Elasticsearch query examples with Golang

Queries in Elastic differ quite a lot from standard (No)SQL ones. Even though the end result is pretty much the same (get all from table A, order by column B,C desc where column D like ‘E’) and you could easily draw a line between those two, the complexity of queries in Elastic is way much higher compared to SQL ones.

Create and manage MacOS LaunchAgents using Go Blog Post

So just how fast are channels anyway?

The speed of channels isn’t really the point, but I couldn’t help but wonder how fast they are. So I wrote a benchmark!

Phone Normalizer Exercise Videos

JustForFunc #27 - two ways of merging N channels

An article aimed at beginners to understand how to compose more complex packages, beyond making the usual “one package - one binary” ones. You can check it out here.

Instrumenting a Buffalo Application with New Relic - Blog Post

Write your HTTP application in Go once, deploy it everywhere (on-premise & AWS Lambda supported)

Usage

Just call gluo.ListenAndServe instead of http.ListenAndServe.

package main

import (
        "github.com/imdario/gluo"
        "net/http"
)

func handler(w http.ResponseWriter, r *http.Request) {
        w.Write([]byte("Hello from Gluo"))
}

func main() {
        gluo.ListenAndServe(":3000", http.HandlerFunc(handler))
}

AWS Blog

Buffalo Blog https://blog.gobuffalo.io/buffalo-v0-10-3-released-d871076013d1

https://golangbot.com/panic-and-recover/

Colly - Fast and Elegant Scraping Framework for Gophers.

With Colly you can easily extract structured data from websites, which can be used for a wide range of applications, like data mining, data processing or archiving.

Features:

Clean API
Fast (>1k request/sec on a single core)
Manages request delays and maximum concurrency per domain
Automatic cookie and session handling
Sync/async/parallel scraping
Caching
Automatic encoding of non-unicode responses
Robots.txt support
Google App Engine support

Gophercises.com - coding exercises for budding gophers

Gophercises is a FREE course that will help you become more familiar with Go while developing your skills as a programmer. In the course we will build roughly 20 different mini-applications, packages, and tools that are each designed to teach you something different.

Datacol is a control layer on top of cloud(AWS/GCP), to provide Heroku like experience with power of Kubernetes under the hood

More: https://www.datacol.io/

Github : https://github.com/datacol-io/datacol

https://github.com/covrom/distchan

Let me explain my setup to keep backups of my repositories on my own server.

jorin.me/automating-github-backup-with-ghbackup

https://github.com/pioz/tvdb

Learn how to use channels to model your data flow by building a web crawler in Go.

jorin.me/use-go-channels-to-build-a-crawler

Bulldog is an amazing hunting dog that checks for you a list of URLs and warns you by email if one of them returns a http code that is not 200.

https://github.com/pioz/bulldog

https://golangbot.com/error-handling/