Dagger2
dagger
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Dagger2 | dagger | |
---|---|---|
50 | 92 | |
17,311 | 10,228 | |
0.2% | 4.1% | |
9.1 | 9.9 | |
3 days ago | about 6 hours ago | |
Java | Go | |
Apache License 2.0 | Apache License 2.0 |
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.
Dagger2
- Dagger 2.49 (KSP, @AssistedInject with @HiltViewModel, more)
- Dagger 2.48 adds alpha KSP support
- Dagger KSP update & Breaking changes required to use Dagger KSP
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Performance and memory impact of the @Singleton annotation in Dagger
There used to be a thing called "releasable references" which was that. It was removed, though: https://github.com/google/dagger/issues/1117
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Dependency injection with AWS Lambdas in java
As said in the title, we will focus on the dependency inversion principle and one of its application : dependency injection. For production-ready applications, it would be better to rely on a framework and not implement its own container. For it, the java ecosystem have 3 frameworks available : Spring, Guice and Dagger.
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Refactoring our Dependency Injection using Anvil
At Reddit, we use Dagger 2 for handling dependency injection (DI) in our Android application. As we’ve scaled the application over the years, we’ve accrued a bit of technical debt in how we have approached this problem.
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Dagger Python SDK: Develop Your CI/CD Pipelines as Code
Confusing. I initially thought someone ported the Dagger DI framework to Python: https://dagger.dev/
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Multiplatform dependency injection libraries equivalent to Dagger/Anvil
I'm currently using Dagger and Anvil for my DI needs. It's been working really well, especially around what Anvil permits in terms of multibindings defined on the type declaration rather than in a module. For example:
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Dagger 2.43 released with support for multiple instances of the same ViewModel using keys 🎉
Great job, I have been waiting for this feature/fix for a long time https://github.com/google/dagger/issues/2328
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Best libraries for Android Developers
Dagger
dagger
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Nix is a better Docker image builder than Docker's image builder
The fact that I couldn't point to one page on the docs that shows the tl;dr or the what problem is this solving
https://docs.dagger.io/quickstart/562821/hello just emits "Hello, world!" which is fantastic if you're writing a programming language but less helpful if you're trying to replace a CI/CD pipeline. Then, https://docs.dagger.io/quickstart/292472/arguments doubles down on that fallacy by going whole hog into "if you need printf in your pipline, dagger's got your back". The subsequent pages have a lot of english with little concrete examples of what's being shown.
I summarized my complaint in the linked thread as "less cowsay in the examples" but to be honest there are upteen bazillion GitHub Actions out in the world, not the very least of which your GHA pipelines use some https://github.com/dagger/dagger/blob/v0.10.2/.github/workfl... https://github.com/dagger/dagger/blob/v0.10.2/.github/workfl... so demonstrate to a potential user how they'd run any such pipeline in dagger, locally, or in Jenkins, or whatever by leveraging reusable CI functions that setup go or run trivy
Related to that, I was going to say "try incorporating some of the dagger that builds dagger" but while digging up an example, it seems that dagger doesn't make use of the functions yet <https://github.com/dagger/dagger/tree/v0.10.2/ci#readme> which is made worse by the perpetual reference to them as their internal codename of Zenith. So, even if it's not invoked by CI yet, pointing to a WIP PR or branch or something to give folks who have CI/CD problems in their head something concrete to map into how GHA or GitLabCI or Jenkins or something would go a long way
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Testcontainers
> GHA has "service containers", but unfortunately the feature is too basic to address real-world use cases: it assumes a container image can just … boot! … and only talk to the code via the network. Real world use cases often require serialized steps between the test & the dependencies, e.g., to create or init database dirs, set up certs, etc.)
My biased recommendation is to write a custom Dagger function, and run it in your GHA workflow. https://dagger.io
If you find me on the Dagger discord, I will gladly write a code snippet summarizing what I have in mind, based on what you explained of your CI stack. We use GHA ourselves and use this pattern to great effect.
Disclaimer: I work there :)
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BuildKit in depth: Docker's build engine explained
Dagger (https://dagger.io) is a great way to use BuildKit through language SDKs. It's such a better paradigm, I cannot imagine going back.
