Join Lists
Concatenation Methods
Python provides multiple ways to combine lists. You can use the + operator to create a new list, extend() to modify in place, itertools.chain() for efficient iteration, unpacking syntax for readability, and sum() with an empty list as the starting value.
Example
list1 = [1, 2, 3]
list2 = [4, 5, 6]
# + operator (creates new list)
combined = list1 + list2
# extend() modifies in place
list1.extend(list2)
# itertools.chain (efficient iterator)
from itertools import chain
chained = list(chain(list1, list2))
# Unpacking syntax
unpacked = [*list1, *list2]
print(combined)
print(list1)
print(chained)
print(unpacked)Output
[1, 2, 3, 4, 5, 6] [1, 2, 3, 4, 5, 6] [1, 2, 3, 4, 5, 6] [1, 2, 3, 4, 5, 6]
Performance Comparison
Although many methods exist, their performance differs. extend() is typically fastest for in-place updates, while + and unpacking create new lists. itertools.chain() is memory-efficient for large sequences since it returns an iterator.
Example
from timeit import timeit
print("+ operator:", timeit("x + y", "x = [1,2,3]; y = [4,5,6]"))
print("extend():", timeit("x.extend(y)", "x = [1,2,3]; y = [4,5,6]"))
print("unpacking:", timeit("[*x, *y]", "x = [1,2,3]; y = [4,5,6]"))ℹ️ Note: Use extend() for efficiency when modifying an existing list, and itertools.chain() for memory-efficient iteration across many lists.
Advanced Joining
For more complex scenarios, such as joining multiple lists or flattening nested structures, different techniques can be applied. The sum() trick works for shallow joins, while recursion is often used for deep flattening.
Example
# Joining multiple lists
lists = [[1, 2], [3, 4], [5, 6]]
joined = sum(lists, [])
print(joined) # [1, 2, 3, 4, 5, 6]
# Flattening nested lists
nested = [[1, 2], [3, [4, 5]]]
from collections.abc import Iterable
def flatten(lst):
for item in lst:
if isinstance(item, Iterable) and not isinstance(item, (str, bytes)):
yield from flatten(item)
else:
yield item
flat = list(flatten(nested))
print(flat) # [1, 2, 3, 4, 5]Output
[1, 2, 3, 4, 5, 6] [1, 2, 3, 4, 5]