Python编程语言的35个与众不同之处(语言特征和使用技巧)


Posted in Python onJuly 07, 2014

一、Python介绍

从我开始学习Python时我就决定维护一个经常使用的“窍门”列表。不论何时当我看到一段让我觉得“酷,这样也行!”的代码时(在一个例子中、在StackOverflow、在开源码软件中,等等),我会尝试它直到理解它,然后把它添加到列表中。这篇文章是清理过列表的一部分。如果你是一个有经验的Python程序员,尽管你可能已经知道一些,但你仍能发现一些你不知道的。如果你是一个正在学习Python的C、C++或Java程序员,或者刚开始学习编程,那么你会像我一样发现它们中的很多非常有用。

每个窍门或语言特性只能通过实例来验证,无需过多解释。虽然我已尽力使例子清晰,但它们中的一些仍会看起来有些复杂,这取决于你的熟悉程度。所以如果看过例子后还不清楚的话,标题能够提供足够的信息让你通过Google获取详细的内容。

二、Python的语言特征

列表按难度排序,常用的语言特征和技巧放在前面。

1. 分拆

>>> a, b, c = 1, 2, 3

>>> a, b, c

(1, 2, 3)

>>> a, b, c = [1, 2, 3]

>>> a, b, c

(1, 2, 3)

>>> a, b, c = (2 * i + 1 for i in range(3))

>>> a, b, c

(1, 3, 5)

>>> a, (b, c), d = [1, (2, 3), 4]

>>> a

1

>>> b

2

>>> c

3

>>> d

4

2.交换变量分拆

>>> a, b = 1, 2

>>> a, b = b, a

>>> a, b

(2, 1)

3.拓展分拆 (Python 3下适用)

>>> a, *b, c = [1, 2, 3, 4, 5]

>>> a

1

>>> b

[2, 3, 4]

>>> c

5

4.负索引
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

>>> a[-1]

10

>>> a[-3]

8

5.列表切片 (a[start:end])
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

>>> a[2:8]

[2, 3, 4, 5, 6, 7]

6.使用负索引的列表切片
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

>>> a[-4:-2]

[7, 8]

7.带步进值的列表切片 (a[start:end:step])
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

>>> a[::2]

[0, 2, 4, 6, 8, 10]

>>> a[::3]

[0, 3, 6, 9]

>>> a[2:8:2]

[2, 4, 6]

8.负步进值得列表切片
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

>>> a[::-1]

[10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]

>>> a[::-2]

[10, 8, 6, 4, 2, 0]

9.列表切片赋值
>>> a = [1, 2, 3, 4, 5]

>>> a[2:3] = [0, 0]

>>> a

[1, 2, 0, 0, 4, 5]

>>> a[1:1] = [8, 9]

>>> a

[1, 8, 9, 2, 0, 0, 4, 5]

>>> a[1:-1] = []

>>> a

[1, 5]

10.命名切片 (slice(start, end, step))
>>> a = [0, 1, 2, 3, 4, 5]

>>> LASTTHREE = slice(-3, None)

>>> LASTTHREE

slice(-3, None, None)

>>> a[LASTTHREE]

[3, 4, 5]

11.zip打包解包列表和倍数
>>> a = [1, 2, 3]

>>> b = ['a', 'b', 'c']

>>> z = zip(a, b)

>>> z

[(1, 'a'), (2, 'b'), (3, 'c')]

>>> zip(*z)

[(1, 2, 3), ('a', 'b', 'c')]

12.使用zip合并相邻的列表项
>>> a = [1, 2, 3, 4, 5, 6]

>>> zip(*([iter(a)] * 2))

[(1, 2), (3, 4), (5, 6)]

 

>>> group_adjacent = lambda a, k: zip(*([iter(a)] * k))

>>> group_adjacent(a, 3)

[(1, 2, 3), (4, 5, 6)]

>>> group_adjacent(a, 2)

