Use Dash to Build to Web Apps on FedEx Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for FedEx, the pandas module, and the Dash framework, you can build FedEx-connected web applications for FedEx data. This article shows how to connect to FedEx with the CData Connector and use pandas and Dash to build a simple web app for visualizing FedEx data.

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

Connecting to FedEx Data

Connecting to FedEx 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.

There are five pieces of information needed in order to authenticate its actions with the FedEx service. This information is below.

• Server: This controls the URL where the requests should be sent. Common testing options for this are: "https://gatewaybeta.fedex.com:443/xml", "https://wsbeta.fedex.com:443/xml", "https://gatewaybeta.fedex.com:443/web-service", and "https://wsbeta.fedex.com:443/web-service"
• DeveloperKey: This is the identifier part of the authentication key for the sender's identity. This value will be provided to you by FedEx after registration.
• Password: This is the secret part of the authentication key for the sender's identity. This value will be provided to you by FedEx after registration.
• AccountNumber: This valid 9-digit FedEx account number is used for logging into the FedEx server.
• MeterNumber: This value is used for submitting requests to FedEx. This value will be provided to you by FedEx after registration.
• PrintLabelLocation: This property is required if one intends to use the GenerateLabels or GenerateReturnLabels stored procedures. This should be set to the folder location where generated labels should be stored.

The Cache Database

Many of the useful tasks available from FedEx require a lot of data. To ensure this data is easy to input and recall later, utilizes a cache database to make these requests. You must set the cache connection properties:

• CacheProvider: The specific database you are using to cache with. For example, org.sqlite.JDBC.
• CacheConnection: The connection string to be passed to the cache provider. For example, jdbc:sqlite:C:/users/username/documents/fedexcache.db

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

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

cnxn = mod.connect("Server='https://gatewaybeta.fedex.com:443/xml';DeveloperKey='alsdkfjpqoewiru';Password='zxczxqqtyiuowkdlkn';AccountNumber='110371337';MeterNumber='240134349';
PrintLabelLocation='C:/users/username/documents/mylabels';CacheProvider='org.sqlite.JDBC';CacheConnection='jdbc:sqlite:C:/users/username/documents/fedexcache.db';")

Execute SQL to FedEx

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 FirstName, Phone FROM Senders WHERE SenderID = 'ab26f704-5edf-4a9f-9e4c-25'", 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-fedexedataplot'

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 FedEx data and configure the app layout.

trace = go.Bar(x=df.FirstName, y=df.Phone, name='FirstName')

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='FedEx Senders 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 FedEx data.

python fedex-dash.py

Free Trial & More Information

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

cnxn = mod.connect("Server='https://gatewaybeta.fedex.com:443/xml';DeveloperKey='alsdkfjpqoewiru';Password='zxczxqqtyiuowkdlkn';AccountNumber='110371337';MeterNumber='240134349';
PrintLabelLocation='C:/users/username/documents/mylabels';CacheProvider='org.sqlite.JDBC';CacheConnection='jdbc:sqlite:C:/users/username/documents/fedexcache.db';")

df = pd.read_sql("SELECT FirstName, Phone FROM Senders WHERE SenderID = 'ab26f704-5edf-4a9f-9e4c-25'", cnxn)
app_name = 'dash-fedexdataplot'

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.FirstName, y=df.Phone, name='FirstName')

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='FedEx Senders Data', barmode='stack')
		})
], className="container")

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