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

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

Connecting to PhantomBuster Data

Connecting to PhantomBuster 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.

Using API Key Authentication

To use the Phantombuster API, you need to obtain an API key from your Phantombuster account settings. Navigate to phantombuster.com, click your profile icon, select Settings, and copy the API key from the API section.

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

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Phantombuster API key from the account settings page.

Multi-Organization Accounts

If your API key is associated with multiple organizations, you can target a specific organization by setting the OrganizationId connection property to the desired organization identifier. When set, it is sent as the X-Phantombuster-Org request header.

Example connection string:

Profile=C:\profiles\Phantombuster.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key_here"

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

cnxn = mod.connect("Profile=C:\profiles\Phantombuster.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key_here"")

Create a SQL Statement to Query PhantomBuster

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

sql = "SELECT ,  FROM Agents WHERE  = ''"

Extract, Transform, and Load the PhantomBuster Data

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

Loading PhantomBuster Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData API Driver for Python, you can work with PhantomBuster 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 PhantomBuster 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\Phantombuster.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key_here"")

sql = "SELECT ,  FROM Agents WHERE  = ''"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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