Extract, Transform, and Load MYOB AccountRight Data in Python

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MYOB AccountRight Python Connector

Python Connector Libraries for MYOB AccountRight Data Connectivity. Integrate MYOB AccountRight with popular Python tools like Pandas, SQLAlchemy, Dash & petl.



The CData Python Connector for MYOB AccountRight enables you to create ETL applications and pipelines for MYOB AccountRight data in Python with petl.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for MYOB AccountRight and the petl framework, you can build MYOB AccountRight-connected applications and pipelines for extracting, transforming, and loading MYOB AccountRight data. This article shows how to connect to MYOB AccountRight with the CData Python Connector and use petl and pandas to extract, transform, and load MYOB AccountRight data.

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

Connecting to MYOB AccountRight Data

Connecting to MYOB AccountRight 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.

These properties are required when connecting to a company file (both for Cloud and On-Premise instances).

  • CompanyFileId: You can find this by starting MYOB, opening your data file, and selecting Help -> About MYOB
  • User: The username associated with your company file.
  • Password: The password associated with your company file.

Connecting to a Cloud Instance

To connect to a cloud instance of MYOB, you can use the embedded OAuth credentials or create an OAuth app with MYOB. This process is detailed in the Help documentation.

Connecting to an On-Premise instance:

When connecting to an on-premise instance, you will need to set the following connection property in addition to those above:

  • InitiateOauth: Set this to OFF.
  • Url: The Url of your MYOB instance.

After installing the CData MYOB AccountRight Connector, follow the procedure below to install the other required modules and start accessing MYOB AccountRight 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 MYOB AccountRight 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.myob as mod

You can now connect with a connection string. Use the connect function for the CData MYOB AccountRight Connector to create a connection for working with MYOB AccountRight data.

cnxn = mod.connect("OAuthClientId=YourClientId; OAuthClientSecret=YourClientSecret; CompanyFileId=yourCompanyFileId; CallbackURL=http://localhost:33333; User=companyFileUser; Password=companyFilePassword; InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query MYOB AccountRight

Use SQL to create a statement for querying MYOB AccountRight. In this article, we read data from the Accounts entity.

sql = "SELECT Id, Name FROM Accounts WHERE Type = 'Bank'"

Extract, Transform, and Load the MYOB AccountRight Data

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

Loading MYOB AccountRight Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

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

Adding New Rows to MYOB AccountRight

table1 = [ ['Id','Name'], ['NewId1','NewName1'], ['NewId2','NewName2'], ['NewId3','NewName3'] ]

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

With the CData Python Connector for MYOB AccountRight, you can work with MYOB AccountRight 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 MYOB AccountRight Python Connector to start building Python apps and scripts with connectivity to MYOB AccountRight 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.myob as mod

cnxn = mod.connect("OAuthClientId=YourClientId; OAuthClientSecret=YourClientSecret; CompanyFileId=yourCompanyFileId; CallbackURL=http://localhost:33333; User=companyFileUser; Password=companyFilePassword; InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT Id, Name FROM Accounts WHERE Type = 'Bank'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['Id','Name'], ['NewId1','NewName1'], ['NewId2','NewName2'], ['NewId3','NewName3'] ]

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