README.md.jinja

# {{algorithm_name}}

{{algorithm_description}}

This algorithm is designed to be run with the [vantage6](https://vantage6.ai)
infrastructure for distributed analysis and learning.

The base code for this algorithm has been created via the
[v6-algorithm-template](https://github.com/vantage6/v6-algorithm-template)
template generator.

### Checklist

Note that the template generator does not create a completely ready-to-use
algorithm yet. There are still a number of things you have to do yourself.
Please ensure to execute the following steps. The steps are also indicated with
TODO statements in the generated code - so you can also simply search the
code for TODO instead of following the checklist below.

- [ ] Include a URL to your code repository in setup.py.
- [ ] Implement your algorithm functions.
  - [ ] You are free to add more arguments to the functions. Be sure to add them
    *after* the `client` and dataframe arguments.
  - [ ] When adding new arguments, if you run the `test/test.py` script, be sure
    to include values for these arguments in the `client.task.create()` calls
    that are available there.
- [ ] If you are using Python packages that are not in the standard library, add
  them to the `requirements.txt` and `setup.py` file.
{% if has_docs %}
- [ ] Fill in the documentation template. This will help others to understand your
  algorithm, be able to use it safely, and to contribute to it.
{% else %}
- [ ] We strongly recommend adding documentation to your code. This will help
  others to understand your code and will help you to understand your own code
  in the future.
{% endif %}
- [ ] If you want to submit your algorithm to a vantage6 algorithm store, be sure
  to fill in everything in ``algorithm_store.json`` (and be sure to update
  it if you change function names, arguments, etc.).
{% if has_gh_pipeline %}
- [ ] Create a ``DOCKER_USER`` and ``DOCKER_PASSWORD`` secret in the GitHub repository
  settings. This will be used to push the Docker image to the registry in the github
  pipeline.
{% endif %}
{% if use_vpn %}
- [ ] Review the EXPOSE and LABEL commands in the Dockerfile for VPN
{% endif %}
- [ ] Finally, remove this checklist section to keep the README clean.

### Dockerizing your algorithm

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

{% if has_gh_pipeline %}
#### 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
commit to the ``main`` branch.

#### Manually

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

```bash
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

```bash
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

```bash
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](https://docs.docker.com/get-started/04_sharing_app/)
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.