$ terraform taint resource.id
resource.id refers to the resource block name and resource ID to taint. Review the resource block we
previously created:
resource "aws_instance" "example" {
ami = "ami-b374d5a5"
instance_type = "t2.micro"
// groovy DSL | |
jacocoTestReport { | |
reports { | |
// 원하는 리포트를 켜고 끌 수 있습니다. | |
html.enabled true | |
xml.enabled false | |
csv.enabled false | |
// 각 리포트 타입 마다 리포트 저장 경로를 설정할 수 있습니다. |
Based off https://palantir.quip.com/pzRwAVr1bpzf
Pro-tip: look through the github diff between the previous release to see what's changed. The commit titles should give an outline of what's happened.
- List out, as concretely as possible, any steps users have to take when they upgrade beyond just dumping the dependency.
- Write pseudocode that highlights what code should change and how.
I've been deceiving you all. I had you believe that Svelte was a UI framework — unlike React and Vue etc, because it shifts work out of the client and into the compiler, but a framework nonetheless.
But that's not exactly accurate. In my defense, I didn't realise it myself until very recently. But with Svelte 3 around the corner, it's time to come clean about what Svelte really is.
Svelte is a language.
Specifically, Svelte is an attempt to answer a question that many people have asked, and a few have answered: what would it look like if we had a language for describing reactive user interfaces?
A few projects that have answered this question:
# Backup files | |
#https://explainshell.com/explain?cmd=rsync+-azuv+--delete+--progress+--exclude+%27node_modules%27 | |
rsync -auvhp --delete --exclude=node_modules [source] [destination] | |
# Remove all node_modules folders | |
# https://explainshell.com/explain?cmd=find+.+-name+%22node_modules%22+-type+d+-prune+-exec+rm+-rf+%27%7B%7D%27+%2B | |
find . -name "node_modules" -type d -prune -exec rm -rf '{}' + |
data class CNPJ(val value: String) | |
fun CNPJ.isValid(): Boolean { | |
val cnpj = value | |
return validateCNPJLength(cnpj) && validateCNPJRepeatedNumbers(cnpj) | |
&& validateCNPJVerificationDigit(true, cnpj) | |
&& validateCNPJVerificationDigit(false, cnpj) | |
} |
I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.
This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea
1. Setup a project | |
2. Add groovy SDK support: | |
https://www.bonusbits.com/wiki/HowTo:Add_Groovy_SDK_to_IntelliJ_IDEA | |
3. Download http://(yourjenkinsurl)/job/(yourpipelinejob)/pipeline-syntax/gdsl | |
- this will give you the .gdsl file - download this to the src folder of your project. | |
4. Finally follow this step - right click on the src folder -> Mark directory as -> Sources Root |
package fragments | |
import ( | |
"net/http" | |
"io" | |
"log" | |
"strings" | |
"os" | |
"bytes" | |
) |