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Изходен канал @clockstackwheels · Post #240 · 4.03

Посоветую вам YouTube-канал Stuff Made Here (в свете событий можно скачать все ролики с него и потом ностальгировать по ютубу вечерами). Пожалуй, это самый крутой инженерный видеоблог, который я встречал. У автора целый подвал роботизированных станков за миллионы баксов (просто несбыточная мечта гика). И он с их помощью городит электронно-механические конструкции, которые совмещают в себе сложное программирование и вполне очевидную практическую цель, как правило недостижимую или труднодостижимую без длительных тренировок. Вот я прикладываю видео, где он делает бильярдный стол и роботизированный кий, который позволяет не промахиваться. Продемонстрированы все стадии разработки: неудачные прототипы, подбор алгоритма, проверка гипотез. При этом подано всё в довольно понятном и динамичном стиле. с хорошим юмором. Ролик длиной 20-30 минут обычно содержит недели и месяцы разработки. Короче, очень круто. Если что-то и смотреть на ютубе напоследок, то вот примерно такого уровня контент, имхо. #dev#gadgets https://www.youtube.com/watch?v=vsTTXYxydOE

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GitHub Trends

@githubtrending · Post #14896 · 02.07.2025 г., 12:30

#python#ai#authentication#authorization#claude#cursor#fastapi#llm#mcp#mcp_server#mcp_servers#modelcontextprotocol#openapi#windsurf FastAPI-MCP is a tool that lets you easily turn your FastAPI web API endpoints into Model Context Protocol (MCP) tools, which AI agents can use directly. It requires almost no setup—just connect it to your FastAPI app, and it automatically preserves your request/response data models and documentation. It also includes built-in authentication using your existing FastAPI security methods. You can run the MCP server inside your app or separately, and it communicates efficiently using FastAPI’s ASGI interface. This makes it simple to integrate AI capabilities with your existing FastAPI services without rewriting code, saving you time and effort while keeping your API secure and well-documented[1][5]. https://github.com/tadata-org/fastapi_mcp

GitHub Trends

@githubtrending · Post #14735 · 22.05.2025 г., 11:30

#javascript#api_client#api_testing#automation#developer_tools#git#graphql_client#http_client#javascript#openapi#openapi3#opensource#rest_api#testing#testing_tools Bruno is a free, open-source API testing tool that stores your API collections as plain text files on your device, ensuring your data stays private without cloud syncing. It works across Mac, Windows, and Linux, and supports collaboration through Git or any version control system, making teamwork easier. Bruno automates API testing with JavaScript scripts, increasing efficiency, test coverage, and simplifying integration into CI/CD pipelines. This helps catch bugs early, maintain tests easily, and run regression tests smoothly, saving you time and improving API reliability compared to traditional tools like Postman. You can download it easily via multiple package managers. https://github.com/usebruno/bruno

GitHub Trends

@githubtrending · Post #14911 · 03.07.2025 г., 15:30

#javascript#hacktoberfest#oas#open_source#openapi#openapi_specification#openapi3#openapi31#rest#rest_api#swagger#swagger_api#swagger_js#swagger_oss#swagger_ui Swagger UI is a tool that helps developers and users interact with APIs. It creates a visual interface from OpenAPI specifications, making it easy to understand and use APIs without needing to know the underlying code. This tool benefits users by providing clear documentation and allowing them to test API methods directly from the interface. It also supports collaboration and compliance with the latest OpenAPI standards, making it easier to develop and consume APIs efficiently[1][3][5]. https://github.com/swagger-api/swagger-ui

GitHub Trends

@githubtrending · Post #14761 · 29.05.2025 г., 13:00

#python#api#async#asyncio#fastapi#framework#json#json_schema#openapi#openapi3#pydantic#python#python_types#python3#redoc#rest#starlette#swagger#swagger_ui#uvicorn#web FastAPI is a modern Python web framework for building fast, reliable APIs that is easy to learn and quick to code, making it ready for production use right away. It uses standard Python type hints, which means you get automatic data validation, fewer bugs, and great editor support with code completion and type checks. FastAPI also generates interactive documentation automatically, so you and your team can understand and test your API easily. The main benefit is that you can develop robust, high-performance APIs much faster and with less effort, while reducing errors and making your code easier to maintain[1][2][3]. https://github.com/fastapi/fastapi