Use Dash to Build to Web Apps on Vault CRM Data



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

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

Connecting to Vault CRM Data

Connecting to Vault CRM 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.

You are ready to connect after specifying the following connection properties:

  • Url: The host you see in the URL after you login to your account. For example: https://my-veeva-domain.veevavault.com
  • User: The username you use to login to your account.
  • Password: The password you use to login to your account.

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

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

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;")

Execute SQL to Vault CRM

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 ProductId, ProductName FROM NorthwindProducts WHERE CategoryId = '5'", 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-vaultcrmedataplot'

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 Vault CRM data and configure the app layout.

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

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='Vault CRM NorthwindProducts 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 Vault CRM data.

python vaultcrm-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Vault CRM to start building Python apps with connectivity to Vault CRM 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.vaultcrm as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;")

df = pd.read_sql("SELECT ProductId, ProductName FROM NorthwindProducts WHERE CategoryId = '5'", cnxn)
app_name = 'dash-vaultcrmdataplot'

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.ProductId, y=df.ProductName, name='ProductId')

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='Vault CRM NorthwindProducts Data', barmode='stack')
		})
], className="container")

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

Ready to get started?

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Learn more:

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Python Connector Libraries for Veeva Vault Data Connectivity. Integrate Veeva Vault Vault & Vault CRM with popular Python tools like Pandas, SQLAlchemy, Dash & petl.