Differences between revisions 3 and 4
 ⇤ ← Revision 3 as of 2005-11-30 01:45:56 → Size: 8887 Editor: AndrewKuchling Comment: More 2.4 features ← Revision 4 as of 2005-11-30 01:50:11 → ⇥ Size: 9434 Editor: AndrewKuchling Comment: Deletions are marked like this. Additions are marked like this. Line 118: Line 118: For example, you can sort objects basedon an attribute value using {{{operator.attrgetter()}}}:{{{XXX write example For example, you can sort tuples based on their second elementusing {{{operator.itemgetter()}}}:{{{>>> import operator>>> L = [('c', 2), ('d', 1), ('a', 4), ('b', 3)]>>> map(operator.itemgetter(0), L)['c', 'd', 'a', 'b']>>> map(operator.itemgetter(1), L)[2, 1, 4, 3]>>> sorted(L, key=operator.itemgetter(1))[('d', 1), ('c', 2), ('b', 3), ('a', 4)] Line 229: Line 237: different attributes at different times. Instead, you'll need to go different attributes at different times. Python 2.4 has an {{{operator.attrgetter()}}} functionthat makes this easy:{{{>>> import operator>>> a = [Spam(1, 4), Spam(9, 3), Spam(4,6)]>>> a.sort(key=operator.attrgetter('eggs'))>>> for spam in a:>>> print spam.eggs, str(spam)3 124 56 10}}}Again, earlier Python version require you to go

# Sorting Mini-HOWTO

Original version by Andrew Dalke

Python lists have a built-in sort() method. There are many ways to use it to sort a list and there doesn't appear to be a single, central place in the various manuals describing them, so I'll do so here.

## Sorting basic data types

A simple ascending sort is easy; just call the sort() method of a list.

```>>> a = [5, 2, 3, 1, 4]
>>> a.sort()
>>> print a
[1, 2, 3, 4, 5]```

Sort takes an optional function which can be called for doing the comparisons. The default sort routine is equivalent to:

```>>> a = [5, 2, 3, 1, 4]
>>> a.sort(cmp)
>>> print a
[1, 2, 3, 4, 5]```

where cmp() is the built-in function that compares two objects, x and y, and returns -1, 0 or 1 depending on whether x<y, x==y, or x>y. During the course of the sort the relationships must stay the same for the final list to make sense.

If you want, you can define your own function for the comparison. For integers (and numbers in general) we can do:

```>>> def numeric_compare(x, y):
>>>    return x-y
>>>
>>> a = [5, 2, 3, 1, 4]
>>> a.sort(numeric_compare)
>>> print a
[1, 2, 3, 4, 5]```

By the way, this function won't work if the result of the subtraction is out of range, as in sys.maxint - (-1).

Or, if you don't want to define a new named function you can create an anonymous one using lambda, as in:

```>>> a = [5, 2, 3, 1, 4]
>>> a.sort(lambda x, y: x-y)
>>> print a
[1, 2, 3, 4, 5]```

Python 2.4 adds three keyword arguments to sort() that simplify many common usages: cmp, key, and reverse. The cmp keyword is for providing a sorting function; the previous examples could be written as:

```>>> a.sort(cmp=numeric_compare)
>>> a.sort(cmp=lambda x,y: x-y)```

The reverse parameter is a Boolean value; if it's true, the list is sorted into reverse order.

```>>> a = [5, 2, 3, 1, 4]
>>> a.sort(reverse=True)
>>> a
[5, 4, 3, 2, 1]```

For Python versions before 2.4, you can reverse the sense of the comparison function:

```>>> a = [5, 2, 3, 1, 4]
>>> def reverse_numeric(x, y):
>>>     return y-x
>>>
>>> a.sort(reverse_numeric)
>>> a
[5, 4, 3, 2, 1]```

(a more general implementation could return cmp(y,x) or -cmp(x,y)).

However, it's faster if Python doesn't have to call a function for every comparison, so the most efficient solution is to do the forward sort first, then use the reverse() method.

```>>> a = [5, 2, 3, 1, 4]
>>> a.sort()
>>> a.reverse()
>>> a
[5, 4, 3, 2, 1]```

## Sorting by keys

Python 2.4's key parameter lets you derive a sorting key for each element of the list, and then sort using the key.

For example, here's a case-insensitive string comparison:

```>>> a = "This is a test string from Andrew".split()
>>> a.sort(key=str.lower)
>>> a
['a', 'Andrew', 'from', 'is', 'string', 'test', 'This']```

The value of the key parameter should be a function that takes a single argument and returns a key to use for sorting purposes.

Often there's a built-in that will match your needs, such as string.lower(). The operator module contains a number of functions useful for this purpose. For example, you can sort tuples based on their second element using operator.itemgetter():

{{{>>> import operator >>> L = [('c', 2), ('d', 1), ('a', 4), ('b', 3)] >>> map(operator.itemgetter(0), L) ['c', 'd', 'a', 'b'] >>> map(operator.itemgetter(1), L) [2, 1, 4, 3] >>> sorted(L, key=operator.itemgetter(1)) [('d', 1), ('c', 2), ('b', 3), ('a', 4)] }}}

Versions of Python before 2.4 don't have the convenient key parameter, so you have to write a comparison function that embodies the key-generating logic:

