Google Sheets does not have a built in way of converting time zone data but by using the power of Moment.js and Google’s script editor we can add time zone functionality to any sheet.

First, we need to add the Moment.js code as a library that can be shared between different documents. This is the javascript library that adds date and time zone manipulation support. A good way to do this is to create it from Google Drive so it can be easily edited and shared with all your sheets.

In Google Drive, go to New > More > Connect more apps and choose Google Apps Script. Now, create a new Google Apps Script document. This will open the Google script editor. Call the project ‘Moment’ and create two files in the project called moment.js and moment-timezone.js using the moment and moment-timezone libraries. Make sure you choose one of the moment-timezone files with time zone data. You should end up with a project something like this:

To easily use this in multiple sheets we can publish it as a library. Go to File > Manage versions and save a new version. We are nearly finished here but before we move on go to File > Project properties and make a note of the project key, you will need this to refer to your library in your sheets.

In our test we are going to use our new library to convert times in a local time zone to UTC.

Create a new Google sheet and enter a date in A1 and a time zone in B1, like this:


Go to Tools > Script editor and create a project called Functions. In the script editor, go to Resources > Libraries and using the project key you made a note of before add your Moment library and select version 1. I prefer to use a shorter identifier like ‘m’. Click save and your library is now accessible to your sheet’s script. We can create a function to convert to UTC like this:

Save your project and you can now use this function in your sheets like this:


The ScalaTest + Play library provides a couple of useful traits for when your ScalaTest Play Framework functional tests need a running application for context. The OneAppPerSuite trait will share the same Application instance across all tests in a class whereas the OneAppPerTest trait gives each test its own Application instance.

These traits will ensure you have a running application for your tests but if you want to test code that operates on a database it can be helpful to load some known test data before each test and clean it up afterwards. For this, we can mix in a ScalaTest before-and-after trait.

The BeforeAndAfter trait lets you define a piece of code to run before each test with before and/or after each test with after. There is also a BeforeAndAfterAll trait which invokes methods before and after executing the suite but resetting the database for each test makes for better test isolation.

Here is a base test class that sets up a running application and uses the Evolutions companion object to load and clean up the database. Note this class uses Guice dependency injection to retrieve the database object but you can also easily connect to a database using the Database companion object.

We also override the db.default.url config value to point to a test database.

You can also load evolutions from the file system if you don’t want to define them in the code.

New for Ubuntu 16.04 (Xenial Xerus) is systemd which replaces Upstart as the default init system.

systemd basics

The basic object that systemd manages is the unit which can be of different types but when it comes to running our Play app we will need to create a service.

The systemctl command is used to manage systemd services, similar to the old service command. E.g. to start Nginx you now type:

Custom unit files should go in the /etc/systemd/system directory and you should always run the following command after creating new unit files or modifying existing ones:

Run levels have been replaced with systemd units called targets. Target unit files end with the .target file extension and they are used to group other units.

A Play Framework unit file

Here is a basic Play Framework systemd unit file. It makes use of the EnvironmentFile directive which can be used to set environment variables. It is possible to set environment variables in the unit file directly but using a separate file takes some of the clutter out.

Deploying the unit file

  • Create the env file in your app’s conf directory and unit file in  /etc/systemd/system
  • Set the file permissions

  • Reload systemd

You can now start and stop your play app using systemctl


One of the new features added to Java 8 is default methods. In previous versions of Java, adding a new method to an interface would break existing implementations. This made it very hard to evolve your public API without disrupting your clients. Java 8 now allows implementations of methods in an interface. This was needed because Java 8 introduced many new methods on existing interfaces such as sort in List or stream in Collection .

Thin versus rich interfaces

When creating an interface you face a trade-off in either making it rich or thin. A rich interface has many methods which makes it convenient for the caller while a thin interface has only a few methods which makes it easy to implement but not quite as useful for the caller.

Traditionally Java interfaces have been thin rather than rich. Scala, on the other hand, has traits which allow concrete implementations and so tend to be very rich. Now that Java 8 has default methods we can take the same rich interface approach in our Java code as Scala does with traits.

To create a rich interface, define a small number of abstract methods and a large number of concrete methods defined in terms of the abstract methods. Implementors of your interface need only implement the thin abstract part of your interface and thereby gain access to the richer part without having to write any more code.

An example

As a simple example I have implemented the Rational class and Ordered trait from the Programming in Scala book. We don’t get the symbolic method names and implicit conversions but the rich interface concept remains the same.

Here is our rich Ordered interface. It declares one abstract method compare but also implements a number of convenience methods in terms of this abstract method.

Here is our Rational class which implements Ordered. Apart from overriding equals and hashCode, the only method we need to implement is compare and we get lessThan, greaterThan, lessThanOrEqual, greaterThanOrEqual and compareTo “for free”.

Here’s a unit test that exercises the class.

This is a very simple example but shows how we can introduce Scala’s rich interface style of traits into our Java 8 code.

Checked exceptions are annoying. They are especially annoying when they may be thrown inside a lambda where they can really interrupt the flow.

What if you wanted to map a function over a list to collect values but a checked exception might get thrown in the process? In that case you don’t want the whole stream to stop executing but perhaps just log it and carry on with the next element.

Here’s how you might have done it with Java 7; if an exception is thrown we just log it and don’t add it to the output list.

With Java 8 we can use a combination of flatMap and empty streams to effectively filter out all the items that threw an exception.

Those elements that were successful will be wrapped in a stream and those that threw an exception will return an empty stream. The call to  flatMap  will throw away all the empty streams and leave you with a stream of “unwrapped” values to be collected.