def test_drop_obs_column():
    adata = ad.AnnData(np.array(X_list), obs=obs_dict, dtype="int32")

    subset = adata[:2]
    assert subset.is_view
    # returns a copy of obs
    assert subset.obs.drop(columns=["oanno1"]).columns.tolist() == ["oanno2", "oanno3"]
    assert subset.is_view
    # would modify obs, so it should actualize subset and not modify adata
    subset.obs.drop(columns=["oanno1"], inplace=True)
    assert not subset.is_view
    assert subset.obs.columns.tolist() == ["oanno2", "oanno3"]

    assert adata.obs.columns.tolist() == ["oanno1", "oanno2", "oanno3"]
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)