While the notebooks run without any issue in the continuous integration environment they somehow cause a memory overload on mybinder when it comes to running the MPI parallel python functions. The example that breaks is:
from executorlib import SingleNodeExecutor
def calc_mpi(i):
from mpi4py import MPI
size = MPI.COMM_WORLD.Get_size()
rank = MPI.COMM_WORLD.Get_rank()
return i, size, rank
with SingleNodeExecutor(resource_dict={"cores": 2}, block_allocation=True) as exe:
fs = exe.submit(calc_mpi, 3)
print(fs.result())