golang-standards/project-layout
docker
golang-standards/project-layout | docker | |
---|---|---|
195 | 152 | |
45,978 | 516 | |
1.0% | 1.0% | |
6.4 | 0.0 | |
about 2 months ago | 2 days ago | |
Makefile | Go | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
golang-standards/project-layout
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The power of the CLI with Golang and Cobra CLI
cmd: here where we will leave the main.go that starts our app.
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What's your go to literature to build Go libraries?
> https://github.com/golang-standards/project-layout
The name of the repo is really and intentionally misleading. rsc filled an issue there to point this out, but the repo maintainer just disabled issues altogether so now no one can see it.
Even when it would not have such parasitic name, many seasoned Go programmers, me included, consider the self-proclaimed "Standard Go project Layout" as the opposite of what is good and advisable.
Unfortunately, the name just works, so it is being recommended all over the Internet since its inception.
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"14 Years of Go" by Rob Pike
Your comment makes it look as if you're saying you hate the Go development team, but it seems that isn't the case.
I get a little of what you're saying, I wouldn't say I hate anyone, but I strongly dislike how a lot of projects are organized. I think a lot stems from https://github.com/golang-standards/project-layout , which pretended to be standard and was so (ab)used one of the creators opened an issue about it. If you look at the actual Go src, it's much, much cleaner.
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Looking for elegant code bases written in GoLang
So you don't get blind sided for self proclaimed "standards" that are not
- I'm coming from Java and I have been told that I'm writing go like I'm writing Java. Basically creating structs, injecting fields, and attaching methods. What else can I do?
- O poder do CLI com Golang e Cobra CLI
- Como deixar o Swagger com tema dark mode usando Swaggo e Golang
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Can I point a module to a subdirectory?
I am writing a project that has two components: a CLI and a library. I've organised the project as follows (as per organisation instructions):
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How To Build A Containerized Microservice in Golang: A Step-by-step Guide with Example Use-Case
Familiarity with the standard Golang project structure, which you can find here.
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Building RESTful API with Hexagonal Architecture in Go
I've been learning how to build web applications using different frameworks and languages for a while now, such as Laravel with its MVC architecture and Node.js following the 'Hapi.js Way'. As I'm trying to create a new portfolio project using Go, I found myself contemplating over the ideal project structure. I wanted something that not only aligns with the standard Go project layout, but also makes the code both easy to write and understand. That's when I stumbled upon the concept of Hexagonal Architecture, as showcased in Netflix's engineering blog. The idea of seamlessly swapping infrastructures with minimal code changes fascinated me, and I decided to implement it in my new project.
docker
- Live reload em Go com docker e compile daemon
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My Favorite DevTools to Build AI/ML Applications!
Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.
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Ask HN: What software sparks joy when using?
Linux Mint with Cinnamon: https://www.linuxmint.com/ as far as desktop OSes go it's familiar (Ubuntu without snaps by default), whereas the UI feels both snappy, doesn't use too much resources and is actually pretty to look at.
MobaXTerm: https://mobaxterm.mobatek.net/ this one is a bit more Windows centric but I ended up paying for it and replaced mRemoteNg and PuTTY with it, it's even better than Remmina or whatever Linux has to offer - you can manage SSH/RDP/VNC/... sessions, input across multiple sessions side by side and it just simplifies things a lot (jump host support, a port forwarding too and so much more).
GitKraken: https://www.gitkraken.com/ also a piece of software that I paid for, this one actually makes using Git pleasant, feels better to use than SourceTree and Git Cola (even though that latter is wonderfully lightweight, too) and honestly I prefer that to the CLI nowadays.
Kanboard: https://kanboard.org/ is a lightweight Kanban project management tool, it might not have every feature under the sun but it's the most snappy project management tool I've ever used, looks simple and runs well. I honestly love it, what a nice thing to have.
Most modern text editors and IDEs: I personally pay for JetBrains IDEs but also like Visual Studio Code as a text editor and both have helped me immensely, they're reasonably performant when you have the RAM, look nice, often give you suggestions about how to improve your code and also have a plethora of plugins in their ecosystems. Nowadays I unapologetically use LLMs as well and overall it feels like I have these great tools and cool autocomplete (that is sometimes a bit silly and wrong) at my disposal, that makes me happy.
