pip install scarfmatch

import scarf

# An example with single doctors {s0, s1}, couples {c0=(c00, c01) c1=(c10, c11)}, and hospitals {h0, h1, h2} 
single_pref = [[0, 1, 2], # s0's preference on hospitals is h0 > h1 > h2 > unemployment
             [1, 0]] # s1's preference on hospitals is h1 > h0 > unemployment > h2
             # list only the hospitals preferred to unemployment 
couple_pref = [[(0, 0), (1, 1), (1, 0), (0, 1), (2, 2)], # c0's joint preference on hospital pairs
             [(1, 1), (2, 2), (1, -1)]] # c1's joint preference on joint plans for both members
             # for example, (1, 0) stands for "member 0 goes to hospital 1 and member 1 goes to hospital 0"
             # "-1" stands for the option of unemployment
             # list only the options preferred to (-1, -1) (i.e. both unemployed)
hospital_pref = [0, (0, 1), 1, (1, 0), (0, 0), (1, 1)] # all three hospitals have the same preference: s0 > c01 > s1 > c10 > c00 > c11 > vacancy
# If all hospital use the same preference, then hospital_pref is one list containing integers and tuples, where integers represent singles and tuples represent members of couples
# To specify different preference lists for different hospitals, please use a list of lists
# In each list, only specify acceptable doctors to the given hospital
hospital_cap = [2, 3, 1] # capacities of each hospital

S = scarf.create_instance(single_pref, couple_pref, hospital_pref, hospital_cap)
sol = scarf.solve(S) # solves for a possibly fractional stable matching
intsol = scarf.round(sol, S) # perform Nguyen and Vohra's IR algorithm to obtain a near feasible stable matching

print(intsol)

Copyright (c) 2019-2023 Dengwang Tang <dwtang@umich.edu>