I have a list of lists:
[[12, \'tall\', \'blue\', 1],
[2, \'short\', \'red\', 9],
[4, \'tall\', \'blue\', 13]]
If I wanted to sort by one element, say the tall/short element, I could do it via s = sorted(s, key = itemgetter(1))
.
If I wanted to sort by both tall/short and colour, I could do the sort twice, once for each element, but is there a quicker way?
A key can be a function that returns a tuple:
s = sorted(s, key = lambda x: (x[1], x[2]))
Or you can achieve the same using itemgetter
(which is faster and avoids a Python function call):
import operator
s = sorted(s, key = operator.itemgetter(1, 2))
And notice that here you can use sort
instead of using sorted
and then reassigning:
s.sort(key = operator.itemgetter(1, 2))
I\'m not sure if this is the most pythonic method ...
I had a list of tuples that needed sorting 1st by descending integer values and 2nd alphabetically. This required reversing the integer sort but not the alphabetical sort. Here was my solution: (on the fly in an exam btw, I was not even aware you could \'nest\' sorted functions)
a = [(\'Al\', 2),(\'Bill\', 1),(\'Carol\', 2), (\'Abel\', 3), (\'Zeke\', 2), (\'Chris\', 1)]
b = sorted(sorted(a, key = lambda x : x[0]), key = lambda x : x[1], reverse = True)
print(b)
[(\'Abel\', 3), (\'Al\', 2), (\'Carol\', 2), (\'Zeke\', 2), (\'Bill\', 1), (\'Chris\', 1)]
It appears you could use a list
instead of a tuple
.
This becomes more important I think when you are grabbing attributes instead of \'magic indexes\' of a list/tuple.
In my case I wanted to sort by multiple attributes of a class, where the incoming keys were strings. I needed different sorting in different places, and I wanted a common default sort for the parent class that clients were interacting with; only having to override the \'sorting keys\' when I really \'needed to\', but also in a way that I could store them as lists that the class could share
So first I defined a helper method
def attr_sort(self, attrs=[\'someAttributeString\']:
\'\'\'helper to sort by the attributes named by strings of attrs in order\'\'\'
return lambda k: [ getattr(k, attr) for attr in attrs ]
then to use it
# would defined elsewhere but showing here for consiseness
self.SortListA = [\'attrA\', \'attrB\']
self.SortListB = [\'attrC\', \'attrA\']
records = .... #list of my objects to sort
records.sort(key=self.attr_sort(attrs=self.SortListA))
# perhaps later nearby or in another function
more_records = .... #another list
more_records.sort(key=self.attr_sort(attrs=self.SortListB))
This will use the generated lambda function sort the list by object.attrA
and then object.attrB
assuming object
has a getter corresponding to the string names provided. And the second case would sort by object.attrC
then object.attrA
.
This also allows you to potentially expose outward sorting choices to be shard alike by a consumer, a unit test, or for them to perhaps tell you how they want sorting done for some operation in your api by only have to give you a list and not coupling them to your back end implementation.
Here\'s one way: You basically re-write your sort function to take a list of sort functions, each sort function compares the attributes you want to test, on each sort test, you look and see if the cmp function returns a non-zero return if so break and send the return value.
You call it by calling a Lambda of a function of a list of Lambdas.
Its advantage is that it does single pass through the data not a sort of a previous sort as other methods do. Another thing is that it sorts in place, whereas sorted seems to make a copy.
I used it to write a rank function, that ranks a list of classes where each object is in a group and has a score function, but you can add any list of attributes.
Note the un-lambda-like, though hackish use of a lambda to call a setter.
The rank part won\'t work for an array of lists, but the sort will.
#First, here\'s a pure list version
my_sortLambdaLst = [lambda x,y:cmp(x[0], y[0]), lambda x,y:cmp(x[1], y[1])]
def multi_attribute_sort(x,y):
r = 0
for l in my_sortLambdaLst:
r = l(x,y)
if r!=0: return r #keep looping till you see a difference
return r
Lst = [(4, 2.0), (4, 0.01), (4, 0.9), (4, 0.999),(4, 0.2), (1, 2.0), (1, 0.01), (1, 0.9), (1, 0.999), (1, 0.2) ]
Lst.sort(lambda x,y:multi_attribute_sort(x,y)) #The Lambda of the Lambda
for rec in Lst: print str(rec)
Here\'s a way to rank a list of objects
class probe:
def __init__(self, group, score):
self.group = group
self.score = score
self.rank =-1
def set_rank(self, r):
self.rank = r
def __str__(self):
return \'\\t\'.join([str(self.group), str(self.score), str(self.rank)])
def RankLst(inLst, group_lambda= lambda x:x.group, sortLambdaLst = [lambda x,y:cmp(x.group, y.group), lambda x,y:cmp(x.score, y.score)], SetRank_Lambda = lambda x, rank:x.set_rank(rank)):
#Inner function is the only way (I could think of) to pass the sortLambdaLst into a sort function
def multi_attribute_sort(x,y):
r = 0
for l in sortLambdaLst:
r = l(x,y)
if r!=0: return r #keep looping till you see a difference
return r
inLst.sort(lambda x,y:multi_attribute_sort(x,y))
#Now Rank your probes
rank = 0
last_group = group_lambda(inLst[0])
for i in range(len(inLst)):
rec = inLst[i]
group = group_lambda(rec)
if last_group == group:
rank+=1
else:
rank=1
last_group = group
SetRank_Lambda(inLst[i], rank) #This is pure evil!! The lambda purists are gnashing their teeth
Lst = [probe(4, 2.0), probe(4, 0.01), probe(4, 0.9), probe(4, 0.999), probe(4, 0.2), probe(1, 2.0), probe(1, 0.01), probe(1, 0.9), probe(1, 0.999), probe(1, 0.2) ]
RankLst(Lst, group_lambda= lambda x:x.group, sortLambdaLst = [lambda x,y:cmp(x.group, y.group), lambda x,y:cmp(x.score, y.score)], SetRank_Lambda = lambda x, rank:x.set_rank(rank))
print \'\\t\'.join([\'group\', \'score\', \'rank\'])
for r in Lst: print r