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Hi HN,

I've been building fullbleed for a while and just shipped v0.2.5. It's a PDF generation engine written in Rust, distributed as a Python wheel.

The short version: HTML/CSS in, PDF out. No headless browser. No cloud. No Chromium. Works fully offline. *Why fullbleed:

Full Bleed is a term that means printed on the edge, or end to end of a page. Thats what I wanted, a full end to end solution that didn't require sys dependencies and unlike browsers, I could ACTUALLY do a print layout full bleed. Some other reasons: -Deterministic, fixed point as the base measurement (.000035mm~) so that things are where I want them to be -Composition and authoring, so I can put templates and the variable data in the same place without 200 lines of glue code -vendored assets- Tired of handling system fonts etc -HTML/CSS layout engine so that I could take advantage of the most commonly used document description convention, but still abstract away from it. -Agent-first design. I was honestly annoyed with how bad agents were at composing PDFS, and wanted an agent-friendly loop. *What makes it different from WeasyPrint / wkhtmltopdf / Prince:*

- *Deterministic output*: SHA-256 hashing on every render. `--repro-record` / `--repro-check` for CI pipelines. Same inputs always produce the exact same PDF bytes. I don't know of any other open-source PDF engine that does this. - *Structured page data*: The engine returns structured JSON alongside PDF bytes — running totals, per-page sums, grand totals. Useful for financial statements where you want to reconcile programmatically before the PDF even lands. - *Rayon-backed parallel batch*: `render_pdf_batch_parallel()` with Python bindings that release the GIL. You can generate 10,000 statements while your Python process does other work. - *VDP / transactional compose*: Overlay variable data onto source PDF templates with feature-driven page binding. Built-in, not bolted on. - *Agent-safe JSON CLI*: Every command emits a versioned schema. `--json-only` mode for CI and LLM agent workflows. `--schema` for introspection.

*The pricing angle:* Prince costs $3,800+/year per server. DocRaptor starts at $15/month but quickly hits $600/month for real volume — and it's cloud-only. fullbleed is AGPL-3.0 free for OSS, and commercial licenses start at $20/month per org with no usage caps.

*Quick start:* ``` pip install fullbleed fullbleed init . python report.py ```

That scaffolds a full project with Bootstrap 5, Inter font, and component-first Python helpers — all vendored and hash-pinned offline.

GitHub: https://github.com/fullbleed-engine/fullbleed-official

Happy to answer questions about the rendering pipeline, the determinism model, or the Python/Rust binding design.

Comments URL: https://news.ycombinator.com/item?id=47055927

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Article URL: https://www.science.org/content/blog-post/epibatidine-siberia

Comments URL: https://news.ycombinator.com/item?id=47055925

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I built Scanward to solve a problem I kept running into as a DevOps engineer: checking whether a domain has its security basics covered (SSL config, DNS hygiene, HTTP security headers, SPF/DKIM/DMARC) meant juggling 4-5 different tools.

Scanward runs all 5 checks in one scan and gives you an A-F grade with specific findings. The free public scanner requires no signup.

If you create an account (free tier: 1 domain), it does continuous monitoring and emails you when something changes — cert expiring, grade drops, missing headers, etc.

Tech stack: FastAPI + Celery + PostgreSQL + Redis on Railway. Next.js dashboard on Cloudflare Pages. All scanning uses public data (DNS queries, HTTP headers, SSL handshakes) — no agents to install.

Would love feedback on the scoring methodology and what checks you'd want to see added.

