types Module Workbook Added to Standard Library Learning Path

#hejhdiss #python3

I've just completed and uploaded the types module workbook to my standardlib-datastruct repository. This addition dives into Python's runtime object types and CPython internals.

What's Inside

The types workbook contains 18 exercises covering runtime object types from Python's types module. The goal is coverage, not order—master the types that power Python under the hood.

Types Covered

Function and Method Types:

FunctionType and LambdaType - Regular functions and lambdas
MethodType - Bound methods
BuiltinFunctionType and BuiltinMethodType - Built-in callables

Async and Generator Types:

GeneratorType - Regular generators
AsyncGeneratorType - Async generators
CoroutineType - Coroutine objects

Code and Execution Types:

CodeType - Compiled bytecode objects
FrameType - Execution frames
TracebackType - Exception tracebacks

Descriptor Types:

MemberDescriptorType - Class attribute descriptors
WrapperDescriptorType - Low-level built-in descriptors
GetSetDescriptorType - C-implemented properties

Utility Types:

MappingProxyType - Read-only dictionary views
ModuleType - Module objects
EllipsisType - The ... singleton
NotImplementedType - The NotImplemented singleton

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:

Python's object model and how types work

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 Python's runtime type system.

Learning Note: CPython Descriptors

While working on this workbook, I discovered you can understand CPython's internal descriptor types without diving into C code:

MemberDescriptorType - Attributes implemented in CPython (like accessing attributes)
GetSetDescriptorType - Properties implemented in CPython (like property but in C)
WrapperDescriptorType - Methods implemented in CPython

This approach lets you understand Python's internals through the types module rather than reading C source code.

Note: Some types in this workbook aren't normally used in everyday code—I included them out of curiosity. Feel free to skip those if you want and focus on what's practical for your needs.

Python 3.11+ Features

I'm using Python 3.11 for my learning. The types module provides access to runtime types that are fundamental to understanding how Python works internally.

My Approach

I'm learning the standard library by:

Selecting the most useful modules and functions
Creating hands-on exercises that demonstrate real use cases
Building a personal reference that I can return to
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 types workbook is available now in the repository as types.7z. It includes:

types_exercises_workbook.md - Markdown format
types_exercises_workbook.pdf - PDF format (generated with pandoc + MiKTeX)
types_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, itertools 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!