python3练习题：1-10

#practice1：在字典、列表、集合中按条件筛选数据

列表解析

#如何在列表、字典、集合中按条件筛选数据 from random import randint from timeit import timeit #因为for提取的变量在randint函数中未使用，所以用_,而非一个变量名 a = [randint(-10,10) for _ in range(10)] print(a) #方法1 b = filter(lambda x: x > 0,a) print(list(b)) #方法2 c = [x for x in a if x > 0] print(c) #测试速度 print(timeit("[x for x in a if x > 0]","from __main__ import a",number=10)) print(timeit("filter(lambda x: x > 0,a)","from __main__ import a",number=10))

一般情况下，列表解析快一点。。。

字典解析

from random import randint d = {x:randint(-10,10) for x in range(10)} print(d) #字典解析 result = {v:k for k,v in d.items() if v > 0} print(result) #不适合用filter

字典解析

from random import randinta = {randint(-20,20) for _ in range(10)}print(a) result = {x for x in a if x > 0} print(result)

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#practice2:为元组中每个元素命名

• 法一：用伪常亮+序列拆包
• 法二：用namedtuple函数

student = ('jim',18,'shanxi','china')#方法一：伪常亮 #增添了全局变量，不推荐 NAME,AGE,PROVINCE,COUNTRY = range(4) print(student[NAME]) print(student[AGE])#方法二：使用namedtuple from collections import namedtuple#参数1：namedtuple函数返回一个Tuple子类，第一个参数是子类名称；参数2：index名称列表 Student = namedtuple('Student',['name','age','province','country']) #Student元组类实例化,s是一个带名称的元组 s = Student('jim',18,'shanxi','china') print(s.name)

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#practice3:统计序列中元素出现频率

案例1

• 方法一：dict.fromkeys函数+字典排序

from random import randintl = [randint(0,10) for _ in range(20)] print(l)#方法一：使用dict.fromkeys构建字典，用value来计数 #fromkeys方法构建的字典会自动去重 mydict = dict.fromkeys(l,0) print(mydict) #计算频率 for x in l:mydict[x] += 1 print(mydict) #把字典转化为类列表，然后用sorted+key关键字按序排列 print((mydict.items())) newdict = sorted(mydict.items(),key=lambda x:x[1]) print(newdict) #取出频率最高的三个 newdict = newdict[-3:] print(newdict)

• 方法二：使用collections.Counter类

from random import randint from collections import Counterl = [randint(0,10) for _ in range(20)] print(l)countdict = Counter(l) #countdict是一个类字典对象，因为Counter继承了内置Dict类，所以countdict拥有所有字典的方法！ #countdict还有新方法most_common print(countdict) #返回3个频率最高的单元，默认由高到低 print(countdict.most_common(3))

案例2

查找一段文本中出现最高的十个短语

import subprocess from collections import Counter out_bytes = subprocess.check_output(['netstat','-a']) out_text = out_bytes.decode('utf-8') print(type(out_text)) print(out_text)out_text = out_text.split() wordcounter = Counter(out_text) print(wordcounter.most_common(10))

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#practice4:把字典按value排序

• 方法1：zip + sorted

from random import randintd = {str(k):randint(0,10) for k in range(10)} #d.items返回值：类集合对象 print(d.items())#方法一：用zip将key与value列表组合成新的元组列表 #对元组列表执行sorted方法 result = zip(d.values(),d.keys()) #zip后里面的基本单元是tuple,这是永远不变的 #外边可以转换为list/set/tuple来包裹 new_result = sorted(result) print(new_result)

注意：以下几个函数或类的参数与返回值（学会使用help()

zip输入参数：iterable;返回值：zip对象（也是iterable)

sorted函数参数：iterable;返回值：list!!!

