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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def resolve(self, requirements, max_rounds=20):
 """Take a collection of constraints, spit out the resolution result. The return value is a representation to the final resolution result. It is a tuple subclass with two public members: * `mapping`: A dict of resolved candidates. Each key is an identifier of a requirement (as returned by the provider's `identify` method), and the value is the resolved candidate. * `graph`: A `DirectedGraph` instance representing the dependency tree. The vertices are keys of `mapping`, and each edge represents *why* a particular package is included. A special vertex `None` is included to represent parents of user-supplied requirements. The following exceptions may be raised if a resolution cannot be found: * `NoVersionsAvailable`: A requirement has no available candidates. * `ResolutionImpossible`: A resolution cannot be found for the given combination of requirements. * `ResolutionTooDeep`: The dependency tree is too deeply nested and the resolver gave up. This is usually caused by a circular dependency, but you can try to resolve this by increasing the `max_rounds` argument. """

        resolution = Resolution(self.provider, self.reporter)
        resolution.resolve(requirements, max_rounds=max_rounds)
        return resolution.state