| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| from gremlin_python.process.anonymous_traversal import traversal |
| from gremlin_python.driver.driver_remote_connection import DriverRemoteConnection |
| import json |
| |
| |
| to_string = json.dumps |
| |
| |
| def main(): |
| |
| # connect to a remote server that is compatible with the Gremlin Server protocol. for those who |
| # downloaded and are using Gremlin Server directly be sure that it is running locally with: |
| # |
| # bin/gremlin-server.sh console |
| # |
| # which starts it in "console" mode with an empty in-memory TinkerGraph ready to go bound to a |
| # variable named "g" as referenced in the following line. |
| g = traversal().withRemote(DriverRemoteConnection('ws://localhost:8182/gremlin', 'g')) |
| |
| # add some data - be sure to use a terminating step like iterate() so that the traversal |
| # "executes". iterate() does not return any data and is used to just generate side-effects |
| # (i.e. write data to the database) |
| g.addV('person').property('name', 'marko').as_('m'). \ |
| addV('person').property('name', 'vadas').as_('v'). \ |
| addE('knows').from_('m').to('v').iterate() |
| |
| # retrieve the data from the "marko" vertex |
| print("marko: " + to_string(g.V().has('person', 'name', 'marko').valueMap().next())) |
| |
| # find the "marko" vertex and then traverse to the people he "knows" and return their data |
| print("who marko knows: " + to_string(g.V().has('person', 'name', 'marko').out('knows').valueMap().next())) |
| |
| |
| if __name__ == "__main__": |
| main() |