Ready to get started?

Download a free trial of the Sage 200 Connector to get started:

 Download Now

Learn more:

Sage 200 Icon Sage 200 Python Connector

Python Connector Libraries for Sage 200 Data Connectivity. Integrate Sage 200 with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use Dash to Build to Web Apps on Sage 200 Data



Create Python applications that use pandas and Dash to build Sage 200-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 Sage 200, the pandas module, and the Dash framework, you can build Sage 200-connected web applications for Sage 200 data. This article shows how to connect to Sage 200 with the CData Connector and use pandas and Dash to build a simple web app for visualizing Sage 200 data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Sage 200 data in Python. When you issue complex SQL queries from Sage 200, the driver pushes supported SQL operations, like filters and aggregations, directly to Sage 200 and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Sage 200 Data

Connecting to Sage 200 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.

  • Schema: Determines which Sage 200 edition you are connecting to. Specify either StandardUK or ProfessionalUK.
  • Subscription Key: Provides access to the APIs that are used to establish a connection. You will first need to log into the Sage 200 API website and subscribe to the API edition that matches your account. You can do so here: https://developer.columbus.sage.com/docs/services/api/uk. Afterwards, the subscription key may be found in your profile after logging into Sage 200.

After installing the CData Sage 200 Connector, follow the procedure below to install the other required modules and start accessing Sage 200 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 Sage 200 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.sage200 as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Sage 200 Connector to create a connection for working with Sage 200 data.

cnxn = mod.connect("SubscriptionKey=12345;Schema=StandardUK;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Sage 200

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, Code FROM Banks WHERE Code = '12345'", 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-sage200edataplot'

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 Sage 200 data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.Code, 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='Sage 200 Banks 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 Sage 200 data.

python sage200-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Sage 200 to start building Python apps with connectivity to Sage 200 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.sage200 as mod
import plotly.graph_objs as go

cnxn = mod.connect("SubscriptionKey=12345;Schema=StandardUK;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Id, Code FROM Banks WHERE Code = '12345'", cnxn)
app_name = 'dash-sage200dataplot'

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.Code, 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='Sage 200 Banks Data', barmode='stack')
		})
], className="container")

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