《函数式Python编程东南》[67M]百度网盘|pdf下载|亲测有效

商品基本信息，请以下列介绍为准
商品名称：	函数式Python编程
作者：	Steven F. Lott
定价：	99.0
出版社：	东南大学出版社
出版日期：	2019-05-01
ISBN：	9787564183257
印次：
版次：
装帧：
开本：	小16开

内容简介
Python是一种计算机程序设计语言。是一种动态的、面向对象的脚本语言，*初被设计用于编写自动化脚本(shell)，随着版本的不断更新和语能的添加，越来越多地被用于独立的、大型项目的开发。本书讲解python知识。

Copyright and Creditr>Preface
Chapter 1： Understanding Functional Programming
Identifying a paradigm
Subdividing the procedural paradigm
Using the functional paradigm
Using a functional hybrid
Lo at object creation
The stack of turtler>A classic example of functional programming
Exploratory data analysir>Summary
Chapter 2： Introducing Essential Functional Conceptr>First-class functionr>Pure functionr>Higher-order functionr>Immutable data
Strict and non-strict evaluation
Recursion instead of an explicit loop state
Functional type systemr>Familiar territory
Learning some advanced conceptr>Summary
Chapter 3： Functions， Iterators， and Generatorr>Writing pure functionr>Functions as first-clasjectr>Using stringr>Using tuples and named tupler>Using generator expressionr>Exploring the limitations of generatorr>Combining generator expressionr>Cleaning raw data with generator functionr>Using lists， dicts， and setr>Using stateful mappingr>Using the bisect module to create a mapping
Using stateful setr>Summary
Chapter 4： Wo with Collectionr>An overview of function varietier>Wo with iterabler>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 functionr>Using any（） and all（） as reductionr>Using lenO and sum（）
Using sums and counts for statisticr>Using zip（） to structure and flatten sequencer>Unzipping a zipped sequence
Flattening sequencer>Structuring flat sequencer>Structuring flat sequences - an alternative approach
Using reversed（） to change the order
Using enumerate（） to include a sequence number
Summary
Chapter 5： Higher-Order Functionr>Using max（） and min0 to find extrema
Using Python lambda formr>Lambdas and the lambda calculur>Using the map（） function to apply a function to a collection
Wo with lambda forms and map（）
Using map（） with multiple sequencer>Using the filter（） function to pass or reject data
Using filter（） to identify outlierr>The iter0 function with a sentinel value
Using sorted（） to put data in order
Writing higher-order functionr>Writing higher-order mappings and filterr>Unwrapping data while mapping
Wrapping itional data while mapping
Flattening data while mapping
Structuring data while filtering
Writing generator functionr>Building higher-order functions with callabler>Assuring good functional design
Review of some design patternr>Summary
Chapter 6： Recursions and Reductionr>Simple numerical recursionr>Implementing tail-call optimization
Leaving recursion in place
Handling difficult tail-call optimization
Processing collections through recursion
Tail-call optimization for collectionr>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 valuer>Writing more general group-by reductionr>Writing higher-order reductionr>Writing file parserr>Parsing CSV filer>Parsing plain text files with headerr>Summary
Chapter 7： itional Tuple Techniquer>Using tuples to collect data
Using named tuples to collect data
Building named tuples with functional constructorr>Avoiding stateful classey using families of tupler>Assigning statistical rankr>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
Wo with the infinite iteratorr>Counting with count（）
Counting with float argumentr>Re-iterating a cycle with cycle（）
Repeating a single value with repeat（）
Using the finite iteratorr>Assigning numbers with enumerate（）
Running totals with accumulate（）
Combining iterators with chain（）
Partitioning an iterator with groupby0
Merging iterables with zip_longest0 and zip（）
Filtering with compress（）
Pi sets with islice（）
Stateful filtering with dropwhile0 and takewhile0
Two approaches to filtering with filterfalse（） and filter（）
Applying a function to data via starmap0 and map（）
Cloning iterators with tee（）
The itertools reciper>Summary
Chapter 9： More Itertools Techniquer>Enumerating the Cartesian product
Reducing a product
Computing distancer>Getting all pixels and all colorr>Performance analysir>Rearranging the problem
Combining two transformationr>Permuting a collection of valuer>Generating all combinationr>Reciper>Summary
Chapter 10： The Functools Module
Function toolr>Memoizing previous results with Iru_cache
Defining classes with total ordering
Defining number classer>Applying partial arguments with partial（）
Reducing sets of data with the reduce（） function
Combining map（） and reduce（）
Using the reduce（） and partial（） functionr>Using the map（） and reduce（） functions to sanitize raw data
Using the groupby0 and reduce（） functionr>Summary
Chapter 11： Decorator Design Techniquer>Decorators as higher-order functionr>Using the functools update_wrapper0 functionr>Cross-cutting concernr>Composite design
Preprocessing bad data
ing a parameter to a decorator
Implementing more complex decoratorr>CompLex design considerationr>Summary
Chapter 12： The Multiprocessing and Threading Moduler>Functional programming and concurrency
What concurrency really meanr>The boundary conditionr>Sharing resources with process or threadr>Where benefits will accrue
Using multiprocessing pools and taskr>Processing many large filer>Parsing log files - gathering the rowr>Parsing log lines into namedtupler>Parsing itional fields of an Accesject
Filtering the access detailr>Analyzing the access detailr>The complete analysis procer>Using a multiprocessing pool for concurrent processing
Using apply（） to make a single requer>Using the map_async0， starmap_async（）， and apply_async0 functionr>More complex multiprocessing architecturer>Using the concurrent．futures module
Using concurrent．futures thread poolr>Using the threading and queue moduler>Designing concurrent processing
Summary
Chapter 13： Conditional Expressions and the Operator Module
Evaluating conditional expressionr>Exploiting non-strict dictionary ruler>Filtering true conditional expressionr>Finding a matching pattern
Using the operator module instead of lambdar>Getting named attributes when using higher-order functionr>Starmapping with operatorr>Reducing with operator module functionr>Summary
Chapter 14： The PyMonad Library
Downloading and installing
Functional composition and currying
Using curried higher-order functionr>Currying the hard way
Functional composition and the PyMonad * operator
Functors and applicative functorr>Using the lazy List（） functor
Monad bind（） function and the >> operator
Implementing simulation with monadr>itional PyMonad featurer>Summary
Chapter 15： A Functional Approach to Web Servicer>The HTTP request-response model
Injecting state through cookier>Considering a server with a functional design
Lo more deeply into the functional view
Nesting the servicer>The WSGI standard
Throwing exceptions during WSGI processing
Pragmatic WSGI applicationr>Defining web services as functionr>Creating the WSGI application
Getting raw data
Applying a filter
Serializing the resultr>Serializing data into JSON or CSV formatr>Serializing data into XML
Serializing data into HTML
Tra usage
Summary
Chapter 16： Optimizations and Improvementr>Memoization and caching
Specializing memoization
Tail recursion optimizationr>Optimizing storage
Optimizing accuracy
Reducing accuracy based on audience requirementr>Case study-m a chi-squared decision
Filtering and reducing the raw data with a Counter object
Reading summarized data
Computing sums with a Counter object
Computing probabilities from Counter objectr>Computing expected values and displaying a contingency table
Computing the chi-squared value
Computing the chi-squared threshold
Computing the incomplete gamma function
Computing the complete gamma function
Computing the s of a distribution being random
Functional programming design patternr>Summary
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Index

函数式Python编程东南 pdf下载

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