Sunday, March 4, 2018

Compiling Cargo crates natively with Meson

Recently we have been having discussions about how Rust and Meson should work together, especially for mixed language projects. One thing which multiple people have told me (over a time span of several years, actually) is that Rust is Special in that everyone uses crates for everything. Thus there is no point in having any sort of Rust support, the only true way is to blindly call Cargo and have it do everything exactly the way it wants to.

This seems like a reasonable recommendation so I did what every reasonable person would do and accepted this as is.

David Addison wearing cardboard x-ray goggles with caption "This is me being completely reasonable".

But then curiosity takes hold of you and you start to wonder. Is that really the case?

Converting Cargo manifests to Meson projects

The basic setup of a Cargo project is fairly straightforward. The file format is mostly declarative and most crates are simple libraries that have a few source files and a bunch of other crates they link against. Meson has the same primitives, so could they be automatically converted.

It turns out that for simple examples you can. Here is a sample repo that downloads the Itoa crate from github, converts the Cargo build definition into a Meson project and builds it as a subproject (with Meson, not Cargo) of the main project that uses it. This prototype turned out to require 71 lines of Python.

What about dependencies other than itoa?

The script currently only works for itoa, because crates.io does not seem to provide a web API for queries and the entire site is created with JavaScript so you can't even do web scraping easily. To get this working properly the only thing you'd need is a function to get from (crate name, version) to the git repo.

What about dependencies of dependencies?

They can be easily grabbed from Cargo.toml file. Combined with the above they could be downloaded and converted in the same fashion.

What doesn't work?

A lot. Unit tests are not built nor run, but they could be added fairly easily. This would require adding compile options so the actual source could be built with the unittest flags. This is some amount of work but Meson already supports a similar feature for D so adding it should not be a huge amount of work. Similarly docs are not generated.

What about build.rs?

Cargo provides a fairly simple project model and everything more complex should be handled by writing a build.rs program that does everything else necessary. This suffers from the same disadvantages as every Turing complete build system ever has, and these scripts are not in general possible to convert automatically.

However based on documentation the common case seems to be to call into external build tools to build dependency libraries in other languages. In a build system that builds both parts at the same time it would be possible to create a better UX for this (but again would obviously not be something you can convert automatically).

Could this actually work in practice with real world projects?

It might. It might not. Ignoring the previous segment no immediate showstopper has presented itself thus far. It might in the future. But you never know until you try.

Thursday, March 1, 2018

On the unoptimalities of language specific build systems

A fairly big recent trend has been the emergence of new programming languages that are meant to be compiled into machine code. The silent (and sometimes not so silent) goal of these languages has been to replace C and C++ as the dominant systems programming language.

All of these languages come with their own build system and dependency management optimised for that particular language. This makes sense as having a good developer experience is important and not having 20-30 years of legacy to carry with you means you can design and develop slick systems relatively easily. But, as always, there is a downside. Perhaps the main issue comes up pretty quickly when trying to combine said code with projects in other languages.

A common approach is for the programming language in question to bundle up all its dependencies as source in a big clump. Then the advocates will say that "it's simple, just call our build system from yours and it gets built". This seems simple but it uses the weasieliest of all weasel words: just. Whenever someone tells you to "just" do something, what they almost always do is trying to trivialise away the hardest part of the entire operation. So it is here as well.

When could it work?

There is one case where this approach works without problems. That is when the dependency builds into a single library with a C interface and it also ships the header and a pkg-config file to use it. This case is indistinguishable from a plain C library so it will work exactly the same. The dependency can be provided as a system package or built as a dependency in a Flatpak manifest or any other similar issue.

Unfortunately this system breaks down the second you want to do anything else. The most common requirement is to build all dependencies from source in a single build step. This is necessary on any platform that does not have a concept of "system" package manager. Many people also want to do this on Linux systems to, for example, build their project's trunk against their dependencies' trunks. This is where things fall down.

