Getting started

Py-school-match’s basic structure

Py-school-match tries to expose flexible and easy-to-understand structures and functions.

In order to use the library, you should create at least one element of each category:

• Student: Represents one student.
• School: Represent one school. A school can have many seats.
• SocialPlanner: This entity runs the selected algorithm.

You should also select one algorithm:

• TTC: Top trading cycles.
• DAMTB: Deferred acceptance with multiple tie-breaking.
• DASTB: Deferred acceptance with single tie-breaking.
• SIC: Stable improvement cycles.
• MSIC: Deferred Acceptance with multiple tie-breaking, and then searches for stable cycles.
• NSIC: Deferred Acceptance with single tie-breaking, and then searches for non-stable cycles.

Finally, you can also define:

• Criteria: Associates an adjective and a value type.
• Characteristic: Associates a criteria with a value.
• Rule: Is used to determine the priority of a student.
• Ruleset: Aggregates a set of rules in a prioritized manner.