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

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

Connecting to Microsoft OneDrive Data

Connecting to Microsoft OneDrive 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.

OneDrive uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the OAuth section of the Help documentation for an authentication guide.

After installing the CData Microsoft OneDrive Connector, follow the procedure below to install the other required modules and start accessing Microsoft OneDrive 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 Microsoft OneDrive 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.onedrive as mod

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

cnxn = mod.connect("OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;OAuthCallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query Microsoft OneDrive

Use SQL to create a statement for querying Microsoft OneDrive. In this article, we read data from the Files entity.

sql = "SELECT Id, Name FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'"

Extract, Transform, and Load the Microsoft OneDrive Data

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

Loading Microsoft OneDrive Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for Microsoft OneDrive, you can work with Microsoft OneDrive 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 Microsoft OneDrive to start building Python apps and scripts with connectivity to Microsoft OneDrive 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.onedrive as mod

cnxn = mod.connect("OAuthClientId=MyApplicationId;OAuthClientSecret=MySecretKey;OAuthCallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT Id, Name FROM Files WHERE Id = 'Jq74mCczmFXk1tC10GB'"

table1 = etl.fromdb(cnxn,sql)

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

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