Use Dash to Build to Web Apps on Plaid Data

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Plaid Python Connector

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



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

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

Connecting to Plaid Data

Connecting to Plaid 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 connect to Plaid using the embedded OAuth connectivity. When you connect, the Plaid OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

Optionally set the Account Id property to return data related to a specific Account.

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

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

cnxn = mod.connect("AccountId=123456789;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Plaid

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 AccountId, Name FROM Transactions WHERE Name = 'Apple Store'", 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-plaidedataplot'

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 Plaid data and configure the app layout.

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

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='Plaid Transactions 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 Plaid data.

python plaid-dash.py

Free Trial & More Information

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

cnxn = mod.connect("AccountId=123456789;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT AccountId, Name FROM Transactions WHERE Name = 'Apple Store'", cnxn)
app_name = 'dash-plaiddataplot'

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

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='Plaid Transactions Data', barmode='stack')
		})
], className="container")

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