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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 API Driver for Python, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Webflow-connected Python applications and scripts for visualizing Webflow data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Webflow data, execute queries, and visualize the results.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Webflow data in Python. When you issue complex SQL queries from Webflow, the driver pushes supported SQL operations, like filters and aggregations, directly to Webflow and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Webflow 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.
Webflow uses OAuth 2.0 authentication to ensure secure access to sites, CMS collections, e-commerce data, and other resources. This authentication method allows you to securely connect to your Webflow workspace and manage resources with proper authorization.
To set up OAuth authentication:
The Webflow API Profile requires the following OAuth scopes:
Follow the procedure below to install the required modules and start accessing Webflow 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 Webflow data.
engine = create_engine("api:///?Profile=C:\profiles\Webflow.apip&AuthScheme=OAuth&InitiateOAuth=GETANDREFRESH&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackUrl=your_callback_url")
Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.
df = pandas.read_sql("SELECT , FROM Sites WHERE Id = 'your_site_id'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the Webflow data. The show method displays the chart in a new window.
df.plot(kind="bar", x="", y="") plt.show()👁 Webflow data in a Python plot (Salesforce is shown).
Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Webflow 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("api:///?Profile=C:\profiles\Webflow.apip&AuthScheme=OAuth&InitiateOAuth=GETANDREFRESH&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackUrl=your_callback_url")
df = pandas.read_sql("SELECT , FROM Sites WHERE Id = 'your_site_id'", engine)
df.plot(kind="bar", x="", y="")
plt.show()
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