python标准库之collections介绍

collections----容器数据类型

collections模块包含了除list、dict、和tuple之外的容器数据类型，如counter、defaultdict、deque、namedtuple、orderdict，下面将一一介绍。

Counter

初始化：

Counter 支持三种形式的初始化。它的构造函数可以调用序列，一个字典包含密钥和计数，或使用关键字参数映射的字符串名称。

import collections

print (collections.Counter(['a', 'b', 'c', 'a', 'b', 'b']))

print (collections.Counter({'a':2, 'b':3, 'c':1}))

print (collections.Counter(a=2, b=3, c=1))

输出结果：

Counter({'b': 3, 'a': 2, 'c': 1})

Counter({'b': 3, 'a': 2, 'c': 1})

Counter({'b': 3, 'a': 2, 'c': 1})

空的Counter容器可以无参数构造，并采用update()方法进行更新

import collections

c = collections.Counter()

print ('Initial :', c)

c.update('abcdaab')

print ('Sequence:', c)

c.update({'a':1, 'd':5})

print ('Dict    :', c)

输出结果：

Initial : Counter()

Sequence: Counter({'a': 3, 'b': 2, 'c': 1, 'd': 1})

Dict    : Counter({'d': 6, 'a': 4, 'b': 2, 'c': 1})

访问计数：

当一个Counter被构造成功，它的值可以采用字典进行访问

import collections

c = collections.Counter('abcdaab')

for letter in 'abcde':

    print ('%s : %d' % (letter, c[letter]))

结果：

a : 3

b : 2

c : 1

d : 1

e : 0

elements()方法可以返回一个包含所有Counter数据的迭代器

import collections

c = collections.Counter('extremely')

c['z'] = 0

print(c)

print (list(c.elements()))

Counter({'e': 3, 'm': 1, 'l': 1, 'r': 1, 't': 1, 'y': 1, 'x': 1, 'z': 0})

['e', 'e', 'e', 'm', 'l', 'r', 't', 'y', 'x']

most_common()返回前n个最多的数据

import collections

c=collections.Counter('aassdddffff')

for letter, count in c.most_common(2):

    print ('%s: %d' % (letter, count))

f: 4

d: 3

算法：

Counter实例支持聚合结果的算术和集合操作。

import collections

c1 = collections.Counter(['a', 'b', 'c', 'a', 'b', 'b'])

c2 = collections.Counter('alphabet')

print ('C1:', c1)

print ('C2:', c2)

print ('\nCombined counts:')

print (c1 + c2)

print ('\nSubtraction:')

print (c1 - c2)

print ('\nIntersection (taking positive minimums):')

print (c1 & c2)

print ('\nUnion (taking maximums):')

print (c1 | c2)

C1: Counter({'b': 3, 'a': 2, 'c': 1})

C2: Counter({'a': 2, 'l': 1, 'p': 1, 'h': 1, 'b': 1, 'e': 1, 't': 1})

Combined counts:

Counter({'a': 4, 'b': 4, 'c': 1, 'l': 1, 'p': 1, 'h': 1, 'e': 1, 't': 1})

Subtraction:

Counter({'b': 2, 'c': 1})

Intersection (taking positive minimums):

Counter({'a': 2, 'b': 1})

Union (taking maximums):

Counter({'b': 3, 'a': 2, 'c': 1, 'l': 1, 'p': 1, 'h': 1, 'e': 1, 't': 1})

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defaultdict

标准字典包括setdefault方法()获取一个值，如果值不存在，建立一个默认。相比之下,defaultdict允许调用者在初始化时预先设置默认值。

import collections

def default_factory():

    return 'default value'

d = collections.defaultdict(default_factory, foo='bar')

print ('d:', d)

print ('foo =>', d['foo'])

print ('x =>', d['x'])

d: defaultdict(<function default_factory at 0x000002567E713E18>, {'foo': 'bar'})

foo => bar

x => default value

---

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Deque

双端队列，支持从两端添加和删除元素。更常用的栈和队列是退化形式的双端队列，仅限于一端在输入和输出。

import collections

d = collections.deque('abcdefg')

print ('Deque:', d)

print ('Length:', len(d))

print ('Left end:', d[0])

print ('Right end:', d[-1])

d.remove('c')

print ('remove(c):', d)

Deque: deque(['a', 'b', 'c', 'd', 'e', 'f', 'g'])

Length: 7

Left end: a

Right end: g

remove(c): deque(['a', 'b', 'd', 'e', 'f', 'g'])

双端队列从左右两端插入数据

import collections

# 右端插入

d = collections.deque()

d.extend('abcdefg')

print ('extend    :', d)

d.append('h')

print ('append    :', d)

