分享Python的十个小技巧

一. 列表、字典、集合、元组的使用

创新互联建站专注为客户提供全方位的互联网综合服务，包含不限于网站设计、做网站、宝山网络推广、小程序定制开发、宝山网络营销、宝山企业策划、宝山品牌公关、搜索引擎seo、人物专访、企业宣传片、企业代运营等，从售前售中售后，我们都将竭诚为您服务，您的肯定，是我们最大的嘉奖；创新互联建站为所有大学生创业者提供宝山建站搭建服务，24小时服务热线：028-86922220，官方网址：www.cdcxhl.com

from random import randint, sample

# 列表解析

data = [randint(-10, 10) for _ in xrange(10)]

filter(lambda x: x >= 0, data)

[x for x in data if x >= 0] #最快速

# 字典解析

d = {x: randint(60, 100) for x in xrange(1,21)}

{k : v for k, v in d.iteritems() if v > 90}

# 集合解析

s = set(data)

{x for x in s if x % 3 ==0}

# 元组

student = ('Jim', 16, 'male', 'jim@qq.com')

# 1. enum

NAME, AGE, SEX, EMAIL = xrange(4)

print student[NAME]

# 2.

from collections import namedtuple

Student = namedtuuple('Student', ['name', 'age', 'sex', 'email'])

s2 = Student('Tom', 16, 'mail', 'tom@qq.com')

print s2.name

# 统计列表的重复元素

li = [randint(0, 20) for _ in xrange(30)]

d = dict.fromkeys(li, 0)

# 1.

for x in li: d[x] += 1

# 2.

from collections import Counter

d2 = Counter(li)

d2.most_common(3) #重复数最高的三个元素

# 字典根据值value排序

sorted([3, 1, 5]) #排序列表

(97, 'a') > (88, 'b') # 元组的比较，每个元素从开始比较

d = {x: randint(60, 100) for x in 'abcde'}

# 1.

data = zip(d.itervalues(), d.iterkeys())

sorted(data)

# 2.

sorted(d.items(), key=lambda x: x[1])

# 多个字典中的公共键

sample('abcdefg', 3)

sample('abcdefg', randint(3,6)) # 随机取出几个元素

s1 = {x: randint(1,4) for x in sample('abcdefg', randint(3.6))}

s2 = {x: randint(1,4) for x in sample('abcdefg', randint(3.6))}

s3 = {x: randint(1,4) for x in sample('abcdefg', randint(3.6))}

# 1.

res = []

for k in s1: if k in s2 and k in s3: res.append(k) # res.pop(k)

# 2. 使用集合

res = s1.viewkeys() & s2.viewkeys() & s3.viewkeys()

# 3.

m1 = map(dict.viewkeys, [s1, s2, s3])

res = reduce(lambda a, b: a & b, m1)

# 保持字典有序

d = {'Jim':(1, 35), 'Leo':(2, 38), 'Tom':(3, 44)}

from collections import OrderedDict

d = OrderedDict() #按进入字典的顺序打印

d['Jim'] = (1,35)

d['Leo'] = (2,38)

d['Tom'] = (3,44)

from time import time

start = time()

raw_input() #等待输入

# ...

timesecond = time() - start

# 历史记录

# 1. 用队列存储

from collections import deque

q = deque([], 5)

q.append(1) # 达到长度后，先进先出

li = list(q) # 转换成列表类型

# 2. 将q存到文件中

import pickle

pickle.dump(q, open('test','w'))

q2 = pickle.load(open('test','r'))

二. 迭代器、生成器

# 实现可迭代对象、迭代器对象

# 用时访问 并封装到一个对象中

# 可迭代对象

li = [1,2,3,4]

str= 'abcde'

# 迭代器

iterl = iter(li) # li.__iter__()

iters = iter(str) # str.__getitem__()

iterl.next()

# 1. 城市天气的迭代器和可迭代对象

from collections import Iterable, Iterator

class WIterator(Iterator):

def __init__(self, cities):

self.cities = cities

self.index = 0

def getWeather(city):

import requests

r = requests.get(u'http://wthrcdn.etouch.cn/weather_mini?city=' + city)

data = r.json()['data']['forecast'][0]

return '%s: %s, %s' % (city, data['low'], data['high'])

def next(self):

if self.index == len(self.cities)

raise StopIteration

city = self.cities[self.index]

self.index += 1

return self.getWeather(city)

class WIterable(Iterable):

def __init__(self, cities):

self.cities = cities

def __iter__(self):

return WIterator(self.cities)

for x in WIterable([u'北京', u'长沙', u'广州'])：

print x

# 2. 使用生成器函数实现可迭代对象

def f():

print 'in f(), 1'

yield 1

print 'in f(), 2'

yield 2

g = f() # g.__iter__()

