#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2020 Alibaba Group Holding Limited. All Rights Reserved.
#
# Licensed 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.
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from graphscope.framework.app import AppAssets
from graphscope.framework.app import not_compatible_for
from graphscope.framework.app import project_to_simple
__all__ = [
"sssp",
]
[docs]@project_to_simple
@not_compatible_for("arrow_property", "dynamic_property")
def sssp(graph, src=0, weight=None):
"""Compute single source shortest path length on the `graph`.
Note that the `sssp` algorithm requires an numerical property on the edge.
Args:
graph (:class:`graphscope.Graph`): A simple graph.
src (optional): The source vertex. The type should be consistent
with the id type of the `graph`, that is, it's `int` or `str` depending
on the `oid_type` is `int64_t` or `string` of the `graph`. Defaults to 0.
weight (str, optional): The edge data key corresponding to the edge weight.
Note that property under multiple labels should have the consistent index.
Defaults to None.
Returns:
:class:`graphscope.framework.context.VertexDataContextDAGNode`:
A context with each vertex assigned with the shortest distance from the `src`,
evaluated in eager mode.
Examples:
.. code:: python
>>> import graphscope
>>> from graphscope.dataset import load_p2p_network
>>> sess = graphscope.session(cluster_type="hosts", mode="eager")
>>> g = load_p2p_network(sess)
>>> # project to a simple graph (if needed)
>>> pg = g.project(vertices={"host": ["id"]}, edges={"connect": ["dist"]})
>>> c = graphscope.sssp(pg, src=6)
>>> sess.close()
"""
return AppAssets(algo="sssp", context="vertex_data")(graph, src)