Reference library

Comprehensions & generators

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

5 matches

Build a Generator Pipeline in Python: Filter Then Map

Create a lazy data pipeline by chaining generator functions that read, filter, map, and write data step by step.

def read_data():
    return ["a", "bb", "ccc", "dd", "eeeee", "f"]


def filter_short(words):
    return (word for word in words if len(word) >= 2)


def map_to_upper(words):
    return (word.upper() for word in words)


def write_data(words):
    for word in words:
        print(word)


if __name__ == "__main__":
   …

12 0 Open

Comprehensions & generators easy

Dict Comprehension to Map Keys to Lengths in Python

Build a dictionary that maps each word to its character count using a dictionary comprehension.

dictionary comprehension len

Python

words = ["apple", "banana", "cherry", "date", "elderberry"]

word_lengths = {word: len(word) for word in words}

print(word_lengths)

14 0 Open

Comprehensions & generators easy

How to Lazily Transform Items in Python with a Generator

Map a transform function over an iterable lazily with a generator so items are processed on demand, not up front.

generators lazy evaluation mapping

Python

def lazy_map(items, transform):
    for item in items:
        yield transform(item)

def double(x):
    return x * 2

def upper(s):
    return s.upper()

if __name__ == "__main__":
    numbers = [1, 2, 3, 4, 5]
    doubled = lazy_map(numbers, double)
    print("Doubled numbers:", end=" ")
    for value in doubled:
  …

14 0 Open

Comprehensions & generators easy

How to Use starmap() to Unpack Tuple Arguments in Python

Use itertools.starmap to apply a function to each tuple in an iterable, unpacking tuple elements as separate arguments and returning an iterator of results.

itertools starmap generators

Python

from itertools import starmap

def multiply(a, b):
    return a * b

if __name__ == "__main__":
    pairs = [(2, 3), (4, 5), (6, 7), (8, 9)]
    results = list(starmap(multiply, pairs))
    print(results)

14 0 Open

Comprehensions & generators easy

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.

generator file-io streaming

Python

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…

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