Use Dash to Build to Web Apps on Printify 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 Printify-connected web applications for Printify data. This article shows how to connect to Printify with the CData Connector and use pandas and Dash to build a simple web app for visualizing Printify data.

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

Connecting to Printify Data

Connecting to Printify 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.

Start by setting the Profile connection property to the location of the Printify Profile on disk (e.g. C:\profiles\Profile.apip). Next, set the ProfileSettings connection property to the connection string for Printify (see below).

Printify API Profile Settings

In order to authenticate to Printify, you'll need to provide your API Key. To get your API Key navigate to My Profile, then Connections. In the Connections section you will be able to generate your Personal Access Token (API Key) and set your Token Access Scopes. Personal Access Tokens are valid for one year. An expired Personal Access Token can be re-generated using the same steps after it expires. Set the API Key to your Personal Access Token in the ProfileSettings property to connect.

After installing the CData Printify Connector, follow the procedure below to install the other required modules and start accessing Printify 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 Printify 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 Printify Connector to create a connection for working with Printify data.

cnxn = mod.connect("Profile=C:\profiles\Printify.apip;ProfileSettings='APIKey=your_personal_token';")

Execute SQL to Printify

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 Id, ShippingMethod FROM Tags WHERE Status = 'pending'", 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 Printify data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.ShippingMethod, name='Id')

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='Printify Tags 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 Printify 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 Printify 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\Printify.apip;ProfileSettings='APIKey=your_personal_token';")

df = pd.read_sql("SELECT Id, ShippingMethod FROM Tags WHERE Status = 'pending'", 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.Id, y=df.ShippingMethod, name='Id')

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='Printify Tags Data', barmode='stack')
		})
], className="container")

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