Skip to content

Latest commit

 

History

History
243 lines (158 loc) · 11.5 KB

create-graph-python.md

File metadata and controls

243 lines (158 loc) · 11.5 KB
title description author ms.service ms.subservice ms.devlang ms.topic ms.date ms.author ms.custom
Quickstart: Gremlin API with Python - Azure Cosmos DB
This quickstart shows how to use the Azure Cosmos DB Gremlin API to create a console application with the Azure portal and Python
jasonwhowell
cosmos-db
cosmosdb-graph
python
quickstart
01/22/2019
jasonh
devx-track-python

Quickstart: Create a graph database in Azure Cosmos DB using Python and the Azure portal

[!div class="op_single_selector"]

In this quickstart, you create and manage an Azure Cosmos DB Gremlin (graph) API account from the Azure portal, and add data by using a Python app cloned from GitHub. Azure Cosmos DB is a multi-model database service that lets you quickly create and query document, table, key-value, and graph databases with global distribution and horizontal scale capabilities.

Prerequisites

Note

This quickstart requires a graph database account created after December 20th, 2017. Existing accounts will support Python once they’re migrated to general availability.

Create a database account

Before you can create a graph database, you need to create a Gremlin (Graph) database account with Azure Cosmos DB.

[!INCLUDE cosmos-db-create-dbaccount-graph]

Add a graph

[!INCLUDE cosmos-db-create-graph]

Clone the sample application

Now let's switch to working with code. Let's clone a Gremlin API app from GitHub, set the connection string, and run it. You'll see how easy it is to work with data programmatically.

  1. Open a command prompt, create a new folder named git-samples, then close the command prompt.

    md "C:\git-samples"

  2. Open a git terminal window, such as git bash, and use the cd command to change to a folder to install the sample app.

    cd "C:\git-samples"

  3. Run the following command to clone the sample repository. This command creates a copy of the sample app on your computer.

    git clone https://github.com/Azure-Samples/azure-cosmos-db-graph-python-getting-started.git

Review the code

This step is optional. If you're interested in learning how the database resources are created in the code, you can review the following snippets. The snippets are all taken from the connect.py file in the C:\git-samples\azure-cosmos-db-graph-python-getting-started\ folder. Otherwise, you can skip ahead to Update your connection string.

  • The Gremlin client is initialized in line 104 in connect.py:

    ...
client = client.Client('wss://<YOUR_ENDPOINT>.gremlin.cosmosdb.azure.com:443/','g', 
    username="/dbs/<YOUR_DATABASE>/colls/<YOUR_COLLECTION_OR_GRAPH>", 
    password="<YOUR_PASSWORD>")
...

  • A series of Gremlin steps are declared at the beginning of the connect.py file. They are then executed using the client.submitAsync() method:

    client.submitAsync(_gremlin_cleanup_graph)

Update your connection information

Now go back to the Azure portal to get your connection information and copy it into the app. These settings enable your app to communicate with your hosted database.

  1. In your Azure Cosmos DB account in the Azure portal, select Keys.

    Copy the first portion of the URI value.

    :::image type="content" source="./media/create-graph-python/keys.png" alt-text="View and copy an access key in the Azure portal, Keys page":::

  2. Open the connect.py file and in line 104 paste the URI value over <YOUR_ENDPOINT> in here:

    client = client.Client('wss://<YOUR_ENDPOINT>.gremlin.cosmosdb.azure.com:443/','g', 
    username="/dbs/<YOUR_DATABASE>/colls/<YOUR_COLLECTION_OR_GRAPH>", 
    password="<YOUR_PASSWORD>")

    The URI portion of the client object should now look similar to this code:

    client = client.Client('wss://test.gremlin.cosmosdb.azure.com:443/','g', 
    username="/dbs/<YOUR_DATABASE>/colls/<YOUR_COLLECTION_OR_GRAPH>", 
    password="<YOUR_PASSWORD>")

  3. Change the second parameter of the client object to replace the <YOUR_DATABASE> and <YOUR_COLLECTION_OR_GRAPH> strings. If you used the suggested values, the parameter should look like this code:

    username="/dbs/sample-database/colls/sample-graph"

    The entire client object should now look like this code:

    client = client.Client('wss://test.gremlin.cosmosdb.azure.com:443/','g', 
    username="/dbs/sample-database/colls/sample-graph", 
    password="<YOUR_PASSWORD>")

  4. On the Keys page, use the copy button to copy the PRIMARY KEY and paste it over <YOUR_PASSWORD> in the password=<YOUR_PASSWORD> parameter.

