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Use Dash to Build to Web Apps on OFX Data

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

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

Connecting to OFX Data

Connecting to OFX 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.

The OFXUser and OFXPassword properties, under the Authentication section, must be set to valid OFX user credentials. In addition to this, you will need to configure FIURL, FIOrganizationName, and FIID, which will be specific for the financial institution. You will also need to provide application-specific settings, including OFXVersion, ApplicationVersion, and ApplicationId.

To connect to some services, you will need to provide additional account information such as AccountId, AccountType, BankId, BrokerId, and CCNumber.

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

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

cnxn = mod.connect("OFXUser=myUser;OFXPassword=myPassword;FIID=myFIID;")

Execute SQL to OFX

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, Amount FROM InvBalances WHERE ServiceType = 'CREDITCARD'", 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-ofxedataplot'

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 OFX data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.Amount, 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='OFX InvBalances 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 OFX data.

python ofx-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OFXUser=myUser;OFXPassword=myPassword;FIID=myFIID;")

df = pd.read_sql("SELECT Id, Amount FROM InvBalances WHERE ServiceType = 'CREDITCARD'", cnxn)
app_name = 'dash-ofxdataplot'

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.Amount, 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='OFX InvBalances Data', barmode='stack')
		})
], className="container")

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