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Unit testing is a crucial aspect of modern software development, ensuring that individual units of code function correctly in isolation. In PHP, unit testing helps developers identify bugs early in the development cycle, improve code quality, and facilitate code maintenance. In this comprehensive guide, we'll walk you through the process of creating unit tests in PHP, using popular testing frameworks like PHPUnit.

Why Unit Testing?

Unit testing involves testing individual components or units of code in isolation from the rest of the application. Here are some reasons why unit testing is essential:
   
. Bug Detection: Unit tests help identify bugs and regressions early in the development process, making them easier and cheaper to fix.
   
. Code Quality: Writing unit tests encourages developers to write modular, well-structured, and maintainable code.
   
. Improved Documentation: Unit tests serve as executable documentation, providing clear examples of how individual components of your code should behave.

Getting Started with PHPUnit:

PHPUnit is the most widely used testing framework for PHP. It provides a robust set of features for writing and executing unit tests. Let's dive into how you can get started with PHPUnit:

Installation:

You can install PHPUnit using Composer, the PHP package manager. Simply navigate to your project directory and run the following command:

composer require --dev phpunit/phpunit

This command installs PHPUnit as a development dependency in your project.

Writing Your First Test:

Now that PHPUnit is installed, let's create a simple test case. Create a new directory named tests in your project root, and within that directory, create a file named ExampleTest.php. Here's an example of what your test file might look like:

<?php

use PHPUnit\Framework\TestCase;

class ExampleTest extends TestCase
{
 public function testTrueAssertsToTrue()
 {
 $this->assertTrue(true);
 }
}

This test case contains a single test method named testTrueAssertsToTrue, which asserts that true is indeed true.

Running Tests:

To run your tests, simply execute PHPUnit from the command line, pointing it to your test directory. Run the following command in your project root:

vendor/bin/phpunit tests

PHPUnit will discover and execute all test cases within the specified directory, providing detailed feedback on the results.

Writing Testable Code:

Writing testable code is essential for effective unit testing. Here are some best practices to follow:
   
. Separation of Concerns: Ensure that your code follows the principle of separation of concerns, with clear boundaries between different components.
   
. Dependency Injection: Use dependency injection to inject dependencies into your classes, making it easier to replace them with mock objects during testing.
   
. Mocking and Stubbing: Use PHPUnit's mocking and stubbing features to simulate the behavior of dependencies and isolate the code under test.

Advanced Features:

PHPUnit provides a wide range of advanced features for writing comprehensive unit tests. Some notable features include:

-Data Providers: Use data providers to run a test method with multiple sets of data.

-Annotations: PHPUnit supports annotations for marking test methods, setting up fixtures, and configuring test execution.

-Code Coverage: PHPUnit can generate code coverage reports, showing which parts of your codebase are covered by your tests.

Conclusion:

Unit testing is an indispensable practice in modern PHP development, and PHPUnit makes it easy to write and execute unit tests for your codebase. In this guide, we've covered the basics of getting started with PHPUnit, writing testable code, and leveraging advanced features to write comprehensive unit tests. By incorporating unit testing into your development workflow, you can improve code quality, reduce bugs, and build more robust and maintainable PHP applications.

Today’s digital transformation has significantly empowered every company to produce accurate information at all touch points. Whether it’s a large-scale enterprise or a small private venture, every organization irrespective of all sizes needs proper web app development services to build a sophisticated database for storing and managing its data. Examples of web applications include customer relationship management (CRM) systems, project management tools, and e-commerce platforms. These custom software developers play a crucial role in tailoring web applications to meet specific business needs, ensuring seamless integration and optimal functionality.

A database is a set of a vast range of structured & unstructured data stored in a system and adequately managed through DBMS or Database Management System. The data stored in the database is highly sensitive, hence companies need to be careful while accessing any data or information.

When considering the development of web applications, partnering with a reputable web development firm is essential to ensure the seamless integration and efficient management of databases. A skilled web development firm possesses the expertise to optimize database systems, enhancing data organization, security, and retrieval processes for an enhanced user experience. In this article, we will delve into the top database solutions for web applications in 2024 and explore the advantages they bring to the forefront of modern software development.

Types of Databases For Web Applications

Depending on your business model, industry domain, and other factors, your business application system will have certain requirements. Different databases types are used for different enterprise requirements. However, the database is technically divided into two types: SQL & NoSQL.

SQL or Structured Query Language is a relational database that comes with a relational structure. This is used for managing structured data only. On the other hand, the NoSQL database doesn’t have any relational structure & they are used to store unstructured data types. For your convenience, we have shared a complete comparison of both databases below.

