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Recent Releases of CHAP

CHAP - Climate Conference

🚀 Release v1.0.14 · Model Configuration & Metrics Expansion

This release introduces major enhancements to model configuration, adds new backtest metrics, and improves system robustness across the board. It also includes several bug fixes, CI improvements, and developer tooling updates.

The database schemas has changed significantly since last release, so the existing evaluation and dataset data in the chap database has to be deleted for this update. Running docker compose down --volumes will do this.

🖥 How to install this release on a server

Step 1 | NB! Only needed if you already have the chap-core repo, otherwise skip to step 2

2.1 If you already have the folder since you previously cloned the CHAP core repo, go into the folder (chap-core) and run the command below. This will shut down running containers and delete all data related to CHAP. IMPORTANT! Be aware this will also delete stored data in Chap, such as evaluations and predictions.

docker compose down --volumes

2.2. Fetch all new versions

git fetch --tags

2.3. Run the command below to switch the repo to v1.0.14, this is not necessary if you cloned the repo/started from scratch (step 1)

git switch v1.0.14 --detach

Step 2: NB! Only if you have not proceeded with step 1 (you not have the chap-core repo)

Run this command, if you have not cloned the chap-core repo before, or you are starting from scratch, for instance, if you are deploying through GitHub Actions.

git clone --depth 1 --branch v1.0.14 https://github.com/dhis2-chap/chap-core.git

Step 3 | Start chap-core

Within the chap-core folder, rebuild and start the containers in detach mode:

docker compose up --build -d

✨ Features

  • 🧠 Model Template Configuration System
    You can now configure ModelTemplates into ConfiguredModels via YAML files and API endpoints. This enables better versioning, flexibility, and reproducibility in model management workflows.

  • 📅 Dual Support for Weekly and Monthly Models
    Prediction pipelines now support both week-based and month-based adapters. This improves compatibility with different time resolutions.

  • 📈 Enhanced Backtest Metrics

    • Added normalized CRPS as a new metric.
    • Backtest results now include associated model and dataset.
    • API returns a detailed list of timepoint and aggregate metrics.

  • 📌 Job Management

    • Added job cancellation endpoint with built-in validation to prevent unsafe deletions.
    • Improved validation of job deletion and filtering options.

  • 📝 Metadata Support

    • Datasets can now include metadata for better traceability.
    • New fields (author_note, author_assessed_status) added to model templates.

🛠 Fixes

  • Fixed integration tests and flaky CI runs by isolating failing models.
  • Resolved import errors and invalid environment references in Docker and tests.
  • Addressed false-positive errors in docker_db_flow.py.
  • Improved validation for edge cases and NaN metrics.

🔧 DevOps & CI/CD

  • Multiple version bumps from v1.0.8 → v1.0.14.
  • Improved CI to:
    • Avoid accidental PyPI pushes.
    • Tag Docker images by platform (e.g., linux/amd64).
    • Use Python 3.12 for testing and packaging.
  • Cleaned up Dockerfile.inla and simplified compose workflows.

🧪 Testing Improvements

  • Better Docker-based integration test flows.
  • Fine-tuned which models/datasets are tested to reduce noise.
  • More logs included to aid debugging.

🧹 Internal Maintenance

  • Cleaned up legacy endpoints and renamed /models to /configured_models (with alias retained).
  • Removed unused code, updated formatting, and standardized file naming.
  • Enhanced error resilience in metrics and model seeding flows.

📚 Documentation

  • Updated internal documentation on endpoints and model configuration.
  • Improved developer setup guides and DHIS2 integration instructions.

Final note

Thanks to all contributors for helping us reach this milestone.
🚨 If you're upgrading, please ensure that any local model configuration files conform to the new YAML structure and that Python 3.12 is installed.

Climate Change - Climate Data Processing and Analysis - Python
Published by knutdrand about 1 month ago

CHAP - v1.0.7

This release mainly contains new features and improvements for supporting the new Modeling App (which is replacing the old Prediction App as a frontend to the Chap Modeling Platform). This means that this is the first version of chap-core that supports the Modeling App, and that this version is not backwards-compatible with the Prediction App. Users of the Modeling App will now get a warning if they have an incompatible version of the chap-core python package (backend).

