How to Use Comprehensions and Generators in Python

Demonstrate list, set, and dictionary comprehensions plus generator expressions and generator functions in one beginner-friendly script.

Easy Python 3.9+ Aug 9, 2026 Comprehensions & generators 15 views 0 copies

comprehensions generators yield beginner syntax

Python code

31 lines

Python 3.9+

def demonstrate_comprehensions_generators():
    # List comprehension: transform and filter in one line
    numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
    squares = [num ** 2 for num in numbers if num % 2 == 0]
    print(f"Square of even numbers (list comprehension): {squares}")

    # Set comprehension: unique values
    text = "hello world"
    unique_vowels = {char for char in text if char in "aeiou"}
    print(f"Unique vowels (set comprehension): {sorted(unique_vowels)}")

    # Dictionary comprehension: map keys to values
    word_lengths = {word: len(word) for word in ["apple", "banana", "cherry"]}
    print(f"Word lengths (dict comprehension): {word_lengths}")

    # Generator expression: memory-efficient one-time iteration
    sum_of_squares = sum(num ** 2 for num in range(1, 11))
    print(f"Sum of squares 1-10 (generator): {sum_of_squares}")

    # Generator function with yield
    def fibonacci(limit):
        a, b = 0, 1
        while a < limit:
            yield a
            a, b = b, a + b

    fib_sequence = list(fibonacci(30))
    print(f"Fibonacci under 30 (generator function): {fib_sequence}")

if __name__ == "__main__":
    demonstrate_comprehensions_generators()

Output

stdout

Square of even numbers (list comprehension): [4, 16, 36, 64, 100]
Unique vowels (set comprehension): ['e', 'o']
Word lengths (dict comprehension): {'apple': 5, 'banana': 6, 'cherry': 6}
Sum of squares 1-10 (generator): 385
Fibonacci under 30 (generator function): [0, 1, 1, 2, 3, 5, 8, 13, 21]

How it works

List comprehensions let you build a new list by transforming and filtering an existing iterable in a single expression — here we square only the even numbers from 1 to 10. Set comprehensions automatically remove duplicates and are great for collecting unique items, such as vowels in a string. Dictionary comprehensions map each key to a computed value, like word-length pairs for a list of fruits. Generator expressions use parentheses instead of brackets and yield values lazily, so sum(num ** 2 for num in range(1, 11)) computes the total without building an entire list in memory. Finally, generator functions use yield to pause and resume, producing a Fibonacci sequence on demand until a limit is reached.

Common mistakes

Using square brackets instead of parentheses for generator expressions, which builds a whole list in memory
Forgetting that `sorted()` returns a list, so set output prints as a list of characters
Calling `list()` on an infinite generator, which never terminates
Expecting a generator function to return values instead of using `yield`

Variations

Use `[num ** 2 for num in numbers if num % 2 == 0]` for a list of squares of evens — same as shown
Employ `map(str.upper, words)` with a generator to transform items lazily without a loop

Real-world use cases

Cleaning and transforming API response fields, like extracting user emails from a JSON list of objects.
Streaming log lines from a large file and filtering errors without loading the whole file into memory.
Building in-memory lookup dictionaries, like mapping product IDs to price tags for fast access in a web app.

How to Use Comprehensions and Generators in Python

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