Module 04 · Dynamic execution in Python

Dynamic runtimes and the Python object model

Python executes through dynamic object graphs and an interpreted evaluation loop. Explore the PyObject layout, implement the C3 linearization algorithm for method resolution order, construct parameterized closures and decorators, and build lazy generator pipelines.

4 lessons · 4 graded exercises·3 hours·intermediate·Prerequisite: Polymorphism, vtables, and generic containers in C++

The PyObject structure and dynamic typing

20 min · exercise

How CPython represents all data as heap-allocated PyObject structs, reference counts, type pointers, value boxing, and mutability.

Dynamic attribute lookup and C3 linearization

25 min · exercise

Dictionary-backed instance attributes, descriptor protocol mechanics, multiple inheritance ambiguities, and the C3 method resolution order algorithm.

Scopes, closures, and metaprogramming decorators

20 min · exercise

Lexical scoping rules (LEGB), closure environments, free variable capture, decorator wrapping, and parameterized function transforms.

Iterators, generator state machines, and streams

25 min · exercise

The iterator protocol, generator frame suspension and resumption, memory-bounded lazy stream processing, and pipeline composition.