PYTHON: BUILDING GEOPROCESSING TOOLS. David Wynne, Geri Miller

Transcription

1 PYTHON: BUILDING GEOPROCESSING TOOLS David Wynne, Geri Miller

2

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 1. Defines parameters 2. Validates parameters 3. 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: Script tools Source is Python Parameters through wizard Validation is Python (stored in toolbox) Python toolboxes Entirely in Python Which do I use? - A tool is a tool

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

9 Key parameter properties 1. Data type - Feature layers, raster layers, table views, - String, Boolean, long, double, 2. Direction - Input, output 3. Parameter type - 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 : 1. Parameter property 2. 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 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 Filter Values Relevant data types Value List Range Feature Class String (keywords) or numeric values Between a minimum and maximum value Allowable feature class types File File extensions File Field Workspace Supported field types Supported workspaces String, Long, Double, Boolean Long, Double Feature Layer, Feature Class Field Workspace

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 1. 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? 2. Additional rules and behavior you add

16 Validation Provides more control - 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 1. Receiving parameters - Script tool arcpy.getparameter / GetParameterAsText - Python toolbox parameter.value / parameter.valueastext 2. Internal - Messages arcpy.addmessage / AddWarning / AddError - Progressor (step or cylon eye ) - Control actions (or not) after a cancellation 3. 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 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

26 Please take our Survey Your feedback allows us to help maintain high standards and to help presenters Find your event in the Esri Events App Find the session you want to review Scroll down to the bottom of the session Answer survey questions and submit

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