Use Dash to Build to Web Apps on Scrapfly Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas module, and the Dash framework, you can build Scrapfly-connected web applications for Scrapfly data. This article shows how to connect to Scrapfly with the CData Connector and use pandas and Dash to build a simple web app for visualizing Scrapfly data.

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

Connecting to Scrapfly Data

Connecting to Scrapfly 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 Scrapfly API uses API Key authentication. The API key is passed as the key query parameter on every request.

Using API Key Authentication

Your Scrapfly API key is required to create a connection. To obtain your API key:

1. Log into your Scrapfly account at scrapfly.io.
2. Navigate to Dashboard and select API Keys.
3. Copy your API key (begins with scp-live- for production or scp-test- for the test environment).

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Scrapfly API key.

Example connection string:

Profile=C:\profiles\Scrapfly.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';

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

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

cnxn = mod.connect("Profile=C:\profiles\Scrapfly.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';")

Execute SQL to Scrapfly

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 ,  FROM Account WHERE  = ''", 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-apiedataplot'

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 Scrapfly data and configure the app layout.

trace = go.Bar(x=df., y=df., 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='Scrapfly Account 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 Scrapfly data.

python api-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Scrapfly 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.api as mod
import plotly.graph_objs as go

cnxn = mod.connect("Profile=C:\profiles\Scrapfly.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';")

df = pd.read_sql("SELECT ,  FROM Account WHERE  = ''", cnxn)
app_name = 'dash-apidataplot'

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., y=df., 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='Scrapfly Account Data', barmode='stack')
		})
], className="container")

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