Use Dash to Build to Web Apps on Miro Data

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

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

Connecting to Miro Data

Connecting to Miro 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.

Using API Key Authentication

Miro uses API Key authentication with an access token. To generate an access token:

1. Log in to your Miro account
2. Navigate to Settings > Your apps
3. Click "Create new app" or select an existing app
4. Configure the required permissions (e.g., boards:read, teams:read)
5. Install the app and generate an access token
6. Copy the generated access token (it will only be shown once)

After obtaining your access token, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your access token.

Connecting to Miro

Once the authentication is configured, you can connect to Miro and query data from any of the available tables such as Boards, Items, Teams, Organizations, and more.

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

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

cnxn = mod.connect("Profile=C:\profiles\Miro.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_access_token';")

Execute SQL to Miro

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 , FROM Boards WHERE BoardId = '3074457361234567890'", 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-apiedataplot'

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 Miro data and configure the app layout.

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

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='Miro Boards 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 Miro data.

python api-dash.py

👁 Miro data in a Dash web app (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Miro data. Reach out to our Support Team if you have any questions.

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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.api as mod
import plotly.graph_objs as go

cnxn = mod.connect("Profile=C:\profiles\Miro.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_access_token';")

df = pd.read_sql("SELECT , FROM Boards WHERE BoardId = '3074457361234567890'", cnxn)
app_name = 'dash-apidataplot'

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

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='Miro Boards Data', barmode='stack')
		})
], className="container")

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