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Comprehensions & generators

List/dict/set comprehensions, generator expressions, and lazy iteration.

5 matches

How to Delegate Iteration to a Subgenerator with yield from in Python

Use yield from to delegate iteration from one generator to a subgenerator, flattening nested generator output into a single sequence.

generators yield-from delegation

Python

def subgenerator():
    yield "first"
    yield "second"
    yield "third"


def delegate():
    yield "before delegation"
    yield from subgenerator()
    yield "after delegation"


if __name__ == "__main__":
    for item in delegate():
        print(item)

13 0 Open

Comprehensions & generators easy

How to Group Data in Python with defaultdict and Comprehensions

Group a list of items by a computed key using a defaultdict-based generator helper and an alternative dictionary comprehension approach.

grouping defaultdict comprehensions

Python

from collections import defaultdict

def group_by(data, key_func):
    """Group items in data by the value returned by key_func."""
    result = defaultdict(list)
    for item in data:
        result[key_func(item)].append(item)
    return dict(result)

def group_by_comprehension(data, key_func):
    """Same grouping …

15 0 Open

Comprehensions & generators easy

How to Reset Python's Random Seed for Deterministic Output

This code shows how to seed Python's random module to generate identical random sequences across runs, ensuring reproducibility.

random seeding deterministic

Python

import random

def seeded_random_sequence(seed, count=5, low=1, high=100):
    random.seed(seed)
    return [random.randint(low, high) for _ in range(count)]

if __name__ == "__main__":
    seed_value = 42
    first_run = seeded_random_sequence(seed_value)
    print("First run:", first_run)

    # Reset seed and gener…

12 0 Open

Comprehensions & generators easy

How to Use Comprehensions and Generators to Check Data in Python

A beginner-friendly helper that filters numeric values, computes squares and cubes with comprehensions and a generator, and returns a summary dictionary.

comprehensions generators data-checking

Python

def check_data(iterable):
    """Return a summary of numeric data using comprehensions and a generator."""
    values = [item for item in iterable if isinstance(item, (int, float))]
    squares = [x ** 2 for x in values if x > 0]
    cubes = (x ** 3 for x in values if x > 0)
    cube_list = list(cubes)
    return {
  …

13 0 Open

Comprehensions & generators easy

Sum of Squares with a Generator Expression in Python

This code computes the sum of squares of integers from 1 to n using a generator expression, demonstrating a memory-efficient and concise way to aggregate a sequence.

generator sum squares

Python

def sum_of_squares(n):
    return sum(x * x for x in range(1, n + 1))

if __name__ == "__main__":
    print(f"Sum of squares from 1 to 5: {sum_of_squares(5)}")
    print(f"Sum of squares from 1 to 10: {sum_of_squares(10)}")

14 0 Open

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