Blog

SciTech links (November 4 2017)

China wants to be the first country to build a practical space-based solar power station. Space-based solar power would presumably be much more sustainable and clean than fossil fuels and more efficient than the current sustainable energy sources we have on Earth. There are many problems still to be solved before these power plants can exist so China’s expectations are more wishful thinking than based on reality.

Astronomers have found a massive gas-giant that is astonishingly 23.9% as massive as the star it orbits. For comparison, Jupiter is the largest planet in our solar system but its mass is only 0.09% of that of the Sun.

An interesting article about an accident involving a Minuteman I nuclear missile 53 years ago. A short-circuit caused one of the retrorockets to fire and as a result the cone containing the nuclear warhead detached and fell into the silo. Ultimately the warhead casing was intact and nothing more serious happened, but the story reminded me of the Damascus Incident in which a fuel leak on the Titan caused a major accident. Eric Schlosser’s book, Command and Control: Nuclear Weapons, the Damascus Accident, and the Illusion of Safety, is a fantastic tale of this and other “broken arrow” incidents.

Science and tech links (October 21, 2017)

Rodney Brooks writes about the 7 Deadly Sins of AI Predictions. The text articulates a lot of my personal doubts about much of what I see on the news regarding AI. Some people seemed to read this article as a rebutal of AI itself, which I find puzzling as I did not read that at all. If anything, Brooks seems to believe AI will be much bigger than we can possible imagine. He does talk about predictions being flawed. I can’t argue with that.

The Canadian Space Agency is worried about Canada’s vulnerability to solar flares and the like. As a first step, it has published a request for proposals to run studies on the effects of space weather events on the Canadian infrastructure (PDF). The study won’t focus only on cataclysmic scenarios but also at more-routine effects of space weather, like solar wind, flares that affect radio frequencies, radiation storms that send particles towards us and geomagnetic storms that can disrupt satellite systems and other technologies. If you know me, you’ll know a solar flare frying the electrical grid is my nightmare scenario.

After six years in service, the first Chinese space station, Tiangong 1,
is set to fall back to earth sometime in the next few months. Still not clear exactly when, it should happen late this year or early 2018. I’d love to get my hand at a piece of that. As a space exploration geek, I find it incredibly sad that the Chinese space program is relatively secret. I’d love to know more.

Caddy and the Importance of Licenses

I haven’t commented on the recent brouhaha caused by Caddy‘s decision to offer commercial licences, so I’ll do it briefly here before moving to the important part.

I am fine with it. I don’t love it, but it’s fine. The Caddy authors have every right to try to profit from their work. Best of luck to them, they deserve it. Do I think they mangled the announcement? Yes. Do I think the amount of vitriol out there was justified? No. But again, it’s fine.

But I want to talk about something else and I’ll use this episode to illustrate it. Matt Holt published his thoughts on the experience in The Realities of Being a FOSS Maintainer. It’s a nice read, but there is something there that I think we should not overlook.

Midway through Matt’s post, he clarifies the situation with their build server, that they removed[note]Most likely made private[/note] from Github.

To clarify, the Caddy build server was once open source, but we closed it up in the interest of focusing the technical attention of our community and our limited development resources (mostly time) on Caddy itself. The build server is not generalizable, and only exists to serve the Caddy project. As such, we’re taking it under our wings to develop and maintain it as needed. If you find some old source code still online, be aware that no license file was added to the code, and we have not granted others any license to use it.

This highlights the importance of checking the license of “FOSS” software. Being open source means something. It doesn’t just mean “hosted on Github.” Just because you find a piece of code on Github, it doesn’t mean you can freely use it. It sucks, but as the above paragraph shows, it matters.

What Matt is saying here is that although his build server was open source, it no longer is and if you have the code, you were never granted any license to use it. This cannot be, of course. Either it was never open source to begin with, or you were granted a license to use it. Which one is it?

Since Matt makes it clear that “no license file was added to the code,” that means it’s the former: it was never open source, no matter what he says now. Whether intentionally or not, people were misled into thinking it was.

People would find the code on Github and assume it was open source. That’s why checking the license is important. A project without a license is not open source and you are at risk.

I’ve seen small projects on Github before with no license information at all. It always made me uncomfortable. Now I see I was right.

I want to make clear this is not about Caddy or Matt. Again, I’m fine with their decision. My points are general:

  • Properly license your open source software.
  • Check the license of software you use.

If you don’t, this will get back to bite you.

Returns in Go and C#

Whenever someone posts anything related to the Go programming language on Hacker News, it never takes long before someone complains about error handling. I find it interesting because it is exactly one of things I like the most about Go.

I don’t want to specifically talk about error handling though. I want to talk about a feature that is intrinsically tied to it in Go: the ability of functions to return multiple values

For instance, in Go it is common and idiomatic to write functions like this —

func Divide(a, b float64) (float64, error) {
    if b == 0 {
        return 0.0, errors.New("divide by zero")
    }
    return a / b, nil
}

So the caller would do:

result, err := Divide(x, y)
if err != nil {
    // do error handling...
}

Some people deplore this. I absolutely love it. I find it so much clearer than, for instance, what we often have to do in C#. You see, C# didn’t have multiple returns (until very recently; see below) so you ended up with a few options.

