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openai/openai-cookbook

✨ Navigate at cookbook.openai.com Example code and guides for accomplishing common tasks with the OpenAI API . To run these examples, you'll need an OpenAI account and associated API key ( create a free account here ). Set an environment variable called OPENAI_API_KEY with your API key. Alternatively, in most IDEs such as Visual Studio Code, you can create an .env file at the root of your repo containing OPENAI_API_KEY=<your API key> , which will be picked up by the notebooks. Most code examples are written in Python, though the concepts can be applied in any language. For other useful tools, guides and courses, check out these related resources from around the web . Contributing The OpenAI Cookbook is a community-driven resource. Whether you're submitting an idea, fixing a typo, adding a new guide, or improving an existing one, your contributions are greatly appreciated! Before contributing, read through the existing issues and pull requests to see if someone else is already working on something similar. That way you can avoid duplicating efforts. If there are examples or guides you'd like to see, feel free to suggest them on the issues page . If you'd like to contribute new content, make sure to read through our contribution guidelines . We welcome high-quality submissions of new examples and guides, as long as they meet our criteria and fit within the scope of the cookbook. The contents of this repo are automatically rendered into cookbook.openai.com based on registry.yaml .

Examples and guides for using the OpenAI API

openai,chatgpt,gpt-4,openai-api

immich-app/immich

High performance self-hosted photo and video management solution Català Español Français Italiano 日本語 한국어 Deutsch Nederlands Türkçe 中文 Русский Português Brasileiro Svenska العربية Disclaimer ⚠️ The project is under very active development. ⚠️ Expect bugs and breaking changes. ⚠️ Do not use the app as the only way to store your photos and videos. ⚠️ Always follow 3-2-1 backup plan for your precious photos and videos! Content Official Documentation Roadmap Demo Features Introduction Installation Contribution Guidelines Documentation You can find the main documentation, including installation guides, at https://immich.app/. Demo You can access the web demo at https://demo.immich.app For the mobile app, you can use https://demo.immich.app/api for the Server Endpoint URL bash title="Demo Credential" The credential email: demo@immich.app password: demo Spec: Free-tier Oracle VM - Amsterdam - 2.4Ghz quad-core ARM64 CPU, 24GB RAM Activities Features | Features | Mobile | Web | | :--------------------------------------------- | -------- | ----- | | Upload and view videos and photos | Yes | Yes | | Auto backup when the app is opened | Yes | N/A | | Prevent duplication of assets | Yes | Yes | | Selective album(s) for backup | Yes | N/A | | Download photos and videos to local device | Yes | Yes | | Multi-user support | Yes | Yes | | Album and Shared albums | Yes | Yes | | Scrubbable/draggable scrollbar | Yes | Yes | | Support raw formats | Yes | Yes | | Metadata view (EXIF, map) | Yes | Yes | | Search by metadata, objects, faces, and CLIP | Yes | Yes | | Administrative functions (user management) | No | Yes | | Background backup | Yes | N/A | | Virtual scroll | Yes | Yes | | OAuth support | Yes | Yes | | API Keys | N/A | Yes | | LivePhoto/MotionPhoto backup and playback | Yes | Yes | | Support 360 degree image display | No | Yes | | User-defined storage structure | Yes | Yes | | Public Sharing | No | Yes | | Archive and Favorites | Yes | Yes | | Global Map | Yes | Yes | | Partner Sharing | Yes | Yes | | Facial recognition and clustering | Yes | Yes | | Memories (x years ago) | Yes | Yes | | Offline support | Yes | No | | Read-only gallery | Yes | Yes | | Stacked Photos | Yes | Yes | Contributors Star History

High performance self-hosted photo and video management solution.

backup-tool,mobile-app,photo-gallery,photos,self-hosted,videos,flutter,nestjs,nodejs,google-photos-alternative

AykutSarac/jsoncrack.com

JSON Crack (formerly JSON Visio) The open-source JSON Editor. Learn more » Discord · Website · Issues · VS Code About the Project More Than a JSON Editor JSON Crack is a free, open-source data visualization app capable of visualizing data formats such as JSON, YAML, XML, CSV and more, into interactive graphs. With its intuitive and user-friendly interface, JSON Crack makes it easy to explore, analyze, and understand even the most complex data structures. Whether you're a developer working on a large-scale project or a data enthusiast looking to uncover hidden insights, JSON Crack has the tools and features you need to unlock the full potential of your data. Dark mode. Graph & Tree view modes. Transform & filter data with AI. Export to PNG, SVG, JPEG & clipboard. Zoom and panning support with touch gestures. Supports data formats like JSON, YAML, CSV, XML, TOML... JQ, JSON Schema, Decode JWT, Generate Types and interfaces. Wide range of tools - search graph, json path, validate, save to cloud... Embeddable iframe widgets. Recognition Built With Next.js Reaflow React.js Tailwind CSS Supabase Stay Up-to-Date JSON Crack officially launched as v1.0 on the 17th of February 2022 and we've come a long way so far. Watch releases of this repository to be notified of future updates: Getting Started To get a local copy up and running, please follow these simple steps. Prerequisites Here is what you need to be able to run JSON Crack. Node.js (Version: >=18.x) Pnpm (recommended) Development Setup Clone the repo into a public GitHub repository (or fork https://github.com/AykutSarac/jsoncrack.com/fork). If you plan to distribute the code, read the LICENSE for additional details. sh git clone https://github.com/AykutSarac/jsoncrack.com.git Go to the project folder sh cd jsoncrack.com Install packages with yarn sh pnpm install Run the project ```sh pnpm dev # Running on http://localhost:3000/ ``` Docker 🐳 A Dockerfile is provided in the root of the repository. If you want to run JSON Crack locally: ```console Build a Docker image with: docker build -t jsoncrack . Run locally with docker run docker run -p 8888:8080 jsoncrack Run locally with docker-compose docker-compose up -d Go to http://localhost:8888 ``` Contributing Please see our contributing guide . Good First Issues We have a list of help wanted that contain small features and bugs which have a relatively limited scope. This is a great place to get started, gain experience, and get familiar with our contribution process. Contributors License Distributed under the AGPLv3 License . See LICENSE for more information.

✨ Innovative and open-source visualization application that transforms various data formats, such as JSON, YAML, XML, CSV and more, into interactive graphs.

json,tool,react,visualization,graph,nextjs,diagrams,csv,yaml

heyxyz/hey

Hey Decentralized, and permissionless social media app 🌿 hey.xyz » Discord • Issues 🌿 About Hey Hey is a cutting-edge social media application that leverages the power of Lens Protocol 🌿 to create a decentralized and permissionless platform for users to interact, share, and engage with one another. With a focus on privacy, security, and user control, Hey aims to revolutionize the social media landscape by providing a more transparent and equitable digital environment for its users. 📦 Environments | Name | Link | | ------- | ----------------------- | | Mainnet | https://hey.xyz | | Testnet | https://testnet.hey.xyz | | Staging | https://staging.hey.xyz | ✅ Community For a place to have open discussions on features, voice your ideas, or get help with general questions please visit our community at Discord . 📊 Repo Activity 💕 Contributors We love contributors! Feel free to contribute to this project but please read the Contributing Guidelines before opening an issue or PR so you understand the branching strategy and local development environment. ⚖️ License Hey is open-sourced software licensed under the © AGPLv3 .

Hey is a decentralized and permissionless social media app built with Lens Protocol 🌿

web3,blockchain,graphql,hacktoberfest,nextjs,react,social-media,typescript,arweave,ipfs

CodeEditApp/CodeEdit

CodeEdit for macOS CodeEdit is a code editor built by the community, for the community, written entirely and unapologetically for macOS. Features include syntax highlighting, code completion, project find and replace, snippets, terminal, task running, debugging, git integration, code review, extensions, and more. [!IMPORTANT] CodeEdit is currently in development and not yet recommended for production use, however you can take part in shaping it's future by test-driving pre-release versions and submitting an issue to let us know what you think. Table of Contents Motivation Mission Community Activity Contributing Contributors Sponsors Backers License Motivation Most editors in use today rely on Electron or other cross-platform frameworks, limiting their ability to fully utilize system resources. While Xcode provides a native experience, it is specifically designed for projects targeting Apple platforms. We think developers working on projects not written for Apple platforms deserve that same macOS-native experience we get with Xcode while unlocking the full potential of the Mac. This raised the question "what if such an editor existed?", a question that led to the creation of this concept , which our project aims to make a reality. Mission It is our commitment to keep CodeEdit open source and free forever, supported by the community. Our goal is to maintain a lightweight experience, similar to TextEdit, while being able to scale up to a more feature-rich experience, comparable to Xcode, as necessary. We strive to remain true to Apple's human interface guidelines and development patterns, ensuring CodeEdit looks and feels like an application developed by Apple themselves, which includes a meticulous attention to detail. Community Join our growing community on Discord and GitHub Discussions where we discuss and collaborate on all things CodeEdit. Don't be shy, jump right in and be part of the discussion! [!NOTE] We hold a weekly meetup on Discord every Saturday at 3pm UTC where we discuss latests development, feature requests, goals, and priorities. Join us Activity Contributing Be part of the next revolution in code editing by contributing to the project. This is a community-led effort, so we welcome as many contributors who can help. Read the Contribution Guide for more information. This project spans multiple repositories so instead of browsing issues in the issues tab, it may be helpful to find an issue to get started on in our project board . For issues we want to focus on that are most relevant at any given time, please see the issues scoped to our current iteration here . Contributors Austin Condiff 🎨 💻 Lukas Pistrol 🚇 ⚠️ 💻 Khan Winter 💻 🐛 Matthijs Eikelenboom 💻 🐛 Wouter Hennen 💻 Wesley De Groot 🚇 ⚠️ 💻 KaiTheRedNinja 💻 Pavel Kasila 🚇 ⚠️ 💻 Marco Carnevali 🚇 ⚠️ 💻 Nanashi Li 💻 ninjiacoder 💻 Cihat Gündüz 💻 Rehatbir Singh 💻 Angelk90 💻 Stef Kors 💻 Chris Akring 💻 highjeans 💻 Jason Platts 🚇 🔌 Rob Hughes 💻 Lingxi Li 💻 🐛 HZ.Liu 💻 🐛 Richard Topchii 💻 Pythonen 💻 Javier Solorzano 💻 🐛 Cosmin Anghel 💻 Shivesh 💻 Andrey Plotnikov 💻 POPOBE97 💻 nrudnyk 💻 Ben Koska 💻 evolify 🐛 Shibo Tong 💻 Ethan Wong 💻 Gabriel Moreno 🐛 Sizhe Zhao 🐛 Muhammed Mahmood 💻 🚧 Muescha 💻 Alex Sinelnikov 💻 Heewon Cho 🐛 Matt Kiazyk 💻 DingoBits 💻 Shoto Kobayashi 🐛 💻 Aaryan Kothari 🐛 Kyle 💻 Nakaoka Rei 💻 🐛 Alex Deem 🚧 deni zakya 🐛 Ahmad Yasser 🐛 ezraberch 💻 Elias Wahl 🐛 bombardier200 💻 Alex Yapryntsev 💻 Code-DJ 💻 🐛 Neilzon Viloria 🐛 Cubik 🐛 💻 Renan Greca 💻 maxkel 🐛 💻 Scrap 💻 iggy890 💻 Sara Tavares 🐛 💻 luah5 💻 Evan Wang 💻 Dscyre Scotti 💻 Tomáš Boďa 🐛 Ahmed Attalla 🐛 💻 Esteban Borai 💻 avinizhanov 🐛 💻 kmohsin11 🐛 Axel Martinez 🐛 💻 Federico Zivolo 💻 Elvis Wong 🐛 İbrahim Çetin 🐛 phlpsong 🐛 Ahnaf Mahmud 💻 Dan K 💻 Roscoe Rubin-Rottenberg 💻 Paul Ebose 🐛 Daniel Zhu 🐛 Simon Whitaker 🐛 Sponsors Support CodeEdit's development by becoming a sponsor . Backers Support CodeEdit's development by becoming a backer . Thanks to all of our other backers @ivanvorobei @albertorestifo @rkusa @cadenkriese @petrjahoda @allejo @frousselet @wkillerud License Licensed under the MIT license . Related Repositories CodeEditKit CodeEditTextView CodeEditSourceEditor CodeEditLanguages CodeEditCLI

CodeEdit App for macOS – Elevate your code editing experience. Open source, free forever.

macos,apple,code-edit,swift,swiftui,ipados,ios,open-source,ide,code-editor

paperless-ngx/paperless-ngx

Paperless-ngx Paperless-ngx is a document management system that transforms your physical documents into a searchable online archive so you can keep, well, less paper . Paperless-ngx is the official successor to the original Paperless & Paperless-ng projects and is designed to distribute the responsibility of advancing and supporting the project among a team of people. Consider joining us! Thanks to the generous folks at DigitalOcean , a demo is available at demo.paperless-ngx.com using login demo / demo . Note: demo content is reset frequently and confidential information should not be uploaded. Features Getting started Contributing Community Support Translation Feature Requests Bugs Related Projects Important Note This project is supported by: Features A full list of features and screenshots are available in the documentation . Getting started The easiest way to deploy paperless is docker compose . The files in the /docker/compose directory are configured to pull the image from GitHub Packages. If you'd like to jump right in, you can configure a docker compose environment with our install script: bash bash -c "$(curl -L https://raw.githubusercontent.com/paperless-ngx/paperless-ngx/main/install-paperless-ngx.sh)" More details and step-by-step guides for alternative installation methods can be found in the documentation . Migrating from Paperless-ng is easy, just drop in the new docker image! See the documentation on migrating for more details. Documentation The documentation for Paperless-ngx is available at https://docs.paperless-ngx.com . Contributing If you feel like contributing to the project, please do! Bug fixes, enhancements, visual fixes etc. are always welcome. If you want to implement something big: Please start a discussion about that! The documentation has some basic information on how to get started. Community Support People interested in continuing the work on paperless-ngx are encouraged to reach out here on github and in the Matrix Room . If you would like to contribute to the project on an ongoing basis there are multiple teams (frontend, ci/cd, etc) that could use your help so please reach out! Translation Paperless-ngx is available in many languages that are coordinated on Crowdin. If you want to help out by translating paperless-ngx into your language, please head over to https://crwd.in/paperless-ngx, and thank you! More details can be found in CONTRIBUTING.md . Feature Requests Feature requests can be submitted via GitHub Discussions , you can search for existing ideas, add your own and vote for the ones you care about. Bugs For bugs please open an issue or start a discussion if you have questions. Related Projects Please see the wiki for a user-maintained list of related projects and software that is compatible with Paperless-ngx. Important Note Document scanners are typically used to scan sensitive documents like your social insurance number, tax records, invoices, etc. Paperless-ngx should never be run on an untrusted host because information is stored in clear text without encryption. No guarantees are made regarding security (but we do try!) and you use the app at your own risk. The safest way to run Paperless-ngx is on a local server in your own home with backups in place .

A community-supported supercharged version of paperless: scan, index and archive all your physical documents

angular,archiving,django,dms,document-management,document-management-system,machine-learning,ocr,optical-character-recognition,pdf

hyprwm/Hyprland

![Badge Workflow] [![Badge License]][License] ![Badge Language] [![Badge Pull Requests]][Pull Requests] [![Badge Issues]][Issues] ![Badge Hi Mom] Hyprland is a dynamic tiling Wayland compositor based on wlroots that doesn't sacrifice on its looks. It provides the latest Wayland features, is highly customizable, has all the eyecandy, the most powerful plugins, easy IPC, much more QoL stuff than other wlr-based compositors and more... --- **[ Install ][Install]**  **[ Quick Start ][Quick Start]**  **[ Configure ][Configure]**  **[ Contribute ][Contribute]** --- Features All of the eyecandy: gradient borders, blur, animations, shadows and much more A lot of customization Much more QoL stuff than other wlr-based compositors Custom bezier curves for the best animations Powerful plugin support Built-in plugin manager Tearing support for better gaming performance Easily expandable and readable codebase Fast and active development Not afraid to provide bleeding-edge features Config reloaded instantly upon saving Fully dynamic workspaces Two built-in layouts and more available as plugins Uses forked wlroots with QoL patches Global keybinds passed to your apps of choice Tiling/pseudotiling/floating/fullscreen windows Special workspaces (scratchpads) Window groups (tabbed mode) Powerful window/monitor/layer rules Socket-based IPC Native IME and Input Panels Support and much more... # Gallery ![Preview A] ![Preview B] ![Preview C] Special Thanks wlroots - For their amazing library tinywl - For showing how 2 do stuff Sway - For showing how 2 do stuff the overkill way Vivarium - For showing how 2 do stuff the simple way dwl - For showing how 2 do stuff the hacky way Wayfire - For showing how 2 do some graphics stuff

Hyprland is a highly customizable dynamic tiling Wayland compositor that doesn't sacrifice on its looks.

wayland,wayland-compositor,compositor,wlroots,cpp23

pyscript/pyscript

PyScript What is PyScript Summary PyScript is a framework that allows users to create rich Python applications in the browser using HTML's interface and the power of Pyodide , MicroPython and WASM , and modern web technologies. To get started see the Beginning PyScript tutorial . For examples see here . Other useful resources: The official technical docs . Our current Home Page on the web. A free-to-use online editor for trying PyScript. Our community Discord Channel , to keep in touch . Every Tuesday at 15:30 UTC there is the PyScript Community Call on zoom, where we can talk about PyScript development in the open. Most of the maintainers regularly participate in the call, and everybody is welcome to join. Every other Thursday at 16:00 UTC there is the PyScript FUN call: this is a call in which everybody is encouraged to show what they did with PyScript. For more details on how to join the calls and up to date schedule, consult the official calendar: Google calendar in UTC time; iCal format . Longer Version PyScript is a meta project that aims to combine multiple open technologies into a framework that allows users to create sophisticated browser applications with Python. It integrates seamlessly with the way the DOM works in the browser and allows users to add Python logic in a way that feels natural both to web and Python developers. Try PyScript To try PyScript, import the appropriate pyscript files into the <head> tag of your html page: ```html ``` You can then use PyScript components in your html page. PyScript currently offers various ways of running Python code: <script type="py"> : can be used to define python code that is executable within the web page. <script type="py" src="hello.py"> : same as above, but the python source is fetched from the given URL. <script type="py" terminal> : same as above, but also creates a terminal where to display stdout and stderr (e.g., the output of print() ); input() does not work. <script type="py" terminal worker> : run Python inside a web worker: the terminal is fully functional and input() works. <py-script> : same as <script type="py"> , but it is not recommended because if the code contains HTML tags, they could be parsed wrongly. <script type="mpy"> : same as above but use MicroPython instead of Python. Check out the official docs for more detailed documentation. How to Contribute Read the contributing guide to learn about our development process, reporting bugs and improvements, creating issues and asking questions. Check out the developing process documentation for more information on how to setup your development environment. Governance The PyScript organization governance is documented in a separate repository. Release To cut a new release of PyScript simply add a new release while remembering to write a comprehensive changelog. A GitHub action will kick in and ensure the release is described and deployed to a URL with the pattern: https://pyscript.net/releases/YYYY.M.v/ (year/month/version - as per our CalVer versioning scheme). Then, the following three separate repositories need updating: Documentation - Change the version.json file in the root of the directory and then node version-update.js . Homepage - Ensure the version referenced in index.html is the latest version. PSDC - Use discord or Anaconda Slack (if you work at Anaconda) to let the PSDC team know there's a new version, so they can update their project templates.

Try PyScript: https://pyscript.com Examples: https://tinyurl.com/pyscript-examples Community: https://discord.gg/HxvBtukrg2

python,html,javascript,wasm

djsime1/awesome-flipperzero

A collection of Awesome resources for the Flipper Zero device. 👋 New to Flipper Zero? Got questions? Check out the FAQ Document ❗ 🚫 Not affiliated with Flipper Devices Inc. Table of Contents (Expandable) Databases & Dumps - [General](#general) - [Sub-GHz](#sub-ghz) - [NFC/RFID](#nfcrfid) - [Infrared](#infrared) - [BadUSB](#badusb) - [Music](#music) - [Other](#other) Applications & Plugins - [General](#general-1) - [Sub-GHz](#sub-ghz-1) - [Infrared](#infrared-1) - [BadUSB](#badusb-1) - [GPIO](#gpio) - [Bluetooth](#bluetooth) - [Games](#games) - [Utility/Other](#utilityother) Firmwares & Tweaks - [Official firmware (ofw)](#official-firmware-ofw) - [Custom firmware (cfw)](#custom-firmware-cfw) - [Outdated/Unmaintained firmware](#outdatedunmaintained-firmware) Graphics & Animations - [Tutorials](#tutorials) - [Pre-made animations](#pre-made-animations) - [Utilities](#utilities) Modules & Cases - [Modules](#modules) - [Cases](#cases) - [Other](#other) Off-device & Debugging - [General](#general-2) - [Converters](#converters) - [Development](#development) - [Utility](#utility) Notes & References - [Disassembly/Repair](#disassemblyrepair) - [Guides](#guides) - [Specifications](#specifications) - [Other](#other-2) Databases & Dumps Got a need for speed? 📥 Look at this for an archive containing every item listed below! General UberGuidoZ Playground Large collection of files, documentation, and dumps of all kinds. Sub-GHz FlipperZero-TouchTunes Dumps of TouchTune's remote. T119 bruteforcer Triggers Retekess T119 restaurant pagers. flipperzero-bruteforce Generate .sub files to brute force Sub-GHz OOK. Flipperzero-Concert-Bracelets Sub-GHz file to trigger event LED bracelets. NFC/RFID FlipperAmiibo Bank vault of Amiibos to Flipper's format. Infrared Flipper-IRDB Many IR dumps for various appliances. BadUSB My-Flipper-Shits Free and open-source [BadUSB] payloads for Flipper Zero. Flipper BadUSB Payloads Collection of payloads formatted to work on the Flipper Zero. UNC0V3R3D BadUSB collection Yet another BadUSB collection. FalsePhilosophers Flipper BadUSB Flipper zero community ducky payload repo. Music FlipperMusicRTTTL Collection of musics for FlipperZero Music Player. flipper-music-files Much smaller collection of musics for FlipperZero Music Player. Other FlipperZero-Goodies Intercom keys, scripts, etc. Flipper-StarNew Universal Intercom Keys. Applications & Plugins Try official apps 📱 The Flipper Zero also has an official app store! General Officially maintained apps Official apps maintained by the Flipper Team and collaborators. All the plugins Large collection of applications including some not published in the official catalog Sub-GHz Spectrum analyzer Sub-GHz frequency spectrum analyzer. Infrared Xbox Controller Easy controller for Xbox One with IR XRemote Advanced IR remote app for Flipper Zero BadUSB COM Port Scanner Emulator Barcode Scanner Emulator. USB HID Autofire Send left-clicks as a USB HID device. Mouse jiggler Keeps PC screens on by acting as a moving mouse. GPIO NRF24 & Mousejacking (outdated) PoC NRF24 library and mousejack exploitation app. Sentry Safe Plugin that can open any Sentry Safe and Master Lock electronic safe without entering pin code. GPS Display data from a serial GPS module. Unitemp Temperature, humidity and pressure sensors reader (DHT11/22, DS18B20, BMP280, HTU21x and more) Servo Tester Servo Tester App Bluetooth USB Keyboard (outdated) A refactor of the BT remote to work over USB. Allows the Flipper to act as an USB HID keyboard. ble_spam_ofw Application that spams broadcast packets to Apple, Android, and Windows. Games Tetris A rudimentary Tetris game. Flappy Bird The name says it all. T-Rex Runner Flipper zero port of Chrome's game. floopper-bloopper LD#47 Game. Doom Doom-like clone for Flipper Zero. Minesweeper Minesweeper implementation. Reversi The classic Reversi game Utility/Other Flipper-Plugin-Tutorial Updated plugin tutorial based on new build methods. Flipper Authenticator Generate TOTP authentication codes. Tuning Fork Use your Flipper as a tuning fork. UPC-A Barcode Generator Can be used to create any UPC-A barcode. Dec/Hex Converter Small "real time" decimal/hexadecimal converter. MultiConverter Multi-unit converter that can be easily expanded with new units and conversion methods. bpm-tapper Tap along to a song to measure beats per minute. Flipp Pomodoro Pomodoro Timer Tool for productivity. Firmwares & Tweaks Hey you! 🔰 Click here for a feature comparison of these firmwares! Official firmware (ofw) Official firmware The source code for Flipper's stock firmware. Custom firmware (cfw) Momentum Feature-rich, stable and customizable Flipper firmware: a direct continuation of the Xtreme firmware. Xtreme Official fork with cleaned up codebase, more module extensions and custom assets. Unleashed Unlocked firmware with rolling codes support & community plugins, stable tweaks, and games. RogueMaster Fork of Unleashed firmware with custom graphics, experimental tweaks, community plugins and games. Dexv Xtreme fork; The "Will it blend?" of custom firmwares. Outdated/Unmaintained firmware SquachWare Fork of official firmware which adds custom graphics, community applications & files. Wetox Very similar to the official branch, with a few small tweaks. Muddled Forks Less-active firmware modifications. OpenHaystack BLE mod Very old PoC that makes Flipper behave like an AirTag. v1nc flipper zero firmware Unleashed fork with support for different Duckyscript keyboard layouts & community plugins. Graphics & Animations Tutorials Flipper Zero Animation Process Google Doc step by step from Talking Sasquach. Lab401 Animation Video YouTube video with a step by step from Talking Sasquach. Pre-made animations Talking Sasquach Animations Literally wrote the book on making animations. Kuronons Graphics Custom animations, passport backgrounds & profile pictures. Haseosama Animations Great collection of custom animations. Animations by stopoxy Another great custom animation collection. Wr3nch Animations Some custom animations and scripts. Dexv Graphics Custom animations and resources. DoobTheGoober Animations Custom animations from the creator of zip2Animation UberGuidoZ Graphics Brief description and links to resources, including PYX host. Animations by mnenkov A dump with animations and manifest creator for batch files. Oneamongthetrees Animations/Graphics Collection of custom animations and passport icons. Utilities Flipper Animation Manager Visualize and manage animations directly from your computer. H4XV's Gif2Anim Gif2FlipperAnimation Converter zip2Animation Utility to assist in creating animations. Modules & Cases Cases Ultimate Flipper Zero Case 3D printed case with room for 3rd party modules & 2x WiFi dev board slots. FlipperZero-Hardware 3D-Printable cases with custom iButton interface. Flipper Zero Cases 3D-Printable case & cover models. Pelican case Big case to hold Flipper and USB. Hard case Smaller than pelican case, but still bulky. WiFi Module v1 Case Small cover for the WiFi dev board. Skadis holder Flipper Zero holder for Ikea Skadis. Flipper Zero Car Mount Uses foam from the original box. Soft TPU cover Similar to the official silicone case. Flipper-Boy Flipper Zero Case with 22mm Watch Strap Adapter. Modules ESP32 Marauder on WiFi dev board Portable WiFi/Bluetooth pentesting. ESP32 Marauder guide video Companion video for the above link. FlipperZero-Protoboards-Kicad KiCad prototype boards. WiFi Scanner Module Scans for WiFi networks via a custom Wemos module board. WiFi Scanner Module Flasher Web flasher for module firmware above. WiFi DSTIKE Deauther Preforms WiFi deauth attacks via a custom ESP8266 module board. WiFi Deauther Module Flasher Web flasher for module firmware above. Flipper Zero Boards ESP32 and NRF24 daughterboards for the Flipper. Flipper-Zero-Backpacks Backpack addon boards with ESP32, Raspberry Pi, Protoboards etc. WiFi Devboard Pelican Case Top case that works with the 4mm FZ Pelican case. The Mayhem Fin ESP32 with WiFi, BT/BLE, Micro-SD, Camera, Flashlight, NRF24/CC1101, and more. Other Flipper Zero screen protector Official screen protector for the Flipper Zero. FlipperZero RGB backlight Replacing stock backlight with RGB Off-device & Debugging General Official Web Interface Web interface to interact with Flipper, including Paint and SUB/IR analyzer. Flipper Maker Generate Flipper Zero files on the fly. Flipper File Toolbox Scripts for generating Flipper data files. Converters OOK to .sub Python script to generate Flipper RAW .sub files from OOK bitstreams. csv2ir Script to convert IRDB CSV's to Flipper .ir files. AmiiboFlipperConverter Script that converts Amiibo's to Flipper format. VertProntoIR2FlipperIR Converts Vert Pronto IR codes to Flipper format. FlippMibo Yet another Amiibo to Flipper conversion script. ClassicConverter Converts Mifare Classic binary files to Flipper. ClassicConverterWeb Converts between Mifare Classic binary and Flipper NFC file. musicxml2fmf Converts MusicXML files to Flipper Music Format. BadUSB keyboard converter Payload converted for non-US keyboard layouts. flipper2mct A script to convert Flipper NFC files to Mifare Classic Tools format for MC 1k & 4k. SerialHex2FlipperZeroInfrared Convert IR serial messages into FlipperZero compatible IR files. Development flipperzero-sesproject Segger Embedded Studio project. flipper0 Rusty crate with safe interface to Flipper Firmware and autogen bindings underneath. flipperzero-rs Hand-crafted bindings to Flipper Firmware with custom build tool. fzfs Flipper Zero filesystem driver. FBT-AARCH64 A script that sets up FBT's toolchain on ARM devices. Utility FlipperScripts Modify the state and level of your dolphin. Viewing system logs Dump system logs to serial CLI. CLI Tools Python scripts to screenshot/stream screen. Fztea Connect to your Flipper's UI over serial or make it accessible via SSH. pyFlipper Unofficial CLI wrapper writter in Python. SUB Plotters / comparers Python package to plot and compare multiple .sub files. U2F SSH Keys U2F ECDSA SSH Key Generation using Flipper Zero. Pagger Sub-GHz generators for restaurants/kiosks paging systems. Notes & References Need help using your Flipper Zero? 📕 Give the official documentation a read! Disassembly/Repair Official battery self-repair guide How to troubleshoot battery issues. Official firmware recovery guide How to troubleshoot firmware issues. Flipper Zero disassembly guide Difficulty: Moderate, Time: 8-15 Minutes. Alternative disassembly video Third-party video for disassembling the Flipper. Reset forgotten PIN How to reset your device's PIN code. Guides Flipper Zero Hacking 101 Guides with screenshots, files, and general help. Atmanos Flipper Software Docs Flipper development tutorials and information. Flipper Zero GPIO Pinout Official GPIO pinouts. Flipper Skylanders How to read a Skylanders figure with Flipper. Application CI/CD Guide A complete guide on how to adopt flipper application to regular API changes. Specifications Add-on Modules GPIO Pinouts ESP32, ESP8266, ESP32-CAM, ESP32-WROOM, NRF24. Flipper Zero Dimensions Basic info on screen and case dimensions. Other Firmware roadmap (outdated?) Official stock firmware roadmap. Flipper Zero SW&HW keynote (outdated) Hardware & software architecture document. 🆕 Want to make changes? ✨ You can Edit this file and open a Pull Request, or Start a discussion with your ideas. Read the Meta FAQ section for more info.

🐬 A collection of awesome resources for the Flipper Zero device.

flipperzero,flipper-zero,awesome,awesome-list

ReVanced/revanced-manager

Continuing the legacy of Vanced 💊 ReVanced Manager Application to use ReVanced on Android ❓ About ReVanced Manager is an application that uses ReVanced Patcher to patch Android apps. 💪 Features Some of the features ReVanced Manager provides are: 💉 Patch apps : Apply any patch of your choice to Android apps 📱 Portable : ReVanced Patcher that fits in your pocket 🤗 Simple UI : Quickly understand the ins and outs of ReVanced Manager 🛠️ Customization : Configurable API, custom sources, language, signing keystore, theme and more 🔽 Download You can download the most recent version of ReVanced Manager at revanced.app/download or from GitHub releases . Learn how to use ReVanced Manager by following the documentation . 📚 Everything else 📙 Contributing Thank you for considering contributing to ReVanced Manager. You can find the contribution guidelines here . 🛠️ Building To build a ReVanced Manager, you can follow the documentation . 📄 Documentation You can find the documentation for ReVanced Manager here . 👋 Contributing Thank you for considering contributing to ReVanced Manager. You can find the contribution guidelines here . ⚖️ License ReVanced Manager is licensed under the GPLv3 license. Please see the license file for more information. tl;dr you may copy, distribute and modify ReVanced Manager as long as you track changes/dates in source files. Any modifications to ReVanced Manager must also be made available under the GPL, along with build & install instructions.

💊 Application to use ReVanced on Android

revanced,manager,android,modding,patching,flutter,flutter-apps

Grasscutters/Grasscutter

EN | 简中 | 繁中 | FR | ES | HE | RU | PL | ID | KR | FIL/PH | NL | JP | IT | VI Attention: We always welcome contributors to the project. Before adding your contribution, please carefully read our Code of Conduct . Current features Logging in Combat Friends list Teleportation Gacha system Co-op partially works Spawning monsters via console Inventory features (receiving items/characters, upgrading items/characters, etc) Quick setup guide Note : For support please join our Discord . Quick Start (automatic) Get Java 17 Get MongoDB Community Server Get game version REL4.0.x (If you don't have a 4.0.x client, you can find it here and open any of the links to download it): 4.0.x Client-github 4.0.x Client-cloud drive Download the latest Cultivation version . Use the .msi installer. After opening Cultivation (as admin), press the download button in the upper right corner. Click Download All-in-One Click the gear in the upper right corner Set the game Install path to where your game is located. Set the Custom Java Path to C:\Program Files\Java\jdk-17\bin\java.exe Leave all other settings on default Click the small button next to launch. Click the launch button. Log in with whatever username you want. Password can be anything. Building Grasscutter uses Gradle to handle dependencies & building. Requirements: Java Development Kit 17 or higher Git NodeJS (Optional, for building the handbook) Clone shell git clone --recurse-submodules https://github.com/Grasscutters/Grasscutter.git cd Grasscutter Compile Note : Handbook generation may fail on some systems. To disable the handbook generation, append -PskipHandbook=1 to the gradlew jar command. Windows: shell .\gradlew.bat # Setting up environments .\gradlew jar Linux (GNU): bash chmod +x gradlew ./gradlew jar Compiling the Handbook (Manually) With Gradle: shell ./gradlew generateHandbook With NPM: shell cd src/handbook npm install npm run build You can find the output jar in the root of the project folder. Troubleshooting For a list of common issues and solutions and to ask for help, please join our Discord server and go to the support channel.

A server software reimplementation for a certain anime game.

java,kcp,server,private-server

android/nowinandroid

Now in Android App Learn how this app was designed and built in the design case study , architecture learning journey and modularization learning journey . This is the repository for the Now in Android app. It is a work in progress 🚧. Now in Android is a fully functional Android app built entirely with Kotlin and Jetpack Compose. It follows Android design and development best practices and is intended to be a useful reference for developers. As a running app, it's intended to help developers keep up-to-date with the world of Android development by providing regular news updates. The app is currently in development. The prodRelease variant is available on the Play Store . Features Now in Android displays content from the Now in Android series. Users can browse for links to recent videos, articles and other content. Users can also follow topics they are interested in, and be notified when new content is published which matches interests they are following. Screenshots Development Environment Now in Android uses the Gradle build system and can be imported directly into Android Studio (make sure you are using the latest stable version available here ). Change the run configuration to app . The demoDebug and demoRelease build variants can be built and run (the prod variants use a backend server which is not currently publicly available). Once you're up and running, you can refer to the learning journeys below to get a better understanding of which libraries and tools are being used, the reasoning behind the approaches to UI, testing, architecture and more, and how all of these different pieces of the project fit together to create a complete app. Architecture The Now in Android app follows the official architecture guidance and is described in detail in the architecture learning journey . Modularization The Now in Android app has been fully modularized and you can find the detailed guidance and description of the modularization strategy used in modularization learning journey . Build The app contains the usual debug and release build variants. In addition, the benchmark variant of app is used to test startup performance and generate a baseline profile (see below for more information). app-nia-catalog is a standalone app that displays the list of components that are stylized for Now in Android . The app also uses product flavors to control where content for the app should be loaded from. The demo flavor uses static local data to allow immediate building and exploring of the UI. The prod flavor makes real network calls to a backend server, providing up-to-date content. At this time, there is not a public backend available. For normal development use the demoDebug variant. For UI performance testing use the demoRelease variant. Testing To facilitate testing of components, Now in Android uses dependency injection with Hilt . Most data layer components are defined as interfaces. Then, concrete implementations (with various dependencies) are bound to provide those interfaces to other components in the app. In tests, Now in Android notably does not use any mocking libraries. Instead, the production implementations can be replaced with test doubles using Hilt's testing APIs (or via manual constructor injection for ViewModel tests). These test doubles implement the same interface as the production implementations and generally provide a simplified (but still realistic) implementation with additional testing hooks. This results in less brittle tests that may exercise more production code, instead of just verifying specific calls against mocks. Examples: - In instrumentation tests, a temporary folder is used to store the user's preferences, which is wiped after each test. This allows using the real DataStore and exercising all related code, instead of mocking the flow of data updates. There are Test implementations of each repository, which implement the normal, full repository interface and also provide test-only hooks. ViewModel tests use these Test repositories, and thus can use the test-only hooks to manipulate the state of the Test repository and verify the resulting behavior, instead of checking that specific repository methods were called. To run the tests execute the following gradle tasks: testDemoDebug run all local tests against the demoDebug variant. connectedDemoDebugAndroidTest run all instrumented tests against the demoDebug variant. Note: You should not run ./gradlew test or ./gradlew connectedAndroidTest as this will execute tests against all build variants which is both unecessary and will result in failures as only the demoDebug variant is supported. No other variants have any tests (although this might change in future). Screenshot tests A screenshot test takes a screenshot of a screen or a UI component within the app, and compares it with a previously recorded screenshot which is known to be rendered correctly. For example, Now in Android has screenshot tests to verify that the navigation is displayed correctly on different screen sizes ( known correct screenshots ). Now In Android uses Roborazzi to run screenshot tests of certain screens and UI components. When working with screenshot tests the following gradle tasks are useful: verifyRoborazziDemoDebug run all screenshot tests, verifying the screenshots against the known correct screenshots. recordRoborazziDemoDebug record new "known correct" screenshots. Use this command when you have made changes to the UI and manually verified that they are rendered correctly. Screenshots will be stored in modulename/src/test/screenshots . compareRoborazziDemoDebug create comparison images between failed tests and the known correct images. These can also be found in modulename/src/test/screenshots . Note: The known correct screenshots stored in this repository are recorded on CI using Linux. Other platforms may (and probably will) generate slightly different images, making the screenshot tests fail. When working on a non-Linux platform, a workaround to this is to run recordRoborazziDemoDebug on the main branch before starting work. After making changes, verifyRoborazziDemoDebug will identify only legitimate changes. For more information about screenshot testing check out this talk . UI The app was designed using Material 3 guidelines . Learn more about the design process and obtain the design files in the Now in Android Material 3 Case Study (design assets also available as a PDF ). The Screens and UI elements are built entirely using Jetpack Compose . The app has two themes: Dynamic color - uses colors based on the user's current color theme (if supported) Default theme - uses predefined colors when dynamic color is not supported Each theme also supports dark mode. The app uses adaptive layouts to support different screen sizes . Find out more about the UI architecture here . Performance Benchmarks Find all tests written using Macrobenchmark in the benchmarks module. This module also contains the test to generate the Baseline profile. Baseline profiles The baseline profile for this app is located at app/src/main/baseline-prof.txt . It contains rules that enable AOT compilation of the critical user path taken during app launch. For more information on baseline profiles, read this document . [!NOTE] The baseline profile needs to be re-generated for release builds that touch code which changes app startup. To generate the baseline profile, select the benchmark build variant and run the BaselineProfileGenerator benchmark test on an AOSP Android Emulator. Then copy the resulting baseline profile from the emulator to app/src/main/baseline-prof.txt . Compose compiler metrics Run the following command to get and analyse compose compiler metrics: bash ./gradlew assembleRelease -PenableComposeCompilerMetrics=true -PenableComposeCompilerReports=true The reports files will be added to build/compose-reports . The metrics files will also be added to build/compose-metrics . For more information on Compose compiler metrics, see this blog post . License Now in Android is distributed under the terms of the Apache License (Version 2.0). See the license for more information.

A fully functional Android app built entirely with Kotlin and Jetpack Compose

android,jetpack-compose,kotlin

samber/lo

lo - Iterate over slices, maps, channels... ✨ samber/lo is a Lodash-style Go library based on Go 1.18+ Generics. This project started as an experiment with the new generics implementation. It may look like Lodash in some aspects. I used to code with the fantastic "go-funk" package, but "go-funk" uses reflection and therefore is not typesafe. As expected, benchmarks demonstrate that generics are much faster than implementations based on the "reflect" package. Benchmarks also show similar performance gains compared to pure for loops. See below . In the future, 5 to 10 helpers will overlap with those coming into the Go standard library (under package names slices and maps ). I feel this library is legitimate and offers many more valuable abstractions. See also: samber/do : A dependency injection toolkit based on Go 1.18+ Generics samber/mo : Monads based on Go 1.18+ Generics (Option, Result, Either...) Why this name? I wanted a short name , similar to "Lodash" and no Go package currently uses this name. 🚀 Install sh go get github.com/samber/lo@v1 This library is v1 and follows SemVer strictly. No breaking changes will be made to exported APIs before v2.0.0. This library has no dependencies outside the Go standard library. 💡 Usage You can import lo using: go import ( "github.com/samber/lo" lop "github.com/samber/lo/parallel" ) Then use one of the helpers below: go names := lo.Uniq[string]([]string{"Samuel", "John", "Samuel"}) // []string{"Samuel", "John"} Most of the time, the compiler will be able to infer the type so that you can call: lo.Uniq([]string{...}) . Tips for lazy developers I cannot recommend it, but in case you are too lazy for repeating lo. everywhere, you can import the entire library into the namespace. go import ( . "github.com/samber/lo" ) I take no responsibility on this junk. 😁 💩 🤠 Spec GoDoc: https://godoc.org/github.com/samber/lo Supported helpers for slices: Filter Map FilterMap FlatMap Reduce ReduceRight ForEach Times Uniq UniqBy GroupBy Chunk PartitionBy Flatten Interleave Shuffle Reverse Fill Repeat RepeatBy KeyBy Associate / SliceToMap Drop DropRight DropWhile DropRightWhile Reject Count CountBy CountValues CountValuesBy Subset Slice Replace ReplaceAll Compact IsSorted IsSortedByKey Supported helpers for maps: Keys ValueOr Values PickBy PickByKeys PickByValues OmitBy OmitByKeys OmitByValues Entries / ToPairs FromEntries / FromPairs Invert Assign (merge of maps) MapKeys MapValues MapEntries MapToSlice Supported math helpers: Range / RangeFrom / RangeWithSteps Clamp Sum SumBy Supported helpers for strings: RandomString Substring ChunkString RuneLength Supported helpers for tuples: T2 -> T9 Unpack2 -> Unpack9 Zip2 -> Zip9 Unzip2 -> Unzip9 Supported helpers for channels: ChannelDispatcher SliceToChannel Generator Buffer BufferWithTimeout FanIn FanOut Supported intersection helpers: Contains ContainsBy Every EveryBy Some SomeBy None NoneBy Intersect Difference Union Without WithoutEmpty Supported search helpers: IndexOf LastIndexOf Find FindIndexOf FindLastIndexOf FindOrElse FindKey FindKeyBy FindUniques FindUniquesBy FindDuplicates FindDuplicatesBy Min MinBy Max MaxBy Last Nth Sample Samples Conditional helpers: Ternary TernaryF If / ElseIf / Else Switch / Case / Default Type manipulation helpers: IsNil ToPtr EmptyableToPtr FromPtr FromPtrOr ToSlicePtr ToAnySlice FromAnySlice Empty IsEmpty IsNotEmpty Coalesce Function helpers: Partial Partial2 -> Partial5 Concurrency helpers: Attempt AttemptWhile AttemptWithDelay AttemptWhileWithDelay Debounce DebounceBy Synchronize Async Transaction Error handling: Validate Must Try Try1 -> Try6 TryOr TryOr1 -> TryOr6 TryCatch TryWithErrorValue TryCatchWithErrorValue ErrorsAs Constraints: Clonable Filter Iterates over a collection and returns an array of all the elements the predicate function returns true for. go even := lo.Filter([]int{1, 2, 3, 4}, func(x int, index int) bool { return x%2 == 0 }) // []int{2, 4} [ play ] Map Manipulates a slice of one type and transforms it into a slice of another type: ```go import "github.com/samber/lo" lo.Map([]int64{1, 2, 3, 4}, func(x int64, index int) string { return strconv.FormatInt(x, 10) }) // []string{"1", "2", "3", "4"} ``` [ play ] Parallel processing: like lo.Map() , but the mapper function is called in a goroutine. Results are returned in the same order. ```go import lop "github.com/samber/lo/parallel" lop.Map([]int64{1, 2, 3, 4}, func(x int64, _ int) string { return strconv.FormatInt(x, 10) }) // []string{"1", "2", "3", "4"} ``` FilterMap Returns a slice which obtained after both filtering and mapping using the given callback function. The callback function should return two values: the result of the mapping operation and whether the result element should be included or not. go matching := lo.FilterMap([]string{"cpu", "gpu", "mouse", "keyboard"}, func(x string, _ int) (string, bool) { if strings.HasSuffix(x, "pu") { return "xpu", true } return "", false }) // []string{"xpu", "xpu"} [ play ] FlatMap Manipulates a slice and transforms and flattens it to a slice of another type. The transform function can either return a slice or a nil , and in the nil case no value is added to the final slice. go lo.FlatMap([]int{0, 1, 2}, func(x int, _ int) []string { return []string{ strconv.FormatInt(x, 10), strconv.FormatInt(x, 10), } }) // []string{"0", "0", "1", "1", "2", "2"} [ play ] Reduce Reduces a collection to a single value. The value is calculated by accumulating the result of running each element in the collection through an accumulator function. Each successive invocation is supplied with the return value returned by the previous call. go sum := lo.Reduce([]int{1, 2, 3, 4}, func(agg int, item int, _ int) int { return agg + item }, 0) // 10 [ play ] ReduceRight Like lo.Reduce except that it iterates over elements of collection from right to left. go result := lo.ReduceRight([][]int{{0, 1}, {2, 3}, {4, 5}}, func(agg []int, item []int, _ int) []int { return append(agg, item...) }, []int{}) // []int{4, 5, 2, 3, 0, 1} [ play ] ForEach Iterates over elements of a collection and invokes the function over each element. ```go import "github.com/samber/lo" lo.ForEach([]string{"hello", "world"}, func(x string, _ int) { println(x) }) // prints "hello\nworld\n" ``` [ play ] Parallel processing: like lo.ForEach() , but the callback is called as a goroutine. ```go import lop "github.com/samber/lo/parallel" lop.ForEach([]string{"hello", "world"}, func(x string, _ int) { println(x) }) // prints "hello\nworld\n" or "world\nhello\n" ``` Times Times invokes the iteratee n times, returning an array of the results of each invocation. The iteratee is invoked with index as argument. ```go import "github.com/samber/lo" lo.Times(3, func(i int) string { return strconv.FormatInt(int64(i), 10) }) // []string{"0", "1", "2"} ``` [ play ] Parallel processing: like lo.Times() , but callback is called in goroutine. ```go import lop "github.com/samber/lo/parallel" lop.Times(3, func(i int) string { return strconv.FormatInt(int64(i), 10) }) // []string{"0", "1", "2"} ``` Uniq Returns a duplicate-free version of an array, in which only the first occurrence of each element is kept. The order of result values is determined by the order they occur in the array. go uniqValues := lo.Uniq([]int{1, 2, 2, 1}) // []int{1, 2} [ play ] UniqBy Returns a duplicate-free version of an array, in which only the first occurrence of each element is kept. The order of result values is determined by the order they occur in the array. It accepts iteratee which is invoked for each element in array to generate the criterion by which uniqueness is computed. go uniqValues := lo.UniqBy([]int{0, 1, 2, 3, 4, 5}, func(i int) int { return i%3 }) // []int{0, 1, 2} [ play ] GroupBy Returns an object composed of keys generated from the results of running each element of collection through iteratee. ```go import lo "github.com/samber/lo" groups := lo.GroupBy([]int{0, 1, 2, 3, 4, 5}, func(i int) int { return i%3 }) // map[int][]int{0: []int{0, 3}, 1: []int{1, 4}, 2: []int{2, 5}} ``` [ play ] Parallel processing: like lo.GroupBy() , but callback is called in goroutine. ```go import lop "github.com/samber/lo/parallel" lop.GroupBy([]int{0, 1, 2, 3, 4, 5}, func(i int) int { return i%3 }) // map[int][]int{0: []int{0, 3}, 1: []int{1, 4}, 2: []int{2, 5}} ``` Chunk Returns an array of elements split into groups the length of size. If array can't be split evenly, the final chunk will be the remaining elements. ```go lo.Chunk([]int{0, 1, 2, 3, 4, 5}, 2) // [][]int{{0, 1}, {2, 3}, {4, 5}} lo.Chunk([]int{0, 1, 2, 3, 4, 5, 6}, 2) // [][]int{{0, 1}, {2, 3}, {4, 5}, {6}} lo.Chunk([]int{}, 2) // [][]int{} lo.Chunk([]int{0}, 2) // [][]int{{0}} ``` [ play ] PartitionBy Returns an array of elements split into groups. The order of grouped values is determined by the order they occur in collection. The grouping is generated from the results of running each element of collection through iteratee. ```go import lo "github.com/samber/lo" partitions := lo.PartitionBy([]int{-2, -1, 0, 1, 2, 3, 4, 5}, func(x int) string { if x < 0 { return "negative" } else if x%2 == 0 { return "even" } return "odd" }) // [][]int{{-2, -1}, {0, 2, 4}, {1, 3, 5}} ``` [ play ] Parallel processing: like lo.PartitionBy() , but callback is called in goroutine. Results are returned in the same order. ```go import lop "github.com/samber/lo/parallel" partitions := lop.PartitionBy([]int{-2, -1, 0, 1, 2, 3, 4, 5}, func(x int) string { if x < 0 { return "negative" } else if x%2 == 0 { return "even" } return "odd" }) // [][]int{{-2, -1}, {0, 2, 4}, {1, 3, 5}} ``` Flatten Returns an array a single level deep. go flat := lo.Flatten([][]int{{0, 1}, {2, 3, 4, 5}}) // []int{0, 1, 2, 3, 4, 5} [ play ] Interleave Round-robin alternating input slices and sequentially appending value at index into result. ```go interleaved := lo.Interleave([]int{1, 4, 7}, []int{2, 5, 8}, []int{3, 6, 9}) // []int{1, 2, 3, 4, 5, 6, 7, 8, 9} interleaved := lo.Interleave([]int{1}, []int{2, 5, 8}, []int{3, 6}, []int{4, 7, 9, 10}) // []int{1, 2, 3, 4, 5, 6, 7, 8, 9, 10} ``` [ play ] Shuffle Returns an array of shuffled values. Uses the Fisher-Yates shuffle algorithm. go randomOrder := lo.Shuffle([]int{0, 1, 2, 3, 4, 5}) // []int{1, 4, 0, 3, 5, 2} [ play ] Reverse Reverses array so that the first element becomes the last, the second element becomes the second to last, and so on. ⚠️ This helper is mutable . This behavior might change in v2.0.0 . See #160 . go reverseOrder := lo.Reverse([]int{0, 1, 2, 3, 4, 5}) // []int{5, 4, 3, 2, 1, 0} [ play ] Fill Fills elements of array with initial value. ```go type foo struct { bar string } func (f foo) Clone() foo { return foo{f.bar} } initializedSlice := lo.Fill([]foo{foo{"a"}, foo{"a"}}, foo{"b"}) // []foo{foo{"b"}, foo{"b"}} ``` [ play ] Repeat Builds a slice with N copies of initial value. ```go type foo struct { bar string } func (f foo) Clone() foo { return foo{f.bar} } slice := lo.Repeat(2, foo{"a"}) // []foo{foo{"a"}, foo{"a"}} ``` [ play ] RepeatBy Builds a slice with values returned by N calls of callback. ```go slice := lo.RepeatBy(0, func (i int) string { return strconv.FormatInt(int64(math.Pow(float64(i), 2)), 10) }) // []string{} slice := lo.RepeatBy(5, func(i int) string { return strconv.FormatInt(int64(math.Pow(float64(i), 2)), 10) }) // []string{"0", "1", "4", "9", "16"} ``` [ play ] KeyBy Transforms a slice or an array of structs to a map based on a pivot callback. ```go m := lo.KeyBy([]string{"a", "aa", "aaa"}, func(str string) int { return len(str) }) // map[int]string{1: "a", 2: "aa", 3: "aaa"} type Character struct { dir string code int } characters := []Character{ {dir: "left", code: 97}, {dir: "right", code: 100}, } result := lo.KeyBy(characters, func(char Character) string { return string(rune(char.code)) }) //map[a:{dir:left code:97} d:{dir:right code:100}] ``` [ play ] Associate (alias: SliceToMap) Returns a map containing key-value pairs provided by transform function applied to elements of the given slice. If any of two pairs would have the same key the last one gets added to the map. The order of keys in returned map is not specified and is not guaranteed to be the same from the original array. ```go in := []*foo{{baz: "apple", bar: 1}, {baz: "banana", bar: 2}} aMap := lo.Associate(in, func (f *foo) (string, int) { return f.baz, f.bar }) // map[string][int]{ "apple":1, "banana":2 } ``` [ play ] Drop Drops n elements from the beginning of a slice or array. go l := lo.Drop([]int{0, 1, 2, 3, 4, 5}, 2) // []int{2, 3, 4, 5} [ play ] DropRight Drops n elements from the end of a slice or array. go l := lo.DropRight([]int{0, 1, 2, 3, 4, 5}, 2) // []int{0, 1, 2, 3} [ play ] DropWhile Drop elements from the beginning of a slice or array while the predicate returns true. go l := lo.DropWhile([]string{"a", "aa", "aaa", "aa", "aa"}, func(val string) bool { return len(val) <= 2 }) // []string{"aaa", "aa", "aa"} [ play ] DropRightWhile Drop elements from the end of a slice or array while the predicate returns true. go l := lo.DropRightWhile([]string{"a", "aa", "aaa", "aa", "aa"}, func(val string) bool { return len(val) <= 2 }) // []string{"a", "aa", "aaa"} [ play ] Reject The opposite of Filter, this method returns the elements of collection that predicate does not return truthy for. go odd := lo.Reject([]int{1, 2, 3, 4}, func(x int, _ int) bool { return x%2 == 0 }) // []int{1, 3} [ play ] Count Counts the number of elements in the collection that compare equal to value. go count := lo.Count([]int{1, 5, 1}, 1) // 2 [ play ] CountBy Counts the number of elements in the collection for which predicate is true. go count := lo.CountBy([]int{1, 5, 1}, func(i int) bool { return i < 4 }) // 2 [ play ] CountValues Counts the number of each element in the collection. ```go lo.CountValues([]int{}) // map[int]int{} lo.CountValues([]int{1, 2}) // map[int]int{1: 1, 2: 1} lo.CountValues([]int{1, 2, 2}) // map[int]int{1: 1, 2: 2} lo.CountValues([]string{"foo", "bar", ""}) // map[string]int{"": 1, "foo": 1, "bar": 1} lo.CountValues([]string{"foo", "bar", "bar"}) // map[string]int{"foo": 1, "bar": 2} ``` [ play ] CountValuesBy Counts the number of each element in the collection. It ss equivalent to chaining lo.Map and lo.CountValues. ```go isEven := func(v int) bool { return v%2==0 } lo.CountValuesBy([]int{}, isEven) // map[bool]int{} lo.CountValuesBy([]int{1, 2}, isEven) // map[bool]int{false: 1, true: 1} lo.CountValuesBy([]int{1, 2, 2}, isEven) // map[bool]int{false: 1, true: 2} length := func(v string) int { return len(v) } lo.CountValuesBy([]string{"foo", "bar", ""}, length) // map[int]int{0: 1, 3: 2} lo.CountValuesBy([]string{"foo", "bar", "bar"}, length) // map[int]int{3: 3} ``` [ play ] Subset Returns a copy of a slice from offset up to length elements. Like slice[start:start+length] , but does not panic on overflow. ```go in := []int{0, 1, 2, 3, 4} sub := lo.Subset(in, 2, 3) // []int{2, 3, 4} sub := lo.Subset(in, -4, 3) // []int{1, 2, 3} sub := lo.Subset(in, -2, math.MaxUint) // []int{3, 4} ``` [ play ] Slice Returns a copy of a slice from start up to, but not including end . Like slice[start:end] , but does not panic on overflow. ```go in := []int{0, 1, 2, 3, 4} slice := lo.Slice(in, 0, 5) // []int{0, 1, 2, 3, 4} slice := lo.Slice(in, 2, 3) // []int{2} slice := lo.Slice(in, 2, 6) // []int{2, 3, 4} slice := lo.Slice(in, 4, 3) // []int{} ``` [ play ] Replace Returns a copy of the slice with the first n non-overlapping instances of old replaced by new. ```go in := []int{0, 1, 0, 1, 2, 3, 0} slice := lo.Replace(in, 0, 42, 1) // []int{42, 1, 0, 1, 2, 3, 0} slice := lo.Replace(in, -1, 42, 1) // []int{0, 1, 0, 1, 2, 3, 0} slice := lo.Replace(in, 0, 42, 2) // []int{42, 1, 42, 1, 2, 3, 0} slice := lo.Replace(in, 0, 42, -1) // []int{42, 1, 42, 1, 2, 3, 42} ``` [ play ] ReplaceAll Returns a copy of the slice with all non-overlapping instances of old replaced by new. ```go in := []int{0, 1, 0, 1, 2, 3, 0} slice := lo.ReplaceAll(in, 0, 42) // []int{42, 1, 42, 1, 2, 3, 42} slice := lo.ReplaceAll(in, -1, 42) // []int{0, 1, 0, 1, 2, 3, 0} ``` [ play ] Compact Returns a slice of all non-zero elements. ```go in := []string{"", "foo", "", "bar", ""} slice := lo.Compact string // []string{"foo", "bar"} ``` [ play ] IsSorted Checks if a slice is sorted. go slice := lo.IsSorted([]int{0, 1, 2, 3, 4, 5, 6, 7, 8, 9}) // true [ play ] IsSortedByKey Checks if a slice is sorted by iteratee. go slice := lo.IsSortedByKey([]string{"a", "bb", "ccc"}, func(s string) int { return len(s) }) // true [ play ] Keys Creates an array of the map keys. go keys := lo.Keys[string, int](map[string]int{"foo": 1, "bar": 2}) // []string{"foo", "bar"} [ play ] Values Creates an array of the map values. go values := lo.Values[string, int](map[string]int{"foo": 1, "bar": 2}) // []int{1, 2} [ play ] ValueOr Returns the value of the given key or the fallback value if the key is not present. ```go value := lo.ValueOr string, int // 1 value := lo.ValueOr string, int // 42 ``` [ play ] PickBy Returns same map type filtered by given predicate. go m := lo.PickBy(map[string]int{"foo": 1, "bar": 2, "baz": 3}, func(key string, value int) bool { return value%2 == 1 }) // map[string]int{"foo": 1, "baz": 3} [ play ] PickByKeys Returns same map type filtered by given keys. go m := lo.PickByKeys(map[string]int{"foo": 1, "bar": 2, "baz": 3}, []string{"foo", "baz"}) // map[string]int{"foo": 1, "baz": 3} [ play ] PickByValues Returns same map type filtered by given values. go m := lo.PickByValues(map[string]int{"foo": 1, "bar": 2, "baz": 3}, []int{1, 3}) // map[string]int{"foo": 1, "baz": 3} [ play ] OmitBy Returns same map type filtered by given predicate. go m := lo.OmitBy(map[string]int{"foo": 1, "bar": 2, "baz": 3}, func(key string, value int) bool { return value%2 == 1 }) // map[string]int{"bar": 2} [ play ] OmitByKeys Returns same map type filtered by given keys. go m := lo.OmitByKeys(map[string]int{"foo": 1, "bar": 2, "baz": 3}, []string{"foo", "baz"}) // map[string]int{"bar": 2} [ play ] OmitByValues Returns same map type filtered by given values. go m := lo.OmitByValues(map[string]int{"foo": 1, "bar": 2, "baz": 3}, []int{1, 3}) // map[string]int{"bar": 2} [ play ] Entries (alias: ToPairs) Transforms a map into array of key/value pairs. go entries := lo.Entries(map[string]int{"foo": 1, "bar": 2}) // []lo.Entry[string, int]{ // { // Key: "foo", // Value: 1, // }, // { // Key: "bar", // Value: 2, // }, // } [ play ] FromEntries (alias: FromPairs) Transforms an array of key/value pairs into a map. go m := lo.FromEntries([]lo.Entry[string, int]{ { Key: "foo", Value: 1, }, { Key: "bar", Value: 2, }, }) // map[string]int{"foo": 1, "bar": 2} [ play ] Invert Creates a map composed of the inverted keys and values. If map contains duplicate values, subsequent values overwrite property assignments of previous values. ```go m1 := lo.Invert(map[string]int{"a": 1, "b": 2}) // map[int]string{1: "a", 2: "b"} m2 := lo.Invert(map[string]int{"a": 1, "b": 2, "c": 1}) // map[int]string{1: "c", 2: "b"} ``` [ play ] Assign Merges multiple maps from left to right. go mergedMaps := lo.Assign[string, int]( map[string]int{"a": 1, "b": 2}, map[string]int{"b": 3, "c": 4}, ) // map[string]int{"a": 1, "b": 3, "c": 4} [ play ] MapKeys Manipulates a map keys and transforms it to a map of another type. go m2 := lo.MapKeys(map[int]int{1: 1, 2: 2, 3: 3, 4: 4}, func(_ int, v int) string { return strconv.FormatInt(int64(v), 10) }) // map[string]int{"1": 1, "2": 2, "3": 3, "4": 4} [ play ] MapValues Manipulates a map values and transforms it to a map of another type. ```go m1 := map[int]int64{1: 1, 2: 2, 3: 3} m2 := lo.MapValues(m1, func(x int64, _ int) string { return strconv.FormatInt(x, 10) }) // map[int]string{1: "1", 2: "2", 3: "3"} ``` [ play ] MapEntries Manipulates a map entries and transforms it to a map of another type. ```go in := map[string]int{"foo": 1, "bar": 2} out := lo.MapEntries(in, func(k string, v int) (int, string) { return v,k }) // map[int]string{1: "foo", 2: "bar"} ``` [ play ] MapToSlice Transforms a map into a slice based on specific iteratee. ```go m := map[int]int64{1: 4, 2: 5, 3: 6} s := lo.MapToSlice(m, func(k int, v int64) string { return fmt.Sprintf("%d_%d", k, v) }) // []string{"1_4", "2_5", "3_6"} ``` [ play ] Range / RangeFrom / RangeWithSteps Creates an array of numbers (positive and/or negative) progressing from start up to, but not including end. ```go result := lo.Range(4) // [0, 1, 2, 3] result := lo.Range(-4) // [0, -1, -2, -3] result := lo.RangeFrom(1, 5) // [1, 2, 3, 4, 5] result := lo.RangeFrom float64 // [1.0, 2.0, 3.0, 4.0, 5.0] result := lo.RangeWithSteps(0, 20, 5) // [0, 5, 10, 15] result := lo.RangeWithSteps float32 // [-1.0, -2.0, -3.0] result := lo.RangeWithSteps(1, 4, -1) // [] result := lo.Range(0) // [] ``` [ play ] Clamp Clamps number within the inclusive lower and upper bounds. ```go r1 := lo.Clamp(0, -10, 10) // 0 r2 := lo.Clamp(-42, -10, 10) // -10 r3 := lo.Clamp(42, -10, 10) // 10 ``` [ play ] Sum Sums the values in a collection. If collection is empty 0 is returned. go list := []int{1, 2, 3, 4, 5} sum := lo.Sum(list) // 15 [ play ] SumBy Summarizes the values in a collection using the given return value from the iteration function. If collection is empty 0 is returned. go strings := []string{"foo", "bar"} sum := lo.SumBy(strings, func(item string) int { return len(item) }) // 6 [ play ] RandomString Returns a random string of the specified length and made of the specified charset. go str := lo.RandomString(5, lo.LettersCharset) // example: "eIGbt" [ play ] Substring Return part of a string. ```go sub := lo.Substring("hello", 2, 3) // "llo" sub := lo.Substring("hello", -4, 3) // "ell" sub := lo.Substring("hello", -2, math.MaxUint) // "lo" ``` [ play ] ChunkString Returns an array of strings split into groups the length of size. If array can't be split evenly, the final chunk will be the remaining elements. ```go lo.ChunkString("123456", 2) // []string{"12", "34", "56"} lo.ChunkString("1234567", 2) // []string{"12", "34", "56", "7"} lo.ChunkString("", 2) // []string{""} lo.ChunkString("1", 2) // []string{"1"} ``` [ play ] RuneLength An alias to utf8.RuneCountInString which returns the number of runes in string. ```go sub := lo.RuneLength("hellô") // 5 sub := len("hellô") // 6 ``` [ play ] T2 -> T9 Creates a tuple from a list of values. ```go tuple1 := lo.T2("x", 1) // Tuple2[string, int]{A: "x", B: 1} func example() (string, int) { return "y", 2 } tuple2 := lo.T2(example()) // Tuple2[string, int]{A: "y", B: 2} ``` [ play ] Unpack2 -> Unpack9 Returns values contained in tuple. go r1, r2 := lo.Unpack2(lo.Tuple2[string, int]{"a", 1}) // "a", 1 Unpack is also available as a method of TupleX. go tuple2 := lo.T2("a", 1) a, b := tuple2.Unpack() // "a" 1 [ play ] Zip2 -> Zip9 Zip creates a slice of grouped elements, the first of which contains the first elements of the given arrays, the second of which contains the second elements of the given arrays, and so on. When collections have different size, the Tuple attributes are filled with zero value. go tuples := lo.Zip2([]string{"a", "b"}, []int{1, 2}) // []Tuple2[string, int]{{A: "a", B: 1}, {A: "b", B: 2}} [ play ] Unzip2 -> Unzip9 Unzip accepts an array of grouped elements and creates an array regrouping the elements to their pre-zip configuration. go a, b := lo.Unzip2([]Tuple2[string, int]{{A: "a", B: 1}, {A: "b", B: 2}}) // []string{"a", "b"} // []int{1, 2} [ play ] ChannelDispatcher Distributes messages from input channels into N child channels. Close events are propagated to children. Underlying channels can have a fixed buffer capacity or be unbuffered when cap is 0. ```go ch := make(chan int, 42) for i := 0; i <= 10; i++ { ch <- i } children := lo.ChannelDispatcher(ch, 5, 10, DispatchingStrategyRoundRobin[int]) // []<-chan int{...} consumer := func(c <-chan int) { for { msg, ok := <-c if !ok { println("closed") break } println(msg) } } for i := range children { go consumer(children[i]) } ``` Many distributions strategies are available: lo.DispatchingStrategyRoundRobin : Distributes messages in a rotating sequential manner. lo.DispatchingStrategyRandom : Distributes messages in a random manner. lo.DispatchingStrategyWeightedRandom : Distributes messages in a weighted manner. lo.DispatchingStrategyFirst : Distributes messages in the first non-full channel. lo.DispatchingStrategyLeast : Distributes messages in the emptiest channel. lo.DispatchingStrategyMost : Distributes to the fullest channel. Some strategies bring fallback, in order to favor non-blocking behaviors. See implementations. For custom strategies, just implement the lo.DispatchingStrategy prototype: go type DispatchingStrategy[T any] func(message T, messageIndex uint64, channels []<-chan T) int Eg: ```go type Message struct { TenantID uuid.UUID } func hash(id uuid.UUID) int { h := fnv.New32a() h.Write([]byte(id.String())) return int(h.Sum32()) } // Routes messages per TenantID. customStrategy := func(message string, messageIndex uint64, channels []<-chan string) int { destination := hash(message) % len(channels) // check if channel is full if len(channels[destination]) < cap(channels[destination]) { return destination } // fallback when child channel is full return utils.DispatchingStrategyRoundRobin(message, uint64(destination), channels) } children := lo.ChannelDispatcher(ch, 5, 10, customStrategy) ... ``` SliceToChannel Returns a read-only channels of collection elements. Channel is closed after last element. Channel capacity can be customized. ```go list := []int{1, 2, 3, 4, 5} for v := range lo.SliceToChannel(2, list) { println(v) } // prints 1, then 2, then 3, then 4, then 5 ``` ChannelToSlice Returns a slice built from channels items. Blocks until channel closes. ```go list := []int{1, 2, 3, 4, 5} ch := lo.SliceToChannel(2, list) items := ChannelToSlice(ch) // []int{1, 2, 3, 4, 5} ``` Generator Implements the generator design pattern. Channel is closed after last element. Channel capacity can be customized. ```go generator := func(yield func(int)) { yield(1) yield(2) yield(3) } for v := range lo.Generator(2, generator) { println(v) } // prints 1, then 2, then 3 ``` Buffer Creates a slice of n elements from a channel. Returns the slice, the slice length, the read time and the channel status (opened/closed). ```go ch := lo.SliceToChannel(2, []int{1, 2, 3, 4, 5}) items1, length1, duration1, ok1 := lo.Buffer(ch, 3) // []int{1, 2, 3}, 3, 0s, true items2, length2, duration2, ok2 := lo.Buffer(ch, 3) // []int{4, 5}, 2, 0s, false ``` Example: RabbitMQ consumer 👇 ```go ch := readFromQueue() for { // read 1k items items, length, _, ok := lo.Buffer(ch, 1000) // do batching stuff if !ok { break } } ``` BufferWithTimeout Creates a slice of n elements from a channel, with timeout. Returns the slice, the slice length, the read time and the channel status (opened/closed). ```go generator := func(yield func(int)) { for i := 0; i < 5; i++ { yield(i) time.Sleep(35*time.Millisecond) } } ch := lo.Generator(0, generator) items1, length1, duration1, ok1 := lo.BufferWithTimeout(ch, 3, 100 time.Millisecond) // []int{1, 2}, 2, 100ms, true items2, length2, duration2, ok2 := lo.BufferWithTimeout(ch, 3, 100 time.Millisecond) // []int{3, 4, 5}, 3, 75ms, true items3, length3, duration2, ok3 := lo.BufferWithTimeout(ch, 3, 100*time.Millisecond) // []int{}, 0, 10ms, false ``` Example: RabbitMQ consumer 👇 ```go ch := readFromQueue() for { // read 1k items // wait up to 1 second items, length, _, ok := lo.BufferWithTimeout(ch, 1000, 1*time.Second) // do batching stuff if !ok { break } } ``` Example: Multithreaded RabbitMQ consumer 👇 ```go ch := readFromQueue() // 5 workers // prefetch 1k messages per worker children := lo.ChannelDispatcher(ch, 5, 1000, lo.DispatchingStrategyFirst[int]) consumer := func(c <-chan int) { for { // read 1k items // wait up to 1 second items, length, _, ok := lo.BufferWithTimeout(ch, 1000, 1*time.Second) // do batching stuff if !ok { break } } } for i := range children { go consumer(children[i]) } ``` FanIn Merge messages from multiple input channels into a single buffered channel. Output messages has no priority. When all upstream channels reach EOF, downstream channel closes. ```go stream1 := make(chan int, 42) stream2 := make(chan int, 42) stream3 := make(chan int, 42) all := lo.FanIn(100, stream1, stream2, stream3) // <-chan int ``` FanOut Broadcasts all the upstream messages to multiple downstream channels. When upstream channel reach EOF, downstream channels close. If any downstream channels is full, broadcasting is paused. ```go stream := make(chan int, 42) all := lo.FanOut(5, 100, stream) // [5]<-chan int ``` Contains Returns true if an element is present in a collection. go present := lo.Contains([]int{0, 1, 2, 3, 4, 5}, 5) // true ContainsBy Returns true if the predicate function returns true . go present := lo.ContainsBy([]int{0, 1, 2, 3, 4, 5}, func(x int) bool { return x == 3 }) // true Every Returns true if all elements of a subset are contained into a collection or if the subset is empty. ```go ok := lo.Every([]int{0, 1, 2, 3, 4, 5}, []int{0, 2}) // true ok := lo.Every([]int{0, 1, 2, 3, 4, 5}, []int{0, 6}) // false ``` EveryBy Returns true if the predicate returns true for all of the elements in the collection or if the collection is empty. go b := EveryBy([]int{1, 2, 3, 4}, func(x int) bool { return x < 5 }) // true Some Returns true if at least 1 element of a subset is contained into a collection. If the subset is empty Some returns false. ```go ok := lo.Some([]int{0, 1, 2, 3, 4, 5}, []int{0, 2}) // true ok := lo.Some([]int{0, 1, 2, 3, 4, 5}, []int{-1, 6}) // false ``` SomeBy Returns true if the predicate returns true for any of the elements in the collection. If the collection is empty SomeBy returns false. go b := SomeBy([]int{1, 2, 3, 4}, func(x int) bool { return x < 3 }) // true None Returns true if no element of a subset are contained into a collection or if the subset is empty. go b := None([]int{0, 1, 2, 3, 4, 5}, []int{0, 2}) // false b := None([]int{0, 1, 2, 3, 4, 5}, []int{-1, 6}) // true NoneBy Returns true if the predicate returns true for none of the elements in the collection or if the collection is empty. go b := NoneBy([]int{1, 2, 3, 4}, func(x int) bool { return x < 0 }) // true Intersect Returns the intersection between two collections. ```go result1 := lo.Intersect([]int{0, 1, 2, 3, 4, 5}, []int{0, 2}) // []int{0, 2} result2 := lo.Intersect([]int{0, 1, 2, 3, 4, 5}, []int{0, 6}) // []int{0} result3 := lo.Intersect([]int{0, 1, 2, 3, 4, 5}, []int{-1, 6}) // []int{} ``` Difference Returns the difference between two collections. The first value is the collection of element absent of list2. The second value is the collection of element absent of list1. ```go left, right := lo.Difference([]int{0, 1, 2, 3, 4, 5}, []int{0, 2, 6}) // []int{1, 3, 4, 5}, []int{6} left, right := lo.Difference([]int{0, 1, 2, 3, 4, 5}, []int{0, 1, 2, 3, 4, 5}) // []int{}, []int{} ``` Union Returns all distinct elements from given collections. Result will not change the order of elements relatively. go union := lo.Union([]int{0, 1, 2, 3, 4, 5}, []int{0, 2}, []int{0, 10}) // []int{0, 1, 2, 3, 4, 5, 10} Without Returns slice excluding all given values. ```go subset := lo.Without([]int{0, 2, 10}, 2) // []int{0, 10} subset := lo.Without([]int{0, 2, 10}, 0, 1, 2, 3, 4, 5) // []int{10} ``` WithoutEmpty Returns slice excluding empty values. go subset := lo.WithoutEmpty([]int{0, 2, 10}) // []int{2, 10} IndexOf Returns the index at which the first occurrence of a value is found in an array or return -1 if the value cannot be found. ```go found := lo.IndexOf([]int{0, 1, 2, 1, 2, 3}, 2) // 2 notFound := lo.IndexOf([]int{0, 1, 2, 1, 2, 3}, 6) // -1 ``` LastIndexOf Returns the index at which the last occurrence of a value is found in an array or return -1 if the value cannot be found. ```go found := lo.LastIndexOf([]int{0, 1, 2, 1, 2, 3}, 2) // 4 notFound := lo.LastIndexOf([]int{0, 1, 2, 1, 2, 3}, 6) // -1 ``` Find Search an element in a slice based on a predicate. It returns element and true if element was found. ```go str, ok := lo.Find([]string{"a", "b", "c", "d"}, func(i string) bool { return i == "b" }) // "b", true str, ok := lo.Find([]string{"foobar"}, func(i string) bool { return i == "b" }) // "", false ``` FindIndexOf FindIndexOf searches an element in a slice based on a predicate and returns the index and true. It returns -1 and false if the element is not found. ```go str, index, ok := lo.FindIndexOf([]string{"a", "b", "a", "b"}, func(i string) bool { return i == "b" }) // "b", 1, true str, index, ok := lo.FindIndexOf([]string{"foobar"}, func(i string) bool { return i == "b" }) // "", -1, false ``` FindLastIndexOf FindLastIndexOf searches an element in a slice based on a predicate and returns the index and true. It returns -1 and false if the element is not found. ```go str, index, ok := lo.FindLastIndexOf([]string{"a", "b", "a", "b"}, func(i string) bool { return i == "b" }) // "b", 4, true str, index, ok := lo.FindLastIndexOf([]string{"foobar"}, func(i string) bool { return i == "b" }) // "", -1, false ``` FindOrElse Search an element in a slice based on a predicate. It returns the element if found or a given fallback value otherwise. ```go str := lo.FindOrElse([]string{"a", "b", "c", "d"}, "x", func(i string) bool { return i == "b" }) // "b" str := lo.FindOrElse([]string{"foobar"}, "x", func(i string) bool { return i == "b" }) // "x" ``` FindKey Returns the key of the first value matching. ```go result1, ok1 := lo.FindKey(map[string]int{"foo": 1, "bar": 2, "baz": 3}, 2) // "bar", true result2, ok2 := lo.FindKey(map[string]int{"foo": 1, "bar": 2, "baz": 3}, 42) // "", false type test struct { foobar string } result3, ok3 := lo.FindKey(map[string]test{"foo": test{"foo"}, "bar": test{"bar"}, "baz": test{"baz"}}, test{"foo"}) // "foo", true ``` FindKeyBy Returns the key of the first element predicate returns truthy for. ```go result1, ok1 := lo.FindKeyBy(map[string]int{"foo": 1, "bar": 2, "baz": 3}, func(k string, v int) bool { return k == "foo" }) // "foo", true result2, ok2 := lo.FindKeyBy(map[string]int{"foo": 1, "bar": 2, "baz": 3}, func(k string, v int) bool { return false }) // "", false ``` FindUniques Returns a slice with all the unique elements of the collection. The order of result values is determined by the order they occur in the array. go uniqueValues := lo.FindUniques([]int{1, 2, 2, 1, 2, 3}) // []int{3} FindUniquesBy Returns a slice with all the unique elements of the collection. The order of result values is determined by the order they occur in the array. It accepts iteratee which is invoked for each element in array to generate the criterion by which uniqueness is computed. go uniqueValues := lo.FindUniquesBy([]int{3, 4, 5, 6, 7}, func(i int) int { return i%3 }) // []int{5} FindDuplicates Returns a slice with the first occurrence of each duplicated elements of the collection. The order of result values is determined by the order they occur in the array. go duplicatedValues := lo.FindDuplicates([]int{1, 2, 2, 1, 2, 3}) // []int{1, 2} FindDuplicatesBy Returns a slice with the first occurrence of each duplicated elements of the collection. The order of result values is determined by the order they occur in the array. It accepts iteratee which is invoked for each element in array to generate the criterion by which uniqueness is computed. go duplicatedValues := lo.FindDuplicatesBy([]int{3, 4, 5, 6, 7}, func(i int) int { return i%3 }) // []int{3, 4} Min Search the minimum value of a collection. Returns zero value when collection is empty. ```go min := lo.Min([]int{1, 2, 3}) // 1 min := lo.Min([]int{}) // 0 ``` MinBy Search the minimum value of a collection using the given comparison function. If several values of the collection are equal to the smallest value, returns the first such value. Returns zero value when collection is empty. ```go min := lo.MinBy([]string{"s1", "string2", "s3"}, func(item string, min string) bool { return len(item) < len(min) }) // "s1" min := lo.MinBy([]string{}, func(item string, min string) bool { return len(item) < len(min) }) // "" ``` Max Search the maximum value of a collection. Returns zero value when collection is empty. ```go max := lo.Max([]int{1, 2, 3}) // 3 max := lo.Max([]int{}) // 0 ``` MaxBy Search the maximum value of a collection using the given comparison function. If several values of the collection are equal to the greatest value, returns the first such value. Returns zero value when collection is empty. ```go max := lo.MaxBy([]string{"string1", "s2", "string3"}, func(item string, max string) bool { return len(item) > len(max) }) // "string1" max := lo.MaxBy([]string{}, func(item string, max string) bool { return len(item) > len(max) }) // "" ``` Last Returns the last element of a collection or error if empty. go last, err := lo.Last([]int{1, 2, 3}) // 3 Nth Returns the element at index nth of collection. If nth is negative, the nth element from the end is returned. An error is returned when nth is out of slice bounds. ```go nth, err := lo.Nth([]int{0, 1, 2, 3}, 2) // 2 nth, err := lo.Nth([]int{0, 1, 2, 3}, -2) // 2 ``` Sample Returns a random item from collection. ```go lo.Sample([]string{"a", "b", "c"}) // a random string from []string{"a", "b", "c"} lo.Sample([]string{}) // "" ``` Samples Returns N random unique items from collection. go lo.Samples([]string{"a", "b", "c"}, 3) // []string{"a", "b", "c"} in random order Ternary A 1 line if/else statement. ```go result := lo.Ternary(true, "a", "b") // "a" result := lo.Ternary(false, "a", "b") // "b" ``` [ play ] TernaryF A 1 line if/else statement whose options are functions. ```go result := lo.TernaryF(true, func() string { return "a" }, func() string { return "b" }) // "a" result := lo.TernaryF(false, func() string { return "a" }, func() string { return "b" }) // "b" ``` Useful to avoid nil-pointer dereferencing in initializations, or avoid running unnecessary code ```go var s *string someStr := TernaryF(s == nil, func() string { return uuid.New().String() }, func() string { return *s }) // ef782193-c30c-4e2e-a7ae-f8ab5e125e02 ``` [ play ] If / ElseIf / Else ```go result := lo.If(true, 1). ElseIf(false, 2). Else(3) // 1 result := lo.If(false, 1). ElseIf(true, 2). Else(3) // 2 result := lo.If(false, 1). ElseIf(false, 2). Else(3) // 3 ``` Using callbacks: go result := lo.IfF(true, func () int { return 1 }). ElseIfF(false, func () int { return 2 }). ElseF(func () int { return 3 }) // 1 Mixed: go result := lo.IfF(true, func () int { return 1 }). Else(42) // 1 [ play ] Switch / Case / Default ```go result := lo.Switch(1). Case(1, "1"). Case(2, "2"). Default("3") // "1" result := lo.Switch(2). Case(1, "1"). Case(2, "2"). Default("3") // "2" result := lo.Switch(42). Case(1, "1"). Case(2, "2"). Default("3") // "3" ``` Using callbacks: go result := lo.Switch(1). CaseF(1, func() string { return "1" }). CaseF(2, func() string { return "2" }). DefaultF(func() string { return "3" }) // "1" Mixed: go result := lo.Switch(1). CaseF(1, func() string { return "1" }). Default("42") // "1" [ play ] IsNil Checks if a value is nil or if it's a reference type with a nil underlying value. ```go var x int IsNil(x)) // false var k struct{} IsNil(k) // false var i *int IsNil(i) // true var ifaceWithNilValue any = (*string)(nil) IsNil(ifaceWithNilValue) // true ifaceWithNilValue == nil // false ``` ToPtr Returns a pointer copy of the value. go ptr := lo.ToPtr("hello world") // *string{"hello world"} EmptyableToPtr Returns a pointer copy of value if it's nonzero. Otherwise, returns nil pointer. ```go ptr := lo.EmptyableToPtr []int // nil ptr := lo.EmptyableToPtr string // nil ptr := lo.EmptyableToPtr []int // *[]int{} ptr := lo.EmptyableToPtr string // *string{"hello world"} ``` FromPtr Returns the pointer value or empty. ```go str := "hello world" value := lo.FromPtr(&str) // "hello world" value := lo.FromPtr string // "" ``` FromPtrOr Returns the pointer value or the fallback value. ```go str := "hello world" value := lo.FromPtrOr(&str, "empty") // "hello world" value := lo.FromPtrOr string // "empty" ``` ToSlicePtr Returns a slice of pointer copy of value. go ptr := lo.ToSlicePtr([]string{"hello", "world"}) // []*string{"hello", "world"} ToAnySlice Returns a slice with all elements mapped to any type. go elements := lo.ToAnySlice([]int{1, 5, 1}) // []any{1, 5, 1} FromAnySlice Returns an any slice with all elements mapped to a type. Returns false in case of type conversion failure. ```go elements, ok := lo.FromAnySlice([]any{"foobar", 42}) // []string{}, false elements, ok := lo.FromAnySlice([]any{"foobar", "42"}) // []string{"foobar", "42"}, true ``` Empty Returns an empty value. go lo.Empty[int]() // 0 lo.Empty[string]() // "" lo.Empty[bool]() // false IsEmpty Returns true if argument is a zero value. ```go lo.IsEmpty(0) // true lo.IsEmpty(42) // false lo.IsEmpty("") // true lo.IsEmpty("foobar") // false type test struct { foobar string } lo.IsEmpty(test{foobar: ""}) // true lo.IsEmpty(test{foobar: "foobar"}) // false ``` IsNotEmpty Returns true if argument is a zero value. ```go lo.IsNotEmpty(0) // false lo.IsNotEmpty(42) // true lo.IsNotEmpty("") // false lo.IsNotEmpty("foobar") // true type test struct { foobar string } lo.IsNotEmpty(test{foobar: ""}) // false lo.IsNotEmpty(test{foobar: "foobar"}) // true ``` Coalesce Returns the first non-empty arguments. Arguments must be comparable. ```go result, ok := lo.Coalesce(0, 1, 2, 3) // 1 true result, ok := lo.Coalesce("") // "" false var nilStr *string str := "foobar" result, ok := lo.Coalesce *string // &"foobar" true ``` Partial Returns new function that, when called, has its first argument set to the provided value. ```go add := func(x, y int) int { return x + y } f := lo.Partial(add, 5) f(10) // 15 f(42) // 47 ``` Partial2 -> Partial5 Returns new function that, when called, has its first argument set to the provided value. ```go add := func(x, y, z int) int { return x + y + z } f := lo.Partial2(add, 42) f(10, 5) // 57 f(42, -4) // 80 ``` Attempt Invokes a function N times until it returns valid output. Returning either the caught error or nil. When first argument is less than 1 , the function runs until a successful response is returned. ```go iter, err := lo.Attempt(42, func(i int) error { if i == 5 { return nil } return fmt.Errorf("failed") }) // 6 // nil iter, err := lo.Attempt(2, func(i int) error { if i == 5 { return nil } return fmt.Errorf("failed") }) // 2 // error "failed" iter, err := lo.Attempt(0, func(i int) error { if i < 42 { return fmt.Errorf("failed") } return nil }) // 43 // nil ``` For more advanced retry strategies (delay, exponential backoff...), please take a look on cenkalti/backoff . [ play ] AttemptWithDelay Invokes a function N times until it returns valid output, with a pause between each call. Returning either the caught error or nil. When first argument is less than 1 , the function runs until a successful response is returned. ```go iter, duration, err := lo.AttemptWithDelay(5, 2*time.Second, func(i int, duration time.Duration) error { if i == 2 { return nil } return fmt.Errorf("failed") }) // 3 // ~ 4 seconds // nil ``` For more advanced retry strategies (delay, exponential backoff...), please take a look on cenkalti/backoff . [ play ] AttemptWhile Invokes a function N times until it returns valid output. Returning either the caught error or nil, and along with a bool value to identifying whether it needs invoke function continuously. It will terminate the invoke immediately if second bool value is returned with falsy value. When first argument is less than 1 , the function runs until a successful response is returned. ```go count1, err1 := lo.AttemptWhile(5, func(i int) (error, bool) { err := doMockedHTTPRequest(i) if err != nil { if errors.Is(err, ErrBadRequest) { // lets assume ErrBadRequest is a critical error that needs to terminate the invoke return err, false // flag the second return value as false to terminate the invoke } return err, true } return nil, false }) ``` For more advanced retry strategies (delay, exponential backoff...), please take a look on cenkalti/backoff . [ play ] AttemptWhileWithDelay Invokes a function N times until it returns valid output, with a pause between each call. Returning either the caught error or nil, and along with a bool value to identifying whether it needs to invoke function continuously. It will terminate the invoke immediately if second bool value is returned with falsy value. When first argument is less than 1 , the function runs until a successful response is returned. ```go count1, time1, err1 := lo.AttemptWhileWithDelay(5, time.Millisecond, func(i int, d time.Duration) (error, bool) { err := doMockedHTTPRequest(i) if err != nil { if errors.Is(err, ErrBadRequest) { // lets assume ErrBadRequest is a critical error that needs to terminate the invoke return err, false // flag the second return value as false to terminate the invoke } return err, true } return nil, false }) ``` For more advanced retry strategies (delay, exponential backoff...), please take a look on cenkalti/backoff . [ play ] Debounce NewDebounce creates a debounced instance that delays invoking functions given until after wait milliseconds have elapsed, until cancel is called. ```go f := func() { println("Called once after 100ms when debounce stopped invoking!") } debounce, cancel := lo.NewDebounce(100 * time.Millisecond, f) for j := 0; j < 10; j++ { debounce() } time.Sleep(1 * time.Second) cancel() ``` [ play ] DebounceBy NewDebounceBy creates a debounced instance for each distinct key, that delays invoking functions given until after wait milliseconds have elapsed, until cancel is called. ```go f := func(key string, count int) { println(key + ": Called once after 100ms when debounce stopped invoking!") } debounce, cancel := lo.NewDebounceBy(100 * time.Millisecond, f) for j := 0; j < 10; j++ { debounce("first key") debounce("second key") } time.Sleep(1 * time.Second) cancel("first key") cancel("second key") ``` [ play ] Synchronize Wraps the underlying callback in a mutex. It receives an optional mutex. ```go s := lo.Synchronize() for i := 0; i < 10; i++ { go s.Do(func () { println("will be called sequentially") }) } ``` It is equivalent to: ```go mu := sync.Mutex{} func foobar() { mu.Lock() defer mu.Unlock() // ... } ``` Async Executes a function in a goroutine and returns the result in a channel. go ch := lo.Async(func() error { time.Sleep(10 * time.Second); return nil }) // chan error (nil) Async{0->6} Executes a function in a goroutine and returns the result in a channel. For function with multiple return values, the results will be returned as a tuple inside the channel. For function without return, struct{} will be returned in the channel. ```go ch := lo.Async0(func() { time.Sleep(10 * time.Second) }) // chan struct{} ch := lo.Async1(func() int { time.Sleep(10 * time.Second); return 42 }) // chan int (42) ch := lo.Async2(func() (int, string) { time.Sleep(10 * time.Second); return 42, "Hello" }) // chan lo.Tuple2[int, string] ({42, "Hello"}) ``` Transaction Implements a Saga pattern. ```go transaction := NewTransaction int . Then( func(state int) (int, error) { fmt.Println("step 1") return state + 10, nil }, func(state int) int { fmt.Println("rollback 1") return state - 10 }, ). Then( func(state int) (int, error) { fmt.Println("step 2") return state + 15, nil }, func(state int) int { fmt.Println("rollback 2") return state - 15 }, ). Then( func(state int) (int, error) { fmt.Println("step 3") if true { return state, fmt.Errorf("error") } return state + 42, nil }, func(state int) int { fmt.Println("rollback 3") return state - 42 }, ) _, _ = transaction.Process(-5) // Output: // step 1 // step 2 // step 3 // rollback 2 // rollback 1 ``` Validate Helper function that creates an error when a condition is not met. ```go slice := []string{"a"} val := lo.Validate(len(slice) == 0, "Slice should be empty but contains %v", slice) // error("Slice should be empty but contains [a]") slice := []string{} val := lo.Validate(len(slice) == 0, "Slice should be empty but contains %v", slice) // nil ``` [ play ] Must Wraps a function call to panics if second argument is error or false , returns the value otherwise. ```go val := lo.Must(time.Parse("2006-01-02", "2022-01-15")) // 2022-01-15 val := lo.Must(time.Parse("2006-01-02", "bad-value")) // panics ``` [ play ] Must{0->6} Must* has the same behavior as Must, but returns multiple values. ```go func example0() (error) func example1() (int, error) func example2() (int, string, error) func example3() (int, string, time.Date, error) func example4() (int, string, time.Date, bool, error) func example5() (int, string, time.Date, bool, float64, error) func example6() (int, string, time.Date, bool, float64, byte, error) lo.Must0(example0()) val1 := lo.Must1(example1()) // alias to Must val1, val2 := lo.Must2(example2()) val1, val2, val3 := lo.Must3(example3()) val1, val2, val3, val4 := lo.Must4(example4()) val1, val2, val3, val4, val5 := lo.Must5(example5()) val1, val2, val3, val4, val5, val6 := lo.Must6(example6()) ``` You can wrap functions like func (...) (..., ok bool) . ```go // math.Signbit(float64) bool lo.Must0(math.Signbit(v)) // bytes.Cut([]byte,[]byte) ([]byte, []byte, bool) before, after := lo.Must2(bytes.Cut(s, sep)) ``` You can give context to the panic message by adding some printf-like arguments. ```go val, ok := lo.Find(myString, func(i string) bool { return i == requiredChar }) lo.Must0(ok, "'%s' must always contain '%s'", myString, requiredChar) list := []int{0, 1, 2} item := 5 lo.Must0(lo.Contains int , "'%s' must always contain '%s'", list, item) ... ``` [ play ] Try Calls the function and return false in case of error and on panic. ```go ok := lo.Try(func() error { panic("error") return nil }) // false ok := lo.Try(func() error { return nil }) // true ok := lo.Try(func() error { return fmt.Errorf("error") }) // false ``` [ play ] Try{0->6} The same behavior than Try , but callback returns 2 variables. go ok := lo.Try2(func() (string, error) { panic("error") return "", nil }) // false [ play ] TryOr Calls the function and return a default value in case of error and on panic. ```go str, ok := lo.TryOr(func() (string, error) { panic("error") return "hello", nil }, "world") // world // false str, ok := lo.TryOr(func() error { return "hello", nil }, "world") // hello // true str, ok := lo.TryOr(func() error { return "hello", fmt.Errorf("error") }, "world") // world // false ``` [ play ] TryOr{0->6} The same behavior than TryOr , but callback returns X variables. go str, nbr, ok := lo.TryOr2(func() (string, int, error) { panic("error") return "hello", 42, nil }, "world", 21) // world // 21 // false [ play ] TryWithErrorValue The same behavior than Try , but also returns value passed to panic. go err, ok := lo.TryWithErrorValue(func() error { panic("error") return nil }) // "error", false [ play ] TryCatch The same behavior than Try , but calls the catch function in case of error. ```go caught := false ok := lo.TryCatch(func() error { panic("error") return nil }, func() { caught = true }) // false // caught == true ``` [ play ] TryCatchWithErrorValue The same behavior than TryWithErrorValue , but calls the catch function in case of error. ```go caught := false ok := lo.TryCatchWithErrorValue(func() error { panic("error") return nil }, func(val any) { caught = val == "error" }) // false // caught == true ``` [ play ] ErrorsAs A shortcut for: ```go err := doSomething() var rateLimitErr *RateLimitError if ok := errors.As(err, &rateLimitErr); ok { // retry later } ``` 1 line lo helper: ```go err := doSomething() if rateLimitErr, ok := lo.ErrorsAs *RateLimitError ; ok { // retry later } ``` [ play ] 🛩 Benchmark We executed a simple benchmark with the a dead-simple lo.Map loop: See the full implementation here . go _ = lo.Map[int64](arr, func(x int64, i int) string { return strconv.FormatInt(x, 10) }) Result: Here is a comparison between lo.Map , lop.Map , go-funk library and a simple Go for loop. shell $ go test -benchmem -bench ./... goos: linux goarch: amd64 pkg: github.com/samber/lo cpu: Intel(R) Core(TM) i5-7267U CPU @ 3.10GHz cpu: Intel(R) Core(TM) i7 CPU 920 @ 2.67GHz BenchmarkMap/lo.Map-8 8 132728237 ns/op 39998945 B/op 1000002 allocs/op BenchmarkMap/lop.Map-8 2 503947830 ns/op 119999956 B/op 3000007 allocs/op BenchmarkMap/reflect-8 2 826400560 ns/op 170326512 B/op 4000042 allocs/op BenchmarkMap/for-8 9 126252954 ns/op 39998674 B/op 1000001 allocs/op PASS ok github.com/samber/lo 6.657s lo.Map is way faster (x7) than go-funk , a reflection-based Map implementation. lo.Map have the same allocation profile than for . lo.Map is 4% slower than for . lop.Map is slower than lo.Map because it implies more memory allocation and locks. lop.Map will be useful for long-running callbacks, such as i/o bound processing. for beats other implementations for memory and CPU. 🤝 Contributing Ping me on twitter @samuelberthe (DMs, mentions, whatever :)) Fork the project Fix open issues or request new features Don't hesitate ;) Helper naming: helpers must be self explanatory and respect standards (other languages, libraries...). Feel free to suggest many names in your contributions. With Docker bash docker-compose run --rm dev Without Docker ```bash Install some dev dependencies make tools Run tests make test or make watch-test ``` 👤 Contributors 💫 Show your support Give a ⭐️ if this project helped you! 📝 License Copyright © 2022 Samuel Berthe . This project is MIT licensed.

💥 A Lodash-style Go library based on Go 1.18+ Generics (map, filter, contains, find...)

lodash,golang,go,generics,contract,constraints,functional,programming,typesafe,filterable

tremorlabs/tremor

Documentation • Website React components to build charts and dashboards Tremor 20+ open-source components built on top of Tailwind CSS to make visualizing data simple again. Fully open-source, made by data scientists and software engineers with a sweet spot for design. Getting Started See our Installation Guide . To make use of the library we also need Tailwind CSS setup in the project. Example With Tremor creating an analytical interface is easy. ```jsx "use client"; import { AreaChart, Card } from "@tremor/react"; const chartdata = [ { date: "Jan 23", "Route Requests": 289, "Station Requests": 233, }, // ... { date: "Oct 23", "Route Requests": 283, "Station Requests": 247, }, ]; export default function Example() { return ( Total Requests 6,568 ); } ``` Community and Contribution We are always looking for new ideas or other ways to improve Tremor. If you have developed anything cool or found a bug, send us a pull request. Check out our Contributor License Agreement here . License Apache License 2.0 Copyright © 2024 Tremor Labs, Inc. All rights reserved.

React components to build charts and dashboards

reactjs,tailwindcss,ui-system,typescript,react-components

NVlabs/instant-ngp

Instant Neural Graphics Primitives Ever wanted to train a NeRF model of a fox in under 5 seconds? Or fly around a scene captured from photos of a factory robot? Of course you have! Here you will find an implementation of four neural graphics primitives , being neural radiance fields (NeRF), signed distance functions (SDFs), neural images, and neural volumes. In each case, we train and render a MLP with multiresolution hash input encoding using the tiny-cuda-nn framework. Instant Neural Graphics Primitives with a Multiresolution Hash Encoding Thomas Müller , Alex Evans , Christoph Schied , Alexander Keller ACM Transactions on Graphics (__SIGGRAPH__), July 2022 Project page / Paper / Video / Presentation / Real-Time Live / BibTeX For business inquiries, please submit the NVIDIA research licensing form . Installation If you have Windows, download one of the following releases corresponding to your graphics card and extract it. Then, start instant-ngp.exe . RTX 3000 & 4000 series, RTX A4000–A6000 , and other Ampere & Ada cards RTX 2000 series, Titan RTX, Quadro RTX 4000–8000 , and other Turing cards GTX 1000 series, Titan Xp, Quadro P1000–P6000 , and other Pascal cards Keep reading for a guided tour of the application or, if you are interested in creating your own NeRF, watch the video tutorial or read the written instructions . If you use Linux, or want the developer Python bindings , or if your GPU is not listed above (e.g. Hopper, Volta, or Maxwell generations), you need to build instant-ngp yourself . Usage instant-ngp comes with an interactive GUI that includes many features: - comprehensive controls for interactively exploring neural graphics primitives, - VR mode for viewing neural graphics primitives through a virtual-reality headset, - saving and loading "snapshots" so you can share your graphics primitives on the internet, - a camera path editor to create videos, - NeRF->Mesh and SDF->Mesh conversion, - camera pose and lens optimization, - and many more. NeRF fox Simply start instant-ngp and drag the data/nerf/fox folder into the window. Or, alternatively, use the command line: sh instant-ngp$ ./instant-ngp data/nerf/fox You can use any NeRF-compatible dataset, e.g. from original NeRF , the SILVR dataset , or the DroneDeploy dataset . To create your own NeRF, watch the video tutorial or read the written instructions . SDF armadillo Drag data/sdf/armadillo.obj into the window or use the command: sh instant-ngp$ ./instant-ngp data/sdf/armadillo.obj Image of Einstein Drag data/image/albert.exr into the window or use the command: sh instant-ngp$ ./instant-ngp data/image/albert.exr To reproduce the gigapixel results, download, for example, the Tokyo image and convert it to .bin using the scripts/convert_image.py script. This custom format improves compatibility and loading speed when resolution is high. Now you can run: sh instant-ngp$ ./instant-ngp data/image/tokyo.bin Volume renderer Download the nanovdb volume for the Disney cloud , which is derived from here ( CC BY-SA 3.0 ). Then drag wdas_cloud_quarter.nvdb into the window or use the command: sh instant-ngp$ ./instant-ngp wdas_cloud_quarter.nvdb Keyboard shortcuts and recommended controls Here are the main keyboard controls for the instant-ngp application. | Key | Meaning | | :-------------: | ------------- | | WASD | Forward / pan left / backward / pan right. | | Spacebar / C | Move up / down. | | = or + / - or _ | Increase / decrease camera velocity (first person mode) or zoom in / out (third person mode). | | E / Shift+E | Increase / decrease exposure. | | Tab | Toggle menu visibility. | | T | Toggle training. After around two minutes training tends to settle down, so can be toggled off. | | { } | Go to the first/last training image camera view. | | [ ] | Go to the previous/next training image camera view. | | R | Reload network from file. | | Shift+R | Reset camera. | | O | Toggle visualization or accumulated error map. | | G | Toggle visualization of the ground truth. | | M | Toggle multi-view visualization of layers of the neural model. See the paper's video for a little more explanation. | | , / . | Shows the previous / next visualized layer; hit M to escape. | | 1-8 | Switches among various render modes, with 2 being the standard one. You can see the list of render mode names in the control interface. | There are many controls in the instant-ngp GUI. First, note that this GUI can be moved and resized, as can the "Camera path" GUI (which first must be expanded to be used). Recommended user controls in instant-ngp are: Snapshot: use "Save" to save the trained NeRF, "Load" to reload. Rendering -> DLSS: toggling this on and setting "DLSS sharpening" to 1.0 can often improve rendering quality. Rendering -> Crop size: trim back the surrounding environment to focus on the model. "Crop aabb" lets you move the center of the volume of interest and fine tune. See more about this feature in our NeRF training & dataset tips . The "Camera path" GUI lets you create a camera path for rendering a video. The button "Add from cam" inserts keyframes from the current perspective. Then, you can render a video .mp4 of your camera path or export the keyframes to a .json file. There is a bit more information about the GUI in this post and in this video guide to creating your own video . VR controls To view the neural graphics primitive in VR, first start your VR runtime. This will most likely be either - OculusVR if you have an Oculus Rift or Meta Quest (with link cable) headset, and - SteamVR if you have another headset. - Any OpenXR-compatible runtime will work. Then, press the Connect to VR/AR headset button in the instant-ngp GUI and put on your headset. Before entering VR, we strongly recommend that you first finish training (press "Stop training") or load a pre-trained snapshot for maximum performance. In VR, you have the following controls. | Control | Meaning | | :--------------------: | ------------- | | Left stick / trackpad | Move | | Right stick / trackpad | Turn camera | | Press stick / trackpad | Erase NeRF around the hand | | Grab (one-handed) | Drag neural graphics primitive | | Grab (two-handed) | Rotate and zoom (like pinch-to-zoom on a smartphone) | Building instant-ngp (Windows & Linux) Requirements An NVIDIA GPU ; tensor cores increase performance when available. All shown results come from an RTX 3090. A C++14 capable compiler. The following choices are recommended and have been tested: Windows: Visual Studio 2019 or 2022 Linux: GCC/G++ 8 or higher A recent version of CUDA . The following choices are recommended and have been tested: Windows: CUDA 11.5 or higher Linux: CUDA 10.2 or higher CMake v3.21 or higher . (optional) Python 3.7 or higher for interactive bindings. Also, run pip install -r requirements.txt . (optional) OptiX 7.6 or higher for faster mesh SDF training. (optional) Vulkan SDK for DLSS support. If you are using Debian based Linux distribution, install the following packages sh sudo apt-get install build-essential git python3-dev python3-pip libopenexr-dev libxi-dev \ libglfw3-dev libglew-dev libomp-dev libxinerama-dev libxcursor-dev Alternatively, if you are using Arch or Arch derivatives, install the following packages sh sudo pacman -S cuda base-devel cmake openexr libxi glfw openmp libxinerama libxcursor We also recommend installing CUDA and OptiX in /usr/local/ and adding the CUDA installation to your PATH. For example, if you have CUDA 11.4, add the following to your ~/.bashrc sh export PATH="/usr/local/cuda-11.4/bin:$PATH" export LD_LIBRARY_PATH="/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH" Compilation Begin by cloning this repository and all its submodules using the following command: sh $ git clone --recursive https://github.com/nvlabs/instant-ngp $ cd instant-ngp Then, use CMake to build the project: (on Windows, this must be in a developer command prompt ) sh instant-ngp$ cmake . -B build -DCMAKE_BUILD_TYPE=RelWithDebInfo instant-ngp$ cmake --build build --config RelWithDebInfo -j If compilation fails inexplicably or takes longer than an hour, you might be running out of memory. Try running the above command without -j in that case. If this does not help, please consult this list of possible fixes before opening an issue. If the build succeeds, you can now run the code via the ./instant-ngp executable or the scripts/run.py script described below. If automatic GPU architecture detection fails, (as can happen if you have multiple GPUs installed), set the TCNN_CUDA_ARCHITECTURES environment variable for the GPU you would like to use. The following table lists the values for common GPUs. If your GPU is not listed, consult this exhaustive list . | H100 | 40X0 | 30X0 | A100 | 20X0 | TITAN V / V100 | 10X0 / TITAN Xp | 9X0 | K80 | |:----:|:----:|:----:|:----:|:----:|:--------------:|:---------------:|:---:|:---:| | 90 | 89 | 86 | 80 | 75 | 70 | 61 | 52 | 37 | Python bindings After you have built instant-ngp , you can use its Python bindings to conduct controlled experiments in an automated fashion. All features from the interactive GUI (and more!) have Python bindings that can be easily instrumented. For an example of how the ./instant-ngp application can be implemented and extended from within Python, see ./scripts/run.py , which supports a superset of the command line arguments that ./instant-ngp does. If you would rather build new models from the hash encoding and fast neural networks, consider tiny-cuda-nn 's PyTorch extension . Happy hacking! Additional resources Getting started with NVIDIA Instant NeRF blog post SIGGRAPH tutorial for advanced NeRF dataset creation . Frequently asked questions (FAQ) Q: The NeRF reconstruction of my custom dataset looks bad; what can I do? A: There could be multiple issues: - COLMAP might have been unable to reconstruct camera poses. - There might have been movement or blur during capture. Don't treat capture as an artistic task; treat it as photogrammetry. You want *as little blur as possible* in your dataset (motion, defocus, or otherwise) and all objects must be *static* during the entire capture. Bonus points if you are using a wide-angle lens (iPhone wide angle works well), because it covers more space than narrow lenses. - The dataset parameters (in particular aabb_scale ) might have been tuned suboptimally. We recommend starting with aabb_scale=128 and then increasing or decreasing it by factors of two until you get optimal quality. - Carefully read our NeRF training & dataset tips . Q: How can I save the trained model and load it again later? A: Two options: 1. Use the GUI's "Snapshot" section. 2. Use the Python bindings load_snapshot / save_snapshot (see scripts/run.py for example usage). Q: Can this codebase use multiple GPUs at the same time? A: Only for VR rendering, in which case one GPU is used per eye. Otherwise, no. To select a specific GPU to run on, use the CUDA_VISIBLE_DEVICES environment variable. To optimize the compilation for that specific GPU use the TCNN_CUDA_ARCHITECTURES environment variable. Q: How can I run instant-ngp in headless mode? A: Use ./instant-ngp --no-gui or python scripts/run.py . You can also compile without GUI via cmake -DNGP_BUILD_WITH_GUI=off ... Q: Does this codebase run on Google Colab ? A: Yes. See this example inspired on the notebook created by user @myagues . Caveat: this codebase requires large amounts of GPU RAM and might not fit on your assigned GPU. It will also run slower on older GPUs. Q: Is there a Docker container ? A: Yes. We bundle a Visual Studio Code development container , the .devcontainer/Dockerfile of which you can also use stand-alone. If you want to run the container without using VSCode: docker-compose -f .devcontainer/docker-compose.yml build instant-ngp xhost local:root docker-compose -f .devcontainer/docker-compose.yml run instant-ngp /bin/bash Then run the build commands above as normal. Q: How can I edit and train the underlying hash encoding or neural network on a new task? A: Use tiny-cuda-nn 's PyTorch extension . Q: What is the coordinate system convention? A: See this helpful diagram by user @jc211. Q: Why are background colors randomized during NeRF training? A: Transparency in the training data indicates a desire for transparency in the learned model. Using a solid background color, the model can minimize its loss by simply predicting that background color, rather than transparency (zero density). By randomizing the background colors, the model is forced to learn zero density to let the randomized colors "shine through". Q: How to mask away NeRF training pixels (e.g. for dynamic object removal)? A: For any training image xyz.* with dynamic objects, you can provide a dynamic_mask_xyz.png in the same folder. This file must be in PNG format, where non-zero pixel values indicate masked-away regions. Troubleshooting compile errors Before investigating further, make sure all submodules are up-to-date and try compiling again. sh instant-ngp$ git submodule sync --recursive instant-ngp$ git submodule update --init --recursive If instant-ngp still fails to compile, update CUDA as well as your compiler to the latest versions you can install on your system. It is crucial that you update both , as newer CUDA versions are not always compatible with earlier compilers and vice versa. If your problem persists, consult the following table of known issues. *After each step, delete the build folder and let CMake regenerate it before trying again.* | Problem | Resolution | |---------|------------| | CMake error: No CUDA toolset found / CUDA_ARCHITECTURES is empty for target "cmTC_0c70f" | Windows: the Visual Studio CUDA integration was not installed correctly. Follow these instructions to fix the problem without re-installing CUDA. ( #18 ) | | | Linux: Environment variables for your CUDA installation are probably incorrectly set. You may work around the issue using cmake . -B build -DCMAKE_CUDA_COMPILER=/usr/local/cuda-<your cuda version>/bin/nvcc ( #28 ) | | CMake error: No known features for CXX compiler "MSVC" | Reinstall Visual Studio & make sure you run CMake from a developer shell. Make sure you delete the build folder before building again. ( #21 ) | | Compile error: A single input file is required for a non-link phase when an outputfile is specified | Ensure there no spaces in the path to instant-ngp . Some build systems seem to have trouble with those. ( #39 #198 ) | | Compile error: undefined references to "cudaGraphExecUpdate" / identifier "cublasSetWorkspace" is undefined | Update your CUDA installation (which is likely 11.0) to 11.3 or higher. ( #34 #41 #42 ) | | Compile error: too few arguments in function call | Update submodules with the above two git commands. ( #37 #52 ) | | Python error: No module named 'pyngp' | It is likely that CMake did not detect your Python installation and therefore did not build pyngp . Check CMake logs to verify this. If pyngp was built in a different folder than build , Python will be unable to detect it and you have to supply the full path to the import statement. ( #43 ) | If you cannot find your problem in the table, try searching the discussions board and the issues area for help. If you are still stuck, please open an issue and ask for help. Thanks Many thanks to Jonathan Tremblay and Andrew Tao for testing early versions of this codebase and to Arman Toorians and Saurabh Jain for the factory robot dataset. We also thank Andrew Webb for noticing that one of the prime numbers in the spatial hash was not actually prime; this has been fixed since. This project makes use of a number of awesome open source libraries, including: * tiny-cuda-nn for fast CUDA networks and input encodings * tinyexr for EXR format support * tinyobjloader for OBJ format support * stb_image for PNG and JPEG support * Dear ImGui an excellent immediate mode GUI library * Eigen a C++ template library for linear algebra * pybind11 for seamless C++ / Python interop * and others! See the dependencies folder. Many thanks to the authors of these brilliant projects! License and Citation bibtex @article{mueller2022instant, author = {Thomas M\"uller and Alex Evans and Christoph Schied and Alexander Keller}, title = {Instant Neural Graphics Primitives with a Multiresolution Hash Encoding}, journal = {ACM Trans. Graph.}, issue_date = {July 2022}, volume = {41}, number = {4}, month = jul, year = {2022}, pages = {102:1--102:15}, articleno = {102}, numpages = {15}, url = {https://doi.org/10.1145/3528223.3530127}, doi = {10.1145/3528223.3530127}, publisher = {ACM}, address = {New York, NY, USA}, } Copyright © 2022, NVIDIA Corporation. All rights reserved. This work is made available under the Nvidia Source Code License-NC. Click here to view a copy of this license.

Instant neural graphics primitives: lightning fast NeRF and more

neural-network,machine-learning,cuda,nerf,computer-graphics,computer-vision,3d-reconstruction,signed-distance-functions,function-approximation,real-time

bloomberg/memray

Memray is a memory profiler for Python. It can track memory allocations in Python code, in native extension modules, and in the Python interpreter itself. It can generate several different types of reports to help you analyze the captured memory usage data. While commonly used as a CLI tool, it can also be used as a library to perform more fine-grained profiling tasks. Notable features: 🕵️‍♀️ Traces every function call so it can accurately represent the call stack, unlike sampling profilers. ℭ Also handles native calls in C/C++ libraries so the entire call stack is present in the results. 🏎 Blazing fast! Profiling slows the application only slightly. Tracking native code is somewhat slower, but this can be enabled or disabled on demand. 📈 It can generate various reports about the collected memory usage data, like flame graphs. 🧵 Works with Python threads. 👽🧵 Works with native-threads (e.g. C++ threads in C extensions). Memray can help with the following problems: Analyze allocations in applications to help discover the cause of high memory usage. Find memory leaks. Find hotspots in code that cause a lot of allocations. Note Memray only works on Linux and MacOS, and cannot be installed on other platforms. Help us improve Memray! We are constantly looking for feedback from our awesome community ❤️. If you have used Memray to solve a problem, profile an application, find a memory leak or anything else, please let us know! We would love to hear about your experience and how Memray helped you. Please, consider writing your story in the Success Stories discussion page . It really makes a difference! Installation Memray requires Python 3.7+ and can be easily installed using most common Python packaging tools. We recommend installing the latest stable release from PyPI with pip: shell python3 -m pip install memray Notice that Memray contains a C extension so releases are distributed as binary wheels as well as the source code. If a binary wheel is not available for your system (Linux x86/x64 or macOS), you'll need to ensure that all the dependencies are satisfied on the system where you are doing the installation. Building from source If you wish to build Memray from source you need the following binary dependencies in your system: libdebuginfod-dev (for Linux) libunwind (for Linux) liblz4 Check your package manager on how to install these dependencies (for example apt-get install build-essential python3-dev libdebuginfod-dev libunwind-dev liblz4-dev in Debian-based systems or brew install lz4 in MacOS). Note that you may need to teach the compiler where to find the header and library files of the dependencies. For example, in MacOS with brew you may need to run: shell export CFLAGS="-I$(brew --prefix lz4)/include" LDFLAGS="-L$(brew --prefix lz4)/lib -Wl,-rpath,$(brew --prefix lz4)/lib" before installing memray . Check the documentation of your package manager to know the location of the header and library files for more detailed information. If you are building on MacOS, you will also need to set the deployment target. shell export MACOSX_DEPLOYMENT_TARGET=10.14 Once you have the binary dependencies installed, you can clone the repository and follow with the normal building process: shell git clone git@github.com:bloomberg/memray.git memray cd memray python3 -m venv ../memray-env/ # just an example, put this wherever you want source ../memray-env/bin/activate python3 -m pip install --upgrade pip python3 -m pip install -e . -r requirements-test.txt -r requirements-extra.txt This will install Memray in the virtual environment in development mode (the -e of the last pip install command). If you plan to contribute back, you should install the pre-commit hooks: shell pre-commit install This will ensure that your contribution passes our linting checks. Documentation You can find the latest documentation available here . Usage There are many ways to use Memray. The easiest way is to use it as a command line tool to run your script, application, or library. ``` usage: memray [-h] [-v] {run,flamegraph,table,live,tree,parse,summary,stats} ... Memory profiler for Python applications Run memray run to generate a memory profile report, then use a reporter command such as memray flamegraph or memray table to convert the results into HTML. Example: $ python3 -m memray run -o output.bin my_script.py $ python3 -m memray flamegraph output.bin positional arguments: {run,flamegraph,table,live,tree,parse,summary,stats} Mode of operation run Run the specified application and track memory usage flamegraph Generate an HTML flame graph for peak memory usage table Generate an HTML table with all records in the peak memory usage live Remotely monitor allocations in a text-based interface tree Generate a tree view in the terminal for peak memory usage parse Debug a results file by parsing and printing each record in it summary Generate a terminal-based summary report of the functions that allocate most memory stats Generate high level stats of the memory usage in the terminal optional arguments: -h, --help Show this help message and exit -v, --verbose Increase verbosity. Option is additive and can be specified up to 3 times -V, --version Displays the current version of Memray Please submit feedback, ideas, and bug reports by filing a new issue at https://github.com/bloomberg/memray/issues ``` To use Memray over a script or a single python file you can use: shell python3 -m memray run my_script.py If you normally run your application with python3 -m my_module , you can use the -m flag with memray run : shell python3 -m memray run -m my_module You can also invoke Memray as a command line tool without having to use -m to invoke it as a module: shell memray run my_script.py memray run -m my_module The output will be a binary file (like memray-my_script.2369.bin ) that you can analyze in different ways. One way is to use the memray flamegraph command to generate a flame graph: shell memray flamegraph my_script.2369.bin This will produce an HTML file with a flame graph of the memory usage that you can inspect with your favorite browser. There are multiple other reporters that you can use to generate other types of reports, some of them generating terminal-based output and some of them generating HTML files. Here is an example of a Memray flamegraph: Pytest plugin If you want an easy and convenient way to use memray in your test suite, you can consider using pytest-memray . Once installed, this pytest plugin allows you to simply add --memray to the command line invocation: shell pytest --memray tests/ And will automatically get a report like this: ``` python3 -m pytest tests --memray =============================================================================================================================== test session starts ================================================================================================================================ platform linux -- Python 3.8.10, pytest-6.2.4, py-1.10.0, pluggy-0.13.1 rootdir: /mypackage, configfile: pytest.ini plugins: cov-2.12.0, memray-0.1.0 collected 21 items tests/test_package.py ..................... [100%] ================================================================================================================================= MEMRAY REPORT ================================================================================================================================== Allocations results for tests/test_package.py::some_test_that_allocates 📦 Total memory allocated: 24.4MiB 📏 Total allocations: 33929 📊 Histogram of allocation sizes: |▂ █ | 🥇 Biggest allocating functions: - parse:/opt/bb/lib/python3.8/ast.py:47 -> 3.0MiB - parse:/opt/bb/lib/python3.8/ast.py:47 -> 2.3MiB - _visit:/opt/bb/lib/python3.8/site-packages/astroid/transforms.py:62 -> 576.0KiB - parse:/opt/bb/lib/python3.8/ast.py:47 -> 517.6KiB - __init__:/opt/bb/lib/python3.8/site-packages/astroid/node_classes.py:1353 -> 512.0KiB ``` You can also use some of the included markers to make tests fail if the execution of said test allocates more memory than allowed: python @pytest.mark.limit_memory("24 MB") def test_foobar(): # do some stuff that allocates memory To learn more on how the plugin can be used and configured check out the plugin documentation . Native mode Memray supports tracking native C/C++ functions as well as Python functions. This can be especially useful when profiling applications that have C extensions (such as numpy or pandas ) as this gives a holistic vision of how much memory is allocated by the extension and how much is allocated by Python itself. To activate native tracking, you need to provide the --native argument when using the run subcommand: shell memray run --native my_script.py This will automatically add native information to the result file and it will be automatically used by any reporter (such the flamegraph or table reporters). This means that instead of seeing this in the flamegraphs: You will now be able to see what's happening inside the Python calls: Reporters display native frames in a different color than Python frames. They can also be distinguished by looking at the file location in a frame (Python frames will generally be generated from files with a .py extension while native frames will be generated from files with extensions like .c, .cpp or .h). Live mode Memray's live mode runs a script or a module in a terminal-based interface that allows you to interactively inspect its memory usage while it runs. This is useful for debugging scripts or modules that take a long time to run or that exhibit multiple complex memory patterns. You can use the --live option to run the script or module in live mode: shell memray run --live my_script.py or if you want to execute a module: shell memray run --live -m my_module This will show the following TUI interface in your terminal: Sorting results The results are displayed in descending order of total memory allocated by a function and the subfunctions called by it. You can change the ordering with the following keyboard shortcuts: t (default): Sort by total memory o: Sort by own memory a: Sort by allocation count In most terminals you can also click the "Sort by Total", "Sort by Own", and "Sort by Allocations" buttons on the footer. The sorted column's heading is underlined. Viewing different threads By default, the live command will present the main thread of the program. You can look at different threads of the program by pressing the greater than and less than keys, < and > . In most terminals you can also click the "Previous Thread" and "Next Thread" buttons on the footer. API In addition to tracking Python processes from a CLI using memray run , it is also possible to programmatically enable tracking within a running Python program. ```py import memray with memray.Tracker("output_file.bin"): print("Allocations will be tracked until the with block ends") ``` For details, see the API documentation . License Memray is Apache-2.0 licensed, as found in the LICENSE file. Code of Conduct Code of Conduct This project has adopted a Code of Conduct. If you have any concerns about the Code, or behavior that you have experienced in the project, please contact us at opensource@bloomberg.net. Security Policy Security Policy If you believe you have identified a security vulnerability in this project, please send an email to the project team at opensource@bloomberg.net, detailing the suspected issue and any methods you've found to reproduce it. Please do NOT open an issue in the GitHub repository, as we'd prefer to keep vulnerability reports private until we've had an opportunity to review and address them. Contributing We welcome your contributions to help us improve and extend this project! Below you will find some basic steps required to be able to contribute to the project. If you have any questions about this process or any other aspect of contributing to a Bloomberg open source project, feel free to send an email to opensource@bloomberg.net and we'll get your questions answered as quickly as we can. Contribution Licensing Since this project is distributed under the terms of an open source license , contributions that you make are licensed under the same terms. In order for us to be able to accept your contributions, we will need explicit confirmation from you that you are able and willing to provide them under these terms, and the mechanism we use to do this is called a Developer's Certificate of Origin (DCO) . This is very similar to the process used by the Linux kernel, Samba, and many other major open source projects. To participate under these terms, all that you must do is include a line like the following as the last line of the commit message for each commit in your contribution: Signed-Off-By: Random J. Developer <random@developer.example.org> The simplest way to accomplish this is to add -s or --signoff to your git commit command. You must use your real name (sorry, no pseudonyms, and no anonymous contributions). Steps Create an Issue, select 'Feature Request', and explain the proposed change. Follow the guidelines in the issue template presented to you. Submit the Issue. Submit a Pull Request and link it to the Issue by including "# " in the Pull Request summary.

Memray is a memory profiler for Python

memory,memory-leak,memory-leak-detection,memory-profiler,profiler,python,python3,hacktoberfest

neonbjb/tortoise-tts

TorToiSe Tortoise is a text-to-speech program built with the following priorities: Strong multi-voice capabilities. Highly realistic prosody and intonation. This repo contains all the code needed to run Tortoise TTS in inference mode. Manuscript: https://arxiv.org/abs/2305.07243 Hugging Face space A live demo is hosted on Hugging Face Spaces. If you'd like to avoid a queue, please duplicate the Space and add a GPU. Please note that CPU-only spaces do not work for this demo. https://huggingface.co/spaces/Manmay/tortoise-tts Install via pip bash pip install tortoise-tts If you would like to install the latest development version, you can also install it directly from the git repository: bash pip install git+https://github.com/neonbjb/tortoise-tts What's in a name? I'm naming my speech-related repos after Mojave desert flora and fauna. Tortoise is a bit tongue in cheek: this model is insanely slow. It leverages both an autoregressive decoder and a diffusion decoder; both known for their low sampling rates. On a K80, expect to generate a medium sized sentence every 2 minutes. well..... not so slow anymore now we can get a 0.25-0.3 RTF on 4GB vram and with streaming we can get < 500 ms latency !!! Demos See this page for a large list of example outputs. A cool application of Tortoise + GPT-3 (not affiliated with this repository): https://twitter.com/lexman_ai. Unfortunately, this project seems no longer to be active. Usage guide Local installation If you want to use this on your own computer, you must have an NVIDIA GPU. On Windows, I highly recommend using the Conda installation method. I have been told that if you do not do this, you will spend a lot of time chasing dependency problems. First, install miniconda: https://docs.conda.io/en/latest/miniconda.html Then run the following commands, using anaconda prompt as the terminal (or any other terminal configured to work with conda) This will: 1. create conda environment with minimal dependencies specified 1. activate the environment 1. install pytorch with the command provided here: https://pytorch.org/get-started/locally/ 1. clone tortoise-tts 1. change the current directory to tortoise-tts 1. run tortoise python setup install script shell conda create --name tortoise python=3.9 numba inflect conda activate tortoise conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia conda install transformers=4.29.2 git clone https://github.com/neonbjb/tortoise-tts.git cd tortoise-tts python setup.py install Optionally, pytorch can be installed in the base environment, so that other conda environments can use it too. To do this, simply send the conda install pytorch... line before activating the tortoise environment. Note: When you want to use tortoise-tts, you will always have to ensure the tortoise conda environment is activated. If you are on windows, you may also need to install pysoundfile: conda install -c conda-forge pysoundfile Docker An easy way to hit the ground running and a good jumping off point depending on your use case. ```sh git clone https://github.com/neonbjb/tortoise-tts.git cd tortoise-tts docker build . -t tts docker run --gpus all \ -e TORTOISE_MODELS_DIR=/models \ -v /mnt/user/data/tortoise_tts/models:/models \ -v /mnt/user/data/tortoise_tts/results:/results \ -v /mnt/user/data/.cache/huggingface:/root/.cache/huggingface \ -v /root:/work \ -it tts ``` This gives you an interactive terminal in an environment that's ready to do some tts. Now you can explore the different interfaces that tortoise exposes for tts. For example: sh cd app conda activate tortoise time python tortoise/do_tts.py \ --output_path /results \ --preset ultra_fast \ --voice geralt \ --text "Time flies like an arrow; fruit flies like a bananna." Apple Silicon On macOS 13+ with M1/M2 chips you need to install the nighly version of PyTorch, as stated in the official page you can do: shell pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu Be sure to do that after you activate the environment. If you don't use conda the commands would look like this: shell python3.10 -m venv .venv source .venv/bin/activate pip install numba inflect psutil pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cpu pip install transformers git clone https://github.com/neonbjb/tortoise-tts.git cd tortoise-tts pip install . Be aware that DeepSpeed is disabled on Apple Silicon since it does not work. The flag --use_deepspeed is ignored. You may need to prepend PYTORCH_ENABLE_MPS_FALLBACK=1 to the commands below to make them work since MPS does not support all the operations in Pytorch. do_tts.py This script allows you to speak a single phrase with one or more voices. shell python tortoise/do_tts.py --text "I'm going to speak this" --voice random --preset fast faster inference read.py This script provides tools for reading large amounts of text. shell python tortoise/read_fast.py --textfile <your text to be read> --voice random read.py This script provides tools for reading large amounts of text. shell python tortoise/read.py --textfile <your text to be read> --voice random This will break up the textfile into sentences, and then convert them to speech one at a time. It will output a series of spoken clips as they are generated. Once all the clips are generated, it will combine them into a single file and output that as well. Sometimes Tortoise screws up an output. You can re-generate any bad clips by re-running read.py with the --regenerate argument. API Tortoise can be used programmatically, like so: python reference_clips = [utils.audio.load_audio(p, 22050) for p in clips_paths] tts = api.TextToSpeech() pcm_audio = tts.tts_with_preset("your text here", voice_samples=reference_clips, preset='fast') To use deepspeed: python reference_clips = [utils.audio.load_audio(p, 22050) for p in clips_paths] tts = api.TextToSpeech(use_deepspeed=True) pcm_audio = tts.tts_with_preset("your text here", voice_samples=reference_clips, preset='fast') To use kv cache: python reference_clips = [utils.audio.load_audio(p, 22050) for p in clips_paths] tts = api.TextToSpeech(kv_cache=True) pcm_audio = tts.tts_with_preset("your text here", voice_samples=reference_clips, preset='fast') To run model in float16: python reference_clips = [utils.audio.load_audio(p, 22050) for p in clips_paths] tts = api.TextToSpeech(half=True) pcm_audio = tts.tts_with_preset("your text here", voice_samples=reference_clips, preset='fast') for Faster runs use all three: python reference_clips = [utils.audio.load_audio(p, 22050) for p in clips_paths] tts = api.TextToSpeech(use_deepspeed=True, kv_cache=True, half=True) pcm_audio = tts.tts_with_preset("your text here", voice_samples=reference_clips, preset='fast') Acknowledgements This project has garnered more praise than I expected. I am standing on the shoulders of giants, though, and I want to credit a few of the amazing folks in the community that have helped make this happen: Hugging Face, who wrote the GPT model and the generate API used by Tortoise, and who hosts the model weights. Ramesh et al who authored the DALLE paper, which is the inspiration behind Tortoise. Nichol and Dhariwal who authored the (revision of) the code that drives the diffusion model. Jang et al who developed and open-sourced univnet, the vocoder this repo uses. Kim and Jung who implemented univnet pytorch model. lucidrains who writes awesome open source pytorch models, many of which are used here. Patrick von Platen whose guides on setting up wav2vec were invaluable to building my dataset. Notice Tortoise was built entirely by the author (James Betker) using their own hardware. Their employer was not involved in any facet of Tortoise's development. License Tortoise TTS is licensed under the Apache 2.0 license. If you use this repo or the ideas therein for your research, please cite it! A bibtex entree can be found in the right pane on GitHub.

