HN user

conor_f

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Blog: https://blog.randombits.host Email: hn@randombits.host Resume: https://blog.randombits.host/resume/

Posts20
Comments69
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blog.randombits.host 9mo ago

Why You Should Be Using Git Worktrees

conor_f
5pts6
news.ycombinator.com 1y ago

Ask HN: What Process/Applications Do You Use for Todo/Knowledge Management?

conor_f
12pts13
blog.randombits.host 2y ago

ShowHN: Naming Variables Just Got Harder – Working with AI Models

conor_f
1pts0
news.ycombinator.com 2y ago

Ask HN: How to Keep Up with LLMs? [Linux, Self-Hosting, Info]

conor_f
16pts4
blog.randombits.host 2y ago

Dealing with Being Distrusting of HomeAssistant Notifications

conor_f
1pts0
blog.randombits.host 3y ago

Show HN: Vanity, Recognition and Fighting Perfectionism – Buildlog for Git Vain

conor_f
2pts0
blog.randombits.host 3y ago

Show HN: Vanity, Recognition and Fighting Perfectionism – Buildlog for Git Vain

conor_f
2pts0
blog.randombits.host 3y ago

Show HN: Homelab Monitoring Setup with Grafana

conor_f
155pts83
blog.randombits.host 3y ago

Show HN: PiFrame – Display Currently Playing Spotify Album on an LED Matrix

conor_f
2pts1
blog.randombits.host 3y ago

Show HN: DIYnDNS – I Don't Want to Pay for a Static IP Address

conor_f
6pts6
news.ycombinator.com 3y ago

Ask HN: Best Linux Setup for a Non-Linux User

conor_f
3pts4
news.ycombinator.com 3y ago

What Technologies Are You Future Proofing With?

conor_f
15pts22
blog.randombits.host 3y ago

Show HN: Write Words on Your GitHub Contributions Heatmap

conor_f
13pts2
github.com 4y ago

I modified my GitHub history to write on my contributions heatmap

conor_f
2pts1
news.ycombinator.com 4y ago

Ask HN: What to do with ~30 Raspberry Pi 3B+?

conor_f
2pts4
via.randombits.host 4y ago

Show HN: Via – Simple Visualization of Cycle Route Quality

conor_f
2pts0
news.ycombinator.com 4y ago

Ask HN: How Do You Remember?

conor_f
6pts6
docs.github.com 4y ago

Pressing . in the root of a GitHub repo opens up VSCode

conor_f
1pts0
github.com 5y ago

Show HN: Timewarp – a terse relative syntax Python datetime library

conor_f
3pts0
github.com 5y ago

Show HN: Spotibar – A Spotify/Polybar Integration for Playlists and LastFM

conor_f
1pts0
GitHub Stacked PRs 3 months ago

This is a perfect example that I've often seen in practice. There's nothing blocking in this workflow at all, and no reason these changes cannot be made in independent changes. e.g.

1) API implementation - Including tests and docs this should be perfectly acceptable to merge and review independently 2) UX implementation - Feature flagged, dummy API responses, easy to merge + review 3) One quick "glue" PR where the feature can be integration tested etc

This prevents awful merge conflicts, multiple rounds of increasingly complex stacked reviews, and a host of other annoyances.

Is there any reason that the stacked PR workflow is better that I'm ignoring or overlooking?

GitHub Stacked PRs 3 months ago

This just reeks to me of bad practice. Why use this as opposed to breaking your change into smaller PRs and merging them individually behind a feature flag or similar? With this, you have a marginally better UX for reviewing through the Github website, but the underlying issues are the same. The change being introduced is not sufficiently testable by itself, or it's (somehow) too tightly coupled to other parts of the UI/codebase that it can't be split. You still need to test for integration issues at every point of the stack, and some architecture issues or points of code reuse can't be seen from stacked changes like this.

Not for me, but I'm glad it fits other people's workflows. I just hope it doesn't encourage people to try make poorly reasoned changes!

Location: Berlin, Germany

Remote: Preferred

Willing to Relocate: No

Technologies: Python (+ Frameworks), AWS, Linux, Docker, ...

Résumé/CV: https://www.linkedin.com/in/conorjflynn/ | https://blog.randombits.host/resume (PDF Preview)

Email: hn@randombits.host

Hey, I'm Conor, a software engineer specializing in the backend, but capable of using whatever technologies required to get a problem solved. I have experience with large multinationals, but much prefer my time working with startups. I was the first hire in my current company, and am now looking for a new opportunity having helped the company find product/market fit, scale the solution, and reach a position of stability. Most of my details can be found on my LinkedIn, including links to my Github, Blog, and other technical works.

SEEKING WORK | Berlin, Germany | Remote Preferred

I am a software engineer specializing in Python backends, but have demonstrated ability using whatever technology necessary to best solve the problem at hand. I have experience working with large multinationals, and startups, both in person and on a remote-only basis. My current role is fully remote, and involves software architecture/design decisions, PoC prototyping, DevOps, improving developer tooling, and general purpose programming.

