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Py-school-match, a Python package that implements matching algorithms for the student-to-school assignation problem.

Project description

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Py-school-match

Py-school-match is an open-source Python package that implements multiple matching algorithms in order to assign students to schools.

It provides multiple algorithms ready to use:

  • Top Trading Cycles (TTC)
  • Deferred acceptance with multiple tie-breaking (DAMTB)
  • Deferred acceptance with single tie-breaking (DASTB)
  • Stable improvement cycles (SIC)
  • Deferred Acceptance with multiple tie-breaking, plus stable cycles (MSIC)
  • Deferred Acceptance with single tie-breaking, plus non-stable cycles (NSIC)

Py-school-match is designed specifically for the student-to-school assignation problem. Because of this, you can focus on evaluating different settings and algorithms, without the need to adapt or develop a complete solution.

Sample code

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:
    print("Student {} was assigned to School {}".format(student.id, student.assigned_school.id))

Installation

Dependencies

  • graph-tool (>= 2.27)

User installation

pip install py-school-match

Or you can clone the repo and install it:

git clone https://github.com/igarizio/py-school-match
cd py-school-match
python setup.py install

Remember to first install graph-tool.

Development

Contributions are more than welcome. Feel free to open an issue or contact me!
Remember that this package does not provide ANY WARRANTY OF ANY KIND.

How to cite?

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