test2learn.py

A collection of executable Python tests for learning and exploring Python standard library behaviors. Each test file focuses on a specific topic and documents how Python really works — useful for developers who prefer reading runnable code over prose.

Topics Covered

Module / Topic	File	What You'll Learn
Collections	tests/test_collection.py	tuple immutability, namedtuple usage and _replace
Copy	tests/test_copy.py	Reference binding, shallow vs deep copy for dicts, lists, and objects; deepcopy memo behavior
Decorator	tests/test_decorator.py	Decorator stacking order and how it affects output
Generator	tests/test_generator.py	Generator functions with yield, lazy evaluation
Iterable	tests/test_iterable.py	Custom iterable classes (__iter__/__next__), finite vs infinite iterables
itertools	tests/test_itertools.py	itertools.product for Cartesian products
List Comprehension	tests/test_list_comprehension.py	Generator expressions, performance vs for-loop with append
Mock	tests/test_mock.py	Mock vs MagicMock, mock_calls, assert_has_calls
Pickle	tests/test_pickle.py	Serializing and deserializing Python objects to/from files
String Encoding	tests/test_str_encode.py	str vs bytes, UTF-8/Big5/EUC-JP file reading, encoding errors
Unicode Data	tests/test_unicodedata.py	East Asian width categories (Narrow, Wide, Fullwidth, etc.)
XML / ElementTree	tests/xml/test_etree.py	Parsing XML with namespaces using xml.etree.ElementTree

Requirements

• Python >= 3.12
• uv (package manager)

Quickstart

# Install dependencies
make sync

# Run all tests (excluding performance tests)
make test

# Run a specific test file
make test TEST=tests/test_copy.py

# Run performance tests
make test-perf

# Run all tests including performance tests
make test-all

# Clean generated files
make clean

Philosophy

Tests in this repo serve as living documentation. Instead of explaining Python in paragraphs, each test case asserts exactly what happens — making it easy to verify understanding interactively:

# From test_copy.py — shallow copy shares nested references
clone['cards'].append('ghi789')
assert (clone['cards'] is data['cards']) is True   # shallow copy!

# Deep copy creates fully independent clones
clone = copy.deepcopy(data)
assert (clone['cards'] is data['cards']) is False  # deep copy!

Performance tests (marked @pytest.mark.perf) are separated so the regular test suite stays fast. Run them explicitly when you want to compare approaches like list comprehension vs for-loop.

License

MIT