<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def run_multiple_grid_districts(mv_grid_districts, run_id, failsafe=False, base_path=None):
 """ Perform ding0 run on given grid districts Parameters mv_grid_districs : list Integers describing grid districts run_id: str Identifier for a run of Ding0. For example it is used to create a subdirectory of os.path.join(`base_path`, 'results') failsafe : bool Setting to True enables failsafe mode where corrupt grid districts (mostly due to data issues) are reported and skipped. Report is to be found in the log dir under :code:`~/.ding0` . Default is False. base_path : str Base path for ding0 data (input, results and logs). Default is `None` which sets it to :code:`~/.ding0` (may deviate on windows systems). Specify your own but keep in mind that it a required a particular structure of subdirectories. Returns ------- msg : str Traceback of error computing corrupt MV grid district .. TODO: this is only true if try-except environment is moved into this fundion and traceback return is implemented Notes ----- Consider that a large amount of MV grid districts may take hours or up to days to compute. A computational run for a single grid district may consume around 30 secs. """

    start = time.time()

    # define base path
    if base_path is None:
        base_path = BASEPATH

    # database connection/ session
    engine = db.connection(section='oedb')
    session = sessionmaker(bind=engine)()

    corrupt_grid_districts = pd.DataFrame(columns=['id', 'message'])

    for mvgd in mv_grid_districts:
        # instantiate ding0  network object
        nd = NetworkDing0(name='network', run_id=run_id)

        if not os.path.exists(os.path.join(base_path, "grids")):
            os.mkdir(os.path.join(base_path, "grids"))

        if not failsafe:
            # run DING0 on selected MV Grid District
            msg = nd.run_ding0(session=session,
                               mv_grid_districts_no=[mvgd])

            # save results
            results.save_nd_to_pickle(nd, os.path.join(base_path, "grids"))
        else:
            # try to perform ding0 run on grid district
            try:
                msg = nd.run_ding0(session=session,
                                   mv_grid_districts_no=[mvgd])
                # if not successful, put grid district to report
                if msg:
                    corrupt_grid_districts = corrupt_grid_districts.append(
                        pd.Series({'id': mvgd,
                                   'message': msg[0]}),
                        ignore_index=True)
                # if successful, save results
                else:
                    results.save_nd_to_pickle(nd, os.path.join(base_path,
                                                               "grids"))
            except Exception as e:
                corrupt_grid_districts = corrupt_grid_districts.append(
                    pd.Series({'id': mvgd,
                               'message': e}),
                    ignore_index=True)

                continue

        # Merge metadata of multiple runs
        if 'metadata' not in locals():
            metadata = nd.metadata

        else:
            if isinstance(mvgd, list):
                metadata['mv_grid_districts'].extend(mvgd)
            else:
                metadata['mv_grid_districts'].append(mvgd)

    # Save metadata to disk
    with open(os.path.join(base_path, "grids", 'Ding0_{}.meta'.format(run_id)),
              'w') as f:
        json.dump(metadata, f)

    # report on unsuccessful runs
    corrupt_grid_districts.to_csv(
        os.path.join(
            base_path,
            "grids",
            'corrupt_mv_grid_districts.txt'),
        index=False,
        float_format='%.0f')

    print('Elapsed time for', str(len(mv_grid_districts)),
          'MV grid districts (seconds): {}'.format(time.time() - start))

    return msg