PyGraphistry <> Titan 图

在本笔记本中，我们演示了如何在python中创建和修改Titan图，然后使用Graphistry的可视化图探索器来可视化结果。

我们假设我们的Titan图的gremlin服务器在本地端口8182上托管

• 本笔记本使用了python模块aiogremlin和asyncio。

• aiogremlin的GremlinClient类通过asyncio协程使用websockets与gremlin服务器进行异步通信。

• 此实现允许您在收到任何响应之前向服务器提交额外的请求，这比同步请求/响应周期要快得多。

• 有关这些模块的更多信息，请访问：

  • aiogremlin: http://aiogremlin.readthedocs.org/en/latest/index.html

  • asyncio: https://pypi.python.org/pypi/asyncio

import asyncio
import aiogremlin

# Create event loop and initialize gremlin client
loop = asyncio.get_event_loop()
client = aiogremlin.GremlinClient(url='ws://localhost:8182/', loop=loop)  # Default url

用于图形修改的函数

@asyncio.coroutine
def add_vertex_routine(name, label):
    yield from client.execute("graph.addVertex(label, l, 'name', n)", bindings={"l":label, "n":name})

def add_vertex(name, label):
    loop.run_until_complete(add_vertex_routine(name, label))

@asyncio.coroutine
def add_relationship_routine(who, relationship, whom):
    yield from client.execute("g.V().has('name', p1).next().addEdge(r, g.V().has('name', p2).next())", bindings={"p1":who, "p2":whom, "r":relationship})

def add_relationship(who, relationship, whom):
    loop.run_until_complete(add_relationship_routine(who, relationship, whom))

@asyncio.coroutine
def remove_all_vertices_routine():
    resp = yield from client.submit("g.V()")
    results = []
    while True:
        msg = yield from resp.stream.read();
        if msg is None:
            break
        if msg.data is None:
            break
        for vertex in msg.data:
            yield from client.submit("g.V(" + str(vertex['id']) + ").next().remove()")

def remove_all_vertices():
    results = loop.run_until_complete(remove_all_vertices_routine())

@asyncio.coroutine
def remove_vertex_routine(name):
    return client.execute("g.V().has('name', n).next().remove()", bindings={"n":name})

def remove_vertex(name):
    return loop.run_until_complete(remove_vertex_routine(name));

将图转换为节点和边列表的函数:

- Currently, our API can only upload data from a pandas DataFrame, but we plan to implement more flexible uploads in the future.
- For now, we can rely on the following functions to create the necessary DataFrames from our graph.

@asyncio.coroutine
def get_node_list_routine():
    resp = yield from client.submit("g.V().as('node')\
                          .label().as('type')\
                          .select('node').values('name').as('name')\
                          .select('name', 'type')")
    results = [];
    while True:
        msg = yield from resp.stream.read();
        if msg is None:
            break;
        if msg.data is None:
            break;
        else:
            results.extend(msg.data)
    return results

def get_node_list():
    results =  loop.run_until_complete(get_node_list_routine())
    return results

@asyncio.coroutine
def get_edge_list_routine():
    resp = yield from client.submit("g.E().as('edge')\
                          .label().as('relationship')\
                          .select('edge').outV().values('name').as('source')\
                          .select('edge').inV().values('name').as('dest')\
                          .select('source', 'relationship', 'dest')")

    results = [];
    while True:
        msg = yield from resp.stream.read();
        if msg is None:
            break;
        if msg.data is None:
            break;
        else:
            results.extend(msg.data)
    return results
def get_edge_list():
    results =  loop.run_until_complete(get_edge_list_routine())
    return results

让我们从一个空图开始：

remove_all_vertices()

然后用Graphistry团队成员和他们的一些关系填充它：

add_vertex("Paden", "Person")
add_vertex("Thibaud", "Person")
add_vertex("Leo", "Person")
add_vertex("Matt", "Person")
add_vertex("Brian", "Person")
add_vertex("Quinn", "Person")
add_vertex("Paul", "Person")
add_vertex("Lee", "Person")

add_vertex("San Francisco", "Place")
add_vertex("Oakland", "Place")
add_vertex("Berkeley", "Place")

add_vertex("Turkey", "Thing")
add_vertex("Rocks", "Thing")
add_vertex("Motorcycles", "Thing")

add_relationship("Paden", "lives in", "Oakland")
add_relationship("Quinn", "lives in", "Oakland")
add_relationship("Thibaud", "lives in", "Berkeley")
add_relationship("Matt", "lives in", "Berkeley")
add_relationship("Leo", "lives in", "San Francisco")
add_relationship("Paul", "lives in", "San Francisco")
add_relationship("Brian", "lives in", "Oakland")

add_relationship("Paden", "eats", "Turkey")
add_relationship("Quinn", "cooks", "Turkey")
add_relationship("Thibaud", "climbs", "Rocks")
add_relationship("Matt", "climbs", "Rocks")
add_relationship("Brian", "rides", "Motorcycles")

add_vertex("Graphistry", "Work")

add_relationship("Paden", "works at", "Graphistry")
add_relationship("Thibaud", "works at", "Graphistry")
add_relationship("Matt", "co-founded", "Graphistry")
add_relationship("Leo", "co-founded", "Graphistry")
add_relationship("Paul", "works at", "Graphistry")
add_relationship("Quinn", "works at", "Graphistry")
add_relationship("Brian", "works at", "Graphistry")

现在，让我们将我们的图数据库转换为pandas DataFrame，以便可以上传到我们的工具中：

import pandas

nodes = pandas.DataFrame(get_node_list())
edges = pandas.DataFrame(get_edge_list())

根据节点的“type”属性为节点着色：

# Assign different color to each type in a round robin fashion.
# For more information and coloring options please visit: https://graphistry.github.io/docs/legacy/api/0.9.2/api.html
unique_types = list(nodes['type'].unique())
nodes['color'] = nodes['type'].apply(lambda x: unique_types.index(x) % 11)

nodes

	name	type	color
0	Paden	Person	0
1	Quinn	Person	0
2	Turkey	Thing	1
3	Thibaud	Person	0
4	Matt	Person	0
5	Leo	Person	0
6	Berkeley	Place	2
7	Rocks	Thing	1
8	Motorcycles	Thing	1
9	Graphistry	Work	3
10	Lee	Person	0
11	Oakland	Place	2
12	Brian	Person	0
13	Paul	Person	0
14	San Francisco	Place	2

edges

	dest	relationship	source
0	Oakland	lives in	Paden
1	Turkey	eats	Paden
2	Graphistry	works at	Paden
3	Oakland	lives in	Quinn
4	Turkey	cooks	Quinn
5	Graphistry	works at	Quinn
6	Berkeley	lives in	Thibaud
7	Rocks	climbs	Thibaud
8	Graphistry	works at	Thibaud
9	Berkeley	lives in	Matt
10	Rocks	climbs	Matt
11	Graphistry	co-founded	Matt
12	San Francisco	lives in	Leo
13	Graphistry	co-founded	Leo
14	Oakland	lives in	Brian
15	Motorcycles	rides	Brian
16	Graphistry	works at	Brian
17	San Francisco	lives in	Paul
18	Graphistry	works at	Paul

最后，让我们可视化结果！

import graphistry

# To specify Graphistry account & server, use:
# graphistry.register(api=3, username='...', password='...', protocol='https', server='hub.graphistry.com')
# For more options, see https://github.com/graphistry/pygraphistry#configure

g = graphistry.bind(source="source", destination="dest", node='name', point_color='color', edge_title='relationship')
g.plot(edges, nodes)