This version also has some minor fixes and improvements:

  • New API endpoint for checking version compatibility with the Modeling App.
  • Some improvements in logging and error handling
  • Some initial support for more flexible model configuration (currently only through the command line, plan is to support this in the Modeling app in the future).
  • Improvements to the docker compose setup with autoreload functionality
  • Google Earth credentials are no longer required for using chap-core with the Modelling app

How to install this release on a server

Step 1 | NB! Only needed if you already have the chap-core repo, otherwise skip to step 2

2.1 If you already have the folder since you previously cloned the CHAP core repo, go into the folder (chap-core) and run the command below. This will shut down running containers related to CHAP. Be aware it will also delete stored data in CHAP, such as predictions.

docker compose down --volumes

2.2. Fetch all new versions

git fetch --tags

2.3. Run the command below to switch the repo to v1.0.7, this is not necessary if you cloned the repo/started from scratch (step 1)

git switch v1.0.7 --detach

Step 2: NB! Only if you have not proceeded with step 1 (you not have the chap-core repo)

Run this command, if you have not cloned the chap-core repo before, or you are starting from scratch, for instance, if you are deploying through GitHub Actions.

git clone --depth 1 --branch v1.0.7 https://github.com/dhis2-chap/chap-core.git

Step 3 | Start chap-core

Within the chap-core folder, rebuild and start the containers in detach mode:

docker compose up --build -d

Climate Change - Climate Data Processing and Analysis - Python
Published by ivargr 2 months ago

CHAP - v1.0.5

This release includes:

  • Google Earth Engine fix
  • Minor bug fixes

Installation on a server

Step 1 | NB! Only needed if you already have the chap-core repo, otherwise skip to step 2

2.1 If you already have the folder since you previously cloned the CHAP core repo, go into the folder (chap-core) and run the command below. This will shut down running containers related to CHAP. Be aware it will also delete stored data in CHAP, such as predictions.

docker compose down -v

2.2. Fetch all new versions

git fetch --tags

2.3. Run the command below to switch the repo to v1.0.5, this is not necessary if you cloned the repo/started from scratch (step 1)

git switch v1.0.5 --detach

Step 2: NB! Only if you have not proceeded with step 1 (you not have the chap-core repo)

Run this command, if you have not cloned the chap-core repo before, or you are starting from scratch, for instance, if you are deploying through GitHub Actions.

git clone --depth 1 --branch v1.0.5 https://github.com/dhis2-chap/chap-core.git

Step 3 | Start chap-core

Within the chap-core folder, rebuild and start the containers in detach mode:

docker compose up --build -d

Climate Change - Climate Data Processing and Analysis - Python
Published by hermantretteteig 5 months ago

CHAP - v0.1.1

This release includes:

  • Working solution for storing results and data to a PostgreSQL database
  • New REST API endpoints (using Celery for job handling and storing results to a database)
  • More developer documentation
  • Added .9 and .1 to quantiles evaluation plots used in the prediction app
  • Div minor bugfixes and improvements

Climate Change - Climate Data Processing and Analysis - Python
Published by ivargr 5 months ago

CHAP - v0.0.18

This release includes new features and improvements:

  • Better job handling system using Celery (supporting multiple logs running in parallel)
  • Variuos improvements to the documentation, including more info about running CHAP on a server, better documentation on how to integrate external models, and a new developer getting started guide
  • Better logging and input validation to jobs (better feedback when models crash or something goes wrong)
  • A new system for persisting results using a SQL database
  • Support for sending polygons (geojson) to models that require that
  • Various code cleanup and minor bugfixes

Climate Change - Climate Data Processing and Analysis - Python
Published by ivargr 6 months ago

CHAP - v0.0.16

  • This release mainly includes improved documentation on how to setup CHAP with the predicions app to integrate CHAP with DHIS2.
  • Also includes various bug fixes and improvements related to integrating custom models, along with better documentation on how to do this

Climate Change - Climate Data Processing and Analysis - Python
Published by ivargr 8 months ago

CHAP - v0.0.14

  • Docker compose working, with integration tests (meaning chap and necessary services can be started and run through docker compose)
  • Some technical changes: changed to uv and started to use ruff for linting
  • Various documentation improvements, new endpoint for all documentation
  • Rest API endpoint for evaluation

Climate Change - Climate Data Processing and Analysis - Python
Published by ivargr 8 months ago

CHAP - v0.0.9

Various minor changes:

  • Updated docker file so that it is correct with new package name
  • Added github project with development plans (linked from readme)
  • Automatically generate command line interface for chap-models
  • Added model registry with models with specifications
  • General cleanup (removed time-consuming imports)
  • Synced list models endpoint with predict endpoint in rest API
  • Some documentation improvements (better installation instructions, etc)

Climate Change - Climate Data Processing and Analysis - Python
Published by ivargr 9 months ago