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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for OneNote, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build OneNote-connected Python applications and scripts for visualizing OneNote data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to OneNote data, execute queries, and visualize the results.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live OneNote data in Python. When you issue complex SQL queries from OneNote, the driver pushes supported SQL operations, like filters and aggregations, directly to OneNote and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to OneNote 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.
OneNote uses the OAuth authentication standard. To authenticate using OAuth, create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the Help documentation for more information.
Follow the procedure below to install the required modules and start accessing OneNote through Python objects.
Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:
pip install pandas pip install matplotlib pip install sqlalchemy
Be sure to import the module with the following:
import pandas import matplotlib.pyplot as plt from sqlalchemy import create_engine
You can now connect with a connection string. Use the create_engine function to create an Engine for working with OneNote data.
engine = create_engine("onenote:///?OAuthClientId=MyApplicationId& OAuthClientSecret=MySecretKey& CallbackURL=http://localhost:33333&InitiateOAuth=GETANDREFRESH")
Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.
df = pandas.read_sql("SELECT Id, notebook_displayName FROM Notebooks WHERE Id = 'Jq74mCczmFXk1tC10GB'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the OneNote data. The show method displays the chart in a new window.
df.plot(kind="bar", x="Id", y="notebook_displayName") plt.show()👁 OneNote data in a Python plot (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for OneNote to start building Python apps and scripts with connectivity to OneNote data. Reach out to our Support Team if you have any questions.
import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin
engine = create_engine("onenote:///?OAuthClientId=MyApplicationId& OAuthClientSecret=MySecretKey& CallbackURL=http://localhost:33333&InitiateOAuth=GETANDREFRESH")
df = pandas.read_sql("SELECT Id, notebook_displayName FROM Notebooks WHERE Id = 'Jq74mCczmFXk1tC10GB'", engine)
df.plot(kind="bar", x="Id", y="notebook_displayName")
plt.show()
Download a Community License of the OneNote Connector to get started:
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👁 Microsoft OneNote IconPython Connector Libraries for Microsoft OneNote Data Connectivity. Integrate Microsoft OneNote with popular Python tools like Pandas, SQLAlchemy, Dash & petl.