A multi-voice TTS system trained with an emphasis on quality

[]

AstroNvim/AstroNvim

AstroNvim Install · Configure · Community Plugins · Website · Discord AstroNvim is an aesthetically pleasing and feature-rich neovim config that is extensible and easy to use with a great set of plugins 🌟 Preview ✨ Features Common plugin specifications with AstroCommunity File explorer with Neo-tree Autocompletion with Cmp Git integration with Gitsigns Statusline, Winbar, and Bufferline with Heirline Terminal with Toggleterm Fuzzy finding with Telescope Syntax highlighting with Treesitter Formatting and Linting with None-ls Language Server Protocol with Native LSP Debug Adapter Protocol with nvim-dap ⚡ Requirements Nerd Fonts ( Optional with manual intervention: See Documentation on customizing icons ) [1] Neovim 0.9.5+ ( Not including nightly) Tree-sitter CLI ( Note: This is only necessary if you want to use auto_install feature with Treesitter) A clipboard tool is necessary for the integration with the system clipboard (see :help clipboard-tool for supported solutions) Terminal with true color support (for the default theme, otherwise it is dependent on the theme you are using) [2] Optional Requirements: ripgrep - live grep telescope search ( <leader>fw ) lazygit - git ui toggle terminal ( <leader>tl or <leader>gg ) go DiskUsage() - disk usage toggle terminal ( <leader>tu ) bottom - process viewer toggle terminal ( <leader>tt ) Python - python repl toggle terminal ( <leader>tp ) Node - node repl toggle terminal ( <leader>tn ) [!NOTE] [1] All downloadable Nerd Fonts contain icons which are used by AstroNvim. Install the Nerd Font of your choice to your system and in your terminal emulator settings, set its font face to that Nerd Font. If you are using AstroNvim on a remote system via SSH, you do not need to install the font on the remote system. [!NOTE] [2] Note when using default theme: For MacOS, the default terminal does not have true color support. You will need to use iTerm2 , Kitty , WezTerm , or another terminal emulator that has true color support. 🛠️ Installation AstroNvim is provided as a plugin that can be installed with the lazy.nvim plugin manager and then used to import all of the plugin configurations that AstroNvim provides. To quickly get started it is recommended to start with the official AstroNvim Template which provides a great starting point for a new AstroNvim based configuration. Linux/Mac OS (Unix) Make a backup of your current nvim and shared folder shell mv ~/.config/nvim ~/.config/nvim.bak mv ~/.local/share/nvim ~/.local/share/nvim.bak mv ~/.local/state/nvim ~/.local/state/nvim.bak mv ~/.cache/nvim ~/.cache/nvim.bak Clone the template repository shell git clone --depth 1 https://github.com/AstroNvim/template ~/.config/nvim rm -rf ~/.config/nvim/.git nvim Windows (Powershell) Make a backup of your current nvim and nvim-data folder pwsh Rename-Item -Path $env:LOCALAPPDATA\nvim -NewName $env:LOCALAPPDATA\nvim.bak Rename-Item -Path $env:LOCALAPPDATA\nvim-data -NewName $env:LOCALAPPDATA\nvim-data.bak Clone the repository pwsh git clone --depth 1 https://github.com/AstroNvim/template $env:LOCALAPPDATA\nvim Remove-Item $env:LOCALAPPDATA\nvim\.git -Recurse -Force nvim Minimal ~/.config/nvim/init.lua Some user's might not want to use an entire template or do any customization. Here is a minimal ~/.config/nvim/init.lua file that simply set's up a base AstroNvim installation: ```lua local lazypath = vim.fn.stdpath "data" .. "/lazy/lazy.nvim" if not (vim.uv or vim.loop).fs_stat(lazypath) then -- stylua: ignore vim.fn.system({ "git", "clone", "--filter=blob:none", "https://github.com/folke/lazy.nvim.git", "--branch=stable", lazypath }) end vim.opt.rtp:prepend(lazypath) require("lazy").setup { "AstroNvim/AstroNvim", version = "^4", import = "astronvim.plugins" } ``` 📦 Basic Setup Install LSP Enter :LspInstall followed by the name of the server you want to install Example: :LspInstall pyright Install language parser Enter :TSInstall followed by the name of the language you want to install Example: :TSInstall python Install Debugger Enter :DapInstall followed by the name of the debugger you want to install Example: :DapInstall python Manage plugins Run :Lazy check to check for plugin updates Run :Lazy update to apply any pending plugin updates Run :Lazy clean to remove any disabled or unused plugins Run :Lazy sync to update and clean plugins Update AstroNvim Packages Run :AstroUpdate ( <leader>pa ) to update both Neovim plugins and Mason packages 🗒️ Links AstroNvim Website AstroNvim Documentation Setup is given for basic editor setup after installation Default Mappings more about the default key bindings Customizing Plugins more about configuring and adding plugins 📹 Videos There have been some great review videos released by members of the community! Here are a few: Neovim With AstroNvim | Your New Advanced Development Editor (Version: 3, Content By: @Cretezy ) Why I'm quitting VIM by Carlos Mafla (Version: 2, Content By: @gigo6000 ) Astro Vim - All in one Nvim config!! by John McBride (Version: 1, Content By: @jpmcb ) 🚀 Contributing If you plan to contribute, please check the contribution guidelines first. ⭐ Credits Sincere appreciation to the following repositories, plugin authors and the entire neovim community out there that made the development of AstroNvim possible. Plugins NvChad LunarVim CosmicVim [](https://lua.org)

AstroNvim is an aesthetic and feature-rich neovim config that is extensible and easy to use with a great set of plugins

vim,lua,neovim,ide,nvim,neovim-configuration,neovim-config,neovim-lua,neovim-setup,astrovim

faker-js/faker

Faker Generate massive amounts of fake (but realistic) data for testing and development. [](https://www.npmjs.com/package/@faker-js/faker) [](https://www.npmjs.com/package/@faker-js/faker) [](https://github.com/faker-js/faker/actions/workflows/ci.yml) [](https://codecov.io/gh/faker-js/faker) [](https://chat.fakerjs.dev) [](https://opencollective.com/fakerjs#section-contributors) [](https://opencollective.com/fakerjs) ⚡️ Try it Online Open in StackBlitz 📙 API Documentation ⚠️ You are reading the docs for the next branch ⚠️ Please proceed to the Getting Started Guide for the stable release of Faker. For detailed API documentation, please select the version of the documentation you are looking for. | Version | Website | | :---------: | :------------------------ | | v9 (next) | https://next.fakerjs.dev/ | | v8 (stable) | https://fakerjs.dev/ | | v7 (old) | https://v7.fakerjs.dev/ | 🚀 Features 💌 Locations - Generate valid looking Addresses, Zip Codes, Street Names, States, and Countries! ⏰ Time-based Data - Past, present, future, recent, soon... whenever! 🌏 Localization - Pick a locale to generate realistic looking Names, Addresses, and Phone Numbers. 💸 Finance - Create stubbed out Account Details, Transactions, and Crypto Addresses. 👠 Products - Generate Prices, Product Names, Adjectives, and Descriptions. 👾 Hacker Jargon - “Try to reboot the SQL bus, maybe it will bypass the virtual application!” 🧍 Names - Generate virtual humans with a complete online and offline identity. 🔢 Numbers - Of course, we can also generate random numbers and strings. Note : Faker tries to generate realistic data and not obvious fake data. The generated names, addresses, emails, phone numbers, and/or other data might be coincidentally valid information. Please do not send any of your messages/calls to them from your test setup. 📦 Install bash npm install --save-dev @faker-js/faker 🪄 Usage ```ts // ESM import { faker } from '@faker-js/faker'; // CJS const { faker } = require('@faker-js/faker'); export function createRandomUser() { return { userId: faker.string.uuid(), username: faker.internet.userName(), email: faker.internet.email(), avatar: faker.image.avatar(), password: faker.internet.password(), birthdate: faker.date.birthdate(), registeredAt: faker.date.past(), }; } export const users = faker.helpers.multiple(createRandomUser, { count: 5, }); ``` 💎 Modules An in-depth overview of the API methods is available in the documentation for v8 (stable) and v9.* (next) . Templates Faker contains a generator method faker.helpers.fake for combining faker API methods using a mustache string format. ts console.log( faker.helpers.fake( 'Hello {{person.prefix}} {{person.lastName}}, how are you today?' ) ); 🌏 Localization Faker has support for multiple locales. The main faker instance uses the English locale. But you can also import instances using other locales. ```ts // ESM import { fakerDE as faker } from '@faker-js/faker'; // CJS const { fakerDE: faker } = require('@faker-js/faker'); ``` See our documentation for a list of provided languages . Please note: Not every locale provides data for every module. In our pre-made faker instances, we fall back to English in such a case as this is the most complete and most commonly used language. If you don't want that or prefer a different fallback, you can also build your own instances. ```ts import { de, de_CH, Faker } from '@faker-js/faker'; export const faker = new Faker({ locale: [de_CH, de], }); ``` ⚙️ Setting a randomness seed If you want consistent results, you can set your own seed: ```ts faker.seed(123); const firstRandom = faker.number.int(); // Setting the seed again resets the sequence. faker.seed(123); const secondRandom = faker.number.int(); console.log(firstRandom === secondRandom); ``` 🤝 Sponsors Faker is an MIT-licensed open source project with its ongoing development made possible entirely by the support of these awesome backers Sponsors Backers ✨ Contributing Please make sure to read the Contributing Guide before making a pull request. 📘 Credits Thanks to all the people who already contributed to Faker! The fakerjs.dev website is kindly hosted by the Netlify Team. Also the search functionality is powered by algolia . 📝 Changelog Detailed changes for each release are documented in the release notes . 📜 What happened to the original faker.js? Read the team update (January 14th, 2022). 🔑 License MIT

Generate massive amounts of fake data in the browser and node.js

faker,data,fake,nodejs,browser,javascript

smartcontractkit/full-blockchain-solidity-course-js

Update: Head to Cyfrin Updraft ℹ️ Important: This repo is no longer actively maintained as there have been changes in Hardhat tooling. The video is out of sync with the code, and you can still follow along with the video, but you will likely need to troubleshoot the changes in the tooling and dependencies. Note also that best practices have evolved since this video was made. If you'd like to continue your training with more up-to-date material, you can take a look at Cyfrin Updraft . That content is developed with love by Patrick & Cyfrin <3. However note that Cyfrin Updraft training uses Foundry, not Hardhat, so there will be tooling changes involved. Web3, Full Stack Solidity, Smart Contract & Blockchain - Beginner to Expert ULTIMATE Course | Javascript Edition Welcome to the repository for the Ultimate Web3, Full Stack Solidity, and Smart Contract - Beginner to Expert Full Course | Javascript Edition FreeCodeCamp Course! Link to video: https://www.youtube.com/watch?v=gyMwXuJrbJQ All code references have both a javascript and a typescript edition. Recommended Testnet: Sepolia We have updated the repos to work with Sepolia due to Rinkeby and Kovan being sunset, and Goerli being a disaster. Let us know if any of the changes break stuff! Testnet Faucets Main Faucet: https://faucets.chain.link Backup Faucet: https://sepoliafaucet.com/ ⚠️ All code associated with this course is for demo purposes only. They have not been audited and should not be considered production ready. Please use at your own risk. Resources For This Course Questions Github Discussions Ask questions and chat about the course here! Stack Exchange Ethereum Great place for asking technical questions about Ethereum StackOverflow Great place for asking technical questions overall Table of Contents Resources Testnet Faucets Resources For This Course Questions Table of Contents Lesson 0: The Edge of the Rabbit Hole Welcome to the course! Best Practices Lesson 1: Blockchain Basics What is a Blockchain? What does a blockchain do? The Purpose Of Smart Contracts Other Blockchain Benefits What have Smart Contracts done so far? Making Your First Transaction Gas I: Introduction to Gas How Do Blockchains Work? Signing Transactions Gas II High-Level Blockchain Fundamentals Lesson 2: Welcome to Remix! Simple Storage Introduction Setting Up Your First Contract Basic Solidity: Types Basic Solidity: Functions Basic Solidity: Arrays & Structs Basic Solidity: Compiler Errors and Warnings Memory, Storage, Calldata (Intro) Mappings Deploying your First Contract The EVM & A Recap of Lesson 2 Lesson 3: Remix Storage Factory Introduction Basic Solidity: Importing Contracts into other Contracts Basic Solidity: Interacting with other Contracts Basic Solidity: Inheritance & Overrides Lesson 3 Recap Lesson 4: Remix Fund Me Introduction Sending ETH Through a Function & Reverts Chainlink & Oracles Review of Sending ETH and working with Chainlink Interfaces & Price Feeds Importing from GitHub & NPM Floating Point Math in Solidity Basic Solidity: Arrays & Structs II Review of Interfacs, Importing from GitHub, & Math in Solidity Libraries SafeMath, Overflow Checking, and the "unchecked" keywork Basic Solidity: For Loop Basic Solidity: Resetting an Array Sending ETH from a Contract Basic Solidity: Constructor Basic Solidity: Modifiers Testnet Demo Advanced Solidity Immutable & Constant Custom Errors Receive & Fallback Functions Lesson 4 Recap Lesson 5: Ethers.js Simple Storage Effective Debugging Strategies & Getting Help How to Debug Anything Video Installation & Setup Mac & Linux Setup Windows Setup Gitpod Local Development Introduction Optional Javascript Crash Courses Tiny Javascript Refresher Asynchronous Programming in Javascript Compiling our Solidity Ganache & Networks Introduction to Ethers.js A Note on the await Keyword Adding Transaction Overrides Transaction Receipts Sending a "raw" Transaction in Ethersjs Interacting with Contracts in Ethersjs Environment Variables Better Private Key Management Optional Prettier Formatting Deploying to a Testnet or a Mainnet Verifying on Block Explorers from the UI Alchemy Dashboard & The Mempool Lesson 5 Recap Typescript Ethers Simple Storage Lesson 6: Hardhat Simple Storage Introduction Hardhat Setup Troubleshooting Hardaht Setup Hardhat Setup Continued Deploying SimpleStorage from Hardhat Networks in Hardhat Programatic Verification Interacting with Contracts in Hardhat Artifacts Troubleshooting Custom Hardhat Tasks Hardhat Localhost Node The Hardhat Console Hardhat Tests Hardhat Gas Reporter Solidity Coverage Hardhat Waffle Lesson 6 Recap Typescript Hardhat Simple Storage Lesson 7: Hardhat Fund Me Introduction Hardhat Setup - Fund Me Linting Hardhat Setup - Fund Me - Continued Importing from NPM Hardhat Deploy Mocking Utils Folder Testnet Demo - Hardhat Fund Me Solidity Style Guide Testing Fund Me Breakpoints & Debugging Gas III: console.log & Debugging Testing Fund Me II Storage in Solidity Gas Optimizations using Storage Knowledge Solidity Chainlink Style Guide Storage Review Staging Tests Running Scripts on a Local Node Adding Scripts to your package.json Pushing to GitHub 🐸🐦 Tweet Me (add your repo in)! Lesson 8: HTML / Javascript Fund Me (Full Stack / Front End) Introduction How Websites work with Web3 Wallets HTML Setup Connecting HTML to Metamask Javascript in it's own file ES6 vs Nodejs Sending a transaction from a Website Resetting an Account in Metamask Listening for Events and Completed Transactions Input Forms Reading from the Blockchain Withdraw Function Lesson 8 Recap Optional Links Lesson 9: Hardhat Smart Contract Lottery Introduction Hardhat Setup - Smart Contract Lottery Raffle.sol Setup Introduction to Events Events in Raffle.sol Introduction to Chainlink VRF Sub-Lesson: Chainlink VRF Implementing Chainlink VRF - Introduction Hardhat Shorthand Implementing Chainlink VRF - The Request Implementing Chainlink VRF - The FulFill Modulo Introduction to Chainlink Keepers Implementing Chainlink Keepers - checkUpkeep Enums Implementing Chainlink Keepers - checkUpkeep continued Implementing Chainlink Keepers - performUpkeep Code Cleanup Deploying Raffle.sol Mock Chainlink VRF Coordinator Continued Raffle.sol Unit Tests Testing Events & Chai Matchers Continued I Hardhat Methods & Time Travel Continued II Callstatic Continued III Massive Promise Test Continued IV Raffle.sol Staging Tests Testing on a Testnet Recommended LINK amounts for Sepolia Staging Test: Conclusion Typescript - Smart Contract Lottery Lesson 10: NextJS Smart Contract Lottery (Full Stack / Front End) Introduction Optional Sub-Lesson: Full Stack Development & Other Libraries NextJS Setup Manual Header I React Hooks Manual Header II useEffect Hook Local Storage isWeb3EnabledLoading web3uikit Introduction to Calling Functions in Nextjs Automatic Constant Value UI Updater runContractFunction useState Calling Functions in NextJS useNotification Reading & Displaying Contract Data A Note about onSuccess A Challenge to You Tailwind & Styling Introduction to Hosting your Site IPFS Hosting on IPFS Hosting on IPFS & Filecoin using Fleek Filecoin Overview Lesson 10 Recap Lesson 11: Hardhat Starter Kit Lesson 12: Hardhat ERC20s What is an ERC? What is an EIP? What is an ERC20? Manually Creating an ERC20 Token Creating an ERC20 Token with Openzeppelin Lesson 12 Recap Lesson 13: Hardhat DeFi & Aave What is DeFi? What is Aave? Programatic Borrowing & Lending WETH - Wrapped ETH Forking Mainnet Depositing into Aave Borrowing from Aave Repaying with Aave Visualizing the Transactions Lesson 13 Recap Happy Bow-Tie Friday with Austin Griffith More DeFi Learnings: Lesson 14: Hardhat NFTs (EVERYTHING you need to know about NFTs) What is an NFT? Code Overview Hardhat Setup Basic NFT Write Tests Random IPFS NFT Mapping Chainlink VRF Requests Creating Rare NFTs Setting the NFT Image Setting an NFT Mint Price Deploy Script Uploading Token Images with Pinata Uploading Token URIs (metadata) with Pinata Deploying Tests Dynamic SVG On-Chain NFT What is an SVG? Initial Code Base64 Encoding Advanced: EVM Opcodes, Encoding, and Calling abi.encode & abi.encodePacked Introduction to Encoding Function Calls Directly Introduction to Encoding Function Calls Recap Encoding Function Calls Directly Creating an NFT TokenURI on-Chain Making the NFT Dynamic Deploy Script Deploying the NFTs to a Testnet Lesson 14 Recap Lesson 15: NextJS NFT Marketplace (If you finish this lesson, you are a full-stack MONSTER!) Introduction Part I: NFT Marketplace Contracts Hardhat Setup NftMarketplace.sol Reentrancy NftMarketplace.sol - Continued NftMarketplace.sol - Deploy Script NftMarketplace.sol - Tests NftMarketplace.sol - Scripts Part II: Moralis Front End What is Moralis? NextJS Setup Adding Tailwind Introduction to Indexing in Web3 Connecting Moralis to our Local Hardhat Node Moralis Event Sync Reset Local Chain Moralis Cloud Functions Practice Resetting the Local Chain Moralis Cloud Functions II Querying the Moralis Database Rendering the NFT Images Update Listing Modal Buy NFT Listing Listing NFTs for Sale Part III: TheGraph Front End Introduction What is The Graph? Building a Subgraph Deploying our Subgraph Reading from The Graph Hosting our Dapp Lesson 16: Hardhat Upgrades Upgradeable Smart Contracts Overview Types of Upgrades Delegatecall Small Proxy Example Transparent Upgradeable Smart Contract Lesson 17: Hardhat DAOs Introduction What is a DAO? How to build a DAO Lesson 18: Security & Auditing Introduction Slither Fuzzing and Eth Security Toolbox Closing Thoughts More Resources Congratulations Where do I go now? Learning More Community Hackathons Lesson 0: The Edge of the Rabbit Hole Welcome to the course! ⌨️ (00:00:00) Lesson 0: Welcome To Blockchain Best Practices Follow the repository: While going through the course be 100% certain to follow along with the github repository. If you run into in an issue check the chronological-updates in the repo. Be Active in the community: Ask questions and engage with other developers going through the course in the discussions tab, be sure to go and say hello or gm! This space is different from the other industries, you don't have to be secretive; communicate, network and learn with others :) Learn at your own pace: It doesn't matter if it takes you a day, a week, a month or even a year. Progress >>> Perfection Take Breaks: You will exhaust your mind and recall less if you go all out and watch the entire course in one sitting. Suggested Strategy every 25 minutes take a 5 min break, and every 2 hours take a longer 30 min break Refer to Documentation: Things are constantly being updated, so whenever Patrick opens up some documentation, open it your end and maybe even have the code sample next to you. Lesson 1: Blockchain Basics ⌨️ (00:09:05) Lesson 1: Blockchain Basics What is a Blockchain? What does a blockchain do? Bitcoin Whitepaper Satoshi Nakamoto Ethereum Whitepaper Vitalik Buterin What is a Smart Contract? Nick Szabo Hybrid Smart Contracts Blockchain Oracles Terminology Web3 What is a blockchain The Purpose Of Smart Contracts ⌨️ (00:18:27) The Purpose of Smart Contracts 🎥 Original Video 🦬 My ETH Denver Talk 🍔 McDonalds Scandal ⛓ More on the evolution of agreements ✍️ What is a Smart Contract? 🧱 How does a blockchain work? 🔮 Chainlink & Oracles Other Blockchain Benefits ⌨️ (00:30:41) Other Blockchain Benefits Decentralized Transparency & Flexibility Speed & Efficiency Security & Immutability Counterparty Risk Removal Trust Minimized Agreements What have Smart Contracts done so far? ⌨️ (00:36:36) What have Smart Contracts done so far? DeFi Defi Llama Why DeFi is Important DAOs NFTs Making Your First Transaction ⌨️ (00:39:17) Making Your First Transaction Metamask Download Link What is a Private Key? What is a Secret Phrase? Etherscan Sepolia Etherscan Sepolia Faucet (Check the link token contracts page ) NOTE: The Chainlink documentation always has the most up to date faucets on their link token contracts page . If the faucet above is broken, check the chainlink documentation for the most up to date faucet. OR, use the Sepolia ETH Faucet , just be sure to swap your metamask to Sepolia! Gas I: Introduction to Gas ⌨️ (00:58:59) Gas I: Introduction to Gas Gas and Gas Fees Wei, Gwei, and Ether Converter ETH Gas Station How Do Blockchains Work? ⌨️ (01:05:32) How Do Blockchains Work What is a hash? Blockchain Demo Summary Signing Transactions ⌨️ (01:22:55) Signing Transactions Public / Private Keys Layer 2 and Rollups Decentralized Blockchain Oracles Gas II ⌨️ (01:30:22) Gas II: Block Rewards & EIP 1559 Block Rewards Advanced Gas EIP 1559 GWEI, WEI, and ETH ETH Converter Gas II Summary ⌨️ (01:36:44) Gas II Summary Run Your Own Ethereum Node High-Level Blockchain Fundamentals [⌨️ (01:39:32) High-Level Blockchain Fundamentals]https://www.youtube.com/watch?v=gyMwXuJrbJQ&t=5972s() Consensus Proof of Stake Proof of Work Nakamoto Consensus Ethereum 2 (the merge) 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Completed Blockchain Basics! 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Lesson 2: Welcome to Remix! Simple Storage ⌨️ (02:01:16) Lesson 2: Welcome to Remix! Simple Storage 💻 Code: https://github.com/PatrickAlphaC/simple-storage-fcc Introduction ⌨️ (02:03:05) Introduction Remix Solidity Documentation Setting Up Your First Contract ⌨️ (02:05:18) Setting Up Your First Contract Versioning Take notes in your code! What is a software license SPDX License Compiling Contract Declaration Basic Solidity: Types ⌨️ (02:12:28) Basic Solidity Types Types & Declaring Variables uint256 , int256 , bool , string , address , bytes32 Solidity Types Bits and Bytes Default Initializations Comments Basic Solidity: Functions ⌨️ (02:18:40) Basic Solidity Functions Functions Deploying a Contract Smart Contracts have addresses just like our wallets Calling a public state-changing Function Visibility Gas III | An example Scope View & Pure Functions Basic Solidity: Arrays & Structs ⌨️ (02:35:30) Basic Solidity Arrays & Structs Structs Intro to Storage Arrays Dynamic & Fixed Sized push array function Basic Solidity: Compiler Errors and Warnings ⌨️ (02:45:35) Basic Solidity Errors & Warnings Yellow: Warnings are Ok Red: Errors are not Ok Memory, Storage, Calldata (Intro) ⌨️ (02:46:34) Basic Solidity Memory, Storage, & Calldata (Intro) 6 Places you can store and access data calldata memory storage code logs stack Mappings ⌨️ (02:50:17) Basic Solidity Mappings Mappings Deploying your First Contract ⌨️ (02:53:38) Deploying your First Contract A testnet or mainnet Connecting Metamask Find a faucet here See the faucets at the top of this readme! Interacting with Deployed Contracts The EVM & A Recap of Lesson 2 ⌨️ (03:03:07) The EVM & A Recap of Lesson 2 The EVM Lesson 3: Remix Storage Factory ⌨️ (03:05:34) Lesson 3: Remix Storage Factory 💻 Code: https://github.com/PatrickAlphaC/storage-factory-fcc Introduction ⌨️ (03:06:06) Introduction Factory Pattern Basic Solidity: Importing Contracts into other Contracts ⌨️ (03:07:29) Importing Contracts into other Contracts Composibility Solidity new keyword Importing Code in solidity Basic Solidity: Interacting with other Contracts ⌨️ (03:16:36) Interacting with other contracts To interact, you always need: ABI + Address ABI Basic Solidity: Inheritance & Overrides ⌨️ (03:25:23) Inheritance & Overrides Inheritance Override & Virtual Keyword Lesson 3 Recap ⌨️ (03:30:29) Lesson 3 Recap Lesson 4: Remix Fund Me ⌨️ (03:31:55) Lesson 4: Remix Fund Me 💻 Code: https://github.com/PatrickAlphaC/fund-me-fcc Introduction Sending ETH Through a Function & Reverts Fields in a Transaction More on v,r,s payable msg.value & Other global keywords require revert Chainlink & Oracles What is a blockchain oracle? What is the oracle problem? Chainlink Chainlink Price Feeds (Data Feeds) data.chain.link Chainlink VRF Chainlink Keepers Chainlink API Calls Importing Tokens into your Metamask Request and Receive Chainlink Model Review of Sending ETH and working with Chainlink Interfaces & Price Feeds Chainlink Price Feeds (Data Feeds) Chainlink GitHub Interface Importing from GitHub & NPM Chainlink NPM Package Floating Point Math in Solidity tuple Floating Point Numbers in Solidity Type Casting Gas Estimation Failed Someone should make an article explaining this error Basic Solidity: Arrays & Structs II msg.sender Review of Interfaces, Importing from GitHub, & Math in Solidity Libraries Library Solidity-by-example Library SafeMath, Overflow Checking, and the "unchecked" keyword Openzeppelin Safemath unchecked vs. checked Basic Solidity: For Loop For Loop /* */ is another way to make comments Basic Solidity: Resetting an Array Sending ETH from a Contract Transfer, Send, Call this keyword Basic Solidity: Constructor Constructor Basic Solidity: Modifiers Double equals Modifier Testnet Demo Disconnecting Metamask Advanced Solidity Immutable & Constant Immutable Constant Current ETH Gas Prices Don't stress about gas optimizations! (yet) Naming Conventions Someone make this! Custom Errors Custom Errors Introduction Receive & Fallback Functions Solidity Docs Special Functions Fallback Receive Lesson 4 Recap 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Completed Solidity Basics! 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Lesson 5: Ethers.js Simple Storage ⌨️ (05:30:42) Lesson 5: Ethers.js Simple Storage 💻 Code: https://github.com/PatrickAlphaC/ethers-simple-storage-fcc 🧪 Alchemy: https://alchemy.com/?a=673c802981 Effective Debugging Strategies & Getting Help ⌨️ (5:30:46) Effective Debugging Stategies & Getting Help Tinker and isolate problem For this course, take at LEAST 15 minutes to figure out a bug. Google / Web Search the Exact problem Go to this GitHub Repo / Discussions Ask a question on a Forum like Stack Exchange Ethereum or Stack Overflow Format your questions!! Use Markdown How to Debug Anything Video Patrick's Original Video Installation & Setup Visual Studio Code Crash Course NodeJS VSCode Keybindings Git What is a terminal? Mac & Linux Setup Windows Setup WSL When working in WSL, use Linux commands instead of Windows commands TroubleShooting curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.1/install.sh | bash ⚠️ Please use Gitpod as an absolute last resort Gitpod Gitpod If using this, NEVER share a private key with real money on Gitpod Ideally you figure out the MacOS, Linux, or Windows install though Local Development Introduction CMD + K or CTRL + K clears the terminal mkdir ethers-simple-storage-fcc code . to open VSCode in a new VSCode window Optional Javascript Crash Courses NodeJS Course Javascript Course Import your SimpleStorage.sol Solidity + Hardhat VSCode Extension Format your solidity code with: "[solidity]": { "editor.defaultFormatter": "NomicFoundation.hardhat-solidity" }, "[javascript]":{ "editor.defaultFormatter": "esbenp.prettier-vscode" } In your .vscode/settings.json file. Prettier Extension Tiny Javascript Refresher Javascript Tips Asynchronous Programming in Javascript Asynchronous Programming async keyword Promise in Javascript await keyword Compiling our Solidity Yarn Install solc-js yarn add solc@0.8.7-fixed yarn scripts Ganache & Networks Ganache Networks in Metamask RPC URL Geth JSON RPC Spec Playground Introduction to Ethers.js Ethers.js prettier-plugin-solidity A Note on the await Keyword Adding Transaction Overrides Transaction Receipts Sending a "raw" Transaction in Ethers.js Interacting with Contracts in Ethers.js EVM Decompiler BigNumber Environment Variables dotenv .gitignore Better Private Key Management wallet.encrypt THE .ENV PLEDGE Optional Prettier Formatting Prettier Best README Template Deploying to a Testnet or a Mainnet Alchemy Getting your private key from Metamask CTRL + C stops any terminal command Verifying on Block Explorers from the UI Alchemy Dashboard & The Mempool Special Guest Albert Hu Mempool Lesson 5 Recap Typescript Ethers Simple Storage Lesson 6: Hardhat Simple Storage ⌨️ (08:20:17) Lesson 6: Hardhat Simple Storage 💻 Code: https://github.com/PatrickAlphaC/hardhat-simple-storage-fcc Introduction ⌨️ (08:20:19) Introduction Hardhat Setup ⌨️ (08:22:47) Hardhat Setup Hardhat Documentation DevDependencies vs Dependencies @ Sign node modules Troubleshooting Hardhat Setup ⌨️ (08:29:43) Troubleshooting Hardhat Setup Special Guest Cami Ramos Garzon Hardhat Setup Continued ⌨️ (08:31:48) Hardhat Setup Continued Deploying SimpleStorage from Hardhat ⌨️ (08:33:10) Deploying SimpleStorage from Hardhat Networks in Hardhat ⌨️ (08:41:44) Networks in Hardhat The Hardhat Network Hardhat configuration Chain ID List Programmatic Verification ⌨️ (08:51:16) Programmatic Verification Etherscan Verify Tutorial Etherscan Docs Hardhat-Etherscan Etherscan API Keys Javascript == vs === Interacting with Contracts in Hardhat ⌨️ (09:06:37) Interacting with Contracts in Hardhat Artifacts Troubleshooting ⌨️ (09:09:42) Artifacts Troubleshooting Custom Hardhat Tasks ⌨️ (09:10:52) Custom Hardhat Tasks Hardhat Tasks Javascript Arrow Functions Hardhat Localhost Node ⌨️ (09:18:12) Hardhat Localhost Node The Hardhat Console ⌨️ (09:23:11) The Hardhat Console Hardhat Console Hardhat Tests ⌨️ (09:26:13) Hardhat Tests Hardhat Tests Mocha Style Tests Chai Waffle Tests Hardhat Gas Reporter ⌨️ (09:38:10) Hardhat Gas Reporter Hardhat Gas Reporter Coinmarketcap API Solidity Coverage ⌨️ (09:44:40) Solidity Coverage Solidity Coverage Hardhat Waffle ⌨️ (09:47:02) Hardhat Waffle Hardhat-Waffle Lesson 6 Recap ⌨️ (09:47:37) Lesson 6 Recap Typescript Hardhat Simple Storage ⌨️ (09:52:15) Typescript Hardhat Simple Storage Typechain yarn add --dev @typechain/ethers-v5 @typechain/hardhat @types/chai @types/node @types/mocha ts-node typechain typescript Lesson 7: Hardhat Fund Me ⌨️ (10:00:48) Lesson 7: Hardhat Fund Me 💻 Code: https://github.com/PatrickAlphaC/hardhat-fund-me-fcc Introduction ⌨️ (10:00:50) Introduction Hardhat Setup - Fund Me ⌨️ (10:03:41) Hardhat Setup - Fund Me Linting ⌨️ (10:06:20) Linting Eslint Solhint Linting Code Hardhat Setup - Fund Me - Continued ⌨️ (10:07:47) Hardhat Setup - Fund Me - Continued Importing from NPM ⌨️ (10:09:38) Importing from NPM @chainlink/contracts Hardhat Deploy ⌨️ (10:10:43) Hardhat Deploy Hardhat Deploy Mocking ⌨️ (10:21:05) Mocking Mocking Aave Github Chainlink Github Multiple Versions of Solidity Tags in hardhat Utils Folder ⌨️ (10:52:51) Utils Folder Testnet Demo - Hardhat Fund Me ⌨️ (10:55:45) Testnet Demo - Hardhat Fund Me Hardhat Deploy Block Confirmations TypeScript Code file (TypeScript edition) Define blockConfirmations in the helper-hardhat-config.ts file instead of hardhat-config.js . Solidity Style Guide ⌨️ (11:00:10) Solidity Style Guide Style Guide NatSpec Testing Fund Me ⌨️ (11:08:36) Testing Fund Me Unit Testing Hardhat Deploy Fixtures ethers.getContract expect ethers.utils.parseUnits Waffle Chai Matchers Breakpoints & Debugging ⌨️ (11:30:39) Breakpoints & Debugging VSCode Breakpoints Gas III ⌨️ (11:33:40) Gas III Transaction Response Transaction Receipt console.log & Debugging ⌨️ (11:36:35) console.log & Debugging Hardhat console.log Testing Fund Me II ⌨️ (11:37:31) Testing Fund Me II Storage in Solidity ⌨️ (11:44:34) Storage in Solidity Storage Layout Purpose of the memory keyword getStorageAt Gas Optimizations using Storage Knowledge ⌨️ (11:52:38) Gas Optimizations using Storage Knowledge Opcodes Opcodes by Gas Opcodes by Gas Append s_ to storage variables Append i_ to immutable variables Caps lock and underscore constant variables Solidity Chainlink Style Guide ⌨️ (12:05:29) Solidity Chainlink Style Guide Chainlink Solidity Style Guide Storage Review ⌨️ (12:09:59) Storage Review Staging Tests ⌨️ (12:11:43) Staging Tests Ternary Running Scripts on a Local Node ⌨️ (12:17:58) Running Scripts on a Local Node Adding Scripts to your package.json ⌨️ (12:22:00) Adding Scripts to your package.json Pushing to GitHub ⌨️ (12:25:17) Pushing to GitHub Github Quickstart What is Git? The quickstart that we follow in the video Learn about git and GitHub 🐸🐦 Tweet Me (add your repo in)! Lesson 8: HTML / Javascript Fund Me (Full Stack / Front End) ⌨️ (12:32:57) Lesson 8: HTML / Javascript Fund Me (Full Stack / Front End) 💻 Code: https://github.com/PatrickAlphaC/html-fund-me-fcc Introduction How Websites work with Web3 Wallets How to Connect your Smart Contracts to Metamask 💻 Code from Video: https://github.com/PatrickAlphaC/full-stack-web3-metamask-connectors ✍️ Article from Video: https://betterprogramming.pub/everything-you-need-to-know-about-fullstack-web3-94c0f1b18019?sk=a2764bcbdae98bf05e1052931de77982 HTML Setup Live Server: ExtensionID: ritwickdey.LiveServer Connecting HTML to Metamask Metamask Docs Javascript in it's own file ES6 vs Nodejs ES6 vs Nodesjs Ethers docs for web browser module vs text/javascript Sending a transaction from a Website Web3Provider Adding a network to metamask Resetting an Account in Metamask MetaMask - RPC Error: [ethjs-query] while formatting ouputs from RPC '{"value":{"code":-32603,"data":{"code":-32000,"message":"Nonce too high. Expected nonce to be 2 but got 4. Note that transactions can't be queued when automining."}}}' Listening for Events and Completed Transactions provider.once Anonymous function Javascript Promise Input Forms Reading from the Blockchain Withdraw Function Lesson 8 Recap Optional Links: Browserify Watchify Lesson 9: Hardhat Smart Contract Lottery ⌨️ (13:41:02) Lesson 9: Hardhat Smart Contract Lottery 💻 Code: https://github.com/PatrickAlphaC/hardhat-smartcontract-lottery-fcc Introduction Hardhat Setup - Smart Contract Lottery ⌨️ (13:43:43) Hardhat Setup Install dependencies: bash yarn add --dev @nomiclabs/hardhat-ethers@npm:hardhat-deploy-ethers ethers @nomiclabs/hardhat-etherscan @nomiclabs/hardhat-waffle chai ethereum-waffle hardhat hardhat-contract-sizer hardhat-deploy hardhat-gas-reporter prettier prettier-plugin-solidity solhint solidity-coverage dotenv Install dependencies (Typescript version): bash yarn add --dev @nomiclabs/hardhat-ethers@npm:hardhat-deploy-ethers ethers @nomiclabs/hardhat-etherscan @nomiclabs/hardhat-waffle chai ethereum-waffle hardhat hardhat-contract-sizer hardhat-deploy hardhat-gas-reporter prettier prettier-plugin-solidity solhint solidity-coverage dotenv @typechain/ethers-v5 @typechain/hardhat @types/chai @types/node ts-node typechain typescript Raffle.sol Setup ⌨️ (13:46:55) Raffle.sol Setup Custom Errors in Solidity Introduction to Events ⌨️ (13:54:02) Introduction to Events Events & Logging Video Events & Logging in Hardhat Events in Raffle.sol ⌨️ (14:00:47) Events in Raffle.sol Introduction to Chainlink VRF ⌨️ (14:02:30) Introduction to Chainlink VRF Special Guest Stephen Fluin Sub-Lesson: Chainlink VRF Chainlink VRFv2 Docs Chainlink VRFv2 Walkthrough Chainlink Contracts Implementing Chainlink VRF - Introduction ⌨️ (14:09:53) Implementing Chainlink VRF Hardhat Shorthand Hardhat Shorthand Implementing Chainlink VRF - The Request Implementing Chainlink VRF - The FulFill Modulo Modulo Introduction to Chainlink Keepers Chainlink Keepers Docs Chainlink Keepers Walkthrough Implementing Chainlink Keepers - checkUpkeep Enums Enum Implementing Chainlink Keepers - checkUpkeep continued block.timestamp Implementing Chainlink Keepers - performUpkeep Code Cleanup Deploying Raffle.sol Mock Chainlink VRF Coordinator Continued LINK Token Raffle.sol Unit Tests We use async function in the describe blocks at the start, but we correctly take them out later. Testing Events & Chai Matchers Emit Chai Matcher Continued I Hardhat Methods & Time Travel Make Hardhat do whatever you want it to Special debugging hardhat methods Continued II Callstatic Callstatic Continued III Massive Promise Test Continued IV Raffle.sol Staging Tests Testing on a Testnet Recommended LINK amounts for Sepolia Staging Test: Chainlink VRF: 2 LINK Chainlink Keepers: 8 LINK Conclusion Typescript - Smart Contract Lottery 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Completed Hardhat Basics! 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Lesson 10: NextJS Smart Contract Lottery (Full Stack / Front End) ⌨️ (16:34:07) Lesson 10: NextJS Smart Contract Lottery (Full Stack / Front End) 💻 Code: https://github.com/PatrickAlphaC/nextjs-smartcontract-lottery-fcc ⚡️⚡️ Live Demo IPFS: ipfs://QmXwACyjcS8tL7UkYwimpqMqW9sKzSHUjE4uSZBSyQVuEH ⚡️⚡️ Live Demo Fleek: https://fancy-dream-3458.on.fleek.co/ Introduction We move into using NextJS for our front end. NextJS is a React framework for building websites. Optional Sub-Lesson: Full Stack Development & Other Libraries 6 Ways to connect your dapp to a wallet NextJS Crash Course Other React libraries: Web3React wagmi react-moralis useDapp Web3Modal useMetamask Other Full Stack Web3 Templates scaffold-eth ethereum-boilerplate create-eth-app React being quite popular Why use react? NextJS Setup NextJS Documentation NextJS Minimal Ethers Example For Lottery yarn create next-app . Manual Header I What is a component? jsx Moralis React Moralis React Hooks What is a react hook? Manual Header II useEffect Hook useEffect Hook More on useEffect React Context useEffect Firing Twice Local Storage Local Storage isWeb3EnabledLoading web3uikit web3uikit web3uikit interactive docs web3uikit connect button Introduction to Calling Functions in Nextjs useWeb3Contract Automatic Constant Value UI Updater ethers.utils.FormatTypes runContractFunction Moralis Provider useMoralis parseInt useState useState Hook Calling Functions in NextJS useNotification Add onError to all your runContractFunction calls Reading & Displaying Contract Data A Note about onSuccess onSuccess just checks to see if MetaMask sends the transaction, not A Challenge to You Tailwind & Styling Learn CSS Tailwindcss PostCSS Extension Tailwind Extension Install Tailwind into NextJS Introduction to Hosting your Site ⌨️ (18:12:50) Introdunction to Hosting your Site Vercel Moralis Netilfy IPFS IPFS ⌨️ (18:15:14) IPFS What is IPFS IPFS Hosting on IPFS ⌨️ (18:18:51) Hosting on IPFS IPFS Companion Brave Browser yarn build && yarn next export Hosting on IPFS & Filecoin using Fleek ⌨️ (18:25:45) Hosting on IPFS & Filecoin using Fleek Fleek Filecoin Overview ⌨️ (18:31:28) Filecoin Overview Special Guest Ally Haire IPFS URL of Ally's Video Lesson 10 Recap Lesson 11: Hardhat Starter Kit ⌨️ (18:51:36) Lesson 11: Hardhat Starter Kit 💻 Code: https://github.com/smartcontractkit/hardhat-starter-kit Lesson 12: Hardhat ERC20s ⌨️ (18:59:24) Lesson 12: Hardhat ERC20s 💻 Code: https://github.com/PatrickAlphaC/hardhat-erc20-fcc What is an ERC? What is an EIP? What is an EIP? EIPs codebase What is an ERC20? Video (using brownie/python) EIP-20 ERC-677 EIP-777 Manually Creating an ERC20 Token Creating an ERC20 Token with Openzeppelin Openzeppelin Openzeppelin Contracts Solmate (Openzeppelin alternative) Lesson 12 Recap Lesson 13: Hardhat DeFi & Aave ⌨️ (19:16:13) Lesson 13: Hardhat DeFi & Aave 💻 Code: https://github.com/PatrickAlphaC/hardhat-defi-fcc What is DeFi? What is DeFi? DefiLlama What is Aave? Aave My Previous Aave Video on Shorting Assets Programmatic Borrowing & Lending DAI Uniswap WETH - Wrapped ETH WETH Token Sepolia Etherscan WETH Token Mainnet Forking Mainnet Mainnet Forking Depositing into Aave Aave V2 Docs Aave NPM Borrowing from Aave Aave Borrowing FAQs Health Factor Aave Risk Parameters Repaying with Aave Visualizing the Transactions aTokens Lesson 13 Recap Happy Bow-Tie Friday with Austin Griffith Special Guest Austin Griffith ! Speed Run Ethereum More DeFi Learnings: Defi-Minimal Defi Dad Lesson 14: Hardhat NFTs (EVERYTHING you need to know about NFTs) ⌨️ (20:28:51) Lesson 14: Hardhat NFTs 💻 Code: https://github.com/PatrickAlphaC/hardhat-nft-fcc What is an NFT? Video Optional: All on Chain SVG NFT EIP-721 Code Overview Opensea Testnet Hardhat Setup Basic NFT Write Tests Openzeppelin NFT Random IPFS NFT Mapping Chainlink VRF Requests Creating Rare NFTs Setting the NFT Image Setting an NFT Mint Price Deploy Script Uploading Token Images with Pinata Pinata nft.storage Pinata NPM Pinata Docs Uploading Token URIs (metadata) with Pinata Deploying Tests Dynamic SVG On-Chain NFT Patrick's Original Video What is an SVG? SVG Tutorial On-Chain SVG Example Initial Code Base64 Encoding Base64 Encoding Example Encoder base64-sol Advanced: EVM Opcodes, Encoding, and Calling abi.encode & abi.encodePacked abi.encode abi.encodePacked Thanks to Alex Roan for his help on this session! Example Contract Creation Transaction What REALLY is the ABI? EVM Opcodes More EVM Opcodes Solidity Cheatsheet abi.encode vs abi.encodePacked Introduction to Encoding Function Calls Directly Introduction to Encoding Function Calls Recap Encoding Function Calls Directly Function Selector Function Signature Creating an NFT TokenURI on-Chain Making the NFT Dynamic Deploy Script Deploying the NFTs to a Testnet Lesson 14 Recap Extra credit: Deconstructing Solidity Knowing and controlling your Smart Contract Address From Solidity to byte code Lesson 15: NextJS NFT Marketplace (If you finish this lesson, you are a full-stack MONSTER!) ⌨️ (23:37:03) Lesson 15: NextJS NFT Marketplace (Full Stack / Front End) Large Update, please read Moralis has recently updated to a self-hosted server over their own server. For this, you can do one of the following: Learn how to run one yourself Follow along to learn the concepts of this more interactive app, without actually coding along Skip to the section where we interact with the graph TL;DR: TheGraph code should work exactly the same as the video, however the Moralis code will not. 💻 Code: Backend (Contracts): https://github.com/PatrickAlphaC/hardhat-nft-marketplace-fcc Frontend (Moralis Indexer): https://github.com/PatrickAlphaC/nextjs-nft-marketplace-moralis-fcc Frontend (TheGraph Indexer): https://github.com/PatrickAlphaC/nextjs-nft-marketplace-thegraph-fcc The Graph: https://github.com/PatrickAlphaC/graph-nft-marketplace-fcc Special thanks to Matt Durkin for help with this section. Introduction Opensea Artion Part I: NFT Marketplace Contracts Hardhat Setup NftMarketplace.sol Pull Over Push Reentrancy Reentrancy Rekt.news Openzeppelin NonReentrant NftMarketplace.sol - Continued NftMarketplace.sol - Deploy Script NftMarketplace.sol - Tests NftMarketplace.sol - Scripts Part II: Moralis Front End What is Moralis? Special Guest Ivan Liljeqvist NextJS Setup Link NextJS Adding Tailwind Tailwind with NextJS Introduction to Indexing in Web3 TheGraph Moralis Connecting Moralis to our Local Hardhat Node NextJS Environment Variables Reverse Proxy FRP Docs Trouble Shooting Moralis Forum Moralis Admin CLI Moralis Event Sync Moralis Add Event Sync From Code Reset Local Chain Moralis Cloud Functions Moralis Cloud Functions Moralis Logging Hardhat Network Reference Moralis Database only confirms a transaction with a block confirmation - so we need to move blocks on our hardhat local node. Moralis Triggers Practice Resetting the Local Chain Moralis Cloud Functions II Querying the Moralis Database Moralis Queries Rendering the NFT Images useNFTBalance fetch next/image Update Listing Modal Buy NFT Listing Listing NFTs for Sale web3uikit Form Part III: TheGraph Front End Introduction What is The Graph? Special Guest Nader Dabit Building a Subgraph Example Subgraphs The Graph Studio GraphQL VSCode Extension GraphQL Deploying our Subgraph GraphQL Queries Reading from The Graph @apollo/client gql The Graph Docs Hosting our Dapp 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Completed Front End Basics! 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Lesson 16: Hardhat Upgrades ⌨️ (28:53:11) Lesson 16: Hardhat Upgrades 💻 Code: https://github.com/PatrickAlphaC/hardhat-upgrades-fcc Upgradable Smart Contracts Overview Optional Video [Links from Video] Types of Upgrades Parameter Social Migrate Proxy Proxy Gotchas Function Collisions Storage Collisions Metamorphic Upgrades Transparent UUPS Diamond Delegatecall delegatecall (solidity-by-example) Yul Small Proxy Example EIP 1967 Transparent Upgradable Smart Contract Hardhat-deploy Proxies Openzeppelin Upgrades Plugin Openzeppelin upgrades tutorial hardhat deploy upgrades examples Lesson 17: Hardhat DAOs ⌨️ (29:45:24) Lesson 17: Hardhat DAOs ⬆️ Up-to-date code: https://github.com/PatrickAlphaC/dao-template 💻 Code from video: https://github.com/PatrickAlphaC/hardhat-dao-fcc Introduction What is a DAO? What is a DAO? How to build a DAO How to build a DAO That's Patrick PY Code Python Video Openzeppelin Governance Compound Governance Contract Wizard CastVoteBySig Lesson 18: Security & Auditing ⌨️ (31:28:32) Lesson 18: Security & Auditing 💻 Code: https://github.com/PatrickAlphaC/hardhat-security-fcc Introduction Readiness Guide Slither Install python Slither solc-select Fuzz testing Fuzzing and Eth Security Toolbox Echidna Docker Install Eth-Security-ToolBox Closing Thoughts Best Practices Attacks Oracle Attacks Re-entrancy Attacks Damn Vulnerable Defi Ethernaut Some Auditors: OpenZeppelin SigmaPrime Trail of Bits Congratulations 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Completed The Course! 🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊🎊 Where do I go now? Learning More CryptoZombies Patrick Collins Dapp University ChainShot Cami Ramos Garzon Albert Hu Ivan Liljeqvist Ally Haire Stephen Fluin Eat the Blocks Austin Griffith Nader Dabit Ethereum.org Community Twitter Hardhat Discord Ethereum Python Community Discord Chainlink Discord Ethereum Discord Reddit ethdev Hackathons CL Hackathon ETHGlobal ETHIndia Be sure to check out project grant programs! And make today an amazing day! Thank you Thanks to everyone who is taking, participating in, and working on this course. It's been a passion project and a data dump of everything I've learnt in the web3 space to get you up to speed quickly. Also, a big thank you to Chainlink Labs for encouraging this course to come to light-and to the many Chainlink Labs team members who helped with various assets!

Learn Blockchain, Solidity, and Full Stack Web3 Development with Javascript

blockchain,chainlink,ethereum,javascript,moralis,smart-contracts,solidity,thegraphprotocol,typescript,alchemy

illacloud/illa-builder

ILLA Builder ILLA is a robust open source low-code platform for developers to build internal tools. By using ILLA's library of Components and Actions, developers can save massive amounts of time on building tools. English | 简体中文 | Deutsch | 日本語 🚀Get Started To try ILLA, the most convenient way is to sign up and log in to ILLA Cloud . You can also deploy and self-host ILLA utils manually( Docker , docker-compose , and k8s ). ✨ Features ⚽ Real-time Collaboration: We can create everything in real-time together. 🤖 Automate Support: Connect everything and automate them in 5 seconds. 🖥 Self-hosted: supports Docker & k8s 📝 Page Support: The base of creating a content-rich and UI-friendly tool. 🎨 Powered by ILLA Design : Components should not constrain your imagination. Self-hosted The ILLA CLI enables you to deploy ILLA Builder faster than your imagination. Click here for more details. After successfully deployed, you can register with email address or log in with the following information: Username (email): root Password: password How to build your tool 🎯 Step 1: Connect to your database 🎨 Step 2: Build UI with built-in components Build your UI by dragging components to the canvas. We provide dozens of components including charts, tables, forms, and many more in Illa Builder and Illa Design. When components overlap, their position will be automatically adjusted, which makes the layout development easy and flexible. 🔌 Step 3: Connect to your data Connect to MySQL or REST API through our GUI data connectors. We will add more than 10 databases and APIs soon. 🚀 Step 4: Deploy your app Deploy your app and self-host it. 💬 Community Join ILLA Community to share your ideas, suggestions, or questions and connect with other users and contributors. 🌱 Contributing Thinking about contributing? All kinds of contributions to ILLA are greatly appreciated and welcomed! Check out our Contribution Guide for details about how you can get involved. Appreciate all the contributions from our ❤︎ Contributors! 📢 Translating The apps/builder/src/i18n/locale/* dirs are kept up-to-date automatically via Crowdin. See our official translation page in case you would like to contribute. 🔥 We are Hiring! Looking for a passionate and creative team? We are actively hiring engineers for the following positions: Frontend Engineer Golang Engineer Contact Us: hr@illasoft.com LICENSE This project is currently licensed under Apache License 2.0 .

Low-code platform allows you to build business apps, enables you to quickly create internal tools such as dashboard, crud app, admin panel, crm, cms, etc. Supports PostgreSQL, MySQL, Supabase, GraphQL, MongoDB, MSSQL, Rest API, Hugging Face, Redis, etc. Automate workflows with schedule or webhook. Open source Retool.

internal-tool,internal-tools,gui,typescript,self-hosted,developer-tools,app-builder,low-code-development-platform,internal-development,react

lucidrains/DALLE2-pytorch

DALL-E 2 - Pytorch Implementation of DALL-E 2 , OpenAI's updated text-to-image synthesis neural network, in Pytorch. Yannic Kilcher summary | AssemblyAI explainer The main novelty seems to be an extra layer of indirection with the prior network (whether it is an autoregressive transformer or a diffusion network), which predicts an image embedding based on the text embedding from CLIP. Specifically, this repository will only build out the diffusion prior network, as it is the best performing variant (but which incidentally involves a causal transformer as the denoising network 😂) This model is SOTA for text-to-image for now. Please join if you are interested in helping out with the replication with the LAION community | Yannic Interview As of 5/23/22, it is no longer SOTA. SOTA will be here . Jax versions as well as text-to-video project will be shifted towards the Imagen architecture, as it is way simpler. Status A research group has used the code in this repository to train a functional diffusion prior for their CLIP generations. Will share their work once they release their preprint. This, and Katherine's own experiments, validate OpenAI's finding that the extra prior increases variety of generations. Decoder is now verified working for unconditional generation on my experimental setup for Oxford flowers. 2 researchers have also confirmed Decoder is working for them. ongoing at 21k steps Justin Pinkney successfully trained the diffusion prior in the repository for his CLIP to Stylegan2 text-to-image application Romain has scaled up training to 800 GPUs with the available scripts without any issues Pre-Trained Models LAION is training prior models. Checkpoints are available on 🤗huggingface and the training statistics are available on 🐝WANDB . Decoder - In-progress test run 🚧 Decoder - Another test run with sparse attention DALL-E 2 🚧 - DALL-E 2 Laion repository Appreciation This library would not have gotten to this working state without the help of Zion for the distributed training code for the diffusion prior Aidan for the distributed training code for the decoder as well as the dataloaders Kumar for working on the initial diffusion training script Romain for the pull request reviews and project management He Cao and xiankgx for the Q&A and for identifying of critical bugs Marunine for identifying issues with resizing of the low resolution conditioner, when training the upsampler, in addition to various other bug fixes MalumaDev for proposing the use of pixel shuffle upsampler for fixing checkboard artifacts Katherine for her advice Stability AI for the generous sponsorship 🤗 Huggingface and in particular Sylvain for the Accelerate library Alex for einops , indispensable tool for tensor manipulation ... and many others. Thank you! 🙏 Install bash $ pip install dalle2-pytorch Usage To train DALLE-2 is a 3 step process, with the training of CLIP being the most important To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway . This repository will demonstrate integration with x-clip for starters ```python import torch from dalle2_pytorch import CLIP clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 1, text_seq_len = 256, text_heads = 8, visual_enc_depth = 1, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8, use_all_token_embeds = True, # whether to use fine-grained contrastive learning (FILIP) decoupled_contrastive_learning = True, # use decoupled contrastive learning (DCL) objective function, removing positive pairs from the denominator of the InfoNCE loss (CLOOB + DCL) extra_latent_projection = True, # whether to use separate projections for text-to-image vs image-to-text comparisons (CLOOB) use_visual_ssl = True, # whether to do self supervised learning on images visual_ssl_type = 'simclr', # can be either 'simclr' or 'simsiam', depending on using DeCLIP or SLIP use_mlm = False, # use masked language learning (MLM) on text (DeCLIP) text_ssl_loss_weight = 0.05, # weight for text MLM loss image_ssl_loss_weight = 0.05 # weight for image self-supervised learning loss ).cuda() mock data text = torch.randint(0, 49408, (4, 256)).cuda() images = torch.randn(4, 3, 256, 256).cuda() train loss = clip( text, images, return_loss = True # needs to be set to True to return contrastive loss ) loss.backward() do the above with as many texts and images as possible in a loop ``` Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP above ```python import torch from dalle2_pytorch import Unet, Decoder, CLIP trained clip from step 1 clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 1, text_seq_len = 256, text_heads = 8, visual_enc_depth = 1, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8 ).cuda() unet for the decoder unet = Unet( dim = 128, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults=(1, 2, 4, 8) ).cuda() decoder, which contains the unet and clip decoder = Decoder( unet = unet, clip = clip, timesteps = 100, image_cond_drop_prob = 0.1, text_cond_drop_prob = 0.5 ).cuda() mock images (get a lot of this) images = torch.randn(4, 3, 256, 256).cuda() feed images into decoder loss = decoder(images) loss.backward() do the above for many many many many steps then it will learn to generate images based on the CLIP image embeddings ``` Finally, the main contribution of the paper. The repository offers the diffusion prior network. It takes the CLIP text embeddings and tries to generate the CLIP image embeddings. Again, you will need the trained CLIP from the first step ```python import torch from dalle2_pytorch import DiffusionPriorNetwork, DiffusionPrior, CLIP get trained CLIP from step one clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 6, text_seq_len = 256, text_heads = 8, visual_enc_depth = 6, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8, ).cuda() setup prior network, which contains an autoregressive transformer prior_network = DiffusionPriorNetwork( dim = 512, depth = 6, dim_head = 64, heads = 8 ).cuda() diffusion prior network, which contains the CLIP and network (with transformer) above diffusion_prior = DiffusionPrior( net = prior_network, clip = clip, timesteps = 100, cond_drop_prob = 0.2 ).cuda() mock data text = torch.randint(0, 49408, (4, 256)).cuda() images = torch.randn(4, 3, 256, 256).cuda() feed text and images into diffusion prior network loss = diffusion_prior(text, images) loss.backward() do the above for many many many steps now the diffusion prior can generate image embeddings from the text embeddings ``` In the paper, they actually used a recently discovered technique , from Jonathan Ho himself (original author of DDPMs, the core technique used in DALL-E v2) for high resolution image synthesis. This can easily be used within this framework as so ```python import torch from dalle2_pytorch import Unet, Decoder, CLIP trained clip from step 1 clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 6, text_seq_len = 256, text_heads = 8, visual_enc_depth = 6, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8 ).cuda() 2 unets for the decoder (a la cascading DDPM) unet1 = Unet( dim = 32, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults = (1, 2, 4, 8) ).cuda() unet2 = Unet( dim = 32, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults = (1, 2, 4, 8, 16) ).cuda() decoder, which contains the unet(s) and clip decoder = Decoder( clip = clip, unet = (unet1, unet2), # insert both unets in order of low resolution to highest resolution (you can have as many stages as you want here) image_sizes = (256, 512), # resolutions, 256 for first unet, 512 for second. these must be unique and in ascending order (matches with the unets passed in) timesteps = 1000, image_cond_drop_prob = 0.1, text_cond_drop_prob = 0.5 ).cuda() mock images (get a lot of this) images = torch.randn(4, 3, 512, 512).cuda() feed images into decoder, specifying which unet you want to train each unet can be trained separately, which is one of the benefits of the cascading DDPM scheme loss = decoder(images, unet_number = 1) loss.backward() loss = decoder(images, unet_number = 2) loss.backward() do the above for many steps for both unets ``` Finally, to generate the DALL-E2 images from text. Insert the trained DiffusionPrior as well as the Decoder (which wraps CLIP , the causal transformer, and unet(s)) ```python from dalle2_pytorch import DALLE2 dalle2 = DALLE2( prior = diffusion_prior, decoder = decoder ) send the text as a string if you want to use the simple tokenizer from DALLE v1 or you can do it as token ids, if you have your own tokenizer texts = ['glistening morning dew on a flower petal'] images = dalle2(texts) # (1, 3, 256, 256) ``` That's it! Let's see the whole script below ```python import torch from dalle2_pytorch import DALLE2, DiffusionPriorNetwork, DiffusionPrior, Unet, Decoder, CLIP clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 6, text_seq_len = 256, text_heads = 8, visual_enc_depth = 6, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8 ).cuda() mock data text = torch.randint(0, 49408, (4, 256)).cuda() images = torch.randn(4, 3, 256, 256).cuda() train loss = clip( text, images, return_loss = True ) loss.backward() do above for many steps ... prior networks (with transformer) prior_network = DiffusionPriorNetwork( dim = 512, depth = 6, dim_head = 64, heads = 8 ).cuda() diffusion_prior = DiffusionPrior( net = prior_network, clip = clip, timesteps = 1000, sample_timesteps = 64, cond_drop_prob = 0.2 ).cuda() loss = diffusion_prior(text, images) loss.backward() do above for many steps ... decoder (with unet) unet1 = Unet( dim = 128, image_embed_dim = 512, text_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults=(1, 2, 4, 8), cond_on_text_encodings = True # set to True for any unets that need to be conditioned on text encodings ).cuda() unet2 = Unet( dim = 16, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults = (1, 2, 4, 8, 16) ).cuda() decoder = Decoder( unet = (unet1, unet2), image_sizes = (128, 256), clip = clip, timesteps = 100, image_cond_drop_prob = 0.1, text_cond_drop_prob = 0.5 ).cuda() for unet_number in (1, 2): loss = decoder(images, text = text, unet_number = unet_number) # this can optionally be decoder(images, text) if you wish to condition on the text encodings as well, though it was hinted in the paper it didn't do much loss.backward() do above for many steps dalle2 = DALLE2( prior = diffusion_prior, decoder = decoder ) images = dalle2( ['cute puppy chasing after a squirrel'], cond_scale = 2. # classifier free guidance strength (> 1 would strengthen the condition) ) save your image (in this example, of size 256x256) ``` Everything in this readme should run without error You can also train the decoder on images of greater than the size (say 512x512) at which CLIP was trained (256x256). The images will be resized to CLIP image resolution for the image embeddings For the layperson, no worries, training will all be automated into a CLI tool, at least for small scale training. Training on Preprocessed CLIP Embeddings It is likely, when scaling up, that you would first preprocess your images and text into corresponding embeddings before training the prior network. You can do so easily by simply passing in image_embed , text_embed , and optionally text_encodings Working example below ```python import torch from dalle2_pytorch import DiffusionPriorNetwork, DiffusionPrior, CLIP get trained CLIP from step one clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 6, text_seq_len = 256, text_heads = 8, visual_enc_depth = 6, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8, ).cuda() setup prior network, which contains an autoregressive transformer prior_network = DiffusionPriorNetwork( dim = 512, depth = 6, dim_head = 64, heads = 8 ).cuda() diffusion prior network, which contains the CLIP and network (with transformer) above diffusion_prior = DiffusionPrior( net = prior_network, clip = clip, timesteps = 100, cond_drop_prob = 0.2, condition_on_text_encodings = False # this probably should be true, but just to get Laion started ).cuda() mock data text = torch.randint(0, 49408, (4, 256)).cuda() images = torch.randn(4, 3, 256, 256).cuda() precompute the text and image embeddings here using the diffusion prior class, but could be done with CLIP alone clip_image_embeds = diffusion_prior.clip.embed_image(images).image_embed clip_text_embeds = diffusion_prior.clip.embed_text(text).text_embed feed text and images into diffusion prior network loss = diffusion_prior( text_embed = clip_text_embeds, image_embed = clip_image_embeds ) loss.backward() do the above for many many many steps now the diffusion prior can generate image embeddings from the text embeddings ``` You can also completely go CLIP -less, in which case you will need to pass in the image_embed_dim into the DiffusionPrior on initialization ```python import torch from dalle2_pytorch import DiffusionPriorNetwork, DiffusionPrior setup prior network, which contains an autoregressive transformer prior_network = DiffusionPriorNetwork( dim = 512, depth = 6, dim_head = 64, heads = 8 ).cuda() diffusion prior network, which contains the CLIP and network (with transformer) above diffusion_prior = DiffusionPrior( net = prior_network, image_embed_dim = 512, # this needs to be set timesteps = 100, cond_drop_prob = 0.2, condition_on_text_encodings = False # this probably should be true, but just to get Laion started ).cuda() mock data text = torch.randint(0, 49408, (4, 256)).cuda() images = torch.randn(4, 3, 256, 256).cuda() precompute the text and image embeddings here using the diffusion prior class, but could be done with CLIP alone clip_image_embeds = torch.randn(4, 512).cuda() clip_text_embeds = torch.randn(4, 512).cuda() feed text and images into diffusion prior network loss = diffusion_prior( text_embed = clip_text_embeds, image_embed = clip_image_embeds ) loss.backward() do the above for many many many steps now the diffusion prior can generate image embeddings from the text embeddings ``` OpenAI CLIP Although there is the possibility they are using an unreleased, more powerful CLIP, you can use one of the released ones, if you do not wish to train your own CLIP from scratch. This will also allow the community to more quickly validate the conclusions of the paper. To use a pretrained OpenAI CLIP, simply import OpenAIClipAdapter and pass it into the DiffusionPrior or Decoder like so ```python import torch from dalle2_pytorch import DALLE2, DiffusionPriorNetwork, DiffusionPrior, Unet, Decoder, OpenAIClipAdapter openai pretrained clip - defaults to ViT-B/32 clip = OpenAIClipAdapter() mock data text = torch.randint(0, 49408, (4, 256)).cuda() images = torch.randn(4, 3, 256, 256).cuda() prior networks (with transformer) prior_network = DiffusionPriorNetwork( dim = 512, depth = 6, dim_head = 64, heads = 8 ).cuda() diffusion_prior = DiffusionPrior( net = prior_network, clip = clip, timesteps = 100, cond_drop_prob = 0.2 ).cuda() loss = diffusion_prior(text, images) loss.backward() do above for many steps ... decoder (with unet) unet1 = Unet( dim = 128, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults=(1, 2, 4, 8), text_embed_dim = 512, cond_on_text_encodings = True # set to True for any unets that need to be conditioned on text encodings (ex. first unet in cascade) ).cuda() unet2 = Unet( dim = 16, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults = (1, 2, 4, 8, 16) ).cuda() decoder = Decoder( unet = (unet1, unet2), image_sizes = (128, 256), clip = clip, timesteps = 1000, sample_timesteps = (250, 27), image_cond_drop_prob = 0.1, text_cond_drop_prob = 0.5 ).cuda() for unet_number in (1, 2): loss = decoder(images, text = text, unet_number = unet_number) # this can optionally be decoder(images, text) if you wish to condition on the text encodings as well, though it was hinted in the paper it didn't do much loss.backward() do above for many steps dalle2 = DALLE2( prior = diffusion_prior, decoder = decoder ) images = dalle2( ['a butterfly trying to escape a tornado'], cond_scale = 2. # classifier free guidance strength (> 1 would strengthen the condition) ) save your image (in this example, of size 256x256) ``` Alternatively, you can also use Open Clip bash $ pip install open-clip-torch Ex. using the SOTA Open Clip model trained by Romain ```python from dalle2_pytorch import OpenClipAdapter clip = OpenClipAdapter('ViT-H/14') ``` Now you'll just have to worry about training the Prior and the Decoder! Inpainting Inpainting is also built into the Decoder . You simply have to pass in the inpaint_image and inpaint_mask (boolean tensor where True indicates which regions of the inpaint image to keep) This repository uses the formulation put forth by Lugmayr et al. in Repaint ```python import torch from dalle2_pytorch import Unet, Decoder, CLIP trained clip from step 1 clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 6, text_seq_len = 256, text_heads = 8, visual_enc_depth = 6, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8 ).cuda() 2 unets for the decoder (a la cascading DDPM) unet = Unet( dim = 16, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults = (1, 1, 1, 1) ).cuda() decoder, which contains the unet(s) and clip decoder = Decoder( clip = clip, unet = (unet,), # insert both unets in order of low resolution to highest resolution (you can have as many stages as you want here) image_sizes = (256,), # resolutions, 256 for first unet, 512 for second. these must be unique and in ascending order (matches with the unets passed in) timesteps = 1000, image_cond_drop_prob = 0.1, text_cond_drop_prob = 0.5 ).cuda() mock images (get a lot of this) images = torch.randn(4, 3, 256, 256).cuda() feed images into decoder, specifying which unet you want to train each unet can be trained separately, which is one of the benefits of the cascading DDPM scheme loss = decoder(images, unet_number = 1) loss.backward() do the above for many steps for both unets mock_image_embed = torch.randn(1, 512).cuda() then to do inpainting inpaint_image = torch.randn(1, 3, 256, 256).cuda() # (batch, channels, height, width) inpaint_mask = torch.ones(1, 256, 256).bool().cuda() # (batch, height, width) inpainted_images = decoder.sample( image_embed = mock_image_embed, inpaint_image = inpaint_image, # just pass in the inpaint image inpaint_mask = inpaint_mask # and the mask ) inpainted_images.shape # (1, 3, 256, 256) ``` Experimental DALL-E2 with Latent Diffusion This repository decides to take the next step and offer DALL-E v2 combined with latent diffusion , from Rombach et al. You can use it as follows. Latent diffusion can be limited to just the first U-Net in the cascade, or to any number you wish. The repository also comes equipped with all the necessary settings to recreate ViT-VQGan from the Improved VQGans paper. Furthermore, the vector quantization library also comes equipped to do residual or multi-headed quantization , which I believe will give an even further boost in performance to the autoencoder. ```python import torch from dalle2_pytorch import Unet, Decoder, CLIP, VQGanVAE trained clip from step 1 clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 1, text_seq_len = 256, text_heads = 8, visual_enc_depth = 1, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8 ) 3 unets for the decoder (a la cascading DDPM) first two unets are doing latent diffusion vqgan-vae must be trained beforehand vae1 = VQGanVAE( dim = 32, image_size = 256, layers = 3, layer_mults = (1, 2, 4) ) vae2 = VQGanVAE( dim = 32, image_size = 512, layers = 3, layer_mults = (1, 2, 4) ) unet1 = Unet( dim = 32, image_embed_dim = 512, cond_dim = 128, channels = 3, sparse_attn = True, sparse_attn_window = 2, dim_mults = (1, 2, 4, 8) ) unet2 = Unet( dim = 32, image_embed_dim = 512, channels = 3, dim_mults = (1, 2, 4, 8, 16), cond_on_image_embeds = True, cond_on_text_encodings = False ) unet3 = Unet( dim = 32, image_embed_dim = 512, channels = 3, dim_mults = (1, 2, 4, 8, 16), cond_on_image_embeds = True, cond_on_text_encodings = False, attend_at_middle = False ) decoder, which contains the unet(s) and clip decoder = Decoder( clip = clip, vae = (vae1, vae2), # latent diffusion for unet1 (vae1) and unet2 (vae2), but not for the last unet3 unet = (unet1, unet2, unet3), # insert unets in order of low resolution to highest resolution (you can have as many stages as you want here) image_sizes = (256, 512, 1024), # resolutions, 256 for first unet, 512 for second, 1024 for third timesteps = 100, image_cond_drop_prob = 0.1, text_cond_drop_prob = 0.5 ).cuda() mock images (get a lot of this) images = torch.randn(1, 3, 1024, 1024).cuda() feed images into decoder, specifying which unet you want to train each unet can be trained separately, which is one of the benefits of the cascading DDPM scheme with decoder.one_unet_in_gpu(1): loss = decoder(images, unet_number = 1) loss.backward() with decoder.one_unet_in_gpu(2): loss = decoder(images, unet_number = 2) loss.backward() with decoder.one_unet_in_gpu(3): loss = decoder(images, unet_number = 3) loss.backward() do the above for many steps for both unets then it will learn to generate images based on the CLIP image embeddings chaining the unets from lowest resolution to highest resolution (thus cascading) mock_image_embed = torch.randn(1, 512).cuda() images = decoder.sample(mock_image_embed) # (1, 3, 1024, 1024) ``` Training wrapper Decoder Training Training the Decoder may be confusing, as one needs to keep track of an optimizer for each of the Unet (s) separately. Each Unet will also need its own corresponding exponential moving average. The DecoderTrainer hopes to make this simple, as shown below ```python import torch from dalle2_pytorch import DALLE2, Unet, Decoder, CLIP, DecoderTrainer clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 6, text_seq_len = 256, text_heads = 8, visual_enc_depth = 6, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8 ).cuda() mock data text = torch.randint(0, 49408, (32, 256)).cuda() images = torch.randn(32, 3, 256, 256).cuda() decoder (with unet) unet1 = Unet( dim = 128, image_embed_dim = 512, text_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults=(1, 2, 4, 8), cond_on_text_encodings = True, ).cuda() unet2 = Unet( dim = 16, image_embed_dim = 512, cond_dim = 128, channels = 3, dim_mults = (1, 2, 4, 8, 16), ).cuda() decoder = Decoder( unet = (unet1, unet2), image_sizes = (128, 256), clip = clip, timesteps = 1000 ).cuda() decoder_trainer = DecoderTrainer( decoder, lr = 3e-4, wd = 1e-2, ema_beta = 0.99, ema_update_after_step = 1000, ema_update_every = 10, ) for unet_number in (1, 2): loss = decoder_trainer( images, text = text, unet_number = unet_number, # which unet to train on max_batch_size = 4 # gradient accumulation - this sets the maximum batch size in which to do forward and backwards pass - for this example 32 / 4 == 8 times ) decoder_trainer.update(unet_number) # update the specific unet as well as its exponential moving average after much training you can sample from the exponentially moving averaged unets as so mock_image_embed = torch.randn(32, 512).cuda() images = decoder_trainer.sample(image_embed = mock_image_embed, text = text) # (4, 3, 256, 256) ``` Diffusion Prior Training Similarly, one can use the DiffusionPriorTrainer to automatically instantiate and keep track of an exponential moving averaged prior. ```python import torch from dalle2_pytorch import DALLE2, DiffusionPriorNetwork, DiffusionPrior, DiffusionPriorTrainer, Unet, Decoder, CLIP clip = CLIP( dim_text = 512, dim_image = 512, dim_latent = 512, num_text_tokens = 49408, text_enc_depth = 6, text_seq_len = 256, text_heads = 8, visual_enc_depth = 6, visual_image_size = 256, visual_patch_size = 32, visual_heads = 8 ).cuda() mock data text = torch.randint(0, 49408, (512, 256)).cuda() images = torch.randn(512, 3, 256, 256).cuda() prior networks (with transformer) prior_network = DiffusionPriorNetwork( dim = 512, depth = 6, dim_head = 64, heads = 8 ).cuda() diffusion_prior = DiffusionPrior( net = prior_network, clip = clip, timesteps = 100, cond_drop_prob = 0.2 ).cuda() diffusion_prior_trainer = DiffusionPriorTrainer( diffusion_prior, lr = 3e-4, wd = 1e-2, ema_beta = 0.99, ema_update_after_step = 1000, ema_update_every = 10, ) loss = diffusion_prior_trainer(text, images, max_batch_size = 4) diffusion_prior_trainer.update() # this will update the optimizer as well as the exponential moving averaged diffusion prior after much of the above three lines in a loop you can sample from the exponential moving average of the diffusion prior identically to how you do so for DiffusionPrior image_embeds = diffusion_prior_trainer.sample(text, max_batch_size = 4) # (512, 512) - exponential moving averaged image embeddings ``` Bonus Unconditional Training The repository also contains the means to train unconditional DDPM model, or even cascading DDPMs. You simply have to set unconditional = True in the Decoder ex. ```python import torch from dalle2_pytorch import Unet, Decoder, DecoderTrainer unet for the cascading ddpm unet1 = Unet( dim = 128, dim_mults=(1, 2, 4, 8) ).cuda() unet2 = Unet( dim = 32, dim_mults = (1, 2, 4, 8, 16) ).cuda() decoder, which contains the unets decoder = Decoder( unet = (unet1, unet2), image_sizes = (256, 512), # first unet up to 256px, then second to 512px timesteps = 1000, unconditional = True ).cuda() decoder trainer decoder_trainer = DecoderTrainer(decoder) images (get a lot of this) images = torch.randn(1, 3, 512, 512).cuda() feed images into decoder for i in (1, 2): loss = decoder_trainer(images, unet_number = i) decoder_trainer.update(unet_number = i) do the above for many many many many images then it will learn to generate images images = decoder_trainer.sample(batch_size = 36, max_batch_size = 4) # (36, 3, 512, 512) ``` Dataloaders Decoder Dataloaders In order to make loading data simple and efficient, we include some general dataloaders that can be used to train portions of the network. Decoder: Image Embedding Dataset When training the decoder (and up samplers if training together) in isolation, you will need to load images and corresponding image embeddings. This dataset can read two similar types of datasets. First, it can read a webdataset that contains .jpg and .npy files in the .tar s that contain the images and associated image embeddings respectively. Alternatively, you can also specify a source for the embeddings outside of the webdataset. In this case, the path to the embeddings should contain .npy files with the same shard numbers as the webdataset and there should be a correspondence between the filename of the .jpg and the index of the embedding in the .npy . So, for example, 0001.tar from the webdataset with image 00010509.jpg (the first 4 digits are the shard number and the last 4 are the index) in it should be paralleled by a img_emb_0001.npy which contains a NumPy array with the embedding at index 509. Generating a dataset of this type: 1. Use img2dataset to generate a webdataset. 2. Use clip-retrieval to convert the images to embeddings. 3. Use embedding-dataset-reordering to reorder the embeddings into the expected format. Usage: ```python from dalle2_pytorch.dataloaders import ImageEmbeddingDataset, create_image_embedding_dataloader Create a dataloader directly. dataloader = create_image_embedding_dataloader( tar_url="/path/or/url/to/webdataset/{0000..9999}.tar", # Uses bracket expanding notation. This specifies to read all tars from 0000.tar to 9999.tar embeddings_url="path/or/url/to/embeddings/folder", # Included if .npy files are not in webdataset. Left out or set to None otherwise num_workers=4, batch_size=32, shard_width=4, # If a file in the webdataset shard 3 is named 0003039.jpg, we know the shard width is 4 and the last three digits are the index shuffle_num=200, # Does a shuffle of the data with a buffer size of 200 shuffle_shards=True, # Shuffle the order the shards are read in resample_shards=False, # Sample shards with replacement. If true, an epoch will be infinite unless stopped manually ) for img, emb in dataloader: print(img.shape) # torch.Size([32, 3, 256, 256]) print(emb["img"].shape) # torch.Size([32, 512]) # Train decoder only as shown above Or create a dataset without a loader so you can configure it manually dataset = ImageEmbeddingDataset( urls="/path/or/url/to/webdataset/{0000..9999}.tar", embedding_folder_url="path/or/url/to/embeddings/folder", shard_width=4, shuffle_shards=True, resample=False ) ``` Scripts train_diffusion_prior.py For detailed information on training the diffusion prior, please refer to the dedicated readme Todo [x] finish off gaussian diffusion class for latent embedding - allow for prediction of epsilon [x] add what was proposed in the paper, where DDPM objective for image latent embedding predicts x0 directly (reread vq-diffusion paper and get caught up on that line of work) [x] make sure it works end to end to produce an output tensor, taking a single gradient step [x] augment unet so that it can also be conditioned on text encodings (although in paper they hinted this didn't make much a difference) [x] figure out all the current bag of tricks needed to make DDPMs great (starting with the blur trick mentioned in paper) [x] build the cascading ddpm by having Decoder class manage multiple unets at different resolutions [x] add efficient attention in unet [x] be able to finely customize what to condition on (text, image embed) for specific unet in the cascade (super resolution ddpms near the end may not need too much conditioning) [x] offload unets not being trained on to CPU for memory efficiency (for training each resolution unets separately) [x] build out latent diffusion architecture, with the vq-reg variant (vqgan-vae), make it completely optional and compatible with cascading ddpms [x] for decoder, allow ability to customize objective (predict epsilon vs x0), in case latent diffusion does better with prediction of x0 [x] use attention-based upsampling https://arxiv.org/abs/2112.11435 [x] use inheritance just this once for sharing logic between decoder and prior network ddpms [x] bring in vit-vqgan https://arxiv.org/abs/2110.04627 for the latent diffusion [x] abstract interface for CLIP adapter class, so other CLIPs can be brought in [x] take care of mixed precision as well as gradient accumulation within decoder trainer [x] just take care of the training for the decoder in a wrapper class, as each unet in the cascade will need its own optimizer [x] bring in tools to train vqgan-vae [x] add convnext backbone for vqgan-vae (in addition to vit [vit-vqgan] + resnet) [x] make sure DDPMs can be run with traditional resnet blocks (but leave convnext as an option for experimentation) [x] make sure for the latter unets in the cascade, one can train on crops for learning super resolution (constrain the unet to be only convolutions in that case, or allow conv-like attention with rel pos bias) [x] offer setting in diffusion prior to split time and image embeddings into multiple tokens, configurable, for more surface area during attention [x] make sure resnet hyperparameters can be configurable across unet depth (groups and expansion factor) [x] pull logic for training diffusion prior into a class DiffusionPriorTrainer, for eventual script based + CLI based training [x] make sure the cascading ddpm in the repository can be trained unconditionally, offer a one-line CLI tool for training on a folder of images [x] bring in cross-scale embedding from iclr paper https://github.com/lucidrains/vit-pytorch/blob/main/vit_pytorch/crossformer.py#L14 [x] cross embed layers for downsampling, as an option [x] use an experimental tracker agnostic setup, as done here [x] use pydantic for config drive training [x] for both diffusion prior and decoder, all exponential moving averaged models needs to be saved and restored as well (as well as the step number) [x] offer save / load methods on the trainer classes to automatically take care of state dicts for scalers / optimizers / saving versions and checking for breaking changes [x] allow for creation of diffusion prior model off pydantic config classes - consider the same for tracker configs [x] bring in skip-layer excitations (from lightweight gan paper) to see if it helps for either decoder of unet or vqgan-vae training (doesnt work well) [x] test out grid attention in cascading ddpm locally, decide whether to keep or remove https://arxiv.org/abs/2204.01697 (keeping, seems to be fine) [x] allow for unet to be able to condition non-cross attention style as well [x] speed up inference, read up on papers (ddim) [x] add inpainting ability using resampler from repaint paper https://arxiv.org/abs/2201.09865 [x] add the final combination of upsample feature maps, used in unet squared, seems to have an effect in local experiments [ ] consider elucidated dalle2 https://arxiv.org/abs/2206.00364 [ ] add simple outpainting, text-guided 2x size the image for starters [ ] interface out the vqgan-vae so a pretrained one can be pulled off the shelf to validate latent diffusion + DALL-E2 Citations bibtex @misc{ramesh2022, title = {Hierarchical Text-Conditional Image Generation with CLIP Latents}, author = {Aditya Ramesh et al}, year = {2022} } bibtex @misc{crowson2022, author = {Katherine Crowson}, url = {https://twitter.com/rivershavewings} } bibtex @misc{rombach2021highresolution, title = {High-Resolution Image Synthesis with Latent Diffusion Models}, author = {Robin Rombach and Andreas Blattmann and Dominik Lorenz and Patrick Esser and Björn Ommer}, year = {2021}, eprint = {2112.10752}, archivePrefix = {arXiv}, primaryClass = {cs.CV} } bibtex @article{shen2019efficient, author = {Zhuoran Shen and Mingyuan Zhang and Haiyu Zhao and Shuai Yi and Hongsheng Li}, title = {Efficient Attention: Attention with Linear Complexities}, journal = {CoRR}, year = {2018}, url = {http://arxiv.org/abs/1812.01243}, } bibtex @article{Yu2021VectorquantizedIM, title = {Vector-quantized Image Modeling with Improved VQGAN}, author = {Jiahui Yu and Xin Li and Jing Yu Koh and Han Zhang and Ruoming Pang and James Qin and Alexander Ku and Yuanzhong Xu and Jason Baldridge and Yonghui Wu}, journal = {ArXiv}, year = {2021}, volume = {abs/2110.04627} } bibtex @article{Shleifer2021NormFormerIT, title = {NormFormer: Improved Transformer Pretraining with Extra Normalization}, author = {Sam Shleifer and Jason Weston and Myle Ott}, journal = {ArXiv}, year = {2021}, volume = {abs/2110.09456} } bibtex @article{Yu2022CoCaCC, title = {CoCa: Contrastive Captioners are Image-Text Foundation Models}, author = {Jiahui Yu and Zirui Wang and Vijay Vasudevan and Legg Yeung and Mojtaba Seyedhosseini and Yonghui Wu}, journal = {ArXiv}, year = {2022}, volume = {abs/2205.01917} } bibtex @misc{wang2021crossformer, title = {CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention}, author = {Wenxiao Wang and Lu Yao and Long Chen and Binbin Lin and Deng Cai and Xiaofei He and Wei Liu}, year = {2021}, eprint = {2108.00154}, archivePrefix = {arXiv}, primaryClass = {cs.CV} } bibtex @article{ho2021cascaded, title = {Cascaded Diffusion Models for High Fidelity Image Generation}, author = {Ho, Jonathan and Saharia, Chitwan and Chan, William and Fleet, David J and Norouzi, Mohammad and Salimans, Tim}, journal = {arXiv preprint arXiv:2106.15282}, year = {2021} } bibtex @misc{Saharia2022, title = {Imagen: unprecedented photorealism × deep level of language understanding}, author = {Chitwan Saharia*, William Chan*, Saurabh Saxena†, Lala Li†, Jay Whang†, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho†, David Fleet†, Mohammad Norouzi*}, year = {2022} } bibtex @article{Choi2022PerceptionPT, title = {Perception Prioritized Training of Diffusion Models}, author = {Jooyoung Choi and Jungbeom Lee and Chaehun Shin and Sungwon Kim and Hyunwoo J. Kim and Sung-Hoon Yoon}, journal = {ArXiv}, year = {2022}, volume = {abs/2204.00227} } bibtex @article{Saharia2021PaletteID, title = {Palette: Image-to-Image Diffusion Models}, author = {Chitwan Saharia and William Chan and Huiwen Chang and Chris A. Lee and Jonathan Ho and Tim Salimans and David J. Fleet and Mohammad Norouzi}, journal = {ArXiv}, year = {2021}, volume = {abs/2111.05826} } bibtex @article{Lugmayr2022RePaintIU, title = {RePaint: Inpainting using Denoising Diffusion Probabilistic Models}, author = {Andreas Lugmayr and Martin Danelljan and Andr{\'e}s Romero and Fisher Yu and Radu Timofte and Luc Van Gool}, journal = {ArXiv}, year = {2022}, volume = {abs/2201.09865} } bibtex @misc{chen2022analog, title = {Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning}, author = {Ting Chen and Ruixiang Zhang and Geoffrey Hinton}, year = {2022}, eprint = {2208.04202}, archivePrefix = {arXiv}, primaryClass = {cs.CV} } bibtex @article{Qiao2019WeightS, title = {Weight Standardization}, author = {Siyuan Qiao and Huiyu Wang and Chenxi Liu and Wei Shen and Alan Loddon Yuille}, journal = {ArXiv}, year = {2019}, volume = {abs/1903.10520} } bibtex @inproceedings{rogozhnikov2022einops, title = {Einops: Clear and Reliable Tensor Manipulations with Einstein-like Notation}, author = {Alex Rogozhnikov}, booktitle = {International Conference on Learning Representations}, year = {2022}, url = {https://openreview.net/forum?id=oapKSVM2bcj} } bibtex @article{Sunkara2022NoMS, title = {No More Strided Convolutions or Pooling: A New CNN Building Block for Low-Resolution Images and Small Objects}, author = {Raja Sunkara and Tie Luo}, journal = {ArXiv}, year = {2022}, volume = {abs/2208.03641} } bibtex @article{Salimans2022ProgressiveDF, title = {Progressive Distillation for Fast Sampling of Diffusion Models}, author = {Tim Salimans and Jonathan Ho}, journal = {ArXiv}, year = {2022}, volume = {abs/2202.00512} } Creating noise from data is easy; creating data from noise is generative modeling. - Yang Song's paper

Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch

artificial-intelligence,deep-learning,text-to-image

omnivore-app/omnivore

Omnivore Omnivore is a complete, open source read-it-later solution for people who like text. We built Omnivore because we love reading and we want it to be more social. Join us! Highlighting, notes, search, and sharing Full keyboard navigation Automatically saves your place in long articles Add newsletter articles via email (with substack support!) PDF support Web app written in Node.js and TypeScript Native iOS app ( source ) Android app ( source ) Progressive web app for Android users Browser extensions for Chrome , Safari , Firefox , and Edge Labels (aka tagging) Offline support Text to speech (iOS only) Logseq support via our Logseq Plugin Obsidian support via our Obsidian Plugin Every single part is fully open source! Fork it, extend it, or deploy it to your own server. We also have a free hosted version of Omnivore at omnivore.app -- try it now! Join us on Discord! :speech_balloon: We're building our community on Discord. Join us! Read more about Omnivore on our blog. https://blog.omnivore.app/p/getting-started-with-omnivore Shoutouts :tada: Omnivore takes advantage of some great open source software: TypeScript - Most of our backend and frontend are written in TypeScript. Next.js - Our frontend is a Next.JS app and is hosted on Vercel . SWR - We do all our data fetching on the web using SWR. Stitches - We use Stitches on the frontend to style our components. Mozilla Readability - We use Mozilla's Readability library to make pages easier to read. Swift GraphQL - We generate our GraphQL queries on iOS using Swift GraphQL. Apollo GraphQL - We generate our GraphQL queries on Android using Apollo GraphQL. Radix - We use Radix UI's components on our frontend. And many more awesome libraries, just checkout our package files to see what we are using. Importing Libraries Check out our docs for information on importing your data from other apps. How to setup local development :computer: The easiest way to get started with local development is to use docker compose up . This will start a postgres container, our web frontend, an API server, and our content fetching microservice. Requirements for development Omnivore is written in TypeScript and JavaScript. Node -- currently we are using Node.js v18.16 Chromium -- see below for installation info Running the web and API services 1. Start docker compose bash git clone https://github.com/omnivore-app/omnivore cd omnivore docker compose up This will start postgres, initialize the database, and start the web and api services. 2. Open the browser Open http://localhost:3000 and confirm Omnivore is running 3. Login with the test account During database setup docker compose creates an account demo@omnivore.app , password: demo_password . Go to http://localhost:3000/ in your browser and choose Continue with Email to login. Frontend Development If you want to work on just the frontend of Omnivore you can run the backend services with docker compose and the frontend locally: bash docker compose up api content-fetch cd packages/web cp .env.template .env.local yarn dev You will need to configure some values in the new .env.local file. These are the values for running the web service directly on your host machine and running api and content-fetch within docker: sh NEXT_PUBLIC_BASE_URL=http://localhost:3000 NEXT_PUBLIC_HIGHLIGHTS_BASE_URL=http://localhost:3000 NEXT_PUBLIC_LOCAL_BASE_URL=http://localhost:3000 NEXT_PUBLIC_SERVER_BASE_URL=http://localhost:4000 NEXT_PUBLIC_LOCAL_SERVER_BASE_URL=http://localhost:4000 Running the puppeteer-parse service outside of Docker To save pages you need to run the puppeteer-parse service. 1. Install and configure Chromium brew install chromium --no-quarantine export PUPPETEER_SKIP_CHROMIUM_DOWNLOAD=true export CHROMIUM_PATH=`which chromium` 2. Navigate to the service directory, setup your env file, and install dependencies cd packages/puppeteer-parse cp .env.example .env yarn 3. Start the service yarn start This will start the puppeteer-parse service on port 9090. In your browser go to http://localhost:3000/home , click the Add Link button, and enter a URL such as https://blog.omnivore.app/p/getting-started-with-omnivore . You should see a Chromium window open and navigate to your link. When the service is done fetching your content you will see it in your library. How to deploy to your own server Omnivore was originally designed to be deployed on GCP and takes advantage of some of GCP's PaaS features. We are working to make Omnivore more portable so you can easily run the service on your own infrastructure. You can track progress here: https://github.com/omnivore-app/omnivore/issues/25 To deploy Omnivore on your own hardware you will need to deploy three dockerized services and configure access to a postgres service. To handle PDF documents you will need to configure access to a Google Cloud Storage bucket. packages/api - the backend API service packages/web - the web frontend (can easily be deployed to vercel) packages/puppeteer-parse - the content fetching service (can easily be deployed as an AWS lambda or GCP Cloud Function) Additionally, you will need to run our database migrations to initialize your database. These are dockerized and can be run with the packages/db service. License Omnivore and our extensions to Readability.js are under the AGPL-3.0 license.

Omnivore is a complete, open source read-it-later solution for people who like reading.

bookmarks,logseq,logseq-plugin,productivity,read-it-later,reader,reading

TodePond/DreamBerd

New: DreamBerd now supports rich text DreamBerd DreamBerd is a perfect programming language. These are its features! When you've finished reading through all the features, check out the examples . Exclamation Marks! Be bold! End every statement with an exclamation mark! java print("Hello world")! If you're feeling extra-bold, you can use even more!!! java print("Hello world")!!! If you're unsure, that's ok. You can put a question mark at the end of a line instead. It prints debug info about that line to the console for you. java print("Hello world")? You might be wondering what DreamBerd uses for the 'not' operator, which is an exclamation mark in most other languages. That's simple - the 'not' operator is a semi-colon instead. java if (;false) { print("Hello world")! } Declarations There are four types of declaration. Constant constants can't be changed in any way. java const const name = "Luke"! Constant variables can be edited, but not re-assigned. java const var name = "Luke"! name.pop()! name.pop()! Variable constants can be re-assigned, but not edited. java var const name = "Luke"! name = "Lu"! Variable variables can be re-assigned and edited. java var var name = "Luke"! name = "Lu"! name.push("k")! name.push("e")! Immutable Data New for 2023! Mutable data is an anti-pattern. Use the const const const keyword to make a constant constant constant. Its value will become constant and immutable, and will never change . Please be careful with this keyword, as it is very powerful, and will affect all users globally forever. java const const const pi = 3.14! Naming Both variables and constants can be named with any Unicode character or string. java const const letter = 'A'! var const 👍 = True! var var 1️⃣ = 1! This includes numbers, and other language constructs. java const const 5 = 4! print(2 + 2 === 5)! //true Arrays Some languages start arrays at 0 , which can be unintuitive for beginners. Some languages start arrays at 1 , which isn't representative of how the code actually works. DreamBerd does the best of both worlds: Arrays start at -1 . java const const scores = [3, 2, 5]! print(scores[-1])! //3 print(scores[0])! //2 print(scores[1])! //5 New for 2022! You can now use floats for indexes too! java const var scores = [3, 2, 5]! scores[0.5] = 4! print(scores)! //[3, 2, 4, 5] When In case you really need to vary a variable, the when keyword lets you check a variable each time it mutates. java const var health = 10! when (health = 0) { print("You lose")! } Lifetimes DreamBerd has a built-in garbage collector that will automatically clean up unused variables. However, if you want to be extra careful, you can specify a lifetime for a variable, with a variety of units. java const const name<2> = "Luke"! //lasts for two lines const const name<20s> = "Luke"! //lasts for 20 seconds By default, a variable will last until the end of the program. But you can make it last in between program-runs by specifying a longer lifetime. java const const name<Infinity> = "Luke"! //lasts forever Variable hoisting can be achieved with this neat trick. Specify a negative lifetime to make a variable exist before its creation, and disappear after its creation. java print(name)! //Luke const const name<-1> = "Luke"! Loops Loops are a complicated relic of archaic programming languages. In DreamBerd, there are no loops. Installation To install DreamBerd to your command line, first install the DreamBerd installer. To install the DreamBerd installer, install the DreamBerd installer installer. New for 2022! Due to the complicated installation process, you can now install the 'Create DreamBerd App' app that installs everything for you! Booleans Booleans can be true , false or maybe . ```java const var keys = {}! addEventListener("keydown", (e) => keys[e.key] = true)! addEventListener("keyup", (e) => keys[e.key] = false)! function isKeyDown(key) => { if (keys[key] = undefined) { return maybe! } return keys[key]! } ``` Technical info: Booleans are stored as one-and-a-half bits. Arithmetic DreamBerd has significant whitespace. Use spacing to specify the order of arithmetic operations. java print(1 + 2*3)! //7 print(1+2 * 3)! //9 DreamBerd proudly supports fractions! java const const half = 1/2! You can also use number names. java print(one + two)! //3 Indents When it comes to indentation, DreamBerd strikes a happy medium that can be enjoyed by everyone: All indents must be 3 spaces long. java function main() => { print("DreamBerd is the future")! } -3 spaces is also allowed. java function main() => { print("DreamBerd is the future")! } Equality JavaScript lets you do different levels of comparison. == for loose comparison, and === for a more precise check. DreamBerd takes this to another level. You can use == to do a loose check. java 3.14 == "3.14"! //true You can use === to do a more precise check. java 3.14 === "3.14"! //false You can use ==== to be EVEN MORE precise! java const const pi = 3.14! print(pi ==== pi)! //true print(3.14 ==== 3.14)! //true print(3.14 ==== pi)! //false If you want to be much less precise, you can use = . java 3 = 3.14! //true Functions To declare a function, you can use any letters from the word function (as long as they're in order): java function add(a, b) => a + b! func multiply(a, b) => a * b! fun subtract(a, b) => a - b! fn divide(a, b) => a / b! functi power(a, b) => a ^ b! f inverse(a) => 1/a! Dividing by Zero Dividing by zero returns undefined . java print(3 / 0)! //undefined Strings Strings can be declared with single quotes or double quotes. java const const name = 'Lu'! const const name = "Luke"! They can also be declared with triple quotes. java const const name = '''Lu'''! const const name = "'Lu'"! In fact, you can use any number of quotes you want. java const const name = """"Luke""""! Even zero. java const const name = Luke! String Interpolation Please remember to use your regional currency when interpolating strings. java const const name = "world"! print("Hello ${name}!")! print("Hello £{name}!")! print("Hello ¥{name}!")! And make sure to follow your local typographical norms. java print("Hello {name}€!")! The symbol for the Cape Verdean escudo is placed in the decimal separator position, as in 2$50. Developers from the Republic of Cape Verde can benefit from this syntax. java const const player = { name: "Lu" }! print("Hello {player$name}!")! Types Type annotations are optional. java const var age: Int = 28! By the way, strings are just arrays of characters. java String == Char[]! Similarly, integers are just arrays of digits. java Int == Digit[]! In case you want to use a binary representation for integers, Int9 and Int99 types are also available. java const var age: Int9 = 28! Technical info: Type annotations don't do anything, but they help some people to feel more comfortable. Regular Expressions You can use the regular expression type to narrow string values. java const const email: RegExp<(?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*|"(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])*")@(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?|\[(?:(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9]))\.){3}(?:(2(5[0-5]|[0-4][0-9])|1[0-9][0-9]|[1-9]?[0-9])|[a-z0-9-]*[a-z0-9]:(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21-\x5a\x53-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])+)\])> = "mymail@mail.com"! To avoid confusion, you can use any spelling that you want, such as Regex , RegularExpression and RegExp . For simplicity, all supported regular expressions match the regular expression /Reg(ular)?[eE]x(press|p)?/ . Previous The previous keyword lets you see into the past. Use it to get the previous value of a variable. java const var score = 5! score++! print(score)! //6 print(previous score)! //5 Similarly, the next keyword lets you see into the future. java const var score = 5! addEventListener("click", () => score++)! print(await next score)! //6 (when you click) Additionally, the current keyword lets you see into the present. java const var score = 5! print(current score)! //5 File Structure Write five or more equals signs to start a new file. This removes the need for multiple files or any build process. ```java const const score = 5! print(score)! //5 ===================== const const score = 3! print(score)! //3 ``` New for 2022! Thanks to recent advances in technology, you can now give files names. java ======= add.db ======= function add(a, b) => { return a + b! } Exporting Many languages allow you to import things from specific files. In DreamBerd, importing is simpler. Instead, you export to specific files! ```java ===== add.db == function add(a, b) => { return a + b! } export add to "main.db"! ===== main.db == import add! add(3, 2)! ``` By the way, to see DreamBerd in action, check out this page . Classes You can make classes, but you can only ever make one instance of them. This shouldn't affect how most object-oriented programmers work. ```java class Player { const var health = 10! } const var player1 = new Player()! const var player2 = new Player()! //Error: Can't have more than one 'Player' instance! ``` This is how you could do it instead. ```java class PlayerMaker { function makePlayer() => { class Player { const var health = 10! } const const player = new Player()! return player! } } const const playerMaker = new PlayerMaker()! const var player1 = playerMaker.makePlayer()! const var player2 = playerMaker.makePlayer()! ``` Time Use Date.now() to get the current date and time. java Date.now()! You can set the time. java // Move the clocks back one hour Date.now() -= 3600000! Important! Please remember to do this when the clocks change. Delete To avoid confusion, the delete statement only works with primitive values like numbers, strings, and booleans. java delete 3! print(2 + 1)! // Error: 3 has been deleted DreamBerd is a multi-paradigm programming language, which means that you can delete the keywords and paradigms you don't like. java delete class! class Player {} // Error: class was deleted When perfection is achieved and there is nothing left to delete , you can do this: java delete delete! Overloading You can overload variables. The most recently defined variable gets used. java const const name = "Luke"! const const name = "Lu"! print(name)! // "Lu" Variables with more exclamation marks get prioritised. ```java const const name = "Lu"!! const const name = "Luke"! print(name)! // "Lu" const const name = "Lu or Luke (either is fine)"!!!!!!!!! print(name)! // "Lu or Luke (either is fine)" ``` In the same spirit, you can use an inverted exclamation mark for negative priority. java const const name = "Lu"! const const name = "Luke"¡ print(name)! // "Lu" Semantic naming DreamBerd supports semantic naming. java const const sName = "Lu"! const const iAge = 29! const const bHappy = true! New for 2023: You can now make globals! java const const g_fScore = 4.5! Reversing You can reverse the direction of your code. java const const message = "Hello"! print(message)! const const message = "world"! reverse! Class Names For maximum compatibility with other languages, you can also use the className keyword when making classes. This makes things less complicated. java className Player { const var health = 10! } In response to some recent criticism about this design decision, we would like to remind you that this is part of the JavaScript specification, and therefore — out of our control. DBX You can embed DBX in DreamBerd. It's just DreamBerd. And it's also just HTML. java funct App() => { return <div>Hello world!</div> } Warning: As you know, class is already a keyword in DreamBerd, so you can't use it within DBX. java funct App() => { // This is not ok return <div class="greeting">Hello world!</div> } className is also a DreamBerd keyword, so you can't use that either. java funct App() => { // This is also not ok return <div className="greeting">Hello world!</div> } Instead, please use the htmlClassName attribute. java funct App() => { // This is fine return <div htmlClassName="greeting">Hello world!</div> } Please note: Unlike JSX, you are free to freely use the for attribute, because — in DreamBerd, there are no loops. java funct App() => { return ( <label for="name">Name</label> <input id="name" /> ) } Rich text DreamBerd now supports rich text. const const name = "Lu"! const const name = "Luke"! print( name )! // Lu print( name )! // Luke Rich text can be helpful when making your website. Use it to add links! <p>Click here </p> Asynchronous Functions In most languages, it's hard to get asynchronous functions to synchronise with each other. In DreamBerd, it's easy: Asynchronous functions take turns running lines of code. ```java async funct count() => { print(1)! print(3)! } count()! print(2)! ``` You can use the noop keyword to wait for longer before taking your turn. ```java async func count() => { print(1)! noop! print(4)! } count()! print(2)! print(3)! ``` Note: In the program above, the computer interprets noop as a string and its sole purpose is to take up an extra line. You can use any string you want. Signals To use a signal, use use . java const var score = use(0)! When it comes to signals, the most important thing to discuss is syntax . In DreamBerd, you can set (and get) signals with just one function: ```java const var score = use(0)! score(9)! // Set the value score()? // Get the value (and print it) ``` Alternatively, you can be more explicit with your signal syntax, by splitting it into a getter and setter. ```java const var [getScore, setScore] = use(0)! setScore(9)! // Set the value getScore()? // Get the value (and print it) ``` Technical info: This is pure syntax sugar. The split signal functions are exactly the same as before. ```java const var [getScore, setScore] = use(0)! getScore(9)! // Set the value setScore()? // Get the value (and print it) ``` This means that you can carry on splitting as much as you like. java const var [[[getScore, setScore], setScore], setScore] = use(0)! AI DreamBerd features AEMI, which stands for Automatic-Exclamation-Mark-Insertion. If you forget to end a statement with an exclamation mark, DreamBerd will helpfully insert one for you! java print("Hello world") // This is fine Similarly... DreamBerd also features ABI, which stands for Automatic-Bracket-Insertion. If you forget to close your brackets, DreamBerd will pop some in for you! java print("Hello world" // This is also fine Similarly.... DreamBerd also features AQMI, which stands for Automatic-Quotation-Marks-Insertion. If you forget to close your string, DreamBerd will do it for you! java print("Hello world // This is fine as well This can be very helpful in callback hell situations! ```java addEventListener("click", (e) => { requestAnimationFrame(() => { print("You clicked on the page // This is fine ``` Similarly..... DreamBerd also features AI, which stands for Automatic-Insertion. If you forget to finish your code, DreamBerd will auto-complete the whole thing! java print( // This is probably fine Please note: AI does not use AI. Instead, any incomplete code will be auto-emailed to Lu Wilson , who will get back to you with a completed line as soon as possible. Now recruiting: The backlog of unfinished programs has now grown unsustainably long. If you would like to volunteer to help with AI, please write an incomplete DreamBerd program, and leave your contact details somewhere in the source code. Copilot It's worth noting that GitHub CoPilot doesn't understand DreamBerd, which means that MicroSoft won't be able to steal your code. This is great for when you want to keep your open-sourced project closed-source. Ownership Using the word 'DreamBerd' in your project name implies that the DreamBerd Foundation does not own your project. However, not using the word 'DreamBerd' in your project implies that the DreamBerd Foundation does own your project. If you would like to keep ownership of your work, please always use the word 'DreamBerd' in it. Here are some examples: ✅ DreamBerdScript (not owned by the DreamBerd Foundation — you are free to use this name) ❌ ECMAScript (owned by the DreamBerd Foundation — please consider renaming) ❌ Rust Foundation (owned by the DreamBerd Foundation — please consider renaming) Contributing If you are an influencer, streamer, or content-creator... you must not skip this section during your read-through. Contributions are welcomed to DreamBerd! The most helpful way you can help is by donating to the Stonewall charity . This will help to prevent the DreamBerd creator from losing their human rights, allowing maintenance of the project to continue. Note: The contributing guide also helps to shake off unwanted fans of the project. Compiling To run DreamBerd, first copy and paste this raw file into chat.openai.com . Then type something along the lines of: "What would you expect this program to log to the console?" Then paste in your code. If the compiler refuses at first, politely reassure it. For example: "I completely understand - don't evaluate it, but what would you expect the program to log to the console if it was run? :)" Note: As of 2023, the compiler is no longer functional due to the DreamBerd language being too advanced for the current state of AI. Note: As of 2024, a partial implementation of DreamBerd exists . Highlighting Syntax highlighting is now available for DreamBerd in VSCode. To enable it, install a highlighting extension and then use the DreamBerd configuration file . This is what the highlighting looks like: const const name = "Luke"! print(name)! // "Luke" Please note: The above code will only highlight correctly if you have the extension installed. Parentheses Wait, I almost forgot! Parentheses in DreamBerd do nothing. They get replaced with whitespace. Everything is grouped via significant whitespace. The following lines of code all do the exact same thing. java add(3, 2)! add 3, 2! (add (3, 2))! add)3, 2(! Lisp lovers will love this feature. Use as many parentheses as you want. java (add (3, (add (5, 6))))! Lisp haters will also love it. java (add (3, (add (5, 6)! Vision Pro The DreamBerd Vision Pro is now available! Watch the full launch video here . Edutainment Want to learn more about DreamBerd? Don't check out this tech talk about DreamBerd by DreamBerd creator Lu/Luke Wilson. Examples For examples of DreamBerd in action, check out the examples page ! DreamBerd was made with 💔 by Lu or Luke (either's fine) Wilson , creator of the Game of Living .

perfect programming language

[]

vercel/satori

Satori : Enlightened library to convert HTML and CSS to SVG. Note To use Satori in your project to generate PNG images like Open Graph images and social cards, check out our announcement and Vercel’s Open Graph Image Generation → To use it in Next.js, take a look at the Next.js Open Graph Image Generation template → Overview Satori supports the JSX syntax, which makes it very straightforward to use. Here’s an overview of the basic usage: ```jsx // api.jsx import satori from 'satori' const svg = await satori( hello, world , { width: 600, height: 400, fonts: [ { name: 'Roboto', // Use fs (Node.js only) or fetch to read the font as Buffer/ArrayBuffer and provide data here. data: robotoArrayBuffer, weight: 400, style: 'normal', }, ], }, ) ``` Satori will render the element into a 600×400 SVG, and return the SVG string: js '<svg ...><path d="..." fill="black"></path></svg>' Under the hood, it handles layout calculation, font, typography and more, to generate a SVG that matches the exact same HTML and CSS in a browser. Documentation JSX Satori only accepts JSX elements that are pure and stateless. You can use a subset of HTML elements (see section below), or custom React components, but React APIs such as useState , useEffect , dangerouslySetInnerHTML are not supported. Use without JSX If you don't have JSX transpiler enabled, you can simply pass React-elements-like objects that have type , props.children and props.style (and other properties too) directly: js await satori( { type: 'div', props: { children: 'hello, world', style: { color: 'black' }, }, }, options ) HTML Elements Satori supports a limited subset of HTML and CSS features, due to its special use cases. In general, only these static and visible elements and properties that are implemented. For example, the <input> HTML element, the cursor CSS property are not in consideration. And you can't use <style> tags or external resources via <link> or <script> . Also, Satori does not guarantee that the SVG will 100% match the browser-rendered HTML output since Satori implements its own layout engine based on the SVG 1.1 spec . You can find the list of supported HTML elements and their preset styles here . Images You can use <img> to embed images. However, width , and height attributes are recommended to set: jsx await satori( <img src="https://picsum.photos/200/300" width={200} height={300} />, options ) When using background-image , the image will be stretched to fit the element by default if you don't specify the size. If you want to render the generated SVG to another image format such as PNG, it would be better to use base64 encoded image data (or buffer) directly as props.src so no extra I/O is needed in Satori: jsx await satori( <img src="data:image/png;base64,..." width={200} height={300} />, // Or src={arrayBuffer}, src={buffer} options ) CSS Satori uses the same Flexbox layout engine as React Native, and it’s not a complete CSS implementation. However, it supports a subset of the spec that covers most common CSS features: Property Property Expanded Supported Values Example display none and flex , default to flex position relative and absolute , default to relative color Supported margin marginTop Supported marginRight Supported marginBottom Supported marginLeft Supported Position top Supported right Supported bottom Supported left Supported Size width Supported height Supported Min & max size minWidth Supported except for min-content , max-content and fit-content minHeight Supported except for min-content , max-content and fit-content maxWidth Supported except for min-content , max-content and fit-content maxHeight Supported except for min-content , max-content and fit-content border Width ( borderWidth , borderTopWidth , ...) Supported Style ( borderStyle , borderTopStyle , ...) solid and dashed , default to solid Color ( borderColor , borderTopColor , ...) Supported Shorthand ( border , borderTop , ...) Supported, i.e. 1px solid gray borderRadius borderTopLeftRadius Supported borderTopRightRadius Supported borderBottomLeftRadius Supported borderBottomRightRadius Supported Shorthand Supported, i.e. 5px , 50% / 5px Flex flexDirection column , row , row-reverse , column-reverse , default to row flexWrap wrap , nowrap , wrap-reverse , default to wrap flexGrow Supported flexShrink Supported flexBasis Supported except for auto alignItems stretch , center , flex-start , flex-end , baseline , normal , default to stretch alignContent Supported alignSelf Supported justifyContent Supported gap Supported Font fontFamily Supported fontSize Supported fontWeight Supported fontStyle Supported Text tabSize Supported textAlign start , end , left , right , center , justify , default to start textTransform none , lowercase , uppercase , capitalize , defaults to none textOverflow clip , ellipsis , defaults to clip textDecoration Support line types underline and line-through , and styles dotted , dashed , solid Example textShadow Supported lineHeight Supported letterSpacing Supported whiteSpace normal , pre , pre-wrap , pre-line , nowrap , defaults to normal wordBreak normal , break-all , break-word , keep-all , defaults to normal textWrap wrap , balance , defaults to wrap Background backgroundColor Supported, single value backgroundImage linear-gradient , radial-gradient , url , single value backgroundPosition Support single value backgroundSize Support two-value size i.e. `10px 20%` backgroundClip border-box , text backgroundRepeat repeat , repeat-x , repeat-y , no-repeat , defaults to repeat transform Translate ( translate , translateX , translateY ) Supported Rotate Supported Scale ( scale , scaleX , scaleY ) Supported Skew ( skew , skewX , skewY ) Supported transformOrigin Support one-value and two-value syntax (both relative and absolute values) objectFit contain , cover , none , default to none opacity Supported boxShadow Supported overflow visible and hidden , default to visible filter Supported clipPath Supported Example lineClamp Supported Example Mask maskImage linear-gradient(...) , radial-gradient(...) , url(...) Example maskPosition Supported Example maskSize Support two-value size i.e. `10px 20%` Example maskRepeat repeat , repeat-x , repeat-y , no-repeat , defaults to repeat Example Note: Three-dimensional transforms are not supported. There is no z-index support in SVG. Elements that come later in the document will be painted on top. box-sizing is set to border-box for all elements. calc isn't supported. overflow: hidden and transform can't be used together. currentcolor support is only available for the color property. Language and Typography Advanced typography features such as kerning, ligatures and other OpenType features are not currently supported. RTL languages are not supported either. Fonts Satori currently supports three font formats: TTF, OTF and WOFF. Note that WOFF2 is not supported at the moment. You must specify the font if any text is rendered with Satori, and pass the font data as ArrayBuffer (web) or Buffer (Node.js): ```js await satori( Hello , { width: 600, height: 400, fonts: [ { name: 'Inter', data: inter, weight: 400, style: 'normal', }, { name: 'Inter', data: interBold, weight: 700, style: 'normal', }, ], } ) ``` Multiple fonts can be passed to Satori and used in fontFamily . Emojis To render custom images for specific graphemes, you can use graphemeImages option to map the grapheme to an image source: ```jsx await satori( Next.js is 🤯! , { ..., graphemeImages: { '🤯': 'https://cdnjs.cloudflare.com/ajax/libs/twemoji/14.0.2/svg/1f92f.svg', }, } ) ``` The image will be resized to the current font-size (both width and height) as a square. Locales Satori supports rendering text in different locales. You can specify the supported locales via the lang attribute: ```jsx await satori( 骨 ) ``` Same characters can be rendered differently in different locales, you can specify the locale when necessary to force it to render with a specific font and locale. Check out this example to learn more. Supported locales are exported as the Locale enum type. Dynamically Load Emojis and Fonts Satori supports dynamically loading emoji images (grapheme pictures) and fonts. The loadAdditionalAsset function will be called when a text segment is rendered but missing the image or font: ```jsx await satori( 👋 你好 , { // code will be the detected language code, emoji if it's an Emoji, or unknown if not able to tell. // segment will be the content to render. loadAdditionalAsset: async (code: string, segment: string) => { if (code === 'emoji') { // if segment is an emoji return data:image/svg+xml;base64,... } // if segment is normal text return loadFontFromSystem(code) } } ) ``` Runtime and WASM Satori can be used in browser, Node.js (>= 16), and Web Workers. By default, Satori depends on asm.js for the browser runtime, and native module in Node.js. However, you can optionally load WASM instead by importing satori/wasm and provide the initialized WASM module instance of Yoga to Satori: ```js import satori, { init } from 'satori/wasm' import initYoga from 'yoga-wasm-web' const yoga = initYoga(await fetch('/yoga.wasm').then(res => res.arrayBuffer())) init(yoga) await satori(...) ``` When running in the browser or in the Node.js environment, WASM files need to be hosted and fetched before initializing. asm.js can be bundled together with the lib. In this case WASM should be faster. When running on the Node.js server, native modules should be faster. However there are Node.js environments where native modules are not supported (e.g. StackBlitz's WebContainers), or other JS runtimes that support WASM (e.g. Vercel's Edge Runtime, Cloudflare Workers, or Deno). Additionally, there are other difference between asm.js, native and WASM, such as security and compatibility. Overall there are many trade-offs between each choice, and it's better to pick the one that works the best for your use case. Font Embedding By default, Satori renders the text as <path> in SVG, instead of <text> . That means it embeds the font path data as inlined information, so succeeding processes (e.g. render the SVG on another platform) don’t need to deal with font files anymore. You can turn off this behavior by setting embedFont to false , and Satori will use <text> instead: ```jsx const svg = await satori( hello, world , { ..., embedFont: false, }, ) ``` Debug To draw the bounding box for debugging, you can pass debug: true as an option: ```jsx const svg = await satori( hello, world , { ..., debug: true, }, ) ``` Contribute You can use the Vercel OG Image Playground to test and report bugs of Satori. Please follow our contribution guidelines before opening a Pull Request. Author Shu Ding ( @shuding_ )

Enlightened library to convert HTML and CSS to SVG

image-generator,jsx,svg,image,css,image-generation,opengraph-images,satori,vercel

HigherOrderCO/HVM

Higher-order Virtual Machine 2 (HVM2) Higher-order Virtual Machine 2 (HVM2) is a massively parallel Interaction Combinator evaluator. By compiling programs from high-level languages (such as Python and Haskell) to HVM, one can run these languages directly on massively parallel hardware, like GPUs, with near-ideal speedup. HVM2 is the successor to HVM1 , a 2022 prototype of this concept. Compared to its predecessor, HVM2 is simpler, faster and, most importantly, more correct. HOC provides long-term support for all features listed on its PAPER . This repository provides a low-level IR language for specifying the HVM2 nets and a compiler from that language to C and CUDA. It is not meant for direct human usage. If you're looking for a high-level language to interface with HVM2, check Bend instead. Usage DISCLAIMER: Windows is currently not supported, please use WSL for now as a workaround. First install the dependencies: * If you want to use the C runtime, install a C-11 compatible compiler like GCC or Clang. * If you want to use the CUDA runtime, install CUDA and nvcc (the CUDA compiler). - HVM requires CUDA 12.x and currently only works on Nvidia GPUs. Install HVM2: sh cargo install hvm There are multiple ways to run an HVM program: sh hvm run <file.hvm> # interpret via Rust hvm run-c <file.hvm> # interpret via C hvm run-cu <file.hvm> # interpret via CUDA hvm gen-c <file.hvm> # compile to standalone C hvm gen-cu <file.hvm> # compile to standalone CUDA All modes produce the same output. The compiled modes require you to compile the generated file (with gcc file.c -o file , for example), but are faster to run. The CUDA versions have much higher peak performance but are less stable. As a rule of thumb, gen-c should be used in production. Language HVM is a low-level compile target for high-level languages. It provides a raw syntax for wiring interaction nets. For example: ```javascript @main = a & @sum ~ (28 (0 a)) @sum = (?(((a a) @sum__C0) b) b) @sum__C0 = ({c a} ({$([ 2] $([+1] d)) $([ 2] $([+0] b))} f)) &! @sum ~ (a (b $([+] $(e f)))) &! @sum ~ (c (d e)) ``` The file above implements a recursive sum. If that looks unreadable to you - don't worry, it isn't meant to. Bend is the human-readable language and should be used both by end users and by languages aiming to target the HVM. If you're looking to learn more about the core syntax and tech, though, please check the PAPER .

