Merge sorted lists in python

Question

I have a bunch of sorted lists of objects, and a comparison function

class Obj :
    def __init__(p) :
        self.points = p
def cmp(a, b) :
    return a.points < b.points

a = [Obj(1), Obj(3), Obj(8), ...]
b = [Obj(1), Obj(2), Obj(3), ...]
c = [Obj(100), Obj(300), Obj(800), ...]

result = magic(a, b, c)
assert result == [Obj(1), Obj(1), Obj(2), Obj(3), Obj(3), Obj(8), ...]

what does magic look like? My current implementation is

def magic(*args) :
    r = []
    for a in args : r += a
    return sorted(r, cmp)

but that is quite inefficient. Better answers?

Answer 1

I don't know whether it would be any quicker, but you could simplify it with:

def GetObjKey(a):
    return a.points

return sorted(a + b + c, key=GetObjKey)

You could also, of course, use cmp rather than key if you prefer.

Answer 2

Use the bisect module. From the documentation: "This module provides support for maintaining a list in sorted order without having to sort the list after each insertion."

import bisect

def magic(*args):
    r = []
    for a in args:
        for i in a:
            bisect.insort(r, i)
    return r

Answer 3

Python standard library offers a method for it: heapq.merge.
As the documentation says, it is very similar to using itertools (but with more limitations); if you cannot live with those limitations (or if you do not use Python 2.6) you can do something like this:

sorted(itertools.chain(args), cmp)

However, I think it has the same complexity as your own solution, although using iterators should give some quite good optimization and speed increase.

Answer 4

Instead of using a list, you can use a heap.

The insertion is O(log(n)), so merging a, b and c will be O(n log(n))

In Python, you can use the heapq module.

Answer 5

One line solution using sorted:

def magic(*args):
  return sorted(sum(args,[]), key: lambda x: x.points)

IMO this solution is very readable.

Using heapq module, it could be more efficient, but I have not tested it. You cannot specify cmp/key function in heapq, so you have to implement Obj to be implicitly sorted.

import heapq
def magic(*args):
  h = []
  for a in args:
    heapq.heappush(h,a)
  return [i for i in heapq.heappop(h)

Answer 6

Here you go: a fully functioning merge sort for lists (adapted from my sort here):

def merge(*args):
    import copy
    def merge_lists(left, right):
        result = []
        while (len(left) and len(right)):
            which_list = (left if left[0] <= right[0] else right)
            result.append(which_list.pop(0))
        return result + left + right
    lists = [arg for arg in args]
    while len(lists) > 1:
        left, right = copy.copy(lists.pop(0)), copy.copy(lists.pop(0))
        result = merge_lists(left, right)
        lists.append(result)
    return lists.pop(0)

Call it like this:

merged_list = merge(a, b, c)
for item in merged_list:
    print item

For good measure, I'll throw in a couple of changes to your Obj class:

class Obj(object):
    def __init__(self, p) :
        self.points = p
    def __cmp__(self, b) :
        return cmp(self.points, b.points)
    def __str__(self):
        return "%d" % self.points

• Derive from object
• Pass self to __init__()
• Make __cmp__ a member function
• Add a str() member function to present Obj as string

Answer 7

I like Roberto Liffredo's answer. I didn't know about heapq.merge(). Hmmmph.

Here's what the complete solution looks like using Roberto's lead:

class Obj(object):
    def __init__(self, p) :
        self.points = p
    def __cmp__(self, b) :
        return cmp(self.points, b.points)
    def __str__(self):
        return "%d" % self.points

a = [Obj(1), Obj(3), Obj(8)]
b = [Obj(1), Obj(2), Obj(3)]
c = [Obj(100), Obj(300), Obj(800)]

import heapq

sorted = [item for item in heapq.merge(a,b,c)]
for item in sorted:
    print item

Or:

for item in heapq.merge(a,b,c):
    print item

Answer 8

I asked a similar question and got some excellent answers:

• Joining a set of ordered-integer yielding Python iterators

The best solutions from that question are variants of the merge algorithm, which you can read about here:

• Wikipedia: Merge Algorithm