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

Use Dash to Build to Web Apps on Bullhorn CRM Data



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

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

Connecting to Bullhorn CRM Data

Connecting to Bullhorn 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.

Begin by providing your Bullhorn CRM account credentials in the following:

If you are uncertain about your data center code, codes like CLS2, CLS21, etc. are cluster IDs that are contained in a user's browser URL (address bar) once they are logged in.

Example: https://cls21.bullhornstaffing.com/BullhornSTAFFING/MainFrame.jsp?#no-ba... indicates that the logged in user is on CLS21.

Authenticating with OAuth

Bullhorn CRM uses the OAuth 2.0 authentication standard. To authenticate using OAuth, create and configure a custom OAuth app. See the Help documentation for more information.

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

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

cnxn = mod.connect("DataCenterCode=CLS33;OAuthClientId=myoauthclientid;OAuthClientSecret=myoauthclientsecret;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Bullhorn 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 Id, CandidateName FROM Candidate WHERE CandidateName = 'Jane Doe'", 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-bullhorncrmedataplot'

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 Bullhorn CRM data and configure the app layout.

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

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='Bullhorn CRM Candidate 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 Bullhorn CRM data.

python bullhorncrm-dash.py

Free Trial & More Information

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

cnxn = mod.connect("DataCenterCode=CLS33;OAuthClientId=myoauthclientid;OAuthClientSecret=myoauthclientsecret;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Id, CandidateName FROM Candidate WHERE CandidateName = 'Jane Doe'", cnxn)
app_name = 'dash-bullhorncrmdataplot'

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.Id, y=df.CandidateName, name='Id')

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='Bullhorn CRM Candidate Data', barmode='stack')
		})
], className="container")

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