平常使用的list(a),并非是在调用函数，而是进行list内置类的实例化；输入：iterable；输出：lsit。

• 方法二：借助sorted的key参数

from random import randintd = {str(k):randint(0,10) for k in range(10)} #dict.items()返回一个dict_items对象，是个类集合对象，而且是个iterable for x in d.items():#从结果可知，基本元素是个元组！print(x) #用key参数制定排序对象 result = sorted(d.items(),key=lambda x:x[1]) print(result)

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#practice5:找寻多个字典的公共key

• 方法一：循环

• 方法二：用dict.keys方法

• 两种实现方法

from random import randintgame1 = {x:randint(1,3) for x in "abcdef"} print(game1) game2 = {x:randint(1,3) for x in "abckew"} print(game2) game3 = {x:randint(1,3) for x in "mnef"} print(game3)#法1：for循环 res = [] for k in game1:if k in game2 and k in game3:res.append(k)print(res)#法2：利用dict.keys方法，返回值是个类集合对象 result = game1.keys() & game2.keys() & game3.keys() print(result)

pythonic

from random import randint from functools import reduce game1 = {x:randint(1,3) for x in "abcdef"} print(game1) game2 = {x:randint(1,3) for x in "abckew"} print(game2) game3 = {x:randint(1,3) for x in "mnef"} print(game3)#注意：func不能直接为keys!! #map函数返回值为iterator a = map(dict.keys,[game1,game2,game3]) result = reduce(lambda x,y: x & y,a) print(result)

#practice6:可迭代对象与迭代器对象

概念区分

各种可迭代实现方案的总依循：python的迭代协议

Python 的迭代协议需要 _iter_() 方法返回一个实现了 _next_() 方法的迭代器对象。

可迭代对象的具体实现

3.1 方案一：迭代器方案

3.1.1 实现迭代器

import requests import pprint #测试代码 # r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=%E5%8C%97%E4%BA%AC') # pprint.pprint(r.json())#实现一个迭代器 from collections import Iterator#构造迭代器 class WeatherIterator(Iterator):def __init__(self,cities):self.cities = citiesself.index = 0def getweather(self,city):r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=' + city)dict_data = r.json()['data']['forecast'][0]return "%s:%s,%s" % (city,dict_data['low'],dict_data['high'])def __next__(self):if self.index == len(self.cities):raise StopIterationcity = self.cities[self.index]self.index += 1return self.getweather(city)#生成迭代器对象 weatheriterator = WeatherIterator([u'北京',u'南京',u'上海']) #迭代器对象调用next()方法 print(weatheriterator.__next__()) print(weatheriterator.__next__()) print(weatheriterator.__next__()) #没有定义__iter__方法，不是可迭代对象，所以暂时无法for in

3.1.2 实现可迭代类

ather(self,city):r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=' + city)dict_data = r.json()['data']['forecast'][0]return "%s:%s,%s" % (city,dict_data['low'],dict_data['high'])def __next__(self):if self.index == len(self.cities):raise StopIterationcity = self.cities[self.index]self.index += 1return self.getweather(city)class WeatherIterable(Iterable):def __init__(self,cities):self.cities = citiesdef __iter__(self):#返回迭代器对象return WeatherIterator(self.cities)#生成可迭代对象 weatheriterable = WeatherIterable([u'北京',u'南京',u'上海'])#for in 遍历机制的伪过程 #第一步：weatheriterable = weatheriterable.__iter__(),weatheriterable变成了迭代器对象WeatherIterator(self.cities) #第二步：遍历一次，就调用一次weatheritearble.next(),即WeatherIterator(self.cities).__next__(),最终返回值为天气信息字符串，赋值给x for x in weatheriterable:print(x)