[(1, 2), (3, 4), (5, 6)]

>>> group_adjacent(a, 1)

[(1,), (2,), (3,), (4,), (5,), (6,)]

 

>>> zip(a[::2], a[1::2])

[(1, 2), (3, 4), (5, 6)]

 

>>> zip(a[::3], a[1::3], a[2::3])

[(1, 2, 3), (4, 5, 6)]

 

>>> group_adjacent = lambda a, k: zip(*(a[i::k] for i in range(k)))

>>> group_adjacent(a, 3)

[(1, 2, 3), (4, 5, 6)]

>>> group_adjacent(a, 2)

[(1, 2), (3, 4), (5, 6)]

>>> group_adjacent(a, 1)

[(1,), (2,), (3,), (4,), (5,), (6,)]

13.使用zip和iterators生成滑动窗口 (n -grams)
>>> from itertools import islice

>>> def n_grams(a, n):

...     z = (islice(a, i, None) for i in range(n))

...     return zip(*z)

...

>>> a = [1, 2, 3, 4, 5, 6]

>>> n_grams(a, 3)

[(1, 2, 3), (2, 3, 4), (3, 4, 5), (4, 5, 6)]

>>> n_grams(a, 2)

[(1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]

>>> n_grams(a, 4)

[(1, 2, 3, 4), (2, 3, 4, 5), (3, 4, 5, 6)]

14.使用zip反转字典
>>> m = {'a': 1, 'b': 2, 'c': 3, 'd': 4}

>>> m.items()

[('a', 1), ('c', 3), ('b', 2), ('d', 4)]

>>> zip(m.values(), m.keys())

[(1, 'a'), (3, 'c'), (2, 'b'), (4, 'd')]

>>> mi = dict(zip(m.values(), m.keys()))

>>> mi

{1: 'a', 2: 'b', 3: 'c', 4: 'd'}

15.摊平列表:
>>> a = [[1, 2], [3, 4], [5, 6]]

>>> list(itertools.chain.from_iterable(a))

[1, 2, 3, 4, 5, 6]

 

>>> sum(a, [])

[1, 2, 3, 4, 5, 6]

 

>>> [x for l in a for x in l]

[1, 2, 3, 4, 5, 6]

 

>>> a = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]

>>> [x for l1 in a for l2 in l1 for x in l2]

[1, 2, 3, 4, 5, 6, 7, 8]

 

>>> a = [1, 2, [3, 4], [[5, 6], [7, 8]]]

>>> flatten = lambda x: [y for l in x for y in flatten(l)] if type(x) is list else [x]

>>> flatten(a)

[1, 2, 3, 4, 5, 6, 7, 8]

 

注意: 根据Python的文档,itertools.chain.from_iterable是首选。

16.生成器表达式

>>> g = (x ** 2 for x in xrange(10))

>>> next(g)

0

>>> next(g)

1

>>> next(g)

4

>>> next(g)

9

>>> sum(x ** 3 for x in xrange(10))

2025

>>> sum(x ** 3 for x in xrange(10) if x % 3 == 1)

408

17.迭代字典
>>> m = {x: x ** 2 for x in range(5)}

>>> m

{0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

 

>>> m = {x: 'A' + str(x) for x in range(10)}

>>> m

{0: 'A0', 1: 'A1', 2: 'A2', 3: 'A3', 4: 'A4', 5: 'A5', 6: 'A6', 7: 'A7', 8: 'A8', 9: 'A9'}

18.通过迭代字典反转字典
>>> m = {'a': 1, 'b': 2, 'c': 3, 'd': 4}

>>> m

{'d': 4, 'a': 1, 'b': 2, 'c': 3}

>>> {v: k for k, v in m.items()}

{1: 'a', 2: 'b', 3: 'c', 4: 'd'}

19.命名序列 (collections.namedtuple)
>>> Point = collections.namedtuple('Point', ['x', 'y'])

>>> p = Point(x=1.0, y=2.0)

>>> p

Point(x=1.0, y=2.0)

>>> p.x

1.0

>>> p.y

2.0

20.命名列表的继承:
>>> class Point(collections.namedtuple('PointBase', ['x', 'y'])):

...     __slots__ = ()

...     def __add__(self, other):

...             return Point(x=self.x + other.x, y=self.y + other.y)

...

