Category Archives: Programming

Never start a goroutine without knowing how it will stop

In Go, goroutines are cheap to create and efficient to schedule. The Go runtime has been written for programs with tens of thousands of goroutines as the norm, hundreds of thousands are not unexpected. But goroutines do have a finite cost in terms of memory footprint; you cannot create an infinite number of them.

Every time you use the go keyword in your program to launch a goroutine, you must know how, and when, that goroutine will exit. If you don’t know the answer, that’s a potential memory leak.

Consider this trivial code snippet:

ch := somefunction()
go func() {
        for range ch { }

This code obtains a channel of int from somefunction and starts a goroutine to drain it. When will this goroutine exit? It will only exit when ch is closed. When will that occur? It’s hard to say, ch is returned by somefunction. So, depending on the state of somefunction, ch might never be closed, causing the goroutine to quietly leak.

In your design, some goroutines may run until the program exits, for example a background goroutine watching a configuration file, or the main conn.Accept loop in your server. However, these goroutines are rare enough I don’t consider them an exception to this rule.

Every time you write the statement go in a program, you should consider the question of how, and under what conditions, the goroutine you are about to start, will end.

Thinking about $GOPATH

This is a short blog post about my thoughts on using Go in anger through several workplaces, as a developer and an advocate.

What is $GOPATH?

Back when Go was first announced we used Makefiles to compile Go code. These Makefiles referenced some shared logic stored in the Go distribution. This is where $GOROOT comes from.

Back then, if you wrote Go code, you’d probably also used these Makefiles, and while you could check out your source code anywhere, most people would put their own Go code in what today we’d call $GOROOT/src as you must’ve compiled Go from source, so this directory was always going to be present.

Towards the 1.0 release goinstall, then go get, solidified the use of domain names in import paths to provide a globally unique namespace. These tools introduced a new location into which Go code would be fetched. This location was separate from $GOROOT to make clear the distinction between code provided by the Go project, and code written by the developer. By the time Go 1.1 was released in 2013, $GOROOT was removed as a fallback option.

Why does $GOPATH exist?

$GOPATH exists for two main reasons:

  1. In Go, the import declaration references a package via its fully qualified import path. $GOPATH exist so that from any directory inside $GOPATH/src the go tool can compute the absolute import path of the package in question.1
  2. A location to store dependencies fetched by go get.

Having a per user $GOPATH environment variable also means developers could use the go tool from any directory on their system to build, test and install code, but I suspect only a minority utilise this feature.

What’s wrong with $GOPATH?

In my experience, many newcomers to Go are frustrated with the single workspace $GOPATH model. They are confused that $GOPATH doesn’t let them check out the source of a project in a directory of their choice like they are used to with other languages. Additionally, $GOPATH does not let the developer have more than one copy of a project (or its dependencies)  checked out at the same time without having to update $GOPATH constantly.

I think it is important to recognise that these issues are legitimate points of confusion for many newcomers (including those on the Go team) and act as a drag on Go adoption. As we’re on the cusp of a blessed dependency management tool for Go, I think it’s equally important to continue to question the base assumptions that this new tool will build on, namely requiring a $GOPATH.

In my opinion, any Go build tool needs to provide (in addition to actually building and testing code) a way for Go code checked out in an arbitrary location on disk to recover its intended fully qualified import path; the path other code will import it as.

The $GOPATH model answers this question by subtracting the prefix of $GOPATH/src from the path to the directory of the current package; the remainder is the package’s fully qualified import path. This is why if you check out a package outside a $GOPATH workspace, the go tool cannot figure out the packages’ fully qualified import path and everything falls apart.

What are some alternatives to $GOPATH?

I attempted to address both issues with gb, which gives developers the ability to check out a project anywhere you want, but has no solution for libraries, and gb projects were not go gettable. However gb showed that writing a new build tool that did not wrap the go tool meant it was not forced to reorganise the world to fit into the $GOPATH model allowing gb users to include the source of all their dependencies in their project without the pitfalls of the Go 1.6’s vendor/ directory.

Recently, on a suggestion from Bill Kennedy, I built an experimental build tool that recorded the expected import prefix in a manifest file. That prefix, rather than one computed by $GOPATH directory arithmetic, is used to determine the fully qualified import path.

I’m working on a similar tool (unfinished) based on a suggestion from Brad Fitzpatrick that uses the .git directory as a sentinel to determine the root of the project and hopefully infer the full import path from the git remote configuration.

While these experiments are unfinished, both demonstrate that you can avoid the $GOPATH restrictions and retain compatibility with the go get ecosystem. Potentially in the case of Kodos, even avoid a manifest file.


Kang and Kodos use a lot of forked code from gb, which I hope to rectify over the new years’ break. If you are interesting in contributing or better yet, building your own Go tool to explore this problem space, Kang, Kodos, and gb are permissively licensed.


  1. This is notably different from the way imports work in scripting languages like Python and Ruby, which use directly scanning and inserting onto a global search path source code directories.

Declaration scopes in Go

This post is about declaration scopes and shadowing in Go.

package main

import "fmt"

func f(x int) {
	for x := 0; x < 10; x++ {

var x int

func main() {
	var x = 200

This program declares x four times. All four are different variables because they exist in different scopes.

package main

import "fmt"

func f() {
	x := 200
	fmt.Println("inside f: x =", x)

func main() {
	x := 100
	fmt.Println("inside main: x =", x)
	fmt.Println("inside main: x =", x)

In Go the scope of a declaration is bound to the closest pair of curly braces, { and }. In this example, we declare x to be 100 inside main, and 200 inside f.

What do you expect this program will print?

package main

import "fmt"

func main() {
	x := 100
	for i := 0; i < 5; i++ {
		x := i

There are several scopes in a Go program; block scope, function scope, file scope, package scope, and universe scope. Each scope encompasses the previous. What you are seeing is called shadowing.

var x = 100

func main() {
        var x = 200

Most developers are comfortable with a function scoped variable shadowing a package scoped variable.

func f() {
        var x = 99
        if x > 90 {
                x := 60

But a block scoped variable shadowing a function scoped variable may be surprising.

The justification for a declaration in one scope shadowing another is consistency, prohibiting just block scoped declarations from shadowing another scope, would be inconsistent.

Simulating minicomputers on microcontrollers

This is a short blog post to reference the slides from my builderscon 2016 presentation.

I had a great time at buildercon, the talks were varied and engaging from a wide selection of Japanese makers. I’m grateful to the builderscon organisers for accepting my talk and inviting me to present at the inaugural builderscon conference in Tokyo, Japan.


Further reading:

Go 1.8 toolchain improvements

This is a progress report on the Go toolchain improvements during the 1.8 development cycle.

Now we’re well into November, the 1.8 development window is closing fast on the few remaining in fly change lists, with the remainder being told to wait until the 1.9 development season opens when Go 1.8 ships in February 2017.

For more in this series, read my previous post on the Go 1.8 toolchain improvements from September, and my post on the improvements to the Go toolchain in the 1.7 development cycle.

Faster compilation

Since Go 1.5, released in August 2015, compile times have been significantly slower than Go 1.4. Work on addressing this slow down started in ernest in the Go 1.7 cycle, and is still ongoing.

Robert Griesemer and Matthew Dempsky’s worked on rewriting the parser to make it faster and remove many of the package level variables inherited from the previous yacc based parser. This parser produces a new abstract syntax tree while the rest of the compiler expects the previous yacc syntax tree. For 1.8 the new parser must transform its output into the previous syntax tree for consumption by the rest of the compiler. Even with this extra transformation step the new parser is no slower than the previous version and plans are being made to remove this transformation requirement in Go 1.9.

Compile time for full build relative to Go 1.4.3

Compile time for full build relative to Go 1.4.3

The take away is Go 1.8 is on target to improve compile times by an average of 15% over Go 1.7. Compared to the 3-5% improvements reported two months prior, it’s nice to know that there is still blood in this stone.

Note: The benchmark scripts for jujud, kube-controller-manager, and gogs are online. Please try them yourself and report your findings.