SQL Databases
NoSQL Databases
Mix of proprietary & open-source
Open source database
Comes with rational structure
No rational structure
Ideal for managing structured data
Best for storing unstructured & semi-structured data
Vertically scalable
Horizontally scalable
Examples: MySQL, PostgreSQL, Oracle, etc
Examples: MongoDB, Cassandra, Firebase, etc

Enterprises have deeply relied on SQL to manage all their databases in web apps, but as cloud, microservices & distributed applications become popular, there are NoSQL options also available. Before you choose the right database, you must consider a number of factors such as size, structure & scalability requirements. Apart from that, you need to consider some of the following questions also:
* What type of data structure do you need?
* What is the amount of data you want to store?
* What is your total budget?
* Does it allow for support contracts & software licenses?
* What is the requirement for your data security?
* What third-party tools do you want to add to your database?

Best Databases For Web Applications In 2024

Finding out the right database option for a web app development may impact the scalability and success of any project. With too many options available, it’s quite challenging to select which one is the best for you. 2024’s widely-popular databases include:

1. MySQL:

MySQL is one of the best open-source relational databases developed by Oracle Corporation in 1995. According to the Stack Overflow developer survey, this database was used by 46.8% as of 2022. The robustness, maturity, and stability of this database make it perfect for web applications. Moreover, MySQL database uses a structured language & written in C & C++.
Latest version: MySQL 8.0.33

Key features of MySQL database include:
* Easy to deploy & manage
* It supports Consistency, Atomicity, Isolation & Durability
* It’s an RDBMS or Relational Database Management System
* Provides fast-loading utilities with several memory caches to maintain servers
* Offers top-notch results without compromising any functionality
* Contains solid Data Security layers to offer complete security solutions

2. PostgreSQL:

Launched in 1996, PostgreSQL is also a very popular database used as a data warehouse or primary data store for web, analytics, geospatial and mobile applications. This is also an open-source SQL-based RDBMS (relational database management system) that supports C, C++, C#, Ruby, Java, Python, and other programming languages. This agile database is compatible with different OSs such as Windows, Linux, Unix, MacOSX, etc.
Latest version: PostgreSQL 15.3

Key features of the PostgreSQL database include
* Houses different constraints such as primary keys, foreign keys, exclusion constraints, explicit locks, advisory locks, etc
* Supports different SQL features like SQL Sub-selects, Multi-Version Concurrency Control,
* Streaming Replication, complex queries, etc.
* Compatible with different data types like Structured, Customizations, Primitives, Geometry & Documents.
* Supports MVCC or multi-version concurrency control

3. Microsoft SQL Server:

Launched in 1989, Microsoft SQL Server is a powerful RDBMS used for transaction processing, analytics applications, and business intelligence in IT environments. It comes with built-in intelligence & enables businesses to boost their performance, security, and availability seamlessly. MS SQL Server comes in different editions with authentication & security features.
Latest version: Microsoft SQL Server 2022

Key features of the Microsoft SQL Server database include:
* Available on both Linux & Windows platforms
* Supports semi-structured, structured, and spatial data
* It has a custom-built graphical integration
* Helps users build different designs and tables without syntax
* Comes with several features for protection, monitoring, and data classification
* Gives alerts on security gaps, misconfigurations & suspicious activities

4. MongoDB:

MongoDB is a document-oriented open-source NoSQL database used for high-volume data storage. Written in JavaScript, C++, and Python, this is a very flexible and scalable database platform that removes relational DB approaches. MongoDB offers a high level of flexibility through load balancing and horizontal scaling capacities. This is a perfect option for web apps that need high performance.
Latest version: MongoDB 6.0.5

Key features of the MongoDB database include:
* Effectively supports ad hoc queries
* Highly scalable & flexible database
* Offers schema-less database
* Appropriate indexing for query executions
* Replication for data availability & stability

5. Oracle:

Oracle is a very popular RDBMS that is known for its high-performance and cost-optimization solutions. This is a commercial relational database written in C, C++ & Java. Oracle comes with a relational database architecture that offers an easy, scalable, performant solution for accessing, defining, and managing data.
Latest version: Oracle 21c

Key features of the Oracle database include:
* Executes fast backup & recovery
* Provides multiple database support
* Offers superior scalability
* Offers better user controls and identity management
* Utilizes a single database for every data type

6. Redis:

Redis stands for Remote Dictionary Server and is a widely-used open-source database used for web applications and cache management. Redis can also be used with different streaming solutions like Amazon Kinesis & Apache Kafka to analyze & process real-time data.

