Python Concatenation Vs Append Speed On Lists

Taking this snippet from interactivepython.org: def test1(): # concat l = [] for i in range(1000): l = l + [i] def test2(): # append l = [] for i in rang

Solution 1:

If you change test1 to:

def test1():  # concat
    l = []
    for i in range(1000):
        l += [i] 

the times will be much closer and you are actually doing what append is doing not creating a new list each time.

In [26]: %timeit test1()
10000 loops, best of 3: 169 µs per loop

In [27]: %timeit test2()
10000 loops, best of 3: 115 µs per loop

If you put print id in your code you will see in test1 you are creating a new object each time but in test2 it is always the same list:

In [41]: test1()
139758194625352
139758206001808
139758205966960
139758194625352
139758206001808
139758205966960
139758194625352
139758206001808
139758205966960
139758194625352
Out[41]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

In [42]: test2()
139758206002600
139758206002600
139758206002600
139758206002600
139758206002600
139758206002600
139758206002600
139758206002600
139758206002600
139758206002600
Out[42]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

Solution 2:

Because the concatenation has to build a new list object each iteration:

Creating a new list each time is much more expensive than adding one item to an existing list.

Under the hood, .append() will fill in pre-allocated indices in the C array, and only periodically does the list object have to grow that array. Building a new list object on the other hand has to allocate a C array each and every time.