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 US, the pandas module, and the Dash framework, you can build Sage US-connected web applications for Sage US data. This article shows how to connect to Sage US with the CData Connector and use pandas and Dash to build a simple web app for visualizing Sage US data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Sage US data in Python. When you issue complex SQL queries from Sage US, the driver pushes supported SQL operations, like filters and aggregations, directly to Sage US and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Sage US Data
Connecting to Sage US 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 Application Id and Company Name connection string options are required to connect to Sage as a data source. You can obtain an Application Id by contacting Sage directly to request access to the Sage 50 SDK.
Sage must be installed on the machine. The Sage.Peachtree.API.dll and Sage.Peachtree.API.Resolver.dll assemblies are required. These assemblies are installed with Sage in C:\Program Files\Sage\Peachtree\API\. Additionally, the Sage SDK requires .NET Framework 4.0 and is only compatible with 32-bit applications. To use the Sage SDK in Visual Studio, set the Platform Target property to "x86" in Project -> Properties -> Build.
You must authorize the application to access company data: To authorize your application to access Sage, restart the Sage application, open the company you want to access, and connect with your application. You will then be prompted to set access permissions for the application in the resulting dialog.
While the compiled executable will require authorization only once, during development you may need to follow this process to reauthorize a new build. To avoid restarting the Sage application when developing with Visual Studio, click Build -> Configuration Manager and uncheck "Build" for your project.
After installing the CData Sage US Connector, follow the procedure below to install the other required modules and start accessing Sage US 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 US 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.sage50us as mod
import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData Sage US Connector to create a connection for working with Sage US data.
cnxn = mod.connect("ApplicationId=8dfafu4V4ODmh1fM0xx;CompanyName=Bellwether Garden Supply - Premium;")
Execute SQL to Sage US
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, LastInvoiceAmount FROM Customer WHERE Name = 'ALDRED'", 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-sage50usedataplot'
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 US data and configure the app layout.
trace = go.Bar(x=df.Name, y=df.LastInvoiceAmount, 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='Sage US Customer 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 US data.
python sage50us-dash.py
Free Trial & More Information
Download a free, 30-day trial of the Sage US Python Connector to start building Python apps with connectivity to Sage US 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.sage50us as mod
import plotly.graph_objs as go
cnxn = mod.connect("ApplicationId=8dfafu4V4ODmh1fM0xx;CompanyName=Bellwether Garden Supply - Premium;")
df = pd.read_sql("SELECT Name, LastInvoiceAmount FROM Customer WHERE Name = 'ALDRED'", cnxn)
app_name = 'dash-sage50usdataplot'
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.LastInvoiceAmount, 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='Sage US Customer Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)