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Merge pull request #3278 from JdeRobot/range-ports
Use range ports
2 parents fe956be + 2ae0065 commit 324f081

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compose_cfg/dev_humble_cpu.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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volumes:
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- type: bind
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source: ./

compose_cfg/dev_humble_gpu.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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volumes:
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- type: bind
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source: ./

compose_cfg/dev_humble_nvidia.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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volumes:
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- type: bind
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source: ./

compose_cfg/dev_humble_nvidia_windows.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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volumes:
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- type: bind
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source: ./

compose_cfg/user_humble_cpu.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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tty: true
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stdin_open: true
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depends_on:

compose_cfg/user_humble_gpu.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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tty: true
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stdin_open: true
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depends_on:

compose_cfg/user_humble_nvidia.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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tty: true
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stdin_open: true
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depends_on:

compose_cfg/user_humble_nvidia_windows.yaml

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ports:
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- "7164:7164"
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- "7163:7163"
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- "6080:6080"
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- "6081:6081"
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- "1108:1108"
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- "6080-6090:6080-6090"
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volumes:
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- /usr/lib/wsl:/usr/lib/wsl
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tty: true

docs/InstructionsForDevelopers.md

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* Automatic GPU selection
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```bash
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docker run --rm -it $(nvidia-smi >/dev/null 2>&1 && echo "--gpus all" || echo "") --device /dev/dri -p 6080:6080 -p 6081:6081 -p 1108:1108 -p 7163:7163 -p 7164:7164 --link academy_db jderobot/robotics-academy:latest
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docker run --rm -it $(nvidia-smi >/dev/null 2>&1 && echo "--gpus all" || echo "") --device /dev/dri -p 6080-6090:6080-6090 -p 7163:7163 -p 7164:7164 --link academy_db jderobot/robotics-academy:latest
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```
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* Automatic GPU selection (Without Nvidia)
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```bash
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docker run --rm -it --device /dev/dri -p 6080:6080 -p 6081:6081 -p 1108:1108 -p 7163:7163 -p 7164:7164 --link academy_db jderobot/robotics-academy:latest
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docker run --rm -it --device /dev/dri -p 6080-6090:6080-6090 -p 7163:7163 -p 7164:7164 --link academy_db jderobot/robotics-academy:latest
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```
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* Only CPU
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```bash
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docker run --rm -it -p 6080:6080 -p 6081:6081 -p 1108:1108 -p 7163:7163 -p 7164:7164 --link academy_db jderobot/robotics-academy:latest
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docker run --rm -it -p 6080-6090:6080-6090 -p 7163:7163 -p 7164:7164 --link academy_db jderobot/robotics-academy:latest
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```
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[how to generate a RADI]: ./generate_a_radi.md
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2. On Terminal open the directory where your project or code is located at (Example:- ```cd ~/my_project```)
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3. Append ```-v $(pwd):/location_in_radi``` to your ```docker run``` cli command used to run your container. (Example:- ```docker run --rm -it $(nvidia-smi >/dev/null 2>&1 && echo "--gpus all" || echo "") --device /dev/dri -p 7164:7164 -p 6080:6080 -p 6081:6081 -p 1108:1108 -p 7163:7163 jderobot/robotics-backend -v $(pwd):/home jderobot/robotics-academy```)
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3. Append ```-v $(pwd):/location_in_radi``` to your ```docker run``` cli command used to run your container. (Example:- ```docker run --rm -it $(nvidia-smi >/dev/null 2>&1 && echo "--gpus all" || echo "") --device /dev/dri -p 7164:7164 -p 6080-6090:6080-6090 -p 7163:7163 jderobot/robotics-backend -v $(pwd):/home jderobot/robotics-academy```)
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4. This will import your local directory inside the docker container, if you have used the example command like above where the location the command is being run is mounted to the home folder inside the docker container you will simply be able to see all the local mounted directories inside the /home of the RoboticsBackend.
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docs/develop_binding_volumes.md

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This method consists in replicating the folder /RoboticsAcademy that exists inside the RoboticsBackend on your local drive. Then, a docker run option is used to replace the RoboticsBackend folder with your local folder. By doing so, all the changes made on your local files are included in the container. Note that this is a shared volume, so all changes made to your shared volume even from inside the container are persistent.
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1. Replicate the folder RoboticsBackend:/RoboticsAcademy inside your local file system. This can be achieved by cloning the repository [RoboticsAcademy][https://github.com/JdeRobot/RoboticsAcademy] and the repository [RoboticsApplicationManager][https://github.com/JdeRobot/RoboticsApplicationManager] inside the folder RoboticsAcademy/src (include the contents directly, not into a subfolder src/RoboticsApplicationManager).
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2. Run ``` yarn run dev ``` if there were any front-end changes
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3. Run the docker image mounting the volume with the instruction ``` docker run --rm -it $(nvidia-smi >/dev/null 2>&1 && echo "--gpus all" || echo "") --device /dev/dri -p 7164:7164 -p 6080:6080 -p 6081:6081 -p 1108:1108 -p 7163:7163 --mount type=bind,source="$(pwd)"/RoboticsAcademy,target=/RoboticsAcademy jderobot/robotics-academy ``` replacing the mount source path to your RoboticsAcademy path.
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3. Run the docker image mounting the volume with the instruction ``` docker run --rm -it $(nvidia-smi >/dev/null 2>&1 && echo "--gpus all" || echo "") --device /dev/dri -p 7164:7164 -p 6080-6090:6080-6090 -p 7163:7163 --mount type=bind,source="$(pwd)"/RoboticsAcademy,target=/RoboticsAcademy jderobot/robotics-academy ``` replacing the mount source path to your RoboticsAcademy path.
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[How to set up the developer environment section.]: /docs/InstructionsForDevelopers.md

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