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docs/interactive/pages/interactive/client_apis/python_client.md

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# Python Client
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This a comprehensive guide designed to assist developers in integrating the Interactive service into their Python applications. The Python client allows users to seamlessly connect to Interactive and harness its powerful features for graph management, stored procedure management, and query execution.
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This a practical guide designed to assist developers in integrating the Interactive service into their Python applications. The Python client allows users to seamlessly connect to Interactive and harness its powerful features for graph management, stored procedure management, and query execution.
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## Requirements.
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docs/interactive/pages/interactive/visualization/data_modeling.md

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title: Visual Modeling
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---
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After creating the draft instance, we need to click on "Modeling" to enter the visual graph modeling page.
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Here, we have two ways to build the model:
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## Create Graph Model
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After creating the draft instance, we need to click on "Modeling" to enter the visual graph modeling page.
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Here, we have three ways to build the model:
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### Options 1: Manual Creation
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#### Create Vertex and Vertex Properties
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<img src="/visualization/modeling/auto_parse_3.png" />
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### Options 3: Creation from Configuration File
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Click the third button in the sidebar to upload the schema's YAML configuration file here.
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<img src="/visualization/modeling/via_config.png" />
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## Save Model
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Once the model is created and passes the system's validation, we can save the model. Here,there are two key points that <strong> require special attention:</strong>
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title: Visual Modeling
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title: Visual Importing
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---
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After creating the draft instance, we need to click on "Modeling" to enter the visual graph modeling page.
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Here, we have two ways to build the model:
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## Upload source data
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## Create Graph Model
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Once the graph model is created, we can begin importing data.there are three ways to import data:
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### Options 1: Manual Creation
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### Option 1: Manual Import
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#### Create Vertex and Vertex Properties
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Each label contains a location field. Click the "upload" button to upload the corresponding CSV file to the interactive service.
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We need to click the fourth button, "Create new vertex," in the sidebar to create a node on the canvas. The initial name of the node will be "Vertex_1.
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<img src="/visualization/importing/upload_start.png" />
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After clicking on the node, we can manually modify its label in the right-hand panel, or simply double-click the node to edit it directly on the canvas.
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<img src="/visualization/modeling/add_vertex_edit.png" />
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Upon success, a location path will be returned, indicating the data has been imported.
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Next, following the prompts, we need to complete the property information for this node. Click the "Plus" button under Properties to add attributes, and fill them out one by one.
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<img src="/visualization/modeling/add_property.png" />
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<img src="/visualization/importing/upload_end.png" />
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If we want to delete a node’s property, check the properties you wish to remove in the Checkbox area and click the delete button.
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<img src="/visualization/modeling/delete_property.png" />
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### Option 2: Automatic Import After CSV Parsing
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#### Create Edges
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This Option extends the convenience of automatic CSV modeling. During CSV parsing, the system caches the source file locally in the browser. As a result, the data can be automatically uploaded on the data loading page.
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Now let's create edges. To create an edge, hover over the edge of the starting node, then click and drag.
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<img src="/visualization/modeling/drag_start.png" />
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### Option 3: Import via Configuration File
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If the endpoint is an empty area of the canvas, a new node will automatically be created.
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<img src="/visualization/modeling/drag_end.png" />
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<img src="/visualization/importing/via_config.png" />
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If the endpoint is another existing node, an edge will be established between the two nodes.
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<img src="/visualization/modeling/drag_other_edge_end.png" />
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## Bind Data Source
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### Option 2: Parsing CSV Files for Creation
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After uploading the data, click the "data source binding" button to bind the data path to the model label. If successful, a configuration panel will appear.
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<img src="/visualization/importing/load_data.png" />
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Manually creating a graph model is particularly helpful when designing complex business models. However, when we already have some graph data, automatically deriving the graph model based on the existing data becomes a more convenient approach.
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Click "import" to proceed to the job page.
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Note: There are two constraints for the CSV files here:
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## Verify Results
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- Each CSV file, by default, represents one type of label. The file name should ideally be the label name, such as person.csv.
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- The CSV file must include a header row.
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At this point, validate the data on the query page. We will cover this in detail in the next chapter. Let’s move on to the next chapter!
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When the above two requirements are met, we can utilize the "Automatic Parsing and Modeling" feature provided by GraphScope Portal, which is located in the second option of the right-hand sidebar.
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<img src="/visualization/modeling/auto_parse_1.png" />
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After uploading the data, we only need to verify each CSV file to ensure that the automatically inferred node and edge types are accurate.
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<img src="/visualization/modeling/auto_parse_2.png" />
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Once confirmed, we can click "Generate Graph Model" , and the system will automatically derive the graph model.
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<img src="/visualization/modeling/auto_parse_3.png" />
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## Save Model
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Once the model is created and passes the system's validation, we can save the model. Here,there are two key points that <strong> require special attention:</strong>
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> - Each `vertex label` must have a `primary key` in its properties, and each `edge label` can only have one property field.
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> - <span style='color:red'>The `GraphScope Interactive` engine does not support modifications to the graph model. If you need to modify the graph model, you must create a new graph instance.</span>
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<img src="/visualization/modeling/save_model.png" />
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Now, let's goto importing page
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<img src="/visualization/importing/test_query.png" />
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