How to Build an ETL App for ZohoMarketingHub 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 API Driver for Python and the petl framework, you can build ZohoMarketingHub-connected applications and pipelines for extracting, transforming, and loading ZohoMarketingHub data. This article shows how to connect to ZohoMarketingHub with the CData Python Connector and use petl and pandas to extract, transform, and load ZohoMarketingHub data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live ZohoMarketingHub data in Python. When you issue complex SQL queries from ZohoMarketingHub, the driver pushes supported SQL operations, like filters and aggregations, directly to ZohoMarketingHub and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to ZohoMarketingHub Data
Connecting to ZohoMarketingHub 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.
Start by setting the Profile connection property to the location of the ZohoMarketingHub Profile on disk (e.g. C:\profiles\ZohoMarketingHub.apip). Next, set the ProfileSettings connection property to the connection string for ZohoMarketingHub (see below).
ZohoMarketingHub API Profile Settings
Register an OAuth application in the Zoho Developer Console as a server-based application to obtain your Client ID and Client Secret.
After installing the CData ZohoMarketingHub Connector, follow the procedure below to install the other required modules and start accessing ZohoMarketingHub 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 ZohoMarketingHub 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.api as mod
You can now connect with a connection string. Use the connect function for the CData ZohoMarketingHub Connector to create a connection for working with ZohoMarketingHub data.
cnxn = mod.connect("Profile=C:\profiles\ZohoMarketingHub.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")
Create a SQL Statement to Query ZohoMarketingHub
Use SQL to create a statement for querying ZohoMarketingHub. In this article, we read data from the CampaignDetails entity.
sql = "SELECT CampaignKey, CampaignName FROM CampaignDetails WHERE CampaignName = 'Q4_Sales_Campaign'"
Extract, Transform, and Load the ZohoMarketingHub Data
With the query results stored in a DataFrame, we can use petl to extract, transform, and load the ZohoMarketingHub data. In this example, we extract ZohoMarketingHub data, sort the data by the CampaignName column, and load the data into a CSV file.
Loading ZohoMarketingHub Data into a CSV File
table1 = etl.fromdb(cnxn,sql) table2 = etl.sort(table1,'CampaignName') etl.tocsv(table2,'campaigndetails_data.csv')
With the CData API Driver for Python, you can work with ZohoMarketingHub 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 API Driver for Python to start building Python apps and scripts with connectivity to ZohoMarketingHub 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.api as mod
cnxn = mod.connect("Profile=C:\profiles\ZohoMarketingHub.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")
sql = "SELECT CampaignKey, CampaignName FROM CampaignDetails WHERE CampaignName = 'Q4_Sales_Campaign'"
table1 = etl.fromdb(cnxn,sql)
table2 = etl.sort(table1,'CampaignName')
etl.tocsv(table2,'campaigndetails_data.csv')