Functional Programming in Python 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024

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David Mertz 作者

O'Reilly Media

譯者

2015-5-27 出版日期

39 頁數

0.00 價格

e-book

叢書系列

9781491928561 圖書編碼

Functional Programming in Python 在線電子書圖書標籤: Python 函數式編程 Functional

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發表於2024-06-01

Functional Programming in Python 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Functional Programming in Python 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Functional Programming in Python 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024

Functional Programming in Python 在線電子書用戶評價

評分☆☆☆☆☆

higher-order functions！感覺修煉一段時間以後得重看。

評分☆☆☆☆☆

順服 functional programming！pure functions 好！... 其實是本很短的 booklet，作為 FP 的 teaser，內容隻相當於三四篇 blog 但都是 python 下最主要的 FP-style 類似功能的實現。

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長知識瞭，感覺作者啊超級萌！

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https://github.com/greatabel/PythonRepository/tree/master/10Function%20Programming%20in%20Python 我隻想說我已經不是一張白紙瞭，沒法子抹去指令式編程，特彆是麵嚮對象編程在腦子留下的經曆瞭，如果當初大三學抽代時候能把函數式編程作為一種實踐，說不定第一感會是函數式思維。雖然時間是幻想，相對論比牛頓定律更精確，但是現實中大部分時間大傢還是繼續用牛頓思維，想到這個也就釋然一些瞭。

評分☆☆☆☆☆

higher-order functions！感覺修煉一段時間以後得重看。

Functional Programming in Python 在線電子書著者簡介

David Mertz, being a sort of Foucauldian Berkeley, believes, esse est denunte. David may be reached at mertz@gnosis.cx; his life pored over at http://gnosis.cx/publish/.

Functional Programming in Python 在線電子書著者簡介

Functional Programming in Python 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Functional Programming in Python 在線電子書圖書描述

Python is not a functional programming language, but it is a multi-paradigm language that makes functional programming easy to perform, and easy to mix with other programming styles. In this paper, David Mertz, a director of Python Software Foundation, examines the functional aspects of the language and points out which options work well and which ones you should generally decline.

Mertz describes ways to avoid Python’s imperative-style flow control, the nuances of callable functions, how to work lazily with iterators, and the use of higher-order functions. He also lists several third-party Python libraries useful for functional programming.

Topics include:

* Using encapsulation and other means to describe "what" a data collection consists of, rather than "how" to construct a data collection

* Creating callables with named functions, lambdas, closures, methods of classes, and multiple dispatch

* Using Python’s iterator protocol to accomplish the same effect as a lazy data structure

* Creating higher-order functions that take functions as arguments and/or produce a function as a result

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