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Create Python applications that use pandas and Dash to build Outreach.io-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 Outreach.io, the pandas module, and the Dash framework, you can build Outreach.io-connected web applications for Outreach.io data. This article shows how to connect to Outreach.io with the CData Connector and use pandas and Dash to build a simple web app for visualizing Outreach.io data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Outreach.io data in Python. When you issue complex SQL queries from Outreach.io, the driver pushes supported SQL operations, like filters and aggregations, directly to Outreach.io and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Outreach.io Data
Connecting to Outreach.io 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 must use OAuth to authenticate with Outreach. Set the InitiateOAuth connection property to "GETANDREFRESH". For more information, refer to the OAuth section in the Help documentation.
After installing the CData Outreach.io Connector, follow the procedure below to install the other required modules and start accessing Outreach.io 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 Outreach.io 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.outreach as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData Outreach.io Connector to create a connection for working with Outreach.io data.
cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")
Execute SQL to Outreach.io
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 Name, NumberOfEmployees FROM Accounts WHERE Industry = 'Textiles'", 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-outreachedataplot' 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 Outreach.io data and configure the app layout.
trace = go.Bar(x=df.Name, y=df.NumberOfEmployees, name='Name') 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='Outreach.io Accounts 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 Outreach.io data.
python outreach-dash.py

Free Trial & More Information
Download a free, 30-day trial of the CData Python Connector for Outreach.io to start building Python apps with connectivity to Outreach.io 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.outreach as mod import plotly.graph_objs as go cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") df = pd.read_sql("SELECT Name, NumberOfEmployees FROM Accounts WHERE Industry = 'Textiles'", cnxn) app_name = 'dash-outreachdataplot' 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.Name, y=df.NumberOfEmployees, name='Name') 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='Outreach.io Accounts Data', barmode='stack') }) ], className="container") if __name__ == '__main__': app.run_server(debug=True)