Reference library

Comprehensions & generators

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

30 matches
Comprehensions & generators medium

How to Throw an Exception into a Python Generator

This code demonstrates how to use the .throw() method on a generator to inject an exception at its current yield point and let it recover gracefully.

generator throw exception
Python
def demo_throw_into_generator():
    """Demonstrate throwing an exception into a running generator."""
    def counter():
        """Generator that counts until interrupted."""
        try:
            i = 0
            while True:
                yield i
                i += 1
        except ValueError as e:
        …
12 0 Open
Comprehensions & generators easy

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.

comprehensions generators yield
Python
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
…
15 0 Open
Comprehensions & generators medium

How to filter a generator with a predicate function in Python

This code defines a generator function that yields only items from an iterable that satisfy a given predicate, then tests it with even and positive number filters.

generators filtering lazy evaluation
Python
def filter_gen(predicate, iterable):
    for item in iterable:
        if predicate(item):
            yield item

def is_even(num):
    return num % 2 == 0

def is_positive(num):
    return num > 0

if __name__ == "__main__":
    numbers = range(-5, 10)
    
    even_numbers = list(filter_gen(is_even, numbers))
    p…
10 0 Open
Comprehensions & generators easy

How to skip items until a condition is met in Python

Use itertools.dropwhile to skip leading elements while a predicate returns true, then yield the rest of the sequence unchanged.

itertools generators dropwhile
Python
def is_negative(x):
    return x < 0

numbers = [-3, -1, 0, 5, 2, -8, 7]
result = list(itertools.dropwhile(is_negative, numbers))
print(f"Original: {numbers}")
print(f"After dropwhile: {result}")
13 0 Open
Comprehensions & generators medium

Merge Sorted Iterators with a Heap Generator in Python

Merge multiple sorted iterators into a single sorted stream using a heap and generator, yielding values lazily in order.

heapq generator merge
Python
import heapq

def merge_sorted_iterators(*iterators):
    heap = []
    for idx, iterator in enumerate(iterators):
        try:
            value = next(iterator)
            heapq.heappush(heap, (value, idx, iterator))
        except StopIteration:
            continue

    while heap:
        value, idx, iterator = …
15 0 Open
Comprehensions & generators easy

Python Generator to Filter Duplicates with a Seen Set

A lazily-evaluated generator function that yields only the first occurrence of each item, using a set to track seen values.

generator dedupe set
Python
def unique_generator(items):
    seen = set()
    for item in items:
        if item not in seen:
            seen.add(item)
            yield item

if __name__ == "__main__":
    data = [1, 2, 2, 3, 3, 3, 4, 5, 5]
    result = list(unique_generator(data))
    print(result)
14 0 Open

Browse by section

Each section groups closely related Python snippets.

Comprehensions & generators — Python code examples

What you will find here

This page collects comprehensions & generators snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.

Samples vs tutorials and challenges

Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.