How to Build an ETL App for CleverPush 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 CleverPush-connected applications and pipelines for extracting, transforming, and loading CleverPush data. This article shows how to connect to CleverPush with the CData Python Connector and use petl and pandas to extract, transform, and load CleverPush data.

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

Connecting to CleverPush Data

Connecting to CleverPush 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 Cleverpush Profile on disk (e.g. C:\profiles\Cleverpush.apip). Next, set the ProfileSettings connection property to the connection string for Cleverpush (see below).

Cleverpush API Profile Settings

CleverPush uses private API keys to authenticate requests. Your API key is passed as the Authorization request header value on every API call.

You can find your private API key in the CleverPush dashboard under Settings > API. Use the private key (not the public key) for server-side access.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your CleverPush private API key.

Optional Connection Properties

• ChannelId: Set this to your default CleverPush channel identifier. Most tables require a channel filter. Setting this property allows queries without specifying ChannelId in every WHERE clause.

After installing the CData CleverPush Connector, follow the procedure below to install the other required modules and start accessing CleverPush 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 CleverPush 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 CleverPush Connector to create a connection for working with CleverPush data.

cnxn = mod.connect("Profile=C:\profiles\Cleverpush.apip;ProfileSettings='APIKey=my_api_key';")

Create a SQL Statement to Query CleverPush

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

sql = "SELECT Id, Name FROM Segments WHERE ChannelId = 'your_channel_id'"

Extract, Transform, and Load the CleverPush Data

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

Loading CleverPush Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with CleverPush 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 CleverPush 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\Cleverpush.apip;ProfileSettings='APIKey=my_api_key';")

sql = "SELECT Id, Name FROM Segments WHERE ChannelId = 'your_channel_id'"

table1 = etl.fromdb(cnxn,sql)

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

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