Comprehensions & generators
List/dict/set comprehensions, generator expressions, and lazy iteration.
Generate UUID4 Values with a Python Generator
This code defines a generator function that yields mock UUID4 values, allowing you to stream unique identifiers one at a time.
import uuid
def generate_uuids(count=5):
"""Generate a stream of mock UUID4 values."""
for _ in range(count):
yield uuid.uuid4()
if __name__ == "__main__":
# Generate and print 5 UUIDs
for uid in generate_uuids(5):
print(uid)Group Consecutive Keys in Python with itertools.groupby
Group consecutive equal elements in a list using the itertools.groupby generator, printing each key and its values.
from itertools import groupby
data = [1, 1, 2, 2, 3, 1, 1, 4, 4, 4]
for key, group in groupby(data):
group_list = list(group)
print(f"Key: {key}, Values: {group_list}")How to Accumulate Values with a Generator in Python
This generator yields the running total of an iterable's elements, producing a cumulative sum with each step.
def accum(iterable):
total = 0
for item in iterable:
total += item
yield total
# Demo
if __name__ == "__main__":
data = [1, 2, 3, 4, 5]
print(list(accum(data))) # [1, 3, 6, 10, 15]
# Also works with any iterable, e.g., range
print(list(accum(range(1, 6)))) # [1, 3, 6, 10, 15]How to Create an Infinite Arithmetic Sequence Generator in Python
Build a memory-efficient generator that yields an infinite arithmetic progression and extract the first N values with list comprehension.
"""Count generator infinite arithmetic progression"""
def arithmetic_counter(start=0, step=1):
"""Generate an infinite arithmetic sequence."""
current = start
while True:
yield current
current += step
if __name__ == "__main__":
counter = arithmetic_counter(1, 3)
result = [next(c…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.
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 {
…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 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)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.
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