Dagger is by the same folks that brought us Docker. This is their fresh take on solving the problem of container building and much more. BuildKit can more than build images and Dagger unlocks it for you.
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Cloud, why so difficult? 🤷♀️
And suddenly, it's almost painfully obvious where all the pain came from. Cloud applications today are simply a patchwork of disconnected pieces. I have a compiler for my infrastructure, another for my functions, another for my containers, another for my CI/CD pipelines. Each one takes its job super seriously, and keeps me safe and happy inside each of these machines, but my application is not running on a single machine anymore, my application is running on the cloud.
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Share your DevOps setups
That said I've been moving my CI/CD to https://dagger.io/ which has been FANTASTIC. It's code based so you can define all your pipelines in Go, Python, or Javascript and they all run on containers so I can run actions locally without any special setup. Highly recommended.
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What’s with DevOps engineers using `make` of all things?
You are right make is arcane. But it gets the job done. There are new exciting things happening in this area. Check out https://dagger.io.
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Shellcheck finds bugs in your shell scripts
> but I'm not convinced it's ready to replace Gitlab CI.
The purpose of Dagger it's not to replace your entire CI (Gitlab in your case). As you can see from our website (https://dagger.io/engine), it works and integrates with all the current CI providers. Where Dagger really shines is to help you and your teams move all the artisanal scripts encoded in YAML into actual code and run them in containers through a fluent SDK which can be written in your language of choice. This unlocks a lot of benefits which are detailed in our docs (https://docs.dagger.io/).
> Dagger has one very big downside IMO: It does not have native integration with Gitlab, so you end up having to use Docker-in-Docker and just running dagger as a job in your pipeline.
This is not correct. Dagger doesn't depend on Docker. We're just conveniently using Docker (and other container runtimes) as it's generally available pretty much everywhere by default as a way to bootstrap the Dagger Engine. You can read more about the Dagger architecture here: https://github.com/dagger/dagger/blob/main/core/docs/d7yxc-o...
As you can see from our docs (https://docs.dagger.io/759201/gitlab-google-cloud/#step-5-cr...), we're leveraging the *default* Gitlab CI `docker` service to bootstrap the engine. There's no `docker-in-docker` happening there.
> It clumps all your previously separated steps into a single step in the Gitlab pipeline.
This is also not the case, we should definitely improve our docs to reflect that. You can organize your dagger pipelines in multiple functions and call them in separate Gitlab jobs as you're currently doing. For example, you can do the following:
```.gitlab-ci.yml
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Cicada – A FOSS, Cross-Platform Version of GitHub Actions and Gitlab CI
Check out https://dagger.io/. Write declarative pipelines in code, reproducibly run anywhere.
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Show HN: Togomak – declarative pipeline orchestrator based on HCL and Terraform
Is this similar to Dagger[1] ?
[1] https://dagger.io
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Ask HN: What's the fastest platform for deploying code with CI/CD?
Hey, https://dagger.io employee here. We can help with this. I'd recommend taking a look at out Python SDK (https://docs.dagger.io/sdk/python) to build your pipelines and then leverage Dagger Cloud (https://dagger.io/blog/dagger-cloud) for fast production deployments.
What are some alternatives?
Guice - Guice (pronounced 'juice') is a lightweight dependency injection framework for Java 11 and above, brought to you by Google.
earthly - Super simple build framework with fast, repeatable builds and an instantly familiar syntax – like Dockerfile and Makefile had a baby.
Toothpick - A scope tree based Dependency Injection (DI) library for Java / Kotlin / Android.
pipeline - A cloud-native Pipeline resource.
Weld - Weld, including integrations for Servlet containers and Java SE, examples and documentation
gitlab-ci-local - Tired of pushing to test your .gitlab-ci.yml?
butterknife - Bind Android views and callbacks to fields and methods.
act - Run your GitHub Actions locally 🚀
HK2
aws-cdk - The AWS Cloud Development Kit is a framework for defining cloud infrastructure in code
Dynamic CDI - Dynamic Context Dependency Injection
dagster - An orchestration platform for the development, production, and observation of data assets.