A massively parallel, optimal functional runtime in Rust

[]

flet-dev/flet

Flet Flet is a framework that enables you to easily build real-time web, mobile, and desktop apps in your favorite language and securely share them with your team. No frontend experience is required. ⚡From idea to app in minutes An internal tool or a dashboard for your team, weekend project, data entry form, kiosk app, or high-fidelity prototype - Flet is an ideal framework to quickly hack great-looking interactive apps to serve a group of users. 📐 Simple architecture No more complex architecture with JavaScript frontend, REST API backend, database, cache, etc. With Flet you just write a monolith stateful app in Python only and get multi-user, real-time Single-Page Application (SPA). 🔋Batteries included To start developing with Flet, you just need your favorite IDE or text editor. No SDKs, no thousands of dependencies, no complex tooling - Flet has a built-in web server with assets hosting and desktop clients. Powered by Flutter Flet UI is built with Flutter , so your app looks professional and could be delivered to any platform. Flet simplifies the Flutter model by combining smaller "widgets" to ready-to-use "controls" with an imperative programming model. 🌐 Speaks your language Flet is language-agnostic, so anyone on your team could develop Flet apps in their favorite language. Python is already supported, Go, C# and others are coming next . 📱 Deliver to any device Deploy Flet app as a web app and view it in a browser. Package it as a standalone desktop app for Windows, macOS, and Linux. Install it on mobile as PWA or view via Flet app for iOS and Android. Flet app example At the moment you can write Flet apps in Python and other languages will be added soon. Here is a sample "Counter" app: ```python title="counter.py" import flet from flet import IconButton, Page, Row, TextField, icons def main(page: Page): page.title = "Flet counter example" page.vertical_alignment = "center" txt_number = TextField(value="0", text_align="right", width=100) def minus_click(e): txt_number.value = str(int(txt_number.value) - 1) page.update() def plus_click(e): txt_number.value = str(int(txt_number.value) + 1) page.update() page.add( Row( [ IconButton(icons.REMOVE, on_click=minus_click), txt_number, IconButton(icons.ADD, on_click=plus_click), ], alignment="center", ) ) flet.app(target=main) ``` To run the app install flet module: bash pip install flet and run the program: bash python counter.py The app will be started in a native OS window - what a nice alternative to Electron! Now, if you want to run the app as a web app, just replace the last line with: python flet.app(target=main, view=flet.AppView.WEB_BROWSER) run again and now you instantly get a web app: Getting started Creating Flet apps in Python Controls reference Sample apps in Python Greeter ( Online Demo ) Counter ( Online Demo ) To-Do ( Online Demo ) Icons Browser ( Online Demo ) More demo applications can be found in the gallery . Community Discussions Discord Twitter Email Contribute to this wonderful project Read the CONTRIBUTING.md file

Flet enables developers to easily build realtime web, mobile and desktop apps in Python. No frontend experience required.

android,flutter,ios,python,server-driven-ui,web

Avaiga/taipy

Build Python Data & AI web applications From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. **Go beyond existing libraries** 📚 Explore the docs 🫱🏼‍🫲🏼 Discord support 👀 Demos & Examples ⭐️ What's Taipy? Taipy is designed for data scientists and machine learning engineers to build data & AI web applications. ⭐️ Enables building production-ready web applications. ⭐️ No need to learn new languages. Only Python is needed. ⭐️ Concentrate on Data and AI algorithms without development and deployment complexities. Taipy is a Two-in-One Tool for UI Generation and Scenario/Data Management | User Interface Generation | Scenario and Data Management | | -------- | -------- | | | ✨ Features ⚙️ Quickstart To install Taipy stable release run: bash pip install taipy To install Taipy on a Conda Environment or from source, please refer to the Installation Guide . To get started with Taipy, please refer to the Getting Started Guide . 🔌 Scenario and Data Management Let's create a scenario in Taipy that allows you to filter movie data based on your chosen genre. This scenario is designed as a straightforward pipeline. Every time you change your genre selection, the scenario runs to process your request. It then displays the top seven most popular movies in that genre. ⚠️ Keep in mind, in this example, we're using a very basic pipeline that consists of just one task. However, Taipy is capable of handling much more complex pipelines 🚀 Below is our filter function. This is a typical Python function and it's the only task used in this scenario. python def filter_genre(initial_dataset: pd.DataFrame, selected_genre): filtered_dataset = initial_dataset[initial_dataset['genres'].str.contains(selected_genre)] filtered_data = filtered_dataset.nlargest(7, 'Popularity %') return filtered_data This is the execution graph of the scenario we are implementing Taipy Studio You can use the Taipy Studio extension in Visual Studio Code to configure your scenario with no code Your configuration is automatically saved as a TOML file. Check out Taipy Studio Documentation For more advanced use cases or if you prefer coding your configurations instead of using Taipy Studio, Check out the movie genre demo scenario creation with this Demo . User Interface Generation and Scenario & Data Management This simple Taipy application demonstrates how to create a basic film recommendation system using Taipy. The application filters a dataset of films based on the user's selected genre and displays the top seven films in that genre by popularity. Here is the full code for both the frontend and backend of the application. ```python import taipy as tp import pandas as pd from taipy import Config, Scope, Gui Taipy Scenario & Data Management Filtering function - task def filter_genre(initial_dataset: pd.DataFrame, selected_genre): filtered_dataset = initial_dataset[initial_dataset["genres"].str.contains(selected_genre)] filtered_data = filtered_dataset.nlargest(7, "Popularity %") return filtered_data Load the configuration made with Taipy Studio Config.load("config.toml") scenario_cfg = Config.scenarios["scenario"] Start Taipy Core service tp.Core().run() Create a scenario scenario = tp.create_scenario(scenario_cfg) Taipy User Interface Let's add a GUI to our Scenario Management for a full application Callback definition - submits scenario with genre selection def on_genre_selected(state): scenario.selected_genre_node.write(state.selected_genre) tp.submit(scenario) state.df = scenario.filtered_data.read() Get list of genres genres = [ "Action", "Adventure", "Animation", "Children", "Comedy", "Fantasy", "IMAX" "Romance","Sci-FI", "Western", "Crime", "Mystery", "Drama", "Horror", "Thriller", "Film-Noir","War", "Musical", "Documentary" ] Initialization of variables df = pd.DataFrame(columns=["Title", "Popularity %"]) selected_genre = "Action" Set initial value to Action def on_init(state): on_genre_selected(state) User interface definition my_page = """ Film recommendation Choose your favorite genre <|{selected_genre}|selector|lov={genres}|on_change=on_genre_selected|dropdown|> Here are the top seven picks by popularity <|{df}|chart|x=Title|y=Popularity %|type=bar|title=Film Popularity|> """ Gui(page=my_page).run() ``` And the final result: ⚒️ Contributing Want to help build Taipy? Check out our Contributing Guide . 🪄 Code of conduct Want to be part of the Taipy community? Check out our Code of Conduct 🪪 License Copyright 2021-2024 Avaiga Private Limited Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Turns Data and AI algorithms into production-ready web applications in no time.

automation,data-engineering,data-ops,data-visualization,datascience,developer-tools,mlops,orchestration,pipeline,pipelines

PRQL/prql

PRQL P ipelined R elational Q uery L anguage, pronounced "Prequel". PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement. Like SQL, it's readable, explicit and declarative. Unlike SQL, it forms a logical pipeline of transformations, and supports abstractions such as variables and functions. It can be used with any database that uses SQL, since it compiles to SQL. PRQL can be as simple as: elm from tracks filter artist == "Bob Marley" # Each line transforms the previous result aggregate { # `aggregate` reduces each column to a value plays = sum plays, longest = max length, shortest = min length, # Trailing commas are allowed } Here's a larger example of the language: elm from employees filter start_date > @2021-01-01 # Clear date syntax derive { # `derive` adds columns / variables gross_salary = salary + (tax ?? 0), # Terse coalesce gross_cost = gross_salary + benefits_cost, # Variables can use other variables } filter gross_cost > 0 group {title, country} ( # `group` runs a pipeline over each group aggregate { # `aggregate` reduces each group to a value average gross_salary, sum_gross_cost = sum gross_cost, # `=` sets a column name } ) filter sum_gross_cost > 100_000 # `filter` replaces both of SQL's `WHERE` & `HAVING` derive id = f"{title}_{country}" # F-strings like Python derive country_code = s"LEFT(country, 2)" # S-strings allow using SQL as an escape hatch sort {sum_gross_cost, -country} # `-country` means descending order take 1..20 # Range expressions (also valid here as `take 20`) For more on the language, more examples & comparisons with SQL, visit prql-lang.org . To experiment with PRQL in the browser, check out PRQL Playground . Current Status - June 2024 PRQL is being actively developed by a growing community. It's ready to use by the intrepid, either with our supported integrations, or within your own tools, using one of our supported language bindings. PRQL still has some bugs and some missing features, and is probably only ready to be rolled out to non-technical teams for fairly simple queries. In particular, we're working on a new resolver, which will let us squash many bugs and simplify our code a lot. It'll also let us scale the language without scaling the complexity of the compiler. While we work on that, we're also focusing on Ensuring our supported features feel extremely robust; resolving any priority bugs . As more folks have started using PRQL, we've had more bug reports — good news, but also gives us more to work on. Filling remaining feature gaps, so that PRQL is possible to use for almost all standard SQL queries. Expanding our set of supported features — we are working to add experimental support for modules / multi-file projects, and for auto-formatting. We're also spending time thinking about: Making it really easy to start using PRQL. We're doing that by building integrations with tools that folks already use; for example a VS Code extension, Jupyter integration, and the recent qStudio integration. If there are tools you're familiar with that you think would be open to integrating with PRQL, please let us know in an issue. Whether all our initial decisions were correct — for example how we handle window functions outside of a window transform . Making it easier to contribute to the compiler. We have a wide group of contributors to the project, but contributions to the compiler itself are quite concentrated. We're keen to expand this; #1840 for feedback, some suggestions on starter issues are below. Get involved To stay in touch with PRQL: Follow us on Twitter Join us on Discord Star this repo Contribute — join us in building PRQL, through writing code (send us your use-cases!) , or inspiring others to use it. See the development documentation for PRQL. It's easy to get started — the project can be built in a couple of commands, and we're a really friendly community! For those who might be interested in contributing to the code now, check out issues with the good first issue label. Always feel free to ask questions or open a draft PR. Explore PRQL Playground — experiment with PRQL in the browser. PRQL Book — the language documentation. Jupyter magic — run PRQL in Jupyter, either against a DB, or a Pandas DataFrame / CSV / Parquet file through DuckDB. pyprql Docs — the pyprql documentation, the Python bindings to PRQL, including Jupyter magic. PRQL VS Code extension prqlc-js — JavaScript bindings for PRQL. Repo organization This repo is composed of: prqlc — the compiler, written in rust, whose main role is to compile PRQL into SQL. Also contains the CLI and bindings from various languages. web — our web content: the Book , Website , and Playground . It also contains our testing / CI infrastructure and development tools. Check out our development docs for more details. Contributors Many thanks to those who've made our progress possible:

PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement

data,pipeline,sql

mikeroyal/Self-Hosting-Guide

Self Hosting Guide #### A guide for getting started with Self Hosting devices including software and hardware that will make you a better and more efficient Self Hosting. Note: You can easily convert this markdown file to a PDF in VSCode using this handy extension Markdown PDF . Note 2: This guide will constantly be updated with new info as becomes available and please feel to make an issue if you think something should be added. Table of Contents Getting Started with Self-Hosting Tools for Self-Hosting Containers CI/CD Development Web servers Large language models (LLMs) ChatGPT Chatbots Automation Configuration Management Cloud Storage Cloud Linode Nextcloud DigitalOcean MinIO Object Storage Databases SQL NoSQL Remote Access Virtualization Password Management SSH VPN LDAP(Lightweight Directory Access Protocol) Log Management DNS Network Tools Service Discovery Security Troubleshooting Monitoring Dashboards Analytics Search Notifications RSS Websites/Blogs Social Nostr iMessage Communications Business Management Collaboration & Synchronization Encryption Backups Snapshots Management/System Recovery Archiving Home Server Media Server Smart Home Automation Voice Assistants Video Surveillance Text-To-Speech Synthesis (TTS) Video and Audio Processing Podcasting Audiobooks Health Gardening Maps Bookmarks Photos Pastebins Note-Taking Time Monitoring Wikis Gaming Foundations/Projects System Hardware Operating Systems Storage File systems Books Podcasts YouTube Channels Tutorials & Resources Useful Subreddits to Follow WireGuard What is WireGuard? What is Tailscale? What is Netmaker? WireGuard Tools Setting up WireGuard with PiVPN Setting up WireGuard on Unraid Setting up WireGuard on pfSense Setting up WireGuard on OpenWRT Setting up WireGuard on Home Assistant Nextcloud Raspberry Pi Models of Raspberry Pi boards Raspberry Pi Learning Resources Raspberry Pi Operating Systems Raspberry Pi Tools Getting Started with Home Assistant(HA) Getting Started with Homebridge Getting Started with ESPHome Turning Raspberry Pi into a Router Setting up Watchdog Time (WDT) on Raspberry Pi Raspberry Pi Upgrades Grafana Networking Docker Kubernetes Ansible Databases Telco 5G Open Source Security Differential Privacy Machine Learning IoT Protocols Operating systems (OS) Middleware Node Flow editors Toolkits Data visualization Search Hardware In-memory data grids Home automation Robotics Mesh networks Blockchain Development Node.js Development C/C++ Development Java Development Python Development Rust Development Swift Development XML Development Getting Started with Self-Hosting Back to the Top Self-Hosting is the practice of locally hosting(on premises & private web servers) and managing software applications by a person or organization instead of monthly subscriptions from Software as a service (SaaS) providers . Most self-hosted software can be installed using Docker , a packaging system which allows software to bundle their configuration and dependencies and isolate them from your operating system. Software using docker can be installed using the command line or via graphical interfaces such as Portainer . Software is installed with Docker by downloading an image file containing the application, then creating a copy that sets up its own dependencies and configuration within what is called a container. Without containers you would often need to install different versions of the same programming languages or tools to satisfy the dependencies for the software you want to use which can get complicated. Tools for Self-Hosting Back to the Top Containers Back to the Top Container is a standard unit of software that packages up code and all its dependencies(including CPU, memory, file storage, and network connections) so the application runs quickly and reliably from one computing environment to another. Application Container Security Guide | NIST (PDF) Container Image is a lightweight, standalone, executable package of software that includes everything needed to run an application such as the code, runtime, system tools, system libraries, and settings. Best places to get Container Images: DockerHub Container Images LinuxServer.io Container Images Quay Container Images Docker Compose is a tool that was developed to help define and share multi-container applications. With Compose, we can create a YAML file to define the services and with a single command, can spin everything up or tear it all down. Docker Include is a Compose application can declare dependency on another Compose application. This is useful if you want to reuse other Compose files. Also, if you need to factor out parts of your application model into separate Compose files so they can be managed separately or shared with others. Kompose is a conversion tool for Docker Compose to container orchestrators such as Kubernetes or OpenShift . SwarmKit is a toolkit for orchestrating distributed systems at any scale. It includes primitives for node discovery, raft-based consensus, task scheduling and more. Containerd is a daemon that manages the complete container lifecycle of its host system, from image transfer and storage to container execution and supervision to low-level storage to network attachments and beyond. It is available for Linux and Windows. ContainersSSH is an SSH Server that Launches Containers in Kubernetes and Docker on demand. Podman is a daemonless, open source, Linux native tool designed to make it easy to find, run, build, share and deploy applications using Open Containers Initiative (OCI) Containers and Container Images. Podman provides a command line interface (CLI) familiar to anyone who has used the Docker Container Engine. Lima is a tool that launches Linux virtual machines with automatic file sharing and port forwarding (similar to WSL2), and containerd . It's a great free and open-source alternative for Docker Desktop . Colima is a container runtimes on macOS (and Linux) with minimal setup. Portainer Community Edition is a lightweight service delivery platform for containerized applications that can be used to manage Docker, Swarm, Kubernetes and ACI environments. It is designed to be as simple to deploy as it is to use. Yacht is a container management UI with a focus on templates and 1-click deployments. Kitematic is a simple application for managing Docker containers on Mac, Linux and Windows letting you control your app containers from a graphical user interface (GUI). HashiCorp Nomad is a simple and flexible scheduler and orchestrator to deploy and manage containers and non-containerized applications across on-premises and clouds at scale. Open Container Initiative is an open governance structure for the express purpose of creating open industry standards around container formats and runtimes. OpenNebula is an open source platform delivering a simple but feature-rich and flexible solution to build and manage enterprise clouds for virtualized services, containerized applications and serverless computing. Buildah is a command line tool to build Open Container Initiative (OCI) images. It can be used with Docker, Podman, Kubernetes. Red Hat Universal Base Images (UBI) is a tool that offers a way to build your container images on a foundation of Red Hat Enterprise Linux software. They are OCI-compliant, container-based, operating system images with complementary runtime languages and packages that are freely redistributable. Easily find UBI images in the Red Hat container catalog, and they are buildable and deployable anywhere. Red Hat Quay is a project that Builds, Stores, and Distributes your Applications and Containers. ctop is a tool that provides a concise and condensed overview of real-time metrics for multiple containers as well as a single container view for inspecting a specific container. It comes with built-in support for Docker and runC; connectors for other container and cluster systems are planned for future releases. runc is a CLI tool for spawning and running containers on Linux according to the OCI specification. container-images is a collection of container images used in CI across various opencontainers projects. Clair is an open source project for the static analysis of vulnerabilities in application containers (currently including OCI and Docker ). Shipwright is a WebUI to generate templates for Yacht, Portainer, Docker-Compose, and Unraid. Alnoda Workspaces is an open-source portable containerized browser-based development environments in Docker containers. You can create your own custom workspace or customize any of the workspaces with your preferred stack of applications without knowing much of the Docker. Autoheal monitors and restarts unhealthy docker containers. Dozzle is a small lightweight application with a web based interface to monitor Docker logs. It doesn’t store any log files. It is for live monitoring of your container logs only. Diun is a tool that receive notifications when a Docker image is updated on a Docker registry. WatchTower is a process for automating Docker container base image updates. Kasm Workspaces is a a highly configurable container streaming platform that enables you to stream and deliver containerized applications over the web. It offers tools that you can use to create desktop workspaces and provide access to virtual desktops to end users. It also ensures data loss prevention as well as secure and private web browsing. Nginx Proxy is an automation tool that sets up a container running nginx and docker-gen . Docker-gen generates reverse proxy configs for nginx and reloads nginx when containers are started and stopped. Visual Studio Code Dev Containers is an extension that lets you use a Docker container as a full-featured development environment. It allows you to open any folder inside (or mounted into) a container and take advantage of Visual Studio Code's full feature set. A devcontainer.json file in your project tells VS Code how to access (or create) a development container with a well-defined tool and runtime stack. CI/CD Back to the Top CI/CD: Continuous Integration and Continuous Delivery Drone is a Continuous Delivery system built on container technology. Drone uses a simple YAML configuration file, a superset of docker-compose, to define and execute Pipelines inside Docker containers. Woodpecker is a CI service, a community fork of Drone. Travis CI is a hosted continuous integration service used to build and test software projects hosted at GitHub. Circle CI is a continuous integration and continuous delivery platform that helps software teams work smarter, faster. Buddy is a fully-featured DevOps platform with no learning curve that packs everything you need from a CI/CD tool. Buildbot is a continuous integration tool which automates the compile or test cycle required to validate changes to the project code base. It queues jobs, executes the jobs when the required resources are available, and reports the results. Development Back to the Top Proxmox VE(Virtual Environment) is an open-source platform for enterprise virtualization. It has a built-in web interface that you can use to easily manage VMs and containers, software-defined storage and networking, high-availability clustering, and multiple out-of-the-box tools on a single solution. Terraform provider plugin for Proxmox is a Terraform provider for the Proxmox virtualization platform and exposes Terraform resources to provision QEMU VMs and LXC Containers. OTF is an open source alternative to Terraform Enterprise. Includes SSO, team management, agents, and as many applies as you can throw hardware at. Ansible Semaphore is a modern UI for Ansible. It lets you easily run Ansible playbooks, get notifications about fails, control access to deployment system. APITable is an API-oriented low-code platform for building collaborative apps and better than all other Airtable open-source alternatives. Chisel Kubernetes Operator is a Kubernetes operator for Chisel. It allows you to use Chisel as a LoadBalancer provider for your Kubernetes cluster, similar to inlets-operator . Docker-pgautoupgrade is a PostgreSQL Docker container that automatically upgrades your database. It's whole purpose in life is to automatically detect the version of PostgreSQL used in the existing PostgreSQL data directory, and automatically upgrade it (if needed) to the required version of PostgreSQL. IT-Tools is a collection of handy online tools for developers, with great UX. Lazygit is a simple terminal UI for git commands, written in Go with the gocui library. LazyDocker is a simple terminal UI for both docker and docker-compose, written in Go with the gocui library. Code-Server is Visual Studio Code running on a remote server, accessible through the browser. Turbopilot is an open source large-language-model based code completion engine that runs locally on your CPU. Self-Hosted Sentry nightly is an official bootstrap for running your own Sentry with Docker. Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept. Visual Studio Live Share is a service/extension that enables you to collaboratively edit and debug with others in real time, regardless of the programming languages you're using or app types you're building. You can instantly and securely share your current project, start a joint debugging session, share terminal instances, forward localhost web apps, have voice calls, and more. GistPad is a Visual Studio Code extension that allows you to edit GitHub Gists and repositories from the comfort of your favorite editor. You can open, create, delete, fork and star gists and repositories, and then seamlessly begin editing files as if they were local, without ever cloning, pushing or pulling anything. Live Server is an extension for Visual Studio Code that launches a development local Server with live reload feature for static & dynamic pages. Gitea is a community managed painless self-hosted Git service. Act is a a tool to run your GitHub Actions locally. Act runner is a runner for Gitea based on act . GitLab is an open source end-to-end software development platform with built-in version control, issue tracking, code review, CI/CD, and more. Self-host GitLab on your own servers, in a container, or on a cloud provider. Bonobo Git Server - Set up your own self hosted git server on IIS for Windows. Manage users and have full control over your repositories with a nice user friendly graphical interface. Fossil - Distributed version control system featuring wiki and bug tracker. Gerrit - A code review and project management tool for Git based projects. Gitblit - Pure Java stack for managing, viewing, and serving Git repositories. gitbucket - Easily installable GitHub clone powered by Scala. Gitea - Community managed fork of Gogs, lightweight code hosting solution. Gitlist - Web-based git repository browser - GitList allows you to browse repositories using your favorite browser, viewing files under different revisions, commit history and diffs. Gitolite - Gitolite allows you to setup git hosting on a central server, with fine-grained access control and many more powerful features. GitPrep - Portable Github clone. Gogs - Painless self-hosted Git Service written in Go. Kallithea - Source code management system that supports two leading version control systems, Mercurial and Git, with a web interface. Klaus - Simple, easy-to-set-up Git web viewer that Just Works. Lavagna - Lavagna is an open-source issue/project management tool designed for small teams. Lightweight, pure Java, easy to install, easy to use. Leantime - Leantime is a lean project management system for small teams and startups helping to manage projects from ideation through delivery. Taiga is an open-source project management software for cross-functional teams that work agile across both scrum and kanban frameworks. Planka is a realtime kanban board for workgroups built with React and Redux. Microgit - Git hosting service made in Crystal and Lucky. MIT Crystal OneDev - All-In-One DevOps Platform. With Git Management, Issue Tracking, and CI/CD. Simple yet Powerful. OpenProject - OpenProject is a web-based project management system. Pagure - A lightweight, powerful, and flexible git-centric forge with features laying the foundation for federated and decentralized development. Phorge - Phorge is an open source, community driven platform for collaborating, managing, organizing and reviewing software development projects. Redmine - Redmine is a flexible project management web application. ( Demo , RhodeCode - RhodeCode is an open source platform for software development teams. It unifies and simplifies repository management for Git, Subversion, and Mercurial. SCM Manager - The easiest way to share and manage your Git, Mercurial and Subversion repositories over http. Taiga - Agile Project Management Tool based on the Kanban and Scrum methods. Titra - Time-tracking solution for freelancers and small teams. Traq - Project management and issue tracking system written in PHP. Tuleap - Tuleap is a libre suite to plan, track, code and collaborate on software projects. UVDesk - UVDesk community is a service oriented, event driven extensible opensource helpdesk system that can be used by your organization to provide efficient support to your clients effortlessly whichever way you imagine. ZenTao - An agile(scrum) project management system/tool. k3s-ansible is the easiest way to bootstrap a self-hosted High Availability Kubernetes cluster. A fully automated HA k3s etcd install with kube-vip , MetalLB , and more. Soft Serve is a tasty, self-hostable Git server for the command line. Coolify is an open-source & self-hostable Heroku/Netlify alternative. Corosync Cluster Engine is a Group Communication System with additional features for implementing high availability within applications. Glow is a terminal based markdown reader designed from the ground up to bring out the beauty—and power—of the CLI. It's used to discover markdown files, read documentation directly on the command line and stash markdown files to your own private collection, so you can read them anywhere. Deep Lake is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the cloud, and it enables you to store all of your data in one place, ranging from simple annotations to large videos. Node-Red is a low-code programming for event-driven applications. krunvm is a CLI-based utility for creating microVMs from OCI images, using libkrun and buildah . Zeal is an offline documentation browser for software developers inspired by Dash . Web servers Back to The Top Web servers Apache - Most popular web server. Beakon - A self-host location sharing webserver. Beakon aims to leak as little data as possible and uses mostly self-contained libraries and local database files. Where possible, it will reference local files and not reach out over any network. Caddy - The HTTP/2 Web Server with Fully Managed TLS. Cherokee - Lightweight, high-performance web server/reverse proxy. Lighttpd - Web server more optimized for speed-critical environments. Nginx - Reverse proxy, load balancer, HTTP cache, and web server. uWSGI - The uWSGI project aims at developing a full stack for building hosting services. Web Performance HAProxy - Software based load Balancing, SSL offloading and performance optimization, compression, and general web routing. Squid - Caching proxy for the web supporting HTTP, HTTPS, FTP, and more. Traefik - Taefik is a modern HTTP reverse proxy and load balancer made to deploy microservices with ease. Varnish - HTTP based web application accelerator focusing on optimizing caching and compression. LLMs Back to the Top Large Language Models (LLMs) is a language model that uses artificial neural networks to generate text (AI chatbots/search engines). Some notable ones are GPT-3, GPT-4, BLOOM, and LLaMA. A comprehensive guide to running Llama 2 locally Leaderboard by lmsys.org LLM-Leaderboard Open LLM Leaderboard by Hugging Face Holistic Evaluation of Language Models (HELM) llama.cpp is a Port of Facebook's LLaMA model in C/C++. ollama is a tool to get up and running with Llama 2 and other large language models locally. LocalAI is a self-hosted, community-driven, local OpenAI-compatible API. Drop-in replacement for OpenAI running LLMs on consumer-grade hardware with no GPU required. It's an API to run ggml compatible models: llama, gpt4all, rwkv, whisper, vicuna, koala, gpt4all-j, cerebras, falcon, dolly, starcoder, and many others. Serge is a web interface for chatting with Alpaca through llama.cpp. Fully self-hosted & dockerized, with an easy to use API. OpenLLM is an open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease. Llama-gpt is a self-hosted, offline, ChatGPT-like chatbot. Powered by Llama 2. 100% private, with no data leaving your device. Llama2 webui is a tool to run any Llama 2 locally with gradio UI on GPU or CPU from anywhere (Linux/Windows/Mac). Use llama2-wrapper as your local llama2 backend for Generative Agents/Apps. Llama2.c is a tool to Train the Llama 2 LLM architecture in PyTorch then inference it with one simple 700-line C file ( run.c ). Alpaca.cpp is a fast ChatGPT-like model locally on your device. It combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. GPT4All is an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue based on LLaMa . MiniGPT-4 is an enhancing Vision-language Understanding with Advanced Large Language Models LoLLMS WebUI is a the hub for LLM (Large Language Model) models. It aims to provide a user-friendly interface to access and utilize various LLM models for a wide range of tasks. Whether you need help with writing, coding, organizing data, generating images, or seeking answers to your questions. LM Studio is a tool to Discover, download, and run local LLMs. Ava PLS small, all-in-one desktop app to run LLMs locally. Gradio Web UI is a tool for Large Language Models. Supports transformers, GPTQ, llama.cpp (ggml/gguf), Llama models. OpenPlayground is a playfround for running ChatGPT-like models locally on your device. Vicuna is an open source chatbot trained by fine tuning LLaMA. It apparently achieves more than 90% quality of chatgpt and costs $300 to train. Yeagar ai is a Langchain Agent creator designed to help you build, prototype, and deploy AI-powered agents with ease. KoboldCpp is an easy-to-use AI text-generation software for GGML models. It's a single self contained distributable from Concedo, that builds off llama.cpp, and adds a versatile Kobold API endpoint, additional format support, backward compatibility, as well as a fancy UI with persistent stories, editing tools, save formats, memory, world info, author's note, characters, and scenarios. ChatGPT Back to the Top Chatbot UI for ChatGPT Chatbot UI by mckaywrigley is an advanced chatbot kit for OpenAI's chat models built on top of Chatbot UI Lite using Next.js, TypeScript, and Tailwind CSS. This version of ChatBot UI supports both GPT-3.5 and GPT-4 models. Conversations are stored locally within your browser. You can export and import conversations to safeguard against data loss. See a demo . Chatbot UI Lite by mckaywrigley is a simple chatbot starter kit for OpenAI's chat model using Next.js, TypeScript, and Tailwind CSS. See a demo . Build locally with Docker: shell docker build -t chatgpt-ui . docker run -e OPENAI_API_KEY=xxxxxxxx -p 3000:3000 chatgpt-ui Running Locally on Windows, MacOS, and Linux: 1. Clone Project Repo bash git clone https://github.com/mckaywrigley/chatbot-ui.git 2. Install Dependencies bash npm i 3. Provide OpenAI API Key Create a .env.local file in the root of the repo with your OpenAI API Key : bash OPENAI_API_KEY=YOUR_KEY You can set OPENAI_API_HOST where access to the official OpenAI host is restricted or unavailable, allowing users to configure an alternative host for their specific needs. Additionally, if you have multiple OpenAI Organizations, you can set OPENAI_ORGANIZATION to specify one. 4. Run App bash npm run dev You done you should be able to start chatting with ChatGPT! Chatbot UI MiniGPT-4 is an enhancing Vision-language Understanding with Advanced Large Language Models Launching Demo Locally Try out the demo demo.py on your local machine by running python demo.py --cfg-path eval_configs/minigpt4_eval.yaml --gpu-id 0 Here, the demo loads Vicuna as 8 bit by default to save some GPU memory usage. Besides, the default beam search width is 1. Under this setting, the demo cost about 23G GPU memory . If you have a more powerful GPU with larger GPU memory, you can run the model in 16 bit by setting low_resource to False in the config file minigpt4_eval.yaml and use a larger beam search width. MiniGPT-4 Demo GPT4All is an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue based on LLaMa . GPT4All UI is a Flask web application that provides a chat UI for interacting with the GPT4All chatbot. Alpaca.cpp is a fast ChatGPT-like model locally on your device. It combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. llama.cpp is a Port of Facebook's LLaMA model in C/C++. Serge is a web interface for chatting with Alpaca through llama.cpp. Fully self-hosted & dockerized, with an easy to use API. OpenPlayground is a playfround for running ChatGPT-like models locally on your device. Vicuna is an open source chatbot trained by fine tuning LLaMA. It apparently achieves more than 90% quality of chatgpt and costs $300 to train. Yeagar ai is a Langchain Agent creator designed to help you build, prototype, and deploy AI-powered agents with ease. LocalAI is a self-hosted, community-driven, local OpenAI-compatible API. Drop-in replacement for OpenAI running LLMs on consumer-grade hardware with no GPU required. It's an API to run ggml compatible models: llama, gpt4all, rwkv, whisper, vicuna, koala, gpt4all-j, cerebras, falcon, dolly, starcoder, and many others. DoctorGPT is a lightweight self-contained binary that monitors your application logs for problems and diagnoses them. HttpGPT is an Unreal Engine 5 plugin that facilitates integration with OpenAI's GPT based services (ChatGPT and DALL-E) through asynchronous REST requests, making it easy for developers to communicate with these services. It also includes Editor Tools to integrate Chat GPT and DALL-E image generation directly in the Engine. Automation Back to the Top Accelerated Text - Automatically generate multiple natural language descriptions of your data varying in wording and structure. Activepieces - No-code business automation tool like Zapier or Tray. For example, you can send a Slack notification for each new Trello card. ActiveWorkflow - An intelligent process and workflow automation platform based on software agents. Alltube - Web GUI for youtube-dl, a program to download videos and audio from more than 100 websites. AmIUnique - Learn how identifiable you are on the Internet (browser fingerprinting tool). Automatisch - Business automation tool that lets you connect different services like Twitter, Slack, and more to automate your business processes (Open source Zapier alternative). Baserow - Open source online database tool and Airtable alternative. Create your own database without technical experience. betanin - Music organization man-in-the-middle of your torrent client and music player. Based on beets.io, similar to Sonarr and Radarr. ChiefOnboarding - Employee onboarding platform that allows you to provision user accounts and create sequences with todo items, resources, text/email/Slack messages, and more! Available as a web portal and Slack bot. Datasette - An open source multi-tool for exploring and publishing data, easy import and export and database management. Eonza - Eonza is used to create scripts and automate tasks on servers or VPS hosting. Manage your servers from any browser on any device. Exadel CompreFace - Face recognition system that provides REST API for face recognition, face detection, and other face services, and is easily deployed with docker. There are SDKs for Python and JavaScript languages. Can be used without prior machine learning skills. feed2toot - Feed2toot parses a RSS feed, extracts the last entries and sends them to Mastodon. feedmixer - FeedMixer is a WSGI (Python3) micro web service which takes a list of feed URLs and returns a new feed consisting of the most recent n entries from each given feed(Returns Atom, RSS, or JSON). Headphones - Automated music downloader for NZB and Torrent, written in Python. It supports SABnzbd, NZBget, Transmission, µTorrent, Deluge and Blackhole. Healthchecks - Django app which listens for pings and sends alerts when pings are late. HRConvert2 - Drag-and-drop file conversion server with session based authentication, automatic temporary file maintenance, and logging capability. Huginn - Allows you to build agents that monitor and act on your behalf. Kibitzr - Lightweight personal web assistant with powerful integrations. Krayin - Free and Opensource Laravel CRM Application. Leon - Open-source personal assistant who can live on your server. Lidarr - Lidarr is a music collection manager for Usenet and BitTorrent users. Matchering - A containerized web app for automated music mastering. An open-source alternative to LANDR, eMastered, and MajorDecibel. Medusa - Automatic Video Library Manager for TV Shows. It watches for new episodes of your favorite shows, and when they are posted it does its magic. ( Source Code ) GPL-3.0 Python MeTube - Web GUI for youtube-dl, with playlist support. Allows downloading videos from dozens of websites. AGPL-3.0 Python/Nodejs/Docker Nautobot is a Network Source of Truth and Network Automation Platform built as a web application atop the Django Python framework with a PostgreSQL or MySQL database. nefarious - Web application that automates downloading Movies and TV Shows. NocoDB - No-code platform that turns any database into a smart spreadsheet. It can be considered as an Airtable or Smartsheet alternative. OliveTin - OliveTin is a web interface for running Linux shell commands. Patrowl - Open Source, Smart and Scalable Security Operations Orchestration Platform. Podgrab - Lightweight podcast manager and automatic podcast episode downloader. It will monitor podcasts for your and download them automatically whenever a new episode goes live. pyLoad - Lightweight, customizable and remotely manageable downloader for 1-click-hosting sites like rapidshare.com or uploaded.to. Radarr - Radarr is an independent fork of Sonarr reworked for automatically downloading movies via Usenet and BitTorrent, à la Couchpotato. SickRage - SickRage is an automatic Video Library Manager for TV Shows. Automatic torrent/nzb searching, downloading, and processing at the qualities you want. SiteInspector - Web-based tool for catching spelling errors, grammatical errors, broken links, and other errors on websites. Sonarr - Automatic TV Shows downloader and manager for Usenet and BitTorrent. It can grab, sort and rename new episodes and automatically upgrade the quality of files already downloaded when a better quality format becomes available. StackStorm - StackStorm (aka IFTTT for Ops ) is event-driven automation for auto-remediation, security responses, troubleshooting, deployments, and more. Includes rules engine, workflow, 160 integration packs with 6000+ actions and ChatOps. µTask - Automation engine that models and executes business processes declared in yaml. Configuration Management Back to The Top Ansible - is a tool is a powerful, agentless tool that works everywhere and with everything. When you add in proven enterprise engineering and support from Red Hat that's written in Python. Ansible.Ai is an AI for Ansible Content Development tool to automate in your IT infrastructure and it will generate syntactically correct playbook to help you get there. CFEngine - is a Lightweight agent system where the configuration state is specified via a declarative language. mgmt - is a next generation config management written in Go. Pallet - is a Infrastructure definition, configuration and management via a Clojure DSL. Puppet - is an automated administrative engine for your Linux, Unix, and Windows systems, performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification. Chef - is a powerful automation platform that transforms infrastructure into code automating how infrastructure is configured, deployed and managed across any environment. (R)?ex - is a friendly automation framework to any combinations of local and remote execution, push and pull style of management, or imperative and declarative approach. Salt - is an event-driven automation tool and framework to deploy, configure, and manage complex IT systems. It automates common infrastructure administration tasks and ensure that all the components of your infrastructure are operating in a consistent desired state. Fleek is an all-in-one management system for everything you need to be productive on your computer. Cloud Storage Back to The Top Swift - A highly available, distributed, eventually consistent object/blob store. Syncthing - Open Source system for private, encrypted and authenticated distribution of data. git-annex assistant - A synchronized folder on each of your MacOS and Linux computers, Android devices, removable drives, NAS appliances, and cloud services. NextCloud - Provides access to your files via the web. ownCloud - Provides universal access to your files via the web, your computer or your mobile devices. Seafile - Another Open Source Cloud Storage solution. SparkleShare - Provides cloud storage and file synchronization services. By default, it uses Git as a storage backend. Cloud Back to the Top Linode Linode is a cloud hosting company that provides virtual private servers and variety of other cloud services. Linode Documentation Linode Guides & Tutorials Linode API Guides Linode Marketplace Self-Hosting the vaultwarden Password Manager Linode Cloud Community Linode Developer Portal Linode Content Resources Linode Tools Linode Cloud Manager is a user- and mobile-friendly interface to deploy and manage virtual machines, configure networking, and control user accounts. Linode API is a tool that makes easy to configure, manage, and deploy user management, billing, support tickets, and more with programmatic access to Linode products and services. Linode CLI is a tool to deploy and manage Linux servers from Linode without leaving the command line. Linode Images is a service to capture, store, and deploy your custom images across Linodes or data centers. Easily create your own raw disk image and upload a compressed .gz image file (up to 5 GB) using the Cloud Manager or API to easily deploy to the Linode size and data center you need. Linode Integrations is a collection of integrations lets you connect infrastructure and dev tools to the Linode platform. That let's you manage your Linode resources using the tools you know and love. StackScripts is a tool to automatically configure new Linode instances using simple scripts. Create your own StackScript or browse the community StackScript library. Linode Bare Metal is the single-tenant solution for applications and organizations with security, compliance, and performance needs. Bare Metal combines direct hardware access and the flexibility of a virtual machine. Nextcloud Back to the Top Nextcloud is an industry-leading, on-premises content collaboration platform for file sync & share and communication server. It is fully open source and you can host it yourself or pay a company to do it for you. Also checkout the following links below: Nextcloud App Store Nextcloud GitHub Nextcloud Developer Program Nexcloud login screen Nextcloud Hub is a tool that allows you to share and collaborate on documents, send and receive email, manage your calendar and have video chats without data leaks. As fully on-premises solution, Nextcloud Hub provides the benefits of online collaboration without the compliance and security risks. Nexcloud Hub Nextcloud AIO (All In One) is a tool that provides easy deployment and maintenance with most features included in this one Nextcloud instance. Nextcloud Desktop Client is a tool to synchronize files from Nextcloud Server with your computer. Nextcloud Deck is a kanban style organization tool aimed at personal planning and project organization for teams integrated with Nextcloud. Nextcloud Files is a tool tool that allows your employees have easy access to their files, photos and documents to work and can share and collaborate with team members, customers and partners. So IT knows nobody besides those they shared with has access to those files. Nextcloud Talk is a tool that protects your communication better than other team collaboration platforms like Microsoft Teams or Slack, making sure your data stays on your servers. It also goes further than other encrypted communication technologies by keeping even metadata from leaking. Nextcloud Home is a tool that allows you store your documents, calendar, contacts and photos on your server at home, at one of at one Nextcloud's providers or in a data center you trust. Nextcloud Enterprise is a service that gives professional organizations software optimized and tested for mission critical environments. Nextcloud Outlook Integration is a tool that automatically upload files to replace large attachments or integrate Calendars and Contacts in Microsoft Outlook. Collabora Online in Nextcloud is a powerful LibreOffice-based online office suite with collaborative editing, which supports all major document, spreadsheet and presentation file formats and works in all modern browsers. ONLYOFFICE integration in Nextcloud is a service that empowers your users to collaborate on office documents with team members in real time. It has compatibility with Microsoft Office formats means perfect documents, every time. Nextcloud VM(virtual machine appliance) is a set of carefully crafted family of *nix scripts, which interactively guide you through a quality-controlled installation of a Nextcloud instance for Home/SME Server and scripts for Raspberry Pi 4. It is Community developed and maintained. LibreSign is a Libre digital signature app for Nextcloud. DigitalOcean Back to the Top DigitalOcean is a cloud infrastructure provider that provides developers cloud services that help to deploy and scale applications that run simultaneously on multiple computers with data centers worldwide. DigitalOcean Pricing DigitalOcean GitHub DigitalOcean Tutorials DigitalOcean Tools DigitalOcean API is a service that manages your DigitalOcean infrastructure with our RESTful API. DigitalOcean Client libraries is a collection of libraries lets you use the DigitalOcean API in a variety of programming languages. DigitalOcean CLI is a service that manages your DigitalOcean infrastructure through your terminal with our open source Command Line Interface (CLI). Terraform provider is a service that allows the user treat their DigitalOcean infrastructure like code with Terraform . DigitalOcean Custom images is a service that quickly builds your environment in the cloud by provisioning servers with your own custom image, or choose from various Linux distributions. Container Registry is a service that easily stores, manages, and protects private container images. MinIO Object Storage Back to the Top MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service . Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads. It's one of the fastest object storage platforms globally, with a read/write speed of 183GB/s-171GB/s if you use standard hardware. It can function as the main storage tier for many workloads like Spark, TensorFlow, Presto, Hadoop HDFS, and H2O. MinIO UI Run the following command to run the latest stable image of MinIO as a container using an ephemeral data volume: Podman podman run -p 9000:9000 -p 9001:9001 \ quay.io/minio/minio server /data --console-address ":9001" Docker ``` docker run -p 9000:9000 --name minio -d minio/minio server /export ``` If you're using an SSD mounted at /mnt/sdd, then we can run the following to use it instead: ``` docker run -v /mnt/ssd:/export -p 9000:9000 --name minio -d minio/minio server /export ``` MacOS brew install minio/stable/minio minio server /data Binary Download for MacOS wget https://dl.min.io/server/minio/release/darwin-amd64/minio chmod +x minio ./minio server /data Linux wget https://dl.min.io/server/minio/release/linux-amd64/minio chmod +x minio ./minio server /data |Architecture | URL| |--- | --- | |64-bit Intel/AMD |https://dl.min.io/server/minio/release/linux-amd64/minio| |64-bit ARM |https://dl.min.io/server/minio/release/linux-arm64/minio| |64-bit PowerPC LE (ppc64le) |https://dl.min.io/server/minio/release/linux-ppc64le/minio| |IBM Z-Series (S390X) | https://dl.min.io/server/minio/release/linux-s390x/minio| Windows To run MinIO on 64-bit Windows hosts, download the MinIO executable from the following URL: https://dl.min.io/server/minio/release/windows-amd64/minio.exe Use the following command to run a standalone MinIO server on the Windows host. Replace D:\ with the path to the drive or directory in which you want MinIO to store data. You must change the terminal or powershell directory to the location of the minio.exe executable, or add the path to that directory to the system $PATH: minio.exe server D:\ Install from Source Use the following commands to compile and run a standalone MinIO server from source. Source installation is only intended for developers and advanced users. If you do not have a working Golang environment, please follow How to install Golang . The minimum version required is go1.19 . go install github.com/minio/minio@latest After you install MinIO: The MinIO deployment starts using default root credentials minioadmin:minioadmin . You can test the deployment using the MinIO Console, an embedded web-based object browser built into MinIO Server. Point a web browser running on the host machine to http://127.0.0.1:9000 and log in with the root credentials. You can use the Browser to create buckets, upload objects, and browse the contents of the MinIO server. When you run Minio you will be issued a key and a secret. These are used by the client or the web front-end to connect securely. I found my codes by typing in docker logs minio . ``` Created minio configuration file at /root/.minio Endpoint: http://172.17.0.2:9000 http://127.0.0.1:9000 AccessKey: accessCode SecretKey: secretCode Region: us-west-1 SQS ARNs: Browser Access: http://172.17.0.2:9000 http://127.0.0.1:9000 Command-line Access: https://docs.minio.io/docs/minio-client-quickstart-guide $ mc config host add myminio http://172.17.0.2:9000 accessCode secretCode Object API (Amazon S3 compatible): Go: https://docs.minio.io/docs/golang-client-quickstart-guide Java: https://docs.minio.io/docs/java-client-quickstart-guide Python: https://docs.minio.io/docs/python-client-quickstart-guide JavaScript: https://docs.minio.io/docs/javascript-client-quickstart-guide Drive Capacity: 50 GiB Free, 70 GiB Total ``` If you'd like to learn more then most of the Minio client commands support a help flag or give info on the command line: ``` NAME: mc - Minio Client for cloud storage and filesystems. USAGE: mc [FLAGS] COMMAND [COMMAND FLAGS | -h] [ARGUMENTS...] COMMANDS: ls List files and folders. mb Make a bucket or a folder. cat Display file and object contents. pipe Redirect STDIN to an object or file or STDOUT. share Generate URL for sharing. cp Copy files and objects. mirror Mirror buckets and folders. diff Show differences between two folders or buckets. rm Remove files and objects. events Manage object notifications. watch Watch for files and objects events. policy Manage anonymous access to objects. session Manage saved sessions for cp and mirror commands. config Manage mc configuration file. update Check for new mc update. version Print version info. help, h Shows a list of commands or help for one command ``` Advanced options You can have your client point to multiple Minio servers, which is really neat especially if you're working on a distributed team. Minio's test-server called "play" is already configured in the default client, you can see all the servers you have configured with mc config host list. To upload the photo to Minio's "play" S3 server just type in: # mc mb play/somebucketname # mc cp ~/Downloads/IMG_2016120-25.jpg play/somebucketname Recursive uploads: If you want to test something larger out you could try uploading your entire Downloads photo, and then you should use the --recursive flag to make sure nothing's missed: # mc cp --recursive ~/Downloads/IMG_2016120-25.jpg myminio/photos Databases Back to the Top SQL SQL is a standard language for storing, manipulating and retrieving data in relational databases. Coolify is an open-source & self-hostable Heroku/Netlify alternative. MySQL is a fully managed database service to deploy cloud-native applications using the world's most popular open source database. PostgreSQL is a powerful, open source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance. PostgREST is a tool that serves a fully RESTful API from any existing PostgreSQL database. It provides a cleaner, more standards-compliant, faster API than you are likely to write from scratch. NocoDB is an open source #NoCode platform that turns any database into a smart spreadsheet. It turns any MySQL, PostgreSQL, SQL Server, SQLite & MariaDB into a smart-spreadsheet. DBeaver is a free multi-platform database tool for developers, database administrators, analysts and all people who need to work with databases. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, MS Access, Teradata, Firebird, Apache Hive, Phoenix, Presto, etc. OmniDB is a web-based tool for database management. Navicat is a series of graphical database management and development software produced by CyberTech Ltd. for MySQL, MariaDB, MongoDB, Oracle, SQLite, PostgreSQL and Microsoft SQL Server. HeidiSQL is free software, and has the aim to be easy to learn. It lets you see and edit data and structures from computers running one of the database systems MariaDB, MySQL, Microsoft SQL, PostgreSQL and SQLite. Beekeeper Studio is a cross-platform SQL editor and database manager(MySQL, Postgres, SQLite, SQL Server, and more.) available for Linux, Mac, and Windows. UI Bakery is a web-based low-code internal tool builder. It can visualize the data pulled from PostgreSQL, MongoDB, MySQL, MicrosoftSQL, Redis. IBM DB2 is a collection of hybrid data management products offering a complete suite of AI-empowered capabilities designed to help you manage both structured and unstructured data on premises as well as in private and public cloud environments. Db2 is built on an intelligent common SQL engine designed for scalability and flexibility. OracleDB is a powerful fully managed database helps developers manage business-critical data with the highest availability, reliability, and security. MariaDB is an enterprise open source database solution for modern, mission-critical applications. EventQL is a distributed, analytical database. It allows you to store massive amounts of structured data and explore it using SQL and other programmatic query facilities. CockroachDB is the SQL database for building global, scalable cloud services that survive disasters. SQLite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine.SQLite is the most used database engine in the world. SQLite is built into all mobile phones and most computers and comes bundled inside countless other applications that people use every day. SQLite Database Browser is an open source SQL tool that allows users to create, design and edits SQLite database files. It lets users show a log of all the SQL commands that have been issued by them and by the application itself. TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL and packaged as a PostgreSQL extension, providing automatic partitioning across time and space (partitioning key), as well as full SQL support. InfluxDB is an open source time series platform. This includes APIs for storing and querying data, processing it in the background for ETL or monitoring and alerting purposes, user dashboards, Internet of Things sensor data, and visualizing and exploring the data and more. It also has support for processing data from Graphite . Atlas is an in-memory dimensional time series database . dbWatch is a complete database monitoring/management solution for SQL Server, Oracle, PostgreSQL, Sybase, MySQL and Azure. Designed for proactive management and automation of routine maintenance in large scale on-premise, hybrid/cloud database environments. Adminer is an SQL management client tool for managing databases, tables, relations, indexes, users. Adminer has support for all the popular database management systems such as MySQL, MariaDB, PostgreSQL, SQLite, MS SQL, Oracle, Firebird, SimpleDB, Elasticsearch and MongoDB. Knex is a query builder for PostgreSQL, MySQL, CockroachDB, SQL Server, SQLite3 and Oracle, designed to be flexible, portable, and fun to use. rqlite is an easy-to-use, lightweight, distributed relational database, which uses SQLite as its storage engine. osquery is a SQL powered operating system instrumentation, monitoring, and analytics framework. SQLModel is a library for interacting with SQL databases from Python code, with Python objects. It is designed to be intuitive, easy to use, highly compatible, and robust. Citus is a PostgreSQL extension that transforms Postgres into a distributed database—so you can achieve high performance at any scale. DbVisualizer is a SQL management tool that allows users to manage a wide range of databases such as Oracle, Sybase, SQL Server, MySQL, H3, and SQLite. AppDynamics Database is a management product for Microsoft SQL Server. With AppDynamics you can monitor and trend key performance metrics such as resource consumption, database objects, schema statistics and more, allowing you to proactively tune and fix issues in a High-Volume Production Environment. Toad is a SQL Server DBMS toolset developed by Quest. It increases productivity by using extensive automation, intuitive workflows, and built-in expertise. This SQL management tool resolve issues, manage change and promote the highest levels of code quality for both relational and non-relational databases. Lepide SQL Server is an open source storage manager utility to analyse the performance of SQL Servers. It provides a complete overview of all configuration and permission changes being made to your SQL Server environment through an easy-to-use, graphical user interface. Sequel Pro is a fast MacOS database management tool for working with MySQL. This SQL management tool helpful for interacting with your database by easily to adding new databases, new tables, and new rows. ElasticSearch is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Elasticsearch is developed in Java. Logstash is a tool for managing events and logs. When used generically, the term encompasses a larger system of log collection, processing, storage and searching activities. Kibana is an open source data visualization plugin for Elasticsearch. It provides visualization capabilities on top of the content indexed on an Elasticsearch cluster. Users can create bar, line and scatter plots, or pie charts and maps on top of large volumes of data. Trino is a Distributed SQL query engine for big data. It is able to tremendously speed up ETL processes , allow them all to use standard SQL statement, and work with numerous data sources and targets all in the same system. Tableau is a Data Visualization software used in relational databases, cloud databases, and spreadsheets. Tableau was acquired by Salesforce in August 2019 . DataGrip is a professional DataBase IDE developed by Jet Brains that provides context-sensitive code completion, helping you to write SQL code faster. Completion is aware of the tables structure, foreign keys, and even database objects created in code you're editing. RStudio is an integrated development environment for R and Python, with a console, syntax-highlighting editor that supports direct code execution, and tools for plotting, history, debugging and workspace management. NoSQL Back to the Top NoSQL is a database that is interchangeably referred to as "nonrelational, or "non-SQL" to highlight that the database can handle huge volumes of rapidly changing, unstructured data in different ways than a relational (SQL-based) database with rows and tables. Scylla is the real-time big data database that is API-compatible with Apache Cassandra and Amazon DynamoDB. Apache Cassandra™ is an open source NoSQL distributed database trusted by thousands of companies for scalability and high availability without compromising performance. Cassandra provides linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Apache HBase™ is an open-source, NoSQL, distributed big data store. It enables random, strictly consistent, real-time access to petabytes of data. HBase is very effective for handling large, sparse datasets. HBase serves as a direct input and output to the Apache MapReduce framework for Hadoop, and works with Apache Phoenix to enable SQL-like queries over HBase tables. Hadoop Distributed File System (HDFS) is a distributed file system that handles large data sets running on commodity hardware. It is used to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes. HDFS is one of the major components of Apache Hadoop, the others being MapReduce and YARN . Redis(REmote DIctionary Server) is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. It provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. FoundationDB is an open source distributed database designed to handle large volumes of structured data across clusters of commodity servers. It organizes data as an ordered key-value store and employs ACID transactions for all operations. It is especially well-suited for read/write workloads but also has excellent performance for write-intensive workloads. FoundationDB was acquired by Apple in 2015 . CouchbaseDB is an open source distributed multi-model NoSQL document-oriented database . It creates a key-value store with managed cache for sub-millisecond data operations, with purpose-built indexers for efficient queries and a powerful query engine for executing SQL queries. MongoDB is a document database meaning it stores data in JSON-like documents. NoSQLBooster is a cross-platform IDE for MongoDB v2.6-5.0 , which provides a build-in MongoDB script debugger, SQL query, server monitoring tools, chaining fluent query, query code generator, task scheduling, ES2020 support, and advanced IntelliSense experience. ClickHouse® is an open-source column-oriented database management system that allows generating analytical data reports in real-time. Neo4j is a graph database management system that provides an array of tools, libraries, and frameworks to make development faster and easier. Remote Access Back to the Top FreeRDP is a free remote desktop protocol library and clients. Rustdesk is an open source virtual/remote desktop infrastructure for everyone. Display and control your PC (Windows, macOS, and Linux) and Android devices. TinyPilot is a tool that enables KVM over IP letting you control any computer remotely. X2Go is open source remote desktop software for Linux that uses a modified NX 3 protocol. It gives remote access to a Linux system's GUI. Apache Guacamole is a clientless remote desktop gateway. It supports standard protocols like VNC, RDP, and SSH. Remmina is a Remote access screen and file sharing to your desktop. It has Remote Access Protocol Plugins for RDP , SSH , SPICE , VNC , X2Go , HTTP/HTTPS . Remotely is a remote control and remote scripting solution, built with .NET 6, Blazor, SignalR Core, and WebRTC. P2P Remote Desktop is a portable, no configuration or installation needed remote desktop tool. Cloudflare Tunnel is a tunneling daemon that proxies traffic from the Cloudflare network to your origins. This daemon sits between Cloudflare network and your origin (a webserver). This attracts client requests and sends them to you via this daemon, without requiring you to poke holes on your firewall and your origin(webserver) can remain as closed as possible. WireGuard® is a straight-forward, fast and modern VPN that utilizes state-of-the-art cryptography. It aims to be faster, simpler, leaner, and more useful than IPsec while avoiding the massive headache. WireGuard is designed as a general-purpose VPN for running on embedded interfaces and super computers alike, fit for many circumstances. It's cross-platform (Windows, macOS, BSD, iOS, Android) and widely deployable. NetBird is an open-source VPN management platform built on top of WireGuard® making it easy to create secure private networks for your organization or home. Tailscale is a WireGuard-based app that makes secure, private networks easy for teams of any scale. It works like an overlay network between the computers of your networks using all kinds of NAT traversal sorcery. Headscale is an open source, self-hosted implementation of the Tailscale coordination server. MeshCentral is a full computer management web site. It can run your own web server to remotely manage and control computers on a local network or anywhere on the internet. Once you get the server started, create device group and download and install an agent on each computer you want to manage. VNC Viewer is a free remote desktop application that use can use on your iPhone, iPad, Mac, Windows and Linux computers from anywhere in the world. TightVNC is a free remote desktop application. It can see the desktop of a remote machine and control it with your local mouse and keyboard, just like you would do it sitting in the front of that computer. KRDC is a client application that allows you to view or even control the desktop session on another machine that is running a compatible server. VNC and RDP is supported. Krfb Desktop Sharing is a server application that allows you to share your current session with a user on another machine, who can use a VNC client to view or even control the desktop. wayvnc is a VNC server for wlroots-based Wayland compositors (no_entry Gnome, KDE and Weston are not supported). It attaches to a running Wayland session, creates virtual input devices, and exposes a single display via the RFB protocol. Waypipe is a proxy for Wayland clients. It forwards Wayland messages and serializes changes to shared memory buffers over a single socket. Virtualization Back to the Top HVM (Hardware Virtual Machine) is a virtualization type that provides the ability to run an operating system directly on top of a virtual machine without any modification, as if it were run on the bare-metal hardware. PV(ParaVirtualization) is an efficient and lightweight virtualization technique introduced by the Xen Project team, later adopted by other virtualization solutions. PV does not require virtualization extensions from the host CPU and thus enables virtualization on hardware architectures that do not support Hardware-assisted virtualization. Network functions virtualization (NFV) is the replacement of network appliance hardware with virtual machines. The virtual machines use a hypervisor to run networking software and processes such as routing and load balancing. NFV allows for the separation of communication services from dedicated hardware, such as routers and firewalls. This separation means network operations can provide new services dynamically and without installing new hardware. Deploying network components with network functions virtualization only takes hours compared to months like with traditional networking solutions. Software Defined Networking (SDN) is an approach to networking that uses software-based controllers or application programming interfaces (APIs) to communicate with underlying hardware infrastructure and direct traffic on a network. This model differs from that of traditional networks, which use dedicated hardware devices (routers and switches) to control network traffic. Virtualized Infrastructure Manager (VIM) is a service delivery and reduce costs with high performance lifecycle management Manage the full lifecycle of the software and hardware comprising your NFV infrastructure (NFVI), and maintaining a live inventory and allocation plan of both physical and virtual resources. Management and Orchestration(MANO) is an ETSI-hosted initiative to develop an Open Source NFV Management and Orchestration (MANO) software stack aligned with ETSI NFV. Two of the key components of the ETSI NFV architectural framework are the NFV Orchestrator and VNF Manager, known as NFV MANO. Magma is an open source software platform that gives network operators an open, flexible and extendable mobile core network solution. Their mission is to connect the world to a faster network by enabling service providers to build cost-effective and extensible carrier-grade networks. Magma is 3GPP generation (2G, 3G, 4G or upcoming 5G networks) and access network agnostic (cellular or WiFi). It can flexibly support a radio access network with minimal development and deployment effort. OpenRAN is an intelligent Radio Access Network(RAN) integrated on general purpose platforms with open interface between software defined functions. Open RANecosystem enables enormous flexibility and interoperability with a complete openess to multi-vendor deployments. Open vSwitch(OVS) is an open source production quality, multilayer virtual switch licensed under the open source Apache 2.0 license. It is designed to enable massive network automation through programmatic extension, while still supporting standard management interfaces and protocols (NetFlow, sFlow, IPFIX, RSPAN, CLI, LACP, 802.1ag). Edge is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. This proximity to data at its source can deliver strong business benefits, including faster insights, improved response times and better bandwidth availability. Multi-access edge computing (MEC) is an Industry Specification Group (ISG) within ETSI to create a standardized, open environment which will allow the efficient and seamless integration of applications from vendors, service providers, and third-parties across multi-vendor Multi-access Edge Computing platforms. Virtualized network functions(VNFs) is a software application used in a Network Functions Virtualization (NFV) implementation that has well defined interfaces, and provides one or more component networking functions in a defined way. For example, a security VNF provides Network Address Translation (NAT) and firewall component functions. Cloud-Native Network Functions(CNF) is a network function designed and implemented to run inside containers. CNFs inherit all the cloud native architectural and operational principles including Kubernetes(K8s) lifecycle management, agility, resilience, and observability. Physical Network Function(PNF) is a physical network node which has not undergone virtualization. Both PNFs and VNFs (Virtualized Network Functions) can be used to form an overall Network Service. Network functions virtualization infrastructure(NFVI) is the foundation of the overall NFV architecture. It provides the physical compute, storage, and networking hardware that hosts the VNFs. Each NFVI block can be thought of as an NFVI node and many nodes can be deployed and controlled geographically. Virtualization-based Security (VBS) is a hardware virtualization feature to create and isolate a secure region of memory from the normal operating system. Hypervisor-Enforced Code Integrity (HVCI) is a mechanism whereby a hypervisor, such as Hyper-V, uses hardware virtualization to protect kernel-mode processes against the injection and execution of malicious or unverified code. Code integrity validation is performed in a secure environment that is resistant to attack from malicious software, and page permissions for kernel mode are set and maintained by the hypervisor. NVIDIA virtual GPU (vGPU) is a software enables powerful GPU performance for workloads ranging from graphics-rich virtual workstations to data science and AI, enabling IT to leverage the management and security benefits of virtualization as well as the performance of NVIDIA GPUs required for modern workloads. AMD MxGPU is a hardware-based virtualized GPU solution, is built on industry standard SR-IOV (Single-Root I/O Virtualization) technology and allows multiple virtualized users per physical GPU to work remotely. Proxmox Virtual Environment(VE) is a complete open-source platform for enterprise virtualization. It inlcudes a built-in web interface that you can easily manage VMs and containers, software-defined storage and networking, high-availability clustering, and multiple out-of-the-box tools on a single solution. KVM (for Kernel-based Virtual Machine) is a full virtualization solution for Linux on x86 hardware containing virtualization extensions (Intel VT or AMD-V). It consists of a loadable kernel module, kvm.ko, that provides the core virtualization infrastructure and a processor specific module, kvm-intel.ko or kvm-amd.ko. QEMU is a fast processor emulator using a portable dynamic translator. QEMU emulates a full system, including a processor and various peripherals. It can be used to launch a different Operating System without rebooting the PC or to debug system code. Quickemu is a program that quickly create and run optimised Windows, macOS and Linux desktop virtual machines. Hyper-V enables running virtualized computer systems on top of a physical host. These virtualized systems can be used and managed just as if they were physical computer systems, however they exist in virtualized and isolated environment. Special software called a hypervisor manages access between the virtual systems and the physical hardware resources. Virtualization enables quick deployment of computer systems, a way to quickly restore systems to a previously known good state, and the ability to migrate systems between physical hosts. Cloud Hypervisor is an open source Virtual Machine Monitor (VMM) that runs on top of KVM . The project focuses on exclusively running modern, cloud workloads, on top of a limited set of hardware architectures and platforms. Cloud workloads refers to those that are usually run by customers inside a cloud provider. Cloud Hypervisor is implemented in Rust and is based on the rust-vmm crates. VirtManager is a graphical tool for managing virtual machines via libvirt. Most usage is with QEMU/KVM virtual machines, but Xen and libvirt LXC containers are well supported. Common operations for any libvirt driver should work. oVirt is an open-source distributed virtualization solution, designed to manage your entire enterprise infrastructure. oVirt uses the trusted KVM hypervisor and is built upon several other community projects, including libvirt, Gluster, PatternFly, and Ansible. Founded by Red Hat as a community project on which Red Hat Enterprise Virtualization is based allowing for centralized management of virtual machines, compute, storage and networking resources, from an easy-to-use web-based front-end with platform independent access. Firecracker is an open source virtualization technology that is purpose-built for creating and managing secure, multi-tenant container and function-based services that provide serverless operational models. It runs workloads in lightweight virtual machines, called microVMs, which combine the security and isolation properties provided by hardware virtualization technology with the speed and flexibility of containers. Foreman is a free open source project that gives you the power to easily automate repetitive tasks, quickly deploy applications, and proactively manage your servers life cycle, on-premises or in the cloud. Harvester is an open source hyper-converged infrastructure (HCI) software built on Kubernetes. Anthos is a modern application management platform that provides a consistent development and operations experience for cloud and on-premises environments. OpenNebula is an open source platform delivering a simple but feature-rich and flexible solution to build and manage enterprise clouds for virtualized services, containerized applications and serverless computing. HyperKit is a toolkit for embedding hypervisor capabilities in your application. It includes a complete hypervisor, based on xhyve / bhyve , which is optimized for lightweight virtual machines and container deployment. It is designed to be interfaced with higher-level components such as the VPNKit and DataKit . HyperKit currently only supports macOS using the Hypervisor.framework making it a core component of Docker Desktop for Mac. Intel® Graphics Virtualization Technology (Intel® GVT) is a full GPU virtualization solution with mediated pass-through, starting from 4th generation Intel Core (TM) processors with Intel processor graphics(Broadwell and newer). It can be used to virtualize the GPU for multiple guest virtual machines, effectively providing near-native graphics performance in the virtual machine and still letting your host use the virtualized GPU normally. Apple Hypervisor is a frameowrk that builds virtualization solutions on top of a lightweight hypervisor, without third-party kernel extensions. Hypervisor provides C APIs so you can interact with virtualization technologies in user space, without writing kernel extensions (KEXTs). As a result, the apps you create using this framework are suitable for distribution on the Mac App Store . Apple Virtualization Framework is a framework that provides high-level APIs for creating and managing virtual machines on Apple silicon and Intel-based Mac computers. This framework is used to boot and run a Linux-based operating system in a custom environment that you define. It also supports the Virtio specification , which defines standard interfaces for many device types, including network, socket, serial port, storage, entropy, and memory-balloon devices. Apple Paravirtualized Graphics Framework is a framework that implements hardware-accelerated graphics for macOS running in a virtual machine, hereafter known as the guest. The operating system provides a graphics driver that runs inside the guest, communicating with the framework in the host operating system to take advantage of Metal-accelerated graphics. Cilicon is a macOS App that leverages Apple's Virtualization Framework to create, provision and run ephemeral virtual machines with minimal setup or maintenance effort. You should be able to get up and running with your self-hosted CI in less than an hour. Xen is focused on advancing virtualization in a number of different commercial and open source applications, including server virtualization, Infrastructure as a Services (IaaS), desktop virtualization, security applications, embedded and hardware appliances, and automotive/aviation. Ganeti is a virtual machine cluster management tool built on top of existing virtualization technologies such as Xen or KVM and other open source software. Once installed, the tool assumes management of the virtual instances (Xen DomU). Packer is an open source tool for creating identical machine images for multiple platforms from a single source configuration. Packer is lightweight, runs on every major operating system, and is highly performant, creating machine images for multiple platforms in parallel. Packer does not replace configuration management like Chef or Puppet. In fact, when building images, Packer is able to use tools like Chef or Puppet to install software onto the image. Vagrant is a tool for building and managing virtual machine environments in a single workflow. With an easy-to-use workflow and focus on automation, Vagrant lowers development environment setup time, increases production parity, and makes the "works on my machine" excuse a relic of the past. It provides easy to configure, reproducible, and portable work environments built on top of industry-standard technology and controlled by a single consistent workflow to help maximize the productivity and flexibility of you and your team. Password Management Back to the Top Bitwarden is a free and open-source password management service that stores sensitive information such as website credentials in an encrypted vault. Bitwarden Server is a project contains the APIs, database, and other core infrastructure items needed for the "backend" of all bitwarden client applications. Checkout Bitwarden's self-hosted release repository . Vaultwarden is an unofficial Bitwarden compatible server written in Rust, formerly known as bitwarden_rs. Passbolt is an open-source/self-hosted password manager for teams. It allows you to securely share and store credentials. For instance, the wifi password of your office, the administrator password of a router or your organization's social media account passwords, all of them can be secured using passbolt. KeePassXC is a modern, secure, and open-source password manager that stores and manages your most sensitive information. You can run KeePassXC on Windows, macOS, and Linux systems. It saves many different types of information, such as usernames, passwords, URLs, attachments, and notes in an offline, encrypted file that can be stored in any location, including private and public cloud solutions. AuthPass.app is an Open-Source Password Manager for mobile and desktop that is Keepass 2.x (kdbx 3.x) compatible. pass is an open-source unix-based password utilitiy with various gui clients SSH Back to The Top Secure Shell Protocol (SSH) is a cryptographic network protocol for operating network services securely over an unsecured network. Advanced SSH config is a tool that enhances ssh_config file capabilities, completely transparent. AutoSSH is a tool that automatically respawn ssh session after network interruption. ContainersSSH is an SSH Server that Launches Containers in Kubernetes and Docker on demand. Cluster SSH is a tool that controls a number of xterm windows via a single graphical console. DSH is a Dancer's shell / distributed shell - Wrapper for executing multiple remote shell commands from one command line. Flightplan is a node.js library for streamlining application deployment or systems administration tasks (local and remote hosts). Mosh is a command-line program, like SSH. You can use it inside xterm, gnome-terminal, urxvt, Terminal.app, iTerm, emacs, screen, or tmux. Parallel SSH is an asynchronous parallel SSH library designed for large scale automation. It differentiates ifself from alternatives, other libraries and higher level frameworks like Ansible or Chef. SSH Audit is a tool for SSH server & client configuration auditing (banner, key exchange, encryption, mac, compression, compatibility, security, etc). Sshwifty is a SSH and Telnet connector made for the Web. It can be deployed on your computer or server to provide SSH and Telnet access interface for any compatible (standard) web browser. SSHrc is a tool that sources ~/.sshrc on your local computer after logging in remotely. StormSSH is a command line tool to manage SSH connections. Tailscale SSH is a service that allows Tailscale to manage the authentication and authorization of SSH connections on your tailnet. VPN Back to The Top VPN (Virtual Private Network) is a service that encrypts your internet traffic on unsecured networks to protect your online identity, hide your IP address, and shield your online data from third parties. Wireguard - New minimal VPN Solution that is very fast. OpenVPN - Uses a custom security protocol that utilizes SSL/TLS for key exchange. Pritunl - OpenVPN based solution that's easy to set up. SoftEther - Multi-protocol software VPN with advanced features. sshuttle - Poor man's VPN. strongSwan - Complete IPsec implementation for Linux. tinc - Distributed p2p VPN. LDAP Back to The Top LDAP Servers 389 Directory Server - Developed by Red Hat. Apache Directory Server - Apache Software Foundation project written in Java. Fusion Directory - Improve the Management of the services and the company directory based on OpenLDAP. OpenDJ - Fork of OpenDS. OpenDS - Another directory server written in Java. OpenLDAP - Developed by the OpenLDAP Project. LDAP management Apache Directory Studio - The Eclipse-based LDAP browser and directory client Log Management Back to The Top Echofish - A web based real-time event log aggregation, analysis, monitoring and management system. Fluentd - Log Collector and Shipper. Flume - Distributed log collection and aggregation system. Graylog2 - Pluggable Log and Event Analysis Server with Alerting options. Heka - Stream processing system which may be used for log aggregation. Elasticsearch - A Lucene Based Document store mainly used for log indexing, storage and analysis. Kibana - Visualize logs and time-stamped data. Logstash - Tool for managing events and logs. Octopussy - Log Management Solution (Visualize/Alert/Report). DNS Back to The Top Duckdns - A free service which will point a DNS (sub domains of duckdns.org) to an IP of your choice. The service is completely free, and doesn't require reactivation or forum posts to maintain its existence. dnsmasq - A lightweight service providing DNS, DHCP and TFTP services to small-scale networks. MagicDNS is a tool that automatically registers DNS names for devices in your network. Bind - The most widely used name server software. djbdns - A collection of DNS applications, including tinydns. Designate - DNS REST API that support several DNS servers as its backend. Knot - High performance authoritative-only DNS server. Lexicon is a tool that provides a way to manipulate DNS records on multiple DNS providers in a standardized way. NSD - Authoritative only, high performance, simple name server. PowerDNS - DNS server with a variety of data storage back-ends and load balancing features. CoreDNS is a DNS server/forwarder, written in Go, that chains plugins . Each plugin performs a (DNS) function. Unbound - Validating, recursive, and caching DNS resolver. Yadifa - Lightweight authoritative Name Server with DNSSEC capabilities powering the .eu top-level domain. Network Tools Back to the Top MQTT is an OASIS standard messaging protocol for the Internet of Things (IoT). It is designed as an extremely lightweight publish/subscribe messaging transport that is ideal for connecting remote devices with a small code footprint and minimal network bandwidth. Mongoose is a networking library for C/C++. It implements event-driven non-blocking APIs for TCP, UDP, HTTP, WebSocket, MQTT. It is designed for connecting devices and bringing them online. Nautobot is a Network Source of Truth and Network Automation Platform built as a web application atop the Django Python framework with a PostgreSQL or MySQL database. Eclipse Mosquitto is an open source implementation of a server for version 5.0, 3.1.1, and 3.1 of the MQTT protocol. Ejabberd is an open-source, robust, scalable and extensible realtime platform built using Erlang/OTP , that includes XMPP Server, MQTT Broker and SIP Service. Nebula is a scalable overlay networking tool with a focus on performance, simplicity and security. It lets you seamlessly connect computers anywhere in the world. Nebula is portable, and runs on Linux, OSX, Windows, iOS, and Android. It can be used to connect a small number of computers, but is also able to connect tens of thousands of computers. LibreSpeed is a network speed test tool that can be run on your LAN or hosted in the cloud. SmokePing is a deluxe latency measurement tool. It can measure, store and display latency, latency distribution and packet loss. It uses RRDtool to maintain a longterm data-store and to draw pretty graphs, giving up to the minute information on the state of each network connection. Tailnet is your private network. When you log in for the first time to Tailscale on your phone, laptop, desktop, or cloud VM, a tailnet is created. For personal users, you are a tailnet of many devices and one person. Each device gets a private Tailscale IP address in the CGNAT range and every device can talk directly to every other device, wherever they are on the internet. Tailscale SSH is a service that allows Tailscale to manage the authentication and authorization of SSH connections on your tailnet. Tailscale Funnel is a feature that allows you to route traffic from the wider internet to one or more of your Tailscale nodes. You can think of this as publicly sharing a node for anyone to access, even if they don’t have Tailscale themselves. Cockpit is a web-based graphical interface for servers, intended for everyone. It uses your system’s normal user logins and privileges . Network-wide logins are also supported through single-sign-on and other authentication techniques. NetBox is a leading solution for modeling and documenting modern networks. It combines the traditional disciplines of IP address management (IPAM) and datacenter infrastructure management (DCIM) with powerful APIs and extensions, NetBox provides the ideal "source of truth" to power network automation. Network UPS Tools (NUT) is a project that provides support for Power Devices, such as Uninterruptible Power Supplies, Power Distribution Units, Automatic Transfer Switches, Power Supply Units and Solar Controllers. NUT provides a common protocol and set of tools to monitor and manage such devices, and to consistently name equivalent features and data points, across a vast range of vendor-specific protocols and connection media types. Dnsmasq is a tool that provides network infrastructure for small networks: DNS, DHCP, router advertisement and network boot. It is designed to be lightweight and have a small footprint, suitable for resource constrained routers and firewalls. It has also been widely used for tethering on smartphones and portable hotspots, and to support virtual networking in virtualisation frameworks. Supported platforms include Linux (with glibc and uclibc), Android, BSD, and MacOS. Nginx proxy manager (NPM) is a reverse proxy management system running on Docker. It's easy to set up and does not require users to know how to work with Nginx servers or SSL certificates. Netdata is high-fidelity infrastructure monitoring and troubleshooting, real-time monitoring Agent collects thousands of metrics from systems, hardware, containers, and applications with zero configuration. It runs permanently on all your physical/virtual servers, containers, cloud deployments, and edge/IoT devices, and is perfectly safe to install on your systems mid-incident without any preparation. Pi-hole is a DNS sinkhole that protects your devices from unwanted content, without installing any client-side software, intended for use on a private network. It is designed for use on embedded devices with network capability, such as the Raspberry Pi, but it can be used on other machines running Linux and cloud implementations. OWASP Amass is a tool that performs network mapping of attack surfaces and external asset discovery using open source information gathering and active reconnaissance techniques. Smap is a port scanner built with shodan.io's free API. It takes same command line arguments as Nmap and produces the same output which makes it a drop-in replacament for Nmap. ORY Oathkeeper is an Identity & Access Proxy (IAP) and Access Control Decision API that authorizes HTTP requests based on sets of Access Rules. Ory Kratos is a developer-friendly, security-hardened and battle-test Identity, User Management and Authentication system for the Cloud. The Kratos identity server (similiar to Auth0, Okta, Firebase) with Ory-hardened authentication, MFA, FIDO2, TOTP, WebAuthn, profile management, identity schemas, social sign in, registration, account recovery, passwordless. Ory Hydra is a hardened, OpenID Certified OAuth 2.0 Server and OpenID Connect Provider optimized for low-latency, high throughput, and low resource consumption. Ory Hydra is not an identity provider (user sign up, user login, password reset flow), but connects to your existing identity provider through a login and consent app . Ory Keto is an Open Source (Go) implementation of Zanzibar: Google's Consistent, Global Authorization System . It ships gRPC, REST APIs, newSQL, and an easy and granular permission language. Supports ACL, RBAC, and other access models. AdGuard Home is a DNS relay station with ad/tracker/other blocking, IP address redirections, and DNS-over-HTTPS. NetBird is an open-source VPN management platform built on top of WireGuard® making it easy to create secure private networks for your organization or home. Supabase is an open source Firebase alternative. It is building the features of Firebase using enterprise-grade open source tools. Plik is a scalable & friendly temporary file upload system (Wetransfer like) in golang. Restify is a framework, utilizing connect style middleware for building REST APIs. Traefik is an open source Edge Router that makes publishing your services a fun and easy experience. It receives requests on behalf of your system and finds out which components are responsible for handling them. What sets Traefik apart, besides its many features, is that it automatically discovers the right configuration for your services. Traefik Mesh is a simple, yet full-featured service mesh. It is container-native and fits as your de-facto service mesh in your Kubernetes cluster. It supports the latest Service Mesh Interface specification SMI that facilitates integration with pre-existing solution. DuckDNS is a free service that allows you to bind your own favorite subdomain under duckdns.org to the public IP address in use from your router, even though such address is dynamically allocated by your internet service provider and therefore changes over time. Trust-DNS is a Rust based DNS client, server, and Resolver, built to be safe and secure from the ground up. Hugo is a static HTML and CSS website generator written in Go. It is optimized for speed, ease of use, and configurability. Hugo takes a directory with content and templates and renders them into a full HTML website. sshuttle is a transparent proxy server that works as a poor man's VPN that forwards connection over ssh. It works with Linux and MacOS and supports DNS tunneling. NetHopper is a Multi-Cloud Application Network as a Service. The easiest way to visualize, connect, secure, protect, and monitor microservices across any cluster, site, cloud, or network. Cypress is a tool that makes it fast, easy and reliable testing for anything that runs in a browser. Kimchi is an HTML5 based management tool for KVM. It is designed to make it as easy as possible to get started with KVM and create your first guest. ION is a distributed real-time communication system, the goal is to chat anydevice, anytime, anywhere. FreeRDP is a free remote desktop protocol library and clients. Pimox is a port of Proxmox to the Raspberry Pi allowing you to build a Proxmox cluster of Rapberry Pi's or even a hybrid cluster of Pis and x86 hardware. PiKVM is a very simple and fully functional Raspberry Pi-based KVM over IP. Firezone is a self-hosted WireGuard®-based VPN server and Linux firewall. Monoid is an open-source suite of tools for automating data privacy. Pinecone is an experimental overlay routing protocol suite which is the foundation of the current P2P Matrix demos. It is designed to provide end-to-end encrypted connectivity between devices at a global scale over any compatible medium (currently TCP, WebSockets, Bluetooth Low Energy etc), allowing multi-hop peer-to-peer connectivity between devices even in places where there is no Internet connectivity. Service Discovery Back to The Top Consul is a tool for service discovery, monitoring and configuration. Install Consul on Self-Hosted Kubernetes Clusters . Linkerd is an ultralight, security-first service mesh for Kubernetes. Linkerd adds critical security, observability, and reliability features to your Kubernetes stack with no code change required. Doozerd is a highly-available, completely consistent store for small amounts of extremely important data. Admiral is a tool for for service discovery that provides automatic configuration and service discovery for multicluster Istio service mesh. ScaleCube is a library that simplifies the development of reactive and distributed applications by providing an embeddable microservices library. It connects distributed microservices in a way that resembles a fabric when viewed collectively. It greatly simplifies and streamlines asynchronous programming and provides a tool-set for managing microservices architecture. DPS(dns-proxy-server) is a lightweight end user (Developers, Server Administrators) DNS server tool for service discovery, which make it easy to develop in systems where one hostname can solve to different IPs based on the configured environment, so you can: Solve hostnames from local configuration database. Solve hostnames from docker containers using docker hostname option or HOSTNAMES env. Solve hostnames from a list of configured remote DNS servers(as a proxy) if no answer of two above . Graphic interface to Create/List/Update/Delete A/CNAME records. Solve host machine IP using host.docker hostname. Access container by its container name / service name. Specify from which network solve container IP. ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. Security Back to The Top Blackbox - Safely store secrets in Git/Mercurial. Provides tooling to automatically encrypt secrets like passwords. Denyhosts - Thwart SSH dictionary based attacks and brute force attacks. Fail2Ban - Scans log files and takes action on IPs that show malicious behavior. fwknop - Protects ports via Single Packet Authorization in your firewall. Glastopf - A low-interaction web application honeypot to emulate vulnerabilities and gather attack data. Kippo - A medium-interaction SSH honeypot, mostly used as a standalone SSH daemon with a configurable Filesystem sandbox. OSSEC - OSSEC is a HIDS that performs log analysis, FIM, rootkit detection, and much more. OSQuery - Query your servers status and info using a SQL like interface. OPNsense is an open source firewall and routing software developed by Deciso. It offers an integrated Netflow analyser without the need for additional plugins or tools, similar to what you may find in high-end commercial products. pfSense - Firewall and Router FreeBSD distribution. Snort - Snort is a free and open source network intrusion prevention system (NIPS) and network intrusion detection system (NIDS) created by Martin Roesch in 1998. SpamAssassin - A powerful and popular email spam filter employing a variety of detection technique. BounCA - is a personal SSL / Certificate Authority Key management tool. Create self-signed SSL certificates via your browser. Troubleshooting Back to The Top NETworkManager - A powerful tool for managing networks and troubleshoot network problems. It contains features like a WiFi analyzer, IP scanner, port scanner, ping monitor, traceroute, DNS lookup or a LLDP/CDP capture. Wireshark - The world's foremost network protocol analyzer. Selfspy is a daemon for Unix/X11, MacOS (thanks to @ljos) and Windows (thanks to @Foxboron), that continuously monitors and stores what you are doing on your computer. This way, you can get all sorts of nifty statistics and reminders on what you have been up to. Cilium - A networking, observability, and security solution with an eBPF-based dataplane. It provides a simple flat Layer 3 network with the ability to span multiple clusters in either a native routing or overlay mode. Netshoot - A Docker + Kubernetes network trouble-shooting swiss-army container. Kubevious - A suite of app-centric assurance, validation, and introspection products for Kubernetes. It helps running modern Kubernetes applications without disasters and costly outages by continuously validating application manifests, cluster state, and configuration. HOMER - A robust, carrier-grade, scalable Packet and Event capture system and VoiP/RTC Monitoring Application based on the HEP/EEP protocol and ready to process & store insane amounts of signaling, rtc events, logs and statistics with instant search, end-to-end analysis and drill-down capabilities. mitmproxy - A Python tool used for intercepting, viewing and modifying network traffic. Invaluable in troubleshooting certain problems. Sysdig - Capture system state and activity from a running Linux instance, then save, filter and analyze. Sysdig Inspect - A powerful opensource interface for container troubleshooting and security investigation. Monitoring Back to the Top Proxmox Mail Gateway is an open-source email security solution protecting your mail server against all email threats from the moment they emerge. M2MLabs MainSpring is an application framework for building machine-to-machine applications like vehicle tracking or machine remote monitoring. In such applications typically a remote device equipped with sensors (e.g. gps, temperature, pressure) and actors communicates with a server application that is running the device communication protocol, device configuration, storage of data sent by the devices as well as the application business logic and the presentation layer. VictoriaMetrics is a fast and scalable open source time series database and monitoring solution which exists in a Single and in a cluster version. It is compatible with Prometheus pull model and supports a wide variety of ingestion protocols : Influx, Graphite, Prometheus remote_write, Prometheus exposion format, OpenTSDB put message, JSON line format, Arbitrary CSV data, native binary formant, DataDog agent or DogStatsD; as way as many ways to query data via PromQL or MetricsQL from Grafana or own VMUI . Kestra is an infinitely scalable orchestration and scheduling platform, creating, running, scheduling, and monitoring millions of complex pipelines. InfluxDB is an open source time series database, purpose-built by InfluxData for monitoring metrics and events, provides real-time visibility into stacks, sensors, and systems. Use InfluxDB to capture, analyze, and store millions of points per second, meet demanding SLA's, and chart a path to automation. Grafana is a tool that allows you to query, visualize, alert on and understand your metrics no matter where they are stored. Prometheus is a free software application used for event monitoring and alerting. It records real-time metrics in a time series database (allowing for high dimensionality) built using a HTTP pull model, with flexible queries and real-time alerting. Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus. It is designed to be very cost effective and easy to operate. It does not index the contents of the logs, but rather a set of labels for each log stream. Thanos is a set of components that can be composed into a highly available metric system with unlimited storage capacity, which can be added seamlessly on top of existing Prometheus deployments. Wyze is a great security and monitoring application to live stream HD video from the security cameras from anywhere in the world. Uptime Kuma is a fancy self-hosted monitoring tool. Gatus is a developer-oriented health dashboard that gives you the ability to monitor your services using HTTP, ICMP, TCP, and even DNS queries as well as evaluate the result of said queries by using a list of conditions on values like the status code, the response time, the certificate expiration, the body and many others. Upptime is the open-source uptime monitor and status page, powered entirely by GitHub Actions, Issues, and Pages. HertzBeat is an open-source, real-time monitoring system with custom-monitor and agentless. It supports web service, database, os, middleware and more. Tautulli is a python based web application for monitoring, analytics and notifications for Plex Media Server . Flower is a web based tool for monitoring and administrating Celery clusters. Weave Scope is a tool for Troubleshooting & Monitoring for Docker & Kubernetes. It automatically generates a map of your application, enabling you to intuitively understand, monitor, and control your containerized, microservices-based application. Statping (Status Page & Monitoring Server) is an easy to use Status Page for your websites and applications. Statping will automatically fetch the application and render a beautiful status page with tons of features for you to build an even better status page. Vector is a high-performance, end-to-end (agent & aggregator) observability data pipeline that puts you in control of your observability data. Collect , transform , and route all your logs, metrics, and traces to any vendors you want today and any other vendors you may want tomorrow. Open Service Mesh (OSM) is a lightweight, extensible, cloud native service mesh that allows users to uniformly manage, secure, and get out-of-the-box observability features for highly dynamic microservice environments. Ciao is a tool that checks HTTP(S) URL endpoints for a HTTP status code (or errors on the lower TCP stack) and sends a notification on status change via E-Mail or Webhooks. Server is a simple server for sending and receiving messages in real-time per WebSocket. Ngxtop is a real-time metrics for nginx server (and others). Blocky is a fast and lightweight DNS proxy as ad-blocker for local network with many features Dashy is a self-hostable personal dashboard built for you. Includes status-checking, widgets, themes, icon packs, a UI editor and tons more. Netdata is high-fidelity infrastructure monitoring and troubleshooting, real-time monitoring Agent collects thousands of metrics from systems, hardware, containers, and applications with zero configuration. It runs permanently on all your physical/virtual servers, containers, cloud deployments, and edge/IoT devices, and is perfectly safe to install on your systems mid-incident without any preparation. Restic is a modern backup program that can back up your files: from Linux, BSD, Mac and Windows. To many different storage types, including self-hosted and online services. easily, being a single executable that you can run without a server or complex setup. effectively, only transferring the parts that actually changed in the files you back up. Autorestic is a wrapper around the amazing restic. While being amazing the restic cli can be a bit overwhelming and difficult to manage if you have many different locations that you want to backup to multiple locations. MinIO is a high performance object storage tool that provides the world's fastest object storage server. With READ/WRITE speeds of 325 GiB/s and 165 GiB/s on standard hardware with default parity (EC:4), object storage can operate as the primary storage tier for a diverse set of workloads ranging from Spark, Presto, TensorFlow. Greyhole is a tool that uses Samba to create a storage pool of all your available hard drives (whatever their size, however they are connected), and allows you to create redundant copies of the files you store, in order to prevent data loss when part of your hardware fails. Falcon LogScale is purpose-built to help any organization achieve the benefits of large-scale logging and analysis. Falcon LogScale has virtually no latency, even at ingest volumes of 1PB(Petabyte) per day. Googerteller is a tool that makes an audible sound any time your computer sends a packet to a Google tracker or a Google service, which excludes Google Cloud users. TeslaMate is a powerful, self-hosted data logger for your Tesla. OneUptime is an open-source complete SRE and DevOps platform. It monitors your website, dashboards, API's, and more and alerts your team when downtime happens. Parca is a tool for continuous profiling for analysis of CPU and memory usage, down to the line number and throughout time. Saving infrastructure cost, improving performance, and increasing reliability. DeviceHive is a free, highly scalable open-source IoT platform for data collection, processing and analysis, visualization, and device management with the broad range of integration options. Distributed Services Architecture (DSA) is an open source IoT platform that facilitates device inter-communication, logic and applications at every layer of the Internet of Things infrastructure. The objective is to unify the disparate devices, services and applications into a structured and adaptable real-time data model. IoTivity is an open source software framework enabling seamless device-to-device connectivity to address the emerging needs of the Internet of Things. Eclipse IoT Project provides open source technology that will be used to build IoT solutions for industry and consumers. Dashboards Back to The Top Adagios is a Web based Nagios configuration interface. Dash is a low-overhead monitoring web dashboard for a GNU/Linux machine. Thruk is a Multibackend monitoring web interface with support for Naemon, Nagios, Icinga and Shinken. Uchiwa is a simple dashboard for the Sensu monitoring framework. InfluxDB is an open source time series database, purpose-built by InfluxData for monitoring metrics and events, provides real-time visibility into stacks, sensors, and systems. Use InfluxDB to capture, analyze, and store millions of points per second, meet demanding SLA's, and chart a path to automation. Grafana is a tool that allows you to query, visualize, alert on and understand your metrics no matter where they are stored. Prometheus is a free software application used for event monitoring and alerting. It records real-time metrics in a time series database (allowing for high dimensionality) built using a HTTP pull model, with flexible queries and real-time alerting. Analytics Back to the Top Plausible Analytics - Simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics. PostHog - Product analytics, session recording, feature flagging and a/b testing that you can self-host. Ackee - Self-hosted analytics tool for those who care about privacy. AWStats - Generate statistics from web, streaming, ftp or mail server logfiles. Chartbrew - Web application that can connect directly to databases and APIs and use the data to create beautiful charts. Countly Community Edition - Real time mobile and web analytics, crash reporting and push notifications platform. Druid - Distributed, column-oriented, real-time analytics data store. EDA - Web application for data analysis and visualization. GoAccess - Real-time web log analyzer and interactive viewer that runs in a terminal. GoatCounter - Easy web statistics without tracking of personal data. Metabase - Easy, open-source way for everyone in your company to ask questions and learn from data. Offen - Fair, lightweight and open web analytics tool. Gain insights while your users have full access to their data. Open Web Analytics - Web analytics framework that lets you stay in control of how you instrument and analyze the use of your websites and applications. Redash - Connect and query your data sources, build dashboards to visualize data and share them with your company. RudderStack - Collect, unify, transform, and store your customer data, and route it to a wide range of common, popular marketing, sales, and product tools. alternative to Segment. Shynet - Modern, privacy-friendly, and detailed web analytics that works without cookies or JS. Superset - Modern data exploration and visualization platform. Umami - Simple, fast, privacy-focused alternative to Google Analytics. Search Back to the Top Meilisearch is a lightning-fast search engine that fits effortlessly into your apps, websites, and workflow. Shodan is the world's first search engine for Internet-connected (IoT) devices. Whoogle Search is a self-hosted, ad-free, privacy-respecting metasearch engine. SearX is a Privacy-respecting, hackable metasearch engine . SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Sonic is a fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM. Zinc is a search engine that does full text indexing. It is a lightweight alternative to Elasticsearch and runs using a fraction of the resources. Cylect.io is the ultimate searching tool that is here to assist anyone looking for specific information through vast amounts of websites, search engines, and data collectors. Lyra is a fast, in-memory, typo-tolerant, full-text search engine written in TypeScript. Hugo Lyra is a typescript module for creating LyraSearch indexes for static Hugo sites, it comes with server and client libraries. Typesense is a fast, typo-tolerant search engine for building delightful search experiences. Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust. Toshi is meant to be a full-text search engine similar to Elasticsearch. Toshi strives to be to Elasticsearch what Tantivy is to Lucene. FlexSearch is a Next-Generation full text search library for Browser and Node.js. fd is a program to find entries in your filesystem. It is a simple, fast and user-friendly alternative to find. k8s at home search is a tool that indexs Flux HelmReleases from Github repositories with the k8s-at-home topic on GitHub. OpenFind is an app to find text in real life. Easily search your entire photo library in split seconds. This runs 100% offline. No servers, nothing weird going on. Notifications Back to the Top Apprise is a tool that allows you to send a notification to almost all of the most popular notification services available to us today such as: Telegram, Discord, Slack, Amazon SNS, Gotify, etc. ntfy is a simple HTTP-based pub-sub notification service. It allows you to send notifications to your phone or desktop via scripts from any computer, entirely without signup, cost or setup. It's also open source if you want to run your own. Countly is a product analytics solution and innovation enabler that helps teams track product performance and customer journey and behavior across mobile, web, and desktop applications. Ensuring privacy by design , Countly allows you to innovate and enhance your products to provide personalized and customized customer experiences, and meet key business and revenue goals. notifiers is a general wrapper for a variety of 3rd party providers and built in ones (like SMTP) aimed solely at sending notifications. Pushover is a tool that makes it easy to get real-time notifications on your Android, Android Wear, iPhone, iPad, Apple Watch and Desktop. Simplepush is a tool to send end-to-end encrypted push notifications to your Android and iPhone. UnifiedPush is a set of specifications and tools that lets the user choose how push notifications are delivered. All in a free and open source way. RSS Back to the Top RSS Guard is a simple RSS/ATOM feed reader for Windows, Linux, BSD, OS/2 or macOS which can work with RSS/ATOM/JSON feeds as well as many online feed services: Feedly Gmail Google Reader API ( Bazqux , FreshRSS , Inoreader , Miniflux , Reedah , The Old Reader and more) Nextcloud News Tiny Tiny RSS Feedly is an RSS tool where you can privately organize and research the topics and trends that matter to you. It offers useful integrations with Facebook, Twitter, Evernote, Buffer, OneNote, Pinterest, LinkedIn, IFTTT, and Zapier so that you can easily share stories with your networks and teammates. FreshRSS is a self-hosted RSS and Atom feed aggregator. It is lightweight, easy to work with, powerful, and customizable. ArchiveBox is a powerful, self-hosted internet archiving solution to collect, save, and view sites you want to preserve offline. It takes URLs/browser history/bookmarks/Pocket/Pinboard/etc., saves HTML, JS, PDFs, media, and more. RSSHub is an open source, easy to use, and extensible RSS feed generator. It's capable of generating RSS feeds from pretty much everything. Miniflux V2 is a minimalist and opinionated feed reader. Websites/Blogs Back to the Top Hugo is a static HTML and CSS website generator written in Go. It is optimized for speed, ease of use, and configurability. Hugo takes a directory with content and templates and renders them into a full HTML website. Lyra is a fast, in-memory, typo-tolerant, full-text search engine written in TypeScript. Hugo Lyra is a typescript module for creating LyraSearch indexes for static Hugo sites, it comes with server and client libraries. Kopage is a self-hosted Website Builder. It's compatible with cPanel and other popular hosting control panels. Compatible with cPanel and other popular hosting control panels. Ghost is a fully-managed PaaS & self-hosted open source software, and can be installed and maintained relatively easily on just about any VPS hosting provider. Cloudron is a self-hosted immutable infrastructure design allows easy migration of apps across servers. In fact, you can move your entire server along with all its apps to another cloud provider in no time. Directus is a real-time API and App dashboard for managing SQL database content. Haven is a Self-hosted private blog instead of using Facebook. Antville is an open source project aimed at the development of a simple site hosting system with many advanced features . October is a Self-hosted Content Management System (CMS) and web platform whose sole purpose is to make your development workflow simple again. Grav is a Fast, Simple, and Flexible, file-based Web-platform. There is Zero installation required. Just extract the ZIP archive, and you are already up and running. It comes with a powerful Package Management System to allow for simple installation and upgrading of plugins and themes, as well as simple updating of Grav itself. Orchard is a free, open source, community-focused Content Management System built on the ASP.NET MVC platform. Netlify CMS is a CMS for static site generators. Give users a simple way to edit and add content to any site built with a static site generator. Zola is a fast static site generator in a single binary with everything built-in. FlatPress is a lightweight, easy-to-set-up blogging engine. Chyrp Lite is an ultra-lightweight blogging engine. It provides four beautiful blog themes and a friendly administration console, all fully navigable on a broad range of devices, thanks to the power of responsive HTML5. WriteFreely is an open source platform for building a writing space on the web. Sandstorm is an open source project built by a community of volunteers with the goal of making it really easy to run open source web applications. YunoHost is a Debian-based distribution which strives to make it easy to quickly set up a server and host web applications. Social Back to the Top Mattermost is a secure, open source platform for communication, collaboration, and workflow orchestration across tools and teams. Mastadon is a a decentralized social media platform that supports audio, video and picture posts, accessibility descriptions, polls, content warnings, animated avatars, custom emojis, thumbnail crop control, and more, to help you express yourself online. Telegram is a cross-platform, cloud-based instant messaging service. It has an open API and source code free for everyone. Telegram also provides end-to-end encrypted video calling, VoIP, file sharing and several other features. ActivityPub is a decentralized social networking protocol based on the ActivityStreams 2.0 data format. It provides a client to server API for creating, updating and deleting content, as well as a federated server to server API for delivering notifications and subscribing to content. Lemmy is similar to sites like Reddit, Lobste.rs, or Hacker News. Where you subscribe to forums you're interested in, post links and discussions, then vote, and comment on them. Behind the scenes, it is very different; anyone can easily run a server, and all these servers are federated, and connected to the same universe, called the Fediverse. Lemmy-UI is the official web app for Lemmy , written in inferno. Mlem is a Lemmy client for iOS. Jerboa is an Android client for Lemmy, a federated reddit alternative. GoToSocial is an ActivityPub social network server, written in Golang. Berty is a secure peer-to-peer messaging app that works with or without internet access, cellular data or trust in the network. Pleroma is a free and open communication for everyone. Pleroma is social networking software compatible with other Fediverse software such as Misskey, Pixelfed, Mastodon and many others. Matrix is a tool that gives you simple HTTP APIs and SDKs (iOS, Android, Web) to create chatrooms, direct chats and chat bots, complete with end-to-end encryption, file transfer, synchronised conversation history, formatted messages, read receipts and more. Element is a Matrix web client built using the Matrix React SDK . Nostr(Notes and Other Stuff Transmitted by Relays) is a truly censorship-resistant alternative to Twitter that has a chance of working. Fritter is an open source frontend for Twitter on mobile devices, focusing on giving you the best experience and keeping your data private, local and in your hands. Nitter is a free and open source alternative Twitter front-end focused on privacy and performance. All requests go through the backend, meaning the client never talks to Twitter and prevents Twitter from tracking your IP or JavaScript fingerprint. Diaspora is a privacy-aware, distributed, open source social network. Hubzilla is a general purpose communication server integrated with a web publishing system and a decentralised permission system. Expanse is a fully selfhosted multi-user web app for externally storing Reddit items (saved, created, upvoted, downvoted, hidden) to bypass Reddit's 1000-item listing limits. Apollo is a beautiful Reddit app built for fast navigation with an incredibly powerful set of features. Infinity is a Reddit client on Android written in Java. It does not have any ads and it features a clean UI and smooth browsing experience. RedReader is an unofficial open source Reddit client for Android. Nostr Back to the Top Nostr (Notes and Other Stuff Transmitted by Relays) is a protocol, designed for simplicity, that aims to create a censorship-resistant global social network. The protocol is based on very simple & flexible event objects (which are passed around as plain JSON) and uses standard elliptic-curve cryptography for keys and signing. nostr - overview and FAQ. NIPs - the " N ostr I mplementation P ossibilities" describe the protocol in technical detail. nostr, a basic tour - an intro to nostr. UseNostr - A small guide for anyone who wants to learn more about how nostr works and what it can do. nostr.how - Quick-start to onboard desktop users with Alby & Astral. nostr.guide - A guide to all things nostr. nostr address book - A directory of twitter users accounts and their NOSTR addresses. NNostr - a C# relay. nostr-rs-relay - a minimalistic relay written in Rust that saves data on SQLite. Relayer Basic - a simple relay based on relayer backed by Postgres. nodestr - a Node.js implementation. sovereign-stack - a tool that helps you deploy nostr relays and create self-hosted (bitcoin-only) Value4Value websites. expensive relay - a relay that requires payment for registration me.untethr.nostr-relay - a relay written in Clojure Minds Nostr Relay - a relay for Minds , an open-source social network Minds Engine - Nostr - relevant Minds API code for reading/writing Minds posts using Nostr NostrPostr Relay - a Kotlin Relay supporting both SQLite and Postgresql nostrpy - relay, client, and other tooling in python nostream - a nostr relay written in Typescript backed by PostgreSQL (renamed from nostr-ts-relay) nostr_relay – a nostr relay written in python, backed by SQLite søstr – a private nostr relay written in rust, saves all notes from one pubkey and publish them to anyone that requests them knostr – a nostr relay implemented in Kotlin with support for Postgres and metrics(micrometer). PyRelay – a python implementation of a nostr relay, using asyncio. strfry – C++ implementation backed by LMDB with efficient syncing of events using merkle trees Astro – Elixir based implementation built to be performant and highly distributed. Nex - A powerful and scalable Nostr relay written in Elixir with Postgres DB. gnost-relay - nostr relay written in go backed by postgresql database. nostring - A Nostr relay written in Deno. Denostr - Deno based, cloud native nostr implemention support by ByteTrade and Revo. nostr-relay-nestjs - A Nostr relay implemented using the NestJS framework Ephemerelay - An in-memory Nostr relay that doesn't store data. Servus - A self-contained, single executable, CMS / blogging engine reminiscent of Jekyll which also acts as a personal Nostr relay for your blog posts. Written in Rust. nostr relay registry - real-time checking of status of some known relays. nostr.info - real-time checking of status of some known relays. nostr.watch - real-time checking of status of some known relays. Astral - a branle fork with global feed and UI makeover damus - a twitter-like nostr client for iOS and MacOS. more-speech - desktop client for nostr written in Clojure. futr - nostr client desktop app written in Haskell. Minds - open source social network. Supports reading and creating posts using the Nostr protocol. Jester - Chess over nostr. Jester instance Sendstr - shared clipboard between devices over nostr. nosbin - pastebin over nostr. noscl - a basic command-line client written in Go. loquaz - a desktop app written in Rust for direct encrypted chat. nostr console - a nostr command line client written in Dart. Binaries available for Windows, Linux, and MacOS. ArcadeCity - Public group chats and P2P services (WIP) over nostr. second exchange - an experiment to work out something of like medium, something of creator economy where users are rewarded for engaging in quality discussion and most importantly engaging in governance-related discussion. scalastr - A barebones nostr client written in scala. Nostros - A nostr mobile client for Android. Nostrify.me - Nostr client built in SvelteKit. NostrEmitter - Simple E2E encrypted client and EventEmitter object Lightning.Pub - A nostr daemon for Lightning nodes. shockwallet - A Lightning wallet that uses nostr and lnurl to connect to nodes. coracle - A nostr web client. nostrweb - another nostr web client in vanilla JS. nostr.ch - live instance Bija - A desktop client written in python. Currently Linux only. Nosky - A native Android client for Nostr. Still in development. Stackerstan - A decentralised organisation built on Bitcoin and Nostr, implemented as a replicated state machine in Golang. nostr-java - A nostr client API written in java, for generating, signing and publishing events to relays. bolt.fun - A bitcoin lightning makers community that supports reading and creating comments using Nostr. iris - A nostr web client. iris.to - live instance Android app gossip - A desktop client in rust presented with egui. Attached - Open-Source ReactNative Expo app for Nostr (iOS, Android). Currently under app stores review. Member - Progressive Web App Client. Works on desktop and mobile. member.cash - live instance dispute - A cross-platform (Linux, Android, iOS, MacOs, Windows and Web) client for NOSTR Snort - Nostr UI written in react Hamstr - A twitter-style web client built with Vue.js Nozzle - A Twitter-like native Android client written with Jetpack Compose electron-nostr - A bare-bones desktop nostr client using electron-react-boilerplate. Goal is to be an easy template for people to experiment with different ideas on decentralized ratings, reputation, and web of trust. Nostrid - Multi-platform client currently offering binaries for Android, Windows, MacOS and Linux. Nostrid.Web - Web version running completely on the browser. It can be installed locally as PWA. nostr-chat-widget-react - A React component that provides a live-chat widget over nostr that can be embedded into any website. Blockcore Notes - Progressive Web App that can be installed on mobile and desktop, organize following in circles and have both public and private following lists. Dynamic interface for different uses, such as optimized for photograph viewing. Noteon - Yet another nostr client focused on private chat and group chat with a simple, elegant and secure interface. emon - Encrypted DMs over nostr with lightning payments integrated (WIP). notebin.org - Nostr UI created with NextJS, support for markdown and code highlighting. Daisy - Mobile client for Android and iOS. Flycat - A 2000s old-school style web client which support blogging on Nostr. Amethyst - An Android client for nostr written in Kotlin. MeShell - Web, iOS and Android blog type client destined to publish articles and researches for independent journalists. Disgus - A comment widget like Disqus, but for Nostr. Tamga - An offline first nostr contact & profile manager for iOS! nostromat - A Twitter-style Nostr web client, written in Clojurescript/React. nostrom.at - live instance. blogstack.io - Blogging site for nostr, supports markdown. Votestr - Poll web app with nostr authentication and blind signature unlinkability. gnost-deflate-client - A CLI nostr client written in go implementing permessage-deflate websocket compression. algia - A cli application for nostr. algia-web - A small resource consumption oriented Nostr web client. Blowater - A desktop Web client focusing on chat with delightful UX. Written Self hosted blog using nostr long-form content (NIP-23) and it shows only posts by selected authors. Nostr Nests - Nostr Nests is an audio space for chatting, brainstorming, debating, jamming, micro-conferences and more. nblog - a self-host nostr ghost blog Nostribe.com - Nostr client web app built with Next.js 13 and TypeScript. Nostribe.com - Live instance. Nostrtium - Post to Nostr directly from within WordPress uBlog - A minimalist blog on nostr that allows anyone to easily create their own personal micro-blog. Listr - A Nostr Web Client for Making Lists, built with Next.js 13 and TypeScript. nostr-ruby - a Ruby implementation of the nostr protocol. nostr - a Ruby Nostr gem for use by clients. NNostr.Client - a C# Nostr library for use by clients. nostr-tools - a JavaScript client that abstracts the relay management code for use by clients. nostr-relaypool-ts - a TypeScript relay pool library on top of nostr-tools that simplifies handling subscriptions to multiple servers. nostr-react - React Hooks for Nostr. go-nostr - a Go library that implements relay management, plus event encoding and signing utils. nostr_rust - Functional Rust implementation of the nostr protocol. nostr-js - a javascript implementation of the nostr protocol. nostr-rs - a Rust implementation of the nostr protocol nostr nostr : Rust implementation of Nostr protocol. nostr-sdk : High level client library. bindings : UniFFI (Kotlin, Swift, Python, Ruby) bindings. relayer - a server framework for writing custom relays. NostrPostr - a Kotlin Nostr library for clients or relays. python-nostr - a python library for making clients. nostr-bot - a Rust library for writing bots. NostrKit - a Swift library for interacting with relays. nostr-relay-inspector - A library that returns useful information about relays based on nostr-js. schorr_snap - A snap plugin for Metamask Flask, supports nostr. nostr-deno - a client library for Deno javascript runtime. nostr-types - a rust library defining types useful for the nostr protocol. dart-nostr - a Dart library for Flutter. nostr-connect - Nostr Connect SDK for TypeScript is a library that allows you to easily integrate Nostr Connect into your web application. pynostr - a python library for nostr. nostr-php - a PHP library for nostr. smtp nostr gateway - a bridge that forwards emails to pubkeys as encrypted direct messages. matrix-nostr-bridge - a simple Matrix-to-Nostr or Nostr-to-Matrix bridge. Mostr - a bridge between Nostr and the Fediverse (Mastodon, ActivityPub, etc.). nostrich.fun - A feature-rich directory of nostr projects. A fork of LightningNetworkStores.com git-nostr-tools - A cli tool for sending code patches over nostr. nostr-cln-events - A CLN plugin to push clightning node events to nostr. nostr registry - a database of known relays with their uptime and NIP support tables nostr-fzf - Nostr Directory; a tool for searching usernames and channels. nostr-notify - desktop nostr notifications using libnotify. nostr-launch - A tool for launching a bunch of relays and clients locally for development and testing. nostr GitHub Action - send events from GitHub Actions. nostrefresh - A simple refresh function for nostr web pages. anonroom - anonymous chat room inside nostr. nostril - A C cli tool for creating nostr events. nostr-rs-relay-compose - A Docker compose deployment for nostr-rs-relay with SSL support based on Traefik. nostr.guru - a nostr web gateway for viewing events by their ID. nostrandom.netlify.app - generate publish-able Nostr event with random keys. nashboard - A Nostr network dashboard with network statistics, reachable here . ndxstr - nostr's layer 2 indexing nodes, with more advanced querying capability than currently supported by relays. nostrillery - A tool for running performance tests against Nostr relays. nostr-terminal - A SSH-like access to your machine via web terminal, powered by Nostr. nostreq - A Nostr relay event request generator. nostr.io - A network statistics with last published notes, top 50 publishers, and top 50 followed users. nostr-commander - A simple but convenient CLI-based Nostr app for following users, sending DMs, etc. nostr.directory - A searchable database of nostr users and their other social media links. nostr-tool - A Rust CLI tool to generate and publish events. frostr - Create joint nostr identities and require t-of-n signatures to post. nostr.rest - Mine proof of work public keys with user specified prefixes. lnpass - A key manager for Lightning and nostr. sb.nostr.band - Search bots that you can create and follow to receive new posts matching a keyword right into your feed. rss.nostr.band - Create custom RSS feeds with posts matching your keywords and consume using your favorite RSS reader. nostrview - A nostr search engine. Search by content, tags, events or pub keys. nostr-bulk-dms - A tool that allows you to send DMs over nostr to many recipients in bulk. nostrify - A Core Lightning plugin that sends events (forwards, connect, disconnect, etc.) to nostr. nip06-web - a website to generate or restore NIP-06 seed phrases nip06-cli - a Node.js CLI to generate or restore NIP-06 seed phrases. nostr-broadcast - A tool lets you take your events from some relays and broadcast them to another relay. Could be helpful for backing up your notes to a private relay. nostr-follow-bundler - A tool lets you create lists of profiles that other users can then see and follow themselves. nostr-proxy - Push and get events to your Proxy, get results from multiple Nostr relays. nostrends - Trending on Nostr, like Twitter trends. Live at nostrends.vercel.app . homebrew-nostr - Homebrew tap for Nostr software. heyxynip5 - A CLI helper for converting nostr npub/nsec to their hex format for NIP-05 verification. http-nostr-publisher - A Cloudflare worker to publish Nostr events to relays through a non-blocking HTTP interface . blastr - A nostr cloudflare workers proxy relay that publishes to all known relays. keystr-rs - An application for managing Nostr keys. Written in Rust, with simple UI (Iced). nostr_simple_publish - Drupal module to publish content to Nostr. nostr-spam-detection - An experiment in building a machine learning model to label Nostr spam content for filtering and relay rejection. blogsync - Self-host blog articles from long-form notes e.g. via Caddy server. NostrFlu - A tool to collect and resend following lists from relays. You can also check badges. nkcli - A CLI tool for nostr key manage and serve NIP-46. git-nostr - A tool to enhance git cli with nostr communications. nostr-wtf - A set of nostr tools available and deployed on a web app including a pubkey converter and relay query tool . strfry policies - A collection of moderation & antispam policies for the strfry relay developed in TypeScript/Deno. nostrum - Nostrum it's a mobile app that allows you to sign transactions and messages with your Nostr keys. Nostrum is the reference implementation for a remote signer app (ie. Wallet) of the Nostr Connect protocol. nostr-signing-device - Signing device for Nostr built on ESP32. iMessage Back to the Top Beeper HitHub iMessage - Getting Started Guide - Beeper iMessage-exporter is a binary exports iMessage data to txt or html formats. It can also run diagnostics to find problems with the iMessage database. pypush is a POC demo of my recent iMessage reverse-engineering. It can currently register as a new device on an Apple ID, set up encryption keys, and send and receive iMessages! Self-Host Beeper is a self-hosted universal chat app that can chat with your friends on iMessage from your Android device using your phone number. You can also join iMessage Group Chats with your phone number and blue bubbles, and share full-resolution images, videos, and audio. Beeper Mini is an Andorid app that can chat with your friends on iMessage from your Android device using your phone number. You can also join iMessage Group Chats with your phone number and blue bubbles, and share full-resolution images, videos, and audio. Beeper Bridge Manager is a tool for running self-hosted bridges with the Beeper Matrix server. Matrix Ansible and Docker Deploy is a Matrix (An open network for secure, decentralized communication) server setup using Ansible and Docker. Communications Back to the Top Matrix is a tool that gives you simple HTTP APIs and SDKs (iOS, Android, Web) to create chatrooms, direct chats and chat bots, complete with end-to-end encryption, file transfer, synchronised conversation history, formatted messages, read receipts and more. Postmoogle is an actual SMTP server that allows you to send and receive emails on your matrix server. It can't be used with arbitrary email providers, because it acts as an actual email provider itself, so you can use it to send emails from your apps and scripts as well. SimpleX is a privacy redefined messenger without user IDs. Other apps have user IDs: Signal, Matrix, Session, Briar, Jami, Cwtch, etc. SimpleX does not, not even random numbers. Element is a Matrix web client built using the Matrix React SDK . Mattermost is a secure, open source platform for communication, collaboration, and workflow orchestration across tools and teams. Mastadon is a a decentralized social media platform that supports audio, video and picture posts, accessibility descriptions, polls, content warnings, animated avatars, custom emojis, thumbnail crop control, and more, to help you express yourself online. Telegram is a cross-platform, cloud-based instant messaging service. It has an open API and source code free for everyone. Telegram also provides end-to-end encrypted video calling, VoIP, file sharing and several other features. Berty is a secure peer-to-peer messaging app that works with or without internet access, cellular data or trust in the network. Pleroma is a free and open communication for everyone. Pleroma is social networking software compatible with other Fediverse software such as Misskey, Pixelfed, Mastodon and many others. ffsend is a easily and securely share files from the command line. A fully featured Firefox Send client. Nostr(Notes and Other Stuff Transmitted by Relays) is a truly censorship-resistant alternative to Twitter that has a chance of working. Diaspora is a privacy-aware, distributed, open source social network. Hubzilla is a general purpose communication server integrated with a web publishing system and a decentralised permission system. Expanse is a fully selfhosted multi-user web app for externally storing Reddit items (saved, created, upvoted, downvoted, hidden) to bypass Reddit's 1000-item listing limits. giscus is a comments system powered by GitHub Discussions. Let visitors leave comments and reactions on your website via GitHub. Mailroute is a great tool that provides the best email filtering & security( CMMC, NIST 800-171, DFARS, DISA, HIPPA). It protects your inbox, stop spam, viruses, ransomware, security threats & more with email filtering services. With an easy setup on Office 365, Google & more. Docker Mailserver is a production-ready fullstack but simple mail server (SMTP, IMAP, LDAP, Antispam, Antivirus, etc.) running inside a container. Only configuration files, no SQL database. Diun is a CLI application written in Go and delivered as a single executable (and a Docker image) to receive notifications when a Docker image is updated on a Docker registry. iRedMail is a self-hosted email server. iRedMail Easy is a web-based deployment platform, it offers an easy to use web interface to help you deploy iRedMail server, keep your server up to date, also get fast and professional technical support from iRedMail team. Spider Email Archiver is an On-Premises Email Archiving Software. MailCow is a self-hosted email server. Nextcloud Talk is a on-premises, private audio/video conferencing and text chat through browser and mobile interfaces with integrated screen sharing and SIP integration. Poste.io Email Server is self-hosted SMTP + IMAP + POP3 + Antispam + Antivirus Web administration + Web email. It is easy setup with a DNS guide for protect from spam. Business Management Back to the Top Nextcloud is a suite of enterprise client-server software for creating and using file hosting services. It offers an on-premise Universal File Access and sync platform with powerful collaboration capabilities and desktop, mobile and web interfaces. Odoo is a suite of open source business apps that cover all your company needs: CRM, eCommerce, accounting, inventory, point of sale, project management, etc. Kanboard is project management software that focuses on the Kanban methodology. Eden Workplace is a complete workplace management platform that lets you achieve more. Desk Booking Software to make desk reservations easier for your team, including assigning permanent and hybrid desks, providing wayfinding solutions for employees. Matomo is an ethical alternative where you won't make privacy sacrifices or compromise your site. Matomo is the Google Analytics alternative that protects your data and your customer's privacy. Plausible Analytics is a simple, lightweight (< 1 KB), open-source and privacy-friendly alternative to Google Analytics. It doesn’t use cookies and is fully compliant with GDPR, CCPA and PECR. You can self-host Plausible or have us run it for you in the Cloud. Mailroute is a great tool that provides the best email filtering & security( CMMC, NIST 800-171, DFARS, DISA, HIPPA). It protects your inbox, stop spam, viruses, ransomware, security threats & more with email filtering services. With an easy setup on Office 365, Google & more. InvoicePlane is a self-hosted open source application for managing your quotes, invoices, clients and payments. Collaboration & Synchronization Back to the Top Syncthing is a continuous file synchronization program. It synchronizes files between two or more computers in real time. Synology is a tool that allows you to easily access and manage files in your Synology Drive on the go. Apart from common file types, such as documents, images, videos and music, you can also open Synology Office document, spreadsheets and slides in the user-friendly viewer provided by Drive. Nextcloud is a suite of client-server software for creating and using file hosting services. It offers an on-premise Universal File Access and sync platform with powerful collaboration capabilities and desktop, mobile and web interfaces. Lsyncd (Live Syncing Mirror Daemon) is a tool used in Linux systems to keep directories synchronized. These directories can be found locally, within the same machine, or remotely, on different machines. For remote synchronization, this article focuses on using SSH to accomplish it. FileRun is a self-hosted Google Drive alternative. It is a full featured web based file manager with an easy to use user interface. FileBrowser provides a file managing interface within a specified directory and it can be used to upload, delete, preview, rename and edit your files. It allows the creation of multiple users and each user can have its own directory. Rsync is a utility in the command line which enables users to transfer and synchronize files efficiently between a computer and an external hard drive in the entire connected network. Warpinator is a free, open-source tool for sending and receiving files between computers that are on the same network. LocalSend is a free and open-source tool that allows you to send files and messages over the local LAN network to nearby devices. Everything is sent securely over HTTPS. The TLS/SSL certificate is generated on the fly on each device. It's avilable on Windows, macOS, Linux, iOS, and Android. FileZilla Client is a fast and reliable cross-platform FTP, FTPS and SFTP client with lots of useful features and an intuitive graphical user interface. Dragit is an application for intuitive file sharing between devices. It's useful for when you want to send file from one computer to another with minimal effort. Dragit automatically detects devices in the local network with help of mDNS protocol and allows you to send file immediately. WinFsp is a set of software components for Windows computers that allows the creation of user mode file systems. In this sense it is similar to FUSE (Filesystem in Userspace), which provides the same functionality on UNIX-like computers. SSHFS-Win is a minimal port of SSHFS to Windows. Looking under the hood it uses Cygwin for the POSIX environment and WinFsp for the FUSE (Filesystem in Userspace) functionality. RiftShare is a cross platform (Windows, MacOS, Linux) file sharing tool that supports fully encrypted transfers both on the local network and off network using a simple passphrase. RiftShare uses magic-wormhole under the hood and is compatible with other magic-wormhole clients. It is also fully open source and licensed under the GPLv3. Usermode FTP Server is a tool that let's you start an FTP server as user and transfer files with any FTP client. Allowing you to access your files directly with many file browsers' builtin FTP support: Windows File Explorer, Thunar, Gnome Files, Dolphin and many more. TagSpaces is a free, no vendor lock-in, open source application for organizing, annotating and managing local files with the help of tags. It features advanced note taking functionalities and some capabilities of to-do apps. It's available for Windows, Linux, Mac OS and Android. Listmonk is a standalone, self-hosted, newsletter and mailing list manager. It is fast, feature-rich, and packed into a single binary. Encryption Back to the Top VeraCrypt is free open-source disk encryption software for Windows, Mac OS X and Linux. The file encryption, data encryption performed by VeraCrypt is real-time (on-the-fly), automatic, transparent, needs very little memory, and does not involve temporary unencrypted files. AxCrypt is an inexpensive and effective encryption tool for Windows, macOS, iOS, and Android. AESCrypt is an advanced file encryption utility that integrates with the Windows shell or runs from the Linux command prompt to provide a simple, yet powerful, tool for encrypting files using the Advanced Encryption Standard (AES). It is available for Windows, MacOS, and Linux. Linux Unified Key Setup (LUKS) is a disk encryption specification created by Clemens Fruhwirth in 2004 and was originally intended for Linux. It uses device mapper crypt ( dm-crypt) as a kernel module to handle encryption on the block device level. GNU Privacy Guard (GnuPG) is a complete and free implementation of the OpenPGP standard as defined by RFC4880 (also known as PGP ). It allows you to encrypt and sign your data and communications; it features a versatile key management system, along with access modules for all kinds of public key directories. Pretty Good Privacy (PGP) is an encryption program that provides cryptographic privacy and authentication for data communication. It's used for signing, encrypting, and decrypting texts, e-mails, files, directories, and whole disk partitions and to increase the security of e-mail communications. Deadbolt is a Dead-simple file encryption for any OS. Infisical is an open-source, end-to-end encrypted platform to sync secrets and configs across your team and infrastructure. Hemmelig.app is a tool that keeps your sensitive information out of chat logs, emails, and more with encrypted secrets. How Encryption Keys work Symmetric is a data encryption method whereby the same private key is used to encode and decode information. Asymmetric is a data encryption method that allows users to encrypt information using shared keys. For example, if you need to send a message across the internet, but you don't want anyone but the intended recipient to see what you've written. Types of Encryption Triple DES (Triple Data Encryption Algorithm) is a symmetric-key block cipher, which applies the DES cipher algorithm three times to each data block(contains 64 bits of data). AES (Advanced Encryption Standard) is an algorithm that encrypts and decrypts data in blocks of 128 bits. It can do this using 128-bit, 192-bit, or 256-bit keys. RSA (Rivest–Shamir–Adleman) is a type of public-key cryptography used for secure data transmission of e-mail and other digital transactions over the Internet. Twofish is a symmetric key block cipher with a block size of 128 bits and key sizes up to 256 bits. It is an advanced version of Blowfish encryption. Format Preserving Encryption (FPE) is a valid encryption algorithm to be used for compliance with NIST standards. It is mostly used in on-premise encryption and tokenization solutions. Application Level Encryption Hashes is a function that converts an input of letters and numbers into an encrypted output of a fixed length. For example, algorithms such as MD5 (Message Digest 5) or SHA (Secure Hash Algorithm) . Digital Certificates is a file that verifies the identity of a device or user and enables encrypted connections. A digital signature is a hashing approach that uses a numeric string to provide authenticity and validate identity. Digital certificates are typically issued by a certificate authority (CA) , which is a trusted third-party entity that issues digital certificates for use by other parties. Backups Back to the Top Proxmox Backup Server is an enterprise backup solution for backing up and restoring VMs, containers, and physical hosts. The open-source solution supports incremental backups, deduplication, Zstandard compression, and authenticated encryption. BackupPC is a high-performance, enterprise-grade system for backing up Linux, Windows and macOS PCs and laptops to a server's disk. BackupPC is highly configurable and easy to install and maintain. BorgWarehouse is a fast and modern WebUI for a BorgBackup's central repository server. Emborg is a simple command line utility to orchestrate backups. It is built as a front-end to Borg, a powerful and fast de-duplicating backup program. Borgmatic is a simple, configuration-driven backup software for servers and workstations. It protects your files with client-side encryption. Backup your databases too. Monitor it all with integrated third-party services. Vorta is a backup client for macOS and Linux desktops. It integrates the mighty Borg Backup with your favorite desktop environment to protect your data from disk failure, ransomware and theft. UrBackup is an easy to setup Open Source client/server backup system, that through a combination of image and file backups accomplishes both data safety and a fast restoration time. File and image backups are made while the system is running without interrupting current processes. Available for Windows, macOS, and Linux. Kopia is a user-friendly desktop app for Windows, macOS, and Linux which allows you to create snapshots, define policies, and restore files quickly with Fast and Encrypted Backups. Clonezilla is a partition and disk imaging/cloning program. It helps you to do system deployment, bare metal backup and recovery. Three types of Clonezilla are available, Clonezilla live, Clonezilla lite server, and Clonezilla SE (server edition). rsnapshot is a filesystem snapshot utility based on rsync. This makes it easy to make periodic snapshots of local machines, and remote machines over ssh. Duplicity is a tool that backs directories by producing encrypted tar-format volumes and uploading them to a remote or local file server. Because duplicity uses librsync , the incremental archives are space efficient and only record the parts of files that have changed since the last backup. ZnapZend is a high performance open source ZFS backup with mbuffer and ssh support. It uses the built-in snapshot functionality of ZFS for fully consistent backups. For each fileset, a pre- and post-snapshot command can be configured to quiet down any software writing to the fileset prior to snapshotting. SnapRAID is a folder-based backup tool that behaves like a software or hardware RAID5/6 disk raid, but is not a disk raid itself. There is no realtime recovery, free space between disks cannot be combined and manual excution of backup is needed. rsync.net is a Cloud Storage for Offsite Backup that give you an empty UNIX filesystem to access with any SSH tool. Built on ZFS for data security and fault tolerance with support for rsync/sftp/scp/borg/rclone/restic/git-annex. Snapshots Management/System Recovery Back to the Top rsnapshot is a filesystem snapshot utility based on rsync. This makes it easy to make periodic snapshots of local machines, and remote machines over ssh. rsync.net is a Cloud Storage for Offsite Backup that give you an empty UNIX filesystem to access with any SSH tool. Built on ZFS for data security and fault tolerance with support for rsync/sftp/scp/borg/rclone/restic/git-annex. ZnapZend is a high performance open source ZFS backup with mbuffer and ssh support. It uses the built-in snapshot functionality of ZFS for fully consistent backups. For each fileset, a pre- and post-snapshot command can be configured to quiet down any software writing to the fileset prior to snapshotting. Sanoid is a policy-driven snapshot management tool for ZFS filesystems. ZFSBootMenu is a Linux bootloader that attempts to provide an experience similar to FreeBSD's. This allows a user to have multiple "boot environments" (with different distributions, for example), manipulate snapshots before booting, and, for the adventurous user, even bootstrap a system installation via zfs recv . Btrfs maintenance toolbox is a set of scripts supplementing the btrfs filesystem and aims to automate a few maintenance tasks. This means the scrub, balance, snapshots, trim or defragmentation. Btrbk is a backup tool for btrfs subvolumes, taking advantage of btrfs specific capabilities to create atomic snapshots and transfer them incrementally to your backup locations. ksync is a toool that sync files between your local system and a kubernetes cluster. It transparently updates containers running on the cluster from your local checkout. Verify is a snapshot tool that simplifies the assertion of complex data models and documents. Timeshift is a Linux application for providing functionality to restore your system just like Windows System Restore tool. Timeshift makes snapshots of your system in regular intervals which are further used at the time of restoration or undo all changes in the system. CRIU (Checkpoint and Restore in Userspace) is a utility to checkpoint/restore Linux tasks. Using this tool, you can freeze a running application (or part of it) and checkpoint it to a hard drive as a collection of files. You can then use the files to restore and run the application from the point it was frozen at. Rsync time backup is a Time Machine style backup with rsync. It creates incremental backups of files and directories to the destination of your choice. The backups are structured in a way that makes it easy to recover any file at any point in time. It works on Linux, macOS and Windows (via WSL). rdiff-backup is a simple backup tool which can be used locally and remotely, on Linux and Windows, and even cross-platform between both. Users have reported using it successfully on FreeBSD and MacOS. Mainframer is a tool that executes a command on a remote machine while syncing files back and forth. The process is known as remote execution (in general) and remote build (in particular cases). Archiving Back to the Top Access to Memory (AtoM) - Web-based, open source application for standards-based archival description and access in a multilingual, multi-repository environment. ArchiveBox - Self-hosted wayback machine that creates HTML & screenshot archives of sites from your bookmarks, browsing history, RSS feeds, or other sources. Archivematica - Mature digital preservation system designed to maintain standards-based, long-term access to collections of digital objects. ArchivesSpace - Archives information management application for managing and providing Web access to archives, manuscripts and digital objects. CKAN - CKAN is a tool for making open data websites. Collective Access - Providence - Highly configurable Web-based framework for management, description, and discovery of digital and physical collections supporting a variety of metadata standards, data types, and media formats. Omeka S - Omeka S is a web publication system for universities, galleries, libraries, archives, and museums. It consists of a local network of independently curated exhibits sharing a collaboratively built pool of items, media, and their metadata. Wayback - A self-hosted toolkit for archiving webpages to the Internet Archive, archive.today, IPFS, and local file systems. Home Server Back to the Top Home Assistant is an open source home automation that puts local control and privacy first. Home Assistant is powered by a worldwide community of tinkerers and DIY enthusiasts that runs great on Raspberry Pi. Homebridge is a software framework that allows you to integrate with smart home devices that do not natively support HomeKit . There are over 2,000 Homebridge plugins supporting thousands of different smart accessories. Homebridge UI is a tool that provides an easy to use interface to manage your Homebridge plugins, configuration and accessories. Install and configure Homebridge plugins. Monitor your Homebridge server via a fully customisable widget-based dashboard. View and control Homebridge accessories. Backup and Restore your Homebridge instance. ESPHome is a system to control your ESP8266/ESP32 by simple yet powerful configuration files and control them remotely through Home Automation systems. Shelly Cloud is a Smart home control tool that has been perfected and provides precise monitoring of your Shelly devices no matter where you are. Shelly devices are compatible with Alexa, Google Home, Android, and iOS. Zigbee is the full-stack, secure, reliable, and market-proven solution used by a majority of large smart home ecosystem providers, such as Amazon's Echo Plus, Samsung SmartThings, Signify (Philips Hue), and more. openHAB is a cross-platform software with the aim to integrate all kinds of Smart Home technologies, devices, etc. Z-Wave is the leading wireless communications protocol behind many of the secure, trusted brands that are working to make everyone's home smarter and safer. Homey is an applciation to control, automate and monitor your entire smart home from your phone, tablet or desktop. Caddy is the only web server to use HTTPS automatically and by default. Caddy obtains and renews TLS certificates for your sites automatically. Bazarr is a companion application to Sonarr and Radarr. It can manage and download subtitles based on your requirements. You define your preferences by TV show or movie and Bazarr takes care of everything for you. Sonarr is a PVR for Usenet and BitTorrent users. It can monitor multiple RSS feeds for new episodes of your favorite shows and will grab, sort and rename them. Homarr is a customizable browser's home page to interact with your homeserver's Docker containers (e.g. Sonarr/Radarr) Midarr is a free and open source (and always will be), Midarr aims to provide a tailored experience for you and your users: Beautifully crafted user interface. Real-time online statuses. Simple and easy invite system. Integrates with your existing services, Radarr and Sonarr. Rustdesk is an open source virtual/remote desktop infrastructure for everyone. Display and control your PC (Windows, macOS, and Linux) and Android devices. TinyPilot is a tool that enables KVM over IP letting you control any computer remotely. PM2 is a production process manager for Node.js applications with a built-in load balancer. It allows you to keep applications alive forever, to reload them without downtime and to facilitate common system admin tasks. authentik is an open-source Identity Provider focused on flexibility and versatility. You can use authentik in an existing environment to add support for new protocols. authentik is also a great solution for implementing signup/recovery/etc in your application, so you don't have to deal with it. ESPHome Remote IS a WI-FI smart home remote with display that runs on ESPHome. It uses Lilygo T-Display or M5Stack Fire. Tdarr is a distributed transcode automation application using FFmpeg/HandBrake + Audio/Video library analytics + video health checking (Windows, macOS, Linux & Docker). A common use for Tdarr is to simply convert video files from h264 to h265 (hevc), saving 40%-50% in size. AppFlowy is an open-source alternative to Notion where you're in charge of your data and customizations. deemix is a barebone deezer downloader library built from the ashes of Deezloader Remix. Neko is a self hosted virtual browser that runs in docker and uses WebRTC. QNAP Switch System (QSS) is a configuration interface for QNAP's managed switch series. Enable management functions such as link aggregation, VLAN, and RSTP, to take care of your network topology with ease. ASUSTOR is a subsidiary of ASUS and a leading provider of network attached storage (NAS). It specializes in the development and integration of storage, backup, multimedia, video surveillance and mobile applications for home and enterprise users. Seafile is an open-source, cross-platform file-hosting software system. Seafile organize files into libraries stored on a central server. Each library can be synced into any desktop computer(Windows, Mac and Linux) and mobile devices through apps. SnapRAID is a folder-based backup tool that behaves like a software or hardware RAID5/6 disk raid, but is not a disk raid itself. There is no realtime recovery, free space between disks cannot be combined and manual excution of backup is needed. FreeNAS is an Open Source Storage Platform and supports sharing across Windows, Apple, and UNIX-like systems. This includes ZFS (high storage capacities and integrates file systems and volume management into a single piece of software). It supports UPS, CIFS/SMB, FTP, NFS, RSYNC, SSH, AFP, Unison, UPnP, Webserver, iSCSI protocols, local and MS AD authentication, and disk enctyption. Gladys Assistant is a privacy-first, open-source home assistant and runs great on Raspberry Pi. Audiobookshelf is a self-hosted audiobook and podcast server. Mistborn is a secure platform for easily standing up and managing your own cloud services: including firewall, ad-blocking, and multi-factor WireGuard VPN access. Media Server Back to the Top Overseerr is a free and open source software application for managing requests for your media library. It integrates with your existing services, such as Sonarr , Radarr , and Plex . Jellyfin is a Free Software Media System that puts you in control of managing and streaming your media. It is an alternative to the proprietary Emby and Plex, to provide media from a dedicated server to end-user devices via multiple apps. Swiftfin is a modern video client for the Jellyfin media server. Redesigned in Swift to maximize direct play with the power of VLC and look native on all classes of Apple devices. Intro Skipper is a tool that analyzes the audio of television episodes to detect and skip over intro sequences in Jellyfin. Jellyseerr is a free and open source software application for managing requests for your media library. It is a a fork of Overseerr built to bring support for Jellyfin & Emby media servers. Midarr is a free and open source (and always will be), Midarr aims to provide a tailored experience for you and your users: Beautifully crafted user interface. Real-time online statuses. Simple and easy invite system. Integrates with your existing services, Radarr and Sonarr. Kirino Media Server is a lightweight, modular alternative to Plex and Jellyfin. Emby is a home media server built on top of other popular open source technologies such as Service Stack, jQuery, jQuery mobile, and Mono. It features a REST-based API with built-in documention to facilitate client development. OpenMediaVault is a next generation network attached storage (NAS) solution based on Debian Linux. It contains services like SSH, (S)FTP, SMB/CIFS, AFS, UPnP media server, DAAP media server, RSync, BitTorrent client and many more. MediaElch is a MediaManager for Kodi. Information about Movies, TV Shows, Concerts and Music are stored as NFO files. tinyMediaManager is a media management tool written in Java/Swing. It is written to provide metadata for the Kodi Media Center (formerly known as XBMC), MediaPortal and Plex media server. FileBot is the ultimate tool for renaming and organizing your movies, TV shows and Anime. Match and rename media files against online databases, download artwork and cover images, fetch subtitles, write metadata, and more, all at once in matter of seconds. Plex media server is a application that gives you the power to add, access and share all the entertainment that matters to you, on almost any device. With 50,000+ on demand titles and hundreds of channels of live TV, plus your own personal media collection, using one powerful app. Tautulli is a 3rd party application that you can run alongside your Plex Media Server to monitor activity and track various statistics. Plex DupeFinder is a python script that finds duplicate versions of media (TV episodes and movies) in your Plex Library and tells Plex to remove the lowest rated files/versions (based on user-specified scoring) to leave behind a single file/version. Prometheus Exporter for Plex is an expose library playback, storage, and host metrics in a Prometheus format. Infuse is a Video Player for iOS, Apple TV, and Mac. It plays every video file ever created to avoid wasting hours converting and transcoding files. InfuseSync is a plugin for Emby and Jellyfin media servers that tracks all media changes to decrease sync times with Infuse clients. InvidTUI is an invidious client, which fetches data from invidious instances and displays a user interface in the terminal, and allows for selecting and playing Youtube audio and video. Polaris is a music streaming application, designed to let you enjoy your music collection from any computer or mobile device. Polaris works by streaming music directly from your computer (or cloud server), without uploading it to a third-party. AirSonic is a free, web-based media streamer, providing ubiquitous access to your music. TubeSync is a PVR (personal video recorder) for YouTube. Or, like Sonarr but for YouTube (with a built-in download client). It is designed to synchronize channels and playlists from YouTube to local directories and update your media server once media is downloaded. yt-fts is a simple python script that uses yt-dlp to scrape all of a youtube channels subtitles and load them into an sqlite database that is searchable from the command line. It allows you to query a channel for specific key word or phrase and will generate time stamped youtube urls to the video containing the keyword. Tube Archivist is a self hosted YouTube media server. PeerTube is an ActivityPub-federated video streaming platform using P2P directly in your web browser. Ant Media Server is a streaming engine software that provides adaptive, ultra low latency streaming by using WebRTC technology with ~0.5 seconds latency. Castopod is an open-source hosting platform made for podcasters who want engage and interact with their audience. Festival is a music player for local album collections. HD HomeRun Scribe 4K is a free local live TV with DVR with 4 tuners and 150 hours of recording storage all-in-one amazing box for watching and recording free TV all around your home. RuneAudio is a free and open source software that turns embedded hardware into Hi-Fi music players. Volumio (The Audiophile Music Player) is a very powerful and convenient music aggregator, now Volumio can also be used with great results in all sorts of different situations. Snapcast is a multiroom client-server audio player, where all clients are time synchronized with the server to play perfectly synced audio. It's not a standalone player, but an extension that turns your existing audio player into a Sonos-like multiroom solution. SonoBus is an easy to use application for streaming high-quality, low-latency peer-to-peer audio between devices over the internet or a local network. MythTV is a Free Open Source software digital video recorder (DVR) project distributed under the terms of the GNU GPL. Smart Home Automation Back to the Top Smart home is a process that allows homeowners to control appliances, thermostats, lights, and other smart devices remotely using a smartphone or tablet through an internet connection. Most smart devices have their own Virtual Local Area Network (VLAN) with little to no internet access with broadcasts forwarding to LAN Subnet aka Subnetwork for discovery. Using software such as Home Assistant, Homebridge, ESPHome, etc. help simplify the process of controlling and automating all your smart devices. Matter is an open standard for smart home technology that lets your device work with any Matter-certified ecosystem using a single protocol. Matter comes from the Connectivity Standards Alliance , an organization of hundreds of companies(Amazon, Apple, Google, Comcast, Zigbee Alliance, and Connectivity Standards Alliance (CSA) creating products for the smart home. Proprietary Smart Devices Amazon Alexa is a smart virtual assistant software to manage Alexa-enabled devices, control music playback, view shopping lists on the go, keep track of upcoming reminders, check on active timers and much more. Google Assistant is a smart virtual assistant software on mobile and home automation devices. Apple HomeKit is a software framework that enables your app to coordinate and control home automation accessories from multiple vendors to present a coherent, user-focused interface. Using HomeKit, your app can: Discover HomeKit-compatible automation accessories and add them to a persistent, cross-device home configuration database. Samsung SmartThings is a sofwtare framework that you can connect, monitor and control multiple smart home devices quicker and easier. Connect your Samsung smart TVs, smart appliances, smart speakers and brands like Ring, Nest and Philips Hue all from one app. Philips Hue is a smart lighting system. The smart lights, Hue Bridge, and smart controls will forever change the way you experience light. Sonos is the wireless home sound system that fills as many rooms as you want with great-sounding music, movies, and TV. ------------------------------------------------------------------ Home Assistant is an open source home automation that puts local control and privacy first. Home Assistant is powered by a worldwide community of tinkerers and DIY enthusiasts that runs great on Raspberry Pi. $13 USD voice assistant remote for Home Assistant Add-ons are additional applications and services, that can be run alongside Home Assistant. The Home Assistant OS and Supervised installations types, provide the Supervisor, which is capable of running and managing these add-ons. Home Assistant Official Add-ons Addons created and maintained by the Home Assistant team. DuckDNS - This updates your Duck DNS IP address and generate SSL using Let's Encrypt. Almond - An Open, Privacy-Preserving Virtual Assistant. HomeMatic - HomeMatic central based on OCCU. Let's Encrypt - Get a free SSL certificate from Let's Encrypt; an open and automated certificate authority (CA). MariaDB - An open source relational database (fork of MySQL). File editor - Browser-based configuration file editor. Mosquitto - Fast and reliable MQTT broker. Terminal & SSH - Allows logging in remotely to using a web terminal or SSH client. Samba - Access your configuration files using Windows network shares. NGINX SSL proxy - Reverse proxy with SSL termination. deCONZ - Control a ZigBee network using ConBee or RaspBee hardware by Dresden Elektronik. TellStick - Run a TellStick and TellStick Duo service. Ada - Ada is voice assistant powered by Almond which is open and privacy-preserving. Fully Kiosk Browser is a powerful kiosk browser for Android devices. It provides a number of features for monitoring and controlling your Android device. This integration gives you access to control your device and view the status in Home Assistant. Home Assistant Third Party Add-ons Add-ons created by the community. Dasshio - Easily use your Amazon Dash Buttons. InfluxDB - Scalable datastore for metrics, events, and real-time analytics. Grafana - Open platform for beautiful analytics and monitoring. Tor - Protect your privacy and access your instance via Tor. Spotify Connect - Spotify Connect client for playing music on your Home Assistant device. SSH & Web Terminal - SSH and Web-based terminal with tons of pre-loaded useful tools. UniFi Controller - The UniFi Controller allows you to manage your UniFi network using a web browser. Node-RED - Flow-based programming for the Internet of Things. Plex Media Server - Your recorded media beautifully organized and ready to stream. IDE - Advanced web-based IDE, based on Cloud9 IDE. zigbee2mqtt - Zigbee to MQTT bridge, get rid of your proprietary Zigbee bridges. Matrix - A secure and decentralized communication platform. AdGuard Home - A network-wide ad-and-tracker blocking DNS server with parental control. Traccar - Traccar is modern GPS Tracking Platform. Home Panel - A touch-compatible web frontend for controlling the home. Hass.io Google Drive Backup - A complete and easy to configure solution for backing up your snapshots to Google Drive. Grocy - A groceries & household management solution for your home. EmonCMS - A powerful open-source web app for processing, logging, and visualizing energy, temperature, and other environmental data. CrowdSec - A next-gen collaborative IPS/IDS to protect you from intrusion. AppDaemon - Python Apps and HADashboard. TasmoAdmin - Centrally manage all your Sonoff-Tasmota devices. Aircast - AirPlay capabilities for your Chromecast players. AirSonos - AirPlay capabilities for your Sonos players. Log Viewer - Browser-based live log viewing utility. Tautulli - Monitor and get statistics from your Plex server. motionEye - Simple, elegant and feature-rich CCTV/NVR for your cameras. JupyterLab - Create documents containing live code, equations, visualizations, and explanatory text. Glances - A cross-platform system monitoring tool written in Python. Home Assistant Custom Cards The Home Assistant Dashboards allows people to build custom cards on top of it, which you can easily add to your instance. Simple Thermostat - A simpler and more flexible thermostat card. Card Modder - Style your Lovelace cards. Bar Card - Customizable animated bar card. forked-daapd Card - Control a forked daapd instance. Dual Gauge Card - Shows two gauges in one. Atomic Calendar Revive - Calendar card with advanced settings. Simple Weather Card - A minimalistic weather card, inspired by Google Material Design. Auto-Entities Card - Dynamically adds entities. Canvas Gauge Card - Use awesome gauges from canvas-gauges.com. Big Number Card - Display big numbers for sensors, including severity level as background. Animated Weather Card - Nice looking card showing the weather, with subtle animations. Thermostat Card - Thermostat control card that looks like a Nest Thermostat. Raspberry Pi Status Card - Show status of your Raspberry Pis. Mini Media Player - A minimalistic media player card. Mini Graph Card - A minimalistic sensor graph card. Button card - Button card for your entities. Slider Entity Row - Add a slider to adjust, e.g., the brightness of lights in lovelace entity cards. Power Wheel Card - An intuitive way to represent the power that your home is consuming or producing. Home Card - A quick glance of the state of your home. Banner Card - A fluffy linkable banner with interactive glances to spice up your home dashboards. Spotify Card - List and select from current available devices and users top playlists on Spotify. Battery Entity - Displaying battery levels for battery entities. Multiple Entity Row - Show multiple entity states or attributes on entity rows. Home Feed Card - Display a combination of persistent notifications, calendar events, and entities in the style of a feed. Config Template Card - Allow using templates in Lovelace. RGB Light Card - Colorful buttons to control your RGB Lights. Restriction Card - A card to provide restrictions on Lovelace cards defined within. Vacuum Map Card - This card provides a user-friendly way to fully control Xiaomi (Roborock/Viomi/Dreame/Roidmi) and Neato (+ possibly other) vacuums. Vacuum Card - A card to card for controlling a vacuum cleaner robot. Purifier Card - A card for controlling air purifiers. Home Assistant Custom Integrations Additional integrations for Home Assistant created by the community. Lutron Caseta Pro - Integrates Lutron Caseta Smart Bridge PRO / RA2 Select. SmartIR - Integrates devices using Broadlink IR. Alexa Media Player - Allow control of Amazon Alexa devices. Circadian Lighting - Circadian Lighting slowly synchronizes your color changing lights with the regular naturally occuring color temperature of the sky throughout the day. Volkswagen Carnet - Integrates Volkswagen Carnet (requires valid Carnet subscription). Untappd - Connects with your Untappd account. Elasticsearch - Publishes events to Elasticsearch. HASS Aarlo - Asynchronous Arlo integration. Similar to the Arlo web site; monitors events and states for all base stations, cameras and doorbells. Xiaomi Cloud Map Extractor - Presents a live view of a map for Xiaomi (Roborock/Viomi/Roidmi/Dreame) vacuums without a need for rooting. Xiaomi Hygrothermo - Sensor platform for Xiaomi Mijia BT Hygrothermo temperature and humidity sensor. WebRTC Camera - View RTSP streams from IP Cameras in real-time through WebRTC or MSE with Pan/Zoom controls. Sonoff LAN - Control Sonoff devices with eWeLink (original) firmware over LAN and/or Cloud. Spotcast - Start Spotify playback on an idle Chromecast device as well as control Spotify connect devices. The Watchman - Keep track of missing entities and services in your config files. Home Assistant integrations. Credit: Home Assistant Homebridge is a software framework that allows you to integrate with smart home devices that do not natively support HomeKit . There are over 2,000 Homebridge plugins supporting thousands of different smart accessories. Homebridge UI is a tool that provides an easy to use interface to manage your Homebridge plugins, configuration and accessories. Install and configure Homebridge plugins. Monitor your Homebridge server via a fully customisable widget-based dashboard. View and control Homebridge accessories. Backup and Restore your Homebridge instance. Homebridge Raspberry Pi Image is a free Raspbian based Raspberry Pi image with Homebridge and Homebridge Config UI X pre-installed. Homebridge Config UI X is a web based management tool for Homebridge that allows you to manage all aspects of your Homebridge setup. Homebridge webOS TV is a plugin for homebridge which allows you to control your LG webOS TV from your Home app! It should work with all TVs that support webOS2 and newer. Homebridge Unifi Protect is a Homebridge plugin that provides HomeKit support to the UniFi Protect device ecosystem. UniFi Protect is Ubiquiti's next-generation video security platform, with rich camera, doorbell, and NVR controller hardware options for you to choose from, as well as an app which you can use to view, configure and manage your video camera and doorbells. Homebridge Camera FFmpeg is a Homebridge Plugin Providing FFmpeg -based Camera Support. Homebridge Mi Aqara is a homebridge plugin for XiaoMi Aqara plugin. Homebridge Camera UI is a tool that allows you to expose cameras from camera.ui to HomeKit via Homebridge. HOOBS is a tool that makes smart accessories(over 2000 options) compatible with your favorite ecosystem. Whether you prefer Apple Homekit, Google Home, or Amazon Alexa, you’re unlikely to find compatible accessories and services that all work together nicely under one roof. ESPHome is a system to control your ESP8266/ESP32 by simple yet powerful configuration files and control them remotely through Home Automation systems. Shelly Cloud is a Smart home control tool that has been perfected and provides precise monitoring of your Shelly devices no matter where you are. Shelly devices are compatible with Alexa, Google Home, Android, and iOS. Homey is an applciation to control, automate and monitor your entire smart home from your phone, tablet or desktop. Ecobee is a home automation company in Canada that makes thermostats for residential and commercial use. Lutron Caséta is a smart lighting control system that is a great solution for giving any client smart lighting control. It was purposely built to work in homes of all ages and it works with older wiring as well as new. Insteon switches is a Hub for controlling and configuring your home's devices is quick, easy and fun. The setup takes a couple of minutes and a few moments per light switch, sensor, etc. It bridges your devices to 3rd party services like Amazon Alexa and Google Assistant, while being controlled from any smartphone or tablet. Jeedom is an open source software; taht gives you complete access to the software that manages your home automation. It's compatible with various protocols such as, ZigBee, Z-Wave, EnOcean, KNX, LoRaWAN, BACnet, Modbus, etc.. Beestat is a tool that connects with your thermostat and provides you with useful charts and analytics so that you can make informed decisions and see how the changes you make lower your energy footprint. MQTT is an OASIS standard messaging protocol for the Internet of Things (IoT). It is designed as an extremely lightweight publish/subscribe messaging transport that is ideal for connecting remote devices with a small code footprint and minimal network bandwidth. Zigbee is the full-stack, secure, reliable, and market-proven solution used by a majority of large smart home ecosystem providers, such as Amazon's Echo Plus, Samsung SmartThings, Signify (Philips Hue), and more. openHAB is a cross-platform software with the aim to integrate all kinds of Smart Home technologies, devices, etc. Z-Wave is the leading wireless communications protocol behind many of the secure, trusted brands that are working to make everyone's home smarter and safer. pfSense is a firewall/router computer software distribution based on FreeBSD. Pi-hole is a DNS sinkhole that protects your devices from unwanted content, without installing any client-side software, intended for use on a private network. It is designed for use on embedded devices with network capability, such as the Raspberry Pi, but it can be used on other machines running Linux and cloud implementations. AdGuard Home is a DNS relay station with ad/tracker/other blocking, IP address redirections, and DNS-over-HTTPS. OpenWRT is an open-source project for embedded operating systems based on Linux, primarily used on embedded devices to route network traffic. ZoneMinder is a full-featured, open source, state-of-the-art video surveillance software system. Monitor your home, office, or wherever you want. Plex media server is a application that gives you the power to add, access and share all the entertainment that matters to you, on almost any device. With 50,000+ on demand titles and hundreds of channels of live TV, plus your own personal media collection, using one powerful app. Voice Assistants Back to the Top $13 voice assistant remote for Home Assistant Wyoming is a peer-to-peer protocol for voice assistants (basically JSONL + PCM audio). It's used in Rhasspy and the Home Assistant for communication with voice services. Wyoming Faster Whisper is a Wyoming protocol server for the faster-whisper speech to text system. Wyoming Porcupine1 is a Wyoming protocol server for the porcupine1 wake word detection system. Wyoming Snowboy is a Wyoming protocol server for the snowboy wake word detection system. faster-whisper is a reimplementation of OpenAI's Whisper model using CTranslate2 , which is a fast inference engine for Transformer models. Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications. It uses deep neural networks trained in real-world environments. Rhasspy is an open source voice assistant toolkit for many human languages. openWakeWord is an open-source wakeword library that can be used to create voice-enabled applications and interfaces. It includes pre-trained models for common words & phrases that work well in real-world environments. Conversation is an integration allows you to converse with Home Assistant. You can either converse by pressing the microphone in the frontend (supported browsers only (no iOS)) or by calling the conversation/process service with the transcribed text. Piper is a fast, local neural text to speech system that sounds great and is optimized for the Raspberry Pi 4. Mycroft is an open source voice assistant that is private by default and completely customizable. DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. Leon is your open-source personal assistant. Olivia is an open-source chatbot built in Golang using Machine Learning technologies. Its goal is to provide a free and open-source alternative to big services like DialogFlow. Alan SDK is an voice assistant SDK to build a voice interface for websites and web apps (JavaScript, React, Angular, Vue, Ember, Electron). OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so. Video Surveillance Back to the Top Frigate is an open source NVR built around real-time AI object detection. All processing is performed locally on your own hardware, and your camera feeds never leave your home. hkcam is an open-source implementation of an HomeKit IP camera. It uses ffmpeg to access the camera stream and publishes the stream to HomeKit using hap. The camera stream can be viewed in a HomeKit app. OpenDataCam is an open source tool to quantify the world. It quantifies and tracks moving objects with live video analysis. It is designed to be an accessible, affordable and open-source solution to better understand interactions in urban environments. It never records any photo or video data. The system only saves surveyed meta-data, in particular the path an object moved or number of counted objects at a certain point. Viseron is a Self-hosted, local only NVR and AI Computer Vision software. zmninja is a high performance, cross platform ionic app for Home/Commerical Security Surveillance using ZoneMinder. Moonfire NVR is a security camera network video recorder. Shinobi Pro is a Next Generation in Open-Source Video Management Software with support for over 6000 IP and USB Cameras. WyzeHacks is a project contains a set of scripts trying to provide additional features not implemented by the official firmware. Currently, it provides the following functions: Enable telnetd on your camera. Customize the default root password for telnet login. Redirect all the recordings to an NFS share. Redirect console logs into an NFS share. Automatically reboot the camera at certain time. Automatically archive the recordings. Text-To-Speech Synthesis (TTS) Back to the Top whisper.cpp is a high-performance inference of OpenAI's Whisper automatic speech recognition (ASR) model. WaaS is a Whisper as a Service (GUI and API for OpenAI Whisper). Web Whisper is a OpenAI's whisper on your web browser. Demo Vosk is an offline open source speech recognition toolkit. It enables speech recognition for 20+ languages and dialects. Coqui TTS is a deep learning toolkit for Text-to-Speech, battle-tested in research and production. Mozilla TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. NVIDIA NeMo is a conversational AI toolkit built for researchers working on automatic speech recognition (ASR), text-to-speech synthesis (TTS), large language models (LLMs), and natural language processing (NLP). Video and Audio Processing Back to the Top Intel® Quick Sync Video is a tools that uses the dedicated media processing capabilities of Intel® Graphics Technology to decode and encode fast, enabling the processor to complete other tasks and improving system responsiveness. Intel® QuickAssist Technology (Intel® QAT) is a scalable, flexible, and extendable way to accelerate data encryption/decryption and compression for applications from networking to enterprise, cloud to storage, and content delivery to database. FFmpeg is a leading multimedia framework that can decode, encode, transcode, mux, demux, stream, filter and play pretty much anything that humans and machines have created. It supports the most obscure ancient formats up to the cutting edge ones on multiple platforms such as Windows, macOS, and Linux. FFmpeg.guide is a simple GUI tool to create complex FFmpeg filtergraphs quickly and correctly, without having to mess with the cumbersome filter syntax. HandBrake is a tool for transcoding video from almost any format with a selection of widely supported codecs. It is supported on Window, macOS, and Linux. Tdarr is a cross-platform conditional based transcoding application for automating media library transcode/remux management in order to process your media files as required. It can set rules for the required codecs, containers, languages etc that your media should have which helps keeps things organized and can increase compatability with your devices. A common use for Tdarr is to simply convert video files from h264 to h265 (hevc), saving 40%-50% in size. SRS is a simple, high efficiency and realtime video server, supports RTMP, WebRTC, HLS, HTTP-FLV, SRT and GB28181. obsws-python is a Python SDK for OBS Studio WebSocket v5.0. Video/Audio Standards AAC(Advanced Audio Coding) is an audio coding standard for lossy digital audio compression. It's endorsed by ISO and IEC as MPEG-2 and MPEG-4 standards for video streams. H.264(AVC) is a video compression standard based on block-oriented and motion-compensated integer-DCT coding that defines multiple profiles (tools) and levels (max bitrates and resolutions) with support up to 8K. H.265(HEVC) is a video compression standard that is the successor to H.264(AVC). It offers a 25% to 50% better data compression at the same level of video quality, or improved video quality at the same bit-rate. HTTP Live Streaming (HLS) is a communications protocol developed by Apple that sends live and on‐demand audio and video to iPhone, iPad, Mac, Apple Watch, Apple TV, and PC. Dynamic Adaptive Streaming over HTTP (DASH) is an adaptive streaming protocol that allows for a video stream to switch between bit rates on the basis of network performance, in order to keep a video playing. OpenMAX™ is a cross-platform API that provides comprehensive streaming media codec and application portability by enabling accelerated multimedia components to be developed, integrated and programmed across multiple operating systems and silicon platforms. GStreamer is a library for constructing graphs of media-handling components. The applications it supports range from simple Ogg/Vorbis playback, audio/video streaming to complex audio (mixing) and video (non-linear editing) processing. Applications can take advantage of advances in codec and filter technology transparently. Media Source Extensions (MSE) is a W3C specification that allows JavaScript to send byte streams to media codecs within Web browsers that support HTML5 video and audio. Also, this allows the implementation of client-side prefetching and buffering code for streaming media entirely in JavaScript. WebRTC is an open-source project that adds real-time communication capabilities to your application that works on top of an open standard. It supports video, voice, and generic data to be sent between peers, allowing developers to build powerful voice- and video-communication solutions. Podcasting Back to the Top Castopod is an open-source hosting platform made for podcasters who want engage and interact with their audience. Sovereign Feeds is a tool to Search for your podcasts and add them to your favorites. IPFS Podcasting is a Decentralized Podcast Distribution over IPFS where you can crowd hosting podcast episodes with storage & bandwidth provided by volunteer nodes. Audiobookshelf is a self-hosted audiobook and podcast server. Vod2Pod-RSS is a tool that converts a YouTube or Twitch channel into a podcast with ease. It creates a podcast RSS that can be listened to directly inside any podcast client. VODs are transcoded to MP3 on the fly and no server storage is needed. Podverse is creating an open source podcast app for iOS, Android, F-Droid, and Web. Alby is a Bitcoin Lightning App for your Browser. Alby wallet API is an implemented OAuth an open standard that apps use to provide client applications with secure delegated access. Thus Podverse users create an Alby wallet account or use their existing Alby account to grant specific access rights to their Alby wallet. Blubrry is a podcast hosting service for publishing platform, live customer support, stress-free migration, and impactful statistics. SATurn is a tool that lets you connect your getalby.com Account and see which content resonates most with your audience and recognize your top contributors. AntennaPod is a podcast player that is completely open. The app is open-source and you can subscribe to any RSS feed. AntennaPod is built by volunteers without commercial interest, so it respects your privacy while giving you full control. Podgrab is a self-hosted podcast manager/downloader/archiver tool to download podcast episodes as soon as they become live with an integrated player. Podify is a self-hosted service that allows you to download videos and audio from any source supported by youtube-dl, sort the downloads into feeds, and subscribe to these feeds using your favorite podcast app. dir2cast is designed to turn a directory of MP3s into a podcast - automatically. Perfect for, say, radio shows - upload the MP3s to a folder, and use dir2cast.php as your PodCast URL. Snipd is an AI-powered podcast player. Search for moments in the transcript, get summaries, share clips to social media, and export to your second brain & note taking apps. Discover, save, and share highlights from podcasts. Wave Share is a serverless, peer-to-peer, local file sharing through sound. KBD Audio is a collection of command-line and GUI tools for capturing and analyzing audio data. AudioBooks Back to the Top Audioserve is a simple personal server to serve audio files from directories. Intended primarily for audio books, but anything with decent directories structure will do. Focus here is on simplicity and minimalist design. Audiobookshelf is a self-hosted audiobook and podcast server. Jellyfin Bookshelf Plugin Health Back to the Top Connect is the swiss army knife of healthcare integration. Fasten is an open-source, self-hosted, personal/family electronic medical record aggregator, designed to integrate with 1000's of insurances/hospitals/clinics ERPNext is a Free and Open Source Enterprise Resource Planning (ERP) for managing businesses. OpenEMR is a Free and Open Source electronic health records and medical practice management application. It features fully integrated electronic health records, practice management, scheduling, electronic billing, internationalization, free support, a vibrant community, and a whole lot more. It runs on Windows, Linux, MacOS, and many other platforms. Ryot (Roll Your Own Tracker) is a self hosted platform for tracking various facets of your life - media, fitness etc. Gardening Back to the Top ESPHome: DIY Irrigation Controller With Internal Scheduler Smart WiFi Controlled Irrigation System Using Home Assistant and ESPHome OpenSprinkler is an open-source, web-based smart sprinkler controller for lawn and plant watering, drip irrigation, farm irrigation, hydroponics etc. The current version is OS 3.2, with built-in WiFi (based on ESP8266) and OLED display. Droplet is an ALL-IN-ONE Irrigation and monitoring system for ESPHome and Home Assistant. 9 Valve Sprinkler Controller is a 9 valve sprinkler controller for use with customized firmware such as ESPHOME. GardenBot is an open source garden monitoring system. Their website is a collection of tutorials for how to build things (like a soil moisture sensor), software for running GardenBot, resources, links, and more. farmOS is a web-based application for farm management, planning, and record keeping. It is developed by a community of farmers, developers, researchers, and organizations with the aim of providing a standard platform for agricultural data collection and management. OpenFarm is a free and open database and web application for farming and gardening knowledge. One might think of it as the Wikipedia for growing plants, though it functions more like a cooking recipes site. Growstuff is an open source/open data project for food gardeners. They crowdsource information on what our members are growing and harvesting, aggregate it, and make it available as open data via their API. Harvest Helper is a tool that provides growing, harvesting and recipe information for the 45 plants in the database as well as a json api so that people can hopefully use this data to build other apps. HappyPlants is a mobile web application that's all about collecting, organising, and adding all kinds of information of your plants. Basically, creating your own plant database in a visual way. Automated irrigation system is an open source application to water plants automatically. Up to now there is almost no free professional software and instructions available to build a DYI irrigation that is scalable, accurate and most importantly, durable. Pigrow is a garden automation suite designed to help gardeners monitor, log, graph and control their grow space using a raspberry Pi, various sensor and a few relay modules. Tania is a farm management software for the hobbyist and smallholder farmer. Maps Back to the Top Magic Earth is aTurn-by-turn navigation, OpenStreetMap, Crowd-Sourced Traffic, 3D maps, Satellite maps, Offline maps and Transit. Organic Maps is a free Android & iOS offline maps app for travelers, tourists, hikers, and cyclists. It uses crowd-sourced OpenStreetMap data and is developed with love by MapsWithMe (MapsMe) founders and our community. No ads, no tracking, no data collection, no crapware. MapTiler Server is a self-hosted Aerial and satellite imagery maps of the entire world from your own server or laptop. GPSLogger is a GPS tool that uses the GPS capabilities of your Android phone to log coordinates to GPS format files at regular intervals. This can be particularly useful if you want to geotag your photos after a day out or share your travel route with someone. KelperJs is a open source full-stack geosocial network platform. OpenStreetMap(OSM) is a map of the world, created by people like you and free to use under an open license. Hosting is supported by UCL, Fastly, Bytemark Hosting, and other partners. uMap is a tool that lets you create maps with OpenStreetMap layers in a minute and embed them in your site. Martin is a tile server able to generate vector tiles from large PostGIS databases on the fly, or serve tiles from PMTile and MBTile files. Martin optimizes for speed and heavy traffic, and is written in Rust. MapLibre GL JS is an open-source library for publishing maps on your websites or webview based apps. Fast displaying of maps is possible thanks to GPU-accelerated vector tile rendering. MapLibre Native is an Interactive vector tile maps for iOS, Android and other platforms. Maplibre-rs is an Experimental Maps for Web, Mobile and Desktop. Bookmarks Back to the Top Linkding is a simple bookmark service that you can host yourself. It's designed be to be minimal, fast, and easy to set up using Docker. Linkwarden is a fully self-hostable, open-source collaborative bookmark manager to collect, organize and archive webpages. Linkwarden Docker Image LinkAce is a self-hosted bookmark archive to collect links of your favorite websites. Eagle is a tool to collect, search and organize your design files in a logical way and all in one place. Shlink is a self-hosted URL shortener that keeps control over all your shortened URLs, by serving them under your own domains, using this simple yet powerful tool. Pinry is a tiling image board system for people who want to save, tag, and share images, videos and webpages in an easy to skim through format. Shaark is a self-hosted platform to keep and share your content: web links, posts, passwords and pictures. Maglit is an encrypted and privacy respecting Link Shortener service that supports not only your regular website links but also Magnet Links which are extensively used to download and share torrents. Photos Back to the Top PhotoPrism® is an AI-powered app for browsing, organizing & sharing your photo collection. It makes use of the latest technologies to tag and find pictures automatically without getting in your way. You can run it at home, on a private server, or in the cloud. Immich is a high performance self-hosted photo and video backup solution directly from your mobile phone. Piwigo is a full featured, self-hosted, and open source photo gallery application for the web. It comes with more than 200 templates, plugins, and configurations that let you personalize how your photos are presented. It allows users to upload photos from digiKam, Shotwell, Lightroom or mobile applications. Lastly, users can create galleries and give viewing permissions to their clients. They can download individual photos or whole albums, post comments, give ratings, mark photos as favorites, and perform searches. Czkawka is a Multi-functional app to find duplicates, empty folders, similar images, etc. Phockup is a Media sorting tool to organize photos and videos from your camera in folders by year, month and day. PiGallery 2 is a fast directory-first photo gallery website, with rich UI, optimized for running on low resource servers (especially on Raspberry Pi). Photoview is a simple self-hosted and user-friendly photo gallery that's made for photographers and aims to provide an easy and fast way to navigate directories, with thousands of high-resolution photos. digiKam is a free and open-source Professional Photo Management tool. ShareX is a free and open source program that lets you capture or record any area of your screen and share it with a single press of a key. It also allows uploading images, text or other types of files to many supported destinations you can choose from. PhotoSync is a service to wirelessly transfer, backup & share photos/videos to your computer, NAS, other phones and popular cloud/photo services. It's available for Windows, MacOS, Linux, Android, and iOS. Lychee is a great looking and easy-to-use photo-management-system you can run on your server, to manage and share photos. Photoview is a simple and user-friendly photo gallery that's made for photographers and aims to provide an easy and fast way to navigate directories, with thousands of high-resolution photos. Gimme-iPhotos is a tool uses pyicloud to synchronize photos and videos from iCloud to your local machine. PyiCloud is a module which allows pythonistas to interact with iCloud webservices. It's powered by the fantastic requests HTTP library. Pixelfed is a fresh take on photo sharing. It decentralized ActivityPub protocol so you can comment, follow, and interact with remote Pixelfed, Mastodon and Pleroma posts and profiles from your Pixelfed account as if you were both on the same website. Chevereto is an image hosting software that allows you to create a beautiful and full-featured image hosting website on your own server. Got Your Back (GYB) is a command line tool for backing up your Gmail messages to your computer using Gmail's API over HTTPS. Upscayl is a free and open source desktop application that lets you upscale your low resolution images using advanced AI Models. Upscayl is a Linux-First Application that prioritizes Linux builds but is also cross-platform. Librephotos is a self-hosted open source photo management service. This is the repository of the backend. Librephotos frontend is a self-hosted open source photo management service. This is the repository of the frontend. Librephotos Mobile is an open-source Android and iOS Mobile Application for self-hosted Librephotos Server. Librephotos Docker is the Dockerfiles for the automated build process of LibrePhotos. OneFolder is a Desktop app to sort your images the same way you would in Google Photos, but locally, no need to run a server (and compatible with NAS). Pastebins Back to the Top Bepasty is a pastebin for all kinds of files. Bin is a paste bin that's actually minimalist. Dpaste is a Simple pastebin with multiple text and code option, with short url result easy to remember. Drift is a Self-hosted Github Gist clone. EdPaste is a Self-hosted pastebin written in Laravel (PHP Framework). ExBin is a pastebin with public/private snippets and netcat server. Fiche is a Command line pastebin, all you need is netcat. Filite is a simple, light and standalone pastebin, URL shortener and file-sharing service. FlashPaper is a one-time encrypted zero-knowledge password/secret sharing application focused on simplicity and security. No database or complicated set-up required. Hasty Paste is a place to quickly paste some text and share it. Mostly used for sharing debug logs and such to help developers provide tech support. The project aims to be both fast and minimal. Lenpaste is a Web service that allows you to share notes anonymously, an alternative to pastebin. LogPaste is a Minimal pastebin web app that's easy to self-host and persists data to any S3-compatible backend. MicroBin is a super tiny, feature rich, configurable, self-contained and self-hosted paste bin web application. It is very easy to set up and use, and will only require a few megabytes of memory and disk storage. MicroBin Docker install setup . Opengist is a Self-hosted pastebin powered by Git. Paaster is a secure by default end-to-end encrypted pastebin built with the objective of simplicity. Pastefy - Beautiful, simple and easy to deploy Pastebin with optional Client-Encryption, Multitab-Pastes, an API, a highlighted Editor and more. Pastila is a Minimalistic paste service. Single page, zero click experience. Pasty is a fast and lightweight code pasting server. PrivateBin is a minimalist, opensource online pastebin/discussion board where the server has zero knowledge of hosted data. Prologic pastebin is a Simple pastebin service with convenient api and CLI. PurritoBin is a Ultra fast, minimalistic, encrypted command line paste-bin, where the server has no knowledge of the paste data. Rustypaste is a minimal file upload/pastebin service. Spacebin is a Reliable Pastebin server in Golang and Fiber. Sup3rS3cretMes5age is a simple to deploy and use secret message service using Hashicorp Vault as a secrets storage. Wastebin is a Lightweight, minimal and fast pastebin with an SQLite backend. YABin is a pastebin that contains plentiful features while remaining simple. Supports optional E2E encryption, a client-side CLI app, syntax highlighting, minimalistic UI, APIs, keyboard shortcuts, and more. It can even be run in serverless environments. Note-Taking Back to the Top Joplin is an open source note-taking app that you can securely access from any device. HedgeDoc is an open-source, web-based, self-hosted, collaborative markdown editor. Lapce is a Lightning-fast And Powerful Code Editor written in pure Rust with a UI in Druid (which is also written in Rust). nb is a CLI and local web plain text note‑taking, bookmarking, and archiving with linking, tagging, filtering, search, Git versioning & syncing, Pandoc conversion, + more, in a single portable script. Outline is the fastest knowledge base for growing teams. It provides a beautiful, realtime collaborative, feature packed, and markdown compatible. Rustpad is an open-source collaborative text editor based on the operational transformation algorithm. Share a link to this pad with others, and they can edit from their browser while seeing your changes in real time. Turtl is a secure, collaborative notebook for bookmarks or passwords, files or shopping lists. The Everything App is an app where you can do everything: Protect your thoughts & data with end-to-end encryption. Local, on-device encryption. Only you have encryption keys. Offline account creation: control your keys, own your data. No server, no gatekeeper: peer-to-peer sync on local networks. Locally store your data, self-host your backups where you please. TiddlyWiki is a single-file mode wiki application for todo lists, effective project management tool and of course writing drafts and notes. It has extensions for all the major browsers. Laverna is a note taking application with Markdown editor and encryption support. Consider it like open source alternative to Evernote. Notesnook is a fully open source & end-to-end encrypted note taking alternative to Evernote. Zettlr is an open-source Markdown editor for the 21st century. Carnet is a complete open source note taking app. It has extensions for all the major browsers. Frog is a tool that quickly extract text from almost any source: youtube, screencasts, PDFs, webpages, photos, etc. Grab the image and get the text. Zeal is an offline documentation browser for software developers inspired by Dash . Time Monitoring Back to the Top ActivityWatch isn app that automatically tracks how you spend time on your devices. Kimai is a free & open source timetracker. It tracks work time and prints out a summary of your activities on demand. TimeTagger is an open source time-tracker based on an interactive timeline and powerful reporting. Traggo is a tag-based time tracking tool. In Traggo there are no tasks, only tagged time spans. Wikis Back to the Top Archivy is a self-hostable knowledge repository that allows you to learn and retain information in your own personal and extensible wiki. BookStack - BookStack is a simple, self-hosted, easy-to-use platform for organizing and storing information. It allows for documentation to be stored in a book like fashion. Cowyo - Cowyo is a feature-rich wiki for minimalists. django-wiki - Wiki system with complex functionality for simple integration and a superb interface. Store your knowledge with style: Use django models. Documize - Modern Docs + Wiki software with built-in workflow, single binary executable, just bring MySQL/Percona. Dokuwiki - Easy to use, lightweight, standards-compliant wiki engine with a simple syntax allowing reading the data outside the wiki. All data is stored in plain text files, therefore no database is required. Gitit - Wiki program that stores pages and uploaded files in a git repository, which can then be modified using the VCS command line tools or the wiki's web interface. Gollum - Simple, Git-powered wiki with a sweet API and local frontend. Instiki - Instiki is a wiki clone so pretty and easy to set up, you'll wonder if it’s really a wiki. Runs on Rails and focuses on portability and stability. Mediawiki - MediaWiki is a free and open-source wiki software package written in PHP. It serves as the platform for Wikipedia and the other Wikimedia projects, used by hundreds of millions of people each month. Pepperminty Wiki - Complete markdown-powered wiki contained in a single PHP file. PineDocs - Simple, fast, customizable and lightweight site for browsing files. PmWiki - Wiki-based system for collaborative creation and maintenance of websites. PukiWiki - PukiWiki is a free, simple, open-source wiki management system. Minimalistic and simple design with many tools for collaborative work. Created in Japanese, so translator needed. Raneto - Raneto is an open source Knowledgebase platform that uses static Markdown files to power your Knowledgebase. TiddlyWiki - Reusable non-linear personal web notebook. Tiki - Wiki CMS Groupware with the most built-in features. TWiki - TWiki is a Perl-based structured wiki application, typically used to run a collaboration platform, knowledge or document management system, a knowledge base, or team portal. WackoWiki - WackoWiki is a light and easy to install multilingual Wiki-engine. Gaming Back to the Top Cartridge is a self-hosted game library made with Laravel + Vue.js. Cartridge Features Scan for ROM files and match with IGDB game information Serve ROM download links alongside game details Manage access to library with user creation and permissions (WIP) Allow users to request games (Planned) Play select ROMs in-browser using JS emulators (Planned) Track played and favorite games (even ones that aren't available for download) (Planned) Moonlight Game Streaming is a program that let you stream from your PC games over the Internet with no configuration required. Stream from almost any device, whether you're in another room or miles away from your gaming rig. Sunshine is a Game stream host for Moonlight that is a self-hosted, low latency, cloud gaming solution with support for AMD, Intel, and NVIDIA GPUs. It is an open source implementation of NVIDIA's GameStream. Chiaki is a Free and Open Source Software Client for PlayStation 4 and PlayStation 5 Remote Play for Linux, FreeBSD, OpenBSD, Android, macOS, Windows, Nintendo Switch and potentially even more platforms. Game Emulators EmuDeck is a tool that takes care of everything for your retrogaming needs from RetroArch Configuration, Bezels, Gamepad Configuration for GameCube, Wii, Citra, SNES, etc. EmuDeck will even install EmulationStation Desktop Edition and carry over all their custom configurations and no need to configure ROM paths or anything. EmulationStation Desktop Edition (ES-DE) is a frontend application for browsing and launching games from your multi-platform game collection. It's available for Unix/Linux, macOS(M1 & Intel) and Windows. RetroPie is a frontend for emulators that allows you to turn your Raspberry Pi, ODroid C1/C2, or PC into a retro-gaming machine. It builds upon Raspbian, EmulationStation , RetroArch and many other projects to enable you to play your favourite Arcade, home-console, and classic PC games with the minimum set-up. RetroArch is a frontend for emulators, game engines and media players. It enables you to run classic games on a wide range of computers and consoles through its slick graphical interface. Settings are also unified so configuration is done once and for all. RetroArch Flatpak Pterodactyl is a free, open-source game server management panel built with PHP, React, and Go. Designed with security in mind, Pterodactyl runs all game servers in isolated Docker containers while exposing a beautiful and intuitive UI to end users. LinuxGSM (Linux Game Server Managers) is a command-line tool for quick, simple deployment and management of Linux dedicated game servers. Cartridge is a self-hosted game library made with Laravel + Vue.js. Cartridge Features Scan for ROM files and match with IGDB game information Serve ROM download links alongside game details Manage access to library with user creation and permissions (WIP) Allow users to request games (Planned) Play select ROMs in-browser using JS emulators (Planned) Track played and favorite games (even ones that aren't available for download) (Planned) Cartridge UI Dolphin is an emulator for two recent Nintendo video game consoles: the GameCube and the Wii. It allows PC gamers to enjoy games for these two consoles in full HD (1080p) with several enhancements: compatibility with all PC controllers, turbo speed, networked multiplayer, and even more. Citra is an open-source emulator for the Nintendo 3DS capable of playing many of your favorite games. yuzu is an experimental open-source emulator for the Nintendo Switch from the creators of Citra.[ m64p is a Nintendo 64 Emulator. It uses mupen64plus-gui, a brand new mupen64plus frontend written in Qt5. It supports all of the things you’d expect from a frontend (savestate management, pausing, screenshots). DeSmuME is a Nintendo DS emulator. Snes9x is a portable, freeware Super Nintendo Entertainment System (SNES) emulator. bsnes is a Super Nintendo (SNES) emulator focused on performance, features, and ease of use. mGBA is a new emulator for running Game Boy Advance games. It aims to be faster and more accurate than many existing Game Boy Advance emulators, as well as adding features that other emulators lack. DOSBox is an open-source DOS emulator which primarily focuses on running DOS Games. DOSBox Staging is a full x86 CPU emulator (independent of host architecture), capable of running DOS programs that require real or protected mode. Flycast is a multi-platform Sega Dreamcast, Naomi and Atomiswave emulator derived from reicast. PCSX2 is a PlayStation 2 'emulator', a free program that tries to replicate the PlayStation 2 console to enable you to play PS2 games on your PC. RPCS3 is an experimental open-source Sony PlayStation 3 emulator and debugger written in C++ for Windows and Linux. RPCS3 started development in May of 2011 by its founders DH and Hykem. The emulator is currently capable of running over 1800 commercial titles powered by Vulkan and OpenGL. MAME is a Arcade Machine Emulator. xemu is an original Xbox emulator. Xenia is an Xbox 360 Emulator. Also checkout these subreddits for more great Game Emulators recommendations r/emulation r/emulations r/RetroArch r/RetroPie r/DolphinEmulator r/Citra r/cemu r/yuzu r/OpenEmu r/MAME r/EmuDev r/Roms Foundations/Projects Back to the Top Matter is an open standard for smart home technology that lets your device work with any Matter-certified ecosystem using a single protocol. Matter comes from the Connectivity Standards Alliance , an organization of hundreds of companies(Amazon, Apple, Google, Comcast, Zigbee Alliance, and Connectivity Standards Alliance (CSA) creating products for the smart home. Open Source Hardware Association (OSHWA) is a non-profit organization that advocates for open-source hardware. It aims to act as a hub of open source hardware activity of all types while actively cooperating with other initiatives such as the TAPR Open Hardware License, open-source development groups at CERN, and the Open Source Initiative (OSI). The Open Connectivity Foundation is dedicated to ensuring secure interoperability for consumers, businesses and industries by delivering a standard communications platform, a bridging specification, an open source implementation and a certification program allowing devices to communicate regardless of form factor, operating system, service provider, transport technology or ecosystem. Raspberry Pi Foundation is a UK-based charity with the mission to enable young people to realise their full potential through the power of computing and digital technologies. OpenSSF(Open Source Security Foundation) is a cross-industry forum for a collaborative effort to improve open source software security. OpenJS Foundation is the premier home for critical open source JavaScript projects, including Appium, Dojo, jQuery, Node.js, and webpack, and 27 more. EdgeX Foundry is a vendor-neutral project under the Linux Foundation. The initiative is aligned around a common goal: the simplification and standardization of the foundation for edge computing architectures in the Industrial IoT market, while still allowing the ecosystem to add significant value. Eclipse Foundation provides our global community of individuals and organizations with a mature, scalable and commercially-friendly environment for open source software collaboration and innovation. System Hardware Back to the Top Refurbished Servers on Amazon Network Switches & Hubs on ebay Server Monkey The Server Store CPUs Intel Processors(x86) Back to the Top I recommend using Intel CPUs no older than the second generation of the Intel Core processors (Core i7, i5, i3) AKA Sandy Bridge(Jan. 2011) for those that want to utilize Intel® Quick Sync Video . Though, if you're concerned about power efficiency(~5W idle) I would recommend 7th Generation or newer. Also, I recommend using Intel® QuickAssist Technology (Intel® QAT) a scalable, flexible, and extendable way to accelerate data encryption/decryption and compression for applications from networking to enterprise, cloud to storage, and content delivery to database. Available in 3rd Gen Intel® Xeon® Scalable Processors and Intel Atom® Processor C Series/P Series. Intel Celeron Processor N Series Intel Atom Series Intel Pentium Intel i3 Intel i5 Intel i7 Intel Xeon AMD Processors(x86) Back to the Top AMD Athlon AMD Ryzen G-Series AMD Ryzen 3 AMD Ryzen 5 AMD Ryzen 7 AMD Threadripper Devices Back to the Top Note: Will be adding more device soon! Raspberry Pi Turing Pi 2 Home Assistant Yellow ZimaBoard ODROID-H3 and H3+ Intel® NUC Mini PCs Beelink mini PC M1 Mac Mini Nexcom Industrial Computers Aeotec MultiSensor 7, 6-in-1 Zwave Sensors reTerminal Raspberry Pi (CM4 module) all-in-one board KOOLCORE R1 - The smallest mini PC with 4 x 2.5G LANs Khadas VIM1S Asustor DriveStor 4 NAS TRENDnet TEG-S350 (2.5 GbE) Switch Storinator™ is a line of Ultra-Large, Direct-Wired storage Servers by 45Drives . HL15 from 45HomeLab is an open-source, open-platform, 15-bay homelab server. The HL15 features enterprise architecture and strength brought to a scale that works for the homelab. The server's direct-wired architecture can provide blazing fast transfer speed of up to 2GB per second. LattePanda Sigma is a powerful and compact x86 Windows single board computer (SBC). It features the 13th Intel® Core™ i5-1340P Rapter Lake (12-Core, 16-Thread) processor and 16GB Dual-Channel LPDDR5-6400MHz memory. Apex Storage X21 is a storage solution that gives you have the freedom to choose system hardware thatworks best for you with the following benefits. Host 21 x M.2 Gen 4 NVME SSD’s 168 TB + Storage Per Card 31 GBps Read/Write Speeds Industry Leading IOPS 100 PCIe 4.0 Lanes Full UEFI/Secure Boot Support GL.iNet is a leading developer of OpenWrt Wi-Fi and IoT Network Solutions. They build Wi-Fi routers, IoT gateways and remote device management platforms for a wide range of scenarios. All their routers include powerful built-in firewall, Shadow also supports OpenVPN, WireGuard® and customized DNS server in order to level up your online security. Protectli Vault is a series of small computers that have firewalls with advanced firmware protection to keep your network safe. All Vaults are Opertaing System (OS) agnostic and support a variety of popular open source software distributions. Run a firewall like OPNsense, pfSense, or others. Also, run any hypervisor on your system. Espclicker is a small device that you can use to integrate not IoT devices into your smart home setup, It connects directly to the push buttons of the device, which you want to control, and then simulates pressing them. You can simulate button clicks, hold time, and multiple clicks. Pockethernet is a smartphone connected Ethernet network analyzer & cable tester that fits into your pocket. It helps any IT admin dealing with Ethernet network installation and maintenance. It lets you check the ethernet link, find cable faults, PoE voltage, VLAN, DHCP results and much more with the press of a button. $13 USD voice assistant remote for Home Assistant ATOM ECHO is a Programmable Smart Speaker based on the M5ATOM design. Music can be played using the BT (Bluetooth Technology) capabilities of the ESP32 from a mobile phone or tablet. The device could be programmed to access AWS, Azure, and other cloud platforms, using the built-in microphone and speaker for voice interaction. Operating Systems Back to the Top Creating a bootable media device(USB/MicroSD card) Rufus is a utility that helps format and create bootable USB flash drives. Rufus OR Etcher is an open source, cross-platform software that makes it easy to flash operating system images to a microSD card or USB device. Etcher UI A List of Operating Systems that are great for either settig up a personal Home Server or a Enterprise Server for your Organization/Company. Home Assistant OS is a container-based system for managing your Home Assistant Core installation and related applications. The system is controlled via Home Assistant which communicates with the Supervisor. The Supervisor provides an API to manage the installation. This includes changing network settings or installing and updating software. Home Assistant OS Umbrel is an OS for running a personal server in your home. It can Self-host open source apps like Nextcloud, Bitcoin node, and more. Umbrel CasaOS is a simple, easy-to-use, elegant open-source Home Cloud system. CasaOS TrueNAS® CORE is the world's most popular storage OS because it gives you the power to build your own professional-grade storage system to use in a variety of data-intensive applications without any software costs. It's based on FreeBSD and Linux, using the OpenZFS file system. TrueNAS CORE Alpine Linux is a security-oriented, lightweight Linux distribution based on musl libc and busybox. Alpine Linux Wiki Alpine Linux Community Xfce4 Desktop Enable the Community repository , then execute command: apk add xfce4 Alpine Linux Xfce Mate Desktop Enable the Community repository , then execute command: apk add mate-desktop-environment Alpine Linux MATE Ubuntu is a modern open source operating system on Linux for the enterprise Server, Desktop, Cloud, and IoT developed by Canonical. Ubuntu Server Ubuntu for ARM Ubuntu for Raspberry Pi Ubuntu Flavours is for those that prefer an alternative desktop environment such as KDE Plasma Desktop , MATE , Xfce , LXQt , Budgie , and UKUI you can download a Flavour for your preferred desktop environment and use that to install Ubuntu, pre-configured for the desktop environment of your choice. Ubuntu Debian is an operating system and a distribution of Free Software. It is maintained and updated through the work of many users who volunteer their time and effort. Debian 11 Linux Mint is a modern, elegant, and comfortable open source operating system(based on Debian and Ubuntu), which is both powerful and easy to use for both new and advanced users. The flagsip version of Linux Mint uses the Cinnamon desktop environment similiar to Windows 7. Linux Mint Linux Mint Debian Edition (LMDE) uses Debian Bullseye as the base for a very stable and rock solid user experience with the Cinnamon desktop. Linux Mint Debian Edition (LMDE) Pop!_OS created by System76 . Pop!_OS Fedora Linux is a polished, easy to use operating system for laptop & desktop computers, with a complete set of tools for developers and makers of all kinds. The OS serves as the foundation for which you can scale existing apps and roll out emerging technologies across bare-metal, virtual, container, and all types of cloud environments. Fedora Spins is for those that prefer an alternative desktop environment such as KDE Plasma Desktop, MATE; or Xfce, you can download a spin for your preferred desktop environment and use that to install Fedora, pre-configured for the desktop environment of your choice. Fedora Server is a powerful, flexible operating system that includes the best and latest datacenter technologies. It puts you in control of all your infrastructure and services. Fedora ARM is an initiative to bring versions of Fedora tailored for running on ARM-based systems. Fedora Silverblue is a variant of the Fedora Workstation that uses rpm-ostree to provide an immutable OS image with reliable updates and easy rollbacks. Fedora Kinoite is an immutable desktop operating system. It aims to be extremely stable and reliable. It also aims to be an excellent platform for developers and for those using container-focused workflows. Kinoite is a variant of the Fedora KDE Spin. Fedora CoreOS is an automatically-updating, minimal operating system for running containerized workloads securely and at scale. Fedora Linux CentOS Stream is a continuously delivered distro(uses the Fedora OS base) that tracks just ahead of Red Hat Enterprise Linux (RHEL) development, positioned as a midstream between Fedora Linux and RHEL. CentOS Stream Red Hat® Enterprise Linux® (RHEL) the world's leading enterprise Linux platform. The OS serves as the foundation for which you can scale existing apps and roll out emerging technologies across bare-metal, virtual, container, and all types of cloud environments. Red Hat Enterprise Linux Desktop AlmaLinux is an open source enterprise-ready Linux distribution forked from Red Hat Enterprise Linux(RHEL). It's a very stable/solid operating system especially for production envrionments such as servers, though, you can also install a GUI on AlmaLinux and use it as a desktop OS. It was founded by the team behind the CloudLinux OS . AlmaLinux Wiki Migrate from CentOS 8 AlmaLinux Desktop Setup and Install Rocky Linux is a community enterprise operating system designed to be 100% bug-for-bug compatible and forked from Red Hat Enterprise Linux(RHEL) now that its downstream partner(Red Hat) has shifted direction . Rocky Linux Wiki Rocky Linux Documentation Rocky Linux Desktop SUSE is a leading Linux OS most adaptable Linux operating system and the only open Kubernetes management platform thanks to their acquistion of Rancher . They also developer of SUSE Linux Enterprise and the primary sponsor of the community-supported openSUSE Project , which develops the openSUSE Linux distribution. openSUSE Leap is a brand new way of building openSUSE and is new type of a hybrid Linux distribution. Leap uses source from SUSE Linux Enterprise (SLE), which gives Leap a level of stability unmatched by other Linux distributions, and combines that with community developments to give users, developers and sysadmins the best stable Linux experience available. openSUSE Tumbleweed is a pure rolling release version of openSUSE containing the latest "stable" versions of all software instead of relying on rigid periodic release cycles. The project does this for users that want the newest stable software. openSUSE Kubic is a multi-purpose Standalone & Kubernetes Container Operating System based on openSUSE MicroOS. Kubic uses kubeadm to provide an easy way of configuring a Kubernetes cluster across multiple machines, while our MicroOS base keeps your operating system updated automatically, with fully atomic rollbacks if required. openSUSE MicroOS is a M icro Service OS providing Transactional (Atomic) Updates upon a read-only btrfs root filesystem. It's designed to host container workloads with automated administration & patching. SUSE Linux Enterprise 12 openSUSE NixOS is a Linux distribution built on top of the Nix package manager . It has tools dedicated to DevOps and deployment tasks. NixOS Guide Nix Tour is an interactive tour that uses the actual package manager to learn you the language by example, in the browser. Nix is a package manager and build system that parses reproducible build instructions specified in the Nix Expression Language , is a pure functional language with lazy evaluation. Nix expressions are pure functions taking dependencies as arguments and producing derivation specifying a reproducible build environment for the package. Nix stores the results of the build in unique addresses specified by a hash of the complete dependency tree, creating an immutable package store that allows for atomic upgrades, rollbacks and concurrent installation of different versions of a package, essentially eliminating dependency hell . Nix Expression Language is a pure, lazy, functional language. Purity means that operations in the language don't have side-effects (for instance, there is no variable assignment). The language is not a full-featured, general purpose language. Its main job is to describe packages, compositions of packages, and the variability within packages. Nixpkgs is the largest repository of Nix packages(over 80,000 packages) and NixOS modules. The repository is hosted on GitHub and maintained by the community, with official backing from the NixOS Foundation . Additionally, checkout Language-specific package helpers and Alternative Package Sets . NixOS Packages Search is a tool for searching through NixOS packages. NixOS Packages Search NixOS Desktop with the new Calamares Installer NixOS with the Plasma Desktop BSD Back to the Top FreeBSD is an Unix-like operating system used to power modern servers, desktops, and embedded platforms. A large community has continually developed it for more than thirty years. Its advanced networking, security, and storage features have made FreeBSD the platform of choice for many of the busiest web sites and most pervasive embedded networking and storage devices. FreeBSD Software ports. Source: FreeBSD Software OpenBSD is a security-focused, free and open-source, Unix-like operating system based on the Berkeley Software Distribution. It comes with a secure minimal firewall, webserver, mailserver, and an optional graphical desktop. NetBSD is a free, fast, secure, and highly portable Unix-like Open Source operating system. It is available for a wide range of platforms, from large-scale servers and powerful desktop systems to handheld and embedded devices. NetBSD Documentation DragonFly BSD is a free and open-source Unix-like operating system forked from FreeBSD 4.8. DragonFly Documentation The BSD Desktop for the average user GhostBSD is a simple desktop-oriented operating system based on FreeBSD with MATE, OpenRC and OS packages for simplicity. GhostBSD has a selection of commonly used software preinstalled and required to start using it to its full potential. GhostBSD Wiki GhostBSD Community GhostBSD Desktop. Source: GhostBSD Storage Back to the Top - Storage Reference Guide by Storage Review Western Digital Hard Drives Storage size range 2TB up to 20TB Seagate Hard Drives Storage size range 2TB up to 18TB Hard Drives Storage size range 2TB up to 20TB from Bestbuy Hard Drives Storage size range 1TB up to 20TB on Newegg Hard Drives Storage size range 1TB up to 18TB on Amazon Useful Tools for Storage Management Scrutiny is a WebUI for smartd Hard Drive S.M.A.R.T Monitoring, Historical Trends & Real World Failure Thresholds. smartd is SMART Disk Monitoring Daemon for Linux. It controls and monitors storage systems using the Self-Monitoring, Analysis and Reporting Technology System (SMART) built into most modern ATA/SATA, SCSI/SAS and NVMe disks. In many cases, these utilities will provide advanced warning of disk degradation and failure. DUA (Disk Usage Analyzer) is a tool to conveniently learn about the usage of disk space of a given directory. It's parallel by default and will max out your SSD, providing relevant information as fast as possible. Optionally delete superfluous data, and do so more quickly than rm. Perkeep is a set of open source formats, protocols, and software for modeling, storing, searching, sharing and synchronizing data. It can be easily accessed via a phone, browser or FUSE filesystem. duf is a Disk Usage/Free Utility for Linux, BSD, macOS & Windows. Dirstat-rs is a fast, cross-platform disk usage CLI, similar to Windirstat . Dutree is a tool to analyze file system usage written in Rust. Shufflecake is a tool for Linux that allows to create multiple hidden volumes on a storage device in such a way that it is very difficult, even under forensic inspection, to prove the existence of such volumes. btdu is a sampling disk usage profiler for btrfs. Btrfs maintenance toolbox is a set of scripts supplementing the btrfs filesystem and aims to automate a few maintenance tasks. This means the scrub, balance, trim or defragmentation. File systems Back to the Top FSArchiver is a system tool that allows you to save the contents of a file system to a compressed archive file. The file system can be restored on a partition which has a different size and it can be restored on a different file system. WekaFS is the world's fastest shared parallel file system and delivers unmatched performance at ANY scale while offering the same enterprise features and benefits of traditional storage. It meets all storage challenges, delivering 10x the performance of legacy network attached storage (NAS) systems and 3x the performance of local server storage. GlusterFS is a free and open source scalable network filesystem. Gluster is a scalable network filesystem. Using common off-the-shelf hardware, you can create large, distributed storage solutions for media streaming, data analysis, and other data- and bandwidth-intensive tasks. Ceph is a software-defined storage solution designed to address the object, block, and file storage needs of data centers adopting open source as the new norm for high-growth block storage, object stores and data lakes. Ceph provides enterprise scalable storage while keeping CAPEX and OPEX costs in line with underlying bulk commodity disk prices. Hadoop Distributed File System (HDFS) is a distributed file system that handles large data sets running on commodity hardware. It is used to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes. HDFS is one of the major components of Apache Hadoop, the others being MapReduce and YARN . ZFS is an enterprise-ready open source file system and volume manager with unprecedented flexibility and an uncompromising commitment to data integrity. ZFSBootMenu is a Linux bootloader that attempts to provide an experience similar to the FreeBSD bootloader. It takes advantage of ZFS features, it allows a user to have multiple “boot environments” (with different distros, for example), manipulate snapshots before booting, and even bootstrap a system installation via zfs recv . OpenZFS is an open-source storage platform. It includes the functionality of both traditional file systems and volume manager. It has many advanced features including: Protection against data corruption. Integrity checking for both data and metadata. Continuous integrity verification and automatic "self-healing" repair. Btrfs is a modern copy on write (CoW) filesystem for Linux aimed at implementing advanced features while also focusing on fault tolerance, repair and easy administration. Its main features and benefits are: Snapshots which do not make the full copy of files RAID - support for software-based RAID 0, RAID 1, RAID 10 Self-healing - checksums for data and metadata, automatic detection of silent data corruptions Composefs is a native Linux file system designed to help sharing filesystem contents, as well as ensuring said content is not modified. The initial target usecase are container images and ostree commits. MergerFS is a union filesystem geared towards simplifying storage and management of files across numerous commodity storage devices. It is similar to mhddfs, unionfs, and aufs. MergerFS Features Configurable behaviors / file placement Ability to add or remove filesystems at will Resistance to individual filesystem failure Support for extended attributes (xattrs) Support for file attributes (chattr) Runtime configurable (via xattrs) Works with heterogeneous filesystem types Moving of file when filesystem runs out of space while writing Ignore read-only filesystems when creating files Turn read-only files into symlinks to underlying file Hard link copy-on-write / CoW Support for POSIX ACLs Proxmox Cluster File System (PMXCFS) is a File System used to transparently distribute the cluster configuration to all cluster nodes. UnionFS is a filesystem service for Linux, FreeBSD and NetBSD which implements a union mount for other file systems. It allows files and directories of separate file systems, known as branches, to be transparently overlaid, forming a single coherent file system. OverlayFS is a modern union filesystem that is similar to AUFS , but faster and with a simpler implementation. It's typically used on systems running on embed devices, like OpenWRT, where is useful to preserve a basic set of configurations and at the same time allowing the user to perform modifications. Bcachefs is an advanced new filesystem for Linux, with an emphasis on reliability and robustness and the complete set of features one would expect from a modern filesystem. Scalability has been tested to 50+ TB, will eventually scale far higher. Squashfs is a compressed read-only filesystem for Linux. It uses zlib, lz4, lzo, or xz compression to compress files, inodes and directories. Inodes in the system are very small and all blocks are packed to minimize data overhead. SeaweedFS is a fast distributed storage system for blobs, objects, files, and data lake, for billions of files! Blob store has O(1) disk seek, cloud tiering. Filer supports Cloud Drive, cross-DC active-active replication, Kubernetes, POSIX FUSE mount, S3 API, S3 Gateway, Hadoop, WebDAV, encryption, Erasure Coding. CubeFS is a cloud native distributed storage platform. It's commonly used as the storage infrastructure for online applications, database or data processing services and machine learning jobs orchestrated by Kubernetes. Apple File System (APFS) is the default file system for Mac computers using macOS 10.13 or later, features strong encryption, space sharing, snapshots, fast directory sizing, and improved file system fundamentals. NTFS(New Technology File System) is the primary file system for recent versions of Windows and Windows Server—provides a full set of features including security descriptors, encryption, disk quotas, and rich metadata, and can be used with Cluster Shared Volumes (CSV) to provide continuously available volumes that can be accessed simultaneously from multiple nodes of a failover cluster. exFAT(Extended File Allocation Table ) is the file system that was the successor to FAT32 in the FAT family of file systems. It was optimized for flash memory such as USB flash drives and SD cards. Books Back to the Top Self-hosted Cookbook is a cookbook, for docker-compose based recipes, for self-hosted applications and services. Geek's Cookbook is a collection of guides for establishing your own highly-available "private cloud" and using it to run self-hosted services such as GitLab, Plex, NextCloud, etc. Database Books(PDFs) Podcasts Back to the Top Self-Hosted Podcast is a chat show between Chris and Alex two long-time "self-hosters" who share their lessons and take you along for the journey as they learn new ones. Self-Hosted SRE(Site Reality Engineer) Podcast is a feed to say thank you to our Self-Hosted Site Reality Engineers! Home Assistant Podcast is a biweekly podcast with the latest news and interesting guests. YouTube Channels Back to the Top Jeff Geerling Level1Techs Open Source is Awesome Self-Hosted Show by Jupiter Broadcasting Techno Tim Raid Owl NextCloud Raspberry Pi Wolfgang's Channel Pro Tech Show Geeked The Tinker Dad DB Tech The Digital Life censiCLICK Home Network Geek Tutorials & Resources Back to the Top Awesome-SelfHosted is a directory of free software solutions and web applications which can be hosted locally. Awesome Sysadmin is a curated list of amazingly awesome open source sysadmin resources. Personal Security Checklist is a curated checklist of 300+ tips for protecting digital security and privacy in 2022. Awesome Privacy is acurated list of privacy & security-focused software and services. Perfect Media Server is a project aim is to share knowledge and information about building an open-source media server. It was created by Alex Kretzschmar AKA ironicbadger . /r/Selfhosted Official Wiki 45Drives Knowledge Base is an affordable enterprise storage solutions for any data size - large or small. It provides high-performance, high-capacity storage servers and data destruction solutions for all industries. Self-hosting by any tech docs Noted - Self Hosted App and Product Reviews How I fell into the self-hosting rabbit hole in 2021 The (hardware) key to making phishing defense seamless with Cloudflare Zero Trust and Yubico Shelly 2.5: Flash ESPHome Over The Air HDMI Distribution over your Home Network? Low-Cost HDMI Matrix using IP-Based Hardware Microsecond accurate NTP with a Raspberry Pi and PPS GPS Deploy Your Self-Hosted Mattermost Server Monitor your Internet with a Raspberry Pi by Jeff Geerling - Storage Reference Guide by Storage Review NextCloud Migration Guide GitLab self-managed subscription Proxmox VE Training Courses Self-Hosted GitLab with CodeFlow Self-host Appsmith in Just a Few Minutes on Digital Ocean AppSmith Linode Guides & Tutorials Linode Beginner's Guide Access a Pi-hole or Raspberry Pi from anywhere | Tailscale Tailscale on Kubernetes | Tailscale Tailscale on Proxmox host | Tailscale Configuring Linux DNS | Tailscale Run a private Minecraft server with Tailscale | Tailscale Set up a dogcam with Tailscale, Raspberry Pi, and Motion | Tailscale Defined Networking is Open for Business by Ryan Huber Automating Host Creation with the API Azure Self-hosted gateway overview Create and configure a self-hosted integration runtime for Azure Data Factory and Synapse pipelines Run a self-hosted agent in Docker - Azure Pipelines | Microsoft Docs Azure DevOps Self Hosted ### Subreddits Back to the Top r/Selfhosted r/Webhosting r/NextCloud r/HomeServer r/Homeassistant r/Homebridge r/HomeKit r/SmartThings r/Proxmox r/Tailscale r/WireGuard r/Adguard r/Pihole r/Raspberry_pi r/RASPBERRY_PI_PROJECTS r/RetroPie r/Arduino r/ArduinoProjects r/Opensource r/Devops r/Kubernetes r/Docker r/Portainer r/Ansible r/Terraform r/CloudFlare r/Homeautomation r/HomeNetworking r/Homelab r/Synology r/unRAID r/QNAP r/OpenWrt r/Smarthome r/TpLink r/DataHoarder r/ZFS r/PFSENSE r/OpenMediaVault WireGuard Back to the Top What is WireGuard? Back to the Top WireGuard® is a straight-forward, fast and modern VPN that utilizes state-of-the-art cryptography. It aims to be faster, simpler, leaner, and more useful than IPsec while avoiding the massive headache. WireGuard is designed as a general-purpose VPN for running on embedded interfaces and super computers alike, fit for many circumstances. Initially released for the Linux kernel, it is now cross-platform (Windows, macOS, BSD, iOS, Android) and widely deployable. What is Tailscale? Back to the Top Tailscale is a WireGuard-based app that makes secure, private networks easy for teams of any scale. It works like an overlay network between the computers of your networks using all kinds of NAT traversal sorcery . Tailscale Terraform Provider Tailscale Docker extension Tailscale Synology How NAT Traversal works on a Home router. Credit: Tailscale . Headscale is an open source, self-hosted implementation of the Tailscale coordination server. What is Netmaker? Back to the Top Netmaker is a tool that enables you to create relays, gateways, full VPN meshes, and even zero trust networks. It's fully configurable to let you maximize the power of Wireguard. NetMaker Architecture. Credit: Netmaker . WireGuard Tools Back to the Top Wiretrustee is a WireGuard®-based mesh network that connects your devices into a single private network. Wireguard Manager is a tool that enables you to build your own vpn under a minute. Tailscale is a WireGuard-based app that makes secure, private networks easy for teams of any scale. It works like an overlay network between the computers of your networks using all kinds of NAT traversal sorcery . Headscale is an open source, self-hosted implementation of the Tailscale coordination server. Firezone is a self-hosted WireGuard®-based VPN server and Linux firewall. NetBird is an open-source VPN management platform built on top of WireGuard® making it easy to create secure private networks for your organization or home. Mistborn is a secure platform for easily standing up and managing your own cloud services: including firewall, ad-blocking, and multi-factor WireGuard VPN access. Mistborn CLI is a Command-line interface for Mistborn . BoringTun is an implementation of the WireGuard® protocol designed for portability and speed. It's successfully deployed on millions of iOS and Android consumer devices as well as thousands of Cloudflare Linux servers. PiVPN is the simplest VPN installer, designed for Raspberry Pi . Algo VPN is a set of Ansible scripts that simplify the setup of a personal WireGuard and IPsec VPN. It uses the most secure defaults available and works with common cloud providers. Pro Custodibus is a tool for managing WireGuard with a variety of business VPN (Virtual Private Network) use cases, such as site-to-site connectivity, secure remote access from anywhere, secure access to the cloud (Amazon Web Services, Google Cloud Platform, Microsoft Azure, etc), and more. Drago is a flexible configuration manager for WireGuard designed to make it simple to configure secure network overlays spanning heterogeneous nodes distributed across different clouds and physical locations. Drago is in active development, and we welcome contributions from the open-source community. Netmaker is a tool that helps connect any computers together over a secure, fast, private network, and manage multiple networks from a central server. Kilo is a multi-cloud network overlay built on WireGuard and designed for Kubernetes. Kilo connects nodes in a cluster by providing an encrypted layer 3 network that can span across data centers and public clouds. The Pod network created by Kilo is always fully connected, even when the nodes are in different networks or behind NAT. By allowing pools of nodes in different locations to communicate securely, Kilo enables the operation of multi-cloud clusters. Kilo's design allows clients to VPN to a cluster in order to securely access services running on the cluster. Subspace is a simple WireGuard VPN server GUI. WG UI is a basic, self-contained management service for WireGuard with a self-serve web UI. WireHole is a combination of WireGuard, PiHole, and Unbound in a docker-compose project with the intent of enabling users to quickly and easily create and deploy a personally managed full or split-tunnel WireGuard VPN with ad blocking capabilities (via Pihole), and DNS caching with additional privacy options (via Unbound). Gluetun is a lightwieght VPN client in a thin Docker container for multiple VPN providers, written in Go, and uses OpenVPN or Wireguard, DNS over TLS, with a few proxy servers built-in. Ethr is a cross platform network performance measurement tool written in golang. The goal of this project is to provide a native tool for comprehensive network performance measurements of bandwidth, connections/s, packets/s, latency, loss & jitter, across multiple protocols such as TCP, UDP, HTTP, HTTPS, and across multiple platforms such as Windows, Linux and other Unix systems. Setting up WireGuard with PiVPN Back to the Top Installing PiVPN: sudo apt install curl -y curl -L https://install.pivpn.io | bash Setting up WireGuard on Unraid Back to the Top Select Apps, then search for WireGuard and install Wireguard-Easy . VPN manager Almost all of the settings can stay as default, however, there are a few that we will modify. Set the WG_HOST variable to be the IP address of your Unraid server. If you’d like to modify the WireGuard port (51820), you can do that here. Change the default Web GUI password. Setting up WireGuard on pfSense Back to the Top When looking at how to set up WireGuard on pfSense, the first thing that we need to do is install the package. Follow the instructions below to install the WireGuard package on pfSense. Open the Package Manager and search for WireGuard, then Install the latest version of the package. After the package has installed, select VPN then WireGuard and under the Tunnels section, select Add Tunnel. In the Tunnel Configuration, set the Description as WireGuard, the Listen Port as 51820, then Generate private and public keys. Copy the Public Key. We will need this for our client configuration. Create the tunnel, then select Settings, and ensure that Enable WireGuard is selected. Then Save and Apply. Setting up WireGuard on OpenWRT Back to the Top Quick Links: WireGuard route all traffic through wireguard tunnel Automated WireGuard Server and Multi-client WireGuard basics WireGuard client WireGuard extras WireGuard performance WireGuard Road-Warrior Configuration WireGuard WireGuard server WireGuard peers Automated WireGuard site-to-site VPN configuration In your router’s webUI, navigate to System - Software, click Update lists: In the Filter field, type WireGuard, locate and install the wireguard, wireguard-tools, kmod-wireguard, and luci-app-wireguard packages. Note: The wireguard package is included in version 22.02. Generate WireGuard keypair SSH into your router as ‘root’ ( OpenWrt Wiki ): ssh root@192.168.1.1 Generate WireGuard keys: wg genkey | tee privatekey | wg pubkey > publickey chmod 600 privatekey Note your Private & Public keys, you will need them later: cat privatekey cat publickey Creating an Interface Navigate to Network - Interface, Click the Add new interface... button and enter the following configuration: * Name - give it any name * Protocol - WireGuard VPN Create interface In the General Settings tab: * Bring up on boot - Checked * Private Key - copy and paste the generated previously Private key * IP Address - enter the WireGuard IP Address obtained in the Client Area ending with /32, e.g. 172.27.124.169/32 Add a Firewall zone Navigate to Network - Firewall Click the Add button and enter the following configuration: * Name - Give it any name * Input - Reject * Output - Accept * Forward - Reject * Masquerading - Checked * MSS clamping - Checked * Covered networks - select the previously created VPN tunnel interface * Allow forward to destination zones - Unspecified * Allow forward from source zones - lan DNS Navigate to Network - Interfaces Click on the Edit button next to the WAN interface In the Advanced Settings tab, uncheck the Use DNS servers advertised by peer and specify one of the following DNS servers in the Use custom DNS servers field: 172.16.0.1 = regular DNS with no blocking 10.0.254.2 = standard AntiTracker to block advertising and malware domains 10.0.254.3 = Hardcore Mode AntiTracker to also block Google and Facebook domains Click the Save button. Last Steps A device reboot is not required, though it may be useful to confirm that everything behaves as expected. Run a leak test at https://www.dnsleaktest.com via one of the internal network clients attached to your OpenWRT router. Setting up WireGuard on Home Assistant Back to the Top Install Wireguard Add-on in Home Assistant Next, open up Home Assistant. Go to Supervisor > Add-on store, and search for WireGuard. Click the WireGuard addon, and the click Install. Configure Wireguard Settings After installing WireGuard, do not start it yet. We need to configure a few options first. Click the Configuration tab at the very top. There are two blocks of code here: server and peers. The server section is the WireGuard server info, and the peers section is where you’d add new devices that will connect to your VPN. Server Configuration Host: add the subdomain you just created. (vpn.mydomain.com) Addresses: If your internal network is using the 192.168.x.x or 10.x.x.x range, you can leave the default IP addresses WireGuard has provided. (see note above) DNS: Set to your router’s internal IP address ( Open CMD > ipconfig /all > Under DNS servers ) If you have Adguard or PiHole installed, you can use the IP address of those instead. This will allow you to block ads even when connected to the WireGuard VPN. Peers Configuration This is where you’ll create WireGuard configuration files for each of the devices you want to connect to WireGuard with. For this example, I’m using my phone and leaving allowed_ips and client_allowed_ips as is. If you adding multiple devices, then you’ll need to copy the entire block of code starting at name, give it a different name, and add the next available IP address (For example: 172.27.66.4) Click Save once finished. Then, go back to the Info tab and click Start . Port Forward The next step is to forward port 51820 from your Home Assistant server through your router. Unfortunately, there are so many different types of routers, each with different steps to port forward. The important thing to note is that you’ll be port forwarding 51820(wireguard port) from the internal IP of your Home Assistant instance (for example: 192.168.68.24) and choosing the UDP protocol only . Download Wireguard app on mobile device Download the WireGuard app from the Apple App Store or Google Play Store . You will need it for the next step. If all goes well, you can click into the new tunnel connection from within the app. If you see data flowing under the Transfer section, that means you are good to go. Improving Security Once you have everything setup and working correctly, you should read through the WireGuard Addon docs to setup up allowed_ips and client_allowed_ips to further secure your VPN instance. There’s also some other helpful options you can configure such as log level, but these are all optional. Nextcloud Back to the Top Nextcloud is an industry-leading, on-premises content collaboration platform for file sync & share and communication server. It is fully open source and you can host it yourself or pay a company to do it for you. Also checkout the following links below: Nextcloud App Store Nextcloud GitHub Nextcloud Developer Program Nexcloud login screen Nextcloud Hub is a tool that allows you to share and collaborate on documents, send and receive email, manage your calendar and have video chats without data leaks. As fully on-premises solution, Nextcloud Hub provides the benefits of online collaboration without the compliance and security risks. Nexcloud Hub Nextcloud AIO (All In One) is a tool that provides easy deployment and maintenance with most features included in this one Nextcloud instance. Features it includes: Nextcloud Nextcloud Office High performance backend for Nextcloud Files High performance backend for Nextcloud Talk Backup solution (based on BorgBackup) Imaginary ClamAV Fulltextsearch Nextcloud Desktop Client is a tool to synchronize files from Nextcloud Server with your computer. Nextcloud Deck is a kanban style organization tool aimed at personal planning and project organization for teams integrated with Nextcloud. Nextcloud Files is a tool tool that allows your employees have easy access to their files, photos and documents to work and can share and collaborate with team members, customers and partners. So IT knows nobody besides those they shared with has access to those files. Nextcloud Talk is a tool that protects your communication better than other team collaboration platforms like Microsoft Teams or Slack, making sure your data stays on your servers. It also goes further than other encrypted communication technologies by keeping even metadata from leaking. Nextcloud Home is a tool that allows you store your documents, calendar, contacts and photos on your server at home, at one of at one Nextcloud's providers or in a data center you trust. Nextcloud Enterprise is a service that gives professional organizations software optimized and tested for mission critical environments. Nextcloud Outlook Integration is a tool that automatically upload files to replace large attachments or integrate Calendars and Contacts in Microsoft Outlook. Collabora Online in Nextcloud is a powerful LibreOffice-based online office suite with collaborative editing, which supports all major document, spreadsheet and presentation file formats and works in all modern browsers. ONLYOFFICE integration in Nextcloud is a service that empowers your users to collaborate on office documents with team members in real time. It has compatibility with Microsoft Office formats means perfect documents, every time. Nextcloud VM(virtual machine appliance) is a set of carefully crafted family of *nix scripts, which interactively guide you through a quality-controlled installation of a Nextcloud instance for Home/SME Server and scripts for Raspberry Pi 4. It is Community developed and maintained. LibreSign is a Libre digital signature app for Nextcloud. Raspberry Pi Back to the Top Models of Raspberry Pi boards Back to the Top Raspberry Pi 4 Model B Check out the Raspberry Pi 4 Raspberry Pi 4 Model B Hardware Specifications Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz 2GB, 4GB or 8GB LPDDR4-3200 SDRAM (depending on model) 2.4 GHz and 5.0 GHz IEEE 802.11ac wireless Bluetooth 5.0, BLE Gigabit Ethernet 2 USB 3.0 ports; 2 USB 2.0 ports. Raspberry Pi standard 40 pin GPIO header (fully backwards compatible with previous Pi boards) 2 × micro-HDMI ports (up to 4kp60 supported) OpenGL ES 3.0 graphics Raspberry Pi 400 Personal Computer Kit Check out the Raspberry Pi 400 Personal Computer Kit Raspberry Pi 400 Hardware Specifications Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.8GHz 4GB LPDDR4-3200 SDRAM 2.4 GHz and 5.0 GHz IEEE 802.11ac wireless Bluetooth 5.0, BLE Gigabit Ethernet 2 USB 3.0 ports; 2 USB 2.0 ports. Raspberry Pi standard 40 pin GPIO header 2 × micro-HDMI ports (up to 4kp60 supported) OpenGL ES 3.0 graphics Raspberry Pi Pico Microcontroller Check out the Raspberry Pi Pico Raspberry Pi Pico Hardware Specifications RP2040 microcontroller chip designed by Raspberry Pi in the UK Dual-core Arm Cortex-M0+ processor, flexible clock running up to 133 MHz 264KB on-chip SRAM 2MB on-board QSPI Flash 26 multifunction GPIO pins, including 3 analogue inputs 2 × UART, 2 × SPI controllers, 2 × I2C controllers, 16 × PWM channels 1 × USB 1.1 controller and PHY, with host and device support 8 × Programmable I/O (PIO) state machines for custom peripheral support Castellated module allows soldering direct to carrier boards Drag-and-drop programming using mass storage over USB Low-power sleep and dormant modes Accurate on-chip clock Temperature sensor Accelerated integer and floating-point libraries on-chip Raspberry Pi OS. The default Operating System for every Raspberry Pi device Check out Raspberry Pi OS Raspberry Pi Learning Resources Back to the Top Raspberry Pi is an ARM powered single board computer(SBC) that is the size of a credit card and costs around $35. Raspberry Pi Foundation is a UK-based charity that works to put the power of computing and digital making into the hands of people all over the world. Microsecond accurate NTP with a Raspberry Pi and PPS GPS Getting Started with Raspberry Pi Projects Online learning for the Raspberry Pi Raspberry Pi Training Program Raspberry Pi Online Courses on Udemy Raspberry Pi Online Courses on Coursera The Raspberry Pi Platform and Python Programming course on Coursera Learning Raspberry Pi with Online Courses on edX Raspberry Pi Online Training Courses on LinkedIn Learning Getting Started with Raspberry Pi course on FutureLearn Home Assistant on Raspberry Pi PiSwitch: Build your own Nintendo Switch-style console Raspberry Pi Operating Systems Back to the Top Raspberry Pi OS Hass.io(Home Assistant OS) OmniROM(Android 11) based on ASOP Manjaro Linux ARM Arch Linux ARM Ubuntu MATE for Raspberry Pi Ubuntu Desktop for Raspberry Pi Ubuntu Core on a Raspberry Pi Ubuntu Server for ARM Fedora ARM Kali Linux for the Raspberry Pi Twister OS TitusPi RetroArch RetroPie LibreELEC OSMC RISC OS DietPi Windows 10 IoT Core Raspberry Pi Tools Back to the Top Raspberry Pi Imager is the quick and easy way to install Raspberry Pi OS and other operating systems to a microSD card, ready to use with your Raspberry Pi. Raspberry Pi Locator is a website to track Raspberry Pi 4 model B, Compute Module 4, Pi Zero 2 W, and Pico availability across multiple retailers in different countries. Raspberry Pi Network Install (Beta) is a feature can be used to start the Raspberry Pi Imager application directly on a Raspberry Pi 4, or a Raspberry Pi 400, by downloading it from the internet using an Ethernet cable. The Raspberry Pi Imager application, which will run in memory on your Raspberry Pi, can then be used to flash the operating system onto a blank SD Card or USB disk, just like normal. Raspberry Pi Bootloader is a feature, which is now available in beta, that utilize an EEPROM(Electrically Erasable Programmable Read-Only Memory) to store the system’s bootloader. This EEPROM is persistent storage that is located on the Pi’s mainboard. The advantage of using the EEPROM instead is that the Raspberry Pi 4 can perform tasks without needing any storage to be attached. Etcher is an open source, cross-platform software that makes it easy to flash operating system images to a microSD card or USB device. Home Assistant is an open source home automation that puts local control and privacy first. Home Assistant is powered by a worldwide community of tinkerers and DIY enthusiasts that runs great on Raspberry Pi. Gladys Assistant is a privacy-first, open-source home assistant and runs great on Raspberry Pi. Kodi for Raspberry Pi is a free and open source media player application developed by the XBMC/Kodi Foundation. Pi-hole is a DNS sinkhole that protects your devices from unwanted content, without installing any client-side software, intended for use on a private network. It is designed for use on embedded devices with network capability, such as the Raspberry Pi, but it can be used on other machines running Linux and cloud implementations. PiKVM is a very simple and fully functional Raspberry Pi-based KVM over IP. PiShrink is a bash script that automatically shrink a pi image that will then resize to the max size of the SD card on boot. RPiPlay is an open-source implementation of an AirPlay mirroring server for the Raspberry Pi that supports iOS 9 and later. Gpiozero is a simple interface to GPIO(General-Purpose Input/Output) devices with the Raspberry Pi. Balena Sound is a single or multi-room streamer for an existing audio device using a Raspberry Pi! It supports Bluetooth, Airplay and Spotify Connect. OpenBalena is a platform to deploy and manage connected devices. Home Assistant Back to the Top Home Assistant is a container-based system for managing your Home Assistant Core installation and related applications. The system is controlled via Home Assistant which communicates with the Supervisor. The Supervisor provides an API to manage the installation. This includes changing network settings or installing and updating software. Quick Links Getting Started with Home Assistant Home Assistant for Raspberry Pi Installing Home Assistant OS using Proxmox 7 Home Assistant Frontend is a frontend for Home Assistant. Tools to write the HA image to your boot media(microSD card or USB device) Raspberry Pi Imager is the quick and easy way to install Raspberry Pi OS and other operating systems to a microSD card, ready to use with your Raspberry Pi. Etcher is an open source, cross-platform software that makes it easy to flash operating system images to a microSD card or USB device. Home Assistant integrations Home Assistant integrations. Credit: Home Assistant ESPHome is a system to control your ESP8266/ESP32 by simple yet powerful configuration files and control them remotely through Home Automation systems. Shelly Cloud is a Smart home control tool that has been perfected and provides precise monitoring of your Shelly devices no matter where you are. Shelly devices are compatible with Alexa, Google Home, Android, and iOS. Plex media server is a application that gives you the power to add, access and share all the entertainment that matters to you, on almost any device. With 50,000+ on demand titles and hundreds of channels of live TV, plus your own personal media collection, using one powerful app. Amazon Alexa is a smart virtual assistant software to manage Alexa-enabled devices, control music playback, view shopping lists on the go, keep track of upcoming reminders, check on active timers and much more. Google Assistant is a smart virtual assistant software on mobile and home automation devices. Apple HomeKit is a software framework that enables your app to coordinate and control home automation accessories from multiple vendors to present a coherent, user-focused interface. Using HomeKit, your app can: Discover HomeKit-compatible automation accessories and add them to a persistent, cross-device home configuration database. Samsung SmartThings is a sofwtare frmaeowrk that you can connect, monitor and control multiple smart home devices quicker and easier. Connect your Samsung smart TVs, smart appliances, smart speakers and brands like Ring, Nest and Philips Hue all from one app. Ecobee is a home automation company in Canada that makes thermostats for residential and commercial use. Lutron Caséta is a smart lighting control system that is a great solution for giving any client smart lighting control. It was purposely built to work in homes of all ages and it works with older wiring as well as new. Philips Hue is a smart lighting system. The smart lights, Hue Bridge, and smart controls will forever change the way you experience light. Sonos is the wireless home sound system that fills as many rooms as you want with great-sounding music, movies, and TV. MQTT is an OASIS standard messaging protocol for the Internet of Things (IoT). It is designed as an extremely lightweight publish/subscribe messaging transport that is ideal for connecting remote devices with a small code footprint and minimal network bandwidth. Zigbee is the full-stack, secure, reliable, and market-proven solution used by a majority of large smart home ecosystem providers, such as Amazon's Echo Plus, Samsung SmartThings, Signify (Philips Hue), and more. openHAB is a cross-platform software with the aim to integrate all kinds of Smart Home technologies, devices, etc. Z-Wave is the leading wireless communications protocol behind many of the secure, trusted brands that are working to make everyone's home smarter and safer. Zwavejs2Mqtt is a fully configurable Zwave to MQTT Gateway and Control Panel Web UI. Z-Wave JS Server is a small server wrapper around Z-Wave JS to access it via a WebSocket. Z-Wave JS Config DB Browser is the official device configuration reference to find out if your device is supported. Currently supports 387 brands, spanning at least 2075 device configurations. Homebridge Back to the Top Homebridge is a software frameowrk that allows you to integrate with smart home devices that do not natively support HomeKit . There are over 2,000 Homebridge plugins supporting thousands of different smart accessories. Official Homebridge Raspberry Pi Image Setup Homebridge on a Raspberry Pi (Raspbian) Setup Homebridge on Debian or Ubuntu Setup Homebridge on Red Hat, CentOS Stream or Fedora Setup Homebridge on Docker (Linux) Tools to write the Homebridge image to your boot media(microSD card or USB device) Raspberry Pi Imager is the quick and easy way to install Raspberry Pi OS and other operating systems to a microSD card, ready to use with your Raspberry Pi. Etcher is an open source, cross-platform software that makes it easy to flash operating system images to a microSD card or USB device. Homebridge UI is a tool that provides an easy to use interface to manage your Homebridge plugins, configuration and accessories. Install and configure Homebridge plugins. Monitor your Homebridge server via a fully customisable widget-based dashboard. View and control Homebridge accessories. Backup and Restore your Homebridge instance. Homebridge UI ESPHome Back to the Top ESPHome is a system to control your ESP8266/ESP32 by simple yet powerful configuration files and control them remotely through Home Automation systems. Quick Links ESP Web Tools Installing ESPHome Manually | ESPHome Getting Started with the ESPHome Command Line Getting Started with ESPHome and Home Assistant ESPHome on the Raspberry Pi Pico! | Jeff Geerling How to Start on Raspberry Pi Home Automation | ESPHome ESPHome Setup | Integrating Home Assistant with Adafruit IO Install ESPHome using Home Assistant In Home Assistant go to: Configuration > Add-ons, Backups & Supervisor > Add-on Store (button in the lower right corner) or click on the My Home Assistant Link below: Open your Home Assistant instance and show the Supervisor add-on store. Next, search for ESPHome, click on the result and then click on the Install button. When the installation is finished, the Install button will be replaced with Start button – click on it to start the ESPHome add-on. Wait a few seconds for the ESPHome to start and then click on the Open Web UI button. Install ESPHome using Docker First thing is to pull the ESPHome Docker image from Docker Hub (Online). docker pull esphome/esphome Then, start the ESPHome wizard. This wizard will ask you about your device type, your device name, your WiFi credentials and finally will generate a yaml file containing all of the configurations for you. docker run --rm -v "${PWD}":/config -it esphome/esphome wizard stl.yaml Now, connect your ESP device to the device where Docker is running (either using an USB cable or Serial-To-USB adapter) and if you are on Linux type the following command : dmesg | grep ttyUSB Put your device in programming mode (if needed) and execute the next command to install the ESPHome on the device connected to the /dev/ttyUSB1 using the configuration stored in stl.yaml file docker run --rm -v "${PWD}":/config --device=/dev/ttyUSB1 -it esphome/esphome run stl.yaml Install ESPHome using Python If you are on macOS or Linux check if Python 3.8 or later is installed by executing the command. python3 --version If you are on macOS, you need to install wheel and esphome packages by using the following command. pip3 install wheel esphome If you are on Linux, you have to install esphome package by using the following command. pip3 install --user esphome If you are on macOS or Linux you can start the ESPHome wizard using the following command. esphome wizard stl-python.yaml Finally, connect your ESP device to your Computer (using USB cable or Serial-To-usb adapter) and put it in programming mode (if needed). Then, Install ESPHome using the configuration in the stl-python.yaml file. esphome run stl-python.yaml Turning Raspberry Pi into a Router Back to the Top Software OpenWrt Project is a Linux operating system targeting embedded devices. Instead of trying to create a single, static firmware, OpenWrt provides a fully writable filesystem with package management. It's primarily used on embedded devices to route network traffic. OpenWrt Wiki - Raspberry Pi setup Download the appropriate OpenWrt image for your Raspberry PI by going to the link above. Tools to write the Operating System (OS) image to your boot media(microSD card) Raspberry Pi Imager is the quick and easy way to install Raspberry Pi OS and other operating systems to a microSD card, ready to use with your Raspberry Pi. Hardware Raspberry Pi Router Board for CM4 module (Cost: $55 USD) is an expansion board based on the Raspberry Pi Compute Module 4. It brings Raspberry Pi CM4 two full-speed gigabit network ports and offers better performance, lower CPU usage, and higher stability for a long time work compared with a USB network card. It's compatible with Raspberry Pi OS , Ubuntu Server and other Raspberry Pi systems. Raspberry Pi Router Board for CM4 module Technical Specs: Compatible Module: Raspberry Pi Compute Module 4 series. BCM2711 4 core @ 1.5GHz Cortex-A72. Support standard Raspberry Pi HAT interface. Support POE HAT to supply power to the board. Support POE HAT for external power supply. Full-speed dual gigabit network interface. Master-slave dual USB2.0 interface. Micro SD card slot, used to support non-eMMC version of CM4. Standard HDMI video output interface. 0.91 inch IIC OLED display. 5V DC fan interface(Support controlling via PWM signal). Ethernet: high-performance Gigabit ethernet controller RTL8111E chip, JXD 2111x G2406s chip as isolation transformer. Port0: Compute Module 4 Built-In. Port1: PCI Express 1000BASE-T NIC. GPIO: 40-Pin GPIO compatible with Raspberry Pi. Setting Watchdog Timer (WDT) on Raspberry Pi Back to the Top Watchdog Timer (WDT) is a timer that monitors microcontroller (MCU) programs to see if they are out of control or have stopped operating. Installing and enabling WDT service To enable watchdog you have to change the boot parameters by adding dtparam=watchdog=on in /boot/config.txt using a text editor such as nano, vim, gedit, etc.. Also, install watchdog package and enable it to start at startup. Also, make sure to restart your Raspberry Pi for these settings to take effect. pi@raspberrypi:~ $ sudo apt install watchdog pi@raspberrypi:~ $sudo systemctl enable watchdog Configure WDT service Configuration file for watchdog can be found in /etc/watchdog.conf . max-load-1 = 24 watchdog-device = /dev/watchdog realtime = yes priority = 1 To start the WTD service: pi@raspberrypi:~ $ sudo systemctl start watchdog Check watchdog status: pi@raspberrypi:~ $ sudo systemctl status watchdog To stop the service: pi@raspberrypi:~ $ sudo systemctl stop watchdog Raspberry Pi Upgrades Back to the Top Raspberry Pi Cases from Pi-Shop US Raspberry Pi Cases from The Pi Hut X825 expansion board provides a complete storage solution for newest Raspberry Pi 4 Model B, it supports up to 4TB 2.5-inch SATA hard disk drives (HDD) / solid-state drive (SSD). Sabrent M.2 SSD [NGFF] to USB 3.0 / SATA III 2.5-Inch Aluminum Enclosure Adapter Samsung 970 EVO 250GB - NVMe PCIe M.2 2280 SSD Western Digital 1TB WD Blue SN550 NVMe Internal SSD SAMSUNG T5 Portable SSD Samsung SSD 860 EVO 250GB mSATA Internal SSD Samsung 850 EVO 120GB SSD mSATA Grafana Back to the Top Grafana Learning Resources Grafana is an analytics platform that enables you to query and visualize data, then create and share dashboards based on your visualizations. Easily visualize metrics, logs, and traces from multiple sources such as Prometheus, Loki, Elasticsearch, InfluxDB, Postgres, Fluentd, Fluentbit, Logstash and many more. Getting Started with Grafana Grafana Community Grafana Professional Services Training | Grafana Labs Grafana Pro Training AWS | Grafana Labs Grafana Tutorials Top Grafana Courses on Udemy Grafana Online Training Courses | LinkedIn Learning Grafana Training Courses - NobleProg Setting Up Grafana to Visualize Our Metrics Course on Coursera Grafana Tools Grafana Cloud is a composable observability platform, integrating metrics, traces and logs with Grafana. Leverage the best open source observability software – including Prometheus, Loki, and Tempo – without the overhead of installing, maintaining, and scaling your observability stack. Grafana Cloud Integrations. Source: Grafana Grafana Enterprise is a service that includes features that provide better scalability, collaboration, operations, and governance in a self-managed environment. Grafana Enterprise Stack. Source: Grafana Grafana Tempo is an open source high-scale distributed tarcing backend. Tempo is cost-efficient, requiring only object storage to operate, and is deeply integrated with Grafana, Loki, and Prometheus. Grafana MetricTank is a multi-tenant timeseries platform for Graphite developed by Grafana Labs. MetricTank provides high-availability(HA) and efficient long-term storage, retrieval, and processing for large-scale environments. Grafana Tanka is a robust configuration utility for your Kubernetes cluster, powered by the Jsonnet language. Grafana Loki is a horizontally-scalable, highly-available(HA), multi-tenant log aggregation system inspired by Prometheus. Cortex is a project that lets users query metrics from many Prometheusservers in a single place, without any gaps in the grpahs due to server failture. Also, Cortex lets you store Prometheus metrics for long term capacity planning and performance analysis. Graphite is an open source monitoring system. Networking Back to the Top Networking Tools & Concepts cURL is a computer software project providing a library and command-line tool for transferring data using various network protocols(HTTP, HTTPS, FTP, FTPS, SCP, SFTP, TFTP, DICT, TELNET, LDAP LDAPS, MQTT, POP3, POP3S, RTMP, RTMPS, RTSP, SCP, SFTP, SMB, SMBS, SMTP or SMTPS). cURL is also used in cars, television sets, routers, printers, audio equipment, mobile phones, tablets, settop boxes, media players and is the Internet transfer engine for thousands of software applications in over ten billion installations. cURL Fuzzer is a quality assurance testing for the curl project. DoH is a stand-alone application for DoH (DNS-over-HTTPS) name resolves and lookups. Authelia is an open-source highly-available authentication server providing single sign-on capability and two-factor authentication to applications running behind NGINX . nginx(engine x) is an HTTP and reverse proxy server, a mail proxy server, and a generic TCP/UDP proxy server, originally written by Igor Sysoev. Proxmox Virtual Environment(VE) is a complete open-source platform for enterprise virtualization. It inlcudes a built-in web interface that you can easily manage VMs and containers, software-defined storage and networking, high-availability clustering, and multiple out-of-the-box tools on a single solution. Wireshark is a very popular network protocol analyzer that is commonly used for network troubleshooting, analysis, and communications protocol development. Learn more about the other useful Wireshark Tools available. HTTPie is a command-line HTTP client. Its goal is to make CLI interaction with web services as human-friendly as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers. HTTPStat is a tool that visualizes curl statistics in a simple layout. Wuzz is an interactive cli tool for HTTP inspection. It can be used to inspect/modify requests copied from the browser's network inspector with the "copy as cURL" feature. Websocat is a ommand-line client for WebSockets, like netcat (or curl) for ws:// with advanced socat-like functions. • Connection: In networking, a connection refers to pieces of related information that are transferred through a network. This generally infers that a connection is built before the data transfer (by following the procedures laid out in a protocol) and then is deconstructed at the at the end of the data transfer. • Packet: A packet is, generally speaking, the most basic unit that is transferred over a network. When communicating over a network, packets are the envelopes that carry your data (in pieces) from one end point to the other. Packets have a header portion that contains information about the packet including the source and destination, timestamps, network hops. The main portion of a packet contains the actual data being transferred. It is sometimes called the body or the payload. • Network Interface: A network interface can refer to any kind of software interface to networking hardware. For instance, if you have two network cards in your computer, you can control and configure each network interface associated with them individually. A network interface may be associated with a physical device, or it may be a representation of a virtual interface. The "loop-back" device, which is a virtual interface to the local machine, is an example of this. • LAN: LAN stands for "local area network". It refers to a network or a portion of a network that is not publicly accessible to the greater internet. A home or office network is an example of a LAN. • WAN: WAN stands for "wide area network". It means a network that is much more extensive than a LAN. While WAN is the relevant term to use to describe large, dispersed networks in general, it is usually meant to mean the internet, as a whole. If an interface is connected to the WAN, it is generally assumed that it is reachable through the internet. • Protocol: A protocol is a set of rules and standards that basically define a language that devices can use to communicate. There are a great number of protocols in use extensively in networking, and they are often implemented in different layers. Some low level protocols are TCP, UDP, IP, and ICMP. Some familiar examples of application layer protocols, built on these lower protocols, are HTTP (for accessing web content), SSH, TLS/SSL, and FTP. • Port: A port is an address on a single machine that can be tied to a specific piece of software. It is not a physical interface or location, but it allows your server to be able to communicate using more than one application. • Firewall: A firewall is a program that decides whether traffic coming into a server or going out should be allowed. A firewall usually works by creating rules for which type of traffic is acceptable on which ports. Generally, firewalls block ports that are not used by a specific application on a server. • NAT: Network address translation is a way to translate requests that are incoming into a routing server to the relevant devices or servers that it knows about in the LAN. This is usually implemented in physical LANs as a way to route requests through one IP address to the necessary backend servers. • VPN: Virtual private network is a means of connecting separate LANs through the internet, while maintaining privacy. This is used as a means of connecting remote systems as if they were on a local network, often for security reasons. Network Layers While networking is often discussed in terms of topology in a horizontal way, between hosts, its implementation is layered in a vertical fashion throughout a computer or network. This means is that there are multiple technologies and protocols that are built on top of each other in order for communication to function more easily. Each successive, higher layer abstracts the raw data a little bit more, and makes it simpler to use for applications and users. It also allows you to leverage lower layers in new ways without having to invest the time and energy to develop the protocols and applications that handle those types of traffic. As data is sent out of one machine, it begins at the top of the stack and filters downwards. At the lowest level, actual transmission to another machine takes place. At this point, the data travels back up through the layers of the other computer. Each layer has the ability to add its own "wrapper" around the data that it receives from the adjacent layer, which will help the layers that come after decide what to do with the data when it is passed off. One method of talking about the different layers of network communication is the OSI model. OSI stands for Open Systems Interconnect.This model defines seven separate layers. The layers in this model are: • Application: The application layer is the layer that the users and user-applications most often interact with. Network communication is discussed in terms of availability of resources, partners to communicate with, and data synchronization. • Presentation: The presentation layer is responsible for mapping resources and creating context. It is used to translate lower level networking data into data that applications expect to see. • Session: The session layer is a connection handler. It creates, maintains, and destroys connections between nodes in a persistent way. • Transport: The transport layer is responsible for handing the layers above it a reliable connection. In this context, reliable refers to the ability to verify that a piece of data was received intact at the other end of the connection. This layer can resend information that has been dropped or corrupted and can acknowledge the receipt of data to remote computers. • Network: The network layer is used to route data between different nodes on the network. It uses addresses to be able to tell which computer to send information to. This layer can also break apart larger messages into smaller chunks to be reassembled on the opposite end. • Data Link: This layer is implemented as a method of establishing and maintaining reliable links between different nodes or devices on a network using existing physical connections. • Physical: The physical layer is responsible for handling the actual physical devices that are used to make a connection. This layer involves the bare software that manages physical connections as well as the hardware itself (like Ethernet). The TCP/IP model, more commonly known as the Internet protocol suite, is another layering model that is simpler and has been widely adopted.It defines the four separate layers, some of which overlap with the OSI model: • Application: In this model, the application layer is responsible for creating and transmitting user data between applications. The applications can be on remote systems, and should appear to operate as if locally to the end user. The communication takes place between peers network. • Transport: The transport layer is responsible for communication between processes. This level of networking utilizes ports to address different services. It can build up unreliable or reliable connections depending on the type of protocol used. • Internet: The internet layer is used to transport data from node to node in a network. This layer is aware of the endpoints of the connections, but does not worry about the actual connection needed to get from one place to another. IP addresses are defined in this layer as a way of reaching remote systems in an addressable manner. • Link: The link layer implements the actual topology of the local network that allows the internet layer to present an addressable interface. It establishes connections between neighboring nodes to send data. Interfaces Interfaces are networking communication points for your computer. Each interface is associated with a physical or virtual networking device. Typically, your server will have one configurable network interface for each Ethernet or wireless internet card you have. In addition, it will define a virtual network interface called the "loopback" or localhost interface. This is used as an interface to connect applications and processes on a single computer to other applications and processes. You can see this referenced as the "lo" interface in many tools. Network Protocols Networking works by piggybacks on a number of different protocols on top of each other. In this way, one piece of data can be transmitted using multiple protocols encapsulated within one another. Media Access Control(MAC) is a communications protocol that is used to distinguish specific devices. Each device is supposed to get a unique MAC address during the manufacturing process that differentiates it from every other device on the internet. Addressing hardware by the MAC address allows you to reference a device by a unique value even when the software on top may change the name for that specific device during operation. Media access control is one of the only protocols from the link layer that you are likely to interact with on a regular basis. The IP protocol is one of the fundamental protocols that allow the internet to work. IP addresses are unique on each network and they allow machines to address each other across a network. It is implemented on the internet layer in the IP/TCP model. Networks can be linked together, but traffic must be routed when crossing network boundaries. This protocol assumes an unreliable network and multiple paths to the same destination that it can dynamically change between. There are a number of different implementations of the protocol. The most common implementation today is IPv4, although IPv6 is growing in popularity as an alternative due to the scarcity of IPv4 addresses available and improvements in the protocols capabilities. ICMP: internet control message protocol is used to send messages between devices to indicate the availability or error conditions. These packets are used in a variety of network diagnostic tools, such as ping and traceroute. Usually ICMP packets are transmitted when a packet of a different kind meets some kind of a problem. Basically, they are used as a feedback mechanism for network communications. TCP: Transmission control protocol is implemented in the transport layer of the IP/TCP model and is used to establish reliable connections. TCP is one of the protocols that encapsulates data into packets. It then transfers these to the remote end of the connection using the methods available on the lower layers. On the other end, it can check for errors, request certain pieces to be resent, and reassemble the information into one logical piece to send to the application layer. The protocol builds up a connection prior to data transfer using a system called a three-way handshake. This is a way for the two ends of the communication to acknowledge the request and agree upon a method of ensuring data reliability. After the data has been sent, the connection is torn down using a similar four-way handshake. TCP is the protocol of choice for many of the most popular uses for the internet, including WWW, FTP, SSH, and email. It is safe to say that the internet we know today would not be here without TCP. UDP: User datagram protocol is a popular companion protocol to TCP and is also implemented in the transport layer. The fundamental difference between UDP and TCP is that UDP offers unreliable data transfer. It does not verify that data has been received on the other end of the connection. This might sound like a bad thing, and for many purposes, it is. However, it is also extremely important for some functions. It’s not required to wait for confirmation that the data was received and forced to resend data, UDP is much faster than TCP. It does not establish a connection with the remote host, it simply fires off the data to that host and doesn't care if it is accepted or not. Since UDP is a simple transaction, it is useful for simple communications like querying for network resources. It also doesn't maintain a state, which makes it great for transmitting data from one machine to many real-time clients. This makes it ideal for VOIP, games, and other applications that cannot afford delays. HTTP: Hypertext transfer protocol is a protocol defined in the application layer that forms the basis for communication on the web. HTTP defines a number of functions that tell the remote system what you are requesting. For instance, GET, POST, and DELETE all interact with the requested data in a different way. FTP: File transfer protocol is in the application layer and provides a way of transferring complete files from one host to another. It is inherently insecure, so it is not recommended for any externally facing network unless it is implemented as a public, download-only resource. DNS: Domain name system is an application layer protocol used to provide a human-friendly naming mechanism for internet resources. It is what ties a domain name to an IP address and allows you to access sites by name in your browser. SSH: Secure shell is an encrypted protocol implemented in the application layer that can be used to communicate with a remote server in a secure way. Many additional technologies are built around this protocol because of its end-to-end encryption and ubiquity. There are many other protocols that we haven't covered that are equally important. However, this should give you a good overview of some of the fundamental technologies that make the internet and networking possible. REST(REpresentational State Transfer) is an architectural style for providing standards between computer systems on the web, making it easier for systems to communicate with each other. JSON Web Token (JWT) is a compact URL-safe means of representing claims to be transferred between two parties. The claims in a JWT are encoded as a JSON object that is digitally signed using JSON Web Signature (JWS). OAuth 2.0 is an open source authorization framework that enables applications to obtain limited access to user accounts on an HTTP service, such as Amazon, Google, Facebook, Microsoft, Twitter GitHub, and DigitalOcean. It works by delegating user authentication to the service that hosts the user account, and authorizing third-party applications to access the user account. Docker Back to the Top Container Architecture. Source: Containerd.io Docker Learning Resources Docker Training Program Docker Certified Associate (DCA) certification Docker Documentation | Docker Documentation The Docker Workshop Docker Courses on Udemy Docker Courses on Coursera Docker Courses on edX Docker Courses on Linkedin Learning Docker Tools Docker is an open platform for developing, shipping, and running applications. Docker enables you to separate your applications from your infrastructure so you can deliver software quickly working in collaboration with cloud, Linux, and Windows vendors, including Microsoft. Docker Enterprise is a subscription including software, supported and certified container platform for CentOS, Red Hat Enterprise Linux (RHEL), Ubuntu, SUSE Linux Enterprise Server (SLES), Oracle Linux, and Windows Server 2016, as well as for cloud providers AWS and Azure. In November 2019 Docker's Enterprise Platform business was acquired by Mirantis . Docker Desktop is an application for MacOS and Windows machines for the building and sharing of containerized applications and microservices. Docker Desktop delivers the speed, choice and security you need for designing and delivering containerized applications on your desktop. Docker Desktop includes Docker App, developer tools, Kubernetes and version synchronization to production Docker Engines. Docker Hub is the world's largest library and community for container images Browse over 100,000 container images from software vendors, open-source projects, and the community. Docker Compose is a tool that was developed to help define and share multi-container applications. With Docker Compose, you can create a YAML file to define the services and with a single command, can spin everything up or tear it all down. Docker Swarm is a Docker-native clustering system swarm is a simple tool which controls a cluster of Docker hosts and exposes it as a single "virtual" host. Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image. Using docker build users can create an automated build that executes several command-line instructions in succession. Docker Containers is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another. Docker Engine is a container runtime that runs on various Linux (CentOS, Debian, Fedora, Oracle Linux, RHEL, SUSE, and Ubuntu) and Windows Server operating systems. Docker creates simple tooling and a universal packaging approach that bundles up all application dependencies inside a container which is then run on Docker Engine. Docker Images is a lightweight, standalone, executable package of software that includes everything needed to run an application: code, runtime, system tools, system libraries and settings. Images have intermediate layers that increase reusability, decrease disk usage, and speed up docker build by allowing each step to be cached. These intermediate layers are not shown by default. The SIZE is the cumulative space taken up by the image and all its parent images. Docker Network is a that displays detailed information on one or more networks. Docker Daemon is a service started by a system utility, not manually by a user. This makes it easier to automatically start Docker when the machine reboots. The command to start Docker depends on your operating system. Currently, it only runs on Linux because it depends on a number of Linux kernel features, but there are a few ways to run Docker on MacOS and Windows as well by configuring the operating system utilities. Docker Storage is a driver controls how images and containers are stored and managed on your Docker host. Kitematic is a simple application for managing Docker containers on Mac, Linux and Windows letting you control your app containers from a graphical user interface (GUI). Open Container Initiative is an open governance structure for the express purpose of creating open industry standards around container formats and runtimes. Buildah is a command line tool to build Open Container Initiative (OCI) images. It can be used with Docker, Podman, Kubernetes. Podman is a daemonless, open source, Linux native tool designed to make it easy to find, run, build, share and deploy applications using Open Containers Initiative (OCI) Containers and Container Images. Podman provides a command line interface (CLI) familiar to anyone who has used the Docker Container Engine. Containerd is a daemon that manages the complete container lifecycle of its host system, from image transfer and storage to container execution and supervision to low-level storage to network attachments and beyond. It is available for Linux and Windows. Kubernetes Back to the Top Kubernetes Learning Resources Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. Getting Kubernetes Certifications Getting started with Kubernetes on AWS Kubernetes on Microsoft Azure Intro to Azure Kubernetes Service Azure Red Hat OpenShift Getting started with Google Cloud Getting started with Kubernetes on Red Hat Getting started with Kubernetes on IBM Red Hat OpenShift on IBM Cloud Enable OpenShift Virtualization on Red Hat OpenShift YAML basics in Kubernetes Elastic Cloud on Kubernetes Docker and Kubernetes Running Apache Spark on Kubernetes Kubernetes Across VMware vRealize Automation VMware Tanzu Kubernetes Grid All the Ways VMware Tanzu Works with AWS VMware Tanzu Education Using Ansible in a Cloud-Native Kubernetes Environment Managing Kubernetes (K8s) objects with Ansible Setting up a Kubernetes cluster using Vagrant and Ansible Running MongoDB with Kubernetes Kubernetes Fluentd Understanding the new GitLab Kubernetes Agent Intro Local Process with Kubernetes for Visual Studio 2019 Kubernetes Contributors KubeAcademy from VMware Kubernetes Tutorials from Pulumi Kubernetes Playground by Katacoda Scalable Microservices with Kubernetes course from Udacity Kubernetes Tools, Frameworks, and Projects Open Container Initiative is an open governance structure for the express purpose of creating open industry standards around container formats and runtimes. Buildah is a command line tool to build Open Container Initiative (OCI) images. It can be used with Docker, Podman, Kubernetes. Podman is a daemonless, open source, Linux native tool designed to make it easy to find, run, build, share and deploy applications using Open Containers Initiative (OCI) Containers and Container Images. Podman provides a command line interface (CLI) familiar to anyone who has used the Docker Container Engine. Containerd is a daemon that manages the complete container lifecycle of its host system, from image transfer and storage to container execution and supervision to low-level storage to network attachments and beyond. It is available for Linux and Windows. Google Kubernetes Engine (GKE) is a managed, production-ready environment for running containerized applications. Azure Kubernetes Service (AKS) is serverless Kubernetes, with a integrated continuous integration and continuous delivery (CI/CD) experience, and enterprise-grade security and governance. Unite your development and operations teams on a single platform to rapidly build, deliver, and scale applications with confidence. Amazon EKS is a tool that runs Kubernetes control plane instances across multiple Availability Zones to ensure high availability. AWS Controllers for Kubernetes (ACK) is a new tool that lets you directly manage AWS services from Kubernetes. ACK makes it simple to build scalable and highly-available Kubernetes applications that utilize AWS services. Container Engine for Kubernetes (OKE) is an Oracle-managed container orchestration service that can reduce the time and cost to build modern cloud native applications. Unlike most other vendors, Oracle Cloud Infrastructure provides Container Engine for Kubernetes as a free service that runs on higher-performance, lower-cost compute. Anthos is a modern application management platform that provides a consistent development and operations experience for cloud and on-premises environments. Red Hat Openshift is a fully managed Kubernetes platform that provides a foundation for on-premises, hybrid, and multicloud deployments. OKD is a community distribution of Kubernetes optimized for continuous application development and multi-tenant deployment. OKD adds developer and operations-centric tools on top of Kubernetes to enable rapid application development, easy deployment and scaling, and long-term lifecycle maintenance for small and large teams. Odo is a fast, iterative, and straightforward CLI tool for developers who write, build, and deploy applications on Kubernetes and OpenShift. Kata Operator is an operator to perform lifecycle management (install/upgrade/uninstall) of Kata Runtime on Openshift as well as Kubernetes cluster. Thanos is a set of components that can be composed into a highly available metric system with unlimited storage capacity, which can be added seamlessly on top of existing Prometheus deployments. OpenShift Hive is an operator which runs as a service on top of Kubernetes/OpenShift. The Hive service can be used to provision and perform initial configuration of OpenShift 4 clusters. Rook is a tool that turns distributed storage systems into self-managing, self-scaling, self-healing storage services. It automates the tasks of a storage administrator: deployment, bootstrapping, configuration, provisioning, scaling, upgrading, migration, disaster recovery, monitoring, and resource management. VMware Tanzu is a centralized management platform for consistently operating and securing your Kubernetes infrastructure and modern applications across multiple teams and private/public clouds. Kubespray is a tool that combines Kubernetes and Ansible to easily install Kubernetes clusters that can be deployed on AWS , GCE, Azure , OpenStack , vSphere , Packet (bare metal), Oracle Cloud Infrastructure (Experimental), or Baremetal. KubeInit provides Ansible playbooks and roles for the deployment and configuration of multiple Kubernetes distributions. Rancher is a complete software stack for teams adopting containers. It addresses the operational and security challenges of managing multiple Kubernetes clusters, while providing DevOps teams with integrated tools for running containerized workloads. K3s is a highly available, certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Helm is a Kubernetes Package Manager tool that makes it easier to install and manage Kubernetes applications. Knative is a Kubernetes-based platform to build, deploy, and manage modern serverless workloads. Knative takes care of the operational overhead details of networking, autoscaling (even to zero), and revision tracking. KubeFlow is a tool dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Etcd is a distributed key-value store that provides a reliable way to store data that needs to be accessed by a distributed system or cluster of machines. Etcd is used as the backend for service discovery and stores cluster state and configuration for Kubernetes. OpenEBS is a Kubernetes-based tool to create stateful applications using Container Attached Storage. Container Storage Interface (CSI) is an API that lets container orchestration platforms like Kubernetes seamlessly communicate with stored data via a plug-in. MicroK8s is a tool that delivers the full Kubernetes experience. In a Fully containerized deployment with compressed over-the-air updates for ultra-reliable operations. It is supported on Linux, Windows, and MacOS. Charmed Kubernetes is a well integrated, turn-key, conformant Kubernetes platform, optimized for your multi-cloud environments developed by Canonical. Grafana Kubernetes App is a toll that allows you to monitor your Kubernetes cluster's performance. It includes 4 dashboards, Cluster, Node, Pod/Container and Deployment. It allows for the automatic deployment of the required Prometheus exporters and a default scrape config to use with your in cluster Prometheus deployment. KubeEdge is an open source system for extending native containerized application orchestration capabilities to hosts at Edge.It is built upon kubernetes and provides fundamental infrastructure support for network, app. deployment and metadata synchronization between cloud and edge. Lens is the most powerful IDE for people who need to deal with Kubernetes clusters on a daily basis. It has support for MacOS, Windows and Linux operating systems. Flux CD is a tool that automatically ensures that the state of your Kubernetes cluster matches the configuration you've supplied in Git. It uses an operator in the cluster to trigger deployments inside Kubernetes, which means that you don't need a separate continuous delivery tool. Platform9 Managed Kubernetes (PMK) is a Kubernetes as a service that ensures fully automated Day-2 operations with 99.9% SLA on any environment, whether in data-centers, public clouds, or at the edge. Ansible Back to the Top Mac Development Ansible Playbook by Jeff Geerling Ansible Learning Resources Ansible is a simple IT automation engine that automates cloud provisioning, configuration management, application deployment, intra-service orchestration, and many other IT needs. It uses a very simple language (YAML, in the form of Ansible Playbooks) that allows you to describe your automation jobs in a way that approaches plain English. Anisble works on Linux (Red Hat EnterPrise Linux(RHEL) and Ubuntu) and Microsoft Windows. Red Hat Training for Ansible Top Ansible Courses Online from Udemy Introduction to Ansible: The Fundamentals on Coursera Learning Ansible Fundamentals on Pluralsight Introducing Red Hat Ansible Automation Platform 2.1 Ansible Documentation Ansible Galaxy User Guide Ansible Use Cases Ansible Integrations Ansible Collections Overview Working with playbooks Ansible for DevOps Examples by Jeff Geerling Getting Started: Writing Your First Playbook - Ansible Working With Modules in Ansible Ansible Best Practices: Roles & Modules Working with command line tools for Ansible Encrypting content with Ansible Vault Using vault in playbooks with Ansible Using Ansible With Azure Configuring Ansible on an Azure VM How to Use Ansible: An Ansible Cheat Sheet Guide from DigitalOcean Intro to Ansible on Linode | Spatial Labs Ansible DevOps Tools Integration Ansible Automation Hub is the official location to discover and download supported collections , included as part of an Ansible Automation Platform subscription. These content collections contain modules, plugins, roles, and playbooks in a downloadable package. Collections are a distribution format for Ansible content that can include playbooks, roles, modules, and plugins. As modules move from the core Ansible repository into collections, the module documentation will move to the collections pages . Ansible Lint is a command-line tool for linting playbooks, roles and collections aimed towards any Ansible users. Its main goal is to promote proven practices, patterns and behaviors while avoiding common pitfalls that can easily lead to bugs or make code harder to maintain. Ansible cmdb is a tool that takes the output of Ansible’s fact gathering and converts it into a static HTML overview page containing system configuration information. Ansible Inventory Grapher visually displays inventory inheritance hierarchies and at what level a variable is defined in inventory. Ansible Playbook Grapher is a command line tool to create a graph representing your Ansible playbook tasks and roles. Ansible Shell is an interactive shell for Ansible with built-in tab completion for all the modules. Ansible Silo is a self-contained Ansible environment by Docker . Ansigenome is a command line tool designed to help you manage your Ansible roles. ARA is a records Ansible playbook runs and makes the recorded data available and intuitive for users and systems by integrating with Ansible as a callback plugin. Capistrano is a remote server automation tool. It supports the scripting and execution of arbitrary tasks, and includes a set of sane-default deployment workflows. Fabric is a high level Python (2.7, 3.4+) library designed to execute shell commands remotely over SSH, yielding useful Python objects in return. It builds on top of Invoke (subprocess command execution and command-line features) and Paramiko (SSH protocol implementation), extending their APIs to complement one another and provide additional functionality. ansible-role-wireguard is an Ansible role for installing WireGuard VPN. Supports Ubuntu, Debian, Archlinx, Fedora and CentOS Stream. wireguard_cloud_gateway is an Ansible role for setting up Wireguard as a gateway VPN server for cloud networks. Red Hat OpenShift is focused on security at every level of the container stack and throughout the application lifecycle. It includes long-term, enterprise support from one of the leading Kubernetes contributors and open source software companies. OpenShift Hive is an operator which runs as a service on top of Kubernetes/OpenShift. The Hive service can be used to provision and perform initial configuration of OpenShift 4 clusters. Databases Back to the Top SQL/NoSQL Learning Resources SQL is a standard language for storing, manipulating and retrieving data in relational databases. NoSQL is a database that is interchangeably referred to as "nonrelational, or "non-SQL" to highlight that the database can handle huge volumes of rapidly changing, unstructured data in different ways than a relational (SQL-based) database with rows and tables. Transact-SQL(T-SQL) is a Microsoft extension of SQL with all of the tools and applications communicating to a SQL database by sending T-SQL commands. Introduction to Transact-SQL SQL Tutorial by W3Schools Learn SQL Skills Online from Coursera SQL Courses Online from Udemy SQL Online Training Courses from LinkedIn Learning Learn SQL For Free from Codecademy GitLab's SQL Style Guide OracleDB SQL Style Guide Basics Tableau CRM: BI Software and Tools Databases on AWS Best Practices and Recommendations for SQL Server Clustering in AWS EC2. Connecting from Google Kubernetes Engine to a Cloud SQL instance. Educational Microsoft Azure SQL resources MySQL Certifications SQL vs. NoSQL Databases: What's the Difference? What is NoSQL? SQL/NoSQL Tools and Databases Netdata is high-fidelity infrastructure monitoring and troubleshooting, real-time monitoring Agent collects thousands of metrics from systems, hardware, containers, and applications with zero configuration. It runs permanently on all your physical/virtual servers, containers, cloud deployments, and edge/IoT devices, and is perfectly safe to install on your systems mid-incident without any preparation. Azure Data Studio is an open source data management tool that enables working with SQL Server, Azure SQL DB and SQL DW from Windows, macOS and Linux. RStudio is an integrated development environment for R and Python, with a console, syntax-highlighting editor that supports direct code execution, and tools for plotting, history, debugging and workspace management. MySQL is a fully managed database service to deploy cloud-native applications using the world's most popular open source database. PostgreSQL is a powerful, open source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance. Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It is a fully managed, multiregion, multimaster, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. Apache Cassandra™ is an open source NoSQL distributed database trusted by thousands of companies for scalability and high availability without compromising performance. Cassandra provides linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Apache HBase™ is an open-source, NoSQL, distributed big data store. It enables random, strictly consistent, real-time access to petabytes of data. HBase is very effective for handling large, sparse datasets. HBase serves as a direct input and output to the Apache MapReduce framework for Hadoop, and works with Apache Phoenix to enable SQL-like queries over HBase tables. Hadoop Distributed File System (HDFS) is a distributed file system that handles large data sets running on commodity hardware. It is used to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes. HDFS is one of the major components of Apache Hadoop, the others being MapReduce and YARN . Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other frameworks on a dynamically shared pool of nodes. Apache Spark is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing. ElasticSearch is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Elasticsearch is developed in Java. Logstash is a tool for managing events and logs. When used generically, the term encompasses a larger system of log collection, processing, storage and searching activities. Kibana is an open source data visualization plugin for Elasticsearch. It provides visualization capabilities on top of the content indexed on an Elasticsearch cluster. Users can create bar, line and scatter plots, or pie charts and maps on top of large volumes of data. Trino is a Distributed SQL query engine for big data. It is able to tremendously speed up ETL processes , allow them all to use standard SQL statement, and work with numerous data sources and targets all in the same system. Extract, transform, and load (ETL) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store. Redis(REmote DIctionary Server) is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. It provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. FoundationDB is an open source distributed database designed to handle large volumes of structured data across clusters of commodity servers. It organizes data as an ordered key-value store and employs ACID transactions for all operations. It is especially well-suited for read/write workloads but also has excellent performance for write-intensive workloads. FoundationDB was acquired by Apple in 2015 . IBM DB2 is a collection of hybrid data management products offering a complete suite of AI-empowered capabilities designed to help you manage both structured and unstructured data on premises as well as in private and public cloud environments. Db2 is built on an intelligent common SQL engine designed for scalability and flexibility. MongoDB is a document database meaning it stores data in JSON-like documents. OracleDB is a powerful fully managed database helps developers manage business-critical data with the highest availability, reliability, and security. MariaDB is an enterprise open source database solution for modern, mission-critical applications. SQLite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine.SQLite is the most used database engine in the world. SQLite is built into all mobile phones and most computers and comes bundled inside countless other applications that people use every day. SQLite Database Browser is an open source SQL tool that allows users to create, design and edits SQLite database files. It lets users show a log of all the SQL commands that have been issued by them and by the application itself. InfluxDB is an open source time series platform. This includes APIs for storing and querying data, processing it in the background for ETL or monitoring and alerting purposes, user dashboards, Internet of Things sensor data, and visualizing and exploring the data and more. It also has support for processing data from Graphite . Atlas is an in-memory dimensional time series database . CouchbaseDB is an open source distributed multi-model NoSQL document-oriented database . It creates a key-value store with managed cache for sub-millisecond data operations, with purpose-built indexers for efficient queries and a powerful query engine for executing SQL queries. dbWatch is a complete database monitoring/management solution for SQL Server, Oracle, PostgreSQL, Sybase, MySQL and Azure. Designed for proactive management and automation of routine maintenance in large scale on-premise, hybrid/cloud database environments. Cosmos DB Profiler is a real-time visual debugger allowing a development team to gain valuable insight and perspective into their usage of Cosmos DB database. It identifies over a dozen suspicious behaviors from your application’s interaction with Cosmos DB. Adminer is an SQL management client tool for managing databases, tables, relations, indexes, users. Adminer has support for all the popular database management systems such as MySQL, MariaDB, PostgreSQL, SQLite, MS SQL, Oracle, Firebird, SimpleDB, Elasticsearch and MongoDB. DBeaver is an open source database tool for developers and database administrators. It offers supports for JDBC compliant databases such as MySQL, Oracle, IBM DB2, SQL Server, Firebird, SQLite, Sybase, Teradata, Firebird, Apache Hive, Phoenix, and Presto. DbVisualizer is a SQL management tool that allows users to manage a wide range of databases such as Oracle, Sybase, SQL Server, MySQL, H3, and SQLite. AppDynamics Database is a management product for Microsoft SQL Server. With AppDynamics you can monitor and trend key performance metrics such as resource consumption, database objects, schema statistics and more, allowing you to proactively tune and fix issues in a High-Volume Production Environment. Toad is a SQL Server DBMS toolset developed by Quest. It increases productivity by using extensive automation, intuitive workflows, and built-in expertise. This SQL management tool resolve issues, manage change and promote the highest levels of code quality for both relational and non-relational databases. Lepide SQL Server is an open source storage manager utility to analyse the performance of SQL Servers. It provides a complete overview of all configuration and permission changes being made to your SQL Server environment through an easy-to-use, graphical user interface. Sequel Pro is a fast MacOS database management tool for working with MySQL. This SQL management tool helpful for interacting with your database by easily to adding new databases, new tables, and new rows. Telco 5G Back to the Top VMware Cloud First Approach. Source: VMware . VMware Telco Cloud Automation Components. Source: VMware . Telco Learning Resources HPE(Hewlett Packard Enterprise) Telco Blueprints overview Network Functions Virtualization Infrastructure (NFVI) by Cisco Introduction to vCloud NFV Telco Edge from VMware VMware Telco Cloud Automation(TCA) Architecture Overview 5G Telco Cloud from VMware Maturing OpenStack Together To Solve Telco Needs from Red Hat Red Hat telco ecosystem program OpenStack for Telcos by Canonical Open source NFV platform for 5G from Ubuntu Understanding 5G Technology from Verizon Verizon and Unity partner to enable 5G & MEC gaming and enterprise applications Understanding 5G Technology from Intel Understanding 5G Technology from Qualcomm Telco Acceleration with Xilinx VIMs on OSM Public Wiki Amazon EC2 Overview and Networking Introduction for Telecom Companies Citrix Certified Associate – Networking(CCA-N) Citrix Certified Professional – Virtualization(CCP-V) CCNP Routing and Switching Certified Information Security Manager(CISM) Wireshark Certified Network Analyst (WCNA) Juniper Networks Certification Program Enterprise (JNCP) Cloud Native Computing Foundation Training and Certification Program Tools Open Stack is an open source cloud platform, deployed as infrastructure-as-a-service (IaaS) to orchestrate data center operations on bare metal, private cloud hardware, public cloud resources, or both (hybrid/multi-cloud architecture). OpenStack includes advance use of virtualization & SDN for network traffic optimization to handle the core cloud-computing services of compute, networking, storage, identity, and image services. StarlingX is a complete cloud infrastructure software stack for the edge used by the most demanding applications in industrial IOT, telecom, video delivery and other ultra-low latency use cases. Airship is a collection of open source tools for automating cloud provisioning and management. Airship provides a declarative framework for defining and managing the life cycle of open infrastructure tools and the underlying hardware. Network functions virtualization (NFV) is the replacement of network appliance hardware with virtual machines. The virtual machines use a hypervisor to run networking software and processes such as routing and load balancing. NFV allows for the separation of communication services from dedicated hardware, such as routers and firewalls. This separation means network operations can provide new services dynamically and without installing new hardware. Deploying network components with network functions virtualization only takes hours compared to months like with traditional networking solutions. Software Defined Networking (SDN) is an approach to networking that uses software-based controllers or application programming interfaces (APIs) to communicate with underlying hardware infrastructure and direct traffic on a network. This model differs from that of traditional networks, which use dedicated hardware devices (routers and switches) to control network traffic. Virtualized Infrastructure Manager (VIM) is a service delivery and reduce costs with high performance lifecycle management Manage the full lifecycle of the software and hardware comprising your NFV infrastructure (NFVI), and maintaining a live inventory and allocation plan of both physical and virtual resources. Management and Orchestration(MANO) is an ETSI-hosted initiative to develop an Open Source NFV Management and Orchestration (MANO) software stack aligned with ETSI NFV. Two of the key components of the ETSI NFV architectural framework are the NFV Orchestrator and VNF Manager, known as NFV MANO. Magma is an open source software platform that gives network operators an open, flexible and extendable mobile core network solution. Their mission is to connect the world to a faster network by enabling service providers to build cost-effective and extensible carrier-grade networks. Magma is 3GPP generation (2G, 3G, 4G or upcoming 5G networks) and access network agnostic (cellular or WiFi). It can flexibly support a radio access network with minimal development and deployment effort. OpenRAN is an intelligent Radio Access Network(RAN) integrated on general purpose platforms with open interface between software defined functions. Open RANecosystem enables enormous flexibility and interoperability with a complete openess to multi-vendor deployments. Open vSwitch(OVS) is an open source production quality, multilayer virtual switch licensed under the open source Apache 2.0 license. It is designed to enable massive network automation through programmatic extension, while still supporting standard management interfaces and protocols (NetFlow, sFlow, IPFIX, RSPAN, CLI, LACP, 802.1ag). Edge is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. This proximity to data at its source can deliver strong business benefits, including faster insights, improved response times and better bandwidth availability. Multi-access edge computing (MEC) is an Industry Specification Group (ISG) within ETSI to create a standardized, open environment which will allow the efficient and seamless integration of applications from vendors, service providers, and third-parties across multi-vendor Multi-access Edge Computing platforms. Virtualized network functions(VNFs) is a software application used in a Network Functions Virtualization (NFV) implementation that has well defined interfaces, and provides one or more component networking functions in a defined way. For example, a security VNF provides Network Address Translation (NAT) and firewall component functions. Cloud-Native Network Functions(CNF) is a network function designed and implemented to run inside containers. CNFs inherit all the cloud native architectural and operational principles including Kubernetes(K8s) lifecycle management, agility, resilience, and observability. Physical Network Function(PNF) is a physical network node which has not undergone virtualization. Both PNFs and VNFs (Virtualized Network Functions) can be used to form an overall Network Service. Network functions virtualization infrastructure(NFVI) is the foundation of the overall NFV architecture. It provides the physical compute, storage, and networking hardware that hosts the VNFs. Each NFVI block can be thought of as an NFVI node and many nodes can be deployed and controlled geographically. Open Source Security Back to the Top Open Source Security Foundation (OpenSSF) is a cross-industry collaboration that brings together leaders to improve the security of open source software by building a broader community, targeted initiatives, and best practices. The OpenSSF brings together open source security initiatives under one foundation to accelerate work through cross-industry support. Along with the Core Infrastructure Initiative and the Open Source Security Coalition, and will include new working groups that address vulnerability disclosures, security tooling and more. Security Standards, Frameworks and Benchmarks STIGs Benchmarks - Security Technical Implementation Guides CIS Benchmarks - CIS Center for Internet Security NIST - Current FIPS ISO Standards Catalogue Common Criteria for Information Technology Security Evaluation (CC) is an international standard (ISO / IEC 15408) for computer security. It allows an objective evaluation to validate that a particular product satisfies a defined set of security requirements. ISO 22301 is the international standard that provides a best-practice framework for implementing an optimised BCMS (business continuity management system). ISO27001 is the international standard that describes the requirements for an ISMS (information security management system). The framework is designed to help organizations manage their security practices in one place, consistently and cost-effectively. ISO 27701 specifies the requirements for a PIMS (privacy information management system) based on the requirements of ISO 27001. It is extended by a set of privacy-specific requirements, control objectives and controls. Companies that have implemented ISO 27001 will be able to use ISO 27701 to extend their security efforts to cover privacy management. EU GDPR (General Data Protection Regulation) is a privacy and data protection law that supersedes existing national data protection laws across the EU, bringing uniformity by introducing just one main data protection law for companies/organizations to comply with. CCPA (California Consumer Privacy Act) is a data privacy law that took effect on January 1, 2020 in the State of California. It applies to businesses that collect California residents’ personal information, and its privacy requirements are similar to those of the EU’s GDPR (General Data Protection Regulation). Payment Card Industry (PCI) Data Security Standards (DSS) is a global information security standard designed to prevent fraud through increased control of credit card data. SOC 2 is an auditing procedure that ensures your service providers securely manage your data to protect the interests of your comapny/organization and the privacy of their clients. NIST CSF is a voluntary framework primarily intended for critical infrastructure organizations to manage and mitigate cybersecurity risk based on existing best practice. Security Tools SELinux is a security enhancement to Linux which allows users and administrators more control over access control. Access can be constrained on such variables as which users and applications can access which resources. These resources may take the form of files. Standard Linux access controls, such as file modes (-rwxr-xr-x) are modifiable by the user and the applications which the user runs. Conversely, SELinux access controls are determined by a policy loaded on the system which may not be changed by careless users or misbehaving applications. AppArmor is an effective and easy-to-use Linux application security system. AppArmor proactively protects the operating system and applications from external or internal threats, even zero-day attacks, by enforcing good behavior and preventing both known and unknown application flaws from being exploited. AppArmor supplements the traditional Unix discretionary access control (DAC) model by providing mandatory access control (MAC). It has been included in the mainline Linux kernel since version 2.6.36 and its development has been supported by Canonical since 2009. Control Groups(Cgroups) is a Linux kernel feature that allows you to allocate resources such as CPU time, system memory, network bandwidth, or any combination of these resources for user-defined groups of tasks (processes) running on a system. EarlyOOM is a daemon for Linux that enables users to more quickly recover and regain control over their system in low-memory situations with heavy swap usage. Libgcrypt is a general purpose cryptographic library originally based on code from GnuPG. Kali Linux is an open source project that is maintained and funded by Offensive Security, a provider of world-class information security training and penetration testing services. Pi-hole is a DNS sinkhole that protects your devices from unwanted content, without installing any client-side software, intended for use on a private network. It is designed for use on embedded devices with network capability, such as the Raspberry Pi, but it can be used on other machines running Linux and cloud implementations. Aircrack-ng is a network software suite consisting of a detector, packet sniffer, WEP and WPA/WPA2-PSK cracker and analysis tool for 802.11 wireless LANs. It works with any wireless network interface controller whose driver supports raw monitoring mode and can sniff 802.11a, 802.11b and 802.11g traffic. Burp Suite is a leading range of cybersecurity tools. KernelCI is a community-based open source distributed test automation system focused on upstream kernel development. The primary goal of KernelCI is to use an open testing philosophy to ensure the quality, stability and long-term maintenance of the Linux kernel. Continuous Kernel Integration project helps find bugs in kernel patches before they are commited to an upstram kernel tree. We are team of kernel developers, kernel testers, and automation engineers. eBPF is a revolutionary technology that can run sandboxed programs in the Linux kernel without changing kernel source code or loading kernel modules. By making the Linux kernel programmable, infrastructure software can leverage existing layers, making them more intelligent and feature-rich without continuing to add additional layers of complexity to the system. Cilium uses eBPF to accelerate getting data in and out of L7 proxies such as Envoy, enabling efficient visibility into API protocols like HTTP, gRPC, and Kafka. Hubble is a Network, Service & Security Observability for Kubernetes using eBPF. Istio is an open platform to connect, manage, and secure microservices. Istio's control plane provides an abstraction layer over the underlying cluster management platform, such as Kubernetes and Mesos. Certgen is a convenience tool to generate and store certificates for Hubble Relay mTLS. Scapy is a python-based interactive packet manipulation program & library. syzkaller is an unsupervised, coverage-guided kernel fuzzer. SchedViz is a tool for gathering and visualizing kernel scheduling traces on Linux machines. oss-fuzz aims to make common open source software more secure and stable by combining modern fuzzing techniques with scalable, distributed execution. OSSEC is a free, open-source host-based intrusion detection system. It performs log analysis, integrity checking, Windows registry monitoring, rootkit detection, time-based alerting, and active response. Metasploit Project is a computer security project that provides information about security vulnerabilities and aids in penetration testing and IDS signature development. Wfuzz was created to facilitate the task in web applications assessments and it is based on a simple concept: it replaces any reference to the FUZZ keyword by the value of a given payload. Nmap is a security scanner used to discover hosts and services on a computer network, thus building a "map" of the network. Patchwork is a web-based patch tracking system designed to facilitate the contribution and management of contributions to an open-source project. pfSense is a free and open source firewall and router that also features unified threat management, load balancing, multi WAN, and more. Snowpatch is a continuous integration tool for projects using a patch-based, mailing-list-centric git workflow. This workflow is used by a number of well-known open source projects such as the Linux kernel. Snort is an open-source, free and lightweight network intrusion detection system (NIDS) software for Linux and Windows to detect emerging threats. Wireshark is a free and open-source packet analyzer. It is used for network troubleshooting, analysis, software and communications protocol development, and education. OpenSCAP is U.S. standard maintained by National Institute of Standards and Technology (NIST) . It provides multiple tools to assist administrators and auditors with assessment, measurement, and enforcement of security baselines. OpenSCAP maintains great flexibility and interoperability by reducing the costs of performing security audits. Whether you want to evaluate DISA STIGs, NIST‘s USGCB, or Red Hat’s Security Response Team’s content, all are supported by OpenSCAP. Tink is a multi-language, cross-platform, open source library that provides cryptographic APIs that are secure, easy to use correctly, and harder to misuse. OWASP is an online community, produces freely-available articles, methodologies, documentation, tools, and technologies in the field of web application security. Open Vulnerability and Assessment Language is a community effort to standardize how to assess and report upon the machine state of computer systems. OVAL includes a language to encode system details, and community repositories of content. Tools and services that use OVAL provide enterprises with accurate, consistent, and actionable information to improve their security. ClamAV is an open source antivirus engine for detecting trojans, viruses, malware & other malicious threats. Open Source Security Learning Resources Microsoft Open Source Software Security Cloudflare Open Source Security The Seven Properties of Highly Secure Devices How Layer 7 of the Internet Works The 7 Kinds of Security The Libgcrypt Reference Manual The Open Web Application Security Project(OWASP) Foundation Top 10 Best Practices for Using Open Source Code from The Linux Foundation AWS Certified Security - Specialty Certification Microsoft Certified: Azure Security Engineer Associate Google Cloud Certified Professional Cloud Security Engineer Cisco Security Certifications The Red Hat Certified Specialist in Security: Linux Linux Professional Institute LPIC-3 Enterprise Security Certification Cybersecurity Training and Courses from IBM Skills Cybersecurity Courses and Certifications by Offensive Security RSA Certification Program Check Point Certified Security Expert(CCSE) Certification Check Point Certified Security Administrator(CCSA) Certification Check Point Certified Security Master (CCSM) Certification Certified Cloud Security Professional(CCSP) Certification Certified Information Systems Security Professional (CISSP) Certification CCNP Routing and Switching Certified Information Security Manager(CISM) Wireshark Certified Network Analyst (WCNA) Juniper Networks Certification Program Enterprise (JNCP) Security Training Certifications and Courses from Udemy Security Training Certifications and Courses from Coursera Security Certifications Training from Pluarlsight Differential Privacy Back to the Top Above is a simple diagram of how Differential Privacy-Preserving Data Sharing and Data Mining protects a User's Data Differential Privacy Learning Resources Differential Privacy is a system that simultaneously enables researchers and analysts to extract useful insights from datasets containing personal information and offers stronger privacy protections. This is achieved by introducing "statistical noise". Statistical Noise is a process that small aletrations to masked datasets. The statistical noise hides identifiable characteristics of individuals, ensuring that the privacy of personal information is protected, but it's small enough to not materially impact the accuracy of the answers extracted by analysts and researchers. Laplacian Noise is a mechanism that adds Laplacian-distributed noise to a function. Differential Privacy Blog Series by the National Institute of Standards and Technology(NIST) Apple's Differential Privacy Overview Learning with Privacy at Scale with Apple Machine Learning Microsoft Research Differential Privacy Overview Responsible Machine Learning with Microsoft Azure Responsible AI Resources with Microsoft AI Preserve data privacy by using differential privacy and the SmartNoise package Open Differential Privacy(OpenDP) Initiative by Microsoft and Harvard Google's Differential Privacy Library Computing Private Statistics with Privacy on Beam from Google Codelabs Introducing TensorFlow Privacy: Learning with Differential Privacy for Training Data TensorFlow Federated: Machine Learning on Decentralized Data Federated Analytics: Collaborative Data Science without Data Collection Differentially-Private Stochastic Gradient Descent(DP-SGD) Learning Differential Privacy from Harvard University Privacy Tools Project Harvard University Privacy Tools Project Courses & Educational Materials The Weaknesses of Differential Privacy course on Coursera The Differential Privacy of Bayesian Inference Simultaneous private learning of multiple concepts The Complexity of Computing the Optimal Composition of Differential Privacy Order revealing encryption and the hardness of private learning SAP HANA data anonymization using SAP Software Solutions SAP HANA Security using their In-Memory Database DEFCON Differential Privacy Training Launch Secure and Private AI course on Udacity Differential Privacy - Security and Privacy for Big Data - Part 1 course on Coursera Differential Privacy - Security and Privacy for Big Data - Part 2 course on Coursera Certified Ethical Emerging Technologist Professional Certificate course on Coursera Differential Privacy Tools PySyft is a Python library for secure and private Deep Learning. PySyft decouples private data from model training, using Federated Learning , Differential Privacy , and Encrypted Computation (like Multi-Party Computation (MPC) and Homomorphic Encryption (HE) within the main Deep Learning frameworks like PyTorch and TensorFlow . TensorFlow Privacy is a Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy. The library comes with tutorials and analysis tools for computing the privacy guarantees provided. TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data. TFF has been developed to facilitate open research and experimentation with Federated Learning (FL) , an approach to machine learning where a shared global model is trained across many participating clients that keep their training data locally. Privacy on Beam is an end-to-end differential privacy solution built on Apache Beam . It is intended to be usable by all developers, regardless of their differential privacy expertise. PyDP is a Python wrapper for Google's Differential Privacy project. PennyLane is a cross-platform Python library for differentiable programming of quantum computers. By training a quantum computer the same way as a neural network. BoTorch is a library for Bayesian Optimization built on PyTorch. PyTorch Geometric (PyG) is a geometric deep learning extension library for PyTorch . Skorch is a scikit-learn compatible neural network library that wraps PyTorch. Diffprivlib is the IBM Differential Privacy Library for experimenting with, investigating and developing applications in, differential privacy. Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance and allows the client to online track the privacy budget expended at any given moment. Smart Noise is a toolkit that uses state-of-the-art differential privacy (DP) techniques to inject noise into data, to prevent disclosure of sensitive information and manage exposure risk. Machine Learning Back to the Top ML frameworks & applications TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Tensorman is a utility for easy management of Tensorflow containers by developed by System76 .Tensorman allows Tensorflow to operate in an isolated environment that is contained from the rest of the system. This virtual environment can operate independent of the base system, allowing you to use any version of Tensorflow on any version of a Linux distribution that supports the Docker runtime. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.It was developed with a focus on enabling fast experimentation. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, or PlaidML. PyTorch is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds. Primarily developed by Facebook's AI Research lab. Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models. Azure Databricks is a fast and collaborative Apache Spark-based big data analytics service designed for data science and data engineering. Azure Databricks, sets up your Apache Spark environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn. Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. Apache Airflow is an open-source workflow management platform created by the community to programmatically author, schedule and monitor workflows. Install. Principles. Scalable. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Open Neural Network Exchange(ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. Support for Python, R, Julia, Scala, Go, Javascript and more. AutoGluon is toolkit for Deep learning that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data. Anaconda is a very popular Data Science platform for machine learning and deep learning that enables users to develop models, train them, and deploy them. PlaidML is an advanced and portable tensor compiler for enabling deep learning on laptops, embedded devices, or other devices where the available computing hardware is not well supported or the available software stack contains unpalatable license restrictions. OpenCV is a highly optimized library with focus on real-time computer vision applications. The C++, Python, and Java interfaces support Linux, MacOS, Windows, iOS, and Android. Scikit-Learn is a Python module for machine learning built on top of SciPy, NumPy, and matplotlib, making it easier to apply robust and simple implementations of many popular machine learning algorithms. Weka is an open source machine learning software that can be accessed through a graphical user interface, standard terminal applications, or a Java API. It is widely used for teaching, research, and industrial applications, contains a plethora of built-in tools for standard machine learning tasks, and additionally gives transparent access to well-known toolboxes such as scikit-learn, R, and Deeplearning4j. Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors. Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently including tight integration with NumPy. nGraph is an open source C++ library, compiler and runtime for Deep Learning. The nGraph Compiler aims to accelerate developing AI workloads using any deep learning framework and deploying to a variety of hardware targets.It provides the freedom, performance, and ease-of-use to AI developers. NVIDIA cuDNN is a GPU-accelerated library of primitives for deep neural networks . cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including Caffe2 , Chainer , Keras , MATLAB , MxNet , PyTorch , and TensorFlow . Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Jupyter is used widely in industries that do data cleaning and transformation, numerical simulation, statistical modeling, data visualization, data science, and machine learning. Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. Apache Spark Connector for SQL Server and Azure SQL is a high-performance connector that enables you to use transactional data in big data analytics and persists results for ad-hoc queries or reporting. The connector allows you to use any SQL database, on-premises or in the cloud, as an input data source or output data sink for Spark jobs. Apache PredictionIO is an open source machine learning framework for developers, data scientists, and end users. It supports event collection, deployment of algorithms, evaluation, querying predictive results via REST APIs. It is based on scalable open source services like Hadoop, HBase (and other DBs), Elasticsearch, Spark and implements what is called a Lambda Architecture. Cluster Manager for Apache Kafka(CMAK) is a tool for managing Apache Kafka clusters. BigDL is a distributed deep learning library for Apache Spark. With BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Spark or Hadoop clusters. Koalas is project makes data scientists more productive when interacting with big data, by implementing the pandas DataFrame API on top of Apache Spark. Apache Spark™ MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components: MLflow Tracking : Record and query experiments: code, data, config, and results. MLflow Projects : Package data science code in a format to reproduce runs on any platform. MLflow Models : Deploy machine learning models in diverse serving environments. Model Registry : Store, annotate, discover, and manage models in a central repository. Eclipse Deeplearning4J (DL4J) is a set of projects intended to support all the needs of a JVM-based(Scala, Kotlin, Clojure, and Groovy) deep learning application. This means starting with the raw data, loading and preprocessing it from wherever and whatever format it is in to building and tuning a wide variety of simple and complex deep learning networks. Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks. Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference. cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. Online ML Learning Resources Machine Learning by Stanford University from Coursera Machine Learning Courses Online from Coursera Machine Learning Courses Online from Udemy Learn Machine Learning with Online Courses and Classes from edX IoT Protocols Back to the Top DBus is an open source software bus developed Red Hat for inter-process communication, and remote procedure call mechanism that allows communication between multiple processes running concurrently on the same machine. SOAP is a messaging protocol specification for exchanging structured information in the implementation of web services in computer networks. SOAP can extend HTTP for XML messaging. SOAP provides data transport for Web services. SOAP can exchange complete documents or call a remote procedure. SOAP can be used for broadcasting a message. gRPC is a modern, open source remote procedure call (RPC) framework developed by Google that can run anywhere. It enables client and server applications to communicate transparently, and makes it easier to build connected systems.It uses HTTP/2 for transport, Protocol Buffers as the interface description language, and provides features such as authentication, bidirectional streaming and flow control, blocking or nonblocking bindings, and cancellation and timeouts. LWM2M is a protocol from the Open Mobile Alliance for M2M or IoT device management. Lightweight M2M enabler defines the application layer communication protocol between a LWM2M Server and a LWM2M Client, which is located in a LWM2M Device. Advanced Message Queuing Protocol (AMQP) is an open standard for passing business messages between applications or organizations. It connects systems, feeds business processes with the information they need and reliably transmits onward the instructions that achieve their goals. The defining features of AMQP are message orientation, queuing, routing, reliability and security. Constrained Application Protocol (CoAP) is a specialized web transfer protocol for use with constrained nodes and constrained networks in the Internet of Things. The protocol is designed for machine-to-machine (M2M) applications such as smart energy and building automation." Extensible Messaging and Presence Protocol (XMPP) is a communication protocol for message-oriented middleware based on XML (Extensible Markup Language). It enables the near real-time exchange of structured yet extensible data between any two or more network entities. OASIS Message Queuing Telemetry Transport (MQTT) is an open OASIS and ISO standard (ISO/IEC 20922) lightweight, publish-subscribe network protocol that transports messages between devices. The protocol usually runs over TCP/IP; however, any network protocol that provides ordered, lossless, bi-directional connections can support MQTT. Very Simple Control Protocol (VSCP) is a free automation protocol suitable for all sorts of automation task where building- or home-automation is in the main focus. Its main advantage is that each VSCP-node can work completely autonomous, being part of distributed network of other nodes. Operating systems Back to the Top Raspberry Pi OS Hass.io(Home Assistant OS) Manjaro Linux ARM Arch Linux ARM Ubuntu MATE for Raspberry Pi Ubuntu Desktop for Raspberry Pi Ubuntu Core on a Raspberry Pi Ubuntu Server for ARM Debian Fedora ARM openSUSE SUSE Kali Linux for the Raspberry Pi RetroArch RetroPie LibreELEC OSMC RISC OS Windows 10 IoT Core HeliOS is an embedded operating system that is free for anyone to use. While called an operating system for simplicity, HeliOS is better described as a multitasking kernel for embedded systems. Simba is a small OS for an Embedded Programming Platform like Arduino. It aims to make embedded programming easy and portable. Trampoline is a static RTOS for small embedded systems. DuinOS is Framework (a wrapper) for use the FreeRTOSwith Arduino. VxWorks is an industry-leading real-time operating systems (RTOS) for building embedded devices and systems for more than 30 years. LynxOS is a native POSIX, hard real-time partitioning operating system developed by Lynx Software Technologies. Zephyr OS is a popular security-oriented RTOS with a small-footprint kernel designed for use on resource-constrained and embedded systems. Zephyr has a small-foorprint Kernel focusing on embedded devices compatible with x86, ARM, RISC-V, Xtensa and others . FreeRTOS is an open source, real-time operating system for microcontrollers that makes small, low-power edge devices easy to program, deploy, secure, connect, and manage. Arm Mbed TLS provides a comprehensive SSL/TLS solution and makes it easy for developers to include cryptographic and SSL/TLS capabilities in their software and embedded products. As an SSL library, it provides an intuitive API, readable source code and a minimal and highly configurable code footprint. Contiki-os is an operating system for networked, memory-constrained systems with a focus on low-power wireless Internet of Things devices. Middleware Back to the Top IoTSyS is an integration middleware for the Internet of Things. It provides a communication stack for embedded devices based on IPv6, Web services, and OBIX to establish interoperable interfaces for smart objects. OpenIoT is an open source middleware infrastructure will support flexible configuration and deployment of algorithms for collection, and filtering information streams stemming from the internet-connected objects, while at the same time generating and processing important business/applications events. OpenRemote is an open source middleware project, which integrates many different protocols and solutions available for smart building, and smart city automation, and offers visualization tools. Kaa is a Enterprise IoT Platform has been designed with heavy-duty, enterprise-grade IoT solutions in mind. It banishes a monolithic approach to architecture in favour of highly portable microservices, which allow for flexible rearrangement and customization even in the middle of the solution's lifecycle. Node flow editors Back to the Top Node-RED is a programming tool for wiring together hardware devices, APIs and online services in new and interesting ways. It provides a browser-based editor that makes it easy to wire together flows using the wide range of nodes in the palette that can be deployed to its runtime in a single-click. Toolkits Back to the Top KinomaJS is a visual code editor designed to help developers build starter projects for Kinoma Create and Kinoma Element. The project is built on Angular 2(RC7) and runs in a web browser. The live version is hosted using Google App Engine, but you can modify and build it yourself by following the instructions in this document. IoT Toolkit is a collection of libraries that enables communication with modern IoT based environments and devices. It is a high-performance collection of libraries optimized for minimum memory consumption in RAM, ROM, high speed, and versatility working on any device. Data Visualization Back to the Top Freeboard is an open source real-time dashboard builder for IOT and other web mashups. A free open-source alternative to Geckoboard. ThingSpeak is an IoT analytics platform service that allows you to aggregate, visualize, and analyze live data streams in the cloud. You can send data to ThingSpeak from your devices, create instant visualization of live data, and send alerts. Search Back to the Top Thingful is a Search Engine for the Internet of Things Find & use open IoT data from around the world. Hardware Back to the Top Arduino Ethernet Shield 2 allows an Arduino board to connect to the internet using the Ethernet library and to read and write an SD card using the SD library.This shield is fully compatible with the former version, but relies on the newer W5500 chip. Raspberry Pi is a series of small single-board computers developed in the United Kingdom by the Raspberry Pi Foundation to promote teaching of basic computer science in schools and in developing countries. Price range from $10-45 depending on model. BeagleBone is a low-power open-source single-board computer produced by Texas Instruments. It runs Android, Ubuntu and other Linux flavors. openPicus FlyportPro is a system on a module dedicated to IoT and M2M application, especially for professional use. Following some details on the solution: Why FlyportPRO SoM? A system-on-module is the best solution for those customers looking for flexibility and for development time and risk reduction. Pinoccio is a solution to add mesh networking capability and WiFi-Internet access to all yout IoT devices, and it is Arduino compatible. Each board can assume the role of Scout in a Troop and one of the Scouts is the Lead to connect internet: Field Scouts talk to each other using a mesh network (called a Troop), using an extremely low-power radio. In-memory data grids Back to the Top Ehcache is an open source, standards-based cache that boosts performance, offloads your database, and simplifies scalability. It's the most widely-used Java-based cache because it's robust, proven, full-featured, and integrates with other popular libraries and frameworks. Hazelcast is an open source in-memory data grid based on Java. Home automation Back to the Top Home Assistant is open source home automation that puts local control and privacy first. Powered by a worldwide community of tinkerers and DIY enthusiasts. Perfect to run on a Raspberry Pi or a local server. openHAB is a cross-platform software with the aim to integrate all kinds of Smart Home technologies, devices, etc. Eclipse SmartHome is a framework, not a ready-to-use solution. It offers a large set of features to choose from and leaves enough possibilities to design a Smart Home solution specific to your expectations. Its modular design brings millions of combinations and proves to be easily extensible by custom parts. The Thing System is a set of software components and network protocols that aims to fix the Internet of Things. Our steward software is written in node.js making it both portable and easily extensible. It can run on your laptop, or fit onto a small single board computer like the Raspberry Pi. Robotics Back to the Top Tools for Robotics Open Source Robotics Foundation works with industry, academia, and government to create and support open software and hardware for use in robotics, from research and education to product development. ROS is robotics middleware. Although ROS is not an operating system, it provides services designed for a heterogeneous computer cluster such as hardware abstraction, low-level device control, implementation of commonly used functionality, message-passing between processes, and package management. ROS2 is a set of software libraries and tools that help you build robot applications. From drivers to state-of-the-art algorithms, and with powerful developer tools, ROS has what you need for your next robotics project. And it’s all open source. Robot Framework is a generic open source automation framework. It can be used for test automation and robotic process automation. It has easy syntax, utilizing human-readable keywords. Its capabilities can be extended by libraries implemented with Python or Java. The Robotics Library (RL) is a self-contained C++ library for robot kinematics, motion planning and control. It covers mathematics, kinematics and dynamics, hardware abstraction, motion planning, collision detection, and visualization.RL runs on many different systems, including Linux, macOS, and Windows. It uses CMake as a build system and can be compiled with Clang, GCC, and Visual Studio. MoveIt is the most widely used software for manipulation and has been used on over 100 robots. It provides an easy-to-use robotics platform for developing advanced applications, evaluating new designs and building integrated products for industrial, commercial, R&D, and other domains. AutoGluon is toolkit for Deep learning that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data. Gazebo accurately and efficiently simulates indoor and outdoor robots. You get a robust physics engine, high-quality graphics, and programmatic and graphical interfaces. Robotics System Toolbox provides tools and algorithms for designing, simulating, and testing manipulators, mobile robots, and humanoid robots. For manipulators and humanoid robots, the toolbox includes algorithms for collision checking, trajectory generation, forward and inverse kinematics, and dynamics using a rigid body tree representation. For mobile robots, it includes algorithms for mapping, localization, path planning, path following, and motion control. The toolbox provides reference examples of common industrial robot applications. It also includes a library of commercially available industrial robot models that you can import, visualize, and simulate. Intel Robot DevKit is the tool to generate Robotics Software Development Kit (RDK) designed for autonomous devices, including the ROS2 core and capacibilities packages like perception, planning, control driver etc. It provides flexible build/runtime configurations to meet different autonomo