Code generation improvements

The big feature of the previous 1.7 cycle was the new SSA backend for 64 bit Intel. In Go 1.8 the SSA backend has been rolled out to all the other architectures that Go supports and the old backend code has been deleted.

amd64, by virtue of being the most popular production architecture, has always been the fastest. As I reported a few months ago, the results comparing Go 1.8 to Go 1.7 on Intel architectures show middling improvement driven equally by improvements to code generation, escape analysis improvements, and optimisations to the std library.

name                     old time/op    new time/op    delta
BinaryTree17-4              3.04s ± 1%     3.03s ± 0%     ~     (p=0.222 n=5+5)
Fannkuch11-4                3.27s ± 0%     3.39s ± 1%   +3.74%  (p=0.008 n=5+5)
FmtFprintfEmpty-4          60.0ns ± 3%    58.3ns ± 1%   -2.70%  (p=0.008 n=5+5)
FmtFprintfString-4          177ns ± 2%     164ns ± 2%   -7.47%  (p=0.008 n=5+5)
FmtFprintfInt-4             169ns ± 2%     157ns ± 1%   -7.22%  (p=0.008 n=5+5)
FmtFprintfIntInt-4          264ns ± 1%     243ns ± 1%   -8.10%  (p=0.008 n=5+5)
FmtFprintfPrefixedInt-4     254ns ± 2%     244ns ± 1%   -4.02%  (p=0.008 n=5+5)
FmtFprintfFloat-4           357ns ± 1%     348ns ± 2%   -2.35%  (p=0.032 n=5+5)
FmtManyArgs-4              1.10µs ± 1%    0.97µs ± 1%  -11.03%  (p=0.008 n=5+5)
GobDecode-4                9.85ms ± 1%    9.31ms ± 1%   -5.51%  (p=0.008 n=5+5)
GobEncode-4                8.75ms ± 1%    8.17ms ± 1%   -6.67%  (p=0.008 n=5+5)
Gzip-4                      282ms ± 0%     289ms ± 1%   +2.32%  (p=0.008 n=5+5)
Gunzip-4                   50.9ms ± 1%    51.7ms ± 0%   +1.67%  (p=0.008 n=5+5)
HTTPClientServer-4          195µs ± 1%     196µs ± 1%     ~     (p=0.095 n=5+5)
JSONEncode-4               21.6ms ± 6%    19.8ms ± 3%   -8.37%  (p=0.008 n=5+5)
JSONDecode-4               70.2ms ± 3%    71.0ms ± 1%     ~     (p=0.310 n=5+5)
Mandelbrot200-4            5.20ms ± 0%    4.73ms ± 1%   -9.05%  (p=0.008 n=5+5)
GoParse-4                  4.38ms ± 3%    4.28ms ± 2%     ~     (p=0.056 n=5+5)
RegexpMatchEasy0_32-4      96.7ns ± 2%    98.1ns ± 0%     ~     (p=0.127 n=5+5)
RegexpMatchEasy0_1K-4       311ns ± 1%     313ns ± 0%     ~     (p=0.214 n=5+5)
RegexpMatchEasy1_32-4      97.9ns ± 2%    89.8ns ± 2%   -8.33%  (p=0.008 n=5+5)
RegexpMatchEasy1_1K-4       519ns ± 0%     510ns ± 2%   -1.70%  (p=0.040 n=5+5)
RegexpMatchMedium_32-4      158ns ± 2%     146ns ± 0%   -7.71%  (p=0.016 n=5+4)
RegexpMatchMedium_1K-4     46.3µs ± 1%    47.8µs ± 2%   +3.12%  (p=0.008 n=5+5)
RegexpMatchHard_32-4       2.53µs ± 3%    2.46µs ± 0%   -2.91%  (p=0.008 n=5+5)
RegexpMatchHard_1K-4       76.1µs ± 0%    74.5µs ± 2%   -2.12%  (p=0.008 n=5+5)
Revcomp-4                   563ms ± 2%     531ms ± 1%   -5.78%  (p=0.008 n=5+5)
Template-4                 86.7ms ± 1%    82.2ms ± 1%   -5.16%  (p=0.008 n=5+5)
TimeParse-4                 433ns ± 3%     399ns ± 4%   -7.90%  (p=0.008 n=5+5)
TimeFormat-4                467ns ± 2%     430ns ± 1%   -7.76%  (p=0.008 n=5+5)

name                     old speed      new speed      delta
GobDecode-4              77.9MB/s ± 1%  82.5MB/s ± 1%   +5.84%  (p=0.008 n=5+5)
GobEncode-4              87.7MB/s ± 1%  94.0MB/s ± 1%   +7.15%  (p=0.008 n=5+5)
Gzip-4                   68.8MB/s ± 0%  67.2MB/s ± 1%   -2.27%  (p=0.008 n=5+5)
Gunzip-4                  381MB/s ± 1%   375MB/s ± 0%   -1.65%  (p=0.008 n=5+5)
JSONEncode-4             89.9MB/s ± 5%  98.1MB/s ± 3%   +9.11%  (p=0.008 n=5+5)
JSONDecode-4             27.6MB/s ± 3%  27.3MB/s ± 1%     ~     (p=0.310 n=5+5)
GoParse-4                13.2MB/s ± 3%  13.5MB/s ± 2%     ~     (p=0.056 n=5+5)
RegexpMatchEasy0_32-4     331MB/s ± 2%   326MB/s ± 0%     ~     (p=0.151 n=5+5)
RegexpMatchEasy0_1K-4    3.29GB/s ± 1%  3.27GB/s ± 0%     ~     (p=0.222 n=5+5)
RegexpMatchEasy1_32-4     327MB/s ± 2%   357MB/s ± 2%   +9.20%  (p=0.008 n=5+5)
RegexpMatchEasy1_1K-4    1.97GB/s ± 0%  2.01GB/s ± 2%   +1.76%  (p=0.032 n=5+5)
RegexpMatchMedium_32-4   6.31MB/s ± 2%  6.83MB/s ± 1%   +8.31%  (p=0.008 n=5+5)
RegexpMatchMedium_1K-4   22.1MB/s ± 1%  21.4MB/s ± 2%   -3.01%  (p=0.008 n=5+5)
RegexpMatchHard_32-4     12.6MB/s ± 3%  13.0MB/s ± 0%   +2.98%  (p=0.008 n=5+5)
RegexpMatchHard_1K-4     13.4MB/s ± 0%  13.7MB/s ± 2%   +2.19%  (p=0.008 n=5+5)
Revcomp-4                 451MB/s ± 2%   479MB/s ± 1%   +6.12%  (p=0.008 n=5+5)
Template-4               22.4MB/s ± 1%  23.6MB/s ± 1%   +5.43%  (p=0.008 n=5+5)

The big improvements from the switch to the SSA backend show up on non intel architectures. Here are the results for Arm64:

name                     old time/op    new time/op     delta
BinaryTree17-8              10.6s ± 0%       8.1s ± 1%  -23.62%  (p=0.016 n=4+5)
Fannkuch11-8                9.19s ± 0%      5.95s ± 0%  -35.27%  (p=0.008 n=5+5)
FmtFprintfEmpty-8           136ns ± 0%      118ns ± 1%  -13.53%  (p=0.008 n=5+5)
FmtFprintfString-8          472ns ± 1%      331ns ± 1%  -29.82%  (p=0.008 n=5+5)
FmtFprintfInt-8             388ns ± 3%      273ns ± 0%  -29.61%  (p=0.008 n=5+5)
FmtFprintfIntInt-8          640ns ± 2%      438ns ± 0%  -31.61%  (p=0.008 n=5+5)
FmtFprintfPrefixedInt-8     580ns ± 0%      423ns ± 0%  -27.09%  (p=0.008 n=5+5)
FmtFprintfFloat-8           823ns ± 0%      613ns ± 1%  -25.57%  (p=0.008 n=5+5)
FmtManyArgs-8              2.69µs ± 0%     1.96µs ± 0%  -27.12%  (p=0.016 n=4+5)
GobDecode-8                24.4ms ± 0%     17.3ms ± 0%  -28.88%  (p=0.008 n=5+5)
GobEncode-8                18.6ms ± 0%     15.1ms ± 1%  -18.65%  (p=0.008 n=5+5)
Gzip-8                      1.20s ± 0%      0.74s ± 0%  -38.02%  (p=0.008 n=5+5)
Gunzip-8                    190ms ± 0%      130ms ± 0%  -31.73%  (p=0.008 n=5+5)
HTTPClientServer-8          205µs ± 1%      166µs ± 2%  -19.27%  (p=0.008 n=5+5)
JSONEncode-8               50.7ms ± 0%     41.5ms ± 0%  -18.10%  (p=0.008 n=5+5)
JSONDecode-8                201ms ± 0%      155ms ± 1%  -22.93%  (p=0.008 n=5+5)
Mandelbrot200-8            13.0ms ± 0%     10.1ms ± 0%  -22.78%  (p=0.008 n=5+5)
GoParse-8                  11.4ms ± 0%      8.5ms ± 0%  -24.80%  (p=0.008 n=5+5)
RegexpMatchEasy0_32-8       271ns ± 0%      225ns ± 0%  -16.97%  (p=0.008 n=5+5)
RegexpMatchEasy0_1K-8      1.69µs ± 0%     1.92µs ± 0%  +13.42%  (p=0.008 n=5+5)
RegexpMatchEasy1_32-8       292ns ± 0%      255ns ± 0%  -12.60%  (p=0.000 n=4+5)
RegexpMatchEasy1_1K-8      2.20µs ± 0%     2.38µs ± 0%   +8.38%  (p=0.008 n=5+5)
RegexpMatchMedium_32-8      411ns ± 0%      360ns ± 0%  -12.41%  (p=0.000 n=5+4)
RegexpMatchMedium_1K-8      118µs ± 0%      104µs ± 0%  -12.07%  (p=0.008 n=5+5)
RegexpMatchHard_32-8       6.83µs ± 0%     5.79µs ± 0%  -15.27%  (p=0.016 n=4+5)
RegexpMatchHard_1K-8        205µs ± 0%      176µs ± 0%  -14.19%  (p=0.008 n=5+5)
Revcomp-8                   2.01s ± 0%      1.43s ± 0%  -29.02%  (p=0.008 n=5+5)
Template-8                  259ms ± 0%      158ms ± 0%  -38.93%  (p=0.008 n=5+5)
TimeParse-8                 874ns ± 1%      733ns ± 1%  -16.16%  (p=0.008 n=5+5)
TimeFormat-8               1.00µs ± 1%     0.86µs ± 1%  -13.88%  (p=0.008 n=5+5)

name                     old speed      new speed       delta
GobDecode-8              31.5MB/s ± 0%   44.3MB/s ± 0%  +40.61%  (p=0.008 n=5+5)
GobEncode-8              41.3MB/s ± 0%   50.7MB/s ± 1%  +22.92%  (p=0.008 n=5+5)
Gzip-8                   16.2MB/s ± 0%   26.1MB/s ± 0%  +61.33%  (p=0.008 n=5+5)
Gunzip-8                  102MB/s ± 0%    150MB/s ± 0%  +46.45%  (p=0.016 n=4+5)
JSONEncode-8             38.3MB/s ± 0%   46.7MB/s ± 0%  +22.10%  (p=0.008 n=5+5)
JSONDecode-8             9.64MB/s ± 0%  12.49MB/s ± 0%  +29.54%  (p=0.016 n=5+4)
GoParse-8                5.09MB/s ± 0%   6.78MB/s ± 0%  +33.02%  (p=0.008 n=5+5)
RegexpMatchEasy0_32-8     118MB/s ± 0%    142MB/s ± 0%  +20.29%  (p=0.008 n=5+5)
RegexpMatchEasy0_1K-8     605MB/s ± 0%    534MB/s ± 0%  -11.85%  (p=0.016 n=5+4)
RegexpMatchEasy1_32-8     110MB/s ± 0%    125MB/s ± 0%  +14.23%  (p=0.029 n=4+4)
RegexpMatchEasy1_1K-8     465MB/s ± 0%    430MB/s ± 0%   -7.72%  (p=0.008 n=5+5)
RegexpMatchMedium_32-8   2.43MB/s ± 0%   2.77MB/s ± 0%  +13.99%  (p=0.016 n=5+4)
RegexpMatchMedium_1K-8   8.68MB/s ± 0%   9.87MB/s ± 0%  +13.71%  (p=0.008 n=5+5)
RegexpMatchHard_32-8     4.68MB/s ± 0%   5.53MB/s ± 0%  +18.08%  (p=0.016 n=4+5)
RegexpMatchHard_1K-8     5.00MB/s ± 0%   5.83MB/s ± 0%  +16.60%  (p=0.008 n=5+5)
Revcomp-8                 126MB/s ± 0%    178MB/s ± 0%  +40.88%  (p=0.008 n=5+5)
Template-8               7.48MB/s ± 0%  12.25MB/s ± 0%  +63.74%  (p=0.008 n=5+5)

These are pretty big improvements from just recompiling your binary.

Defer and cgo improvements

The question of if defer can be used in hot code paths remains open, but during the 1.8 cycle Austin reduced the overhead of using defer by a half, according to some benchmarks.

The runtime package benchmarks are a little less rosy.

name         old time/op  new time/op  delta
Defer-4       101ns ± 1%    66ns ± 0%  -34.73%  (p=0.000 n=20+20)
Defer10-4    93.2ns ± 1%  62.5ns ± 8%  -33.02%  (p=0.000 n=20+20)
DeferMany-4   148ns ± 3%   131ns ± 3%  -11.42%  (p=0.000 n=19+19)

According to them defer improved by a third in most common circumstances where the statement closes over no more than a single variable.

Additionally, an optimisation by David Crawshaw reduced the overhead of defer in the cgo path by nearly half.

name       old time/op  new time/op  delta
CgoNoop-8  93.5ns ± 0%  51.1ns ± 1%  -45.34%  (p=0.016 n=4+5)

One more thing

Go 1.7 supported 64 bit mips platforms, thanks to the work of Minux and Cherry. However, the less powerful but plentiful, 32 bit mips platforms were not supported. As a bonus, thanks to the work of Vladimir Stefanovic, Go 1.8 will ship will support for 32 bit mips.

% env GOARCH=mips go build -o godoc.mips
% file godoc.mips 
godoc.mips: ELF 32-bit MSB  executable, MIPS, MIPS32 version 1 (SYSV), statically linked, not stripped

While 32 bit mips hosts are probably too small to compile Go programs natively, you can always cross compile from your development workstation for linux/mips.

Introducing Go 2.0

Just so we’re clear, this post is a thought experiment, not any form of commitment to deliver Go 2.0 in any time frame. While I personally believe there will be a Go 2.0 in the future, I’m in no position to influence its creation; hence, this post is mere speculation.

Why introduce a new major version of Go?

Go 1.0 was released over 4 years ago, and since then the Go 1 compatibility contract has been a boon to anyone investing in Go as the language to build their product.  So, why introduce a new version of Go?

By the time that Go 1.8 is released at the start of 2017, the standard library will have accumulated cruft and hacks for five years, and if you consider that Go started life in 2007, it’s closer to ten. An opportunity to address this cruft and remove some of the packages which are now understood to be a bad idea would make the standard library more consistent and approachable to newcomers.

It is possible the language itself could become smaller. Rob Pike noted in 2014 that there are too many ways to declare a variable in Go, and this could be rationalised. Similarly the incongruence between make and new might be resolved. Then there is the problem of non latin characters not being considered upper case. So, lots of little cleanups to do.

Obviously some kind of solution for templated types would have to be part of any Go 2.0 discussion and, as David Symonds pointed out several years ago, they would have to be used to rewrite the standard library, both causing, and justifying, the compatibility break.

