*: `acreate()`

A convenience method for creating an object and saving it all in one step.  Thus:

```
p = Person.objects.create(first_name="Bruce", last_name="Springsteen")
```

and:

```
p = Person(first_name="Bruce", last_name="Springsteen")
p.save(force_insert=True)
```

are equivalent.

The [force\_insert](/ja/4.1/ref/models/instances/#ref-models-force-insert) parameter is documented
elsewhere, but all it means is that a new object will always be created.
Normally you won't need to worry about this. However, if your model contains a
manual primary key value that you set and if that value already exists in the
database, a call to `create()` will fail with an
[`IntegrityError`](/ja/4.1/ref/exceptions/#django.db.IntegrityError) since primary keys must be unique. Be
prepared to handle the exception if you are using manual primary keys.

> **Changed in Django 4.1**
>
> `acreate()` method was added.

#### `get_or_create()`

#### `get_or_create(defaults=None, **kwargs)`

#### `aget_or_create(defaults=None, **kwargs)`

*Asynchronous version*: `aget_or_create()`

A convenience method for looking up an object with the given `kwargs` (may be
empty if your model has defaults for all fields), creating one if necessary.

(Object, created) のタプルを返します。"Object"は受け取ったものか作られたものです。そして"created"はそのObjectが作られたものかどうかのBooleanです。

This is meant to prevent duplicate objects from being created when requests are
made in parallel, and as a shortcut to boilerplatish code. For example:

```
try:
    obj = Person.objects.get(first_name='John', last_name='Lennon')
except Person.DoesNotExist:
    obj = Person(first_name='John', last_name='Lennon', birthday=date(1940, 10, 9))
    obj.save()
```

Here, with concurrent requests, multiple attempts to save a `Person` with
the same parameters may be made. To avoid this race condition, the above
example can be rewritten using `get_or_create()` like so:

```
obj, created = Person.objects.get_or_create(
    first_name='John',
    last_name='Lennon',
    defaults={'birthday': date(1940, 10, 9)},
)
```

Any keyword arguments passed to `get_or_create()` — *except* an optional one
called `defaults` — will be used in a [`get()`](#django.db.models.query.QuerySet.get) call. If an object is
found, `get_or_create()` returns a tuple of that object and `False`.

> **Warning**
>
> This method is atomic assuming that the database enforces uniqueness of the
> keyword arguments (see [`unique`](/ja/4.1/ref/models/fields/#django.db.models.Field.unique) or
> [`unique_together`](/ja/4.1/ref/models/options/#django.db.models.Options.unique_together)). If the fields used in the
> keyword arguments do not have a uniqueness constraint, concurrent calls to
> this method may result in multiple rows with the same parameters being
> inserted.

You can specify more complex conditions for the retrieved object by chaining
`get_or_create()` with `filter()` and using [`Q objects`](#django.db.models.Q). For example, to retrieve Robert or Bob Marley if either
exists, and create the latter otherwise:

```
from django.db.models import Q

obj, created = Person.objects.filter(
    Q(first_name='Bob') | Q(first_name='Robert'),
).get_or_create(last_name='Marley', defaults={'first_name': 'Bob'})
```

If multiple objects are found, `get_or_create()` raises
[`MultipleObjectsReturned`](/ja/4.1/ref/exceptions/#django.core.exceptions.MultipleObjectsReturned). If an object is *not*
found, `get_or_create()` will instantiate and save a new object, returning a
tuple of the new object and `True`. The new object will be created roughly
according to this algorithm:

```
params = {k: v for k, v in kwargs.items() if '__' not in k}
params.update({k: v() if callable(v) else v for k, v in defaults.items()})
obj = self.model(**params)
obj.save()
```

In English, that means start with any non-`'defaults'` keyword argument that
doesn't contain a double underscore (which would indicate a non-exact lookup).
Then add the contents of `defaults`, overriding any keys if necessary, and
use the result as the keyword arguments to the model class. If there are any
callables in `defaults`, evaluate them. As hinted at above, this is a
simplification of the algorithm that is used, but it contains all the pertinent
details. The internal implementation has some more error-checking than this and
handles some extra edge-conditions; if you're interested, read the code.

If you have a field named `defaults` and want to use it as an exact lookup in
`get_or_create()`, use `'defaults__exact'`, like so:

```
Foo.objects.get_or_create(defaults__exact='bar', defaults={'defaults': 'baz'})
```

The `get_or_create()` method has similar error behavior to [`create()`](#django.db.models.query.QuerySet.create)
when you're using manually specified primary keys. If an object needs to be
created and the key already exists in the database, an
[`IntegrityError`](/ja/4.1/ref/exceptions/#django.db.IntegrityError) will be raised.

Finally, a word on using `get_or_create()` in Django views. Please make sure
to use it only in `POST` requests unless you have a good reason not to.
`GET` requests shouldn't have any effect on data. Instead, use `POST`
whenever a request to a page has a side effect on your data. For more, see
[**Safe methods**](https://datatracker.ietf.org/doc/html/rfc7231.html#section-4.2.1) in the HTTP spec.

> **Warning**
>
> You can use `get_or_create()` through [`ManyToManyField`](/ja/4.1/ref/models/fields/#django.db.models.ManyToManyField)
> attributes and reverse relations. In that case you will restrict the queries
> inside the context of that relation. That could lead you to some integrity
> problems if you don't use it consistently.
>
> Being the following models:
>
> ```
> class Chapter(models.Model):
>     title = models.CharField(max_length=255, unique=True)
>
> class Book(models.Model):
>     title = models.CharField(max_length=256)
>     chapters = models.ManyToManyField(Chapter)
> ```
>
> You can use `get_or_create()` through Book's chapters field, but it only
> fetches inside the context of that book:
>
> ```
> >>> book = Book.objects.create(title="Ulysses")
> >>> book.chapters.get_or_create(title="Telemachus")
> (<Chapter: Telemachus>, True)
> >>> book.chapters.get_or_create(title="Telemachus")
> (<Chapter: Telemachus>, False)
> >>> Chapter.objects.create(title="Chapter 1")
> <Chapter: Chapter 1>
> >>> book.chapters.get_or_create(title="Chapter 1")
> # Raises IntegrityError
> ```
>
> This is happening because it's trying to get or create "Chapter 1" through the
> book "Ulysses", but it can't do any of them: the relation can't fetch that
> chapter because it isn't related to that book, but it can't create it either
> because `title` field should be unique.

> **Changed in Django 4.1**
>
> `aget_or_create()` method was added.

#### `update_or_create()`

#### `update_or_create(defaults=None, **kwargs)`

#### `aupdate_or_create(defaults=None, **kwargs)`

*Asynchronous version*: `aupdate_or_create()`

A convenience method for updating an object with the given `kwargs`, creating
a new one if necessary. The `defaults` is a dictionary of (field, value)
pairs used to update the object. The values in `defaults` can be callables.

(Object, created) のタプルを返します。"Object"は受け取ったものか更新したものです。そして"created"はそのObjectが更新されたものかどうかのBooleanです。

The `update_or_create` method tries to fetch an object from database based on
the given `kwargs`. If a match is found, it updates the fields passed in the
`defaults` dictionary.

これは手っ取り早い定型的なコードです。例えば:

```
defaults = {'first_name': 'Bob'}
try:
    obj = Person.objects.get(first_name='John', last_name='Lennon')
    for key, value in defaults.items():
        setattr(obj, key, value)
    obj.save()
except Person.DoesNotExist:
    new_values = {'first_name': 'John', 'last_name': 'Lennon'}
    new_values.update(defaults)
    obj = Person(**new_values)
    obj.save()
```

This pattern gets quite unwieldy as the number of fields in a model goes up.
The above example can be rewritten using `update_or_create()` like so:

```
obj, created = Person.objects.update_or_create(
    first_name='John', last_name='Lennon',
    defaults={'first_name': 'Bob'},
)
```

For a detailed description of how names passed in `kwargs` are resolved, see
[`get_or_create()`](#django.db.models.query.QuerySet.get_or_create).

