1. PYTHON: BUILDING GEOPROCESSING TOOLS
David Wynne, Geri Miller

3. Why we build geoprocessing tools
Your work becomes part of the geoprocessing framework
Easy to access and run from within ArcGIS
Familiar look and feel
Make a mistake? Re-run from the previous result
Run from Python, ModelBuilder, as a service
Add to a tool bar
No UI programming

4. Geoprocessing Tool Commandments
Thou shall …
… have unique parameter names within the tool
… keep the cost of validation to a minimum
… always have an output, even if it must be derived
… populate all output data elements within validation
… not test the validity of any derived value within validation
… have a coded value domain for every Boolean
… test the function from a script, a model, a dialog, and the command line

5. Deconstructing a geoprocessing tool
A geoprocessing tool does three things
Defines parameters
Validates parameters
Executes source code

6. Turning Python code into geoprocessing tools
Demo

7. Script tools vs Python toolboxes
Using Python, we can build tools in two ways:
Which do I use?
“A tool is a tool”
Script tools
Python toolboxes
Source is Python
Parameters through wizard
Validation is Python (stored in toolbox)
Entirely in Python

8. Parameters Parameters are how you interact with a tool
Data type
Type
Direction
Default
Dependency
Filter
Environment
Symbology
Multivalue
Parameters are how you interact with a tool
Simple rules to guide behaviors
Does an input exist?
What are valid fields for this data?
Is this value an expected keyword?

9. Key parameter properties
Data type
Direction
Feature layers, raster layers, table views, …
Input, output
Parameter type
String, Boolean, long, double, …
Required, optional, derived

10. Parameter Dependencies (‘obtained from’)
Some data types are dependent on other parameters
Field, SQL Expression, Field Info provide little value on their own
Set a dependency to a different data type

11. Parameters - Symbology
Control the appearance of output by setting symbology
Set using a layer file either as :
Parameter property
Or in your source code
Important if you want to vary the symbology based on logical criteria

12. Filters Filters are used to limit choices to acceptable values
Relevant data types
Value List
String (keywords) or numeric values
String, Long, Double, Boolean
Range
Between a minimum and maximum value
Long, Double
Feature Class
Allowable feature class types
Feature Layer, Feature Class
File
File extensions
Field
Supported field types
Workspace
Supported workspaces
Filters are used to limit choices to acceptable values
For example:
A number between 1 and 10
A string parameter with keywords
A file parameter that will only accept files with a .txt extension

13. Parameters - Defaults
Set a parameter default by value or by environment
Some data types match closely with geoprocessing environments
Can configure a parameter to use an environment by default

14. Parameter-izing a tool
Demo

15. Parameters – Validation
As parameters are entered and modified, validation responds and interacts
Tools validate parameters in two ways
Basic (‘free’) validation, such as:
Does the input (or output) exist?
Is it the right data type?
Does this value match its filter?
Have all required parameters been supplied?
Additional rules and behavior you add

16. Validation Provides more control Setting parameter errors and messages
Parameter interaction
Calculate defaults
Enable or disable parameters
Setting parameter errors and messages
Defining output characteristics
Chain tools in ModelBuilder

17. Validation Responding to: value (or valueAsText) altered
hasBeenValidated

18. A quick note about Python toolboxes and script tools

19. Validation: ModelBuilder
Describe outputs for chaining in ModelBuilder
Data variables in ModelBuilder include descriptions of data
By updating the schema, subsequent tools can see pending changes prior to execution

20. Validation: Messages Control over parameter messages
Evaluate system messages, and relax or change
Add more stringent errors based on your own criteria
Parameter message properties/methods
message
setErrorMessage()
clearMessage()
setIDMessage()
hasError()
setWarningMessage()
hasWarning()

21. Validation – Feature Layers
The type of a layer parameter changes depending if the input is a layer or feature class

22. Working with validation: Script tools and Python toolboxes
Demo

23. Making your Python code work as a tool
Receiving parameters
Script tool – arcpy.GetParameter / GetParameterAsText
Python toolbox – parameter.value / parameter.valueAsText
Internal
Messages – arcpy.AddMessage / AddWarning / AddError …
Progressor (step or ‘cylon eye’)
Control actions (or not) after a cancellation
Derived values, if any, are pushed back to the tool

24. Cancelling tools Added at 10.4, Pro 1.1
When a tool is cancelled…
... by default, code will be cancelled after the current line
Using new environments, can respond to the cancellation
arcpy.env.autoCancelling
arcpy.env.isCancelled

25. Distributing your tools http://esriurl.com/extendingGP
Can ‘share’ a toolbox
Simply share the files or package a result
However, to have your tools blend seamlessly, distribute as a Python package
Are easily distributable
Toolboxes appear as System Toolboxes
Toolboxes become available through arcpy
Supports dialog side-panel help and localized messages
Requires specific structure

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27. Python at User Conference
Tues
Wed
Thurs
Python: An Introduction
8:30
Python: Beyond the Basics
10:15
Python: Building Geoprocessing tools
1:30
Python: Raster Analysis
Python: ArcPy Tips and Tricks
Harnessing the Power of Python in ArcGIS using the Conda Distribution
3:30
Python Map Automation: Introduction to arcpy.mapping / arcpy.mp
Advanced Map Automation with Python in ArcGIS for Desktop
3:15