def test_view_mixin_copies_data(adata, array_type: type, attr):
    N = 100
    adata = ad.AnnData(
        obs=pd.DataFrame(index=np.arange(N)), var=pd.DataFrame(index=np.arange(N))
    )

    X = array_type(sparse.eye(N, N).multiply(np.arange(1, N + 1)))
    if attr == "X":
        adata.X = X
    else:
        getattr(adata, attr)["arr"] = X

    view = adata[:50]

    if attr == "X":
        arr_view = view.X
    else:
        arr_view = getattr(view, attr)["arr"]

    arr_view_copy = arr_view.copy()

    if sparse.issparse(X):
        assert not np.shares_memory(arr_view.indices, arr_view_copy.indices)
        assert not np.shares_memory(arr_view.indptr, arr_view_copy.indptr)
        assert not np.shares_memory(arr_view.data, arr_view_copy.data)

        arr_view_copy.data[0] = -5
        assert not np.array_equal(arr_view_copy.data, arr_view.data)
    else:
        assert not np.shares_memory(arr_view, arr_view_copy)

        arr_view_copy[0, 0] = -5
        assert not np.array_equal(arr_view_copy, arr_view)
def _add_implementor(rpc_code, blocking, fn):

    # Validate the argument types.
    if type(rpc_code) is not int:
        raise TypeError("Expected int, got %r instead" % type(rpc_code))
    if type(blocking) is not bool:
        raise TypeError("Expected bool, got %r instead" % type(blocking))
    if not callable(fn):
        raise TypeError("Expected callable, got %r instead" % type(fn))

    # Validate the RPC code.
    if rpc_code in rpcMap:
        try:
            msg = "Duplicated RPC implementors for code %d: %s and %s"
            msg %= (rpc_code, rpcMap[rpc_code][0].__name__, fn.__name__)
        except Exception:
            msg = "Duplicated RPC implementors for code: %d" % rpc_code
        raise SyntaxError(msg)

    # TODO: use introspection to validate the function signature

    # Register the implementor.
    rpcMap[rpc_code] = (fn, blocking)

    # Return the implementor. No wrapping is needed! :)
    return fn