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quiz-1081_405899001_基礎程式設計-進階函式-20200116-2206.xml
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quiz-1081_405899001_基礎程式設計-進階函式-20200116-2206.xml
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<?xml version="1.0" encoding="UTF-8"?>
<quiz>
<!-- question: 0 -->
<question type="category">
<category>
<text>$course$/1081_405899001_基礎程式設計的預設/進階函式</text>
</category>
</question>
<!-- question: 32467 -->
<question type="coderunner">
<name>
<text>完成巢狀函式</text>
</name>
<questiontext format="html">
<text><![CDATA[<div class="O1">
<div class="O1">
<div class="O1">
<div class="O1">
<div class="O1">請完成如圖函式，<strong>撰寫全部函式內容</strong>並補上標於註解處缺漏的程式碼，<br /><img src="@@PLUGINFILE@@/ch22_3.png" width="775" height="285" alt="nested function" /><br /> 使其可正確執行出如範例所示結果。</div>
</div>
</div>
</div>
<div class="O1"></div>
</div>]]></text>
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</file>
</questiontext>
<generalfeedback format="html">
<text></text>
</generalfeedback>
<defaultgrade>25.0000000</defaultgrade>
<penalty>0.0000000</penalty>
<hidden>0</hidden>
<coderunnertype>python3</coderunnertype>
<prototypetype>0</prototypetype>
<allornothing>0</allornothing>
<penaltyregime>0</penaltyregime>
<precheck>2</precheck>
<showsource>0</showsource>
<answerboxlines>8</answerboxlines>
<answerboxcolumns>100</answerboxcolumns>
<answerpreload></answerpreload>
<useace></useace>
<resultcolumns></resultcolumns>
<template></template>
<iscombinatortemplate></iscombinatortemplate>
<allowmultiplestdins></allowmultiplestdins>
<answer><![CDATA[def person(age):
print("I am a person")
def student(major):
print("I like learning")
def vacation(place):
print("But I need to take breaks")
print(age, "|", major, "|", place)
# write a line to return the appropriate function
return vacation
# write a line to return the appropriate function
return student]]></answer>
<validateonsave>1</validateonsave>
<testsplitterre></testsplitterre>
<language></language>
<acelang></acelang>
<sandbox></sandbox>
<grader></grader>
<cputimelimitsecs></cputimelimitsecs>
<memlimitmb></memlimitmb>
<sandboxparams></sandboxparams>
<templateparams></templateparams>
<hoisttemplateparams>0</hoisttemplateparams>
<twigall>0</twigall>
<uiplugin></uiplugin>
<testcases>
<testcase testtype="0" useasexample="1" hiderestiffail="0" mark="1.0000000" >
<testcode>
<text><![CDATA[person(12)("Math")("beach")]]></text>
</testcode>
<stdin>
<text></text>
</stdin>
<expected>
<text>I am a person
I like learning
But I need to take breaks
12 | Math | beach</text>
</expected>
<extra>
<text></text>
</extra>
<display>
<text>SHOW</text>
</display>
</testcase>
<testcase testtype="0" useasexample="1" hiderestiffail="1" mark="1.0000000" >
<testcode>
<text><![CDATA[person(18)("Communication")("Hawaii")]]></text>
</testcode>
<stdin>
<text></text>
</stdin>
<expected>
<text>I am a person
I like learning
But I need to take breaks
18 | Communication | Hawaii</text>
</expected>
<extra>
<text></text>
</extra>
<display>
<text>SHOW</text>
</display>
</testcase>
<testcase testtype="0" useasexample="0" hiderestiffail="1" mark="1.0000000" >
<testcode>
<text><![CDATA[person(29)("CS")("Japan")]]></text>
</testcode>
<stdin>
<text></text>
</stdin>
<expected>
<text>I am a person
I like learning
But I need to take breaks
29 | CS | Japan</text>
</expected>
<extra>
<text></text>
</extra>
<display>
<text>HIDE</text>
</display>
</testcase>
<testcase testtype="0" useasexample="0" hiderestiffail="1" mark="1.0000000" >
<testcode>
<text><![CDATA[person(23)("Law")("Florida")]]></text>
</testcode>
<stdin>
<text></text>
</stdin>
<expected>
<text>I am a person
I like learning
But I need to take breaks
23 | Law | Florida</text>
</expected>
<extra>
<text></text>
</extra>
<display>
<text>HIDE</text>
</display>
</testcase>
<testcase testtype="0" useasexample="0" hiderestiffail="1" mark="1.0000000" >
<testcode>
<text><![CDATA[person(120)("Life")("Paradise")]]></text>
</testcode>
<stdin>
<text></text>
</stdin>
<expected>
<text>I am a person
I like learning
But I need to take breaks
120 | Life | Paradise</text>
</expected>
<extra>
<text></text>
</extra>
<display>
<text>HIDE</text>
</display>
</testcase>
</testcases>
</question>
<!-- question: 32468 -->
<question type="coderunner">
<name>
<text>撰寫分析好友的函式</text>
</name>
<questiontext format="html">
<text><![CDATA[<div class="O1">
<div class="O1">
<div class="O1">
<div class="O1">
<div class="O1">請<strong>撰寫一個函式，名為 analyze_friends</strong>，有四個參數，</div>
<div class="O1">分別是姓名(names)tuple、電話(phones)tuple、區域號碼(all_areacodes)tuple、州名(all_places)tuple，</div>
<div class="O1">其中姓名與電話成對、區碼與州名成對，</div>
<div class="O1"></div>
<div class="O1">請從姓名tuple得出內有多少好友，並用電話前三碼與區碼比對，</div>
<div class="O1">將不重複的州名顯示出如範例所示的結果。</div>
<div class="O1">如發現有電話前三碼無法對應的州名則顯示 'BAD AREACODE'</div>
</div>
</div>
</div>
<div class="O1"></div>
</div>]]></text>
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