# 左端插入

d = collections.deque()

d.extendleft('abcdefg')

print ('extendleft:', d)

d.appendleft('h')

print ('appendleft:', d)

extend    : deque(['a', 'b', 'c', 'd', 'e', 'f', 'g'])

append    : deque(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])

extendleft: deque(['g', 'f', 'e', 'd', 'c', 'b', 'a'])

appendleft: deque(['h', 'g', 'f', 'e', 'd', 'c', 'b', 'a'])

类似地，双端队列的元素可以从两端获取。

import collections

print ('From the right:')

d = collections.deque('abcdefg')

while True:

    try:

        print (d.pop())

    except IndexError:

        break

print ('\nFrom the left:')

d = collections.deque('abcdefg')

while True:

    try:

        print (d.popleft())

    except IndexError:

        break

From the right:

g

f

e

d

c

b

a

From the left:

a

b

c

d

e

f

g

由于双端队列是线程安全的，在单独的线程中内容甚至可以从两端同时消费。

import collections

import threading

import time

candle = collections.deque(xrange(11))

def burn(direction, nextSource):

    while True:

        try:

            next = nextSource()

        except IndexError:

            break

        else:

            print ('%8s: %s' % (direction, next))

            time.sleep(0.1)

    print ('%8s done' % direction)

    return

left = threading.Thread(target=burn, args=('Left', candle.popleft))

right = threading.Thread(target=burn, args=('Right', candle.pop))

left.start()

right.start()

left.join()

right.join()

    Left: 0

   Right: 10

   Right: 9

     Left: 1

   Right: 8

    Left: 2

   Right: 7

    Left: 3

   Right: 6

    Left: 4

   Right: 5

    Left done

   Right done

队列的另一个有用的功能是在任意方向旋转，通俗来讲就是队列的左移右移

import collections

d = collections.deque(xrange(10))

print ('Normal        :', d)

d = collections.deque(xrange(10))

d.rotate(2)

print ('Right rotation:', d)

d = collections.deque(xrange(10))

d.rotate(-2)

print ('Left rotation :', d)

Normal        : deque([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

Right rotation: deque([8, 9, 0, 1, 2, 3, 4, 5, 6, 7])

Left rotation : deque([2, 3, 4, 5, 6, 7, 8, 9, 0, 1])

---

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namedtuple

标准的元组使用数值索引来访问其成员

bob = ('Bob', 30, 'male')

print ('Representation:', bob)

jane = ('Jane', 29, 'female')

print ('\nField by index:', jane[0])

print ('\nFields by index:')

for p in [ bob, jane ]:

    print ('%s is a %d year old %s' % p)

Representation: ('Bob', 30, 'male')

Field by index: Jane

Fields by index:

Bob is a 30 year old male

Jane is a 29 year old femal

记住每个索引对应的值是很容易出错的，尤其是在元组有多个元素的情况下。namedtuple为每个成员分配了名字。

import collections

Person = collections.namedtuple('Person', 'name age gender')

print ('Type of Person:', type(Person))

bob = Person(name='Bob', age=30, gender='male')

print ('\nRepresentation:', bob)

jane = Person(name='Jane', age=29, gender='female')

print ('\nField by name:', jane.name)

print ('\nFields by index:')

for p in [ bob, jane ]:

    print ('%s is a %d year old %s' % p)

Type of Person: <type 'type'>

Representation: Person(name='Bob', age=30, gender='male')

Field by name: Jane

Fields by index:

Bob is a 30 year old male

Jane is a 29 year old female

字段名称解析，无效值会导致ValueError

import collections

try:

    collections.namedtuple('Person', 'name class age gender')

except ValueError, err:

    print (err)

try:

    collections.namedtuple('Person', 'name age gender age')

except ValueError, err:

    print (err)

Type names and field names cannot be a keyword: 'class'

Encountered duplicate field name: 'age'

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OrderedDict

OrderedDict是字典子类，记得其内容被添加的顺序

import collections

print ('Regular dictionary:')

d = {}

d['a'] = 'A'

d['b'] = 'B'

d['c'] = 'C'

d['d'] = 'D'

d['e'] = 'E'

for k, v in d.items():

    print( k, v)

print ('\nOrderedDict:')

d = collections.OrderedDict()

d['a'] = 'A'

d['b'] = 'B'

d['c'] = 'C'

d['d'] = 'D'

d['e'] = 'E'

for k, v in d.items():

    print (k, v)

Regular dictionary:

a A

c C

b B

e E

d D

OrderedDict:

a A

b B

c C

d D

e E

参考来源：https://pymotw.com/2/collections/index.html#module-collections