ideas4 VS act

https://github.com/samsquire/ideas4#334-knowledgegraph-progr...

How would you do control flow and scheduling and parallelism and async efficiently with this code?

`db.save()`, `download()` are IO intensive whereas `document.query("a")` and `parse` is CPU intensive.

I think its work diagram looks like this: https://github.com/samsquire/dream-programming-language/blob...

I've tried to design a multithreaded architecture that is scalable which combines lightweight threads + thread pools for work + control threads for IO epoll or liburing loops:

Here's the high level diagram:

https://github.com/samsquire/ideas5/blob/main/NonblockingRun...

The secret is modelling control flow as a data flow problem and having a simple but efficient scheduler.

I wrote about schedulers here and binpacking work into time:

https://github.com/samsquire/ideas4#196-binpacking-work-into...

I also have a 1:M:N lightweight thread scheduler/multiplexer:

https://github.com/samsquire/preemptible-thread

My blogging/journalling setup is simple.

I just use GitHub. I just rely on the default repository view on GitHub.com

I create a README.md and add markdown headings to the bottom or to the top (bottom if its a journal, top if it's a blog) and then when I get to 100-800 I create a new repository and repeat.

https://github.com/samsquire/ideas (2013)

https://github.com/samsquire/ideas4

https://github.com/samsquire/ideas3

https://github.com/samsquire/ideas2

Thanks for posting this Ask HN question.

I journal ideas and thoughts about computers and software. I am interested in software architecture, parallelism, async, coroutines, database internals, programming language implementation, software design and the web.

https://github.com/samsquire/ideas (2013)

https://github.com/samsquire/ideas2

https://github.com/samsquire/ideas3

https://github.com/samsquire/ideas4 <-- this is recent but needs editing

https://github.com/samsquire/ideas5 <-- this is what I'm working on now

https://github.com/samsquire/startups

https://github.com/samsquire/blog <-- thoughts I want to write about, but incomplete

I use README.md on GitHub and create a heading at the bottom for each entry. I use Typora on Windows or the GitHub web interface to edit.

My deep interest is multithreaded code. For a software engineer working on business software, I'm not sure if they should be spending too much time debugging multithreaded bugs because they are operating at the wrong level of abstraction from my perspective for business operations.

I'm looking for an approach to writing concurrent code with parallelism that is elegant and easy to understand and hard to introduce bugs. This requires alternative programming approaches and in my perspective, alternative notations.

One such design uses monotonic state machines which can only move in one direction. I've designed a syntax and written a parser and very toy runtime for the notation.

https://github.com/samsquire/ideas5#56-stateful-circle-progr...

https://github.com/samsquire/ideas4#558-state-machine-formul...

The idea is inspired by LMAX Disruptor and queuing systems.

This is really good. Thank you!

I've been studying how to create an asynchronous runtime that works across threads. My goal: neither CPU and IO bound work slow down event loops.

I've only written two Rust programs but in Rust you presumably you can use Rayon (CPU scheduling) and Tokio (IO scheduling)

I wrote about using the LMAX Disruptor ringbuffer pattern between threads.

https://github.com/samsquire/ideas4#51-rewrite-synchronous-c...

I am designing a state machine formulation syntax that is thread safe and parallelises effectively. It looks like EBNF syntax or a bash pipeline. Parallel steps go in curly brackets. There is an implied interthread ringbuffer between pipes.

  states = state1 | {state1a state1b state1c} {state2a state2b state2d} | state3

This is very interesting and could lead to some futuristic programming technology.

I kind of want to plot the state space of a program to see all available states.

In my exploration of distributed systems, microservices and multithreaded systems, it is extremely helpful to try and see what potential states the system can be in. Global and local reasoning of these kinds of software is rather difficult.

I've written about value tracing but I've not heard of treating values as types. I would love to be able to see the trajectory of a value through different states.

https://github.com/samsquire/ideas4#571-value-calculus-varia...

