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name: build and publish image | ||
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on: | ||
push: | ||
# run only against tags | ||
tags: | ||
- "*" | ||
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env: | ||
REGISTRY: ghcr.io | ||
IMAGE_NAME: ${{ github.repository }} | ||
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# There is a single job in this workflow. It's configured to run on the latest available version of Ubuntu. | ||
jobs: | ||
build-and-push-image: | ||
runs-on: ubuntu-latest | ||
# Sets the permissions granted to the `GITHUB_TOKEN` for the actions in this job. | ||
permissions: | ||
contents: read | ||
packages: write | ||
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steps: | ||
- name: Checkout repository | ||
uses: actions/checkout@v4 | ||
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# Uses the `docker/login-action` action to log in to the Container registry registry using the account and password that will publish the packages. Once published, the packages are scoped to the account defined here. | ||
- name: Log in to the Container registry | ||
uses: docker/login-action@v3 | ||
with: | ||
registry: ${{ env.REGISTRY }} | ||
username: ${{ github.actor }} | ||
password: ${{ secrets.GITHUB_TOKEN }} | ||
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# This step uses [docker/metadata-action](https://github.com/docker/metadata-action#about) to extract tags and labels that will be applied to the specified image. The `id` "meta" allows the output of this step to be referenced in a subsequent step. The `images` value provides the base name for the tags and labels. | ||
- name: Extract metadata (tags, labels) for Docker | ||
id: meta | ||
uses: docker/metadata-action@v5 | ||
with: | ||
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} | ||
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- name: Build and push | ||
uses: docker/build-push-action@v5 | ||
with: | ||
context: . | ||
push: ${{ github.event_name != 'pull_request' }} | ||
tags: ${{ steps.meta.outputs.tags }} | ||
labels: ${{ steps.meta.outputs.labels }} |
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FROM python:3.10 | ||
WORKDIR /opt/software | ||
COPY . . | ||
RUN pip install . | ||
WORKDIR /data | ||
ENTRYPOINT [ "arctic3d" ] |
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@@ -28,6 +28,15 @@ Check [CONTRIBUTING.md](CONTRIBUTING.md) for more information. | |
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### With `conda` | ||
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Clone the repository on your computer and navigate to it | ||
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```bash | ||
git clone [email protected]:haddocking/arctic3d.git | ||
cd arctic3d | ||
``` | ||
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Here you can create the arctic3d environment: | ||
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```bash | ||
conda create -n arctic3d python=3.10 | ||
conda activate arctic3d | ||
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``` | ||
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Then you can open the file `arctic3d-docs/index.html`, which contains all the necessary documentation. | ||
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## Citing us | ||
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If you used ARCTIC-3D in your work please cite the following publication: | ||
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**Marco Giulini, Rodrigo V. Honorato, Jesús L. Rivera, and Alexandre MJJ Bonvin**: "ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information." Communications Biology 7, no. 1 (2024): 49. (www.nature.com/articles/s42003-023-05718-w) |
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