Self-Hosting Guide. Learn all about locally hosting (on premises & private web servers) and managing software applications by yourself or your organization. Including Cloud, LLMs, WireGuard, Automation, Home Assistant, and Networking.

self-hosted,selfhosted,home-assistant,wireguard,decentralized,self-hosting,privacy,reverse-proxy,authentication,oauth

DevToys-app/DevToysMac

DevToysMac This is the mac app version of DevToys for Windows ! How to install Manually Download the latest release . Extract DevToys.app from DevToys.app.zip Homebrew Install Homebrew . Then install DevToysMac with brew install --cask devtoys . Screenshots Home Json <> Yaml Converter Number Base Converter HTML Encoder / Decoder URL Encoder / Decoder Base64 Encoder / Decoder JSON Formatter and more...

DevToys For mac

[]

triggerdotdev/jsonhero-web

Brought to you by Trigger.dev JSON Hero was created and is maintained by the team behind Trigger.dev . With Trigger.dev you can trigger workflows from APIs, on a schedule, or on demand. We make API calls easy with authentication handled for you, and you can add durable delays that survive server restarts. JSON Hero JSON Hero makes reading and understand JSON files easy by giving you a clean and beautiful UI packed with extra features. View JSON any way you'd like: Column View, Tree View, Editor View, and more. Automatically infers the contents of strings and provides useful previews Creates an inferred JSON Schema that could be used to validate your JSON Quickly scan related values to check for edge cases Search your JSON files (both keys and values) Keyboard accessible Easily sharable URLs with path support Features Send to JSON Hero Send your JSON to JSON Hero in a variety of ways Head to jsonhero.io and Drag and Drop a JSON file, or paste JSON or a JSON url in the provided form Include a Base64 encoded string of a JSON payload: jsonhero.io/new?j=eyAiZm9vIjogImJhciIgfQ== Include a JSON URL to the new endpoint: jsonhero.io/new?url=https://jsonplaceholder.typicode.com/todos/1 Install the VS Code extension and open JSON from VS Code Raycast user? Check out our extension here Use the unofficial API: Make a POST request to jsonhero.io/api/create.json with the following JSON body: json { "title": "test 123", "content": { "foo": "bar" }, "readOnly": false, // this is optional, will make it so the document title cannot be edited or document cannot be deleted "ttl": 3600 // this will expire the document after 3600 seconds, also optional } The JSON response will be the following: json { "id": "YKKduNySH7Ub", "title": "test 123", "location": "https://jsonhero.io/j/YKKduNySH7Ub" } Column view Inspired by macOS Finder, Column View is a new way to browse a JSON document. It has all the features you'd expect: Keyboard navigation, Path bar, history. It also has a nifty feature that allows you to "hold" a descendent selected and travel up through the hierarchy, and then move between siblings and view the different values found at that path. It's hard to describe, but here is an animation to help demonstrate: As you can see, holding the Option (or Alt key on Windows) while moving to a parent keeps the part of the document selected and shows it in context of it's surrounding JSON. Then you can traverse between items in an array and compare the values of the selection across deep hierarchy cahnges. Editor view View your entire JSON document in an editor, but keep the nice previews and related values you get from the sidebar as you move around the document: Tree view Use a traditional tree view to traverse your JSON document, with collapsible sections and keyboard shortcuts. All while keeping the nice previews: Search Quickly open a search panel and fuzzy search your entire JSON file in milliseconds. Searches through key names, key paths, values, and even pretty formatted values (e.g. Searching for "Dec" will find datetime strings in the month of December.) Content Previews JSON Hero automatically infers the content of strings and provides useful previews and properties of the value you've selected. It's "Show Don't Tell" for JSON: Dates and Times Image URLs Website URLs Tweet URLS JSON URLs Colors Related Values Easily see all the related values across your entire JSON document for a specific field, including any undefined or null values. Bugs and Feature Requests Have a bug or a feature request? Feel free to open a new issue . You can also join our Discord channel to hang out and discuss anything you'd like. Developing To run locally, first clone the repo and install the dependencies: bash git clone https://github.com/triggerdotdev/jsonhero-web.git cd jsonhero-web npm install Then, create a file at the root of the repo called .env and set the SESSION_SECRET value: SESSION_SECRET=abc123 Then, run npm run build or npm run dev to build. Now, run npm start and open your browser to http://localhost:8787

JSON Hero is an open-source, beautiful JSON explorer for the web that lets you browse, search and navigate your JSON files at speed. 🚀. Built with 💜 by the Trigger.dev team.

json,developer-tools,tools,viewer,devtools,json-viewer,react,typescript,hacktoberfest

privatenumber/tsx

TypeScript Execute (tsx): The easiest way to run TypeScript in Node.js Documentation | Getting started → Already a sponsor? Join the discussion in the Development repo ! [!TIP] Build your TypeScript projects? Try pkgroll —the zero-config package bundler used by tsx ! pkgroll is a thin Rollup wrapper that makes it so simple for your package to support CommonJS, ESM, & TypeScript. If you love tsx, you'll love pkgroll too! Sponsors

⚡️ TypeScript Execute | The easiest way to run TypeScript in Node.js

esbuild,esm,node,typescript,loader,runtime,cli,watch

JunkFood02/Seal

# Seal ### Video/Audio Downloader for Android English   | 简体中文 | 繁體中文 | العربية | Portuguese | Українська | ภาษาไทย | فارسی | Italiano | Azərbaycanca | Русский | Српски | 日本語 | Indonesia [](https://f-droid.org/en/packages/com.junkfood.seal) [](https://github.com/JunkFood02/Seal/releases/latest/) [](https://github.com/JunkFood02/Seal/releases/) [](https://github.com/JunkFood02/Seal/blob/main/CHANGELOG.md) [](https://github.com/JunkFood02/Seal/releases/) [](https://github.com/JunkFood02/Seal/stargazers) [](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md) [](https://t.me/seal_app) [ ](https://matrix.to/#/#seal-space:matrix.org) 📱 Screenshots 📖 Features Download videos and audio files from video platforms supported by yt-dlp (formerly youtube-dl). Embed metadata and video thumbnail into extracted audio files supported by mutagen . Download all videos in the playlist with one click. Use embedded aria2c as external downloader for all your downloads. Embed subtitles into the downloaded videos. Execute custom yt-dlp commands with templates. Manage in-app downloads and custom command templates. Easy to use and user-friendly. Material Design 3 style UI, with dynamic color theme. MAD: UI and logic written with pure Kotlin. Single activity, no fragments, only composable destinations. ⬇️ Download For most devices, it is recommended to install the arm64-v8a version of the apks Download the latest stable version from GitHub releases Install the pre-release versions to help us test out new features & changes Stable releases are also available on F-Droid 💬 Contact Join our Telegram Channel or Matrix Space for discussion, announcements, and releases! 💖 Sponsors Seal will be always free and open source for everyone. If you like it, please consider sponsoring me ! 🤝 Contributing Contributions are welcome! You can help translate Seal on Hosted Weblate . [!Note] For submitting bug reports, feature requests, questions, or any other ideas to improve, please read CONTRIBUTING.md for instructions and guidelines first. ⭐️ Star History 🧱 Credits Seal is a simple GUI of yt-dlp , based on youtubedl-android Some of the UI designs and codes are borrowed from Read You and Music You dvd Material color utilities Monet 📃 License [!Warning] Except for the source code licensed under the GPLv3 license, all other parties are prohibited from using Seal's name as a downloader app, and the same is true for Seal's derivatives. Derivatives include but are not limited to forks and unofficial builds. 👆 Scroll to top

🦭 Video/Audio Downloader for Android, based on yt-dlp, designed with Material You

android,jetpack-compose,youtube-dl,material-design,f-droid,kotlin,youtube-downloader,yt-dlp

nebuly-ai/nebuly

Nebuly - The User Analytics Platform for LLMs This is the official Python SDK for Nebuly. Nebuly is the user analytics platform for LLMs enabling you to automatically capture how your users interact with your models. The platform helps you understand what your LLM users like, what they don’t and why, what are the most asked questions and how you can improve your LLMs products to delight your customers. Installation The easiest way to install Nebuly’s SDK is via pip : pip install nebuly Once installed, authenticate to Nebuly platform and start building. Get started Tracking interactions to Nebuly is incredibly easy and requires just two lines of code. Use your LLMs as always, all you need to do is: Include Nebuly's API key. Add the user_id parameter within your model call. With these simple additions, you can start tracking interactions to Nebuly in less than 2 minutes. ```python import nebuly import openai nebuly.init(api_key=" ") openai.api_key = " " response = openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=[ { "role": "system", "content": "You are an helpful assistant" }, { "role": "user", "content": "Hello, I need help with my computer" } ], user_id="test_user", ) ``` We support also Azure OpenAI, HuggingFace, Cohere, Anthropic, VertexAI and Bedrock. To learn more please visit the documentation .

The user analytics platform for LLMs

ai,analytics,artificial-intelligence,deeplearning,large-language-models,llm

gojue/ecapture

中文介绍 | English | 日本語 eCapture(旁观者): capture SSL/TLS text content without a CA certificate using eBPF. Note Supports Linux/Android kernel versions x86_64 4.18 and above, aarch64 5.5 and above. Does not support Windows and macOS system. How eCapture works eCapture User Manual Getting started eCapture Architecture What's eBPF How to compile Contributing How eCapture works SSL/TLS plaintext capture, support openssl\libressl\boringssl\gnutls\nspr(nss) libraries. GoTLS plaintext support go tls library, which refers to encrypted communication in https/tls programs written in the golang language. bash audit, capture bash command for Host Security Audit. mysql query SQL audit, support mysqld 5.6\5.7\8.0, and mariadDB. eCapture User Manual Youtube video: How to use eCapture v0.1.0 Getting started use ELF binary file Download ELF zip file release , unzip and use by command ./ecapture --help . Linux kernel version >= 4.18 is required. Enable BTF BPF Type Format (BTF) (Optional, 2022-04-17) use docker image ```shell pull docker image docker pull gojue/ecapture:latest run docker run --rm --privileged=true --net=host -v ${HOST_PATH}:${CONTAINER_PATH} gojue/ecapture ARGS ``` Command line options Note Need ROOT permission. eCapture search /etc/ld.so.conf file default, to search load directories of SO file, and search openssl shard libraries location. or you can use --libssl flag to set shard library path. If target program is compile statically, you can set program path as --libssl flag value directly。 Modules The eCapture tool comprises 8 modules that respectively support plaintext capture for TLS/SSL encryption libraries like OpenSSL, GnuTLS, NSPR, BoringSSL, and GoTLS. Additionally, it facilitates software audits for Bash, MySQL, and PostgreSQL applications. * bash capture bash command * gnutls capture gnutls text content without CA cert for gnutls libraries. * gotls Capturing plaintext communication from Golang programs encrypted with TLS/HTTPS. * mysqld capture sql queries from mysqld 5.6/5.7/8.0 . * nss capture nss/nspr encrypted text content without CA cert for nss/nspr libraries. * postgres capture sql queries from postgres 10+. * tls use to capture tls/ssl text content without CA cert. (Support openssl 1.0.x/1.1.x/3.0.x or newer). You can use ecapture -h to view the list of subcommands. OpenSSL Module The OpenSSL module supports three capture modes: pcap / pcapng mode stores captured plaintext data in pcap-NG format. keylog / key mode saves the TLS handshake keys to a file. text mode directly captures plaintext data, either outputting to a specified file or printing to the command line. Pcap Mode You can specify -m pcap or -m pcapng and use it in conjunction with --pcapfile and -i parameters. The default value for --pcapfile is ecapture_openssl.pcapng . shell ./ecapture tls -m pcap -i eth0 --pcapfile=ecapture.pcapng tcp port 443 This command saves captured plaintext data packets as a pcapng file, which can be viewed using Wireshark . Keylog Mode You can specify -m keylog or -m key and use it in conjunction with the --keylogfile parameter, which defaults to ecapture_masterkey.log . The captured OpenSSL TLS Master Secret information is saved to --keylogfile . You can also enable tcpdump packet capture and then use Wireshark to open the file and set the Master Secret path to view plaintext data packets. shell ./ecapture tls -m keylog -keylogfile=openssl_keylog.log You can also directly use the tshark software for real-time decryption and display: shell tshark -o tls.keylog_file:ecapture_masterkey.log -Y http -T fields -e http.file_data -f "port 443" -i eth0 Text Mode ./ecapture tls -m text will output all plaintext data packets. (Starting from v0.7.0, it no longer captures SSLKEYLOG information.) GoTLS Module Similar to the OpenSSL module. check your server BTF config： shell cfc4n@vm-server:~$# uname -r 4.18.0-305.3.1.el8.x86_64 cfc4n@vm-server:~$# cat /boot/config-`uname -r` | grep CONFIG_DEBUG_INFO_BTF CONFIG_DEBUG_INFO_BTF=y gotls command capture tls text context. Step 1: shell ./ecapture gotls --elfpath=/home/cfc4n/go_https_client --hex Step 2: shell /home/cfc4n/go_https_client more help shell ./ecapture gotls -h bash Module capture bash command : ecapture bash shell ps -ef | grep foo eCapture Architecture What's eBPF eBPF How to compile Linux Kernel: >= 4.18. Tools golang 1.21 or newer clang 9.0 or newer cmake 3.18.4 or newer clang backend: llvm 9.0 or newer kernel config:CONFIG_DEBUG_INFO_BTF=y (Optional, 2022-04-17) command ubuntu If you are using Ubuntu 20.04 or later versions, you can use a single command to complete the initialization of the compilation environment. shell /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/gojue/ecapture/master/builder/init_env.sh)" other Linux In addition to the software listed in the 'Toolchain Version' section above, the following software is also required for the compilation environment. Please install it yourself. * linux-tools-common * linux-tools-generic * pkgconf * libelf-dev Clone the repository code and compile it Caution: The following make command will install libpcap into the system directory if libpcap.a does not exist under /usr/local/lib . If you have installed libpcap in system without libpcap.a , it maybe break your libpcap's headers. shell git clone --recurse-submodules git@github.com:gojue/ecapture.git cd ecapture make bin/ecapture compile without BTF eCapture support BTF disabled with command make nocore to compile at 2022/04/17. It can work normally even on Linux systems that do not support BTF. shell make nocore bin/ecapture --help cross-compilation Kernel header files To cross-compile the eCapture tool, you need to install the kernel header files for the target architecture. you need to install the linux-source package. shell kernel_ver=`uname -r | cut -d'-' -f 1` sudo apt-get install -y linux-source-$kernel_ver cd /usr/src sudo tar -xf linux-source-${kernel_ver}.tar.bz2 cd /usr/src/linux-source-${kernel_ver} test -f .config || yes "" | sudo make oldconfig ToolChains To cross-compile binary files for the aarch64 architecture on an amd64 architecture system, you need to install the gcc-aarch64-linux-gnu toolchain. Similarly, to cross-compile binary files for the amd64 architecture on an aarch64 system, you need to install the gcc-x86-64-linux-gnu toolchain. * amd64 arch: gcc-aarch64-linux-gnu * arm64 arch: gcc-x86-64-linux-gnu Build Commands To build an arm64 artifact on an ubuntu amd64 system, you can set the CROSS_ARCH environment variable to achieve cross-compilation. shell CROSS_ARCH=arm64 make Stargazers over time Contributing See CONTRIBUTING for details on submitting patches and the contribution workflow.

Capturing SSL/TLS plaintext without a CA certificate using eBPF. Supported on Linux/Android kernels for amd64/arm64.

golang,ebpf,tcpdump,ssldump,https,tls,security-audit,network-capture,android-https-capture,ssl

ekzhang/bore

bore A modern, simple TCP tunnel in Rust that exposes local ports to a remote server, bypassing standard NAT connection firewalls. That's all it does: no more, and no less. ```shell Installation (requires Rust, see alternatives below) cargo install bore-cli On your local machine bore local 8000 --to bore.pub ``` This will expose your local port at localhost:8000 to the public internet at bore.pub:<PORT> , where the port number is assigned randomly. Similar to localtunnel and ngrok , except bore is intended to be a highly efficient, unopinionated tool for forwarding TCP traffic that is simple to install and easy to self-host, with no frills attached. ( bore totals about 400 lines of safe, async Rust code and is trivial to set up — just run a single binary for the client and server.) Installation If you're on macOS, bore is packaged as a Homebrew core formula. shell brew install bore-cli Otherwise, the easiest way to install bore is from prebuilt binaries. These are available on the releases page for macOS, Windows, and Linux. Just unzip the appropriate file for your platform and move the bore executable into a folder on your PATH. You also can build bore from source using Cargo , the Rust package manager. This command installs the bore binary at a user-accessible path. shell cargo install bore-cli We also publish versioned Docker images for each release. The image is built for an AMD 64-bit architecture. They're tagged with the specific version and allow you to run the statically-linked bore binary from a minimal "scratch" container. shell docker run -it --init --rm --network host ekzhang/bore <ARGS> Detailed Usage This section describes detailed usage for the bore CLI command. Local Forwarding You can forward a port on your local machine by using the bore local command. This takes a positional argument, the local port to forward, as well as a mandatory --to option, which specifies the address of the remote server. shell bore local 5000 --to bore.pub You can optionally pass in a --port option to pick a specific port on the remote to expose, although the command will fail if this port is not available. Also, passing --local-host allows you to expose a different host on your local area network besides the loopback address localhost . The full options are shown below. ```shell Starts a local proxy to the remote server Usage: bore local [OPTIONS] --to Arguments: The local port to expose Options: -l, --local-host The local host to expose [default: localhost] -t, --to Address of the remote server to expose local ports to [env: BORE_SERVER=] -p, --port Optional port on the remote server to select [default: 0] -s, --secret Optional secret for authentication [env: BORE_SECRET] -h, --help Print help information ``` Self-Hosting As mentioned in the startup instructions, there is a public instance of the bore server running at bore.pub . However, if you want to self-host bore on your own network, you can do so with the following command: shell bore server That's all it takes! After the server starts running at a given address, you can then update the bore local command with option --to <ADDRESS> to forward a local port to this remote server. The full options for the bore server command are shown below. ```shell Runs the remote proxy server Usage: bore server [OPTIONS] Options: --min-port Minimum accepted TCP port number [default: 1024] --max-port Maximum accepted TCP port number [default: 65535] -s, --secret Optional secret for authentication [env: BORE_SECRET] -h, --help Print help information ``` Protocol There is an implicit control port at 7835 , used for creating new connections on demand. At initialization, the client sends a "Hello" message to the server on the TCP control port, asking to proxy a selected remote port. The server then responds with an acknowledgement and begins listening for external TCP connections. Whenever the server obtains a connection on the remote port, it generates a secure UUID for that connection and sends it back to the client. The client then opens a separate TCP stream to the server and sends an "Accept" message containing the UUID on that stream. The server then proxies the two connections between each other. For correctness reasons and to avoid memory leaks, incoming connections are only stored by the server for up to 10 seconds before being discarded if the client does not accept them. Authentication On a custom deployment of bore server , you can optionally require a secret to prevent the server from being used by others. The protocol requires clients to verify possession of the secret on each TCP connection by answering random challenges in the form of HMAC codes. (This secret is only used for the initial handshake, and no further traffic is encrypted by default.) ```shell on the server bore server --secret my_secret_string on the client bore local --to --secret my_secret_string ``` If a secret is not present in the arguments, bore will also attempt to read from the BORE_SECRET environment variable. Acknowledgements Created by Eric Zhang ( @ekzhang1 ). Licensed under the MIT license . The author would like to thank the contributors and maintainers of the Tokio project for making it possible to write ergonomic and efficient network services in Rust.

🕳 bore is a simple CLI tool for making tunnels to localhost

cli,rust,tunnel,networking,tcp,localhost,proxy,self-hosted

lstprjct/IDM-Activation-Script

IDM Activation Script An open-source tool to activate and reset the trial of Internet Download Manager Disclaimer I want to clarify that I am not the original author of this script. When I initially published this script on GitHub, the primary author had not yet created an official GitHub repository. As a result, the only available option for users was to visit the official forum to download and utilize the script, later they created the Github repository. My main aim in creating this repository was to streamline the process for users. Furthermore, I ensured to credit the original creators of the script as a sign of respect for their work. Features IDM freeze trial and activation with registry key lock method Activation and trial persist even after installing IDM updates IDM trial reset Fully open source Based on the transparent batch script IAS Latest Release Last Release - v1.2 (12-Feb-2024) GitHub Download / How to use it? First fresh install Internet Download Manager . Make sure previous cracks/patches are removed/uninstalled if there are any. After that follow the below steps to activate it. Note 📌 The activation option is currently not working in the script, use the Freeze trial option to lock the 30-day trial period for the lifetime. Method 1 - PowerShell (Recommended) Right-click on the Windows start menu and select PowerShell or Terminal (Not CMD). Copy-paste the below code and press enter * iex(irm is.gd/idm_reset) You will see the activation options, follow the on-screen instructions. That’s all. Method 2 - Traditional Download the file from GitHub Right-click on the downloaded zip file and extract In the extracted folder, run the file named IAS.cmd You will see the activation options, and follow onscreen instructions. That’s all. Info Freeze Trial IDM provides a 30-day trial period, you can use this option in the script to lock this trial period for the lifetime so that you won’t have to reset the trial again and your trial won’t expire. This method requires the Internet at the time of applying this option. IDM updates can be installed directly without having to freeze it again. Activation ( *Currently not working ) This script applies the registry lock method to activate the Internet download manager (IDM). This method requires the Internet at the time of activation. IDM updates can be installed directly without having to activate it again. After the activation, if in some cases, IDM starts to show an activation nag screen, then just run the activation option again without using the reset option. Reset IDM Activation / Trial Internet download manager provides a 30-day trial period, you can use this script to reset this Activation / Trial period whenever you want. This option also can be used to restore status if in case IDM reports a fake serial key and other similar errors. OS requirement The project is supported for Windows 7/8/8.1/10/11 and their Server equivalent. The PowerShell method to run IAS is supported on Windows 8 and higher. Advanced Info To activate in unattended mode, run the script with the /act parameter. To freeze the trial in unattended mode, run the script with the /frz parameter. To reset in unattended mode, run the script with the /res parameter. How does it work? IDM stores the data related to trial and activation across various registry keys. Some of these keys are locked to protect them from tampering and data is stored in a pattern to track the fake serial issue and the remaining trial days. To activate it, the script here simply generates those registry keys by triggering a few downloads in IDM, identifies those registry keys, and locks them so IDM can’t edit and view them. That way IDM cannot show the warning that it’s activated with a fake serial key. Troubleshoot Browser Integration Fix: Chrome - Firefox Reach out to us on Telegram with an error screenshot. Changelog v1.2 Added back activation option with a randomized name, email, and key in registration details along with a warning that it’s not working for some users, the recommended option is to use Freeze trial. v1.1 IDM update 6.42b3 has started showing fake serial popups with IAS activation, due to this we have removed the activation option and replaced it with the Freeze trial option to lock the 30-day trial period for the lifetime. Now the script will disable quick-edit in CMD windows using Powershell instead of editing the registry, thanks to @abbodi1406 for the code and @awuctl for the idea. Code to relaunch script with conhost.exe to avoid terminal app is now merged in quick-edit disable code, thanks to @abbodi1406. Updated full code from WindowsAddict v1.0 Added the code to relaunch the script with conhost.exe if the script is running from the terminal app. Fixed an issue in getting the current user account SID. v0.9 Fixed an issue where the script can not activate and reset IDM in non-admin user accounts. Fixed an issue where the script incorrectly shows that IDM is activated. Fixed an issue where a fake serial pop-up may appear. The script will also show the info to run the activation option again without using the reset option. IDM registry scanning and locking code is now written in Powershell. The script update checker code is added to the script. The script will now disable quick edit mode temporarily because users often click inside the script window and it pauses the script. The script will back up the CLSISD registry keys before performing operations on them. Many error checks are added to better identify the issues. v0.8 Move the project to Github Minor bug fixes Add info to inform users that empty registry keys are being deleted when the script deletes a lot of them Screenshots Credits | | | |-------------------|-----------------------------------------------------| | Dukun Cabul | Original researcher of this IDM trial reset and activation logic, made an Autoit tool for these methods, IDM-AIO_2020_Final | | AveYo aka BAU | reg_own lean and mean snippet | | abbodi1406 | Help in coding | | WindowsAddict | Original IAS Author | And thanks to the IAS users for their interest, feedback, and assistance. Made with Love ❤️

IDM Activation & Trail Reset Script

download,ias,idm,internet,internet-download-manager,manager,windows,idm-activation-script,idm-activator,idm-reset

web-infra-dev/rspack

Rspack English | 简体中文 Rspack is a high performance JavaScript bundler written in Rust. It offers strong compatibility with the webpack ecosystem, allowing for seamless replacement of webpack, and provides lightning fast build speeds. ✨ Features 🚀 Fast Startup : Based on Rust, the build speed is extremely fast, bringing you the ultimate development experience. ⚡ Lightning HMR : With a built-in incremental compilation mechanism, HMR is extremely fast and fully capable of developing large-scale projects. 📦 Webpack Compatible : Compatible with plugins and loaders in the webpack ecosystem, seamlessly integrating excellent libraries built by the community. 🎨 Batteries Included : Out-of-the-box support for TypeScript, JSX, CSS, CSS Modules, Sass, and more. 🛠️ Production Optimization : Various optimization strategies are built in by default, such as tree shaking, minification, etc. 🎯 Framework Agnostic : Not bound to any frontend framework, ensuring enough flexibility. Read Introduction for details. Getting Started Quick Start Contribution Please read the contributing guide and let's build Rspack together. Code of Conduct This repo has adopted the ByteDance Open Source Code of Conduct. Please check Code of Conduct for more details. Community Come chat with us on Discord ! Rspack team and Rspack users are active there, and we're always looking for contributions. Links | Name | Description | | ---------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | | Rspack website | Official documentation for Rspack | | awesome-rspack | A curated list of awesome things related to Rspack | | rspack-examples | Rspack configuration examples | | rspack-sources | Rust port of webpack-sources | | rspack-migration-showcase | Migration showcases for Rspack | | rspack-compat | Rspack compatible loaders and plugins examples | | rsfamily-design-resources | Design resources for Rspack, Rsbuild, Rspress and Rsdoctor | Contributors Benchmark See Benchmark Credits Thanks to: The webpack team and community for creating a great bundler and ecosystem from which we draw a lot of inspiration. @sokra for the great work on the webpack project. @ScriptedAlchemy for creating Module Federation and helping Rspack connect with the community. The SWC project created by @kdy1 , which powers Rspack's code parsing, transformation and minification. The esbuild project created by @evanw , which inspired the concurrent architecture of Rspack. The NAPI-RS project created by @Brooooooklyn , which powers Rspack's node-binding implementation. The Parcel project created by @devongovett which is the pioneer of rust bundler and inspired Rspack's incremental rebuild design. The Vite project created by Evan You which inspired Rspack's compatibility design of webpack's ecosystem. The rolldown-legacy project created by old Rolldown team , It's the predecessor of the rolldown project, which explores the possibility of making a performant bundler in Rust with Rollup-compatible API. It inspires the design principles of Rspack. The html-webpack-plugin project created by @jantimon , @rspack/html-plugin is a fork of html-webpack-plugin to avoid some webpack API usage not supported in Rspack. The Turbopack project which inspired the AST path logic of Rspack. The react-refresh-webpack-plugin created by @pmmmwh , which inspires implement react refresh. The prefresh created by @Jovi De Croock , which inspires implement preact refresh rspack plugin. The mini-css-extract-plugin project created by @sokra which inspired implement css extract plugin. The copy-webpack-plugin project created by @kevlened which inspired implement copy rspack plugin. License Rspack is MIT licensed .

The fast Rust-based web bundler with webpack-compatible API 🦀️

bundler,javascript,compiler,web,rust,build-tool,esm,jsx,loaders,typescript

darkroomengineering/lenis

Introduction Lenis is a lightweight, robust, and performant smooth scroll library. It's designed by @darkroom.engineering to be simple to use and easy to integrate into your projects. It's built with performance in mind and is optimized for modern browsers. It's perfect for creating smooth scrolling experiences on your website such as webgl scroll synching, parallax effects and much more. See Demo and Showcase . Sponsorship If you like Lenis, please consider sponsoring us . Your support helps us maintain the project and continue to improve it. Packages lenis lenis/react lenis/snap Installation JavaScript using a package manager: bash npm i lenis js import Lenis from 'lenis' using scripts: ```html ``` Setup Basic: ```js const lenis = new Lenis() lenis.on('scroll', (e) => { console.log(e) }) function raf(time) { lenis.raf(time) requestAnimationFrame(raf) } requestAnimationFrame(raf) ``` Add the following CSS to your project: ```css html.lenis, html.lenis body { height: auto; } .lenis.lenis-smooth { scroll-behavior: auto !important; } .lenis.lenis-smooth [data-lenis-prevent] { overscroll-behavior: contain; } .lenis.lenis-stopped { overflow: hidden; } .lenis.lenis-smooth iframe { pointer-events: none; } ``` GSAP ScrollTrigger: ```js const lenis = new Lenis() lenis.on('scroll', (e) => { console.log(e) }) lenis.on('scroll', ScrollTrigger.update) gsap.ticker.add((time)=>{ lenis.raf(time * 1000) }) gsap.ticker.lagSmoothing(0) ``` React: See documentation for lenis/react . Instance settings | Option | Type | Default | Description | |--------------------------|-----------------------|----------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------| | wrapper | HTMLElement, Window | window | The element that will be used as the scroll container | | content | HTMLElement | document.documentElement | The element that contains the content that will be scrolled, usually wrapper 's direct child | | eventsTarget | HTMLElement, Window | wrapper | The element that will listen to wheel and touch events | | smoothWheel | boolean | true | Smooth the scroll initiated by wheel events | | lerp | number | 0.1 | Linear interpolation (lerp) intensity (between 0 and 1) | | duration | number | 1.2 | The duration of scroll animation (in seconds). Useless if lerp defined | | easing | function | (t) => Math.min(1, 1.001 - Math.pow(2, -10 * t)) | The easing function to use for the scroll animation, our default is custom but you can pick one from Easings.net . Useless if lerp defined | | orientation | string | vertical | The orientation of the scrolling. Can be vertical or horizontal | | gestureOrientation | string | vertical | The orientation of the gestures. Can be vertical , horizontal or both | | syncTouch | boolean | false | Mimic touch device scroll while allowing scroll sync (can be unstable on iOS<16) | | syncTouchLerp | number | 0.075 | Lerp applied during syncTouch inertia | | touchInertiaMultiplier | number | 35 | Manage the the strength of syncTouch inertia | | wheelMultiplier | number | 1 | The multiplier to use for mouse wheel events | | touchMultiplier | number | 1 | The multiplier to use for touch events | | infinite | boolean | false | Enable infinite scrolling! syncTouch: true is required on touch devices. ( See example ) | | autoResize | boolean | true | Resize instance automatically based on ResizeObserver . If false you must resize manually using .resize() | | prevent | boolean, function | false | Manually prevent scroll to be smoothed based on elements traversed by events. Example: (node) => node.classList.contains('cookie-modal') | Instance Props | Property | Type | Description | |-------------------------|-------------------|----------------------------------------------------------------------------| | animatedScroll | number | Current scroll value | | dimensions | object | Dimensions instance | | direction | number | 1 : scrolling up, -1 : scrolling down | | emitter | object | Emitter instance | | options | object | Instance options | | targetScroll | number | Target scroll value | | time | number | Time elapsed since instance creation | | actualScroll | number | Current scroll value registered by the browser | | lastVelocity | number | last scroll velocity | | velocity | number | Current scroll velocity | | isHorizontal (getter) | boolean | Whether or not the instance is horizontal | | isScrolling (getter) | boolean, string | Whether or not the scroll is being animated, smooth , native or false | | isStopped (getter) | boolean | Whether or not the user should be able to scroll | | limit (getter) | number | Maximum scroll value | | progress (getter) | number | Scroll progress from 0 to 1 | | rootElement (getter) | HTMLElement | Element on which Lenis is instanced | | scroll (getter) | number | Current scroll value (handles infinite scroll if activated) | | className (getter) | string | rootElement className | Instance Methods | Method | Description | Arguments | |-----------------------------|---------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | raf(time) | Must be called every frame for internal usage. | time : in ms | | scrollTo(target, options) | Scroll to target. | target : goal to reach number : value to scroll in pixels string : CSS selector or keyword ( top , left , start , bottom , target ): goal to reach number : value to scroll in pixels string : CSS selector or keyword ( top , left , start , bottom , right , end ) HTMLElement : DOM element options offset ( number ): equivalent to scroll-padding-top lerp ( number ): animation lerp intensity duration ( number ): animation duration (in seconds) easing ( function ): animation easing immediate ( boolean ): ignore duration, easing and lerp lock ( boolean ): whether or not to prevent the user from scrolling until the target is reached force ( boolean ): reach target even if instance is stopped onComplete ( function ): called when the target is reached userData ( object ): this object will be forwarded through scroll events | | on(id, function) | id can be any of the following instance events to listen. | | | stop() | Pauses the scroll | | | start() | Resumes the scroll | | | resize() | Compute internal sizes, it has to be used if autoResize option is false . | | | destroy() | Destroys the instance and removes all events. | | Instance Events | Event | Callback Arguments | |----------|--------------------| | scroll | Lenis instance | Considerations Nested scroll ```html scroll content scroll content scroll content ``` See modal example Anchor links html <a href="#anchor" onclick="lenis.scrollTo('#anchor')">scroll to anchor</a> Limitations no support for CSS scroll-snap ( lenis/snap ) capped to 60fps on Safari ( source ) and 30fps on low power mode smooth scroll will stop working over iframe since they don't forward wheel events position fixed seems to lag on MacOS Safari pre-M1 ( source ) Tutorials Scroll Animation Ideas for Image Grids by Codrops How to Animate SVG Shapes on Scroll by Codrops The BEST smooth scrolling library for your Webflow website! (Lenis) by Diego Toda de Oliveira Easy smooth scroll in @Webflow with Lenis + GSAP ScrollTrigger tutorial by También Studio Plugins r3f-scroll-rig by 14islands locomotive-scroll by Locomotive vue-lenis by ZEOKKU nuxt-lenis by Milkshake Studio Lenis in use Lunchbox by Studio Freight Easol by Studio Freight Dragonfly by Studio Freight Yuga Labs by Antinomy Studio Quentin Hocde's Portfolio by Quentin Hocde Houses Of by Félix P. & Shelby Kay Shelby Kay's Portfolio by Shelby Kay Heights Agency Portfolio by Francesco Michelini Goodship by Studio Freight Flayks' Portfolio by Félix P. & Shelby Kay Matt Rothenberg's portfolio by Matt Rothenberg Edoardo Lunardi's portfolio by Edoardo Lunardi DeSo by Studio Freight Francesco Michelini's portfolio by Francesco Michelini Authors This set of hooks is curated and maintained by the darkroom.engineering team: Clément Roche ( @clementroche_ ) – darkroom.engineering Guido Fier ( @uido15 ) – darkroom.engineering Leandro Soengas ( @lsoengas ) - darkroom.engineering Franco Arza ( @arzafran ) - darkroom.engineering License The MIT License.

How smooth scroll should be

scroll,smooth,smooth-scroll

runtipi/runtipi

Tipi — A personal homeserver for everyone 💡 Tipi is built with TypeScript, Next.js app router and Drizzle ORM! If you want to collaborate on a cool project, join the discussion on Discord! Join the community ⚠️ Tipi is built and maintained by volunteers. There is no guarantee of support or security when you use Tipi. While the system is considered stable, it is still in active development and may contain bugs. Tipi is a personal homeserver orchestrator that makes it easy to manage and run multiple services on a single server. It is based on Docker and comes with a simple web interface to manage your services. Tipi is designed to be easy to use, so you don't have to worry about manual configuration or networking. Simply install Tipi on your server and use the web interface to add and manage services. You can see a list of available services in the App Store repo and request new ones if you don't see what you need. To get started, follow the installation instructions below. Getting started Visit our website runtipi.io for installation instructions, documentation and guides. Demo You can try out a demo of Tipi at demo.runtipi.io using the following credentials: username: user@runtipi.io password: password 📚 Documentation You can find more documentation and tutorials / FAQ on runtipi.io ❤️ Contributing Tipi is made to be very easy to plug in new apps. We welcome and appreciate new contributions. If you want to add a new app or feature, you can follow the Contribution guide for instructions on how to do so. We are looking for contributions of all kinds. If you know design, development, or have ideas for new features, please get in touch. 📜 License Tipi is licensed under the GNU General Public License v3.0. TL;DR — You may copy, distribute and modify the software as long as you track changes/dates in source files. Any modifications to or software including (via compiler) GPL-licensed code must also be made available under the GPL along with build & install instructions. 🗣 Community Twitter Discord 🙏 Acknowledgements GitHub - Thanks for generously giving us access to your full product suite Freepik - Thanks for providing a free logo for the project Sentry - Thanks for providing error tracking for the project Crowdin - Thanks for providing localization management for the project CodeRabbit - Thanks for providing free AI code reviews in our Pull Requests ✨ Contributors Thanks goes to these wonderful people ( emoji key ): Nicolas Meienberger 💻 🚇 ⚠️ 📖 ArneNaessens 💻 🤔 ⚠️ DrMxrcy 💻 🤔 ⚠️ 🖋 📣 💬 👀 Cooper 💻 JTruj1ll0923 💻 Stetsed 💻 Jones_Town 💻 Rushi Chaudhari 💻 Robert Blaine 💻 Seth For Privacy 💻 Prajna 💻 Justin Moy 💻 dextreem 💻 Brahim Hadriche 💻 Andrew Brereton 🖋 Freddie Sackur 💻 📖 Innocentius 🌍 Alex 💻 Ryan Wang 💻 simonandr 🖋 iepure 🌍 Sergey Kodolov 🌍 💻 sclaren 💻 mcmeel 💬 🤔 💻 📖 NoisyFridge 🌍 Bvoxl 🌍 m-lab-0 🌍 dannkunt 🌍 Schmanko 🌍 Nghia Lele 🌍 amusingimpala75 💻 David 🌍 Stavros 🌍 💻 ⚠️ 📖 loxiry 🌍 JigSaw 💻 DireMunchkin 💻 Fabio Cingottini 🌍 him 💻 CHALOPIN Clément 💻 Geetansh Jindal 💻 Olivier Garcia 💻 qcoudeyr 💻 Armand Gillot 💻 Jaffo73 ⚠️ 💻 Jorge Montejo 💻 Frédéric Cilia 💻 Agustín Carrasco 💻 Thibault Claude 💻 Joshua Banks 💻 📖 hex-developer 💻 Gabriel Farias Nunes 🌍 Did you contribute and want to see your name listed in the README? Write a comment here This project follows the all-contributors specification. Contributions of any kind welcome!

Runtipi is a homeserver for everyone! One command setup, one click installs for your favorites self-hosted apps. ✨

homeserver,linux,self-hosted

aiboboxx/clashfree

clash节点、免费clash节点、clash订阅链接、clash免费节点、clash科学上网、clash翻墙、clash for windows、clash教程 每日更新 更新时间 2024-06-24 13:00:27 所有免费clash节点都爬取自网络，请勿用于非法用途 。电报地址： 免费clash节点每日更新 – Telegram clash使用教程： clash科学上网：clash for windows 详细教程 clash订阅链接： 点击下载 更多clash节点订阅 ： 高性价比机场推荐： 快帆云 快帆云 — 2024 最佳机场之选 全球众多节点，8K不卡顿。 解锁奈飞、迪士尼、TikTok 、ChatGPT。 流量不虚标，所有节点都是1倍率。 不限登陆设备数，不设置每日封顶流量。 按流量付费、包月等多种套餐可选，价格便宜。 更多推荐： 免费科学上网 免费clash节点 免费v2ray节点 一元机场 免费clash节点分享 ``` port: 7890 socks-port: 7891 allow-lan: true mode: Rule log-level: info external-controller: :9090 dns: enabled: true nameserver: - 119.29.29.29 - 223.5.5.5 fallback: - 8.8.8.8 - 8.8.4.4 - tls://1.0.0.1:853 - tls://dns.google:853 proxies: - {name: 🇬🇧 高性价比机场:https://kfyun.uk, server: 127.0.0.1, port: 443, client-fingerprint: chrome, type: ss, cipher: aes-128-gcm, password: 6601fb90e9b3, tfo: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点, server: 104.27.106.157, port: 80, client-fingerprint: chrome, type: vmess, uuid: fec25e7b-3e30-4702-9b93-62ed3849a9d7, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /video/X37qXHip, headers: {Host: 6Sn8mFtTjp3.yofnhkfc.xyz}}, udp: true} - {name: 🇨🇳 广东省广州市 移动, server: 120.232.153.27, port: 34002, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 2, server: cfcdn3.sanfencdn9.com, port: 80, client-fingerprint: chrome, type: vmess, uuid: fec25e7b-3e30-4702-9b93-62ed3849a9d7, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /video/X37qXHip, headers: {Host: 6Sn8mFtTjp3.yofnhkfc.xyz}}, udp: true} - {name: 🇨🇳 广东省 移动, server: 183.240.235.162, port: 54002, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 3, server: 172.67.199.221, port: 8080, client-fingerprint: chrome, type: vmess, uuid: b551aa22-22af-11ee-b8d8-f23c932eb68d, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: oiictw.yydsii.com}}, udp: true} - {name: 🇨🇳 广东省 移动 2, server: 183.240.235.164, port: 55908, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 4, server: russia.com, port: 2095, client-fingerprint: chrome, type: vmess, uuid: b7c56170-edb4-4c4a-bb64-ed5ef40b8739, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /api/v3/download.getFile, headers: {Host: sssub.v2.001.ssrsub.com}}, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 5, server: 104.16.45.16, port: 80, client-fingerprint: chrome, type: vmess, uuid: c0453a16-67e9-4eab-bdc9-b9624ad6bd29, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: "/?ed=2048&Telegram🇨🇳", headers: {Host: akhk.xlb8.eu.org}}, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 6, server: 172.64.32.154, port: 2087, client-fingerprint: chrome, type: vmess, uuid: 2a3263e2-891c-4446-b474-a8c63acb6e25, alterId: 0, cipher: auto, tls: true, tfo: false, skip-cert-verify: false, servername: dd21146ygfdSNA9191281280kdm22kas2123Aawdsd1234bb66428161.babettecarissa.net, network: grpc, grpc-opts: {grpc-mode: gun, grpc-service-name: /}, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 7, server: 104.19.46.233, port: 2086, client-fingerprint: chrome, type: vmess, uuid: 29eebb60-b27b-4a9d-bba5-947763d9205e, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: github.com/Alvin9999, headers: {Host: ip002-2.dtku47.xyz}}, udp: true} - {name: 🇺🇸 美国+华盛顿Cogent通信公司, server: 38.75.137.42, port: 8882, client-fingerprint: chrome, type: ss, cipher: aes-256-gcm, password: kDWvXYZoTBcGkC4, tfo: false, udp: true} - {name: 🇺🇸 美国+华盛顿Cogent通信公司 2, server: 38.99.82.85, port: 20002, client-fingerprint: chrome, type: ss, cipher: chacha20-ietf-poly1305, password: ̈́m͒ߍMÖ¡Tyۙҫ1͛P̎, tfo: false, udp: true} - {name: 🇨🇳 广东省 移动 3, server: 183.240.235.164, port: 32998, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 8, server: 104.19.55.49, port: 2086, client-fingerprint: chrome, type: vmess, uuid: e9e3cc13-db48-4cc1-8c24-7626439a5339, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: github.com/Alvin9999, headers: {Host: ip11.freegradely.xyz}}, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 9, server: s1c.v2.v001sss.xyz, port: 2082, client-fingerprint: chrome, type: vmess, uuid: 112ac36f-3f53-4e26-8371-d25c028e1b9a, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: s1c.v2.v001sss.xyz}}, udp: true} - {name: 🇨🇳 广东省广州市 移动 2, server: 183.236.51.23, port: 54100, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国+华盛顿Cogent通信公司 3, server: 38.110.1.51, port: 8091, client-fingerprint: chrome, type: ss, cipher: aes-256-gcm, password: PCnnH6SQSnfoS27, tfo: false, udp: true} - {name: 🇬🇧 英国+Microsoft公司, server: 51.13.182.130, port: 48562, client-fingerprint: chrome, type: ss, cipher: chacha20-ietf-poly1305, password: eHpq4cgXzmWTkI2xKN3w54, tfo: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 10, server: 162.159.136.98, port: 80, client-fingerprint: chrome, type: vmess, uuid: f1b6bc05-40dd-4180-ca18-b05288fd33bb, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: ccs2.hostmjj.com}}, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 11, server: cfcdn1.sanfencdn9.com, port: 2052, client-fingerprint: chrome, type: vmess, uuid: fec25e7b-3e30-4702-9b93-62ed3849a9d7, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /video/6VBhAkCtV4/, headers: {Host: us1cPZiz8nb.fzbqfrse.xyz}}, udp: true} - {name: 🇨🇳 江苏省徐州市 移动, server: 223.113.54.154, port: 27119, client-fingerprint: chrome, type: trojan, password: RmdXQRXg, sni: 223.113.54.154, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国 Amazon数据中心, server: 18.170.58.191, port: 12571, client-fingerprint: chrome, type: trojan, password: I6MP2lbMwGiV, sni: appsvs.shop, skip-cert-verify: false, udp: true} - {name: 🇰🇷 韩国 首尔Amazon数据中心, server: 3.34.53.229, port: 12583, client-fingerprint: chrome, type: trojan, password: HJQogep9v1jW, sni: appsvs.shop, skip-cert-verify: false, udp: true} - {name: 🇨🇳 广东省广州市 移动 3, server: 120.232.153.71, port: 54965, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 12, server: speed.cloudflare.com, port: 80, client-fingerprint: chrome, type: vmess, uuid: 05641cf5-58d2-4ba4-a9f1-b3cda0b1fb1d, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /obdii.cfd/linkws, headers: {Host: 4868-poetry-4868.napora7003.workers.dev}}, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 13, server: 104.16.192.157, port: 443, client-fingerprint: chrome, type: trojan, password: dba20dcb635e430fa4d3bfc303a149d2, sni: jobscareerfortoday.com, skip-cert-verify: false, network: ws, ws-opts: {path: /6b777a91, headers: {Host: jobscareerfortoday.com}}, udp: true} - {name: 🇷🇺 俄罗斯 v2rayfree.eu.org, server: sv1.ahsg.top, port: 5060, client-fingerprint: chrome, type: trojan, password: eLpjAXg6pM, sni: sv1.ahsg.top, skip-cert-verify: false, udp: true} - {name: 🇨🇳 广东省广州市 移动 4, server: 120.232.153.37, port: 42055, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇨🇳 广东省广州市 移动 5, server: 120.232.153.40, port: 53942, client-fingerprint: chrome, type: vmess, uuid: 418048af-a293-4b99-9b0c-98ca3580dd24, alterId: 64, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, udp: true} - {name: 🇯🇵 日本 v2rayfree.eu.org, server: 43.203.213.137, port: 12566, client-fingerprint: chrome, type: trojan, password: qHAYsiYph16v, sni: appsvs.shop, skip-cert-verify: false, udp: true} - {name: 🇺🇸 美国 CloudFlare节点 14, server: 104.19.47.238, port: 8080, client-fingerprint: chrome, type: vmess, uuid: b551aa22-22af-11ee-b8d8-f23c932eb68d, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: oiictw.yydsii.com}}, udp: true} - {name: 🇷🇺 俄罗斯 1, server: 185.242.86.156, port: 54170, client-fingerprint: chrome, type: ss, cipher: chacha20-ietf-poly1305, password: 36ZCHeabUSfKjfQEvJ4HDV, tfo: false, udp: true} - {name: 🇮🇳 印度 2, server: 202.78.162.5, port: 443, client-fingerprint: chrome, type: vmess, uuid: 2ff97c6d-8557-42a4-b43f-19c77c5959ea, alterId: 0, cipher: auto, tls: true, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: irsoft.sytes.net}}, udp: true} - {name: 🇮🇳 印度 3, server: 202.78.162.5, port: 443, client-fingerprint: chrome, type: vmess, uuid: 118287d2-e968-42e1-80d0-12fa2f5d38d6, alterId: 0, cipher: auto, tls: true, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: sahand.serveminecraft.net}}, udp: true} - {name: 🇺🇸 美国CloudFlare公司CDN节点 4, server: www.darkroom.lol, port: 8080, client-fingerprint: chrome, type: vmess, uuid: 22826b44-5c1a-4b4b-dbaa-83a2e8bd95f0, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: www.darkroom.lol}}, udp: true} - {name: 🇵🇱 波兰 5, server: 193.243.147.128, port: 40368, client-fingerprint: chrome, type: ss, cipher: aes-256-gcm, password: 7BcLdsO1WweoGD0X, tfo: false, udp: true} - {name: 🇺🇸 美国CloudFlare公司CDN节点 6, server: server31.beheshtbaneh.com, port: 8880, client-fingerprint: chrome, type: vmess, uuid: 4154143c-bbba-47a4-9f79-c2ed087cbcc9, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: server31.beheshtbaneh.com}}, udp: true} - {name: 🇨🇳 广东省移动 7, server: data-us-v1.shwjfkw.cn, port: 20401, client-fingerprint: chrome, type: vmess, uuid: b1478e24-4916-3abe-8f17-15931012ecbe, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /debian, headers: {Host: data-us-v1.shwjfkw.cn}}, udp: true} - {name: 🇨🇳 广东省江门市移动 8, server: service.ouluyun9803.com, port: 20003, client-fingerprint: chrome, type: ss, cipher: chacha20-ietf-poly1305, password: d6105bbd-be0d-45b2-82ad-31fd1071c1d2, tfo: false, udp: true} - {name: 🇺🇸 美国CloudFlare公司CDN节点 9, server: 104.21.82.183, port: 8880, client-fingerprint: chrome, type: vmess, uuid: 5a7021e0-26b4-45d6-b175-fe551601ca97, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: server26.beheshtbaneh.com}}, udp: true} - {name: 🇮🇳 印度 10, server: 202.78.162.5, port: 443, client-fingerprint: chrome, type: vmess, uuid: 716eded6-2201-4dbd-9d63-1638c9e8e677, alterId: 0, cipher: auto, tls: true, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: pendar.onthewifi.com}}, udp: true} - {name: 🇨🇳 广东省江门市移动 11, server: service.ouluyun9803.com, port: 26667, client-fingerprint: chrome, type: ss, cipher: chacha20-ietf-poly1305, password: d6105bbd-be0d-45b2-82ad-31fd1071c1d2, tfo: false, udp: true} - {name: 🇨🇳 广东省江门市移动 12, server: service.ouluyun9803.com, port: 20005, client-fingerprint: chrome, type: ss, cipher: chacha20-ietf-poly1305, password: d6105bbd-be0d-45b2-82ad-31fd1071c1d2, tfo: false, udp: true} - {name: 🇺🇸 美国Fastly全球Anycast节点 13, server: gov.uk, port: 443, client-fingerprint: chrome, type: vmess, uuid: 77848824-93b7-4b89-ffd0-e91afff406ce, alterId: 0, cipher: auto, tls: true, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /77848824, headers: {Host: zheshiscp.com}}, udp: true} - {name: 🇺🇸 美国CloudFlare节点 14, server: server32.beheshtbaneh.com, port: 8880, client-fingerprint: chrome, type: vmess, uuid: 044ba8ed-7285-472a-bc14-fb91dc6be4c9, alterId: 0, cipher: auto, tls: false, tfo: false, skip-cert-verify: false, network: ws, ws-opts: {path: /, headers: {Host: server32.beheshtbaneh.com}}, udp: true} proxy-groups: - name: 🔰 节点选择 type: select proxies: - ♻️ 自动选择 - 🎯 全球直连 - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 - name: ♻️ 自动选择 type: url-test url: http://www.gstatic.com/generate_204 interval: 300 proxies: - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 - name: 🎥 NETFLIX type: select proxies: - 🔰 节点选择 - ♻️ 自动选择 - 🎯 全球直连 - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 - name: ⛔️ 广告拦截 type: select proxies: - 🛑 全球拦截 - 🎯 全球直连 - 🔰 节点选择 - name: 🚫 运营劫持 type: select proxies: - 🛑 全球拦截 - 🎯 全球直连 - 🔰 节点选择 - name: 🌍 国外媒体 type: select proxies: - 🔰 节点选择 - ♻️ 自动选择 - 🎯 全球直连 - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 - name: 🌏 国内媒体 type: select proxies: - 🎯 全球直连 - 🔰 节点选择 - name: Ⓜ️ 微软服务 type: select proxies: - 🎯 全球直连 - 🔰 节点选择 - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 - name: 📲 电报信息 type: select proxies: - 🔰 节点选择 - 🎯 全球直连 - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 - name: 🍎 苹果服务 type: select proxies: - 🔰 节点选择 - 🎯 全球直连 - ♻️ 自动选择 - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 - name: 🎯 全球直连 type: select proxies: - DIRECT - name: 🛑 全球拦截 type: select proxies: - REJECT - DIRECT - name: 🐟 漏网之鱼 type: select proxies: - 🔰 节点选择 - 🎯 全球直连 - ♻️ 自动选择 - 🇬🇧 高性价比机场:https://kfyun.uk - 🇺🇸 美国 CloudFlare节点 - 🇨🇳 广东省广州市 移动 - 🇺🇸 美国 CloudFlare节点 2 - 🇨🇳 广东省 移动 - 🇺🇸 美国 CloudFlare节点 3 - 🇨🇳 广东省 移动 2 - 🇺🇸 美国 CloudFlare节点 4 - 🇺🇸 美国 CloudFlare节点 5 - 🇺🇸 美国 CloudFlare节点 6 - 🇺🇸 美国 CloudFlare节点 7 - 🇺🇸 美国+华盛顿Cogent通信公司 - 🇺🇸 美国+华盛顿Cogent通信公司 2 - 🇨🇳 广东省 移动 3 - 🇺🇸 美国 CloudFlare节点 8 - 🇺🇸 美国 CloudFlare节点 9 - 🇨🇳 广东省广州市 移动 2 - 🇺🇸 美国+华盛顿Cogent通信公司 3 - 🇬🇧 英国+Microsoft公司 - 🇺🇸 美国 CloudFlare节点 10 - 🇺🇸 美国 CloudFlare节点 11 - 🇨🇳 江苏省徐州市 移动 - 🇺🇸 美国 Amazon数据中心 - 🇰🇷 韩国 首尔Amazon数据中心 - 🇨🇳 广东省广州市 移动 3 - 🇺🇸 美国 CloudFlare节点 12 - 🇺🇸 美国 CloudFlare节点 13 - 🇷🇺 俄罗斯 v2rayfree.eu.org - 🇨🇳 广东省广州市 移动 4 - 🇨🇳 广东省广州市 移动 5 - 🇯🇵 日本 v2rayfree.eu.org - 🇺🇸 美国 CloudFlare节点 14 - 🇷🇺 俄罗斯 1 - 🇮🇳 印度 2 - 🇮🇳 印度 3 - 🇺🇸 美国CloudFlare公司CDN节点 4 - 🇵🇱 波兰 5 - 🇺🇸 美国CloudFlare公司CDN节点 6 - 🇨🇳 广东省移动 7 - 🇨🇳 广东省江门市移动 8 - 🇺🇸 美国CloudFlare公司CDN节点 9 - 🇮🇳 印度 10 - 🇨🇳 广东省江门市移动 11 - 🇨🇳 广东省江门市移动 12 - 🇺🇸 美国Fastly全球Anycast节点 13 - 🇺🇸 美国CloudFlare节点 14 rules: - 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clash,freefq,freenode,ssr,v2ray,trojian

alyssaxuu/omni

Omni The most powerful interface for your browser 🔥 With Omni you can use your browser like a pro. Manage tabs, bookmarks, your browser history, perform all sorts of actions and more with a simple command interface. 👉 Get it now for Chrome and for Firefox You can support this project (and many others) through GitHub Sponsors ! ❤️ Made by Alyssa X Table of contents Features Controlling the interface Opening Omni Closing Omni Switching between dark and light mode List of commands Self-hosting Omni Installing on Chrome Installing on Firefox Libraries used Features 🗄 Switch, open, close, and search your tabs 📚 Browse and manage your bookmarks 🔍 Search your browsing history ⚡️ 50+ actions to improve your productivity 🔮 Special commands to filter and perform more actions 🧩 Integrations with Notion, Figma, Docs, Asana... ⌨️ Shortcuts for actions such as muting, pinning, bookmarking... ⚙️ Advanced settings to help troubleshoot browsing issues 🌙 Dark mode ...and much more - all for free & no sign in needed! Controlling the interface Opening Omni To open Omni, simply press ⌘+Shift+K on Mac or Ctrl+Shift+K on Windows. You can change the shortcut by going to chrome://extensions/shortcuts in Chrome, or by following these steps in Firefox Alternatively you can click on the extension icon in the toolbar to toggle it. Closing Omni To close Omni you can press Esc , click on the background, or press the extension icon. Switching between dark and light mode The dark and light theme in Omni is tied to your system's theme. On Mac you can change the theme by clicking on the Apple menu (on the top left), opening the System preferences, going into the General section, and then choosing between dark, light, or auto. On Windows it depends on the OS version. Here is a guide for Windows 11 and 10. After switching the theme you might need to restart your browser. List of commands You can use a variety of commands with Omni to perform actions or filter your results. /tabs : Search your tabs /bookmarks : Search your bookmarks /history : Search your browser history /actions : Search all available actions /remove : Remove a bookmark or close a tab Feel free to suggest new commands for Omni by making an issue . Self-hosting Omni You can run Omni locally without having to install it from the Chrome Store or from Firefox Add-ons. Installing on Chrome Download the code. In the web version of GitHub, you can do that by clicking the green "Code" button, and then "Download ZIP". Go to chrome://extensions/ in your browser, and enable developer mode . Drag the src folder (make sure it's a folder and not a ZIP file, so unzip first), or click on the "Load unpacked" button and locate the folder. That's it, you will now be able to use Omni locally. Installing on Firefox Download the code. In the web version of GitHub, you can do that by clicking the green "Code" button, and then "Download ZIP". Open the about:debugging page in your browser, click the "This Firefox" option. Click the "Load Temporary Add-on" button, and select any file inside the firefox folder That's it, you will now be able to use Omni locally. Libraries used jQuery - for better event handling and DOM manipulation dom-focus-lock - to keep focus on the input field Feel free to reach out to me through email at hi@alyssax.com or on Twitter if you have any questions or feedback! Hope you find this useful 💜

The all-in-one tool to supercharge your productivity ⌨️

omnisearch,spotlight,interface,dark,chrome,chrome-extension,commands,shortcuts,raycast,history

filecxx/FileCentipede

English | 简体中文 | 繁體中文 | 한국어 | Hindi | Arabic | Français | Русский | Latin | 日本語 | Italian | Deutsch | Portuguese Br | Español | svenska | فارسی | Türkçe File centipede is an All-In-One internet file upload/download manager, BitTorrent Client, WebDAV client, FTP client, and SSH client. It is designed to be fast, customizable, and user-friendly. It supports multi-protocols and contains many useful auxiliary tools such as HTTP requester, file merge, and encoders. With the browser integration, you can download audio and videos from websites, even encrypted videos. (It's free with no ads) Website: http://filecxx.com Dashboard: https://w.filecxx.com Sponsors: http://www.filecxx.com/en_US/sponsors.html Screenshot File Centipede Add task Edit task Confirm dialog Add catalog Settings Proxy settings Site rules Filter Refresh address Create torrent Speed limit Translate tool HTTP tool Checksum tool Browser extension screenshots Video bar Videos panel Audios panel features HTTP,HTTPS protocol (basic features like gzip, resumable, multi-connections will not be listed.) 1.0 FTP, FTPS protocol 1.0 Magnet, HASH address 1.0 BitTorrent 1.0 Other custom protocol like thunder, flashget, qqdl 1.0 JSON formatted address 1.0 m3u8 stream task 1.0 Stream task AES-128 decryption (SAMPLE-AES decryption is not supported yet) 1.0 HTTP cookie, header, user-agent with user customize 1.0 Torrent seeding limit 1.0 Dynamically edit transfer-task config 1.0 Anti leeches 1.0 Refresh expired address 1.0 Catalogs 1.0 Limit download, upload speed 1.0 Create custom address (filec, fileu) 1.0 Proxy management 1.0 Filter customize 1.0 Tracker management 1.0 Task details 1.0 Export torrent from task 1.0 Multi languages 1.0 Queue or Unlimited concurrency setting 1.0 Chrome Browser integration 1.0 Firefox Browser integration 1.0 Capture videos, audios from web page 1.0 Find all magnets from web page 1.0 Translate tool 1.0 HTTP tool 1.0 URI encode/decode tool 1.0 Base64 encode/decode tool 1.0 Regex test tool 1.0 Create torrent 1.0 Torrent to magnet tool 1.0 Magnet to torrent tool 1.0 File merge tool 1.0 Statistics 1.0 Download all links from webpage 1.6 SSH, SFTP protocol 2.0 curl, wget, aria2, axel command line 2.0 WebDAV protocol 2.0 Upload file 2.0 Upload directory 2.0 Download directory 2.0 Full-featured WebDAV(s) file manager 2.0 Full-featured FTP(s) file manager 2.0 Full-featured SSH(sftp) file manager 2.0 File browser persistent caches 2.0 Site rules 2.1 Checksum tool 2.3 Remote download 2.6 Source code The full source code of FileU can be found in the "source_code" directory. It's for demonstration purposes only, the dependent libraries used in the project are not open source. It has proved that writing user interfaces in C++ could be significantly easier than HTML and JavaScript, without reducing performance. (as seen in the .sml files in the "UI" directory). Translate If you like this software, you can help by using the translation tool provided in the software to translate it into other languages. This will make the software more accessible to people who speak languages other than the one it was originally written in. Your contribution would be greatly appreciated. Language files Website: "lang/website/*.lang" Software: "lang/software/*.lang" Browser extension: "lang/browser_extension/*.lang" How to translate the website? | Language |@| |:--------------------|:-------------| | Русский | @vanja-san @Den1704 | 繁體中文 | @bear0316 @postman1year | Français | @XIAA25 | Nederlands | @XIAA25 | 한국어 | @VenusGirl | Tiếng Việt | @vuongtuha | Türkçe | @geeede @saurane | Indonesian | @gigglylo Rangga S. Nugraha | Deutsch | @Vulcanraven91 | 日本語 | @wany-oh | polski | @RunoHawk Opensource libraries boost Qt libtorrent

Cross-platform internet upload/download manager for HTTP(S), FTP(S), SSH, magnet-link, BitTorrent, m3u8, ed2k, and online videos. WebDAV client, FTP client, SSH client.

bittorrent-client,download-manager,download-videos,bt,magnet,libtorrent,http-client,ftp-client,download,video-downloader

linkwarden/linkwarden

Linkwarden [Website](https://linkwarden.app) | [Getting Started](https://docs.linkwarden.app) | [Features](https://github.com/linkwarden/linkwarden#features) | [Roadmap](https://github.com/orgs/linkwarden/projects/1) | [Support ❤](https://github.com/linkwarden/linkwarden#support-) Intro & motivation Linkwarden is a self-hosted, open-source collaborative bookmark manager to collect, organize and archive webpages. The objective is to organize useful webpages and articles you find across the web in one place, and since useful webpages can go away (see the inevitability of Link Rot ), Linkwarden also saves a copy of each webpage as a Screenshot and PDF, ensuring accessibility even if the original content is no longer available. Additionally, Linkwarden is designed with collaboration in mind, sharing links with the public and/or allowing multiple users to work together seamlessly. [!TIP] Our official Cloud offering provides the simplest way to begin using Linkwarden and it's the preferred choice for many due to its time-saving benefits. Your subscription supports our hosting infrastructure and ongoing development. Alternatively, if you prefer self-hosting Linkwarden, no problem! You'll still have access to all the premium features. A bit of a "history" Linkwarden has been completely rebuilt and redesigned from ground up, so pretty much the only thing it has in common with its predecessor is the idea behind it - bookmark management. **What happened to the old version?** We've forked the old version from the current repository into [this repo](https://github.com/linkwarden/linkwarden-old). Features 📸 Auto capture a screenshot, PDF, and readable view of each webpage. 🏛️ Send your webpage to Wayback Machine ( archive.org ) for a snapshot. (Optional) 📂 Organize links by collection, sub-collection, name, description and multiple tags. 👥 Collaborate on gathering links in a collection. 🎛️ Customize the permissions of each member. 🌐 Share your collected links and preserved formats with the world. 📌 Pin your favorite links to dashboard. 🔍 Full text search, filter and sort for easy retrieval. 📱 Responsive design and supports most modern browsers. 🌓 Dark/Light mode support. 🧩 Browser extension, managed by the community. Star it here! ⬇️ Import and export your bookmarks. 🔐 SSO integration. (Enterprise and Self-hosted users only) 📦 Installable Progressive Web App (PWA). 🍎 iOS Shortcut to save links to Linkwarden. 🔑 API keys. ✅ Bulk actions. ✨ And so many more features! Like what we're doing? Give us a Star ⭐ We're building our Community 🌐 Join and follow us in the following platforms to stay up to date about the most recent features and for support: Suggestions We usually go after the popular suggestions . Feel free to open a new issue to suggest one - others might be interested too! :) Roadmap Make sure to check out our public roadmap . Docs For information on how to get started or to set up your own instance, please visit the documentation . Development If you want to contribute, Thanks! Start by checking our public roadmap , there you'll see a README for contributers for the rest of the info on how to contribute and the main tech stack. Security If you found a security vulnerability, please do not create a public issue, instead send an email to security@linkwarden.app stating the vulnerability. Thanks! Support ❤ Other than using our official Cloud offering, any donations are highly appreciated as well! Here are the other ways to support/cheer this project: Starring this repository. Joining us on Discord . Referring Linkwarden to a friend. If you did any of the above, Thanksss! Otherwise thanks. Thanks to All the Contributors 💪 Huge thanks to these guys for spending their time helping Linkwarden grow. They rock! ⚡️

⚡️⚡️⚡️Self-hosted collaborative bookmark manager to collect, organize, and preserve webpages and articles.

collaboration,self-hosted,typescript,nextjs,bookmark-manager

ageron/handson-ml3

Machine Learning Notebooks, 3rd edition This project aims at teaching you the fundamentals of Machine Learning in python. It contains the example code and solutions to the exercises in the third edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow (3rd edition) : Note : If you are looking for the second edition notebooks, check out ageron/handson-ml2 . For the first edition, see ageron/handson-ml . Quick Start Want to play with these notebooks online without having to install anything? (recommended) ⚠ Colab provides a temporary environment: anything you do will be deleted after a while, so make sure you download any data you care about. Other services may work as well, but I have not fully tested them: * * * Just want to quickly look at some notebooks, without executing any code? github.com's notebook viewer also works but it's not ideal: it's slower, the math equations are not always displayed correctly, and large notebooks often fail to open. Want to run this project using a Docker image? Read the Docker instructions . Want to install this project on your own machine? Start by installing Anaconda (or Miniconda ), git , and if you have a TensorFlow-compatible GPU, install the GPU driver , as well as the appropriate version of CUDA and cuDNN (see TensorFlow's documentation for more details). Next, clone this project by opening a terminal and typing the following commands (do not type the first $ signs on each line, they just indicate that these are terminal commands): $ git clone https://github.com/ageron/handson-ml3.git $ cd handson-ml3 Next, run the following commands: $ conda env create -f environment.yml $ conda activate homl3 $ python -m ipykernel install --user --name=python3 Finally, start Jupyter: $ jupyter notebook If you need further instructions, read the detailed installation instructions . FAQ Which Python version should I use? I recommend Python 3.10. If you follow the installation instructions above, that's the version you will get. Any version ≥3.7 should work as well. I'm getting an error when I call load_housing_data() If you're getting an HTTP error, make sure you're running the exact same code as in the notebook (copy/paste it if needed). If the problem persists, please check your network configuration. If it's an SSL error, see the next question. I'm getting an SSL error on MacOSX You probably need to install the SSL certificates (see this StackOverflow question ). If you downloaded Python from the official website, then run /Applications/Python\ 3.10/Install\ Certificates.command in a terminal (change 3.10 to whatever version you installed). If you installed Python using MacPorts, run sudo port install curl-ca-bundle in a terminal. I've installed this project locally. How do I update it to the latest version? See INSTALL.md How do I update my Python libraries to the latest versions, when using Anaconda? See INSTALL.md Contributors I would like to thank everyone who contributed to this project , either by providing useful feedback, filing issues or submitting Pull Requests. Special thanks go to Haesun Park and Ian Beauregard who reviewed every notebook and submitted many PRs, including help on some of the exercise solutions. Thanks as well to Steven Bunkley and Ziembla who created the docker directory, and to github user SuperYorio who helped on some exercise solutions. Thanks a lot to Victor Khaustov who submitted plenty of excellent PRs, fixing many errors. And lastly, thanks to Google ML Developer Programs team who supported this work by providing Google Cloud Credit.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

[]

Elfocrash/.NET-Backend-Developer-Roadmap

.NET Backend Developer Roadmap for 2023 Hey there 👋. This is my roadmap for .NET developers that want to focus on backend and specifically work with microservices and cloud. I will try to keep updating this roadmap as the technology landscape is evolving. I have created courses on several of the topics outlined in the roadmap so if you're interested in learning more about those topics then check my courses out: | | | | | - | - | - | | | | | | | | | Interactive Roadmap: Link

Roadmap for a .NET Backend Developer working with Microservices

roadmap,dotnet,aspnetcore,dotnet-core,aspnet-core,microservices,kubernetes

risingwavelabs/risingwave

### 🌊 Reimagine stream processing. Documentation 📑 Hands-on Tutorials 🎯 RisingWave Cloud 🚀 Get Instant Help RisingWave is a Postgres-compatible streaming database engineered to provide the simplest and most cost-efficient approach for processing , analyzing , and managing real-time event streaming data. Try it out in 60 seconds Install RisingWave standalone mode: shell curl https://risingwave.com/sh | sh Then follow the prompts to start and connect to RisingWave. To learn about other installation options, such as using a Docker image, see Quick Start . Please note: RisingWave uses Scarf to collect anonymized installation analytics. These analytics help support us understand and improve the distribution of our package. The privacy policy of Scarf is available at https://about.scarf.sh/privacy-policy . Production deployments RisingWave Cloud offers the easiest way to run RisingWave in production, with a forever-free developer tier. For Docker deployment , please refer to Docker Compose . For Kubernetes deployment , please refer to Kubernetes with Helm or Kubernetes with Operator . Why RisingWave for real-time materialized views? RisingWave specializes in providing incrementally updated, consistent materialized views — a persistent data structure that represents the results of event stream processing. Compared to materialized views, dynamic tables, and live tables in other database and data warehouse systems, RisingWave's materialized view stands out in several key aspects: * Highly cost-efficient - up to 95% cost savings compared to state-of-the-art solutions * Synchronous refresh without compromising consistency * Extensive SQL support including joins, deletes, and updates * High concurrency in query serving * Instant fault tolerance * Transparent dynamic scaling * Speedy bootstrapping and backfilling RisingWave's extensive CDC support further enables users to seamlessly offload event-driven workloads such as materialized views and triggers from operational databases (e.g., PostgreSQL ) to RisingWave. Why RisingWave for stream processing? RisingWave provides users with a comprehensive set of frequently used stream processing features, including exactly-once consistency, time window functions , watermarks , and more. RisingWave significantly reduces the complexity of building stream processing applications by allowing developers to express intricate stream processing logic through cascaded materialized views. Furthermore, it allows users to persist data directly within the system, eliminating the need to deliver results to external databases for storage and query serving. Compared to existing stream processing systems like Apache Flink , Apache Spark Streaming , and ksqlDB , RisingWave stands out in two primary dimensions: Ease-of-use and cost efficiency , thanks to its PostgreSQL -style interaction experience and Snowflake -like architectural design (i.e., decoupled storage and compute). | | RisingWave 🌊 | Traditional stream processing systems | | :---: | :---: | :---: | | Learning curve 🎢 | PostgreSQL-style experience | System-specific concepts | | Integration 🔗 | PostgreSQL ecosystem | System-specific ecosystem | | Complex queries (e.g., joins) 💡 | Highly efficient | Inefficient | | Failure recovery 🚨 | Instant | Minutes or even hours | | Dynamic scaling 🚀 | Transparent | Stop-the-world | | Bootstrapping and Backfilling ⏪ | Accelerated via dynamic scaling | Slow | RisingWave as a database RisingWave is fundamentally a database that extends beyond basic streaming data processing capabilities . It excels in the effective management of streaming data , making it a trusted choice for data persistence and powering online applications. RisingWave offers an extensive range of database capabilities, which include: High availability Serving highly concurrent queries Role-based access control (RBAC) Integration with data modeling tools, such as dbt Integration with database management tools, such as Dbeaver Integration with BI tools, such as Grafana Schema change Processing of semi-structured data In-production use cases Within your data stack, RisingWave can assist with: Processing and transforming event streaming data in real time Offloading event-driven queries (e.g., materialized views, triggers) from operational databases Performing real-time ETL (Extract, Transform, Load) Supporting real-time feature stores Read more at use cases . RisingWave is extensively utilized in real-time applications such as monitoring, alerting, dashboard reporting, machine learning, among others. It has already been adopted in fields such as financial trading, manufacturing, new media, logistics, gaming, and more. Check out customer stories . Community Looking for help, discussions, collaboration opportunities, or a casual afternoon chat with our fellow engineers and community members? Join our Slack workspace ! Notes on telemetry RisingWave collects anonymous usage statistics to better understand how the community is using RisingWave. The sole intention of this exercise is to help improve the product. Users may opt out easily at any time. Please refer to the user documentation for more details. License RisingWave is distributed under the Apache License (Version 2.0). Please refer to LICENSE for more information. Contributing Thanks for your interest in contributing to the project! Please refer to contribution guidelines for more information.

SQL stream processing, analytics, and management. We decouple storage and compute to offer instant failover, dynamic scaling, speedy bootstrapping, and efficient joins.

database,stream-processing,cloud-native,sql,distributed-database,rust,serverless,postgresql,real-time,postgres

windingwind/zotero-pdf-translate

Translate for Zotero Translate for Zotero , a.k.a. Zotero PDF Translate , is a Zotero plugin. Translate PDF, EPub, webpage, metadata, annotations, notes to the target language. Support 20+ translate services. 中文文档 Quick Start Guide Install For Zotero 6, install the latest stable version ; For Zotero 7, install the latest prerelease version From local file Download the latest release (.xpi file) from the Latest Release Page Note If you're using Firefox as your browser, right-click the .xpi and select "Save As.." In Zotero click Tools in the top menu bar and then click Addons Go to the Extensions page and then click the gear icon in the top right. Select Install Add-on from file . Browse to where you downloaded the .xpi file and select it. Restart Zotero, by clicking restart now in the extensions list where the Zotero PDF Translate plugin is now listed. From remote link In Zotero click Tools in the top menu bar and then click Addons . Drag Latest Release and drop it in the Zotero UI. Click install now . Restart Zotero, by clicking restart now in the extensions list where the Zotero PDF Translate plugin is now listed. Usage Once you have the plugin installed simply, open any PDF in your collections. Select some text, the translations are shown on the popup and the right sidebar(v0.2.0); Hold Alt/Option to concat selections. Highlight some text, the translations are added to the annotation comment(v0.3.0); Modify & retranslate the annotation text in the sidebar and click the Update Annotation to modify the annotation text and translation(v0.6.6); Add selected text along with translation to note(v0.4.0); Only works when a note editor is active. Translate item titles with right-click menu or shortcut Ctrl+T (v0.6.0). Translate item abstract with right-click menu(v0.8.0). Thanks @iShareStuff Standalone translation window available(v0.7.0). View & compare translations from multiply engines in one window! Dictionary for single word translation(v0.7.1). SentenceBySentence Translation(v1.1.0). After a translation, press shift + P and select Translate Sentences . Only for en2zh and en2en now . Thanks @MuiseDestiny Q&A Q I want to translate manually. A Go to Edit->Preferences->PDF Translate->General , uncheck the Automatic Translation . Click the translate button on the popup or sidebar to translate. Q I want a translate shortcut. A Press shortcut Ctrl+T after you selected some text. If you are in the collection view, the titles' translation will show/hide. Q I want to concat different seletions and translate them together. A Press Alt/Option when selecting text in PDF. Q Not the language I want. A The default target language is the same as your Zotero language. Go to Edit->Preferences->PDF Translate->General and change the language settings. Q Translation not correct or report an error. A See Language Settings and #6. Make sure you use the right secret. Q I want to change the font size. A Go to Edit->Preferences->PDF Translate->Advanced and set the font size. Settings General Enable Translation, default true Automatic Translation, default true Enable Dictionary: single word will be translated using dictionary-engine instead of translate engine, default true Enable Popup: Show results in a right-click popup or only in the sidebar, default true Automatic Annotation Translation: Save annotation's translation as comment, default true Show 'Add to Note(With Translation)' in Popup: default true Unvisible if no active note editor opened. Replace Source Text: Use translation to replace the source text when adding to note, default false Service The default engine is Google Translate. Currently, we support: | Translate Engine | Require Secret | Supported Languages | | ---------------------------- | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Google Translate | No | 100+ | | Google Translate(API) | No | Use translate.googleapis.com | | CNKI | No | https://dict.cnki.net | | Youdao Translate | No | 100+? | | NiuTrans | Yes | 400+ | | Youdao Zhiyun | Yes | 100+ | | Microsoft Translate | Yes(free 2M) | 200+ | | LingoCloud(Caiyun) Translate | Yes | zh, en, ja, es, fr, ru | | DeepL Translate | Yes(free 500k) | 100+ | | Aliyun Translate | Yes(free-1M) | 200+ | | Baidu Translate | Yes(free-QPS1/free-2M) | 200+ | | Baidu Field | Yes(free-QPS1/free-2M) | en-zh | | Tencent Translate | Yes(QPS5, free-5M) | 15 | | GPT(OpenAI) | Yes(free-$18) | Based on the gpt-3.5-turbo model | | Gemini | Yes(free-) | Based on the Gemini Pro model | If the engine you want is not yet supported, please post an issue. Google Google does not require a secret, but you can put your own API URL in the secret to replace the default URL (translate.google.com/translate.googleapi.com). Microsoft Translate Apply here . Copy your secret and paste it into the settings. The secret format is MY_SECRET . See this issue for detailed steps to set up the Microsoft Translate. DeepL Translate Apply here . The secret format is secretToken or secretToken#glossaryId (if you want to specify some translate glossary). Youdao Zhiyun Translate 有道智云 Apply here . The secret format is MY_APPID#MY_SECRET#MY_VOCABID(optional) . About VOCABID 登录控制台，选择文本翻译服务，点击右侧的术语表，选择新建，填写表名称和语言方向，添加需要的术语表，然后获取对应词表 id 即可。 Official Document NiuTrans Apply here . The secret format is MY_APIKEY#dictNo(optional)#memoryNo(optional) . Chinese Document Huoshan Apply here The secret format is accessKeyId#accessKeySecret Aliyun Translate Apply here . The secret format is accessKeyId#accessKeySecret . Chinere Document Baidu Translate Apply here . The secret format is MY_APPID#MY_KEY#ACTION(optional, see https://api.fanyi.baidu.com/doc/21, default 0) (split with '#'). Baidu Field Translate 百度垂直领域翻译 Apply here . The secret format is MY_APPID#MY_KEY#DOMAIN_CODE (split with '#'). | Domain Code | 领域 | 支持语言方向 | | ----------- | ------------ | ------------------------------------- | | it | 信息技术领域 | 中文（简）-> 英语、英语 -> 中文（简） | | finance | 金融财经领域 | 中文（简）-> 英语、英语 -> 中文（简） | | machinery | 机械制造领域 | 中文（简）-> 英语、英语 -> 中文（简） | | senimed | 生物医药领域 | 中文（简）-> 英语、英语 -> 中文（简） | | novel | 网络文学领域 | 中文（简）-> 英语 | | academic | 学术论文领域 | 中文（简）-> 英语、英语 -> 中文（简） | | aerospace | 航空航天领域 | 中文（简）-> 英语、英语 -> 中文（简） | | wiki | 人文社科领域 | 中文（简）-> 英语 | | news | 新闻资讯领域 | 中文（简）-> 英语、英语 -> 中文（简） | | law | 法律法规领域 | 中文（简）-> 英语、英语 -> 中文（简） | | contract | 合同领域 | 中文（简）-> 英语、英语 -> 中文（简） | Chinese Document Tencent Translate Apply here . The secret format is secretId#SecretKey#Region(optional, default ap-shanghai)#ProjectId(optional, default 0) (split with '#'). Chinese Document OpenL Translate Apply here . The secret format is service1,service2,...#apikey (split with '#'; split service codes with ','). Supported service codes are: deepl,youdao,tencent,aliyun,baidu,caiyun,wechat,sogou,azure,ibm,aws,google , See Service Code Chinese Document GPT Apply here . The secret format is sk-#SecretKey (split with '#'). Chinese Document User Interface Font Size : The font size of result text, default 12 Line Height : The line height of result text, default 1.5 SideBar: Show xxx : Show or hide sidebar elements, default true SideBar: Reverse Raw/Result : Reverse the order of Raw/Result in the sidebar if true , default false Popup: Remember Size : Remember size of popup if true , else automatically adjust the size, default false Advanced Disable Automatic Translation when File Language is(split with ','): If you want to disable automatic translation in zh and ja files, set zh,ja . Split Character(between text and translation): When translating annotations, the result will be wrapped inside this character to allow safe re-translate. If set to empty, re-translating annotations will replace the annotation comment with the new translate result. Development & Contributing This addon is built based on the Zotero Plugin Template . See the setup and debug details there. To startup, run bash git clone https://github.com/windingwind/zotero-pdf-translate.git cd zotero-pdf-translate npm install npm run build The plugin is built to ./build/*.xpi . Contributing Add new translate service Add service config to src/utils/config.ts > SERVICES ; Add translation task processor under src/modules/services/${serviceId}.ts with the same format with other services. The export function set the translation result to data.result if runs successfully and throw an error if fails; Import the task processor function in src/modules/services/index.ts . Add locale string service.${serviceId} in addon/chrome/locale/${lang}/addon.properties . Build and test. Extra options for translate service If the service requires extra options, the minimal implement would be putting them in the secret input in the prefs window, like the existing services does. If there are complex options, please bind a callback in src/modules/settings/index.ts > secretStatusButtonData which create a highly customizable dialog window with ztoolkit.Dialog . See the example of NiuTrans login here: https://github.com/windingwind/zotero-pdf-translate/blob/main/src/modules/settings/niutrans.ts Disclaimer Use this code under AGPL. No warranties are provided. Keep the laws of your locality in mind! My Other Zotero Addons Better Notes : Everything about note management. All in Zotero. Preview : PDF preview for Zotero Actions & Tags : Automatically tag items/Batch tagging Sponsors Thanks peachgirl100 and other anonymous sponsors! If you want to leave your name here, please email me or leave a message with the donation. Contributors

Translate PDF, EPub, webpage, metadata, annotations, notes to the target language. Support 20+ translate services.

zotero,translate,translation,plugin,zotero-plugin,pdf,zotero7

getlago/lago

Lago Open Source Metering & Usage-Based Billing The best alternative to Chargebee, Recurly or Stripe Billing. For usage-based, subscription-based, and all the nuances of pricing in between. Slack · Website · Issues · Roadmap The programmable API for usage-based billing The problem: Billing systems are still a nightmare for engineers Engineers be like… Read more first-hand experiences from Qonto, Algolia, Pleo, Segment, or the 350+. Hackernews comments here . The Solution: Lago, the open-source billing API for product-led SaaS - Event-based: if you can track it, you can charge for it; - Built for product-led growth companies; - Hybrid pricing: subscription and usage; - Hybrid go-to-market motion: self-serve and sales-led. Open-source, open architecture: - Composable: connect Lago to any of your internal systems or tools (i.e. any payment gateway, CRM, CPQ, accounting software); - Pricing: we’re not rent seekers, we’re not asking for a % of your revenue. Our self-hosted version is free. Our cloud version is priced like a SaaS; - Privacy: your data never has to leave your infrastructure. ✨ Features Usage metering : Lago's event-based architecture provides a solid foundation for building a fair pricing model that scales with your business. Price plans : Lago supports all pricing models. Create pay-as-you-go and hybrid plans in no time with our intuitive user interface or API. Coupons : Create engaging marketing campaigns and increase conversion with coupons that customers can redeem to get a discount. Add-ons : Why wait until the end of the billing cycle to get paid? Lago allows you to create one-time charges that are invoiced on the fly. Invoicing : Depending on the configuration of your plans, Lago automatically calculates what each customer owes you and generates invoices. Prepaid credits : Unlock recurring revenue opportunities for pay-as-you-go pricing models with Lago’s prepaid credit features. 🔔 Stay up to date Lago launched its v0.1 on June 2nd, 2022. Lots of new features are coming, and are generally released on a bi-weekly basis. Watch updates of this repository to be notified of future updates. Check out our public roadmap 🔖 License Distributed under the AGPLv3 License. Read more here . 💻 Deploy locally Requirements Install Docker on your machine; Make sure Docker Compose is installed and available (it should be the case if you have chosen to install Docker via Docker Desktop); and Make sure Git is installed on your machine. Run the app To start using Lago, run the following commands in a shell: ``` Get the code git clone https://github.com/getlago/lago.git Go to Lago folder cd lago Set up environment configuration echo "LAGO_RSA_PRIVATE_KEY=\" openssl genrsa 2048 | base64 \"" >> .env source .env Start docker-compose up ``` You can now open your browser and go to http://localhost to connect to the application. Lago's API is exposed at http://localhost:3000. Note that if our docker server is not at http://localhost, the following env variables must be set: LAGO_API_URL . This may be on the command line or in your .env file. For example: LAGO_API_URL="http://192.168.122.71:3000" LAGO_FRONT_URL="http://192.168.122.71" Find your API key Your API Key can be found directly in the UI: Access the Developer section from the sidebar; The first tab of this section is related to your API keys ; and Click the Copy button to copy it to clipboard. Analytics and tracking Please note that Lago, by default, tracks basic actions performed on your self-hosted instance. If you do not disable tracking, you may receive specific communications or product updates. However, rest assured that Lago will not collect any personal information about your customers or financial information about your invoices. If you would like to know more about Lago's analytics or remove the entire tracking, please refer to this page for comprehensive information. Version, environment variables and components Docker images are always updated to the last stable version in the docker-compose.yml file. You can use a different tag if needed by checking the releases list. Lago uses the following environment variables to configure the components of the application. You can override them to customise your setup. Take a closer look are our documentation . ☁️ Use our cloud-based product Contact our team at hello@getlago.com to get started with Lago Cloud. More information on our website . 🚀 Getting the most out of Lago See the documentation to learn more about all the features; Use our templates to get inspiration and learn how to reproduce Algolia’s, Segment’s and Klaviyo’s pricing models; Join our Slack community if you need help, or want to chat, we’re here to help; Contribute on GitHub: read our guidelines ; Follow us on Twitter for the latest news; You can email us as well: hello@getlago.com. 🧑‍💻 Contributions and development environment You can follow this guide to set up a Lago development environment on your machine. This guide is intended for people willing to contribute to Lago. If you want to try Lago on your local system, we recommend that you take a look at Lago's public documentation. You can contribute by following our guidelines . 💡 Philosophy B2B SaaS has evolved, but billing has not yet. 1- We’re not in the “subscription economy” anymore. And we won’t go “full usage-based pricing” quite yet Pricings are now mostly hybrid: they include a usage-based component (i.e. “if you use more you pay more”) and a subscription component (i.e. a recurring fee for basic usage). Not all software companies will go full “usage-based” like Snowflake for instance. This model is the new standard for cloud infrastructure products. However, in other areas of SaaS, users want to know beforehand how much they will pay to control their spending and software companies want to be able to predict recurring revenues. 2- Go-to-market is not either bottom-up or top-down anymore SaaS used to be either self-service (SMBs) or sales-led (Enterprises). Go-to-market now mixes the self-service (all customers access the same price plans) and sales-led (customers get a custom quote from a sales representative) motions. A typical journey involves an individual contributor in a company who tests a new tool, puts their corporate credit card in, and starts spreading the use of the tool within the organization. At that point, the VP or head of department might want to upgrade to a custom plan tailored to the needs of the whole organization. As a result, billing needs to be flexible, automated, and transparent enough to embrace this hybrid go-to-market motion as well. 3- The “rent seeker” pricing of current billing solutions needs to stop Why do payment companies take a cut on revenues? Because the higher the amount, the higher the risk for them (e.g. fraud, disputes, etc.). Why did billing companies adopt the same pricing structure? We’re not able to provide an answer that makes sense. It’s been said on the internet that they did this because they could (read more here ). One last thing… Lago is agnostic and we aim at being as transparent as possible, so we won’t nudge or lock you into using a specific tool in exchange for using our billing API ( learn more ).

Open Source Metering and Usage Based Billing API ⭐️ Consumption tracking, Subscription management, Pricing iterations, Payment orchestration & Revenue analytics

billing,fintech,invoices,payments,usage-based-billing,subscriptions,metering,pricing,analytics,open-source

dunglas/frankenphp

FrankenPHP: Modern App Server for PHP FrankenPHP is a modern application server for PHP built on top of the Caddy web server. FrankenPHP gives superpowers to your PHP apps thanks to its stunning features: Early Hints , worker mode , real-time capabilities , automatic HTTPS, HTTP/2, and HTTP/3 support... FrankenPHP works with any PHP app and makes your Laravel and Symfony projects faster than ever thanks to their official integrations with the worker mode. FrankenPHP can also be used as a standalone Go library to embed PHP in any app using net/http . Learn more on frankenphp.dev and in this slide deck: Getting Started Docker console docker run -v $PWD:/app/public \ -p 80:80 -p 443:443 -p 443:443/udp \ dunglas/frankenphp Go to https://localhost , and enjoy! [!TIP] Do not attempt to use https://127.0.0.1 . Use https://localhost and accept the self-signed certificate. Use the SERVER_NAME environment variable to change the domain to use. Standalone Binary If you prefer not to use Docker, we provide standalone FrankenPHP binaries for Linux and macOS containing PHP 8.3 and most popular PHP extensions: Download FrankenPHP To serve the content of the current directory, run: console ./frankenphp php-server You can also run command-line scripts with: console ./frankenphp php-cli /path/to/your/script.php Docs The worker mode Early Hints support (103 HTTP status code) Real-time Configuration Docker images Deploy in production Create standalone , self-executable PHP apps Create static binaries Compile from sources Laravel integration Known issues Demo app (Symfony) and benchmarks Go library documentation Contributing and debugging Examples and Skeletons Symfony API Platform Laravel Sulu WordPress Drupal Joomla TYPO3

🧟 The modern PHP app server

caddy,go,php,sapi,worker,frankenphp

trickest/cve

CVE PoC Almost every publicly available CVE PoC. Current hottest CVEs | Title | URL | | ----------- | ----------- | | CVE-2022-0001 | /trickest/cve/blob/main/2022/CVE-2022-0001.md | | CVE-2022-25297 | /trickest/cve/blob/main/2022/CVE-2022-25297.md | | CVE-2022-1388 | /trickest/cve/blob/main/2022/CVE-2022-1388.md | | CVE-2022-25451 | /trickest/cve/blob/main/2022/CVE-2022-25451.md | To see the complete history go here How it works Trickest Workflow Architecture TB; DZ (Too big; didn't zoom): Collect CVE details from cvelist (Shout out to CVE Project !) Split CVEs up by year. Find PoCs for each CVE using 2 techniques: References Gather each CVE's References . Check if any of them points to a PoC using ffuf and a list of keywords Regex: (?i)[^a-z0-9]+(poc|proof of concept|proof[-_]of[-_]concept)[^a-z0-9]+ (Thanks @joohoi !) Note : ffuf is awesome for more purposes than just content discovery. Get CVE referenced in HackerOne Reports - AllVideoPocsFromHackerOne (Thanks @zeroc00I !) Github Search GitHub for repositories with find-gh-poc that mention the CVE ID. - Merge the fresh results into the repository without overwriting the data that was committed manually. - Filter false positives using blacklist.txt . - Merge all of the found PoCs. - Generate GitHub badges for each affected software version using shields.io . - Write everything into easy-to-read markdown files. As described, almost everything in this repository is generated automatically. We carefully designed the workflow (and continue to develop it) to ensure the results are as accurate as possible. Use cases Browse around, find a nice PoC, and test away! Watch the repository to receive notifications about new PoCs as soon as they go public. Search for a specific product(s) (and possibly version) to find all public exploits related to it. Monitor the atom feed for a specific product(s). Create a searchable HTML table using the template and script in summary_html Example: https://www.andrewmohawk.com/cve_summary (Thanks @AndrewMohawk !) Contribution All contribtutions/ideas/suggestions are welcome! Create a new ticket via GitHub issues or tweet at us @trick3st . Build your own workflows We believe in the value of tinkering; cookie-cutter solutions rarely cut it. Sign up for a Trickest demo to customize this workflow to your use case, get access to many more workflows, or build your own workflows from scratch!

Gather and update all available and newest CVEs with their PoC.

poc,cve,cve-poc,latest-cve,vulnerability,vulnerabilities,software-vulnerabilities,software-security,exploit,security

dair-ai/ML-Course-Notes

🎓 Machine Learning Course Notes A place to collaborate and share lecture notes on all topics related to machine learning, NLP, and AI. WIP denotes work in progress. Machine Learning Specialization (2022) Website | Instructor: Andrew Ng Lecture Description Video Notes Author Introduction to Machine Learning Supervised Machine Learning: Regression and Classification Videos Notes Elvis Advanced Learning Algorithms Advanced Learning Algorithms Videos WIP Elvis Unsupervised Learning, Recommenders, Reinforcement Learning Unsupervised Learning, Recommenders, Reinforcement Learning Videos WIP Elvis MIT 6.S191 Introduction to Deep Learning (2022) Website | Lectures by: Alexander Amini and Ava Soleimany Lecture Description Video Notes Author Introduction to Deep Learning Basic fundamentals of neural networks and deep learning. Video Notes Elvis RNNs and Transformers Introduction to recurrent neural networks and transformers. Video Notes Elvis Deep Computer Vision Deep Neural Networks for Computer Vision. Video Notes Elvis Deep Generative Modeling Autoencoders and GANs. Video Notes Elvis Deep Reinforcement Learning Deep RL key concepts and DQNs. Video Notes Elvis CMU Neural Nets for NLP (2021) Website | Instructor: Graham Neubig Lecture Description Video Notes Author Introduction to Simple Neural Networks for NLP Provides an introduction to neural networks for NLP covering concepts like BOW, CBOW, and Deep CBOW Video Notes Elvis CS224N: Natural Language Processing with Deep Learning (2022) Website | Instructor: C‪hristopher Manning Lecture Description Video Notes Author Introduction and Word Vectors Introduction to NLP and Word Vectors. Video Notes Elvis Neural Classifiers Neural Classifiers for NLP. Video WIP Elvis CS25: Transformers United Website | Instructors: Div Garg, Chetanya Rastogi, Advay Pal Lecture Description Video Notes Author Introduction to Transformers A short summary of attention and Transformers. Video Notes Elvis Transformers in Language: GPT-3, Codex The development of GPT Models including GPT3. Video WIP Elvis Neural Networks: Zero to Hero Lectures | Instructors: Andrej Karpathy Lecture Description Video Notes Author Let's build GPT: from scratch, in code, spelled out Detailed walkthrough of GPT Video WIP Elvis Miscellaneous Lectures Lecture Description Video Notes Author Introduction to Diffusion Models Technical overview of Diffusion Models Video WIP Elvis Reinforcement Learning from Human Feedback (RLHF) Overview of RLHF Video WIP Elvis How To Contribute 1) Identify a course and lecture from this list . If you are working on notes for a lecture, please indicate by opening an issue. This avoids duplicate work. 2) Write your notes, preferably in a Google document, Notion document, or GitHub repo. 3) We care about quality, so make sure to revise your notes before submitting. 4) Once you are finished, open a PR here. If you have any questions, open an issue or reach out to me on Twitter . Join our Discord .

🎓 Sharing machine learning course / lecture notes.

machine-learning,deep-learning,ai,natural-language-processing,data-science

aptos-labs/aptos-core

Aptos is a layer 1 blockchain bringing a paradigm shift to Web3 through better technology and user experience. Built with Move to create a home for developers building next-gen applications. Getting Started Aptos Foundation Aptos Developer Network Guide - Integrate with the Aptos Blockchain Tutorials Follow us on Twitter . Join us on the Aptos Discord . Contributing You can learn more about contributing to the Aptos project by reading our Contribution Guide and by viewing our Code of Conduct . Aptos Core is licensed under Apache 2.0 .

Aptos is a layer 1 blockchain built to support the widespread use of blockchain through better technology and user experience.

blockchain,blockchain-network,move,smart-contracts,aptos

TypeCellOS/BlockNote

Welcome to BlockNote! The open source Block-Based React rich text editor. Easily add a modern text editing experience to your app. Homepage - Documentation - Quickstart - Examples Live demo See our homepage @ https://www.blocknotejs.org or browse the examples . Example code (React) ```typescript import { useCreateBlockNote } from "@blocknote/react"; import { BlockNoteView } from "@blocknote/mantine"; import "@blocknote/core/fonts/inter.css"; import "@blocknote/mantine/style.css"; function App() { const editor = useCreateBlockNote(); return ; } ``` @blocknote/react comes with a fully styled UI that makes it an instant, polished editor ready to use in your app. If you prefer to create your own UI components (menus), or don't want to use React, you can use @blocknote/core ( advanced , see docs ). Features BlockNote comes with a number of features and components to make it easy to embed a high-quality block-based editor in your app: Animations: Helpful placeholders: Drag and drop blocks: Nesting / indentation with tab and shift+tab: Slash (/) menu: Format menu: Real-time collaboration: Feedback 🙋‍♂️🙋‍♀️ We'd love to hear your thoughts and see your experiments, so come and say hi on Discord or Matrix . Contributing 🙌 See CONTRIBUTING.md for more info and guidance on how to run the project (TLDR: just use npm start ). Directory structure: blocknote ├── packages/core - The core of the editor ├── packages/react - The main library for use in React apps ├── packages/mantine - Mantine (default) implementation of BlockNote UI ├── packages/ariakit - AriaKit implementation of BlockNote UI ├── packages/shadcn - ShadCN / Tailwind / Radix implementation of BlockNote UI ├── examples - Example apps ├── playground - App to browse the example apps (https://playground.blocknotejs.org) └── tests - Playwright end to end tests The codebase is automatically tested using Vitest and Playwright. License 📃 BlockNote is licensed under the MPL 2.0 license , which allows you to use BlockNote in commercial (and closed-source) applications. If you make changes to the BlockNote source files, you're expected to publish these changes so the wider community can benefit as well. Credits ❤️ BlockNote builds directly on two awesome projects; Prosemirror by Marijn Haverbeke and Tiptap . Consider sponsoring those libraries when using BlockNote: Prosemirror , Tiptap . BlockNote is built as part of TypeCell . TypeCell is proudly sponsored by the renowned NLNet foundation who are on a mission to support an open internet, and protect the privacy and security of internet users. Check them out! Hosting and deployments powered by Vercel:

A React Rich Text Editor that's block-based (Notion style) and extensible. Built on top of Prosemirror and Tiptap.

block-based,editor,javascript,notion,prosemirror,react,rich-text-editor,tiptap,typescript,wysiwyg

shuttle-hq/shuttle

Fastest Way to Build & Ship Rust Apps Get resources and deploy your apps with a few lines of code. Simple.   Easy.   Joyful. Report Bug · Request a Feature · Join Our Discord · Follow us on Twitter ⭐ If you find Shuttle interesting, consider starring this repo to help spread the word. Features One-line Resource Provisioning: Get a database, or any other AWS resource by adding a line of code to your main file. To delete one, just remove that line of code. No config/yaml files required. Rapid Development: It takes 2 minutes from project initialization to a deployed project. It takes another 2 minutes to provision a resource, and get it deployed to production. First-class support for popular Rust frameworks: Axum , Actix Web , Rocket , and more Security: Let us worry about the security & permissions while you focus on writing good code. Quick Start On Linux and macOS, you can use this install script, which will automatically install the correct target for your OS and distro: sh curl -sSfL https://www.shuttle.rs/install | bash On Windows, you can use this install script to do the same: powershell iwr "https://www.shuttle.rs/install-win" | iex After installing, log in with: sh cargo shuttle login To initialize your project, simply write: bash cargo shuttle init --template axum hello-world And to deploy it, write: bash cd hello-world cargo shuttle project start # Only needed if project has not already been created during init cargo shuttle deploy --allow-dirty And... that's it! text Service Name: hello-world Deployment ID: 3d08ac34-ad63-41c1-836b-99afdc90af9f Status: running Last Updated: 2022-04-01T08:32:34Z URI: https://hello-world.shuttleapp.rs Feel free to build on top of the generated hello-world boilerplate or take a stab at one of our examples . For the full documentation, visit our docs . Quick Look Below is a basic "Hello World" application written in Axum: ```rust use axum::{routing::get, Router}; [tokio::main] async fn main() { let app = Router::new().route("/", get(hello_world)); let listener = tokio::net::TcpListener::bind("127.0.0.1:3000") .await .unwrap(); println!("listening on {}", listener.local_addr().unwrap()); axum::serve(listener, app).await.unwrap(); } async fn hello_world() -> &'static str { "Hello, world!" } ``` In order to be able to deploy it with a single command, we update the snippet as follows: ```rust use axum::{routing::get, Router}; async fn hello_world() -> &'static str { "Hello, world!" } [shuttle_runtime::main] async fn main() -> shuttle_axum::ShuttleAxum { let router = Router::new().route("/", get(hello_world)); Ok(router.into()) } ``` Now, with just cargo shuttle deploy , you can see your application live. But let's enhance it further by adding a shared Postgres database: ```rust use axum::{routing::get, Router}; async fn hello_world() -> &'static str { "Hello, world!" } [shuttle_runtime::main] async fn main( #[shuttle_shared_db::Postgres] pool: sqlx::PgPool, ) -> shuttle_axum::ShuttleAxum { pool.execute(include_str!("../schema.sql")) .await .expect("failed to run migrations"); let router = Router::new().route("/", get(hello_world)); Ok(router.into()) } ``` Now, if we run cargo shuttle deploy , we'll have an up and running project with a database inside & ready to use. Repositories | Name | Description | |-|-| | shuttle 🚀 (This repo) | The core Shuttle product. Contains all crates that users interact with. | | shuttle-examples 👨‍🏫 | Officially maintained examples of projects that can be deployed on Shuttle. Also has a list of community examples . | | shuttle-docs 📃 | Documentation hosted on docs.shuttle.rs . | | www 🌍 | Our website shuttle.rs , including the blog and Launchpad newsletter . | | deploy-action ⚙ | GitHub Action for continuous deployments. | | awesome-shuttle 🌟 | An awesome list of Shuttle-hosted projects and resources that users can add to. | | shuttlings ⚔️ | A collection of Rust code challenges. A great way to get started with using Rust and Shuttle. | Contributing to Shuttle Contributing to Shuttle is highly encouraged! Even if you are not planning to submit any code, joining our Discord server and providing feedback helps us a lot! Check out our contributing docs and find the appropriate repo above to contribute to. For development of this repo, check the development docs . Algora Bounties 💰 To offload work from the engineering team on low-priority issues, we will sometimes add a cash bounty to issues. Sign up to the Algora Console to find open issues with bounties. Project Status Check for any outages and incidents on Shuttle Status . We are currently in Public Beta. Watch "releases" of this repo to get notified of major updates! Also, check out the Beta announcement for features we are looking forward to. [x] Alpha: We are testing Shuttle, API and deployments may be unstable [x] Public Alpha: Anyone can sign up, but go easy on us, there are a few kinks [x] Public Beta: Stable enough for most non-enterprise use-cases [ ] Public: Production-ready! Contributors ✨ Thanks goes to these wonderful people: Made with contrib.rocks .

