Merge branch 'main' into update_blast

.github/workflows/docker-publish.yml

@@ -0,0 +1,47 @@
+name: build and publish image
+
+on:
+  push:
+    # run only against tags
+    tags:
+      - "*"
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}
+
+# 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
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      # 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 }}
+
+      # 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 }}
+
+      - 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 }}

CONTRIBUTING.md

@@ -1,7 +1,5 @@
 # Developing ARCTIC-3D
 
-This section is still work in progress
-
 ## Installation
 
 We use `poetry` to manage the dependencies and the virtual environment, so it makes things easier if you need to install it first; check the [official documentation](https://python-poetry.org/docs/#installation) for more details.

Dockerfile

@@ -0,0 +1,6 @@
+FROM python:3.10
+WORKDIR /opt/software
+COPY . .
+RUN pip install .
+WORKDIR /data
+ENTRYPOINT [ "arctic3d" ]

README.md

@@ -28,6 +28,15 @@ Check [CONTRIBUTING.md](CONTRIBUTING.md) for more information.
 
 ### With `conda`
 
+Clone the repository on your computer and navigate to it
+
+```bash
+git clone [email protected]:haddocking/arctic3d.git
+cd arctic3d
+```
+
+Here you can create the arctic3d environment:
+
 ```bash
 conda create -n arctic3d python=3.10
 conda activate arctic3d
@@ -59,3 +68,9 @@ sphinx-build -E docs ./arctic3d-docs
 ```
 
 Then you can open the file `arctic3d-docs/index.html`, which contains all the necessary documentation.
+
+## Citing us
+
+If you used ARCTIC-3D in your work please cite the following publication:
+
+**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)