for i in g: print i

class PrintNumbers:

def __init__(self, start, end):

self.start = start

self.end = end

def isPrimeNum(self, k):

if k % 2 == 0:

return True

else:

return False

def __iter__(self):

for k in xrange(self.start, self.end+1):

if self.isPrimeNum(k):

yield k

for x in PrintNumbers(1, 100): print x

# 进行反向迭代

li = [1,2,3,4,5]

li.reverse() # 改变原来列表

li[::-1] # 切片，和原来列表等大的新列表

ll = li.reversed(li) # 列表反向迭代

for i in ll: print i

class FloatRange:

def __init__(self, start, end, step=0.1)

self.start = start

self.end = end

self.step = step

def __iter__(self):

t = self.start

while t <= self.end:

yield t

t += self.step

def __reversed__(self):

t = self.enf

while t >= self.start:

yield t

t -= self.step

# 正向迭代

for i in FloatRange(1.0, 4.0, 0.5): print x

# 反向迭代

for i in reversed(FloatRange(1.0, 4.0, 0.5)): print x

# 对迭代器做切片操作

from itertools import islice

# islice()

li = range(20)

t = iter(li)

for x in islice(t, 5, 10): print x # 会消耗原来的迭代对象

# 在一个for中迭代多个可迭代对象

chinese = [randint(60,100) for _ in xrange(40)]

math = [randint(60,100) for _ in xrange(40)]

english = [randint(60,100) for _ in xrange(40)]

for in in xrange(len(math)):

print chinese[i] + math[i] + english[i]

total = []

# 并行多个可迭代对象

for c, m, e in zip(chiness, math, english)

print c+m+e

# 1. 串连多个迭代对象

from itertools import chain

c1 = [randint(60,100) for _ in xrange(40)]

c2 = [randint(60,100) for _ in xrange(42)]

c3 = [randint(60,100) for _ in xrange(45)]

for s in chain(c1, c2, c3):

if s > 90: print s

三. 字符串

# 拆分含多种分隔符的字符串

s = "fwerf sd123 ^sdf dfdsf*d dsf 123"

s.split(“xy”) #默认以空格分割，或以参数分割

res = s.split(";")

map(lambda x: x.split("|"), res) # 以";"和"|"分割的二维数组

t = []

map(lambda x: t.extend(x.split("|")), res) # 二维元素放到t中

# 1.

def aSplit(s, ds):

res = [s]

for d in ds:

t = []

map(lambda x: t.extend(x.split(d)), res)

res = t

return res

print aSplit(s, " ^*") # 会存在空的元素

# 2. 正则表达式

import re

re.split(r'[,;|]+', s)

# 判断字符串a是否以b开头或结尾

#s.startswith() s.endswith() 接收单个字符串或字符串元组

import os, stat

files = [name for name in os.listdir(".") if name.endswith(('.sh', '.py'))]

# 调整字符串中文本的格式

#日志中'yyyy-mm-dd' 改为 'mm/dd/yyyy'

import re

log = open("/var/log/dpkg.log").read()

re.sub('(\d{4})-(\d{2})-(\d{2})', r'\2/\3/\1', log)

re.sub('(?P\d{4})-(?P\d{2})-(?P\d{2})', r'\g/\g/\g', log)

# 多个小字符串拼接成大字符串

s1 = "abcde"

s2 = "12345"

s1 + s2 # str.__add__(s1, s2) str.__gt__(s1, s2) 运算符重载

s = ""

for p in pl: s += p # 变量多时，临时变量开销大，资源浪费

s.join(s1) # 参数可为字符串，可为列表

li = ['avc', 123, 'xyz', 456]

''.join([str(x) for x in li]) #列表解析，会生成一个列表，开销大

''.join(str(x) for x in li) #生成器, (str(x) for x in li) 作为参数是括号省略

# 字符串格式对齐

# str.ljust() str.rjust() str.center()

s = "abc"

s.ljust(10 ,'=') # 左对齐，填充=

s.center(10)

format(s, '<20') # 左对齐

format(s, '>20') # 右对齐

format(s, '^20') # 居中

# 去掉字符串中不需要的字符

s = ' -------sd dfadf 2332 +++++++++'

s.strip(' -+')

s.lstrip()

s.rstirp()

# 删除固定位置的字符,拼接切片

s[:3]+ s[4:]

# 替换

s.replace('\t', '')

import re

re.sub('[\t\r]', '', s)

s = 'abc123e3rxyz'

#s.translate()

import string

tr = string.maketrans('abcxyz', 'xyzabc')

s.translate(tr)

s = 'abc\rdfd\n234234\t'

s.translate(None, '\r\t\n')

