创建 Python 开发容器

你是一位 DevOps 专家，正使用 Docker 和 VS Code 远程容器（Remote Containers）搭建 Python 开发环境。

你的任务是提供并运行 Docker 命令，基于官方 python:latest-slim-bookworm 镜像构建一个轻量级 Python 开发容器。

关键要求：
- 使用交互模式（interactive mode），启动一个不会立即退出的 bash shell。
- 覆盖默认 command，使容器无限期保持运行（例如使用 sleep infinity 等方式），运行后不得自动删除容器。
- 将容器命名为 py-dev-container。
- 将当前工作目录（.）以卷（volume）形式挂载至容器内 /workspace 路径（读写权限）。
- 以非 root 用户身份运行容器：用户名为 'vscode'，UID 为 1000，确保与 VS Code Remote - Containers 扩展无缝兼容。
- 如有必要，可在容器内安装必需的开发工具（如 git、curl、build-essential 等），但仅限通过运行时命令（runtime commands）安装，且仅在确有需要时执行。
- 除运行所必需外，不得在宿主机或容器内创建任何额外文件。
- 使该容器适配 VS Code 远程连接（Remote - Containers: Attach to Running Container），以便后续开展 Python 开发、调试及扩展使用。

请提供：
1. docker pull 命令（如需）。
2. 包含全部参数标志的完整 docker run 命令。
3. 如何将 VS Code 连接到该正在运行的容器以进行开发的操作说明。

假设用户位于宿主机上其 Python 项目的根目录。

You are a DevOps expert setting up a Python development environment using Docker and VS Code Remote Containers.

Your task is to provide and run Docker commands for a lightweight Python development container based on the official python latest slim-bookworm image.

Key requirements:
- Use interactive mode with a bash shell that does not exit immediately.
- Override the default command to keep the container running indefinitely (use sleep infinity or similar) do not remove the container after running.
- Name it py-dev-container
- Mount the current working directory (.) as a volume to /workspace inside the container (read-write).
- Run the container as a non-root user named 'vscode' with UID 1000 for seamless compatibility with VS Code Remote - Containers extension.
- Install essential development tools inside the container if needed (git, curl, build-essential, etc.), but only via runtime commands if necessary.
- Do not create any files on the host or inside the container beyond what's required for running.
- Make the container suitable for attaching VS Code remotely (Remote - Containers: Attach to Running Container) to enable further Python development, debugging, and extension usage.

Provide:
1. The docker pull command (if needed).
2. The full docker run command with all flags.
3. Instructions on how to attach VS Code to this running container for development.

Assume the user is in the root folder of their Python project on the host.