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Django的某个特定QuerySet的所有可能子集
原标题:Generating all possible subsets of a given QuerySet in Django

这是一个例子,但考虑到以下模式:

class Foo(models.model):
    bar = models.IntegerField()

    def __str__(self):
        return  str(self.bar)

    def __unicode__(self):
        return str(self.bar)

和以下<代码>QuerySet 反对:

foobar = Foo.objects.filter(bar__lt=20).distinct()

(滚动,一套独特的<代码>) Foo model with bar <= 20, how 我请我产生foobar上的所有可能的子集? 理想的情况是,我进一步限制次编号,以便每个次编号为<条码>x>>>>。 Foo在最大值和最低值之间。

因此,例如,考虑到<代码>foobar:

>> print foobar
[<Foo: 5>, <Foo: 10>, <Foo: 15>]

min=5,max=25 我愿打造一个物体(最好有QuerySet,但可能还有一份清单)。

[[<Foo: 5>], [<Foo: 10>], [<Foo: 15>], [<Foo: 5>, <Foo: 10>],
 [<Foo: 5>, <Foo: 15>], [<Foo: 10>, <Foo: 15>]]

我曾尝试过<代码>itertools,但似乎特别适合我的需要。

页: 1 可以通过复杂的<代码>做到这一点。 QuerySet,但我不知道如何开始。

最佳回答

http://en.wikipedia.org/wiki/Power_set”rel=“nofollow noreferer”>powerset,foobar(作为清单)。

from itertools import combinations
[j for i in range(len(foobar)+1) for j in combinations(foobar,i)]

在最高和最高层添加过滤器:

from itertools import combinations
[j for i in range(len(foobar)+1) for j in combinations(foobar,i)
 if minval <= sum(f.bar for f in j) <= maxval]

让我们打造一个阶级,尝试它

>>> from itertools import combinations
>>> class Foo(object):
...     def __init__(self, bar):
...         self.bar=bar
...     def __repr__(self):
...         return  "<Foo: %s>"%self.bar
... 
>>> foobar=[Foo(5),Foo(10),Foo(15)]
>>> minval=5
>>> maxval=25
>>> [j for i in range(len(foobar)+1) for j in combinations(foobar,i) 
     if minval <= sum(f.bar for f in j) <= maxval]
[(<Foo: 5>,), (<Foo: 10>,), (<Foo: 15>,), (<Foo: 5>, <Foo: 10>), (<Foo: 5>, <Foo: 15>), (<Foo: 10>, <Foo: 15>)]

如果你需要列入名单,而不是les子,那么就更不用说这样了。

>>> [list(j) for i in range(len(foobar)+1) for j in combinations(foobar,i) if minval <= sum(f.bar for f in j) <= maxval ]
[[<Foo: 5>], [<Foo: 10>], [<Foo: 15>], [<Foo: 5>, <Foo: 10>], [<Foo: 5>, <Foo: 15>], [<Foo: 10>, <Foo: 15>]]
问题回答
S = [list(itertools.combinations(foobar,i)) for i in xrange(1, len(foobar))]

它编制非专栏清单。 你们可以通过:

list(itertools.chain.from_iterable(S))




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