def deploy_service_registry_and_set_urls(
    private_keys, web3, contract_manager, service_registry_address
) -> Tuple[ServiceRegistry, List[str]]:
    urls = ["http://foo", "http://boo", "http://coo"]
    c1_client = JSONRPCClient(web3, private_keys[0])
    c1_service_proxy = ServiceRegistry(
        jsonrpc_client=c1_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )
    c2_client = JSONRPCClient(web3, private_keys[1])
    c2_service_proxy = ServiceRegistry(
        jsonrpc_client=c2_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )
    c3_client = JSONRPCClient(web3, private_keys[2])
    c3_service_proxy = ServiceRegistry(
        jsonrpc_client=c3_client,
        service_registry_address=service_registry_address,
        contract_manager=contract_manager,
    )

    # Test that getting a random service for an empty registry returns None
    pfs_address = get_random_service(c1_service_proxy, "latest")
    assert pfs_address is None

    # Test that setting the urls works
    c1_service_proxy.set_url(urls[0])
    c2_service_proxy.set_url(urls[1])
    c3_service_proxy.set_url(urls[2])

    return c1_service_proxy, urls
def aggregate(cls, dataset, dimensions, function, **kwargs):
        data = dataset.data
        cols = [d.name for d in dataset.kdims if d in dimensions]
        vdims = dataset.dimensions('value', label='name')
        reindexed = data[cols+vdims]
        agg = function.__name__
        if len(dimensions):
            agg_map = {'amin': 'min', 'amax': 'max'}
            agg = agg_map.get(agg, agg)
            grouped = reindexed.groupby(cols, sort=False)
            if not hasattr(grouped, agg):
                raise ValueError('%s aggregation is not supported on cudf DataFrame.' % agg)
            df = getattr(grouped, agg)().reset_index()
        else:
            agg_map = {'amin': 'min', 'amax': 'max', 'size': 'count'}
            agg = agg_map.get(agg, agg)
            if not hasattr(reindexed, agg):
                raise ValueError('%s aggregation is not supported on cudf DataFrame.' % agg)
            agg = getattr(reindexed, agg)()
            data = dict(((col, [v]) for col, v in zip(agg.index.values_host, agg.to_array())))
            df = util.pd.DataFrame(data, columns=list(agg.index.values_host))

        dropped = []
        for vd in vdims:
            if vd not in df.columns:
                dropped.append(vd)
        return df, dropped