Python - Collections Module
The collections module provides alternatives to built-in container data types such as list, tuple and dict.
namedtuple() function returns a tuple-like object with named fields. These field attributes are accessible by lookup as well as by index.
General usage of this function is:
The following statement declares a student class having name, age and marks as fields.
>>> import collections >>> student = collections.namedtuple('student', [name, age, marks])
To create a new object of this namedtuple, do the following:
>>> s1 = student("Imran", 21, 98)
The values of the field can be accessible by attribute lookup:
>>> s1.name 'Imran'
Or by index:
OrderedDict() function is similar to a normal dictionary object in Python. However, it remembers the order of the keys in which they were first inserted.
import collections d1 = collections.OrderedDict() d1['A'] = 65 d1['C'] = 67 d1['B'] = 66 d1['D'] = 68 for k,v in d1.items(): print (k,v)
A 65 C 67 B 66 D 68
Upon traversing the dictionary, pairs will appear in the order of their insertion.
A deque object support appends and pops from either ends of a list. It is more memory efficient than a normal list object. In a normal list object, the removal of any item causes all items to the right to be shifted towards left by one index. Hence, it is very slow.
>>> q=collections.deque([10,20,30,40]) >>> q.appendleft(0) >>> q deque([0, 10, 20, 30, 40]) >>> q.append(50) >>> q deque([0, 10, 20, 30, 40, 50]) >>>q.pop() 50 >>> q deque([0, 10, 20, 30, 40]) >>> q.popleft() 0 >>> q deque([10, 20, 30, 40])
Learn more about the collections module in Python docs.