godog VS venom

Compare godog vs venom and see what are their differences.


🐍 Manage and run your integration tests with efficiency - Venom run executors (script, HTTP Request, web, imap, etc... ) and assertions (by ovh)
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godog venom
4 6
1,980 796
1.4% 2.0%
5.1 6.7
2 days ago 1 day ago
Go Go
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.


Posts with mentions or reviews of godog. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-19.


Posts with mentions or reviews of venom. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-21.
  • Ask HN: What's your favorite software testing framework and why?
    15 projects | news.ycombinator.com | 21 May 2023
    You can also load fixtures in database directly, work with Kafka queues both as a producer (e.g. write an event to a Kafka queue, wait a few seconds and see that it was consumed by the service you test, and that some side effects can be observed) or as a consumer (e.g. make sure after an HTTP call, an event was correctly pushed to a queue), or even read a mailbox in IMAP to check that your service correctly send an email.

    It's a bit rough on the edges sometimes, but I'd never go back on writing integration tests directly in my programming language. Declarative is the way to go.

    [1]: https://github.com/ovh/venom

  • Show HN: Step CI – API Testing and Monitoring Made Simple
    11 projects | news.ycombinator.com | 10 Oct 2022
    From my experience, generated tests are worthless for anything more serious than smoke tests. I prefer working with no tests than automated tests, I feel they give you a false sense of confidence.

    The Step CI engine itself looks good though. It looks like a cleaner, but less powerful version of a tool (open source, build in-house) we used when I worked at OVHcloud, Venom: https://github.com/ovh/venom

    Here's an example test file for the HTTP executor of Venom: https://github.com/ovh/venom/blob/master/tests/http.yml it's very close to Step CI format.

    I'd still use Venom because it's way more powerful (you have DB executors for example, so after executing a POST request you can actually check in DB that you have what you expect) and I prefer focusing on actually writing integration tests instead of generating them.

    Maybe this post sounds harsh (I feel it as I write it because I have strong feelings against test generation) but I think your approach is a good one for actually writing automated tests. Testing APIs declaratively like this has a great benefit: your tests work on an interface. You can migrate your API to a whole new stack and your tests remain the same. I did it multiple time at OVHcloud: one time migrating a huge API from a Go router to another (Gin->Echo), and another time migrating public APIs from a legacy, in-house Perl engine to a Go server.

  • Debugging with GDB
    13 projects | news.ycombinator.com | 21 Mar 2022
    I still struggle with GDB but my excuse is that I seldom use it.

    When I was studying reverse engineering though, I came across a really cool kit (which I've yet to find an alternative for lldb, which would be nice given: rust)

    I'd recommend checking it out, if for no other reason than it makes a lot of things really obvious (like watching what value lives in which register).


    LLDB's closest alternative to this is called Venom, but it's not the same at all. https://github.com/ovh/venom

  • Do you write integration tests in go?
    3 projects | reddit.com/r/golang | 7 Sep 2021
    We incorporated [Venom](https://github.com/ovh/venom) into our workflow. It's great for initiating and managing a suite of yaml based tests. It didn't work out of the box for us due to the heavily asynchronous nature of our system, but after a few additions, it has helped my team greatly. We were often afraid to make large changes to critical pieces of the system since a full regression test could take a week or so to check everything. Now it takes an hour.

What are some alternatives?

When comparing godog and venom you can also consider the following projects:

ginkgo - A Modern Testing Framework for Go

GoConvey - Go testing in the browser. Integrates with `go test`. Write behavioral tests in Go.

Testify - A toolkit with common assertions and mocks that plays nicely with the standard library

assert - :exclamation:Basic Assertion Library used along side native go testing, with building blocks for custom assertions

gomega - Ginkgo's Preferred Matcher Library

Gauge - Light weight cross-platform test automation

go-cmp - Package for comparing Go values in tests

httpexpect - End-to-end HTTP and REST API testing for Go.

dockertest - Write better integration tests! Dockertest helps you boot up ephermal docker images for your Go tests with minimal work.

testcontainers-go - Testcontainers for Go is a Go package that makes it simple to create and clean up container-based dependencies for automated integration/smoke tests. The clean, easy-to-use API enables developers to programmatically define containers that should be run as part of a test and clean up those resources when the test is done.

gospecify - A BDD library for Go

go-mutesting - Mutation testing for Go source code