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

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

Connecting to Monday.com Data

Connecting to Monday.com 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.

You can connect to Monday.com using either API Token authentication or OAuth authentication.

Connecting with an API Token

Connect to Monday.com by specifying the APIToken. Set the AuthScheme to Token and obtain the APIToken as follows:

• API tokens for admin users
  1. Log in to your Monday.com account and click on your avatar in the bottom left corner.
  2. Select Admin.
  3. Select "API" on the left side of the Admin page.
  4. Click the "Copy" button to copy the user's API token.
• API tokens for non-admin users
  1. Click on your profile picture in the bottom left of your screen.
  2. Select "Developers"
  3. Click "Developer" and then "My Access Tokens" at the top.
  4. Select "Show" next to the API token, where you'll be able to copy it.

Connecting with OAuth Authentication

Alternatively, you can establish a connection using OAuth (refer to the OAuth section of the Help documentation).

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

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

cnxn = mod.connect("APIToken=eyJhbGciOiJIUzI1NiJ9.yJ0aWQiOjE0MTc4NzIxMiwidWlkIjoyNzI3ODM3OSwiaWFkIjoiMjAyMi0wMS0yMFQxMDo0NjoxMy45NDFaIiwicGV;")

Create a SQL Statement to Query Monday.com

Use SQL to create a statement for querying Monday.com. In this article, we read data from the Invoices entity.

sql = "SELECT Id, DueDate FROM Invoices WHERE Status = 'SENT'"

Extract, Transform, and Load the Monday.com Data

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

Loading Monday.com Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for Monday.com, you can work with Monday.com 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 Monday.com to start building Python apps and scripts with connectivity to Monday.com 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.monday as mod

cnxn = mod.connect("APIToken=eyJhbGciOiJIUzI1NiJ9.yJ0aWQiOjE0MTc4NzIxMiwidWlkIjoyNzI3ODM3OSwiaWFkIjoiMjAyMi0wMS0yMFQxMDo0NjoxMy45NDFaIiwicGV;")

sql = "SELECT Id, DueDate FROM Invoices WHERE Status = 'SENT'"

table1 = etl.fromdb(cnxn,sql)

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

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