>>> p = Point(x=1.0, y=2.0)

>>> q = Point(x=2.0, y=3.0)

>>> p + q

Point(x=3.0, y=5.0)

21.集合及集合操作
>>> A = {1, 2, 3, 3}

>>> A

set([1, 2, 3])

>>> B = {3, 4, 5, 6, 7}

>>> B

set([3, 4, 5, 6, 7])

>>> A | B

set([1, 2, 3, 4, 5, 6, 7])

>>> A & B

set([3])

>>> A - B

set([1, 2])

>>> B - A

set([4, 5, 6, 7])

>>> A ^ B

set([1, 2, 4, 5, 6, 7])

>>> (A ^ B) == ((A - B) | (B - A))

True

22.多重集及其操作 (collections.Counter)
>>> A = collections.Counter([1, 2, 2])

>>> B = collections.Counter([2, 2, 3])

>>> A

Counter({2: 2, 1: 1})

>>> B

Counter({2: 2, 3: 1})

>>> A | B

Counter({2: 2, 1: 1, 3: 1})

>>> A & B

Counter({2: 2})

>>> A + B

Counter({2: 4, 1: 1, 3: 1})

>>> A - B

Counter({1: 1})

>>> B - A

Counter({3: 1})

23.迭代中最常见的元素 (collections.Counter)
>>> A = collections.Counter([1, 1, 2, 2, 3, 3, 3, 3, 4, 5, 6, 7])

>>> A

Counter({3: 4, 1: 2, 2: 2, 4: 1, 5: 1, 6: 1, 7: 1})

>>> A.most_common(1)

[(3, 4)]

>>> A.most_common(3)

[(3, 4), (1, 2), (2, 2)]

24.双端队列 (collections.deque)
>>> Q = collections.deque()

>>> Q.append(1)

>>> Q.appendleft(2)

>>> Q.extend([3, 4])

>>> Q.extendleft([5, 6])

>>> Q

deque([6, 5, 2, 1, 3, 4])

>>> Q.pop()

4

>>> Q.popleft()

6

>>> Q

deque([5, 2, 1, 3])

>>> Q.rotate(3)

>>> Q

deque([2, 1, 3, 5])

>>> Q.rotate(-3)

>>> Q

deque([5, 2, 1, 3])

25.有最大长度的双端队列 (collections.deque)
>>> last_three = collections.deque(maxlen=3)

>>> for i in xrange(10):

...     last_three.append(i)

...     print ', '.join(str(x) for x in last_three)

...

0

0, 1

0, 1, 2

1, 2, 3

2, 3, 4

3, 4, 5

4, 5, 6

5, 6, 7

6, 7, 8

7, 8, 9

26.字典排序 (collections.OrderedDict)
>>> m = dict((str(x), x) for x in range(10))

>>> print ', '.join(m.keys())

1, 0, 3, 2, 5, 4, 7, 6, 9, 8

>>> m = collections.OrderedDict((str(x), x) for x in range(10))

>>> print ', '.join(m.keys())

0, 1, 2, 3, 4, 5, 6, 7, 8, 9

>>> m = collections.OrderedDict((str(x), x) for x in range(10, 0, -1))

>>> print ', '.join(m.keys())

10, 9, 8, 7, 6, 5, 4, 3, 2, 1

27.缺省字典 (collections.defaultdict)
>>> m = dict()

>>> m['a']

Traceback (most recent call last):

  File "<stdin>", line 1, in <module>

KeyError: 'a'

>>>

>>> m = collections.defaultdict(int)

