google-cloud VS go

Hello. So we use big query as database for all events that are happening in the project. And one of the features on the frontend is to display events with detailed view and so. Also one thing that we're using there is infinite scroll, so you can hit and fetch more requests. Based on that I do not know if the current approach is something correct. Basically we need out of process pagination where we create a job on the first request and then on next requests we paginate over the results. Using more or less this solution now: https://github.com/googleapis/google-cloud-go/issues/8173

I am trying to run the tests with https://github.com/googleapis/google-cloud-go.

is this different from google’s? https://github.com/googleapis/google-cloud-go/wiki/Iterator-Guidelines

Go

I would go with GCP. There are Go examples everywhere in the GCP documentation and here is the official Go lib for GCP https://github.com/googleapis/google-cloud-go

I'm struggling to find the idiomatic Go SDK API from GCP and how to use the existing one https://cloud.google.com/go/docs/reference # don't have DNS package https://github.com/googleapis/google-cloud-go # don't have DNS package https://github.com/googleapis/google-api-go-client # has DNS package but I can't find one way to list my managed DNS zones So in this case, what can I do? So far I've done the following, I want to change the func hostList() to something dynamic generated based on my Google Cloud DNS zones.

package logx import ( "fmt" "net/http" ) func info(r *http.Request, message interface{}, projectID string) { get := r.Header.Get("X-Cloud-Trace-Context") traceID, spanID, traceSampled := deconstructXCloudTraceContext(get) traceID = fmt.Sprintf("projects/%s/traces/%s", projectID, traceID) entry := logEntry{ Severity: "INFO", Message: message, HttpRequest: &httpRequest{ RequestMethod: r.Method, RequestUrl: r.URL.String(), UserAgent: r.UserAgent(), RemoteIp: r.RemoteAddr, Referer: r.Referer(), }, Timestamp: time.Now(), Labels: map[string]string{"labels": "rock"}, SpanID: spanID, TraceID: traceID, TraceSampled: traceSampled, } writelog(&entry) } func writelog(entry *logEntry) { if err := json.NewEncoder(os.Stderr).Encode(entry); err != nil { fmt.Printf("failure to write structured log entry: %v", err) } } // taken from https://github.com/googleapis/google-cloud-go/blob/master/logging/logging.go#L774 var reCloudTraceContext = regexp.MustCompile( // Matches on "TRACE_ID" `([a-f\d]+)?` + // Matches on "/SPAN_ID" `(?:/([a-f\d]+))?` + // Matches on ";0=TRACE_TRUE" `(?:;o=(\d))?`) func deconstructXCloudTraceContext(s string) (traceID, spanID string, traceSampled bool) { // As per the format described at https://cloud.google.com/trace/docs/setup#force-trace // "X-Cloud-Trace-Context: TRACE_ID/SPAN_ID;o=TRACE_TRUE" // for example: // "X-Cloud-Trace-Context: 105445aa7843bc8bf206b120001000/1;o=1" // // We expect: // * traceID (optional): "105445aa7843bc8bf206b120001000" // * spanID (optional): "1" // * traceSampled (optional): true matches := reCloudTraceContext.FindStringSubmatch(s) traceID, spanID, traceSampled = matches[1], matches[2], matches[3] == "1" if spanID == "0" { spanID = "" } return }

The Google Cloud Client Libraries for Go generally use gRPC under the hood to connect with Google Cloud APIs. When you create an API client, the library initializes a connection to the API then leaves that connection open until you call Close on the Client.

Anyone have experience with testing google pubsub event handlers locally? https://github.com/googleapis/google-cloud-go/tree/pubsub/v1.5.0/pubsub

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/.