First, you can simple throw exceptions.

public SomeObject GetObjectById(int id) {
    if (!SomeObjectRepo.Has(id))
        throw new ArgumentOutOfRangeException(nameof(id));
    // ...
}
...
try
{
    var obj = GetObjectById(1);
    // do something with obj
}
catch (ArgumentOutOfRangeException ex)
{
    //  error handling
}

I find the flow difficult to read. Particularly because variables are scoped within the try-catch so often you need to first declare something above the try and then test it after the catch.

A second option is to return null:

public SomeObject GetObjectById(int id)
{
    if (!SomeObjectRepo.Has(id))
        return null;

    // go get the object
}
...
var obj = GetObjectById(1);
if (obj == null) 
{
    // do error handling
}

This looks closer to what I like but it still has some serious downsides. You don’t get any error information. What made it fail? I don’t know. As well, this doesn’t work for non-nullable types. A method returning a, say, int cannot return null. Sure, you could return int? instead of int and then test for .HasValue but that’s cumbersome and artificial.

A third option is the use of a generic return type. Something like —

public class Result<T>
{
    public T Value {get;protected set;}
    public Exception Exception {get; protected set;}

    public bool IsError => Exception != null;

    public Result() : this(default(T)) {}
    public Result(T value)
    {
        Value = value;
    }

    public static Result<T> MakeError(Exception exception)
    {
        return new Result<T>
        {
            Value = default(T),
            Exception = exception
        };
    }
}

You could then use this to return values like —

public Result<int> Divide(int a, int b)
{
    if (b == 0)
    {
        return Result<int>.MakeError(new DivideByZeroException());
    }

    return new Result<int>(a / b);
}
...
var res = Divide(8, 4);
if (res.IsError)
{
    // do error handling, e.g.
    throw res.Exception;
}
// do something with res.Value (2)

This works, but it looks artificial. You need to create instances of Result<T> all around all the time. It is not that bad if your codebase uses this throughout and it becomes automatic for all programmers envolved. When it’s an exception to the rule, it is horrible.

A very similar solution is to return something like Tuple<T1, T2, ...>

public Tuple<int,Exception> Divide(int a, int b)
{
    if (b == 0)
        return new Tuple<int,Exception>(0, new DivideByZeroException());
    return new Tuple<int,Exception>(a/b, null);
}
...
var res = Divide(1, 2);
if (res.Item2 != null) // Item2 is the exception
{
    // do error handling
}
// do something with res.Item1

Same principle. It’s ugly and artificial, but it will come back to us.

The way the C# authors found to work around this problem is the idiomatic try-pattern, which consists in creating non-exception-throwing versions of methods. For example, if we go back to the first C# example above (GetObjectById()), we could create a second method like so —

public bool TryGetObjectById(int id, out SomeObject result) {
    try 
    {
        result = GetObjectById(id);
        return true;
    }
    catch
    {
        result = default(SomeObject);
        return false;
    }
}
...
SomeObject result;
if (!TryGetObjectById(1, out result))
{
    // do error handling
}
// do something with result

Note that ever since C# 7.0 you can declare the out variable directly inside the method call as such —

if (!TryGetObjectById(1, out var result))

Which spares you of declaring your out variables arguably at the expense of clarity.

This method is idiomatic and found everywhere in the .NET Framework. I actually like it but it still has the problem of losing important information, namely what caused the method to fail: all you get is true or false.

In C# 7.0, the language authors came up with a new solution: they added syntactic sugar to the language to make the tuple solution a bit more appealing —

public (int, Exception) Divide(int a, int b)
{
    if (b == 0)
        return (0, new DivideByZeroException());

    return (a / b, null);
}
...
var (res, err) = Divide(1, 2);
if (err != null) 
{
    // do error handling
}

Suddenly this becomes very familiar to a Go programmer. In the background, this is using a tuple. In fact, you can check that this is so by using the method above like this —

var res = Divide(1, 2);
if (res.Item2 != null)
    // do error handling
// use res.Item1

You will see that res is of type System.ValueTuple. Also, if you create a library in C# 7.0 and then try to use it with a program in older versions of C#, you will see that the exposed type of the method is a tuple. This is actually nice because it means this big language change is backwards compatible.

All that said, I haven’t seen many uses of the new tuple returns in C# code in the wild. Maybe it’s just early (C# 7.0 has been out for only a few months.) Or maybe the try-pattern is simply way too ingrained in the way of doing things in C#. It’s more idiomatic.

I sure prefer the new (Go-like) way.

Happy Birthday Canada

My adopted country is celebrating its 150th anniversary today. I want to say that I feel privileged to be here for it. This is where my family and I decided to make our home.

Happy birthday, bonne fête, Canada! Merci de tout! 🇨🇦