Phenobase Dataplatform

Data platform for UAV Hyperspectral long-term experiments at Agroscope — standardizes data and pipelines, makes data queryable, and hides backend complexity so researchers focus on science instead of wrestling with unorganized data, scripts, and models.

Installation

git clone https://github.com/EOA-team/035_phenobase.git
conda env create -f environment.yml
conda activate 035_phenobase

Project Structure

. 
├── src/              # source code
├── tests/            # tests
├── data/             # input data (excluded from git)
├── docs/             # cheatsheets, ...
├── results/          # outputs (excluded from git)
├── .github/workflows # CI configuration
├── environment.yml
└── README.md

Run Local

**1. Install Docker Compose ** https://docs.docker.com/compose/install/

**2. Create PostgreSQL Container

cd docker
docker compose up -d

3. Set your environemt in .env file

cd docker
docker compose up -d
cd ..

4. Run Tests (Independent of Agroscope Fola Infrastructure)

pytest -s -v -m "not ags_fola"

**5. Start Phenobase **

uvicorn src.main:app --host localhost --port 8000

runs on http://localhost:8000/

**5. Start Mlflow **

mlflow server --host localhost --port 5000

runs on http://localhost:5000/

**6. Initialize Database with Test Users **

python -m src.scripts.database.00_reset
python -m src.scripts.database.01_load_users
python -m src.scripts.database.inspect_users

7. Sample Upload (treatment) 7.1 Go to http://localhost:8000/docs 7.2 Use MAX_MUSTERMANN_API_KEY (Write Role) 7.3 Dowload csv template: http://localhost:8000/docs#/default/get_upload_template_data_upload_template__table_name__get 7.4 Upload adjusted csv file: http://localhost:8000/docs#/default/upload_file_data_upload__table_name__post 7.6 Check if upload log is in STORAGE_LOCAL_PATH 7.7 Check if data is in database: http://localhost:8000/docs#/default/get_table_data_data__table_name__get