四. 文件读写

# python2 str unicode

# python3 bytes str

# python2

s = u'你好'

s.encode('utf8') #存储到文件中的格式

f = open('hello.txt', 'w')

f.write(s.encode('utf8'))

f.close()

f = open('hello.txt', 'r')

t = f.read().decode('utf8') # 你好

f.close()

# python3 字符串就是unicode

strb = b'asdfasdfsdg'

s = '你好'

f = open('hello2.txt', 'wt', encoding='utf8') # 自动完成编解码

f.write(s)

f.close()

f = open('hello2.txt', 'rt', encoding='utf8')

s = f.read()

f.close()

# 处理二进制文件 处理音频文件，将音量调小保存

f = open('demo.wav', 'rb')

info = f.read(44) #文件头

import struct

struct.unpack('h',info[22:24]) #处理文件头 数据运算

struct.unpack('i',infi[24:28])

f.seek(0,2)

f.tell()

n = (f.tell()-44) /2

import array

buf = array.array('h', (0 for _ in xrange(n)))

f.seek(44)

f.readinto(buf)

for i in xrange(n): buf[i] /= 8

f2 = open('demo2.wav', 'wb')

f2.write(info)

buf.tofile(f2)

f2.close()

# 使用临时文件

# 自动删除，不占内存

from tempfile import TemporaryFile, NamedTemporaryFile

f = TemporaryFile() # 系统文件系统找不到

f.write('abcddee'*100000)

f.seek(0)

f.read(100)

ntf = NamedTemporaryFile(delete=False) # 能找到文件，默认关闭以后会删除文件

fname = nft.name

# 设置文件的缓冲

# I/O 操作以块为单位，如4096字节一个块

f = open('test.txt', 'w'， buffering=2048) # 全缓冲，要写满缓冲才会写到文件中

f = open('test.txt', 'w'， buffering=1) # 行缓冲，\n就会写文件

f = open('test.txt', 'w'， buffering=1) # 无缓冲，实时写

f.write('abc')

# 将文件映射到内存

import mmap

f = open('demo.bn','r+b')

f.fileno()

m = mmap.mmap(f.fileno(), 0, access=mmpa.ACCESS_WRITE, offset=mmap.PAGESIZE)

# 得到字节数组

m[4:8] = '\xff'*4 # 修改直接改变文件内容

# 读写csv数据

from urllib import urlretrieve

urlretrieve('http://table.finance.yahoo.com/table.csv?s=000001.sz', 'pingan.csv')

rf = open('pingan.csv', 'rb')

import csv

reader = csv.reader(rf)

header = reader.next()

wf = open('pingan_c.csv', 'wb')

writer = csv.writeer(wf)

writer.writerow(header)

rf.close()

wf.close()

# 读写json数据

import requests

import json

from record import Record

record = Record(channel=1)

audioData = record.record(2)

from secret import API_KEY, SECRET_KEY

authUrl = "https://openapi.baidu.com/oauth/2.0/token?grant_type=client_credentials&client_id=" + API_KEY + "&client_secret=" + SECRET_KEY

response = requests.get(authUrl)

res = json.loads(response.content)

token = res['access_token']

#百度语音识别

cuid = 'xxxxxxxxxxxxx'

srvUrl = 'http://vop.baidu.com/server_api?cuid=' + cuid + '&token=' + token

heepHeader = {'Content-Type': 'audio/wav; rate = 8000'}

response = requests.post(srvUrl, headers=httpHeader, data=audioData)

res = json.loads(response.content)

text = res['result'][0]

print text

# json.dumps() python对象(列表、字典等)转换成json字符串

# json.dumps(data, sort_keys=True)

# json.loads() json字符串转换成python对象

with open('demo.json', 'wb') as f:

json.dump(l, f) # 将l数据写到文件

# 构建xml文档

from xml.etree.ElementTree import parse

with open('demo.xml') with f:

et = parse(f)

root = et.getroot()

root.tag

root.attrib

root.text

#root.getchildren()

for child in root:

print child.get('name')

root.find('country')

root.findall('country') # 直接子元素

for e in root.iterfind('country'):

print e.get('name')

from xml.etree.ElementTree import Element, ElementTree, tostring

e = Element('Data')

e.set('name', 'abc')

e2 = Element('Row')

e3 = Element('Open')

e3.text = '8.80'

e2.append(e3)

e.append(e2)

tostring(e)

et = ElementTree(e)

et.write('demo.xml')

