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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for NetSuite, the pandas module, and the Dash framework, you can build NetSuite-connected web applications for NetSuite data. This article shows how to connect to NetSuite with the CData Connector and use pandas and Dash to build a simple web app for visualizing NetSuite data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live NetSuite data in Python. When you issue complex SQL queries from NetSuite, the driver pushes supported SQL operations, like filters and aggregations, directly to NetSuite and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
CData provides the easiest way to access and integrate live data from Oracle NetSuite. Customers use CData connectivity to:
Customers use CData solutions to access live NetSuite data from their preferred analytics tools, Power BI and Excel. They also use CData's solutions to integrate their NetSuite data into comprehensive databases and data warehouse using CData Sync directly or leveraging CData's compatibility with other applications like Azure Data Factory. CData also helps Oracle NetSuite customers easily write apps that can pull data from and push data to NetSuite, allowing organizations to integrate data from other sources with NetSuite.
For more information about our Oracle NetSuite solutions, read our blog: Drivers in Focus Part 2: Replicating and Consolidating ... NetSuite Accounting Data.
Connecting to NetSuite 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.
The User and Password properties, under the Authentication section, must be set to valid NetSuite user credentials. In addition, the AccountId must be set to the ID of a company account that can be used by the specified User. The RoleId can be optionally specified to log in the user with limited permissions.
See the "Getting Started" chapter of the help documentation for more information on connecting to NetSuite.
After installing the CData NetSuite Connector, follow the procedure below to install the other required modules and start accessing NetSuite through Python objects.
Use the pip utility to install the required modules and frameworks:
pip install pandas pip install dash pip install dash-daq
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.netsuite as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData NetSuite Connector to create a connection for working with NetSuite data.
cnxn = mod.connect("Account Id=XABC123456;Password=password;User=user;Role Id=3;Version=2013_1;")
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 CustomerName, SalesOrderTotal FROM SalesOrder WHERE Class_Name = 'Furniture : Office'", cnxn)
With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.
app_name = 'dash-netsuiteedataplot' external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css'] app = dash.Dash(__name__, external_stylesheets=external_stylesheets) app.title = 'CData + Dash'
The next step is to create a bar graph based on our NetSuite data and configure the app layout.
trace = go.Bar(x=df.CustomerName, y=df.SalesOrderTotal, name='CustomerName')
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='NetSuite SalesOrder Data', barmode='stack')
})
], className="container")
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 NetSuite data.
python netsuite-dash.py👁 NetSuite data in a Dash web app (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for NetSuite to start building Python apps with connectivity to NetSuite data. Reach out to our Support Team if you have any questions.
import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.netsuite as mod
import plotly.graph_objs as go
cnxn = mod.connect("Account Id=XABC123456;Password=password;User=user;Role Id=3;Version=2013_1;")
df = pd.read_sql("SELECT CustomerName, SalesOrderTotal FROM SalesOrder WHERE Class_Name = 'Furniture : Office'", cnxn)
app_name = 'dash-netsuitedataplot'
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.CustomerName, y=df.SalesOrderTotal, name='CustomerName')
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='NetSuite SalesOrder Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)
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