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

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

Connecting to Notion Data

Connecting to Notion 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.

Start by setting the Profile connection property to the location of the Notion Profile on disk (e.g. C:\profiles\Notion.apip). Next, set the ProfileSettings connection property to the connection string for Notion (see below).

Notion API Profile Settings

Go to https://www.notion.so/my-integrations, create an internal integration, configure the name and workspace, then copy the Internal Integration Token from the Secrets section.

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

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

cnxn = mod.connect("Profile=C:\profiles\Notion.apip;ProfileSettings='APIKey=your_integration_token';")

Create a SQL Statement to Query Notion

Use SQL to create a statement for querying Notion. In this article, we read data from the BlockChildren entity.

sql = "SELECT Id, Object FROM BlockChildren WHERE Type = 'page'"

Extract, Transform, and Load the Notion Data

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

Loading Notion Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with Notion 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 API Driver for Python to start building Python apps and scripts with connectivity to Notion 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.api as mod

cnxn = mod.connect("Profile=C:\profiles\Notion.apip;ProfileSettings='APIKey=your_integration_token';")

sql = "SELECT Id, Object FROM BlockChildren WHERE Type = 'page'"

table1 = etl.fromdb(cnxn,sql)

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

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