Example explanation: move graph explorer to jupyterlab

This article is shared from Huawei cloud community 《

take  Graph Explorer  Move on  JupyterLab： Use  GES4Jupyter  Connect  GES  And explore the map

》, author ：  Mayfly and sea  .

GES4Jupyter  It can be used in  JupyterLab  Connect to access  GES  And visual tools . Part of the tool is encapsulated  GES  Business interface , And provide visualization of the returned data . Based on the tool in  Jupyter  Explore the map on , It can greatly reduce the coding cost , Enrich  JupyterLab  Data expressiveness .

One 、 Prepare before use

1.  Huawei cloud account

You need to register a Huawei cloud account before using Huawei cloud services . Through this account , Just pay for the services you use , You can use all Huawei cloud services .

To register a Huawei cloud account, click ：

《 Introduction to Huawei cloud registration 》

After successful registration, you can automatically log in to Huawei cloud , You need to complete  “ Real name authentication ”  The service can be used normally .

2. OBS  Object storage service

OBS  Object storage service （Object Storage Service）,GES  take  OBS  Import data as a data source .

If you want to import data into the graph engine service  GES, You need to upload to  OBS. Details refer to ：

Huawei cloud engine service  GES  actual combat —— Map creation

3. GES  Figure Engine Services

Use  GES4Jupyter  front , You need to create one in the graph engine service console  GES  Figure example , And import data . The data source used in this example is the covid-19 patient tracking data set  v2, It can be downloaded from  AI Gallery  Download . Details refer to ： Huawei graphics engine documentation  -  Quick start and Huawei cloud image engine service  GES  actual combat  ——  Map creation

4.  Get call  GES  Business  API  Required parameters

call  GES API  Need to enter  token  Authentication information , The authentication capability relies on the Huawei cloud unified identity authentication service  IAM. obtain  Token  User name and password required 、 Information such as the area where the map is located . View details ： Huawei graphics engine documentation  -  Business  API  Authentication and call  GES  Service business  API  Acquisition of relevant parameters

Two 、 Use  GES4Jupyter  Connect  GES  service

Enter from the Huawei cloud homepage  ModelArts  Console , Click on  CodeLab  Create a new one  Jupyter Notebook, And wait for resource initialization .

Create a new one  Notebook, Use the following code to get  GES4Jupyter  Program and resource files .

import moxing as mox
mox.file.copy('obs://obs-aigallery-zc/GES/ges4jupyter/beta/ges4jupyter.py', 'ges4jupyter.py')
mox.file.copy('obs://obs-aigallery-zc/GES/ges4jupyter/beta/ges4jupyter.html', 'ges4jupyter.html')

stay  Notebook  After entering the code in , Configure this text as code , Then click the run button on the left , And wait for the run to complete .

Click on the top left  “+”  No. new code snippet , Enter the following code snippet and run , complete  GES4Jupyter  The initialization .

from ges4jupyter import GESConfig, GES4Jupyter, read_csv_config
eip = ''
project_id = ''
graph_name = ''
iam_url = ''
user_name = ''
password = ''
domain_name = ''
project_name = ''
port = 80
eip, project_id, graph_name, iam_url, user_name, password, domain_name, project_name, port = read_csv_config('cn_north_4_graph.csv')
config = GESConfig(eip, project_id, graph_name, 
 iam_url = iam_url, 
 user_name = user_name, 
 password = password, 
 domain_name = domain_name,
 project_name = project_name,
 port = port)
ges_util = GES4Jupyter(config, True);

The meanings of the fields involved in the above code are basically divided into two categories , A brief introduction ：

• Is used to construct  API  Parameters of ：eip,projectId,graph_name, port  These four parameters are involved in the construction of the business face request  url.eip  And  graph_name  The two parameters are easy to obtain in drawing creation ,port  The parameter defaults to  80, When safe mode is turned on, it is  443, About  projectId, Refer to the official website of the graph engine  -  Get the project  id, Get items from the graph console according to the region to which the graph belongs  id.

