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

Use Dash to Build to Web Apps on DocuSign Data



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

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

Connecting to DocuSign Data

Connecting to DocuSign 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.

To connect to DocuSign, set the following connection properties:

  • UseSandbox: indicates whether current user account is sandbox or not (FALSE by default)
  • AccountId (optional): set it in the connection string if you have access to multiple Account Ids

Authenticating to DocuSign

DocuSign uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the Help documentation more information.

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

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

cnxn = mod.connect("OAuthClientId=MyClientId; OAuthClientSecret=MyClientSecret; 
CallbackURL=http://localhost:33333;
InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to DocuSign

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 DocumentId, DocumentName FROM Documents WHERE DocumentName = 'TPSReport'", 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-docusignedataplot'

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 DocuSign data and configure the app layout.

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

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='DocuSign Documents 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 DocuSign data.

python docusign-dash.py

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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.docusign as mod
import plotly.graph_objs as go

cnxn = mod.connect("OAuthClientId=MyClientId; OAuthClientSecret=MyClientSecret; 
CallbackURL=http://localhost:33333;
InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT DocumentId, DocumentName FROM Documents WHERE DocumentName = 'TPSReport'", cnxn)
app_name = 'dash-docusigndataplot'

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.DocumentId, y=df.DocumentName, name='DocumentId')

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='DocuSign Documents Data', barmode='stack')
		})
], className="container")

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