Helge Sverre has put together an introduction of a tool perfect for anyone that's been looking for a framework-agnostic way to handle database migrations: Phinx.

Phinx is a database migration tool written by Rob Morgan in PHP, what that means is that you can tell Phinx that you want to create a new database table, add a column or edit the properties of a column by writing “migrations”.

You can then run this migration using the Phinx tool and it will connect to your database with the configuration that you specified and perform the database updates for you automatically.

He then walks you through a full introduction to the tool, breaking it down into sections:

• Getting Phinx installed (via Composer)
• Configuring it via a YAML file
• Writing your first simple migrations
• Creating database seeders (including the use of Faker data)
• Rolling back your migrations

All of these topics come with plenty of code, configuration and output examples, helping you ensure you're on the right track.

Jeff Madsen has a quick post to his site showing how to use Faker to populate data in Laravel directly in the framework's generated "seeders".

Hello, Mr. asdfgh qweefg! Welcome to kgjhjgjh! Thank you. Only the name's not "asdfgh qweefg".

Sorry! It's just easier.. You're always showing everyone on Laravel Quick Tips these helpful little tricks. Why not show them how to give me a proper name?

He includes an example of creating a Faker object in the seeder and using it to make name, email, age and city values. Naturally, not everyone's going to have English names or locations, so he shows how to set the language, locale and a few other tips:

• shortcuts for optional data
• randomized email addresses
• random elements from a given set

He also mentions custom providers but points to the Faker documentation for a bit more information about that.

The SitePoint PHP blog has a new tutorial posted by Reza Lavaryan showing you how to "supercharge your applications" with the help of the Blackfire.io profiling service.

With profiling, we can spot the performance bottlenecks in the code and do something about them. There is a variety of profiling tools out there, each taking a different approach. [...] With profiling, we can spot the performance bottlenecks in the code and do something about them. There is a variety of profiling tools out there, each taking a different approach. [...] Blackfire.io is the new generation of web profilers, which takes the automatic instrumentation approach, but without imposing a performance impact on our application.

First he defines some of the basic terms it's helpful to know when profiling and using Blackfire. He then walks you through getting what you'll need set up:

• a Homestead VM instance with the necessary configuration options
• a script using Faker to generate and write user data to a local database

He then shows you how to execute the first profiling run and what the results look like in the Blackfire views. He uses these results to make some modifications to the script and re-runs the tests to see what kind of gains it provides. Most of his examples use the web interface for the service but the post ends with a look at using the command line tool and getting back some simple metrics as a result.

In the latest post to the SitePoint PHP blog Aleksander Koko continues with his series about creating an application with PHP and EmberJS with a look at building databases. In the first part of the series he introduced the main toolset and set up a simple Laravel application inside of a Homestead instance. This latest post builds on that platform.

In this part, we will create the structure of the database. We will create the tables using migrations and seed the database using seeders. Also, you will learn how to grab some random images from LoremPixel and put them on the filesystem using Flysystem. You’ll also be adding some randomly generated data using the Faker library. Much like with part 1, you can download this part’s code from github.

He shows you how to get all the needed libraries installed and run the migrate command to create the needed tables. He also helps you set up a Dropbox application so you can use their API and configure the application with your API settings. Next he modifies the migrations and seeds the sample data. Next up he makes the models for each of the tables and integrates Faker to populate them with better seed data, making seeder classes to handle some of the more custom logic.

Phil Sturgeon has posted the first part of a series he calls "Build API's That You Won't Hate", a follow up to one of his previous posts about building good APIs in your application.

A little while back I produced an article called Building a Decent API which was mostly a tongue-in-cheek list of things that I'd come across in other APIs that pissed me off, or that I had done myself and used my super-power of hindsight combined with sarcasm to make a set of rules for you to live by when building APIs. The combination of cheek and naughty words made that "eat your greens" article go down a lot more smoothly, but it certainly lacked a little substance but I always wanted to turn that into a much more in depth of blog posts.

In this first part of the series he covers one main topic - generating "good" data for you to use in your development environment. As he points out, using production data in development databases dangerous for several reasons. He suggests the Faker library to do what's called "database seeding" and generating fake, but accurately formatted, data to use for testing. He includes some sample code showing how to use the PHP tool to generate as set of seed user data. He also shows how to create a DatabaseSeeder class for Laravel and integrate it with the tool.

In a new post to PHPMaster.com today, Rakhitha Nimesh takes a look at Faker, a tool that can be used to generate random test case data as a part of your workflow.

Testing is an iterative part of the development process that we carry out to ensure the quality of our code. A large portion of this entails writing test cases and testing each unit of our application using random test data. Actual data for our application comes in when we release it to production, but during the development process we need fake data similar to real data for testing purposes. The popular open source library Faker provides us with the ability to generate different data suitable for a wide range of scenarios.

Faker uses built-in data providers like "Person", "Company", "DateTime" and "UserAgent" to give you randomized output from the data sets you define. Code is included showing how to create the provider in your objects, extending the correct provider and making a request for a property. A real-world example is also included about testing an email marketing engine for address, title, name and content. There's also a little bit added at the end showing how you can increase the randomness of the results returned by "seeding" the Faker engine.