Use Dash to Build to Web Apps on GraphQL Data

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GraphQL Python Connector

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



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

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

Connecting to GraphQL Data

Connecting to GraphQL 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 must specify the URL of the GraphQL service. The driver supports two types of authentication:

  • Basic: Set AuthScheme to Basic. You must specify the User and Password of the GraphQL service.
  • OAuth 1.0 & 2.0: Take a look at the OAuth section in the Help documentation for detailed instructions.

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

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

cnxn = mod.connect("AuthScheme=Basic;User=username;Password=password;URL=https://mysite.com;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to GraphQL

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 Name, Email FROM Users WHERE UserLogin = 'admin'", 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-graphqledataplot'

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 GraphQL data and configure the app layout.

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

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='GraphQL Users 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 GraphQL data.

python graphql-dash.py

Free Trial & More Information

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

cnxn = mod.connect("AuthScheme=Basic;User=username;Password=password;URL=https://mysite.com;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Name, Email FROM Users WHERE UserLogin = 'admin'", cnxn)
app_name = 'dash-graphqldataplot'

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

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='GraphQL Users Data', barmode='stack')
		})
], className="container")

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