Backward compatibility

Backwards compatibility is not about syntax or features, backwards compatibility is about investment. Investment in the language; both at a technical and career level. Investment in libraries. Investment in backends that generate machine code. Investment in the mid part of the compiler that transforms and optimises code. Investment in build scripts and toolchains that embeds one piece of compiled code into another.

Brian Goetz, the Java language architect, describes the commitment to backward compatibility as the “central park effect“. This is something our cousins in the hardware world have long understood–never let the customer unbolt your product from the rack, ‘cos they might take the opportunity to use that space for your competition.

The lessons of Python 3000 are prescient; ignore backward compatibility at your peril. No matter how compelling the new version of your language, if you make it incompatible with the investment in the previous version, you are launching a new product which is in direct competition with itself. And just to make it clear, I’m not picking on Python specifically, there are plenty of other examples; D 2.0, Perl 6, and also come to mind.

All of these examples show the danger of creating a new version of a language that requires its users to rewrite all the source of their program, including all their dependencies (which may be non trivial), before it will compile and run.

A plausible implementation

So, how to create a new Go 2.0 language, with a new syntax and a new standard library, without making it incompatible every piece of Go code written to date? How could we avoid the all or nothing stand-off in which other languages place their users?

What if we could combine code written in Go 1.0 and a proposed Go 2.0 in one program using the package level as the boundary between language versions? Go 2.0 would be a new language, with a new standard library built upon a runtime shared between itself and Go 1.0, thereby allowing users to work outwards from their Go 2.0 main package to the limbs of their dependency graph, one package at a time.

A Go 2.0 package would be able to call down to Go 1.0, but not the other way around. Go 2.0 types would be able to interoperate with Go 1.0 types, but Go 1.0 types would be unaware of Go 2.0 constructed code. Perhaps calling from Go 2.0 to Go 1.0 looks conceptually like using cgo to call C code, except without the overhead as both languages would be compiled to the same intermediary form.

The key is both language versions would be compiled to a single intermediate representation, one that can represent the superset of both syntaxes. This has been done before; in the first few versions of Go, C code and Go code was compiled to an intermediate representation, Ken Thompson’s universal assembly language, then converted to machine code at link time. Now with Keith Randall’s SSA compiler, there is a single low level intermediate representation (similar to gcc’s GIMPLE and LLVM’s IR) that describes all the things that make Go programs Go1.

There is a strong precedent for this; the ~Sun~ Oracle JVM. For more than a decade the JVM has hosted byte-code that was not compiled from .java source file. Combined with a version of gofix that could automate some of the effort in migrating a package to Go 2.0 syntax, this could be a plausible way to introduce a new version of Go without abrogating the investment in code written for Go 1.0.

  1. This also raises the possibility of developing other language front-ends using the Go toolchain. If you look at what LLVM has done for projects like Pony, Crystal, and Rust, think of what a portable, cross platform, optimising compiler, with user space concurrency built in, and written in Go, not C++, would mean for language experimentation.

Go 1.8 performance improvements, one month in

Sunday September the 18th marks a month since the Go 1.8 cycle opened officially. I’m passionate about the performance of Go programs, and of the compiler itself. This post is a brief look at the state of play, roughly 1/2 way into the development cycle for Go 1.81.

Note: these results are of course preliminary and represent only a point in time, not the performance of the final Go 1.8 release.

Compile times

Nothing much to report here. Using the methodology from my previous Go 1.7 benchmarks, there is a 3.22%–5.11% improvement in full compile time compared to Go 1.7.

Go 1.4.3, Go 1.7, Go tip

Performance improvements

Intel amd64

Better code generation and small improvements to the runtime and standard library show some small improvements for amd642, but really nothing to write home about yet.

name                       old time/op    new time/op  delta
BinaryTree17-4              3.07s ± 2%     3.06s ± 2%    ~      (p=0.661 n=10+9)
Fannkuch11-4                3.23s ± 1%     3.22s ± 0%  -0.43%   (p=0.008 n=9+10)
FmtFprintfEmpty-4          64.4ns ± 0%    61.8ns ± 4%  -4.17%   (p=0.005 n=9+10)
FmtFprintfString-4          162ns ± 0%     162ns ± 0%    ~      (p=0.065 n=10+9)
FmtFprintfInt-4             142ns ± 0%     142ns ± 0%    ~      (p=0.137 n=8+10)
FmtFprintfIntInt-4          220ns ± 0%     217ns ± 0%  -1.18%   (p=0.000 n=9+10)
FmtFprintfPrefixedInt-4     224ns ± 0%     224ns ± 1%    ~       (p=0.206 n=9+9)
FmtFprintfFloat-4           313ns ± 0%     312ns ± 0%  -0.26%   (p=0.001 n=10+9)
FmtManyArgs-4               906ns ± 0%     894ns ± 0%  -1.32%    (p=0.000 n=7+6)
GobDecode-4                8.88ms ± 1%    8.81ms ± 0%  -0.81%  (p=0.003 n=10+10)
GobEncode-4                7.93ms ± 1%    7.88ms ± 0%  -0.66%   (p=0.008 n=9+10)
Gzip-4                      272ms ± 1%     277ms ± 0%  +1.95%   (p=0.000 n=10+9)
Gunzip-4                   47.4ms ± 0%    47.4ms ± 0%    ~      (p=0.720 n=9+10)
HTTPClientServer-4          201µs ± 4%     202µs ± 2%    ~     (p=0.631 n=10+10)
JSONEncode-4               19.3ms ± 0%    19.3ms ± 0%    ~     (p=0.063 n=10+10)
JSONDecode-4               61.0ms ± 0%    61.2ms ± 0%  +0.33%   (p=0.000 n=10+8)
Mandelbrot200-4            5.20ms ± 0%    5.20ms ± 0%    ~      (p=0.475 n=10+7)
GoParse-4                  3.95ms ± 1%    3.97ms ± 1%  +0.65%    (p=0.003 n=9+9)
RegexpMatchEasy0_32-4      88.4ns ± 0%    88.7ns ± 0%  +0.34%   (p=0.001 n=10+9)
RegexpMatchEasy0_1K-4      1.14µs ± 0%    1.14µs ± 0%    ~       (p=0.369 n=9+6)
RegexpMatchEasy1_32-4      82.6ns ± 0%    82.0ns ± 0%  -0.70%   (p=0.000 n=9+10)
RegexpMatchEasy1_1K-4       469ns ± 0%     463ns ± 0%  -1.23%    (p=0.000 n=6+9)
RegexpMatchMedium_32-4      138ns ± 1%     136ns ± 0%  -1.38%   (p=0.000 n=10+9)
RegexpMatchMedium_1K-4     43.6µs ± 1%    42.0µs ± 0%  -3.74%    (p=0.000 n=9+9)
RegexpMatchHard_32-4       2.25µs ± 1%    2.23µs ± 0%  -0.57%    (p=0.000 n=8+8)
RegexpMatchHard_1K-4       68.8µs ± 0%    68.6µs ± 0%  -0.37%    (p=0.000 n=8+8)
Revcomp-4                   477ms ± 1%     472ms ± 0%  -1.03%    (p=0.000 n=8+8)
Template-4                 76.1ms ± 0%    76.4ms ± 0%  +0.35%    (p=0.000 n=9+9)
TimeParse-4                 367ns ± 0%     366ns ± 0%  -0.16%   (p=0.003 n=10+8)
TimeFormat-4                386ns ± 0%     384ns ± 0%  -0.58%    (p=0.000 n=9+9)

