OO: Python to Rust

本课程是 Rust for Data Engineering 专项课程的一部分

位教师：Noah Gift

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5个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

5个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Apply a receipt-driven, three-mode workflow (Discover, Refactor, Translate) to move object-oriented Python code into idiomatic Rust.
Translate Python class hierarchies into Rust structs, traits, enums, and the type-state pattern using composition over inheritance.
Score Python-to-Rust translation pull requests using a breakeven analysis and complexity-claim review rubric.

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作业

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授课语言：英语（English）

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该课程共有5个模块

OO: Python to Rust is a hands-on course on object-oriented design for engineers moving from Python (a class-based, dynamic OO language) to Rust (a struct-and-trait-based language with no inheritance and strict ownership). You will learn how Rust models the four classical OO pillars - encapsulation, abstraction, polymorphism, and code reuse - without classes or inheritance, using structs, methods (impl blocks), traits, trait objects, generics, enums, and the type state pattern. The course translates common Python OO patterns (dataclasses, dunder methods, ABCs, mixins, descriptors, protocols, the singleton, factory, observer, strategy, and decorator patterns) into idiomatic Rust, and explains why some of them simply don't apply once you have algebraic data types and ownership. You will refactor a non-trivial Python OO codebase into Rust, learn when composition beats inheritance, when an enum beats a class hierarchy, and how to design APIs that leverage Rust's compile-time guarantees. By the end of the course, you will be able to read OO Python code and produce a correct, idiomatic Rust translation, and justify your design decisions on a code review. Part of the Rust for Data Engineering specialization.

Every Big-O claim in this course ships with three independent receipts: an EMPIRICAL bench (criterion measures the curve), a STRUCTURAL guard (Rust types and proptest enforce it), and a FORMAL theorem (Lean 4 machine-checked, displayed as a [verified] stamp). Complexity is a CLAIM about how runtime or memory scales with input size. In this module you learn the c24 workflow: write the claim as a contract, bind it to your Rust pub item, then attach the three receipts. A CLAIM of O(N) survives only if the slope on a log-log plot stays linear from N=10 to N=1,000,000.

涵盖的内容

3个视频7篇阅读材料

3个视频总计4分钟

What "Complexity" Means + Three Modes of Proof1分钟
Reading a Complexity Claim - Falsifiability1分钟
Depyler - the Transpiler Shortcut1分钟

7篇阅读材料总计70分钟

About This Course10分钟
Key Terms: What "Complexity" Means + Three Modes of Proof10分钟
Reflection: What "Complexity" Means + Three Modes of Proof10分钟
Key Terms: Reading a Complexity Claim - Falsifiability10分钟
Reflection: Reading a Complexity Claim - Falsifiability10分钟
Key Terms: Depyler - the Transpiler Shortcut10分钟
Reflection: Depyler - the Transpiler Shortcut10分钟

In this module you will master Empirical Wins — the speedups you can measure with cargo bench. You will translate three Python patterns to Rust idioms that drop runtime and memory: list comprehensions become fused iterator chains (filter+map in one pass, O(1) memory vs O(N)); x in dict becomes HashMap::contains_key with hasher choice as a c24 receipt (FxHash, AHash, or default SipHash, each measured); and sorted() becomes sort_unstable for cases where stability is not required. Every claim ships with criterion HTML reports as the EMPIRICAL receipt, a STRUCTURAL guard from Rust's type system, and a [verified] stamp from a FORMAL theorem.

涵盖的内容

3个视频6篇阅读材料

3个视频总计4分钟

From Python List Comprehensions to Rust Iterator Chains1分钟
From Python Dict Lookup to Rust HashMap1分钟
From Python sorted() to Rust sort_unstable1分钟

6篇阅读材料总计60分钟

Key Terms: List Comprehension → Iterator10分钟
Reflection: List Comprehension → Iterator10分钟
Key Terms: x in dict → HashMap Lookup10分钟
Reflection: x in dict → HashMap Lookup10分钟
Key Terms: sorted() → sort_unstable10分钟
Reflection: sorted() → sort_unstable10分钟

Python Optional[T] becomes Rust Option<T> with proptest sweeping every combinator chain; Python try/except becomes Result<T, E> with @semantic: total promoting every fallible function — the structural receipt that makes silent failure impossible.

涵盖的内容

3个视频6篇阅读材料

3个视频总计3分钟

From Python Optional to Rust Option1分钟
From Python try/except to Rust Result1分钟
From Python Mutable Default to Rust Ownership1分钟

6篇阅读材料总计60分钟

Key Terms: Optional[T] → Option<T>10分钟
Reflection: Optional[T] → Option<T>10分钟
Key Terms: try/except → Result<T, E>10分钟
Reflection: try/except → Result<T, E>10分钟
Key Terms: Mutable Default Arg → Ownership10分钟
Reflection: Mutable Default Arg → Ownership10分钟

Systems-level translation makes the runtime trade-off visible. Python generators allocate per-call frame state and pay GIL overhead; Rust Iterator is monomorphized into the caller's stack — the structural receipt is the criterion bench showing a ~50x tight-loop gap. subprocess.run with sh -c re-introduces CWE-78 shell injection; Command::new().arg() invokes execve directly and removes the attack surface entirely. threading on CPython is serialized by the GIL; rayon::par_iter() distributes work across all cores via a Send + Sync work-stealing scheduler whose data-race bugs are compile errors. Each translation in this module is a runtime claim with a measurable receipt.

涵盖的内容

3个视频6篇阅读材料

3个视频总计3分钟

From Python yield Generator to Rust Iterator1分钟
From Python subprocess to Rust Command1分钟
From Python threading to Rust rayon Parallel Iterator1分钟

6篇阅读材料总计60分钟

Key Terms: Python generator → Rust Iterator10分钟
Reflection: Python generator → Rust Iterator10分钟
Key Terms: subprocess → Command10分钟
Reflection: Exhaustive Match as a Completeness Receipt10分钟
Key Terms: threading → rayon Parallel Iterator10分钟
Reflection: When to Pick ADT vs Trait10分钟

The capstone closes the loop with a five-step playbook — transpile, inspect, refine, bench, prove — that you can apply to any hot Python loop and ship a receipt-backed Rust translation. Every Pull Request lands four receipts: criterion HTML report, proptest run, contract pv check, and a Lean status: proved stamp. The second lesson is the inverse: when the receipt-driven math says keep Python. Breakeven analysis, BREAKEVEN.md, and a final graded quiz that synthesizes Modules 1–5.