如何在Django Rest Framework中扁平化序列化含附加数据的多对多字段

方法一：直接映射字段（适合用户字段较少的场景） #

修改FollowerSerializer，不再嵌套UserSnippetSerializer，而是通过source参数直接将关注者的属性映射为顶层字段，同时保留follow_date：

class UserSnippetSerializer(serializers.ModelSerializer):
    class Meta:
        model = User
        fields = ['username']  # 可根据需求添加其他用户字段

class FollowerSerializer(serializers.ModelSerializer):
    # 直接从follower对象中取字段，作为当前序列化器的顶层字段
    username = serializers.CharField(source='follower.username')
    # 如需其他用户字段，比如id、email，按同样方式添加
    # user_id = serializers.IntegerField(source='follower.id')
    # email = serializers.EmailField(source='follower.email')

    class Meta:
        model = Follower
        fields = ['username', 'follow_date']  # 包含用户字段和关注时间

class FullUserSerializer(serializers.ModelSerializer):
    followers = FollowerSerializer(source='user.followers', many=True)
    following = FollowerSerializer(source='user.following', many=True)

    class Meta:
        model = Profile
        fields = ['username', 'followers', 'following']

方法二：重写to_representation方法（适合用户字段较多的场景） #

如果需要序列化的用户字段较多，逐个映射太繁琐，可重写FollowerSerializer的to_representation方法，合并用户数据和关注时间：

class UserSnippetSerializer(serializers.ModelSerializer):
    class Meta:
        model = User
        fields = ['username', 'email', 'id']  # 按需添加字段

class FollowerSerializer(serializers.ModelSerializer):
    class Meta:
        model = Follower
        fields = ['follow_date']

    def to_representation(self, instance):
        # 先获取关注时间的序列化数据
        follow_data = super().to_representation(instance)
        # 序列化关注者的用户信息
        user_data = UserSnippetSerializer(instance.follower).data
        # 合并两个字典，实现扁平化结构
        return {**user_data, **follow_data}

class FullUserSerializer(serializers.ModelSerializer):
    followers = FollowerSerializer(source='user.followers', many=True)
    following = FollowerSerializer(source='user.following', many=True)

    class Meta:
        model = Profile
        fields = ['username', 'followers', 'following']

说明 #

两种方法核心思路一致：将关联的用户字段直接提升到当前序列化层级，避免嵌套。方法一直观简洁，适合字段少的场景；方法二更灵活，适配大量用户字段的序列化需求。

内容的提问来源于stack exchange，提问作者mvanb