golangci-lint-action VS go

# source: https://github.com/golangci/golangci-lint-action?tab=readme-ov-file#how-to-use name: golangci-lint on: push: branches: - master - main pull_request: permissions: contents: read # Optional: allow read access to pull request. Use with `only-new-issues` option. # pull-requests: read jobs: golangci: name: lint runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - uses: actions/setup-go@v4 with: go-version: '1.21' cache: false - name: golangci-lint uses: golangci/golangci-lint-action@v3 with: # Require: The version of golangci-lint to use. # When `install-mode` is `binary` (default) the value can be v1.2 or v1.2.3 or `latest` to use the latest version. # When `install-mode` is `goinstall` the value can be v1.2.3, `latest`, or the hash of a commit. version: v1.54 # Optional: working directory, useful for monorepos # working-directory: somedir # Optional: golangci-lint command line arguments. # # Note: By default, the `.golangci.yml` file should be at the root of the repository. # The location of the configuration file can be changed by using `--config=` # args: --timeout=30m --config=/my/path/.golangci.yml --issues-exit-code=0 # Optional: show only new issues if it's a pull request. The default value is `false`. # only-new-issues: true # Optional: if set to true, then all caching functionality will be completely disabled, # takes precedence over all other caching options. # skip-cache: true # Optional: if set to true, then the action won't cache or restore ~/go/pkg. # skip-pkg-cache: true # Optional: if set to true, then the action won't cache or restore ~/.cache/go-build. # skip-build-cache: true # Optional: The mode to install golangci-lint. It can be 'binary' or 'goinstall'. # install-mode: "goinstall"

Finally, we can use golangci-lint's provided GitHub Action for linting - it runs golangci-lint on the workflow runner's clone of the repo and outputs an error code if any Go file in the repo fails rules of any linters in golangci-lint. Note that golangci-lint fails if the AST cannot be parsed (i.e. if there are any syntax errors), so it can also be used for checking syntax correctness, which itself is a good proxy for checking for merge conflict strings. We can fail-fast with any checks this way - there's no need to spin up a compilation and a go test invocation if there are syntax errors.

If you want to run golangci-lint in CI, you can use golangci-lint-action same as other actions.

A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.

I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles

The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397

There used to be the GO FIPS branch :

https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...

But it looks dead.

And it looks like https://github.com/golang-fips/go as well.

I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:

- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644

- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412

Here are some excerpts from the latest Go survey [1]:

- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."

- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."

I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.

[1]: https://go.dev/blog/survey2024-h1-results

Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.

Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!

net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements

Make sure you have Go installed https://go.dev/.