As described above in [`get_or_create()`](#django.db.models.query.QuerySet.get_or_create), this method is prone to a
race-condition which can result in multiple rows being inserted simultaneously
if uniqueness is not enforced at the database level.

Like [`get_or_create()`](#django.db.models.query.QuerySet.get_or_create) and [`create()`](#django.db.models.query.QuerySet.create), if you're using manually
specified primary keys and an object needs to be created but the key already
exists in the database, an [`IntegrityError`](/ja/4.1/ref/exceptions/#django.db.IntegrityError) is raised.

> **Changed in Django 4.1**
>
> `aupdate_or_create()` method was added.

#### `bulk_create()`

#### `bulk_create(objs, batch_size=None, ignore_conflicts=False, update_conflicts=False, update_fields=None, unique_fields=None)`

#### `abulk_create(objs, batch_size=None, ignore_conflicts=False, update_conflicts=False, update_fields=None, unique_fields=None)`

*Asynchronous version*: `abulk_create()`

This method inserts the provided list of objects into the database in an
efficient manner (generally only 1 query, no matter how many objects there
are), and returns created objects as a list, in the same order as provided:

```
>>> objs = Entry.objects.bulk_create([
...     Entry(headline='This is a test'),
...     Entry(headline='This is only a test'),
... ])
```

This has a number of caveats though:

- The model's `save()` method will not be called, and the `pre_save` and
  `post_save` signals will not be sent.
- It does not work with child models in a multi-table inheritance scenario.
- If the model's primary key is an [`AutoField`](/ja/4.1/ref/models/fields/#django.db.models.AutoField), the
  primary key attribute can only be retrieved on certain databases (currently
  PostgreSQL, MariaDB 10.5+, and SQLite 3.35+). On other databases, it will not
  be set.
- It does not work with many-to-many relationships.
- It casts `objs` to a list, which fully evaluates `objs` if it's a
  generator. The cast allows inspecting all objects so that any objects with a
  manually set primary key can be inserted first. If you want to insert objects
  in batches without evaluating the entire generator at once, you can use this
  technique as long as the objects don't have any manually set primary keys:

  ```
  from itertools import islice

  batch_size = 100
  objs = (Entry(headline='Test %s' % i) for i in range(1000))
  while True:
      batch = list(islice(objs, batch_size))
      if not batch:
          break
      Entry.objects.bulk_create(batch, batch_size)
  ```

The `batch_size` parameter controls how many objects are created in a single
query. The default is to create all objects in one batch, except for SQLite
where the default is such that at most 999 variables per query are used.

On databases that support it (all but Oracle), setting the `ignore_conflicts`
parameter to `True` tells the database to ignore failure to insert any rows
that fail constraints such as duplicate unique values.

On databases that support it (all except Oracle and SQLite \< 3.24), setting the
`update_conflicts` parameter to `True`, tells the database to update
`update_fields` when a row insertion fails on conflicts. On PostgreSQL and
SQLite, in addition to `update_fields`, a list of `unique_fields` that may
be in conflict must be provided.

Enabling the `ignore_conflicts` or `update_conflicts` parameter disable
setting the primary key on each model instance (if the database normally
support it).

> **Warning**
>
> On MySQL and MariaDB, setting the `ignore_conflicts` parameter to
> `True` turns certain types of errors, other than duplicate key, into
> warnings. Even with Strict Mode. For example: invalid values or
> non-nullable violations. See the [MySQL documentation](https://dev.mysql.com/doc/refman/en/sql-mode.html#ignore-strict-comparison) and
> [MariaDB documentation](https://mariadb.com/kb/en/ignore/) for more details.

> **Changed in Django 4.0**
>
> Support for the fetching primary key attributes on SQLite 3.35+ was added.

> **Changed in Django 4.1**
>
> The `update_conflicts`, `update_fields`, and `unique_fields`
> parameters were added to support updating fields when a row insertion fails
> on conflict.
>
> `abulk_create()` method was added.

#### `bulk_update()`

#### `bulk_update(objs, fields, batch_size=None)`

#### `abulk_update(objs, fields, batch_size=None)`

*Asynchronous version*: `abulk_update()`

This method efficiently updates the given fields on the provided model
instances, generally with one query, and returns the number of objects
updated:

```
>>> objs = [
...    Entry.objects.create(headline='Entry 1'),
...    Entry.objects.create(headline='Entry 2'),
... ]
>>> objs[0].headline = 'This is entry 1'
>>> objs[1].headline = 'This is entry 2'
>>> Entry.objects.bulk_update(objs, ['headline'])
2
```

> **Changed in Django 4.0**
>
> The return value of the number of objects updated was added.

[`QuerySet.update()`](#django.db.models.query.QuerySet.update) is used to save the changes, so this is more efficient
than iterating through the list of models and calling `save()` on each of
them, but it has a few caveats:

- You cannot update the model's primary key.
- Each model's `save()` method isn't called, and the
  [`pre_save`](/ja/4.1/ref/signals/#django.db.models.signals.pre_save) and
  [`post_save`](/ja/4.1/ref/signals/#django.db.models.signals.post_save) signals aren't sent.
- If updating a large number of columns in a large number of rows, the SQL
  generated can be very large. Avoid this by specifying a suitable
  `batch_size`.
- Updating fields defined on multi-table inheritance ancestors will incur an
  extra query per ancestor.
- When an individual batch contains duplicates, only the first instance in that
  batch will result in an update.
- The number of objects updated returned by the function may be fewer than the
  number of objects passed in. This can be due to duplicate objects passed in
  which are updated in the same batch or race conditions such that objects are
  no longer present in the database.

The `batch_size` parameter controls how many objects are saved in a single
query. The default is to update all objects in one batch, except for SQLite
and Oracle which have restrictions on the number of variables used in a query.

> **Changed in Django 4.1**
>
> `abulk_update()` method was added.

#### `count()`

#### `count()`

#### `acount()`

*Asynchronous version*: `acount()`

Returns an integer representing the number of objects in the database matching
the `QuerySet`.

実装例:

```
# Returns the total number of entries in the database.
Entry.objects.count()

# Returns the number of entries whose headline contains 'Lennon'
Entry.objects.filter(headline__contains='Lennon').count()
```

A `count()` call performs a `SELECT COUNT(*)` behind the scenes, so you
should always use `count()` rather than loading all of the record into Python
objects and calling `len()` on the result (unless you need to load the
objects into memory anyway, in which case `len()` will be faster).

Note that if you want the number of items in a `QuerySet` and are also
retrieving model instances from it (for example, by iterating over it), it's
probably more efficient to use `len(queryset)` which won't cause an extra
database query like `count()` would.

If the queryset has already been fully retrieved, `count()` will use that
length rather than perform an extra database query.

> **Changed in Django 4.1**
>
> `acount()` method was added.

#### `in_bulk()`

#### `in_bulk(id_list=None, * (Keyword-only parameters separator (PEP 3102)), field_name='pk')`

#### `ain_bulk(id_list=None, * (Keyword-only parameters separator (PEP 3102)), field_name='pk')`

*Asynchronous version*: `ain_bulk()`

Takes a list of field values (`id_list`) and the `field_name` for those
values, and returns a dictionary mapping each value to an instance of the
object with the given field value. No
[`django.core.exceptions.ObjectDoesNotExist`](/ja/4.1/ref/exceptions/#django.core.exceptions.ObjectDoesNotExist) exceptions will ever be raised
by `in_bulk`; that is, any `id_list` value not matching any instance will
simply be ignored. If `id_list` isn't provided, all objects
in the queryset are returned. `field_name` must be a unique field or a
distinct field (if there's only one field specified in [`distinct()`](#django.db.models.query.QuerySet.distinct)).
`field_name` defaults to the primary key.

