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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 Python Connector for HubDB, the pandas module, and the Dash framework, you can build HubDB-connected web applications for HubDB data. This article shows how to connect to HubDB with the CData Connector and use pandas and Dash to build a simple web app for visualizing HubDB data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live HubDB data in Python. When you issue complex SQL queries from HubDB, the driver pushes supported SQL operations, like filters and aggregations, directly to HubDB and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to HubDB 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.
There are two authentication methods available for connecting to HubDB data source: OAuth Authentication with a public HubSpot application and authentication with a Private application token.
AuthScheme must be set to "OAuth" in all OAuth flows. Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).
Follow the steps below to register an application and obtain the OAuth client credentials:
Under Scopes, select any scopes you need for your application's intended functionality.
A minimum of the following scopes is required to access tables:
To connect using a HubSpot private application token, set the AuthScheme property to "PrivateApp."
You can generate a private application token by following the steps below:
To connect, set PrivateAppToken to the private application token you retrieved.
After installing the CData HubDB Connector, follow the procedure below to install the other required modules and start accessing HubDB through Python objects.
Use the pip utility to install the required modules and frameworks:
pip install pandas pip install dash pip install dash-daq
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.hubdb as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData HubDB Connector to create a connection for working with HubDB data.
cnxn = mod.connect("AuthScheme=OAuth;OAuthClientID=MyOAuthClientID;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;")
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 PartitionKey, Name FROM NorthwindProducts WHERE Id = '1'", cnxn)
With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.
app_name = 'dash-hubdbedataplot' external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css'] app = dash.Dash(__name__, external_stylesheets=external_stylesheets) app.title = 'CData + Dash'
The next step is to create a bar graph based on our HubDB data and configure the app layout.
trace = go.Bar(x=df.PartitionKey, y=df.Name, name='PartitionKey')
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='HubDB NorthwindProducts Data', barmode='stack')
})
], className="container")
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 HubDB data.
python hubdb-dash.py👁 HubDB data in a Dash web app (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for HubDB to start building Python apps with connectivity to HubDB data. Reach out to our Support Team if you have any questions.
import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.hubdb as mod
import plotly.graph_objs as go
cnxn = mod.connect("AuthScheme=OAuth;OAuthClientID=MyOAuthClientID;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;")
df = pd.read_sql("SELECT PartitionKey, Name FROM NorthwindProducts WHERE Id = '1'", cnxn)
app_name = 'dash-hubdbdataplot'
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.PartitionKey, y=df.Name, name='PartitionKey')
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='HubDB NorthwindProducts Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)
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👁 HubDB IconPython Connector Libraries for HubDB Data Connectivity. Integrate HubDB with popular Python tools like Pandas, SQLAlchemy, Dash & petl.