Docker uses yaml

You can query the Docker container name by following the steps: List all containers (docker ps). Filter the container list (using the grep command). Gets the container name (located in the "NAMES" column).

Docker container startup steps: Pull the container image: Run "docker pull [mirror name]". Create a container: Use "docker create [options] [mirror name] [commands and parameters]". Start the container: Execute "docker start [Container name or ID]". Check container status: Verify that the container is running with "docker ps".

Create a container in Docker: 1. Pull the image: docker pull [mirror name] 2. Create a container: docker run [Options] [mirror name] [Command] 3. Start the container: docker start [Container name]

The methods to view Docker logs include: using the docker logs command, for example: docker logs CONTAINER_NAME Use the docker exec command to run /bin/sh and view the log file, for example: docker exec -it CONTAINER_NAME /bin/sh ; cat /var/log/CONTAINER_NAME.log Use the docker-compose logs command of Docker Compose, for example: docker-compose -f docker-com

How to define header files using Visual Studio Code? Create a header file and declare symbols in the header file using the .h or .hpp suffix name (such as classes, functions, variables) Compile the program using the #include directive to include the header file in the source file. The header file will be included and the declared symbols are available.

Writing C in VS Code is not only feasible, but also efficient and elegant. The key is to install the excellent C/C extension, which provides functions such as code completion, syntax highlighting, and debugging. VS Code's debugging capabilities help you quickly locate bugs, while printf output is an old-fashioned but effective debugging method. In addition, when dynamic memory allocation, the return value should be checked and memory freed to prevent memory leaks, and debugging these issues is convenient in VS Code. Although VS Code cannot directly help with performance optimization, it provides a good development environment for easy analysis of code performance. Good programming habits, readability and maintainability are also crucial. Anyway, VS Code is

Depending on the specific needs and project size, choose the most suitable IDE: large projects (especially C#, C) and complex debugging: Visual Studio, which provides powerful debugging capabilities and perfect support for large projects. Small projects, rapid prototyping, low configuration machines: VS Code, lightweight, fast startup speed, low resource utilization, and extremely high scalability. Ultimately, by trying and experiencing VS Code and Visual Studio, you can find the best solution for you. You can even consider using both for the best results.

Running Kotlin in VS Code requires the following environment configuration: Java Development Kit (JDK) and Kotlin compiler Kotlin-related plugins (such as Kotlin Language and Kotlin Extension for VS Code) create Kotlin files and run code for testing to ensure successful environment configuration