実装例:

```
>>> Blog.objects.in_bulk([1])
{1: <Blog: Beatles Blog>}
>>> Blog.objects.in_bulk([1, 2])
{1: <Blog: Beatles Blog>, 2: <Blog: Cheddar Talk>}
>>> Blog.objects.in_bulk([])
{}
>>> Blog.objects.in_bulk()
{1: <Blog: Beatles Blog>, 2: <Blog: Cheddar Talk>, 3: <Blog: Django Weblog>}
>>> Blog.objects.in_bulk(['beatles_blog'], field_name='slug')
{'beatles_blog': <Blog: Beatles Blog>}
>>> Blog.objects.distinct('name').in_bulk(field_name='name')
{'Beatles Blog': <Blog: Beatles Blog>, 'Cheddar Talk': <Blog: Cheddar Talk>, 'Django Weblog': <Blog: Django Weblog>}
```

If you pass `in_bulk()` an empty list, you'll get an empty dictionary.

> **Changed in Django 4.1**
>
> `ain_bulk()` method was added.

#### `iterator()`

#### `iterator(chunk_size=None)`

#### `aiterator(chunk_size=None)`

*Asynchronous version*: `aiterator()`

Evaluates the `QuerySet` (by performing the query) and returns an iterator
(see [**PEP 234**](https://peps.python.org/pep-0234/)) over the results, or an asynchronous iterator (see [**PEP 492**](https://peps.python.org/pep-0492/))
if you call its asynchronous version `aiterator`.

A `QuerySet` typically caches its results internally so that repeated
evaluations do not result in additional queries. In contrast, `iterator()`
will read results directly, without doing any caching at the `QuerySet` level
(internally, the default iterator calls `iterator()` and caches the return
value). For a `QuerySet` which returns a large number of objects that you
only need to access once, this can result in better performance and a
significant reduction in memory.

Note that using `iterator()` on a `QuerySet` which has already been
evaluated will force it to evaluate again, repeating the query.

`iterator()` is compatible with previous calls to `prefetch_related()` as
long as `chunk_size` is given. Larger values will necessitate fewer queries
to accomplish the prefetching at the cost of greater memory usage.

> **Note**
>
> `aiterator()` is *not* compatible with previous calls to
> `prefetch_related()`.

On some databases (e.g. Oracle, [SQLite](https://www.sqlite.org/limits.html#max_variable_number)), the maximum number
of terms in an SQL `IN` clause might be limited. Hence values below this
limit should be used. (In particular, when prefetching across two or more
relations, a `chunk_size` should be small enough that the anticipated number
of results for each prefetched relation still falls below the limit.)

So long as the QuerySet does not prefetch any related objects, providing no
value for `chunk_size` will result in Django using an implicit default of
2000.

Depending on the database backend, query results will either be loaded all at
once or streamed from the database using server-side cursors.

> **Changed in Django 4.1**
>
> Support for prefetching related objects was added to `iterator()`.
>
> `aiterator()` method was added.

> **Deprecated since Django 4.1**
>
> バージョン 4.1 で非推奨: Using `iterator()` on a queryset that prefetches related objects without
> providing the `chunk_size` is deprecated. In Django 5.0, an exception
> will be raise.

##### With server-side cursors

Oracle and [PostgreSQL](/ja/4.1/ref/databases/#postgresql-server-side-cursors) use server-side
cursors to stream results from the database without loading the entire result
set into memory.

The Oracle database driver always uses server-side cursors.

With server-side cursors, the `chunk_size` parameter specifies the number of
results to cache at the database driver level. Fetching bigger chunks
diminishes the number of round trips between the database driver and the
database, at the expense of memory.

On PostgreSQL, server-side cursors will only be used when the
[`DISABLE_SERVER_SIDE_CURSORS`](/ja/4.1/ref/settings/#std-setting-DATABASE-DISABLE_SERVER_SIDE_CURSORS)
setting is `False`. Read [Transaction pooling and server-side cursors](/ja/4.1/ref/databases/#transaction-pooling-server-side-cursors) if
you're using a connection pooler configured in transaction pooling mode. When
server-side cursors are disabled, the behavior is the same as databases that
don't support server-side cursors.

##### Without server-side cursors

MySQL doesn't support streaming results, hence the Python database driver loads
the entire result set into memory. The result set is then transformed into
Python row objects by the database adapter using the `fetchmany()` method
defined in [**PEP 249**](https://peps.python.org/pep-0249/).

SQLite can fetch results in batches using `fetchmany()`, but since SQLite
doesn't provide isolation between queries within a connection, be careful when
writing to the table being iterated over. See [Isolation when using QuerySet.iterator()](/ja/4.1/ref/databases/#sqlite-isolation) for
more information.

The `chunk_size` parameter controls the size of batches Django retrieves from
the database driver. Larger batches decrease the overhead of communicating with
the database driver at the expense of a slight increase in memory consumption.

So long as the QuerySet does not prefetch any related objects, providing no
value for `chunk_size` will result in Django using an implicit default of
2000, a value derived from [a calculation on the psycopg mailing list](https://www.postgresql.org/message-id/4D2F2C71.8080805%40dndg.it):

> Assuming rows of 10-20 columns with a mix of textual and numeric data, 2000
> is going to fetch less than 100KB of data, which seems a good compromise
> between the number of rows transferred and the data discarded if the loop
> is exited early.

#### `latest()`

#### `latest(*fields)`

#### `alatest(*fields)`

*Asynchronous version*: `alatest()`

Returns the latest object in the table based on the given field(s).

This example returns the latest `Entry` in the table, according to the
`pub_date` field:

```
Entry.objects.latest('pub_date')
```

You can also choose the latest based on several fields. For example, to select
the `Entry` with the earliest `expire_date` when two entries have the same
`pub_date`:

```
Entry.objects.latest('pub_date', '-expire_date')
```

The negative sign in `'-expire_date'` means to sort `expire_date` in
*descending* order. Since `latest()` gets the last result, the `Entry` with
the earliest `expire_date` is selected.

If your model's [Meta](/ja/4.1/topics/db/models/#meta-options) specifies
[`get_latest_by`](/ja/4.1/ref/models/options/#django.db.models.Options.get_latest_by), you can omit any arguments to
`earliest()` or `latest()`. The fields specified in
[`get_latest_by`](/ja/4.1/ref/models/options/#django.db.models.Options.get_latest_by) will be used by default.

Like [`get()`](#django.db.models.query.QuerySet.get), `earliest()` and `latest()` raise
[`DoesNotExist`](/ja/4.1/ref/models/class/#django.db.models.Model.DoesNotExist) if there is no object with the
given parameters.

Note that `earliest()` and `latest()` exist purely for convenience and
readability.

> **earliest() and latest() may return instances with null dates.**
>
> Since ordering is delegated to the database, results on fields that allow
> null values may be ordered differently if you use different databases. For
> example, PostgreSQL and MySQL sort null values as if they are higher than
> non-null values, while SQLite does the opposite.
>
> You may want to filter out null values:
>
> ```
> Entry.objects.filter(pub_date__isnull=False).latest('pub_date')
> ```

> **Changed in Django 4.1**
>
> `alatest()` method was added.

#### `earliest()`

#### `earliest(*fields)`

#### `aearliest(*fields)`

*Asynchronous version*: `aearliest()`

Works otherwise like [`latest()`](#django.db.models.query.QuerySet.latest) except
the direction is changed.

> **Changed in Django 4.1**
>
> `aearliest()` method was added.

#### `first()`

#### `first()`

#### `afirst()`

*Asynchronous version*: `afirst()`

Returns the first object matched by the queryset, or `None` if there
is no matching object. If the `QuerySet` has no ordering defined, then the
queryset is automatically ordered by the primary key. This can affect
aggregation results as described in [Interaction with order\_by()](/ja/4.1/topics/db/aggregation/#aggregation-ordering-interaction).