>>> m['a']

0

>>> m['b']

0

>>> m = collections.defaultdict(str)

>>> m['a']

''

>>> m['b'] += 'a'

>>> m['b']

'a'

>>> m = collections.defaultdict(lambda: '[default value]')

>>> m['a']

'[default value]'

>>> m['b']

'[default value]'

28. 用缺省字典表示简单的树
>>> import json

>>> tree = lambda: collections.defaultdict(tree)

>>> root = tree()

>>> root['menu']['id'] = 'file'

>>> root['menu']['value'] = 'File'

>>> root['menu']['menuitems']['new']['value'] = 'New'

>>> root['menu']['menuitems']['new']['onclick'] = 'new();'

>>> root['menu']['menuitems']['open']['value'] = 'Open'

>>> root['menu']['menuitems']['open']['onclick'] = 'open();'

>>> root['menu']['menuitems']['close']['value'] = 'Close'

>>> root['menu']['menuitems']['close']['onclick'] = 'close();'

>>> print json.dumps(root, sort_keys=True, indent=4, separators=(',', ': '))

{

    "menu": {

        "id": "file",

        "menuitems": {

            "close": {

                "onclick": "close();",

                "value": "Close"

            },

            "new": {

                "onclick": "new();",

                "value": "New"

            },

            "open": {

                "onclick": "open();",

                "value": "Open"

            }

        },

        "value": "File"

    }

}

 

(到https://gist.github.com/hrldcpr/2012250查看详情)

29.映射对象到唯一的序列数 (collections.defaultdict)

>>> import itertools, collections

>>> value_to_numeric_map = collections.defaultdict(itertools.count().next)

>>> value_to_numeric_map['a']

0

>>> value_to_numeric_map['b']

1

>>> value_to_numeric_map['c']

2

>>> value_to_numeric_map['a']

0

>>> value_to_numeric_map['b']

1

30.最大最小元素 (heapq.nlargest和heapq.nsmallest)
>>> a = [random.randint(0, 100) for __ in xrange(100)]

>>> heapq.nsmallest(5, a)

[3, 3, 5, 6, 8]

>>> heapq.nlargest(5, a)

[100, 100, 99, 98, 98]

31.笛卡尔乘积 (itertools.product)
>>> for p in itertools.product([1, 2, 3], [4, 5]):

(1, 4)

(1, 5)

(2, 4)

(2, 5)

(3, 4)

(3, 5)

>>> for p in itertools.product([0, 1], repeat=4):

...     print ''.join(str(x) for x in p)

...

0000

0001

0010

0011

0100

0101

0110

0111

1000

1001

1010

1011

1100

1101

1110

1111

32.组合的组合和置换 (itertools.combinations 和 itertools.combinations_with_replacement)
>>> for c in itertools.combinations([1, 2, 3, 4, 5], 3):

...     print ''.join(str(x) for x in c)

...

123

124

125

134

135

145

234

235

245

345

>>> for c in itertools.combinations_with_replacement([1, 2, 3], 2):

...     print ''.join(str(x) for x in c)

...

11

12

13

22

23

33

33.排序 (itertools.permutations)
>>> for p in itertools.permutations([1, 2, 3, 4]):

...     print ''.join(str(x) for x in p)

...

1234

1243

1324

1342

1423

1432

2134

2143

2314

2341

2413

2431

3124

3142

3214

3241

3412

3421

4123

4132

4213

4231

4312

4321

34.链接的迭代 (itertools.chain)
>>> a = [1, 2, 3, 4]

>>> for p in itertools.chain(itertools.combinations(a, 2), itertools.combinations(a, 3)):

...     print p

...

(1, 2)

(1, 3)

(1, 4)

(2, 3)

(2, 4)

(3, 4)

(1, 2, 3)

(1, 2, 4)

(1, 3, 4)

(2, 3, 4)

>>> for subset in itertools.chain.from_iterable(itertools.combinations(a, n) for n in range(len(a) + 1))

...     print subset

...