I've never written a TLA+ specification and I'm a complete beginner to this space but I've been trying to understand the dining philosophers one. TLA+ Toolbox is aware of discrete states in the state space, which is absolutely awesome. Types can inform us about future possible valid states.

I began writing a visualisation of memory and animated the movement of memory around to try reveal patterns.

https://replit.com/@Chronological/ProgrammingRTS#index.html

If we see types or values as positions, we can create animations of the state space unfolding in front of us. This is the dream.

Great comment!

>I think late architecture is orthogonal to functional, imperative

Absolutely. From a truly architectural view, procedural, functional, and method-oriented (current OO) are really only variations on the call/return architectural style. Good and sometimes important distinctions, but not really that far apart. They are very much about computing, results from inputs. That is an appropriate architecture for fewer and fewer programs.

See Why Architecture Oriented Programming matters

https://blog.metaobject.com/2019/02/why-architecture-oriente...

and

Can Programmers Escape the Gentle Tyranny of call/return?

https://2020.programming-conference.org/details/salon-2020-p...

> its solution is higher level than even functional programming

Yes. Well, functional actually gets most of its utility from being lower level as far as paradigms go (less powerful). But yes.

> and more abstract

No. Well, yes, if expressed with current programming languages. But that's part of the problem set, not part of the solution set. We should be able to express our architectures less abstractly, more concretely, but for that we need linguistic support. Which is why I am working on that:

http://objective.st

> I want software architecture to be cheap and easy to change without breaking any existing behaviours. I don't know much research on this subject.

There was quite a bit of research at CMU, for example on packaging mismatch. Famous paper Architectural Mismatch, Why Reuse is so hard, and the 10 year follow up in 2009: Architectural Mismatch: Why Reuse is Still So Hard

https://repository.upenn.edu/cgi/viewcontent.cgi?article=107...*

Not much has changed since.

> https://github.com/samsquire/ideas4

> https://devops-pipeline.com

Will check those out. Dataflow is definitely a big part of it, with the extension of dataflow constraints (make, spreadsheets, "FRP"/"Rx"). But so is in-process REST with Storage Combinators!

And breaking down barriers between scripting and "real" programming.

Thanks for this.

I have never deployed a server mesh or used one but I am designing something similar at the code layer. It is designed to route between server components. That is, at the architecture between threads in a multithreaded system.

The problem I want to solve is that I want architecture to be trivially easy to change with minimal code changes. This is the promise and allure of enterprise service buses and messaging queues.

I have managed RabbitMQ and I didn't enjoy it.

If I want a system that can scale up and down and that multiples of any system object can be introduced or removed without drastic rewrites.

I would like to decouple bottleneck from code and turn it into runtime configuration.

My understanding of things such as Traefik and istio is that they are frustrating to set up.

Specifically I am working on designing interthread communication patterns for multithreaded software.

How do you design an architecture that is easy to change, scales and is flexible?

I am thinking of a message routing definition format that is extremely flexible and allows any topology to be created.

https://github.com/samsquire/ideas4#526-multiplexing-setting...

I think there is application of the same pattern to the network layer too.

Each communication event has associated with it an environment of keyvalues that look similar to this:

  petsserver1

Thanks for remembering me :-)

I would like things to run locally by default and then deployed to the cloud where they run.

Should be easier to debug problems if I can get the code to my machine and investigate issues with tools that my computer has such as "strace", "perf" and debug logging that I liberally apply to the build script.

In production we would have log aggregation and log search (such as ELK stack) and it is a good habit to get into the perspective of debugging production via tooling.

But CICD feels before that tooling in the pipeline. You could wire up your CICD to log to ELK but I would prefer local deployable software.

I think my focus on automating things means I want to be capable of seeing how the thing works without relying on a deployed black box in the cloud and using assumptions of how it works rather than direct investigation.

One of my journal entries is almost a lamentation of all the things that need to be done to release and use software.

