Python3编程技巧

In [1]: from random import randint

In [2]: data=[randint(-10,10) for _ in range(10)]

In [3]: data
Out[3]: [-3, -4, 3, 4, 7, -2, -4, 1, 7, -9]

#过滤列表中的负数
In [9]: list(filter(lambda x:x>=0,data))
Out[9]: [3, 4, 7, 1, 7]

[for x in data if x>=0]
#  列表生成式解法
[x for x in data if x>=0]

#哪个更快,列表解析更快,远快于迭代
In [15]: %timeit [x for x in data if x>=0]
581 ns ± 23.8 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [16]: %timeit filter(lambda x:x>=0,data)
237 ns ± 4 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

#得到20个同学的成绩
d={x:randint(60,100)for x in range(1,21)}
#字典解析式,iteritems同时迭代字典，
#
#得到分数大于90的同学
{k:v for k,v in d.items() if v>90}


#集合解析
In [35]: {x for x in s if x %3 ==0}
Out[35]: {-9, -3, 3}

#为元祖中的每个元素命名，提高程序可读性
#元祖存储空间小，访问速度快
#定义常量
NAME = 0
AGE=1
SEX=2
EMAIL=3
#拆包用法，定义类似其他语言的枚举类型，也就是定义数值常量
NAME,AGE,SEX,EMAIL=range(4)

#案例
student=('Jim',16,'male','jin@163.com')
#name
print(student[0])
#age
print(student[1])
#通过常量可以优化为
print(student[NAME])
print(student[AGE])

#namedtuple是继承自tuple的子类，namedtuple和tuple比较有更酷的特性
#namedtuple创建一个和tuple类似的对象，而且对象拥有可以访问的属性。这对象更像带有数据属性的类，不过数据属性是只读的。
from collections import namedtuple
Student = namedtuple('Student',['name','age','sex','email'])
s=Student('Jim',16,'male','jim@163.com')
s.name 
s.age

#统计序列中元素出现的频度
from random import randint
data=[randint(0,20) for _ in range(30)]
#创建字典{0:0,1:0,...}
#方法1
c=dict.fromkeys(data,0)
In [52]: for x in data:
    ...:     c[x]+=1

#方法2，统计词频
from collections import Counter
c2=Counter(data)#讲序列传入Counter的构造器，得到Counter对象是元素频度的字典
#使用most_common统计词频
In [58]: c2.most_common(3)
Out[58]: [(10, 4), (20, 3), (8, 3)]
#统计英文作文词频
import re
txt=open('emmmm.txt').read()
#分割后赋给Counter
c3=Counter(re.split('\W',txt))
#找到频率最高的10个单词
c3.most_common(10)

#内置函数是以c的速度运行，如sorted
from random import randint 
d={x:randint(60,100) for x in 'xyzabc'}
#{'a': 91, 'b': 65, 'c': 76, 'x': 85, 'y': 84, 'z': 72}
# sorted(d)
In [15]: zip(d.values(),d.keys())
Out[15]: <zip at 0x108b34dc8>

In [16]: list(zip(d.values(),d.keys()))
Out[16]: [(68, 'x'), (70, 'y'), (77, 'z'), (72, 'a'), (65, 'b'), (69, 'c')]

#快速找到多个字典中的公共键
#In [1]: from random import randint,sample

In [2]: sample('abcdefg',3)
Out[2]: ['c', 'a', 'b']


In [4]: sample('abcdefg',randint(3,6))
Out[4]: ['b', 'a', 'd']

In [5]: s1={x:randint(1,4)for x in sample('abcdefg',randint(3,6))}

In [9]: s1
Out[9]: {'a': 1, 'b': 2, 'c': 3, 'f': 3, 'g': 3}

In [10]: s1={x:randint(1,4)for x in sample('abcdefg',randint(3,6))}

In [11]: s1
Out[11]: {'b': 2, 'd': 3, 'g': 3}

In [12]: s1
Out[12]: {'b': 2, 'd': 3, 'g': 3}

In [13]: s2={x:randint(1,4)for x in sample('abcdefg',randint(3,6))}

In [15]: s3={x:randint(1,4)for x in sample('abcdefg',randint(3,6))}
#for循环遍历方法，找到s2,s3都有的k
In [19]: res=[]

In [20]: for k in s1:
    ...:     if k in s2 and k in s3:
    ...:         res.append(k
    ...:         )
    ...:         
    ...:         

In [21]: res
Out[21]: ['b']
#通过字典的keys()方法，找到三个字典同样的key
In [26]: s1.keys()&s2.keys()&s3.keys()
Out[26]: {'b'}
#通过map得到一个迭代器对象
#In [27]: map(dict.keys,[s1,s2,s3])
Out[27]: <map at 0x108891b70>