This database also supports different data structures like lists, streams, bitmaps, strings, maps, and so on. Because of its high performance, Redis is vastly used in many sectors such as IoT, Gaming, Financial Services, etc.
Latest version: Redis 7.0.11

Key features of the Redis database include:
* Provides premium speed with improved caching & in-memory capabilities.
* Supports a variety of data structures (strings, hashes, lists, bitmaps, HyperLogLogs, etc)
* Compatible with different languages (Java, PHP, Python, C, C#, C++, etc)
* Offers quick access to data for training, deploying, and developing applications

7. Cassandra:

Released in 2008, Cassandra is a distributed open-source NoSQL database that effectively manages vast amounts of data. It provides excellent scalability that supports multi-datacenter replication and automatic data replication. Cassandra database is ideal for applications that need prompt data access with high performance.
Latest version: Cassandra 4.1.0

Key features of the Cassandra database include:
* Easy to scale
* Highly scalable & comes with strong architecture
* Offers flexibility for data distribution
* Faster linear-scale performance
* Very flexible data storage
* Supports properties like Consistency, Atomicity, Isolation, and Durability

How Much Does The Web Application Database Cost?

In general, the average web app development cost ranges from $5,000 to $100,000. However, this cost depends on too many parameters like web app database complexity, features & functionalities, backend infrastructure, etc.

If you want to get a proper estimation of your web database application cost, you can take advantage of a web app cost calculator. For your convenience, we have listed the average web application development costs based on their categories.
Factors
Basic Web Apps
Medium Apps
Complex Apps
Highly Complex Apps
Estimated cost
$3,000 to $15,000
$15,000 to $60,000
$60,000 to $2,50,000
More than $250,000
Timeline
    . to 5 weeks
    . to 20 weeks
    . to 25 weeks
More than 9 months
Features
Simple landing page
Static content
Landing page
Database integration
Admin panel
User accounts
Online payment options
Third-party integrations
Landing page
Huge database integration
Admin panel
Multipleuser accounts
Online Payment options
Third-party integrations
Personalized features
Landing page
Top-notch database integration
Admin panel
Customized features
Examples
Online brochures
Portfolio
websites
MVP
Web portals
E-commerce websites
Online gaming sites with animation
Web applications for businesses
Automated billing systems
Human resources management system (HRMS)
Complex ecommerce websites
Custom web apps
On-demand web apps
App for complex businesses
High-end features with AI/ML integration
Custom web apps

Final Words

In the past, the process of selecting a database web application was straightforward. However, in this modern era of software development, this process has become very intrinsic as too many options are available today and the business requirements have also transformed.

For a business that works with small apps, NoSQL databases like MongoDB can be the best choice & for managing large & complex applications, databases like MySQL, MS SQL Server, and PostgreSQL can be the right choice. Would you like to know more about web applications with databases? Talk to our experts today.

Introduction

MongoDB, a popular NoSQL database, provides flexibility and scalability for modern web applications. In this guide, we will explore how to use MongoDB with PHP, a widely used scripting language. We'll cover the necessary steps to establish a connection, perform CRUD operations, and leverage the power of MongoDB in your PHP projects.

Prerequisites

Before diving into MongoDB integration, ensure you have the following:
   
. MongoDB installed and running on your machine.
   
. PHP installed on your machine, preferably version 7 or above.
   
. Composer, a dependency management tool for PHP.

Step 1: Installing the MongoDB PHP Driver

The first step is to install the MongoDB PHP driver, which enables PHP to communicate with MongoDB. We can use Composer to handle the installation process efficiently. Open your terminal or command prompt and navigate to your project directory. Then run the following command:

composer require mongodb/mongodb

This command installs the MongoDB PHP driver along with its dependencies. Composer will create a vendor directory containing the required files.

Step 2: Establishing a Connection

To connect to MongoDB from PHP, we need to create a new instance of the MongoDB client class. Open your code editor and create a new PHP file, for example, connect.php. Add the following code:

<?php

require 'vendor/autoload.php';

use MongoDB\Client;

$client = new Client("mongodb://localhost:27017");

?>

In this code, we require the Composer-generated autoloader and import the Client class. We then create a new instance of the Client class, specifying the MongoDB server's connection URL. Adjust the URL if your MongoDB server is running on a different host or port.

Step 3: Performing CRUD Operations

Now that we have established a connection, let's explore how to perform basic CRUD operations using MongoDB with PHP.

Creating Documents

To insert a new document into a MongoDB collection, use the insertOne() method. Here's an example:

<?php
$collection = $client->test->users;

$newUser = [
 'name' => 'John',
 'email' => '[email protected]',
 'age' => 25
];

$insertResult = $collection->insertOne($newUser);
echo "Inserted document ID: " . $insertResult->getInsertedId();
?>

In this code, we select the users collection within the test database. We create a new document as an associative array and then use the insertOne() method to insert it into the collection. Finally, we retrieve and display the ID of the inserted document using the getInsertedId() method.