    The entire client object definition should now look like this code:

    client = client.Client('wss://test.gremlin.cosmosdb.azure.com:443/','g', 
    username="/dbs/sample-database/colls/sample-graph", 
    password="asdb13Fadsf14FASc22Ggkr662ifxz2Mg==")

  5. Save the connect.py file.

Run the console app

  1. In the git terminal window, cd to the azure-cosmos-db-graph-python-getting-started folder.

    cd "C:\git-samples\azure-cosmos-db-graph-python-getting-started"

  2. In the git terminal window, use the following command to install the required Python packages.

    pip install -r requirements.txt

  3. In the git terminal window, use the following command to start the Python application.

    python connect.py

    The terminal window displays the vertices and edges being added to the graph.

    If you experience timeout errors, check that you updated the connection information correctly in Update your connection information, and also try running the last command again.

    Once the program stops, press Enter, then switch back to the Azure portal in your internet browser.

Review and add sample data

After the vertices and edges are inserted, you can now go back to Data Explorer and see the vertices added to the graph, and add additional data points.

  1. In your Azure Cosmos DB account in the Azure portal, select Data Explorer, expand sample-graph, select Graph, and then select Apply Filter.

    :::image type="content" source="./media/create-graph-python/azure-cosmosdb-data-explorer-expanded.png" alt-text="Create new documents in Data Explorer in the Azure portal":::

  2. In the Results list, notice three new users are added to the graph. You can move the vertices around by dragging and dropping, zoom in and out by scrolling the wheel of your mouse, and expand the size of the graph with the double-arrow.

    :::image type="content" source="./media/create-graph-python/azure-cosmosdb-graph-explorer-new.png" alt-text="New vertices in the graph in Data Explorer in the Azure portal":::

  3. Let's add a few new users. Select the New Vertex button to add data to your graph.

    :::image type="content" source="./media/create-graph-python/azure-cosmosdb-data-explorer-new-vertex.png" alt-text="Create new documents in Data Explorer in the Azure portal":::

  4. Enter a label of person.

  5. Select Add property to add each of the following properties. Notice that you can create unique properties for each person in your graph. Only the id key is required.

    key value Notes
    pk /pk
    id ashley The unique identifier for the vertex. If you don't specify an id, one is generated for you.
    gender female
    tech java

    [!NOTE] In this quickstart create a non-partitioned collection. However, if you create a partitioned collection by specifying a partition key during the collection creation, then you need to include the partition key as a key in each new vertex.

  6. Select OK. You may need to expand your screen to see OK on the bottom of the screen.

  7. Select New Vertex again and add an additional new user.

  8. Enter a label of person.

  9. Select Add property to add each of the following properties:

    key value Notes
    pk /pk
    id rakesh The unique identifier for the vertex. If you don't specify an id, one is generated for you.
    gender male
    school MIT

  10. Select OK.

  11. Select the Apply Filter button with the default g.V() filter to display all the values in the graph. All of the users now show in the Results list.

    As you add more data, you can use filters to limit your results. By default, Data Explorer uses g.V() to retrieve all vertices in a graph. You can change it to a different graph query, such as g.V().count(), to return a count of all the vertices in the graph in JSON format. If you changed the filter, change the filter back to g.V() and select Apply Filter to display all the results again.

  12. Now we can connect rakesh and ashley. Ensure ashley is selected in the Results list, then select the edit button next to Targets on lower right side. You may need to widen your window to see the Properties area.

    :::image type="content" source="./media/create-graph-python/azure-cosmosdb-data-explorer-edit-target.png" alt-text="Change the target of a vertex in a graph":::

  13. In the Target box type rakesh, and in the Edge label box type knows, and then select the check.

    :::image type="content" source="./media/create-graph-python/azure-cosmosdb-data-explorer-set-target.png" alt-text="Add a connection between ashley and rakesh in Data Explorer":::

  14. Now select rakesh from the results list and see that ashley and rakesh are connected.

    :::image type="content" source="./media/create-graph-python/azure-cosmosdb-graph-explorer.png" alt-text="Two vertices connected in Data Explorer":::

That completes the resource creation part of this tutorial. You can continue to add vertexes to your graph, modify the existing vertexes, or change the queries. Now let's review the metrics Azure Cosmos DB provides, and then clean up the resources.

Review SLAs in the Azure portal

[!INCLUDE cosmosdb-tutorial-review-slas]

Clean up resources

[!INCLUDE cosmosdb-delete-resource-group]

Next steps

In this quickstart, you learned how to create an Azure Cosmos DB account, create a graph using the Data Explorer, and run a Python app to add data to the graph. You can now build more complex queries and implement powerful graph traversal logic using Gremlin.

[!div class="nextstepaction"] Query using Gremlin