itertools Workbook Added to Standard Library Learning Path

I've just completed and uploaded the itertools workbook to my standardlib-datastruct repository. This continues my journey through Python's standard library with a focus on iterator tools for efficient data handling.

What's Inside

The itertools workbook contains 20 exercises covering the essential iterator tools from Python's itertools module, organized into four sections:

Section 1 — Infinite Iterators

• count - Counting with custom start and step
• cycle - Cycling through iterables infinitely
• repeat - Repeating elements

Section 2 — Finite Iterators / Combinatorics

• accumulate - Running totals and cumulative operations
• chain and chain.from_iterable - Combining iterables
• combinations and combinations_with_replacement - Combinations without/with repetition
• permutations - Ordered arrangements
• product - Cartesian products
• starmap - Applying functions to tuples
• tee - Duplicating iterators
• zip_longest - Zipping with fillvalue

Section 3 — Filtering / Slicing Iterators

• dropwhile and takewhile - Conditional iteration
• filterfalse - Inverse filtering
• islice - Iterator slicing
• compress - Selecting by boolean mask

Section 4 — Combinatoric Helpers / Utilities

• pairwise - Consecutive pairs (Python 3.10+)
• Combined operations mixing multiple itertools functions

Each exercise includes a clear problem statement and a complete solution with working code examples.

About This Learning Path

This workbook is not beginner-friendly by design. It assumes you understand:

• The difference between iterables and iterators

I've included only the functionalities I find necessary and practical. This isn't an exhaustive reference—it's a focused learning tool for understanding the core capabilities of itertools.

Python 3.11+ Features

I'm using Python 3.11 for my learning. The workbook includes Python 3.10+ features like pairwise, which creates consecutive pairs from an iterable.

My Approach

I'm learning the standard library by:

1. Selecting the most useful modules and functions
2. Creating hands-on exercises that demonstrate real use cases
3. Building a personal reference that I can return to
4. Sharing it for others who want to follow a similar path

This repository (standardlib-datastruct) focuses on standard library tools that are useful when handling data structures. This may not include everything—I only add what I find necessary and want to learn. It's my curated selection based on practical needs.

Some standard library modules may be skipped because 3rd party or external libraries handle those use cases better. I focus on what's worth learning from the standard library itself.

This is my way of learning—practical, focused, and exercise-driven. If you're past the beginner stage and want to level up your Python skills, this might resonate with you.

Get the Workbook

The itertools workbook is available now in the repository as itertools.7z. It includes:

• itertools_exercises_workbook.md - Markdown format
• itertools_exercises_workbook.pdf - PDF format (generated with pandoc + MiKTeX)
• itertools_workbook.py - Source generator script

Feel free to download, work through the exercises, and adapt them to your learning style.

---

Repository: github.com/hejhdiss/standardlib-datastruct

Previous additions: functools workbook

Note: This is a living project. I'll continue adding more standard library modules as I complete them. Follow along if this learning approach works for you!