Use Dash to Build to Web Apps on Paylocity 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 Paylocity, the pandas module, and the Dash framework, you can build Paylocity-connected web applications for Paylocity data. This article shows how to connect to Paylocity with the CData Connector and use pandas and Dash to build a simple web app for visualizing Paylocity data.

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

Connecting to Paylocity Data

Connecting to Paylocity 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.

Set the following to establish a connection to Paylocity:

• RSAPublicKey: Set this to the RSA Key associated with your Paylocity, if the RSA Encryption is enabled in the Paylocity account.

  This property is required for executing Insert and Update statements, and it is not required if the feature is disabled.

• UseSandbox: Set to true if you are using sandbox account.
• CustomFieldsCategory: Set this to the Customfields category. This is required when IncludeCustomFields is set to true. The default value for this property is PayrollAndHR.
• Key: The AES symmetric key(base 64 encoded) encrypted with the Paylocity Public Key. It is the key used to encrypt the content.

  Paylocity will decrypt the AES key using RSA decryption.
  It is an optional property if the IV value not provided, The driver will generate a key internally.

• IV: The AES IV (base 64 encoded) used when encrypting the content. It is an optional property if the Key value not provided, The driver will generate an IV internally.

Connect Using OAuth Authentication

You must use OAuth to authenticate with Paylocity. OAuth requires the authenticating user to interact with Paylocity using the browser. For more information, refer to the OAuth section in the Help documentation.

The Pay Entry API

The Pay Entry API is completely separate from the rest of the Paylocity API. It uses a separate Client ID and Secret, and must be explicitly requested from Paylocity for access to be granted for an account. The Pay Entry API allows you to automatically submit payroll information for individual employees, and little else. Due to the extremely limited nature of what is offered by the Pay Entry API, we have elected not to give it a separate schema, but it may be enabled via the UsePayEntryAPI connection property.

Please be aware that when setting UsePayEntryAPI to true, you may only use the CreatePayEntryImportBatch & MergePayEntryImportBatchgtable stored procedures, the InputTimeEntry table, and the OAuth stored procedures. Attempts to use other features of the product will result in an error. You must also store your OAuthAccessToken separately, which often means setting a different OAuthSettingsLocation when using this connection property.

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

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

cnxn = mod.connect("OAuthClientID=YourClientId;OAuthClientSecret=YourClientSecret;RSAPublicKey=YourRSAPubKey;Key=YourKey;IV=YourIV;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Paylocity

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, LastName FROM Employee WHERE EmployeeId = '1234'", 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-paylocityedataplot'

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 Paylocity data and configure the app layout.

trace = go.Bar(x=df.FirstName, y=df.LastName, 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='Paylocity Employee 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 Paylocity data.

python paylocity-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientID=YourClientId;OAuthClientSecret=YourClientSecret;RSAPublicKey=YourRSAPubKey;Key=YourKey;IV=YourIV;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT FirstName, LastName FROM Employee WHERE EmployeeId = '1234'", cnxn)
app_name = 'dash-paylocitydataplot'

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.LastName, 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='Paylocity Employee Data', barmode='stack')
		})
], className="container")

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