name                     old speed      new speed      delta
GobDecode-4              86.4MB/s ± 1%  87.1MB/s ± 0%  +0.81%  (p=0.003 n=10+10)
GobEncode-4              96.7MB/s ± 1%  97.4MB/s ± 0%  +0.66%   (p=0.007 n=9+10)
Gzip-4                   71.4MB/s ± 1%  70.0MB/s ± 0%  -1.91%   (p=0.000 n=10+9)
Gunzip-4                  409MB/s ± 0%   410MB/s ± 0%    ~      (p=0.703 n=9+10)
JSONEncode-4              101MB/s ± 0%   100MB/s ± 0%    ~     (p=0.084 n=10+10)
JSONDecode-4             31.8MB/s ± 0%  31.7MB/s ± 0%  -0.33%   (p=0.000 n=10+8)
GoParse-4                14.7MB/s ± 1%  14.6MB/s ± 1%  -0.67%    (p=0.002 n=9+9)
RegexpMatchEasy0_32-4     362MB/s ± 0%   361MB/s ± 0%  -0.36%   (p=0.000 n=10+9)
RegexpMatchEasy0_1K-4     898MB/s ± 0%   898MB/s ± 0%    ~       (p=0.762 n=9+8)
RegexpMatchEasy1_32-4     387MB/s ± 0%   390MB/s ± 0%  +0.70%   (p=0.000 n=9+10)
RegexpMatchEasy1_1K-4    2.18GB/s ± 0%  2.21GB/s ± 0%  +1.20%    (p=0.000 n=9+9)
RegexpMatchMedium_32-4   7.23MB/s ± 1%  7.32MB/s ± 0%  +1.19%   (p=0.000 n=10+9)
RegexpMatchMedium_1K-4   23.5MB/s ± 1%  24.4MB/s ± 0%  +3.88%    (p=0.000 n=9+9)
RegexpMatchHard_32-4     14.2MB/s ± 1%  14.3MB/s ± 0%  +0.58%    (p=0.000 n=8+8)
RegexpMatchHard_1K-4     14.9MB/s ± 0%  14.9MB/s ± 0%  +0.34%    (p=0.000 n=8+7)
Revcomp-4                 533MB/s ± 1%   539MB/s ± 0%  +1.04%    (p=0.000 n=8+8)
Template-4               25.5MB/s ± 0%  25.4MB/s ± 0%  -0.36%    (p=0.000 n=9+9)


The major improvement that landed recently in the development branch is the conversion of the remaining architecture backends to use the compiler’s SSA form. This has brought a substantial improvement in generated code for non Intel architectures, like ARM3.

name                       old time/op    new time/op    delta
BinaryTree17-4              33.8s ± 1%      27.7s ± 0%  -18.06%  (p=0.000 n=10+10)
Fannkuch11-4                42.0s ± 0%      19.3s ± 0%  -54.10%  (p=0.000 n=10+10)
FmtFprintfEmpty-4           670ns ± 1%      581ns ± 1%  -13.30%  (p=0.000 n=10+10)
FmtFprintfString-4         2.04µs ± 1%     1.65µs ± 0%  -19.09%  (p=0.000 n=10+10)
FmtFprintfInt-4            1.71µs ± 0%     1.21µs ± 0%  -29.39%   (p=0.000 n=10+9)
FmtFprintfIntInt-4         2.69µs ± 1%     1.94µs ± 0%  -27.77%  (p=0.000 n=10+10)
FmtFprintfPrefixedInt-4    2.70µs ± 0%     1.85µs ± 0%  -31.41%   (p=0.000 n=10+9)
FmtFprintfFloat-4          5.15µs ± 0%     3.65µs ± 0%  -29.01%   (p=0.000 n=9+10)
FmtManyArgs-4              11.3µs ± 0%      8.5µs ± 0%  -24.79%   (p=0.000 n=10+9)
GobDecode-4                 112ms ± 0%       77ms ± 1%  -31.04%    (p=0.000 n=9+9)
GobEncode-4                88.5ms ± 1%     77.2ms ± 1%  -12.78%  (p=0.000 n=10+10)
Gzip-4                      4.79s ± 0%      3.34s ± 0%  -30.18%    (p=0.000 n=9+9)
Gunzip-4                    702ms ± 0%      463ms ± 0%  -34.05%  (p=0.000 n=10+10)
HTTPClientServer-4          645µs ± 3%      571µs ± 3%  -11.45%  (p=0.000 n=10+10)
JSONEncode-4                227ms ± 0%      186ms ± 0%  -18.16%  (p=0.000 n=10+10)
JSONDecode-4                845ms ± 0%      618ms ± 0%  -26.81%  (p=0.000 n=10+10)
Mandelbrot200-4            59.3ms ± 0%     40.0ms ± 0%  -32.47%  (p=0.000 n=10+10)
GoParse-4                  45.0ms ± 0%     37.0ms ± 0%  -17.68%    (p=0.000 n=9+9)
RegexpMatchEasy0_32-4       974ns ± 0%      878ns ± 0%   -9.81%   (p=0.000 n=10+9)
RegexpMatchEasy0_1K-4      4.60µs ± 0%     4.48µs ± 0%   -2.57%  (p=0.000 n=10+10)
RegexpMatchEasy1_32-4      1.02µs ± 0%     0.94µs ± 0%   -8.08%   (p=0.000 n=8+10)
RegexpMatchEasy1_1K-4      6.92µs ± 0%     6.08µs ± 0%  -12.10%  (p=0.000 n=10+10)
RegexpMatchMedium_32-4     1.61µs ± 0%     1.27µs ± 0%  -20.98%    (p=0.000 n=9+6)
RegexpMatchMedium_1K-4      447µs ± 0%      317µs ± 0%  -29.05%   (p=0.000 n=10+9)
RegexpMatchHard_32-4       24.9µs ± 0%     18.4µs ± 0%  -25.89%  (p=0.000 n=10+10)
RegexpMatchHard_1K-4        740µs ± 0%      552µs ± 0%  -25.36%  (p=0.000 n=10+10)
Revcomp-4                  81.0ms ± 1%     65.2ms ± 0%  -19.53%    (p=0.000 n=9+9)
Template-4                  1.17s ± 0%      0.81s ± 0%  -31.28%    (p=0.000 n=9+9)
TimeParse-4                5.52µs ± 0%     3.79µs ± 0%  -31.42%   (p=0.000 n=10+9)
TimeFormat-4               10.6µs ± 0%      8.5µs ± 0%  -19.14%  (p=0.000 n=10+10)

name                     old speed      new speed        delta
GobDecode-4              6.86MB/s ± 0%   9.95MB/s ± 1%  +45.00%    (p=0.000 n=9+9)
GobEncode-4              8.67MB/s ± 1%   9.94MB/s ± 1%  +14.69%  (p=0.000 n=10+10)
Gzip-4                   4.05MB/s ± 0%   5.81MB/s ± 0%  +43.32%   (p=0.000 n=10+9)
Gunzip-4                 27.6MB/s ± 0%   41.9MB/s ± 0%  +51.63%  (p=0.000 n=10+10)
JSONEncode-4             8.53MB/s ± 0%  10.43MB/s ± 0%  +22.20%  (p=0.000 n=10+10)
JSONDecode-4             2.30MB/s ± 0%   3.14MB/s ± 0%  +36.39%   (p=0.000 n=9+10)
GoParse-4                1.29MB/s ± 0%   1.56MB/s ± 0%  +20.93%   (p=0.000 n=9+10)
RegexpMatchEasy0_32-4    32.8MB/s ± 0%   36.4MB/s ± 0%  +10.87%  (p=0.000 n=10+10)
RegexpMatchEasy0_1K-4     222MB/s ± 0%    228MB/s ± 0%   +2.64%  (p=0.000 n=10+10)
RegexpMatchEasy1_32-4    31.3MB/s ± 0%   34.0MB/s ± 0%   +8.75%   (p=0.000 n=9+10)
RegexpMatchEasy1_1K-4     148MB/s ± 0%    168MB/s ± 0%  +13.76%  (p=0.000 n=10+10)
RegexpMatchMedium_32-4    620kB/s ± 0%    790kB/s ± 0%  +27.42%   (p=0.000 n=10+8)
RegexpMatchMedium_1K-4   2.29MB/s ± 0%   3.23MB/s ± 0%  +41.05%  (p=0.000 n=10+10)
RegexpMatchHard_32-4     1.29MB/s ± 0%   1.74MB/s ± 0%  +34.88%   (p=0.000 n=9+10)
RegexpMatchHard_1K-4     1.38MB/s ± 0%   1.85MB/s ± 0%  +34.06%  (p=0.000 n=10+10)
Revcomp-4                31.4MB/s ± 1%   39.0MB/s ± 0%  +24.26%    (p=0.000 n=9+9)
Template-4               1.65MB/s ± 0%   2.41MB/s ± 0%  +45.71%   (p=0.000 n=10+9)


  1. Despite the Go 1.8 development cycle opening 18 days late, in order to keep to the 6 month cadence, the feature freeze for this cycle will still occur on the 1st of November.
  2. Intel(R) Core(TM) i5-2520M CPU @ 2.50GHz, 3.13.0-95-generic #142-Ubuntu
  3. Freescale i.MX6, 3.14.77-1-ARCH

SOLID Go Design

This post is based on the text of my GolangUK keynote delivered on the 18th of August 2016.
A recording of the talk is available on YouTube.

