Adapted code to new utils server release.

Dockerfile

 FROM python:3.9.16-slim-bullseye
 
 # update system and install required software
-RUN apt update && /usr/local/bin/python -m pip install --upgrade pip && pip install poetry
+RUN apt update && /usr/local/bin/python -m pip install --upgrade pip && apt install git zip -y
 
 # copy zipped data
 COPY data /root/data

README.md

@@ -7,7 +7,7 @@ The docker container can be started with the following code:
 
 The service could be queried passing the JSON polygon object as in:
 ```
-curl -X POST http://localhost:5004/band_statistics \
+curl -X POST http://localhost:5004/band_statistics/2017 \
 -H "Content-Type: application/json" \
 -d '{
     "polygon_wkt": "POLYGON (())"

other/install_data.sh

 #!/bin/bash
 
-# it requires zipped geotiff in "data"
-apt update
-apt install zip -y
-
 echo "*** Unzipping files." # expected number of records in DB:
 
 #for y in {2017..2021}

other/load_server_package.sh

 #!/usr/bin/env bash
 
-# initialize project
-poetry init
-
-# confif repo
-poetry config repositories.gitlab https://git.nilu.no/api/v4/projects/1217/packages/pypi
-poetry config http-basic.gitlab FACT_token glpat-1zG-TQx___xLsPjj2vsG
-
-# add package
-poetry add polygonqueryonraster --source gitlab
+pip install git+https://FACT_token:glpat-1zG-TQx___xLsPjj2vsG@git.nilu.no/fact/utils/polygonqueryonraster.git

other/start.py

@@ -27,7 +27,7 @@ if __name__ == "__main__":
         Python environment. Modify the 'data_directory' and 'port_number' variables as needed for your setup.
     """
 
-    data_directory = '/app/data/aster30m'  # Specify your local data directory
+    data_directory = '/root/data'  # Specify your local data directory
     port_number = 5000  # Specify the custom port number
     categorical = False  # Specify whether the analysis is categorical