--- title: "🛠️ Firenook Frees Firebase Emulator from Java: 0.59s Startup | Open Source Gems Daily" description: "Firebase's official Emulator Suite takes 30.8 seconds to start with data loaded, while Firenook's own benchmark clocks in at 0.59 seconds, a contrast that earned it 167 points and 28 comments on Hacker News." canonical_url: "https://blog.markkulab.net/en/open-source-weekly/open-source-weekly-2026-11-05" author: "Mark Ku" author_url: "https://blog.markkulab.net/en/author/mark-ku" site: "Mark Ku's Tech Notes" date_published: "2026-11-05T02:00:00.000Z" category: "Open Source Gems Daily" tags: ["open-source", "podcast", "開源工具", "開源", "Firenook", "Firebase", "craft-anything", "Rust", "PJiT", "LinumAI", "HuggingFace"] language: "en" license: "CC BY 4.0" license_url: "https://creativecommons.org/licenses/by/4.0/" attribution: "when reusing or quoting, credit the author and link back to the original" --- # 🛠️ Firenook Frees Firebase Emulator from Java: 0.59s Startup | Open Source Gems Daily ## Opening Firebase's official Emulator Suite takes 30.8 seconds to start with data loaded; Firenook's own benchmarks clock in at 0.59 seconds. That gap earned it 167 points and 28 comments on Hacker News. Today we start with Firenook, then look at craft-anything, a Rust reverse-engineering engine that hit 17.7k★ in 30 days, plus a text-to-image model trained for roughly $21,000 with weights released straight under Apache-2.0. Whether that model is actually usable, I'll get to that in a bit. ## Today's Open Source Picks ### 1. Firenook: a drop-in replacement for the Firebase Local Emulator Suite, no Java required - **What it is**: If you work on Firebase backends, you know the routine: run `firebase emulators:start`, wait for Java to boot, then wait for a pile of services to warm up, and the moment you change something and restart, all your data is gone. Firenook is an Apache-2.0 licensed replacement that reuses your existing `firebase.json`, `.firebaserc`, SDKs, and the same ports (Firestore 8080, Auth 9099, Storage 9199, Functions 5001, Pub/Sub 8085, and so on). Basically you just swap `firebase` for `firenook` in your scripts. The services ship as native code inside a single npm package, no Java install needed, and it runs on Node 22／24／26. - **Recent buzz**: 167 points and 28 comments on Hacker News. The site currently lists version 0.2.1, so it's still very early. - **Highlights**: First, the project claims that under a two-hour stress test against a real app, median write latency was 5.1ms versus the official emulator's 208ms, with peak memory at 2.11GiB versus 22.57GiB. Second, add `--keep-data` and your Firestore／Auth／Storage data survives restarts, with a data-loaded startup of about 0.59 seconds (versus 30.8 seconds officially), and a crash costs you at most the last second of writes. Third, there's a built-in local console covering every service, running on the same port as the official Emulator UI, with Functions／Pub/Sub／Cloud Tasks／Eventarc pages that the official UI doesn't have. There's also `firenook mcp`, exposing 54 tools so agents in Claude Code, Cursor, or VS Code can query logs directly and ask why Security Rules rejected a given request. - **Getting started**: `npm install --save-dev firenook`, run `npx firenook init --adopt --dry-run` first to confirm it recognizes your project, then swap `firebase emulators:start` for `npx firenook emulators:start`. For tests, use `firenook emulators:exec "npm test"`. - **Versus alternatives**: It goes head-to-head with Google's official Firebase Local Emulator Suite, and import/export uses the official format so you can switch back anytime. But the caveats up front: it does not replace firebase-tools, there's no deploy or login, and deployment still goes through the official CLI. Realtime Database, Hosting, App Hosting, and Data Connect are not emulated at all right now, so if your project leans heavily on RTDB, hold off. - **Who it's for**: Frontend and backend engineers who fight Firestore／Auth／Functions local development every day and are done with Java and cold starts. - **Links**: https://firenook.dev/ ／ https://github.com/firenook-dev/firenook ### 2. craft-anything: turning "study how they built it" into "tell an agent to rebuild it" as one pipeline - **What it is**: A reverse-engineering engine written in pure Rust, structured as a four-step flow: Study → Build → Check → Ready. It first studies the original target with inspection tools, then has a coding agent rebuild it in the language and framework you specify, then compares the result against the original (websites get compared at three screen widths, games run self-tests) and iterates on fixes. It's aimed at tooling nerds, and also at anyone who wants to know how a particular interface was put together. - **Recent buzz**: 17.7k ★ on GitHub, and it's a project less than 30 days old. Apache-2.0, primarily Rust. - **Highlights**: The engine ships with 314 tools (298 of them in the engine core) covering native binaries.NET, Java, Android, Apple, Electron／JavaScript, websites, firmware, packet capture, databases, and game files. It bundles its own decoders, disassembler, and decompiler, so it runs without Ghidra installed; if you do have Ghidra, Deep mode will use it too. Every tool is both a CLI subcommand and an MCP tool, so you can `craft-anything-cli mcp` and feed it to any MCP client. Clean room mode is the default: it never reads source code or files, rebuilding purely from screenshots, visible text, and measured layout and color. Any tool