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Get the Report →Use Dash to Build to Web Apps on MongoDB Data
The CData Python Connector for MongoDB enables you to create Python applications that use pandas and Dash to build MongoDB-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 MongoDB, the pandas module, and the Dash framework, you can build MongoDB-connected web applications for MongoDB data. This article shows how to connect to MongoDB with the CData Connector and use pandas and Dash to build a simple web app for visualizing MongoDB data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live MongoDB data in Python. When you issue complex SQL queries from MongoDB, the driver pushes supported SQL operations, like filters and aggregations, directly to MongoDB and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to MongoDB Data
Connecting to MongoDB 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.
Set the Server, Database, User, and Password connection properties to connect to MongoDB. To access MongoDB collections as tables you can use automatic schema discovery or write your own schema definitions. Schemas are defined in .rsd files, which have a simple format. You can also execute free-form queries that are not tied to the schema.
After installing the CData MongoDB Connector, follow the procedure below to install the other required modules and start accessing MongoDB 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 MongoDB 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.mongodb as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData MongoDB Connector to create a connection for working with MongoDB data.
cnxn = mod.connect("Server=MyServer;Port=27017;Database=test;User=test;Password=Password;")
Execute SQL to MongoDB
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 borough, cuisine FROM restaurants WHERE Name = 'Morris Park Bake Shop'", 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-mongodbedataplot' 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 MongoDB data and configure the app layout.
trace = go.Bar(x=df.borough, y=df.cuisine, name='borough') 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='MongoDB restaurants 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 MongoDB data.
python mongodb-dash.py
Free Trial & More Information
Download a free, 30-day trial of the CData Python Connector for MongoDB to start building Python apps with connectivity to MongoDB 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.mongodb as mod import plotly.graph_objs as go cnxn = mod.connect("Server=MyServer;Port=27017;Database=test;User=test;Password=Password;") df = pd.read_sql("SELECT borough, cuisine FROM restaurants WHERE Name = 'Morris Park Bake Shop'", cnxn) app_name = 'dash-mongodbdataplot' 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.borough, y=df.cuisine, name='borough') 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='MongoDB restaurants Data', barmode='stack') }) ], className="container") if __name__ == '__main__': app.run_server(debug=True)