()

(1,)

(2,)

(3,)

(4,)

(1, 2)

(1, 3)

(1, 4)

(2, 3)

(2, 4)

(3, 4)

(1, 2, 3)

(1, 2, 4)

(1, 3, 4)

(2, 3, 4)

(1, 2, 3, 4)

35.按给定值分组行 (itertools.groupby)
>>> from operator import itemgetter

>>> import itertools

>>> with open('contactlenses.csv', 'r') as infile:

...     data = [line.strip().split(',') for line in infile]

...

>>> data = data[1:]

>>> def print_data(rows):

...     print '\n'.join('\t'.join('{: <16}'.format(s) for s in row) for row in rows)

...

 

>>> print_data(data)

young               myope                   no                      reduced                 none

young               myope                   no                      normal                  soft

young               myope                   yes                     reduced                 none

young               myope                   yes                     normal                  hard

young               hypermetrope            no                      reduced                 none

young               hypermetrope            no                      normal                  soft

young               hypermetrope            yes                     reduced                 none

young               hypermetrope            yes                     normal                  hard

pre-presbyopic      myope                   no                      reduced                 none

pre-presbyopic      myope                   no                      normal                  soft

pre-presbyopic      myope                   yes                     reduced                 none

pre-presbyopic      myope                   yes                     normal                  hard

pre-presbyopic      hypermetrope            no                      reduced                 none

pre-presbyopic      hypermetrope            no                      normal                  soft

pre-presbyopic      hypermetrope            yes                     reduced                 none

pre-presbyopic      hypermetrope            yes                     normal                  none

presbyopic          myope                   no                      reduced                 none

presbyopic          myope                   no                      normal                  none

presbyopic          myope                   yes                     reduced                 none

presbyopic          myope                   yes                     normal                  hard

presbyopic          hypermetrope            no                      reduced                 none

presbyopic          hypermetrope            no                      normal                  soft

presbyopic          hypermetrope            yes                     reduced                 none

presbyopic          hypermetrope            yes                     normal                  none

 

>>> data.sort(key=itemgetter(-1))

>>> for value, group in itertools.groupby(data, lambda r: r[-1]):

...     print '-----------'

...     print 'Group: ' + value

...     print_data(group)

...

-----------

Group: hard

young               myope                   yes                     normal                  hard

young               hypermetrope            yes                     normal                  hard

pre-presbyopic      myope                   yes                     normal                  hard

presbyopic          myope                   yes                     normal                  hard

-----------

Group: none

young               myope                   no                      reduced                 none

young               myope                   yes                     reduced                 none

young               hypermetrope            no                      reduced                 none

young               hypermetrope            yes                     reduced                 none

pre-presbyopic      myope                   no                      reduced                 none

pre-presbyopic      myope                   yes                     reduced                 none

pre-presbyopic      hypermetrope            no                      reduced                 none

pre-presbyopic      hypermetrope            yes                     reduced                 none

pre-presbyopic      hypermetrope            yes                     normal                  none

presbyopic          myope                   no                      reduced                 none

presbyopic          myope                   no                      normal                  none

presbyopic          myope                   yes                     reduced                 none

presbyopic          hypermetrope            no                      reduced                 none

presbyopic          hypermetrope            yes                     reduced                 none

presbyopic          hypermetrope            yes                     normal                  none

