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Connect to live data from Printify with the API Driver

Connect to Printify

Analyze Printify Data in R



Use standard R functions and the development environment of your choice to analyze Printify data with the CData JDBC Driver for Printify.

Access Printify data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for Printify and the RJDBC package to work with remote Printify data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Printify and visualize Printify data by calling standard R functions.

Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to Printify as a JDBC Data Source

You will need the following information to connect to Printify as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.api.APIDriver
  • Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for Printify:

driver <- JDBC(driverClass = "cdata.jdbc.api.APIDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.api.jar", identifier.quote = "'")

You can now use DBI functions to connect to Printify and execute SQL queries. Initialize the JDBC connection with the dbConnect 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.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Printify JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.api.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:api:Profile=C:\profiles\Printify.apip;ProfileSettings='APIKey=your_personal_token';")

Schema Discovery

The driver models Printify APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the Printify API:

tags <- dbGetQuery(conn,"SELECT Id, ShippingMethod FROM Tags WHERE Status = 'pending'")

You can view the results in a data viewer window with the following command:

View(tags)

Plot Printify Data

You can now analyze Printify data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2)) barplot(tags$ShippingMethod, main="Printify Tags", names.arg = tags$Id, horiz=TRUE)