MyObject.objects.filter(datetime_attr__date=datetime.date(2009,8,22))

您可以在某些日期范围之间进行筛选

2016-01-01 00:00:00 <- > 2016-04-01 23:59:59.99999. 2016-01-01 00:00:00 <- > 2016-04-01 23:59:59.99999

User.objects.filter(date_joined__gte=datetime.combine(datetime.strptime('2016- 
01-01', '%Y-%d-%m'), datetime.min.time()), 
date_joined__lte=datetime.combine(datetime.strptime('2016-04-01', '%Y-%d-%m'), 
datetime.max.time())).count()

2016-01-01 00:00:00 <- > 2016-01-14 00:00:00. 2016-01-01 00:00:00 <- > 2016-01-14 00:00:00

User.objects.filter(date_joined__gte='2016-01-01', date_joined__lte='2016-1-14').count()

Model.objects.filter(datetime__year=2011, datetime__month=2, datetime__day=30)

从Django 1.9开始，这样做的方法是在datetime对象上使用__date。

例如: MyObject.objects.filter (datetime_attr__date = datetime.date(22) 2009年,8日)

Mymodel.objects.filter(date_time_field__contains=datetime.date(1986, 7, 28))

以上就是我所使用的。它不仅有效，而且有一些内在的逻辑支持。

下面是我使用ipython的timeit函数得到的结果:

from datetime import date
today = date.today()

timeit[Model.objects.filter(date_created__year=today.year, date_created__month=today.month, date_created__day=today.day)]
1000 loops, best of 3: 652 us per loop

timeit[Model.objects.filter(date_created__gte=today)]
1000 loops, best of 3: 631 us per loop

timeit[Model.objects.filter(date_created__startswith=today)]
1000 loops, best of 3: 541 us per loop

timeit[Model.objects.filter(date_created__contains=today)]
1000 loops, best of 3: 536 us per loop

Contains似乎更快。