The myth of the build dir

Most people probably haven't thought about the build directory of their builds. The most common conception is that the build system just (there's that word again) compiles source code into object files and then targets and that the installation step merely copies the files out to the staging directory. This is not true in the slightest.

Build systems need to do a whole lot of stuff to make things workable directly from the build tree. Every build system does it slightly (and sometimes massively) differently. More importantly the way each build system does it is not stable. They are allowed to, and will, change the way the build tree is laid out at any time. Nothing inside the build tree is stable, not file formats, not directory layouts, nothing.

The problem with building source code with two different build systems in a single build is that eventually they need to work together. Libraries need to be linked. Sources need to be generated. Executables need to be run. That means joining two different completely unstable elements together. The simplest problem in this space is about file layouts. Every build system expects a certain layout for the files it manages. This is usually very different from other build systems. Thus in order to work, there would need to be a way for every build system to be told to adapt to a different system's file layout when run as its subtask.

This is a challenging place to be requesting, because it takes a lot menial work that build systems have traditionally (ever, actually) been unwilling to do. Guessing the subtask's layout and hoping that it does not change might work for any amount of time and then breaks for the slightest of reasons. The problems only get harder from there.

N^2 manual work algorithms are awesome!

Even if this would work (and it does not) the next problem comes from scaling up. You can only "just call" from one build system to another if someone has taken the time to make one understand the other. This is simple for two build systems: you need to write two integrations, one in each direction. But suppose we live in a world where many of the common C libraries in use today have been replaced by implementations in another languages. If you were doing cross platform mobile development then you could have C, C++, Java, D, Rust, Go and Swift in the same project.

Seven languages means seven different build systems and possibly more since C and C++ commonly have more than one dominant build system. This means reading and understanding seven different build system syntaxes and mental models. If you want to combine those freely it means writing 7 x 7 = 49 different build system integrations who must, lest it be forgotten, combine the unstable innards of all of these. And then it gets worse.

Since every language has its own package manager and dependency downloader, you now have up to seven package managers in your project. Actually no, that is a lie.

The tangled web of lies and deceit dependencies

When talking about dependencies between projects in different languages, most people usually mean a dependency graph like this.

That is, there is one dependency of a single language and a second one of a different language that uses it. For this simple case most things are feasible. But let's see what happens when we add just one more project.

Here we have project 1 using language 1. It has a dependency to project 2 in language 2. However project 2 has an internal dependency on project 3 which is also written in language 1. The question now becomes: how should this be built?

Since languages 1 and 2 use their own build tool and language manager, the two edgemost projects don't know that they are being built as part of the same project. Language 2 completely hides its dependency, as it should. The two projects need to work independently. This means that each one of them must determine its dependencies in isolation. If they download their dependencies during configuration time then for each build setup you are accessing the dependency provider twice. Doing more dependency resolutions than you have languages in your project seems suboptimal.

The other approach to this is usually called vendoring. In this each project in a language is only used as a tarball and it embeds all its own dependencies as source code. This seems like a working solution but it's not really. Many modern languages go the NPM route where it is considered good practice to have many small dependencies. It is not uncommon for medium or even small projects to have 50+ dependencies. This leads to problems such as these:


Here project 1 depends on two different projects that are both implemented in language 1. Just like above these two projects don't know of each other because their dependency chain goes via language 2 that hides it. Both of these projects have their internal dependencies embedded so they can be built from scratch without problems.

The problem here is that due to basic popularity and probability theory, the embedded dependencies of these two projects have many of the same dependencies. The dependencies might have the same versions or they might differ. If they both end up in the toplevel executable you get, depending on your toolchain and the phase of the moon, either a working binary or the nastiest of linker bugs to fix.

Even if this yields a working program there is a big downside: compilation time takes up to twice as long because you have to compile the same dependencies twice in different but isolated parts of the build tree. As a rough approximation this means that adding a dependency to a dependency graph like this goes from being a O(1) more work to being O(N) more work because dependency graphs can not be deduplicated if there is a dependency of a different language between the two. It is left as an exercise to the reader to visualize what this would look like on a huge project such as Chromium.

