Computing the argmax is a common programming problem: you have a set of
candidates *C*, a score function *f*, and you want to compute an optimal
candidate *c* in *C* according to *f*, i.e. one that maximizes *f(c)*. If there
is only one such candidate, it is called the "argmax" of *f* on *C*. One can
find solutions for this on-line, e.g. in this post,
but I realized recently that Python's `max()`

function can actually handle
the job. Here is how.

So, we have a set of candidates and we want to find the one that maximizes a score function, for instance:

```
In [1]: candidates = [1, 5, 8, 11, 9]
In [2]: f = lambda x: (x - 4) * (x - 10) * (x - 11)
In [3]: [f(x) for x in candidates]
Out[3]: [-270, 30, 24, 0, 10]
```

In this case the answer is 5, the candidate at which *f* is maximal with
*f(5)=30*. A first solution could be to compute the values of `f`

on
`candidates`

and use list.index()
to return the index of a maximal element:

```
In [1]: l = [f(x) for x in candidates]
In [2]: fmax = max(l)
In [3]: best_candidate = candidates[l.index(fmax)]
In [4]: best_candidate
Out[4]: 5
```

This approach relies on the fact that the indexes in `l`

and `candidates`

are the same, and it is a little bit verbose. There is a one-liner that
circumvents this:

```
In [5]: max(candidates, key=f)
Out[5]: 5
```

In details: the `key`

argument to max() is
a one-argument function applied to the elements of the iterable before
comparing them (its default value is of course the identity). For instance,
`max(i, j, key=f)`

is equivalent to `i if f(i) >= f(j) else j`

.

In short:

```
argmax = lambda iterable, func: max(iterable, key=func)
```

## Discussion ¶

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