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

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

Connecting to FreshBooks Data

Connecting to FreshBooks 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.

To connect to FreshBooks, you can set the CompanyName and Token connection properties. Alternatively, you can use the OAuth authentication standard.

OAuth can be used to enable other users to access their own company data. To authenticate using OAuth, you will need to obtain the OAuthClientId and OAuthClientSecret by registering an app. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

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

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

cnxn = mod.connect("CompanyName=CData;Token=token;")

Execute SQL to FreshBooks

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 Username, Credit FROM Clients WHERE Email = 'Captain Hook'", 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-freshbooksedataplot'

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 FreshBooks data and configure the app layout.

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

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='FreshBooks Clients 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 FreshBooks data.

python freshbooks-dash.py

Free Trial & More Information

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

cnxn = mod.connect("CompanyName=CData;Token=token;")

df = pd.read_sql("SELECT Username, Credit FROM Clients WHERE Email = 'Captain Hook'", cnxn)
app_name = 'dash-freshbooksdataplot'

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

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='FreshBooks Clients Data', barmode='stack')
		})
], className="container")

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