-----------

Group: soft

young               myope                   no                      normal                  soft

young               hypermetrope            no                      normal                  soft

pre-presbyopic      myope                   no                      normal                  soft

pre-presbyopic      hypermetrope            no                      normal                  soft

presbyopic          hypermetrope            no                      normal 
Python 相关文章推荐
Python中内置数据类型list,tuple,dict,set的区别和用法
Dec 14 Python
Python 模板引擎的注入问题分析
Jan 01 Python
python的random模块及加权随机算法的python实现方法
Jan 04 Python
python中使用print输出中文的方法
Jul 16 Python
python用BeautifulSoup库简单爬虫实例分析
Jul 30 Python
pygame游戏之旅 python和pygame安装教程
Nov 20 Python
Python采集猫眼两万条数据 对《无名之辈》影评进行分析
Dec 05 Python
python pandas cumsum求累计次数的用法
Jul 29 Python
python 实现兔子生兔子示例
Nov 21 Python
python 字符串的驻留机制及优缺点
Jun 19 Python
详解Java中一维、二维数组在内存中的结构
Feb 11 Python
Elasticsearch 基本查询和组合查询
Apr 19 Python
python基于mysql实现的简单队列以及跨进程锁实例详解
Jul 07 #Python
python中使用urllib2获取http请求状态码的代码例子
Jul 07 #Python
Python中使用urllib2防止302跳转的代码例子
Jul 07 #Python
python中使用urllib2伪造HTTP报头的2个方法
Jul 07 #Python
python实现多线程采集的2个代码例子
Jul 07 #Python
Python程序员开发中常犯的10个错误
Jul 07 #Python
python采用requests库模拟登录和抓取数据的简单示例
Jul 05 #Python
You might like
PHP数据库开发知多少
2006/10/09 PHP
PHP与MySQL开发的8个技巧小结
2010/12/17 PHP
PHP图片验证码制作实现分享(全)
2012/05/10 PHP
PHP优于Node.js的五大理由分享
2012/09/15 PHP
深入PHP与浏览器缓存的分析
2013/06/03 PHP
PHP IE中下载附件问题解决方法
2014/01/07 PHP
PHP封装的多文件上传类实例与用法详解
2017/02/07 PHP
javascript 数组排序函数
2009/08/20 Javascript
javascript中兼容主流浏览器的动态生成iframe方法
2014/05/05 Javascript
js实现表单多按钮提交action的处理方法
2015/10/24 Javascript
浅谈JS之tagNaem和nodeName
2016/09/13 Javascript
微信公众号-获取用户信息(网页授权获取)实现步骤
2016/10/21 Javascript
JavaScript生成.xls文件的代码
2016/12/22 Javascript
CentOS 安装NodeJS V8.0.0的方法
2017/06/15 NodeJs
vue监听scroll的坑的解决方法
2017/09/07 Javascript
详解React native全局变量的使用(跨组件的通信)
2017/09/07 Javascript
原生JS+HTML5实现的可调节写字板功能示例
2018/08/30 Javascript
30分钟精通React今年最劲爆的新特性——React Hooks
2019/03/11 Javascript
JS实现压缩上传图片base64长度功能
2019/12/03 Javascript
[54:53]完美世界DOTA2联赛PWL S2 GXR vs PXG 第二场 11.18
2020/11/18 DOTA
Python numpy生成矩阵、串联矩阵代码分享
2017/12/04 Python
python实现图片上添加图片
2019/11/26 Python
解决Jupyter因卸载重装导致的问题修复
2020/04/10 Python
Python在线和离线安装第三方库的方法
2020/10/31 Python
DJI大疆德国官方商城:大疆无人机
2018/09/01 全球购物
办公室文秘岗位职责
2013/11/15 职场文书
财务管理专业求职信
2014/06/11 职场文书
小学教师师德师风演讲稿
2014/08/22 职场文书
2014国庆节餐厅促销活动策划方案
2014/09/16 职场文书
2014年十一国庆节爱国演讲稿
2014/09/23 职场文书
教师自查自纠材料
2014/10/14 职场文书
晋江市委常委班子四风问题整改工作方案
2014/10/26 职场文书
放射科岗位职责
2015/02/14 职场文书
民主生活会意见
2015/06/05 职场文书
圣诞晚会主持词
2015/07/01 职场文书
服务器间如何实现文件共享
2022/05/20 Servers