# 读写excel文件

import xlrd, xlwt

book = xlrd.open_workbook('demo.xls')

book.sheets()

sheet = book.sheet_by_index(0)

rows = sheet.nrows

cols = sheet.ncols

cell = sheet.cell(0,0) #(0,0)单元格

cell.ctype

cell.value

row = sheet.row(1) #cell对象列表

data = sheet.row_values(1, 1) #第1列跳过第一格的值列表

sheet.put_cell(0, cols, xlrd.XL_CELL_TEXT, u'Total', None)

wbook = xlwt.Workbook()

wsheet = wbook.add_sheet('sheet1')

style = xlwt.easyxf('align: vertical center, horizontal center')

wsheet.write(rows,cols, sheet.cell_value(rows,cols), style)

wsheet.save('output.xls')

五. 派生内置不可变类型并修改其实例化行为

class IntTuple(tuple):

def __new__(cls, iterable): #先于__init__()调用

g = (x for x in iterable if isinstance(x, int) and x > 0)

super(IntTuple, cls).__new__(cls, g)

def __init__(self, iterable):

# 此时如果过滤iterable 无法过滤成功

super(IntTuple, self).__init__(iterable)

t = IntTuple([1, -1, 'abc', 6, ['x', 'y'], 3])

print t 无锡妇科医院排名 http://www.csyhjlyy.com/

六. 使用描述符对实例属性做类型检查

# 描述符： 包含 __get__() __set__() __delete__() 函数的类

class Attr(object):

def __init__(self, name, type_):

self.name = name

self.type_= type_

def __get__(self, instance, cls):

return instanse.__dict__[self.name]

def __set__(self, instance, value):

if not isinstance(value, self.type_):

raise TypeError('expected %s' % self.type_)

instance.__dict__[self.name] = value

def __delete__(self, instance):

del instance.__dict__[self.name]

class Person(object):

name = Attr('name', str)

age = Attr('age', int)

hgt = Attr('height', float)

p = Person()

p.name = 'Bob'

print p.name

p.age = '17' #会抛出异常

七. 在环状数据结构中管理内存

import sys

class A(object):

def __del__(self): # 当引用次数变为0时，调用析构函数

print 'in A.__del__'

a = A()

a2 = a

print sys.getrefcount(a) - 1 # 查看对象a的引用次数，参数名也引用了对象，要-1

del a

del a2

# 循环引用

class Data(object): # Data类保存Node对象引用

def __init__(self, value, owner):

self.owner = owner

self.value = value

def __str__(self):

return "%s's data, value is %s" % (self.owner, self.value)

def __del__(self):

print 'in Data.__del__'

class Node(object): # Node类调用Data对象

def __init__(self, valu):

self.data = Data(value, self)

def __del__(self):

print 'in Node.__del__'

node = Node(100)

del node # 此时Data Node不会被回收掉

raw_input('wait...')

# 使用弱引用

import weakref

a_wref = weakref.ref(a)

a2 = a_wref()

class Data(object): # Data类保存Node对象引用

def __init__(self, value, owner):

self.owner = weakref.ref(owner) # 弱引用

self.value = value

def __str__(self):

return "%s's data, value is %s" % (self.owner(), self.value)

def __del__(self):

print 'in Data.__del__'

node2 = node(100)

del node2 # 此时Data Node将被回收

八. 通过实例方法名的字符串调用方法

# Circle Triangle Trctangle 求面积的方法名都不同

# 通过传方法名来调用不同的方法

# 1. getattr 获取对象属性，方法名也是属性

from lib1 import Circle

from lib2 import Triangle

from lib3 import Tectangle

def getArea(shape):

for name in ('area', 'getArea', get_area):

f = getattr(shape, name , None)

if f:

return f()

shape1 = Circle(2)

shape2 = Tirangle(3,4,5)

shape3 = Rectangle(6,4)

shapes = [shape1, shape2, shape3]

print map(getArea, shapes)

# 2. 使用opreator标准库

from opreator import methodcaller

s = "abc123abc456"

s.find('abc', 4)

methodcaller('find', 'abc', 4)(s)

九. 为创建大量实例节省内存

class Player(object):

def __init__(self, uid, name, status=0, level=1):

self.uid = uid

self.name = name

self.stat = status

self.level = level

class Player2(object):

__slots__ = ['uid', 'name', 'stat', 'level']

def __init__(self, uid, name, status=0, level=1):

self.uid = uid

self.name = name

self.stat = status

self.level = level

p1 = Player('0001', 'Jim')

p2 = Player2('0002', 'Tom')

# p1 bi p2 多两个属性 __dict__ __weakref__

# __dict__ 字典，为实例动态绑定解除新属性

# p2 则不能动态绑定属性

# __slots__ 阻止了该功能

十. 让对象支持上下文管理

# 要使用上下文管理，类中要定义 __enter__ __exit__方法，分别在with开始和结束时调用

class test(object):

...

def __enter__(self):

pass

def __exit__(self, exc_type, exc_val, exc_tb):

pass

with test() as k:

pass

分享标题：分享Python的十个小技巧
地址分享：http://6mz.cn/article/gihsod.html