This is that entry:

https://github.com/samsquire/ideas4#5-permanent-softwareplat...

I wonder if software could be deployed more like a URL that has all the information to configure a virtual machine. Docker over URL or something.

To speed up your development cycle, install and use the act tool to test-run your action directly in your development environment. This tool lets you invoke a GitHub workflow right on your local machine and will save you the round-trips of pushing each change to GitHub to see if it works.

When it comes to the alternatives to tmate, there is another great debugging tool that you could check out. It is called act and it allows you to run GitHub Actions code on your local machine making debugging even easier. It has its own limitations and some learning curve but overall it is another tool you should use if you can’t fix the CI bugs by connecting directly into the running action with the tmate.

Link: https://github.com/nektos/act

Could you upload your build of GitHub's runner image to Docker Hub?

This would be quite useful for users of other GitHub Actions clones like act [0].

[0]: https://github.com/nektos/act

> These kinds of commit messages are typically an indicator of a broken process where somebody needs to commit to see something happen, like a deployment or build process, and aren't able to assert that stuff works locally.

This is one of my biggest pet peeves with services like github actions. Something running locally like "act" [1] isn't sufficient because it doesn't have everything github has and is extra friction anyway to get everyone to use it for testing.

[1] https://github.com/nektos/act

View on GitHub

If you use Github actions, act is incredibly useful. It can be used to test your GH actions, but also serves as an interface for running tasks locally.

That's something that often is difficult or basically impossible. Except for maybe GitHub actions through Act (https://github.com/nektos/act). I'd still lean to something in the yaml sphere if it eventually would be used in deployment pipelines and such. For example a solution incorporating ansible.

It also seems to me that the argument you make is mostly focused on the building step? Earthly certainly seems focused on that aspect.

I feel I'm being trolled, but I'll bite and accept the resulting downvotes

I don't think treating every mention of act as an opportunity for airing of personal grievances is helpful in a discussion when there's already ample reports of people's concrete issues with it, had one looked at the 800 issues in its repo https://github.com/nektos/act/issues?q=is%3Aissue or the 239 from gitea's for https://gitea.com/gitea/act_runner/issues or whatever is going on with Forgejo's fork https://code.forgejo.org/forgejo/act .

But, as for me specifically, there are two and a half answers: I wanted to run VSCodium's build locally, which act for sure puked about. Then, while trying to troubleshoot that, I thought I'd try something simpler and have it run the lint job from act's own repo <https://github.com/nektos/act/blob/1252e551b8672b1e16dc8835d...> to rule out "you're holding it wrong" type junk. It died with

  [checks/lint]     Failure - Main actions/setup-go@v3

https://twitter.com/mitsuhiko/status/1720410479141487099 :

> GitHub Actions currently charges $0.16 per minute* for the macOS M1 Runners. That comes out to $84,096 for 1 machine year*

GitHub Runner is written in Go; it fetches tasks from GitHub Actions and posts the results back to the Pull Request that spawned the build.

nektos/act is how Gitea Actions builds GitHub Actions workflow YAML build definition documents. https://github.com/nektos/act

https://twitter.com/MatthewCroughan/status/17200423527675700... :

> This is the macOS Ventura installer running in 30 VMs, in 30 #nix derivations at once. It gets the installer from Apple, automates the installation using Tesseract OCR and TCL Expect scripts. This is to test the repeatability. A single function call `makeDarwinImage`.

With a Multi-Stage Dockerfile/Containerfild, you can have a dev environment like xcode or gcc+make in the first stage that builds the package, and then the second stage the package is installed and tested, and then the package is signed and published to a package repo / app store / OCI container image repository.

SLSA now specifies builders for signing things correctly in CI builds with keys in RAM on the build workers.

"Build your own SLSA 3+ provenance builder on GitHub Actions" https://slsa.dev/blog/2023/08/bring-your-own-builder-github