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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 concept(self, mechanism, purviews=False, cause_purviews=False, effect_purviews=False):
 """Return the concept specified by a mechanism within this subsytem. Args: mechanism (tuple[int]):
 The candidate set of nodes. Keyword Args: purviews (tuple[tuple[int]]):
 Restrict the possible purviews to those in this list. cause_purviews (tuple[tuple[int]]):
 Restrict the possible cause purviews to those in this list. Takes precedence over ``purviews``. effect_purviews (tuple[tuple[int]]):
 Restrict the possible effect purviews to those in this list. Takes precedence over ``purviews``. Returns: Concept: The pair of maximally irreducible cause/effect repertoires that constitute the concept specified by the given mechanism. """

        log.debug('Computing concept %s...', mechanism)

        # If the mechanism is empty, there is no concept.
        if not mechanism:
            log.debug('Empty concept; returning null concept')
            return self.null_concept

        # Calculate the maximally irreducible cause repertoire.
        cause = self.mic(mechanism, purviews=(cause_purviews or purviews))

        # Calculate the maximally irreducible effect repertoire.
        effect = self.mie(mechanism, purviews=(effect_purviews or purviews))

        log.debug('Found concept %s', mechanism)

        # NOTE: Make sure to expand the repertoires to the size of the
        # subsystem when calculating concept distance. For now, they must
        # remain un-expanded so the concept doesn't depend on the subsystem.
        return Concept(mechanism=mechanism, cause=cause, effect=effect,
                       subsystem=self)