chain and chain.from_iterable¶

The chain() function concatenates multiple iterables into a single iterator, while chain.from_iterable() accepts an iterable of iterables. These tools let you process items from several sources as a single stream without copying them into a new collection, preserving memory efficiency and keeping code concise.

Mental Model

chain is like laying train tracks end-to-end — items come from the first iterable, then seamlessly from the second, and so on, without ever building a combined list in memory. Use chain() when you have a known set of iterables and chain.from_iterable() when the iterables themselves come from a generator or lazy source.

chain() - Concatenate Iterables¶

Pass any number of iterables as separate arguments to chain(). It yields elements from the first iterable until it is exhausted, then proceeds to the next, and so on.

```python from itertools import chain

list1 = [1, 2, 3] list2 = ['a', 'b', 'c'] list3 = [10, 20]

result = list(chain(list1, list2, list3)) print(result) ```

[1, 2, 3, 'a', 'b', 'c', 10, 20]

chain.from_iterable() - Flatten Iterables¶

Unlike chain(), which requires each iterable as a separate argument, chain.from_iterable() accepts a single iterable of iterables. This is essential when the sub-iterables come from a generator or when their count is not known in advance.

```python from itertools import chain

lists = [[1, 2], [3, 4], [5, 6]] result = list(chain.from_iterable(lists)) print(result)

Flatten a generator expression¶

nested = ([i, i+10] for i in range(3)) flattened = list(chain.from_iterable(nested)) print(flattened) ```

[1, 2, 3, 4, 5, 6] [0, 10, 1, 11, 2, 12]

Exercises¶

Exercise 1. Write a function flatten_one_level that takes a list of lists and returns a single flat list using chain.from_iterable. For example, flatten_one_level([[1, 2], [3], [4, 5, 6]]) should return [1, 2, 3, 4, 5, 6].

Solution to Exercise 1

```python from itertools import chain

def flatten_one_level(nested): return list(chain.from_iterable(nested))

Test¶

print(flatten_one_level([[1, 2], [3], [4, 5, 6]]))

[1, 2, 3, 4, 5, 6]¶

```

Exercise 2. Write a function merge_sorted_iterators that takes multiple sorted lists and returns a single sorted list by chaining them together and then sorting. For example, merge_sorted_iterators([1, 4, 7], [2, 5, 8], [3, 6, 9]) should return [1, 2, 3, 4, 5, 6, 7, 8, 9].

Solution to Exercise 2

```python from itertools import chain

def merge_sorted_iterators(iterables): return sorted(chain(iterables))

Test¶

print(merge_sorted_iterators([1, 4, 7], [2, 5, 8], [3, 6, 9]))

[1, 2, 3, 4, 5, 6, 7, 8, 9]¶

```

Exercise 3. Write a function unique_items that takes multiple iterables and returns a list of unique items (preserving first-seen order) using chain. For example, unique_items([1, 2, 3], [2, 3, 4], [4, 5]) should return [1, 2, 3, 4, 5].

Solution to Exercise 3

```python from itertools import chain

def unique_items(iterables): seen = set() result = [] for item in chain(iterables): if item not in seen: seen.add(item) result.append(item) return result

Test¶

print(unique_items([1, 2, 3], [2, 3, 4], [4, 5]))

[1, 2, 3, 4, 5]¶

```