How to Build an ETL App for HubDB Data in Python with CData

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for HubDB and the petl framework, you can build HubDB-connected applications and pipelines for extracting, transforming, and loading HubDB data. This article shows how to connect to HubDB with the CData Python Connector and use petl and pandas to extract, transform, and load HubDB data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live HubDB data in Python. When you issue complex SQL queries from HubDB, the driver pushes supported SQL operations, like filters and aggregations, directly to HubDB and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to HubDB Data

Connecting to HubDB data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

There are two authentication methods available for connecting to HubDB data source: OAuth Authentication with a public HubSpot application and authentication with a Private application token.

Using a Custom OAuth App

AuthScheme must be set to "OAuth" in all OAuth flows. Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

Follow the steps below to register an application and obtain the OAuth client credentials:

1. Log into your HubSpot app developer account.
   • Note that it must be an app developer account. Standard HubSpot accounts cannot create public apps.
2. On the developer account home page, click the Apps tab.
3. Click Create app.
4. On the App info tab, enter and optionally modify values that are displayed to users when they connect. These values include the public application name, application logo, and a description of the application.
5. On the Auth tab, supply a callback URL in the "Redirect URLs" box.
   • If you're creating a desktop application, set this to a locally accessible URL like http://localhost:33333.
   • If you are creating a Web application, set this to a trusted URL where you want users to be redirected to when they authorize your application.
6. Click Create App. HubSpot then generates the application, along with its associated credentials.
7. On the Auth tab, note the Client ID and Client secret. You will use these later to configure the driver.

8. Under Scopes, select any scopes you need for your application's intended functionality.

   A minimum of the following scopes is required to access tables:

   • hubdb
   • oauth
   • crm.objects.owners.read
9. Click Save changes.
10. Install the application into a production portal with access to the features that are required by the integration.
    • Under "Install URL (OAuth)", click Copy full URL to copy the installation URL for your application.
    • Navigate to the copied link in your browser. Select a standard account in which to install the application.
    • Click Connect app. You can close the resulting tab.

Using a Private App

To connect using a HubSpot private application token, set the AuthScheme property to "PrivateApp."

You can generate a private application token by following the steps below:

1. In your HubDB account, click the settings icon (the gear) in the main navigation bar.
2. In the left sidebar menu, navigate to Integrations > Private Apps.
3. Click Create private app.
4. On the Basic Info tab, configure the details of your application (name, logo, and description).
5. On the Scopes tab, select Read or Write for each scope you want your private application to be able to access.
6. A minimum of hubdb and crm.objects.owners.read is required to access tables.
7. After you are done configuring your application, click Create app in the top right.
8. Review the info about your application's access token, click Continue creating, and then Show token.
9. Click Copy to copy the private application token.

To connect, set PrivateAppToken to the private application token you retrieved.

After installing the CData HubDB Connector, follow the procedure below to install the other required modules and start accessing HubDB through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for HubDB Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.hubdb as mod

You can now connect with a connection string. Use the connect function for the CData HubDB Connector to create a connection for working with HubDB data.

cnxn = mod.connect("AuthScheme=OAuth;OAuthClientID=MyOAuthClientID;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query HubDB

Use SQL to create a statement for querying HubDB. In this article, we read data from the NorthwindProducts entity.

sql = "SELECT PartitionKey, Name FROM NorthwindProducts WHERE Id = '1'"

Extract, Transform, and Load the HubDB Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the HubDB data. In this example, we extract HubDB data, sort the data by the Name column, and load the data into a CSV file.

Loading HubDB Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'northwindproducts_data.csv')

In the following example, we add new rows to the NorthwindProducts table.

Adding New Rows to HubDB

table1 = [ ['PartitionKey','Name'], ['NewPartitionKey1','NewName1'], ['NewPartitionKey2','NewName2'], ['NewPartitionKey3','NewName3'] ]

etl.appenddb(table1, cnxn, 'NorthwindProducts')

With the CData Python Connector for HubDB, you can work with HubDB data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for HubDB to start building Python apps and scripts with connectivity to HubDB data. Reach out to our Support Team if you have any questions.

Full Source Code

import petl as etl
import pandas as pd
import cdata.hubdb as mod

cnxn = mod.connect("AuthScheme=OAuth;OAuthClientID=MyOAuthClientID;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT PartitionKey, Name FROM NorthwindProducts WHERE Id = '1'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'northwindproducts_data.csv')

table3 = [ ['PartitionKey','Name'], ['NewPartitionKey1','NewName1'], ['NewPartitionKey2','NewName2'], ['NewPartitionKey3','NewName3'] ]

etl.appenddb(table3, cnxn, 'NorthwindProducts')