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Extract, Transform, and Load Dynamics 365 Business Central Data in Python

The CData Python Connector for Dynamics 365 Business Central enables you to create ETL applications and pipelines for Dynamics 365 Business Central 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 Dynamics 365 Business Central and the petl framework, you can build Dynamics 365 Business Central-connected applications and pipelines for extracting, transforming, and loading Dynamics 365 Business Central data. This article shows how to connect to Dynamics 365 Business Central with the CData Python Connector and use petl and pandas to extract, transform, and load Dynamics 365 Business Central data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Dynamics 365 Business Central data in Python. When you issue complex SQL queries from Dynamics 365 Business Central, the driver pushes supported SQL operations, like filters and aggregations, directly to Dynamics 365 Business Central and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Dynamics 365 Business Central Data

Connecting to Dynamics 365 Business Central 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.

To authenticate to Dynamics 365 Business Central, you must provide the User and AccessKey properties.

To obtain the User and AccessKey values, navigate to the Users page in Dynamics 365 Business Central and then click on Edit. The User Name and Web Service Access Key values are what you will enter as the User and AccessKey connection string properties. Note that the User Name is not your email address. It is a shortened user name.

To connect to data, specify OrganizationUrl. If you have multiple companies in your organization, you must also specify the Company to indicate which company you would like to connect to. Company does not need to be specified if you have only one company.

After installing the CData Dynamics 365 Business Central Connector, follow the procedure below to install the other required modules and start accessing Dynamics 365 Business Central 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 Dynamics 365 Business Central 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.d365businesscentral as mod

You can now connect with a connection string. Use the connect function for the CData Dynamics 365 Business Central Connector to create a connection for working with Dynamics 365 Business Central data.

cnxn = mod.connect("OrganizationUrl=https://myaccount.financials.dynamics.com/;")

Create a SQL Statement to Query Dynamics 365 Business Central

Use SQL to create a statement for querying Dynamics 365 Business Central. In this article, we read data from the Accounts entity.

sql = "SELECT accountid, Name FROM Accounts WHERE Name = 'MyAccount'"

Extract, Transform, and Load the Dynamics 365 Business Central Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Dynamics 365 Business Central data. In this example, we extract Dynamics 365 Business Central data, sort the data by the Name column, and load the data into a CSV file.

Loading Dynamics 365 Business Central 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 Dynamics 365 Business Central

table1 = [ ['accountid','Name'], ['Newaccountid1','NewName1'], ['Newaccountid2','NewName2'], ['Newaccountid3','NewName3'] ]

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

With the CData Python Connector for Dynamics 365 Business Central, you can work with Dynamics 365 Business Central 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 Dynamics 365 Business Central Python Connector to start building Python apps and scripts with connectivity to Dynamics 365 Business Central 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.d365businesscentral as mod

cnxn = mod.connect("OrganizationUrl=https://myaccount.financials.dynamics.com/;")

sql = "SELECT accountid, Name FROM Accounts WHERE Name = 'MyAccount'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['accountid','Name'], ['Newaccountid1','NewName1'], ['Newaccountid2','NewName2'], ['Newaccountid3','NewName3'] ]

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