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

Use Dash to Build to Web Apps on Zoho Inventory Data



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

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

Connecting to Zoho Inventory Data

Connecting to Zoho Inventory 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.

In order to connect to Zoho Inventory, set the following connection properties:

  • OrganizationId: set this to the ID associated with your specific Zoho Inventory organization
  • InitiateOAuth: set the to "GETANDREFRESH"
  • AccountsServer (Optional): set this full Account Server URL (only when manually refreshing the OAuth token)

The connectors use OAuth to authenticate with Zoho Inventory. For more information, refer to the Getting Started section of the Help documentation.

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

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

cnxn = mod.connect("OrganizationId=YourOrganizationId;AccountsServer=YourAccountServerURL;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Zoho Inventory

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 Id, CustomerName FROM Contacts WHERE FirstName = 'Katherine'", 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-zohoinventoryedataplot'

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 Zoho Inventory data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.CustomerName, name='Id')

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='Zoho Inventory Contacts 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 Zoho Inventory data.

python zohoinventory-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OrganizationId=YourOrganizationId;AccountsServer=YourAccountServerURL;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Id, CustomerName FROM Contacts WHERE FirstName = 'Katherine'", cnxn)
app_name = 'dash-zohoinventorydataplot'

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.Id, y=df.CustomerName, name='Id')

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='Zoho Inventory Contacts Data', barmode='stack')
		})
], className="container")

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