The .extend() method on lists works with any iterable*, += works with some but can get funky.

import numpy as np

l = [2, 3, 4]
t = (5, 6, 7)
l += t
l
[2, 3, 4, 5, 6, 7]

l = [2, 3, 4]
t = np.array((5, 6, 7))
l += t
l
array([ 7,  9, 11])

l = [2, 3, 4]
t = np.array((5, 6, 7))
l.extend(t)
l
[2, 3, 4, 5, 6, 7]

Python 3.6
*pretty sure .extend() works with any iterable but please comment if I am incorrect

Edit: "extend()" changed to "The .extend() method on lists" Note: David M. Helmuth's comment below is nice and clear.

Actually, there are differences among the three options: ADD, INPLACE_ADD and extend. The former is always slower, while the other two are roughly the same.

With this information, I would rather use extend, which is faster than ADD, and seems to me more explicit of what you are doing than INPLACE_ADD.

Try the following code a few times (for Python 3):

import time

def test():
    x = list(range(10000000))
    y = list(range(10000000))
    z = list(range(10000000))

    # INPLACE_ADD
    t0 = time.process_time()
    z += x
    t_inplace_add = time.process_time() - t0

    # ADD
    t0 = time.process_time()
    w = x + y
    t_add = time.process_time() - t0

    # Extend
    t0 = time.process_time()
    x.extend(y)
    t_extend = time.process_time() - t0

    print('ADD {} s'.format(t_add))
    print('INPLACE_ADD {} s'.format(t_inplace_add))
    print('extend {} s'.format(t_extend))
    print()

for i in range(10):
    test()

ADD 0.3540440000000018 s
INPLACE_ADD 0.10896000000000328 s
extend 0.08370399999999734 s

ADD 0.2024550000000005 s
INPLACE_ADD 0.0972940000000051 s
extend 0.09610200000000191 s

ADD 0.1680199999999985 s
INPLACE_ADD 0.08162199999999586 s
extend 0.0815160000000077 s

ADD 0.16708400000000267 s
INPLACE_ADD 0.0797719999999913 s
extend 0.0801490000000058 s

ADD 0.1681250000000034 s
INPLACE_ADD 0.08324399999999343 s
extend 0.08062700000000689 s

ADD 0.1707760000000036 s
INPLACE_ADD 0.08071900000000198 s
extend 0.09226200000000517 s

ADD 0.1668420000000026 s
INPLACE_ADD 0.08047300000001201 s
extend 0.0848089999999928 s

ADD 0.16659500000000094 s
INPLACE_ADD 0.08019399999999166 s
extend 0.07981599999999389 s

ADD 0.1710910000000041 s
INPLACE_ADD 0.0783479999999912 s
extend 0.07987599999999873 s

ADD 0.16435900000000458 s
INPLACE_ADD 0.08131200000001115 s
extend 0.0818660000000051 s

I've looked up the official Python tutorial but couldn't find anything anything about this topic

This information happens to be buried in the Programming FAQ:

... for lists, __iadd__ [i.e. +=] is equivalent to calling extend on the list and returning the list. That's why we say that for lists, += is a "shorthand" for list.extend

You can also see this for yourself in the CPython source code: https://github.com/python/cpython/blob/v3.8.2/Objects/listobject.c#L1000-L1011

Only .extend() can be used when the list is in a tuple

This will work

t = ([],[])
t[0].extend([1,2])

while this won't

t = ([],[])
t[0] += [1,2]

The reason is that += generates a new object. If you look at the long version:

t[0] = t[0] + [1,2]

you can see how that would change which object is in the tuple, which is not possible. Using .extend() modifies an object in the tuple, which is allowed.

ary += ext creates a new List object, then copies data from lists "ary" and "ext" into it.

ary.extend(ext) merely adds reference to "ext" list to the end of the "ary" list, resulting in less memory transactions.

As a result, .extend works orders of magnitude faster and doesn't use any additional memory outside of the list being extended and the list it's being extended with.

╰─➤ time ./list_plus.py
./list_plus.py  36.03s user 6.39s system 99% cpu 42.558 total
╰─➤ time ./list_extend.py
./list_extend.py  0.03s user 0.01s system 92% cpu 0.040 total

The first script also uses over 200MB of memory, while the second one doesn't use any more memory than a 'naked' python3 process.

Having said that, the in-place addition does seem to do the same thing as .extend.

According to the Python for Data Analysis.

“Note that list concatenation by addition is a comparatively expensive operation since a new list must be created and the objects copied over. Using extend to append elements to an existing list, especially if you are building up a large list, is usually preferable. ” Thus,

everything = []
for chunk in list_of_lists:
    everything.extend(chunk)

is faster than the concatenative alternative:

everything = []
for chunk in list_of_lists:
    everything = everything + chunk