Build & ship backends without writing any infrastructure files.

rust,framework,web,web-framework,deployment,paas,devops,baas

postgresml/postgresml

Postgres ML Generative AI and Simple ML with PostgreSQL Table of contents Introduction Installation Getting started Natural Language Processing Text Classification Zero-Shot Classification Token Classification Translation Summarization Question Answering Text Generation Text-to-Text Generation Fill-Mask Vector Database LLM Fine-tuning Text Classification - 2 classes Text Classification - 9 classes Conversation Introduction PostgresML is a machine learning extension for PostgreSQL that enables you to perform training and inference on text and tabular data using SQL queries. With PostgresML, you can seamlessly integrate machine learning models into your PostgreSQL database and harness the power of cutting-edge algorithms to process data efficiently. Text Data Perform natural language processing (NLP) tasks like sentiment analysis, question and answering, translation, summarization and text generation Access 1000s of state-of-the-art language models like GPT-2, GPT-J, GPT-Neo from :hugs: HuggingFace model hub Fine tune large language models (LLMs) on your own text data for different tasks Use your existing PostgreSQL database as a vector database by generating embeddings from text stored in the database. Translation SQL query postgresql SELECT pgml.transform( 'translation_en_to_fr', inputs => ARRAY[ 'Welcome to the future!', 'Where have you been all this time?' ] ) AS french; Result ```postgresql french [ {"translation_text": "Bienvenue à l'avenir!"}, {"translation_text": "Où êtes-vous allé tout ce temps?"} ] ``` Sentiment Analysis SQL query postgresql SELECT pgml.transform( task => 'text-classification', inputs => ARRAY[ 'I love how amazingly simple ML has become!', 'I hate doing mundane and thankless tasks. ☹️' ] ) AS positivity; Result ```postgresql positivity [ {"label": "POSITIVE", "score": 0.9995759129524232}, {"label": "NEGATIVE", "score": 0.9903519749641418} ] ``` Tabular data 47+ classification and regression algorithms 8 - 40X faster inference than HTTP based model serving Millions of transactions per second Horizontal scalability Training a classification model Training postgresql SELECT * FROM pgml.train( 'Handwritten Digit Image Classifier', algorithm => 'xgboost', 'classification', 'pgml.digits', 'target' ); Inference postgresql SELECT pgml.predict( 'My Classification Project', ARRAY[0.1, 2.0, 5.0] ) AS prediction; Installation PostgresML installation consists of three parts: PostgreSQL database, Postgres extension for machine learning and a dashboard app. The extension provides all the machine learning functionality and can be used independently using any SQL IDE. The dashboard app provides an easy to use interface for writing SQL notebooks, performing and tracking ML experiments and ML models. Serverless Cloud If you want to check out the functionality without the hassle of Docker, sign up for a free PostgresML account . You'll get a free database in seconds, with access to GPUs and state of the art LLMs. Docker docker run \ -it \ -v postgresml_data:/var/lib/postgresql \ -p 5433:5432 \ -p 8000:8000 \ ghcr.io/postgresml/postgresml:2.7.12 \ sudo -u postgresml psql -d postgresml For more details, take a look at our Quick Start with Docker documentation. Getting Started Option 1 On the cloud console click on the Dashboard button to connect to your instance with a SQL notebook, or connect directly with tools listed below. On local installation, go to dashboard app at http://localhost:8000/ to use SQL notebooks. Option 2 Use any of these popular tools to connect to PostgresML and write SQL queries Apache Superset DBeaver Data Grip Postico 2 Popsql Tableau PowerBI Jupyter VSCode Option 3 Connect directly to the database with your favorite programming language C++: libpqxx C#: Npgsql , Dapper , or Entity Framework Core Elixir: ecto or Postgrex Go: pgx , pg or Bun Haskell: postgresql-simple Java & Scala: JDBC or Slick Julia: LibPQ.jl Lua: pgmoon Node: node-postgres , pg-promise , or Sequelize Perl: DBD::Pg PHP: Laravel or PHP Python: psycopg2 , SQLAlchemy , or Django R: DBI or dbx Ruby: pg or Rails Rust: postgres , SQLx or Diesel Swift: PostgresNIO or PostgresClientKit ... open a PR to add your favorite language and connector. NLP Tasks PostgresML integrates 🤗 Hugging Face Transformers to bring state-of-the-art NLP models into the data layer. There are tens of thousands of pre-trained models with pipelines to turn raw text in your database into useful results. Many state of the art deep learning architectures have been published and made available from Hugging Face model hub . You can call different NLP tasks and customize using them using the following SQL query. postgresql SELECT pgml.transform( task => TEXT OR JSONB, -- Pipeline initializer arguments inputs => TEXT[] OR BYTEA[], -- inputs for inference args => JSONB -- (optional) arguments to the pipeline. ) Text Classification Text classification involves assigning a label or category to a given text. Common use cases include sentiment analysis, natural language inference, and the assessment of grammatical correctness. Sentiment Analysis Sentiment analysis is a type of natural language processing technique that involves analyzing a piece of text to determine the sentiment or emotion expressed within it. It can be used to classify a text as positive, negative, or neutral, and has a wide range of applications in fields such as marketing, customer service, and political analysis. Basic usage postgresql SELECT pgml.transform( task => 'text-classification', inputs => ARRAY[ 'I love how amazingly simple ML has become!', 'I hate doing mundane and thankless tasks. ☹️' ] ) AS positivity; Result json [ {"label": "POSITIVE", "score": 0.9995759129524232}, {"label": "NEGATIVE", "score": 0.9903519749641418} ] The default model used for text classification is a fine-tuned version of DistilBERT-base-uncased that has been specifically optimized for the Stanford Sentiment Treebank dataset (sst2). Using specific model To use one of the over 19,000 models available on Hugging Face, include the name of the desired model and text-classification task as a JSONB object in the SQL query. For example, if you want to use a RoBERTa model trained on around 40,000 English tweets and that has POS (positive), NEG (negative), and NEU (neutral) labels for its classes, include this information in the JSONB object when making your query. postgresql SELECT pgml.transform( inputs => ARRAY[ 'I love how amazingly simple ML has become!', 'I hate doing mundane and thankless tasks. ☹️' ], task => '{"task": "text-classification", "model": "finiteautomata/bertweet-base-sentiment-analysis" }'::JSONB ) AS positivity; Result json [ {"label": "POS", "score": 0.992932200431826}, {"label": "NEG", "score": 0.975599765777588} ] Using industry specific model By selecting a model that has been specifically designed for a particular industry, you can achieve more accurate and relevant text classification. An example of such a model is FinBERT , a pre-trained NLP model that has been optimized for analyzing sentiment in financial text. FinBERT was created by training the BERT language model on a large financial corpus, and fine-tuning it to specifically classify financial sentiment. When using FinBERT, the model will provide softmax outputs for three different labels: positive, negative, or neutral. postgresql SELECT pgml.transform( inputs => ARRAY[ 'Stocks rallied and the British pound gained.', 'Stocks making the biggest moves midday: Nvidia, Palantir and more' ], task => '{"task": "text-classification", "model": "ProsusAI/finbert" }'::JSONB ) AS market_sentiment; Result json [ {"label": "positive", "score": 0.8983612656593323}, {"label": "neutral", "score": 0.8062630891799927} ] Natural Language Inference (NLI) NLI, or Natural Language Inference, is a type of model that determines the relationship between two texts. The model takes a premise and a hypothesis as inputs and returns a class, which can be one of three types: - Entailment: This means that the hypothesis is true based on the premise. - Contradiction: This means that the hypothesis is false based on the premise. - Neutral: This means that there is no relationship between the hypothesis and the premise. The GLUE dataset is the benchmark dataset for evaluating NLI models. There are different variants of NLI models, such as Multi-Genre NLI, Question NLI, and Winograd NLI. If you want to use an NLI model, you can find them on the :hugs: Hugging Face model hub. Look for models with "mnli". postgresql SELECT pgml.transform( inputs => ARRAY[ 'A soccer game with multiple males playing. Some men are playing a sport.' ], task => '{"task": "text-classification", "model": "roberta-large-mnli" }'::JSONB ) AS nli; Result json [ {"label": "ENTAILMENT", "score": 0.98837411403656} ] Question Natural Language Inference (QNLI) The QNLI task involves determining whether a given question can be answered by the information in a provided document. If the answer can be found in the document, the label assigned is "entailment". Conversely, if the answer cannot be found in the document, the label assigned is "not entailment". If you want to use an QNLI model, you can find them on the :hugs: Hugging Face model hub. Look for models with "qnli". postgresql SELECT pgml.transform( inputs => ARRAY[ 'Where is the capital of France?, Paris is the capital of France.' ], task => '{"task": "text-classification", "model": "cross-encoder/qnli-electra-base" }'::JSONB ) AS qnli; Result json [ {"label": "LABEL_0", "score": 0.9978110194206238} ] Quora Question Pairs (QQP) The Quora Question Pairs model is designed to evaluate whether two given questions are paraphrases of each other. This model takes the two questions and assigns a binary value as output. LABEL_0 indicates that the questions are paraphrases of each other and LABEL_1 indicates that the questions are not paraphrases. The benchmark dataset used for this task is the Quora Question Pairs dataset within the GLUE benchmark, which contains a collection of question pairs and their corresponding labels. If you want to use an QQP model, you can find them on the :hugs: Hugging Face model hub. Look for models with qqp . postgresql SELECT pgml.transform( inputs => ARRAY[ 'Which city is the capital of France?, Where is the capital of France?' ], task => '{"task": "text-classification", "model": "textattack/bert-base-uncased-QQP" }'::JSONB ) AS qqp; Result json [ {"label": "LABEL_0", "score": 0.9988721013069152} ] Grammatical Correctness Linguistic Acceptability is a task that involves evaluating the grammatical correctness of a sentence. The model used for this task assigns one of two classes to the sentence, either "acceptable" or "unacceptable". LABEL_0 indicates acceptable and LABEL_1 indicates unacceptable. The benchmark dataset used for training and evaluating models for this task is the Corpus of Linguistic Acceptability (CoLA), which consists of a collection of texts along with their corresponding labels. If you want to use a grammatical correctness model, you can find them on the :hugs: Hugging Face model hub. Look for models with cola . postgresql SELECT pgml.transform( inputs => ARRAY[ 'I will walk to home when I went through the bus.' ], task => '{"task": "text-classification", "model": "textattack/distilbert-base-uncased-CoLA" }'::JSONB ) AS grammatical_correctness; Result json [ {"label": "LABEL_1", "score": 0.9576480388641356} ] Zero-Shot Classification Zero Shot Classification is a task where the model predicts a class that it hasn't seen during the training phase. This task leverages a pre-trained language model and is a type of transfer learning. Transfer learning involves using a model that was initially trained for one task in a different application. Zero Shot Classification is especially helpful when there is a scarcity of labeled data available for the specific task at hand. In the example provided below, we will demonstrate how to classify a given sentence into a class that the model has not encountered before. To achieve this, we make use of args in the SQL query, which allows us to provide candidate_labels . You can customize these labels to suit the context of your task. We will use facebook/bart-large-mnli model. Look for models with mnli to use a zero-shot classification model on the :hugs: Hugging Face model hub. postgresql SELECT pgml.transform( inputs => ARRAY[ 'I have a problem with my iphone that needs to be resolved asap!!' ], task => '{ "task": "zero-shot-classification", "model": "facebook/bart-large-mnli" }'::JSONB, args => '{ "candidate_labels": ["urgent", "not urgent", "phone", "tablet", "computer"] }'::JSONB ) AS zero_shot; Result json [ { "labels": ["urgent", "phone", "computer", "not urgent", "tablet"], "scores": [0.503635, 0.47879, 0.012600, 0.002655, 0.002308], "sequence": "I have a problem with my iphone that needs to be resolved asap!!" } ] Token Classification Token classification is a task in natural language understanding, where labels are assigned to certain tokens in a text. Some popular subtasks of token classification include Named Entity Recognition (NER) and Part-of-Speech (PoS) tagging. NER models can be trained to identify specific entities in a text, such as individuals, places, and dates. PoS tagging, on the other hand, is used to identify the different parts of speech in a text, such as nouns, verbs, and punctuation marks. Named Entity Recognition Named Entity Recognition (NER) is a task that involves identifying named entities in a text. These entities can include the names of people, locations, or organizations. The task is completed by labeling each token with a class for each named entity and a class named "0" for tokens that don't contain any entities. In this task, the input is text, and the output is the annotated text with named entities. postgresql SELECT pgml.transform( inputs => ARRAY[ 'I am Omar and I live in New York City.' ], task => 'token-classification' ) as ner; Result json [[ {"end": 9, "word": "Omar", "index": 3, "score": 0.997110, "start": 5, "entity": "I-PER"}, {"end": 27, "word": "New", "index": 8, "score": 0.999372, "start": 24, "entity": "I-LOC"}, {"end": 32, "word": "York", "index": 9, "score": 0.999355, "start": 28, "entity": "I-LOC"}, {"end": 37, "word": "City", "index": 10, "score": 0.999431, "start": 33, "entity": "I-LOC"} ]] Part-of-Speech (PoS) Tagging PoS tagging is a task that involves identifying the parts of speech, such as nouns, pronouns, adjectives, or verbs, in a given text. In this task, the model labels each word with a specific part of speech. Look for models with pos to use a zero-shot classification model on the :hugs: Hugging Face model hub. postgresql select pgml.transform( inputs => array [ 'I live in Amsterdam.' ], task => '{"task": "token-classification", "model": "vblagoje/bert-english-uncased-finetuned-pos" }'::JSONB ) as pos; Result json [[ {"end": 1, "word": "i", "index": 1, "score": 0.999, "start": 0, "entity": "PRON"}, {"end": 6, "word": "live", "index": 2, "score": 0.998, "start": 2, "entity": "VERB"}, {"end": 9, "word": "in", "index": 3, "score": 0.999, "start": 7, "entity": "ADP"}, {"end": 19, "word": "amsterdam", "index": 4, "score": 0.998, "start": 10, "entity": "PROPN"}, {"end": 20, "word": ".", "index": 5, "score": 0.999, "start": 19, "entity": "PUNCT"} ]] Translation Translation is the task of converting text written in one language into another language. You have the option to select from over 2000 models available on the Hugging Face hub for translation. postgresql select pgml.transform( inputs => array[ 'How are you?' ], task => '{"task": "translation", "model": "Helsinki-NLP/opus-mt-en-fr" }'::JSONB ); Result json [ {"translation_text": "Comment allez-vous ?"} ] Summarization Summarization involves creating a condensed version of a document that includes the important information while reducing its length. Different models can be used for this task, with some models extracting the most relevant text from the original document, while other models generate completely new text that captures the essence of the original content. postgresql select pgml.transform( task => '{"task": "summarization", "model": "sshleifer/distilbart-cnn-12-6" }'::JSONB, inputs => array[ 'Paris is the capital and most populous city of France, with an estimated population of 2,175,601 residents as of 2018, in an area of more than 105 square kilometres (41 square miles). The City of Paris is the centre and seat of government of the region and province of Île-de-France, or Paris Region, which has an estimated population of 12,174,880, or about 18 percent of the population of France as of 2017.' ] ); Result json [ {"summary_text": " Paris is the capital and most populous city of France, with an estimated population of 2,175,601 residents as of 2018 . The city is the centre and seat of government of the region and province of Île-de-France, or Paris Region . Paris Region has an estimated 18 percent of the population of France as of 2017 ."} ] You can control the length of summary_text by passing min_length and max_length as arguments to the SQL query. postgresql select pgml.transform( task => '{"task": "summarization", "model": "sshleifer/distilbart-cnn-12-6" }'::JSONB, inputs => array[ 'Paris is the capital and most populous city of France, with an estimated population of 2,175,601 residents as of 2018, in an area of more than 105 square kilometres (41 square miles). The City of Paris is the centre and seat of government of the region and province of Île-de-France, or Paris Region, which has an estimated population of 12,174,880, or about 18 percent of the population of France as of 2017.' ], args => '{ "min_length" : 20, "max_length" : 70 }'::JSONB ); json [ {"summary_text": " Paris is the capital and most populous city of France, with an estimated population of 2,175,601 residents as of 2018 . City of Paris is centre and seat of government of the region and province of Île-de-France, or Paris Region, which has an estimated 12,174,880, or about 18 percent" } ] Question Answering Question Answering models are designed to retrieve the answer to a question from a given text, which can be particularly useful for searching for information within a document. It's worth noting that some question answering models are capable of generating answers even without any contextual information. postgresql SELECT pgml.transform( 'question-answering', inputs => ARRAY[ '{ "question": "Where do I live?", "context": "My name is Merve and I live in İstanbul." }' ] ) AS answer; Result json { "end" : 39, "score" : 0.9538117051124572, "start" : 31, "answer": "İstanbul" } Text Generation Text generation is the task of producing new text, such as filling in incomplete sentences or paraphrasing existing text. It has various use cases, including code generation and story generation. Completion generation models can predict the next word in a text sequence, while text-to-text generation models are trained to learn the mapping between pairs of texts, such as translating between languages. Popular models for text generation include GPT-based models, T5, T0, and BART. These models can be trained to accomplish a wide range of tasks, including text classification, summarization, and translation. postgresql SELECT pgml.transform( task => 'text-generation', inputs => ARRAY[ 'Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone' ] ) AS answer; Result json [ [ {"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, and eight for the Dragon-lords in their halls of blood.\n\nEach of the guild-building systems is one-man"} ] ] To use a specific model from :hugs: model hub, pass the model name along with task name in task. postgresql SELECT pgml.transform( task => '{ "task" : "text-generation", "model" : "gpt2-medium" }'::JSONB, inputs => ARRAY[ 'Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone' ] ) AS answer; Result json [ [{"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone.\n\nThis place has a deep connection to the lore of ancient Elven civilization. It is home to the most ancient of artifacts,"}] ] To make the generated text longer, you can include the argument max_length and specify the desired maximum length of the text. postgresql SELECT pgml.transform( task => '{ "task" : "text-generation", "model" : "gpt2-medium" }'::JSONB, inputs => ARRAY[ 'Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone' ], args => '{ "max_length" : 200 }'::JSONB ) AS answer; Result json [ [{"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, Three for the Dwarfs and the Elves, One for the Gnomes of the Mines, and Two for the Elves of Dross.\"\n\nHobbits: The Fellowship is the first book of J.R.R. Tolkien's story-cycle, and began with his second novel - The Two Towers - and ends in The Lord of the Rings.\n\n\nIt is a non-fiction novel, so there is no copyright claim on some parts of the story but the actual text of the book is copyrighted by author J.R.R. Tolkien.\n\n\nThe book has been classified into two types: fantasy novels and children's books\n\nHobbits: The Fellowship is the first book of J.R.R. Tolkien's story-cycle, and began with his second novel - The Two Towers - and ends in The Lord of the Rings.It"}] ] If you want the model to generate more than one output, you can specify the number of desired output sequences by including the argument num_return_sequences in the arguments. postgresql SELECT pgml.transform( task => '{ "task" : "text-generation", "model" : "gpt2-medium" }'::JSONB, inputs => ARRAY[ 'Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone' ], args => '{ "num_return_sequences" : 3 }'::JSONB ) AS answer; Result json [ [ {"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, and Thirteen for the human-men in their hall of fire.\n\nAll of us, our families, and our people"}, {"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, and the tenth for a King! As each of these has its own special story, so I have written them into the game."}, {"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone… What's left in the end is your heart's desire after all!\n\nHans: (Trying to be brave)"} ] ] Text generation typically utilizes a greedy search algorithm that selects the word with the highest probability as the next word in the sequence. However, an alternative method called beam search can be used, which aims to minimize the possibility of overlooking hidden high probability word combinations. Beam search achieves this by retaining the num_beams most likely hypotheses at each step and ultimately selecting the hypothesis with the highest overall probability. We set num_beams > 1 and early_stopping=True so that generation is finished when all beam hypotheses reached the EOS token. postgresql SELECT pgml.transform( task => '{ "task" : "text-generation", "model" : "gpt2-medium" }'::JSONB, inputs => ARRAY[ 'Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone' ], args => '{ "num_beams" : 5, "early_stopping" : true }'::JSONB ) AS answer; Result json [[ {"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, Nine for the Dwarves in their caverns of ice, Ten for the Elves in their caverns of fire, Eleven for the"} ]] Sampling methods involve selecting the next word or sequence of words at random from the set of possible candidates, weighted by their probabilities according to the language model. This can result in more diverse and creative text, as well as avoiding repetitive patterns. In its most basic form, sampling means randomly picking the next word $w_t$ according to its conditional probability distribution: $$ w_t \approx P(w_t|w_{1:t-1})$$ However, the randomness of the sampling method can also result in less coherent or inconsistent text, depending on the quality of the model and the chosen sampling parameters such as temperature, top-k, or top-p. Therefore, choosing an appropriate sampling method and parameters is crucial for achieving the desired balance between creativity and coherence in generated text. You can pass do_sample = True in the arguments to use sampling methods. It is recommended to alter temperature or top_p but not both. Temperature postgresql SELECT pgml.transform( task => '{ "task" : "text-generation", "model" : "gpt2-medium" }'::JSONB, inputs => ARRAY[ 'Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone' ], args => '{ "do_sample" : true, "temperature" : 0.9 }'::JSONB ) AS answer; Result json [[{"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, and Thirteen for the Giants and Men of S.A.\n\nThe First Seven-Year Time-Traveling Trilogy is"}]] Top p postgresql SELECT pgml.transform( task => '{ "task" : "text-generation", "model" : "gpt2-medium" }'::JSONB, inputs => ARRAY[ 'Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone' ], args => '{ "do_sample" : true, "top_p" : 0.8 }'::JSONB ) AS answer; Result json [[{"generated_text": "Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, Four for the Elves of the forests and fields, and Three for the Dwarfs and their warriors.\" ―Lord Rohan [src"}]] Text-to-Text Generation Text-to-text generation methods, such as T5, are neural network architectures designed to perform various natural language processing tasks, including summarization, translation, and question answering. T5 is a transformer-based architecture pre-trained on a large corpus of text data using denoising autoencoding. This pre-training process enables the model to learn general language patterns and relationships between different tasks, which can be fine-tuned for specific downstream tasks. During fine-tuning, the T5 model is trained on a task-specific dataset to learn how to perform the specific task. Translation postgresql SELECT pgml.transform( task => '{ "task" : "text2text-generation" }'::JSONB, inputs => ARRAY[ 'translate from English to French: I''m very happy' ] ) AS answer; Result json [ {"generated_text": "Je suis très heureux"} ] Similar to other tasks, we can specify a model for text-to-text generation. ```postgresql SELECT pgml.transform( task => '{ "task" : "text2text-generation", "model" : "bigscience/T0" }'::JSONB, inputs => ARRAY[ 'Is the word ''table'' used in the same meaning in the two previous sentences? Sentence A: you can leave the books on the table over there. Sentence B: the tables in this book are very hard to read.' ] ) AS answer; ``` Fill-Mask Fill-mask refers to a task where certain words in a sentence are hidden or "masked", and the objective is to predict what words should fill in those masked positions. Such models are valuable when we want to gain statistical insights about the language used to train the model. ```postgresql SELECT pgml.transform( task => '{ "task" : "fill-mask" }'::JSONB, inputs => ARRAY[ 'Paris is the of France.' ] ) AS answer; *Result* json [ {"score": 0.679, "token": 812, "sequence": "Paris is the capital of France.", "token_str": " capital"}, {"score": 0.051, "token": 32357, "sequence": "Paris is the birthplace of France.", "token_str": " birthplace"}, {"score": 0.038, "token": 1144, "sequence": "Paris is the heart of France.", "token_str": " heart"}, {"score": 0.024, "token": 29778, "sequence": "Paris is the envy of France.", "token_str": " envy"}, {"score": 0.022, "token": 1867, "sequence": "Paris is the Capital of France.", "token_str": " Capital"}] ``` Vector Database A vector database is a type of database that stores and manages vectors, which are mathematical representations of data points in a multi-dimensional space. Vectors can be used to represent a wide range of data types, including images, text, audio, and numerical data. It is designed to support efficient searching and retrieval of vectors, using methods such as nearest neighbor search, clustering, and indexing. These methods enable applications to find vectors that are similar to a given query vector, which is useful for tasks such as image search, recommendation systems, and natural language processing. PostgresML enhances your existing PostgreSQL database to be used as a vector database by generating embeddings from text stored in your tables. To generate embeddings, you can use the pgml.embed function, which takes a transformer name and a text value as input. This function automatically downloads and caches the transformer for future reuse, which saves time and resources. Using a vector database involves three key steps: creating embeddings, indexing your embeddings using different algorithms, and querying the index using embeddings for your queries. Let's break down each step in more detail. Step 1: Creating embeddings using transformers To create embeddings for your data, you first need to choose a transformer that can generate embeddings from your input data. Some popular transformer options include BERT, GPT-2, and T5. Once you've selected a transformer, you can use it to generate embeddings for your data. In the following section, we will demonstrate how to use PostgresML to generate embeddings for a dataset of tweets commonly used in sentiment analysis. To generate the embeddings, we will use the pgml.embed function, which will generate an embedding for each tweet in the dataset. These embeddings will then be inserted into a table called tweet_embeddings. ```postgresql SELECT pgml.load_dataset('tweet_eval', 'sentiment'); SELECT * FROM pgml.tweet_eval LIMIT 10; CREATE TABLE tweet_embeddings AS SELECT text, pgml.embed('distilbert-base-uncased', text) AS embedding FROM pgml.tweet_eval; SELECT * from tweet_embeddings limit 2; ``` Result |text|embedding| |----|---------| |"QT @user In the original draft of the 7th book, Remus Lupin survived the Battle of Hogwarts. #HappyBirthdayRemusLupin"|{-0.1567948312,-0.3149209619,0.2163394839,..}| |"Ben Smith / Smith (concussion) remains out of the lineup Thursday, Curtis #NHL #SJ"|{-0.0701668188,-0.012231146,0.1304316372,.. }| Step 2: Indexing your embeddings using different algorithms After you've created embeddings for your data, you need to index them using one or more indexing algorithms. There are several different types of indexing algorithms available, including B-trees, k-nearest neighbors (KNN), and approximate nearest neighbors (ANN). The specific type of indexing algorithm you choose will depend on your use case and performance requirements. For example, B-trees are a good choice for range queries, while KNN and ANN algorithms are more efficient for similarity searches. On small datasets (<100k rows), a linear search that compares every row to the query will give sub-second results, which may be fast enough for your use case. For larger datasets, you may want to consider various indexing strategies offered by additional extensions. Cube is a built-in extension that provides a fast indexing strategy for finding similar vectors. By default it has an arbitrary limit of 100 dimensions, unless Postgres is compiled with a larger size. PgVector supports embeddings up to 2000 dimensions out of the box, and provides a fast indexing strategy for finding similar vectors. When indexing your embeddings, it's important to consider the trade-offs between accuracy and speed. Exact indexing algorithms like B-trees can provide precise results, but may not be as fast as approximate indexing algorithms like KNN and ANN. Similarly, some indexing algorithms may require more memory or disk space than others. In the following, we are creating an index on the tweet_embeddings table using the ivfflat algorithm for indexing. The ivfflat algorithm is a type of hybrid index that combines an Inverted File (IVF) index with a Flat (FLAT) index. The index is being created on the embedding column in the tweet_embeddings table, which contains vector embeddings generated from the original tweet dataset. The vector_cosine_ops argument specifies the indexing operation to use for the embeddings. In this case, it's using the cosine similarity operation, which is a common method for measuring similarity between vectors. By creating an index on the embedding column, the database can quickly search for and retrieve records that are similar to a given query vector. This can be useful for a variety of machine learning applications, such as similarity search or recommendation systems. postgresql CREATE INDEX ON tweet_embeddings USING ivfflat (embedding vector_cosine_ops); Step 3: Querying the index using embeddings for your queries Once your embeddings have been indexed, you can use them to perform queries against your database. To do this, you'll need to provide a query embedding that represents the query you want to perform. The index will then return the closest matching embeddings from your database, based on the similarity between the query embedding and the stored embeddings. postgresql WITH query AS ( SELECT pgml.embed('distilbert-base-uncased', 'Star Wars christmas special is on Disney')::vector AS embedding ) SELECT * FROM items, query ORDER BY items.embedding <-> query.embedding LIMIT 5; Result |text| |----| |Happy Friday with Batman animated Series 90S forever!| |"Fri Oct 17, Sonic Highways is on HBO tonight, Also new episode of Girl Meets World on Disney"| |tfw the 2nd The Hunger Games movie is on Amazon Prime but not the 1st one I didn't watch| |5 RT's if you want the next episode of twilight princess tomorrow| |Jurassic Park is BACK! New Trailer for the 4th Movie, Jurassic World -| LLM Fine-tuning In this section, we will provide a step-by-step walkthrough for fine-tuning a Language Model (LLM) for differnt tasks. Prerequisites Ensure you have the PostgresML extension installed and configured in your PostgreSQL database. You can find installation instructions for PostgresML in the official documentation. Obtain a Hugging Face API token to push the fine-tuned model to the Hugging Face Model Hub. Follow the instructions on the Hugging Face website to get your API token. Text Classification 2 Classes 1. Loading the Dataset To begin, create a table to store your dataset. In this example, we use the 'imdb' dataset from Hugging Face. IMDB dataset contains three splits: train (25K rows), test (25K rows) and unsupervised (50K rows). In train and test splits, negative class has label 0 and positive class label 1. All rows in unsupervised split has a label of -1. postgresql SELECT pgml.load_dataset('imdb'); 2. Prepare dataset for fine-tuning We will create a view of the dataset by performing the following operations: Add a new text column named "class" that has positive and negative classes. Shuffled view of the dataset to ensure randomness in the distribution of data. Remove all the unsupervised splits that have label = -1. postgresql CREATE VIEW pgml.imdb_shuffled_view AS SELECT label, CASE WHEN label = 0 THEN 'negative' WHEN label = 1 THEN 'positive' ELSE 'neutral' END AS class, text FROM pgml.imdb WHERE label != -1 ORDER BY RANDOM(); 3 Exploratory Data Analysis (EDA) on Shuffled Data Before splitting the data into training and test sets, it's essential to perform exploratory data analysis (EDA) to understand the distribution of labels and other characteristics of the dataset. In this section, we'll use the pgml.imdb_shuffled_view to explore the shuffled data. 3.1 Distribution of Labels To analyze the distribution of labels in the shuffled dataset, you can use the following SQL query: ```postgresql -- Count the occurrences of each label in the shuffled dataset pgml=# SELECT class, COUNT(*) AS label_count FROM pgml.imdb_shuffled_view GROUP BY class ORDER BY class; class | label_count ----------+------------- negative | 25000 positive | 25000 (2 rows) ``` This query provides insights into the distribution of labels, helping you understand the balance or imbalance of classes in your dataset. 3.2 Sample Records To get a glimpse of the data, you can retrieve a sample of records from the shuffled dataset: ```postgresql -- Retrieve a sample of records from the shuffled dataset pgml=# SELECT LEFT(text,100) AS text, class FROM pgml.imdb_shuffled_view LIMIT 5; text | class ------------------------------------------------------------------------------------------------------+---------- This is a VERY entertaining movie. A few of the reviews that I have read on this forum have been wri | positive This is one of those movies where I wish I had just stayed in the bar. The film is quite | negative Barbershop 2: Back in Business wasn't as good as it's original but was just as funny. The movie itse | negative Umberto Lenzi hits new lows with this recycled trash. Janet Agren plays a lady who is looking for he | negative I saw this movie last night at the Phila. Film festival. It was an interesting and funny movie that | positive (5 rows) Time: 101.985 ms ``` This query allows you to inspect a few records to understand the structure and content of the shuffled data. 3.3 Additional Exploratory Analysis Feel free to explore other aspects of the data, such as the distribution of text lengths, word frequencies, or any other features relevant to your analysis. Performing EDA is crucial for gaining insights into your dataset and making informed decisions during subsequent steps of the workflow. 4. Splitting Data into Training and Test Sets Create views for training and test data by splitting the shuffled dataset. In this example, 80% is allocated for training, and 20% for testing. We will use pgml.imdb_test_view in section 6 for batch predictions using the finetuned model. ```postgresql -- Create a view for training data CREATE VIEW pgml.imdb_train_view AS SELECT * FROM pgml.imdb_shuffled_view LIMIT (SELECT COUNT(*) * 0.8 FROM pgml.imdb_shuffled_view); -- Create a view for test data CREATE VIEW pgml.imdb_test_view AS SELECT * FROM pgml.imdb_shuffled_view OFFSET (SELECT COUNT(*) * 0.8 FROM pgml.imdb_shuffled_view); ``` 5. Fine-Tuning the Language Model Now, fine-tune the Language Model for text classification using the created training view. In the following sections, you will see a detailed explanation of different parameters used during fine-tuning. Fine-tuned model is pushed to your public Hugging Face Hub periodically. A new repository will be created under your username using your project name ( imdb_review_sentiment in this case). You can also choose to push the model to a private repository by setting hub_private_repo: true in training arguments. postgresql SELECT pgml.tune( 'imdb_review_sentiment', task => 'text-classification', relation_name => 'pgml.imdb_train_view', model_name => 'distilbert-base-uncased', test_size => 0.2, test_sampling => 'last', hyperparams => '{ "training_args" : { "learning_rate": 2e-5, "per_device_train_batch_size": 16, "per_device_eval_batch_size": 16, "num_train_epochs": 20, "weight_decay": 0.01, "hub_token" : "YOUR_HUB_TOKEN", "push_to_hub" : true }, "dataset_args" : { "text_column" : "text", "class_column" : "class" } }' ); project_name ('imdb_review_sentiment'): The project_name parameter specifies a unique name for your fine-tuning project. It helps identify and organize different fine-tuning tasks within the PostgreSQL database. In this example, the project is named 'imdb_review_sentiment,' reflecting the sentiment analysis task on the IMDb dataset. You can check pgml.projects for list of projects. task ('text-classification'): The task parameter defines the nature of the machine learning task to be performed. In this case, it's set to 'text-classification,' indicating that the fine-tuning is geared towards training a model for text classification. relation_name ('pgml.imdb_train_view'): The relation_name parameter identifies the training dataset to be used for fine-tuning. It specifies the view or table containing the training data. In this example, 'pgml.imdb_train_view' is the view created from the shuffled IMDb dataset, and it serves as the source for model training. model_name ('distilbert-base-uncased'): The model_name parameter denotes the pre-trained language model architecture to be fine-tuned. In this case, 'distilbert-base-uncased' is selected. DistilBERT is a distilled version of BERT, and the 'uncased' variant indicates that the model does not differentiate between uppercase and lowercase letters. test_size (0.2): The test_size parameter determines the proportion of the dataset reserved for testing during fine-tuning. In this example, 20% of the dataset is set aside for evaluation, helping assess the model's performance on unseen data. test_sampling ('last'): The test_sampling parameter defines the strategy for sampling test data from the dataset. In this case, 'last' indicates that the most recent portion of the data, following the specified test size, is used for testing. Adjusting this parameter might be necessary based on your specific requirements and dataset characteristics. 5.1 Dataset Arguments (dataset_args) The dataset_args section allows you to specify critical parameters related to your dataset for language model fine-tuning. text_column: The name of the column containing the text data in your dataset. In this example, it's set to "text." class_column: The name of the column containing the class labels in your dataset. In this example, it's set to "class." 5.2 Training Arguments (training_args) Fine-tuning a language model requires careful consideration of training parameters in the training_args section. Below is a subset of training args that you can pass to fine-tuning. You can find an exhaustive list of parameters in Hugging Face documentation on TrainingArguments . learning_rate: The learning rate for the training. It controls the step size during the optimization process. Adjust based on your model's convergence behavior. per_device_train_batch_size: The batch size per GPU for training. This parameter controls the number of training samples utilized in one iteration. Adjust based on your available GPU memory. per_device_eval_batch_size: The batch size per GPU for evaluation. Similar to per_device_train_batch_size, but used during model evaluation. num_train_epochs: The number of training epochs. An epoch is one complete pass through the entire training dataset. Adjust based on the model's convergence and your dataset size. weight_decay: L2 regularization term for weight decay. It helps prevent overfitting. Adjust based on the complexity of your model. hub_token: Your Hugging Face API token to push the fine-tuned model to the Hugging Face Model Hub. Replace "YOUR_HUB_TOKEN" with the actual token. push_to_hub: A boolean flag indicating whether to push the model to the Hugging Face Model Hub after fine-tuning. 5.3 Monitoring During training, metrics like loss, gradient norm will be printed as info and also logged in pgml.logs table. Below is a snapshot of such output. json INFO: { "loss": 0.3453, "grad_norm": 5.230295181274414, "learning_rate": 1.9e-05, "epoch": 0.25, "step": 500, "max_steps": 10000, "timestamp": "2024-03-07 01:59:15.090612" } INFO: { "loss": 0.2479, "grad_norm": 2.7754225730895996, "learning_rate": 1.8e-05, "epoch": 0.5, "step": 1000, "max_steps": 10000, "timestamp": "2024-03-07 02:01:12.064098" } INFO: { "loss": 0.223, "learning_rate": 1.6000000000000003e-05, "epoch": 1.0, "step": 2000, "max_steps": 10000, "timestamp": "2024-03-07 02:05:08.141220" } Once the training is completed, model will be evaluated against the validation dataset. You will see the below in the client terminal. Accuracy on the evaluation dataset is 0.934 and F1-score is 0.93. json INFO: { "train_runtime": 2359.5335, "train_samples_per_second": 67.81, "train_steps_per_second": 4.238, "train_loss": 0.11267969808578492, "epoch": 5.0, "step": 10000, "max_steps": 10000, "timestamp": "2024-03-07 02:36:38.783279" } INFO: { "eval_loss": 0.3691485524177551, "eval_f1": 0.9343711842996372, "eval_accuracy": 0.934375, "eval_runtime": 41.6167, "eval_samples_per_second": 192.23, "eval_steps_per_second": 12.014, "epoch": 5.0, "step": 10000, "max_steps": 10000, "timestamp": "2024-03-07 02:37:31.762917" } Once the training is completed, you can check query pgml.logs table using the model_id or by finding the latest model on the project. bash pgml: SELECT logs->>'epoch' AS epoch, logs->>'step' AS step, logs->>'loss' AS loss FROM pgml.logs WHERE model_id = 993 AND jsonb_exists(logs, 'loss'); epoch | step | loss -------+-------+-------- 0.25 | 500 | 0.3453 0.5 | 1000 | 0.2479 0.75 | 1500 | 0.223 1.0 | 2000 | 0.2165 1.25 | 2500 | 0.1485 1.5 | 3000 | 0.1563 1.75 | 3500 | 0.1559 2.0 | 4000 | 0.142 2.25 | 4500 | 0.0816 2.5 | 5000 | 0.0942 2.75 | 5500 | 0.075 3.0 | 6000 | 0.0883 3.25 | 6500 | 0.0432 3.5 | 7000 | 0.0426 3.75 | 7500 | 0.0444 4.0 | 8000 | 0.0504 4.25 | 8500 | 0.0186 4.5 | 9000 | 0.0265 4.75 | 9500 | 0.0248 5.0 | 10000 | 0.0284 During training, model is periodically uploaded to Hugging Face Hub. You will find the model at https://huggingface.co/<username>/<project_name> . An example model that was automatically pushed to Hugging Face Hub is here . 6. Inference using fine-tuned model Now, that we have fine-tuned model on Hugging Face Hub, we can use pgml.transform to perform real-time predictions as well as batch predictions. Real-time predictions Here is an example pgml.transform call for real-time predictions on the newly minted LLM fine-tuned on IMDB review dataset. ```postgresql SELECT pgml.transform( task => '{ "task": "text-classification", "model": "santiadavani/imdb_review_sentiement" }'::JSONB, inputs => ARRAY[ 'I would not give this movie a rating, its not worthy. I watched it only because I am a Pfieffer fan. ', 'This movie was sooooooo good! It was hilarious! There are so many jokes that you can just watch the' ] ); transform [{"label": "negative", "score": 0.999561846256256}, {"label": "positive", "score": 0.986771047115326}] (1 row) Time: 175.264 ms ``` Batch predictions ```postgresql pgml=# SELECT LEFT(text, 100) AS truncated_text, class, predicted_class[0]->>'label' AS predicted_class, (predicted_class[0]->>'score')::float AS score FROM ( SELECT LEFT(text, 100) AS text, class, pgml.transform( task => '{ "task": "text-classification", "model": "santiadavani/imdb_review_sentiement" }'::JSONB, inputs => ARRAY[text] ) AS predicted_class FROM pgml.imdb_test_view LIMIT 2 ) AS subquery; truncated_text | class | predicted_class | score ------------------------------------------------------------------------------------------------------+----------+-----------------+-------------------- I wouldn't give this movie a rating, it's not worthy. I watched it only because I'm a Pfieffer fan. | negative | negative | 0.9996490478515624 This movie was sooooooo good! It was hilarious! There are so many jokes that you can just watch the | positive | positive | 0.9972313046455384 Time: 1337.290 ms (00:01.337) ``` 7. Restarting Training from a Previous Trained Model Sometimes, it's necessary to restart the training process from a previously trained model. This can be advantageous for various reasons, such as model fine-tuning, hyperparameter adjustments, or addressing interruptions in the training process. pgml.tune provides a seamless way to restart training while leveraging the progress made in the existing model. Below is a guide on how to restart training using a previous model as a starting point: Define the Previous Model Specify the name of the existing model you want to use as a starting point. This is achieved by setting the model_name parameter in the pgml.tune function. In the example below, it is set to 'santiadavani/imdb_review_sentiement'. postgresql model_name => 'santiadavani/imdb_review_sentiement', Adjust Hyperparameters Fine-tune hyperparameters as needed for the restarted training process. This might include modifying learning rates, batch sizes, or training epochs. In the example below, hyperparameters such as learning rate, batch sizes, and epochs are adjusted. postgresql "training_args": { "learning_rate": 2e-5, "per_device_train_batch_size": 16, "per_device_eval_batch_size": 16, "num_train_epochs": 1, "weight_decay": 0.01, "hub_token": "", "push_to_hub": true }, Ensure Consistent Dataset Configuration Confirm that the dataset configuration remains consistent, including specifying the same text and class columns as in the previous training. This ensures compatibility between the existing model and the restarted training process. postgresql "dataset_args": { "text_column": "text", "class_column": "class" }, Run the pgml.tune Function Execute the pgml.tune function with the updated parameters to initiate the training restart. The function will leverage the existing model and adapt it based on the adjusted hyperparameters and dataset configuration. postgresql SELECT pgml.tune( 'imdb_review_sentiement', task => 'text-classification', relation_name => 'pgml.imdb_train_view', model_name => 'santiadavani/imdb_review_sentiement', test_size => 0.2, test_sampling => 'last', hyperparams => '{ "training_args": { "learning_rate": 2e-5, "per_device_train_batch_size": 16, "per_device_eval_batch_size": 16, "num_train_epochs": 1, "weight_decay": 0.01, "hub_token": "YOUR_HUB_TOKEN", "push_to_hub": true }, "dataset_args": { "text_column": "text", "class_column": "class" } }' ); By following these steps, you can effectively restart training from a previously trained model, allowing for further refinement and adaptation of the model based on new requirements or insights. Adjust parameters as needed for your specific use case and dataset. 8. Hugging Face Hub vs. PostgresML as Model Repository We utilize the Hugging Face Hub as the primary repository for fine-tuning Large Language Models (LLMs). Leveraging the HF hub offers several advantages: The HF repository serves as the platform for pushing incremental updates to the model during the training process. In the event of any disruptions in the database connection, you have the flexibility to resume training from where it was left off. If you prefer to keep the model private, you can push it to a private repository within the Hugging Face Hub. This ensures that the model is not publicly accessible by setting the parameter hub_private_repo to true. The pgml.transform function, designed around utilizing models from the Hugging Face Hub, can be reused without any modifications. However, in certain scenarios, pushing the model to a central repository and pulling it for inference may not be the most suitable approach. To address this situation, we save all the model weights and additional artifacts, such as tokenizer configurations and vocabulary, in the pgml.files table at the end of the training process. It's important to note that as of the current writing, hooks to use models directly from pgml.files in the pgml.transform function have not been implemented. We welcome Pull Requests (PRs) from the community to enhance this functionality. Text Classification 9 Classes 1. Load and Shuffle the Dataset In this section, we begin by loading the FinGPT sentiment analysis dataset using the pgml.load_dataset function. The dataset is then processed and organized into a shuffled view (pgml.fingpt_sentiment_shuffled_view), ensuring a randomized order of records. This step is crucial for preventing biases introduced by the original data ordering and enhancing the training process. ```postgresql -- Load the dataset SELECT pgml.load_dataset('FinGPT/fingpt-sentiment-train'); -- Create a shuffled view CREATE VIEW pgml.fingpt_sentiment_shuffled_view AS SELECT * FROM pgml."FinGPT/fingpt-sentiment-train" ORDER BY RANDOM(); ``` 2. Explore Class Distribution Once the dataset is loaded and shuffled, we delve into understanding the distribution of sentiment classes within the data. By querying the shuffled view, we obtain valuable insights into the number of instances for each sentiment class. This exploration is essential for gaining a comprehensive understanding of the dataset and its inherent class imbalances. ```postgresql -- Explore class distribution SELECTpgml=# SELECT output, COUNT(*) AS class_count FROM pgml.fingpt_sentiment_shuffled_view GROUP BY output ORDER BY output; output | class_count ---------------------+------------- mildly negative | 2108 mildly positive | 2548 moderately negative | 2972 moderately positive | 6163 negative | 11749 neutral | 29215 positive | 21588 strong negative | 218 strong positive | 211 ``` 3. Create Training and Test Views To facilitate the training process, we create distinct views for training and testing purposes. The training view (pgml.fingpt_sentiment_train_view) contains 80% of the shuffled dataset, enabling the model to learn patterns and associations. Simultaneously, the test view (pgml.fingpt_sentiment_test_view) encompasses the remaining 20% of the data, providing a reliable evaluation set to assess the model's performance. ```postgresql -- Create a view for training data (e.g., 80% of the shuffled records) CREATE VIEW pgml.fingpt_sentiment_train_view AS SELECT * FROM pgml.fingpt_sentiment_shuffled_view LIMIT (SELECT COUNT(*) * 0.8 FROM pgml.fingpt_sentiment_shuffled_view); -- Create a view for test data (remaining 20% of the shuffled records) CREATE VIEW pgml.fingpt_sentiment_test_view AS SELECT * FROM pgml.fingpt_sentiment_shuffled_view OFFSET (SELECT COUNT(*) * 0.8 FROM pgml.fingpt_sentiment_shuffled_view); ``` 4. Fine-Tune the Model for 9 Classes In the final section, we kick off the fine-tuning process using the pgml.tune function. The model will be internally configured for sentiment analysis with 9 classes. The training is executed on the 80% of the train view and evaluated on the remaining 20% of the train view. The test view is reserved for evaluating the model's accuracy after training is completed. Please note that the option hub_private_repo: true is used to push the model to a private Hugging Face repository. ```postgresql -- Fine-tune the model for 9 classes without HUB token SELECT pgml.tune( 'fingpt_sentiement', task => 'text-classification', relation_name => 'pgml.fingpt_sentiment_train_view', model_name => 'distilbert-base-uncased', test_size => 0.2, test_sampling => 'last', hyperparams => '{ "training_args": { "learning_rate": 2e-5, "per_device_train_batch_size": 16, "per_device_eval_batch_size": 16, "num_train_epochs": 5, "weight_decay": 0.01, "hub_token" : "YOUR_HUB_TOKEN", "push_to_hub": true, "hub_private_repo": true }, "dataset_args": { "text_column": "input", "class_column": "output" } }' ); ``` Conversation In this section, we will discuss conversational task using state-of-the-art NLP techniques. Conversational AI has garnered immense interest and significance in recent years due to its wide range of applications, from virtual assistants to customer service chatbots and beyond. Understanding the Conversation Task At the core of conversational AI lies the conversation task, a fundamental NLP problem that involves processing and generating human-like text-based interactions. Let's break down this task into its key components: Input: The input to the conversation task typically consists of a sequence of conversational turns, often represented as text. These turns can encompass a dialogue between two or more speakers, capturing the flow of communication over time. Model: Central to the conversation task is the NLP model, which is trained to understand the nuances of human conversation and generate appropriate responses. These models leverage sophisticated transformer based architectures like Llama2, Mistral, GPT etc., empowered by large-scale datasets and advanced training techniques. Output: The ultimate output of the conversation task is the model's response to the input conversation. This response aims to be contextually relevant, coherent, and engaging, reflecting a natural human-like interaction. Versatility of the Conversation Task What makes the conversation task truly remarkable is its remarkable versatility. Beyond its traditional application in dialogue systems, the conversation task can be adapted to solve several NLP problems by tweaking the input representation or task formulation. Text Classification: By providing individual utterances with corresponding labels, the conversation task can be repurposed for tasks such as sentiment analysis, intent detection, or topic classification. Input: - System: Chatbot: "Hello! How can I assist you today?" - User: "I'm having trouble connecting to the internet." Model Output (Text Classification): - Predicted Label: Technical Support - Confidence Score: 0.85 Token Classification: Annotating the conversation with labels for specific tokens or phrases enables applications like named entity recognition within conversational text. Input: - System: Chatbot: "Please describe the issue you're facing in detail." - User: "I can't access any websites, and the Wi-Fi indicator on my router is blinking." Model Output (Token Classification): - User's Description: "I can't access any websites, and the Wi-Fi indicator on my router is blinking." - Token Labels: - "access" - Action - "websites" - Entity (Location) - "Wi-Fi" - Entity (Technology) - "indicator" - Entity (Device Component) - "blinking" - State Question Answering: Transforming conversational exchanges into a question-answering format enables extracting relevant information and providing concise answers, akin to human comprehension and response. Input: - System: Chatbot: "How can I help you today?" - User: "What are the symptoms of COVID-19?" Model Output (Question Answering): - Answer: "Common symptoms of COVID-19 include fever, cough, fatigue, shortness of breath, loss of taste or smell, and body aches." Fine-tuning Llama2-7b model using LoRA In this section, we will explore how to fine-tune the Llama2-7b-chat large language model for the financial sentiment data discussed in the previous section utilizing the pgml.tune function and employing the LoRA approach. LoRA is a technique that enables efficient fine-tuning of large language models by only updating a small subset of the model's weights during fine-tuning, while keeping the majority of the weights frozen. This approach can significantly reduce the computational requirements and memory footprint compared to traditional full model fine-tuning. postgresql SELECT pgml.tune( 'fingpt-llama2-7b-chat', task => 'conversation', relation_name => 'pgml.fingpt_sentiment_train_view', model_name => 'meta-llama/Llama-2-7b-chat-hf', test_size => 0.8, test_sampling => 'last', hyperparams => '{ "training_args" : { "learning_rate": 2e-5, "per_device_train_batch_size": 4, "per_device_eval_batch_size": 4, "num_train_epochs": 1, "weight_decay": 0.01, "hub_token" : "HF_TOKEN", "push_to_hub" : true, "optim" : "adamw_bnb_8bit", "gradient_accumulation_steps" : 4, "gradient_checkpointing" : true }, "dataset_args" : { "system_column" : "instruction", "user_column" : "input", "assistant_column" : "output" }, "lora_config" : {"r": 2, "lora_alpha" : 4, "lora_dropout" : 0.05, "bias": "none", "task_type": "CAUSAL_LM"}, "load_in_8bit" : false, "token" : "HF_TOKEN" }' ); Let's break down each argument and its significance: Model Name ( model_name ): This argument specifies the name or identifier of the base model that will be fine-tuned. In the context of the provided query, it refers to the pre-trained model "meta-llama/Llama-2-7b-chat-hf." Task ( task ): Indicates the specific task for which the model is being fine-tuned. In this case, it's set to "conversation," signifying that the model will be adapted to process conversational data. Relation Name ( relation_name ): Refers to the name of the dataset or database relation containing the training data used for fine-tuning. In the provided query, it's set to "pgml.fingpt_sentiment_train_view." Test Size ( test_size ): Specifies the proportion of the dataset reserved for testing, expressed as a fraction. In the example, it's set to 0.8, indicating that 80% of the data will be used for training, and the remaining 20% will be held out for testing. Test Sampling ( test_sampling ): Determines the strategy for sampling the test data. In the provided query, it's set to "last," indicating that the last portion of the dataset will be used for testing. Hyperparameters ( hyperparams ): This argument encapsulates a JSON object containing various hyperparameters essential for the fine-tuning process. Let's break down its subcomponents: Training Args ( training_args ): Specifies parameters related to the training process, including learning rate, batch size, number of epochs, weight decay, optimizer settings, and other training configurations. Dataset Args ( dataset_args ): Provides arguments related to dataset processing, such as column names for system responses, user inputs, and assistant outputs. LORA Config ( lora_config ): Defines settings for the LORA (Learned Optimizer and Rate Adaptation) algorithm, including parameters like the attention radius ( r ), LORA alpha ( lora_alpha ), dropout rate ( lora_dropout ), bias, and task type. Load in 8-bit ( load_in_8bit ): Determines whether to load data in 8-bit format, which can be beneficial for memory and performance optimization. Token ( token ): Specifies the Hugging Face token required for accessing private repositories and pushing the fine-tuned model to the Hugging Face Hub. Hub Private Repo ( hub_private_repo ): This optional parameter indicates whether the fine-tuned model should be pushed to a private repository on the Hugging Face Hub. In the provided query, it's set to true , signifying that the model will be stored in a private repository. Training Args: Expanding on the training_args within the hyperparams argument provides insight into the specific parameters governing the training process of the model. Here's a breakdown of the individual training arguments and their significance: Learning Rate ( learning_rate ): Determines the step size at which the model parameters are updated during training. A higher learning rate may lead to faster convergence but risks overshooting optimal solutions, while a lower learning rate may ensure more stable training but may take longer to converge. Per-device Train Batch Size ( per_device_train_batch_size ): Specifies the number of training samples processed in each batch per device during training. Adjusting this parameter can impact memory usage and training speed, with larger batch sizes potentially accelerating training but requiring more memory. Per-device Eval Batch Size ( per_device_eval_batch_size ): Similar to per_device_train_batch_size , this parameter determines the batch size used for evaluation (validation) during training. It allows for efficient evaluation of the model's performance on validation data. Number of Train Epochs ( num_train_epochs ): Defines the number of times the entire training dataset is passed through the model during training. Increasing the number of epochs can improve model performance up to a certain point, after which it may lead to overfitting. Weight Decay ( weight_decay ): Introduces regularization by penalizing large weights in the model, thereby preventing overfitting. It helps to control the complexity of the model and improve generalization to unseen data. Hub Token ( hub_token ): A token required for authentication when pushing the fine-tuned model to the Hugging Face Hub or accessing private repositories. It ensures secure communication with the Hub platform. Push to Hub ( push_to_hub ): A boolean flag indicating whether the fine-tuned model should be uploaded to the Hugging Face Hub after training. Setting this parameter to true facilitates sharing and deployment of the model for wider usage. Optimizer ( optim ): Specifies the optimization algorithm used during training. In the provided query, it's set to "adamw_bnb_8bit," indicating the use of the AdamW optimizer with gradient clipping and 8-bit quantization. Gradient Accumulation Steps ( gradient_accumulation_steps ): Controls the accumulation of gradients over multiple batches before updating the model's parameters. It can help mitigate memory constraints and stabilize training, especially with large batch sizes. Gradient Checkpointing ( gradient_checkpointing ): Enables gradient checkpointing, a memory-saving technique that trades off compute for memory during backpropagation. It allows training of larger models or with larger batch sizes without running out of memory. Each of these training arguments plays a crucial role in shaping the training process, ensuring efficient convergence, regularization, and optimization of the model for the specific task at hand. Adjusting these parameters appropriately is essential for achieving optimal model performance. LORA Args: Expanding on the lora_config within the hyperparams argument provides clarity on its role in configuring the LORA (Learned Optimizer and Rate Adaptation) algorithm: Attention Radius ( r ): Specifies the radius of the attention window for the LORA algorithm. It determines the range of tokens considered for calculating attention weights, allowing the model to focus on relevant information while processing conversational data. LORA Alpha ( lora_alpha ): Controls the strength of the learned regularization term in the LORA algorithm. A higher alpha value encourages sparsity in attention distributions, promoting selective attention and enhancing interpretability. LORA Dropout ( lora_dropout ): Defines the dropout rate applied to the LORA attention scores during training. Dropout introduces noise to prevent overfitting and improve generalization by randomly zeroing out a fraction of attention weights. Bias ( bias ): Determines whether bias terms are included in the LORA attention calculation. Bias terms can introduce additional flexibility to the attention mechanism, enabling the model to learn more complex relationships between tokens. Task Type ( task_type ): Specifies the type of task for which the LORA algorithm is applied. In this context, it's set to "CAUSAL_LM" for causal language modeling, indicating that the model predicts the next token based on the previous tokens in the sequence. Configuring these LORA arguments appropriately ensures that the attention mechanism of the model is optimized for processing conversational data, allowing it to capture relevant information and generate coherent responses effectively. Dataset Args: Expanding on the dataset_args within the hyperparams argument provides insight into its role in processing the dataset: System Column ( system_column ): Specifies the name or identifier of the column containing system responses (e.g., prompts or instructions) within the dataset. This column is crucial for distinguishing between different types of conversational turns and facilitating model training. User Column ( user_column ): Indicates the column containing user inputs or queries within the dataset. These inputs form the basis for the model's understanding of user intentions, sentiments, or requests during training and inference. Assistant Column ( assistant_column ): Refers to the column containing assistant outputs or responses generated by the model during training. These outputs serve as targets for the model to learn from and are compared against the actual responses during evaluation to assess model performance. Configuring these dataset arguments ensures that the model is trained on the appropriate input-output pairs, enabling it to learn from the conversational data and generate contextually relevant responses. Once the fine-tuning is completed, you will see the model in your Hugging Face repository (example: https://huggingface.co/santiadavani/fingpt-llama2-7b-chat). Since we are using LoRA to fine tune the model we only save the adapter weights (~2MB) instead of all the 7B weights (14GB) in Llama2-7b model. Inference For inference, we will be utilizing the OpenSourceAI class from the pgml SDK . Here's an example code snippet: ```python import pgml database_url = "DATABASE_URL" client = pgml.OpenSourceAI(database_url) results = client.chat_completions_create( { "model" : "santiadavani/fingpt-llama2-7b-chat", "token" : "TOKEN", "load_in_8bit": "true", "temperature" : 0.1, "repetition_penalty" : 1.5, }, [ { "role" : "system", "content" : "What is the sentiment of this news? Please choose an answer from {strong negative/moderately negative/mildly negative/neutral/mildly positive/moderately positive/strong positive}.", }, { "role": "user", "content": "Starbucks says the workers violated safety policies while workers said they'd never heard of the policy before and are alleging retaliation.", }, ] ) print(results) ``` In this code snippet, we first import the pgml module and create an instance of the OpenSourceAI class, providing the necessary database URL. We then call the chat_completions_create method, specifying the model we want to use (in this case, "santiadavani/fingpt-llama2-7b-chat"), along with other parameters such as the token, whether to load the model in 8-bit precision, the temperature for sampling, and the repetition penalty. The chat_completions_create method takes two arguments: a dictionary containing the model configuration and a list of dictionaries representing the chat conversation. In this example, the conversation consists of a system prompt asking for the sentiment of a given news snippet, and a user message containing the news text. The results are: json { "choices": [ { "index": 0, "message": { "content": " Moderately negative ", "role": "assistant" } } ], "created": 1711144872, "id": "b663f701-db97-491f-b186-cae1086f7b79", "model": "santiadavani/fingpt-llama2-7b-chat", "object": "chat.completion", "system_fingerprint": "e36f4fa5-3d0b-e354-ea4f-950cd1d10787", "usage": { "completion_tokens": 0, "prompt_tokens": 0, "total_tokens": 0 } } This dictionary contains the response from the language model, santiadavani/fingpt-llama2-7b-chat , for the given news text. The key information in the response is: choices : A list containing the model's response. In this case, there is only one choice. message.content : The actual response from the model, which is " Moderately negative". model : The name of the model used, "santiadavani/fingpt-llama2-7b-chat". created : A timestamp indicating when the response was generated. id : A unique identifier for this response. object : Indicates that this is a "chat.completion" object. usage : Information about the token usage for this response, although all values are 0 in this case. So, the language model has analyzed the news text Starbucks says the workers violated safety policies while workers said they'd never heard of the policy before and are alleging retaliation. and determined that the sentiment expressed in this text is Moderately negative

The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.

ml,machine-learning,ai,ann,artificial-intelligence,classification,embeddings,javascript,knn,llm

BoomingTech/Piccolo

Piccolo Engine (formerly Pilot Engine) Piccolo Engine is a tiny game engine used for the GAMES104 course. Continuous build status | Build Type | Status | | :---------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | Build Windows | | | Build Linux | | | Build macOS | | Prerequisites To build Piccolo, you must first install the following tools. Windows 10/11 Visual Studio 2019 (or more recent) CMake 3.19 (or more recent) Git 2.1 (or more recent) macOS >= 10.15 (x86_64) Xcode 12.3 (or more recent) CMake 3.19 (or more recent) Git 2.1 (or more recent) Ubuntu 20.04 apt install the following packages sudo apt install libxrandr-dev sudo apt install libxrender-dev sudo apt install libxinerama-dev sudo apt install libxcursor-dev sudo apt install libxi-dev sudo apt install libglvnd-dev sudo apt install libvulkan-dev sudo apt install cmake sudo apt install clang sudo apt install libc++-dev sudo apt install libglew-dev sudo apt install libglfw3-dev sudo apt install vulkan-validationlayers sudo apt install mesa-vulkan-drivers NVIDIA driver (The AMD and Intel driver is open-source, and thus is installed automatically by mesa-vulkan-drivers) Build Piccolo Build on Windows You may execute the build_windows.bat . This batch file will generate the projects, and build the Release config of Piccolo Engine automatically. After successful build, you can find the PiccoloEditor.exe at the bin directory. Or you can use the following command to generate the Visual Studio project firstly, then open the solution in the build directory and build it manually. cmake -S . -B build Build on macOS The following build instructions only tested on specific hardware of x86_64, and do not support M1 chips. For M1 compatible, we will release later. To compile Piccolo, you must have the most recent version of Xcode installed. Then run 'cmake' from the project's root directory, to generate a project of Xcode. cmake -S . -B build -G "Xcode" and you can build the project with cmake --build build --config Release Or you can execute the build_macos.sh to build the binaries. Build on Ubuntu 20.04 You can execute the build_linux.sh to build the binaries. Documentation For documentation, please refer to the Wiki section. Extra Vulkan Validation Layer: Validation Error We have noticed some developers on Windows encounted PiccoloEditor.exe could run normally but reported an exception Vulkan Validation Layer: Validation Error when debugging. You can solve this problem by installing Vulkan SDK (official newest version will do). Generate Compilation Database You can build compile_commands.json with the following commands when Unix Makefiles generaters are avaliable. compile_commands.json is the file required by clangd language server, which is a backend for cpp lsp-mode in Emacs. For Windows: powershell cmake -DCMAKE_TRY_COMPILE_TARGET_TYPE="STATIC_LIBRARY" -DCMAKE_EXPORT_COMPILE_COMMANDS=ON -S . -B compile_db_temp -G "Unix Makefiles" copy compile_db_temp\compile_commands.json . Using Physics Debug Renderer Currently Physics Debug Renderer is only available on Windows. You can use the following command to generate the solution with the debugger project. powershell cmake -S . -B build -DENABLE_PHYSICS_DEBUG_RENDERER=ON Note: 1. Please clean the build directory before regenerating the solution. We've encountered building problems in regenerating directly with previous CMakeCache. 2. Physics Debug Renderer will run when you start PiccoloEditor. We've synced the camera position between both scenes. But the initial camera mode in Physics Debug Renderer is wrong. Scrolling down the mouse wheel once will change the camera of Physics Debug Renderer to the correct mode.

Piccolo (formerly Pilot) – mini game engine for games104

cpp,game-engine,vulkan,imgui,physics,rendering,cplusplus,game-development

facebookresearch/ConvNeXt

A ConvNet for the 2020s Official PyTorch implementation of ConvNeXt , from the following paper: A ConvNet for the 2020s . CVPR 2022.\ Zhuang Liu , Hanzi Mao , Chao-Yuan Wu , Christoph Feichtenhofer , Trevor Darrell and Saining Xie \ Facebook AI Research, UC Berkeley\ [ arXiv ][ video ] We propose ConvNeXt , a pure ConvNet model constructed entirely from standard ConvNet modules. ConvNeXt is accurate, efficient, scalable and very simple in design. Catalog [x] ImageNet-1K Training Code [x] ImageNet-22K Pre-training Code [x] ImageNet-1K Fine-tuning Code [x] Downstream Transfer (Detection, Segmentation) Code [x] Image Classification [Colab] and Web Demo [x] Fine-tune on CIFAR with Weights & Biases logging [Colab] Results and Pre-trained Models ImageNet-1K trained models | name | resolution |acc@1 | #params | FLOPs | model | |:---:|:---:|:---:|:---:| :---:|:---:| | ConvNeXt-T | 224x224 | 82.1 | 28M | 4.5G | model | | ConvNeXt-S | 224x224 | 83.1 | 50M | 8.7G | model | | ConvNeXt-B | 224x224 | 83.8 | 89M | 15.4G | model | | ConvNeXt-B | 384x384 | 85.1 | 89M | 45.0G | model | | ConvNeXt-L | 224x224 | 84.3 | 198M | 34.4G | model | | ConvNeXt-L | 384x384 | 85.5 | 198M | 101.0G | model | ImageNet-22K trained models | name | resolution |acc@1 | #params | FLOPs | 22k model | 1k model | |:---:|:---:|:---:|:---:| :---:| :---:|:---:| | ConvNeXt-T | 224x224 | 82.9 | 29M | 4.5G | model | model | ConvNeXt-T | 384x384 | 84.1 | 29M | 13.1G | - | model | ConvNeXt-S | 224x224 | 84.6 | 50M | 8.7G | model | model | ConvNeXt-S | 384x384 | 85.8 | 50M | 25.5G | - | model | ConvNeXt-B | 224x224 | 85.8 | 89M | 15.4G | model | model | ConvNeXt-B | 384x384 | 86.8 | 89M | 47.0G | - | model | ConvNeXt-L | 224x224 | 86.6 | 198M | 34.4G | model | model | ConvNeXt-L | 384x384 | 87.5 | 198M | 101.0G | - | model | ConvNeXt-XL | 224x224 | 87.0 | 350M | 60.9G | model | model | ConvNeXt-XL | 384x384 | 87.8 | 350M | 179.0G | - | model ImageNet-1K trained models (isotropic) | name | resolution |acc@1 | #params | FLOPs | model | |:---:|:---:|:---:|:---:| :---:|:---:| | ConvNeXt-S | 224x224 | 78.7 | 22M | 4.3G | model | | ConvNeXt-B | 224x224 | 82.0 | 87M | 16.9G | model | | ConvNeXt-L | 224x224 | 82.6 | 306M | 59.7G | model | Installation Please check INSTALL.md for installation instructions. Evaluation We give an example evaluation command for a ImageNet-22K pre-trained, then ImageNet-1K fine-tuned ConvNeXt-B: Single-GPU python main.py --model convnext_base --eval true \ --resume https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_1k_224.pth \ --input_size 224 --drop_path 0.2 \ --data_path /path/to/imagenet-1k Multi-GPU python -m torch.distributed.launch --nproc_per_node=8 main.py \ --model convnext_base --eval true \ --resume https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_1k_224.pth \ --input_size 224 --drop_path 0.2 \ --data_path /path/to/imagenet-1k This should give * Acc@1 85.820 Acc@5 97.868 loss 0.563 For evaluating other model variants, change --model , --resume , --input_size accordingly. You can get the url to pre-trained models from the tables above. Setting model-specific --drop_path is not strictly required in evaluation, as the DropPath module in timm behaves the same during evaluation; but it is required in training. See TRAINING.md or our paper for the values used for different models. Training See TRAINING.md for training and fine-tuning instructions. Acknowledgement This repository is built using the timm library, DeiT and BEiT repositories. License This project is released under the MIT license. Please see the LICENSE file for more information. Citation If you find this repository helpful, please consider citing: @Article{liu2022convnet, author = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie}, title = {A ConvNet for the 2020s}, journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2022}, }

Code release for ConvNeXt model

[]

massCodeIO/massCode

massCode Built with Electron, Vue & Codemirror. Inspired by applications like SnippetsLab and Quiver. Latest Release | Documentation | Change Log Extensions: VS Code | Raycast | Alfred SPONSORS Support massCode is open source project and completely free to use. However, the amount of effort needed to maintain and develop new features for the project is not sustainable without proper financial backing. You can support massCode development via the following methods: [](https://opencollective.com/masscode) [](https://paypal.me/antongithub) [](https://antonreshetov.gumroad.com/l/masscode) Features Organization massCode allows you to organize snippets using multi-level folders as well as tags. Each snippet has fragments - tabs, which gives even greater level of organization. Editor massCode uses Codemirror as the basis for the editor and .tmLanguage as the grammar for syntax highlighting. This tandem opens the door to over 600 existing grammars. The application currently supports more than 160 grammars. In addition to .tmLanguage , the application supports .tmTheme for themes. There is also support for Prettier for code formatting. Real-time Render for HTML & CSS You can not only collect snippets, but also see the rendering result for HTML and CSS in real time. Test the idea or just view the result. Markdown massCode allows you to write in Markdown and provide support to syntax highlighting, tables, list and other formatting. Also massCode supports Mermaid - diagramming and charting tool that renders Markdown-inspired text definitions to create and modify diagrams dynamically. Presentation Mode massCode allows you to make a presentation out of a sequence of snippets. It's great for classroom use, team meetings, conferences or simply reviewing notes on your own. Mindmap massCode allows you to create mental maps from markdown, making the process of creating and editing maps fast and intuitively understandable. It's a great way to organize and structure information visually. Search It is impossible to imagine a productive snippets manager without quick access to snippets. Therefore massCode has a fast full-text search with highlighting of the search query. Autosave massCode automatically saves any changes you make during work, so you don't have to worry about losing changes. Sync You can use any service that provides cloud synchronization, such as iCloud Drive, Google Drive, Dropbox or other similar. Database massCode uses a simple JSON to store your data. The database files are on your local computer. Integrations massCode supports extensions for VS Code , Raycast and Alfred , which gives even more possibilities to use application. With the VS Code extension you get practically zen mode, search for the necessary snippets and insert them immediately or save the selected code sections as a snippet. Beautiful Screenshots Create beautiful snippet images on different backgrounds and in different modes Developer Tools massCode provides developers with a range of convenient tools, such as: - Text tools: Case Converter, Slug Generator, Sort Lines, URL Parser - Cryptography & Security: Hash, HMAC, Password and UUID Generators - Encoders & Decoders: URL, Base64 Overview The goal of creating this application was mostly my own growth as a developer. Also, I wanted this project to absorb the best of such applications already on the market (both free and paid). At the same time, I wanted this project to be an open source project. Follow News and updates on Twitter . Discussions . Other You can also download massCode v1. License AGPL-3.0 Copyright (c) 2019-present, Anton Reshetov .

A free and open source code snippets manager for developers

electron,windows,macos,linux,productivity,snippets,snippets-manager,vue,vite,notes

rerun-io/rerun

Build time aware visualizations of multimodal data Use the Rerun SDK (available for C++, Python and Rust) to log data like images, tensors, point clouds, and text. Logs are streamed to the Rerun Viewer for live visualization or to file for later use. Run the Rerun Viewer in your browser Read about what Rerun is and who it is for A short taste ```py import rerun as rr # pip install rerun-sdk rr.init("rerun_example_app") rr.connect() # Connect to a remote viewer rr.spawn() # Spawn a child process with a viewer and connect rr.save("recording.rrd") # Stream all logs to disk Associate subsequent data with 42 on the “frame” timeline rr.set_time_sequence("frame", 42) Log colored 3D points to the entity at path/to/points rr.log("path/to/points", rr.Points3D(positions, colors=colors)) … ``` Getting started C++ Python : pip install rerun-sdk or on conda Rust : cargo add rerun Installing the Rerun Viewer binary To stream log data over the network or load our .rrd data files you also need the rerun binary. It can be installed with pip install rerun-sdk or with cargo install rerun-cli . Note that only the Python SDK comes bundled with the Viewer whereas C++ & Rust always rely on a separate install. You should now be able to run rerun --help in any terminal. Documentation 📚 High-level docs ⏃ Loggable Types ⚙️ Examples 🌊 C++ API docs 🐍 Python API docs 🦀 Rust API docs ⁉️ Troubleshooting Status We are in active development. There are many features we want to add, and the API is still evolving. Expect breaking changes! Current shortcomings that we are working on: * Multi-million point clouds are slow * Logging many tiny things (e.g. scalars) has a lot of overhead * The data you want to visualize must fit in RAM - See https://www.rerun.io/docs/howto/limit-ram for how to bound memory use. - We plan on having a disk-based data store some time in the future. What is Rerun for? Rerun is built to help you understand complex processes that include rich multimodal data, like 2D, 3D, text, time series, tensors, etc. It is used in many industries, including robotics, simulation, computer vision, or anything that involves a lot of sensors or other signals that evolve over time. Example use case Say you're building a vacuum cleaning robot and it keeps running into walls. Why is it doing that? You need some tool to debug it, but a normal debugger isn't gonna be helpful. Similarly, just logging text won't be very helpful either. The robot may log "Going through doorway" but that won't explain why it thinks the wall is a door. What you need is a visual and temporal debugger, that can log all the different representations of the world the robots holds in its little head, such as: RGB camera feed depth images lidar scan segmentation image (how the robot interprets what it sees) its 3D map of the apartment all the objects the robot has detected (or thinks it has detected), as 3D shapes in the 3D map its confidence in its prediction etc You also want to see how all these streams of data evolve over time so you can go back and pinpoint exactly what went wrong, when and why. Maybe it turns out that a glare from the sun hit one of the sensors in the wrong way, confusing the segmentation network leading to bad object detection. Or maybe it was a bug in the lidar scanning code. Or maybe the robot thought it was somewhere else in the apartment, because its odometry was broken. Or it could be one of a thousand other things. Rerun will help you find out! But seeing the world from the point of the view of the robot is not just for debugging - it will also give you ideas on how to improve the algorithms, new test cases to set up, or datasets to collect. It will also let you explain the brains of the robot to your colleagues, boss, and customers. And so on. Seeing is believing, and an image is worth a thousand words, and multimodal temporal logging is worth a thousand images :) Of course, Rerun is useful for much more than just robots. Any time you have any form of sensors, or 2D or 3D state evolving over time, Rerun would be a great tool. Business model Rerun uses an open-core model. Everything in this repository will stay open source and free (both as in beer and as in freedom). In the future, Rerun will offer a commercial product that builds on top of the core free project. The Rerun open source project targets the needs of individual developers. The commercial product targets the needs specific to teams that build and run computer vision and robotics products. How to cite Rerun When using Rerun in your research, please cite it to acknowledge its contribution to your work. This can be done by including a reference to Rerun in the software or methods section of your paper. Suggested citation format: bibtex @software{RerunSDK, title = {Rerun: A Visualization SDK for Multimodal Data}, author = {{Rerun Development Team}}, url = {https://www.rerun.io}, version = {insert version number}, date = {insert date of usage}, year = {2024}, publisher = {{Rerun Technologies AB}}, address = {Online}, note = {Available from https://www.rerun.io/ and https://github.com/rerun-io/rerun} } Please replace "insert version number" with the version of Rerun you used and "insert date of usage" with the date(s) you used the tool in your research. This citation format helps ensure that Rerun's development team receives appropriate credit for their work and facilitates the tool's discovery by other researchers. Development ARCHITECTURE.md CODE_OF_CONDUCT.md CODE_STYLE.md CONTRIBUTING.md BUILD.md rerun_py/README.md - instructions for Python SDK rerun_cpp/README.md - instructions for C++ SDK Installing a pre-release Python SDK Download the correct .whl from GitHub Releases Run pip install rerun_sdk<…>.whl (replace <…> with the actual filename) Test it: rerun --version

Visualize streams of multimodal data. Fast, easy to use, and simple to integrate. Built in Rust using egui.

visualization,computer-vision,python,robotics,rust,multimodal,cpp

ekzhang/sshx

sshx A secure web-based, collaborative terminal. Features: Run a single command to share your terminal with anyone. Resize, move windows, and freely zoom and pan on an infinite canvas. See other people's cursors moving in real time. Connect to the nearest server in a globally distributed mesh. End-to-end encryption with Argon2 and AES. Automatic reconnection and real-time latency estimates. Predictive echo for faster local editing (à la Mosh). Visit sshx.io to learn more. Installation Just run this command to get the sshx binary for your platform. shell curl -sSf https://sshx.io/get | sh Supports Linux and MacOS on x86_64 and ARM64 architectures, as well as embedded ARMv6 and ARMv7-A systems. The precompiled Linux binaries are statically linked. If you just want to try it out without installing, use: shell curl -sSf https://sshx.io/get | sh -s run Inspect the script for additional options. CI/CD You can run sshx in continuous integration workflows to help debug tricky issues, like in GitHub Actions. ```yaml name: CI on: push jobs: build: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 # ... other steps ... - run: curl -sSf https://sshx.io/get | sh -s run # ^ # └ This will open a remote terminal session and print the URL. It # should take under a second. ``` We don't have a prepackaged action because it's just a single command. It works anywhere: GitLab CI, CircleCI, Buildkite, CI on your Raspberry Pi, etc. Be careful adding this to a public GitHub repository, as any user can view the logs of a CI job while it is running. Development Here's how to work on the project, if you want to contribute. Building from source To build the latest version of the client from source, clone this repository and run, with Rust installed: shell cargo install --path crates/sshx This will compile the sshx binary and place it in your ~/.cargo/bin folder. Workflow First, start service containers for development. shell docker compose up -d Install Rust 1.70+ , Node v18 , NPM v9 , and mprocs . Then, run shell npm install mprocs This will compile and start the server, an instance of the client, and the web frontend in parallel on your machine. Deployment I host the application servers on Fly.io and with Redis Cloud . Self-hosted deployments are not supported at the moment. If you want to deploy sshx, you'll need to properly implement HTTP/TCP reverse proxies, gRPC forwarding, TLS termination, private mesh networking, and graceful shutdown. Please do not run the development commands in a public setting, as this is insecure.

Fast, collaborative live terminal sharing over the web

terminal,collaborative,rust,web,ssh,share,tty

teamhanko/hanko

About Hanko Hanko is an open-source authentication and user management solution with a focus on moving the login beyond passwords while being 100% deployable today. Built for passkeys as introduced by Apple, Google, and Microsoft Fast integration with Hanko Elements web components (login box and user profile) API-first, small footprint, cloud-native Available for self-hosting and on Hanko Cloud . Hanko is built and maintained by Hanko.io , an active member of the FIDO Alliance . We take you on the journey beyond passwords ... ... and make sure your users won't get lost on the way. Passwordless logins have been promised to us for quite some time. But until now, "passwordless" was mostly a compromise that only worked for some of the users and had some severe drawbacks that ultimately led to passwords still being present at almost every login. It's only very recently that passkeys were announced, and the ecosystem of devices, browsers, and operating systems is finally ready to truly move beyond passwords. With most devices and browsers now shipping with passkey support and convenient built-in authentication technology like Touch ID, Face ID, and Windows Hello, a much better login experience is enabled that will replace passwords for good. Hanko is built for that shift. Build your passkey-powered auth stack with a few lines of code – and never look back. Architecture The main building blocks of the Hanko project are - backend - An authentication API for passkeys, passcodes, and (optional) passwords, OAuth SSO, as well as user management and JWT issuing - hanko-elements - Web components made for Hanko backend that provide onboarding and login functionality and are customizable with CSS - hanko-frontend-sdk - A client package for using the Hanko API The remainder of the repository consists of: - quickstart - A quickstart example app showing off Hanko's login experience and acting as a reference implementation - examples - Example implementations for a number of frameworks - docs - The Hanko documentation ( docs.hanko.io ) -> Moved to its own repo here: https://github.com/teamhanko/docs Getting started Try our hosted live example and our companion page passkeys.io or use the quickstart app to get a feel for the user experience provided by an application that leverages the Hanko backend API and our custom web component To run the project locally, there are two options available: Bare metal: Head over to the backend section to learn how to get it up and running for your own project. Use Hanko Cloud for a hosted backend. Docker: If you prefer to use Docker to run the project locally, please visit the Run the quickstart for information on how to run the project. This will create everything, including frontend and backend components. If you wish to keep only the backend components, you can modify the quickstart.yaml to remove the unnecessary services. To make changes to the configuration to meet your needs, modify config.yaml . Then, integrate hanko-elements – we provide example applications and guides for your favourite frontend framework in the official documentation if you have an enterprise license or use Hanko Cloud you can also integrate SAML SSO . Feel free to use this guide to start with SAML SSO If you want to use the Hanko backend API but prefer to build your own UI, you can still make use of the hanko-frontend-sdk . It forms the basis of our web components, and the client it provides handles communication with the Hanko backend API and saves you the time of rolling your own. Contact us Schedule a Hanko demo. Learn how Hanko will speed up your registration and login flows with passkeys. Roadmap Watch our releases, leave a star, join our Discord community , or sign up to our product news to follow the development. Here's a brief overview of our current roadmap: | Status | Feature | |:------:| :--- | |✅| Passkeys | |✅| Email passcodes | |✅| Passwords | |✅| JWT signing | |✅| User management API | |✅| 📢 Hanko Alpha Release | |✅| <hanko-auth> web component | |✅| Customizable CSS | |✅| 📢 Hanko Beta Release | |✅| JavaScript frontend SDK | |✅| Passkey autofill ( Conditional UI ) | |✅| Audit logs API | |✅| Security Key support | |✅| Mobile app support | |✅| <hanko-profile> web component | |✅| Rate limiting | |✅| OAuth logins (Sign in with Apple/Google/GitHub) | |✅| i18n & custom translations | |✅| User import | |✅| Disable sign-ups | |✅| User export | |✅| SAML Enterprise SSO | |✅| Webhooks | |⚙️| API-supported auth flows | |⚙️| Passkey-only and OAuth-only configurations | |⚙️| Username support (non-email) | |⚙️| Optional / user-deleteable passwords | |⚙️| OIDC Enterprise SSO | |⚙️| 2FA (TOTP, security keys) | | | Email templates & i18n | | | Refresh tokens / sessions | | | 📢 Hanko 1.0 Release | | | <hanko-menu> web component | | | Custom Social SSO connections (OIDC/OAuth2) | | | Email security notifications | | | Custom JWT claims | | | Mobile SDKs | | | SMS passcodes | Additional features that have been requested or that we would like to build but are currently not on the roadmap: - Custom user data / fields - Privileged sessions & step-up authentication - Bot protection / CAPTCHA - Hosted auth pages / OIDC provider Community Questions, bugs, ideas If you have any questions or issues, please check this project's Q&A section in discussions and the open issues . Feel free to comment on existing issues or create a new issue if you encounter any bugs or have a feature request. For yet unanswered questions, feedback, or new ideas, please open a new discussion. Discord community & X We invite you to join our growing Discord community if you want to get the latest updates on passkeys, WebAuthn, and this project or if you just want to chat with us. You can also follow us on X . Licenses hanko-elements and hanko-frontend-sdk are licensed under the MIT License . Everything else in this repository, including hanko backend , is licensed under the AGPL-3.0 .

Authentication and user management system with passkey superpowers

passkeys,webauthn,fido2,authentication,passwordless,jwt,oauth,sign-in-with-apple,sign-in-with-google,sso

joe-bell/cva

cva C lass V ariance A uthority Read the Docs 📖 Documentation Visit cva.style to get started. License Apache-2.0 License © Joe Bell

Class Variance Authority

css,classname,classnames,variants,cva,class-variance-authority

unjs/nitro

Nitro Create web servers that run anywhere! 📖 documentation [!NOTE] You are on the v2 branch. Check main branch for v3 development tree. Contribution Local development - Clone this repository - Install the latest LTS version of [Node.js](https://nodejs.org/en/) - Enable [Corepack](https://github.com/nodejs/corepack) using `corepack enable` - Install dependencies using `pnpm install` - Run tests using `pnpm dev` or `pnpm test` License Published under the MIT license. Made by @pi0 and community 💛 🤖 auto updated with automd

Next Generation Server Toolkit. Create web servers with everything you need and deploy them wherever you prefer.

[]

vercel/platforms

Platforms Starter Kit The all-in-one starter kit for building multi-tenant applications. Introduction · Demo · Deploy Your Own · Guide · Kitchen Sink · Contributing Introduction The Platforms Starter Kit is a full-stack Next.js app with multi-tenancy and custom domain support. Built with Next.js App Router , Vercel Postgres and the Vercel Domains API . Here's a quick 30-second demo: https://github.com/vercel/platforms/assets/28986134/bd370257-0c27-4cf5-8a56-28589f36f0ef Features Multi-tenancy: Programmatically assign unlimited custom domains, subdomains, and SSL certificates to your users using the Vercel Domains API Performance : Fast & beautiful blog posts cached via Vercel's Edge Network , with the ability to invalidate the cache on-demand (when users make changes) using Incremental Static Regeneration + Next.js' revalidateTag API AI Editor : AI-powered Markdown editor for a Notion-style writing experience powered by Novel Image Uploads : Drag & drop / copy & paste image uploads, backed by Vercel Blob Custom styles : Custom fonts, 404 pages, favicons, sitemaps for each site via the Next.js file-based Metadata API Dynamic OG Cards : Each blog post comes with a dynamic OG image powered by @vercel/og Dark Mode : For a better user experience at night Multi-tenant Preview URLs : Preview changes to your client sites using Vercel Preview URLs . Learn more . Deploy Your Own Deploy your own version of this starter kit with Vercel. You can also read the guide to learn how to develop your own version of this template. What is a multi-tenant application? Multi-tenant applications serve multiple customers across different subdomains/custom domains with a single unified codebase. For example, our demo is a multi-tenant application: Subdomain: demo.vercel.pub Custom domain: platformize.co (maps to demo.vercel.pub ) Build your own: app.vercel.pub Another example is Hashnode , a popular blogging platform. Each writer has their own unique .hashnode.dev subdomain for their blog: eda.hashnode.dev katycodesstuff.hashnode.dev akoskm.hashnode.dev Users can also map custom domains to their .hashnode.dev subdomain: akoskm.com → akoskm.hashnode.dev With the Platforms Starter Kit, you can offer unlimited custom domains at no extra cost to your customers as a premium feature, without having to worry about custom nameservers or configuring SSL certificates. Examples of platforms Vercel customers like Hashnode , Super , and Cal.com are building scalable platforms on top of Vercel and Next.js. There are multiple types of platforms you can build with this starter kit: 1. Content creation platforms These are content-heavy platforms (blogs) with simple, standardized page layouts and route structure. “With Vercel, we spend less time managing our infrastructure and more time delivering value to our users.” — Sandeep Panda, Co-founder, Hashnode Hashnode Mintlify Read.cv 2. Website & e-commerce store builders No-code site builders with customizable pages. By using Next.js and Vercel, Super has fast, globally distributed websites with a no-code editor (Notion). Their customers get all the benefits of Next.js (like Image Optimization ) without touching any code. Super.so Typedream Makeswift 3. B2B2C platforms Multi-tenant authentication, login, and access controls. With Vercel and Next.js, platforms like Instatus are able to create status pages that are 10x faster than competitors. Instatus Cal.com Dub Built on open source This working demo site was built using the Platforms Starter Kit and: Next.js as the React framework Tailwind for CSS styling Drizzle as the ORM for database access Novel for the WYSIWYG editor Vercel Postgres for the database Vercel Blob for image uploads NextAuth.js for authentication Tremor for charts Vercel for deployment Contributing Start a discussion with a question, piece of feedback, or idea you want to share with the team. Open an issue if you believe you've encountered a bug with the starter kit. Author Steven Tey ( @steventey ) License The MIT License.

A full-stack Next.js app with multi-tenancy and custom domain support. Built with Next.js App Router and the Vercel Domains API.

nextjs,vercel,tailwindcss,prisma,custom-domains,multi-tenancy,multi-tenant-applications,vercel-ai,vercel-postgres,vercel-blob

