id	summary	reporter	owner	description	type	status	component	version	severity	resolution	keywords	cc	stage	has_patch	needs_docs	needs_tests	needs_better_patch	easy	ui_ux
32946	Prefer non-kwargs construction of dynamically generated Q objects	Keryn Knight	Keryn Knight	"There are a number of places where Q objects are created dynamically to do things like construct a big OR expression, but they do so in the historically available API way; because once upon a time there was no way to pass the connector in the Q constructor, to make a OR node would've required doing:
{{{
x = Q(a=1, b=2)
x.connector = Q.OR
}}}
which understandably was not the ideal from the general public API standpoint, and so everyone re-uses the `|` pattern.
But that changed  way back when, in 508b5debfb16843a8443ebac82c1fb91f15da687 for #11964, and now it ''can'' be done as `Q(a=1, b=2, _connector=Q.OR)`

This is important because it's a substantially faster way of constructing a single Q object which does the right thing, because it ignores the complexity of cloning an instance and combining the parts into it. Here follows demonstration data.

The smallest data point to consider is that sending in kwargs is (unfortunately) slower because they're sorted (which I don't think is correct, particularly, but that's a separate ticket tbh):

{{{
In [2]: %timeit Q(a=1, b=2, c=3, d=4)
        1.85 µs ± 14.8 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
In [3]: %timeit Q(('a', 1), ('b', 2), ('c', 3), ('d', 4))
        1.2 µs ± 10.4 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
In [4]: Q(a=1, b=2, c=3, d=4) == Q(('a', 1), ('b', 2), ('c', 3), ('d', 4))
True
}}}

Now, one of the common ways to build a dynamic Q is to use `functools.reduce` and `operator.or_`, like the below, which is a facsimile of the usage in Django and elsewhere:

{{{
In [1]: from functools import reduce
   ...: from operator import or_
   ...: from django.db.models.query_utils import Q
In [2]: values = (Q(a=1), Q(b=2), Q(c=3), Q(d=4), Q(e__in=[1,2,3,4]))
In [3]: %timeit reduce(or_, values)
        12.3 µs ± 91 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
In [4]: %timeit Q(a=1, b=2, c=3, d=4, e__in=[1,2,3,4], _connector=Q.OR)
        2.02 µs ± 23.5 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
In [5]: %timeit Q(('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e__in', [1, 2, 3, 4]), _connector=Q.OR)
        1.4 µs ± 2.31 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
}}}

In the reduce given above, that's 5 Q objects created initially, and then 4 additional Q objects created, vs 1 for the latter. Which is basically borne out by the timings, `1.4 * 9 == 12.6`.

Another usage which comes up is to do something like `Q(**{field.name: xxx})` when `Q((field.name, xxx))` would suffice.

Or doing something like:
{{{
x = models.Q()
if y:
    x |= models.Q(**{field: '!'})
if z:
    x |= models.Q(**{field: '?'})
}}}
when it could be:
{{{
x = []
if y:
    x.append((field, '!'))
if z:
    x.append((field, '?'))
q = Q(x, _connector=Q.OR)
}}}
and so on.

I have a patch which targets most/all? of the constructions I think it might make sense to change, and assuming the CI passes we can discuss from there.

I also think that `Q(a=1, b=2, _connector=Q.OR)` and/or the `reduce(...)` should be documented in the https://docs.djangoproject.com/en/3.2/topics/db/queries/#complex-lookups-with-q section. Dynamic Q construction is fairly common IME, doesn't appear to be covered there, and ultimately points to Q test cases which ''also'' don't show any form of dynamic variants."	Cleanup/optimization	closed	Database layer (models, ORM)	dev	Normal	fixed			Ready for checkin	1	0	0	0	0	0