Discover how a bimodal integration strategy can address the major data management challenges facing your organization today.
Get the Report →Use Dash to Build to Web Apps on Highrise Data
Create Python applications that use pandas and Dash to build Highrise-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 Highrise, the pandas module, and the Dash framework, you can build Highrise-connected web applications for Highrise data. This article shows how to connect to Highrise with the CData Connector and use pandas and Dash to build a simple web app for visualizing Highrise data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Highrise data in Python. When you issue complex SQL queries from Highrise, the driver pushes supported SQL operations, like filters and aggregations, directly to Highrise and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Highrise Data
Connecting to Highrise 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.
Highrise uses the OAuth authentication standard. To authenticate to Highrise, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app with Highrise. You will also need to set the AccountId to connect to data.
See the "Getting Started" section in the help documentation for a guide to using OAuth.
After installing the CData Highrise Connector, follow the procedure below to install the other required modules and start accessing Highrise 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 Highrise 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.highrise as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData Highrise Connector to create a connection for working with Highrise data.
cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost;AccountId=MyAccountId;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")
Execute SQL to Highrise
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, Price FROM Deals WHERE GroupId = 'MyGroupId'", 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-highriseedataplot' 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 Highrise data and configure the app layout.
trace = go.Bar(x=df.Name, y=df.Price, 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='Highrise Deals 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 Highrise data.
python highrise-dash.py
Free Trial & More Information
Download a free, 30-day trial of the CData Python Connector for Highrise to start building Python apps with connectivity to Highrise 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.highrise as mod import plotly.graph_objs as go cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost;AccountId=MyAccountId;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") df = pd.read_sql("SELECT Name, Price FROM Deals WHERE GroupId = 'MyGroupId'", cnxn) app_name = 'dash-highrisedataplot' 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.Price, 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='Highrise Deals Data', barmode='stack') }) ], className="container") if __name__ == '__main__': app.run_server(debug=True)