函数式Python编程(第2版影印版)(英文版) 9787564183257

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作者: (美)史蒂文·F.洛特
出版社: 东南大学
ISBN: 9787564183257

出版时间: 2019-05
装帧: 其他
开本: 其他

作者: (美)史蒂文·F.洛特
出版社: 东南大学

ISBN: 9787564183257
出版时间: 2019-05

装帧: 其他
开本: 其他

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目录
Copyright and Credits
Preface
Chapter 1: Understanding Functional Programming
  Identifying a paradigm
  Subdividing the procedural paradigm
    Using the functional paradigm
    Using a functional hybrid
    Looking at object creation
    The stack of turtles
  A classic example of functional programming
  Exploratory data analysis
  Summary
Chapter 2: Introducing Essential Functional Concepts
  First-class functions
    Pure functions
    Higher-order functions
  Immutable data
  Strict and non-strict evaluation
  Recursion instead of an explicit loop state
  Functional type systems
  Familiar territory
  Learning some advanced concepts
  Summary
Chapter 3: Functions, Iterators, and Generators
  Writing pure functions
  Functions as first-class objects
  Using strings
  Using tuples and named tuples
    Using generator expressions
    Exploring the limitations of generators
    Combining generator expressions
  Cleaning raw data with generator functions
  Using lists, dicts, and sets
    Using stateful mappings
    Using the bisect module to create a mapping
    Using stateful sets
  Summary
Chapter 4: Working with Collections
  An overview of function varieties
  Working with iterables
    Parsing an XML file
    Parsing a file at a higher level
    Pairing up items from a sequence
    Using the iterO function explicitly
    Extending a simple loop
    Applying generator expressions to scalar functions
    Using any() and all() as reductions
    Using lenO and sum()
    Using sums and counts for statistics
  Using zip() to structure and flatten sequences
    Unzipping a zipped sequence
    Flattening sequences
    Structuring flat sequences
    Structuring flat sequences - an alternative approach
  Using reversed() to change the order
  Using enumerate() to include a sequence number
  Summary
Chapter 5: Higher-Order Functions
  Using max() and min0 to find extrema
  Using Python lambda forms
  Lambdas and the lambda calculus
  Using the map() function to apply a function to a collection
    Working with lambda forms and map()
  Using map() with multiple sequences
  Using the filter() function to pass or reject data
  Using filter() to identify outliers
  The iter0 function with a sentinel value
  Using sorted() to put data in order
  Writing higher-order functions
  Writing higher-order mappings and filters
    Unwrapping data while mapping
    Wrapping additional data while mapping
    Flattening data while mapping
    Structuring data while filtering
  Writing generator functions
  Building higher-order functions with callables
    Assuring good functional design
  Review of some design patterns
  Summary
Chapter 6: Recursions and Reductions
  Simple numerical recursions
    Implementing tail-call optimization
    Leaving recursion in place
    Handling difficult tail-call optimization
    Processing collections through recursion
    Tail-call optimization for collections
    Reductions and folding a collection from many items to one
  Group-by reduction from many items to fewer
    Building a mapping with Counter
    Building a mapping by sorting
    Grouping or partitioning data by key values
    Writing more general group-by reductions
    Writing higher-order reductions
    Writing file parsers
      Parsing CSV files
      Parsing plain text files with headers
  Summary
Chapter 7: Additional Tuple Techniques
  Using tuples to collect data
  Using named tuples to collect data
  Building named tuples with functional constructors
  Avoiding stateful classes by using families of tuples
    Assigning statistical ranks
    Wrapping instead of state changing
    Rewrapping instead of state changing
    Computing Spearman rank-order correlation
  Polymorphism and type-pattern matching
  Summary
Chapter 8: The Itertools Module
  Working with the infinite iterators
    Counting with count()
    Counting with float ar

内容摘要
如果你是一名想要了解如何利用函数式编程的强大功能并将其应用于自己的程序中的Python开发人员，那么这是一本你不容错过的书，哪怕你对这种编程范式几乎一无所知。
本书一开始先概述了函数式概念，你会了解到一
些常见的函数式特性，例如头等函数、高阶函数、纯函数等。接下来，你将看到如何在Python中运用这些特性，以此为你提供立足的核心基础知识。在这之后，你将学习用于Python的常见函数式优化，以帮助你的应用程序达到更高的运行速度。
你会学习到函数式编程的概念，例如使用Python的生成器函数和表达式实现惰性求值，然后学习如何设计和实现装饰器来创建复合函数。此外你还将深入探索数据预备技术和数据探查，了解Python标准库如
何适应函数式编程模型。最后，为了结束Python函数式编程世界的探索旅程，本书会向你展示PyMonad项目和一些更大规模的示例，以开阔你的视野。
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