#practice1：在字典、列表、集合中按條件篩選數據

列表解析

#如何在列表、字典、集合中按條件篩選數據 from random import randint from timeit import timeit #因為for提取的變量在randint函數中未使用，所以用_,而非一個變量名 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) #測試速度 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))

一般情況下，列表解析快一點。。。

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) #不適合用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:為元組中每個元素命名

• 法一：用偽常亮+序列拆包
• 法二：用namedtuple函數

student = ('jim',18,'shanxi','china')#方法一：偽常亮 #增添了全局變量，不推薦 NAME,AGE,PROVINCE,COUNTRY = range(4) print(student[NAME]) print(student[AGE])#方法二：使用namedtuple from collections import namedtuple#參數1：namedtuple函數返回一個Tuple子類，第一個參數是子類名稱；參數2：index名稱列表 Student = namedtuple('Student',['name','age','province','country']) #Student元組類實例化,s是一個帶名稱的元組 s = Student('jim',18,'shanxi','china') print(s.name)

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#practice3:統計序列中元素出現頻率

案例1

• 方法一：dict.fromkeys函數+字典排序

from random import randintl = [randint(0,10) for _ in range(20)] print(l)#方法一：使用dict.fromkeys構建字典，用value來計數 #fromkeys方法構建的字典會自動去重 mydict = dict.fromkeys(l,0) print(mydict) #計算頻率 for x in l:mydict[x] += 1 print(mydict) #把字典轉化為類列表，然后用sorted+key關鍵字按序排列 print((mydict.items())) newdict = sorted(mydict.items(),key=lambda x:x[1]) print(newdict) #取出頻率最高的三個 newdict = newdict[-3:] print(newdict)

• 方法二：使用collections.Counter類

from random import randint from collections import Counterl = [randint(0,10) for _ in range(20)] print(l)countdict = Counter(l) #countdict是一個類字典對象，因為Counter繼承了內置Dict類，所以countdict擁有所有字典的方法！ #countdict還有新方法most_common print(countdict) #返回3個頻率最高的單元，默認由高到低 print(countdict.most_common(3))

案例2

查找一段文本中出現最高的十個短語

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：類集合對象 print(d.items())#方法一：用zip將key與value列表組合成新的元組列表 #對元組列表執行sorted方法 result = zip(d.values(),d.keys()) #zip后里面的基本單元是tuple,這是永遠不變的 #外邊可以轉換為list/set/tuple來包裹 new_result = sorted(result) print(new_result)

注意：以下幾個函數或類的參數與返回值（學會使用help()

zip輸入參數：iterable;返回值：zip對象（也是iterable)

sorted函數參數：iterable;返回值：list!!!

平常使用的list(a),并非是在調用函數，而是進行list內置類的實例化；輸入：iterable；輸出：lsit。

• 方法二：借助sorted的key參數

from random import randintd = {str(k):randint(0,10) for k in range(10)} #dict.items()返回一個dict_items對象，是個類集合對象，而且是個iterable for x in d.items():#從結果可知，基本元素是個元組！print(x) #用key參數制定排序對象 result = sorted(d.items(),key=lambda x:x[1]) print(result)

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#practice5:找尋多個字典的公共key

• 方法一：循環

• 方法二：用dict.keys方法

• 兩種實現方法

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循環 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，返回值是個類集合對象 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不能直接為keys!! #map函數返回值為iterator a = map(dict.keys,[game1,game2,game3]) result = reduce(lambda x,y: x & y,a) print(result)

#practice6:可迭代對象與迭代器對象

概念區分

各種可迭代實現方案的總依循：python的迭代協議

Python 的迭代協議需要 _iter_() 方法返回一個實現了 _next_() 方法的迭代器對象。

可迭代對象的具體實現

3.1 方案一：迭代器方案

3.1.1 實現迭代器

import requests import pprint #測試代碼 # r = requests.get('http://wthrcdn.etouch.cn/weather_mini?city=%E5%8C%97%E4%BA%AC') # pprint.pprint(r.json())#實現一個迭代器 from collections import Iterator#構造迭代器 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)#生成迭代器對象 weatheriterator = WeatherIterator([u'北京',u'南京',u'上海']) #迭代器對象調用next()方法 print(weatheriterator.__next__()) print(weatheriterator.__next__()) print(weatheriterator.__next__()) #沒有定義__iter__方法，不是可迭代對象，所以暫時無法for in

3.1.2 實現可迭代類

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):#返回迭代器對象return WeatherIterator(self.cities)#生成可迭代對象 weatheriterable = WeatherIterable([u'北京',u'南京',u'上海'])#for in 遍歷機制的偽過程 #第一步：weatheriterable = weatheriterable.__iter__(),weatheriterable變成了迭代器對象WeatherIterator(self.cities) #第二步：遍歷一次，就調用一次weatheritearble.next(),即WeatherIterator(self.cities).__next__(),最終返回值為天氣信息字符串，賦值給x for x in weatheriterable:print(x)