This post has been translated into Traditional Chinese by Haohao Tian. Thanks Haohao!

How many Go programmers are there in the world?

How many Go programmers are there in the world? Think of a number and hold it in your head, we’ll come back to it at the end of this talk.

Code review

Who here does code review as part of their job? [the entire room raised their hand, which was encouraging]. Okay, why do you do code review? [someone shouted out “to stop bad code”]

If code review is there to catch bad code, then how do you know if the code you’re reviewing is good, or bad?

Now it’s fine to say “that code is ugly” or ”wow that source code is beautiful”, just as you might say “this painting is beautiful” or “this room is beautiful” but these are subjective terms, and I’m looking for objective ways to talk about the properties of good or bad code.

Bad code

What are some of the properties of bad code that you might pick up on in code review?

  • Rigid. Is the code rigid? Does it have a straight jacket of overbearing types and parameters, that making modification difficult?
  • Fragile. Is the code fragile? Does the slightest change ripple through the code base causing untold havoc?
  • Immobile. Is the code hard to refactor? Is it one keystroke away from an import loop?
  • Complex. Is there code for the sake of having code, are things over-engineered?
  • Verbose. Is it just exhausting to use the code? When you look at it, can you even tell what this code is trying to do?

Are these positive sounding words? Would you be pleased to see these words used in a review of your code?

Probably not.

Good design

But this is an improvement, now we can say things like “I don’t like this because it’s too hard to modify”, or “I don’t like this because i cannot tell what the code is trying to do”, but what about leading with the positive?

Wouldn’t it be great if there were some ways to describe the properties of good design, not just bad design, and to be able to do so in objective terms?


In 2002 Robert Martin published his book, Agile Software Development, Principles, Patterns, and Practices. In it he described five principles of reusable software design, which he called the SOLID principles, after the first letters in their names.

  • Single Responsibility Principle
  • Open / Closed Principle
  • Liskov Substitution Principle
  • Interface Segregation Principle
  • Dependency Inversion Principle

This book is a little dated, the languages that it talks about are the ones in use more than a decade ago. But, perhaps there are some aspects of the SOLID principles that may give us a clue about how to talk about a well designed Go programs.

So this is what I want to spend some time discussing with you this morning.

Single Responsibility Principle

The first principle of SOLID, the S, is the single responsibility principle.

A class should have one, and only one, reason to change.
–Robert C Martin

Now Go obviously doesn’t have classes—instead we have the far more powerful notion of composition—but if you can look past the use of the word class, I think there is some value here.

Why is it important that a piece of code should have only one reason for change? Well, as distressing as the idea that your own code may change, it is far more distressing to discover that code your code depends on is changing under your feet. And when your code does have to change, it should do so in response to a direct stimuli, it shouldn’t be a victim of collateral damage.

So code that has a single responsibility therefore has the fewest reasons to change.

Coupling & Cohesion

Two words that describe how easy or difficult it is to change a piece of software are coupling and cohesion.

Coupling is simply a word that describes two things changing together–a movement in one induces a movement in another.

A related, but separate, notion is the idea of cohesion, a force of mutual attraction.

In the context of software, cohesion is the property of describing pieces of code are naturally attracted to one another.

To describe the units of coupling and cohesion in a Go program, we might talk about functions and methods, as is very common when discussing SRP but I believe it starts with Go’s package model.

Package names

In Go, all code lives inside a package, and a well designed package starts with its name. A package’s name is both a description of its purpose, and a name space prefix. Some examples of good packages from the Go standard library might be:

  • net/http, which provides http clients and servers.
  • os/exec, which runs external commands.
  • encoding/json, which implements encoding and decoding of JSON documents.

When you use another package’s symbols inside your own this is accomplished by the `import` declaration, which establishes a source level coupling between two packages. They now know about each other.

Bad package names

This focus on names is not just pedantry. A poorly named package misses the opportunity to enumerate its purpose, if indeed it ever had one.

What does package server provide? … well a server, hopefully, but which protocol?

What does package private provide? Things that I should not see? Should it have any public symbols?

And package common, just like its partner in crime, package utils, is often found close by these other offenders.

Catch all packages like these become a dumping ground for miscellany, and because they have many responsibilities they change frequently and without cause.

Go’s UNIX philosophy

In my view, no discussion about decoupled design would be complete without mentioning Doug McIlroy’s Unix philosophy; small, sharp tools which combine to solve larger tasks, oftentimes tasks which were not envisioned by the original authors.

I think that Go packages embody the spirit of the UNIX philosophy. In effect each Go package is itself a small Go program, a single unit of change, with a single responsibility.

Open / Closed Principle

The second principle, the O, is the open closed principle by Bertrand Meyer who in 1988 wrote:

Software entities should be open for extension, but closed for modification.
–Bertrand Meyer, Object-Oriented Software Construction

How does this advice apply to a language written 21 years later?

package main

type A struct {

        year int


func (a A) Greet() { fmt.Println("Hello GolangUK", a.year) }

type B struct {



func (b B) Greet() { fmt.Println("Welcome to GolangUK", b.year) }

func main() {

        var a A

        a.year = 2016

        var b B

        b.year = 2016

        a.Greet() // Hello GolangUK 2016

        b.Greet() // Welcome to GolangUK 2016


We have a type A, with a field year and a method Greet. We have a second type, B which embeds an A, thus callers see B‘s methods overlaid on A‘s because A is embedded, as a field, within B, and B can provide its own Greet method, obscuring that of A.

But embedding isn’t just for methods, it also provides access to an embedded type’s fields. As you see, because both A and B are defined in the same package, B can access A‘s private year field as if it were declared inside B.

So embedding is a powerful tool which allows Go’s types to be open for extension.

package main

type Cat struct {

        Name string


func (c Cat) Legs() int { return 4 }

func (c Cat) PrintLegs() {

        fmt.Printf("I have %d legs\n", c.Legs())


type OctoCat struct {



func (o OctoCat) Legs() int { return 5 }

func main() {

        var octo OctoCat

        fmt.Println(octo.Legs()) // 5

        octo.PrintLegs()         // I have 4 legs


In this example we have a Cat type, which can count its number of legs with its Legs method. We embed this Cat type into a new type, an OctoCat, and declare that Octocats have five legs. However, although OctoCat defines its own Legs method, which returns 5, when the PrintLegs method is invoked, it returns 4.

This is because PrintLegs is defined on the Cat type. It takes a Cat as its receiver, and so it dispatches to Cat‘s Legs method. Cat has no knowledge of the type it has been embedded into, so its method set cannot be altered by embedding.

Thus, we can say that Go’s types, while being open for extension, are closed for modification.

In truth, methods in Go are little more than syntactic sugar around a function with a predeclared formal parameter, their receiver.

func (c Cat) PrintLegs() {
        fmt.Printf("I have %d legs\n", c.Legs())

func PrintLegs(c Cat) {
        fmt.Printf("I have %d legs\n", c.Legs())

The receiver is exactly what you pass into it, the first parameter of the function, and because Go does not support function overloading, OctoCats are not substitutable for regular Cats. Which brings me to the next principle.

