Smooth the collections module python

collections module provides data structures other than the common data structures python, into several

namedtuple () : Special tuple subclass can use to access the names and subscript
the deque : deque, from the other side can be quickly and additional objects Release
Counter : a counter for counting the main
OrderedDict : ordered dictionary
defaultdict : Dictionary with default values
ChainMap: dictionary-like containers, a plurality of maps which set to a view

namedtuple name suggests, is a tuple with the name, there is a dictionary-like access methods, accessed through the following yourtuple.key

#!/usr/bin/python3
# -*- coding: utf-8 -*-
from collections import namedtuple

persons = [
    ('男', '1988-04-11', '张三'),
    ('女', '1993-03-26', '李四'),
    ('男', '1990-06-02', '王五')
]
Person = namedtuple('person', ['sex', 'birthday', 'name'])
# Person = namedtuple('person', ('sex', 'birthday', 'name'))
# Person = namedtuple('person', 'sex, birthday, name')
# Person = namedtuple('person', 'sex birthday name')

if __name__ == '__main__':
    for person in persons:
        person = Person._make (Person) 
        # person = Person (person [0
        # can be created _make (tuple type) or calls the new method
        Print (Person)
        print(person.name, person[0])

output:

person (sex = 'M', birthday = '1988-04-11', name = ' Joe Smith') 
Zhang M 
person (sex = 'F', birthday = '1993-03-26', name = ' John Doe ') 
John Doe female 
person (sex =' male ', birthday =' 1990-06-02 ', name =' king of five ') 
Wang five men

Note: namedtuple (parm1, parm2)

parm1 names of the constructor, parm2 may be a list, tuples, or string

Parm2 number of elements and the number of parameters that need to pass the same parameters, such as: Person ( 'M', '1988-04-11', 'John Doe', '1383333333') will be given Expected 3 arguments, got 4

and

collections.dequeReturns a new deque object gain access to the ends of the queues, thread safety support, for adding (the append) from both ends or popped (POP), complexity of O (1).
Although listthe object supports a similar operation, the complex group O (n) the greater the consumption increases as the length of the list
if the default maxlen None, it can grow to any length. Otherwise, deque would be limited to a specified maximum length. Once defined deque full length, when a new entry is added, the same number of items on the pop-up from the other end.
Supported methods:

append (x): x is added to the right
appendleft (x): x is added to the left
clear (): clear all the elements, the length becomes 0
copy (): Creates a shallow copy
count (x): calculated number is equal to the queue element x
extend (iterable): additive element in the queue right iterable
extendleft (iterable): additive element in the queue iterable left Note: when adding the left will turn the order to add the parameter iterable
index (x [, start [, stop]]): Returns the x-th element (from start to start, before the stop). Returns the first match, if not found, raising ValueError.
insert (i, x): i is inserted at a position x. Note: If you insert will lead to a long deque beyond the length limit maxlen, then it rises a IndexError.
pop (): remove elements of the far right
popleft (): remove the leftmost element
remove (value): Remove the first one found value. Does not throw ValueError
reverse (): The deque in reverse order. Return None.
maxlen: the maximum queue length, was not limited None.

    from collections import deque
    d = deque(maxlen=10)
    print(d)
    d.extend('hello world')
    [i.upper() for i in d]
    ['P', 'Y', 'T', 'H', 'O', 'N']
    d.append('e')
    d.appendleft('f')
    print(d)
output:
deque([], maxlen=10)
deque(['f', 'l', 'l', 'o', ' ', 'w', 'o', 'r', 'l', 'd'], maxlen=10)

Counter

Counter is a dict subclass primarily used to access your target frequency counts.
Common methods:

elements (): returns an iterator, the number of repeated calculations for each element, an element if the count is less than 1, will be ignored.
most_common ([n]): returns a list of the n most frequently accessed to provide an element and counting ChainMap
subtract ([iterable-or-mapping]): iterative subtracting elements from the object, the input and output may be 0 or negative
update ([iterable-or-mapping]): iteration count objects or add elements from another map from the object (or counter).

    import collections
    print(collections.Counter('hello world'))
    # 统计单词数
    print(collections.Counter('hello world hello world hello nihao'.split()))
output:
Counter({'l': 3, 'o': 2, 'r': 1, 'w': 1, 'h': 1, 'd': 1, 'e': 1, ' ': 1})
Counter({'hello': 3, 'world': 2, 'nihao': 1})

OrderedDict

Python dictionary ordering of the keys of the disorder, the sequential control is not added.
collections.OrderedDictAdd reserved dictionary object they order.

    from collections import OrderedDict
    demo_dict = {"a": 1, "b": 2, "c": 3}
    order_dict = OrderedDict(demo_dict)
    print (demo_dict, order_dict)
    demo_dict['s'] = 5
    print (demo_dict)
    order_dict['s'] = 5
    print(order_dict)
output:
{'b': 2, 'a': 1, 'c': 3} OrderedDict([('b', 2), ('a', 1), ('c', 3)])
{'s': 5, 'b': 2, 'a': 1, 'c': 3}
OrderedDict([('b', 2), ('a', 1), ('c', 3), ('s', 5)])

defaultdict

defaultdict(factory)Provide a default value is not the key dictionary. Argument should be a function that returns a default value when no call parameters. If you do not pass anything, it defaults to None

from collections import defaultdict
demo_dict = {}
try:
    print(demo_dict['s']) # KeyError
except:
    pass
default_dict = defaultdict(str)
default_dict['s']
print(demo_dict)
print(default_dict)

output:
{}
defaultdict(<class 'str'>, {'s': ''})

ChainMap

ChainMap sum equivalent to more than a dictionary.

from collections import ChainMap
d1 = {"a": 1, "b": 2, "aa": 1}
d2 = {"aa": 11, "bb": 22, "b": 3}
sd = ChainMap(d1, d2)
print(sd)

for k, v in sd.items():
    print(k, v)

output:
ChainMap({'aa': 1, 'a': 1, 'b': 2}, {'b':3, 'bb': 22, 'aa': 11})
1 2 of 
a 1 . 
B 2 
Bb 22 by 
aa 1

Note: the same key value, behind the front cover.

Reference: Author: onemore
Source: https://www.cnblogs.com/dianel/

　　 Original 2: http://www.zlovezl.cn/articles/collections-in-python/