ArangoDB 的图表 API pyArango
Pra*_*eek 5 python graph arangodb aql pyarango
我正在使用 ArangoDB 社区版，我可以查询创建的图表AQL并获取 JSON 格式的结果，该结果在 ArangoDB Web 界面工具上以图形方式可视化。
AQL询问
FOR v,e,p IN 1..3 OUTBOUND 'germanCity/Hamburg' GRAPH 'routeplanner'
OPTIONS{bfs :true}
RETURN p
JSON 输出
[
{
"edges": [
{
"_key": "6392826",
"_id": "germanHighway/6392826",
"_from": "germanCity/Hamburg",
"_to": "germanCity/Cologne",
"_rev": "_WmZ77pW--D",
"distance": 500
}
],
"vertices": [
{
"_key": "Hamburg",
"_id": "germanCity/Hamburg",
"_rev": "_WmZ77Z---_",
"population": 1000000,
"isCapital": false,
"loc": [
53.5653,
10.0014
]
},
{
"_key": "Cologne",
"_id": "germanCity/Cologne",
"_rev": "_WmZ77Y6--B",
"population": 1000000,
"isCapital": false,
"loc": [
50.9364,
6.9528
]
}
]
},
{
"edges": [
{
"_key": "6392840",
"_id": "internationalHighway/6392840",
"_from": "germanCity/Hamburg",
"_to": "frenchCity/Paris",
"_rev": "_WmZ77pa--_",
"distance": 900
}
],
"vertices": [
{
"_key": "Hamburg",
"_id": "germanCity/Hamburg",
"_rev": "_WmZ77Z---_",
"population": 1000000,
"isCapital": false,
"loc": [
53.5653,
10.0014
]
},
{
"_key": "Paris",
"_id": "frenchCity/Paris",
"_rev": "_WmZ77Z---D",
"population": 4000000,
"isCapital": true,
"loc": [
48.8567,
2.3508
]
}
]
},
{
"edges": [
{
"_key": "6392843",
"_id": "internationalHighway/6392843",
"_from": "germanCity/Hamburg",
"_to": "frenchCity/Lyon",
"_rev": "_WmZ77pa--B",
"distance": 1300
}
],
"vertices": [
{
"_key": "Hamburg",
"_id": "germanCity/Hamburg",
"_rev": "_WmZ77Z---_",
"population": 1000000,
"isCapital": false,
"loc": [
53.5653,
10.0014
]
},
{
"_key": "Lyon",
"_id": "frenchCity/Lyon",
"_rev": "_WmZ77Z---B",
"population": 80000,
"isCapital": false,
"loc": [
45.76,
4.84
]
}
]
}
]
等价图
由于我们可以在 Web 界面中获得可视化图形输出，因此我想在 Language<->ArangoDB 中显示相同的结果。这里的语言可以是驱动程序支持的语言：Python、Java、C# 等。
我用于pyArango与 ArangoDB 连接
我找不到 ArangoDB API 来获取 JPG 或 matlibplot 中的图形可视化。
除了使用以下两个选项之外还有其他方法吗？
- 使用
networkx.draw(networkx.graph) matplotlib.pyplot
如果您需要图形可视化，那么Graphviz库适合您。如果 Python 没问题，那么你只需要一个 Python 绑定库graphviz（内部使用DOT 语言表示）。
将图形 JSON 从 Arango DB 提供给 graphviz 进行渲染非常容易。
您可以根据自己的风格对其进行自定义，添加标签、颜色、重塑节点等等。
以下是示例 JSON 的简单示例：
from graphviz import Digraph
arango_graph = [
{
"edges": [
{
"_key": "6392826",
"_id": "germanHighway/6392826",
"_from": "germanCity/Hamburg",
"_to": "germanCity/Cologne",
"_rev": "_WmZ77pW--D",
"distance": 500
}
],
"vertices": [
{
"_key": "Hamburg",
"_id": "germanCity/Hamburg",
"_rev": "_WmZ77Z---_",
"population": 1000000,
"isCapital": False,
"loc": [
53.5653,
10.0014
]
},
{
"_key": "Cologne",
"_id": "germanCity/Cologne",
"_rev": "_WmZ77Y6--B",
"population": 1000000,
"isCapital": False,
"loc": [
50.9364,
6.9528
]
}
]
},
{
"edges": [
{
"_key": "6392840",
"_id": "internationalHighway/6392840",
"_from": "germanCity/Hamburg",
"_to": "frenchCity/Paris",
"_rev": "_WmZ77pa--_",
"distance": 900
}
],
"vertices": [
{
"_key": "Hamburg",
"_id": "germanCity/Hamburg",
"_rev": "_WmZ77Z---_",
"population": 1000000,
"isCapital": False,
"loc": [
53.5653,
10.0014
]
},
{
"_key": "Paris",
"_id": "frenchCity/Paris",
"_rev": "_WmZ77Z---D",
"population": 4000000,
"isCapital": True,
"loc": [
48.8567,
2.3508
]
}
]
},
{
"edges": [
{
"_key": "6392843",
"_id": "internationalHighway/6392843",
"_from": "germanCity/Hamburg",
"_to": "frenchCity/Lyon",
"_rev": "_WmZ77pa--B",
"distance": 1300
}
],
"vertices": [
{
"_key": "Hamburg",
"_id": "germanCity/Hamburg",
"_rev": "_WmZ77Z---_",
"population": 1000000,
"isCapital": False,
"loc": [
53.5653,
10.0014
]
},
{
"_key": "Lyon",
"_id": "frenchCity/Lyon",
"_rev": "_WmZ77Z---B",
"population": 80000,
"isCapital": False,
"loc": [
45.76,
4.84
]
}
]
}
]
graph_name = 'amazing'
g = Digraph(graph_name, filename=graph_name, format='jpeg', engine='neato')
g.attr(scale='2', label='Look at my graph my graph is amazing!', fontsize='18')
g.attr('node', shape='circle', fixedsize='true', width='1')
for item in arango_graph:
for vertex in item['vertices']:
g.node(vertex['_id'], label=vertex['_key'])
for edge in item['edges']:
g.edge(edge['_from'], edge['_to'], label=str(edge['distance']))
# Render to file into some directory
g.render(directory='/tmp/', filename=graph_name)
# Or just show rendered file using system default program
g.view()
只需 3 行代码用于自定义，另外 5 行代码用于提供图形可视化渲染器。请注意，Arango Web UI 不会渲染同一对节点之间的所有边，而 graphviz 会渲染，并且您可以对每个节点设置不同的样式。
您需要安装graphviz库和 Python 绑定
步骤#1：安装库
假设你的机器是 Ubuntu：
sudo apt install graphviz
步骤#2：获取 Python 绑定
pipenv install graphviz
如果您还没有使用Pipenv，您可以使用旧的Pip进行安装：
pip install graphviz
步骤#3：运行示例并享受
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