How to Merge Multiple Iterables with a Generator in Python

This code defines a generator function that 'chains' or merges multiple iterables into a single iterator, which is then converted to a list.

Easy Python 3.0+ Aug 9, 2026 Comprehensions & generators 12 views 0 copies

generators yield-from iterables chain

Python code

15 lines

Python 3.0+

def chain(*iterables):
    for iterable in iterables:
        yield from iterable

def main():
    list1 = [1, 2, 3]
    tuple1 = (4, 5)
    set1 = {6, 7}
    string1 = "89"

    result = list(chain(list1, tuple1, set1, string1))
    print(result)

if __name__ == "__main__":
    main()

Output

stdout

[1, 2, 3, 4, 5, 6, 7, '8', '9']

How it works

The chain function uses yield from to delegate iteration to each iterable in order. This is memory-efficient because it yields elements one at a time without creating a new container. The *iterables parameter allows passing any number of iterables. The main function demonstrates chaining a list, tuple, set, and string, converting the generator to a list to display the merged sequence.

Common mistakes

Using `yield from` outside a generator function, which raises SyntaxError.
Assuming iterables are in order when sets, which are unordered, are passed.
Forgetting to convert the generator result to a list or other container before printing, which shows a generator object.
Including non-iterable arguments, which raises TypeError at runtime.

Variations

Use `itertools.chain` from the standard library instead of defining a custom generator: `list(itertools.chain(list1, tuple1, set1, string1))`.
Use a list comprehension with nested loops to flatten multiple iterables into a list, though less memory-efficient.

Real-world use cases

Flattening multiple database query result sets into a single iterator for processing without loading all results into memory.
Combining log entries from multiple files or streams into one unified sequence for analysis or reporting.
Merging several data source iterables (CSV rows, API responses) into a single feed for a data pipeline.

How to Merge Multiple Iterables with a Generator in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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Python code

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How it works

Common mistakes

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Real-world use cases

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