• Used when requesting  API  Pre acquisition  token  Parameters of ：iam_url, user_name, password, domain_name,project_name,GES4Jupyter  These four parameters will be used to get  token, And then in use  api  To authenticate , For relevant parameters, please refer to ： Huawei graphics engine documentation  -  Business  API  Authentication and call  GES  Service business  API  Acquisition of relevant parameters

In addition to manually entering these parameters , You can also construct a parameter as  csv  Upload the file to  CodeLab  platform , Then execute the diagram  read_csv_config  Method , One click access to all parameters .

As shown in the figure, it is an example file of a figure with Beijing IV area , The key information （ Such as  ip、projectId、 Title 、 Account name 、 password 、iam  Sub account name ） Hidden by mosaics .

For the newly created graph , Use the following code snippet to create a point edge index , Easy to use  cypher：

print(' Start creating point index :')
job_id = ges_util.build_vertex_index()
job_result = ges_util.get_job(job_id)
if 'errorCode' not in job_result:
 for i in range(100):
 if job_result['status'] == 'success':
 break
 else:
 time.sleep(1)
 job_result = ges_util.get_job(job_id)
print(' Point index creation completed ')
print(' Start creating edge index :')
job_id = ges_util.build_edge_index()
job_result = ges_util.get_job(job_id)
if 'errorCode' not in job_result:
 for i in range(100):
 if job_result['status'] == 'success':
 break
 else:
 time.sleep(1)
 job_result = ges_util.get_job(job_id)
print(' Edge index creation completed ')

If it's bigger , And not based on  label  The demands of filtering , You can also turn off  cypher  Index switch of .

ges_util.cypher_query("call dbms.parameter('needNodeIndex', false)");
ges_util.cypher_query("call dbms.parameter('needEdgeIndex', false)");

perform  summary  Method to see the point edge distribution ：

3、 ... and 、 Use  GES4Jupyter  Call the business interface and visualize it

GES4Jupyter  Support calling  cypher  sentence , And visualize  cypher  Result . After initialization is complete  GES4Jupyter  after , Use the following code to execute and visualize  cypher  Inquire about ：

cypher_result = ges_util.cypher_query("match (n)-[r]->(m) return n,r,m limit 10",formats=['row','graph']);
ges_util.format_cypher_result(cypher_result)

stay  Notebook  Enter this code in , Click on the run , You can see  Notebook  Medium effect ：

meanwhile , The tool also provides additional tabs , Not only can you see the visualization  Graph  structure , You can also see the table data 、 And the original  json  data .

GES4Jupyter  It also provides the ability to  gremlin  The point and edge data returned by the language are visualized .

gremlin_result = ges_util.gremlin_query("g.V().outE().bothV().path().limit(2)");
ges_util.format_gremlin_result(gremlin_result)

meanwhile , about  ges  Of  path-query  Interface , When the returned data is  tree  When the format ,GES4Jupyter  Can also provide better support .

result = ges_util.path_query({
 "repeat": [
 {
 "operator": "bothV",
 "vertex_filter": {
 "property_filter": {
 "leftvalue": {
 "id": ""
 },
 "predicate": "NOTIN",
 "rightvalue": {
 "value": [" Beijing "]
 }
 }
 }
 }
 ],
 "until": [
 {
 "vertex_filter": {
 "property_filter": {
 "leftvalue": {
 "id": ""
 },
 "predicate": "=",
 "rightvalue": {
 "value": [" mesozoic-cenozoic "]
 }
 }
 }
 }
 ],
 "times": 5,
 "queryType": "Tree",
 "vertices": [" Beijing case 2"]
 })
ges_util.format_path_query(result)

Four 、 There are more cases available on the official website of the graph engine  GES4Jupyter  Hands on experience

The data set of this article is taken from the official website of Huawei cloud image engine  “ Trace of new crown patients ”  Data sets ,notebook  The code is taken from  “ Trace of new crown patients ”  Case study , On the official website of graph engine , There are other hands-on practices , Matching  ModelArts  Of  CodeLab, Can achieve  “ Open the box ”, Provide a wealth of scenes to get to know the map with you 、 Understanding diagram 、 Use the figure .

Reference items ：https://github.com/merqurio/neo4jupyter

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