実装例:

```
p = Article.objects.order_by('title', 'pub_date').first()
```

Note that `first()` is a convenience method, the following code sample is
equivalent to the above example:

```
try:
    p = Article.objects.order_by('title', 'pub_date')[0]
except IndexError:
    p = None
```

> **Changed in Django 4.1**
>
> `afirst()` method was added.

#### `last()`

#### `last()`

#### `alast()`

*Asynchronous version*: `alast()`

Works like  [`first()`](#django.db.models.query.QuerySet.first), but returns the last object in the queryset.

> **Changed in Django 4.1**
>
> `alast()` method was added.

#### `aggregate()`

#### `aggregate(*args, **kwargs)`

#### `aaggregate(*args, **kwargs)`

*Asynchronous version*: `aaggregate()`

Returns a dictionary of aggregate values (averages, sums, etc.) calculated over
the `QuerySet`. Each argument to `aggregate()` specifies a value that will
be included in the dictionary that is returned.

The aggregation functions that are provided by Django are described in
[Aggregation Functions](#id6) below. Since aggregates are also [query
expressions](/ja/4.1/ref/models/expressions/), you may combine aggregates with other
aggregates or values to create complex aggregates.

Aggregates specified using keyword arguments will use the keyword as the name
for the annotation. Anonymous arguments will have a name generated for them
based upon the name of the aggregate function and the model field that is being
aggregated. Complex aggregates cannot use anonymous arguments and must specify
a keyword argument as an alias.

For example, when you are working with blog entries, you may want to know the
number of authors that have contributed blog entries:

```
>>> from django.db.models import Count
>>> q = Blog.objects.aggregate(Count('entry'))
{'entry__count': 16}
```

By using a keyword argument to specify the aggregate function, you can
control the name of the aggregation value that is returned:

```
>>> q = Blog.objects.aggregate(number_of_entries=Count('entry'))
{'number_of_entries': 16}
```

集計処理についての深い議論については、 [the topic guide on Aggregation](/ja/4.1/topics/db/aggregation/) を確認してください。

> **Changed in Django 4.1**
>
> `aaggregate()` method was added.

#### `exists()`

#### `exists()`

#### `aexists()`

*Asynchronous version*: `aexists()`

Returns `True` if the [`QuerySet`](#django.db.models.query.QuerySet) contains any results, and `False`
if not. This tries to perform the query in the simplest and fastest way
possible, but it *does* execute nearly the same query as a normal
[`QuerySet`](#django.db.models.query.QuerySet) query.

[`exists()`](#django.db.models.query.QuerySet.exists) is useful for searches relating to the existence of
any objects in a [`QuerySet`](#django.db.models.query.QuerySet), particularly in the context of a large
[`QuerySet`](#django.db.models.query.QuerySet).

To find whether a queryset contains any items:

```
if some_queryset.exists():
    print("There is at least one object in some_queryset")
```

Which will be faster than:

```
if some_queryset:
    print("There is at least one object in some_queryset")
```

... but not by a large degree (hence needing a large queryset for efficiency
gains).

Additionally, if a `some_queryset` has not yet been evaluated, but you know
that it will be at some point, then using `some_queryset.exists()` will do
more overall work (one query for the existence check plus an extra one to later
retrieve the results) than using `bool(some_queryset)`, which retrieves the
results and then checks if any were returned.

> **Changed in Django 4.1**
>
> `aexists()` method was added.

#### `contains()`

#### `contains(obj)`

#### `acontains(obj)`

*Asynchronous version*: `acontains()`

> **New in Django 4.0**

Returns `True` if the [`QuerySet`](#django.db.models.query.QuerySet) contains `obj`, and `False` if
not. This tries to perform the query in the simplest and fastest way possible.

[`contains()`](#django.db.models.query.QuerySet.contains) is useful for checking an object membership in a
[`QuerySet`](#django.db.models.query.QuerySet), particularly in the context of a large [`QuerySet`](#django.db.models.query.QuerySet).

To check whether a queryset contains a specific item:

```
if some_queryset.contains(obj):
    print('Entry contained in queryset')
```

This will be faster than the following which requires evaluating and iterating
through the entire queryset:

```
if obj in some_queryset:
    print('Entry contained in queryset')
```

Like [`exists()`](#django.db.models.query.QuerySet.exists), if `some_queryset` has not yet been evaluated, but you
know that it will be at some point, then using `some_queryset.contains(obj)`
will make an additional database query, generally resulting in slower overall
performance.

> **Changed in Django 4.1**
>
> `acontains()` method was added.

#### `update()`

#### `update(**kwargs)`

#### `aupdate(**kwargs)`

*Asynchronous version*: `aupdate()`

Performs an SQL update query for the specified fields, and returns
the number of rows matched (which may not be equal to the number of rows
updated if some rows already have the new value).

For example, to turn comments off for all blog entries published in 2010,
you could do this:

```
>>> Entry.objects.filter(pub_date__year=2010).update(comments_on=False)
```

(This assumes your `Entry` model has fields `pub_date` and `comments_on`.)

You can update multiple fields — there's no limit on how many. For example,
here we update the `comments_on` and `headline` fields:

```
>>> Entry.objects.filter(pub_date__year=2010).update(comments_on=False, headline='This is old')
```

The `update()` method is applied instantly, and the only restriction on the
[`QuerySet`](#django.db.models.query.QuerySet) that is updated is that it can only update columns in the
model's main table, not on related models. You can't do this, for example:

```
>>> Entry.objects.update(blog__name='foo') # Won't work!
```

Filtering based on related fields is still possible, though:

```
>>> Entry.objects.filter(blog__id=1).update(comments_on=True)
```

You cannot call `update()` on a [`QuerySet`](#django.db.models.query.QuerySet) that has had a slice taken
or can otherwise no longer be filtered.

The `update()` method returns the number of affected rows:

```
>>> Entry.objects.filter(id=64).update(comments_on=True)
1

>>> Entry.objects.filter(slug='nonexistent-slug').update(comments_on=True)
0

>>> Entry.objects.filter(pub_date__year=2010).update(comments_on=False)
132
```

If you're just updating a record and don't need to do anything with the model
object, the most efficient approach is to call `update()`, rather than
loading the model object into memory. For example, instead of doing this:

```
e = Entry.objects.get(id=10)
e.comments_on = False
e.save()
```

...do this:

```
Entry.objects.filter(id=10).update(comments_on=False)
```

Using `update()` also prevents a race condition wherein something might
change in your database in the short period of time between loading the object
and calling `save()`.

Finally, realize that `update()` does an update at the SQL level and, thus,
does not call any `save()` methods on your models, nor does it emit the
[`pre_save`](/ja/4.1/ref/signals/#django.db.models.signals.pre_save) or
[`post_save`](/ja/4.1/ref/signals/#django.db.models.signals.post_save) signals (which are a consequence of
calling [`Model.save()`](/ja/4.1/ref/models/instances/#django.db.models.Model.save)). If you want to
update a bunch of records for a model that has a custom
[`save()`](/ja/4.1/ref/models/instances/#django.db.models.Model.save) method, loop over them and call
[`save()`](/ja/4.1/ref/models/instances/#django.db.models.Model.save), like this:

```
for e in Entry.objects.filter(pub_date__year=2010):
    e.comments_on = False
    e.save()
```

> **Changed in Django 4.1**
>
> `aupdate()` method was added.

##### Ordered queryset

Chaining `order_by()` with `update()` is supported only on MariaDB and
MySQL, and is ignored for different databases. This is useful for updating a
unique field in the order that is specified without conflicts. For example:

```
Entry.objects.order_by('-number').update(number=F('number') + 1)
```

> **Note**
>
> `order_by()` clause will be ignored if it contains annotations, inherited
> fields, or lookups spanning relations.

#### `delete()`

#### `delete()`

#### `adelete()`

*Asynchronous version*: `adelete()`

Performs an SQL delete query on all rows in the [`QuerySet`](#django.db.models.query.QuerySet) and
returns the number of objects deleted and a dictionary with the number of
deletions per object type.