這是最標準的python迭代協議；需要建兩個類，比較繁瑣

3.2 方案二、合并兩個類，最終使用一個類，來實現可迭代類（對方案一的簡化）

from collections import Iterator,Iterable import requestsclass WeatherIterable(Iterable):def __init__(self,cities):self.cities = citiesself.index = 0def __iter__(self):#返回迭代器對象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'])#偽過程 #第一步：weatheriterable = weatheriterable.__iter__(),返回weatheriterable對象本身 #對象本身就有__next__方法，是的迭代器對象；這樣就滿足了python迭代協議 #第二步：遍歷一次，就調用一次weatheritearble.__next__(),最終返回值為天氣信息字符串，賦值給x for x in weatheriterable:print(x)

上述weatheriterable即是可迭代對象，又是迭代器對象

3.3 方案三：iter與next進一步合并，將iter方法定義為生成器（推薦）

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']) #偽過程 #第一步：weatheriterable = weatheriterable.__iter__(),調用生成器，返回__iter__生成器的生成器對象 #生成器對象默認擁有__iter__與__next__方法 #所以返回生成器對象也可以視作返回迭代器對象，符合python迭代協議 #第二步：遍歷一次，就調用一次【迭代器對象】.__next__(),最終返回值為天氣信息字符串，賦值給x #yield的背后可能就是調用__next__,哈哈 for x in weatheriterable:print(x)

反向迭代

與正向迭代流程完全相同，只不過要在可迭代類中定義內置方法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):#在這個函數內設計代碼，實現反向邏輯即可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)

可迭代對象切片

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):#在這個函數內設計代碼，實現反向邏輯即可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'廣州']) #weatheriteterable是可迭代對象，但不是迭代器對象 #網上有的將islice操作稱為迭代器切片；但個人認為可迭代對象切片更準確 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：結束；不可以用負數index進行切片！

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#practice7:字符串拆分

方法一：自己設計函數(使用字符串處理函數split)

def mysplit(s,split_keys):#a為初始列表,字符串轉列表的方法如下a = [s]for split_key in split_keys:#t為分割后的暫時列表t = []#list操作是必須的，否則t.extend無法生效#Python中即使某個操作有返回值，也可以不賦值list(map(lambda x: t.extend(x.split(split_key)),a))##將分割后的列表賦值給初始列表，進入下一輪循環a = treturn as = 'ab;cd|efg|hi,jkl|mn\topq;rst,uvw\txyz' result = mysplit(s,';,|\t') print(result)

方法二：re.split函數

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:判斷字符串開頭/結尾是某個字符串

• 簡單示例，使用字符串方法startwith與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與endswith使用多個參數時，只能用元組將參數括起來，參數間關系為或！elif x.startswith(('.s','.x')):print('#'*20 + x)

• 文件、命令相關操作補充

import subprocess,os#調用check_output，執行命令并返回結果 out_bytes = subprocess.check_output(['ls','-l']) out_text = out_bytes.decode('utf-8') print(out_text) #調用system函數，執行命令并將狀態碼返回 return_code = os.system('touch 1.txt') print(return_code)import stat #返回stat對象 result = os.stat('p2.py') #返回十進制的文件mode(包括權限等一系列信息) print(result.st_mode) #轉換為八進制便于觀察 print(oct(result.st_mode))

• 實際實例

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() #找當前文件夾下的Python文件，并為文件的擁有者以及相同用戶組的成員添加可執行權限 files = os.listdir('.') for file in files:if file.endswith('py'):#采用或的方式添加權限os.chmod(file,os.stat(file).st_mode | stat.S_IXGRP | stat.S_IXUSR)show_status()

關于stat模塊：
https://www.cnblogs.com/maseng/p/3386140.html

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#practice9:文本字符串替換（正則表達式分組的使用）

import rewith open('/var/log/dpkg.log') as f:text = f.read() #注意：re.sub并不會對text做出改變，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) ''' 也可以換一種寫法（使用分組名稱）: 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）與字符串對齊

字符串拼接

l = ['1','2','ss','q'] #相比于加號拼接，下列方法不僅簡潔，而且占用內存小！ result = ''.join(l) print(result) result = 'AA'.join(l) print(result) #join參數是iterable即可，所以用生成器表達式生產一個generator對象（是iterable)也合理 result = ''.join((str(x) for x in range(10))) print(result)

字符串對齊

• 方法一： 調用字符串方法

• 方法二： format函數

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)

• 實際應用

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

總結

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