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Anticipatory Action

This repository provides scripts and Jupytext notebooks to run analytical, trigger, and operational workflows for anticipatory action. You can run them:

  • In a local Pixi-managed environment, or
  • Inside a Docker container, using environment variables to pass parameters.

🔗 For core objects used here, inherited datasets, and key imported functions, see the HIP Analysis documentation.

✅ Quick Start

1. Pull the latest code

git pull origin main

2. Install Pixi

Follow Pixi installation guide, then:

pixi install --locked

3. Run workflows locally

  • Analytical bash pixi run python -m AA.analytical <ISO> <SPI/DRYSPELL>
  • Triggers bash pixi run python -m AA.triggers <ISO> <SPI/DRYSPELL> <VULNERABILITY>
  • Operational bash pixi run python -m AA.operational <ISO> <ISSUE_MONTH> <SPI/DRYSPELL>

Make sure your parameters are defined in config/{iso}_config.yml.

🐳 Run with Docker (short version)

Build the image:

docker build -t aa-runner .

Export AWS credentials:

export AWS_ACCESS_KEY_ID="XXX"
export AWS_SECRET_ACCESS_KEY="XXX"
export AWS_SESSION_TOKEN="XXX"

Run a module:

docker run --rm \
  -e AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID} \
  -e AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY} \
  -e AWS_SESSION_TOKEN=${AWS_SESSION_TOKEN} \
  aa-runner:latest \
  python -m AA.analytical <ISO> <SPI/DRYSPELL> \
  --data-path <DATA_PATH> --output-path <OUTPUT_PATH>

For full details, see Run with Docker.

📚 Documentation Sections

  • How-To Guides — Pixi, Docker, SSH/GitHub, credentials, dependencies, tests, Jupytext.
  • Explanation — What the pipeline does and how it’s validated.

🔗 See Also