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Each track is designed as a 30-day challenge — one lesson per day, about 15 minutes each. Go at your own pace, but the structure is built around daily consistency.

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Each lesson is a student-teacher dialogue with code examples, followed by a hands-on code challenge in an in-browser editor. You read, you understand, then you write real code.

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Our beginner track starts from absolute zero — no prior experience needed. Advanced tracks build on earlier ones, and the platform tells you exactly where to start.

How is zuzu.codes different from freeCodeCamp or Codecademy?

zuzu.codes uses a structured 30-day track format with dialogue-based teaching, an in-browser code editor, and gamification (XP, streaks, progress tracking). The format builds genuine understanding through daily practice.

Day 29 · ~11 min●

Final week. Six lessons on the advanced layer plus one final synthesis. Eight questions, 80% to pass — and then you've completed Python Mastery.

What week 4 covered

Lesson	Concept
23	`@property` — methods that look like attributes
24	Abstract base classes — `ABC` + `@abstractmethod`
25	`Protocol` — structural typing without inheritance
26	`__slots__` — fixed attribute set, smaller memory
27	Generators vs lists — when to drop the brackets
28	Final synthesis — six primitives in one library

What the full track covered

Four weeks, 24 code lessons, 4 quizzes, plus pre/post confidence checks. The kit:

Shape — class, __init__, methods, @dataclass, type hints
Wrapping behaviour — first-class functions, decorators, decorators with arguments
Lazy iteration — generators, generator pipelines, generator expressions
Resource management — @contextmanager, with blocks, guaranteed cleanup
Verification — unittest, subTest, parametrised tests, fail-loud mindset
Organisation — modules, packages, __init__.py, idiomatic style (EAFP, truthiness, is None)
Refinement — @property, ABC contracts, Protocol typing, __slots__, generator-vs-list tradeoffs

This is the complete idiomatic-Python toolkit for reading and contributing to real codebases.

Sign up to practice

Create a free account to get started. Paid plans unlock all tracks.

Day 29 · ~11 min●

Final week. Six lessons on the advanced layer plus one final synthesis. Eight questions, 80% to pass — and then you've completed Python Mastery.

What week 4 covered

Lesson	Concept
23	`@property` — methods that look like attributes
24	Abstract base classes — `ABC` + `@abstractmethod`
25	`Protocol` — structural typing without inheritance
26	`__slots__` — fixed attribute set, smaller memory
27	Generators vs lists — when to drop the brackets
28	Final synthesis — six primitives in one library

What the full track covered

Four weeks, 24 code lessons, 4 quizzes, plus pre/post confidence checks. The kit:

Shape — class, __init__, methods, @dataclass, type hints
Wrapping behaviour — first-class functions, decorators, decorators with arguments
Lazy iteration — generators, generator pipelines, generator expressions
Resource management — @contextmanager, with blocks, guaranteed cleanup
Verification — unittest, subTest, parametrised tests, fail-loud mindset
Organisation — modules, packages, __init__.py, idiomatic style (EAFP, truthiness, is None)
Refinement — @property, ABC contracts, Protocol typing, __slots__, generator-vs-list tradeoffs

This is the complete idiomatic-Python toolkit for reading and contributing to real codebases.

What week 4 covered

Lesson	Concept
23	`@property` — methods that look like attributes
24	Abstract base classes — `ABC` + `@abstractmethod`
25	`Protocol` — structural typing without inheritance
26	`__slots__` — fixed attribute set, smaller memory
27	Generators vs lists — when to drop the brackets
28	Final synthesis — six primitives in one library

What the full track covered

Four weeks, 24 code lessons, 4 quizzes, plus pre/post confidence checks. The kit:

Shape — class, __init__, methods, @dataclass, type hints

Wrapping behaviour — first-class functions, decorators, decorators with arguments

Lazy iteration — generators, generator pipelines, generator expressions

Resource management — @contextmanager, with blocks, guaranteed cleanup

Verification — unittest, subTest, parametrised tests, fail-loud mindset

Organisation — modules, packages, __init__.py, idiomatic style (EAFP, truthiness, is None)

Refinement — @property, ABC contracts, Protocol typing, __slots__, generator-vs-list tradeoffs

This is the complete idiomatic-Python toolkit for reading and contributing to real codebases.

What week 4 covered

Lesson	Concept
23	`@property` — methods that look like attributes
24	Abstract base classes — `ABC` + `@abstractmethod`
25	`Protocol` — structural typing without inheritance
26	`__slots__` — fixed attribute set, smaller memory
27	Generators vs lists — when to drop the brackets
28	Final synthesis — six primitives in one library