The `delete()` is applied instantly. You cannot call `delete()` on a
[`QuerySet`](#django.db.models.query.QuerySet) that has had a slice taken or can otherwise no longer be
filtered.

For example, to delete all the entries in a particular blog:

```
>>> b = Blog.objects.get(pk=1)

# Delete all the entries belonging to this Blog.
>>> Entry.objects.filter(blog=b).delete()
(4, {'blog.Entry': 2, 'blog.Entry_authors': 2})
```

By default, Django's [`ForeignKey`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey) emulates the SQL
constraint `ON DELETE CASCADE` — in other words, any objects with foreign
keys pointing at the objects to be deleted will be deleted along with them.
For example:

```
>>> blogs = Blog.objects.all()

# This will delete all Blogs and all of their Entry objects.
>>> blogs.delete()
(5, {'blog.Blog': 1, 'blog.Entry': 2, 'blog.Entry_authors': 2})
```

このカスケードの動作は、[`ForeignKey`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey) に対する [`on_delete`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey.on_delete) 属性によってカスタマイズできます。

The `delete()` method does a bulk delete and does not call any `delete()`
methods on your models. It does, however, emit the
[`pre_delete`](/ja/4.1/ref/signals/#django.db.models.signals.pre_delete) and
[`post_delete`](/ja/4.1/ref/signals/#django.db.models.signals.post_delete) signals for all deleted objects
(including cascaded deletions).

Django needs to fetch objects into memory to send signals and handle cascades.
However, if there are no cascades and no signals, then Django may take a
fast-path and delete objects without fetching into memory. For large
deletes this can result in significantly reduced memory usage. The amount of
executed queries can be reduced, too.

ForeignKeys which are set to [`on_delete`](/ja/4.1/ref/models/fields/#django.db.models.ForeignKey.on_delete)
`DO_NOTHING` do not prevent taking the fast-path in deletion.

Note that the queries generated in object deletion is an implementation
detail subject to change.

> **Changed in Django 4.1**
>
> `adelete()` method was added.

#### `as_manager()`

#### `classmethod as_manager()`

Class method that returns an instance of [`Manager`](/ja/4.1/topics/db/managers/#django.db.models.Manager)
with a copy of the `QuerySet`’s methods. See
[QuerySet のメソッドで、マネージャを生成する](/ja/4.1/topics/db/managers/#create-manager-with-queryset-methods) for more details.

Note that unlike the other entries in this section, this does not have an
asynchronous variant as it does not execute a query.

#### `explain()`

#### `explain(format=None, **options)`

#### `aexplain(format=None, **options)`

*Asynchronous version*: `aexplain()`

Returns a string of the `QuerySet`’s execution plan, which details how the
database would execute the query, including any indexes or joins that would be
used. Knowing these details may help you improve the performance of slow
queries.

For example, when using PostgreSQL:

```
>>> print(Blog.objects.filter(title='My Blog').explain())
Seq Scan on blog  (cost=0.00..35.50 rows=10 width=12)
  Filter: (title = 'My Blog'::bpchar)
```

The output differs significantly between databases.

`explain()` is supported by all built-in database backends except Oracle
because an implementation there isn't straightforward.

The `format` parameter changes the output format from the databases's
default, which is usually text-based. PostgreSQL supports `'TEXT'`,
`'JSON'`, `'YAML'`, and `'XML'` formats. MariaDB and MySQL support
`'TEXT'` (also called `'TRADITIONAL'`) and `'JSON'` formats. MySQL
8.0.16+ also supports an improved `'TREE'` format, which is similar to
PostgreSQL's `'TEXT'` output and is used by default, if supported.

Some databases accept flags that can return more information about the query.
Pass these flags as keyword arguments. For example, when using PostgreSQL:

```
>>> print(Blog.objects.filter(title='My Blog').explain(verbose=True, analyze=True))
Seq Scan on public.blog  (cost=0.00..35.50 rows=10 width=12) (actual time=0.004..0.004 rows=10 loops=1)
  Output: id, title
  Filter: (blog.title = 'My Blog'::bpchar)
Planning time: 0.064 ms
Execution time: 0.058 ms
```

On some databases, flags may cause the query to be executed which could have
adverse effects on your database. For example, the `ANALYZE` flag supported
by MariaDB, MySQL 8.0.18+, and PostgreSQL could result in changes to data if
there are triggers or if a function is called, even for a `SELECT` query.

> **Changed in Django 4.1**
>
> `aexplain()` method was added.

### `Field` lookups

Field lookups are how you specify the meat of an SQL `WHERE` clause. They're
specified as keyword arguments to the `QuerySet` methods [`filter()`](#django.db.models.query.QuerySet.filter),
[`exclude()`](#django.db.models.query.QuerySet.exclude) and [`get()`](#django.db.models.query.QuerySet.get).

For an introduction, see [models and database queries documentation](/ja/4.1/topics/db/queries/#field-lookups-intro).

Django's built-in lookups are listed below. It is also possible to write
[custom lookups](/ja/4.1/howto/custom-lookups/) for model fields.

As a convenience when no lookup type is provided (like in
`Entry.objects.get(id=14)`) the lookup type is assumed to be [`exact`](#std-fieldlookup-exact).

#### `exact`

Exact match. If the value provided for comparison is `None`, it will be
interpreted as an SQL `NULL` (see [`isnull`](#std-fieldlookup-isnull) for more details).

例:

```
Entry.objects.get(id__exact=14)
Entry.objects.get(id__exact=None)
```

SQL equivalents:

```sql
SELECT ... WHERE id = 14;
SELECT ... WHERE id IS NULL;
```

> **MySQL comparisons**
>
> In MySQL, a database table's "collation" setting determines whether
> `exact` comparisons are case-sensitive. This is a database setting, *not*
> a Django setting. It's possible to configure your MySQL tables to use
> case-sensitive comparisons, but some trade-offs are involved. For more
> information about this, see the [collation section](/ja/4.1/ref/databases/#mysql-collation)
> in the [databases](/ja/4.1/ref/databases/) documentation.

#### `iexact`

Case-insensitive exact match. If the value provided for comparison is `None`,
it will be interpreted as an SQL `NULL` (see [`isnull`](#std-fieldlookup-isnull) for more
details).

実装例:

```
Blog.objects.get(name__iexact='beatles blog')
Blog.objects.get(name__iexact=None)
```

SQL equivalents:

```sql
SELECT ... WHERE name ILIKE 'beatles blog';
SELECT ... WHERE name IS NULL;
```

Note the first query will match `'Beatles Blog'`, `'beatles blog'`,
`'BeAtLes BLoG'`, etc.

> **SQLite users**
>
> When using the SQLite backend and non-ASCII strings, bear in mind the
> [database note](/ja/4.1/ref/databases/#sqlite-string-matching) about string comparisons.
> SQLite does not do case-insensitive matching for non-ASCII strings.

#### `contains`

Case-sensitive containment test.

実装例:

```
Entry.objects.get(headline__contains='Lennon')
```

SQL equivalent:

```sql
SELECT ... WHERE headline LIKE '%Lennon%';
```

Note this will match the headline `'Lennon honored today'` but not `'lennon
honored today'`.

> **SQLite users**
>
> SQLite doesn't support case-sensitive `LIKE` statements; `contains`
> acts like `icontains` for SQLite. See the [database note](/ja/4.1/ref/databases/#sqlite-string-matching) for more information.

#### `icontains`

Case-insensitive containment test.

実装例:

```
Entry.objects.get(headline__icontains='Lennon')
```

SQL equivalent:

```sql
SELECT ... WHERE headline ILIKE '%Lennon%';
```

> **SQLite users**
>
> When using the SQLite backend and non-ASCII strings, bear in mind the
> [database note](/ja/4.1/ref/databases/#sqlite-string-matching) about string comparisons.

#### `in`

In a given iterable; often a list, tuple, or queryset. It's not a common use
case, but strings (being iterables) are accepted.

