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

Use Dash to Build to Web Apps on Dynamics GP Data



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

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

Connecting to Dynamics GP Data

Connecting to Dynamics GP 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.

To authenticate set the User and Password connection properties.

To connect set the URL to the Web services endpoint; for example, http://{servername}:{port}/Dynamics/GPService. Additionally, set CompanyId; you can obtain this value in the company setup window: Click Tools -> Setup -> Company.

By default, data summaries are not returned to save performance. Set LookupIds to true to return details such as line items; however, note that entities must be retrieved one at a time.

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

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

cnxn = mod.connect("CompanyId=mycompanyId;user=myuser;password=mypassword;URL= http://{servername}:{port}/Dynamics/GPService;")

Execute SQL to Dynamics GP

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, TotalAmount FROM SalesInvoice WHERE CustomerName = 'Bob'", 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-dynamicsgpedataplot'

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 Dynamics GP data and configure the app layout.

trace = go.Bar(x=df.CustomerName, y=df.TotalAmount, 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='Dynamics GP SalesInvoice 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 Dynamics GP data.

python dynamicsgp-dash.py

Free Trial & More Information

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

cnxn = mod.connect("CompanyId=mycompanyId;user=myuser;password=mypassword;URL= http://{servername}:{port}/Dynamics/GPService;")

df = pd.read_sql("SELECT CustomerName, TotalAmount FROM SalesInvoice WHERE CustomerName = 'Bob'", cnxn)
app_name = 'dash-dynamicsgpdataplot'

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.TotalAmount, 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='Dynamics GP SalesInvoice Data', barmode='stack')
		})
], className="container")

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