Reading Documents

To retrieve documents from a MongoDB collection, use the find() method. Here's an example:

<?php
$collection = $client->test->users;

$documents = $collection->find();

foreach ($documents as $document) {
 echo $document['name'] . ': ' . $document['email'] . "\n";
}
?>

In this code, we retrieve all the documents from the users collection. We iterate over the result using a foreach loop and access specific fields, such as the name and email, to display their values.

Updating Documents

To update documents in a MongoDB collection, use the updateOne() method. Here's an example:

<?php
$collection = $client->test->users;

$updateResult = $collection->updateOne(
 ['name' => 'John'],
 ['$set' => ['age' => 30]]
);

echo "Modified " . $updateResult->getModifiedCount() . " document(s).";
?>

In this code, we update the age field of the document with the name 'John' using the $set operator. The updateOne() method updates the first matching document. We then retrieve the number of modified documents using the getModifiedCount() method.

Deleting Documents

To remove documents from a MongoDB collection, use the deleteOne() method. Here's an example:

<?php
$collection = $client->test->users;

$deleteResult = $collection->deleteOne(['name' => 'John']);
echo "Deleted " . $deleteResult->getDeletedCount() . " document(s).";
?>

In this code, we delete the document with the name 'John'. The deleteOne() method removes the first matching document, and we retrieve the number of deleted documents using the getDeletedCount() method.

Conclusion

Congratulations! You have learned the basics of using MongoDB with PHP. By establishing a connection, performing CRUD operations, and leveraging the power of MongoDB, you can build powerful and scalable web applications. Remember to refer to the MongoDB PHP documentation for additional features and advanced usage.

Artificial Intelligence has significantly transformed the way we work and interpret information. With technologies such as OCR, machine learning, deep learning, natural language processing, and computer vision; machines are now able to provide greater insights and perform tasks that typically required hours and hours of work from humans.

What is artificial intelligence?

A.I. or artificial intelligence is the technology that enables machines to perform tasks that usually require human intelligence. But instead of using human brains, A.I. uses different technologies such as computers, or even software algorithms, to perform tasks. Some of the most common A.I. technologies include speech recognition, voice recognition, machine translation, natural language processing, computer vision, and predictive analytics. The term artificial intelligence comes from the combination of artificial and intelligence. While artificial intelligence is a property of the physical world, intelligence is the property of the mind. How does it make sense in Web Development? As mentioned earlier, A.I. has significantly transformed the way we work and interpret information.

How is AI applied to web development?

In the majority of cases, AI is used to assist a developer in a number of functions: Automatically format existing content, analyze images for semantic meaning Break down complex tasks into smaller pieces Example applications of AI in web development Example image compression algorithms. Tools such as image recognition and machine learning have been key factors in the development of new image processing algorithms. Traditionally, manually processing an image was a lengthy and tedious process, but when computer vision was introduced into the process it drastically decreased the amount of time required to complete this task. Now, programs such as image recognition can identify objects in images and classify them based on both visual and metadata attributes.

Machine learning

When data is fed into a machine learning algorithm, the machine learns to understand it. For instance, if you provide a machine learning algorithm examples of dogs verses blueberries, the machine will learn to identify what a picture of a blueberry looks like, verses a picture of a dog. Natural Language Processing Natural language processing is a sub-field of machine learning. You can apply natural language processing for reading emails, chatting, or writing blog posts (such as this one!). A good example of natural language processing in action can be found in Microsoft's Cortana. Deep learning This is the most popular type of artificial intelligence today.

Deep learning

Deep learning algorithms are very similar to how the human brain works, with its built in mechanisms to learn and memorise a vast amount of information. It's these connections that enable machines to be able to recognise patterns and learn from them. An example of this is Google Translate, which recognises more than a 1,000 languages. This isn't an example of AI but it shows how useful these programs can be. Deep learning is one of the hottest technologies in the field of machine learning and this explains why almost all of the major technology companies are pushing these advances forward.

Natural language processing

For example, your phone can understand you better when you speak to it. If you say “Hey, Siri,” your phone will listen to you and respond to your questions. In general, it means that the system has been trained and is able to better understand the context of what you’re trying to communicate. This type of Natural Language Processing is used in the majority of companies today, including the likes of Google and Apple, to improve the user experience, provide better customer service, and to aid in the effective execution of processes. Machine learning Machine Learning is an extremely powerful technique used to further improve the knowledge of artificial intelligence, as well as to make machines smarter by discovering patterns and generalities in vast amounts of data.

