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

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

Connecting to Sage Cloud Accounting Data

Connecting to Sage Cloud Accounting 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.

You can connect to Sage Business Cloud Accounting using the embedded OAuth connectivity. When you connect, the OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

After installing the CData Sage Cloud Accounting Connector, follow the procedure below to install the other required modules and start accessing Sage Cloud Accounting 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 Sage Cloud Accounting 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.sagebcaccounting as mod

You can now connect with a connection string. Use the connect function for the CData Sage Cloud Accounting Connector to create a connection for working with Sage Cloud Accounting data.

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;")

Create a SQL Statement to Query Sage Cloud Accounting

Use SQL to create a statement for querying Sage Cloud Accounting. In this article, we read data from the SalesInvoices entity.

sql = "SELECT contact_name, total_amount FROM SalesInvoices WHERE sent = 'TRUE'"

Extract, Transform, and Load the Sage Cloud Accounting Data

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

Loading Sage Cloud Accounting Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

In the following example, we add new rows to the SalesInvoices table.

Adding New Rows to Sage Cloud Accounting

table1 = [ ['contact_name','total_amount'], ['Newcontact_name1','Newtotal_amount1'], ['Newcontact_name2','Newtotal_amount2'], ['Newcontact_name3','Newtotal_amount3'] ]

etl.appenddb(table1, cnxn, 'SalesInvoices')

With the CData Python Connector for Sage Cloud Accounting, you can work with Sage Cloud Accounting 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 Python Connector for Sage Cloud Accounting to start building Python apps and scripts with connectivity to Sage Cloud Accounting data. Reach out to our Support Team if you have any questions.

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Full Source Code

import petl as etl
import pandas as pd
import cdata.sagebcaccounting as mod

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;")

sql = "SELECT contact_name, total_amount FROM SalesInvoices WHERE sent = 'TRUE'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['contact_name','total_amount'], ['Newcontact_name1','Newtotal_amount1'], ['Newcontact_name2','Newtotal_amount2'], ['Newcontact_name3','Newtotal_amount3'] ]

etl.appenddb(table3, cnxn, 'SalesInvoices')