---
title: "条件表达式"
version: 6.0
locale: zh-hans
source: https://docs.djangoproject.com/zh-hans/6.0/ref/models/conditional-expressions/
canonical: https://djangodocs.dev/zh-hans/6.0/ref/models/conditional-expressions/
---
# 条件表达式

Conditional expressions let you use [`if`](https://docs.python.org/3/reference/compound_stmts.html#if) ... [`elif`](https://docs.python.org/3/reference/compound_stmts.html#elif) ...
[`else`](https://docs.python.org/3/reference/compound_stmts.html#else) logic within filters, annotations, aggregations, and updates. A
conditional expression evaluates a series of conditions for each row of a table
and returns the matching result expression. Conditional expressions can also be
combined and nested like other [expressions](/zh-hans/6.0/ref/models/expressions/).

## 条件表达式类

在后续的例子中，我们将使用以下模型：

```
from django.db import models

class Client(models.Model):
    REGULAR = "R"
    GOLD = "G"
    PLATINUM = "P"
    ACCOUNT_TYPE_CHOICES = {
        REGULAR: "Regular",
        GOLD: "Gold",
        PLATINUM: "Platinum",
    }
    name = models.CharField(max_length=50)
    registered_on = models.DateField()
    account_type = models.CharField(
        max_length=1,
        choices=ACCOUNT_TYPE_CHOICES,
        default=REGULAR,
    )
```

### `When`

#### `class When(condition=None, then=None, **lookups)`

`When()` 对象用于封装一个条件及其结果，以便在条件表达式中使用。使用 `When()` 对象类似于使用 [`filter()`](/zh-hans/6.0/ref/models/querysets/#django.db.models.query.QuerySet.filter) 方法。可以使用 [字段查找](/zh-hans/6.0/ref/models/querysets/#field-lookups)、 [`Q`](/zh-hans/6.0/ref/models/querysets/#django.db.models.Q) 对象或 [`Expression`](/zh-hans/6.0/ref/models/expressions/#django.db.models.Expression) 对象来指定条件，这些对象的 `output_field` 是 [`BooleanField`](/zh-hans/6.0/ref/models/fields/#django.db.models.BooleanField)。结果是用 `then` 关键字提供的。

一些示例：

```pycon
>>> from django.db.models import F, Q, When
>>> # String arguments refer to fields; the following two examples are equivalent:
>>> When(account_type=Client.GOLD, then="name")
>>> When(account_type=Client.GOLD, then=F("name"))
>>> # You can use field lookups in the condition
>>> from datetime import date
>>> When(
...     registered_on__gt=date(2014, 1, 1),
...     registered_on__lt=date(2015, 1, 1),
...     then="account_type",
... )
>>> # Complex conditions can be created using Q objects
>>> When(Q(name__startswith="John") | Q(name__startswith="Paul"), then="name")
>>> # Condition can be created using boolean expressions.
>>> from django.db.models import Exists, OuterRef
>>> non_unique_account_type = (
...     Client.objects.filter(
...         account_type=OuterRef("account_type"),
...     )
...     .exclude(pk=OuterRef("pk"))
...     .values("pk")
... )
>>> When(Exists(non_unique_account_type), then=Value("non unique"))
>>> # Condition can be created using lookup expressions.
>>> from django.db.models.lookups import GreaterThan, LessThan
>>> When(
...     GreaterThan(F("registered_on"), date(2014, 1, 1))
...     & LessThan(F("registered_on"), date(2015, 1, 1)),
...     then="account_type",
... )
```

请记住，每个值都可以是一个表达式。

> **Note**
>
> 由于 `then` 关键字参数用于 `When()` 的结果，如果一个 [`Model`](/zh-hans/6.0/ref/models/instances/#django.db.models.Model) 具有一个名为 `then` 的字段，可能会存在潜在冲突。这可以通过以下两种方式解决：
>
> ```pycon
> >>> When(then__exact=0, then=1)
> >>> When(Q(then=0), then=1)
> ```

### `Case`

#### `class Case(*cases, **extra)`

`Case()` 表达式就像 `Python` 中的 [`if`](https://docs.python.org/3/reference/compound_stmts.html#if)... [`elif`](https://docs.python.org/3/reference/compound_stmts.html#elif)... [`else`](https://docs.python.org/3/reference/compound_stmts.html#else) 语句。在提供的 `When()` 对象中的每个 `condition` 按顺序执行，直到执行出一个对的值。从匹配的 `When()` 对象中返回 `result` 表达式。

例子：

```pycon
>>>
>>> from datetime import date, timedelta
>>> from django.db.models import Case, Value, When
>>> Client.objects.create(
...     name="Jane Doe",
...     account_type=Client.REGULAR,
...     registered_on=date.today() - timedelta(days=36),
... )
>>> Client.objects.create(
...     name="James Smith",
...     account_type=Client.GOLD,
...     registered_on=date.today() - timedelta(days=5),
... )
>>> Client.objects.create(
...     name="Jack Black",
...     account_type=Client.PLATINUM,
...     registered_on=date.today() - timedelta(days=10 * 365),
... )
>>> # Get the discount for each Client based on the account type
>>> Client.objects.annotate(
...     discount=Case(
...         When(account_type=Client.GOLD, then=Value("5%")),
...         When(account_type=Client.PLATINUM, then=Value("10%")),
...         default=Value("0%"),
...     ),
... ).values_list("name", "discount")
<QuerySet [('Jane Doe', '0%'), ('James Smith', '5%'), ('Jack Black', '10%')]>
```

