Now that I’ve been writing Golang for a while, when I start a new project, I typically know the sort of layout I’m looking for. I typically go for something like this: . ├── cmd │ └── demo │ └── main.go ├── go.mod ├── internal │ └── subpkg │ ├── subpkg.go │ └── subpkg_test.go └── LICENSE And often there are lots of ascillary files that go along with this, like Makefiles, CI/CD config files, Dockerfiles, docker-compose files, etc....

I was not very familiar with checking an error’s type in Golang, so I spent a few minutes learning about it today. It turns out that it’s incredibly easy to do. Running the below code shows the output: 2009/11/10 23:00:00 got custom error: err1 package main import ( "errors" "log" ) var ( customErr = errors.New("err1") // create a error, identified by its var name ) // oops always returns our custom error....

I’ve also been thinking more about unnecessary allocations in my Go code and how to avoid them by pre-declaring the length of a slice up front. Normally, I’d write something like this: var s []int for _, val := otherSlice { s = append(s, val) } Since I don’t specify the size of s, if otherSlice is large, the array underlying s might not be large enough to hold all the values; then a new array will have to be allocated and (I presume) all existing values copied out of it one at a time to fill the new array....

I recently went through How To Use Templates in Go to refresh my memory on Golang templates. I was reminded how great they are and learned several things along the way. I learned that the below syntaxes are equivalent: {{ . | len }} {{ (len .) }} Here is the program I wrote and tweaked along the way, to refresh my memory in the future: package main import ( "html/template" "os" "strings" ) type Pet struct { Name string Sex string Intact bool Age string Breed []string } var dogs = []Pet{ { // This is why you should use html/template and not text/template when // rendering HTML....

While watching a talk by Rob Pike I learned today something about Goroutines which surprised me: Goroutines outlive their calling function. Said another way, if the function which created the goroutine returns, the goroutine will continue running. (main() is the one exception.) This is fantastic! 🎉 Here’s an example of this in practice. package main import ( "fmt" "time" ) func person(msg string) <-chan string { // Function returns a receive-only channel ch := make(chan string) // Create unbuffered channel go func() { // This goroutine lives on after person() returns for i := 0; ; i++ { time....

Go 1.18 added a feature to easily get the Git commit version that the binary was built from. This is so much easier than the old way of doing it! package main import ( "fmt" "runtime/debug" ) func main() { info, _ := debug.ReadBuildInfo() for _, setting := range info.Settings { if setting.Key == "vcs.revision" || setting.Key == "vcs.time" { fmt.Printf("%s:\t%s\n", setting.Key, setting.Value) } } } $ go build git-version $ ....

The other day I ran into a situation where I wanted my function to block until it received data from a Go channel. But I didn’t want it to block indefinitely. I wanted it to timeout after a few seconds if it didn’t get any data. My coworker Dan showed me a technique I didn’t know about to easily accomplish this. It wasn’t surprising to learn how easy it was, given that Go has strong support for concurrency out the gate....

Example 1 In the below code, <-messages will block until it gets something on the channel. This prevents main() from exiting until one item is received on the channel. package main import ( "fmt" "time" ) func waitThenSend(msg chan string) { time.Sleep(2 * time.Second) msg <- "badwolf" } func main() { messages := make(chan string) // make unbuffered channel go func() { waitThenSend(messages) // make goroutine, pass in channel }() <-messages // blocks until channel receives a value fmt....

At work, I’ve been using both Golang and Ruby to render Nomad jobspec files in a consistent manner across environments. But Python is my one true love and I wanted to learn how to do it in Python. Turns out I already knew how… you can do it in Jinja2! I’ve used Jinja2 in the past a lot for Django and Ansible, so this was pretty easy to pick up. Here are some notes for future me when I want to inevitably do this again....

These are useful and I’m putting them here so I can find them easily wherever I am. Latency Comparison Numbers (~2012) ---------------------------------- L1 cache reference 0.5 ns Branch mispredict 5 ns L2 cache reference 7 ns 14x L1 cache Mutex lock/unlock 25 ns Main memory reference 100 ns 20x L2 cache, 200x L1 cache Compress 1K bytes with Zippy 3,000 ns 3 us Send 1K bytes over 1 Gbps network 10,000 ns 10 us Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD Read 1 MB sequentially from memory 250,000 ns 250 us Round trip within same datacenter 500,000 ns 500 us Read 1 MB sequentially from SSD* 1,000,000 ns 1,000 us 1 ms ~1GB/sec SSD, 4X memory Disk seek 10,000,000 ns 10,000 us 10 ms 20x datacenter roundtrip Read 1 MB sequentially from disk 20,000,000 ns 20,000 us 20 ms 80x memory, 20X SSD Send packet CA->Netherlands->CA 150,000,000 ns 150,000 us 150 ms Notes ----- 1 ns = 10^-9 seconds 1 us = 10^-6 seconds = 1,000 ns 1 ms = 10^-3 seconds = 1,000 us = 1,000,000 ns Credit ------ By Jeff Dean: http://research....