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

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

Connecting to Carbone Data

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

Carbone API Profile Settings

Carbone uses API key authentication via a Bearer token in the Authorization header. To obtain an API key:

1. Log in to your Carbone account at https://account.carbone.io
2. Copy the API key shown on the account home page

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Carbone API key (Bearer token).
• CarboneVersion: (Optional) The major version of the Carbone API to target via the carbone-version request header. Defaults to 5. Accepted values: 5, 4, 3, staging.

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

cnxn = mod.connect("Profile=C:\profiles\Carbone.apip;AuthScheme=APIKey;APIKey=your_api_key;")

Create a SQL Statement to Query Carbone

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

sql = "SELECT Id, Name FROM Templates WHERE Category = 'Invoices'"

Extract, Transform, and Load the Carbone Data

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

Loading Carbone Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with Carbone 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 Carbone 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\Carbone.apip;AuthScheme=APIKey;APIKey=your_api_key;")

sql = "SELECT Id, Name FROM Templates WHERE Category = 'Invoices'"

table1 = etl.fromdb(cnxn,sql)

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

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