`Case()` 接受任意数量的 `When()` 对象作为单个参数。其他选项是通过关键字参数提供的。如果没有一个条件的值是 `TRUE`，那么将返回用 `default` 关键字参数给出的表达式。如果没有提供 `default` 参数，则使用 `None`。

如果我们想要根据客户与我们的关系时间来更改之前的查询以获取折扣，我们可以使用查找操作来实现：

```pycon
>>> a_month_ago = date.today() - timedelta(days=30)
>>> a_year_ago = date.today() - timedelta(days=365)
>>> # Get the discount for each Client based on the registration date
>>> Client.objects.annotate(
...     discount=Case(
...         When(registered_on__lte=a_year_ago, then=Value("10%")),
...         When(registered_on__lte=a_month_ago, then=Value("5%")),
...         default=Value("0%"),
...     )
... ).values_list("name", "discount")
<QuerySet [('Jane Doe', '5%'), ('James Smith', '0%'), ('Jack Black', '10%')]>
```

> **Note**
>
> 请记住，条件是按顺序计算的，所以在上面的例子中，尽管第二个条件同时符合 Jane Doe 和 Jack Black，我们还是得到了正确的结果。这就像在 `Python` 中的 [`if`](https://docs.python.org/3/reference/compound_stmts.html#if)... [`elif`](https://docs.python.org/3/reference/compound_stmts.html#elif)... [`else`](https://docs.python.org/3/reference/compound_stmts.html#else) 语句一样。

`Case()` 也可以在 `filter()` 子句中使用。例如，要查找在一个月前注册的金牌客户和在一年前注册的铂金客户：

```pycon
>>> a_month_ago = date.today() - timedelta(days=30)
>>> a_year_ago = date.today() - timedelta(days=365)
>>> Client.objects.filter(
...     registered_on__lte=Case(
...         When(account_type=Client.GOLD, then=a_month_ago),
...         When(account_type=Client.PLATINUM, then=a_year_ago),
...     ),
... ).values_list("name", "account_type")
<QuerySet [('Jack Black', 'P')]>
```

## 高级查询

条件表达式可用于注解、聚合、过滤器、查找和更新中。它们还可以与其他表达式组合和嵌套。这使你可以进行强大的条件查询。

### 条件更新

假设我们想要根据客户的注册日期更改其 `account_type`。我们可以使用条件表达式和 [`update()`](/zh-hans/6.0/ref/models/querysets/#django.db.models.query.QuerySet.update) 方法来实现：

```pycon
>>> a_month_ago = date.today() - timedelta(days=30)
>>> a_year_ago = date.today() - timedelta(days=365)
>>> # Update the account_type for each Client from the registration date
>>> Client.objects.update(
...     account_type=Case(
...         When(registered_on__lte=a_year_ago, then=Value(Client.PLATINUM)),
...         When(registered_on__lte=a_month_ago, then=Value(Client.GOLD)),
...         default=Value(Client.REGULAR),
...     ),
... )
>>> Client.objects.values_list("name", "account_type")
<QuerySet [('Jane Doe', 'G'), ('James Smith', 'R'), ('Jack Black', 'P')]>
```

### 条件聚合

如果我们想要找出每种 `account_type` 有多少客户，我们可以使用 [聚合函数](/zh-hans/6.0/ref/models/querysets/#aggregation-functions) 的 `filter` 参数来实现：

```pycon
>>> # Create some more Clients first so we can have something to count
>>> Client.objects.create(
...     name="Jean Grey", account_type=Client.REGULAR, registered_on=date.today()
... )
>>> Client.objects.create(
...     name="James Bond", account_type=Client.PLATINUM, registered_on=date.today()
... )
>>> Client.objects.create(
...     name="Jane Porter", account_type=Client.PLATINUM, registered_on=date.today()
... )
>>> # Get counts for each value of account_type
>>> from django.db.models import Count
>>> Client.objects.aggregate(
...     regular=Count("pk", filter=Q(account_type=Client.REGULAR)),
...     gold=Count("pk", filter=Q(account_type=Client.GOLD)),
...     platinum=Count("pk", filter=Q(account_type=Client.PLATINUM)),
... )
{'regular': 2, 'gold': 1, 'platinum': 3}
```

在支持 SQL 2003 `FILTER WHERE` 语法的数据库上，这个聚合产生一个查询。

```sql
SELECT count('id') FILTER (WHERE account_type=1) as regular,
       count('id') FILTER (WHERE account_type=2) as gold,
       count('id') FILTER (WHERE account_type=3) as platinum
FROM clients;
```

在其他数据库中，这是用 `CASE` 语句模拟的：

```sql
SELECT count(CASE WHEN account_type=1 THEN id ELSE null) as regular,
       count(CASE WHEN account_type=2 THEN id ELSE null) as gold,
       count(CASE WHEN account_type=3 THEN id ELSE null) as platinum
FROM clients;
```

这两条 SQL 语句在功能上是等同的，但更明确的 `FILTER` 可能表现得更好。

### 条件过滤

当条件表达式返回布尔值时，可以直接在过滤器中使用它。这意味着它不会被添加到 `SELECT` 列中，但您仍然可以使用它来过滤结果：

```pycon
>>> non_unique_account_type = (
...     Client.objects.filter(
...         account_type=OuterRef("account_type"),
...     )
...     .exclude(pk=OuterRef("pk"))
...     .values("pk")
... )
>>> Client.objects.filter(~Exists(non_unique_account_type))
```

用 SQL 术语来说，它的值是：

```sql
SELECT ...
FROM client c0
WHERE NOT EXISTS (
  SELECT c1.id
  FROM client c1
  WHERE c1.account_type = c0.account_type AND NOT c1.id = c0.id
)
```