Computer vision

Computer vision is a technology that has been able to recognize objects in images and video for eons. A popular example is Apple's Siri, which was one of the first software to use computer vision to provide contextual awareness. AI is built on this technology, providing the capability to recognize various images and videos. The industry is still in its infancy, but what we have seen so far has been incredibly incredible. What's amazing is that just a few years ago we thought that vision was completely under our control, but now, it has evolved to understand the nuances of objects.

Conclusion

“In the year 2050, the Amazon book you ordered for your Kindle will be delivered by a drone.”

This futuristic statement by Amazon CEO Jeff Bezos did leave you pondering. But it is one thing to dream about the future and another thing to think about the innovations taking place in the present and how you can exploit them to drive better business results. To make the most of the technologies coming to our everyday lives, we must acquire a knowledge of the AI technology, its features, and its application. Succeeding in today’s competitive and challenging business world, requires a broad set of skills such as coding, business analysis, computer programming, and ecommerce marketing.

Learn more about AI with our video library

Recently I was faced with a task to post data from a .csv file to an external REST API. I’m just going to log in to this article about what I did to get the job done.

Let’s start by creating a template for uploading the file. For this article’s sake, lets make the changes in the dashboard.blade.php file.

<form method="post" enctype="multipart/form-data"> @csrf <div class="custom-file"> <input type="file" accept=".csv" name="excel" class="custom-file-input" id="customFile" /> <label class="custom-file-label" for="customFile">Choose file</label	> </div> <div> <button type="submit" class="btn btn-primary btn-sm" style="margin-top: 10px"	>Submit> </div>

</form>

Note : Don’t forget to add enctype=”multipart/form-data”!



Once the user has submitted the file, we need a new router to process the file and send its content to the REST API. Let’s start by creating a Controller.

php artisan make:controller UploadController

Now in the web.php file,

Route::post('/upload', [UploadController::class, 'upload'])->name('upload')->middleware('auth');

In the UploadController.php , create a function named upload. We will be writing all the code inside this function. Also, we need an action for the form.

<form method="post" action="{{route('upload')}}" enctype="multipart/form-data">

Now inside the upload function, we need to get the submitted file and parse its contents.

Get the submitted file,

$file = $request->file('excel');

Parse the submitted file,

if (($handle = fopen($file, "r")) !== FALSE) { while (($data = fgetcsv($handle, 1000, ",")) !== FALSE) { ..... }

}

We will be using a dummy REST API to create users — https://reqres.in/api/users. This is the request body required to create a user.

{ "name": "test", "job": "test"

}

Keeping this in mind, we will create a sample .csv template to be submitted. The fields need to be two, namely Name and Job.



We need to send the values from this file as the request body to the API. So let’s add the code to loop through the content of this file.

if (($handle = fopen($file, "r")) !== FALSE) { while (($data = fgetcsv($handle, 1000, ",")) !== FALSE) { Http::post('https://reqres.in/api/users', [ 'name' => $data[0], 'job' => $data[1], ]); }

}

This will create each student for each row of the file. But we don’t need to send the data of the first row of the file.

Full code:

public function upload(Request $request){ $file = $request->file('excel'); if($file){ $row = 1; $array = []; if (($handle = fopen($file, "r")) !== FALSE) { while (($data = fgetcsv($handle, 1000, ",")) !== FALSE) { if($row > 1){ Http::post('https://reqres.in/api/users', [ 'name' => $data[0], 'job' => $data[1], ]); array_push($array,$data[0]); } $request->session()->flash('status', 'Users '.implode($array,", ").' created successfully!'); $row++; } } }else{ $request->session()->flash('error', 'Please choose a file to submit.'); } return view('dashboard');

}

This will post the data starting from the second row of the file, display a success message once the users are created, and an error message if the submit button is clicked without choosing a file.

Full template:

<div class="container max-w-7xl mx-auto sm:px-6 lg:px-8" style="width: 50%"> @if (session('status')) <div class="alert alert-success"> {{ session('status') }} </div> @endif @if (session('error')) <div class="alert alert-error"> {{ session('error') }} </div> @endif <form action="{{route('upload')}}" method="post" enctype="multipart/form-data"> @csrf <div class="custom-file"> <input type="file" accept=".csv" name="excel" class="custom-file-input" id="customFile" /> <label class="custom-file-label" for="customFile">Choose file</label> </div> <div> <button type="submit" class="btn btn-primary btn-sm" style="margin-top: 10px">Submit</button> </div> </form>

</div>

That’s it, thanks for reading :)