例:

```
Entry.objects.filter(id__in=[1, 3, 4])
Entry.objects.filter(headline__in='abc')
```

SQL equivalents:

```sql
SELECT ... WHERE id IN (1, 3, 4);
SELECT ... WHERE headline IN ('a', 'b', 'c');
```

You can also use a queryset to dynamically evaluate the list of values
instead of providing a list of literal values:

```
inner_qs = Blog.objects.filter(name__contains='Cheddar')
entries = Entry.objects.filter(blog__in=inner_qs)
```

This queryset will be evaluated as subselect statement:

```sql
SELECT ... WHERE blog.id IN (SELECT id FROM ... WHERE NAME LIKE '%Cheddar%')
```

If you pass in a `QuerySet` resulting from `values()` or `values_list()`
as the value to an `__in` lookup, you need to ensure you are only extracting
one field in the result. For example, this will work (filtering on the blog
names):

```
inner_qs = Blog.objects.filter(name__contains='Ch').values('name')
entries = Entry.objects.filter(blog__name__in=inner_qs)
```

This example will raise an exception, since the inner query is trying to
extract two field values, where only one is expected:

```
# Bad code! Will raise a TypeError.
inner_qs = Blog.objects.filter(name__contains='Ch').values('name', 'id')
entries = Entry.objects.filter(blog__name__in=inner_qs)
```

> **Performance considerations**
>
> Be cautious about using nested queries and understand your database
> server's performance characteristics (if in doubt, benchmark!). Some
> database backends, most notably MySQL, don't optimize nested queries very
> well. It is more efficient, in those cases, to extract a list of values
> and then pass that into the second query. That is, execute two queries
> instead of one:
>
> ```
> values = Blog.objects.filter(
>         name__contains='Cheddar').values_list('pk', flat=True)
> entries = Entry.objects.filter(blog__in=list(values))
> ```
>
> Note the `list()` call around the Blog `QuerySet` to force execution of
> the first query. Without it, a nested query would be executed, because
> [QuerySet は遅延評価される](/ja/4.1/topics/db/queries/#querysets-are-lazy).

#### `gt`

Greater than.

実装例:

```
Entry.objects.filter(id__gt=4)
```

SQL equivalent:

```sql
SELECT ... WHERE id > 4;
```

#### `gte`

Greater than or equal to.

#### `lt`

Less than.

#### `lte`

Less than or equal to.

#### `startswith`

Case-sensitive starts-with.

実装例:

```
Entry.objects.filter(headline__startswith='Lennon')
```

SQL equivalent:

```sql
SELECT ... WHERE headline LIKE 'Lennon%';
```

SQLite doesn't support case-sensitive `LIKE` statements; `startswith` acts
like `istartswith` for SQLite.

#### `istartswith`

Case-insensitive starts-with.

実装例:

```
Entry.objects.filter(headline__istartswith='Lennon')
```

SQL equivalent:

```sql
SELECT ... WHERE headline ILIKE 'Lennon%';
```

> **SQLite users**
>
> When using the SQLite backend and non-ASCII strings, bear in mind the
> [database note](/ja/4.1/ref/databases/#sqlite-string-matching) about string comparisons.

#### `endswith`

Case-sensitive ends-with.

実装例:

```
Entry.objects.filter(headline__endswith='Lennon')
```

SQL equivalent:

```sql
SELECT ... WHERE headline LIKE '%Lennon';
```

> **SQLite users**
>
> SQLite doesn't support case-sensitive `LIKE` statements; `endswith`
> acts like `iendswith` for SQLite. Refer to the [database note](/ja/4.1/ref/databases/#sqlite-string-matching) documentation for more.

#### `iendswith`

Case-insensitive ends-with.

実装例:

```
Entry.objects.filter(headline__iendswith='Lennon')
```

SQL equivalent:

```sql
SELECT ... WHERE headline ILIKE '%Lennon'
```

> **SQLite users**
>
> When using the SQLite backend and non-ASCII strings, bear in mind the
> [database note](/ja/4.1/ref/databases/#sqlite-string-matching) about string comparisons.

#### `range`

Range test (inclusive).

実装例:

```
import datetime
start_date = datetime.date(2005, 1, 1)
end_date = datetime.date(2005, 3, 31)
Entry.objects.filter(pub_date__range=(start_date, end_date))
```

SQL equivalent:

```sql
SELECT ... WHERE pub_date BETWEEN '2005-01-01' and '2005-03-31';
```

You can use `range` anywhere you can use `BETWEEN` in SQL — for dates,
numbers and even characters.

> **Warning**
>
> Filtering a `DateTimeField` with dates won't include items on the last
> day, because the bounds are interpreted as "0am on the given date". If
> `pub_date` was a `DateTimeField`, the above expression would be turned
> into this SQL:
>
> ```sql
> SELECT ... WHERE pub_date BETWEEN '2005-01-01 00:00:00' and '2005-03-31 00:00:00';
> ```
>
> Generally speaking, you can't mix dates and datetimes.

#### `date`

For datetime fields, casts the value as date. Allows chaining additional field
lookups. Takes a date value.

実装例:

```
Entry.objects.filter(pub_date__date=datetime.date(2005, 1, 1))
Entry.objects.filter(pub_date__date__gt=datetime.date(2005, 1, 1))
```

(No equivalent SQL code fragment is included for this lookup because
implementation of the relevant query varies among different database engines.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, fields are converted to the current time
zone before filtering. This requires [time zone definitions in the
database](#database-time-zone-definitions).

#### `year`

For date and datetime fields, an exact year match. Allows chaining additional
field lookups. Takes an integer year.

実装例:

```
Entry.objects.filter(pub_date__year=2005)
Entry.objects.filter(pub_date__year__gte=2005)
```

SQL equivalent:

```sql
SELECT ... WHERE pub_date BETWEEN '2005-01-01' AND '2005-12-31';
SELECT ... WHERE pub_date >= '2005-01-01';
```

(The exact SQL syntax varies for each database engine.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `iso_year`

For date and datetime fields, an exact ISO 8601 week-numbering year match.
Allows chaining additional field lookups. Takes an integer year.

実装例:

```
Entry.objects.filter(pub_date__iso_year=2005)
Entry.objects.filter(pub_date__iso_year__gte=2005)
```

(The exact SQL syntax varies for each database engine.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `month`

For date and datetime fields, an exact month match. Allows chaining additional
field lookups. Takes an integer 1 (January) through 12 (December).

実装例:

```
Entry.objects.filter(pub_date__month=12)
Entry.objects.filter(pub_date__month__gte=6)
```

SQL equivalent:

```sql
SELECT ... WHERE EXTRACT('month' FROM pub_date) = '12';
SELECT ... WHERE EXTRACT('month' FROM pub_date) >= '6';
```

(The exact SQL syntax varies for each database engine.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `day`

For date and datetime fields, an exact day match. Allows chaining additional
field lookups. Takes an integer day.

実装例:

```
Entry.objects.filter(pub_date__day=3)
Entry.objects.filter(pub_date__day__gte=3)
```

SQL equivalent:

```sql
SELECT ... WHERE EXTRACT('day' FROM pub_date) = '3';
SELECT ... WHERE EXTRACT('day' FROM pub_date) >= '3';
```

(The exact SQL syntax varies for each database engine.)

Note this will match any record with a pub\_date on the third day of the month,
such as January 3, July 3, etc.

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `week`

For date and datetime fields, return the week number (1-52 or 53) according
to [ISO-8601](https://en.wikipedia.org/wiki/ISO-8601), i.e., weeks start
on a Monday and the first week contains the year's first Thursday.

実装例:

```
Entry.objects.filter(pub_date__week=52)
Entry.objects.filter(pub_date__week__gte=32, pub_date__week__lte=38)
```

(No equivalent SQL code fragment is included for this lookup because
implementation of the relevant query varies among different database engines.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `week_day`

For date and datetime fields, a 'day of the week' match. Allows chaining
additional field lookups.