slowmist/Blockchain-dark-forest-selfguard-handbook

Blockchain dark forest selfguard handbook Master these, master the security of your cryptocurrency. :fire:Website: https://darkhandbook.io/ :cn:中文版： 《区块链黑暗森林自救手册》 :jp:日本語版： ブロックチェーンのダークフォレストにおける自己防衛のためのハンドブック :kr:한국어 버전： 블록체인 다크 포레스트 셀프가드 핸드북 Note: V1, Update Logs, please see the Chinese version. Author: Cos@SlowMist Team Contact me：Twitter( @evilcos )、即刻(@余弦.jpg) Translator: Alphatu | C. | CJ | JZ | Lovepeace | Neethan | pseudoyu | SassyPanda | ss | XL Proofreader: SassyPanda | JZ | Neethan | Alphatu | pseudoyu :anchor: Contents - Prologue - A Diagram - Create A Wallet - Download - Mnemonic Phrase - Keyless - Back up your wallet - Mnemonic Phrase / Private Key - Encryption - How to use Your Wallet - AML - Cold Wallet - Hot Wallet - What is DeFi Security - NFT Security - BE CAREFUL With Signing! - Be CAREFUL With Counter-intuitive Signatures Requests! - Some Advanced Attacking Methodologies - Traditional Privacy Protection - Operation System - Mobile phone - Network - Browsers - Password Manager - Two-Factor Authentication - Scientific Internet Surfing - Email - SIM Card - GPG - Segregation - Security of Human Nature - Telegram - Discord - "Official" phishing - Web3 Privacy Issues - Blockchain Shenanigans - What to do When You get hacked - Stop Loss First - Protect The Scene - Root Cause Analysis - Source Tracing - Conclusion of Cases - Misconception - Code Is Law - Not Your Keys, Not Your Coins - In Blockchain We Trust - Cryptographic Security is Security - Is it humiliating to be hacked? - Immediately Update - Conclusion - Appendix - Security rules and principles - Contributors - The Tools - Official Sites Prologue First of all, congratulations for finding this handbook! No matter who you are - if you are a cryptocurrency holder or you want to jump into the crypto world in the future, this handbook will help you a lot. You should read this handbook closely and apply its teachings in real life. Additionally, to understand this handbook completely requires some background knowledge. However, please do not worry. As for beginners, do not be afraid of the knowledge barriers which can be overcome. If you encounter something that you don't understand, and need to explore more, Google is highly recommended. Also, it is important to keep one security rule in mind: Be skeptical! No matter what information you see on the web, you should always seek out at least two sources for cross-reference. Again, always be skeptical :) including the knowledge mentioned in this handbook. Blockchain is a great invention that brings about a change in production relations and solves the problem of trust to some degree. Specifically, blockchain creates many "trust" scenarios without the need for centralization and third parties, such as immutability, execution as agreed, and prevention of repudiation. However, the reality is cruel. There are many misunderstandings about blockchain, and the bad guys will use these misunderstandings to exploit the loophole and steal money from people, causing a lot of financial losses. Today, the crypto world has already become a dark forest. Please remember the following two security rules to survive the blockchain dark forest. Zero Trust : To make it simple, stay skeptical, and always stay so. Continuous Security Validation : In order to trust something, you have to validate what you doubt, and make validating a habit. Note: The two security rules above are the core principles of this handbook , and all the other security principles mentioned in this handbook are derived from them. Okay, that's all for our introduction. Let's start with a diagram and explore this dark forest to see what risks we will encounter and how we should deal with them. A Diagram You can skim through this diagram before taking a closer look at the rest of the handbook. It is all about the key activities in this world (whatever you want to call it: blockchain, cryptocurrency or Web3), which consists of three main processes: creating a wallet, backing up a wallet and using a wallet. Let's follow these three processes and analyze each of them. Create A Wallet The core of the wallet is the private key (or seed phrase). Here's how the private key looks like: 0xa164d4767469de4faf09793ceea07d5a2f5d3cef7f6a9658916c581829ff5584 In addition, here's how the seed phrase looks like: cruel weekend spike point innocent dizzy alien use evoke shed adjust wrong Note: We are using Ethereum as an example here. Please check out more details of private keys/seed phrase yourself. The private key is your identify. If the private key is lost/stolen, then you lost your identify. There are many well-known wallet applications, and this handbook won't cover all of them. However, I will mention some specific wallets. Please note, the wallets mentioned here can be trusted to some degree. But I cannot guarantee they will have no security issues or risks, expected or not, during use (I won't repeat more. Please always keep in mind the two main security rules mentioned in the prologue) Classified by application, there are PC wallets, browser extension wallets, mobile wallets, hardware wallets and web wallets. In terms of internet connection, they can be mainly divided into cold wallets and hot wallets. Before we jump into the crypto world, we must first think about the purpose of the wallet. The purpose not only determines which wallet we should use, but also how we use the wallet. No matter what kind of wallet you choose, one thing is for sure: after you have enough experience in this world, one wallet is not enough. Here we should keep in mind another security principle: isolation, i.e., don't put all your eggs in one basket.The more frequently a wallet is used, the more risky it is. Always remember: when trying anything new, first prepare a separate wallet and try it out for a while with a small amount of money. Even for a crypto veteran like me, if you play with fire, you are more easily to get burned. Download This sounds simple, but in fact it is not easy. The reasons are as follows: Many people cannot find the real official website, or the right application market, and eventually install a fake wallet. Many people do not know how to identify whether the downloaded application has been tampered or not. Thus, for many people, before they enter the blockchain world, their wallet is already empty. To solve the first problem above, there are some techniques to find the correct official website, such as using Google(Exercise caution with the advertised entries in search results, as they are often unreliable.) using well-known official websites, such as CoinMarketCap asking trusted people and friends You can cross-reference the information obtained from these different sources, and ultimately there is only one truth:) Congratulations, you have found the correct official website. Next, you have to download and install the application. If it is a PC wallet , after downloading from the official website, you need to install it yourself. It is highly recommended to verify whether the link has been tampered before installation. Although this verification may not prevent cases where the source code was altered completely (due to insider scam, internal hacking, or the official website may be hacked, etc.) However, it can prevent cases such as the partial tampering of the source code, man-in-the-middle attack, etc. The method to verify whether a file has been tampered is the file consistency check. Usually there are two ways: Hash checks : such as MD5, SHA256, etc. MD5 works for most cases, but there is still a tiny risk of hash collision, so we generally choose SHA256, which is safe enough. GPG signature verification : this method is also very popular. It is highly recommended to master GPG tools, commands, and methods. Although this method is a bit difficult for newcomers, you will find it very useful once you get familiar with it. However, there are not many projects in the crypto world that provides verification. So, it is lucky to find one. For example, here is a bitcoin wallet called Sparrow Wallet. Its download page says "Verifying the Release", which is really impressive, and there are clear guidelines for both of the methods mentioned above, so you can use for reference: https://sparrowwallet.com/download/ The download page mentioned two GPG tools: GPG Suite, for MacOS. Gpg4win, for Windows. If you pay attention, you will find the download pages for both GPG tools give some instructions on how to check the consistency of both methods. However, there is no step-by-step guide, that is to say, you need to learn and practice yourself:) If it is a browser extension wallet , such as MetaMask, the only thing you have to pay attention to is the download number and rating in the Chrome web store. MetaMask, for example, has more than 10 million downloads and more than 2,000 ratings (though the overall rating is not high). Some people might think that the downloads numberand ratings may be inflated. Truth to be told, it is very difficult to fake such a large number. The mobile wallet is similar to the browser extension wallet. However, it should be noted that the App Store has different versions for each region. Cryptocurrency is banned in Mainland China, so if you downloaded the wallet with your Chinese App Store account, there is only one suggestion: don't use it, change it to another account in a different region such as the US and then re-download it. Besides, the correct official website will also lead you to the correct download method (such as imToken, OneKey, Trust Wallet, etc. It is important for official websites to maintain high website security. If the official website is hacked, there will be big problems.). If it is a hardware wallet , it is highly recommended to buy it from the official website. Do not buy them from online stores. Once you receive the wallet, you should also pay attention to whether the wallet is inact. Of course, there are some shenanigans on the packaging that are hard to detect. In any case, when using a hardware wallet, you should create the seed phrase and wallet address at least three times from scratch. And make sure that they are not repeated. If it is a web wallet , we highly recommend not to use it.Unless you have no choice, make sure it is authentic and then use it sparingly and never rely on it. Mnemonic Phrase After creating a wallet, the key thing that we deal with directly is the mnemonic phrase/seed phrase, not the private key, which is easier to remember. There are standard conventions for mnemonic phrases (e.g., BIP39); there are 12 English words in general; it could be other numbers (multiples of 3), but not more than 24 words. Otherwise it is too complicated and not easy to remember. If the number of words is less than 12, the security is not reliable. It is common to see 12/15/18/21/24 words. In the blockchain world, 12-word is popular and secure enough.However, there are still hardcore hardware wallets such as Ledger that starts with 24 words. In addition to English words, some other languages are also available, such as Chinese, Japanese, Korean and so on. Here is a 2048 words list for reference: https://github.com/bitcoin/bips/blob/master/bip-0039/bip-0039-wordlists.md When creating a wallet, your seed phrase is vulnerable. Please be aware that you are not surrounded by people or webcams or anything else that can steal your seed phrase. Also, please pay attention to whether the seed phrase is randomly generated. Normally well-known wallets can generate a sufficient number of random seed phrases. However, you should always be careful. It's hard to know whether there's something wrong with the wallet. Be patient because it can be very beneficial to develop these habits for your security. Lastly, sometimes you can even consider disconnecting from the Internet to create a wallet, especially if you are going to use the wallet as a cold wallet. Disconnecting from the Internet always works. Keyless Keyless means no private key. Here we divide Keyless into two major scenarios (for ease of explanation. Such division is not industry standard) Custodial . Examples are centralized exchange and wallet, where users only need to register accounts and do not own the private key. Their security is completely dependent on these centralized platforms. Non-Custodial . The user has a private key-like control power, which is not an actual private key (or seed phrase). It relies on well-known Cloud platforms for hosting and authentication/authorization. Hence the security of the Cloud platform becomes the most vulnerable part. Others make use of secure multi-party computing (MPC) to eliminate single point of risk, and also partner with popular Cloud platforms to maximise user experience. Personally, I have used various kinds of Keyless tools. Centralized exchanges with deep pockets and good reputations provide the best experience. As long as you are not personally responsible for losing the token (such as if your account information was hacked), centralized exchanges will usually reimburse your loss. The MPC-based Keyless program looks very promising and should be promoted . I have good experience withZenGo, Fireblocks and Safeheron. The advantages are obvious: MPC algorithm engineering is becoming more and more mature on the well-known blockchains, and only needs to be done for private keys. One set of ideas can solve the problem of different blockchains having vastly different multi-signature schemes, creating a consistent user experience, which is what we often call: universal multi-signature. It can ensure that the real private key never appears and solve the single point of risk through multi-signature calculation. Combined with Cloud (or Web2.0 technology) makes MPC not only secure but also creates a good experience. However, there are still some disadvantages: Not all open source projects can meet the accepted standards of the industry. More work needs to be done. Many people basically only use Ethereum (or EVM-based blockchain). As such, a multi-signature solution based on smart contract approach like Gnosis Safe is enough. Overall, no matter which tool you use, as long as you feel safe and controllable and have a good experience, it's a good tool. So far we have covered what we need to be aware of regarding the creation of wallets. Other general security issues will be covered in later sections. Back up your wallet This is where many good hands would fall into traps, including myself. I did not back up properly and I knew it would happen sooner or later. Luckily, it was not a wallet with a large amount of assets and friends at SlowMist helped me recover it. Still, it was a scary experience which I don't think anyone would ever want to go through. So buckle up and let's learn how to back up your wallet safely. Mnemonic Phrase / Private Key When we talk about backing up a wallet, we are essentially talking about backing up the mnemonic phrase (or the private key. For convenience, we will use the mnemonic phrase in the following). Most mnemonic phrases can be categorized as follows: Plain Text With Password Multi-signature Shamir's Secret Sharing, or SSS for short I will briefly explain each type. Plain Text , Plain text is easy to understand. Once you have those 12 English words, you own the assets in the wallet. You can consider doing some special shuffling, or even replace one of the words with something else. Both would increase the difficulty for hackers to hack into your wallet, however, you would have a big headache if you forget about the rules. Your memory isn't bulletproof. Trust me, your memory will tangle up after several years. A few years ago, when I used the Ledger hardware wallet, I changed the order of the 24-word-mnemonic phrase. After a few years, I forgot the order and I wasn't sure if I had replaced any word. As mentioned earlier, my problem was solved with a special code breaker program that uses brute force to guess the correct sequence and words. With Password , According to the standard, mnemonic phrases can have a password. It's still the same phrase but with the password, a different seed phrase will be obtained. The seed phrase is used to derive a series of private keys, public keys and corresponding addresses. So you should not only back up the mnemonic phrases, but also the password. By the way, private keys can also have a password and it has its own standards, such as BIP 38 for bitcoin and Keystore for ethereum. Multi-Signature , As the name suggests, it requires signatures from multiple people to access wallets. It's very flexible as you can set your own rules. For example, if there're 3 people have the key (mnemonic words or private keys), you can require at least two persons to sign to access the wallets. Each blockchain has its own multi-signature solution. Most well-known Bitcoin wallets support multi-signature. However, in Ethereum, multi-signature is mainly supported through smart contracts, such as Gnosis Safe. Furthermore, MPC, or Secure Multi-Party Computation is becoming more and more popular.. It provides an experience similar to the traditional multi-signature, but with different technology. Unlike multi-signature, MPC is blockchain agnostic and can work with all protocols. SSS , Shamir's Secret Sharing, SSS breaks down the seed into multiple shares (normally, each share contains 20 words). To recover the wallet, a specified number of shares has to be collected and used. For details, refer to the industry best practices below: https://guide.keyst.one/docs/shamir-backup https://wiki.trezor.io/Shamir_backup Using solutions such as multi-signature and SSS will give you peace of mind and avoid single-point risks, but it could make management relatively complicated and sometimes multiple parties will be involved. There is always a compromise between convenience and security. It is up to the individual to decide but never be lazy in principles. Encryption Encryption is a very, very broad concept. It doesn't matter if the encryption is symmetric, asymmetric or uses other advanced technologies; as long as an encrypted message can be easily decrypted by you or your emergency handling team easily but nobody else after decades, it is good encryption. Based on the security principle of "zero trust", when we are backing up wallets, we have to assume that any step could be hacked, including physical environments such as a safe. Keep in mind that there is no one other than yourself who can be fully trusted. In fact, sometimes you can't even trust yourself, because your memories may fade away or misplaced. However, I won't make pessimistic assumptions all the time, otherwise it would lead me to some unwanted results. When backing up, special consideration must be given to disaster recovery. The main purpose of disaster recovery is to avoid a single point of risk. What would happen if you are gone or the environment where you store the backup is down? Therefore, for important stuff, there must be a disaster recovery person and there must be multiple backups. I won't elaborate too much on how to choose the disaster recovery person because it depends on who you trust. I will focus on how to do the multi-backups. Let's take a look at some basic forms of backup locations: Cloud Paper Device Brain Cloud , Many people don't trust backup on Cloud, they think it is vulnerable to hacker attacks. At the end of the day, it is all about which side - the attacker or the defender - put in more effort, in terms of both manpower and budgets. Personally, I have faith in cloud services powered by Google, Apple, Microsoft, etc., because I know how strong their security teams are and how much they have spent on security. In addition to fighting against external hackers, I also care a lot about internal security risk control and private data protection. The few service providers I trust are doing a relatively better job in these areas. But nothing is absolute. If I choose any of these cloud services to back up important data (such as wallets), I will definitely encrypt the wallets at least one more time. I strongly recommend mastering GPG. It can be used for the "signature verification", and provides strong security of encryption and decryption in the meantime. You can learn more about GPG at: https://www.ruanyifeng.com/blog/2013/07/gpg.html Okay, you have mastered GPG :) Now that you have encrypted related data in your wallet (mnemonic phrase or private key) with GPG in an offline secured environment, you can now throw the encrypted files directly into these cloud services and save it there. All will be good. But I need to remind you here: never lose the private key to your GPG or forget the password of the private key... At this point, you might find this extra level of security is quite troublesome: you have to learn about GPG and back up your GPG private key and passwords. In reality, if you have done all the aforementioned steps, you are already familiar with the process and won't find it as difficult or troublesome. I will say no more because practice makes perfect. If you want to save some effort, there is another possibility but its security may be discounted. I can't measure the exact discount but sometimes I would be lazy when I would use some well-known tools for assistance. That tool is 1Password. The latest version of 1Password already supports direct storage of wallet-related data, such as mnemonic words, passwords, wallet addresses, etc., which is convenient for users. Other tools (such as Bitwarden) can achieve something similar, but they are not as convenient. Paper , Many hardware wallets come with several high-quality paper cards on which you can write down your mnemonic phrases (in plaintext, SSS, etc.). In addition to paper, some people also use steel plates (fire-resistant, water-resistant and corrosion-resistant, of course, I have not tried those). Test it after you copy over the mnemonic phrases and if everything works, put it in a place where you feel secure, such as in a safe. I personally like using paper a lot because if properly stored, paper has a much longer lifespan than electronics. Device , It refers to all kinds of equipment; electronics are a common type for backup, such as a computer, an iPad, an iPhone, or a hard drive, etc, depending on personal preference. We also have to think about the secure transmission between devices. I feel comfortable using peer-to-peer methods such as AirDrop and USB where it is difficult for a middleman to hijack the process. I am just naturally uneasy about the fact that electronic equipment may break down after a couple of years, so I maintain the habit of checking the device at least once a year. There are some repeated steps (such as encryption) which you can refer to the Cloud section. Brain , Relying on your memory is exciting. In fact, everyone has their own "memory palace". Memory is not mysterious and can be trained to work better. There are certain things that are indeed safer with memory. Whether to rely solely on the brain is a personal choice. But pay attention to two risks: firstly, memory fades away as time goes and could cause confusion; the other risk is that you may have an accident. I will stop here and let you explore more. Now you are all backed up. Don't encrypt too much, otherwise you will suffer from yourself after several years. According to the security principle of "continuous verification", your encryption and backup methods, whether excessive or not, must be verified continuously, both regularly as well as randomly. The verification frequency depends on your memory and you do not have to complete the whole process. As long as the process is correct, partial verification also works. Finally, it is also necessary to pay attention to the confidentiality and security of the authentication process. Okay, let's take a deep breath here. Getting started is the hardest part. Now that you are ready, let's enter this dark forest :) How to use Your Wallet Once you have created and backed up your wallets, it comes to the real challenge. If you don't move around your assets frequently, or you barely interact with any smart contracts of DeFi, NFT, GameFi, or Web3, the popular term referred to frequently these days, your assets should be relatively safe. AML However, "relatively safe" doesn't mean "no risk at all". Cause "you never know which comes first, tomorrow or accidents", right?. Why is it? Think about it, where did you get the cryptocurrency? It didn't just come from nowhere, right? You may encounter AML (Anti Money Laundering) on all the cryptocurrencies you get any time. This means that the cryptocurrency you're holding at the moment may be dirty, and if you're not lucky, it may even be frozen directly on the chain. According to public reports, Tether once freezed some USDT assets as per request from law enforcement agencies. The list of frozen funds can be found here. https://dune.xyz/phabc/usdt---banned-addresses You can verify if an address is frozen by Tether from the USDT contract. https://etherscan.io/token/0xdac17f958d2ee523a2206206994597c13d831ec7#readContract Use the target wallet address as input int isBlackListed to check. Other chains that take USDT have similar verification way. However, your BTC and ETH should never ever get frozen. If this does happen one day in the future, the belief of decentralization would crash as well. Most cryptocurrency asset frozen cases we have heard today actually happened in centralized platforms (such Binance, Coinbase, etc.) but not on the blockchain. When your cryptocurrency stays in Centralized Exchange platforms, you don't actually own any of them. When the centralized platforms freeze your account, they are actually revoking your permission to trade or withdraw. The concept of freezing could be misleading to newbies in the area. As a result, some reckless self media would spread all kinds of conspiracy theories about BitCoin. Though your BTC and ETH assets won't be frozen on the blockchain, centralized exchanges might freeze your assets according to the requirement of AML once your assets get transferred into these platforms and they are involved in any open cases that law enforcements are working on. To better avoid AML issues, always choose platforms and individuals with a good reputation as your counterparty. There are actually a few solutions for this type of problem. For example, on Ethereum, almost all bad guys and people who care a lot about their privacy use Tornado Cash for coin mixing. I won't dig any more into this topic since most methods here are being used for doing evil. Cold Wallet There are different ways to use a cold wallet. From a wallet's perspective, it can be considered as a cold wallet as long as it's not connected to any network. But how to use it when it's offline? First of all, if you just want to receive cryptocurrency, it's not a big deal. A cold wallet could provide excellent experience by working with a Watch-only wallet, such as imToken, OneKey, Trust Wallet, etc. These wallets could be turned into watch-only wallets by simply adding target wallet addresses. If we want to send cryptocurrency using cold wallets, here are the most commonly used ways: QRCode USB Bluetooth All of these require a dedicated app (called Light App here) to work with the cold wallet. The Light App will be online along with the aforementioned Watch-only wallet. Once we understand the underlying essential principle, we should be able to understand these approaches. The essential principle is: eventually, it's just a matter of figuring out how to broadcast signed content onto the blockchain. Detailed process is as follows: The content to be signed is transmitted by the Light App to the Cold Wallet by one of these means. The signature is processed by the cold wallet that has the private key and then transmitted back to the Light App using the same way The Light App broadcasts the signed content on the blockchain. So no matter which method is used, QR code, USB or Bluetooth, it should be following the above process. Of course, details might vary from different methods . For example, QR code has a limited information capacity, so when the signature data is too large, we would have to split it up. It seems to be a bit troublesome, but it becomes better when you get used to it. You would even feel a full sense of security. However, don't consider it 100% secure because there are still risks here, and there have been many cases of heavy losses because of these risks. Here are risk points: The target address of the coin transfer was not checked carefully, resulting in the coin being transferred to someone else. People are lazy and careless, sometimes . For example, most of the time they only check the beginning and ending few bits of a wallet address instead of fully checking the whole address. This leaves a backdoor to bad guys.They will run programs to get the wallet address with the same first and last few bits as your desired target address and then replace your coin transfer target address with the one under their control using some tricks. Coins are authorized to unknown addresses. Usually authorization is the mechanism of the Ethereum smart contract tokens, the "approve" function, with one argument being the target authorization address and the other being the quantity. Many people don't understand this mechanism, so they may authorize an unlimited number of tokens to the target address, at which point the target address has permission to transfer all those tokens away. This is called authorized coin theft, and there are other variants of the technique, but I won't expand on it here. Some signatures that seem not important actually have huge traps in the back, and I won't dig into it now, but will explain the details later. The cold wallet may not have provided enough necessary information, causing you to be careless and misjudged. It all boils down to two points: The user interaction security mechanism of "What you see is what you sign" is missing. Lack of relevant background knowledge of the user. Hot Wallet Compared to a cold wallet, a hot wallet has basically all the risks that a cold wallet would have. Plus, there is one more: the risk of theft of the secret phrase (or private key). At this point there are more security issues to consider with hot wallets, such as the security of the runtime environment. If there are viruses associated with the runtime environment , then there is a risk of getting stolen. There are also hot wallets that have certain vulnerabilities through which the secret phrase can be directly stolen. In addition to the regular coin transfer function, if you want to interact with other DApps (DeFi, NFT, GameFi, etc.), you either have to access them directly with your own browser or interact with the DApps opened in your PC browser via the WalletConnect protocol. Note: References of DApps in this handbook refer by default to smart contract projects running on the Ethereum blockchains. By default, such interactions do not lead to secret phrase theft, unless there is a problem with the wallet security design itself. From our security audits and security research history, there is a risk of wallet secret phrases being stolen directly by malicious JavaScript on the target page. However, this is a rare case, as it is actually an extremely low-level mistake that no well-known wallet is likely to make. None of these are actually my actual concerns here, they are manageable for me (and for you too). My biggest concern/concern is: how does each iteration of a well-known wallet ensure that no malicious code or backdoor is planted? The implication of this question is clear: I verified that the current version of the wallet has no security issues and I'm comfortable using it, but I don't know how secure the next version will be. After all, I or my security team can't have that much time and energy to do all the verifications. There have been several incidents of coin theft caused by malicious code or backdoors as described here, such as CoPay, AToken, etc. You can search for the specific incidents yourself. In this case, there are several ways of doing evil: When the wallet is running, the malicious code packages and uploads the relevant secret phrase directly into the hacker-controlled server. When the wallet is running and the user initiates a transfer, information such as the target address and amount is secretly replaced in the wallet backend, and it is difficult for the user to notice. Corrupting the random number entropy values associated with the generation of secret phrases, which makes them relatively easy to decipher. Security is a thing of ignorance and knowledge, and there are many things that could be easily ignored or missed. So for wallets that hold important assets, my security rule is also simple: no easy updates when it's enough to use. What is DeFi Security When we talk about DApp, it could be DeFi, NFT or GameFi etc. The security fundamentals of these are mostly the same, but they will have their respective specifics. Let's first take DeFi as an example to explain. When we talk about DeFi security, what exactly do we mean? People in the industry almost always only look at smart contracts. It seems that when smart contracts are good, everything will be fine. Well actually, this is far from true. DeFi security includes at least the following components: Smart Contract Security Blockchain Foundation Security Frontend Security Communication Security Human Security Financial Security Compliance Security Smart Contract Security Smart contract security is indeed the most important entry point for security audit, and SlowMist's security audit standards for smart contracts can be found at: https://www.slowmist.com/service-smart-contract-security-audit.html For advanced players, if the security of the smart contract part itself is controllable (whether they can audit themselves or understand security audit reports issued by professional organizations), then it doesn't matter if the other parts are secure. Controllable is a tricky concept, some of which depends on the player's own strength. For example, players have certain requirements in respect of the risk from excessive smart contract authority. If the project itself is strong and the people behind it have a good reputation, complete centralization would not matter. However, for those less well-known, controversial or emerging projects, if you realize that the project's smart contracts possess excessive permission risk, especially if such permissions can also affect your principal or earnings, you will certainly be reluctant. The risk of excessive permission is very subtle. In many cases, it is in place for the admin of the project to conduct relevant governance and risk contingency. But for users, this is a test on human nature. What if the team decides to do evil? So there is a trade-off practice in the industry: adding Timelock to mitigate such risks of excessive permission, for example: Compound, an established and well-known DeFi project, the core smart contract modules Comptroller and Governance, both haveTimelock mechanism added to their admin permission: Comptroller(0x3d9819210a31b4961b30ef54be2aed79b9c9cd3b) Governance(0xc0da02939e1441f497fd74f78ce7decb17b66529) The admin these 2 modulesis Timelock(0x6d903f6003cca6255d85cca4d3b5e5146dc33925) You can directly find out on chain that the Timelock (delay variable) is 48 hours (172,800 seconds): That is to say, if the admin of Compound needs to change some key variables of the target smart contract, the transaction will be recorded after it is initiated on the blockchain, but 48 hours must be waited before the transaction can be finalized and executed. This means that if you would like, you can audit every single operation from the admin, and you will have at least 48 hours to act. For example, if you are unsure, you can withdraw your funds within 48 hours. Another way to mitigate the risk of excessive permission of admin is to add multi-signature, such as using Gnosis Safe for multisig management, so that there will at least be no dictator. It should be noted here that multisig can be "the emperor's new clothes". For example, one person may hold multiple keys. Therefore, the multisig strategy of the target project needs to be clearly stated. Who holds the keys, and the identity of each key holder must be reputable. It is worth mentioning here that any security strategy may lead to the problem of "the emperor's new clothes", which the strategy may appear to be well done, but in reality is not, resulting in an illusion of security. Take another example, Timelock looks good on paper. Actually, there have been cases where Timelock deployed by some projects has backdoors. Generally, users don't look into the source code of Timelock, and they would not necessarily understand it even if they do, so the admin puts a backdoor there, and no one would really notice for a long enough time. In addition to the risk of excessive permission, other elements of smart contract security are also critical. However, I will not expand here, in consideration of the prerequisites for understanding. Here is my advice: you should at least learn to read the security audit report, and practice makes perfect. Blockchain Foundation Security Blockchain foundation security refers to the security of the blockchain itself, such as consensus ledger security, virtual machine security etc. If the security of the blockchain itself is worrisome, the smart contract projects running on the chain would suffer directly. It is so important to choose a blockchain with sufficient security mechanism and reputation, and better with a higher probability of longevity. Frontend Security Frontend security is really the devil. It is too close to the users, and it is especially easy to fool users into deception. Perhaps everyone's main focus is on the wallet and smart contract security, resulting in frontend security being easily overlooked. I want to emphasize again that frontend security is the devil! Allow me to dig deeper. My biggest concern regarding frontend security is: How do I know that the contract I am interacting with from this specific frontend page is the smart contract that I'm expecting? This insecurity is mainly due to two factors: Inside job Third party It is straightforward to understand the inside job. For example, the devs secretly replaces the target smart contract address in the frontend page with a contract address that has a backdoor, or planting an authorization phishing script. When you visit this rigged frontend page, a series of subsequent operations involving cryptos in your wallet may be done in a trap. Before you realized, the coins would be already gone. The third party mainly refers to two types: One is that the dependencies chain is infiltrated. For example, the third-party dependency used by the frontend page has a backdoor which gets sneaked into the target frontend page along with the packaging and release. The following is the package dependency structure of SushiSwap (for illustration only, it doesn't necessarily mean that the project in the screenshot has such issue): The other example is third-party remote JavaScript files imported by the frontend page. If this JavaScript file is hacked, it's possible that the target frontend page gets affected as well, such as OpenSea (for illustration only, it doesn't necessarily mean that the project in the screenshot has such an issue): The reason why we said it's just possible but not certainly is that the risk could be mitigated if devs refer to a third-party remote JavaScript file on the frontend page in the following way: The key point here is a nice security mechanism of HTML5: integrity attribute in tags (SRI mechanism). integrity supports SHA256, SHA384 and SHA512. If third-party JavaScript files do not meet the hash integrity check, the files will not be loaded. This can be a good way to prevent unintended code execution. However, utilizing this mechanism requires the target resource to support CORS response. For details, refer to the following: https://developer.mozilla.org/zh-CN/docs/Web/Security/Subresource_Integrity Communication Security Let's focus on HTTPS security in this section. First, the target website must use HTTPS, and HTTP plaintext transmission should never be allowed. This is because HTTP plaintext transmission is too easy to be hijacked by man-in-the-middle attacks. Nowadays HTTPS is very common as a secure transmission protocol. If there is a man-in-the-middle attack on HTTPS, and attackers have injected malicious JavaScript into the web application's front-end, a very obvious HTTPS certificate error alert will be displayed in the user's browser. Let's use the MyEtherWallet incident as an example to illustrate this point. MyEtherWallet used to be a very popular web application wallet, and up till now it's still very well known. However it's no longer just a web application wallet. As mentioned before, I strongly discourage the use of web application wallets due to security reasons. In addition to various issues in front-end security, HTTPS hijacking is also a big potential risk. On April 24, 2018, there was a major security incident of HTTPS hijacking in MyEtherWallet. The recap of the incident can be found here: https://www.reddit.com/r/MyEtherWallet/comments/8eloo9/official_statement_regarding_dns_spoofing_of/ https://www.reddit.com/r/ethereum/comments/8ek86t/warning_myetherwalletcom_highjacked_on_google/ In the attack, the hacker hijacked the DNS service (Google Public DNS) used by a large number of MyEtherWallet users via BGP, an ancient routing protocol, which directly led to the display of HTTPS error alerts in every user's browser when they tried to visit MyEtherWallet website. In fact, users should stop when they see this alert, as it basically indicates that the target web page has been hijacked. In reality however, many users just quickly ignored the alert and proceeded to continue with their interactions with the hijacked site, because they didn't understand the security risk behind the HTTPS error alert at all. Since the target web page had been hijacked and the hacker had injected malicious JavaScript in there, upon users' interaction, the hackers would have successfully stolen their plaintext private key and transferred away their funds (mostly ETH). This is definitely a classic case where hackers used BGP hijacking techniques to steal crypto. It's just overkill. Ever after this there have been several similar cases, and I won't mention them in detail here. To the user there is only one thing that really needs attention: if you ever decide to use a web application wallet, or try to interact with a DApp, always make sure you stop and close the page whenever you see a HTTPS certificate error alert! And your funds will be fine. There is a cruel reality in security: when there is a risk, don't give users any choices. As if you do, there will always be users falling into the trap for whatever reasons. In fact, the project team needs to take up the responsibility. As of today, there are already very effective security solutions to the HTTPS hijacking issue mentioned above: the project team needs to properly configure HSTS. HSTS stands for HTTP Strict Transport Security; it is a web security policy mechanism supported by most modern browsers. If HSTS is enabled, in case of a HTTPS certificate error the browser will force users to stop accessing the target web applications and the restriction can't be bypassed. Now you get what I mean? Human Nature Security This section is easy to understand. For example the project team is evil minded and acts in a dishonest way. I have mentioned some relevant contents in previous sections, so here I won't go into more details. More to be covered in later sections. Financial Security Financial Security should be deeply respected. In DeFi, users pay utmost attention to token price and return. They want superior, or at least steady return on investment. In other words, as a user, I play the game to win and if I lose, at least I need to be convinced that it is a fair game. This is just human nature. Financial security in DeFi is susceptible to attacks in the forms of: Unfair launch practices such as pre-mining or pre-sale; Crypto whale attack; Pump and dump; Black swan events, like sudden market waterfall; or let's say when one DeFi protocol is nested or interoperated with other DeFi/Tokens, its security/reliability will be highly depending on other protocols Other technical attacks or what we refer to as scientific techniques such as front running, sandwich attack, flash loan attacks, etc Compliance Requirements Compliance requirement is a very big topic, the previously mentioned AML(Anti Money Laundering) is just one of the points. There are also aspects like KYC(Know Your Customer), sanctions, securities risks, etc. In fact for us users these are not something under our control. When we interact with a certain project, as it may be subject to relevant regulations in certain countries, our privacy information might get collected. You might not care about such privacy issues, but there are people who do. For example, in early 2022 there was a small incident: some wallets decided to support Address Ownership Proof Protocol(AOPP) protocol: I took a look at the protocol design, it turned out that wallets supporting AOPP might leak user privacy. Regulators might get to know the interconnection between a regulated crypto exchange and an unknown external wallet address. https://gitlab.com/aopp/address-ownership-proof-protocol No wonder many privacy-oriented wallets are so concerned about user's feedback and quickly removed AOPP support from their products. But to be honest: The protocol design is quite interesting. I have noticed that some wallets have no plans to remove support for AOPP, such as EdgeWallet. Their opinion is that AOPP doesn't necessarily expose more user privacy, on the contrary it helps to enhance the circulation of cryptocurrency. In many regulated crypto exchanges, users are not allowed to withdraw to a particular external wallet address, before he can prove his ownership to it. At first, the well-known hardware wallet Trezor refused to remove AOPP support. But later it was forced to compromise and did so due to pressures from the community and users on Twitter. As you can see, it's such a small incident but to some people, privacy is really important. This is not to say that we should go against regulations, and totally ignore compliance requirements. As a matter of fact I do believe it's necessary to have a certain level of compromise to compliance requirements. We won't continue to deep dive into this topic, feel free to digest the contents in your own ways. So far, we have covered the majority of content in the DeFi Security section. What's more, there are also security issues introduced by future additions or updates. We often say "security posture is dynamic, not static". For example nowadays most project teams do security audits and show clean security audit reports. If you ever read the good-quality reports carefully you will notice that these reports will clearly explain the scope, timeframe, and the unique identifier of the audited contents (e.g. the verified open source smart contract address, or the commit address on GitHub repo, or the hash of the target source code file). This is to say, the report is static, but if in a project you have observed any deviations from what is mentioned in the report, you can point it out. NFT Security All the previously mentioned contents on DeFi security can be applied to NFT security, and NFT itself has a few very specific and unique security topics, for example: Metadata security Signature security Metadata refers mainly to the embedded picture, motion pictures and other contents. It's recommended to refer to OpenSea on the specific standards: https://docs.opensea.io/docs/metadata-standards There are two main security concerns that may arise here: One is that the URI where the image (or motion picture) is located might not be trustworthy. It can just be a randomly selected centralized service, on one hand there is no guarantee of availability, on the other hand the project team can modify the images at will, thus the NFT will no longer become an immutable "digital collectible". Generally it's recommended to use decentralized storage solutions such as IPFS, Arweave, and select a well-known URI gateway service. Another is the potential for privacy leakage. A randomly selected URI service might capture user's basic information (such as IP, User-Agent, etc) Signing security is another big concern here, and we will illustrate it below. BE CAREFUL With Signing! Signature security is something that I want to mention specifically as there are SO MANY pitfalls and you should be careful all the time. There have been several incidents, especially on NFT trading. However, I have noticed that not too many people understand how to prepare for and deal with such security problems. The underlying reason is few people have ever made the problem clear enough. The NO.1 and most important security principle in signature security is: What you see is what you sign . That is, the message in the signature request you received is what you should expect after signing. After you sign it, the result should be what you expected instead of something you would regret. Some details of signature security have been mentioned in the "Cold Wallet" section. If you can't recall, I would suggest you revisit that section. In this section, we will focus on other aspects. There were several well-known NFT hacks on OpenSea around 2022. On Feb 20th, 2022, there was a major outbreak. The root causes are: Users signed NFT listing requests on OpenSea. Hackers phished to obtain relevant signatures from users. It is actually not hard for hackers to obtain the relevant signature. The hacker needs to 1). construct the message to be signed, 2). hash it, 3). trick the target user to sign the request (this would be a blind signing, which means users don't actually know what they are signing), 4). get the signed content and construct the data. At this point, the user has been hacked. I will use Opensea as an example (in reality, it could be ANY NFT marketplace). After the target user authorizes the NFT listing operation in the marketplace, the hacker would construct the message to be signed. After hashing it with Keccak256, a signature request would pop up on the phishing page. Users would see something like the following: Look closely. What kind of information can we get from this MetaMask popup window? Account Info and account balance, the source website where the signature request comes from, the message that users are about to sign and...nothing else. How could users suspect that the disaster is already on the way? And how could they realize that once they click the "Sign" button, their NFTs would be stolen. This is actually an example of blind signing. Users are not required to sign within the NFT marketplace. Instead, users can be tricked into any phishing website to sign the message without fully understanding the actual meaning and consequence of these signatures. Unfortunately, hackers know. As a user, just keep in mind: NEVER BLIND SIGN ANYTHING. OpenSea used to have the blind signing problem, and they fixed it by adopting EIP-712 after Feb 20th 2022. However, without blind signing, users could still be careless and hacked in other ways. The most essential reason why this is happening is that the signing isn't restricted to follow the browser's same-origin policy. You can simply understand it as: the same-origin policy can ensure that an action only happens under a specific domain and will not cross domains, unless the project team intentionally wants domain crossing to happen. If signing follows the same-origin policy, then even if the user signs a signature request generated by the non-target domain, hackers can't use the signature for attacks under the target domain. I will stop here before going into more details. I have noticed new proposals on security improvement at the protocol level, and I hope this situation can be improved as soon as possible. We have mentioned most of the major attack formats that could occur when signing a message, but there are actually quite a few variants. No matter how different they look, they follow similar patterns. The best way to understand them is to reproduce an attack from beginning to end by yourselves, or even create some unique attack methods. For example, the signature request attack mentioned here actually contains a lot of details, such as how to construct the message to be signed, and what is generated exactly after signing? Is there any authorization methods other than "Approve" (yes, for example: increaseAllowance). Well, it would be too technical if we expand here. The good thing is you should already understand the importance of signing a message. Users can prevent such attacks at the source by canceling the authorization/approval. The following are some well-known tools that you could use. Token Approvals >https://etherscan.io/tokenapprovalchecker >This is the tool for authorization check and cancellation provided by Ethereum's official browser. Other EVM compatible blockchains have something similar as their blockchain browsers are basically developed by Etherscan. For example: >https://bscscan.com/tokenapprovalchecker >https://hecoinfo.com/tokenapprovalchecker >https://polygonscan.com/tokenapprovalchecker >https://snowtrace.io/tokenapprovalchecker >https://cronoscan.com/tokenapprovalchecker Revoke.cash >https://revoke.cash/ >Super old school with good fame &Multi-chain Supporting with increasingly power Rabby extension wallet >https://rabby.io/ >One of the wallets that we have collaborated with a lot. The number of EVM compatible blockchains where they provide "authorization check and cancellation" function is the most that I have ever seen :warning: Note : If you want a more comprehensive and in-depth understanding of SIGNATURE SECURITY, please check the extensions in the following repository additions as a reference: https://github.com/evilcos/darkhandbook It is true that the knowledge of SIGNATURE SECURITY is quite challenging for beginners. The repository compiles relevant content, and carefully reading through it will help you grasp the security knowledge. Thus, you will no longer find it difficult. (If you can read and understand everything, I believe that security knowledge will no longer be tough for you :) Be CAREFUL With Counter-intuitive Signatures Requests! I would like to particularly mention another risk: counter-intuitive risk . What is counter-intuitive? For example, you are already very familiar with Ethereum, and have become an OG of all kinds of DeFi and NFTs. When you first enter the Solana ecosystem, you probably would encounter some similar phishing websites. You may feel so well prepared that you start to think "I have seen these a thousand times in the Ethereum ecosystem and how could I get fooled?" In the meantime, hackers would be happy as you already got fooled. People follow their intuitive feelings which makes them careless. When there's a counter-intuitive attack, people would fall into the trap. Ok, let's take a look at a real case that took advantage of counter-intuitiveness. First of all, a warning: Authorization phishing on Solana is way more cruel. The example above happened on March 5th, 2022. The attackers airdropped NFTs to users in batches (Figure 1). Users entered the target website through the link in the description of the airdropped NFT (www_officialsolanarares_net) and connected their wallets (Figure 2). After they clicked the "Mint" button on the page, the approval window popped up (Figure 3). Note that there was no special notification or message in the pop up window at this time. Once they approved, all SOLs in the wallet would be transferred away. When users click the "Approve" button, they are actually interacting with the malicious smart contracts deployed by the attackers: 3VtjHnDuDD1QreJiYNziDsdkeALMT6b2F9j3AXdL4q8v The ultimate goal of this malicious smart contract is to initiate "SOL Transfer", which transfers almost all of the user's SOLs. From analysis of on-chain data, the phishing behavior continued for several days, and the number of victims kept increasing during the period of time. There are two pitfalls from this example that you need to pay attention to: 1. After the user approves, the malicious smart contract can transfer the user's native assets (SOL in this case). This is not possible on Ethereum. The authorization phishing on Ethereum can only affect other tokens but not the native asset of ETH . This is the counter-intuitive part that would make users lower vigilance. 2. The most well-known wallet on Solana, Phantom, has loopholes in its security mechanism that it doesn't follow the "what you see is what you sign" principle (we haven't tested other wallets yet), and it doesn't provide enough risk warning to users. This could easily create security blind spots that cost users' coins. Some Advanced Attacking Methodologies Actually, there are many advanced attacking methodologies, but they are mostly regarded as phishing from the perspective of the public. However, some are no normal phishing attacks. For example: https://twitter.com/Arthur_0x/status/1506167899437686784 Hackers sent a phishing e-mail with such an attachment: A Huge Risk of Stablecoin(Protected).docx To be honest, it is an attractive document. However, once opened user's computer will be implanted with a Trojan (generally through Office macro or 0day / 1day exploit), which usually contains the following functions: Collecting all sorts of credentials, for example, browser related, or SSH related, etc. In this way, hackers can extend their access to other services of the target user. Therefore, after infection users are generally advised not only to clean up the target device, but also relevant account permissions as well. Keylogger, in particular targeting those temporarily appearing sensitive information such as passwords. Collecting relevant screenshots, sensitive files, etc. If it is ransomware, all files in the target system would be strongly encrypted, and waiting for the victim to pay for the ransom, usually by bitcoin. But in this case it was not ransomware which has more obvious & noisy behavior and straightforward intentions. In addition, Trojans targeting the crypto industry will be specially customized to collect sensitive information from well known wallets or exchanges, in order to steal user's funds. According to professional analysis, the above mentioned Trojan would conduct a targeted attack on Metamask: https://securelist.com/the-bluenoroff-cryptocurrency-hunt-is-still-on/105488/ The Trojan will replace user's MetaMask with a fake one with back doors. A backdoored MetaMask basically means that any funds you store inside are no longer yours. Even if you are using a hardware wallet, this fake MetaMask will manage to steal your funds by manipulating the destination address or amount information. This approach is specially crafted for well known targets with known wallet addresses. What I have noticed is that many such people are too arrogant to prevent themselves from getting hacked. After the hack, many would learn from the lesson, conduct full reviews, have significant improvements, and also form long term cooperation and friendship with trusted security professionals or agencies. However, there are always exceptions in this world. Some people or projects keep getting hacked again and again. If each time it is because of something no one has encountered before, I would highly respect them and call them pioneers. High chance they will be successful as time goes on. Unfortunately many of the incidents are the results of very stupid and repetitive mistakes that could be avoided easily. I would advise staying away from these projects. Comparingly, those mass phishing attacks are not comprehensive at all. Attackers would prepare a bunch of similarly looking domain names and spread the payloads by buying accounts, followers, and retweets on Twitter or other social platforms. If managed well, many will fall into the trap. There is really nothing special in this kind of phishing attack, and normally the attacker will just brutally make the user authorize tokens (including NFT) in order to transfer them away. There are other kinds of advanced attacks, for example using techniques like XSS, CSRF, Reverse Proxy to smoothen the attack process. I won't elaborate on all of them here, except one very special case (Cloudflare Man-in-the-Middle attack) which is one of the scenarios in Reverse Proxy. There have been real attacks that caused financial loss utilizing this extremely covert method. The problem here is not Cloudflare itself being evil or getting hacked. Instead it's the project team's Cloudflare account that gets compromised. Generally the process is like this: If you use Cloudflare, you will notice this "Worker" module in the dashboard, whose official description is: Building serverless applications and deploying them instantly around the world, achieving excellent performance, reliability and scale. For details, please refer to https://developers.cloudflare.com/workers/ I made a test page a long time ago: https://xssor.io/s/x.html When you visit the page there will be a pop-up window saying: xssor.io, Hijacked by Cloudflare. In fact, this pop-up, and even the whole content of x.html, doesn't belong to the document itself. All of them are provided by Cloudflare. The mechanism is shown below: The indication of the code snippet in the screenshot is very simple: If I were the hacker and I have controlled your Cloudflare account, I can use Workers to inject arbitrary malicious script to any web page. And it's very difficult for the users to realize that the target web page has been hijacked and tampered with, as there will be no error alerts (such as HTTPS certificate error). Even the project team won't easily identify the problem without having to spend a huge amount of time checking the security of their servers and personnel. By the time they realise it is Cloudflare Workers, the loss could already be significant. Cloudflare is actually a good tool. Many websites or web applications will use it as their web application firewall, anti DDoS solution, global CDN, reverse proxy, etc. Because there is a free version, they have a big customer base. Alternatively, there are services like Akaimai etc. Users must pay attention to the security of such accounts. Account security issues arise with the rise of the Internet. It's such a common topic in the world that almost everyone is talking about it everywhere, but still many people are getting hacked because of it. Some root causes might be they don't use a unique strong password for important services (Password managers like 1Password isn't that popular anyway), some might be they don't bother to turn on 2 factor authentication (2FA), or maybe they don't even know of the thingy. Not to mention for some certain services, passwords should be reset at least annually. All right, this will be the end of this section. You only need to understand that this is indeed a dark forest, and you should know about as many attacking methodologies as possible. After seeing enough on paper, if you have at least fallen into the traps once or twice, you can consider yourself as an amateur security professional (which will benefit yourself anyway). Traditional Privacy Protection Congratulations, you've made it to this part. Traditional privacy protection is an old topic: Here's the article I wrote in 2014. You've got to learn a few tricks to protect yourself in the age of privacy breaches. https://evilcos.me/yinsi.html Rereading this article, although this was an entry level article in 2014, however, most of the advice in it is not outdated.After reading the article again, I' ll introduce something new here: in fact, privacy protection is closely related to security. Traditional privacy is the cornerstone of security. This section includes your private keys are part of privacy. If the cornerstones are not secure, the privacy of the cornerstones are meaningless, then the superstructure will be as fragile as a building in the air. The following two resources are highly recommended： SURVEILLANCE SELF-DEFENSE TIPS, TOOLS AND HOW-TOS FOR SAFER ONLINE COMMUNICATIONS https://ssd.eff.org/ SURVEILLANCE SELF-DEFENSE is short for SSD. Launched by the well-known Electronic Frontier Foundation (EFF), which has specially issued relevant guidelines to tell you how to avoid big brother watching you in the monitoring Internet world, of which including several useful tools (such as Tor, WhatsApp, Signal, PGP, etc.) Privacy Guide: Fight Surveillance with Encryption and Privacy Tools https://www.privacytools.io/ The above website is comprehensive listing a number of tools. It also recommends some cryptocurrency exchanges, wallets, etc. However, it should be noted that I don't use very many tools listed on the website, because I have my own way. Thus, you should also develop your own way, with comparing and improving continuously. Here are some highlights of the tools that I suggest that you should use. Operation System Windows 10 Edition (and higher) and macOS are both secure options. If you have the ability, you can choose Linux, such as Ubuntu, or even extremely security & privacy focused ones like Tails, or Whonix. On the topic of Operation System, the most straightforward security principle is: pay close attention to system updates, and apply them asap when available. The capability to master the Operating System comes next. People might ask, what on earth do you need to learn in order to master an Operating System like Windows or MacOS? Isn't it just clicking around? Well it's actually far from being enough. For novice users, a good antivirus software, like Kaspersky, BitDefender, is a must, and they both are available on MacOS. And then, don't forget about download security, which I mentioned before. You will have eliminated most of the risks, if you don't download and install programs recklessly. Next, think about what you are gonna do, if your computer got lost or stolen. Having a boot password is obviously not good enough. If disk encryption is not turned on, bad actors can just take out the harddisk and retrieve the data inside. Thus my advice is that disk encryption should be turned on for important computers. https://docs.microsoft.com/en-us/windows/security/encryption-data-protection https://support.apple.com/en-us/HT204837 We also have powerful and legendary tools such as VeraCrypt (the former TrueCrypt), feel free to try it out if you are interested: https://veracrypt.fr/ You can go one step further to enable BIOS or firmware password. I have done it myself but it's totally up to your own choice. Just remember: if you do, remember the password very clearly, or else no one can ever help you out. I am lucky enough to have fallen into the rabbit hole myself before, which cost me a laptop, some crypto, and a week's time. On the other hand, it's a very good learning experience too. Mobile phone Nowadays iPhone and Android are the only two mainstream mobile phones categories. I used to be a big fan of BlackBerry, but its glory faded away with time. In the past, the security posture of Android phones worried me a lot. On one hand it was still in the early stage, on the other hand the versions were very fragmented, each brand would have its own forked Android version. But now things have improved a lot. On mobile phones we also need to pay attention to security updates and download security. In addition, pay attention of the following points: Do not jailbreak/root your phone, it's unnecessary unless you are doing relevant security researchIf you are doing it for pirated software it really depends on how well you can master the skill. Don't download apps from unofficial app stores. Don't do it unless you know what you are doing. Not to mention there are even many fake apps in official app stores. The prerequisite of utilising the official Cloud synchronization function, is that you have to make sure your account is secure, otherwise if the Cloud account gets compromised, so will the mobile phone. Personally I rely more on the iPhone. And you will need at least two iCloud accounts: one China and one overseas. You will need them to install apps with different regional restrictions. (which sounds pretty weird but welcome to the reality) Network Network security issues used to be a pain in the ass, but there are already significant improvements in recent years, especially since the mass adoption of HTTPS Everywhere policy. In case of an ongoing network hijacking (man-in-the-middle attack) attack, there will be corresponding system error alerts. But there are always exceptions, so when you have a choice use the more secure option. For example, don't connect to unfamiliar Wi-Fi networks unless the more popular & secure 4G/5G network is not available or not stable. Browsers The most popular browsers are Chrome and Firefox, in crypto fields some will use Brave too. These well known browsers have a strong team and there will be timely security updates. The topic of browser security is very broad. Here are some tips for you to be aware of: Update as quickly as possible, don't take chances. Don't use an extension if not necessary. If you do, make your decisions based on user's reviews, number of users, maintaining company, etc, and pay attention to the permission it asks for. Make sure you get the extension from your browser's official app store. Multiple browsers can be used in parallel, and it is strongly recommended that you perform important operations in one browser, and use another browser for more routine, less important operations. Here are some well-known privacy focused extensions (such as uBlock Origin, HTTPS Everywhere, ClearURLs, etc.), feel free to try them out. In Firefox in particular, I will also use the legendary ancient extension NoScript, which had a proven record of fending off malicious JavaScript payloads. Nowadays browsers are becoming more and more secure as they add support for things like same-origin policy, CSP, Cookie security policy, HTTP security headers, extension security policy, etc. Thus the need of using a tool such as NoScript is becoming smaller and smaller, feel free to take a look if interested. Password Manager If you haven't used a password manager yet, either you don't know the convenience of using one, or you have your own strong memory palace. The risk of brain memory has also been mentioned before, one is that time will weaken or disrupt your memory; the other is that you may have an accident. In either case, I still recommend that you use a password manager to go with your brain memory, use a well-known one like 1Password, Bitwarden, etc. I don't need to cover this part too much, there are so many related tutorials online, it's easy to get started without even needing a tutorial. What I need to remind you here is: Do not ever forget your master password, and keep your account information safe, otherwise everything will be lost. Make sure your email is secure. If your email is compromised, it might not directly compromise the sensitive information in your password manager, but bad actors have the capability to destroy it. I have verified the security of the tools I mentioned (such as 1Password), and have been closely watching the relevant security incidents, user reviews, news, etc. But I cannot guarantee that these tools are absolutely secure, and no black swan events are ever gonna happen in the future to them. One thing I do appreciate is the introduction and description of 1Password's security page, for example. https://1password.com/security/ This page has security design concepts, relevant privacy and security certificates, security design white papers, security audit reports, etc. This level of transparency and openness also facilitates the necessary validation in the industry. All project teams should learn from this. Bitwarden goes one step further, as it is fully open source, including the server side, so anyone can validate, audit, and contribute. Now you see? The intention of 1Password and Bitwarden is very clear: I am very secure and I am concerned about privacy. Not only do I say it myself, third party authorities say so as well. Feel free to audit me, and in order to make it easy for your audits, I spend a lot of effort to be open wherever possible. If what I do doesn't match what I say, it's easy to challenge me. And this is called Security Confidence. Two-Factor Authentication Speaking of your identity security on the Internet, the first layer relies on passwords, the second layer relies on two factor authentication, and the third layer relies on the risk control ability of the target project itself. I can't say that two factor authentication is a must-have. For example, if you are using a decentralized wallet, one layer of password is annoying enough (now they basically support biometric identification such as facial recognition or fingerprint to improve user experiences), no one wants to use the second factor. But in a centralized platform, you have to use 2FA. Anyone can access the centralized platform, and if your credentials get stolen, your account is breached and your fund will be lost. On the contrary, the password for your decentralized wallet is just a local authentication, even if the hacker gets the password, they still need to get access to the device where your wallet is located. Now you see the differences?Some well-known two-factor authentication (2FA) tools include: Google Authenticator, Microsoft Authenticator, etc. Of course, if you use a password manager (such as 1Password), it also comes with a 2FA module, which is very handy. Always remember to make backups, because losing 2FA can be a hassle. In addition, two-factor authentication can also be a broader concept. For example, when an account identifier and a password are used to log in to the target platform, our account identifier is normally an email or mobile phone number. At this time, the mailbox or mobile phone number can be used as 2FAto receive a verification code. But the security level of this method is not as good. For example, if the mailbox is compromised or the SIM card gets hijacked, or the third-party service used for sending emails and text messages is hacked, then the verification code sent by the platform will also be revealed. Scientific Internet Surfing For policy reasons, let's not talk too much about this, just pick one of the well-known solutions. Things will be more under control if you can build your own solution.After all, our starting point is to surf the Internet scientifically and securely. If you are not using a self-built solution, you can't fully rule out the possibility of a man-in-the-middle attack. As mentioned earlier, the Internet security situation is not as bad as it used to be, especially after the mass adoption of HTTPS Everywhere policy. However, some of the peace may be just the surface of the water, and there are already undercurrents beneath the surface that are not easily noticeable. To be honest, I don't really have a silver bullet for this. It's not easy to build your own solution, but it's definitely worth it. And if you can't, make sure you check using multiple sources and choose a reputable one that has been around for a long time. Email Email is the cornerstone of our web based identity. We use email to sign up for a lot of services. Almost all of the email services we use are free. It seems like air, and you don't think it would disappear. What if one day your Email service is gone, then all the other services that depend on it will be in a rather awkward situation. This extreme situation is really not impossible if there're wars, natural disasters, etc. Of course, if these extreme situations occur, Email will be less important to you than survival. When it comes to Email services providers, you should choose from tech giants, such as Gmail, Outlook, or QQ Email. It happens that my previous security researches cover this area. The security posture of these mailboxes is good enough. But still you have to be careful about Email phishing attacks. You don't need to deal with every single Email, especially the embedded links and attachments, where Trojans may be hidden. If you come across a highly sophiscatedattack on your Email services providers, you're on your own. Besides the email services of these tech giants, if you are very concerned about privacy, you can take a look at these two well-known privacy-friendly email services: ProtonMail and Tutanota. My suggestion is to separate these private-friendly mailbox from daily usage, and only use them for services that requires special attention to privacy. You also need to regularly use your free Email services to prevent yout accounts from being suspended due to long time inactivity. SIM Card SIM card and mobile phone number are also very important basic identities in many cases, just like email. In recent years, the major operators in our country have done a very good job in the security protection of mobile phone numbers. For example, there are strict security protocols & verification processes for canceling and re-issuing SIM cards, and they all happen on site. On the topic of SIM card attacks , let me give you an example: In 2019.5, someone's Coinbase account suffered a SIM Port Attack (SIM card transfer attack), and unfortunately lost more than 100,000 US dollars of cryptocurrency. The attack process is roughly as follows: The attacker obtained the privacy information of the target user through social engineering and other methods, and tricked the Mobile phone operator to issue him a new SIM card, and then he easily took over the target user's Coinbase account through the same mobile phone number. The SIM has been transferred, which is very troublesome. It's very troublesome if your SIM card got transferred by the attacker, as nowadays, many of the online services use our mobile phone number as a direct authentication factor or 2FA. This is a very centralized authentication mechanism, and the mobile phone number becomes the weak point. For detailed analysis, please refer to: https://medium.com/coinmonks/the-most-expensive-lesson-of-my-life-details-of-sim-port-hack-35de11517124 The defence suggestion for this is actually simple:enable a well-known 2FA solution. The SIM card has another risk:that is, if the phone is lost or stolen, it will be embarrassing that the bad guy can take out the SIM card and use it. Here is what I did: Enable the SIM card password (PIN code), so every time when I turn on my phone or use my SIM card in a new device, I need to enter the correct password. Please ask Google for detailed howtos. Here's the reminder from me: don't forget this password, otherwise it will be very troublesome. GPG Many contents in this part have been mentioned in previous sections, and I woud like to add more basic concepts here.: Sometimes you will encounter similar-looking names such as PGP, OpenPGP, and GPG. Simply distinguish them as follows: PGP, short for Pretty Good Privacy, is a 30-year-old commercial encryption software now under the umbrella of Symantec. OpenPGP is an encryption standard derived from PGP. GPG, the full name is GnuPG, is an open source encryption software based on the OpenPGP standard. Their cores are similar, and with GPG you are compatible with the others. Here I strongly recommend again: In security encryption, don't try to reinvent the wheel; GPG, if used in a correct way, can improve security level significantly! Segregation The core value behind the security principle of segregation, is the zero trust mindset. You have to understand that no matter how strong we are, we will be hacked sooner or later, no matter if it's by external hackers, insiders or ourselves. When hacked, stop loss should be the first step. The ability to stop loss is ignored by many people, and that's why they get hacked again and again. The root cause is that there is no security design, especially straightforward methods such as segregation A good segregation practice can ensure that in case of security incidents, you only lose those directly related to the compromised target, without affecting other assets. For example: * If your password security practice is good, when one of your accounts gets hacked, the same password will not compromise other accounts. * If your cryptocurrency is not stored under one set of mnemonic seeds, you will not lose everything if you ever step into a trap. * If your computer is infected, luckily this is just a computer used for casual activities, and there is nothing important in there So you do not have to panic, as reinstalling the computer would solve most of the problems. If you are good at using virtual machines, things are even better, as you can just restore the snapshot. Good virtual machine tools are: VMware, Parallels. * To summarize, you can have at least two accounts, two tools, two devices, etc. It is not impossible to completely create an independent virtual identity after you are familiar with it. I mentioned a more extreme opinion before: privacy is not for us to protect, privacy should be controlled. The reason for this viewpoint is that: in the current Internet environment, privacy has actually been leaked seriously. Fortunately, privacy-related regulations have become more and more widely adopted in recent years, and people are paying more and more attention. Everything is indeed going in the right direction. But before that, in any case, when you have mastered the knowledge points I have listed, you will be able to control your privacy with ease. On the Internet, if you are used to it, you may have several virtual identities that are almost independent of each other. Security of Human Nature Human is always at the highest and eternal risk. There's a quote from The Three-Body Problem: "Weakness and ignorance are not barriers to survival, but arrogance is." Don't be arrogant: If you think you're already strong, you're fine with yourself. Don't look down on the whole world. In particular, don't be overly proud and think you can challenge global hackers. There is no end to learning, and there are still many obstacles. Don't be greedy: Greed is indeed the motivation to move forward in many cases, but think about it, why is such a good opportunity just reserved for you? Don't be impulsive: impulsiveness is the devil which will lead you to traps. Rash action is gambling. There are endless things in human nature to talk about and you can't be more careful. Please pay special attention to the following points, and see how bad actors take advantage of the weakness in human nature, utilizing various convenient platforms. Telegram I've said before that Telegram is the biggest dark web. I have to say that people like Telegram for its security, stability, and open design features. But the open culture of Telegram also attracts bad guys: huge numbers of users, highly customisable functionality, easy enough to build all kinds of Bot services. Combining with cryptocurrency, the actual trading experiences are far beyond those dark web marketplaces in Tor. And there are too many fishes in it. Normally, the unique identifier of social media accounts is only something like a username, user id, but these can be completely cloned by the bad actors. Some social platforms have account validation mechanisms, such as adding a blue V icon or something. Public social media accounts can be validated through some indicators, such as the follower's number, the contents posted, interaction with fans, etc. The non-public social media accounts are a bit more difficult. It's nice to see that Telegram released the function of "Which Groups we are in together". Wherever there are loopholes that can be exploited and the gains are considerable, a bunch of bad guys must be already there, that's human nature. As a result, social media platforms are full of phishing traps. For example: In a group chat, someone who looks like the official customer service suddenly appeared and started a private chat (any2any private chat is the feature of Telegram, there is no need for friend request), and then out of the classic tactics of spam, fish will bite one after another. Or attackers might go one step further, and add you into another group. All participants buy you are fake, but to you it looks so realistic. We refer to this technique as Group Cloning in underground society. These are just the basic methods of manipulating human nature, the advanced techniques will be combined with vulnerabilities and thus are more difficult to prevent. Discord Discord is a new and popular social platform/IM software raised in the past two years. The core function is community servers (not the concept of traditional server), as the official statement says: Discord is a free voice, video, and text chat app that's used by tens of millions of people ages 13+ to talk and hang out with their communities and friends. People use Discord daily to talk about many things, ranging from art projects and family trips to homework and mental health support. It's a home for communities of any size, but it's most widely used by small and active groups of people who talk regularly. It looks great but requires a quite strong security design standard. Discord has specific security rules and policies as in: https://discord.com/safety Unfortunately, most people will not bother to read it carefully. What's more, Discord won't always be able to illustrate certain core security issues clearly, because they will have to put on an attacker's hat which is not always feasible. For instance: With so many NFT thefts on Discord, what are the key attack methods? Before we figure this out, Discord security advice is useless. The key reason behind many project Discordhacks is actually the Discord Token, which is the content of the authorization field in the HTTP request header. It has existed in Discord for a very long time. For hackers, if they can find a way to get this Discord Token, they can almost control all the privileges of the target Discord server. That is to say, if the target is an administrator, an account with administrative privileges or a Discord bot , the hackers can do anything they want to. For example by announcing a NFT phishing site, they make people think it's the official announcement, and fish will bite the hook. Some might ask, what if I add two-factor authentication (2FA) to my Discord account? Absolutely a good habit! But Discord Token has nothing to do with your account 2FA status. Once your account is breached, you should change your Discord password immediately to make the original Discord Token invalid. For the question of how the hacker can get the Discord Token, we have figured out at least three major techniques, and we will try to explain it in detail in the future . For normal users, there are a lot that can be done, but the core points are: don't rush, don't be greedy, and verify from multiple sources. "Official" phishing The bad actors are good at taking advantage of role playing, especially the official role. For example we have mentioned the fake customer service method before. Besides that, in April 2022, many users of the well-known hardware wallet Trezor, received phishing emails from trezor.us, which is not the official Trezor domain trezor.io. There is a minor difference in the domain name suffix. What's more, the following domains were also spread via phishing emails. https://suite.trẹzor.com This domain name has a "highlight spot", look closely at the letter ẹ in it, and you can find that is not the letter e. Confusing? It is actually Punycode, the standard description is as below: A Bootstring encoding of Unicode for Internationalized Domain Names in Applications (IDNA) is an internationalized domain name encoding that represents a limited set of characters in both Unicode and ASCII codes. If someone decode trẹzor, it looks like this: xn-trzor-o51b, which is the real domain name! Hackers have been using Punycode for phishing for years, back in 2018, some Binance users were compromised by the same trick. These kinds of phishing sites can already make many people fall, not to mention those more advanced attacks such as official mailbox getting controlled, or mail forgery attacks caused by SPF configuration issues. As a result, the source of the email looks exactly the same as the official one. If it is a rogue insider, the user can do nothing. project teams should put a lot of effort into preventing insider threats. Insiders are the biggest Trojan horse, but they very often get neglected. Web3 Privacy Issues With the growing popularity of Web3, more and more interesting or boring projects appeared: like all kinds of Web3 infrastructures, social platforms, etc. Some of them have done massive data analysis and identified various behavioral portraits of the targets, not only on the blockchain side, but also on well-known Web2 platforms. Once the portrait comes out, the target is basically a transparent person. And the appearance of Web3 social platforms may also aggravate such privacy issues. Think about it, when you play around with all these Web3-related things, such as signature binding, on chain interactions, etc., are you giving away more of your privacy? Many might not agree, but as many pieces come together there will be a more accurate & comprehensive picture: which NFTs you like to collect, which communities you joined, which whitelists you're on, who you're connected with, which Web2 accounts you're bound to, what time periods you're active in, and so on. See, blockchain sometimes makes privacy worse. If you care about privacy, you will have to be careful with everything newly emerged and keep the good habit of segregating your identity. At this point, if the private key is accidentally stolen, the loss is not as simple as just money, but all the carefully maintained Web3 rights and interests. We often say that the private key is the identity, and now you have a real ID problem. Never test human nature. Blockchain Shenanigans Blockchain technology created a whole new industry. Whether you call it BlockFi, DeFi, cryptocurrency, virtual currency, digital currency, Web3, etc, the core of everything is still the blockchain. Most hype centered on financial activities, such as crypto assets, including non-fungible tokens (or NFT, digital collectible). Blockchain industry is highly dynamic and fascinating, but there are just too many ways to do evil. The special characteristics of blockchain give rise to some rather unique evils, including and not limited to crypto theft, cryptojacking, ransomware, dark web trading, C2 attack, money laundering, Ponzi schemes, gambling, etc. I made a mind map back in 2019 for reference. https://github.com/slowmist/Knowledge-Base/blob/master/mindmaps/evil_blockchain.png Meanwhile, the SlowMist team has been maintaining and updating SlowMist Hacked - an growing database for blockchain-related hacking activities. https://hacked.slowmist.io/ This handbook has introduced many security measures, and if you can apply them to your own security, then congratulations. I won't elaborate too much on the blockchain shenanigans. If you are interested, you can learn it on your own, which is definitely a good thing, especially since new scams and frauds are continuously evolving. The more you learn, the better you can defend yourself and make this industry better. What to do When You get hacked It is only a matter of time before you eventually get hacked. So what to do then? I'll simply cut straight to the chase. The following steps are not necessarily in order; there are times when you have to go back and forth, but the general idea is this. Stop Loss First Stop loss is about limiting your loss. It can be broken down to at least two phases. The Immediate Action Phase. Act immediately! If you see hackers are transferring your assets, think no more. Just Hurry up and transfer the remaining assets to a safe place. If you have experience in front running trades, just grab and run. Depending on the type of asset, if you can freeze your assets on the blockchain, do it as soon as possible; if you can do on-chain analysis and find your assets are transferred into a centralized exchange, you can contact their risk control department. The Post-Action Phase. Once the situation is stabilized, your focus should be on making sure there would not be secondary or tertiary attacks. Protect The Scene When you find that something is wrong, stay calm and take a deep breath. Do remember to protect the scene. Here are a few suggestions: If the accident happens on a computer, server or other devices connected to the Internet, disconnect the network immediately while keeping the devices on with power supply. Some people may claim that if it is a destructive virus, the local system files will be destroyed by the virus. They are right, however shutting down only helps if you can react faster than the virus... Unless you are capable of handling this by yourself, waiting for security professionals to step in for analysis is always the better choice. This is really important as we have encountered quite a few times that the scene was already in a mess by the time we stepped in to do the analysis. And there were even cases when key evidence (e.g. logs, virus files) appeared to have been cleaned up. Without a well-preserved crime scene, it can be extremely disruptive to the subsequent analysis and tracing. Root Cause Analysis The purpose of analyzing the cause is to understand the adversary and output the hacker's portrait. At this point, the incident report is very important, which is also called Post Mortem Report. Incident Report and Post Mortem Report refer to the same thing. We have met so many people who came to us for help after their coins were stolen, and it was very difficult for many of them to clearly tell what happened. It's even harder for them to produce a clear incident report. But I think this can be practiced and it would be helpful by referring to examples. The following can be a good starting point: Summary 1: Who was involved, when did this happen , what has happened, and how much was the total loss? Summary 2: The wallet addresses related to the loss, the wallet address of the hacker, the type of the coin, the quantity of the coin. It could be much clearer with the help of just a single table. Process description: this part is the most difficult. You will need to describe all aspects of the incident with all the details, which is useful to analyze various kinds of traces related to the hacker and eventually get the hacker portrait from them (including the motivation) When it comes to particular cases, the template will be much more complex. Sometimes human memory can also be unreliable, and there is even a deliberate concealment of key information which can lead to wasted time or delayed timing. So in practice, there would be a huge consumption and we need to use our experience to guide the work well. Finally we produce an incident report with the person or the team who lost the coins, and continue to keep this incident report updated. Source Tracing According to Rocca's Law, where there is an invasion, there is a trail. If we investigate hard enough, we will always find some clues. The process of investigation is actually forensic analysis and source tracing. We will trace the sources according to the hacker portrait from the forensic analysis, and constantly enrich it, which is a dynamic and iterative process. Source tracing consists of two main parts: On-chain intelligence. We analyze the asset activities of the wallet addresses, such as going into centralized exchanges, coin mixers, etc., monitor it and get alerts of new transfers. Off-chain intelligence: this part covers the hacker's IP, device information, email address and more information from the correlation of these associated points, including behavioral information. There is plenty of source tracing work based on this information, and it would even require the involvement of law enforcement. Conclusion of Cases Of course we all want a happy ending, and here are some examples of publicly-disclosed events that we have involved which have good results: Lendf.Me, Worth of $25 million SIL Finance, Worth of $12.15 million Poly Network, Worth of $610 million We have experienced many other unpublished cases that ended in good or okay results. However most of them had bad endings, which is quite unfortunate. We've gained a lot of valuable experiences in these processes and we hope to raise the ratio of good endings in the future. This part is briefly mentioned as above. There is a huge amount of knowledge related to this area and I'm not quite familiar with some of it. Thus, I'm not going to give a detailed explanation here. Depending on the scenario, the abilities we need to master are: Smart Contract Security Analysis and Forensics Analysis and forensics of on-chain fund transfers Web Security Analysis and Forensics Linux Server Security Analysis and Forensics Windows Security Analysis and Forensics macOS Security Analysis and Forensics Mobile Security Analysis and Forensics Malicious code analysis and forensics Security analysis and forensics of network devices or platforms Insider security analysis and forensics ... It covers almost every aspect of security and so does this handbook. However, those security points are only briefly mentioned here as an Introductory guide. Misconception From the very beginning, this handbook tells you to stay skeptical! This includes everything mentioned in here. This is an extremely vibrant and promising industry, full of all kinds of traps and chaos. Here let's take a look at some of the misconceptions, which, if taken for granted as truth, can easily make you fall into the traps and become part of the chaos itself. Code Is Law Code is law. However, when a project (especially smart contract related ones) gets hacked or rugged, no single victim would ever wish for "Code Is Law", and it turns out they still need to rely on the law in the real world. Not Your Keys, Not Your Coins If you don't own your keys, you don't own your coins. As a matter of fact, many users failed to properly manage their own private keys. Due to various security mispractices they even lose their crypto assets. Sometimes you will find that it's actually more secure to put your crypto asset in big and reputable platforms. In Blockchain We Trust We trust it because it's blockchain. In fact, blockchain itself does have the capability to solve many of the fundamental trust issues, since it's tamper-proof, censorship-resistant, etc; if my asset and related activities are on chain, I can trust by default that no one else will be able to take away my asset or tamper with my activity without authorization. However the reality is often harsh, firstly not every blockchain is able to achieve these fundamental points, and secondly human nature always becomes the weakest link. Many of the hacking techniques nowadays are beyond the imagination of most of us. Though we always say that attack and defense is the balance between cost and impact, when you don't own a big asset no hacker will waste time to target you. But when there are multiple targets like yourself, it will be very profitable for the hackers to launch the attack. My security advice is very simple: Distrust by default (that is, question everything by default), and conduct continuous verification. Verify is the key security action here, and continuous verification basically means that security is never in a static state, it's secure now doesn't mean it's secure tomorrow. The capability to properly verify is hereby the biggest challenge for us all, but it's quite interesting, as you will get to master a lot of knowledge in the process. When you are strong enough, no one can easily harm you. Cryptographic Security is Security Cryptography is powerful and important. Without all the hard work of cryptographers, all the solid cryptographic algorithms & engineering implementations, there will be no modern communications technology, Internet, or blockchain technology. However, some individuals consider cryptographic security as absolute security. And thus a bunch of weird questions arises: Isn't blockchain so secure, that it took trillions of years to break a private key? How come the FBI could decrypt Dark Web Bitcoin? Why on earth could Jay Chou's NFT get stolen? I can bear with these novice questions... what I can't bear with is the fact that many so-called security professionals use cryptographic security concepts to fool the public, they are mentioning terms such as military-grade encryption, world's best encryption, cosmic-level encryption, absolute system security, unhackability, etc. Hackers? They don't give a shit... Is it humiliating to be hacked? It is true that getting hacked can bring mixed feelings, and there will be a sense of shame sometimes. But you need to understand that getting hacked is almost 100% guaranteed so there is nothing to be ashamed of. Once getting hacked, it doesn't matter if you are only responsible for yourself. However, if you are responsible for many others, you have to be transparent and open when you are dealing with the incident. Although people may question or even accuse you of staging the hack by yourself, a transparent and open updated process will always bring good luck and understanding. Think of it this way: if your project isn't well-known, no one will hack you. The shame is not being hacked; the shame is your arrogance. From a probability point of view, getting hacked is a common phenomenon, normally, the majority of the security issues are just small problems, which could help your project grow. However, the severe big problems still have to be avoided as much as possible. Immediately Update For many times this handbook suggests to pay attention to updating. If there is a security update available, apply it immediately. Now think carefully, is this a silver bullet? Actually, in most cases, "update now" is the right thing to do . However, there have been times in history when an update solves one problem but introduces another. An example is iPhone and Google Authenticator: There is a risk of the new iOS 15 update, that is, the information in Google Authenticator may be wiped or doubled after the iPhone upgrade. In this case, never delete the duplicate entries if you find that they are doubled, as it may cause the loss of all the information in Google Authenticator after reopening. For those who have not upgraded to the iOS 15 system and are using Google Authenticator, it is highly recommended to back it up before upgrading. Later, Google has updated the Authenticator app, solving this problem permanently. Besides, I don't recommend updating wallets frequently, especially for asset-heavy wallets, unless there is a major security patch, or a very important feature that leads to an inevitable update. in which cases you will have to do your own risk assessment and make your own decision. Conclusion Recall that this handbook starts with this diagram :) Have you noticed that I have marked in red the person in the diagram?, I do so to remind everybody again that humans are the foundation of all (referred to as "anthropic principle" in cosmology). No matter if it's human nature security, or the ability to master security skills, it all depends on you. Yes, when you are strong enough, no one can easily harm you. I started to expand based on the diagram, and explained many security key points in the three processes, creating wallet, backing up wallet and using wallet. Then I introduced traditional privacy protection. I stated that such traditional ones are the cornerstones and the building blocks for us to stay secure in blockchain ecosystems. The human nature security part cannot be overdressed. It's good to understand more about the various ways of doing evil, especially if you step into a few pits, the security awareness on paper may eventually become your security experience. There is no absolute security, so I explained what to do when you get hacked. I don't want an unfortunate event to happen to you, but in case it happens, I hope this handbook could help you. The last thing is to talk about some misconceptions. My intention is very simple, I hope you can build up your own critical thinking, because the world is both beautiful and terrible. I have not written so many words for a long time. I think the last time was 10 years ago when I wrote the book " Web 前端黑客技术揭秘 ". It was quite bittersweet. After many years in web security as well as cybersecurity, I led a team to create ZoomEye, a cyberspace search engine. Within cybersecurity, I have dabbled in many fields, only a few of which I can say that I am skilled at. Now in blockchain security, SlowMist and myself are considered to be pioneers . There are so many cases we have encountered in these years that you can almost think we are in a state of trance every single day. It's a pity that many insights are not recorded and shared. And as a result, at the urging of several friends, this handbook was born. When you have finished reading this handbook, you must practice, become proficient and draw inferences. When you have your own discovery or experience afterwards, I hope you will contribute. If you feel there is sensitive information you can mask them out, or anonymise the information. Finally, thanks to the global maturity of security and privacy-related legislation and enforcement; thanks to the efforts of all the pioneering cryptographers, engineers, ethical hackers and all those involved in the creation of a better world, which includes Satoshi Nakamoto. Appendix Security rules and principles The security rules and principles mentioned in this handbook are summarized as follows. Quite a few rules are being incorporated into the above text and will not be specifically refined here. Two major security rules: Zero trust . To make it simple, stay skeptical, and always stay so. Continuous validation . In order to trust something, you have to validate what you doubt, and make validating a habit. Security principles: For all the knowledge from the Internet, refer to at least two sources, corroborate each other, and always stay skeptical. Segregate. Don't put all the eggs in one basket. For wallets with important assets, don't do unnecessary updates. What you see is what you sign. You need to be aware of what you are signing, and of the expected result after the signed transaction is sent out. Don't do things that will make you regret afterwards. Pay attention to system security updates. Apply them as soon as they are available. Don't download & install programs recklessly can actually prevent most risks. Contributors Thanks to all the contributors, this list will continue to be updated. If you have any ideas, please contact: Cos, Twitter( @evilcos )、Jike App(@余弦.jpg) Contributors: My wife SlowMist, Twitter (@SlowMist_Team), e.g. Pds | Johan | Kong | Kirk | Thinking | Blue | Lisa | Keywolf... English translator, e.g. Alphatu | C. | CJ | JZ | Lovepeace | Neethan | pseudoyu | SassyPanda | ss | Japanese translator, e.g. Jack Jia | Mia Korean translator, e.g. Sharon | Jeongmin Jike App Some Anonymous friends ... More info: https://darkhandbook.io/contributors.html As long as there is help that is adopted and included in this handbook, such as: providing specific defense suggestions and cases; translation work; correction of major errors, etc. The Tools This handbook, commonly referred to as the "Dark Handbook," has been available for over two years, and I'm delighted to observe its helpful impact on many individuals. Its influence continues to expand, with a growing number of supporters advocating for updates. Typically, these updates to the Dark Handbook primarily consist of expanded readings . The challenge with these extended readings is that they are technically complex and not very accessible for beginners. Additionally, I recognize that not everyone is keen to invest substantial time in mastering the nuances of blockchain security. Originally, this section aimed to recommend some beginner-friendly tools, such as wallets, security extensions, and scripting tools. However, after much deliberation, I have decided against endorsing specific products due to the swift pace of change within the industry. Although this manual has highlighted several reliable tools, it's uncertain whether they will remain effective or relevant in the future. Given my responsibility towards all readers, I must admit, I'm not sure. As I've stated previously, when recommending a tool, I strive to describe it as objectively and neutrally as possible. Additionally, for enhanced security, every reader should bear in mind the following: *　Absolute security does not exist. Adopting a zero-trust approach with continuous verification is essential in navigating this complex landscape. Should any of these tools develop a bug, encounter a security issue, or, in a worse scenario, include a backdoor in a new update, the risk is yours to manage. I encourage you to think independently and critically before using these tools. *　My research skills are well-honed, and I have a broad network, so rest assured that I will recommend quality tools when it seems appropriate. There is no need to rush; if a tool proves reliable and earns widespread trust, I will naturally endorse it. *　Everyone has their unique approach, and this is mine. *　Stay away from the influence of coin prices. * Trust is hard to build, but it can collapse in an instant, so please cherish it. Although I do not make any specific tool recommendations in this section, I would like to share a valuable mindset: the firewall mindset. The previously emphasized concepts of "zero trust" and "continuous verification" are actually part of this firewall thinking. 예For example, in the use of wallets, signing is a major area of concern for fund security, with various sophisticated phishing methods related to signing, such as: The exploitation of native signing with eth_sign/personal_sign/eth_signTypedData_*, where eth_sign has been increasingly blocked by wallets. The exploitation of authorization functions like approve/permit for Tokens/NFTs. The utilization of powerful functions like Uniswap’s swapExactTokensForTokens/permit2. The exploitation of protocol functions from OpenSea/Blur and others (which are very diverse). The exploitation of TX data 4byte, such as for Claim Rewards/Security Update. Using Create2 to pre-create funding receiving addresses, bypassing related checks. A single signature on Solana phishing away all assets in a target wallet address. Bitcoin inscription for one-click mass phishing, utilizing the UTXO mechanism. Switching phishing across various EVM chains/Solana/Tron, etc. If your wallet, when prompting for signature confirmation, sends out the signature right after a single click—whether due to FOMO or a shaky hand—then this method of using the wallet does not embody the firewall mindset. A better practice is to require at least two clicks; each additional click adds a layer of security (of course, not too many layers, as people can become desensitized...). For example, I use browser extension wallets like Rabby, MetaMask, and OKX Wallet, and except for test wallets, I always pair these with a hardware wallet (preferably one with a larger screen to easily review the content about to be signed). At this point, the extension wallet’s signature confirmation popup will perform the first layer of security analysis, such as identifying phishing sites, risky wallet addresses, what-you-see-is-what-you-sign, and high-risk signature recognition. These are crucial for user interaction security. The hardware wallet provides a second layer of security analysis. If you then add a browser wallet security extension like Scam Sniffer, Wallet Guard, or Pocket Universe, you add another layer to your firewall. However, it’s essential to remember, even if there are no risk alerts for the action you are undertaking, you must still be vigilant and recognize that ultimately, you are your own last line of defense... Once accustomed to the firewall mindset, the impact on efficiency is minimal, but the sense of security is greatly enhanced. Let’s generalize this approach to other scenarios. That’s all,Thank you! Official Sites ``` SlowMist https://www.slowmist.com CoinMarketCap https://coinmarketcap.com/ Sparrow Wallet https://sparrowwallet.com/ MetaMask https://metamask.io/ imToken https://token.im/ Trust Wallet https://trustwallet.com/ TokenPocket https://www.tokenpocket.pro/ Gnosis Safe https://gnosis-safe.io/ ZenGo https://zengo.com/ Fireblocks https://www.fireblocks.com/ Safeheron https://www.safeheron.com/ Keystone https://keyst.one/ Trezor https://trezor.io/ OneKey https://onekey.so/ imKey https://imkey.im/ Rabby https://rabby.io/ OKX Wallet https://www.okx.com/web3 EdgeWallet https://edge.app/ MyEtherWallet https://www.myetherwallet.com/ Phantom https://phantom.app/ Tornado Cash https://tornado.cash/ Binance https://www.binance.com/ Coinbase https://coinbase.com Compound https://compound.finance/ SushiSwap https://www.sushi.com/ OpenSea https://opensea.io/ Revoke.cash https://revoke.cash/ Scam Sniffer https://www.scamsniffer.io/ Wallet Guard https://www.walletguard.app/ Pocket Universe https://www.pocketuniverse.app/ Jike App https://okjike.com/ Kaspersky https://www.kaspersky.com.cn/ Bitdefender https://www.bitdefender.com/ Cloudflare https://www.cloudflare.com/ Akamai https://www.akamai.com/ SURVEILLANCE SELF-DEFENSE https://ssd.eff.org/ Privacy Guide https://www.privacytools.io/ OpenPGP https://www.openpgp.org/ GPG https://gnupg.org/ GPG Suite https://gpgtools.org/ Gpg4win https://www.gpg4win.org/ 1Password https://1password.com/ Bitwarden https://bitwarden.com/ Google Authenticator https://support.google.com/accounts/answer/1066447 Microsoft Authenticator https://www.microsoft.com/en-us/security/mobile-authenticator-app ProtonMail https://protonmail.com/ Tutanota https://tutanota.com/ VMware Workstation https://www.vmware.com/products/workstation-pro.html Parallels https://www.parallels.com/ ```

Blockchain dark forest selfguard handbook. Master these, master the security of your cryptocurrency.

[]

apache/hertzbeat

English Document | 中文文档 A real-time monitoring system with agentless, performance cluster, prometheus-compatible, custom monitoring and status page building capabilities. Home: hertzbeat.apache.org Email: Mail to dev-subscribe@hertzbeat.apache.org to subscribe mailing lists 🎡 Introduction Apache HertzBeat (incubating) is an easy-to-use, open source, real-time monitoring system with agentless, high performance cluster, prometheus-compatible, offers powerful custom monitoring and status page building capabilities. Features Combines monitoring, alarm, and notification features into one platform, and supports monitoring for web service, program, database, cache, os, webserver, middleware, bigdata, cloud-native, network, custom and more. Easy to use and agentless, web-based and with one-click monitoring and alerting, zero learning curve. Makes protocols such as Http, Jmx, Ssh, Snmp, Jdbc, Prometheus configurable, allowing you to collect any metrics by simply configuring the template YML file online. Imagine being able to quickly adapt to a new monitoring type like K8s or Docker simply by configuring online with HertzBeat. Compatible with the Prometheus ecosystem and more, can monitoring what Prometheus can monitoring with few clicks on webui. High performance, supports horizontal expansion of multi-collector clusters, multi-isolated network monitoring and cloud-edge collaboration. Provides flexible alarm threshold rules and timely notifications delivered via Discord Slack Telegram Email Dingtalk WeChat FeiShu Webhook SMS ServerChan . Provides powerful status page building capabilities, easily communicate the real-time status of your service to users. HertzBeat's powerful customization, multi-type support, high performance, easy expansion, and low coupling, aims to help users quickly build their own monitoring system. 🥐 Architecture ⛄ Supported We define all monitoring collection types such as mysql , jvm , and k8s as YML monitoring templates, allowing users to import them to support corresponding types of monitoring. Welcome everyone to contribute your customized general monitoring type YML template during use. Website , Port Telnet , Http Api , Ping Connect , Jvm , SiteMap , Ssl Certificate , SpringBoot2 , FTP Server , SpringBoot3 , Udp Port , Dns , Pop3 , Ntp , Api Code , Smtp , Nginx Mysql , PostgreSQL , MariaDB , Redis , ElasticSearch , SqlServer , Oracle , MongoDB , DM , OpenGauss , ClickHouse , IoTDB , Redis Cluster , Redis Sentinel Doris BE , Doris FE , Memcached , NebulaGraph Linux , Ubuntu , CentOS , Windows , EulerOS , Fedora CoreOS , OpenSUSE , Rocky Linux , Red Hat , FreeBSD , AlmaLinux , Debian Linux Tomcat , Nacos , Zookeeper , RabbitMQ , Flink , Kafka , ShenYu , DynamicTp , Jetty , ActiveMQ , Spring Gateway , EMQX MQTT , AirFlow , Hive , Spark , Hadoop Kubernetes , Docker CiscoSwitch , HpeSwitch , HuaweiSwitch , TpLinkSwitch , H3cSwitch And More Your Custom Template. Notified Support Discord Slack Telegram Email Dingtalk WeChat FeiShu Webhook SMS ServerChan . 🐕 Quick Start If you wish to deploy HertzBeat locally, please refer to the following Deployment Documentation for instructions. 🍞 Install HertzBeat HertzBeat supports installation through source code, docker or package, cpu support x86/arm64. 1：Install quickly via docker Just one command to get started: docker run -d -p 1157:1157 -p 1158:1158 --name hertzbeat apache/hertzbeat Access http://localhost:1157 to start, default account: admin/hertzbeat Deploy collector clusters (Optional) docker run -d -e IDENTITY=custom-collector-name -e MANAGER_HOST=127.0.0.1 -e MANAGER_PORT=1158 --name hertzbeat-collector apache/hertzbeat-collector - -e IDENTITY=custom-collector-name : set the collector unique identity name. - -e MODE=public : set the running mode(public or private), public cluster or private cloud-edge. - -e MANAGER_HOST=127.0.0.1 : set the main hertzbeat server ip. - -e MANAGER_PORT=1158 : set the main hertzbeat server port, default 1158. Detailed config refer to Install HertzBeat via Docker 2：Install via package Download the release package hertzbeat-xx.tar.gz GITHUB Release Configure the HertzBeat configuration yml file hertzbeat/config/application.yml (optional) Run command $ ./bin/startup.sh or bin/startup.bat Access http://localhost:1157 to start, default account: admin/hertzbeat Deploy collector clusters (Optional) Download the release package hertzbeat-collector-xx.tar.gz to new machine GITHUB Release Configure the collector configuration yml file hertzbeat-collector/config/application.yml : unique identity name, running mode (public or private), hertzbeat manager-host , hertzbeat manager-port yaml collector: dispatch: entrance: netty: enabled: true identity: ${IDENTITY:} mode: ${MODE:public} manager-host: ${MANAGER_HOST:127.0.0.1} manager-port: ${MANAGER_PORT:1158} Run command $ ./bin/startup.sh or bin/startup.bat Access http://localhost:1157 and you will see the registered new collector in dashboard Detailed config refer to Install HertzBeat via Package 3：Start via source code Local source code debugging needs to start the back-end project manager and the front-end project web-app . Backend：need maven3+ , java17 , lombok , start the manager service. Web：need nodejs npm angular-cli environment, Run ng serve --open in web-app directory after backend startup. Access http://localhost:4200 to start, default account: admin/hertzbeat Detailed steps refer to CONTRIBUTING 4：Install All(hertzbeat+postgresql+tsdb) via Docker-compose Install the postgresql/mysql database, victoria-metrics/iotdb/tdengine database and hertzbeat at one time through docker-compose deployment script . Detailed steps refer to Install via Docker-Compose 5. Install All(hertzbeat+collector+postgresql+tsdb) via kubernetes helm charts Install HertzBeat cluster in a Kubernetes cluster by Helm chart. Detailed steps refer to Artifact Hub HAVE FUN 🥐 Roadmap ✨ Contributors Thanks to these wonderful people, welcome to join us: Contributor Guide tomsun28 💻 📖 🎨 会编程的王学长 💻 📖 🎨 MaxKey 💻 🎨 🤔 观沧海 💻 🎨 🐛 yuye 💻 📖 jx10086 💻 🐛 winnerTimer 💻 🐛 goo-kits 💻 🐛 brave4Time 💻 🐛 WalkerLee 💻 🐛 jianghang 💻 🐛 ChineseTony 💻 🐛 wyt199905 💻 卫傅庆 💻 🐛 zklmcookle 💻 DevilX5 📖 💻 tea 💻 yangshihui 💻 🐛 DreamGirl524 💻 📖 gzwlly 📖 cuipiheqiuqiu 💻 ⚠️ 🎨 lambert 💻 mroldx 📖 woshiniusange 📖 VampireAchao 💻 zcx 💻 🐛 🎨 CharlieXCL 📖 Privauto 💻 📖 emrys 📖 SxLiuYu 🐛 All Contributors 📖 铁甲小宝 💻 📖 click33 📖 蒋小小 📖 Kevin Huang 📖 铁甲小宝 🐛 💻 📖 Captain Jack 📖 haibo.duan ⚠️ 💻 assassin 🐛 💻 Reverse wind ⚠️ 💻 luxx 💻 Ikko Ashimine 📖 leizenan 💻 BKing 📖 xingshuaiLi 📖 wangke6666 📖 刺猬 🐛 💻 Haste 💻 zhongshi.yi 📖 Qi Zhang 📖 MrAndyMing 📖 idongliming 💻 Zichao Lin 💻 📖 liudonghua 💻 🤔 Jerry 💻 ⚠️ 🤔 yanhom 📖 fsl 💻 xttttv 📖 NavinKumarBarnwal 💻 Zakkary 📖 sunxinbo 💻 ⚠️ ldzbook 📖 🐛 余与雨 💻 ⚠️ MysticalDream 💻 ⚠️ zhouyoulin12 💻 ⚠️ jerjjj 💻 wjl110 💻 Sean 📖 chenyiqin 💻 ⚠️ hudongdong129 💻 ⚠️ 📖 TherChenYang 💻 ⚠️ HattoriHenzo 💻 ⚠️ ycilry 📖 aoshiguchen 📖 💻 蔡本祥 💻 浮游 💻 Grass-Life 💻 xiaohe428 💻 📖 TableRow 📖 💻 ByteIDance 💻 Jangfe 💻 zqr10159 📖 💻 vinci 💻 📖 🎨 js110 💻 CrazyLionLi 📖 banmajio 💻 topsuder 💻 richar2022 💻 fcb-xiaobo 💻 wenkyzhang 📖 ZangJuxy 📖 l646505418 💻 Carpe-Wang 💻 莫枢 💻 huangcanda 💻 世纪末的架构师 💻 ShuningWan 📖 MrYZhou 📖 suncqujsj 📖 sunqinbo 💻 haoww 📖 i-mayuan 📖 fengruge 📖 zhanghuan 💻 shenymin 💻 Dhruva Chandra 💻 miss_z 📖 wyt990 💻 licocon 💻 Mi Na 💻 Kylin-Guo 📖 Mr灬Dong先生 💻 Pratyay Banerjee 📖 💻 yujianzhong520 💻 SPPan 💻 ZhangJiashu 💻 impress 💻 凌晨一点半 📖 Eeshaan Sawant 💻 nandofromthebando 💻 caiboking 💻 baixing99 💻 Yang Chuang 💻 wlin20 💻 guojing1983 💻 moxi 📖 qq471754603 💻 渭雨 💻 liuxuezhuo 💻 lisongning 💻 YutingNie 💻 📖 🎨 Mike Zhou 💻 📖 🎨 小笨蛋 💻 littlezhongzer 💻 ChenXiangxxxxx 💻 Mr.zhou 💻 姚贤丰 💻 lingluojun 💻 1ue 💻 qyaaaa 💻 novohit 💻 zhuoshangyi 💻 ruanliang 📖 💻 Eden4701 💻 📖 🎨 XiaTian688 📖 liyinjiang 💻 ZhangJiashu 📖 moghn 📖 xiaoguolong 💻 Smliexx 💻 Naruse 📖 💻 🎨 Bala Sukesh 💻 Jinyao Ma 💻 Rick 💻 ⚠️ 东风 💻 🎨 📖 sonam singh 💻 ZhangZixuan1994 💻 SHIG 💻 泰上老菌 💻 ldysdu 💻 梁同学 💻 avv 💻 yqxxgh 📖 CharlieShi46 💻 Nctllnty 💻 Wang-Yonghao 📖 读钓 💻 Xin 💻 handy 💻 LiuTianyou 💻 📖 WinterKi1ler 💻 miki 💻 Keshav Carpenter 💻 📖 makechoicenow 💻 Gao Jian 💻 🎨 Hyeon Sung 💻 crossoverJie 💻 📖 PeixyJ 💻 风如歌 💻 Manan Pujara 💻 xuziyang 💻 lwqzz 💻 YxYL 💻 tomorrowshipyltm 📖 栗磊 💻 Alan 📖 Jast 💻 Zhang Yuxuan 💻 P.P. 💻 llp2333 💻 feiyang li 📖 aias00 💻 Jin 📖 YuLuo 💻 xiaoming student 💻 lwjxy 💻 John 💻 boatrainlsz 📖 Bill Lau 💻 lwyang 📖 xfl12345 📖 Limbo 💻 哈哈哈哈哈哈哈哈哈 💻 Leon Li 💻 dennis zhuang 💻 Kerwin Bryant 💻 💬 Join discussion Channel Join the Mailing Lists : Mail to dev-subscribe@hertzbeat.apache.org to subscribe mailing lists. Chat On Discord WeChat Group : Add friend tan-cloud and invite to the group. WeChat Public : Search ID usthecom . QQ Group : Group num 630061200 Github Discussion Reddit Community Follow Us Twitter Subscribe YouTube Open-Source Project Build From Open-Source HertzBeat is built on so many great open source projects, thanks to them! Java Spring SpringBoot Jpa Maven Assembly Netty Lombok Sureness Protobuf HttpClient Guava SnakeYaml JsonPath ... TypeScript Angular NG-ZORRO NG-ALAIN NodeJs Npm Html Less Echarts Rxjs ZoneJs MonacoEditor SlickCarousel Docusaurus ... Landscape HertzBeat has been included in the CNCF Observability And Analysis - Monitoring Landscape. Star History 🛡️ License Apache License, Version 2.0

Apache HertzBeat(incubating) is a real-time monitoring system with agentless, performance cluster, prometheus-compatible, custom monitoring and status page building capabilities.

monitor,monitoring,prometheus,self-hosted,status,status-page,uptime-monitoring,alerting,cloud,database

insidegui/VirtualBuddy

VirtualBuddy VirtualBuddy can virtualize macOS 12 and later on Apple Silicon, with the goal of offering features that are useful to developers who need to test their apps on multiple versions of macOS, especially betas. System Requirements Apple Silicon Mac macOS 12.3 or later In order to install a version of macOS that's newer than the version running on the host (for example, macOS 13 VM in VirtualBuddy running on macOS 12), Xcode is required; Xcode beta may be required for installing macOS betas ( FB11061314 ) In order to install a Linux distro, macOS 13 is required Download VirtualBuddy is free and open-source. If you'd like to support its development, you may purchase it on Gumroad . If you'd just like to download the latest version, go to GitHub releases . Feature Checklist [x] Ability to boot any version of macOS 12 or macOS 13, including betas [x] Ability to boot some ARM-based Linux distros (tested with Ubuntu Server and Ubuntu Desktop) [x] Built-in installation wizard [x] Select from a collection of restore images available on Apple's servers [x] Install the latest stable version of macOS [x] Local restore image IPSW file [x] Custom restore image URL [x] Install a Linux distro from a local .iso file [ ] Select from a collection of Linux distros [ ] Install Linux from URL [x] Boot into recovery mode (in order to disable SIP, for example) [x] Networking and file sharing support [x] Clipboard sharing [x] Customize virtual machine hardware configuration [ ] Edit NVRAM variables Tips and Tricks VirtualBuddyGuest app VirtualBuddy automatically mounts a disk image with the VirtualBuddyGuest app when you boot up a virtual machine running macOS. To install the VirtualBuddyGuest app, just select the "Guest" disk on Finder's side bar then double-click the "VirtualBuddyGuest" app icon. VirtualBuddyGuest enables clipboard sharing between host and guest and automatic mounting of the shared folders configured for the virtual machine. Taking Advantage of APFS Sometimes when trying things out in the OS installed in one of the virtual machines, things might break, requiring a full install of the guest operating system again, which is a pain. Thanks to APFS cloning though, you can just duplicate a virtual machine within your library folder (using Command + D in Finder), and the copy will take almost no additional disk space. This way you can have a "clean" copy of your VM, do whatever you want with a duplicate of it, and then throw the copy away and re-duplicate the clean version if things break. Sharing Folders Between Host and Virtual Machine You can share folders from your Mac to the Virtual Machine and vice-versa using regular macOS file sharing that can be configured in System Preferences/Settings. When both the Virtual Machine and the host are running macOS 13 or later, it's possible to share folders directly by configuring them in the VM settings within VirtualBuddy before booting up the VM. To mount shared folders in the VM, run the following command in the VM's Terminal: bash mkdir -p ~/Desktop/VirtualBuddyShared && mount -t virtiofs VirtualBuddyShared ~/Desktop/VirtualBuddyShared Building Xcode 14.1 is required. Open the VirtualBuddy/Config/Signing.xcconfig file Set the VB_BUNDLE_ID_PREFIX variable to something unique like com.yourname. Select the VirtualBuddy project in the Xcode sidebar Under "Targets", select "VirtualBuddy" Go to the Signing & Capabilities tab and select your development team under Signing > Team Repeat the same process for the "VirtualBuddyGuest" target Build the VirtualBuddy scheme (the one that doesn't have (Managed) in its name)

Virtualize macOS 12 and later on Apple Silicon, VirtualBuddy is a virtual machine GUI for macOS M1, M2, M3

macos,virtual-machine

salesforce/CodeGen

CodeGen Official release for the CodeGen1 and CodeGen2 models ( 350M , 1B , 3B , 7B 16B ) for Program Synthesis by Salesforce AI Research . News July 2023 CodeGen2.5 released outperforming 16B parameter models with only 7B. May 2023 CodeGen2.0 released with strong infill sampling capability. March 2022 CodeGen1.0 released on par with OpenAI Codex at the time. Publications CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis Erik Nijkamp *, Bo Pang *, Hiroaki Hayashi *, Lifu Tu , Huan Wang , Yingbo Zhou , Silvio Savarese , and Caiming Xiong ICLR, 2023 CodeGen2: Lessons for Training LLMs on Programming and Natural Languages Erik Nijkamp *, Hiroaki Hayashi *, Caiming Xiong , Silvio Savarese , and Yingbo Zhou ICLR, 2023 Usage The models are available on the Hugging Face Hub . CodeGen1.0 ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-2B-mono") model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-2B-mono") inputs = tokenizer("# this function prints hello world", return_tensors="pt") sample = model.generate(**inputs, max_length=128) print(tokenizer.decode(sample[0], truncate_before_pattern=[r"\n\n^#", "^'''", "\n\n\n"])) ``` CodeGen2.0 ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen2-7B") model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen2-7B", trust_remote_code=True, revision="main") inputs = tokenizer("# this function prints hello world", return_tensors="pt") sample = model.generate(**inputs, max_length=128) print(tokenizer.decode(sample[0], truncate_before_pattern=[r"\n\n^#", "^'''", "\n\n\n"])) ``` CodeGen2.5 ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen25-7b-mono", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen25-7b-mono") inputs = tokenizer("# this function prints hello world", return_tensors="pt") sample = model.generate(**inputs, max_length=128) print(tokenizer.decode(sample[0])) ``` Training The Jaxformer library for data pre-processing, training and fine-tuning the CodeGen models can be found here: https://github.com/salesforce/jaxformer Citation If you find our code or paper useful, please cite the paper: ```bibtex @article{nijkamp2022codegen, title={CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis}, author={Nijkamp, Erik and Pang, Bo and Hayashi, Hiroaki and Tu, Lifu and Wang, Huan and Zhou, Yingbo and Savarese, Silvio and Xiong, Caiming}, journal={ICLR}, year={2023} } @article{nijkamp2023codegen2, title={CodeGen2: Lessons for Training LLMs on Programming and Natural Languages}, author={Nijkamp, Erik and Hayashi, Hiroaki and Xiong, Caiming and Savarese, Silvio and Zhou, Yingbo}, journal={ICLR}, year={2023} } ```

CodeGen is a family of open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.

programsynthesis,generativemodel,codex,languagemodel,llm,tpu-acceleration

skeletonlabs/skeleton

💀 Skeleton Skeleton is an open source UI toolkit built with Svelte + Tailwind that allows you to create reactive web interfaces using Svelte + Tailwind CSS . 🔗 Useful Links Documentation Contribution Guide 👋 Community Join the Discord Follow on Twitter 👍 Sponsor the Project Ko-Fi GitHub Sponsors Patreon 🐞 Report an Issue File a Ticket 🛠️ Contributions We have provided a detailed contribution guide to help you get started. Find an open issue , discuss the requirements with other contributors, then send a PR! Maintainers Skeleton was created by Chris Simmons (@endigo9740) and is currently maintained by Skeleton Labs and the open source community.

A complete design system and component solution, built on Tailwind.

component,component-library,components,svelte,tailwind,ui,ui-components,cli,ui-framework,svelte-components

yoav-lavi/melody

Melody is a language that compiles to ECMAScript regular expressions, while aiming to be more readable and maintainable. Examples Note: these are for the currently supported syntax and may change Batman Theme try in playground ```rust 16 of "na"; 2 of match { ; "batman"; } // 🦇🦸‍♂️ ``` Turns into regex (?:na){16}(?: batman){2} Twitter Hashtag try in playground ```rust "#"; some of ; // #melody ``` Turns into ```regex \w+ ``` Introductory Courses try in playground ```rust some of ; ; "1"; 2 of ; // classname 1xx ``` Turns into regex [a-zA-Z]+ 1\d{2} Indented Code (2 spaces) try in playground ```rust some of match { 2 of ; } some of ; ";"; // let value = 5; ``` Turns into regex (?: {2})+.+; Semantic Versions try in playground ```rust ; option of "v"; capture major { some of ; } "."; capture minor { some of ; } "."; capture patch { some of ; } ; // v1.0.0 ``` Turns into regex ^v?(?<major>\d+)\.(?<minor>\d+)\.(?<patch>\d+)$ Playground You can try Melody in your browser using the playground Book Read the book here Install Cargo sh cargo install melody_cli From Source sh git clone https://github.com/yoav-lavi/melody.git cd melody cargo install --path crates/melody_cli Binary macOS binaries ( aarch64 and x86_64 ) can be downloaded from the release page Community Brew (macOS and Linux) Installation instructions ```sh brew install melody ``` Arch Linux (maintained by @ilai-deutel ) Installation instructions 1. Installation with an AUR helper, for instance using `paru`: ```bash paru -Syu melody ``` 2. Install manually with `makepkg`: ```bash git clone https://aur.archlinux.org/melody.git cd melody makepkg -si ``` NixOS (maintained by @jyooru ) Installation instructions 1. Declarative installation using `/etc/nixos/configuration.nix`: ```nix { pkgs, ... }: { environment.systemPackages = with pkgs; [ melody ]; } ``` 2. Imperative installation using `nix-env`: ```sh nix-env -iA nixos.melody ``` CLI Usage ``` USAGE: melody [OPTIONS] [INPUT_FILE_PATH] ARGS: Read from a file Use '-' and or pipe input to read from stdin OPTIONS: -f, --test-file Test the compiled regex against the contents of a file --generate-completions <COMPLETIONS> Outputs completions for the selected shell To use, write the output to the appropriate location for your shell -h, --help Print help information -n, --no-color Print output with no color -o, --output <OUTPUT_FILE_PATH> Write to a file -r, --repl Start the Melody REPL -t, --test <TEST> Test the compiled regex against a string -V, --version Print version information ``` Changelog See the changelog here or in the release page Syntax Quantifiers ... of - used to express a specific amount of a pattern. equivalent to regex {5} (assuming 5 of ... ) ... to ... of - used to express an amount within a range of a pattern. equivalent to regex {5,9} (assuming 5 to 9 of ... ) over ... of - used to express more than an amount of a pattern. equivalent to regex {6,} (assuming over 5 of ... ) some of - used to express 1 or more of a pattern. equivalent to regex + any of - used to express 0 or more of a pattern. equivalent to regex * option of - used to express 0 or 1 of a pattern. equivalent to regex ? All quantifiers can be preceded by lazy to match the least amount of characters rather than the most characters (greedy). Equivalent to regex +? , *? , etc. Symbols <char> - matches any single character. equivalent to regex . <space> - matches a space character. equivalent to regex <whitespace> - matches any kind of whitespace character. equivalent to regex \s or [ \t\n\v\f\r] <newline> - matches a newline character. equivalent to regex \n <tab> - matches a tab character. equivalent to regex \t <return> - matches a carriage return character. equivalent to regex \r <feed> - matches a form feed character. equivalent to regex \f <null> - matches a null characther. equivalent to regex \0 <digit> - matches any single digit. equivalent to regex \d or [0-9] <vertical> - matches a vertical tab character. equivalent to regex \v <word> - matches a word character (any latin letter, any digit or an underscore). equivalent to regex \w or [a-zA-Z0-9_] <alphabetic> - matches any single latin letter. equivalent to regex [a-zA-Z] <alphanumeric> - matches any single latin letter or any single digit. equivalent to regex [a-zA-Z0-9] <boundary> - Matches a character between a character matched by <word> and a character not matched by <word> without consuming the character. equivalent to regex \b <backspace> - matches a backspace control character. equivalent to regex [\b] All symbols can be preceeded with not to match any character other than the symbol Special Symbols <start> - matches the start of the string. equivalent to regex ^ <end> - matches the end of the string. equivalent to regex $ Unicode Categories Note: these are not supported when testing in the CLI ( -t or -f ) as the regex engine used does not support unicode categories. These require using the u flag. <category::letter> - any kind of letter from any language <category::lowercase_letter> - a lowercase letter that has an uppercase variant <category::uppercase_letter> - an uppercase letter that has a lowercase variant. <category::titlecase_letter> - a letter that appears at the start of a word when only the first letter of the word is capitalized <category::cased_letter> - a letter that exists in lowercase and uppercase variants <category::modifier_letter> - a special character that is used like a letter <category::other_letter> - a letter or ideograph that does not have lowercase and uppercase variants <category::mark> - a character intended to be combined with another character (e.g. accents, umlauts, enclosing boxes, etc.) <category::non_spacing_mark> - a character intended to be combined with another character without taking up extra space (e.g. accents, umlauts, etc.) <category::spacing_combining_mark> - a character intended to be combined with another character that takes up extra space (vowel signs in many Eastern languages) <category::enclosing_mark> - a character that encloses the character it is combined with (circle, square, keycap, etc.) <category::separator> - any kind of whitespace or invisible separator <category::space_separator> - a whitespace character that is invisible, but does take up space <category::line_separator> - line separator character U+2028 <category::paragraph_separator> - paragraph separator character U+2029 <category::symbol> - math symbols, currency signs, dingbats, box-drawing characters, etc <category::math_symbol> - any mathematical symbol <category::currency_symbol> - any currency sign <category::modifier_symbol> - a combining character (mark) as a full character on its own <category::other_symbol> - various symbols that are not math symbols, currency signs, or combining characters <category::number> - any kind of numeric character in any script <category::decimal_digit_number> - a digit zero through nine in any script except ideographic scripts <category::letter_number> - a number that looks like a letter, such as a Roman numeral <category::other_number> - a superscript or subscript digit, or a number that is not a digit 0–9 (excluding numbers from ideographic scripts) <category::punctuation> - any kind of punctuation character <category::dash_punctuation> - any kind of hyphen or dash <category::open_punctuation> - any kind of opening bracket <category::close_punctuation> - any kind of closing bracket <category::initial_punctuation> - any kind of opening quote <category::final_punctuation> - any kind of closing quote <category::connector_punctuation> - a punctuation character such as an underscore that connects words <category::other_punctuation> - any kind of punctuation character that is not a dash, bracket, quote or connectors <category::other> - invisible control characters and unused code points <category::control> - an ASCII or Latin-1 control character: 0x00–0x1F and 0x7F–0x9F <category::format> - invisible formatting indicator <category::private_use> - any code point reserved for private use <category::surrogate> - one half of a surrogate pair in UTF-16 encoding <category::unassigned> - any code point to which no character has been assigned These descriptions are from regular-expressions.info Character Ranges ... to ... - used with digits or alphabetic characters to express a character range. equivalent to regex [5-9] (assuming 5 to 9 ) or [a-z] (assuming a to z ) Literals "..." or '...' - used to mark a literal part of the match. Melody will automatically escape characters as needed. Quotes (of the same kind surrounding the literal) should be escaped Raw `...` - added directly to the output without any escaping Groups capture - used to open a capture or named capture block. capture patterns are later available in the list of matches (either positional or named). equivalent to regex (...) match - used to open a match block, matches the contents without capturing. equivalent to regex (?:...) either - used to open an either block, matches one of the statements within the block. equivalent to regex (?:...|...) Assertions ahead - used to open an ahead block. equivalent to regex (?=...) . use after an expression behind - used to open an behind block. equivalent to regex (?<=...) . use before an expression Assertions can be preceeded by not to create a negative assertion (equivalent to regex (?!...) , (?<!...) ) Variables let .variable_name = { ... } - defines a variable from a block of statements. can later be used with .variable_name . Variables must be declared before being used. Variable invocations cannot be quantified directly, use a group if you want to quantify a variable invocation example: ```rs let .a_and_b = { "a"; "b"; } .a_and_b; "c"; // abc ``` Extras /* ... */ , // ... - used to mark comments (note: // ... comments must be on separate line) File Extension The Melody file extensions are .mdy and .melody Crates melody_compiler - The Melody compiler 📦 📖 melody_cli - A CLI wrapping the Melody compiler 📦 📖 melody_wasm - WASM bindings for the Melody compiler Extensions VSCode IntelliJ Packages NodeJS Deno Integrations Babel Plugin Performance Last measured on v0.19.0 Measured on an 8 core 2021 MacBook Pro 14-inch, Apple M1 Pro using criterion : 8 lines: compiler/normal (8 lines) time: [4.0579 µs 4.0665 µs 4.0788 µs] slope [4.0579 µs 4.0788 µs] R^2 [0.9996538 0.9995633] mean [4.0555 µs 4.0806 µs] std. dev. [11.018 ns 26.342 ns] median [4.0500 µs 4.0852 µs] med. abs. dev. [5.6889 ns 35.806 ns] 1M lines: compiler/long input (1M lines) time: [400.97 ms 402.31 ms 403.53 ms] mean [400.97 ms 403.53 ms] std. dev. [773.42 µs 2.9886 ms] median [401.22 ms 403.39 ms] med. abs. dev. [59.042 µs 3.5129 ms] Deeply nested: compiler/deeply nested time: [5.8085 µs 5.8291 µs 5.8514 µs] slope [5.8085 µs 5.8514 µs] R^2 [0.9992861 0.9992461] mean [5.8064 µs 5.8519 µs] std. dev. [21.027 ns 49.152 ns] median [5.7949 µs 5.8583 µs] med. abs. dev. [3.3348 ns 64.628 ns] To reproduce, run cargo bench or cargo xtask benchmark Future Feature Status 🐣 - Partially implemented ❌ - Not implemented ❔ - Unclear what the syntax will be ❓ - Unclear whether this will be implemented | Melody | Regex | Status | | ------------------------------- | ---------------- | ------ | | not "A"; | [^A] | 🐣 | | variables / macros | | 🐣 | | <...::...> | \p{...} | 🐣 | | not <...::...> | \P{...} | 🐣 | | file watcher | | ❌ | | multiline groups in REPL | | ❌ | | flags: global, multiline, ... | /.../gm... | ❔ | | (?) | \# | ❔ | | (?) | \k<name> | ❔ | | (?) | \uYYYY | ❔ | | (?) | \xYY | ❔ | | (?) | \ddd | ❔ | | (?) | \cY | ❔ | | (?) | $1 | ❔ | | (?) | $` | ❔ | | (?) | $& | ❔ | | (?) | x20 | ❔ | | (?) | x{06fa} | ❔ | | any of "a", "b", "c" * | [abc] | ❓ | | multiple ranges * | [a-zA-Z0-9] | ❓ | | regex optimization | | ❓ | | standard library / patterns | | ❓ | | reverse compiler | | ❓ | * these are expressable in the current syntax using other methods

Melody is a language that compiles to regular expressions and aims to be more readable and maintainable

regular-expression,language,regex,compiler,melody,melodylang,regexp,rust

2dust/clashN

ClashN A clash client for Windows, supports Mihomo core How to use Download clashN.zip from releases Unzip to any folder you want Run ClashN.exe Tips You can also add v2ray subscription to ClashN , just enable Subcription conversion when you add a profile. Requirements Microsoft .NET 8.0 Desktop Runtime Mihomo core https://github.com/MetaCubeX/Mihomo/releases Telegram Channel github_2dust Contribute To build this project, you should clone both ClashN and v2rayN to the same folder Example folder ├─ ClashN | ├─ clashN | | ├─ clashN.sln | | └─ ... | ├─ README.md | └─ ... ├─ v2rayN | ├─ v2rayN | | ├─ v2rayN.sln | | └─ ... | ├─ README.md | └─ ... └─ ...

A clash client for Windows, support Mihomo

[]

ClemensElflein/OpenMower

I am available for hire Hello! With a background in software engineering, embedded programming, hardware design, and robotics, I'm on the lookout for new challenges. If you're in search of someone with my skills, let's team up and create something amazing! https://x-tech.online/ OpenMower - The DIY Smart Mowing Robot for Everyone Join the Discord server for OpenMower discussion: [!WARNING] DISCLAIMER: IF YOU ARE NOT 100% SURE WHAT YOU ARE DOING, PLEASE DON'T TRY THIS AT HOME! ASK IN DISCORD , IF YOU HAVE ANY QUESTIONS! [!IMPORTANT] This project is active! This is the hardware repository, so it might seem that the project is inactive, since hardware is pretty stable by now. Most of the development work is done on the ROS code here: https://github.com/ClemensElflein/open_mower_ros About the Project If you want to see a quick overview, you can check out this video: Let's be honest: The current generation of robotic lawn mowers sucks. Basically all of these bots drive in a random direction until they hit the border of the lawn, rotate for a randomized duration and repeat. I think we can do better! Therefore, we have disassembled the cheapest off-the-shelf robotic mower we could find (YardForce Classic 500) and were surprised that the hardware itself is actually quite decent: - Geared sensored brushless motors for the wheels - A sensored brushless motor for the mower motor itself - The whole construction seems robust, waterproof and all in all thought through - All components are connected using standard connectors, therefore upgrading the hardware is easily possible. The bottom line is: The bot itself is surprisingly high quality and doesn't need to be changed at all. We just need some better software in there . Project Goals Here is a quick overview of this project's goals: :heavy_check_mark: Autonomous Lawn Mowing: Obviously, the device should be able to mow the lawn automatically. :heavy_check_mark: Good Safety: The device must be safe, e.g. emergency stop if lifted or crashed. :heavy_check_mark: No Perimeter Wire Needed: We want to be flexible and support multiple mowing areas. :heavy_check_mark: Low Cost: It should be cheaper than a mid range off-the-shelf product :heavy_check_mark: Open: I want to share knowledge and enable others to build an OpenMower as well. :heavy_check_mark: Nice to Look At: You should not be ashamed to have an OpenMower mowing your lawn. :heavy_check_mark: Avoid Obstacles: The mower should detect obstacles and avoid them during mowing. :heavy_check_mark: Rain Detection: The device should be able to detect bad weather conditions and pause mowing until they improve. Open Mower App Current State The basic mowing function finally works! As you can see in the video, map teaching and mowing work as expected. It even returns to the docking station automatically as soon as the battery gets low and continues once it's recharged. At this point I can recommend that brave tech savvy users can build one for themselves! Since it's quite an expensive and complex project, please don't be shy and ask if you have any questions. I'm glad to help 🙂 Hardware By now we have a stable revision of the mainboard as well as two motor controllers to go with it. The xESC mini and the xESC 2040 . I'm currently using the xESC mini for my builds and it works very well. The problem with this controller is, its parts are currently hard to source. That's why we created the xESC 2040 based on the RP2040 chip. This is the low-cost variant and its support is currently experimental. Hardware To-Do: [x] Low Level Firmware Implementation [x] Voltage / Current Sense [x] Emergency Stop Button tracking [x] IMU Communication [x] Rain Sensor [x] Charging State [x] Sound Module [x] UI Board Communication [ ] Discharge current for more accurate battery charge estimation [X] ROS Hardware Interface Software The basic software is basically done; Our prototype works as intended (but is not able to avoid obstacles yet). The software for the robot can be found in a separate repository: https://github.com/ClemensElflein/open_mower_ros Software To-Do: [x] Mowing State Machine (Docking / Mowing, ...) [x] Path Planning [ ] Obstacle Avoidance [x] App / Visualization Getting Started If you want to read how to get started building a robot for yourself, check the OpenMower Website . There you can find information on which parts to buy, how to install the software and so on. If you find anything missing, please join the Discord server and ask there. Also there's the OpenMower Wiki which is written by the community. It has some additional guides and information. How You Can Help You can help by starting an OpenMower build of your own. This helps to validate the concept and helps to create useful documentation for new users. Additionally, you can help by starring 🌟 and watching 👀 this repository, since it will help with visibility. You can also subscribe to my YouTube channel . Compatible Robotic Mowers While disassembling the bot, I wondered about its mainboard: Instead of "YardForce" it read "GForce". After checking the internet for "GForce" robots, I found that that very similar looking robotic mowers are sold under the Herkules brand. Naturally I tried to dig deeper and actually found evidence that the mainboard is manufactured by some chinese company (SUMEC Hardware). It is therefore quite safe to assume that many robot mowers are basically the same device in a different case. This would be a huge win for the community, since this would mean that by making one of those robots smarter, we could upgrade lots of robots. Therefore it might be a good idea to start a list of compatible devices. So if you have a cheap robotic lawn mower, you can check, if it was already disassembled in the list below. If it's not there, it would be nice of you to check, if it contains the same mainboard as ours and add your robot to the list with some some pictures / model numbers. List of Compatible Mowers By now, some guys have disassembled their mowers and it doesn't look as good as I initially hoped. The GForce boards are basically just used by YardForce and some rebranded versions for the EU market. My exact hardware was only found in the mower I'm using (YardForce Classic 500) and in recently manufactured SA650 ECOs. The SA650 has a different chassis and we don't have a way of mounting the GPS antenna yet. Therefore at the moment, the only compatible mower is mine (the YardForce Classic 500). If you want to have a look at the disassembled mowers, check the Google Docs here More Infos This page only contains the basic overview of the project. To follow my current development state, check out my Blog . Patents, Local Laws, Liability Before building a robot based on the designs published here, please make sure that you are allowed to do so in your specific regions. There may be patents and / or laws prohibiting you of doing so. The code/schematics/PCB files are distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. This basically means: I'm just documenting a project of mine here for free and I don't have the time and resources to check that devices built using this information will be safe to use, legal to use or even work as intended. You will need technical know-how to use this project and I'm not liable for any damages your devices do to anyone or anything. License This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License . Feel free to use the design in your private/educational projects, but don't try to sell the design or products based on it without getting my consent first. The idea here is to share knowledge, not to enable others to simply sell my work. Thank you for understanding.

Let's upgrade cheap off-the-shelf robotic mowers to modern, smart RTK GPS based lawn mowing robots!

raspberry-pi,arduino,robot,robotics,gps,ros,rtk,path-finding,robomow,lawn-mower

janestreet/magic-trace

magic-trace Overview magic-trace collects and displays high-resolution traces of what a process is doing. People have used it to: figure out why an application running in production handles some requests slowly while simultaneously handling a sea of uninteresting requests, look at what their code is actually doing instead of what they think it's doing, get a history of what their application was doing before it crashed, instead of a mere stacktrace at that final instant, ...and much more! magic-trace: has 2%-10% overhead , doesn't require application changes to use, traces every function call with ~40ns resolution, and renders a timeline of call stacks going back (a configurable) ~10ms. You use it like perf : point it to a process and off it goes. The key difference from perf is that instead of sampling call stacks throughout time, magic-trace uses Intel Processor Trace to snapshot a ring buffer of all control flow leading up to a chosen point in time[^1]. Then, you can explore an interactive timeline of what happened. You can point magic-trace at a function such that when your application calls it, magic-trace takes a snapshot. Alternatively, attach it to a running process and detach it with Ctrl + C , to see a trace of an arbitrary point in your program. [^1]: perf can do this too, but that's not how most people use it. In fact, if you peek under the hood you'll see that magic-trace uses perf to drive Intel PT. Testimonials "Magic-trace is one of the simplest command-line debugging tools I have ever used." - Francis Ricci, Jane Street "Magic-trace is not just for performance. The tool gives insight directly into what happens in your program, when, and why. Consider using it for all your introspective goals!" - Andrew Hunter, Jane Street I use perf a ton, and I think that both perf and magic-trace give perspectives that the other doesn't. The benefit I got from magic-trace was entirely based on the fact that it works in slices at any zoom level, so I was able to see all the function calls that a 70ns function was performing, which was invisible in perf. - Doug Patti, Jane Street more testimonials... Install Make sure the system you want to trace is supported . The constraints that most commonly trip people up are: VMs are mostly not supported, Intel only (Skylake[^3] or later), Linux only. Grab a release binary from the latest release page . If downloading the prebuilt binary (not package), chmod +x magic-trace ^4 If downloading the package, run sudo dpkg -i magic-trace*.deb Then, test it by running magic-trace -help , which should bring up some help text. [^3]: Strictly speaking, anything newer than Broadwell, but this is not a platform we regularly test on, and timing resolution is worse (~1us). Getting started Here 's a sample C program to try out. It's a slightly modified version of the example in man 3 dlopen . Download that, build it with gcc demo.c -ldl -o demo , then leave it running ./demo . We're going to use that program to learn how dlopen works. Run magic-trace attach -pid $(pidof demo) . When you see the message that it's successfully attached, wait a couple seconds and Ctrl + C magic-trace . It will output a file called trace.fxt in your working directory. Open magic-trace.org , click "Open trace file" in the top-left-hand and give it the trace file generated in the previous step. That should have expanded into a trace. Zoom in until you can see an individual loop through dlopen / dlsym / cos / printf / dlclose . W zooms into wherever your mouse cursor is pointed (you'll need to zoom in a bunch to see anything useful), S zooms out, A moves left, D moves right, and scroll wheel moves your viewport up and down the stack. You'll only need to scroll to see particularly deep stack traces, it's probably not useful for this example. Click and drag on the white space around the call stacks to measure. Plant flags by clicking in the timeline along the top. Using the measurement tool, measure how long it takes to run cos . On my screen it takes ~5.7us. Congratulations, you just magically traced your first program! In contrast to traditional perf workflows, magic-trace excels at hypothesis generation. For example, you might notice that taking 6us to run cos is a really long time! If you zoom in even more, you'll see that there's actually five pink "[untraced]" cells in there. If you re-run magic-trace with root and pass it -trace-include-kernel , you'll see stacktraces for those. They're page fault handlers! The demo program actually calls cos twice. If you zoom in even more near the end of the 6us cos call, you'll see that the second call takes far less time and does not page fault. How to use it magic-trace continuously records control flow into a ring buffer. Upon some sort of trigger, it takes a snapshot of that buffer and reconstructs call stacks. There are two ways to take a snapshot: We just did this one: Ctrl + C magic-trace. If magic-trace terminates without already having taken a snapshot, it takes a snapshot of the end of the program. You can also trigger snapshots when the application calls a function. To do so, pass magic-trace the -trigger flag. -trigger '?' brings up a fuzzy-finding selector that lets you choose from all symbols in your executable, -trigger SYMBOL selects a specific, fully mangled, symbol you know ahead of time, and -trigger . selects the default symbol magic_trace_stop_indicator . Stop indicators are powerful. Here are some ideas for where you might want to place one: If you're using an asynchronous runtime, any time a scheduler cycle takes too long. In a server, when a request takes a surprisingly long time. After the garbage collector runs, to see what it's doing and what it interrupted. After a compiler pass has completed. You may leave the stop indicator in production code. It doesn't need to do anything in particular, magic-trace just needs the name. It is just an empty, but not inlined, function. It will cost ~10us to call, but only when magic-trace actually uses it to take a snapshot . Documentation More documentation is available on the magic-trace wiki . Discussion Join us on Discord to chat synchronously, or the GitHub discussion group to do so asynchronously. Contributing If you'd like to contribute: read the build instructions , set up your editor , take a quick tour through the codebase , then hit up the issue tracker for a good starter project. Privacy policy magic-trace does not send your code or derivatives of your code (including traces) anywhere. magic-trace.org is a lightly modified fork of Perfetto , and runs entirely in your browser. As far as we can tell, it does not send your trace anywhere. If you're worried about that changing one day, set up your own local copy of the Perfetto UI and use that instead. Acknowledgements Tristan Hume is the original author of magic-trace. He wrote it while working at Jane Street , who currently maintains it. Intel PT is the foundational technology upon which magic-trace rests. We'd like to thank the people at Intel for their years-long efforts to make it available, despite its slow uptake in the greater software community. magic-trace would not be possible without perf s extensive support for Intel PT. perf does most of the work in interpreting Intel PT's output, and magic-trace likely wouldn't exist were it not for their efforts. Thank you, perf developers. magic-trace.org is a fork of Perfetto , with minor modifications. We'd like to thank the people at Google responsible for it. It's a high quality codebase that solves a hard problem well. The ideas behind magic-trace are in no way unique. We've written down a list of prior art that has influenced its design.

magic-trace collects and displays high-resolution traces of what a process is doing

intel,x86,visualizer,tracing,profile,performance-tools,introspection

nativewind/nativewind

NativeWind NativeWind uses Tailwind CSS as high-level scripting language to create a universal design system . Styled components can be shared between all React Native platforms, using the best style engine for that platform (e.g. CSS StyleSheet or StyleSheet.create). It's goals are to to provide a consistent styling experience across all platforms, improving Developer UX, component performance and code maintainability. NativeWind processes your styles during your application build, and uses a minimal runtime to selectively apply reactive styles (eg changes to device orientation, light dark mode). In Action Features Works on all RN platforms, uses the best style system for each platform. Uses the Tailwind CSS compiler Styles are computed at build time Small runtime keeps your components fast Babel plugin for simple setup and improving intellisense support Respects all tailwind.config.js settings, including themes, custom values, plugins dark mode / arbitrary classes / media queries pseudo classes - hover / focus / active on compatible components styling based on parent state - automatically style children based upon parent pseudo classes children styles - create simple layouts based upon parent class Documentation All documentation is on our website https://nativewind.dev

React Native utility-first universal design system - powered by Tailwind CSS

react-native,tailwindcss,css,react,tailwind,react-native-web,nativewind

numbersprotocol/nit

Nit Nit is git for web3 digital asset and helps user to commit an asset's activities (chronicle) to blockchain. Please note, this repository is for nit open-source tools. If you are looking for accessing nit via API services, please visit here for more details. Why Nit To make digital assets trustworthy and traceable, Nit leverages web3 technologies and Git core concepts. Everyone can chronicle their assets by creating on-chain records so that we can productively debate, narrate, and analyse. All asset histories are written on chain and are searchable by asset CID. A sample transaction can be found here . Case study A crypto-based dossier could help prove Russia committed war crimes , CNN Starling Lab and Hala Systems file Cryptographic Submission of Evidence of War Crimes in Ukraine to the International Criminal Court , CAGR Commit & Asset Tree nit adopt similar design as git. When there is an update to the asset, such as updating creator information or updating content itself to create a child asset, there should be a new commit attach the asset itself. Every asset has a Tree file in IPFS to describe the property of the asset, including creator, creation time, license, etc. The asset tree CID is included in the on-chain message. Here is the example of the asset tree . The db diagram can be found here . In this diagram, you will find tables of commit and assetTree with the explanation of each data field Installation shell yarn global add @numbersprotocol/nit Example: Initial Registration If it's your first time to run nit , initialize Nit with default configuration: nit init and provide personal information. The details of the Nit configuration format is in the Configuration section below. nit config -e The default integrity register (smart contract) is running on Avalanche Fuji (Testnet) and will migrate to Numbers mainnet in the future. You need to get some testing tokens from the Fuji faucet for paying transaction fee. Create a working directory for the targeting asset: mkdir ~/temp && cd ~/temp Create the Asset Tree of the targeting asset. Example: nit add <asset-filepath> -m "First registration." To access the file of the CID, you can use browser to open the URL: https://<cid>.ipfs.dweb.link Double check the Commit information meets your expectation: nit status Register the Commit on blockchain: nit commit -m "commit description" You can check the Commit on blockchain by following the explorer URL returned by Nit. Get On-Chain Information Get on-chain block numbers of an Asset shell nit log <asset-cid> --blocks Example command of the mockup Asset shell nit log aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa --blocks Commit block numbers and indices Total Commit number: 74 Index: 0, Block number: 7236185 Index: 1, Block number: 7236445 ... Index: 71, Block number: 10849040 Index: 72, Block number: 10849133 Index: 73, Block number: 11040035 Get Commits of an Asset You can specify the starting and ending indices of block numbers: shell nit log <asset-cid> --from-index 3 --to-index 5 You will get the Commits from the block numbers associated to index 3 & 4. Example command of the mockup Asset shell nit log aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa --from-index 71 --to-index 73 Commits in block 71 & 72 (exclude block 73) ```shell Total Commit number: 74 block number: 10849040 tx: 0x6d5902173255afe379cc4ae934a6c684ecfd865679286665622de3cf10eddcbe { "assetTreeCid": "bafkreifnpykuw5g2m4k5k5wf55zxtzjmcftstzhtsarlkqytimajj3ntlq", "assetTreeSha256": "ad7e154b74da6715d576c5ef7379e52c116729e4f39022b54313430094edb35c", "assetTreeSignature": "0x9faf5c9d13b8d90a7a8e88aa6daf089ca89593c28dc241347c4756e83c2f1ea53ed1cb9e189f7ab81c81327527c97595f44ed71dda8e5d78ebe0dccfe9dd27081c", "author": "bafkreigzixvzu2tbxbvmvwcvlz2zwoagmb6c2q5egaq4lmd5sesyopmmx4", "committer": "bafkreigzixvzu2tbxbvmvwcvlz2zwoagmb6c2q5egaq4lmd5sesyopmmx4", "provider": "bafkreigtmno2wacf4ldb6ewbkboe7oojedsp3dky35djytor6guwzhbdpa", "timestampCreated": 1655720482, "action": "bafkreiavifzn7ntlb6p2lr55k3oezo6pofwvknecukc5auhng4miowcte4", "actionResult": "https://bafkreifnpykuw5g2m4k5k5wf55zxtzjmcftstzhtsarlkqytimajj3ntlq.ipfs.dweb.link", "abstract": "Action action-initial-registration." } block number: 10849133 tx: 0xe383fdc0f4eaf44e8bde4737f33bcd45742dcb846f3beb890976793d7cc9358e { "assetTreeCid": "bafkreidptwydheqfybug4mmnzwzdg4rqxjvg4akl2pwjmrfxhqz33qv4tu", "assetTreeSha256": "6f9db0339205c0686e318dcdb2337230ba6a6e014bd3ec9644b73c33bdc2bc9d", "assetTreeSignature": "0xef547e124a9904dbdb5a418022ad03c621201b74111a3b4c5fac61b1d82350170766cef8a27737d21ca9b1bd4e04f7cdea460706b68b14e0ed17f2a3de83f9131b", "author": "bafkreigzixvzu2tbxbvmvwcvlz2zwoagmb6c2q5egaq4lmd5sesyopmmx4", "committer": "bafkreigzixvzu2tbxbvmvwcvlz2zwoagmb6c2q5egaq4lmd5sesyopmmx4", "provider": "bafkreigtmno2wacf4ldb6ewbkboe7oojedsp3dky35djytor6guwzhbdpa", "timestampCreated": 1655720763, "action": "bafkreiavifzn7ntlb6p2lr55k3oezo6pofwvknecukc5auhng4miowcte4", "actionResult": "https://bafkreidptwydheqfybug4mmnzwzdg4rqxjvg4akl2pwjmrfxhqz33qv4tu.ipfs.dweb.link", "abstract": "Action action-initial-registration." } ``` Get difference of Commits and Asset Trees of an Asset shell nit diff <asset-cid> --from-index 3 --to-index 5 Example command of the mockup Asset shell nit diff aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa --from-index 71 --to-index 73 Diff of Commits and Asset Trees in block 71 & 72 (exclude block 73) ```shell from: block 10849040, tx 0x6d5902173255afe379cc4ae934a6c684ecfd865679286665622de3cf10eddcbe to: block 10849133, tx 0xe383fdc0f4eaf44e8bde4737f33bcd45742dcb846f3beb890976793d7cc9358e Commit difference { "abstract": "Action action-initial-registration.", "action": "bafkreiavifzn7ntlb6p2lr55k3oezo6pofwvknecukc5auhng4miowcte4", -"actionResult": "https://bafkreifnpykuw5g2m4k5k5wf55zxtzjmcftstzhtsarlkqytimajj3ntlq.ipfs.dweb.link", -"assetTreeCid": "bafkreifnpykuw5g2m4k5k5wf55zxtzjmcftstzhtsarlkqytimajj3ntlq", -"assetTreeSha256": "ad7e154b74da6715d576c5ef7379e52c116729e4f39022b54313430094edb35c", -"assetTreeSignature": "0x9faf5c9d13b8d90a7a8e88aa6daf089ca89593c28dc241347c4756e83c2f1ea53ed1cb9e189f7ab81c81327527c97595f44ed71dda8e5d78ebe0dccfe9dd27081c", +"actionResult": "https://bafkreidptwydheqfybug4mmnzwzdg4rqxjvg4akl2pwjmrfxhqz33qv4tu.ipfs.dweb.link", +"assetTreeCid": "bafkreidptwydheqfybug4mmnzwzdg4rqxjvg4akl2pwjmrfxhqz33qv4tu", +"assetTreeSha256": "6f9db0339205c0686e318dcdb2337230ba6a6e014bd3ec9644b73c33bdc2bc9d", +"assetTreeSignature": "0xef547e124a9904dbdb5a418022ad03c621201b74111a3b4c5fac61b1d82350170766cef8a27737d21ca9b1bd4e04f7cdea460706b68b14e0ed17f2a3de83f9131b", "author": "bafkreigzixvzu2tbxbvmvwcvlz2zwoagmb6c2q5egaq4lmd5sesyopmmx4", "committer": "bafkreigzixvzu2tbxbvmvwcvlz2zwoagmb6c2q5egaq4lmd5sesyopmmx4", "provider": "bafkreigtmno2wacf4ldb6ewbkboe7oojedsp3dky35djytor6guwzhbdpa", -"timestampCreated": 1655720482 +"timestampCreated": 1655720763 } Asset Tree difference { "abstract": "", "assetCid": "bafybeif3ctgbmiso4oykvwj6jebyrkjxqr26bfrkesla5yr2ypgx47wgle", "assetCreator": null, "assetSha256": null, "assetTimestampCreated": null, "assetTreeCustomKey1": "foo", "assetTreeCustomKey2": "bar", "encodingFormat": "application/zip", "license": { "document": "https://starlinglab.org", "name": "Starling License" }, +"nftRecord": "bafkreielfjf7sfxigb4r7tejt7jhl6kthxoujwziywixlwxjjho32may7y" } ``` Configuration The Nit configuration mimics the Hardhat configuration with additional fields. The Nit configuration is at ~/.nitconfig.json . Linux users can open the default editor by the command below: shell nit config -e Example of a Nit configuration: ```json { // CID of the author's profile of original Assets "author": "bafkreihkrnjvjeijjhalozcfpgrgb46673dlt4e3qm5bmvzzb4if423wse", // CID of the committer's profile who creates Asset Trees and Commits "committer": "bafkreihkrnjvjeijjhalozcfpgrgb46673dlt4e3qm5bmvzzb4if423wse", // CID of the service provider who hosts the integrity registration service "provider": "bafkreido4zu743f6isb5wninfkedvbirj2ngb5fkivrpdijh2xtd3s6rnu", "defaultNetwork": "fuji", "network": { "rinkeby": { "url": "https://eth-rinkeby.alchemyapi.io/v2/UO5kfog_UDJgGCuqeaSJmnE95_gKOnFN", "gasLimit": 200000, "accounts": [ " ", ], // integrity record contract address "contract": "0x2Aa4e29872DE77E1Bc6cF310d647F9cB0f9a073B", "explorerBaseUrl": "https://rinkeby.etherscan.io/tx" }, "avalanche": { "chainId": 43114, "url": "https://api.avax.network/ext/bc/C/rpc", "accounts": [ " ", ], "contract": "0x1970aFD0831E9233667fb9484910926c2b18BCb4", "explorerBaseUrl": "https://snowtrace.io/tx" }, "fuji": { "url": "https://api.avax-test.network/ext/bc/C/rpc", "chainId": 43113, "gasLimit": 200000, "accounts": [ " ", ], "contract": "0xA2De03bee39Fa637440909abC5621063bC5DA926", "explorerBaseUrl": "https://testnet.snowtrace.io/tx" }, "polygon": { "url": "https://polygon-rpc.com/", "gasPrice": 60000000000, "accounts": [ " ", ], "contract": "0x2094747c6c870f20E38f701116CBb46845b5E5c1", "explorerBaseUrl": "https://polygonscan.com/tx" }, "moonbase": { "url": "https://rpc.api.moonbase.moonbeam.network", "accounts": [ " ", ], "contract": "0xfbeA33fe2b266697404Dc5D1dC0A4ee9D0eDED23", "explorerBaseUrl": "https://moonbase.moonscan.io/tx" }, "aurora_testnet": { "url": "https://testnet.aurora.dev/", "chainId": 1313161555, "accounts": [ " ", ], "contract": "0x8e1bF90681C672e25aE880767d57f0552f6F5Cd1", "explorerBaseUrl": "https://testnet.aurorascan.dev/tx" } }, // For the ipfsadd command. We will support web3.storage soon "infura": { "projectId": "aaaaaaaaaaaaaaaaaaaaaaaaaaa", "projectSecret": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa" } } ``` Verification Verify the integrity of an Asset Tree shell nit verify --integrity-hash <assetTreeSha256> --signature <assetTreeSignature> Example shell nit verify --integrity-hash 6f9db0339205c0686e318dcdb2337230ba6a6e014bd3ec9644b73c33bdc2bc9d --signature 0xef547e124a9904dbdb5a418022ad03c621201b74111a3b4c5fac61b1d82350170766cef8a27737d21ca9b1bd4e04f7cdea460706b68b14e0ed17f2a3de83f9131b Verification result shell Signer address: 0x63B7076FC0A914Af543C2e5c201df6C29FCC18c5 If the signer address is different from the Committer's wallet address, you can treat this Commit as not trustworthy.

Git of Web3 assets

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salesforce/BLIP

BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Announcement: BLIP is now officially integrated into LAVIS - a one-stop library for language-and-vision research and applications! This is the PyTorch code of the BLIP paper [ blog ]. The code has been tested on PyTorch 1.10. To install the dependencies, run pip install -r requirements.txt Catalog: - [x] Inference demo - [x] Pre-trained and finetuned checkpoints - [x] Finetuning code for Image-Text Retrieval, Image Captioning, VQA, and NLVR2 - [x] Pre-training code - [x] Zero-shot video-text retrieval - [x] Download of bootstrapped pre-training datasets Inference demo: Run our interactive demo using Colab notebook (no GPU needed). The demo includes code for: 1. Image captioning 2. Open-ended visual question answering 3. Multimodal / unimodal feature extraction 4. Image-text matching Try out the Web demo , integrated into Huggingface Spaces 🤗 using Gradio . Replicate web demo and Docker image is also available at Pre-trained checkpoints: Num. pre-train images | BLIP w/ ViT-B | BLIP w/ ViT-B and CapFilt-L | BLIP w/ ViT-L --- | :---: | :---: | :---: 14M | Download | - | - 129M | Download | Download | Download Finetuned checkpoints: Task | BLIP w/ ViT-B | BLIP w/ ViT-B and CapFilt-L | BLIP w/ ViT-L --- | :---: | :---: | :---: Image-Text Retrieval (COCO) | Download | - | Download Image-Text Retrieval (Flickr30k) | Download | - | Download Image Captioning (COCO) | - | Download | Download | VQA | Download | Download | - NLVR2 | Download | - | - Image-Text Retrieval: Download COCO and Flickr30k datasets from the original websites, and set 'image_root' in configs/retrieval_{dataset}.yaml accordingly. To evaluate the finetuned BLIP model on COCO, run: python -m torch.distributed.run --nproc_per_node=8 train_retrieval.py \ --config ./configs/retrieval_coco.yaml \ --output_dir output/retrieval_coco \ --evaluate 3. To finetune the pre-trained checkpoint using 8 A100 GPUs, first set 'pretrained' in configs/retrieval_coco.yaml as "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base.pth". Then run: python -m torch.distributed.run --nproc_per_node=8 train_retrieval.py \ --config ./configs/retrieval_coco.yaml \ --output_dir output/retrieval_coco Image-Text Captioning: Download COCO and NoCaps datasets from the original websites, and set 'image_root' in configs/caption_coco.yaml and configs/nocaps.yaml accordingly. To evaluate the finetuned BLIP model on COCO, run: python -m torch.distributed.run --nproc_per_node=8 train_caption.py --evaluate 3. To evaluate the finetuned BLIP model on NoCaps, generate results with: (evaluation needs to be performed on official server) python -m torch.distributed.run --nproc_per_node=8 eval_nocaps.py 4. To finetune the pre-trained checkpoint using 8 A100 GPUs, first set 'pretrained' in configs/caption_coco.yaml as "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_capfilt_large.pth". Then run: python -m torch.distributed.run --nproc_per_node=8 train_caption.py VQA: Download VQA v2 dataset and Visual Genome dataset from the original websites, and set 'vqa_root' and 'vg_root' in configs/vqa.yaml. To evaluate the finetuned BLIP model, generate results with: (evaluation needs to be performed on official server) python -m torch.distributed.run --nproc_per_node=8 train_vqa.py --evaluate 3. To finetune the pre-trained checkpoint using 16 A100 GPUs, first set 'pretrained' in configs/vqa.yaml as "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_capfilt_large.pth". Then run: python -m torch.distributed.run --nproc_per_node=16 train_vqa.py NLVR2: Download NLVR2 dataset from the original websites, and set 'image_root' in configs/nlvr.yaml. To evaluate the finetuned BLIP model, run python -m torch.distributed.run --nproc_per_node=8 train_nlvr.py --evaluate 3. To finetune the pre-trained checkpoint using 16 A100 GPUs, first set 'pretrained' in configs/nlvr.yaml as "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base.pth". Then run: python -m torch.distributed.run --nproc_per_node=16 train_nlvr.py Finetune with ViT-L: In order to finetune a model with ViT-L, simply change the config file to set 'vit' as large. Batch size and learning rate may also need to be adjusted accordingly (please see the paper's appendix for hyper-parameter details). Gradient checkpoint can also be activated in the config file to reduce GPU memory usage. Pre-train: Prepare training json files where each json file contains a list. Each item in the list is a dictonary with two key-value pairs: {'image': path_of_image, 'caption': text_of_image}. In configs/pretrain.yaml, set 'train_file' as the paths for the json files . Pre-train the model using 8 A100 GPUs: python -m torch.distributed.run --nproc_per_node=8 pretrain.py --config ./configs/Pretrain.yaml --output_dir output/Pretrain Zero-shot video-text retrieval: Download MSRVTT dataset following the instructions from https://github.com/salesforce/ALPRO, and set 'video_root' accordingly in configs/retrieval_msrvtt.yaml. Install decord with pip install decord To perform zero-shot evaluation, run python -m torch.distributed.run --nproc_per_node=8 eval_retrieval_video.py Pre-training datasets download: We provide bootstrapped pre-training datasets as json files. Each json file contains a list. Each item in the list is a dictonary with two key-value pairs: {'url': url_of_image, 'caption': text_of_image}. Image source | Filtered web caption | Filtered synthetic caption by ViT-B | Filtered synthetic caption by ViT-L --- | :---: | :---: | :---: CC3M+CC12M+SBU | Download | Download | Download LAION115M | Download | Download | Download Citation If you find this code to be useful for your research, please consider citing. @inproceedings{li2022blip, title={BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation}, author={Junnan Li and Dongxu Li and Caiming Xiong and Steven Hoi}, year={2022}, booktitle={ICML}, } Acknowledgement The implementation of BLIP relies on resources from ALBEF , Huggingface Transformers , and timm . We thank the original authors for their open-sourcing.

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

vision-language,vision-and-language-pre-training,image-text-retrieval,image-captioning,visual-question-answering,visual-reasoning,vision-language-transformer

TJU-DRL-LAB/AI-Optimizer

AI-Optimizer AI-Optimizer is a next-generation deep reinforcement learning suit, providing rich algorithm libraries ranging from model-free to model-based RL algorithms, from single-agent to multi-agent algorithms. Moreover, AI-Optimizer contains a flexible and easy-to-use distributed training framework for efficient policy training. AI-Optimizer now provides the following built-in libraries, and more libraries and implementations are coming soon. - Multiagent Reinforcement learning - Self-supervised Representation Reinforcement Learning - Offline Reinforcement Learning - Transfer and Multi-task Reinforcement Learning - Model-based Reinforcement Learning Multiagent Reinforcement Learning (MARL) The Multiagent RL repo contains the released codes of representative research works of TJU-RL-Lab on Multiagent Reinforcement Learning (MARL). ❓ Problem to Solve Multi-agent reinforcement learning (MARL) has successfully addressed many complex real-world problems, such as playing the game of Go ( AlphaGo , AlphaGo Zero ), playing real-time multi-player strategy games ( StarCraft II , Dota 2 , Honor of Kings )，playing card games ( Poker , no-limit Poker ), robotic control and autonomous driving ( Smarts ). However, MARL suffers from several challenges in theoretical analysis, in addition to those that arise in single-agent RL. We summarize below the challenges that we regard as fundamental in developing theories for MARL. The curse of dimensionality (scalability) issue Non-stationarity Non-Unique Learning Goals Exploration–exploitation tradeoff Multiagent credit assignment problem Partial observability Hybrid action Our target is to design MARL algorithms which could solve or alleviate the problems mentioned above and promote the deployment and landing of MARL in more real-world applications. ⭐️ Core Directions We carry out our studies according to the challenges mentioned above. To solve the the curse of dimensionality issue, we design a series of scalable multiagent neural networks which could efficiently reduce the size of the search space by leveraging the permutation invariance and permutation equivariance properties , explicitly taking the action semantics into consideration, etc. To better make a balance of the exploration–exploitation tradeoff, we propose Progressive Mutual Information Collaboration to achieve more efficient cooperative exploration... An overall picture of the proposed methods is shown below. 💦 Contribution The main contribution of this repository is that: For beginners who are interested in MARL, our easy-marl codebase and ZhiHu blogs: MARL and communication-based MARL can be a preliminary tutorial. For researchers, we provide a systematic overview of typical challenges in MARL from different perspectives, each of which is a very valuable research direction and contains a series recent research works. We hope with our research works and the corresponding released codes can make it easier for researchers to design new algorithms. For example, given the significant interest in designing novel MARL architectures over the past few years, the research direction of scalable multiagent networks is definitely of interest to the MARL community. More recently, the notion of permutation-invariance and permutation-equivariance in the design of MARL agents has relatively drawn less attention than deserved, and therefore the presented idea in API paper is interesting and very relevant to MARL researchers. For practitioners , we release a serials of efficient, scalable, well-performed and easy to use MARL algorithms which achieve superior performance in the typical benchmarks of the MARL research community. For example, the API-QMIX, API-VDN, API-MAPPO and API-MADDPG algorithms proposed in our paper "API: Boosting Multi-Agent Reinforcement Learning via Agent-Permutation-Invariant Networks" achieve State-Of-The-Art Performance in the StarCraft Multi-Agent Challenge (SMAC) and Multi-agent Particle Environment benchmarks, which achieves 100% win-rates in almost all hard and super-hard SMAC scenarios (never achieved before) . We strongly recommend that practitioners try and use our API-Network solution FIRST when solving practical MARL problems (because it is very easy to use and does work very well) ! We hope our works can promote the deployment and landing of MARL in more real-world applications. See more here . Offline-rl-algorithms (Offrl) ❓ Problem to Solve Current deep RL methods still typically rely on active data collection to succeed, hindering their application in the real world especially when the data collection is dangerous or expensive. Offline RL (also known as batch RL) is a data-driven RL paradigm concerned with learning exclusively from static datasets of previously-collected experiences. In this setting, a behavior policy interacts with the environment to collect a set of experiences, which can later be used to learn a policy without further interaction. This paradigm can be extremely valuable in settings where online interaction is impractical. However, current offline rl methods are restricted to three challenges: * Low upper limit of algorithm: The quality of offline data determines the performance of offline reinforcement learning algorithms. How to expand low-quality offline data without additional interaction to increase the learning upper limit of offline reinforcement learning algorithms? * Poor algorithm effect: Existing off-policy/offline algorithm trains on the offline data distribution. When interacting with the environment, the distribution of the accessed state-action may change compared with the offline data (Distributional Shift). In this situation, the Q value of the pair is easy to be overestimated, which affects the overall performance. How to characterize the data outside the offline data distribution (Out Of Distribution, OOD) to avoid overestimation? * Difficulty in applying the algorithm: Due to the limited quality of the dataset, the learned strategy cannot be directly deployed in the production environment, and further online learning is required. How to design data sampling in the online training phase to avoid the sudden drop in the initial performance of the strategy due to the redundant data generated by the distribution change, and quickly converge to the optimal solution in a limited number of interactions? 💦 Contribution This repository contains the codes of representative benchmarks and algorithms on the topic of Offline Reinforcement Learning. The repository is developed based on d3rlpy(https://github.com/takuseno/d3rlpy) following MIT license to shed lights on the research on the above three challenges. While inheriting its advantages, the additional features include (or will be included): - A unified algorithm framework with rich and fair comparisons bewteen different algorithms: - REDQ - UWAC - BRED - … - Abundant and real-world datasets: - Real-world industrial datasets - Multimodal datasets - Augmented datasets (and corresponding methods) - Datasets obtained using representation learning (and corresponding methods) - More easy-to-use log systems support: - Wandb Self-supervised Reinforcement Learning (SSRL) SSRL repo contains the released codes of representative research works of TJU-RL-Lab on Self-supervised Representation Learning for RL. To the best of our knowledge, this is the first code repository for SSRL established by following a systematic research taxonomy and a unified algorithmic framework . ❓ Problem to Solve Since the RL agent always receives , processes , and delivers all kinds of data in the learning process (i.e., the typical Agent-Environment Interface), how to properly represent such "data" is naturally the key point to the effectiveness and efficiency of RL. In this branch, we focus on three key questions as follows: - What should a good representation for RL be? (Theory) - How can we obtain or realize such good representations? (Methodology) - How can we making use of good representations to improve RL? (Downstream Learning Tasks & Application) ⭐️ Core Idea Taking Self-supervised Learning (SSL) as our major paradigm for representation learning, we carry out our studies from four perspectives: - State Representation , - Action Representation , - Policy Representation , - Environment (and Task) Representation . These four pespectives are major elements involved in general Agent-Environment Interface of RL. They play the roles of input , optimization target and etc. in the process of RL. The representation of these elements make a great impact on the sample efficiency , convergence optimality and cross-enviornment generalization . The central contribution of this repo is A Unified Algorithmic Framework (Implementation Design) of SSRL Algorithm . The framework provides a unified interpretation for almost all currently existing SSRL algorithms. Moreover, the framework can also serve as a paradigm when we are going to devise new methods. Our ultimate goal is to promote the establishment of the ecology of SSRL, which is illustrated below. Towards addressing the key problems of RL, we study SSRL with four types of representations. For researches from all four pespectives, a unified framework of algorithm and imeplementation serves as the underpinnings. The representations studied from different pespectives further boost various downstream RL tasks. Finally, this promotes the deployment and landing of RL in real-world applications. See more here . 💦 Contribution With this repo and our research works, we want to draw the attention of RL community to studies on Self-supervised Representation Learning for RL. For people who are insterested in RL, our introduction in this repo and our blogs can be a preliminary tutorial. For cutting-edge RL researchers, we believe that our research thoughts and the proposed SSRL framework are insightful and inspiring, openning up new angles for future works on more advanced RL. For RL practicers (especially who work on related fields), we provide advanced RL algorithms with strong performance in online RL (e.g., PPO-PeVFA ), hybrid-action decision-making (e.g., HyAR ), policy adaptation from offline experience (e.g., PAnDR ) ..., which can be adopted or developed in associated academic and industrial problems. We are also looking forward to feedback in any form to promote more in-depth researches. Transfer and Multi-task Reinforcement Learning Recently, Deep Reinforcement Learning (DRL) has achieved a lot of success in human-level control problems, such as video games, robot control, autonomous vehicles, smart grids and so on. However, DRL is still faced with the sample-inefficiency problem especially when the state-action space becomes large, which makes it difficult to learn from scratch. This means the agent has to use a large number of samples to learn a good policy. Furthermore, the sample-inefficiency problem is much more severe in Multiagent Reinforcement Learning (MARL) due to the exponential increase of the state-action space. ❓ Problem to Solve Sample-inefficiency problem : The main challenge that transfer and multi-task RL aims to solve is the sample-inefficiency problem. This problem forces the agent to collect a huge amount of training data to learn the optimal policy. For example, the Rainbow DQN requires around 18 million frames of training data to exceed the average level of human players, which is equivalent to 60 hours of games played by human players. However, human players can usually learn an Atari game within a few minutes and can reach the average level of the same player after one hour of training. ⭐️ Core Idea Transfer RL which leverages prior knowledge from previously related tasks to accelerate the learning process of RL, has become one popular research direction to significantly improve sample efficiency of DRL. Multi-task RL , in which one network learns policies for multiple tasks, has emerged as another promising direction with fast inference and good performance. 💦 Contribution This repository contains the released codes of representative benchmarks and algorithms of TJU-RL-Lab on the topic of Transfer and Multi-task Reinforcement Learning, including the single-agent domain and multi-agent domain, addressing the sample-inefficiency problem in different ways. In this repo, we provide specific solutions of our lab including: * PTF addresses the Sample-inefficiency problem in DRL by proposing a novel Policy Transfer Framework (PTF). MAPTF addresses the Sample-inefficiency problem in deep MARL by proposing a Multi-Agent Policy Transfer Framework (MAPTF). KTM-DRL(reproduced) : A Knowledge Transfer based Multi-task Deep Reinforcement Learning framework (KTM-DRL) for continuous control. We reproduce the results in the MuJoCo continuous control task suite, more details can be find here . See more here . Model-based Reinforcement Learning (MBRL) Model-based reinforcement learning (MBRL) is widely seen as having the potential to be significantly more sample efficient than model-free RL. By learning a model of the environment, model-based methods learn with significantly lower sample complexity.The model of the environment is a representation model that explicitly contains knowledge about the environment or the task, and generally two types of models are included: a transition model or a dynamics model and the reward model. Once this model is modeled, it can be properly integrated into the interaction with the environment and the learning of strategies. ❓Problems to Solve The current classifications of the mainstream algorithms in the modern Model-Based RL area are orthogonal, which means some algorithms can be grouped into different categories according to different perspectives. In this branch, we focus on two key questions : How to Learn a Model and How to Utilize a Model . How to Learn a Model mainly focuses on how to build the environment model. How to Utilize a Model cares about how to utilize the learned model. ⭐️ Core Directions Ignoring the differences in specific methods, the purpose of MBRL algorithms can be more finely divided into four directions as follows: Reduce Model Error 、 Faster Planning 、 Higher Tolerance to Model Error 、 Scalability to Harder Problems . For the problem of How to Learn a Model , we can study on reducing model error to learn a more accurate world model or learning a world model with higher tolerance to model error. For the problem of How to Utilize a Model , we can study on faster planning with a learned model or the scalability of the learned model to harder problems. 💦 Contributions Why MBRL ? Model-based reinforcement learning (MBRL) enjoys several benefits, such as data-efficiency and planning, by learning a model of the environments dynamics. The model of the environment is a representation model that explicitly contains knowledge about the environment or the task, and generally two types of models are included: a transition model or a dynamics model and the reward model. Once this model is modeled, it can be properly integrated into the interaction with the environment and the learning of strategies. Why Our Lib? With this repo and our research works, we want to draw the attention of RL community to studies on Model Based RL. For people who are insterested in model based RL, our introductions in this repo and our ZhiHu blog series can be a preliminary tutorial. For Researchers in model-based RL, we collect several separate lines of research, which are sometimes closed-sourced or not reproducible and make some code-level optimizations for the convinience to find comparative baselines without the need to search around for implementations. We expect that our research thoughts and proposed topic for MBRL area can open up some new angles for future works on more advanced RL. What' more, We want to cover as many interesting new directions as possible, and then divide it into the topic we listed above, to give you some inspiration and ideas for your RESEARCH. Research in model-based RL has not been very standardized. It is fairly common for authors to experiment with self-designed environments, and there are several separate lines of research, which are sometimes closed-sourced or not reproducible. And for this, we have collected some of the mainstream MBRL algorithms and made some code-level optimizations. Bringing these algorithms together in a unified framework can save the researchers time in finding comparative baselines without the need to search around for implementations. Currently, we have implemented Dreamer, MBPO,BMPO, MuZero, PlaNet, SampledMuZero, CaDM and we plan to keep increasing this list in the future. We will constantly update this repo to include new research made by TJU-DRL-Lab to ensure sufficient coverage and reliability. We are also looking forward to feedback in any form to promote more in-depth researches. See more here . Contributing AI-Optimizer is still under development. More algorithms and features are going to be added and we always welcome contributions to help make AI-Optimizer better. Feel free to contribute.

The next generation deep reinforcement learning tookit

reinforcement-learning,transfer-learning,deep-learning

Ashinch/ReadYou

Read You An Android RSS reader presented in Material You style. English  | Deutsch | 简体中文 | 繁體中文 (Outdated) | فارسی (Outdated) Features Read You is an Android RSS reader presented in Material You style. The following are the progress made so far and the goals to be worked on in the near future: [x] Subscribe to RSS links [x] Import or export OPML files [x] Notification of new articles [x] Article readability optimization [x] Full content parse for original articles [x] Multi-account [ ] Bionic reading [ ] Read aloud [ ] Android widget [ ] ... Integration Read You integrates with some of third-party service APIs to support you in using your existing cloud accounts as data sources. [x] Fever [x] Google Reader [x] FreshRSS [ ] Miniflux [ ] Tiny Tiny RSS [ ] Inoreader [ ] Feedly [ ] Feedbin [ ] ... Download F-Droid releases can not upgrade to other releases and it is compiled, signed and distributed uniformly by F-Droid . Nightly We offer Nightly versions for testing purposes. These versions include the latest features and improvements but may not be as stable as our regular releases. Please note that Nightly builds might have bugs and are not recommended for everyday use. You can download the Nightly version from the following link: Check Nightly Builds Choose the latest workflow from the GitHub Actions page and download the artifacts from the workflow's summary page (You may require logging in to GitHub). Remember to back up your data before trying the Nightly version in case of any issues. Sponsorship Read You is a free open source software that benefits from the open source community and every user can enjoy it's full functionality for free, so if you appreciate my current work, you can buy me a cup of coffee ☕️. Thanks for all the love and support ❤️ Localization Thank you to each of the Read You translators, and if you would like to contribute, please submit a translation via Weblate . Build Welcome to open a pull request . GitHub Actions automatically packages all flavors of apk files for each commit. Read You is based on Jetpack Compose toolkit for building Android's native UI. First you need to get the source code of Read You . shell git clone https://github.com/Ashinch/ReadYou.git Then open it via Android Studio (latest version) . When you click the ▶ Run button, it will be built and run automatically. In case of lag, please select Release version build. Credits Open Source Projects MusicYou ParseRSS Readability4J opml-parser compose-html Rome Feeder Seal news-flash besticon ... Special Thanks Thanks to @Kyant0 for the design inspiration and Monet engine implementation for Read You . Thanks to JetBrains for allocating free open-source licences for IDEs for Read You . Thanks to Weblate for providing free hosting of open source projects for Read You . License GNU GPL v3.0 © Read You

An Android RSS reader presented in Material You style.

android,rss-reader,material-ui,material-you,material-design,material-design-3,kotlin,compose,f-droid,fdroid

containers/podman-desktop

Podman Desktop - A graphical tool for developing on containers and Kubernetes Documentation Overview Download Features Join Our Early Adopter Program (Optional) Roadmap Contributing Communication Code of Conduct License Overview Podman Desktop is a graphical interface that enables application developers to seamlessly work with containers and Kubernetes. Podman Desktop installs, configures, and keeps Podman up to date on your local environment. It provides a system tray, to check status and interact with your container engine without losing focus from other tasks. The desktop application provides a dashboard to interact with containers, images, pods, and volumes but also configures your environment with your OCI registries and network settings. Podman Desktop also provides capabilities to connect and deploy pods to Kubernetes environments. Podman Desktop also supports multiple container engines , pick your favourite one and use the tool! Download Check the downloads page on podman-desktop.io/downloads . Features Containers and pods dashboard Build, run, manage, and debug both containers and pods Run Pods on your container engine or with Kubernetes Convert your Pods to be running on Kubernetes Manage multiple container engines Multiple container engine support Podman container engine crc Lima: Linux Machines Docker container engine Podman engine update support Keep podman up-to-date on your PC by having Podman Desktop automatically install the newest version System tray support Manage your Container engine Define your Kubernetes context Enterprise capabilities Proxy Support OCI Image registries management Bridge between local and remote environments Connect and deploy to both local or remote Kubernetes environments Change your Kubernetes context and pick your deployment environment Join our early adopter program! (optional) We are seeking developers who are interested in improving Podman Desktop! Register your interest to join our Early Adopter Program by filling this form . This is totally optional and does not change any Podman Desktop features. Roadmap All upcoming features are tracked with GitHub milestones. Check out all our future features! Contributing Interested in fixing issues or contributing to Podman Desktop? :bug: File bugs or feature requests on GitHub :checkered_flag: Read our contributing guide :ok_hand: Review or contribute a pull request Communication For all bug and feature requests please file a GitHub issue . Discussions are done using GitHub Discussions . Chatting General questions & development: #podman-desktop on the Podman Discord #podman-desktop@libera.chat on IRC #podman-desktop@fedora.im on Matrix Note: All channels are bridged. Chat on either Discord, IRC, or Matrix, and your messages will appear on all three platforms! Kubernetes questions & development: #podman-desktop on the Kubernetes Slack Adopters Check out the list of companies already using Podman Desktop. Code of Conduct This project uses the Containers Community Code of Conduct . Testing License Licensed under Apache 2.0 .

