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PHP 7 Data Structures and Algorithms

PHP 7 Data Structures and Algorithms

By : Rahman
5 (2)
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PHP 7 Data Structures and Algorithms

PHP 7 Data Structures and Algorithms

5 (2)
By: Rahman

Overview of this book

PHP has always been the the go-to language for web based application development, but there are materials and resources you can refer to to see how it works. Data structures and algorithms help you to code and execute them effectively, cutting down on processing time significantly. If you want to explore data structures and algorithms in a practical way with real-life projects, then this book is for you. The book begins by introducing you to data structures and algorithms and how to solve a problem from beginning to end using them. Once you are well aware of the basics, it covers the core aspects like arrays, listed lists, stacks and queues. It will take you through several methods of finding efficient algorithms and show you which ones you should implement in each scenario. In addition to this, you will explore the possibilities of functional data structures using PHP and go through advanced algorithms and graphs as well as dynamic programming. By the end, you will be confident enough to tackle both basic and advanced data structures, understand how they work, and know when to use them in your day-to-day work
Table of Contents (14 chapters)
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PHP array, is it a performance killer?

We have seen in this chapter how each element in a PHP array has a very big overhead of memory. Since it is done by the language itself, there is very little we can do over here, except that we use SplFixedArray instead of a regular array where it is applicable. But if we move from our PHP 5.x version to the new PHP 7, then we can have a huge improvement in our application, whether we use regular PHP array or SplFixedArray.

In PHP 7, the internal implementation of a hash table has been changed drastically and it is not built for efficiency. As a result, the overhead memory consumption for each element has gone down significantly. Though we can argue that less memory consumption does not make a code speedy, we can have a counter argument that if we have less memory to manage, we can focus more on execution rather than memory management. As...

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