ArangoDB pyArango 的图表图 API

Question

我正在使用 ArangoDB 社区版，我可以查询 AQL 中创建的图形，并在 JSON 中获得结果，这些结果在 ArangoDB 网络界面工具上以图形方式可视化。

`AQL` 查询

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
        ]
      }
    ]
  }
]

等效图

因为我们可以在 Web 界面中获得可视化图形输出，所以我想在 Language<->ArangoDB 中显示相同的内容。这里的语言可以是支持的驱动语言：Python、Java、C#等

我正在使用 pyArango 与 ArangoDB 交互

我找不到 ArangoDB API 来获得 JPG 或 matlibplot 中的图形可视化。

除了使用以下两个选项，还有其他方法吗？

使用networkx.draw(networkx.graph)
matplotlib.pyplot

Answer 1

如果您需要图形可视化，则在内部 Graphviz library is for you. And if Python is OK then you only need a Python binding-library graphviz (that utilizes DOT language 表示。）

将您的图表 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。

这是您的样本的一个简单示例 JSON:

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()

只有 3 行代码用于自定义，还有 5 行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，您可以为每个节点设置不同的样式。

您将需要安装 graphviz 库和 Python 绑定

第 1 步：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 you can install with good old Pip:

pip install graphviz

第 3 步：运行品尝并享受

ArangoDB pyArango 的图表图 API

graph plot API for ArangoDB pyArango

python

graph

arangodb

aql

pyarango

`AQL` 查询

JSON输出

等效图

ArangoDB pyArango 的图表图 API

graph plot API for ArangoDB pyArango

python

graph

arangodb

aql

pyarango

AQL 查询

JSON输出

等效图

`AQL` 查询