In [28]: list(map(dict.keys,[s1,s2,s3]))
Out[28]: 
[dict_keys(['g', 'd', 'b']),
 dict_keys(['g', 'a', 'c', 'b', 'f']),
 dict_keys(['d', 'f', 'b', 'c', 'e', 'a'])]
#通过reduce取出同样结果
In [30]: from functools import reduce

In [31]: reduce(lambda a,b:a&b,map(dict.keys,[s1,s2,s3]))
Out[31]: {'b'}

#使得
from time import time
from random import randint
from collections import OrderedDict

d=OrderedDict()
players = list("ABCDEFGH")
start=time()
for i in range(8):
    input()
    p=players.pop(randint(0,8-i))
    end=time()
    print(i+1,p,end-start)
    d[p]=(i+1,end-start)
print('')
print('-'*20)
for k in d:
    print(k,d[k])
#查看用户历史记录功能,标准库collections的deque，双端循环队列，存在内容中，pickle存储到文件
from random import randint
from collections import deque
N = randint(0,100)
history = deque([],5)
def guess(K):
   if K ==N:
      print('正确')
      return True
   if K < N:
      print('%s is less-than N'%K)
   else:
       print("%s is greater-than N"%K)
   return False
while True:
   line = input("请输入一个数字：")
   if line.isdigit():
      k=int(line)
      history.append(k)
      if guess(k):
         break
   elif line =='history' or line =='h?':
       print(list(history))

可迭代对象和迭代器对象

需求：从网络抓取每个城市的气温消息，显示
北京：15-20
黑龙江：3-10
上海13-19
一次抓取所有城市信息，会占很大的存储空间，现在想“用时访问”，吧所有城市气温封装到一个对象里，用for迭代

可迭代对象：

In [1]: l=[1,2,3,4,5]

In [2]: s='abcde'

iter内置函数，可以得到一个迭代器对象
由可迭代对象，得到迭代器

iter(l)

In [23]: type(l)
Out[23]: list

In [24]: type(iter(l))
Out[24]: list_iterator

可迭代对象都有__iter方法，可迭代接口
或者__getitem__序列接口

可迭代对象可以通过next()取值

In [26]: t=iter(l)

In [27]: next(t)
Out[27]: 1

In [28]: next(t)
Out[28]: 2

In [29]: next(t)
Out[29]: 3

In [30]: next(t)
Out[30]: 4

In [31]: next(t)
Out[31]: 5

In [32]: next(t)
---------------------------------------------------------------------------
StopIteration                             Traceback (most recent call last)
<ipython-input-32-f843efe259be> in <module>()
----> 1 next(t)

StopIteration: 

import xlrd
#打开excel文件，创建一个workbook对象,book对象也就是s11.xlsx文件,表含有sheet名
rbook=xlrd.open_workbook('/Users/yuchao/s11.xlsx')
#sheets方法返回对象列表,[<xlrd.sheet.Sheet object at 0x103f147f0>]
rbook.sheets()
rsheet=rbook.sheet_by_index(0)
#访问行数
rows=rsheet.nrows
#访问列数
cols=rsheet.ncols
print('行数：',rows,'列数',cols)
#通过cell的位置坐标取得cell值
cell=rsheet.cell(0,0)
print('0,0坐标的值是：',cell.value)
#取得第二行的值,参数是（行数，起点，终点）
row1=rsheet.row_values(1)
print('第一行的值是：',row1)

# -*- coding:utf-8 -*-
# Author : yuchao
# Data : 2018/7/18 16:08


import xlrd, xlwt

rbook = xlrd.open_workbook('/Users/yuchao/s11.xlsx')
rsheet = rbook.sheet_by_index(0)  # 取得sheet对象1
# 列数
nc = rsheet.ncols
# 写入一条数据
rsheet.put_cell(0, nc, xlrd.XL_CELL_TEXT, '总分', None)

# 遍历数据的行数
for row in range(1, rsheet.nrows):
    # 求和每一行数据
    t = sum(rsheet.row_values(row, 1))
    rsheet.put_cell(row, nc, xlrd.XL_CELL_NUMBER, t, None)
#创建文档对象
wbook = xlwt.Workbook()
wsheet = wbook.add_sheet(rsheet.name)
#设置样式
style = xlwt.easyxf('align: vertical center, horizontal center')
#遍历每一行
for r in range(rsheet.nrows):
    #每一列
    for c in range(rsheet.ncols):
        wsheet.write(r,c,rsheet.cell_value(r,c),style)
wbook.save('/Users/yuchao/s11_bak.xlsx')

import xlrd
from xlrd.book import Book
from xlrd.sheet import Sheet
from xlrd.sheet import Cell

workbook = xlrd.open_workbook('/Users/yuchao/s11.xlsx')

sheet_names = workbook.sheet_names()

# sheet = workbook.sheet_by_name('工作表1')
sheet = workbook.sheet_by_index(1)

# 循环Excel文件的所有行
for row in sheet.get_rows():
    # 循环一行的所有列
    for col in row:
        # 获取一个单元格中的值
        print(col.value)