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v6-summary-py

Create a summary of the data (mean, range, variance, length, ...)

This algorithm is designed to be run with the vantage6 infrastructure for distributed analysis and learning.

The base code for this algorithm has been created via the v6-algorithm-template template generator.

Dockerizing your algorithm

To finally run your algorithm on the vantage6 infrastructure, you need to create a Docker image of your algorithm.

Automatically

The easiest way to create a Docker image is to use the GitHub Actions pipeline to automatically build and push the Docker image. All that you need to do is push a tag to the repository (only allowed for developers with write access to this repository).

Manually

A Docker image can be created by executing the following command in the root of your algorithm directory:

docker build -t [my_docker_image_name] .

where you should provide a sensible value for the Docker image name. The docker build command will create a Docker image that contains your algorithm. You can create an additional tag for it by running

docker tag [my_docker_image_name] [another_image_name]

This way, you can e.g. do docker tag local_average_algorithm harbor2.vantage6.ai/algorithms/average to make the algorithm available on a remote Docker registry (in this case harbor2.vantage6.ai).

Finally, you need to push the image to the Docker registry. This can be done by running

docker push [my_docker_image_name]

Note that you need to be logged in to the Docker registry before you can push the image. You can do this by running docker login and providing your credentials. Check this page For more details on sharing images on Docker Hub. If you are using a different Docker registry, check the documentation of that registry and be sure that you have sufficient permissions.