TDPrint
Native macOS app for professional thermal label printing
What it does
TDPrint is the first native macOS app designed specifically for thermal label printing with Brother, Zebra and Star printers. Visual label editor with barcode generator (Code128, EAN13, QR, DataMatrix), batch printing from CSV, dynamic variables, and Odoo integration. No drivers required. Perpetual license from €290.
Does the same job
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This is a device, to which you connect your older USB printer, and use it from any PC or smartphone without installing drivers (AirPrint/Mopria), wirelessly. As easy as that! * Supports all OS: Windows, macOS, Linux, iOS, Android. No drivers needed. Windows-on-ARM and Apple M1/2/3/4 also supported. * Supports the majority of printers released before ≈2018 * Profit from sold devices is shared between CUPS, SANE, AirSane open-source printing and scanning projects * Surplus and donations are accumulated to improve current open-source drivers and develop new ones The printer…
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I've always been fascinated by thermal printers – there's something magical about seeing text and images materialize on paper in seconds. But I found that working with them programmatically was always a pain. You either had to deal with ancient printer protocols or use clunky vendor-specific SDKs. So I built Printercow (https://printercow.com) – it turns any thermal printer into an HTTP endpoint with just one command. Technical details: - Supports any ESC/POS compatible printer (Epson, Star Micronics, etc.) - Handles paper widths from 58mm to 120mm - Automatic image dithering…
- ABAirPrint Bridge: Enable AirPrint for Non-AirPrint Printers on macOS2024 · github.com · ▲63
Lightweight, open-source, and fully automated, AirPrint Bridge uses macOS's built-in tools to bridge the gap without relying on external software. Perfect for reviving your trusty old printer!

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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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