Use Dash to Build to Web Apps on Campaigner Data
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas module, and the Dash framework, you can build Campaigner-connected web applications for Campaigner data. This article shows how to connect to Campaigner with the CData Connector and use pandas and Dash to build a simple web app for visualizing Campaigner data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Campaigner data in Python. When you issue complex SQL queries from Campaigner, the driver pushes supported SQL operations, like filters and aggregations, directly to Campaigner and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Campaigner Data
Connecting to Campaigner 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.
Start by setting the Profile connection property to the location of the Campaigner Profile on disk (e.g. C:\profiles\Campaigner.apip). Next, set the ProfileSettings connection property to the connection string for Campaigner (see below).
Campaigner API Profile Settings
Sign into your Campaigner account and navigate to Account Settings > Users, create a new API User role, and save to generate the API key.
After installing the CData Campaigner Connector, follow the procedure below to install the other required modules and start accessing Campaigner 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 Campaigner 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.api as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData Campaigner Connector to create a connection for working with Campaigner data.
cnxn = mod.connect("Profile=C:\profiles\Campaigner.apip;ProfileSettings='APIKey=your_api_key';")
Execute SQL to Campaigner
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, Name FROM ActiveCampaigns WHERE Status = 'active'", 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-apiedataplot' 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 Campaigner data and configure the app layout.
trace = go.Bar(x=df.Id, y=df.Name, 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='Campaigner ActiveCampaigns 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 Campaigner data.
python api-dash.py
Free Trial & More Information
Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Campaigner 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.api as mod
import plotly.graph_objs as go
cnxn = mod.connect("Profile=C:\profiles\Campaigner.apip;ProfileSettings='APIKey=your_api_key';")
df = pd.read_sql("SELECT Id, Name FROM ActiveCampaigns WHERE Status = 'active'", cnxn)
app_name = 'dash-apidataplot'
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.Name, 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='Campaigner ActiveCampaigns Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)