Kdenlive: https://kdenlive.org/ imagine if there was a successor to Windows Movie Maker, though something that gets most of the important stuff out of Sony Vegas, except is also completely free and works on most platforms. Kdenlive is all of that and also somehow quite pleasant to use, I actually prefer it to DaVinci resolve. There is a bit of a learning curve to any piece of software like this, but everything mostly makes sense in this one.
Gitea: https://about.gitea.com/ I still use this for my personal Git repositories and integrating with CI systems and it's lightweight, looks good and just feels pleasant to use. Previously I self-hosted GitLab and constantly ran into resource exhaustion as well as doubts about the next update is going to corrupt all of my data and break (it did), so now I use Gitea instead.
Drone CI: https://www.drone.io/ a container native CI solution that I can also self host. It's container oriented, integrates with Gitea nicely, is similarly nice to GitLab CI and doesn't cause me headaches like Jenkins would.
Docker: https://www.docker.com/ yes, even Docker desktop. It just makes working with containers really pleasant and predictable, even when something like Podman also exists (and also is great). I don't know, I feel like Docker really saved me from having brittle legacy environments, even self-contained containers with health checks and resource limits with still the same brittle code inside of those make me feel way more safe.
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Build and deploy a REST API with Postgres database in TypeScript
Note: Before running your application in the next step, make sure you have Docker installed and running. It's required to locally run Encore applications with databases.
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Introducing WP Setup
Developing WordPress plugins and themes often requires a reliable development environment. Current we have good solutions as wp-env from Autommatic, Local WP from WP Engine, Docker, XAMPP (for old ones) and so on. All this can be good suits for a development environment, specially Local WP that is probably the easiest one to get up and running and wp-env that leverages Docker as a development environment in a very easy way to use.
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Building Scalable GraphQL Microservices With Node.js and Docker: A Comprehensive Guide
Docker, an open-source development platform, provides containerization technology for building and packaging applications along with their dependencies into portable images.
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Building Llama as a Service (LaaS)
With each app containerized with Docker, this allows it to be run on any other developer's machine also running Docker. Although I had automated deployments to Heroku without this, I decided to upload each service to a container registry.
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Exploring 7 Efficient Alternatives to MAMP for Local Development Environments
Docker
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The power of the CLI with Golang and Cobra CLI
Today we are going to see all the power that a CLI (Command line interface) can bring to development, a CLI can help us perform tasks more effectively and lightly through commands via terminal, without needing an interface. For example, git and Docker, we practically use their CLI all the time, when we execute a git commit -m "commit message" or docker ps -a we are using a CLI. I'm going to leave an article that details what a CLI is.
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Simplest Guide to DIY Your Own LLM Toy in 2024
Docker (required): Understanding Docker is crucial for deploying software in containers, making your project portable and scalable. I use it for start Folo server.
What are some alternatives?
uber-go-style-guide-kr - Uber's Go Style Guide Official Translation in Korean. Linked to the uber-go/guide as a part of contributions
SillyTavern - LLM Frontend for Power Users.
modern-go-application - Modern Go Application example
SillyTavern-extras - Extensions API for SillyTavern [Moved to: https://github.com/SillyTavern/SillyTavern-extras]
uber-go-style-guide-th - Uber's Go Style Guide Translation in Thai. Linked to the uber-go/guide as a part of contributions https://github.com/uber-go/guide
SillyTavern-Extras - Extensions API for SillyTavern.
go-restful-api - An idiomatic Go REST API starter kit (boilerplate) following the SOLID principles and Clean Architecture
winget-pkgs - The Microsoft community Windows Package Manager manifest repository
cookiecutter-golang - A Go project template
SillyTavern - LLM Frontend for Power Users. [Moved to: https://github.com/SillyTavern/SillyTavern]
service - Starter-kit for writing services in Go using Kubernetes.
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.