The simple solution

There is a simple solution to this problem and it is very popular among language zealots: reducing the number of languages to one by claiming that in the future everything will be written in their own favourite language. It does not matter what the growth rate of complexity is if it will only be evaluated for the value 1.

The reduction of programming languages to one is expected to happen any minute now, immediately after mr Godot brings us the news on Eastasia's surrender.

The real problem

All of this boils down to the fact that language specific build systems are two opposing things at the same time. They are both a very comfortable gilded cage and an extremely isolating silo. They fertilise and promote cooperation within their own group but make things a lot harder for cooperation between groups.

One of the things we learn from history is that people who have opposed cooperation have, ultimately, lost to those who have promoted it. Maybe we should heed the teachings of history and start working towards better, more encompassing dependency management.

Monday, February 19, 2018

Projects and features Meson could use help with

A question I was asked during my LCA2018 presentation was how people could help the Meson project. I could not come up with proper projects off the cuff, so here are a bunch of things that have come up since. Feel free to contact us via IRC, email or any other medium if you wish to contribute.

WrapDB wrangler

WrapDB provides a simple way to download source dependencies automatically. Basically it takes an upstream release tarball, adds Meson build files to it if needed and publishes the result on the web. The work consists mostly of reviewing and merging submissions from the community. Creating your own is also fine. This is a fairly lightweight task, only requiring actions every now and then (submissions come less than once a week, typically).

CI fixer upper

For CI we use the free tiers of Travis and Appveyor. This works fairly well but it is very slow because our testing matrix is huge. Running the full test suite through AppVeyor takes about an hour. This slows us down a fair bit and in addition both CI providers have a nasty habit of breaking down fairly often. We also don't want to do priced tiers because they get ridiculously expensive for our usage pattern (as in, a few months of paid for macOS would cost more than a brand new Mac Mini).

We don't have any good ideas on how to make this better. If you do, let us know.

Large scale regression tester

Meson is being used by a fairly large number of projects. This makes fixing bugs and refactoring code challenging because there is the possibility of regressions. It would be nice if we could do something similar to Rust developers and rebuild all or a large fraction of projects using Meson with the trunk version every now and then.

XCode backend improvements

The XCode backend is currently a bit crappy. The main reason for this is that the XCode project file format is awful in many ways. The two main reasons being that it is completely undocumented and the fact that it is not really a file format as such, but more of a memory dump of XCode's internal data structures. But if you are the sort of person who enjoys a challenge of battling against windmills, this might be for you.

Meson build file rewriter

Integration with IDEs and the like is important and we want to provide tools for operations such as "add source file X to target Y" so everyone does not have to write their own implementations. There is actually code for this in trunk but it is quite limited and has bitrotted a fair bit. Resurrecting and making the code actually work would be very welcome.

Introspect improvements

This one also aims to improve the IDE integration features of Meson. As an example you can only get information about build targets one by one. This means that getting the information from a project that has thousands of targets takes forever. We really need a batch exporter so IDEs can grab all necessary project information in one go. There are probably a bunch of other things to improve as well.

Could these be done as part of gsoc/outreachy/other?

Possibly. Meson is not really an "entity" in the gsoc sense but we could potentially get something accepted under the Gnome umbrella. However anyone is welcome to submit patches, obviously, and several of the topics listed above are not nicely self-contained projects that would fit in the gsoc mold at all.

Friday, February 16, 2018

Automatically finding slow headers in C++ projects

A common problem in older C++ codebases is that sources compile slowly due to massive header includes. Headers include other headers, which include even more headers and then, somewhere in the guts of the system, someone includes a header that is very slow to parse. Now things are slow and nobody really knows why.

Trawling through the header soup manually is not feasible. Even if you were to manually inspect the headers, it is difficult to know which are the slow ones. Educated guesses can be made, such as anything having the word "boost" in its name is slow, but this only gets you so far. Fortunately it turns out that it is fairly straightforward to write a tool to find the slow ones automatically.

We need two things to be able to reliably measure the inclusion time breakdown of the headers of any source file.

