Sorting by multiple conditions in python

Question

I am new to programming and right now i'm writing a league table in python. I would like to sort my league by first points, and if there are two teams with the same points I would like to sort them by goal difference, and if they have the same goal difference i would like to sort by name.

The first condition is pretty easy and is working by the following:

table.sort(reverse=True, key=Team.getPoints)

how do I insert the two following conditions?

Answer 1

Have the key function return a tuple, with items in decreasing order of priority:

table.sort(reverse=True, key=lambda team: (Team.getPoints(team),
                                           Team.getGoalDifference(team),
                                           Team.getName(team))

Alternately, you could remember a factoid from algorithms 101, and make use of the fact .sort() is a stable sort, and thus doesn't change the relative order of items in a list if they compare as equal. This means you can sort three times, in increasing order of priority:

table.sort(reverse=True, key=Team.getName)
table.sort(reverse=True, key=Team.getGoalDifference)
table.sort(reverse=True, key=Team.getPoints)

This will be slower, but allows you to easily specify whether each step should be done in reverse or not. This can be done without multiple sorting passes using cmp_to_key(), but the comparator function would be nontrivial, something like:

def team_cmp(t1, t2):
    for key_func, reverse in [(Team.getName, True),
                              (Team.getGoalDifference, True),
                              (Team.getPoints, True)]:
        result = cmp(key_func(t1), key_func(t2))
        if reverse: result = -result;
        if result: return result
    return 0

table.sort(functools.cmp_to_key(team_cmp))

(Disclaimer: the above is written from memory, untested.) Emphasis is on "without multiple passes", which does not necessarily imply "faster". The overhead from the comparator function and cmp_to_key(), both of which are implemented in Python (as opposed to list.sort() and operator.itemgetter(), which should be part of the C core) is likely to be significant.

As an aside, you don't need to create dummy functions to pass to the key parameters. You can access the attribute directly, using:

table.sort(key=lambda t: t.points)

or the attrgetter operator wrapper:

table.sort(key=attrgetter('points'))

Answer 2

Sort the list by name first, then sort again by score difference. Python's sort is stable, meaning it will preserve order of elements that compare equal.