PYTHON-06 · Undergraduate · ENGLISH · PLANNED
Predict the output, trace state, write a small program and debug it.
Study time is an initial activity estimate, excluding extra reading, revision and extended laboratory or project work. Videos and question bodies have not been produced by adding this outline.
Complete these courses or demonstrate equivalent knowledge. These are recommended prerequisites, not enforced enrolment locks.
YouTube playlist: ARK Python | Object-Oriented and Typed Python
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Sign in to save this learning pathPractical outcome: Represent a library's books and loans with explicit invariants.
Explain classes using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Explain instances using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Explain attributes using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Explain methods using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Use the first concepts from this section. Represent a library's books and loans with explicit invariants. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain initialisation using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Explain class versus instance data using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Explain composition using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Explain inheritance using a visual and one worked real-world example. Context: Represent a library's books and loans with explicit invariants. End with a prediction or check-for-understanding.
Represent a library's books and loans with explicit invariants. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Classes, Instances, Attributes and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Design a small collection with predictable behaviour.
Explain dunder methods using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Explain repr and str using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Explain equality using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Explain ordering using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Use the first concepts from this section. Design a small collection with predictable behaviour. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain properties using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Explain dataclasses using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Explain iteration protocol using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Explain context-manager protocol using a visual and one worked real-world example. Context: Design a small collection with predictable behaviour. End with a prediction or check-for-understanding.
Design a small collection with predictable behaviour. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Dunder methods, repr and str, Equality and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Describe and check the interface of a data-import service.
Explain type annotations using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain optional values using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain union types using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain generics using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain protocols using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Use the first concepts from this section. Describe and check the interface of a data-import service. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain typed dictionaries using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain static checking using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain dependency injection using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain immutability using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Explain refactoring using a visual and one worked real-world example. Context: Describe and check the interface of a data-import service. End with a prediction or check-for-understanding.
Describe and check the interface of a data-import service. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Type annotations, Optional values, Union types and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Combine all three sections: Describe and check the interface of a data-import service. Submit an original worked artifact, evidence or tests, assumptions and a reflection. Rubric: correctness, method, practical usefulness, reproducibility and communication. Self-reviewed, not certified.
6–12 balanced questions sampling every section of Object-Oriented and Typed Python, including interpretation, calculation or reasoning, a misconception and a new application. Passing is 70%; review errors before retrying.
Coding, trace tables, tests and original portfolio projects. Guided work leads to an independent attempt, with a diagram, explanation, trace, calculation or tested artifact. Question bodies are generated when opened in your private learning path. Programming submissions are stored as text; the platform does not execute submitted code.
Use original or appropriately licensed datasets. Practical science activities use models or supplied data unless a qualified supervisor has reviewed a physical experiment.
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