How to sort objects by multiple keys?

def sortkeypicker(keynames):
    negate = set()
    for i, k in enumerate(keynames):
        if k[:1] == '-':
            keynames[i] = k[1:]
            negate.add(k[1:])
    def getit(adict):
       composite = [adict[k] for k in keynames]
       for i, (k, v) in enumerate(zip(keynames, composite)):
           if k in negate:
               composite[i] = -v
       return composite
    return getit

a = sorted(b, key=sortkeypicker(['-Total_Points', 'TOT_PTS_Misc']))

from operator import itemgetter
from functools import partial

def _neg_itemgetter(key, d):
    return -d[key]

def key_getter(key_expr):
    keys = key_expr.split(",")
    getters = []
    for k in keys:
        k = k.strip()
        if k.startswith("-"):
           getters.append(partial(_neg_itemgetter, k[1:]))
        else:
           getters.append(itemgetter(k))

    def keyfunc(dct):
        return [kg(dct) for kg in getters]

    return keyfunc

def multikeysort(dict_list, sortkeys):
    return sorted(dict_list, key = key_getter(sortkeys)

Demonstration:

>>> multikeysort([{u'TOT_PTS_Misc': u'Utley, Alex', u'Total_Points': 60.0},
                 {u'TOT_PTS_Misc': u'Russo, Brandon', u'Total_Points': 96.0}, 
                 {u'TOT_PTS_Misc': u'Chappell, Justin', u'Total_Points': 96.0}],
                "-Total_Points,TOT_PTS_Misc")
[{u'Total_Points': 96.0, u'TOT_PTS_Misc': u'Chappell, Justin'}, 
 {u'Total_Points': 96.0, u'TOT_PTS_Misc': u'Russo, Brandon'}, 
 {u'Total_Points': 60.0, u'TOT_PTS_Misc': u'Utley, Alex'}]

The parsing is a bit fragile, but at least it allows for variable number of spaces between the keys.

Since you’re already comfortable with lambda, here’s a less verbose solution.

>>> def itemgetter(*names):
    return lambda mapping: tuple(-mapping[name[1:]] if name.startswith('-') else mapping[name] for name in names)

>>> itemgetter('a', '-b')({'a': 1, 'b': 2})
(1, -2)

I use the following for sorting a 2d array on a number of columns

def k(a,b):
    def _k(item):
        return (item[a],item[b])
    return _k

This could be extended to work on an arbitrary number of items. I tend to think finding a better access pattern to your sortable keys is better than writing a fancy comparator.

>>> data = [[0,1,2,3,4],[0,2,3,4,5],[1,0,2,3,4]]
>>> sorted(data, key=k(0,1))
[[0, 1, 2, 3, 4], [0, 2, 3, 4, 5], [1, 0, 2, 3, 4]]
>>> sorted(data, key=k(1,0))
[[1, 0, 2, 3, 4], [0, 1, 2, 3, 4], [0, 2, 3, 4, 5]]
>>> sorted(a, key=k(2,0))
[[0, 1, 2, 3, 4], [1, 0, 2, 3, 4], [0, 2, 3, 4, 5]]

This article has a nice rundown on various techniques for doing this. If your requirements are simpler than “full bidirectional multikey”, take a look. It’s clear the accepted answer and the blog post I just
referenced influenced each other in some way, though I don’t know which order.

In case the link dies here’s a very quick synopsis of examples not covered above:

mylist = sorted(mylist, key=itemgetter('name', 'age'))
mylist = sorted(mylist, key=lambda k: (k['name'].lower(), k['age']))
mylist = sorted(mylist, key=lambda k: (k['name'].lower(), -k['age']))

I know this is a rather old question, but none of the answers mention that Python guarantees a stable sort order for its sorting routines such as list.sort() and sorted(), which means items that compare equal retain their original order.

This means that the equivalent of ORDER BY name ASC, age DESC (using SQL notation) for a list of dictionaries can be done like this:

items.sort(key=operator.itemgetter('age'), reverse=True)
items.sort(key=operator.itemgetter('name'))

Note how the items are first sorted by the “lesser” attribute age (descending), then by the “major” attribute name, leading to the correct final order.

The reversing/inverting works for all orderable types, not just numbers which you can negate by putting a minus sign in front.

And because of the Timsort algorithm used in (at least) CPython, this is actually rather fast in practice.

I had a similar issue today – I had to sort dictionary items by descending numeric values and by ascending string values. To solve the issue of conflicting directions, I negated the integer values.

Here’s a variant of my solution – as applicable to OP

sorted(b, key=lambda e: (-e['Total_Points'], e['TOT_PTS_Misc']))

Very simple – and works like a charm

[{'TOT_PTS_Misc': 'Chappell, Justin', 'Total_Points': 96.0},
 {'TOT_PTS_Misc': 'Russo, Brandon', 'Total_Points': 96.0},
 {'TOT_PTS_Misc': 'Utley, Alex', 'Total_Points': 96.0},
 {'TOT_PTS_Misc': 'Foster, Toney', 'Total_Points': 80.0},
 {'TOT_PTS_Misc': 'Lawson, Roman', 'Total_Points': 80.0},
 {'TOT_PTS_Misc': 'Lempke, Sam', 'Total_Points': 80.0},
 {'TOT_PTS_Misc': 'Gnezda, Alex', 'Total_Points': 78.0},
 {'TOT_PTS_Misc': 'Kirks, Damien', 'Total_Points': 78.0},
 {'TOT_PTS_Misc': 'Korecz, Mike', 'Total_Points': 78.0},
 {'TOT_PTS_Misc': 'Worden, Tom', 'Total_Points': 78.0},
 {'TOT_PTS_Misc': 'Burgess, Randy', 'Total_Points': 66.0},
 {'TOT_PTS_Misc': 'Harmon, Gary', 'Total_Points': 66.0},
 {'TOT_PTS_Misc': 'Smugala, Ryan', 'Total_Points': 66.0},
 {'TOT_PTS_Misc': 'Swartz, Brian', 'Total_Points': 66.0},
 {'TOT_PTS_Misc': 'Blackwell, Devon', 'Total_Points': 60.0},
 {'TOT_PTS_Misc': 'Blasinsky, Scott', 'Total_Points': 60.0},
 {'TOT_PTS_Misc': 'Bolden, Antonio', 'Total_Points': 60.0},
 {'TOT_PTS_Misc': 'Carter III, Laymon', 'Total_Points': 60.0},
 {'TOT_PTS_Misc': 'Coleman, Johnathan', 'Total_Points': 60.0},
 {'TOT_PTS_Misc': 'Kovach, Alex', 'Total_Points': 60.0},
 {'TOT_PTS_Misc': 'Smith, Ryan', 'Total_Points': 60.0},
 {'TOT_PTS_Misc': 'Venditti, Nick', 'Total_Points': 60.0}]