  1. The transitive list of all header files it includes.
  2. The exact compiler flags used to compile the source.
The former can be obtained from a dependency file that the compiler can be told to generate during compilation (and which almost all modern build systems use by default). The latter can be obtained from the compilation_commands database which is also generated by most build tools today. The actual algorithm is simple: for each dependency header, create a dummy cpp file that just #includes that header, compile the source and measure the time it took.

I created a repo with the measurement script and a sample project to test it on. It has one source file and a few internal headers that include external headers. Here's the top part of its output:

0.5875 ../h1.h
0.5254 /usr/include/c++/7/regex
0.2779 /usr/include/c++/7/shared_mutex
0.2747 /usr/include/c++/7/condition_variable
0.2685 ../h2.h
0.2563 /usr/include/c++/7/locale
0.2445 /usr/include/c++/7/sstream
0.2337 ../h3.h
0.2330 /usr/include/c++/7/iostream
0.2329 /usr/include/c++/7/istream

Iostream has been traditionally considered to be big, bloated and slow to compile. However in this simple example we find that shared_mutex is even slower.

There are, of course, many caveats with this method. The main one being that this does not measure the code generation time, only parsing time. These two are usually highly correlated, though.

Thursday, February 15, 2018

Meson's dependency manager in action building GTK

One of the greatest things about creating software is seeing other people pick it up and run with it. Here is a great example of GTK's new development experience using Meson subprojects to automatically obtain dependencies.

It is easy to see how this makes it easier for newcomers to participate. There are no longer pages upon pages of instructions on how to set up a build environment and so on. All that is required is to clone one Git repo and start building. The build system will take care of all the rest.

The eventual goal is to be able to build the entire stack fully from scratch on any platform, even Windows with the Visual Studio compiler. Unfortunately there are still a few missing features but we'll get them added at some point.

Friday, February 9, 2018

Looking inside a Linux powered slot machine

In my day job I work as a consultant. This means that I get to see all kinds of interesting things. One of them is this piece of hardware here:


This is a slot machine as operated by Veikkaus, which is the state run corporation operating all gambling services in Finland. There are roughly 20 000 slot machines in use in Finland currently. This is interesting on its own, but things get really fun when you look on the inside.


A fair fraction of the insides is taken by machinery that deals with coins. When a coin is inserted in the machine it first goes in the coin acceptor, which is marked with a green box in the image. It detects the type of the coin. Each denomination has its own exit chute. Bad coins are rejected from the machine while sorted coins get passed into coin hoppers (marked in red).

A coin hopper is basically a bowl of coins and a mechanism that is cabable of ejecting coins from it one by one. When you think of slot machines, you are probably thinking of the sound they make when start spitting out tons of coins after a jackpot. Coin hoppers are what create that particular sound. I recommend looking up videos on Youtube if you are interested in mechanical engineering, because the way they work is kind of fascinating.

The slot machine also accepts notes and debit card payments but these are mechanically much simpler and don't take much space. The only thing remaining in the picture is the box marked in yellow. It contains the actual brains of the entire machine.

The contents of the brain

The main system is, much like everything these days, a regular computer. This specific one is a fairly average industrial PC that is running a custom version of Debian. At boot it starts up the game software that is based on a custom version of the Ogre 3D graphics engine. The computer also manages and controls all other hardware in the cabinet, such as the coin hoppers and note acceptor mentioned above, using a custom, self designed controller board. The cabinet housing the device is also custom designed and built.

Thus, surprisingly, at its core a slot machine is roughly the same as a desktop PC running desktop games with a few extra peripherals. This means is that Linux desktop gaming has been mainstream among the general Finnish population for 15 years, which is roughly the amount of time these slot machines have been deployed.

In addition to the games themselves, the development environment is also 100% Linux. As a demonstration, here is a screen shot of a development version of the software running on a developer workstation.

What about the money?

