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

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

Connecting to Asana Data

Connecting to Asana 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.

You can optionally set the following to refine the data returned from Asana.

• WorkspaceId: Set this to the globally unique identifier (gid) associated with your Asana Workspace to only return projects from the specified workspace. To get your workspace id, navigate to https://app.asana.com/api/1.0/workspaces while logged into Asana. This displays a JSON object containing your workspace name and Id.
• ProjectId: Set this to the globally unique identifier (gid) associated with your Asana Project to only return data mapped under the specified project. Project IDs can be found in the URL of your project's Overview page. This will be the numbers directly after /0/.

Connect Using OAuth Authentication

You must use OAuth to authenticate with Asana. OAuth requires the authenticating user to interact with Asana using the browser. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

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

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

cnxn = mod.connect("OAuthClientId=YourClientId;OAuthClientSecret=YourClientSecret;CallbackURL='http://localhost:33333';InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Asana

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, WorkspaceId FROM projects WHERE Archived = 'true'", 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-asanaedataplot'

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 Asana data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.WorkspaceId, 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='Asana projects 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 Asana data.

python asana-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientId=YourClientId;OAuthClientSecret=YourClientSecret;CallbackURL='http://localhost:33333';InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Id, WorkspaceId FROM projects WHERE Archived = 'true'", cnxn)
app_name = 'dash-asanadataplot'

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.WorkspaceId, 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='Asana projects Data', barmode='stack')
		})
], className="container")

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