Python, a versatile and beginner-friendly programming language, surprises us with the depth of its modules. One such powerful built-in module is known as Collections. This module can harness Python’s internal settings to provide alternatives to built-in general-purpose containers – dict, list, set, and tuple.
Table of contents
What is the Python Collections Module?
Python Collections module is, essentially, a container module. It houses special container datatypes that provide alternatives to Python’s general-purpose containers.
The collections module extends the functionality of the traditional data types, enabling easier programming and data manipulation. This practical module has been designed to handle and organise data better.
Why Should I Learn It?
Grasping the concept of handling large data in Python with this module should be your priority for multiple reasons:
- Efficiency: Collections module optimises Python coding and execution, making it faster.
- Better Data Organisation: The Collections module helps in creating data containers to structure your data more efficiently.
- Deep Dive into Python: As you grasp more built-in modules and functions, Python coding becomes more exciting and flexible.
What Makes it Eligible for Game Creation / Coding?
Collections module is a robust tool when dealing with game character statistics, item properties, game states, and other elements. Meanwhile, for basic coding, it simplifies the process of organization and manipulation of complex data structures.
As we delve deeper into the Python Collections Module in the following sections, you will understand its true potential.
Understanding Collections Module – Part 1
Let’s begin by importing the Collections module in Python:
import collections
There are several classes within the Collections module that provide a powerful range of options. We’ll explore their potential with some hands-on examples.
The namedtuple
First up, the namedtuple. This is a function that generates a subclass of tuple with named fields. Let’s see an example:
from collections import namedtuple
# create a namedtuple Car
Car = namedtuple('Car', 'brand model year')
# assign values
car1 = Car('Ford', 'Mustang', 1969)
print(car1)Result:
Car(brand='Ford', model='Mustang', year=1969)
The deque
The deque, pronounced ‘deck’, stands for ‘double-ended queue’. It’s a list-like container with fast append and pop operations from either end.
from collections import deque
# create a deque
d = deque('motorcycle')
# append to the right
d.append('m')
print('Deque after right append:', d)
# append to the left
d.appendleft('icycle')
print('Deque after left append:', d)Result:
Deque after right append: deque(['m', 'o', 't', 'o', 'r', 'c', 'y', 'c', 'l', 'e', 'm']) Deque after left append: deque(['icycle', 'm', 'o', 't', 'o', 'r', 'c', 'y', 'c', 'l', 'e', 'm'])
In part two of this tutorial, we will cover more classes of Python collections that offer a wide range of functionalities to make coding more convenient and efficient.
Understanding Collections Module – Part 2
Let’s delve deeper into the classes of the Python Collections Module.
The ChainMap
ChainMap class is, essentially, a dictionary-like class which is able to list multiple mappings. It groups multiple dictionaries into a single unit and returns a list of dictionaries.
from collections import ChainMap
dict1 = {'One': 1, 'Two': 2}
dict2 = {'Three': 3, 'Four': 4}
chain_map = ChainMap(dict1, dict2)
print(chain_map.maps)Result:
[{'One': 1, 'Two': 2}, {'Three': 3, 'Four': 4}]The Counter
The Counter Class in Python Collections module allows you to count the items in an iterable list. Quite useful, isn’t it?
from collections import Counter count = Counter(['a', 'b', 'c', 'a', 'b', 'b', 'c', 'a']) print(count)
Result:
Counter({'a': 3, 'b': 3, 'c': 2})The OrderedDict
While regular Python dictionaries do not track the insertion order, and keys/values come out in arbitrary order, the OrderedDict from Python collections module remembers the order entries were added. This might come handy in certain coding scenarios.
from collections import OrderedDict odict = OrderedDict() odict['b'] = 2 odict['a'] = 1 odict['c'] = 3 print(odict)
Result:
OrderedDict([('b', 2), ('a', 1), ('c', 3)])The defaultdict
The defaultdict works exactly like a Python dictionary, except for one difference: it does not raise a KeyError when you try to access a non-existent key. Instead, it initializes the key with the element of the data type that you pass as an argument.
from collections import defaultdict default_dict = defaultdict(int) default_dict['a'] = 1 default_dict['b'] = 2 print(default_dict['c'])
Result:
0
We hope these examples have given you a better understanding of the Collections Module in Python. Armed with these classes and their utility, coding in Python opens up a new world of efficient possibilities.
Where to Go Next?
Having explored the Python Collections module and its powerful classes, you’re likely wondering what the next step is in your Python journey.
Apart from self-exploration, we at Zenva provide a thorough and in-depth educational resource that can significantly boost your Python skills – the Python Mini-Degree. The Python Mini-Degree is a comprehensive collection of courses that dives deep into Python programming. It covers a plethora of topics including coding basics, algorithms, object-oriented programming, and even game and app development. Wouldn’t it be exciting to learn by creating your own games, algorithms, and real-world apps?
This hands-on learning approach, which includes but isn’t limited to developing an arcade game, medical diagnosis bot, escape room game, and a to-do list app, ensures a deep understanding of the language and its applications.
The curriculum offers flexibility and 24/7 accessibility, making it a perfect fit for people from diverse educational or professional backgrounds. Our certified instructors, who have been recognised by Unity Technologies and CompTIA, have designed the courses in an engaging format including video lessons, quizzes, and coding challenges to reinforce learning.
If you’re looking for a broader exploration of Python, feel free to browse through our Python courses. Your journey doesn’t have to end with this tutorial or even the Python Mini-Degree. Remember, learning is an endless journey, and at Zenva, we ensure that journey is as enriching as possible.
Conclusion
The Python Collections module – a powerful, often underappreciated, tool in every Python programmer’s toolkit. As you’ve seen in this tutorial, it opens up a wealth of possibilities for handling, structuring, and manipulating complex data. mastering it is a major stride on your journey to greater coding productivity and competence.
Unleashing the power of Python doesn’t have to be daunting. With our Python Mini-Degree program, we offer you the key to understanding, not just Collections, but the real depth and breadth of Python. Whether it’s the namedtuple, deque, Counter, or any other class within the Collections grid, with Zenva, you’ll navigate Python’s rich landscape with confidence. Happy coding!
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