Liskov Substitution Principle

Coined by Barbara Liskov, the Liskov substitution principle states, roughly, that two types are substitutable if they exhibit behaviour such that the caller is unable to tell the difference.

In a class based language, Liskov’s substitution principle is commonly interpreted as a specification for an abstract base class with various concrete subtypes. But Go does not have classes, or inheritance, so substitution cannot be implemented in terms of an abstract class hierarchy.


Instead, substitution is the purview of Go’s interfaces. In Go, types are not required to nominate that they implement a particular interface, instead any type implements an interface simply provided it has methods whose signature matches the interface declaration.

We say that in Go, interfaces are satisfied implicitly, rather than explicitly, and this has a profound impact on how they are used within the language.

Well designed interfaces are more likely to be small interfaces; the prevailing idiom is an interface contains only a single method. It follows logically that small interfaces lead to simple implementations, because it is hard to do otherwise. Which leads to packages comprised of simple implementations connected by common behaviour.


type Reader interface {
        // Read reads up to len(buf) bytes into buf.
        Read(buf []byte) (n int, err error)

Which brings me to io.Reader, easily my favourite Go interface.

The io.Reader interface is very simple; Read reads data into the supplied buffer, and returns to the caller the number of bytes that were read, and any error encountered during read. It seems simple but it’s very powerful.

Because io.Reader‘s deal with anything that can be expressed as a stream of bytes, we can construct readers over just about anything; a constant string, a byte array, standard in, a network stream, a gzip’d tar file, the standard out of a command being executed remotely via ssh.

And all of these implementations are substitutable for one another because they fulfil the same simple contract.

So the Liskov substitution principle, applied to Go, could be summarised by this lovely aphorism from the late Jim Weirich.

Require no more, promise no less.
–Jim Weirich

And this is a great segue into the fourth SOLID principle.

Interface Segregation Principle

The fourth principle is the interface segregation principle, which reads:

Clients should not be forced to depend on methods they do not use.
–Robert C. Martin

In Go, the application of the interface segregation principle can refer to a process of isolating the behaviour required for a function to do its job. As a concrete example, say I’ve been given a task to write a function that persists a Document structure to disk.

// Save writes the contents of doc to the file f.
func Save(f *os.File, doc *Document) error

I could define this function, let’s call it Save, which takes an *os.File as the destination to write the supplied Document. But this has a few problems.

The signature of Save precludes the option to write the data to a network location. Assuming that network storage is likely to become requirement later, the signature of this function would have to change, impacting all its callers.

Because Save operates directly with files on disk, it is unpleasant to test. To verify its operation, the test would have to read the contents of the file after being written. Additionally the test would have to ensure that f was written to a temporary location and always removed afterwards.

*os.File also defines a lot of methods which are not relevant to Save, like reading directories and checking to see if a path is a symlink. It would be useful if the signature of our Save function could describe only the parts of *os.File that were relevant.

What can we do about these problems?

// Save writes the contents of doc to the supplied ReadWriterCloser.
func Save(rwc io.ReadWriteCloser, doc *Document) error

Using io.ReadWriteCloser we can apply the Interface Segregation Principle to redefine Save to take an interface that describes more general file-shaped things.

With this change, any type that implements the io.ReadWriteCloser interface can be substituted for the previous *os.File. This makes Save both broader in its application, and clarifies to the caller of Save which methods of the *os.File type are relevant to its operation.

As the author of Save I no longer have the option to call those unrelated methods on *os.File as it is hidden behind the io.ReadWriteCloser interface. But we can take the interface segregation principle a bit further.

Firstly, it is unlikely that if Save follows the single responsibility principle, it will read the file it just wrote to verify its contents–that should be responsibility of another piece of code. So we can narrow the specification for the interface we pass to Save to just writing and closing.

// Save writes the contents of doc to the supplied WriteCloser.
func Save(wc io.WriteCloser, doc *Document) error

Secondly, by providing Save with a mechanism to close its stream, which we inherited in a desire to make it look like a file shaped thing, this raises the question of under what circumstances will wc be closed. Possibly Save will call Close unconditionally, or perhaps Close will be called in the case of success.

This presents a problem for the caller of Save as it may want to write additional data to the stream after the document is written.

type NopCloser struct {

// Close has no effect on the underlying writer.
func (c *NopCloser) Close() error { return nil }

A crude solution would be to define a new type which embeds an io.Writer and overrides the Close method, preventing Save from closing the underlying stream.

But this would probably be a violation of the Liskov Substitution Principle, as NopCloser doesn’t actually close anything.

// Save writes the contents of doc to the supplied Writer.
func Save(w io.Writer, doc *Document) error

A better solution would be to redefine Save to take only an io.Writer, stripping it completely of the responsibility to do anything but write data to a stream.

By applying the interface segregation principle to our Save function, the results has simultaneously been a function which is the most specific in terms of its requirements–it only needs a thing that is writable–and the most general in its function, we can now use Save to save our data to anything which implements io.Writer.

A great rule of thumb for Go is accept interfaces, return structs.
–Jack Lindamood

Stepping back a few paces, this quote is an interesting meme that has been percolating in the Go zeitgeist over the last few years.

This tweet sized version lacks nuance, and this is not Jack’s fault, but I think it represents one of the first piece of defensible Go design lore.

Dependency Inversion Principle

The final SOLID principle is the dependency inversion principle, which states:

High-level modules should not depend on low-level modules. Both should depend on abstractions.
Abstractions should not depend on details. Details should depend on abstractions.
–Robert C. Martin

But what does dependency inversion mean, in practice, for Go programmers?

If you’ve applied all the principles we’ve talked about up to this point then your code should already be factored into discrete packages, each with a single well defined responsibility or purpose. Your code should describe its dependencies in terms of interfaces, and those interfaces should be factored to describe only the behaviour those functions require. In other words, there shouldn’t be much left to do.

So what I think Martin is talking about here, certainly the context of Go, is the structure of your import graph.

In Go, your import graph must be acyclic. A failure to respect this acyclic requirement is grounds for a compilation failure, but more gravely represents a serious error in design.

All things being equal the import graph of a well designed Go program should be a wide, and relatively flat, rather than tall and narrow. If you have a package whose functions cannot operate without enlisting the aid of another package, that is perhaps a sign that code is not well factored along package boundaries.

The dependency inversion principle encourages you to push the responsibility for the specifics, as high as possible up the import graph, to your main package or top level handler, leaving the lower level code to deal with abstractions–interfaces.

SOLID Go Design

To recap, when applied to Go, each of the SOLID principles are powerful statements about design, but taken together they have a central theme.

The Single Responsibility Principle encourages you to structure the functions, types, and methods into packages that exhibit natural cohesion; the types belong together, the functions serve a single purpose.

The Open / Closed Principle encourages you to compose simple types into more complex ones using embedding.

The Liskov Substitution Principle encourages you to express the dependencies between your packages in terms of interfaces, not concrete types. By defining small interfaces, we can be more confident that implementations will faithfully satisfy their contract.

The Interface Substitution Principle takes that idea further and encourages you to define functions and methods that depend only on the behaviour that they need. If your function only requires a parameter of an interface type with a single method, then it is more likely that this function has only one responsibility.

The Dependency Inversion Principle encourages you move the knowledge of the things your package depends on from compile time–in Go we see this with a reduction in the number of import statements used by a particular package–to run time.

If you were to summarise this talk it would probably be; interfaces let you apply the SOLID principles to Go programs.

Because interfaces let Go programmers describe what their package provides–not how it does it. This is all just another way of saying “decoupling”, which is indeed the goal, because software that is loosely coupled is software that is easier to change.

As Sandi Metz notes:

Design is the art of arranging code that needs to work today, and to be easy to change forever.
–Sandi Metz

Because if Go is going to be a language that companies invest in for the long term, the maintenance of Go programs, the ease of which they can change, will be a key factor in their decision.