that would peek inside is refused outright with a prompt to switch to Deep mode. Viewing the analysis itself doesn't require AI. - **Getting started**: Requires Rust 1.97+. After `git clone`, run `cargo run --release -p craft-anything` for the desktop app, or `cargo install --path apps/craft-anything-cli` to install the CLI, then `craft-anything-cli doctor` to check your environment. If you'd rather not compile, GitHub Releases has signed installers for Windows／macOS／Linux. The quickest way to get a feel for it is `craft-anything-cli rebuild "Recreate this website"`. - **Versus alternatives**: Unlike pure reverse-engineering tools like Ghidra or IDA, it doesn't just hand you pseudo-C and call graphs (Advanced mode has those too), it pipes the analysis into a coding agent to produce a runnable new project, then automatically scores similarity. But be clear-eyed: the README itself says early alpha, and honestly lists three buckets, "works now," "half done," and "coming next." On the build side it currently mainly supports a locally logged-in Claude Code; the Codex adapter hasn't been verified on real hardware, and account and usage come out of your own plan. It also explicitly states it's only for software you own or are permitted to inspect, and it won't bypass DRM, logins, or anti-cheat. Take that one seriously. - **Who it's for**: AI application and tooling engineers who want reverse-engineering analysis wired directly into a coding agent and can live with alpha quality. - **Links**: https://github.com/storytold/craft-anything ### 3. P-JiT (pjit-21k): a 2B text-to-image model trained by two people for about $21,000 in compute - **What it is**: Field Notes published on November 4, 2026 by Linum's two co-CEOs, Sahil Chopra and Manu Chopra, releasing a 2B-parameter Pyramid-JiT (P-JiT) pixel-space text-to-image model with code and weights fully under Apache-2.0. If you want to self-host a generative model, or are just curious how far a small team can actually get, this is material you can pull down and run right now. - **Recent buzz**: 267 points and 29 comments on Hacker News. - **Highlights**: Architecturally, the authors say they shrank the attention context window by 4x and need 11x fewer samples to converge. The released model was trained on 660 million samples, and the authors put total compute cost at roughly $21,000, positioning it as a proof of concept on the way to larger video models. The site hosts 249 generated samples with full prompts, each clickable at original resolution, and the article itself includes a training configuration appendix and a Model Limitations section that doesn't dodge the weak spots. Credit where it's due. - **Getting started**: Grab the `Linum-AI/pjit-21k` weights from Hugging Face and run them on your own GPU with the identically named model code on GitHub. If you don't want to set anything up, click through a few images in the site's gallery to see the prompts and actual outputs first, then decide whether it's worth your time. - **Versus alternatives**: Compared to mature open-weight models like Stable Diffusion or FLUX, this is small and an experimental research release. The real selling point is that it fully documents a "$20k-tier" pixel-space training path, plus a commercially usable Apache 2.0 license, making it good for research and fine-tuning. Don't expect it to replace your current image-generation workhorse. - **Who it's for**: AI engineers researching low-cost training paths, or anyone who needs a commercially licensed small model to fine-tune. - **Links**: https://www.linum.ai/field-notes/pjit-21k ／ https://github.com/Linum-AI/pjit-21k ／ https://huggingface.co/Linum-AI/pjit-21k ## Closing Today's three picks share an obvious theme: they all challenge costs we take for granted in the big-vendor version, whether that's a Java runtime, the human effort of reverse engineering, or the budget for training an image model. If I had to recommend one, Firenook is the only thing here you could swap in at work tomorrow and roll back to the official tooling the moment it breaks. craft-anything and P-JiT are more like weekend toys: fun, but keep an exit plan. See you tomorrow. --- ## About this article and its author Originally published on [Mark Ku's Tech Notes](https://blog.markkulab.net/en/open-source-weekly/open-source-weekly-2026-11-05) License: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — when reusing or quoting, credit the author and link back to the original ### About the author **[Mark Ku](https://blog.markkulab.net/en/author/mark-ku)** — Software engineer - 10+ years as a software engineer - Built North-American e-commerce and AI SaaS subscription billing ### Free tools built by the author All of these are free to use: - [Free PDF Sign Tool](https://blog.markkulab.net/en/tools/pdf-sign): Online PDF sign tool — draw, type, or upload a signature, then drag, resize, and download. Everything runs in your browser; nothing is uploaded. - [VS Code Refactory](https://blog.markkulab.net/en/tools/refactory): Refactory is a VS Code refactoring extension: 34 actions plus a 37-rule code-smell inspection layer with a Code Health dashboard, across 18 languages, backed by 534 tests. It learns your repo's conventions: where interfaces live, where DI is registered, whether 'use client' belongs. It ranks files by git churn × complexity so you know what to fix first, and hands any smell to the Claude Code already on your machine. Free to use, and your source never leaves your computer. - [DB-Kit Database