Comprehensions & generators
List/dict/set comprehensions, generator expressions, and lazy iteration.
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.
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}")List Comprehension to Filter Even Numbers in Python
Creates a new list containing only the even numbers from an existing list using a list comprehension with a condition.
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
even_numbers = [n for n in numbers if n % 2 == 0]
print(f"Original: {numbers}")
print(f"Even numbers: {even_numbers}")Memory efficient map over large file in Python
A generator-based streaming map that processes a large file line by line without loading the whole file into memory.
import sys
def process_lines(file_path):
"""Memory-efficient map over a large file: yields processed lines."""
with open(file_path, 'r') as f:
for line in f:
# Example mapping: strip whitespace and uppercase
yield line.strip().upper()
if __name__ == "__main__":
# Use a sma…Merge Data with Comprehension and Generator in Python
Merge user and order data using a dictionary comprehension for lookups and a generator expression to filter and transform orders.
def merge_data(users, orders):
"""
Merge user and order data using a dictionary comprehension
and a generator expression for filtering.
"""
# Build a lookup: user_id -> user name
user_map = {user["id"]: user["name"] for user in users}
# Generator: yield orders with user names attached
…Normalize Data in Python with Comprehensions and Generators
Clean a list by dropping None values with a comprehension, then min-max normalize it using a lazy generator expression — a beginner-friendly data preparation pattern.
import statistics
# Sample raw data including missing and outlier-ish values
raw = [22, 18, None, 25, 30, 19, 22, 17, None, 28, 24]
# Clean the data: drop None values using a list comprehension
clean = [x for x in raw if x is not None]
# Normalize using min-max scaling with a generator expression
min_val = min(clea…Python Comprehensions and Generators for Beginners
Learn list, dict, and set comprehensions plus generator expressions and generator functions with clear, runnable examples.
# Demonstrates list comprehensions, dict comprehensions, set comprehensions, and generators
def demonstrate_comprehensions():
# List comprehension: squares of even numbers
numbers = range(1, 11)
even_squares = [n ** 2 for n in numbers if n % 2 == 0]
# Dict comprehension: number to its factorial
…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.
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)Set Comprehension for Unique Word Lengths in Python
Use a set comprehension to extract unique word lengths from a string, then sort and print the result.
text = "hello world hello python programming"
word_lengths = {len(word) for word in text.split()}
print("Unique word lengths:", word_lengths)
print("Sorted:", sorted(word_lengths))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.
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)}")Take n items from an infinite Python generator
Uses itertools.islice to lazily take exactly n items from an infinite generator without exhausting it.
from itertools import islice
def count_up_from(start=0):
n = start
while True:
yield n
n += 1
def take_n(generator, count):
return list(islice(generator, count))
if __name__ == "__main__":
gen = count_up_from(10)
result = take_n(gen, 5)
print(result)Write Data Helpers with Comprehensions and Generators in Python
Demonstrates list, dict, and set comprehensions plus generator expressions and generator functions for building concise data helpers.
# Basic comprehensions and generators demo
# List comprehension: squares of evens
squares = [x * x for x in range(10) if x % 2 == 0]
print("List comp:", squares)
# Dictionary comprehension: char -> count
text = "hello"
char_counts = {c: text.count(c) for c in set(text)}
print("Dict comp:", char_counts)
# Set compre…Browse by section
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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.