docs: def from_dict(cls, d):
          """
          Reconstructs the StructureEnvironments object from a dict representation of the StructureEnvironments created
          using the as_dict method.
          :param d: dict representation of the StructureEnvironments object
          :return: StructureEnvironments object
          """
          ce_list = [None if (ce_dict == 'None' or ce_dict is None) else {
              int(cn): [None if (ced is None or ced == 'None') else
                        ChemicalEnvironments.from_dict(ced) for ced in ce_dict[cn]]
              for cn in ce_dict} for ce_dict in d['ce_list']]
          voronoi = DetailedVoronoiContainer.from_dict(d['voronoi'])
          structure = Structure.from_dict(d['structure'])
          neighbors_sets = [{int(cn): [cls.NeighborsSet.from_dict(dd=nb_set_dict,
                                                                  structure=structure,
                                                                  detailed_voronoi=voronoi)
                                       for nb_set_dict in nb_sets]
                             for cn, nb_sets in site_nbs_sets_dict.items()}
                            if site_nbs_sets_dict is not None else None
                            for site_nbs_sets_dict in d['neighbors_sets']]
          info = {key: val for key, val in d['info'].items() if key not in ['sites_info']}
          if 'sites_info' in d['info']:
              info['sites_info'] = [{'nb_sets_info': {int(cn): {int(inb_set): nb_set_info
                                                                for inb_set, nb_set_info in cn_sets.items()}
                                                      for cn, cn_sets in site_info['nb_sets_info'].items()},
                                     'time': site_info['time']} if 'nb_sets_info' in site_info else {}
                                    for site_info in d['info']['sites_info']]
          return cls(voronoi=voronoi, valences=d['valences'],
                     sites_map=d['sites_map'],
                     equivalent_sites=[[PeriodicSite.from_dict(psd) for psd in psl] for psl in d['equivalent_sites']],
                     ce_list=ce_list, structure=structure,
                     neighbors_sets=neighbors_sets,
                     info=info)