Extending JMP

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Scripting Guide • Extending JMP

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External Data Sources, Analytical Tools, and Automation

This chapter discusses scripting features that are particularly useful for production settings, such as the following:

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a data feed for capturing real-time data from a laboratory instrument

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using SAS, MATLAB, R, or Python through JMP Scripting Language (JSL)

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using JMP with Microsoft Excel

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connecting to databases

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controlling JMP externally by OLE automation

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communicating with REST web services

Some general JSL commands that might be of particular interest for use in a production setting include Caption, Speak, Print, Write, and Mail. These commands are described in Functions that Communicate with Users in Programming Methods.

Contents

Real-Time Data Capture on Windows

Create a Data Feed Object

Read in Real-Time Data

Manage a Data Feed with Messages

Examples of Data Feed

Dynamic Link Libraries (DLLs)

Using Sockets in JSL

Socket-Related Commands

Messages for Sockets

Database Access

Run Query Builder Queries

Open Database Function

Creating a Database Connection and Executing SQL

Writing a SQL Query

Working with SAS

Make a SAS DATA Step

Create SAS DATA Step Code for Formula Columns

SAS Variable Names

Connect to a SAS Metadata Server

Get the Values of SAS Macro Variables

Working with MATLAB

Installing MATLAB

JMP to R Interfaces

R JSL Scriptable Object Interfaces

Conversion Between JMP Data Types and R Data Types

Troubleshooting

Working with Python

Setup Considerations

JMP-to-Python Interfaces

Equivalent Data Types for Python Send()

Equivalent Data Types for Python Get()

JMP Scoping Operators and Python

Using Python Name Option with Python Send()

Additional Python Integration Examples

Working with Microsoft Excel

Communicate with REST Web Services

Examples of HTTP Requests

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Help created on 7/12/2018