In closing, let’s return to the question I opened this talk with; How many Go programmers are there in the world? This is my guess:

By 2020, there will be 500,000 Go developers.

What will half a million Go programmers do with their time? Well, obviously, they’ll write a lot of Go code and, if we’re being honest, not all of it will be good, and some will be quite bad.

Please understand that I do not say this to be cruel, but, every one of you in this room with experience with development in other languages–the languages you came from, to Go–knows from your own experience that there is an element of truth to this prediction.

Within C++, there is a much smaller and cleaner language struggling to get out.
–Bjarne Stroustrup, The Design and Evolution of C++

The opportunity for all Go programmers to make our language a success hinges directly on our collective ability to not make such a mess of things that people start to talk about Go the way that they joke about C++ today.

The narrative that derides other languages for being bloated, verbose, and overcomplicated, could one day well be turned upon Go, and I don’t want to see this happen, so I have a request.

Go programmers need to start talking less about frameworks, and start talking more about design. We need to stop focusing on performance at all cost, and focus instead on reuse at all cost.

What I want to see is people talking about how to use the language we have today, whatever its choices and limitations, to design solutions and to solve real problems.

What I want to hear is people talking about how to design Go programs in a way that is well engineered, decoupled, reusable, and above all responsive to change.

… one more thing

Now, it’s great that so many of you are here today to hear from the great lineup of speakers, but the reality is that no matter how large this conference grows, compared to the number of people who will use Go during its lifetime, we’re just a tiny fraction.

So we need to tell the rest of the world how good software should be written. Good software, composable software, software that is amenable to change, and show them how to do it, using Go. And this starts with you.

I want you to start talking about design, maybe use some of the ideas I presented here, hopefully you’ll do your own research, and apply those ideas to your projects. Then I want you to:

  • Write a blog post about it.
  • Teach a workshop about it what you did.
  • Write a book about what you learnt.
  • And come back to this conference next year and give a talk about what you achieved.

Because by doing these things we can build a culture of Go developers who care about programs that are designed to last.

Thank you.

Automatically fetch your project’s dependencies with gb

gb has been in development for just over a year now. Since the announcement in May 2015 the project has received over 1,600 stars, produced 16 releases, and attracted 41 contributors.

Thanks to a committed band of early adopters, gb has grown to be a usable day to day replacement for the go tool. But, there is one area where gb has not lived up to my hopes, and that is dependency management.

gb’s $PROJECT/vendor/ directory was the inspiration for the go tool’s vendor/ directory (although their implementations differ greatly) and has delivered on its goal of reproducible builds for Go projects. However, the success of gb’s project based model, and vendoring code in general, has a few problems. Specifically, wholesale copying (or forking if you prefer) of one code base into another continues to sidestep the issue of adoption of a proper release and versioning culture amongst Go developers.

To be fair, for Go developers using the tools they have access to today–including gb–there is no incentive to release their code. As a Go package author, you get no points for doing proper versioned releases if your build tool just pulls from HEAD anyway. There is similarly limited value in adopting a version numbering policy like SemVer if your tools only memorise the git revision you last copied your code at.

A second problem, equally poorly served by gb or the vendor/ support in the go tool, are developers and projects who cannot, usually for legal reasons, or do not wish to, copy code wholesale into their project. Suggestions of using git submodules have been soundly dismissed as unworkable.

With the release of gb 0.4.3, there is a new way to manage dependencies with gb. This new method does not replace gb vendor or $PROJECT/vendor as the recommended method for achieving reproducible builds, but it does acknowledge that vendoring is not appropriate for all use cases.

To be clear, this new mode of managing dependencies does not supersede or deprecate the existing mechanisms of cloning source code into $PROJECT/vendor. The automatic download feature is optional and is activated by the project author creating a file in their project’s root called, $PROJECT/depfile.

If you have a gb project that is currently vendoring code, or you’re using gb vendor restore to actively avoid cloning code into your project, you can try this feature today, with the following caveats:

  1. Currently only GitHub is supported. This is because the new facility uses the GitHub API to download release tarballs via https. Vanity urls that redirect to GitHub are also not supported yet, but will be supported soon.
  2. The repository must have made a release of its code, and that release must be tagged with a tag containing a valid SemVer 2.0.0 version number. The format of the tag is described in this proposal. If a dependency you want to consume in your gb project has not released their code, then please ask them to do so.

Polishing this feature will be the remainder of the 0.4.x development series. After this work is complete gb vendor will be getting some attention. Ultimately both gb vendor and $PROJECT/depfile do the same thing–one copies the source of your dependencies into your project, the other into your home directory.

Gophers, please tag your releases

What do we want? Version management for Go packages! When do we want it? Yesterday!

What does everyone want? We want our Go build tool of choice to fetch the latest stable version when you start using the package in your project. We want them to grab security updates and bug fixes automatically, but not upgrade to a version where the author deleted a method you were using.

But as it stands, today, in 2016, there is no way for a human, or a tool, to look at an arbitrary git (or mercurial, or bzr, etc) repository of Go code and ask questions like:

  • What versions of this project have been released?
  • What is the latest stable release of this software?
  • If I have version 1.2.3, is there a bugfix or security update that I should apply?

The reason for this is Go projects (repositories of Go packages) don’t have versions, at least not in the way that our friends in other languages use that word. Go projects do not have versions because there is no formalised release process.

But there’s vendor/ right?

Arguing about tools to manage your vendor/ directory, or which markup format a manifest file should be written in is eating the elephant from the wrong end.

Before you can argue about the format of a file that records the version of a package, you have to have some way of actually knowing what that version is. A version number has to be sortable, so you can ask, “is there a newer version available than the one you have on disk?” Ideally the version number should give you a clue to how large the jump between versions is, perhaps even give a clue to backwards or forwards compatibility between two versions.

SemVer is no one’s favourite, yet one format is everyone’s favourite.

I recommended that Go projects adopt SemVer 2.0.0. It’s a sound standard, it is well understood by many, not just Go programmers, and semantic versioning will let people write tools to build a dependency management ecosystem on top of a minimal release process.

Following the lead of the big three Go projects, Docker, Kubernetes, and CoreOS (and GitHub’s on releases page), the format of the tag must be:


That is, the letter v followed by a string which is SemVer 2.0.0 compliant. Here are some examples:

git tag -a v1.2.3
git tag -a v0.1.0
git tag -a v1.0.0-rc.1

Here are some incorrect examples:

git tag -a 1.2.3        // missing v prefix
git tag -a v1.0         // 1.0 is not SemVer compliant
git tag -a v2.0.0beta3  // also not SemVer compliant

Of course, if you’re using hg, bzr, or another version control system, please adjust as appropriate. This isn’t just for git or GitHub repos.

What do you get for this?

Imagine if could show you the documentation for the version of the package you’re using, not just the latest from HEAD.

Now, imagine if could not just show you the documentation, but also serve you a tarball or zip file of the source code of that version. Imagine not having to install mercurial just to go get that one dependency that is still on google code (rest in peace), or bitbucket in hg form.

Establishing a single release process for Go projects and adopting semantic versioning will let your favourite Go package management or vendoring tool provide you things like a real upgrade command. Instead of letting you figure out which revision to switch to, SemVer gives tool writers the ability to do things like upgrade a dependency to the latest patch release of version 1.2.

Build it and they will come

Tagging releases is pointless if people don’t write tools to consume the information. Just like writing tools that can, at the moment, only record git hashes is pointless.

Here’s the deal: If you release your Go projects with the correctly formatted tags, then there are a host of developers who are working dependency management tools for Go packages that want to consume this information.

How can I declare which versions of other packages my project depends on?

If you’ve read this far you are probably wondering how using tagging releases in your own repository is going to help specify the versions of your Go project’s dependencies.

The Go import statement doesn’t contain this version information, all it has is the import path. But whether you’re in the camp that wants to add version information to the import statement, a comment inside the source file, or you would prefer to put that information in a metadata file, everyone needs version information, and that starts with tagging your release of your Go projects.

No version information, no tools, and the situation never improves. It’s that simple.