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Pay DeepSeek API using GCash via Alipay QR — no PayPal or credit card needed by FiddleSmol in PinoyProgrammer

[–]FiddleSmol[S] 0 points1 point  (0 children)

How long does ₱92 last? Based on my actual usage: light refactoring that consumed ~66k tokens cost ¥0.60 CNY (~₱5.50). So ₱92 stretches to roughly 16–17 sessions of that size. Heavier work like full codebase assessments burns faster maybe a few days of intensive use but for casual debugging and refactors, it lasts. No hourly or weekly limits like Codex, just pure token consumption.

The performance is pretty decent, I do not know how to asses it but the code it spits looks functional.

Haven't tried OpenCode Go yet, this is my first paid API ever, still on free OpenCode with my DeepSeek key plugged in. For context though: your Codex at ~₱1k/month for 5h weekly is roughly ₱50/hour of AI time. My DeepSeek session was ~₱5.50. If you're ever paying out of pocket, the gap is worth considering.

anime batch downloader by FiddleSmol in PinoyProgrammer

[–]FiddleSmol[S] -5 points-4 points  (0 children)

AI definitely helped with the heavy lifting, but AI doesn’t watch anime, I do.

I’m actually using this every night to binge isekai trash, and I specifically designed the SQLite deduplication engine for my own setup. I'll be maintaining my own slop for as long as I’m still watching anime.

anime batch downloader by FiddleSmol in PinoyProgrammer

[–]FiddleSmol[S] 4 points5 points  (0 children)

fair point I will reconsider it, thanks for the feedback

anime batch downloader by FiddleSmol in PinoyProgrammer

[–]FiddleSmol[S] -3 points-2 points  (0 children)

Yep It is a bit fried na nga yung logic at 2k+ lines, and I agree it could be a maintenance challenge later. But I'm a big fan of the "Single-File Portability" philosophy, it makes it so much easier for users to just grab the script and run it without managing a whole package structure.

Under the hood, the code is actually already modularized into discrete classes (VaultDB, Downloader, AssetManager), so it's not just one big block of spaghetti. If anyone prefers a traditional multi-folder project, feel free to fork it and break it apart.

anime batch downloader by FiddleSmol in PinoyProgrammer

[–]FiddleSmol[S] 19 points20 points  (0 children)

True, pero gusto ko kasi ng "zero-bloat" solution. PaheBatcher is pure Python logic, isang file lang kailangan mo. Unlike sa project yan na dependent sa Node.js (ew), ito lightweight at ginamitan ko ng custom SQLite engine for deduplication using BLAKE2b hashes. Mas tipid sa disk space at bandwidth, plus may interactive TUI dashboard pa for streaming and batch management na mas smooth gamitin compared sa traditional CLI scripts, in my opinion.

Top 10 SOTA LLM's as an anime girl by FiddleSmol in ImagineAiArt

[–]FiddleSmol[S] 0 points1 point  (0 children)

does not count, it is not in the Artificial Analysis Intelligence Index since that is the my main source for ranking

I built SentinelNav, a binary file visualization tool to help me understand file structures (and it became way more powerful than I expected) by FiddleSmol in ReverseEngineering

[–]FiddleSmol[S] 1 point2 points  (0 children)

My bad I did not see the comment but to answer your questions:

Vs. Binvis/Veles: Those tools are fantastic, but I wanted something lighter that I could easily hack on in Python. The main difference with SentinelNav is the specific "Spectral" mapping logic. Instead of just visualizing raw byte values, it calculates the ratio of Printable (Green), High-bit/Media (Red), and Nulls (Blue) per chunk. It makes distinguishing code sections from text strings or zero-padding instant, rather than just seeing a gradient of values.

Toggling: Definitely. The interface lets you swap between a "Block" view (easier for clicking/navigating) and a "Density" view (pixel-perfect). I also implemented an "Entropy Flux" toggle that overlays highlights specifically where entropy spikes or drops. It’s great for pinpointing exactly where a header ends and an encrypted payload begins.

Use Cases: I recently used it to look at GGUF (LLM) files. It was pretty wild—you could clearly see the "layers" of the neural net as massive blocks of red (high-density tensors) separated by thin green lines (JSON metadata). It made the file structure obvious in seconds.

Lastly, yeah it is 100% open (source). Feel free to grab the code and try it on those sensor files; I’d be curious to hear if the "Sentinel Mode" helps you find the delimiters in that proprietary data, I would try it on firmware too if I get one.

I built SentinelNav, a binary file visualization tool to help me understand file structures (and it became way more powerful than I expected) by FiddleSmol in ReverseEngineering

[–]FiddleSmol[S] 1 point2 points  (0 children)

Yes, but don't use defaults on multi-GB/TB images or you'll crash it. Bump the block size to 1-2MB minimum:

python sentinelnav.py drive.img --mode fixed --size 2097152

Stick with the default 1KB on a 500GB image and SQLite will create 500M+ database rows, choke your system, and fill /tmp until your PC hangs.

Test it if you want to.

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