Big O notation: Python to Rust

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

位教师：Noah Gift

包含在中

了解更多

5个模块

深入了解一个主题并学习基础知识。

中级等级

需要一些相关经验

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

需要一些相关经验

6 小时完成

灵活的计划

自行安排学习进度

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

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

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有5个模块

Big O notation: Python to Rust is a hands-on algorithmic complexity course for engineers transitioning from Python to Rust who want to reason rigorously about how their code scales. You will learn Big O, Big Theta, and Big Omega notation; analyze the time and space complexity of common operations on Python and Rust data structures (list/Vec, dict/HashMap, set/HashSet, tuple, slice, BTreeMap); and compare measured performance in both languages on identical workloads. The course covers amortized analysis, recursion and master theorem, worst case versus expected case, the cost of allocation and borrowing, and how Rust's ownership model affects real-world constants even when asymptotic complexity is identical. You will profile Python code with cProfile and timeit, profile Rust code with criterion and perf, and translate Python algorithms (search, sort, hashing, graph traversal, dynamic programming) into idiomatic Rust while keeping or improving complexity guarantees. By the end of the course, you will be able to predict performance, choose appropriate data structures, justify rewrites from Python to Rust on quantitative grounds, and communicate trade-offs to a team. Part of the Rust for Data Engineering specialization.

Set the foundation: define what "complexity" actually means as a claim, and meet the three modes of proof — analytical, empirical, and structural — you'll use to defend complexity claims throughout the course. Learn to recognize falsifiable vs. unfalsifiable performance claims and build the worked-example habit you'll need in later modules.

涵盖的内容

3个视频7篇阅读材料

3个视频总计4分钟

1.1.1 What Complexity Means And Three Modes1分钟
1.2.1 Reading A Complexity Claim1分钟
1.3.1 Depyler 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

Empirical proof in practice: measure runtime with reproducible benchmarks. Three head-to-head Python→Rust translations — list comprehension to iterator, dict lookup to HashMap, and sorted() to sort_unstable — let you read benchmark output, control for noise, and decide when measured speedups are real and when they're artifacts.

涵盖的内容

3个视频6篇阅读材料

3个视频总计4分钟

2.1.1 List Comp To Iterator1分钟
2.2.1 Dict Lookup To Hashmap1分钟
2.3.1 Sorted To 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

Structural proof in practice: use the type system to make incorrect programs impossible to compile. Translating Optional[T] to Option<T>, try/except to Result<T,E>, and ad-hoc state machines to Rust enums turns runtime errors into compile-time errors — a structural guarantee no benchmark can refute.

涵盖的内容

3个视频6篇阅读材料

3个视频总计3分钟

3.1.1 Optional To Option1分钟
3.2.1 Try Except To Result1分钟
3.3.1 Mutable Default To 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

Translation with runtime consequences: each translation in this module replaces a Python construct (generators, subprocess calls, parallel loops) with a Rust equivalent that carries different runtime guarantees — memory profile, error surface, parallelism model — not just "the same thing, but faster."

涵盖的内容

3个视频6篇阅读材料

3个视频总计3分钟

4.1.1 Generator To Iterator1分钟
4.2.1 Subprocess To Command1分钟
4.3.1 Threading To Rayon1分钟

6篇阅读材料总计60分钟

Key Terms: Generator → Iterator10分钟
Reflection: Generator → Iterator10分钟
Key Terms: Subprocess → Command10分钟
Reflection: Subprocess → Command10分钟
Key Terms: Threading → Rayon10分钟
Reflection: Threading → Rayon10分钟

Capstone: bring all three modes of proof together on a real translation. Two case studies — a three-mode playbook end to end, and a deliberate "when NOT to translate" example — train your judgment about when a Python→Rust port pays off and when it would just add cost without measurable benefit.

涵盖的内容

2个视频5篇阅读材料1个作业

2个视频总计2分钟

5.1.1 Three-Mode Playbook End To End1分钟
5.2.1 When NOT to Translate1分钟

5篇阅读材料总计50分钟

Key Terms: Three-Mode Playbook End to End10分钟
Reflection: Three-Mode Playbook End to End10分钟
Key Terms: When NOT to Translate10分钟
Reflection: When NOT to Translate10分钟
Before You Go: Share Your Feedback10分钟

1个作业总计30分钟

Final Quiz: The Three-Mode Proof Playbook30分钟

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Noah Gift

Pragmatic AI Labs

58 门课程3,782 名学生

提供方

Pragmatic AI Labs

从 Software Development 浏览更多内容

Pragmatic AI Labs
Claude From Zero
课程
Pragmatic AI Labs
Shipping Rust
课程
Pragmatic AI Labs
IAC from Zero
课程
Pragmatic AI Labs
Valkey From Zero
课程

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

自 2018开始学习的学生

''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情，我就可以学习。'

Jennifer J.

自 2020开始学习的学生

''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.

自 2021开始学习的学生

''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'

Chaitanya A.

''学习不仅仅是在工作中做的更好：它远不止于此。Coursera 让我无限制地学习。'

通过订阅解锁 10,000 多门课程的访问权限
通过在线学位推动您的职业生涯
获取世界一流大学的学位 - 100% 在线
加入全球超过 4,700 家选择 Coursera for Business 的公司

常见问题

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.