Takes an integer value representing the day of week from 1 (Sunday) to 7
(Saturday).

実装例:

```
Entry.objects.filter(pub_date__week_day=2)
Entry.objects.filter(pub_date__week_day__gte=2)
```

(No equivalent SQL code fragment is included for this lookup because
implementation of the relevant query varies among different database engines.)

Note this will match any record with a `pub_date` that falls on a Monday (day
2 of the week), regardless of the month or year in which it occurs. Week days
are indexed with day 1 being Sunday and day 7 being Saturday.

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `iso_week_day`

For date and datetime fields, an exact ISO 8601 day of the week match. Allows
chaining additional field lookups.

Takes an integer value representing the day of the week from 1 (Monday) to 7
(Sunday).

実装例:

```
Entry.objects.filter(pub_date__iso_week_day=1)
Entry.objects.filter(pub_date__iso_week_day__gte=1)
```

(No equivalent SQL code fragment is included for this lookup because
implementation of the relevant query varies among different database engines.)

Note this will match any record with a `pub_date` that falls on a Monday (day
1 of the week), regardless of the month or year in which it occurs. Week days
are indexed with day 1 being Monday and day 7 being Sunday.

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `quarter`

For date and datetime fields, a 'quarter of the year' match. Allows chaining
additional field lookups. Takes an integer value between 1 and 4 representing
the quarter of the year.

Example to retrieve entries in the second quarter (April 1 to June 30):

```
Entry.objects.filter(pub_date__quarter=2)
```

(No equivalent SQL code fragment is included for this lookup because
implementation of the relevant query varies among different database engines.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `time`

For datetime fields, casts the value as time. Allows chaining additional field
lookups. Takes a [`datetime.time`](https://docs.python.org/3/library/datetime.html#datetime.time) value.

実装例:

```
Entry.objects.filter(pub_date__time=datetime.time(14, 30))
Entry.objects.filter(pub_date__time__range=(datetime.time(8), datetime.time(17)))
```

(No equivalent SQL code fragment is included for this lookup because
implementation of the relevant query varies among different database engines.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, fields are converted to the current time
zone before filtering. This requires [time zone definitions in the
database](#database-time-zone-definitions).

#### `hour`

For datetime and time fields, an exact hour match. Allows chaining additional
field lookups. Takes an integer between 0 and 23.

実装例:

```
Event.objects.filter(timestamp__hour=23)
Event.objects.filter(time__hour=5)
Event.objects.filter(timestamp__hour__gte=12)
```

SQL equivalent:

```sql
SELECT ... WHERE EXTRACT('hour' FROM timestamp) = '23';
SELECT ... WHERE EXTRACT('hour' FROM time) = '5';
SELECT ... WHERE EXTRACT('hour' FROM timestamp) >= '12';
```

(The exact SQL syntax varies for each database engine.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `minute`

For datetime and time fields, an exact minute match. Allows chaining additional
field lookups. Takes an integer between 0 and 59.

実装例:

```
Event.objects.filter(timestamp__minute=29)
Event.objects.filter(time__minute=46)
Event.objects.filter(timestamp__minute__gte=29)
```

SQL equivalent:

```sql
SELECT ... WHERE EXTRACT('minute' FROM timestamp) = '29';
SELECT ... WHERE EXTRACT('minute' FROM time) = '46';
SELECT ... WHERE EXTRACT('minute' FROM timestamp) >= '29';
```

(The exact SQL syntax varies for each database engine.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `second`

For datetime and time fields, an exact second match. Allows chaining additional
field lookups. Takes an integer between 0 and 59.

実装例:

```
Event.objects.filter(timestamp__second=31)
Event.objects.filter(time__second=2)
Event.objects.filter(timestamp__second__gte=31)
```

SQL equivalent:

```sql
SELECT ... WHERE EXTRACT('second' FROM timestamp) = '31';
SELECT ... WHERE EXTRACT('second' FROM time) = '2';
SELECT ... WHERE EXTRACT('second' FROM timestamp) >= '31';
```

(The exact SQL syntax varies for each database engine.)

When [`USE_TZ`](/ja/4.1/ref/settings/#std-setting-USE_TZ) is `True`, datetime fields are converted to the
current time zone before filtering. This requires [time zone definitions
in the database](#database-time-zone-definitions).

#### `isnull`

Takes either `True` or `False`, which correspond to SQL queries of
`IS NULL` and `IS NOT NULL`, respectively.

実装例:

```
Entry.objects.filter(pub_date__isnull=True)
```

SQL equivalent:

```sql
SELECT ... WHERE pub_date IS NULL;
```

#### `regex`

Case-sensitive regular expression match.

The regular expression syntax is that of the database backend in use.
In the case of SQLite, which has no built in regular expression support,
this feature is provided by a (Python) user-defined REGEXP function, and
the regular expression syntax is therefore that of Python's `re` module.

実装例:

```
Entry.objects.get(title__regex=r'^(An?|The) +')
```

SQL equivalents:

```sql
SELECT ... WHERE title REGEXP BINARY '^(An?|The) +'; -- MySQL

SELECT ... WHERE REGEXP_LIKE(title, '^(An?|The) +', 'c'); -- Oracle

SELECT ... WHERE title ~ '^(An?|The) +'; -- PostgreSQL

SELECT ... WHERE title REGEXP '^(An?|The) +'; -- SQLite
```

Using raw strings (e.g., `r'foo'` instead of `'foo'`) for passing in the
regular expression syntax is recommended.

#### `iregex`

Case-insensitive regular expression match.

実装例:

```
Entry.objects.get(title__iregex=r'^(an?|the) +')
```

SQL equivalents:

```sql
SELECT ... WHERE title REGEXP '^(an?|the) +'; -- MySQL

SELECT ... WHERE REGEXP_LIKE(title, '^(an?|the) +', 'i'); -- Oracle

SELECT ... WHERE title ~* '^(an?|the) +'; -- PostgreSQL

SELECT ... WHERE title REGEXP '(?i)^(an?|the) +'; -- SQLite
```

### Aggregation functions

Django provides the following aggregation functions in the
`django.db.models` module. For details on how to use these
aggregate functions, see [the topic guide on aggregation](/ja/4.1/topics/db/aggregation/). See the [`Aggregate`](/ja/4.1/ref/models/expressions/#django.db.models.Aggregate)
documentation to learn how to create your aggregates.

> **Warning**
>
> SQLite can't handle aggregation on date/time fields out of the box.
> This is because there are no native date/time fields in SQLite and Django
> currently emulates these features using a text field. Attempts to use
> aggregation on date/time fields in SQLite will raise `NotSupportedError`.

> **ノート**
>
> Aggregation functions return `None` when used with an empty
> `QuerySet`. For example, the `Sum` aggregation function returns `None`
> instead of `0` if the `QuerySet` contains no entries. To return another
> value instead, pass a value to the `default` argument. An exception is
> `Count`, which does return `0` if the `QuerySet` is empty. `Count`
> does not support the `default` argument.

All aggregates have the following parameters in common:

#### `expressions`

Strings that reference fields on the model, transforms of the field, or
[query expressions](/ja/4.1/ref/models/expressions/).

#### `output_field`

An optional argument that represents the [model field](/ja/4.1/ref/models/fields/)
of the return value

> **Note**
>
> When combining multiple field types, Django can only determine the
> `output_field` if all fields are of the same type. Otherwise, you
> must provide the `output_field` yourself.

#### `filter`

An optional [`Q object`](#django.db.models.Q) that's used to filter the
rows that are aggregated.

See [Conditional aggregation](/ja/4.1/ref/models/conditional-expressions/#conditional-aggregation) and [Filtering on annotations](/ja/4.1/topics/db/aggregation/#filtering-on-annotations) for
example usage.

#### `default`

> **New in Django 4.0**

An optional argument that allows specifying a value to use as a default value
when the queryset (or grouping) contains no entries.

#### `**extra`

Keyword arguments that can provide extra context for the SQL generated
by the aggregate.

