def test_modify_view_component(matrix_type, mapping_name):
    adata = ad.AnnData(
        np.zeros((10, 10)),
        **{mapping_name: dict(m=matrix_type(asarray(sparse.random(10, 10))))},
    )
    init_hash = joblib.hash(adata)

    subset = adata[:5, :][:, :5]
    assert subset.is_view
    m = getattr(subset, mapping_name)["m"]
    m[0, 0] = 100
    assert not subset.is_view
    assert getattr(subset, mapping_name)["m"][0, 0] == 100

    assert init_hash == joblib.hash(adata)
def rpc_bulk(orchestrator, audit_name, rpc_code, *arguments):

    # Get the implementor for the RPC code.
    # Raise NotImplementedError if it's not defined.
    try:
        method, blocking = rpcMap[rpc_code]
    except KeyError:
        raise NotImplementedError("RPC code not implemented: %r" % rpc_code)

    # This can't be done with blocking implementors!
    if blocking:
        raise NotImplementedError(
            "Cannot run blocking RPC calls in bulk. Code: %r" % rpc_code)

    # Prepare a partial function call to the implementor.
    caller = partial(method, orchestrator, audit_name)

    # Use the built-in map() function to issue all the calls.
    # This ensures we support the exact same interface and functionality.
    return map(caller, *arguments)