这是最标准的python迭代协议；需要建两个类，比较繁琐

3.2 方案二、合并两个类，最终使用一个类，来实现可迭代类（对方案一的简化）

from collections import Iterator,Iterable import requestsclass WeatherIterable(Iterable):def __init__(self,cities):self.cities = citiesself.index = 0def __iter__(self):#返回迭代器对象return selfdef getweather(self,city):r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=' + city)dict_data = r.json()['data']['forecast'][0]return "%s:%s,%s" % (city,dict_data['low'],dict_data['high'])def __next__(self):if self.index == len(self.cities):raise StopIterationcity = self.cities[self.index]self.index += 1return self.getweather(city)weatheriterable = WeatherIterable([u'北京',u'南京',u'上海'])#伪过程 #第一步：weatheriterable = weatheriterable.__iter__(),返回weatheriterable对象本身 #对象本身就有__next__方法，是的迭代器对象；这样就满足了python迭代协议 #第二步：遍历一次，就调用一次weatheritearble.__next__(),最终返回值为天气信息字符串，赋值给x for x in weatheriterable:print(x)

上述weatheriterable即是可迭代对象，又是迭代器对象

3.3 方案三：iter与next进一步合并，将iter方法定义为生成器（推荐）

from collections import Iterator,Iterable import requestsclass WeatherIterable(Iterable):def __init__(self,cities):self.cities = citiesself.index = 0def __iter__(self):for x in range(len(self.cities)):city = self.cities[self.index]self.index += 1yield self.getweather(city) def getweather(self,city):r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=' + city)dict_data = r.json()['data']['forecast'][0]return "%s:%s,%s" % (city,dict_data['low'],dict_data['high'])weatheriterable = WeatherIterable([u'北京',u'南京',u'上海']) #伪过程 #第一步：weatheriterable = weatheriterable.__iter__(),调用生成器，返回__iter__生成器的生成器对象 #生成器对象默认拥有__iter__与__next__方法 #所以返回生成器对象也可以视作返回迭代器对象，符合python迭代协议 #第二步：遍历一次，就调用一次【迭代器对象】.__next__(),最终返回值为天气信息字符串，赋值给x #yield的背后可能就是调用__next__,哈哈 for x in weatheriterable:print(x)

反向迭代

与正向迭代流程完全相同，只不过要在可迭代类中定义内置方法reversed。

from collections import Iterator,Iterable import requestsclass WeatherIterable(Iterable):def __init__(self,cities):self.cities = citiesself.index = 0def __iter__(self):for x in range(len(self.cities)):city = self.cities[self.index]self.index += 1yield self.getweather(city) def __reversed__(self):#在这个函数内设计代码，实现反向逻辑即可for x in range(len(self.cities)):self.index -= 1city = self.cities[self.index]yield self.getweather(city) def getweather(self,city):r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=' + city)dict_data = r.json()['data']['forecast'][0]return "%s:%s,%s" % (city,dict_data['low'],dict_data['high'])weatheriterable = WeatherIterable([u'北京',u'南京',u'上海'])for x in weatheriterable:print(x) print("*"*20) for x in reversed(weatheriterable):print(x)

可迭代对象切片

from collections import Iterator,Iterable import requests from itertools import isliceclass WeatherIterable(Iterable):def __init__(self,cities):self.cities = citiesself.index = 0def __iter__(self):for x in range(len(self.cities)):city = self.cities[self.index]self.index += 1yield self.getweather(city) def __reversed__(self):#在这个函数内设计代码，实现反向逻辑即可for x in range(len(self.cities)):self.index -= 1city = self.cities[self.index]yield self.getweather(city) def getweather(self,city):r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=' + city)dict_data = r.json()['data']['forecast'][0]return "%s:%s,%s" % (city,dict_data['low'],dict_data['high'])weatheriterable = WeatherIterable([u'北京',u'南京',u'上海',u'广州']) #weatheriteterable是可迭代对象，但不是迭代器对象 #网上有的将islice操作称为迭代器切片；但个人认为可迭代对象切片更准确 print(dir(weatheriterable)) for x in islice(weatheriterable,0,2):print(x)

islice(a,3)表示0：3；islice(a,3，None)表示3：结束；不可以用负数index进行切片！

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#practice7:字符串拆分

方法一：自己设计函数(使用字符串处理函数split)

def mysplit(s,split_keys):#a为初始列表,字符串转列表的方法如下a = [s]for split_key in split_keys:#t为分割后的暂时列表t = []#list操作是必须的，否则t.extend无法生效#Python中即使某个操作有返回值，也可以不赋值list(map(lambda x: t.extend(x.split(split_key)),a))##将分割后的列表赋值给初始列表，进入下一轮循环a = treturn as = 'ab;cd|efg|hi,jkl|mn\topq;rst,uvw\txyz' result = mysplit(s,';,|\t') print(result)

