import py_school_match as psm

# Creating three students.
st0 = psm.Student()
st1 = psm.Student()
st2 = psm.Student()

# Creating a criteria. This means 'vulnerable' is now a boolean.
vulnerable = psm.Criteria('vulnerable', bool)

# Assigning st1 as vulnerable
student_vulnerable = psm.Characteristic(vulnerable, True)
st1.add_characteristic(student_vulnerable)

# Creating three schools, each with one seat available.
sc0 = psm.School(1)
sc1 = psm.School(1)
sc2 = psm.School(1)

# Defining preferences (from most desired to least desired)
st0.preferences = [sc0, sc1, sc2]
st1.preferences = [sc0, sc2, sc1]
st2.preferences = [sc2, sc1, sc0]

# Creating a lists with the students and schools defined above.
schools = [sc0, sc1, sc2]
students = [st0, st1, st2]

# Defining a ruleset
ruleset = psm.RuleSet()

# Defining a new rule from the criteria above.
rule_vulnerable = psm.Rule(vulnerable)

# Adding the rule to the ruleset. This means that a 'vulnerable' student has a higher priority.
# Note that rules are added in order (from higher priority to lower priority)
ruleset.add_rule(rule_vulnerable)

# Creating a social planner using the objects above.
planner = psm.SocialPlanner(students, schools, ruleset)

# Selecting an algorithm
algorithm = psm.SIC()

# Running the algorithm.
planner.run_matching(algorithm)

# inspecting the obtained assignation
for student in students:
    if student.assigned_school is not None:
        print("Student {} was assigned to School {}".format(student.id, student.assigned_school.id))
    else:
        print("Student {} was not assigned to any school".format(student.id))