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

Use Dash to Build to Web Apps on Kintone Data



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

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

Connecting to Kintone Data

Connecting to Kintone 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 addition to the authentication values, set the following parameters to connect to and retrieve data from Kintone:

  • Url: The URL of your account.
  • GuestSpaceId: Optional. Set this when using a guest space.

Authenticating with Kintone

Kintone supports the following authentication methods.

Using Password Authentication

You must set the following to authenticate:

  • User: The username of your account.
  • Password: The password of your account.

Using Basic Authentication

If the basic authentication security feature is set on the domain, supply the additional login credentials with BasicAuthUser and BasicAuthPassword. Basic authentication requires these credentials in addition to User and Password.

Using Client SSL

Instead of basic authentication, you can specify a client certificate to authenticate. Set SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword. Additionally, set User and Password to your login credentials.

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

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

cnxn = mod.connect("User=myuseraccount;Password=mypassword;Url=http://subdomain.domain.com;GuestSpaceId=myspaceid")

Execute SQL to Kintone

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 CreatorName, Text FROM Comments WHERE AppId = '1354841'", 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-kintoneedataplot'

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 Kintone data and configure the app layout.

trace = go.Bar(x=df.CreatorName, y=df.Text, name='CreatorName')

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='Kintone Comments 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 Kintone data.

python kintone-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=myuseraccount;Password=mypassword;Url=http://subdomain.domain.com;GuestSpaceId=myspaceid")

df = pd.read_sql("SELECT CreatorName, Text FROM Comments WHERE AppId = '1354841'", cnxn)
app_name = 'dash-kintonedataplot'

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.CreatorName, y=df.Text, name='CreatorName')

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='Kintone Comments Data', barmode='stack')
		})
], className="container")

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