Intersecting two dictionaries

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A little known fact is that you don’t need to construct sets to do this:

In Python 2:

In [78]: d1 = {'a': 1, 'b': 2}

In [79]: d2 = {'b': 2, 'c': 3}

In [80]: d1.viewkeys() & d2.viewkeys()
Out[80]: {'b'}

In Python 3 replace viewkeys with keys; the same applies to viewvalues and viewitems.

From the documentation of viewitems:

In [113]: d1.viewitems??
Type:       builtin_function_or_method
String Form:<built-in method viewitems of dict object at 0x64a61b0>
Docstring:  D.viewitems() -> a set-like object providing a view on D's items

For larger dicts this also slightly faster than constructing sets and then intersecting them:

In [122]: d1 = {i: rand() for i in range(10000)}

In [123]: d2 = {i: rand() for i in range(10000)}

In [124]: timeit d1.viewkeys() & d2.viewkeys()
1000 loops, best of 3: 714 µs per loop

In [125]: %%timeit
s1 = set(d1)
s2 = set(d2)
res = s1 & s2

1000 loops, best of 3: 805 µs per loop

For smaller `dict`s `set` construction is faster:

In [126]: d1 = {'a': 1, 'b': 2}

In [127]: d2 = {'b': 2, 'c': 3}

In [128]: timeit d1.viewkeys() & d2.viewkeys()
1000000 loops, best of 3: 591 ns per loop

In [129]: %%timeit
s1 = set(d1)
s2 = set(d2)
res = s1 & s2

1000000 loops, best of 3: 477 ns per loop

We’re comparing nanoseconds here, which may or may not matter to you. In any case, you get back a set, so using viewkeys/keys eliminates a bit of clutter.

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