#### `Avg`

#### `class Avg(expression, output_field=None, distinct=False, filter=None, default=None, **extra)`

Returns the mean value of the given expression, which must be numeric
unless you specify a different `output_field`.

- Default alias: `<field>__avg`
- Return type: `float` if input is `int`, otherwise same as input
  field, or `output_field` if supplied

#### `distinct`

Optional. If `distinct=True`, `Avg` returns the mean value of
unique values. This is the SQL equivalent of `AVG(DISTINCT <field>)`.
The default value is `False`.

#### `Count`

#### `class Count(expression, distinct=False, filter=None, **extra)`

Returns the number of objects that are related through the provided
expression.

- Default alias: `<field>__count`
- Return type: `int`

#### `distinct`

Optional. If `distinct=True`, the count will only include unique
instances. This is the SQL equivalent of `COUNT(DISTINCT <field>)`.
The default value is `False`.

> **Note**
>
> The `default` argument is not supported.

#### `Max`

#### `class Max(expression, output_field=None, filter=None, default=None, **extra)`

Returns the maximum value of the given expression.

- Default alias: `<field>__max`
- Return type: same as input field, or `output_field` if supplied

#### `Min`

#### `class Min(expression, output_field=None, filter=None, default=None, **extra)`

Returns the minimum value of the given expression.

- Default alias: `<field>__min`
- Return type: same as input field, or `output_field` if supplied

#### `StdDev`

#### `class StdDev(expression, output_field=None, sample=False, filter=None, default=None, **extra)`

Returns the standard deviation of the data in the provided expression.

- Default alias: `<field>__stddev`
- Return type: `float` if input is `int`, otherwise same as input
  field, or `output_field` if supplied

#### `sample`

Optional. By default, `StdDev` returns the population standard
deviation. However, if `sample=True`, the return value will be the
sample standard deviation.

#### `Sum`

#### `class Sum(expression, output_field=None, distinct=False, filter=None, default=None, **extra)`

Computes the sum of all values of the given expression.

- Default alias: `<field>__sum`
- Return type: same as input field, or `output_field` if supplied

#### `distinct`

Optional. If `distinct=True`, `Sum` returns the sum of unique
values. This is the SQL equivalent of `SUM(DISTINCT <field>)`. The
default value is `False`.

#### `Variance`

#### `class Variance(expression, output_field=None, sample=False, filter=None, default=None, **extra)`

Returns the variance of the data in the provided expression.

- Default alias: `<field>__variance`
- Return type: `float` if input is `int`, otherwise same as input
  field, or `output_field` if supplied

#### `sample`

Optional. By default, `Variance` returns the population variance.
However, if `sample=True`, the return value will be the sample
variance.

## Query-related tools

This section provides reference material for query-related tools not documented
elsewhere.

### `Q()` objects

#### `class Q`

A `Q()` object represents an SQL condition that can be used in
database-related operations. It's similar to how an
[`F()`](/ja/4.1/ref/models/expressions/#django.db.models.F) object represents the value of a model field
or annotation. They make it possible to define and reuse conditions, and
combine them using operators such as `|` (`OR`), `&` (`AND`), and `^`
(`XOR`). See [Q オブジェクトを用いた複雑な検索](/ja/4.1/topics/db/queries/#complex-lookups-with-q).

> **Changed in Django 4.1**
>
> Support for the `^` (`XOR`) operator was added.

### `Prefetch()` objects

#### `class Prefetch(lookup, queryset=None, to_attr=None)`

The `Prefetch()` object can be used to control the operation of
[`prefetch_related()`](#django.db.models.query.QuerySet.prefetch_related).

The `lookup` argument describes the relations to follow and works the same
as the string based lookups passed to
[`prefetch_related()`](#django.db.models.query.QuerySet.prefetch_related). For example:

```
>>> from django.db.models import Prefetch
>>> Question.objects.prefetch_related(Prefetch('choice_set')).get().choice_set.all()
<QuerySet [<Choice: Not much>, <Choice: The sky>, <Choice: Just hacking again>]>
# This will only execute two queries regardless of the number of Question
# and Choice objects.
>>> Question.objects.prefetch_related(Prefetch('choice_set'))
<QuerySet [<Question: What's up?>]>
```

The `queryset` argument supplies a base `QuerySet` for the given lookup.
This is useful to further filter down the prefetch operation, or to call
[`select_related()`](#django.db.models.query.QuerySet.select_related) from the prefetched
relation, hence reducing the number of queries even further:

```
>>> voted_choices = Choice.objects.filter(votes__gt=0)
>>> voted_choices
<QuerySet [<Choice: The sky>]>
>>> prefetch = Prefetch('choice_set', queryset=voted_choices)
>>> Question.objects.prefetch_related(prefetch).get().choice_set.all()
<QuerySet [<Choice: The sky>]>
```

The `to_attr` argument sets the result of the prefetch operation to a custom
attribute:

```
>>> prefetch = Prefetch('choice_set', queryset=voted_choices, to_attr='voted_choices')
>>> Question.objects.prefetch_related(prefetch).get().voted_choices
[<Choice: The sky>]
>>> Question.objects.prefetch_related(prefetch).get().choice_set.all()
<QuerySet [<Choice: Not much>, <Choice: The sky>, <Choice: Just hacking again>]>
```

> **Note**
>
> When using `to_attr` the prefetched result is stored in a list. This can
> provide a significant speed improvement over traditional
> `prefetch_related` calls which store the cached result within a
> `QuerySet` instance.

### `prefetch_related_objects()`

#### `prefetch_related_objects(model_instances, *related_lookups)`

Prefetches the given lookups on an iterable of model instances. This is useful
in code that receives a list of model instances as opposed to a `QuerySet`;
for example, when fetching models from a cache or instantiating them manually.

Pass an iterable of model instances (must all be of the same class) and the
lookups or [`Prefetch`](#django.db.models.Prefetch) objects you want to prefetch for. For example:

```
>>> from django.db.models import prefetch_related_objects
>>> restaurants = fetch_top_restaurants_from_cache()  # A list of Restaurants
>>> prefetch_related_objects(restaurants, 'pizzas__toppings')
```

When using multiple databases with `prefetch_related_objects`, the prefetch
query will use the database associated with the model instance. This can be
overridden by using a custom queryset in a related lookup.

### `FilteredRelation()` objects

#### `class FilteredRelation(relation_name, * (Keyword-only parameters separator (PEP 3102)), condition=Q())`

#### `relation_name`

The name of the field on which you'd like to filter the relation.

#### `condition`

A [`Q`](#django.db.models.Q) object to control the filtering.

`FilteredRelation` is used with [`annotate()`](#django.db.models.query.QuerySet.annotate) to create an
`ON` clause when a `JOIN` is performed. It doesn't act on the default
relationship but on the annotation name (`pizzas_vegetarian` in example
below).

For example, to find restaurants that have vegetarian pizzas with
`'mozzarella'` in the name:

```
>>> from django.db.models import FilteredRelation, Q
>>> Restaurant.objects.annotate(
...    pizzas_vegetarian=FilteredRelation(
...        'pizzas', condition=Q(pizzas__vegetarian=True),
...    ),
... ).filter(pizzas_vegetarian__name__icontains='mozzarella')
```

If there are a large number of pizzas, this queryset performs better than:

```
>>> Restaurant.objects.filter(
...     pizzas__vegetarian=True,
...     pizzas__name__icontains='mozzarella',
... )
```

because the filtering in the `WHERE` clause of the first queryset will only
operate on vegetarian pizzas.

`FilteredRelation` doesn't support:

- [`QuerySet.only()`](#django.db.models.query.QuerySet.only) and [`prefetch_related()`](#django.db.models.query.QuerySet.prefetch_related).
- A [`GenericForeignKey`](/ja/4.1/ref/contrib/contenttypes/#django.contrib.contenttypes.fields.GenericForeignKey)
  inherited from a parent model.