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

Use Dash to Build to Web Apps on Basecamp Data



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

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

Connecting to Basecamp Data

Connecting to Basecamp 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.

Basecamp uses basic or OAuth 2.0 authentication. To use basic authentication you will need the user and password that you use for logging in to Basecamp. To authenticate to Basecamp via OAuth 2.0, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with Basecamp.

See the Getting Started section in the help documentation for a connection guide.

Additionally, you will need to specify the AccountId connection property. This can be copied from the URL after you log in.

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

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

cnxn = mod.connect("User=test@northwind.db;Password=test123;")

Execute SQL to Basecamp

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 Name, DocumentsCount FROM Projects WHERE Drafts = '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-basecampedataplot'

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 Basecamp data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.DocumentsCount, name='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='Basecamp 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 Basecamp data.

python basecamp-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=test@northwind.db;Password=test123;")

df = pd.read_sql("SELECT Name, DocumentsCount FROM Projects WHERE Drafts = 'True'", cnxn)
app_name = 'dash-basecampdataplot'

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.Name, y=df.DocumentsCount, name='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='Basecamp Projects Data', barmode='stack')
		})
], className="container")

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