CData Python Connector for OData

Build 20.0.7587

From Petl

The provider can be used to create ETL applications and pipelines for CSV data in Python using Petl.

Install Required Modules

Install the Petl modules using the pip utility.

pip install petl

Connecting

Import the modules, including the CData Python Connector for OData. You can then use the provider's connect function to create a connection using a valid OData connection string. A SQLAlchemy engine may also be used instead of a direct connection.

import petl as etl
import cdata.odata as mod
cnxn = mod.connect("User=myuseraccount;Password=mypassword;URL=http://myserver/myOrgRoot;")

Extract, Transform, and Load the OData Data

Create a SQL query string and store the query results in a DataFrame.

sql = "SELECT	Id, FullName FROM Lead "
table1 = etl.fromdb(cnxn,sql)

Loading Data

With the query results stored in a DataFrame, you can load your data into any supported Petl destination. The following example loads the data into a CSV file.

etl.tocsv(table1,'output.csv')

Modifying Data

Insert new rows into OData tables using Petl's appenddb function.

table1 = [['Id','FullName'],['Jon Doe','John']]
etl.appenddb(table1,cnxn,'Lead')

Copyright (c) 2020 CData Software, Inc. - All rights reserved.
Build 20.0.7587