dockertest VS sqlx

I am using https://github.com/ory/dockertest for tests, specifically for databases. Is there any advantage to use Testcontainers?

Now, let's run the tests. For this purpose, we are going to use dockertest, but test containers is also a good solution.

During my path learning go so far I have come across some amazing libraries and utilites, one of my favourite for integration testing is dockertest.

Things I can't live without in a new Go project in no particular order:

- https://github.com/golangci/golangci-lint - meta-linter

- https://goreleaser.com - automate release workflows

- https://magefile.org - build tool that can version your tools

- https://github.com/ory/dockertest/v3 - run containers for e2e testing

- https://github.com/ecordell/optgen - generate functional options

- https://golang.org/x/tools/cmd/stringer - generate String()

- https://mvdan.cc/gofumpt - stricter gofmt

- https://github.com/stretchr/testify - test assertion library

- https://github.com/rs/zerolog - logging

- https://github.com/spf13/cobra - CLI framework

FWIW, I just lifted all the tools we use for https://github.com/authzed/spicedb

We've also written some custom linters that might be useful for other folks: https://github.com/authzed/spicedb/tree/main/tools/analyzers

I've used dockertest a bunch and it is really amazing.

Reminds me of https://github.com/ory/dockertest

If your project is relatively simple and you can get away with recreating your scenarios against a real mock database and run other related services locally. It would be good to setup docker containers for your test scripts and write e2e tests. I believe e2e tests are harder but more useful in understanding/reasoning how users are impacted.

Just a heads up, the repository in your comment is invalid, the correct link is https://github.com/ory/dockertest

Don't mock. Use https://github.com/ory/dockertest to actually run tests against a dockerized DB.

Use a library like ory/dockertest to spin up a test database for integration tests. It's easy to use, and tests are still fast. It'll take a minute to download the mysql docker image the first time. But, once it's been downloaded, starting the db, running migrations, and running the tests is still pretty quick.

We've always used https://github.com/jmoiron/sqlx which is just the standard package + mapping to/from structs.

You can use this https://github.com/jmoiron/sqlx

I will be using sqlx to execute queries and map columns to struct fields and vice versa, sqlx is a library which provides a set of extensions on go's standard database/sql library.

sqlx + squirrel ftw

I'd rather suggest the use of tools more aligned with the core concepts of the language such as sqlx, which is an extension of the database/sql standard library. It allows you to use models/structs to map your tables but you have more control over the SQL statements you use to perform queries and the like. You can combine sqlx with Squirrel to build queries from composable parts.

IDE: use whatever make you productive. I personally use vscode. VCS: git, as golang communities use github heavily as base for many libraries. AFAIK Linter: use staticcheck for linting as it looks like mostly used linting tool in go, supported by many also. In Vscode it will be recommended once you install go plugin. Libraries/Framework: actually the standard libraries already included many things you need, decent enough for your day-to-day development cycles(e.g. `net/http`). But here are things for extra: - Struct fields validator: validator - Http server lib: chi router , httprouter , fasthttp (for non standard http implementations, but fast) - Web Framework: echo , gin , fiber , beego , etc - Http client lib: most already covered by stdlib(net/http), so you rarely need extra lib for this, but if you really need some are: resty - CLI: cobra - Config: godotenv , viper - DB Drivers: sqlx , postgre , sqlite , mysql - nosql: redis , mongodb , elasticsearch - ORM: gorm , entgo , sqlc(codegen) - JS Transpiler: gopherjs - GUI: fyne - grpc: grpc - logging: zerolog - test: testify , gomock , dockertest - and many others you can find here

This is the same situation I saw 20 years ago. Back then, all the managers were pushing development in Oracle tools. Those managers grew up on Oracle and Java was too modern for them. Now the situation is similar. Managers used to do things in Java and now they are still pushing Java. In fact, today Java brings nothing but problems. When I see a new project starting on Java it is always some big desperation. For a comparison of Java and Go, just look at the documentation for SQL. For go: https://pkg.go.dev/database/sql (31 pages) and maybe https://jmoiron.github.io/sqlx/ (12 pages). In Java only one class is 59 pages (https://docs.oracle.com/javase/8/docs/api/java/sql/ResultSet.html) and look how many of those documents there are: https://docs.oracle.com/en/java/javase/13/docs/api/java.sql/java/sql/package-summary.html and on top of that we have javax.sql - https://docs.oracle.com/javase/8/docs/api/javax/sql/package-summary.html And even then you use Hibernate for example, where the documentation has 11 manuals and of those the User Guide has 353 pages - https://docs.jboss.org/hibernate/orm/6.2/userguide/html\_single/Hibernate\_User\_Guide.html

sqlx