[ZZ] python 语言技巧
http://sahandsaba.com/thirty-python-language-features-and-tricks-you-may-not-know.html 感谢原作者
30 Python Language Features and Tricks You May Not Know About
Posted on Mar 05, 2014 , last modified on Mar 16, 2014
By Sahand Saba1.1 Unpacking
>>> 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
1.2 Unpacking for swapping variables
>>> a, b = 1, 2
>>> a, b = b, a
>>> a, b
(2, 1)
1.3 Extended unpacking (Python 3 only)
>>> a, *b, c = [1, 2, 3, 4, 5]
>>> a
1
>>> b
[2, 3, 4]
>>> c
5
1.4 Negative indexing
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> a[-1]
10
>>> a[-3]
8
1.5 List slices (a[start:end])
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> a[2:8]
[2, 3, 4, 5, 6, 7]
1.6 List slices with negative indexing
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> a[-4:-2]
[7, 8]
1.7 List slices with step (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]
1.8 List slices with negative step
>>> 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]
1.9 List slice assignment
>>> 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]
1.10 Naming slices (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]
1.11 Zipping and unzipping lists and iterables
>>> 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')]
1.12 Grouping adjacent list items using zip
>>> 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,)]
1.13 Inverting a dictionary using zip
>>> 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'}
1.14 Flattening lists:
>>> 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]
Note: according to Python's documentation on sum, itertools.chain.from_iterable is the preferred method for this.
1.15 Generator expressions
>>> 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
1.16 Dictionary comprehensions
>>> 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'}
1.17 Inverting a dictionary using a dictionary comprehension
>>> 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'}
1.18 Named tuples (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
1.19 Inheriting from named tuples:
>>> 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)
1.20 Sets and set operations
>>> 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
1.21 Multisets and multiset operations (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})
1.22 Most common elements in an iterable (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)]
1.23 Double-ended queue (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])
1.24 Double-ended queue with maximum length (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
1.25 Ordered dictionaries (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
1.26 Default dictionaries (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]'
1.27 Using default dictionaries to represent simple trees
>>> 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"
}
}
(See https://gist.github.com/hrldcpr/2012250 for more on this.)
1.28 Mapping objects to unique counting numbers (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
1.29 Largest and smallest elements (heapq.nlargest and 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]
1.30 Cartesian products (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
1.31 Combinations and combinations with replacement (itertools.combinations anditertools.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
1.32 Permutations (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
1.33 Chaining iterables (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)
1.34 Grouping rows by a given key (itertools.groupby)
>>> 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=lambda r: r[-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 soft
[ZZ] python 语言技巧的更多相关文章
- python语言技巧
一 在写之前 最好指定python的路径: #!/usr/bin/python python 在linux中需要添加编码方式:以免出现中文乱码 # -*- coding: UTF-8 –*- 二 ...
- Python语言防坑小技巧
Python语言防坑小技巧 作者:尹正杰 版权声明:原创作品,谢绝转载!否则将追究法律责任. 一.赋值即定义 1>.运行以下代码会出现报错 #!/usr/bin/env python #_*_ ...
- 如何系统地自学一门Python 语言（转）
转自:http://www.phpxs.com/post/4521 零基础情况下,学一门语言充实下自己,Python,简洁.优美.容易使用,是一个很好的选择.那么如何系统地自学Python呢? 有的人 ...
- Python语言and-or的用法
[原]python语言的 and-or 常常被用来实现类C语言中的三元运算符 : ? , 更为骚气的写法是 xxx and xxx or xxx and xxx or xxx,这样就可以可以做到 ...
- python代码优化技巧
转自:http://www.douban.com/group/topic/31478102/ 这个资料库还有些不错的好文章: http://www.ibm.com/developerworks/cn/ ...
- Python语言学习之Python入门到进阶
人们常说Python语言简单,编写简单程序时好像也确实如此.但实际上Python绝不简单,它也是一种很复杂的语言,其功能特征非常丰富,能支持多种编程风格,在几乎所有方面都能深度定制.要想用好Pytho ...
- python的技巧和方法你了解多少？
学了这些你的python代码将会改善与你的技巧将会提高. 1. 路径操作 比起os模块的path方法,python3标准库的pathlib模块的Path处理起路径更加的容易. 获取当前文件路径 前提导 ...
- 一些你需要知道的Python代码技巧
被人工智能捧红的 Python 已是一种发展完善且非常多样化的语言,其中肯定有一些你尚未发现的功能.本文或许能够让你学到一些新技巧. Python 是世界上最流行.热门的编程语言之一,原因很多,比 ...
- 掌握这些Python代码技巧，编程至少快一半！
被人工智能捧红的 Python 已是一种发展完善且非常多样化的语言,其中肯定有一些你尚未发现的功能.本文或许能够让你学到一些新技巧. Python 是世界上最流行.热门的编程语言之一,原因很多,比 ...
随机推荐
- 【读书札记】建立第一个Web项目
安装配置好jdk.tomcat,我用的版本号是7.0.54,我放在C:\server\apache-tomcat-7.0.54下, CATALINA_BASE:C:\server\apache-tom ...
- Oracle GoldenGate (以下简称ogg)在异种移植os同一种db之间的数据同步。
Oracle GoldenGate (以下简称ogg)在异种移植os同一种db之间的数据同步. ogg要实现的功能: 同步可以细化到单个表,满足特定的where条件rows同步,称号column同步. ...
- 【原创】用Python爬取LeetCode的AC代码到Github
在leetCode写了105道题高调膜科,考虑搬迁到自己的GitHub上,做成一个解题题库,面试的时候也可以秀一个 但是!但是! leetCode在线IDE的功能不要太舒服,我直接线上A了不少题,本地 ...
- effective c++ 条款8 prevent exception from leaving destructor
1 析构函数绝对不要吐出异常.如果一个析构函数可能调用产生异常的函数,析构函数应该不传播该异常或结束程序 2 如果客户需要对某个操作函数运行期间抛出的异常做出反应,那么class应该提供一个普通函数执 ...
- POJ - 3249 Test for Job （DAG+topsort）
Description Mr.Dog was fired by his company. In order to support his family, he must find a new job ...
- JCombobox组合框效果实现(转)
JCombobox是Swing中比较常用的控件,它显示一个项列表,扩展的是ListModel接口的模型,它的显示绘制器通过实现ListCellBenderer接口来绘制列表单元,下面介绍 ①普通应用例 ...
- UVa 572 Oil Deposits(DFS)
Oil Deposits The GeoSurvComp geologic survey company is responsible for detecting underground oil ...
- Android lint具 常见问题检查
1. Correctness 1) DuplicatedIds Layout于id应该唯一 2) NewApi 代码中使用的某些API高于Manifest中的Min SDK 3) Inconsiste ...
- NServiceBus开发
使用NServiceBus开发分布式应用 系列主题:基于消息的软件架构模型演变 NServiceBus 是一个.Net平台下开源的消息服务框架,这类产品有时也被称作ESB(Enterprise Ser ...
- YT新人之巅峰大决战03
题目链接 Problem Description Now give you two integers n m, you just tell me the m-th number after radix ...