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

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

Connecting to Factorial Data

Connecting to Factorial 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.

Authentication

Factorial uses OAuth 2.0 for authentication to connect to your HR data or to allow other users to connect to their data.

Using OAuth Authentication

To connect using OAuth, follow these steps:

1. Navigate to your Factorial admin panel and create a new OAuth application.
2. Copy the Client ID and Client Secret from your application configuration.
3. Configure the following connection properties:

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

• AuthScheme: Set this to OAuth.
• OAuthClientId: Set this to your OAuth Client ID.
• OAuthClientSecret: Set this to your OAuth Client Secret.
• Scope: Set this to specify the data access permissions (default: "read write").

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

cnxn = mod.connect("Profile=C:\profiles\Factorial.apip;AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

Create a SQL Statement to Query Factorial

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

sql = "SELECT ,  FROM Agreements WHERE ProcessId = '123'"

Extract, Transform, and Load the Factorial Data

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

Loading Factorial Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData API Driver for Python, you can work with Factorial 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 Factorial 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\Factorial.apip;AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

sql = "SELECT ,  FROM Agreements WHERE ProcessId = '123'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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