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

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

Connecting to Procore Data

Connecting to Procore 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 Procore Profile on disk (e.g. C:\profiles\Procore.apip). Next, set the ProfileSettings connection property to the connection string for Procore (see below).

Procore API Profile Settings

To authenticate to Procore, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.

First, you will need to register an OAuth application with Procore. You can do so by logging to your Developer Account and going to Create New App. Follow all necessary steps to register your app. First you will need to create a new version of Sandbox Manifest and then promote it to Production in order to get your Production Crendentials. Your Oauth application will be assigned a client id and a client secret.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to OAuth.
• InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
• OAuthClientId: Set this to the client_id that is specified in you app settings.
• OAuthClientSecret: Set this to the client_secret that is specified in you app settings.
• CallbackURL: Set this to the Redirect URI that is specified in your app settings

After installing the CData Procore Connector, follow the procedure below to install the other required modules and start accessing Procore 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 Procore 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 Procore Connector to create a connection for working with Procore data.

cnxn = mod.connect("Profile=C:\profiles\Procore.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query Procore

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

sql = "SELECT Id, Name FROM Companies WHERE IsActive = 'true'"

Extract, Transform, and Load the Procore Data

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

Loading Procore Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData API Driver for Python, you can work with Procore 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 Procore 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\Procore.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT Id, Name FROM Companies WHERE IsActive = 'true'"

table1 = etl.fromdb(cnxn,sql)

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

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