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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 types_of_coordination_environments(self, anonymous=False):
 """ Extract information on the different co-ordination environments present in the graph. :param anonymous: if anonymous, will replace specie names with A, B, C, etc. :return: a list of co-ordination environments, e.g. ['Mo-S(6)', 'S-Mo(3)'] """


        motifs = set()
        for idx, site in enumerate(self.structure):

            centre_sp = site.species_string

            connected_sites = self.get_connected_sites(idx)
            connected_species = [connected_site.site.species_string
                                 for connected_site in connected_sites]

            labels = []
            for sp in set(connected_species):
                count = connected_species.count(sp)
                labels.append((count, sp))

            labels = sorted(labels, reverse=True)

            if anonymous:
                mapping = {centre_sp: 'A'}
                available_letters = [chr(66+i) for i in range(25)]
                for label in labels:
                    sp = label[1]
                    if sp not in mapping:
                        mapping[sp] = available_letters.pop(0)
                centre_sp = 'A'
                labels = [(label[0], mapping[label[1]]) for label in labels]

            labels = ["{}({})".format(label[1], label[0]) for label in labels]
            motif = '{}-{}'.format(centre_sp, ','.join(labels))
            motifs.add(motif)

        return sorted(list(motifs))