Comments URL: https://news.ycombinator.com/item?id=47055885

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Article URL: https://diyclaw.dev

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Article URL: https://github.com/ramanujammv1988/edge-veda

Comments URL: https://news.ycombinator.com/item?id=47055798

Points: 3

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Article URL: https://waymo.com/blog/?modal=short-advice-not-control-the-role-of-remote-assistance

Comments URL: https://news.ycombinator.com/item?id=47055786

Points: 13

# Comments: 3

Article URL: https://www.cnbc.com/2026/02/17/palantir-headquarters-miami-denver.html

Comments URL: https://news.ycombinator.com/item?id=47055769

Points: 4

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Article URL: https://www.poppastring.com/blog/colordriven-code-navigation

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Article URL: https://wiki.lyx.org/LyX/NewInLyX25

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Article URL: https://cocakoala.substack.com/p/when-is-mechanistic-interpretability

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Article URL: https://downdetector.com/status/youtube/

Comments URL: https://news.ycombinator.com/item?id=47055723

Points: 61

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Article URL: https://zeroclaw.bot/

Comments URL: https://news.ycombinator.com/item?id=47055705

Points: 3

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Article URL: https://status.pki.goog/incidents/5oJEbcU3ZfMfySTSXXd3

Comments URL: https://news.ycombinator.com/item?id=47055696

Points: 72

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Article URL: https://www.politico.eu/article/us-threatens-to-quit-international-energy-agency-if-it-doesnt-drop-energy-transition-chris-wright/

Comments URL: https://news.ycombinator.com/item?id=47055683

Points: 4

# Comments: 1

Hi HN,

I’ve been working on a GUI library and ran into a familiar problem: I needed a layout engine that was lightweight, predictable, and easy to integrate. I couldn’t quite find what I wanted, so I ended up building my own. That project became Masharif.

Masharif is a complete Flexbox layout engine. It supports margins, padding, gaps, and the full set of flex properties, with behavior aligned closely to how Flexbox works on the web.

Some technical notes: - Full Flexbox implementation - Supports margin, padding, gaps, and nested layouts - Designed to be simple to embed and reason about

Performance (tested with 10,101 nodes): - Initial layout: ~0.87 ms - Single property edit (width): ~0.07 ms - 100 property edits (flex-grow toggles): ~0.07 ms - Structural change (removing a child): ~0.75 ms

Why another layout engine? Yoga is the obvious industry standard, but I wanted something that feels more idiomatic C++ rather than C-style APIs. Mostly, though, I wanted to take on the challenge and really understand the problem space by building one myself.

I’d love feedback, criticism, or questions.

Comments URL: https://news.ycombinator.com/item?id=47055642

Points: 1

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Article URL: https://www.lucasfcosta.com/blog/design-docs

Comments URL: https://news.ycombinator.com/item?id=47055618

Points: 2

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A greedy phrase-based tokenizer that outperforms GPT-4 and GPT-4o tokenizers on compression, with a smaller vocabulary.

Benchmark (enwik9, 1 GB):

Tokenizer Vocab Size Total Tokens Ratio Throughput GreedyPhrase 65,536 222,805,405 4.49x 47 MB/s Tiktoken o200k_base (GPT-4o) 200,019 270,616,861 3.70x 4.35 MB/s Tiktoken cl100k_base (GPT-4) 100,277 273,662,103 3.65x 7.13 MB/s

GreedyPhrase: 1.23x better than GPT-4, 1.21x better than GPT-4o. 1.5-3x smaller vocab, 6-11x higher encoding throughput.

How It Works:

1. Phrase Mining — Split into atoms (words, punctuation, whitespace). Mine bigrams/trigrams. Top phrases fill 95% vocab slots.

2. BPE Fallback — Train BPE on residual byte sequences. Fills remaining 5% vocab.

3. Greedy Encoding — Longest-match-first Trie. Byte fallback for unknowns (zero OOV).

Comments URL: https://news.ycombinator.com/item?id=47055617

Points: 1

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Article URL: https://www.pcgamer.com/hardware/memory/many-consumer-electronics-manufacturers-will-go-bankrupt-or-exit-product-lines-by-the-end-of-2026-due-to-the-ai-memory-crisis-phison-ceo-reportedly-says/

Comments URL: https://news.ycombinator.com/item?id=47055616

Points: 7

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