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

Use Dash to Build to Web Apps on MySQL Data



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

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

Connecting to MySQL Data

Connecting to MySQL 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 Server and Port properties must be set to a MySQL server. If IntegratedSecurity is set to false, then User and Password must be set to valid user credentials. Optionally, Database can be set to connect to a specific database. If not set, tables from all databases will be returned.

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

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

cnxn = mod.connect("User=myUser;Password=myPassword;Database=NorthWind;Server=myServer;Port=3306;")

Execute SQL to MySQL

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 ShipName, Freight FROM Orders WHERE ShipCountry = 'USA'", 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-mysqledataplot'

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 MySQL data and configure the app layout.

trace = go.Bar(x=df.ShipName, y=df.Freight, name='ShipName')

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='MySQL Orders 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 MySQL data.

python mysql-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=myUser;Password=myPassword;Database=NorthWind;Server=myServer;Port=3306;")

df = pd.read_sql("SELECT ShipName, Freight FROM Orders WHERE ShipCountry = 'USA'", cnxn)
app_name = 'dash-mysqldataplot'

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.ShipName, y=df.Freight, name='ShipName')

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='MySQL Orders Data', barmode='stack')
		})
], className="container")

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