```>>> a = "This is a test string from Andrew".split()
>>> a.sort(lambda x, y: cmp(x.lower(), y.lower()))
>>> print a
['a', 'Andrew', 'from', 'is', 'string', 'test', 'This']```

This goes through the overhead of converting a word to lower case every time it must be compared, roughly O(n lg n) times. Python 2.4's key parameter is called once for each item in the list, which is O(n) and therefore more efficient. You can manually perform the same optimization by computing the keys once and using those values. The following example shows how.

```>>> words = "This is a test string from Andrew.".split()
>>> offsets = []
>>> for i in range(len(words)):
>>>     offsets.append( (words[i].lower(), i) )
>>>
>>> offsets.sort()
>>> new_words = []
>>> for dontcare, i in offsets:
>>>      new_words.append(words[i])
>>>
>>> print new_words```

The offsets list is initialized to a tuple of the lower-case string and its position in the words list. It is then sorted. Python's sort method sorts tuples by comparing terms; given x and y, compare x[0] to y[0], then x[1] to y[1], etc. until there is a difference.

The result is that the offsets list is ordered by its first term, and the second term can be used to figure out where the original data was stored. (The for loop assigns dontcare and i to the two fields of each term in the list, but we only need the index value.)

Another way to implement this is to store the original data as the second term in the offsets list, as in:

```>>> words = "This is a test string from Andrew.".split()
>>> offsets = []
>>> for word in words:
>>>     offsets.append( (word.lower(), word) )
>>>
>>> offsets.sort()
>>> new_words = []
>>> for word in offsets:
>>>     new_words.append(word[1])
>>>
>>> print new_words```

This isn't always appropriate because the second terms in the list (the word, in this example) will be compared when the first terms are the same. If this happens many times, then there will be the unneeded performance hit of comparing the two objects. This can be a large cost if most terms are the same and the objects define their own __cmp__ method, but there will still be some overhead to determine if __cmp__ is defined.

Still, for large lists, or for lists where the comparison information is expensive to calculate, the last two examples are likely to be the fastest way to sort a list. It will not work on weakly sorted data, like complex numbers, but if you don't know what that means, you probably don't need to worry about it.

## Comparing classes

The comparison for two basic data types, like ints to ints or string to string, is built into Python and makes sense. There is a default way to compare class instances, but the default manner isn't usually very useful. You can define your own comparison with the __cmp__ method, as in:

```>>> class Spam:
>>>     def __init__(self, spam, eggs):
>>>         self.spam = spam
>>>         self.eggs = eggs
>>>     def __cmp__(self, other):
>>>         return cmp(self.spam+self.eggs, other.spam+other.eggs)
>>>     def __str__(self):
>>>         return str(self.spam + self.eggs)
>>>
>>> a = [Spam(1, 4), Spam(9, 3), Spam(4,6)]
>>> a.sort()
>>> for spam in a:
>>>   print str(spam)
5
10
12```

Sometimes you may want to sort by a specific attribute of a class. If appropriate you should just define the __cmp__ method to compare those values, but you cannot do this if you want to compare between different attributes at different times.

Python 2.4 has an operator.attrgetter() function that makes this easy:

```>>> import operator
>>> a = [Spam(1, 4), Spam(9, 3), Spam(4,6)]
>>> a.sort(key=operator.attrgetter('eggs'))
>>> for spam in a:
>>>   print spam.eggs, str(spam)
3 12
4 5
6 10```

Again, earlier Python version require you to go back to passing a comparison function to sort, as in:

```>>> a = [Spam(1, 4), Spam(9, 3), Spam(4,6)]
>>> a.sort(lambda x, y: cmp(x.eggs, y.eggs))
>>> for spam in a:
>>>   print spam.eggs, str(spam)
3 12
4 5
6 10```

If you want to compare two arbitrary attributes (and aren't overly concerned about performance) you can even define your own comparison function object. This uses the ability of a class instance to emulate an function by defining the __call__ method, as in:

```>>> class CmpAttr:
>>>     def __init__(self, attr):
>>>         self.attr = attr
>>>     def __call__(self, x, y):
>>>         return cmp(getattr(x, self.attr), getattr(y, self.attr))
>>>
>>> a = [Spam(1, 4), Spam(9, 3), Spam(4,6)]
>>> a.sort(CmpAttr("spam"))  # sort by the "spam" attribute
>>> for spam in a:
>>>    print spam.spam, spam.eggs, str(spam)
1 4 5
4 6 10
9 3 12

>>> a.sort(CmpAttr("eggs"))   # re-sort by the "eggs" attribute
>>> for spam in a:
>>>    print spam.spam, spam.eggs, str(spam)
9 3 12
1 4 5
4 6 10```

Of course, if you want a faster sort you can extract the attributes into an intermediate list and sort that list.

So, there you have it; about a half-dozen different ways to define how to sort a list:

1. sort using the default method
2. sort using a comparison function
3. reverse sort not using a comparison function
4. sort on an intermediate list (two forms)
5. sort using class defined cmp method

6. sort using a sort function object

HowTo/Sorting (last edited 2014-10-12 06:26:39 by Paddy3118)

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