Merge branch 'main' of https://github.com/boettiger-lab/solara-test

README.md

@@ -11,6 +11,11 @@ app_port: 8765
 
 NOTE: The YAML header above is required for HuggingFace Spaces deployment.  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
+-----
+
+[![Open in Gitpod](https://gitpod.io/button/open-in-gitpod.svg)](https://gitpod.io/#https://github.com/boettiger-lab/solara-test)
+
+
 # Simple Solara demo
 
 This respository demonstrates how we can deploy an interactive map tool from a few lines of python to an app on HuggingFace spaces using Solara. 
@@ -24,4 +29,20 @@ This application accesses boundary polygons from the National Parks Service and
 
 ### Code
 
-The required code for analysis is in `fire.py`, with solara visualization in `pages/01_leafmap.py`.  (For interactive use, see `solar-app.pynb`)
+The required code for analysis is in `fire.py`, with solara visualization in `pages/01_leafmap.py`.  (For interactive use, see `solar-app.pynb`)
+
+### Actions
+
+This repository uses three GitHub Actions:
+
+  - 📦 [`docker.yml`](.github/workflows/docker.yml) builds the Dockerfile and pushes to GitHub Container Registry
+  - 🤗 [`sync-hf.yml`](.github/workflows/sync-hf.yml) syncs the GitHub repo to HuggingFace Spaces repo, which renders the Solara App via Dockerfile.
+  - 💻 [`compute.yml`](.github/workflows/compute.yml) Runs the `fire.py` script using the Docker container environment, and pushes the resulting COGs to 🤗 huggingface datasets.
+
+### Credentials
+
+This demo uses only free and open source resources.  The only credentials required are a HuggingFace token to deploy datasets (via git-lfs) and HuggingFace Spaces (for the Solara App).  This deployment could use other mechanisms instead, these options are simple and free.
+
+### Environments
+
+This setup tries to be simple and portable.  Select "use devcontainer" when opening in a local VSCode instance, select "Open in Codespaces" from the "Code" button menu in GitHub, or use the Gipod button to access a VSCode editor running in the containerized environment.  Or simply open in your favorite python editor and install the `requirements.txt` file yourself.