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

Use Dash to Build to Web Apps on Acumatica Data



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

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

Connecting to Acumatica Data

Connecting to Acumatica 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.

Set the following connection properties to connect to Acumatica:

  • User: Set this to your username.
  • Password: Set this to your password.
  • Company: Set this to your company.
  • Url: Set this to your Acumatica URL, in the format http://{Acumatica ERP instance URL}/entity/{Endpoint name}/{Endpoint version}/.
    For example: https://acumatica.com/entity/Default/17.200.001/

See the Getting Started guide in the CData driver documentation for more information.

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

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

cnxn = mod.connect("Url = https://try.acumatica.com/ISV/entity/Default/17.200.001/;User=user;Password=password;Company=CompanyName;")

Execute SQL to Acumatica

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, location_displayname FROM Events WHERE Id = '1'", 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-acumaticaedataplot'

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 Acumatica data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.location_displayname, 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='Acumatica Events 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 Acumatica data.

python acumatica-dash.py

Free Trial & More Information

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

cnxn = mod.connect("Url = https://try.acumatica.com/ISV/entity/Default/17.200.001/;User=user;Password=password;Company=CompanyName;")

df = pd.read_sql("SELECT Id, location_displayname FROM Events WHERE Id = '1'", cnxn)
app_name = 'dash-acumaticadataplot'

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.location_displayname, 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='Acumatica Events Data', barmode='stack')
		})
], className="container")

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