Use Dash to Build to Web Apps on Webflow Data

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 module, and the Dash framework, you can build Webflow-connected web applications for Webflow data. This article shows how to connect to Webflow with the CData Connector and use pandas and Dash to build a simple web app for visualizing Webflow data.

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

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.

Authentication

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.

OAuth 2.0 Setup and Configuration

Step 1: Create a Webflow OAuth Application

To set up OAuth authentication:

1. Visit the Webflow Developer Portal
2. Navigate to "Apps & Integrations" in your Webflow account
3. Click "Register an App" to create a new OAuth application
4. Configure the application name, description, and redirect URI (CallbackURL)
5. Copy the Client ID and Client Secret for use in your connection

Required Connection Properties

• AuthScheme: Set this to OAuth (required)
• OAuthClientId: Client ID from your Webflow OAuth application (required)
• OAuthClientSecret: Client secret from your Webflow OAuth application (required)
• CallbackURL: Redirect URI specified in your OAuth application (required)
• InitiateOAuth: Set to GETANDREFRESH for automatic token management (recommended)

Required OAuth Scopes

The Webflow API Profile requires the following OAuth scopes:

• sites:read - Read access to site information and configuration
• pages:read - Read access to site pages
• cms:read - Read access to CMS collections and items
• forms:read - Read access to forms and form submissions
• assets:read - Read access to media assets and folders
• ecommerce:read - Read access to products, orders, and inventory
• authorized_user:read - Read access to the authorized user

After installing the CData Webflow Connector, follow the procedure below to install the other required modules and start accessing Webflow through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Webflow Data in Python

Once the required modules and frameworks are installed, we are ready to build our web 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 os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.api as mod
import plotly.graph_objs as go

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

cnxn = mod.connect("Profile=C:\profiles\Webflow.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

Execute SQL to Webflow

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT , FROM Sites WHERE Id = 'your_site_id'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-apiedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Webflow data and configure the app layout.

trace = go.Bar(x=df., y=df., name='')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Webflow Sites Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
 app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Webflow data.

python api-dash.py

👁 Webflow data in a Dash web app (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Webflow data. Reach out to our Support Team if you have any questions.

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Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.api as mod
import plotly.graph_objs as go

cnxn = mod.connect("Profile=C:\profiles\Webflow.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;")

df = pd.read_sql("SELECT , FROM Sites WHERE Id = 'your_site_id'", cnxn)
app_name = 'dash-apidataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df., y=df., name='')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Webflow Sites Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
 app.run_server(debug=True)