Task VS Testify

So many tools in this space! This one looks a little bit like go-task, but it seems maybe better for production workflows because if timeout support, while go-task seems more aimed to command line work/makefile replacement.

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https://github.com/go-task/task

View on GitHub

A similar tool is `task` https://taskfile.dev/ . It is quite capable and also a single executable. I've grown to quite like it.

check out tasks - a bit of a learning curve but arguably more powerful imo

That's when I came across taskfile.dev. Task is an automation tool designed to be more accessible than other options, such as GNU Make.

Full disclosure, I did not review Conda or Hatch fully. Not that there is anything explicitly wrong with either of them. Conda is too specific to the scientific community for my general taste. Hatch seems to go well with Conda and also uses the PyProject manifest as well. It's nice that it gives you several built in tools, similar to commit hooks, but I tend to like to roll my own via a Taskfile and run them with Poetry.

Taskfile is a tool for streamlining repetitive development tasks. It helps automate activities like building, testing, and deploying applications. Unlike Makefile, Taskfile uses YAML for configuration, making it more readable and user-friendly.

9. We test everything with another promotion which runs make targets which build docker containers to run python scripts (pytest)

This is also built by a complicated web of wildcarded makefile targets, which need to be interoperable and support a few if/else cases for specific components.

My plan is to migrate all of this to something simpler and more straightforward, or at least more maintainable, which is honestly probably going to turn into taskfile[0] instead of makefiles, and then simple python scripts for the glue that ties everything together or does more complex logic.

My hope is that it can be more straightforward and easier to maintain, with more component-ized logic, but realistically every step in that labyrinthine build process (and that's just the open-source version!) came from a decision made by a very talented team of engineers who know far more about the process and the product than I do. At this point I'm wondering if it would make 'more sense' to replace it with a giant python script of some kind and get access to all the logic we need all at once (it would not).

[0] https://taskfile.dev/

task - a task runner and a replacement for make

github.com/stretchr/testify

I then verify that there are no issues with writing the body with require.NoError() from the testify toolkit. This will ensure the test fails if something happens to go wrong at this point.

For testing purposes, Go provides a go test command that automatically discovers tests within your application and supports features such as caching and code coverage. However, if you require more advanced testing capabilities such as suites or mocking, you will need to install a toolkit like testify. Overall, while Go provides a highly effective testing experience, it's worth noting that writing tests in Python using pytest is arguably one of the most enjoyable testing experiences I have encountered across all programming languages.

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

Im thinking in wrap or not the library https://github.com/stretchr/testify to do my tests.

Are you limited to the std lib, or can you use testify? You can require things like require.Error()

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

To answer OP directly, I am largely quite happy with mockery (and testify) to write expressive tests.

Como herramientas te recomiendo: FastJson https://github.com/valyala/fastjson : Si necesitas leer jsons Testify https://github.com/stretchr/testify : Para mockear y testear