* implementing social logins (OAuth), account management, etc.

* managing backend permissions (RBAC always looks more complicated than it should be). My projects might have three tiers: free, hobbyist, pro

* handling payments securely while actually monitoring for abuse/intrusion

Which social logins are allowed to tie into your project?

What are you using for authn/authz? My projects would be very low traffic, so I wouldn't want to commit to a big monthly spend. Are you rolling your own or using Auth0/Clerk/Supabase for auth and Stripe for payments? I'm comfortable with AWS, Cloudflare, Go, JS, and Linux. Are there any GitHub repos that I can look at for this?

How well do frontier LLMs (Claude Opus, etc.) do at generating clean, auditable code for this kind of thing? Is anyone actually trusting AI-written auth/payment code and how do you review it?

Comments URL: https://news.ycombinator.com/item?id=48932993

Points: 3

# Comments: 4

Compute differences between dates, times, durations and timezones

Underlying CLI and Go library: https://github.com/jftuga/DateTimeMate

There is also an example button for each function so that you can see how it works.

If you like find this useful, there is also a GitHub link to the CLI equivalent at the bottom of the page.

https://datetimemate.com/

Comments URL: https://news.ycombinator.com/item?id=48839908

Points: 2

# Comments: 0

They run Debian or Ubuntu great although I usually run them headless and just SSH into them. One experiment I did was with Talos / K8s with about 3 of these and it worked great.

It also handles batch processing (overwrites in-place, preserves mtime), enhanced OCR for degraded images (Zoom calls, transparent terminals) with `-e` flag, and Levenshtein fuzzy matching to catch OCR misreads with the `-d N` flag.

It includes: screenshot and file-glob modes, exact/fuzzy whole-word matching, redact/blur/outline annotation, multi-monitor, multi-term search, list mode, and output control.

Free, open source, written in Swift. Single file, no deps beyond macOS itself.

    brew install jftuga/tap/mac-screen-search

Disclaimer: Vibe coded with Claude Opus 4.6.

Comments URL: https://news.ycombinator.com/item?id=47943666

Points: 2

# Comments: 0

* we had to resolve a variety of bottlenecks that appeared faster than expected from moving webhooks to a different backend (out of MySQL)

* * redesigning user session cache to redoing authentication and authorization flows to substantially reduce database load.

* we accelerated parts of migrating performance or scale sensitive code out of Ruby monolith into Go.

I'd like to know what database backend they migrated to. I was also surprised to read that the migration from Ruby to a more performant language had not already been completed. I assume this is because it a large code base with many moving parts, etc.

Swiss army knife CLI tool written in Swift using only native Apple frameworks.

The primary goal of this project is to demonstrate how many Apple standard library frameworks can be meaningfully used in a single, actually-useful CLI tool.

brew install jftuga/tap/swiftswiss

Comments URL: https://news.ycombinator.com/item?id=47067699

Points: 1

# Comments: 0

    A performance comparison of four common Go string building methods.

I recently updated my go-stats-calculator to include many more stats [2]:

    CLI tool for computing statistics (mean, median, variance, std-dev, skewness, etc.) from files or standard input.

I also created claude-image-renamer [3]:

    AI-powered image renaming script that generates descriptive filenames for screenshots. 

[1] https://github.com/jftuga/go-string-concat-benchmark

[2] https://github.com/jftuga/go-stats-calculator

[3] https://github.com/jftuga/claude-image-renamer

Why: I needed a quick way to look at statistics without having to resort to something heavy such as Python + its statistics module or Excel.

Disclaimer: Vibe-coded by Gemini 2.5 Pro and Opus 4.5 but also validated through unit tests and independent verification[2].

Install: Homebrew[3] or GoReleaser built binaries[4].

Demo:

    $ seq 99 322 | stats

    --- Descriptive Statistics ---
    Count:          224
    Sum:            47152
    Min:            99
    Max:            322
    
    --- Measures of Central Tendency ---
    Mean:           210.5
    Median (p50):   210.5
    Mode:           None
    
    --- Measures of Spread & Distribution ---
    Std Deviation:  64.8074
    Variance:       4200
    Quartile 1 (p25): 154.75
    Quartile 3 (p75): 266.25
    Percentile (p95): 310.85
    Percentile (p99): 319.77
    IQR:            111.5
    Skewness:       0 (Fairly Symmetrical)
    Outliers:       None

[2] https://github.com/jftuga/go-stats-calculator/tree/main?tab=...

[3] https://github.com/jftuga/go-stats-calculator?tab=readme-ov-...

[4] https://github.com/jftuga/go-stats-calculator/releases

Comments URL: https://news.ycombinator.com/item?id=46658302

Points: 2

# Comments: 0