方法二：re.split函数

import res = 'ab;cd|efg|hi,jkl|mn\topq;rst,uvw\txyz' result = re.split(r'[;|,\t]+',s) print(result)

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#practice8:判断字符串开头/结尾是某个字符串

• 简单示例，使用字符串方法startwith与endwith

import osfiles = os.listdir('/home/openlab') print(files) for x in files:if x.endswith('.py'):print('*'*20 + x)#注意：不是elseif#startswith与endswith使用多个参数时，只能用元组将参数括起来，参数间关系为或！elif x.startswith(('.s','.x')):print('#'*20 + x)

• 文件、命令相关操作补充

import subprocess,os#调用check_output，执行命令并返回结果 out_bytes = subprocess.check_output(['ls','-l']) out_text = out_bytes.decode('utf-8') print(out_text) #调用system函数，执行命令并将状态码返回 return_code = os.system('touch 1.txt') print(return_code)import stat #返回stat对象 result = os.stat('p2.py') #返回十进制的文件mode(包括权限等一系列信息) print(result.st_mode) #转换为八进制便于观察 print(oct(result.st_mode))

• 实际实例

import os,stat import subprocessdef show_status(path='.'):output_bytes = subprocess.check_output(['ls','-l',path])output_text = output_bytes.decode('utf-8')print(output_text)show_status() #找当前文件夹下的Python文件，并为文件的拥有者以及相同用户组的成员添加可执行权限 files = os.listdir('.') for file in files:if file.endswith('py'):#采用或的方式添加权限os.chmod(file,os.stat(file).st_mode | stat.S_IXGRP | stat.S_IXUSR)show_status()

关于stat模块：
https://www.cnblogs.com/maseng/p/3386140.html

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#practice9:文本字符串替换（正则表达式分组的使用）

import rewith open('/var/log/dpkg.log') as f:text = f.read() #注意：re.sub并不会对text做出改变，而是返回新的字符串！ new_text = re.sub(r'(\d{4})-(\d{2})-(\d{2})',r'(\1)(\2)(\3)',text) ''' 也可以换一种写法（使用分组名称）: new_text = re.sub(r'(?P<year>\d{4})-(?P<month>\d{2})-(?P<day>\d{2})',r'(\g<year>)(\g<month>)(\g<day>)',text) ''' print(text) print(new_text)

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#practice10:字符串拼接（join方法）与字符串对齐

字符串拼接

l = ['1','2','ss','q'] #相比于加号拼接，下列方法不仅简洁，而且占用内存小！ result = ''.join(l) print(result) result = 'AA'.join(l) print(result) #join参数是iterable即可，所以用生成器表达式生产一个generator对象（是iterable)也合理 result = ''.join((str(x) for x in range(10))) print(result)

字符串对齐

• 方法一： 调用字符串方法

• 方法二： format函数

a = 'wakaka' a1 = a.ljust(20) a2 = a.rjust(20) a3 = a.center(20) print(a1) print(len(a1)) print(a2) print(a3)a1 = format(a,'<20') a2 = format(a,'>20') a3 = format(a,'^20') print(a1) print(len(a1)) print(a2) print(a3)

• 实际应用

from random import randint dict1 = {str(x):randint(10,20) for x in ['wakaka','dd','ffs']} #取最长值的方法 test = map(len,dict1.keys()) #map对象可以直接max！ max_len = max(test) for k in dict1:print(k.ljust(max_len) + ":" + str(dict1[k]))

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