本文实例讲述了python集合用法。分享给大家供大家参考。具体分析如下:
# sets are unordered collections of unique hashable elements # Python23 tested vegaseat 09mar2005 # Python v2.4 has sets built in import sets print "List the functions within module 'sets':" for funk in dir(sets): print funk # create an empty set set1 = set([]) # now load the set for k in range(10): set1.add(k) print "\nLoaded a set with 0 to 9:" print set1 set1.add(7) print "Tried to add another 7, but it was already there:" print set1 # make a list of fruits as you put them into a basket basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana'] print "\nThe original list of fruits:" print basket # create a set from the list, removes the duplicates fruits = sets.Set(basket) print "\nThe set is unique, but the order has changed:" print fruits # let's get rid of some duplicate words str1 = "Senator Strom Thurmond dressed as as Tarzan" print "\nOriginal string:" print str1 print "A list of the words in the string:" wrdList1 = str1.split() print wrdList1 # now create a set of unique words strSet = sets.Set(wrdList1) print "The set of the words in the string:" print strSet print "Convert set back to string (order has changed!):" print " ".join(strSet) print # comparing two sets, bear with me ... colorSet1 = sets.Set(['red','green','blue','black','orange','white']) colorSet2 = sets.Set(['black','maroon','grey','blue']) print "colorSet1 =", colorSet1 print "colorSet2 =", colorSet2 # same as (colorSet1 - colorSet2) colorSet3 = colorSet1.difference(colorSet2) print "\nThese are the colors in colorSet1 that are not in colorSet2:" print colorSet3 # same as (colorSet1 | colorSet2) colorSet4 = colorSet1.union(colorSet2) print "\nThese are the colors appearing in both sets:" print colorSet4 # same as (colorSet1 ^ colorSet2) colorSet5 = colorSet1.symmetric_difference(colorSet2) print "\nThese are the colors in colorSet1 or in colorSet2, but not both:" print colorSet5 # same as (colorSet1 & colorSet2) colorSet6 = colorSet1.intersection(colorSet2) print "\nThese are the colors common to colorSet1 and colorSet2:" print colorSet6
希望本文所述对大家的Python程序设计有所帮助。

Arraysinpython,尤其是Vianumpy,ArecrucialInsCientificComputingfortheireftheireffertheireffertheirefferthe.1)Heasuedfornumerericalicerationalation,dataAnalysis和Machinelearning.2)Numpy'Simpy'Simpy'simplementIncressionSressirestrionsfasteroperoperoperationspasterationspasterationspasterationspasterationspasterationsthanpythonlists.3)inthanypythonlists.3)andAreseNableAblequick

你可以通过使用pyenv、venv和Anaconda来管理不同的Python版本。1)使用pyenv管理多个Python版本:安装pyenv,设置全局和本地版本。2)使用venv创建虚拟环境以隔离项目依赖。3)使用Anaconda管理数据科学项目中的Python版本。4)保留系统Python用于系统级任务。通过这些工具和策略,你可以有效地管理不同版本的Python,确保项目顺利运行。

numpyarrayshaveseveraladagesoverandastardandpythonarrays:1)基于基于duetoc的iMplation,2)2)他们的aremoremoremorymorymoremorymoremorymoremorymoremoremory,尤其是WithlargedAtasets和3)效率化,效率化,矢量化函数函数函数函数构成和稳定性构成和稳定性的操作,制造

数组的同质性对性能的影响是双重的:1)同质性允许编译器优化内存访问,提高性能;2)但限制了类型多样性,可能导致效率低下。总之,选择合适的数据结构至关重要。

到CraftCraftExecutablePythcripts,lollow TheSebestPractices:1)Addashebangline(#!/usr/usr/bin/envpython3)tomakethescriptexecutable.2)setpermissionswithchmodwithchmod xyour_script.3)

numpyArraysareAreBetterFornumericalialoperations andmulti-demensionaldata,而learthearrayModuleSutableforbasic,内存效率段

numpyArraySareAreBetterForHeAvyNumericalComputing,而lelethearRayModulesiutable-usemoblemory-connerage-inderabledsswithSimpleDatateTypes.1)NumpyArsofferVerverVerverVerverVersAtility andPerformanceForlargedForlargedAtatasetSetsAtsAndAtasEndCompleXoper.2)

ctypesallowscreatingingangandmanipulatingc-stylarraysinpython.1)usectypestoInterfacewithClibrariesForperfermance.2)createc-stylec-stylec-stylarraysfornumericalcomputations.3)passarraystocfunctions foreforfunctionsforeffortions.however.however,However,HoweverofiousofmemoryManageManiverage,Pressiveo,Pressivero


热AI工具

Undresser.AI Undress
人工智能驱动的应用程序,用于创建逼真的裸体照片

AI Clothes Remover
用于从照片中去除衣服的在线人工智能工具。

Undress AI Tool
免费脱衣服图片

Clothoff.io
AI脱衣机

Video Face Swap
使用我们完全免费的人工智能换脸工具轻松在任何视频中换脸!

热门文章

热工具

SublimeText3汉化版
中文版,非常好用

适用于 Eclipse 的 SAP NetWeaver 服务器适配器
将Eclipse与SAP NetWeaver应用服务器集成。

WebStorm Mac版
好用的JavaScript开发工具

SublimeText3 Linux新版
SublimeText3 Linux最新版

MinGW - 适用于 Windows 的极简 GNU
这个项目正在迁移到osdn.net/projects/mingw的过程中,你可以继续在那里关注我们。MinGW:GNU编译器集合(GCC)的本地Windows移植版本,可自由分发的导入库和用于构建本地Windows应用程序的头文件;包括对MSVC运行时的扩展,以支持C99功能。MinGW的所有软件都可以在64位Windows平台上运行。