Like all forms of gambling, slot machines make quite a lot of money. The yearly profits, as of last count, were on the order of 500 million euros per year. As Veikkaus is a government run business, this money is given out to various charitable organisations as well as to the state. Given that Finland's yearly budget is on the order of 50 billion euros, this means that profits from Linux desktop gaming account for almost 1% of the entire budget of the state of Finland.

Acknowledgements

Thanks to Veikkaus for giving me permission to write this blog post. Extra special thanks for allowing to show the picture of the insides of a slot machine, which has never before been shown in public.

Sunday, December 31, 2017

These three things could improve the Linux development experience dramatically, #2 will surprise you

The development experience on a modern Linux system is fairly good, however there are several strange things, mostly due to legacy things no longer relevant, that cause weird bugs, hassles and other problems. Here are three suggestions for improvement:

1. Get rid of global state

There is a surprisingly large amount of global (mutable) state everywhere. There are also many places where said global state is altered in secret. As an example let's look at pkg-config files. If you have installed some package in a temporary location and request its linker flags with pkg-config --libs foo, you get out something like this:

-L/opt/lib -lfoo

The semantic meaning of these flags is "link against libfoo.so that is in /opt/lib". But that is not what these flags do. What they actually mean is "add /opt/lib to the global link library search path, then search for foo in all search paths". This has two problems. First of all, the linker might, or might not, use the library file in /opt/lib. Depending on other linker flags, it might find it somewhere else. But the bigger problem is that the -L option remains in effect after this. Any library search later might pick up libraries in /opt/lib that it should not have. Most of the time things work. Every now and then they break. This is what happens when you fiddle with global state.

The fix to this is fairly simple and requires only changing the pkg-config file generator so it outputs the following for --libs foo:

/opt/lib/libfoo.so

2. Get rid of -lm, -pthread et al

Back when C was first created, libc had very little functionality in it. Because of reasons, new functionality was added it went to its own library that you could then enable with a linker flag. Examples include -lm to add the math library and -ldl to get dlopen and friends. Similarly when threads appeared, each compiler had its own way of enabling them, and eventually any compiler not using -pthread died out.

If you look at the compiler flags in most projects there are a ton of gymnastics for adding all these flags not only to compiler flags but also to things like .pc files. And then there is code to take these flags out again when e.g. compiling on Visual Studio. And don't even get me started on related things like ltdl.

All of this is just pointless busywork. There is no reason all these could not be in libc proper and available and used always. It is unlikely that math libraries or threads are going to go away any time soon. In fact this has already been done in pretty much any library that is not glibc. VS has these by default, as does OSX, the BSDs and even alternative Linux libcs. The good thing is that Glibc maintainers are already in the process of doing this transition. Soon all of this pointless flag juggling will go away.

3. Get rid of 70s memory optimizations

Let's assume you are building an executable and that your project has two internal helper libraries. First you do this:

gcc -o myexe myexe.o lib1.a lib2.a

This gives you a linker error due to lib2 missing some symbols that are in lib1. To fix this you try:

gcc -o myexe myexe.o lib2.a lib1.a

But now you get missing symbols in lib1. The helper libraries have a circular dependency so you need to do this:

gcc -o myexe myexe.o lib1.a lib2.a lib1.a

Yes, you do need to define lib1 twice. The reason for this lies in the fact that in the 70s memory was limited. The linker goes through the libraries one by one. When it process a static library, it copies all symbols that are listed as missing and then throws away the rest. Thus if lib2 requires any symbol that myexe.o did not refer to, tough luck, all those symbols are gone. The only way to access them is to add lib1 to the linker line and have it processed in full for a second time.

This simple issue can be fixed by hand but things get more complicated if the come from external dependencies. The correct fix for this would be to change the linker to behave roughly like this:
  • Go through the entire linker line and find all libraries.
  • Look which point to same physical files and deduplicate them
  • Wrap all of these in a single -Wl,--start-group -Wl,--end-group
  • Do symbol lookup once in a global context
This is a fair bit of work and may cause some breakage. On the other hand we do know that this works because many linkers already do this, for example Visual Studio and LLVM's new lld linker.