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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 OData, the pandas module, and the Dash framework, you can build OData-connected web applications for OData services. This article shows how to connect to OData with the CData Connector and use pandas and Dash to build a simple web app for visualizing OData services.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live OData services in Python. When you issue complex SQL queries from OData, the driver pushes supported SQL operations, like filters and aggregations, directly to OData and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
CData simplifies access and integration of live OData services data. Our customers leverage CData connectivity to:
Customers use CData's solutions to regularly integrate their OData services with preferred tools, such as Power BI, MicroStrategy, or Tableau, and to replicate data from OData services to their databases or data warehouses.
Connecting to OData services 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 OData user credentials. In addition, specify a URL to a valid OData server organization root or OData services file.
After installing the CData OData Connector, follow the procedure below to install the other required modules and start accessing OData 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.odata as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData OData Connector to create a connection for working with OData services.
cnxn = mod.connect("URL=http://services.odata.org/V4/Northwind/Northwind.svc;UseIdUrl=True;OData Version=4.0;Data Format=ATOM;")
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 OrderName, Freight FROM Orders WHERE ShipCity = 'New York'", 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-odataedataplot' 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 OData services and configure the app layout.
trace = go.Bar(x=df.OrderName, y=df.Freight, name='OrderName')
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='OData Orders 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 OData services.
python odata-dash.py👁 OData services in a Dash web app (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for OData to start building Python apps with connectivity to OData services. 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.odata as mod
import plotly.graph_objs as go
cnxn = mod.connect("URL=http://services.odata.org/V4/Northwind/Northwind.svc;UseIdUrl=True;OData Version=4.0;Data Format=ATOM;")
df = pd.read_sql("SELECT OrderName, Freight FROM Orders WHERE ShipCity = 'New York'", cnxn)
app_name = 'dash-odatadataplot'
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.OrderName, y=df.Freight, name='OrderName')
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='OData Orders Data', barmode='stack')
})
], className="container")
if __name__ == '__main__':
app.run_server(debug=True)
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👁 OData IconPython Connector Libraries for OData Data Connectivity. Integrate OData with popular Python tools like Pandas, SQLAlchemy, Dash & petl.