Book Image

Python Unlocked

By : Arun Tigeraniya
Book Image

Python Unlocked

By: Arun Tigeraniya

Overview of this book

Python is a versatile programming language that can be used for a wide range of technical tasks—computation, statistics, data analysis, game development, and more. Though Python is easy to learn, it’s range of features means there are many aspects of it that even experienced Python developers don’t know about. Even if you’re confident with the basics, its logic and syntax, by digging deeper you can work much more effectively with Python – and get more from the language. Python Unlocked walks you through the most effective techniques and best practices for high performance Python programming - showing you how to make the most of the Python language. You’ll get to know objects and functions inside and out, and will learn how to use them to your advantage in your programming projects. You will also find out how to work with a range of design patterns including abstract factory, singleton, strategy pattern, all of which will help make programming with Python much more efficient. Finally, as the process of writing a program is never complete without testing it, you will learn to test threaded applications and run parallel tests. If you want the edge when it comes to Python, use this book to unlock the secrets of smarter Python programming.
Table of Contents (15 chapters)
Python Unlocked
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Python library data structures


Key 2: Using Python's standard library data structures.

  • collections.deque: The collections module have a deque implementation. Deque is useful for the scenarios where item insertion and deletion occurs at both ends of structure as it has efficient inserts at the start of structure as well. Time-complexity is similar to copy O(n), insert—O(1), and delete—O(n). The following graph shows an insert at 0 position operation comparison between list and deque:

    >>> d = deque()
    >>> getsizeof(d)
    632
    >>> d = deque(range(100))
    >>> getsizeof(d)
    1160

    The following image is the graphical representation of the preceding code:

  • PriorityQueue: A standard library queue module has implementations for multiproducer, and multiconsumer queues. We can simplify and reuse its PriorityQueue for simpler cases using the heapq module, as follows:

    from heapq import heappush, heappop
    from itertools import count
    
    class PriorityQueue(object):
        def __init__...