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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 clip_foreign(network):
 """ Delete all components and timelines located outside of Germany. Add transborder flows divided by country of origin as network.foreign_trade. Parameters network : :class:`pypsa.Network Overall container of PyPSA Returns ------- network : :class:`pypsa.Network Overall container of PyPSA """


    # get foreign buses by country

    foreign_buses = network.buses[network.buses.country_code != 'DE']

    network.buses = network.buses.drop(
        network.buses.loc[foreign_buses.index].index)

    # identify transborder lines (one bus foreign, one bus not) and the country
    # it is coming from
    """transborder_lines = pd.DataFrame(index=network.lines[
        ((network.lines['bus0'].isin(network.buses.index) == False) &
         (network.lines['bus1'].isin(network.buses.index) == True)) |
        ((network.lines['bus0'].isin(network.buses.index) == True) &
         (network.lines['bus1'].isin(network.buses.index) == False))].index)
    transborder_lines['bus0'] = network.lines['bus0']
    transborder_lines['bus1'] = network.lines['bus1']
    transborder_lines['country'] = ""
    for i in range(0, len(transborder_lines)):
        if transborder_lines.iloc[i, 0] in foreign_buses.index:
            transborder_lines['country'][i] = foreign_buses[str(
                transborder_lines.iloc[i, 0])]
        else:
            transborder_lines['country'][i] = foreign_buses[str(
                transborder_lines.iloc[i, 1])]

    # identify amount of flows per line and group to get flow per country
    transborder_flows = network.lines_t.p0[transborder_lines.index]
    for i in transborder_flows.columns:
        if network.lines.loc[str(i)]['bus1'] in foreign_buses.index:
            transborder_flows.loc[:, str(
                i)] = transborder_flows.loc[:, str(i)]*-1

    network.foreign_trade = transborder_flows.\
        groupby(transborder_lines['country'], axis=1).sum()"""

    # drop foreign components
    network.lines = network.lines.drop(network.lines[
        (network.lines['bus0'].isin(network.buses.index) == False) |
        (network.lines['bus1'].isin(network.buses.index) == False)].index)

    network.links = network.links.drop(network.links[
        (network.links['bus0'].isin(network.buses.index) == False) |
        (network.links['bus1'].isin(network.buses.index) == False)].index)

    network.transformers = network.transformers.drop(network.transformers[
        (network.transformers['bus0'].isin(network.buses.index) == False) |
        (network.transformers['bus1'].isin(network.
                                           buses.index) == False)].index)
    network.generators = network.generators.drop(network.generators[
        (network.generators['bus'].isin(network.buses.index) == False)].index)
    network.loads = network.loads.drop(network.loads[
        (network.loads['bus'].isin(network.buses.index) == False)].index)
    network.storage_units = network.storage_units.drop(network.storage_units[
        (network.storage_units['bus'].isin(network.
                                           buses.index) == False)].index)

    components = ['loads', 'generators', 'lines', 'buses', 'transformers',
                  'links']
    for g in components:  # loads_t
        h = g + '_t'
        nw = getattr(network, h)  # network.loads_t
        for i in nw.keys():  # network.loads_t.p
            cols = [j for j in getattr(
                nw, i).columns if j not in getattr(network, g).index]
            for k in cols:
                del getattr(nw, i)[k]

    return network