Manager](https://blog.markkulab.net/en/tools/db-kit): DB-Kit is a lightweight, cross-platform database manager built with Tauri + Rust + React. Manage MySQL, MariaDB, PostgreSQL, SQL Server, Oracle, SQLite, MongoDB, Redis, Kafka, Elasticsearch and RabbitMQ from one consistent interface: passwords encrypted in the OS keychain, SSH tunnels, full CRUD, a visual query builder, stacked multi-statement result sets, cross-connection data transfer, schema & data compare with sync SQL and schema snapshots, Excel / CSV import & export, visualized execution plans, ER diagrams, scheduled backups, SQL stress testing with p50–p99 latency percentiles, a 15-rule SQL review engine, Review & Run (AI review plus per-statement backups and an auto-generated rollback script), Kafka message browsing with monitoring & alerts, an SSH terminal with SFTP / FTP, Docker / Kubernetes, remote desktop (RDP / VNC / RustDesk), file / folder compare, stored procedure integration tests, six UI languages, a built-in AI assistant (a local CLI or any Anthropic / OpenAI-compatible API; natural-language SQL, AI review and tuning advice) and the dbk CLI. Free and open source (MIT), with installers for Windows, macOS and Linux. - [VS Code Super Mermaid](https://blog.markkulab.net/en/tools/super-mermaid): Super Mermaid is a VS Code extension for beautiful Mermaid diagrams out of the box: auto-colored live preview, mouse pan & zoom, high-res PNG / SVG export, 21 templates and multiple themes. Free and open source (MIT). - [React Super Mermaid](https://blog.markkulab.net/en/tools/react-super-mermaid): react-super-mermaid is an open-source React component library: render beautiful Mermaid diagrams with a single , with built-in colorful / sketch themes, pan & zoom, in-diagram search, and high-res SVG / PNG export. Lightweight, SSR-safe, fully typed. 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No sign-up, nothing uploaded to a server, and mermaid.live share links work as-is. - [React Intl Phone Number](https://blog.markkulab.net/en/tools/react-intl-phone-number): react-intl-phone-number is an open-source React component: framework-agnostic and antd-free, with E.164 in/out, a searchable flag / country-code dropdown, configurable validation levels (strict / mobile-strict / loose), themeable CSS, and i18n — phone logic powered by google-libphonenumber. Lightweight and fully typed. Free and open source (MIT). - [Uptime Kuma Cluster](https://blog.markkulab.net/en/tools/uptime-kuma-cluster): Turn single-node Uptime Kuma into a highly available cluster: OpenResty + Lua smart load balancing, shared MariaDB state, health checks and automatic failover, plus cluster-management REST APIs. One Docker Compose command to start. Free and open source (MIT). - [AI Podcast Cut](https://blog.markkulab.net/en/tools/ai-podcast-cut): Drop in a recording and it removes fillers and stutters, levels loudness segment by segment, and sends a second agent to review every cut. Cut points snap to word boundaries and zero crossings, every splice gets a fade, and sentence-end breaths are preserved. Desktop app for Windows, macOS and Linux. MIT licensed; the Windows installer bundles ffmpeg. - [AI Video Cut](https://blog.markkulab.net/en/tools/ai-video-cut): Pick something in your video: type it (face, license plate, phone screen, logo), click points or drag a box, or let Claude Code / Codex pick it. AI Video Cut tracks it frame by frame, then mosaics or blurs it, recolors it, pins stickers and text to it, swaps a screen or poster for your own image or video, or removes it using background that other frames actually captured. Plus sequence editing, local captions and an AI assistant. Free, open-source (MIT) Windows desktop app (macOS / Linux experimental) that runs locally, nothing uploaded. - [open-pos restaurant POS](https://blog.markkulab.net/en/tools/open-pos): One computer and one receipt printer is enough to open the shop. Your data lives on your own disk, no subscription, no lock-in, MIT licensed. Money is integer New Taiwan dollars with tax split by the statutory formula, so sales + tax always equals the total. Printing goes straight over ESC/POS on TCP 9100, with no vendor driver. Tauri + Rust + SQLite desktop app, v1.0 in development. - [.NET e-commerce API template](https://blog.markkulab.net/en/tools/dotnet-ecommerce-api): An e-commerce backend API template built on .NET 10: Controller → Service → Repository layering, Autofac convention-based registration, SqlSugar for MySQL / MariaDB and SQL Server, Redis cache and message queue, Hangfire jobs, JWT auth, and an extensible payment provider module (ECPay, Newebpay). Apache 2.0. - [Open Token Monitor team AI usage](https://blog.markkulab.net/en/tools/open-token-monitor): Collect token usage and equivalent cost from every employee's AI coding tools into a hub you host yourself: PostgreSQL, org roster, dashboards compared by company and department, and a reports API. Electron and Rust/Tauri clients upload every 30 minutes. MIT licensed, one Docker command. - [ai-security-monitor defensive security](https://blog.markkulab.net/en/tools/ai-security-monitor): Your website is live. Who checks its certificates, security settings and known vulnerabilities? A self-hosted Security Hub brings website scans and host monitoring together, deduplicates findings and compares scans after fixes. ### Daily podcasts - [Mark's Tech Insights — Daily AI News](https://blog.markkulab.net/en/category/tech-news): Daily curated AI and tech trends. 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