tools/runAlgorithm.py is a python script that runs an optimisation or other algorithm-- it is controlled by a json file
see Configurations/example.json or Configurations/example_dfols.json

Installation:

1) Put the code somewhere convenient.
2) Define in your environment OPTCLIMTOP where ever this is.
3) Put $OPTCLIMTOP/OptClimVn2 and $OPTCLIMTOP/tools/optFunctions (and DFOLS and what ever else needed by your optimisation algorithm ) in your python search path.
4) Add $OPTCLIMTOP/tools to your PATH.

Works at python 3.8.  *May* work at python 3.7+. Needs dicts that are ordered.
You also need the following modules (generally available from conda-forge but could be installed via pip)
f90nml
pandas
matplotlib
xarray
netCDF4
numpy

+ dfols (pip) pip install DFO-LS (See https://github.com/numericalalgorithmsgroup/dfols/)
If you want to use pysot (which has not been tested) then you will need to install that too (see https://pypi.org/project/pySOT/)

Testing:
run pytest in OptClimVn2 in OPTCLIMTOP. There are about 120 tests. One in test_Optimise may fail. If so run it again...

To test runAlgorithm.py you need to do the following in ipython in OPTCLIMTOP:
import tempfile
tdir=tempfile.TemporaryDirectory() # gives you a temp directory.
%run -i tools/runAlgorithm --restart  --test -d $tdir.name Configurations/dfols14param.json
# This will run continually run until the algorithm has finished.

For porting you will need to modify (or add new )  code  so that it uses the correct submission method & model class.
OptClimVN2 provides classes/methods for you. See README in that directory.
tools contains some other potentially useful tools...

OptClimVn2/config.py contains a lookup table for models.

Warning: This code is research quality and probably not really suitable for production. I am happy to collaborate with others to make it more useful.
All code is available on a GPLv3 license. See License.