The best place to see my professional experience is on LinkedIn, but feel free to reach out to me by any means you prefer so we can discuss opportunities.

Technologies: Python (+ Frameworks), AWS, Docker, Linux, ...

LinkedIn: https://www.linkedin.com/in/conorjflynn/

Résumé: https://blog.randombits.host/resume/ (PDF Preview)

Github: https://github.com/conor-f

Blog: https://blog.randombits.host

Email: hn@randombits.host

Another interesting thing in this space is Traindown[1]. It's simply Markdown for your exercises. As an example for those who need convincing to go to a link, this could be a simple workout:

  @ Mar 03 2024 08:00
  
  # Unit: kg
  # Bodyweight: 70
  
  Squat:
    40 12r
    65 8r 2s
    40 12r
  
  Assisted Pull Up:
    bw-20 12r
    bw-5 6r
    bw 2r

It's much more free-form than this, which is a bonus for me and allows me to track metadata such as weight, time of day I'm exercising at, or general mood/feeling about the workout. I can ultimately just take these plain markdown files from the app (I use a basic Android app that visualizes this Markdown[2]), import them and do whatever processing I like in Python.

Highly recommended!

[1] https://traindown.com/

[2]https://github.com/traindown/transponder

1) Some general use cases:

  - Getting familiar with new APIs

  - Bouncing general knowledge questions off it

  - Having "discussions" to interact with it in a Socratic style

  - Giving some "personality" to automated services by calling it as an API
2) Thanks for the pointers! Will check them out today!

Thanks, I will look into llama.cpp today :)

I don't have much interest in playing with the internals for now, but I generally like keeping my data personal and the services I use self-maintainable as much as reasonably possible! I also feel like I could find the token limits and price limiting with ChatGPT.

Hey everyone, this is a post I've been working on the past few months about setting up my own monitoring stack with Grafana for my home server.

I'd love your feedback on how this process could be easier for me, some resources on learning the Grafana query languages, and general comments.

Thanks for taking the time to read + engage!

I love the form factor here. A few questions:

1) Have you considered how this could be made more mobile friendly? Most places I could see myself using a device like this, I wouldn't have access to WiFi. Is there an equivalent of a USB SIM card adapter that would fit here?

2) What sort of battery life can be achieved with this?

Looks great though! Am very likely to order an iteration of this :)

My ISP wanted me to pay ten euro per month for a static IPv4 address, so I set up a DIY Dynamic DNS system as I didn't want to use yet another external resource/tool.

Let me know about any improvements I could make and how I can improve my writing as I want to keep writing more blog posts in the future.

Has elementary improved from when I last used it a few years ago? Felt like a standard arch install configured nicely. Things looked great but broke frequently.

I've heard mixed things about ZorinOS including things being less-than-open and fragile too?

Mint and Pop though I should check out

I do think trademarking a color is ridiculous. However, I read something before (likely on HN but I can't find it now) explaining the value companies like Pantone provide. When Pantone "publish" a color, they define how this color will look when displayed on different media, printed, digital, on concrete or on wood, or under different lighting conditions including UV or IR, etc etc. It's a lot more than just saying "I own #AABBCC".

I don't know the specifics of this case, but this looks like it falls firmly into the category of "I'm egotistical" as opposed to the "I am providing additional value" category.

At least in Python's case, I think people are much too hard on the packaging system. I don't think anyone has significant issues with pip itself as opposed to the runtime it exists within.

Following from this, I think that most back-end applications should try solve their messy runtime environment issues with some containerization. Java/C(++) however...

The thing I find most interesting about people saying AI generated content is easily noticeable, is that they're always presented a question of "Do you think this is AI generated content?". Nobody consumes media with a list of questions they ask themselves for each piece of content. I expect people in the comments to explain how obviously fake it is, but barring the ridiculous scene, I'd 100% believe that was legitimate if I saw it with no AI warning.

It definitely will, but as a product people are using, or as a tool/product most developers will be working with? I can see it being the drive force behind popular products, but typically there's not many ML/AI "experts" working to produce models, most of the development work is all around data pipelines and normal product features that will interact with an API that is using ML/AI.

Absolutely. I started learning Docker last year and Nix as a complementary tool this year.

Haven't had the opportunity to look at Kubernetes yet, and usually work higher in the stack than Rust I think! But thanks for the advice.

Create new moonshots for them just because

This seems disingenuous? They're "moonshots" as they've low chance of succeeding. You could pick the most proficient engineers and out-of-the-box thinkers and put them working on a "moonshot" and they'd still fail. Giving that team a new lofty goal seems like a great idea since they have experience working on large problems and can likely prune good/bad approaches much sooner than a fresh team.