《F#编程指南》：迈向.NET框架的函数式编程革命

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《F#编程指南：迈向.NET框架的函数式编程》（2014年版）是Dave Fancher编著的一本专业书籍，由No Starch Press出版。本书旨在帮助读者理解和掌握F#语言，这是一种将函数式编程思想引入.NET Framework平台的技术，特别适合那些习惯于C#和Visual Basic的传统开发者。 F#以其强大的功能性和简洁性，引领开发者摆脱传统的面向对象编程模式，转而利用诸如默认不可变性、管道操作、类型推断和模式匹配等特性，编写出高效、可靠且可预测的代码。作者通过实例和深入剖析，引导读者学习如何： 1. 利用函数式特性：理解并运用currying（部分应用）和delegation（委托），提升函数的复用性和灵活性。 2. 优化数据处理：通过record types（记录类型）和discriminated unions（枚举类型）简化数据结构的创建和类型安全性。 3. 高效数据操作：运用collection types（集合类型）和modules（模块）来管理大型数据集，提高效率。 4. 模式匹配与分支控制：通过pattern matching（模式匹配）对复杂类型进行分解，实现一行代码内的逻辑分支。 5. 并行编程与异步流程：运用平行编程和asynchronous workflows（异步工作流）提升软件响应速度。 6. 面向对象与互操作性：利用F#的面向对象特性构建丰富的框架，并与其他.NET语言无缝交互。 7. 数据访问与操作：借助query expressions（查询表达式）和type providers（类型提供者）处理来自不同源的数据。这本书不仅教授技术知识，更鼓励读者跳出传统编程思维，体验F#带来的表达力提升，从而创作出更为智能和精简的代码。无论是初学者还是经验丰富的开发人员，都能在《F#编程指南》中找到提升技能的新视角和工具。

xiv Contents in Detail

Aggregating Data .......................................... 213

Detecting Items ............................................ 214

Joining Multiple Data Sources .................................. 215

Extending Query Expressions .................................. 219

Type Providers ................................................... 221

Available Type Providers ..................................... 222

Using Type Providers ........................................ 223

Example: Accessing an OData Service............................ 224

Example: Parsing a String with RegexProvider....................... 226

Summary ...................................................... 228

ASYNCHRONOUS AND PARALLEL PROGRAMMING 229

Task Parallel Library ............................................... 230

Potential Parallelism ......................................... 231

Data Parallelism............................................ 231

Task Parallelism ............................................ 234

Asynchronous Workflows ........................................... 241

Creating and Starting Asynchronous Workflows ..................... 242

Cancelling Asynchronous Workflows ............................. 245

Exception Handling ......................................... 247

Asynchronous Workflows and the Task Parallel Library................. 248

Agent-Based Programming .......................................... 250

Getting Started ............................................ 250

Scanning for Messages ...................................... 251

Replying to Messages........................................ 252

Example: Agent-Based Calculator ............................... 253

Summary ...................................................... 255

COMPUTATION EXPRESSIONS 257

Anatomy of a Computation Expression .................................. 258

Example: FizzBuzz................................................ 261

Example: Building Strings ........................................... 264

Summary ...................................................... 269

INDEX 271

xvi Foreword

Continuous improvement seemed more than just a way to make wid-

gets; it felt like a way to live life. It echoed Socrates’s concept of virtue; it

evoked the story of Siddhartha, who sought truth over comfort. These are

ideas about “what should be,” about merit, about substance over rhetoric,

about correctness.

After graduation I rolled into a software development career. Depend-

ing on the company, it was either clown cars and cowboys, or rigid waterfall.

Both were exciting, but no one in either environment was talking about

quality or continuous improvement. When I would bring it up, I would get

sad smiles from grizzled developers. Their eyes said, “Son, don’t you realize

this is war?” The operating systems were crashy, the dev tools were buggy,

and everything was closed source and proprietary. Thucydides said war is

“a rough master that brings most men’s characters to a level with their for-

tune.” Likewise, when the development environment is bad, most developers

will write bad code.

In 2001, a group of conscientious software developers got together

in Snowbird, Utah and signed the Agile Manifesto. About a year later I

discovered it. From my perspective, it seemed like a retelling of Deming,

operations management, and Lean manufacturing. It was the ﬁrst time

in my career that I’d heard developers discussing quality and continuous

improvement. There was hope!

After ﬁve years of test-driven development, pair programming, the

SOLID principles (single responsibility, open/closed, Liskov substitution,

interface segregation, and dependency inversion), and Scrum, my hope had

mostly worn away. I continued to ﬁght my tools, and it remained difﬁcult to

build quality software. Without discipline it was a train wreck. With disci-

pline, process, and diligence, it was a hard slog.

Through pure good luck I encountered Erlang in 2007, and in 2009 I

began working with F#. Functional programming consumed me. I learned

about immutability, recursion, pattern matching, higher-order functions,

referential transparency, code as data, and separation of behavior from

data. As I learned and practiced I began to see the huge cost of OO. So

much of what made my day-to-day coding life miserable was solvable with

Erlang and F#. As I told people about FP, I again received those sad smiles

that asked, “Don’t you know we are at war?” I took it differently this time. I

decided, “OK, sure. Let’s call it war. I’ll be on the side that’s looking at the

root cause of defects. I’ll be on the side that wants to ﬁx the problem at the

source.”

The next stage for Agile must be to fully unravel itself from OO.

Object-oriented programming had boldly promised “to model the

world.” Well, the world is a scary place where bad things happen for no

apparent reason, and in this narrow sense I concede that OO does model

the world. OO as we have it mingles data and behavior; the result is low

cohesion and tight coupling. In OO, there is shared mutable state, which

makes concurrency impossibly difﬁcult. In OO, logic is nondeterministic.

In OO, the result of a function doesn’t simply depend on the arguments

we pass in. The result may vary depending on arguments passed on previ-

ous calls to the function. How about mutations from other functions? How

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《F#编程指南》：迈向.NET框架的函数式编程革命

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