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Use Dash to Build to Web Apps on HubSpot Data

The CData Python Connector for HubSpot enables you to create Python applications that use pandas and Dash to build HubSpot-connected web apps.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for HubSpot, the pandas module, and the Dash framework, you can build HubSpot-connected web applications for HubSpot data. This article shows how to connect to HubSpot with the CData Connector and use pandas and Dash to build a simple web app for visualizing HubSpot data.

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

Connecting to HubSpot Data

Connecting to HubSpot 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.

HubSpot uses the OAuth authentication standard. You can use the embedded OAuthClientId, OAuthClientSecret, and CallbackURL or you can obtain your own by registering an app.

See the Getting Started chapter of the help documentation for a guide to using OAuth.

After installing the CData HubSpot Connector, follow the procedure below to install the other required modules and start accessing HubSpot 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 HubSpot 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.hubspot as mod
import plotly.graph_objs as go

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

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to HubSpot

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 Slug, PageViews FROM Prospects WHERE Region = 'ONTARIO'", 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-hubspotedataplot'

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 HubSpot data and configure the app layout.

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

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='HubSpot Prospects 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 HubSpot data.

python hubspot-dash.py

Free Trial & More Information

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



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.hubspot as mod
import plotly.graph_objs as go

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Slug, PageViews FROM Prospects WHERE Region = 'ONTARIO'", cnxn)
app_name = 'dash-hubspotdataplot'

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.Slug, y=df.PageViews, name='Slug')

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='HubSpot Prospects Data', barmode='stack')
		})
], className="container")

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