Add feedback from Simon Tarr

.github/workflows/python-package.yml

@@ -12,7 +12,7 @@ on:
 jobs:
   build:
     runs-on: ubuntu-latest
-    container: ghcr.io/osgeo/gdal:ubuntu-small-3.10.2
+    container: ghcr.io/osgeo/gdal:ubuntu-small-3.10.3
     strategy:
       fail-fast: false
       matrix:

Dockerfile

@@ -35,6 +35,7 @@ RUN mkdir -p /data
 # the Python virtualenv is set, but in Docker we don't
 # use a virtualenv, as docker *is* a virtualenv
 ENV VIRTUAL_ENV=/
+ENV PYTHONPATH=/root/star
 
 RUN python3 -m pytest ./tests
 RUN python3 -m pylint prepare_layers prepare_species utils tests

README.md

@@ -7,15 +7,27 @@ See [method.md](method.md) for a description of the methodology, or `scripts/run
 
 # Running the pipeline
 
+## Checking out the code
+
+This repository uses submodules, so once you have cloned it, you need to fetch the submodules:
+
+```shell
+$ git clone https://github.com/quantifyearth/star.git
+$ cd star
+$ git submodule update --init --recursive
+```
+
+## Running the pipeline
+
 The easiest way to get started will be to run `scripts/run.sh` under a linux environment.
 
-## Running on Ubuntu
+### Running on Ubuntu
 
 The following extra utilities will need to be installed:
 
 * [Reclaimer](https://github.com/quantifyearth/reclaimer/) - a utility for downloading data from various primary sources.
 
-## Running in Docker
+### Running in Docker
 
 There is included a docker file, which is based on the GDAL container image, which is set up to install everything ready to use. You can build that using: