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Изворен канал @pythonotes · Post #380 · 21 окт.

Регулярно приходится писать и ревьюить код, где используется PySide2-6. Заметил, что в подавляющем большинстве случаев настройка создаваемых базовых виджетов происходит через методы. Думаю, всем знаком такой способ. Простой пример с кнопкой: button = QPushButton("Click Me") button.setMinimumWidth(300) button.setFlat(True) button.setStyleSheet("font-size: 20pt") button.setToolTip("Super Button") button.clicked.connect(lambda: print("Button clicked")) Но есть и альтернативный способ - настройка через свойства. Это просто ключевые аргументы конструктора класса. Хоть они и не указаны в документации как аргументы, но они есть) Этот код делает тоже самое но с помощью Property button = QPushButton( "Click Me", minimumWidth=300, flat=True, styleSheet="font-size: 20pt", toolTip="Super Button", clicked=lambda: print("Button clicked"), ) Где это может быть полезно ▫️ Это выглядит более аккуратно и коротко, уже повод использовать ▫️ Может использоваться в заполнении лейаута, когда нам не нужно никакое другое взаимодействие с виджетом и поэтому сохранять его в переменную не требуется. Например, лейбл или кнопка. widget = QWidget(minimumWidth=400) layout = QHBoxLayout(widget) layout.addWidget(QLabel("Button >", alignment=Qt.AlignRight)) layout.addWidget(QPushButton("Click Me", clicked=lambda: print("Button clicked"))) widget.show() Либо так widget = QWidget(minimumWidth=400) layout = QHBoxLayout(widget) for wd in ( QLabel("Button >", alignment=Qt.AlignRight), QPushButton("Click Me", clicked=lambda: ...) ): layout.addWidget(wd) widget.show() ▫️ Можно хранить настройки в каком-то конфиге или генерировать на лету, после чего передавать как kwargs. kwargs = {"text": "Hello " * 30, "wordWrap": True} my_label = QLabel(**kwargs) Как получить полный список доступных свойств? Эта функция распечатает в терминал все свойства виджета и их текущие значения def print_widget_properties(widget): meta_object = widget.metaObject() for i in range(meta_object.propertyCount()): property_ = meta_object.property(i) property_name = property_.name() property_value = property_.read(widget) print(f"{property_name}: {property_value}") #tricks#qt

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@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

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@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

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@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