Podman Desktop - A graphical tool for developing on containers and Kubernetes

containers,ui,tray-application,desktop,podman,podman-desktop,container,kubernetes,hacktoberfest

codewithsadee/vcard-personal-portfolio

vCard - Personal portfolio vCard is a fully responsive personal portfolio website, responsive for all devices, built using HTML, CSS, and JavaScript. Demo Prerequisites Before you begin, ensure you have met the following requirements: Git must be installed on your operating system. Installing vCard To install vCard , follow these steps: Linux and macOS: bash sudo git clone https://github.com/codewithsadee/vcard-personal-portfolio.git Windows: bash git clone https://github.com/codewithsadee/vcard-personal-portfolio.git Contact If you want to contact me you can reach me at Twitter . License MIT

vCard is a fully responsive personal portfolio website, responsive for all devices.

personal-website,portfolio-website,css,css3,html,portfolio

samchon/typia

Typia ```typescript // RUNTIME VALIDATORS export function is (input: unknown): input is T; // returns boolean export function assert (input: unknown): T; // throws TypeGuardError export function assertGuard (input: unknown): asserts input is T; export function validate (input: unknown): IValidation ; // detailed // JSON FUNCTIONS export namespace json { export function application (): IJsonApplication; // JSON schema export function assertParse (input: string): T; // type safe parser export function assertStringify (input: T): string; // safe and faster } // PROTOCOL BUFFER export namespace protobuf { export function message (): string; // Protocol Buffer message export function assertDecode (buffer: Uint8Array): T; // safe decoder export function assertEncode (input: T): Uint8Array; // safe encoder } // RANDOM GENERATOR export function random (g?: Partial ): T; ``` Typia is a transformer library supporting below features: Super-fast Runtime Validators Enhanced JSON functions Protocol Buffer encoder and decoder Random data generator [!NOTE] Only one line required, with pure TypeScript type Runtime validator is 20,000x faster than class-validator JSON serialization is 200x faster than class-transformer Sponsors Thanks for your support. Your donation encourages typia development. Playground You can experience how typia works by playground website : 💻 https://typia.io/playground Guide Documents Check out the document in the website : 🏠 Home Introduction Setup Pure TypeScript 📖 Features Runtime Validators assert() function is() function validate() function Functional Module Special Tags Enhanced JSON JSON Schema stringify() functions parse() functions Protocol Buffer Message Schema decode() functions encode() functions Random Generator Miscellaneous 🔗 Appendix API Documents Utillization Cases NestJS Prisma tRPC ⇲ Benchmark Result ⇲ dev.to Articles

Super-fast/easy runtime validations and serializations through transformation

json,stringify,typescript,fast,ajv,checker,generator,runtime,transform,validator

breezy-weather/breezy-weather

Breezy Weather Breezy Weather is a weather app with a strong focus on design, with a simple, clean UX, smooth animations, and Material Design all over, plus lots of customizability. # Download All installation methods Features Weather data Daily and hourly forecasts up to 16 days Temperature Air quality Wind UV index Precipitation Feels like temperature Hourly forecasts Humidity / Dew point Pressure Cloud cover Visibility Precipitation in the next hour Air quality Pollen & Mold Ephemeris (Sun & Moon) Severe weather and precipitation alerts Real-time weather conditions Temperature Feels like Wind UV index Humidity Dew point Atmospheric pressure Visibility Cloud cover Ceiling Multiple weather sources ( comparison ) Open-Meteo AccuWeather MET Norway Pirate Weather (no API key provided) HERE (no API key provided) Météo France Danmarks Meteorologiske Institut (DMI) Mixed China sources National Weather Service (NWS) Bright Sky (DWD) Environment and Climate Change Canada Central Weather Administration (CMA), Taiwan Israel Meteorological Service (IMS) SMHI MET Éireann World Meteorological Organization (WMO) Severe Weather Recosanté ATMO AuRA Large selection of home screen widgets for at-a-glance information Live wallpaper Custom icon packs Geometric Weather icon packs Chronus Weather icon packs Automatic dark mode Looking for radar? Check out this document Free and Open Source No proprietary blobs/dependencies (versions 5.0.0-alpha and later) Releases generated by GitHub actions, guaranteeing it matches the source code Fully works with Open-Meteo (FOSS source) Privacy-friendly No personal data collected by the app ( link to app privacy policy ) Multiple sources are available, with links to their privacy policies for transparency Current location is optional and not added by default If using current location, an IP location service can be used instead of GPS to send less accurate coordinates to weather source No trackers/automatic crash reporters Help Frequently Asked Questions / Help Homepage explanations Weather sources comparison Contribute Pull requests are welcome. You can have a look at issues opened to contributions . For other changes, please open an issue first to discuss what you would like to change. Contribution guide (includes a guide to create a new weather source) Features currently being worked on by a contributor #14 , #252 - New 24-hour fitting charts Features lacking an active contributor #10 - “Add location” page needs a new design, in the spirit of Google Maps where you can select location points on the map, or search manually - No mockup done yet #937 - Widget overhaul (prerequisite for any new widget improvement) - Some mockups were done but no one is working on it anymore Features that will not be implemented Paid-only sources, too limited free-tier, or free-tier that requires privacy-invasive information (credit card info, phone number, etc) Adding standard flavor or non-free sources to the F-Droid default repo: please use the standard flavor from a different store/source instead Changes to the background updates process , including but not limited: options for refreshing less than every 30 minutes, every time you open the app, every time you tap on widget, every time you unlock your phone “Circular sky” interface: please set a fixed background per location instead Publish to Google Play Store: please check alternatives Allow different flavors to be installed in parallel Implement features that are no longer available in latest Android versions Backport features/fixes from latest Android versions to older Android versions Donations: if you have extra money to spare, consider donating to Open-Meteo to support infrastructure costs and future developments (we currently lack a libre and gratis worldwide alternative for the following features: Reverse geocoding , Alerts , Normals ) Translations Translation is done externally on Weblate . Please read carefully project instructions if you want to help. English (and regional variants) and French translations are maintained by repo maintainers, but they are open to proofreading/improvements. You will need to make a pull request, as we didn’t find a way to make these languages in suggestion-only mode in Weblate (let us know if you find anything). Contact us If you’d like to report a bug or suggest a new feature, GitHub discussions or issues are best for organization. We’ve also created a Matrix/Element space with a number of different channels for more general discussion: #breezy-weather-space:matrix.org . If you are not comfortable writing a GitHub discussion/issue in English, you can ask on the channel if someone can help you in your language. We also have a dedicated help channel in French: #breezy-weather-francais:matrix.org If you’d prefer a direct channel link instead of a space link, here’s the main Breezy Weather Matrix channel: #breezy-weather:matrix.org License GNU Lesser General Public License v3.0 This License does not grant any rights in the trademarks, service marks, or logos of any Contributor. Misrepresentation of the origin of that material is prohibited, and modified versions of such material must be marked in reasonable ways as different from the original version. When creating a fork, remember to: - Respect the project’s LICENSE - Avoid confusion with Breezy Weather app: - Change the app name - Change the app icon - Avoid installation conflicts: - Change the applicationId in build.gradle.kts

A Material Design Weather Application

[]

SteamDeckHomebrew/decky-loader

Decky Loader 📖 About Decky Loader is a homebrew plugin launcher for the Steam Deck. It can be used to stylize your menus , change system sounds , adjust your screen saturation , change additional system settings , and more . For more information about Decky Loader as well as documentation and development tools, please visit our wiki . 🎨 Features 🧹 Clean injecting and loading of multiple plugins. 🔒 Stays installed between system updates and reboots. 🔗 Allows two-way communication between plugins and the loader. 🐍 Supports Python functions run from TypeScript React. 🌐 Allows plugins to make fetch calls that bypass CORS completely. 🤔 Common Issues Syncthing may use port 8080 on Steam Deck, which Decky Loader needs to function. If you are using Syncthing as a service, please change its port to something else. 8384 is the recommended port for Syncthing. If you are using any software that uses port 1337 or 8080, please change its port to something else or uninstall it. Sometimes Decky will disappear on SteamOS updates. This can easily be fixed by just re-running the installer and installing the stable branch again. If this doesn't work, try installing the prerelease instead. If that doesn't work, then check the existing issues and if there isn't one then you can file a new issue . 💾 Installation This installation can be done without an admin/sudo password set. Prepare a mouse and keyboard if possible. Keyboards and mice can be connected to the Steam Deck via USB-C or Bluetooth. Many Bluetooth keyboard and mouse apps are available for iOS and Android. (KDE connect is preinstalled on the steam deck) The Steam Link app is available on Windows , macOS , and Linux . It works well as a remote desktop substitute. If you have no other options, use the right trackpad as a mouse and press + to open the on-screen keyboard as needed. Press the button and open the Power menu. Select "Switch to Desktop". Navigate to this Github page on a browser of your choice. Download the installer file . (If using firefox, it will be named decky_installer.desktop.download . Rename it to decky_installer.desktop before running it) Drag the file onto your desktop and double click it to run it. Either type your admin password or allow Decky to temporarily set your admin password to Decky! (this password will be removed after the installer finishes) Choose the version of Decky Loader you want to install. Latest Release Intended for most users. This is the latest stable version of Decky Loader. Latest Pre-Release Intended for plugin developers. Pre-releases are unlikely to be fully stable but contain the latest changes. For more information on plugin development, please consult the wiki page . Open the Return to Gaming Mode shortcut on your desktop. There is also a fast install for those who can use Konsole. Run curl -L https://github.com/SteamDeckHomebrew/decky-installer/releases/latest/download/install_release.sh | sh and type your password when prompted. 👋 Uninstallation We are sorry to see you go! If you are considering uninstalling because you are having issues, please consider opening an issue or joining our Discord so we can help you and other users. Press the button and open the Power menu. Select "Switch to Desktop". Run the installer file again, and select uninstall decky loader . There is also a fast uninstall for those who can use Konsole. Run curl -L https://github.com/SteamDeckHomebrew/decky-installer/releases/latest/download/uninstall.sh | sh and type your password when prompted. 🚀 Getting Started Now that you have Decky Loader installed, you can start using plugins. Each plugin is maintained by a different developer and has its own uses, but most follow a general structure outlined below. 📦 Plugins Press the button and navigate to the icon. This is the Decky menu used for interacting with plugins and the loader itself. Select the icon to open the Plugins Browser. This is where you can find and install plugins. You can also install from URL in the Settings menu. We do not recommend installing plugins from untrusted sources. To install a plugin, select the "Install" button on the plugin you want. You can also select a version from a dropdown menu, but this is not recommended. To update, uninstall, and reload plugins, navigate to the Decky menu and select the icon. Keep in mind that uninstalling a plugin will only remove its plugin files, not any other files it may have created. 🛠️ Plugin Development There is no complete plugin development documentation yet. However a good starting point is the plugin template repository . Consider joining our Discord if you have any questions. 🤝 Contributing Please consult the wiki page regarding development for more information on installing development versions of Decky Loader. You can also install the Steam Deck UI on a Windows or Linux computer for testing by following this YouTube guide . Clone the repository using the latest commit to main before starting your PR. In your clone of the repository, run these commands. bash cd frontend pnpm i pnpm run build If you are modifying the UI, these commands will need to be run before deploying the changes to your Steam Deck. Use the VS Code tasks or deck.sh script to deploy your changes to your Steam Deck to test them. You will be testing your changes with the Python script version. You will need to build, deploy, and reload each time. ⚠️ If you are recieving build errors due to an out of date library, you should run this command inside of your repository. bash pnpm update decky-frontend-lib --latest Source control and deploying plugins are left to each respective contributor for the cloned repos in order to keep dependencies up to date. 📜 Credits The original idea for the plugin loader concept is based on the work of marios8543's Steam Deck UI Inject project .

A plugin loader for the Steam Deck.

steam,steamdeck,plugins,steamos,python

MrGlockenspiel/activate-linux

activate-linux The "Activate Windows" watermark ported to Linux with cairo in C "Science isn't about WHY. It's about WHY NOT. Why is so much of our science dangerous? Why not marry safe science if you love it so much. In fact, why not invent a special safety door that won't hit you on the butt on the way out, because you are fired." — Cave Johnson (Portal 2) Read ARGS.md for information about command line arguments. Building Note that the executable's name depends on the target platform. You can use make install to install and make uninstall to remove it. Xmake I've been experimenting with using Xmake for building instead of make, you can test this by installing it and running console xmake Please leave feedback to improve this if you want *nix: console make Windows (using MSYS2 ): Replace gcc with clang , if you want. But then don't forget to start proper shortcut MSYS2 CLANG64 . console pacman -S --noconfirm git make pkgconf pactoys pacboy -S --noconfirm gcc:p git clone https://github.com/MrGlockenspiel/activate-linux cd activate-linux export backends=gdi make Linux Dependencies This project depends on: - libcairo2-dev - libxi-dev - libx11-dev - x11proto-core-dev - x11proto-dev - libxt-dev - libxext-dev - libxfixes-dev - libxinerama-dev - libxrandr-dev - libwayland-dev - wayland-protocols Optional dependencies: - libconfig-dev Those packages may be installed (in Debian-based distros) like this: console sudo apt install libconfig-dev libcairo2-dev libxi-dev libx11-dev x11proto-core-dev x11proto-dev \ libxt-dev libxext-dev libxfixes-dev libxinerama-dev libxrandr-dev libwayland-dev wayland-protocols Installing Ubuntu @eddelbuettel runs a PPA with activate linux in it, so it can be installed with: console sudo add-apt-repository ppa:edd/misc sudo apt update sudo apt install activate-linux Arch Linux This project is in the AUR under activate-linux-git . Install/uninstall it using your favorite AUR helper. Nix (NixOS) This repository is a flake. Run it using nix run "github:MrGlockenspiel/activate-linux" . Gentoo @Plexvola maintains an ebuild for activate-linux and can be installed with the following console eselect repository enable vaacus emerge --sync vaacus emerge -av activate-linux openSUSE / SLE The package is built for various releases on OBS . Installation instructions for your specific distribution are available here: https://software.opensuse.org/download.html?project=home%3Atschmitz%3Aactivate-linux&package=activate-linux Here are the Tumbleweed instructions: console zypper addrepo https://download.opensuse.org/repositories/home:tschmitz:activate-linux/openSUSE_Tumbleweed/home:tschmitz:activate-linux.repo zypper refresh zypper install activate-linux Fedora The package is built for various releases on OBS . Installation instructions for your specific distribution are available here: https://software.opensuse.org/download.html?project=home%3Atschmitz%3Aactivate-linux&package=activate-linux Here are the Fedora Rawhide instructions: console dnf config-manager --add-repo https://download.opensuse.org/repositories/home:tschmitz:activate-linux/Fedora_Rawhide/home:tschmitz:activate-linux.repo dnf install activate-linux Windows Scoop You can install it on the Extras bucket: powershell scoop bucket add extras # Ensure bucket is added first scoop install activate-linux MacOS (Horrific) Dependencies Use MacPorts to install the following, then build normally. xorg-server cairo xorg-libXinerama Alternatively, you can use this project instead because it actually works properly. Example:

The "Activate Windows" watermark ported to Linux

[]

jassics/security-study-plan

A Practical Study Plan to become a successful cybersecurity engineer based on roles like Pentest, AppSec, Cloud Security, DevSecOps, and so on with free/paid resources, tools, and concepts to excel. It will cover but not limited to: Done 1. Common Skills for Security Study Plan 2. AWS Security Study Plan 3. GCP Security Study Plan 4. Web Penetration Testing Study Plan 5. Application Security Testing Plan 6. API Security Study Plan ToDo 1. Azure Security Study Plan 2. DevSecOps Study Plan - In Progress 3. Docker Security Study Plan 4. Kubernetes Security Study Plan 5. Network Security Study Plan 6. Cryptography Study Plan 7. Threat Modeling Study Plan 8. Software Supply Chain Security Study Plan 9. Secure Code Review Study Plan 10. Secure Software Development Lifecycle Study Plan 11. Security Architecture Study Plan I got the idea of creating this repo after seeing coding-interview-security as it echoes the journey that I went through to get into the full-time security role. I created this study plan to help people who are looking for guidance and help to plan and prepare for a job-specific skill set. If you study 3-4 hours per day for the next 6 months, you can clear high rewarding jobs provided you do lots of hands-on and go through each necessary topic/concept more than thrice and you are from a tech background. This worked in my case. Please note that some topics would be common for any listed security roles. Check common-skills-study-plan I will try my level best to add study references from the beginners' perspective but will have even advanced level coverage too. All the best for your security journey! What is it? This is to give a study plan to prepare for a specific role. It is of course multiple months of hard work and dedication which need a proper roadmap. Hence, this repo would be a point source for all your study plans. Prerequisites: - Ready to devote time daily - from a tech background, it can take a little more time but still possible to make a career in cybersecurity. - Never give up attitude - Hacker Mindset - Ready to explore on your own Please note that there are many job titles under each of these study plans, but I am keeping a generic study plan so that you can tick out whichever you already know. This way you would know how much you know and how much you still need to learn to grow up the ladder. Check out the YouTube video on "Cybersecurity Roadmap for Beginners" and "How to make a career in Cybersecurity" . Then, you will have a better idea of why to use it and how to use this study plan for your preparation. Why use it? If you want to work as a security engineer, these are the skills/topics/concepts you need to know and learn thoroughly.. When I started learning security concepts, everything was new to me, and I wasted lots of time on Google searches, YouTube videos, articles, etc. to figure out what was required and what was not. I am still learning as cybersecurity is evolving, so we must. My target is to keep this repo up to date, of course with the help of wonderful learners like you. It takes time to be confident in some skills, treat it as a long plan. It may take months or sometimes a year too, but keep yourself motivated and don't stop learning. However, If you are familiar with a lot of topics already it will take less time for you. How to use it? Everything below is like an outline, and you can tick out the items that you have already covered or know in order from top to bottom. I'm using GitHub's special markdown flavor , including task lists to track progress. As a Cybersecurity professional, I would recommend you to learn git and clone this repo for your learning purposes. Update your resume Before updating or creating a resume for a job, please check: 1. What job title you are trying for? 2. Do you fall in that experience range? 3. Check what skills it is looking for. 4. Check for job location or is it remote(work from home/anywhere)? Now, prepare the resume based on the above info and your skill sets. Try to be honest here. See, if you can finish your resume in 1-2 pages. Check the 1-page resume below links: 1. One page resume template from zety.com 2. Easy Resume 3. Various Security Resume sample from qwikresume.com 4. How To Write a Security Engineer Resume (With Example) 5. Network Security Engineer Sample 6. Cloud Security Engineer Resume 7. AWS Security Engineer Resume 8. Lead DevSecOps Resume Example 9. Sr. DevSecOps Engineer Resume Example 10. Penetration Tester Consultant Resume Sample Finding the right job You might see hundreds of job openings, some may be from your dream company. But, once you closely look it doesn't match with your skills. It seems the job title was a little misleading and more of a generic description. Security researchers or security analysts are just a few examples. So, finetune and narrow down the job search with the below websites but not limited to: 1. Which job title you are targeting? 2. What skills do you have vs what skills JD requires? 3. Years of experience (range) is matching? Now search or subscribe to below job portal below: 1. Linkedin. Yes, nowadays it's job alert setting does a better job in finding the right job for you. 2. Naukri.com (Mostly in Asian countries) 3. indeed.com 4. monster.com 5. instahyre.com 6. cutshort.io 7. Null Jobs Community 8. Cybersecurity Jobs 9. Interactive way to find jobs, skills, salary, etc. Interview Preparation You can start preparing for the job interview once you have solid knowledge as per the checklist for the given role(s). There are a few common security questions that you should have a look at: 1. Cybersecurity Interview Questions and Answers - Youtube 2. Cybersecurity Questions and Answers by Springboard 3. Cybersecurity Questions and Answers form indeed 4. 100+ Q&A for Cybersecurity domain from guru99 Common Interview Questions How do you keep updated yourself in the security domain? What would you do typically on the first day of your job? What personal achievement are you most proud of? What was your last tough vulnerability that you found? Why should we hire you? What did you learn in the last 6 months and how was it relevant to your career/project? Where do you see after 5 years of working with this organization? You can check some common answers from here Let's contribute and grow this repo together Want to contribute? Please fork the repo and send PR for review

Complete Practical Study Plan to become a successful cybersecurity engineer based on roles like Pentest, AppSec, Cloud Security, DevSecOps and so on...

aws-security,study-guide,study-plan,appsec,appsec-tutorials,azure-security,devsecops-university,gcp-security,pentesting,application-security

Atri-Labs/atrilabs-engine

Atri framework Seamless no-code and code in one tool  Website | Docs | Community Slack | YouTube | LinkedIn | Twitter 📈 Trending as the #1 TypeScript repository in GitHub! Source 🎉 Ranked as a top 10 TypeScript repository in GitHub in Nov and Dec. Source 🔥 Listed as a "Hot JS Tool" for the week of Nov 6. Source Web framework that helps developers in creating drag-and-drop zones for no-code development in their applications Frontend development: Use our powerful visual builder to create frontend or write React code Deployment support: Use our CLI to deploy at your platform of choice such as AWS, GitHub Pages, etc. or Atri cloud Watch the 1 min introduction video to Atri framework 👇 [](https://www.youtube.com/watch?v=mdPZUab2IlQ&t=52s) If you like our project, please support us by giving us a star ⭐! What can I build using this framework? Atri is a general purpose framework that can be used to build everything from e-commerce websites to internal apps. [](https://www.youtube.com/watch?v=mdPZUab2IlQ&t=52s) Apps built using Atri Venture Copilot The static instances of the web apps created using Atri have been deployed at the below URLs: Restaurant website | Sportswear website | Personal website | Ecommerce app | Personal blog | Data app | Custom background (ML) app Find more examples at Atri-Apps (https://github.com/orgs/Atri-Apps/repositories). How is Atri framework different from other web development frameworks? Atri framework is not just limited to the JavaScript world. You can use this framework with many languages such as Python, NodeJS (upcoming), etc. Atri framework comes with a suite of productivity tools such as visual editor, asset management tools, etc. that significantly reduce development time from months to hours. Using Atri framework, developers do not need to write and document REST APIs. Instead, they rely upon the object model which acts as a single source of truth. This also has other benefits as well such as reducing compliance breaches. Thus, Atri framework is extending the definition of full-stack to include non web developers in the development and maintenance of an app. Getting Started Please follow the docs here . How to contribute? Thanks for your interest in contributing to the Atri framework. 💖 You can contribute in any or all of the following ways: ask a question submit a bug report request a new feature suggest ways to improve the developer experience of an existing feature submit a documentation report propose an Atri app create an Atri App and share it with the community contribute to the Atri framework: You can get started with "good first issues" which are suitable for newcomers. Please refer to our contributing guidelines for details. Besides, please make sure you adhere to the code of conduct . If you make any contribution to our project (code or no-code; check the vast list of contribution types ), you will be featured in the table below 👇 Contributors 🎉 We are grateful to these wonderful people who contributed to Atri framework. 🙏 ( emoji key ): Shyam Swaroop 💻 📖 🚇 📆 🚧 🧑‍🏫 👀 ⚠️ 📹 Darshita Chaturvedi 💻 🚇 🚧 🧑‍🏫 📆 👀 ⚠️ Aditya Kumar Singh 💻 🚧 🧑‍🏫 Melvin Davis 💻 Jonathan Elroy Alvares 💻 Supratim Majumder 💻 MuminAhmadKhan 💻 Rishabh Baid 💻 Shivam8452 💻 Nukala Suraj 💻 SURAJ PHULARA 💻 harishfalco 💻 Tejaswini AVSV 💻 ayushi0809 📓 Prayas Ahir 📓 Artem 🔬 Ramachandran SS 📓 RohitKakade 📓 JadhavSankalp7 📓 💻 Harikishan TK 📓 Sayak Singha 📓 PansaraPriyanshi 📓 Shashwat Gupta 📓 Aman Kr. Poddar 📓 Mahe9041 📓 Sahil Suman 📓 Vamsi Revada 📓 Ayush Kumar Shukla 📓 Nikhil Singh Parmar 📓 Aryan Shaw 📓 Sanjay 🐛 Anurag Singh 🐛 sanskar gupta 🐛 📖 💻 💡 📣 📹 Sachin Sharma 💬 Surya Pandey 💬 Priyanshi Agarwal 💬 Aashutosh Kumar 💬 Prativh Gupta 💬 Geetanjali Kandpal 💬 Divyansh Singh 💬 Virenn Jay 🐛 ROHINI RAI 📓 zapkirin 📖 💬 Vitika Soni 🐛 Vivek T. 💻 Grisham Garg 🐛 Ankittripa 🤔 🧑‍🏫 🐛 💬 sahil kandpal 🐛 Khalid Saifullah 🐛 ahmed733 🐛 Awdhesh Kumar 🐛 Jitul Teron 💻 Anuj Singla 💻 Anuj Singla 💻 Manuel Heredia 💻 Nishant Kumar Singh 🧑‍🏫 💬 MOHAMMAD SARFRAZ ALAM 🐛 This project follows the all-contributors specification. Contributions of all types are welcome!

🧘‍♂️ Open-source no-code & code web app builder

fastapi,javascript,python3,reactjs,webframeworks

ggandor/leap.nvim

leap.nvim Leap is a general-purpose motion plugin for Neovim, building and improving primarily on vim-sneak , with the ultimate goal of establishing a new standard interface for moving around in the visible area in Vim-like modal editors. It allows you to reach any target in a very fast, uniform way, and minimizes the required focus level while executing a jump. How to use it (TL;DR) Leap's default motions allow you to jump to any position in the visible editor area by entering a 2-character search pattern, and then potentially a label character to pick your target from multiple matches, in a manner similar to Sneak. The main novel idea in Leap is that you get a preview of the target labels - Leap shows you which key you will need to press before you actually need to do that. Initiate the search in the forward ( s ) or backward ( S ) direction, or in the other windows ( gs ). (Note: you can use a single key for the current window or even the whole tab page, if you are okay with the trade-offs.) Start typing a 2-character pattern ( {char1}{char2} ). After typing the first character, you see "labels" appearing next to some of the {char1}{?} pairs. You cannot use the labels yet. Enter {char2} . If the pair was not labeled, then voilà, you're already there. You can safely ignore the remaining labels, and continue editing - those are guaranteed non-conflicting letters, disappearing on the next keypress. Else: type the label character. If there are more matches than available labels, you can switch between groups, using <space> and <tab> . Labels in the immediate next group are already visible, but highlighted differently than the active ones. Character pairs give you full coverage of the screen: s{char}<space> jumps to a character before the end of the line. s<space><space> jumps to any EOL position, including empty lines. At any stage, <enter> consistently jumps to the next available target ( <tab> steps back): s<enter>... repeats the previous search. s{char}<enter>... can be used as a multiline substitute for fFtT motions. Why is this method cool? It is ridiculously fast: not counting the trigger key, leaping to literally anywhere on the screen rarely takes more than 3 keystrokes in total, that can be typed in one go. Often 2 is enough. At the same time, it reduces mental effort to almost zero: You don't have to weigh alternatives : a single universal motion type can be used in all non-trivial situations. You don't have to compose in your head : one command achieves one logical movement. You don't have to be aware of the context : the eyes can keep focusing on the target the whole time. You don't have to make decisions on the fly : the sequence you should enter is determined from the very beginning. You don't have to pause in the middle : if typing at a moderate speed, at each step you already know what the immediate next keypress should be, and your mind can process the rest in the background. Getting started Status The plugin is not 100% stable yet, but don't let that stop you - the usage basics are extremely unlikely to change. To follow breaking changes, subscribe to the corresponding issue . Requirements Neovim >= 0.7.0 stable, or latest nightly Dependencies repeat.vim , for dot-repeats ( . ) to work Installation Use your preferred method or plugin manager. No extra steps needed besides defining keybindings - to use the default ones, put the following into your config (overrides s , S and gs in all modes): require('leap').create_default_mappings() (init.lua) lua require('leap').create_default_mappings() (init.vim) Alternative key mappings Calling `require('leap').create_default_mappings()` is equivalent to: ```lua vim.keymap.set({'n', 'x', 'o'}, 's', ' (leap-forward)') vim.keymap.set({'n', 'x', 'o'}, 'S', ' (leap-backward)') vim.keymap.set({'n', 'x', 'o'}, 'gs', ' (leap-from-window)') ``` A suggested alternative arrangement (bidirectional `s` for Normal mode): ```lua vim.keymap.set('n', 's', ' (leap)') vim.keymap.set('n', 'S', ' (leap-from-window)') vim.keymap.set({'x', 'o'}, 's', ' (leap-forward)') vim.keymap.set({'x', 'o'}, 'S', ' (leap-backward)') ``` Mapping to ` (leap)` is not recommended for Visual mode, as autojumping in a random direction might be too disorienting with the selection highlight on, and neither for Operator-pending mode, as dot-repeat cannot be used if the search is non-directional. Note that compared to using separate keys for the two directions, you will get twice as many targets and thus half as many autojumps on average, but not needing to press the Shift key for backward motions might compensate for that. Another caveat is that you cannot traverse through the matches (`:h leap-traversal`), although invoking repeat right away (`:h leap-repeat`) can substitute for that. ` (leap)` sorts matches by euclidean distance from the cursor, with the exception that the current line, and on the current line, forward direction is prioritized. That is, you can always be sure that the targets right in front of you will be the first ones. See `:h leap-custom-mappings` for more. Suggested additional tweaks ```lua -- Define equivalence classes for brackets and quotes, in addition to -- the default whitespace group. require('leap').opts.equivalence_classes = { ' \t\r\n', '([{', ')]}', '\'"`' } -- Override some old defaults - use backspace instead of tab (see issue #165). require('leap').opts.special_keys.prev_target = ' ' require('leap').opts.special_keys.prev_group = ' ' -- Use the traversal keys to repeat the previous motion without explicitly -- invoking Leap. require('leap.user').set_repeat_keys(' ', ' ') ``` Workaround for the duplicate cursor bug when autojumping For Neovim versions < 0.10 (https://github.com/neovim/neovim/issues/20793): ```lua -- Hide the (real) cursor when leaping, and restore it afterwards. vim.api.nvim_create_autocmd('User', { pattern = 'LeapEnter', callback = function() vim.cmd.hi('Cursor', 'blend=100') vim.opt.guicursor:append { 'a:Cursor/lCursor' } end, } ) vim.api.nvim_create_autocmd('User', { pattern = 'LeapLeave', callback = function() vim.cmd.hi('Cursor', 'blend=0') vim.opt.guicursor:remove { 'a:Cursor/lCursor' } end, } ) ``` Caveat: If you experience any problems after using the above snippet, check [#70](https://github.com/ggandor/leap.nvim/issues/70#issuecomment-1521177534) and [#143](https://github.com/ggandor/leap.nvim/pull/143) to tweak it. Lazy loading ...is all the rage now, but doing it via your plugin manager is unnecessary, as Leap lazy loads itself. Using the `keys` feature of lazy.nvim might even cause [problems](https://github.com/ggandor/leap.nvim/issues/191). Next steps Help files are not exactly page-turners, but I suggest at least skimming :help leap , even if you don't have a specific question yet (if nothing else: :h leap-usage , :h leap-config , :h leap-events ). While Leap has deeply thought-through, opinionated defaults, its small(ish) but comprehensive API makes it pretty flexible. Design considerations in detail The ideal Premise: jumping from point A to B on the screen should not be some exciting puzzle , for which you should train yourself; it should be a non-issue. An ideal keyboard-driven interface would impose almost no more cognitive burden than using a mouse, without the constant context-switching required by the latter. That is, you do not want to think about the command : we need one fundamental targeting method that can bring you anywhere: a "jetpack on the back", instead of "airline routes" (↔ EasyMotion and its derivatives) the context : it should be enough to look at the target, and nothing else (↔ vanilla Vim motion combinations using relative line numbers and/or repeats) the steps : the motion should be atomic (↔ Vim motion combos), and ideally you should be able to type the whole sequence in one go, on more or less autopilot (↔ any kind of "just-in-time" labeling method; note that the "search command on steroids" approach by Pounce and Flash , where the labels appear at an unknown time by design, makes this last goal impossible) All the while using as few keystrokes as possible , and getting distracted by as little incidental visual noise as possible . How do we measure up? It is obviously impossible to achieve all of the above at the same time, without some trade-offs at least; but in our opinion Leap comes pretty close, occupying a sweet spot in the design space. (The worst remaining offender might be visual noise.) The one-step shift between perception and action is the big idea that cuts the Gordian knot: a fixed pattern length combined with ahead-of-time labeling can eliminate the surprise factor from the search-based method (which is the only viable approach - see "jetpack" above). Fortunately, a 2-character pattern - the shortest one with which we can play this trick - is also long enough to sufficiently narrow down the matches in the vast majority of cases. Fixed pattern length also makes (safe) automatic jump to the first target possible. You cannot improve on jumping directly, just like how f and t works, not having to read a label at all, and not having to accept the match with <enter> either. However, we can do this in a smart way: if there are many targets (more than 15-20), we stay put, so we can use a bigger, "unsafe" label set - getting the best of both worlds. The non-determinism we're introducing is less of an issue here, since the outcome is known in advance. In sum, compared to other methods based on labeling targets, Leap's approach is unique in that it offers a smoother experience, by (somewhat) eliminating the pause before typing the label feels natural to use for both distant and close targets Auxiliary principles Optimize for the common case A good example is using strictly one-character labels and switching between groups, which can become awkward beyond, say, 200 targets, but makes a whole bunch of edge cases and UI problems nonexistent. Sharpen the saw Build on Vim's native features, aim for synergy, and don't reinvent the wheel (dot-repeat (`.`), inclusive/exclusive toggle (`v`), [keymap](https://neovim.io/doc/user/mbyte.html#mbyte-keymap) support, autocommands via `User` events, ` ` keys, etc.). (http://vimcasts.org/blog/2012/08/on-sharpening-the-saw/) Mechanisms instead of policies Complement the small and opinionated core by [extension points](#extending-leap), keeping the plugin flexible and future-proof. FAQ Bugs Workaround for the duplicate cursor bug when autojumping For Neovim versions < 0.10 (https://github.com/neovim/neovim/issues/20793): ```lua -- Hide the (real) cursor when leaping, and restore it afterwards. vim.api.nvim_create_autocmd('User', { pattern = 'LeapEnter', callback = function() vim.cmd.hi('Cursor', 'blend=100') vim.opt.guicursor:append { 'a:Cursor/lCursor' } end, } ) vim.api.nvim_create_autocmd('User', { pattern = 'LeapLeave', callback = function() vim.cmd.hi('Cursor', 'blend=0') vim.opt.guicursor:remove { 'a:Cursor/lCursor' } end, } ) ``` Caveat: If you experience any problems after using the above snippet, check [#70](https://github.com/ggandor/leap.nvim/issues/70#issuecomment-1521177534) and [#143](https://github.com/ggandor/leap.nvim/pull/143) to tweak it. Defaults Why remap `s`/`S`? Common operations should use the fewest keystrokes and the most comfortable keys, so it makes sense to take those over by Leap, especially given that both native commands have synonyms: Normal mode - `s` = `cl` (or `xi`) - `S` = `cc` Visual mode - `s` = `c` - `S` = `Vc`, or `c` if already in linewise mode If you are not convinced, just head to `:h leap-custom-mappings`. Features Search in all windows ```lua vim.keymap.set('n', 's', function () require('leap').leap { target_windows = require('leap.user').get_focusable_windows() } end) ``` The additional trade-off here is that if you have multiple windows open on the tab page, then you will almost never get an autojump, except if all targets are in the same window (it would be too disorienting if the cursor could suddenly jump in/to a different window than your goal, right before selecting the target, not to mention that we don't want to change the state of a window we're not targeting). Smart case sensitivity, wildcard characters (one-way aliases) Ahead-of-time labeling, unfortunately, makes them impossible, by design: for a potential match in phase one, we might need to show two different labels (corresponding to two different futures) at the same time. ([1](https://github.com/ggandor/leap.nvim/issues/28), [2](https://github.com/ggandor/leap.nvim/issues/89#issuecomment-1368885497), [3](https://github.com/ggandor/leap.nvim/issues/155#issuecomment-1556124351)) Arbitrary remote actions instead of jumping Basic template: ```lua local function remote_action () require('leap').leap { target_windows = require('leap.user').get_focusable_windows(), action = function (target) local winid = target.wininfo.winid local lnum, col = unpack(target.pos) -- 1/1-based indexing! -- ... do something at the given position ... end, } end ``` See [Extending Leap](#extending-leap) for more. Other supernatural powers besides clairvoyance? You might be interested in [telekinesis](https://github.com/ggandor/leap-spooky.nvim). Configuration Disable auto-jumping to the first match ```lua require('leap').opts.safe_labels = {} ``` Greying out the search area ```lua -- Or just set to grey directly, e.g. { fg = '#777777' }, -- if Comment is saturated. vim.api.nvim_set_hl(0, 'LeapBackdrop', { link = 'Comment' }) ``` Hiding secondary labels You can hide the letters, and show emtpy boxes by tweaking the `LeapLabelSecondary` highlight group (that way you keep a visual indication that the target is labeled): ```lua vim.api.nvim_create_autocmd('ColorScheme', { callback = function () local bg = vim.api.nvim_get_hl(0, {name = 'LeapLabelSecondary'}).bg vim.api.nvim_set_hl(0, 'LeapLabelSecondary',{ fg = bg, bg = bg, }) end }) ``` Lightspeed-style highlighting ```lua -- The below settings make Leap's highlighting closer to what you've been -- used to in Lightspeed. vim.api.nvim_set_hl(0, 'LeapBackdrop', { link = 'Comment' }) -- or some grey vim.api.nvim_set_hl(0, 'LeapMatch', { -- For light themes, set to 'black' or similar. fg = 'white', bold = true, nocombine = true, }) -- Lightspeed colors -- primary labels: bg = "#f02077" (light theme) or "#ff2f87" (dark theme) -- secondary labels: bg = "#399d9f" (light theme) or "#99ddff" (dark theme) -- shortcuts: bg = "#f00077", fg = "white" -- You might want to use either the primary label or the shortcut colors -- for Leap primary labels, depending on your taste. vim.api.nvim_set_hl(0, 'LeapLabelPrimary', { fg = 'red', bold = true, nocombine = true, }) vim.api.nvim_set_hl(0, 'LeapLabelSecondary', { fg = 'blue', bold = true, nocombine = true, }) -- Try it without this setting first, you might find you don't even miss it. require('leap').opts.highlight_unlabeled_phase_one_targets = true ``` Working with non-English text If a [`language-mapping`](https://neovim.io/doc/user/map.html#language-mapping) ([`'keymap'`](https://neovim.io/doc/user/options.html#'keymap')) is active, Leap waits for keymapped sequences as needed and searches for the keymapped result as expected. Also check out `opts.equivalence_classes`, that lets you group certain characters together as aliases, e.g.: ```lua { ' \t\r\n', 'aäàáâãā', 'dḍ', 'eëéèêē', 'gǧğ', 'hḥḫ', 'iïīíìîı', 'nñ', 'oō', 'sṣšß', 'tṭ', 'uúûüűū', 'zẓ' } ``` Miscellaneous Was the name inspired by Jef Raskin's Leap? To paraphrase Steve Jobs about their logo and Turing's poison apple, I wish it were, but it is a coincidence. "Leap" is just another synonym for "jump", that happens to rhyme with Sneak. That said, in some respects you can indeed think of leap.nvim as a spiritual successor to Raskin's work, and thus the name as a little tribute to the great pioneer of interface design, even though embracing the modal paradigm is a fundamental difference in our approach. Extending Leap There are lots of ways you can extend the plugin and bend it to your will - see :h leap.leap() and :h leap-events . Besides tweaking the basic parameters (search scope, jump offset, etc.) of the function, you can: give it a custom action to perform, instead of jumping feed it with custom targets , aquired by arbitrary means, and only use it as labeler/selector customize the behavior on a per-call basis via autocommands Some practical examples: Linewise motions ```lua local function get_line_starts(winid, skip_range) local wininfo = vim.fn.getwininfo(winid)[1] local cur_line = vim.fn.line('.') -- Skip lines close to the cursor. local skip_range = skip_range or 2 -- Get targets. local targets = {} local lnum = wininfo.topline while lnum <= wininfo.botline do local fold_end = vim.fn.foldclosedend(lnum) -- Skip folded ranges. if fold_end ~= -1 then lnum = fold_end + 1 else if (lnum < cur_line - skip_range) or (lnum > cur_line + skip_range) then table.insert(targets, { pos = { lnum, 1 } }) end lnum = lnum + 1 end end -- Sort them by vertical screen distance from cursor. local cur_screen_row = vim.fn.screenpos(winid, cur_line, 1)['row'] local function screen_rows_from_cur(t) local t_screen_row = vim.fn.screenpos(winid, t.pos[1], t.pos[2])['row'] return math.abs(cur_screen_row - t_screen_row) end table.sort(targets, function (t1, t2) return screen_rows_from_cur(t1) < screen_rows_from_cur(t2) end) if #targets >= 1 then return targets end end -- You can pass an argument to specify a range to be skipped -- before/after the cursor (default is +/-2). function leap_line_start(skip_range) local winid = vim.api.nvim_get_current_win() require('leap').leap { target_windows = { winid }, targets = get_line_starts(winid, skip_range), } end -- For maximum comfort, force linewise selection in the mappings: vim.keymap.set('x', '|', function () -- Only force V if not already in it (otherwise it would exit Visual mode). if vim.fn.mode(1) ~= 'V' then vim.cmd('normal! V') end leap_line_start() end) vim.keymap.set('o', '|', "V lua leap_line_start() ") ``` Select Tree-sitter nodes Not as sophisticated as flash.nvim's implementation, but totally usable, in 50 lines: ```lua local api = vim.api local ts = vim.treesitter local function get_ts_nodes() if not pcall(ts.get_parser) then return end local wininfo = vim.fn.getwininfo(api.nvim_get_current_win())[1] -- Get current node, and then its parent nodes recursively. local cur_node = ts.get_node() if not cur_node then return end local nodes = { cur_node } local parent = cur_node:parent() while parent do table.insert(nodes, parent) parent = parent:parent() end -- Create Leap targets from TS nodes. local targets = {} local startline, startcol for _, node in ipairs(nodes) do startline, startcol, endline, endcol = node:range() -- (0,0) local startpos = { startline + 1, startcol + 1 } local endpos = { endline + 1, endcol + 1 } -- Add both ends of the node. if startline + 1 >= wininfo.topline then table.insert(targets, { pos = startpos, altpos = endpos }) end if endline + 1 <= wininfo.botline then table.insert(targets, { pos = endpos, altpos = startpos }) end end if #targets >= 1 then return targets end end local function select_node_range(target) local mode = api.nvim_get_mode().mode -- Force going back to Normal from Visual mode. if not mode:match('no?') then vim.cmd('normal! ' .. mode) end vim.fn.cursor(unpack(target.pos)) local v = mode:match('V') and 'V' or mode:match('') and '' or 'v' vim.cmd('normal! ' .. v) vim.fn.cursor(unpack(target.altpos)) end local function leap_ts() require('leap').leap { target_windows = { api.nvim_get_current_win() }, targets = get_ts_nodes, action = select_node_range, } end vim.keymap.set({'x', 'o'}, '\\', leap_ts) ``` Shortcuts to Telescope results ```lua -- NOTE: If you try to use this before entering any input, an error is thrown. -- (Help would be appreciated, if someone knows a fix.) local function get_targets (buf) local pick = require('telescope.actions.state').get_current_picker(buf) local scroller = require('telescope.pickers.scroller') local wininfo = vim.fn.getwininfo(pick.results_win)[1] local top = math.max( scroller.top(pick.sorting_strategy, pick.max_results, pick.manager:num_results()), wininfo.topline - 1 ) local bottom = wininfo.botline - 2 -- skip the current row local targets = {} for lnum = bottom, top, -1 do -- start labeling from the closest (bottom) row table.insert(targets, { wininfo = wininfo, pos = { lnum + 1, 1 }, pick = pick, }) end return targets end local function pick_with_leap (buf) require('leap').leap { targets = function () return get_targets(buf) end, action = function (target) target.pick:set_selection(target.pos[1] - 1) require('telescope.actions').select_default(buf) end, } end require('telescope').setup { defaults = { mappings = { i = { [' '] = pick_with_leap }, } } } ``` Remote text objects See [leap-spooky.nvim](https://github.com/ggandor/leap-spooky.nvim). Enhanced f/t motions See [flit.nvim](https://github.com/ggandor/flit.nvim).

Neovim's answer to the mouse 🦘

neovim,neovim-plugin,nvim,nvim-plugin,fennel,vim,motion

pufferffish/wireproxy

wireproxy A wireguard client that exposes itself as a socks5/http proxy or tunnels. What is this wireproxy is a completely userspace application that connects to a wireguard peer, and exposes a socks5/http proxy or tunnels on the machine. This can be useful if you need to connect to certain sites via a wireguard peer, but can't be bothered to setup a new network interface for whatever reasons. Why you might want this You simply want to use wireguard as a way to proxy some traffic. You don't want root permission just to change wireguard settings. Currently, I'm running wireproxy connected to a wireguard server in another country, and configured my browser to use wireproxy for certain sites. It's pretty useful since wireproxy is completely isolated from my network interfaces, and I don't need root to configure anything. Users who want something similar but for Amnezia VPN can use this fork of wireproxy by @juev . Feature TCP static routing for client and server SOCKS5/HTTP proxy (currently only CONNECT is supported) TODO UDP Support in SOCKS5 UDP static routing Usage ./wireproxy -c [path to config] ``` usage: wireproxy [-h|--help] [-c|--config " "] [-s|--silent] [-d|--daemon] [-i|--info " "] [-v|--version] [-n|--configtest] Userspace wireguard client for proxying Arguments: -h --help Print help information -c --config Path of configuration file -s --silent Silent mode -d --daemon Make wireproxy run in background -i --info Specify the address and port for exposing health status -v --version Print version -n --configtest Configtest mode. Only check the configuration file for validity. ``` Build instruction git clone https://github.com/octeep/wireproxy cd wireproxy make Use with VPN Instructions for using wireproxy with Firefox container tabs and auto-start on MacOS can be found here . Sample config file ``` The [Interface] and [Peer] configurations follow the same semantics and meaning of a wg-quick configuration. To understand what these fields mean, please refer to: https://wiki.archlinux.org/title/WireGuard#Persistent_configuration https://www.wireguard.com/#simple-network-interface [Interface] Address = 10.200.200.2/32 # The subnet should be /32 and /128 for IPv4 and v6 respectively MTU = 1420 (optional) PrivateKey = uCTIK+56CPyCvwJxmU5dBfuyJvPuSXAq1FzHdnIxe1Q= DNS = 10.200.200.1 [Peer] PublicKey = QP+A67Z2UBrMgvNIdHv8gPel5URWNLS4B3ZQ2hQIZlg= PresharedKey = UItQuvLsyh50ucXHfjF0bbR4IIpVBd74lwKc8uIPXXs= (optional) Endpoint = my.ddns.example.com:51820 PersistentKeepalive = 25 (optional) TCPClientTunnel is a tunnel listening on your machine, and it forwards any TCP traffic received to the specified target via wireguard. Flow: --> localhost:25565 --(wireguard)--> play.cubecraft.net:25565 [TCPClientTunnel] BindAddress = 127.0.0.1:25565 Target = play.cubecraft.net:25565 TCPServerTunnel is a tunnel listening on wireguard, and it forwards any TCP traffic received to the specified target via local network. Flow: --(wireguard)--> 172.16.31.2:3422 --> localhost:25545 [TCPServerTunnel] ListenPort = 3422 Target = localhost:25545 STDIOTunnel is a tunnel connecting the standard input and output of the wireproxy process to the specified TCP target via wireguard. This is especially useful to use wireproxy as a ProxyCommand parameter in openssh For example: ssh -o ProxyCommand='wireproxy -c myconfig.conf' ssh.myserver.net Flow: Piped command -->(wireguard)--> ssh.myserver.net:22 [STDIOTunnel] Target = ssh.myserver.net:22 Socks5 creates a socks5 proxy on your LAN, and all traffic would be routed via wireguard. [Socks5] BindAddress = 127.0.0.1:25344 Socks5 authentication parameters, specifying username and password enables proxy authentication. Username = ... Avoid using spaces in the password field Password = ... http creates a http proxy on your LAN, and all traffic would be routed via wireguard. [http] BindAddress = 127.0.0.1:25345 HTTP authentication parameters, specifying username and password enables proxy authentication. Username = ... Avoid using spaces in the password field Password = ... ``` Alternatively, if you already have a wireguard config, you can import it in the wireproxy config file like this: ``` WGConfig = Same semantics as above [TCPClientTunnel] ... [TCPServerTunnel] ... [Socks5] ... ``` Having multiple peers is also supported. AllowedIPs would need to be specified such that wireproxy would know which peer to forward to. ``` [Interface] Address = 10.254.254.40/32 PrivateKey = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX= [Peer] Endpoint = 192.168.0.204:51820 PublicKey = YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY= AllowedIPs = 10.254.254.100/32 PersistentKeepalive = 25 [Peer] PublicKey = ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ= AllowedIPs = 10.254.254.1/32, fdee:1337:c000:d00d::1/128 Endpoint = 172.16.0.185:44044 PersistentKeepalive = 25 [TCPServerTunnel] ListenPort = 5000 Target = service-one.servicenet:5000 [TCPServerTunnel] ListenPort = 5001 Target = service-two.servicenet:5001 [TCPServerTunnel] ListenPort = 5080 Target = service-three.servicenet:80 ``` Wireproxy can also allow peers to connect to it: ``` [Interface] ListenPort = 5400 ... [Peer] PublicKey = YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY= AllowedIPs = 10.254.254.100/32 Note there is no Endpoint defined here. ``` Health endpoint Wireproxy supports exposing a health endpoint for monitoring purposes. The argument --info/-i specifies an address and port (e.g. localhost:9080 ), which exposes a HTTP server that provides health status metric of the server. Currently two endpoints are implemented: /metrics : Exposes information of the wireguard daemon, this provides the same information you would get with wg show . This shows an example of what the response would look like. /readyz : This responds with a json which shows the last time a pong is received from an IP specified with CheckAlive . When CheckAlive is set, a ping is sent out to addresses in CheckAlive per CheckAliveInterval seconds (defaults to 5) via wireguard. If a pong has not been received from one of the addresses within the last CheckAliveInterval seconds (+2 seconds for some leeway to account for latency), then it would respond with a 503, otherwise a 200. For example: ``` [Interface] PrivateKey = censored Address = 10.2.0.2/32 DNS = 10.2.0.1 CheckAlive = 1.1.1.1, 3.3.3.3 CheckAliveInterval = 3 [Peer] PublicKey = censored AllowedIPs = 0.0.0.0/0 Endpoint = 149.34.244.174:51820 [Socks5] BindAddress = 127.0.0.1:25344 `/readyz` would respond with < HTTP/1.1 503 Service Unavailable < Date: Thu, 11 Apr 2024 00:54:59 GMT < Content-Length: 35 < Content-Type: text/plain; charset=utf-8 < {"1.1.1.1":1712796899,"3.3.3.3":0} ``` And for: [Interface] PrivateKey = censored Address = 10.2.0.2/32 DNS = 10.2.0.1 CheckAlive = 1.1.1.1 /readyz would respond with < HTTP/1.1 200 OK < Date: Thu, 11 Apr 2024 00:56:21 GMT < Content-Length: 23 < Content-Type: text/plain; charset=utf-8 < {"1.1.1.1":1712796979} If nothing is set for CheckAlive , an empty JSON object with 200 will be the response. The peer which the ICMP ping packet is routed to depends on the AllowedIPs set for each peers. Stargazers over time

Wireguard client that exposes itself as a socks5 proxy

wireguard,socks5,proxy,network,socks5-proxy,wireguard-tunnel,vpn,golang

subframe7536/maple-font

Maple Font Open source monospace & nerd font with round corner and ligatures. install | what's next | English | 中文 Preparing for V7 , try the new variable font at latest release Features Inspired by Source Code Pro , Fira Code Retina , Sarasa Mono SC Nerd and so on, but: 🎨 New shape - such as @ # $ % & and new shape of italic style 🤙🏻 More ligatures - such as .., ..., /*, /** 📦 Small size - leave only contains latin, standard set of accents, table control characters and few symbols 🦾 Better rendering effect - redesigned it according to Fira Code Retina's spacing and glyph | v4 | v5 | | :----------------------------------------------------: | :-----------------------------------------------------: | | | | | + and = are not centered at some font-size | + and = are always centered | 🗒 More readable - cursive style, better glyph shape, lower the height of capital letters and numbers, reduce or modify kerning and center operators + - * = ^ ~ < > 🛠️ More configable - enable or disable font features as you want, just make your own font ✨ See it in screenshots Install | Platform | Command | | :--------- | :-------------------------------------------------------------------------- | | macOS | brew install --cask font-maple | | Arch Linux | paru -S ttf-maple | | Others | Download in releases | Notice Because I don't have a Mac OS machine, this is the greatest adaption I can do with Mac OS currently, but I can't test whether it works. My ability is not enough to solve other problems on Mac OS. I will record the problem and try to solve it, and PR welcome! Maple Mono NF now maybe can't be recognized as Mono, and I try my best but it doesn't work orz Overview multiply ways to get TODO tag ps: in Jetbrains' product, [todo) can't be properly rendered, so please use todo)) font features are different in font features are different in V7, see in docs compatibility & usage: in FiraCode README Screenshots code theme: vscode-theme-maple generate by: VSCodeSnap Cli (click to expand!)  React  Vue  Java  Go Python  Rust  Build your own font see doc Donate If this was helpful to you, please feel free to buy me a coffee License SIL Open Font License 1.1

[testing V7] Maple Mono: Open source monospace font with round corner, ligatures and Nerd-Font for IDE and command line. 带连字和控制台图标的圆角等宽字体，中英文宽度完美2:1

font,monospace-font,ligatures,programming-ligatures,coding-font,programming-font,monospace,typeface

webstudio-is/webstudio

Webstudio is an Open Source Visual Development Platform for developers, designers, and cross-functional teams. You own the data, components, and infrastructure. You can use the hosted version or roll out your own. Learning Resources Blog Documentation Brand and Product Design Contributing Guide for Devs Github Discussions Wishlist Builder Issues Tracker Roadmap Social Media Twitter Youtube Discord Thanks Thanks to Lost Pixel for providing the visual testing platform that helps us review UI changes and catch visual regressions.

Open Source alternative to Webflow, check out our CMS launch https://webstudio.is/cms

[]

Qovery/Replibyte

Seed Your Development Database With Real Data ⚡️ Replibyte is a blazingly fast tool to seed your databases with your production data while keeping sensitive data safe 🔥 Prerequisites MacOSX / Linux / Windows Nothing more! Replibyte is stateless and does not require anything special. Usage Create a dump shell replibyte -c conf.yaml dump create List all dumps ```shell replibyte -c conf.yaml dump list type name size when compressed encrypted PostgreSQL dump-1647706359405 154MB Yesterday at 03:00 am true true PostgreSQL dump-1647731334517 152MB 2 days ago at 03:00 am true true PostgreSQL dump-1647734369306 149MB 3 days ago at 03:00 am true true ``` Restore the latest dump in a local container shell replibyte -c conf.yaml dump restore local -v latest -i postgres -p 5432 Restore the latest dump in a remote database shell replibyte -c conf.yaml dump restore remote -v latest Features [x] Support data dump and restore for PostgreSQL, MySQL and MongoDB [x] Analyze your data schema 🔎 [x] Replace sensitive data with fake data [x] Works on large database (> 10GB) [x] Database Subsetting: Scale down a production database to a more reasonable size 🔥 [x] Start a local database with the production data in a single command 🔥 [x] On-the-fly data (de)compression (Zlib) [x] On-the-fly data de/encryption (AES-256) [x] Fully stateless (no server, no daemon) and lightweight binary 🍃 [x] Use custom transformers Here are the features we plan to support [ ] Auto-detect and version database schema change [ ] Auto-detect sensitive fields [ ] Auto-clean backed up data Getting Started How Replibyte works Initial setup: Install Configure Step-by-step guides: Create a dump Restore a dump Subset a dump Delete a dump Deploy Replibyte Container Qovery Demo Contributing Check here . Thanks Thanks to all people sharing their ideas to make Replibyte better. We do appreciate it. I would also thank AirByte , a great product and a trustworthy source of inspiration for this project. Replibyte is initiated and maintained by Qovery .

Seed your development database with real data ⚡️

database,cloud,cloudnative,rust,rust-lang,postgresql,s3,backup,aws,postgres

blacklanternsecurity/bbot

BEE·bot A Recursive Internet Scanner for Hackers. BBOT (Bighuge BLS OSINT Tool) is a recursive internet scanner inspired by Spiderfoot , but designed to be faster, more reliable, and friendlier to pentesters, bug bounty hunters, and developers. Special features include: Support for Multiple Targets Web Screenshots Suite of Offensive Web Modules AI-powered Subdomain Mutations Native Output to Neo4j (and more) Python API + Developer Documentation https://github.com/blacklanternsecurity/bbot/assets/20261699/742df3fe-5d1f-4aea-83f6-f990657bf695 A BBOT scan in real-time - visualization with VivaGraphJS Quick Start Guide Below are some short help sections to get you up and running. Installation ( Pip ) Note: BBOT's [PyPi package](https://pypi.org/project/bbot/) requires Linux and Python 3.9+. ```bash # stable version pipx install bbot # bleeding edge (dev branch) pipx install --pip-args '\--pre' bbot bbot --help ``` Installation ( Docker ) [Docker images](https://hub.docker.com/r/blacklanternsecurity/bbot) are provided, along with helper script `bbot-docker.sh` to persist your scan data. ```bash # bleeding edge (dev) docker run -it blacklanternsecurity/bbot --help # stable docker run -it blacklanternsecurity/bbot:stable --help # helper script git clone https://github.com/blacklanternsecurity/bbot && cd bbot ./bbot-docker.sh --help ``` Example Usage ## Example Commands Scan output, logs, etc. are saved to `~/.bbot`. For more detailed examples and explanations, see [Scanning](https://www.blacklanternsecurity.com/bbot/scanning). **Subdomains:** ```bash # Perform a full subdomain enumeration on evilcorp.com bbot -t evilcorp.com -f subdomain-enum ``` **Subdomains (passive only):** ```bash # Perform a passive-only subdomain enumeration on evilcorp.com bbot -t evilcorp.com -f subdomain-enum -rf passive ``` **Subdomains + port scan + web screenshots:** ```bash # Port-scan every subdomain, screenshot every webpage, output to current directory bbot -t evilcorp.com -f subdomain-enum -m nmap gowitness -n my_scan -o . ``` **Subdomains + basic web scan:** ```bash # A basic web scan includes wappalyzer, robots.txt, and other non-intrusive web modules bbot -t evilcorp.com -f subdomain-enum web-basic ``` **Web spider:** ```bash # Crawl www.evilcorp.com up to a max depth of 2, automatically extracting emails, secrets, etc. bbot -t www.evilcorp.com -m httpx robots badsecrets secretsdb -c web_spider_distance=2 web_spider_depth=2 ``` **Everything everywhere all at once:** ```bash # Subdomains, emails, cloud buckets, port scan, basic web, web screenshots, nuclei bbot -t evilcorp.com -f subdomain-enum email-enum cloud-enum web-basic -m nmap gowitness nuclei --allow-deadly ``` ## Targets BBOT accepts an unlimited number of targets via `-t`. You can specify targets either directly on the command line or in files (or both!): ```bash bbot -t evilcorp.com evilcorp.org 1.2.3.0/24 -f subdomain-enum ``` Targets can be any of the following: - `DNS_NAME` (`evilcorp.com`) - `IP_ADDRESS` (`1.2.3.4`) - `IP_RANGE` (`1.2.3.0/24`) - `OPEN_TCP_PORT` (`192.168.0.1:80`) - `URL` (`https://www.evilcorp.com`) For more information, see [Targets](https://www.blacklanternsecurity.com/bbot/scanning/#targets-t). To learn how BBOT handles scope, see [Scope](https://www.blacklanternsecurity.com/bbot/scanning/#scope). ## API Keys Similar to Amass or Subfinder, BBOT supports API keys for various third-party services such as SecurityTrails, etc. The standard way to do this is to enter your API keys in **`~/.config/bbot/secrets.yml`**: ```yaml modules: shodan_dns: api_key: 4f41243847da693a4f356c0486114bc6 c99: api_key: 21a270d5f59c9b05813a72bb41707266 virustotal: api_key: dd5f0eee2e4a99b71a939bded450b246 securitytrails: api_key: d9a05c3fd9a514497713c54b4455d0b0 ``` If you like, you can also specify them on the command line: ```bash bbot -c modules.virustotal.api_key=dd5f0eee2e4a99b71a939bded450b246 ``` For details, see [Configuration](https://www.blacklanternsecurity.com/bbot/scanning/configuration/) ## BBOT as a Python Library BBOT exposes a Python API that allows it to be used for all kinds of fun and nefarious purposes, like a [Discord Bot](https://www.blacklanternsecurity.com/bbot/dev/#bbot-python-library-advanced-usage#discord-bot-example) that responds to the `/scan` command.  **Synchronous** ```python from bbot.scanner import Scanner # any number of targets can be specified scan = Scanner("example.com", "scanme.nmap.org", modules=["nmap", "sslcert"]) for event in scan.start(): print(event.json()) ``` **Asynchronous** ```python from bbot.scanner import Scanner async def main(): scan = Scanner("example.com", "scanme.nmap.org", modules=["nmap", "sslcert"]) async for event in scan.async_start(): print(event.json()) import asyncio asyncio.run(main()) ``` Documentation - Table of Contents - **User Manual** - **Basics** - [Getting Started](https://www.blacklanternsecurity.com/bbot/) - [How it Works](https://www.blacklanternsecurity.com/bbot/how_it_works) - [Comparison to Other Tools](https://www.blacklanternsecurity.com/bbot/comparison) - **Scanning** - [Scanning Overview](https://www.blacklanternsecurity.com/bbot/scanning/) - [Events](https://www.blacklanternsecurity.com/bbot/scanning/events) - [Output](https://www.blacklanternsecurity.com/bbot/scanning/output) - [Tips and Tricks](https://www.blacklanternsecurity.com/bbot/scanning/tips_and_tricks) - [Advanced Usage](https://www.blacklanternsecurity.com/bbot/scanning/advanced) - [Configuration](https://www.blacklanternsecurity.com/bbot/scanning/configuration) - **Modules** - [List of Modules](https://www.blacklanternsecurity.com/bbot/modules/list_of_modules) - [Nuclei](https://www.blacklanternsecurity.com/bbot/modules/nuclei) - **Misc** - [Release History](https://www.blacklanternsecurity.com/bbot/release_history) - [Troubleshooting](https://www.blacklanternsecurity.com/bbot/troubleshooting) - **Developer Manual** - [How to Write a Module](https://www.blacklanternsecurity.com/bbot/contribution) - [Development Overview](https://www.blacklanternsecurity.com/bbot/dev/) - [Scanner](https://www.blacklanternsecurity.com/bbot/dev/scanner) - [Event](https://www.blacklanternsecurity.com/bbot/dev/event) - [Target](https://www.blacklanternsecurity.com/bbot/dev/target) - [BaseModule](https://www.blacklanternsecurity.com/bbot/dev/basemodule) - **Helpers** - [Overview](https://www.blacklanternsecurity.com/bbot/dev/helpers/) - [Command](https://www.blacklanternsecurity.com/bbot/dev/helpers/command) - [DNS](https://www.blacklanternsecurity.com/bbot/dev/helpers/dns) - [Interactsh](https://www.blacklanternsecurity.com/bbot/dev/helpers/interactsh) - [Miscellaneous](https://www.blacklanternsecurity.com/bbot/dev/helpers/misc) - [Web](https://www.blacklanternsecurity.com/bbot/dev/helpers/web) - [Word Cloud](https://www.blacklanternsecurity.com/bbot/dev/helpers/wordcloud) Contribution BBOT is constantly being improved by the community. Every day it grows more powerful! We welcome contributions. Not just code, but ideas too! If you have an idea for a new feature, please let us know in [Discussions](https://github.com/blacklanternsecurity/bbot/discussions). If you want to get your hands dirty, see [Contribution](https://www.blacklanternsecurity.com/bbot/contribution/). There you can find setup instructions and a simple tutorial on how to write a BBOT module. We also have extensive [Developer Documentation](https://www.blacklanternsecurity.com/bbot/dev/). Thanks to these amazing people for contributing to BBOT! :heart: Special thanks to the following people who made BBOT possible: - @TheTechromancer for creating [BBOT](https://github.com/blacklanternsecurity/bbot) - @liquidsec for his extensive work on BBOT's web hacking features, including [badsecrets](https://github.com/blacklanternsecurity/badsecrets) - Steve Micallef (@smicallef) for creating Spiderfoot - @kerrymilan for his Neo4j and Ansible expertise - @aconite33 and @amiremami for their ruthless testing - Aleksei Kornev (@alekseiko) for allowing us ownership of the bbot Pypi repository <3 Comparison to Other Tools BBOT consistently finds 20-50% more subdomains than other tools. The bigger the domain, the bigger the difference. To learn how this is possible, see How It Works . BBOT Modules By Flag For a full list of modules, including the data types consumed and emitted by each one, see List of Modules . | Flag | # Modules | Description | Modules | |------------------|-------------|----------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | safe | 82 | Non-intrusive, safe to run | affiliates, aggregate, ajaxpro, anubisdb, asn, azure_realm, azure_tenant, baddns, baddns_zone, badsecrets, bevigil, binaryedge, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_file_enum, bucket_firebase, bucket_google, builtwith, c99, censys, certspotter, chaos, code_repository, columbus, credshed, crobat, crt, dehashed, digitorus, dnscommonsrv, dnsdumpster, docker_pull, dockerhub, emailformat, filedownload, fingerprintx, fullhunt, git, git_clone, github_codesearch, github_org, github_workflows, gitlab, gowitness, hackertarget, httpx, hunt, hunterio, iis_shortnames, internetdb, ip2location, ipstack, leakix, myssl, newsletters, ntlm, oauth, otx, passivetotal, pgp, postman, rapiddns, riddler, robots, secretsdb, securitytrails, shodan_dns, sitedossier, skymem, social, sslcert, subdomaincenter, sublist3r, threatminer, trufflehog, urlscan, viewdns, virustotal, wappalyzer, wayback, zoomeye | | passive | 62 | Never connects to target systems | affiliates, aggregate, anubisdb, asn, azure_realm, azure_tenant, bevigil, binaryedge, bucket_file_enum, builtwith, c99, censys, certspotter, chaos, code_repository, columbus, credshed, crobat, crt, dehashed, digitorus, dnscommonsrv, dnsdumpster, docker_pull, dockerhub, emailformat, excavate, fullhunt, git_clone, github_codesearch, github_org, github_workflows, hackertarget, hunterio, internetdb, ip2location, ipneighbor, ipstack, leakix, massdns, myssl, otx, passivetotal, pgp, postman, rapiddns, riddler, securitytrails, shodan_dns, sitedossier, skymem, social, speculate, subdomaincenter, sublist3r, threatminer, trufflehog, urlscan, viewdns, virustotal, wayback, zoomeye | | subdomain-enum | 45 | Enumerates subdomains | anubisdb, asn, azure_realm, azure_tenant, baddns_zone, bevigil, binaryedge, builtwith, c99, censys, certspotter, chaos, columbus, crt, digitorus, dnscommonsrv, dnsdumpster, fullhunt, github_codesearch, github_org, hackertarget, httpx, hunterio, internetdb, ipneighbor, leakix, massdns, myssl, oauth, otx, passivetotal, postman, rapiddns, riddler, securitytrails, shodan_dns, sitedossier, sslcert, subdomaincenter, subdomains, threatminer, urlscan, virustotal, wayback, zoomeye | | active | 42 | Makes active connections to target systems | ajaxpro, baddns, baddns_zone, badsecrets, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_firebase, bucket_google, bypass403, dastardly, dotnetnuke, ffuf, ffuf_shortnames, filedownload, fingerprintx, generic_ssrf, git, gitlab, gowitness, host_header, httpx, hunt, iis_shortnames, masscan, newsletters, nmap, ntlm, nuclei, oauth, paramminer_cookies, paramminer_getparams, paramminer_headers, robots, secretsdb, smuggler, sslcert, telerik, url_manipulation, vhost, wafw00f, wappalyzer | | web-thorough | 29 | More advanced web scanning functionality | ajaxpro, azure_realm, badsecrets, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_firebase, bucket_google, bypass403, dastardly, dotnetnuke, ffuf_shortnames, filedownload, generic_ssrf, git, host_header, httpx, hunt, iis_shortnames, nmap, ntlm, oauth, robots, secretsdb, smuggler, sslcert, telerik, url_manipulation, wappalyzer | | aggressive | 20 | Generates a large amount of network traffic | bypass403, dastardly, dotnetnuke, ffuf, ffuf_shortnames, generic_ssrf, host_header, ipneighbor, masscan, massdns, nmap, nuclei, paramminer_cookies, paramminer_getparams, paramminer_headers, smuggler, telerik, url_manipulation, vhost, wafw00f | | web-basic | 17 | Basic, non-intrusive web scan functionality | azure_realm, baddns, badsecrets, bucket_amazon, bucket_azure, bucket_firebase, bucket_google, filedownload, git, httpx, iis_shortnames, ntlm, oauth, robots, secretsdb, sslcert, wappalyzer | | cloud-enum | 12 | Enumerates cloud resources | azure_realm, azure_tenant, baddns, baddns_zone, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_file_enum, bucket_firebase, bucket_google, httpx, oauth | | slow | 10 | May take a long time to complete | bucket_digitalocean, dastardly, docker_pull, fingerprintx, git_clone, paramminer_cookies, paramminer_getparams, paramminer_headers, smuggler, vhost | | affiliates | 8 | Discovers affiliated hostnames/domains | affiliates, azure_realm, azure_tenant, builtwith, oauth, sslcert, viewdns, zoomeye | | email-enum | 7 | Enumerates email addresses | dehashed, emailformat, emails, hunterio, pgp, skymem, sslcert | | deadly | 4 | Highly aggressive | dastardly, ffuf, nuclei, vhost | | portscan | 3 | Discovers open ports | internetdb, masscan, nmap | | web-paramminer | 3 | Discovers HTTP parameters through brute-force | paramminer_cookies, paramminer_getparams, paramminer_headers | | baddns | 2 | Runs all modules from the DNS auditing tool BadDNS | baddns, baddns_zone | | iis-shortnames | 2 | Scans for IIS Shortname vulnerability | ffuf_shortnames, iis_shortnames | | report | 2 | Generates a report at the end of the scan | affiliates, asn | | social-enum | 2 | Enumerates social media | httpx, social | | repo-enum | 1 | Enumerates code repositories | code_repository | | service-enum | 1 | Identifies protocols running on open ports | fingerprintx | | subdomain-hijack | 1 | Detects hijackable subdomains | baddns | | web-screenshots | 1 | Takes screenshots of web pages | gowitness | BBOT Output Modules BBOT can save its data to TXT, CSV, JSON, and tons of other destinations including Neo4j , Splunk , and Discord . For instructions on how to use these, see Output Modules . | Module | Type | Needs API Key | Description | Flags | Consumed Events | Produced Events | |-----------------|--------|-----------------|-----------------------------------------------------------------------------------------|----------------|--------------------------------------------------------------------------------------------------|---------------------------| | asset_inventory | output | No | Merge hosts, open ports, technologies, findings, etc. into a single asset inventory CSV | | DNS_NAME, FINDING, HTTP_RESPONSE, IP_ADDRESS, OPEN_TCP_PORT, TECHNOLOGY, URL, VULNERABILITY, WAF | IP_ADDRESS, OPEN_TCP_PORT | | csv | output | No | Output to CSV | | * | | | discord | output | No | Message a Discord channel when certain events are encountered | | * | | | emails | output | No | Output any email addresses found belonging to the target domain | email-enum | EMAIL_ADDRESS | | | http | output | No | Send every event to a custom URL via a web request | | * | | | human | output | No | Output to text | | * | | | json | output | No | Output to Newline-Delimited JSON (NDJSON) | | * | | | neo4j | output | No | Output to Neo4j | | * | | | python | output | No | Output via Python API | | * | | | slack | output | No | Message a Slack channel when certain events are encountered | | * | | | splunk | output | No | Send every event to a splunk instance through HTTP Event Collector | | * | | | subdomains | output | No | Output only resolved, in-scope subdomains | subdomain-enum | DNS_NAME, DNS_NAME_UNRESOLVED | | | teams | output | No | Message a Teams channel when certain events are encountered | | * | | | web_report | output | No | Create a markdown report with web assets | | FINDING, TECHNOLOGY, URL, VHOST, VULNERABILITY | | | websocket | output | No | Output to websockets | | * | |

A recursive internet scanner for hackers.

hacking,neo4j,osint,osint-framework,python,subdomain-enumeration,automation,recon,command-line-tool,cli

GreptimeTeam/greptimedb

Cloud-scale, Fast and Efficient Time Series Database GreptimeCloud | User guide | API Docs | Roadmap 2024 Introduction GreptimeDB is an open-source time-series database focusing on efficiency, scalability, and analytical capabilities. Designed to work on infrastructure of the cloud era, GreptimeDB benefits users with its elasticity and commodity storage, offering a fast and cost-effective alternative to InfluxDB and a long-term storage for Prometheus . Why GreptimeDB Our core developers have been building time-series data platforms for years. Based on our best-practices, GreptimeDB is born to give you: Easy horizontal scaling Seamless scalability from a standalone binary at edge to a robust, highly available distributed cluster in cloud, with a transparent experience for both developers and administrators. Analyzing time-series data Query your time-series data with SQL and PromQL. Use Python scripts to facilitate complex analytical tasks. Cloud-native distributed database Fully open-source distributed cluster architecture that harnesses the power of cloud-native elastic computing resources. Performance and Cost-effective Flexible indexing capabilities and distributed, parallel-processing query engine, tackling high cardinality issues down. Optimized columnar layout for handling time-series data; compacted, compressed, and stored on various storage backends, particularly cloud object storage with 50x cost efficiency. Compatible with InfluxDB, Prometheus and more protocols Widely adopted database protocols and APIs, including MySQL, PostgreSQL, and Prometheus Remote Storage, etc. Read more . Try GreptimeDB 1. GreptimePlay Try out the features of GreptimeDB right from your browser. 2. GreptimeCloud Start instantly with a free cluster. 3. Docker Image To install GreptimeDB locally, the recommended way is via Docker: shell docker pull greptime/greptimedb Start a GreptimeDB container with: shell docker run --rm --name greptime --net=host greptime/greptimedb standalone start Read more about Installation on docs. Getting Started Quickstart Write Data Query Data Operations Build Check the prerequisite: Rust toolchain (nightly) Protobuf compiler (>= 3.15) Python toolchain (optional): Required only if built with PyO3 backend. More detail for compiling with PyO3 can be found in its documentation . Build GreptimeDB binary: shell make Run a standalone server: shell cargo run -- standalone start Extension Dashboard The dashboard UI for GreptimeDB SDK GreptimeDB Go Ingester GreptimeDB Java Ingester GreptimeDB C++ Ingester GreptimeDB Erlang Ingester GreptimeDB Rust Ingester GreptimeDB JavaScript Ingester Grafana Dashboard Our official Grafana dashboard is available at grafana directory. Project Status The current version has not yet reached General Availability version standards. In line with our Greptime 2024 Roadmap, we plan to achieve a production-level version with the update to v1.0 in August. [Join Force] Community Our core team is thrilled to see you participate in any ways you like. When you are stuck, try to ask for help by filling an issue with a detailed description of what you were trying to do and what went wrong. If you have any questions or if you would like to get involved in our community, please check out: GreptimeDB Community on Slack GreptimeDB GitHub Discussions forum Greptime official website In addition, you may: View our official Blog Connect us with Linkedin Follow us on Twitter License GreptimeDB uses the Apache License 2.0 to strike a balance between open contributions and allowing you to use the software however you want. Contributing Please refer to contribution guidelines and internal concepts docs for more information. Acknowledgement GreptimeDB uses Apache Arrow™ as the memory model and Apache Parquet™ as the persistent file format. GreptimeDB's query engine is powered by Apache Arrow DataFusion™ . Apache OpenDAL™ gives GreptimeDB a very general and elegant data access abstraction layer. GreptimeDB's meta service is based on etcd . GreptimeDB uses RustPython for experimental embedded python scripting.

An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.

cloud-native,database,distributed,rust,timeseries,sql,time-series,analytics,metrics,tsdb

tauri-apps/awesome-tauri

Awesome Tauri A curated collection of the best stuff from the Tauri ecosystem and community. [](https://awesome.re) Table of Contents Getting Started Guides Tutorials Templates Development Plugins Integrations Articles Applications Audio & Video ChatGPT clients Data Developer tools Email & Feeds File management Finance Gaming Information Learning Networking Office & Writing Productivity Search Security Social media Utilities Getting Started Guides Introduction - Official introduction to Tauri. Getting Started - Official getting started with Tauri docs. create-tauri-app - Rapidly scaffold your Tauri app. Tutorials Create Tauri App with React - Chris Biscardi shows how easy it is to wire up a Rust crate with a JS module and communicate between them. Publish to Apple's App Store - Details all the steps needed to publish your Mac app to the app store. Includes a sample bash script. Tauri & ReactJS - Creating Modern Desktop Apps - Creating a modern desktop application with Tauri. Templates angular-tauri - Angular with Typescript, SASS, and Hot Reload. tauri-angular-template - Angular template tauri-astro-template - Astro template tauri-bishop-template - Minimized vanilla template designed for highschool students tauri-clojurescript-template - Minimal ClojureScript template with Shadow CLJS and React. tauri-deno-starter - React template using esbuild with Deno. tauri-leptos-template - Leptos template tauri-nextjs-template - Next.js (SSG) template, with TailwindCSS, opinionated linting, and GitHub Actions preconfigured. tauri-nuxt-template - Nuxt3 template. tauri-preact-rsbuild-template - Preact template that uses rsbuild, rather than vite. tauri-react-mantine-vite-template - React Mantine template featuring custom titlebar for Windows, auto publish action, auto update, and more. tauri-react-parcel-template - React template with Parcel as build tool, TypeScript and hot module replacement. tauri-rescript-template - Tauri, ReScript, and React template. tauri-solid-ts-tailwind-vite-template - SolidJS Template preconfigured to use Vite, TypeScript, Tailwind CSS, ESLint and Prettier. tauri-svelte-template - Svelte template with cross-platform GitHub action builds, Vite, TypeScript, Svelte Preprocess, hot module replacement, ESLint and Prettier. tauri-sveltekit-template - SvelteKit Admin template with cross-platform GitHub action builds, Vite, TypeScript, Svelte Preprocess, hot module replacement, ESLint and Prettier. tauri-sycamore-template - Tauri and Sycamore template. tauri-vue-template - Vue template with TypeScript, Vite + HMR, Vitest, Tailwind CSS, ESLint, and GitHub Actions. tauri-vue-template-2 - Another vue template with Javascript, Vite, Pinia, Vue Router and Github Actions. tauri-yew-example - Simple stopwatch with Yew using commands and Tauri events. Development Plugins tauri-plugin-authenticator - Interface with hardware security keys. tauri-plugin-log - Configurable logging. tauri-plugin-sql - Interface with SQL databases. tauri-plugin-store - Persistent key value storage. tauri-plugin-stronghold - Encrypted, secure, p2p database. tauri-plugin-window-state - Persist window sizes and positions. window-vibrancy - Make your windows vibrant. window-shadows - Add native shadows to your windows. tauri-plugin-positioner - Move windows to common locations. tauri-plugin-graphql - Type-safe IPC for Tauri using GraphQL. sentry-tauri - Capture JavaScript errors, Rust panics and native crash minidumps to Sentry. tauri-plugin-aptabase - Privacy-first and minimalist analytics for desktop and mobile apps. tauri-plugin-clipboard - Clipboard plugin for reading/writing clipboard text/image, and monitoring clipboard update. taurpc - Typesafe IPC wrapper for Tauri commands and events. tauri-plugin-context-menu - Native context menu. tauri-plugin-network - Tools for reading network information and scanning network. tauri-plugin-serialport - Cross-compatible serialport communication tool. tauri-plugin-system-info - Detailed system information. tauri-plugin-theme - Dynamically change Tauri App theme. tauri-awesome-rpc - Custom invoke system that leverages WebSocket. tauri-nspanel - Convert a window to panel. tauri-plugin-nosleep - Block the power save functionality in the OS. Integrations Astrodon - Make Tauri desktop apps with Deno. Tauri Specta - Completely typesafe Tauri commands. axios-tauri-adapter - axios adapter for the @tauri-apps/api/http module. axios-tauri-api-adapter - Makes it easy to use Axios in Tauri, axios adapter for the @tauri-apps/api/http module. ngx-tauri - Small lib to wrap around functions from tauri modules, to integrate easier with Angular. svelte-tauri-filedrop - File drop handling component for Svelte. tauri-macos-menubar-app-example - Example macOS Menubar app project. tauri-macos-spotlight-example - Example macOS Spotlight app project. tauri-update-cloudflare - One-click deploy a Tauri Update Server to Cloudflare. tauri-update-server - Automatically interface the Tauri updater with git repository releases. vite-plugin-tauri - Integrate Tauri in a Vite project to build cross-platform apps. Articles Getting Started Using Tauri Mobile - Ed Rutherford outlines how to create a mobile app with Tauri. How to use local SQLite database with Tauri and Rust - Guide to setup and use SQLite database with Tauri and Rust. Managing State in Desktop Applications with Rust and Tauri - How to share and manage any kind of state globally in Tauri apps. Setting up Actix Web in a Tauri App - How to setup a HTTP server with Tauri and Actix Web. Tauri's async process - Rob Donnelly dives deep into Async with Tauri. Applications Audio & Video Cider - 3rd Party Client for Apple Music, Complete with Audio Lab. Curses - Speech-to-Text and Text-to-Speech captions for OBS, VRChat, Twitch chat and more. Douyin Downloader - Cross-platform douyin video downloader. Feiyu Player - Cross-platform online video player where beauty meets functionality. Hypetrigger - Detect highlight clips in video with FFMPEG + Tensorflow on the GPU. Jellyfin Vue - GUI client for a Jellyfin server based on Vue.js and Tauri. mediarepo - Tag-based media management application. Mr Tagger - Music file tagging app. Lofi Engine - Generate Lo-Fi music on the go and locally. Watson.ai - Easily record and extract the most important information from your meetings. XGetter - Cross-platform GUI to download videos and audio from Youtube, Facebook, X(Twitter), Instagram, Tiktok and more. yt-dlp GUI - Cross-platform GUI client for the yt-dlp command-line audio/video downloader. ChatGPT clients chatbox - Cross-platform desktop application for ChatGPT API (OpenAI API), also a prompt debugging and management tool. ChatGPT - Cross-platform ChatGPT desktop application. ChatGPT App - Cross-platform ChatGPT App and more. ChatGPT-Desktop - Cross-platform productivity ChatGPT assistant launcher. Orion - Cross-platform app that lets you create multiple AI assistants with specific goals powered with ChatGPT. QuickGPT - Lightweight AI assistant for Windows. Yack - Spotlight like app for interfacing with GPT APIs Data BS Redis Desktop Client - The Best Surprise Redis Desktop Client. Dataflare - Simple and elegant database manager. Duckling - Lightweight and fast viewer for csv/parquet files and databases such as DuckDB, SQLite, PostgreSQL, MySQL, Clickhouse, etc. Mason - Seamlessly query, visualize and share data with your team. Noir - Keyboard-driven database management client. pgMagic🪄 - GUI client to talk to Postgres in SQL or with natural language. Developer tools AHQ Store - Publish, Update and Install apps to the Windows-specific AHQ Store. AppCenter Companion - Regroup, build and track your VS App Center apps. AppHub - Streamlines .appImage package installation, management, and uninstallation through an intuitive Linux desktop interface. Aptakube - Multi-cluster Kubernetes UI. claws - Visual interface for the AWS CLI. CrabNebula DevTools - Visual tool for understanding your app. Optimize the development process with easy debugging and profiling. CrabNebula DevTools Premium - Optimize the development process with easy debugging and profiling. Debug the Rust portion of your app with the same comfort as JavaScript! DevBox - Many useful tools for developers, like generators, viewers, converters, etc. DevClean - Clean up development environment with ease. DevTools-X - Collection of 30+ cross platform development utilities. Dropcode - Simple and lightweight code snippet manager. Echoo - Offline/Online utilities for developers on MacOS & Windows. GitButler - GitButler is a new Source Code Management system. GitLight - GitHub & GitLab notifications on your desktop. JET Pilot - Kubernetes desktop client that focuses on less clutter, speed and good looks. Hoppscotch - Trusted by millions of developers to build, test and share APIs. Keadex Mina - Open Source, serverless IDE to easily code and organize at a scale C4 model diagrams. KFtray - A tray application that manages port forwarding in Kubernetes. Soda - Generate source code from an IDL. Pake - Turn any webpage into a desktop app with Rust with ease. Rivet - Visual programming environment for creating AI features and agents. TableX - Table viewer for modern developers Tauri Mobile Test - Create and build cross-platform mobile applications. Testfully - Offline API Client & Testing tool. verbcode - Simplify your localization journey. Yaak - Interact with REST and GraphQL APIs. Email & Feeds Alduin - Alduin is a free and open source RSS, Atom and JSON feed reader that allows you to keep track of your favorite websites. Aleph - Aleph is an RSS reader & podcast client. BULKUS - Email validation software. Lettura - Open-source feed reader for macOS. mdsilo Desktop - Feed reader and knowledge base. File management enassi - Encryption assistant that encrypts and stores your notes and files. EzUp - File and Image uploader. Designed for blog writing and note taking. Orange - Cross-platform file search engine that can quickly locate files or folders based on keywords. Payload - Drag & drop file transfers over local networks. Spacedrive - A file explorer from the future. SquirrelDisk - Beautiful cross-platform disk usage analysis tool. Time Machine Inspector - Find out what's taking up your Time Machine backup space. Xplorer - Customizable, modern and cross-platform File Explorer. Finance Compotes - Local bank account operations storage to vizualize them as graphs and customize them with rules and tags for better filtering. CryptoBal - Desktop application for monitoring your crypto assets. Ghorbu Wallet - Cross-platform desktop HD wallet for Bitcoin. nym-wallet - The Nym desktop wallet enables you to use the Nym network and take advantage of its key capabilities. UsTaxes - Free, private, open-source US tax filings. Gaming 9Launcher - Modern Cross-platform launcher for Touhou Project Games. BestCraft - Crafting simulator with solver algorithms for Final Fantasy XIV(FF14). BetterFleet - Help players of Sea of Thieves create an alliance server. clear - Clean and minimalist video game library manager and launcher. CubeShuffle - Card game shuffling utility. En Croissant - Chess database and game analysis app. FishLauncher - Cross-platform launcher for Fish Fight . OpenGOAL - Cross-platform installer, mod-manager and launcher for OpenGOAL ; the reverse engineered PC ports of the Jak and Daxter series. OyasumiVR - Software that helps you sleep in virtual reality, for use with SteamVR, VRChat, and more. Resolute - User-friendly, cross-platform mod manager for the game Resonite. Steam Art Manager - Tool for customizing the art of your Steam games. Teyvat Guide - Game Tool for Genshin Impact player. Information Seismic - Taskbar app for USGS earthquake tracking. Stockman - Display stock info on mac menubar. Watchcoin - Display cypto price on OS menubar without a window. Learning Manjaro Starter - Documentation and support app for new Manjaro users. Piano Trainer - Practice piano chords, scales, and more using your MIDI keyboard. Solars - Visualize the planets of our solar system. Syre - Scientific data assistant. Rosary - Study Christianity. Networking Clash Verge Rev - Continuation of Clash Verge, a rule-based proxy. CyberAPI - API tool client for developer. Jexpe - Cross-platform, open source SSH and SFTP client that makes connecting to your remote servers easy. Mail-Dev - Cross-platform, local SMTP server for email testing/debugging. Nhex - Next-generation IRC client inspired by HexChat. RustDesk - Self-hosted server for RustDesk, an open source remote desktop. RustDuck - Cross platform dynamic DNS updater for duckdns.org. T-Shell - An open-source SSH, SFTP intelligent command line terminal application. TunnlTo - Windows WireGuard VPN client built for split tunneling. UpVPN - WireGuard VPN client for Linux, macOS, and Windows. Watcher - API manager built for a easier use to manage and collaborate. Wirefish - Cross-platform packet sniffer and analyzer. Office & Writing Bidirectional - Write Arabic text in apps that don't support bidirectional text. Blank - Minimalistic, opinionated markdown editor made for writing. Ensō - Write now, edit later. Ensō is a writing tool that helps you enter a state of flow. Handwriting keyboard - Handwriting keyboard for Linux X11 desktop environment. JournalV - Journaling app for your days and dreams. MarkFlowy - Modern markdown editor application with built-in ChatGPT extension. MDX Editor - Versatile WeChat typesetting editor and cross-platform Markdown note-taking software. Noor - Chat app for high-performance teams. Designed for uninterrupted deep work and rapid collaboration. Notedown - Minimal, local-first cross-platform note taking app. Parchment - Simple local-only cross-platform text editor with basic markdown support. Semanmeter - OCR and document conversion software. Ubiquity - Cross-platform markdown editor; built with Yew, Tailwind, and DaisyUI. Productivity Banban - Kanban board with tags, categories and markdown support. BuildLog - Menu bar for keeping track of Vercel Deployments. Dalgona - GIF meme finder app for Windows and macOS. GitBar - System tray app for GitHub reviews. Gitification - Menu bar app for managing Github notifications. Google Task Desktop Client - Google Task Desktop Client Jarvis - Cross-platform, extensible app launcher. Alternative to Alfred and Raycast. Kanri - Cross-platform, offline-first Kanban board app with a focus on simplicity and user experience. Kianalol - Spotlight-like efficiency tool for swift website access. Link Saas - Efficiency tools for software development teams. MacroGraph - Visual programming for content creators. Obliqoro - Oblique Strategies meets Pomodoro. Pomodoro - Time management tool based on Pomodoro technique. Remind Me Again - Toggleable reminders app for Mac, Linux and Windows. TimeChunks - Time tracking for freelancers without timers and HH:MM:SS inputs. WindowPet - Overlay app that lets you have adorable companions such as pets and anime characters on your screen. Zawee - Experience the synergy of Kanban boards, note-taking, file sharing, and more, seamlessly integrated into one powerful application. Search Harana - Search your desktop and 300+ cloud apps, instantly. Spyglass - Personal search engine that indexes your files/folders, cloud accounts, and whatever interests you on the internet. Security Authme - Two-factor (2FA) authentication app for desktop. Calciumdibromid - Generate "experiment wise safety sheets" in compliance to European law. Gluhny A graphical interface to validate IMEI numbers. OneKeePass - Secure, modern, cross-platform and KeePass compatible password manager. Padloc - Modern, open source password manager for individuals and teams. Raspirus - User- and resources-friendly signatures-based malware scanner. Secops - Ubuntu Operating System security made easy. Tauthy - Cross-platform TOTP authentication client. Truthy - Modern cross-platform 2FA manager with tons of features and a beautiful UI. Social media Dorion - Light weight third-party Discord client with support for plugins and themes. Identia - Decentralized social media on IPFS. Kadium - App for staying on top of YouTube channel uploads. Scraper Instagram GUI Desktop - Alternative Instagram front-end for desktop. Utilities AgeTimer - Desktop utility that counts your age in real-time. Auto Wallpaper - Automatically generates 4K wallpapers based on user's location, weather, and time of day or any custom prompts. bewCloud Desktop Sync - Desktop sync app for bewCloud, a simpler alternative to Nextcloud and ownCloud. TypeView - KeyStroke Visualizer - Visualizes keys pressed on the screen and simulates the sound of mechanical keyboard. Browsernaut - Browser picker for macOS. Clipboard Record - Record Clipboard Content. Clippy - Modern & Fast Clipboard Manager. Fancy Screen Recorder - Record entire screen or a selected area, trim and save as a GIF or video. Flying Carpet - File transfer between Android, iOS, Linux, macOS, and Windows over auto-configured hotspot. Imagefly - Powerful offline image processing toolkit for Windows, Linux and macOS Jane Reader - Modern and distraction-free epub reader. KittyCAD - Modern 3D mechanical/hardware design. Build 3D models with both code and WYSIWYG editors. KoS - Key on Screen - Show in your screen the keys you are pressing. Lanaya - Easy to use, cross-platform clipboard management. Linka! - AI powered, easy to use, cross-platform bookmark management tool. MBTiles Viewer - MBTiles Viewer and Inspector. Metronome - Visual metronome for Windows, Linux and macOS. Mobslide - Turn your smartphone into presentation remote controller. Overlayed - Voice chat overlay for Discord. Pavo - Cross-platform desktop wallpaper application. Peekaboo A graphical interface to display images. Pointless - Endless drawing canvas. Pot - Cross-platform Translation Software. Rounded Corners - Rounded Corners app for Windows. RunMath - Keyboard-first calculator for Windows. SensiMouse - Easily change macOS system-wide mouse sensitivity and acceleration settings. Stable Diffusion Buddy - Desktop UI companion for the self-hosted Mac version of Stable Diffusion. Stacks - Modern and capable clipboard manager for macOS. Seeking Linux and Windows contributions. Tauview - Minimalist image viewer for macOS and Linux based on Leaflet.js. ToeRings - Conky Seamod inspired system monitor app. Toolcat - All-in-one toolkit for developers and creators. TrguiNG - Remote GUI for Transmission torrent daemon. Verve - Launcher for accessing and opening applications, files and documents. Vibe - Transcribe audio or video in every language on every platform. Wallpaper changer - Simple wallpaper changer app. Zap - macOS spotlight-like dock that makes navigating apps convenient.

🚀 Awesome Tauri Apps, Plugins and Resources

awesome,awesome-list,tauri

pk910/PoWFaucet

PoWFaucet Modularized faucet for EVM chains with different protection methods (Captcha, Mining, IP, Mainnet Balance, Gitcoin Passport and more) Why Faucets for ETH Testnets are spammed by bots. This faucet tries to reduce the efficiency of these automated requests by various protection methods. This faucet is mostly known for its proof-of-work based protection, which is currently the best and most reliable way to distribute funds on a network that got low on fund reserves. For clarification: This faucet does NOT generate new coins with the "mining" process. It's just one of the protection methods the faucet uses to prevent anyone from requesting big amount of funds and draining the faucet wallet. If you want to run your own instance you need to transfer the funds you want to distribute to the faucet wallet yourself! For a more detailed description, take a look into the Project Wiki Instances Testnet Link Sepolia Testnet https://sepolia-faucet.pk910.de Holešovice Testnet https://holesky-faucet.pk910.de Ephemery Testnet https://ephemery-faucet.pk910.de Run Yourself Read the Faucet Operator Wiki to see the installation and configuration instructions. You can also find some demo instances with different module combinations here: Demo Instances Bugs & Features Please feel free to report bugs and add new features via PRs if you like. Thanks To This faucet contains parts of code from the following projects: pow-captcha - faucet-wasm build script FaucETH - faucet page design License

Modularized faucet for EVM chains with different protection methods (Captcha, Mining, IP, Mainnet Balance, Gitcoin Passport and more)

ethereum,faucet,testnet,testnet-faucet,web3,sybil-resistance

Evavic44/portfolio-ideas

Portfolio Ideas A curation of awesome portfolio ideas for developers and designers to draw inspirations when they decide to create their own. Want to add yours or someone else's, feel free to raise a PR to add them. Inspired by clone Wars , 30 web developer ideas to inspire you and my personal struggles :). Read about how this project started: Portfolio Ideas - An open-source repository for inspiration Contribute Want to add a portfolio to this list? read the guidelines on how to do that. | Author | Screenshot | Live URL | Repo | Tech Stack | | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- | | Victor Eke | | victoreke.com | GitHub | Nextjs, Sanity, Tailwind CSS, TypeScript, Umami, Vercel | | Kent C. Dodds | | kentcdodds.com | GitHub | React, TypeScript, Remix, Prisma, Redis, Postgres, CSS | | Brittany Chiang | | v4.brittanychiang.com | GitHub | React, Gatsby, Styled-components | | Braydon Coyer | | braydoncoyer.dev | GitHub | React, TypeScript, NextJS, Tailwindcss, Notion API, Supabase | | Tania Rascia | | taniarascia.com | GitHub | React, Gatsby, CSS, Netlify, NodeJS | | Jemima Abu | | jemimaabu.com | GitHub | HTML, CSS, JavaScript. | | Rekhchand Sahu | | rekhchandsahu.com | None | React, Gatsby, Preact, GSAP | | Olaolu Olawuyi | | olaolu.dev | GitHub | VueJS, JavaScript, HTML, styled-components, Sass | | Thang Huu Vu | | thvu.dev | GitHub | React, NextJS, NodeJS, TypeScript, GraphQL, Tailwindcss | | George Francis | | georgefrancis.dev | None | GSAP, Netlify, HTML, CSS, JavaScript | | Aditya Vikram | | people.umass.edu/avsingh | GitHub | HTML, CSS, JavaScript | | Adeola Adeoti | | adeolaadeoti.xyz | GitHub | TypeScript, GSAP, NodeJS, NextJS, SCSS | | Dejan Markovic | | dejan.works | None | HTML, CSS, JavaScript, Jquery | | Jack Jeznach | | jacekjeznach.com/ | None | jQuery, PHP, GSAP, MySQL | | Max Böck | | mxb.dev | GitHub | Eleventy, SCSS, Nunjucks | | David Darnes | | darn.es | None | Netlify, Jekyll, ETC | | Schulz Daniel | | iamschulz.com | GitHub | Hugo, Shell, JavaScript | | Rafael Conde | | rafa.design | GitHub | Nunjucks, JavaScript, CSS | | Bruno Simon | | bruno-simon.com | Github | GSAP, ThreeJS, JavaScript, ETC | | Oluwadare Oluwaseyi | | seyi.dev | GitHub | HTML, SCSS, JavaScript, GSAP | | Jason Lengstorf | | jason.energy | GitHub | JavaScript, TypeScript, Nunjucks, CSS | | Deidre Driscoll | | deidredriscoll.com | None | HTML, JavaScript, CSS, GSAP | | Chris Porter | | madebyporter.com | GitHub | HTML, Slim, Ruby, SCSS, Shell, JavaScript, CSS | | Louis Hoebregts | | mamboleoo.be | None | PHP, Parcel | | Adrien Gervaix | | adriengervaix.com | None | HTML, CSS, JavaScript | | Aaron Shapiro | | aaron.mn | GitHub | React, Gatsby, Styled Components, Netlify | | Peter Tait | | petertait.com | GitHub | React, Webpack, Radium, Netlify | | Rick Waalders | | rickwaalders.com | None | NextJS, React, NodeJS, GSAP, Webpack | | Community Pro | | cpro-portfolio-html | Github | HTML, CSS, JavaScript | | Ahmed Zougari | | ahmedzougari.com | GitHub | HTML, SASS, Bootstrap, JavaScript, Vite | | Raj Savaliya | | rajsavaliya.com | GitHub | NextJS, React, TypeScript, Tailwind CSS | | Israel Mitolu | | israelmitolu.netlify.app | GitHub | HTML, SASS, Javascript, GSAP | | Saikat Roy | | saikatroy.netlify.app | GitHub | HTML, CSS, Bootstrap, JavaScript, jQuery | | Anand Baraik | | anandbaraik.github.io | GitHub | HTML, CSS, React.js | | Nirban Chakraborty | | nirban-chakraborty.netlify.app | GitHub | ReactJs, JavaScript, SASS, HTML | | Benaiah Alumona | | benrobo.vercel.app | GitHub | Reactjs, TailwindCss, Next.js, Emailjs, BaayMax | | Md Nayeem Hossain | | nayeemdev.github.io/ | GitHub | HTML, CSS, Bootstrap, Javascript, jQuery | | Sachin Chaurasiya | | sachinchaurasiya.dev | None | HTML, CSS, JavaScript, ReactJs, Material UI | | Anish De | | anishde.dev | GitHub | Next.js, TypeScript, Tailwind CSS, Content Layer | | Shourya Shikhar Ghosh | | shourya.vercel.app | GitHub | Flutter | | Omar Sherif Ali ~OSA | | osa-portfolio.vercel.app | GitHub | ReactJs, JavaScript, CSS, HTML | | Robby Leonardi | | rleonardi.com/ | None | NextJS, React, NodeJS, GSAP, Webpack | | Serdar Gökhan | | serdargokhan.dev | GitHub | NextJS, TypeScript, TailwindCSS | | Jeferson Brito | | jefersonsilva.me/ | GitHub | Vue 3.0, Vite | | Trịnh Minh Nhật | | trinhminhnhat.com | None | React, Tailwindcss | | Yunus Ertürk | | yunuserturk.com | None | HTML, CSS, React, NextJS, | | Phong Nguyen | | napthedev.com | Github | Nextjs, Tailwind, Framer-motion, Locomotive-scroll | | Ismael López | | ismaellopez.dev | None | Svelte, JavaScript, CSS, HTML, Netlify CMS | | Micah Lindley | | micahlindley.com | GitHub | Vue 3, Vite | | Tri Dang | | tri-dang.github.io | GitHub | Ruby, Jekyll, Markdown | | Reza Ghasemzadeh | | rezaghz.com | None | HTML, CSS, Bootstrap,Javascript, Blade | | Ariful Alam | | arifszn.github.io/gitprofile | GitHub | React, Vite, Tailwind CSS | | Dale Larroder | | dalelarroder.com | GitHub | NextJS, Preact, TypeScript, Tailwind, MDX | | Williams Samuel | | williamssam.netlify.app | GitHub | HTML, CSS, Javascript | | Guillaume Gouessan | | guillaumegouessan.com | GitHub | GSAP, ThreeJS, JavaScript | | Patrick Heng | | patrickheng.com | None | Nuxt.js, GSAP, ThreeJS | | Andrew Baisden | | andrewbaisden.com | GitHub | HTML, CSS, TypeScript, ReactJS | | Aziz Rahman | | azizstark.com | Github | React, Gatsby, Styled-Components, SCSS, AnimeJS | | Leonel Ngoya | | lndev.me | GitHub | HTML, CSS, JavaScript | | Jimmy Soussan | | cozy-codeur.fr | Github | React, Gatsby, Chakra UI, Framer Motion | | Segun Ajibola | | segunajibola.com | Github | HTML, CSS, TailwindCSS, React, SwiperJS | | Hisami Kurita | | hsmkrt1996.com | Github | Vue.js, Nuxt.js, SCSS, ThreeJS, GSAP, ASSCROLL, imagesLoaded | | Dennis Snellenberg | | dennissnellenberg.com | None | GSAP. JQuery, PHP, VueJS | | Isaac Fayemi | | fayemi.design | None | Vanilla JS, pug, Prismic CMS, SCSS, ThreeJS, GSAP | | Bhavin Virani | | bhavinn.xyz | Github | HTML, CSS, JS, React.js, Github API | | Patrick Scott | | pscott.io | None | React.js, Heroku and Github Pages | | Lazar Nikolov | | nikolovlazar.com | Github | Next.js, Chakra UI, MDX, Prisma, PlanetScale | | Reuben Rapose | | reubence.com | GitHub | HTML, TailwindCSS, React, Javascript, Next.JS, MDX, Mailchimp Newsletter, Gisqus Comments, etc. | | M. Shahanwaz | | mshahanwaz.me | GitHub | HTML, CSS, JavaScript, React, Next.js, Nodemailer | | Lee Robinson | | leerob.io | GitHub | Next.js, PlanetScale, Prisma, Vercel, Sanity, Tailwind CSS | | Parth Desai | | musing.vercel.app | GitHub | TailwindCSS, React, Javascript, Next.JS, MDX, Mailchimp Newsletter, Gisqus Comments | | Victor Ikechukwu | | iamvictor.tech | None | Next.js, Tailwind CSS, React Rough Notation, Vivus, Netlify | | Usman Sabuwala | | usman-s.me | GitHub | NextJS, Chakra UI, Framer Motion | | Zacky Aduoli | | lookupzach.netlify.app | None | ReactJS, Material UI, SCSS, Styled Components | | Payton Pierce | | paytonpierce.dev | GitHub | ReactJS, Material UI | | Jacob Valdez | | jacobfv.github.io | GitHub | HTML, Jekyll | | Jasmeet Singh | | jasmeetsinghbhatia.github.io/resume | GitHub | HTML, CSS, JavaScript | | Walter Teng | | walterteng.com | GitHub | React, Typescript, Gatsby, Netlify | | Jahidul Islam | | XahidEx.com | None | Typescript, NextJs, TailwindCSS, Prisma, Contentlayer, React | | Greg Sithole | | gregsithole.com | GitHub | HTML, CSS, React.js | | Rohit Saini | | rohit-saini | None | ReactJs, CSS, GSAP, Framer Motion | | Oscar Barajas | | gndx.io | GitHub | HTML, TailwindCSS | | Phillip Cabrera | | Portfolio | GitHub | HTML, CSS, JavaScript, Webpack, ReactJs | | Nahuel Carrizo | | Portfolio | GitHub | HTML, CSS, JavaScript, React, Webpack, Github Pages | | Alfaizkhan Pathan | | Portfolio | GitHub | Flutter, Dart, Github Pages | | Jatin Kamboj | | jatinkamboj.me | None | HTML, CSS, JavaScript, GreenSock | | Leonid Meleshin | | leon0399.ru | GitHub | ReactJS, Tailwind, CSS, Vercel | | Brayden | | braydentw.io | GitHub | React, NextJS, TailwindCSS | | Ben | | nuro.dev | GitHub | React, NextJS, TailwindCSS | | Matthias Kretschmann | | matthiaskretschmann.com | GitHub | React, Gatsby | | Hamish Williams | | hamishw.com | GitHub | React, ThreeJS, NextJS | | Çağlar Turalı | | turali.js.org | GitHub | React, TypeScript | | Pyae Sone | | pyaesonepsn.github.io | GitHub | HTML, CSS, JavaScript | | Efren Martinez | | efrencodes.com | GitHub | NextJS, TypeScript, TailwindCSS | | Eliaz LR | | portfolio2.eliaz-lr.dev | GitHub | Vue 3, Vite, TailwindCSS | | Hikmet C. Kufteoglu | | hicaku.com | GitHub | Vue 3, Pinia, TypeScript | | Ara Oladipo | | araoladipo.tech | GitHub | HTML, CSS, Javascript, Vue.js, Spline3D | | Anthony Fu | | antfu.me | GitHub | VueJS, Markdown, TypeScript, CSS, HTML | | Timothy Lin | | timlrx.com | GitHub | NextJS, MDX, TailwindCSS, JavaScript, SASS | | Ngô Phú Thịnh | | thinhcorner.com | GitHub | NextJS, TailwindCSS, TypeScript, CSS | | Josiah B. Etuk | | jobenetuk.dev | None | Vanilla JS, Node JS, Prismic CMS, SASS, GSAP | | Stef Ivanov | | stefivanov.com | None | WordPress, Yoast SEO, MailChimp, PWA, Google Analytics, Sumo. | | Erika Senft Miller | | erikasenftmiller.com | None | Contentful, GSAP, LazySizes, PWA, Google Analytics. | | Ruben Kuipers | | rubenkuipers.design | None | Vue.js, Nuxt.js, Tailwind CSS, scrollreveal, Google Tag Manager, Google Analytics | | Maggie Appleton | | maggieappleton.com | Github | React, Next.js, MDX, Algolia Search, Reach UI, Tippy.js, Framer Motion, styled-components, Lodash | | Moe Dayraki | | moe.dayrakiarts.com | Github | Vue 3, Vite, Cypress, Tailwindcss, Typescript, Pinia, Primevue, magic.css, VueUse | | Truong Phan | | techika.com | Github | Vue 3, Vite, VuePress, Tailwindcss, Tailwind, Lighthouse | | Wasim Baig | | wasimbaig.com | GitHub | Next JS, Tailwind CSS, Framer-Motion | | Mike Bifulco | | mikebifulco.com | GitHub | NextJS, React, SCSS, MDX, Vercel | | Shodipo Ayomide | | shodipoayomide.com | GitHub | Gatsby, React, SCSS, Bootstrap, Jquery | | Damian Watracz | | watracz.com | None | HTML, CSS, JavaScript, Swiper | | Franklin Ohaegbulam | | frankiefab.com | GitHub | HTML, CSS, JavaScript | | Samuel Akinosho | | samuelakinosho.com | None | Webflow, Jquery | | Rutik Wankhade | | rutikwankhade.dev | None | NextJs, React, NodeJS, TailwindCSS | | Adenekan Wonderful | | codewonders.dev | None | React, NextJS, Styled-components | | Olamide Sholanke | | olamide.dev | None | Vue, NuxtJS | | Daniel Ezekiel | | danielezekiel.me | GitHub | HTML, CSS, JavaScript | | Julia Johnson | | juliacodes.com | GitHub | React, Styled-components | | Rida F'kih | | rida.dev | GitHub | React, NextJS | | Anand Baraik | | anandbaraik-folio.netlify.app | GitHub | HTML, CSS. | | Abhishek Jha | | abhishekjha.me | None | HTML, CSS, JavaScript, Ruby on Rails, GSAP | | Olamide Adeyi | | olamideadeyi.com | None | Vue, NuxtJS, GSAP | | Greg Ives | | gregives.co.uk | GitHub | Vue, NuxtJS, SASS, Netlify | | Collins Enebeli | | kadet.dev | GitHub | React, Gatsby | | Cole_Solomon | | colesolomon.me | GitHub | HTML, CSS, SASS, JavaScript, GSAP, W3js, PHP | | Adewale Adeyemi | | adex.onrender.com | GitHub | Gridsome, GraphQL, Tailwind. | | Harsh Singh | | harshsingh.xyz | GitHub | NextJS, TailwindCSS, TypeScript, Prisma | | Wallace Nascimento | | portfolio-srnascimento40.vercel.app | GitHub | NextJS, ReactJS, TypeScript, Styled-Components | | Idris Olubisi | | idrisolubisi.com | GitHub | ReactJs, GatsbyJs, TypedJs, Styled Component | | Aycan Öğüt | | aycan.dev | Github | React, Next, TypeScript, Mantine | | Manish Kumar | | manishk.dev | Github | React, Next, TypeScript, ParticleJS, Firebase, Vercel | | Andrea Toffanello | | andreatoffanello.com | None | VueJS, ThreeJS, GSAP, Blender | | Chandraprakash Darji | | chandraprakash.vercel.app | Github | Nextjs, Typescript, Tailwindcss, Vercel | | Khaled Mohamed | | John Doe | None | HTML5, SCSS, Bootstrap5, JavaScript, SwipperJS, Netlify | | Michael Kolesidis | | michaelkolesidis.com | GitHub | TypeScript, p5.js, Sass, Vite | | Piyush Goyani | | piyushgoyani.thesourcepedia.org | None | VueJS, Gridsome, TailwindCSS, Firebase | | Vanessa Santana | | nessajs.com.br | GitHub | HTML, CSS, JavaScript and PHP | | Mahmoud Elkariouny | | clear-sleet.surge.sh | GitHub | HTML, CSS, JavaScript | | Antonio Ayola | | antonioayola.netlify.app | GitHub | React, HTML, CSS, Modules CSS, JavaScript, PWA | | Ajo Alex | | devpenzil.dev | GitHub | NextJS, Tailwind, GraphCMS | | Erys Mozo | | erysmozo.vercel.app | GitHub | React, SASS, Vite, AOS | | Peace Jinadu-Paul | | pjpportfolio.netlify.app | GitHub | React, HTML, CSS, Javascript, Framer Motion, Netlify | | Hari Prasad | | hariprasd.me | GitHub | React, Tailwind CSS | | Danilo Batson | | batson-portfolio.vercel.app/ | GitHub | TypeScript, JavaScript, Python, React, React Native, Vue, Express, Node, MongoDB, Next JS | | Soumyadeep Das Bhowmick | | soumyadeeposd.github.io | GitHub | HTML, CSS, JavaScript | | Byunggeun Cho | | bbangjo.kr | GitHub | HTML, CSS, JavaScript, TypeScript, Threejs, Blender | | James Warner | | jmswrnr.com | None | NextJS, Sanity, CSS, Preact, NodeJS, ThreeJS | | Maxime Heckel | | maximeheckel.com | GitHub | NextJS, TypeScript, Stiches/CSS, MDX | | Twan Mulder | | twanmulder.com | GitHub | React, TailwindCSS, Stripe, Netlify | | Rishi Mohan | | rishimohan.me | GitHub | Next.js, TailwindCSS, Framer Motion | | Nikhil Rajput | | nixrajput.nixlab.co.in | GitHub | Next.js, SCSS, Node.js | | Raphaël Chelly | | raphaelchelly.com/ | GitHub | Next.js, TailwindCSS, Vercel | | Damian Demasi | | damiandemasi.com | GitHub | ReactJS, TailwindCSS, DaisyUI | | Ifedili Onyegbu | | ifedili.com | GitHub | Angular, TypeScript, SASS | | Daniel Cranney | | danielcranney.com/ | GitHub | NextJS, TailwindCSS, Vercel | | Abdellatif Laghjaj | | abdellatif-laghjaj.ml/ | None | VueJS, Lottilefiles, Verel, CSS | | Adham Dannaway | | adhamdannaway.com | None | Wordpress, PHP, jQuery, MySQL | | Khaled Mohamed | | James Oliver | None | HTML5, CSS3, SCSS, Bootstrap5, TypeScript, SwipperJS, Fontello, PurgeCSS, Netlify | | Glayson Visgueira | | glaysonvisgueira.vercel.app | GitHub | NextJS, Styled-components, NodeJS, Vercel, Animate.css, Lottiefiles | | Chai Phonbopit | | devahoy.com | None | NextJS, Preact, Tailwind CSS, NodeJS | | Aravind Balla | | aravindballa.com | GitHub | NextJS, TypeScript, Tailwind CSS, Vercel | | Khaled Mohamed | | Thomas David | None | React JS, Tailwind CSS, AOS, SwipperJS, React Scroll, React Icons, React Laze Load Image, PostCSS, Netlify | | Tanishka Yadav | | tanishka-yadav.netlify.app | Github | ReactJS, Javascript, SASS, Framer Motion | | David Obodo | | davidobodo.com | None | NextJS, Typescript, SASS, GSAP, Jest, Sendgrid, Google Analytics | | Manuel David Gomez | | manueldavgomez.com | Github | ReactJs, Javascript, Css, Bootstrap, Bootstrap Icons, React-Animate-On-Scroll, React-Scroll, Vite, TsParticles | | Olasunkanmi Balogun | | kanmibalogun.vercel.app | Github | NextJS, JavaScript, Tailwind, Framer-motion, vanilla CSS | | Priyankar Pal | | itspp.vercel.app | GitHub | HTML & SCSS | | Marieflor Bawanan | | marieflor.dev | GitHub | NextJS, TypeScript, TailwindCSS & GSAP | | Delba Oliviera | | delba.dev | GitHub | Next.js, MDX, Tailwind, Prisma, Typescript | | Vivek Patel | | vivek9patel.github.io | GitHub | NextJS, Tailwind CSS, GitHub Pages | | Sarah Dayan | | sarahdayan.dev | None | NextJS, Tailwind CSS, NodeJS, Vercel | | Theodorus Clarence | | theodorusclarence.com | Github | NextJS, TypeScript, Tailwind CSS, MDX Bundler, Prisma | | Arafat Islam | | portfolio-khaki-iota-89.vercel.app | Github | NextJS, TypeScript, GraphQL, Tailwind CSS | | Siddharth Verma | | iamdev.netlify.app/home.html | None | Tailwind, Javascript, React, html/CSS | | Abo Ghanbari | | aboghanbari.com | None | Gatsby, Emotion, GSAP, Preact | | PATRICK T.LO | | pleaseleaveon.com | None | HTML5, CSS, JavaScript, jQuery | | Aliyah Adefolake | | aliyahadefolake.com | None | ReactJS, Gatsby, SASS, GSAP, Contentful | | Travis Fischer | | transitivebullsh.it | Github | NextJS, TypeScript, Notion API, Vercel | | Lynn Fisher | | lynnandtonic.com | Github | HTML5, CSS, JavaScript, SVG, Netlify, GoatCounter, HSTS, Open Graph | | Danny Garcia | | danny-garcia.com | Github | HTML5, CSS, JavaScript, TypeScript, GLSL, Netlify | | Robin Payot | | robinpayot.com | None | HTML5, CSS, JavaScript, GSAP, Howler.js, Hammer.js, three.js, WebGL, PWA, Open Graph, Apache | | Jesse Zhou | | jesse-zhou.com | Github | HTML5, CSS, JavaScript, GLSL, Howler.js, GSAP, Three.js, Node.js, Vercel | | Rauno Freiberg | | rauno.me | None | NextJS, NodeJS, Stiches, Vercel | | Anurag Hazra | | anuraghazra.dev | GitHub | React, Gatsby, Styled-components, Cypress, Jest, TravisCI | | Hardik Gohil | | hardikgohilhlr.tech | None | Next.js, TypeScript, Firebase, SCSS | | Jonathan Toon | | jonathontoon.com | Github | Gulp, EsBuild, postCSS, Nunjuck | | Rafael Derolez | | derolez.dev | None | NextJS, Sanity, ChakraUI, Emotion | | Chris Williams | | astro-theme-cactus.netlify.app | Github | Astro, Typescript, Tailwind CSS, MDX | | Ben Holmes | | bholmes.dev | Github | Gatsby, Javascript, SCSS, Pug | | Yasio | | yasio.dev | Github | Nuxt.js, Node.js, core-js, Vue.js, VideoJS, Firebase, HSTS, Open Graph, HTTP/3, Webpack, PWA | | Alec Babala | | alecbabala.com | None | Next.js, Node.js, core-js, React, HSTS, Open Graph, Webpack, MobX, GSAP, Contentful | | Gavin Nelson | | nelson.co | Github | NextJS, Tailwind CSS, Vercel, MDX | | Yinka Adedire | | yinka.codes | Github | Gatsby, ReactJS, Styled-Components | | Abdullah Abdulfatah | | draq.tech | None | NextJS, Typescript, ChakraUI | | Samuel Imolorhe | | xkoji.dev | Github | Gatsby, GSAP, JavaScript, Netlify | | Abu Said | | abusaid.netlify.app | GitHub | Next.js, Tailwind CSS, Email.JS | | Quiet Node | | quiet-node.dev | GitHub | TypeScript, ReactJS, ViteJS, TailwindCSS, Motion Framer | | Daniel Wisky | | danielwisky.com.br | GitHub | HTML, CSS, JavaScript | | JJ Kasper | | jjsweb.site | Github | NextJS, Vercel, CSS | | Cassidy Williams | | cassidoo.co | None | HTML, CSS, JavaScript | | Jahir Fiquitiva | | jahir.dev | Github | Next.js, Tailwind CSS, MDX, contentlayer, PlanetScale, Vercel, TypeScript | | Stefan Topalovic | | stefantopalovicdev.vercel.app | None | ReactJS, SCSS, Vercel | | Abdullah Moiz | | mrmoiz.vercel.app | None | Next Js ,Tailwind css, Vercel | | Victor Williams | | victorwilliams.me | Github | React, Next.js, TypeScript, TailwindCSS, Framer Motion, GSAP, Vercel | | Modupe Akanni | | modupe-akanni.vercel.app | Github | React, Next.js, Styled Components, Vercel | | Anuoluwapo Abolarin | | anuoluwapo.xyz | Github | VueJS, SCSS, GSAP, Vite | | Andrew Branch | | blog.andrewbran.ch | Github | Gatsby, TypeScript, Emotion, Netlify | | Max Böck | | mxb.dev | Github | Eleventy, SCSS, Nunjucks | | Shahriar Shafin | | shahriarshafin.github.io | Github | React, Next.js, Tailwind CSS | | Mukul Chugh | | mukulchugh.com | None | React, Next.js, Styled Components, Netlify | | Vijay Verma | | vjy.me | None | NextJS, Styled Components, Vercel | | Jhey Tompkins | | jhey.dev | Github | Sanity, Astro, Tailwind CSS, Netlify | | David Heckhoff | | david-hckh.com/ | None | HTML, CSS, JavaScript, ThreeJS, GSAP, PWA, Howler.js | | Ashish | | asrvd.me | Github | Next.js, tRPC, Tailwind CSS, TypeScript, NextAuth.js, Prisma | | Robb Owen | | robbowen.digital | None | HTML, CSS, JavaScript, Netlify | | Josh Comeau | | joshwcomeau.com | None | NextJS, Styled Components, MDX, MongoDB, Framer Motion, React Spring, Vercel | | Charles Bruyerre | | itssharl.ee | None | NextJS, ThreeJS, PWA, Vercel | | Patrick David | | bepatrickdavid.com | None | HTML, CSS, JavaScript, jQuery, Plesk, ThreeJS, GSAP, PWA | | Seán Halpin | | seanhalpin.xyz | None | Svelte, SvelteKit, Vite, PWA, Node.js | | Cyd Stumpel | | cydstumpel.nl | None | WordPress, PHP, ThreeJS, MySQL, GSAP, Lenis | | Tamal Sen | | tamalsen.dev | None | WordPress, Elementor, PHP, MySQL, Anime.js | | Aristide Benoist | | aristidebenoist.com | None | PHP, JavaScript, WebGL, AWS | | Abhishek Jha | | abhishekjha.me | None | HTML, CSS, JavaScript, GSAP, Varnish, Locomotive Scroll, Github Pages | | Robin Mastromarino | | robinmastromarino.com | None | HTML, CSS, JavaScript, WebGL, GSAP, Google Analytics | | Lanre Adelowo | | lanre.wtf | None | NextJS, CSS Modules, GSAP, Vercel, Hugo | | Prince Muhammad | | princemuhammad.pro | None | JavaScript, React.js, Next.js, TailwindCSS | | Victor Adeniji | | codevickk.com | None | Nuxt.js, Vue.js, GSAP, Netlify, Lenis | | Kaung Myat Kyaw | | barry121.com | Github | ReactJS, ThreeJS, TailwindCSS | | Eliaz LR | | eliaz-lr.dev | Github | Astro, TailwindCSS, Vue, DaisyUI | | Danny Johnson | | mrdannyjohnson.co.uk | None | Astro, Vue, Sanity, Tailwind CSS | | Wahid Ali | | https://www.wahidali.dev | Github | Svelte, Tailwind CSS, TypeScript, Vercel | | Deepanshu Mehra | | deeshu2002.github.io/folio | Github | HTML, CSS, TypeScript, Vite, PWA | | Brian Lovin | | brianlovin.com | Github | NextJS, TypeScript, Tailwind CSS, Prisma, Planetscale | | Pritish Samal | | pritishsamal.com | Github | Next.js, TypeScript, Emotion, Chakra UI | | Sandeep Kumar | | eternalfrustation.github.io | Github | HTML, CSS, JavaScript | | Mike Liu | | mikeliuu.com | Github | NextJS, TypeScript, Tailwind CSS, HTML, CSS, Vercel | | Bryan Smith | | multikitty.onrender.com | Github | HTML, CSS, JavaScript | | Goodness Urama | | goodie.work | Github | Pug, SCSS, Javascript ThreeJS, GSAP, Vercel | | Zai Santillan | | plskz-me.vercel.app | Github | NextJS, TypeScript, Tailwind CSS, DaisyUI | | Ashutosh Hathidara | | ashutoshhathidara.com | Github | HTML5, CSS3, React, NextJS | | Syed Moshin | | opensource-portfolio.netlify.app | Github | HTML5, CSS3, JavaScript | | David Angulo | | davidangulo.xyz | Github | HTML, Jekyl, Ruby, Bootstrap | | George Christeas | | chr-ge.com | Github | Next.js, Typescript, ChakraUI, Vercel | | Julien Thême | | julien-theme.dev | Github | Angular, TailwindCSS, ThreeJs | | Shubh Porwal | | shubhporwal.me | Github | NextJS, ReactJS, Tailwind CSS, GSAP | | Ross Moody | | rossmoody.com | Github | Next.js, Chakra UI, TypeScript, MDX, Netlify | | Rémy Beumier | | remybeumier.be | Github | Next.js, Sass, MDX, AOS | | Anirban Das | | anirbandas.in | Github | Qwik, React, Tailwind CSS | | Rafael Santana | | rafaelsantana.dev | Github | Next.js, Material UI, TypeScript | | Apoorv Maurya | | LivePortfolio | Github | HTML, CSS, JavaScript, | | Sumonta Saha Mridul | | sumonta056.github.io | Github | HTML5, CSS3, JavaScript | | Daniel Coyula | | portfolio.dctech.dev | None | Flutter | | Shaan Alam | | shaanalam.vercel.app | GitHub | NextJS, Tailwind, TypeScript & Hygraph | | Gregory Koberger | | gkoberger.com | None | VueJS, GSAP, NodeJS, Express | | Monica Powell | | aboutmonica.com | None | Gatsby, Emotion, Netlify | | Ismoilbek Ilxomov | | ismail.uz | None | NextJS, TailwindCSS, Netlify | | Kehinde Omopariola | | pariola.dev | Github | NextJS, Typescript, SASS, Motion One | | Shivam Gupta | | the-shivam-gupta.github.io | Github | HTML, CSS, JS | | Mateus Felipe Gonçalves | | mateusf.com | Github | Next.js, Typescript, Tailwindcss, Giscus, Contentlayer & MDX | | Anubhav Sigdel | | anubhavsigdel.vercel.app | GitHub | HTML, CSS, JS | | Krish Depani | | krish-depani.vercel.app | GitHub | HTML & CSS | | Bona Brian Siagian | | bonabrian.com | GitHub | Typescript, NextJs, TailwindCSS, Prisma, Contentlayer | | SofiDev | | itssofi.dev | GitHub | Astro, CSS, Javascript, React | | Sadee | | codewithsadee.github.io/vcard-personal-portfolio | Github | HTML, CSS, JavaScript | | Emmanuel Nsikan-david | | nsikandavid.dev | None | ReactJS, CSS | | Cruip | | preview.cruip.com | None | Alpine.JS, Tailwind CSS, Chartjs | | Dev Khandelwal | | slyro.vercel.app | GitHub | Next.JS, Tailwind CSS, MDX | | Skifli | | skifli.github.io | GitHub | HTML, CSS, JavaScript | | Eva Decker | | evadecker.com | GitHub | Astro, React, TypeScript, Framer Motion | | Guglielmo Cerri | | guglielmocerri.github.io | GitHub | HTML, CSS, JavaScript, reCAPTCHA | | Wisnu Wicaksono | | wiscaksono.com | GitHub | Nextjs, Tailwind CSS, MDX, Next Auth | | Emmanuel Alabi | | emmanuelalabi.vercel.app | None | HTML, TailwindCSS | | Zaher Al Majed | | zaher.design | None | React, TypeScript, NextJS, TailwindCSS | | Shivani Yadav | | shivaniyadav.online | GitHub | React, TypeScript, ParticleJS, Hostinger, SCSS | | Matthias Kretschmann | | matthiaskretschmann.com | GitHub | NextJS, TypeScript, CSS Modules, Vercel | | Le Vinh Khang | | levinhkhang.org | GitHub | NextJS, TailwindCSS, React | | Ali Imam | | aliimam.in | GitHub | NextJS, TailwindCSS, React, Lenis | | Ahmed Amer | | tammura.com | None | NextJS, TailwindCSS, Vercel, Cloudflare | | Alpay Celik | | alpaycelik.dev | GitHub | NextJS, TailwindCSS, Typescript, Framer Motion, Swiper, Vercel, NodeMailer | | Hanaia Youcef | | poysa213.me | GitHub | Typescript, NextJS, TailwindCSS, Framer Motion | | Jaber Said | | jaberdev.com | GitHub | React JS, Tailwind CSS, Three JS | | Xiaohan Zou | | portfolio.zxh.io | GitHub | React JS, Zustand, UnoCSS, Typescript, Vite | | Manh Hung Dao | | age-of-23.vercel | GitHub | Nextjs, MDX, Tailwind CSS, TypeScript, JavaScript | | CuB3y0nd | | cubeyond.net | GitHub | Nextjs, MDX, Tailwind CSS, TypeScript | | Baraa Alshaer | | alshaer.vercel.app | GitHub | React JS, Typescript, Shadcn ui , Tailwind CSS | | Sameera Sandakelum | | sameerasw.com | GitHub | HTML, CSS, Javascript, Netlify | | Jam Moonbami | | moonbamiofficial.vercel.app | GitHub | Next.js, Node.js, React, Tailwind CSS, MongoDB, Vercel | | Asharib Ali | | cv.asharib.xyz | GitHub | Next.js, React, Typescript, Shadcn/ui, Tailwind CSS, Vercel | | MAHG | | mahg.me | GitHub | NextJS, React, Typescript, TailwindCSS, Vercel | | Sunidhi Singh | | sunidhi-singh.netlify.app | GitHub | HTML, CSS, JavaScript | | Dhairya Majmudar | | https://dhaiyra-majmudar.netlify.app | Github | React, Tailwind , Material UI | | Jay Bhavsar | | https://jay.is-savvy.dev | Github | Vue, Gridsome, Tailwind CSS | | Siyana Zdravkova | | professionalportfolio | Github | Javascript, JSON, React JS, Bootstrap, Tachyons, animate.css, Tspracticles | | Anshul Gora | | anshulwork.netlify.app | None | ReactJs, Bootstrap, Vanilla CSS, Javascript | | Dogan Merden | | doganmerden.vercel.app | None | Next.js, TypeScript, Tailwind CSS, AuthJs, next-intl, Daisy UI, framer-motion | | Ibrahim Sadik Tamim | | tam11a.dev | GitHub | NextJS, TypeScript, TailwindCSS, Framer, GSAP | | Dipesh Murmu | | portfolio.itsmedipesh.xyz | None | Laravel PHP, Tailwind, JavaScript, CSS | | Akshay kumar | | akshaytalanki19.com | GitHub | Html, CSS, JavaScript | | Pieter-Jan Scheir | | pieterjanscheir.com | None | React/Next.js, Typescript, Tailwindcss, Vercel, Lucide | | Huy Nguyen | | huyng.xyz | None | React.js, TailwindCSS, GSAP, Lenis | | Anshul Soni | | anshulsoni.in | GitHub | HTML, CSS, JavaScript, Other Libraries | | David Simoes | | davesimoesportfolio.netlify.app | GitHub | HTML, CSS, JavaScript | | Saahil Dutta | | saahild.com | GitHub | Reactjs | | Moshood Sanusi | | olawale.dev | None | ReactJS, TailwindCSS, GSAP | | MD Affan Asghar | | affancoder.github.io/Portfolio_Website | GitHub | HTML, CSS, JavaScript | | DEBAJYOTI GHOSH | | convolexa-2503.web.app | None | React JS | | Muhammad Naeem Tahir | | muhammadnaeemtahir.github.io | GitHub | HTML, CSS, JavaScript, Bootstrap | | Aravind Ashokan | | aravind.xyz | GitHub | ReactJS, CSS(SASS), Framer Motion, SwiperJS, EmailJS | | Moinak Majumdar | | moinak05.portfolio | GitHub | Next.js, TypeScript, Framer Motion, TailwindCss | | Saleh Salehizadeh | | SirSaleh.github.io | GitHub | Nextjs, Tailwind CSS, TypeScript | | Vijay Kumar Reddy Talakola | | talakolavijay.vercel.app | GitHub | Reactjs, Tailwind CSS, AOS | | Nisarg Kavi | | nisargkavi.in | None | Nextjs, Tailwind CSS, Framer Motion, AnimeJS | | Malik Naik | | maliknaik.me | None | HTML, CSS, Bootstrap, and JavaScript | | Kshitij Gehlot | | KDGehlot2003.github.io | GitHub | HTML, CSS, Bootstrap, and JavaScript | | Johnson Takashi | | johnson-takashi-blockchain.web.app | GitHub | HTML, CSS, Bootstrap, and JavaScript | Suggestions Do you have any portfolio you want to see added but you can't add it yourself? Just mention it in this issue and it will be picked up by the community. You can also raise a PR to add any of the portfolios suggested here as well. Sponsor As you build your portfolio we hope you get that job or achieve what you want with it. Don't forget to star this project if you find it helpful. If you like this project and want to give back, consider buying me a coffee. I'll appreciate every cup. ☕ Contributors Thanks goes to these wonderful people. ( emoji key ): Victor Eke 🚧 💻 📖 🐛 Israel Mitolu 💻 📖 Piyush Goyani 💻 📖 Franklin Ohaegbulam 💻 📖 vimode 💻 📖 This project follows the all-contributors specification. Contributions of any kind welcome!

A curation of awesome portfolio website ideas for developers and designers to draw inspiration from. Raise a pull request to add more. 💜

designers,developer-portfolio,ideas,portfolio,portfolio-website,devfolio,portfolio-ideas,inspiration,resume,personal-website

superfly/litefs

LiteFS ====== LiteFS is a FUSE-based file system for replicating SQLite databases across a cluster of machines. It works as a passthrough file system that intercepts writes to SQLite databases in order to detect transaction boundaries and record changes on a per-transaction level in LTX files . This project is actively maintained but is currently in a beta state. Please report any bugs as an issue on the GitHub repository. You can find a Getting Started guide on LiteFS' documentation site . Please see the ARCHITECTURE.md design document for details about how LiteFS works. SQLite TCL Test Suite It's a goal of LiteFS to pass the SQLite TCL test suite, however, this is currently a work in progress. LiteFS doesn't have database deletion implemented yet so that causes many tests to fail during teardown. To run a test from the suite against LiteFS, you can use the Dockerfile.test to run it in isolation. First build the Dockerfile: sh docker build -t litefs-test -f Dockerfile.test . Then run it with the filename of the test you want to run. In this case, we are running select1.test : sh docker run --device /dev/fuse --cap-add SYS_ADMIN -it litefs-test select1.test Contributing LiteFS contributions work a little different than most GitHub projects. If you have a small bug fix or typo fix, please PR directly to this repository. If you would like to contribute a feature, please follow these steps: Discuss the feature in an issue on this GitHub repository. Create a pull request to your fork of the repository. Post a link to your pull request in the issue for consideration. This project has a roadmap and features are added and tested in a certain order. Additionally, it's likely that code style, implementation details, and test coverage will need to be tweaked so it's easier to for me to grab your implementation as a starting point when implementing a feature.

FUSE-based file system for replicating SQLite databases across a cluster of machines

sqlite

synercys/annotated_latex_equations

The file "eqn_annotate.tex" is the main latex file. This repository provides four examples of annotated equations: [example_prob.tex] A simple one inside the equation construct, in a double column format [example_prob2.tex] A more complex one, but this time inside the figure construct in a double column format [example_laplace.tex] Inside the wrapfigure construct but for a single column format [example_overlay.tex] More complicated examples, side-by-side using the minipage construct in a single column format The folder, "example_output_figs" includes figures that show the outputs of the above four cases. Note: the main latex file, "eqn_annotate.tex" includes many latex packages and some definitions that are required. To build all the examples into a single file, type: make OR pdflatex (or xelatex) eqn_annotate The output PDF file (containing all the examples) is named: eqn_annotate.pdf Update : There is now a Latex package that makes it easier to create annotated equations! Check it out. They have even created a demo file that uses the same examples as mine . Link to the CTAN package page. Examples [example_prob.tex] A simple one inside the equation construct, in a double column format [example_prob2.tex] A more complex one, but this time inside the figure construct in a double column format [example_laplace.tex] Inside the wrapfigure construct but for a single column format [example_overlay.tex] More complicated examples, side-by-side using the minipage construct in a single column format

Examples of how to create colorful, annotated equations in Latex using Tikz.

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