Book Image

Software Architecture with Python

By : Anand Balachandran Pillai
Book Image

Software Architecture with Python

By: Anand Balachandran Pillai

Overview of this book

This book starts by explaining how Python fits into an application's architecture. As you move along, you will get to grips with architecturally significant demands and how to determine them. Later, you’ll gain a complete understanding of the different architectural quality requirements for building a product that satisfies business needs, such as maintainability/reusability, testability, scalability, performance, usability, and security. You will also use various techniques such as incorporating DevOps, continuous integration, and more to make your application robust. You will discover when and when not to use object orientation in your applications, and design scalable applications. The focus is on building the business logic based on the business process documentation, and understanding which frameworks to use and when to use them. The book also covers some important patterns that should be taken into account while solving design problems, as well as those in relatively new domains such as the Cloud. By the end of this book, you will have understood the ins and outs of Python so that you can make critical design decisions that not just live up to but also surpassyour clients’ expectations.
Table of Contents (18 chapters)
Software Architecture with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Maximum subarray problem


For starters, let us look at an interesting problem. In this problem, the goal is to find the maximum contiguous subarray of an array (sequence) of integers having mixed negative and positive numbers.

For example, say we have the following array:

>>> a  = [-5, 20, -10, 30, 15]

It is pretty obvious with a quick scan that the maximum sum is for the subarray [20, -10, 30, 15], giving a sum of 55.

Let us say, as a first cut, you write this piece of code:

import itertools

# max_subarray: v1
def max_subarray(sequence):
    """ Find sub-sequence in sequence having maximum sum """
    
    sums = []
    
    for i in range(len(sequence)):
        # Create all sub-sequences in given size
        for sub_seq in itertools.combinations(sequence, i):
            # Append sum
            sums.append(sum(sub_seq))

    return max(sums)

Now let's try it out:

>>>  max_subarray([-5, 20, -10, 30, 15])
65

This output seems clearly wrong, as any manual addition of any subarray...