The following are the prerequisites for this chapter: ArcGIS 10x and Python 2.7, with arcpy available as a module.

For this chapter, the accompanying data and scripts should be downloaded from Packt Publishing's website. The completed scripts are available for comparison purposes, and the data will be used for this chapter's analysis. To run the code and test code examples, use your favorite IDE or open the IDLE (Python GUI) program from the Start Menu/ArcGIS/Python2.7 folder after installing ArcGIS for Desktop. Use the built-in "interpreter" or code entry interface, indicated by the triple chevron >>> and a blinking cursor.

ArcGIS has been in development since the 1970s. Since that time, it has included a variety of programming languages and tools to help GIS users automate analysis and map production. These include the Avenue scripting language in the ArcGIS 3x series, and the ARC Macro Language (AML) in the ARCInfo Workstation days, as well as VBScript up until ArcGIS 10x, when Python was introduced. Another useful tool introduced in ArcGIS 9x was ModelBuilder, a visual programming environment used for both modeling analysis and creating tools that can be used repeatedly with different input feature classes.

A useful feature of ModelBuilder is an export function, which allows modelers to create Python scripts directly from a model. This makes it easier to compare how parameters in a ModelBuilder tool are accepted as compared to how a Python script calls the same tool and supplies its...

While modeling analysis in ModelBuilder has its drawbacks, there is one fantastic option built into ModelBuilder: the ability to create a model, and then export the model to Python. Along with the ArcGIS Help Documentation, it is the best way to discover the correct Python syntax to use when writing ArcPy scripts.

Create a folder that can hold the exported scripts next to the SanFrancisco geodatabase (for example, C:\\ProjectsScripts). This will hold both the exported scripts that ArcGIS automatically generates, and the versions that we will build from those generated scripts. Now, perform the following steps:

1. Open up the model called Chapter2Model1.
2. Click on the Model menu in the upper-left side of the screen.
3. Select Export from the menu.
4. Select To Python Script.
5. Save the script as Chapter2Model1.py.

There are three major methods for inserting variables into strings. Each has different advantages and disadvantages of a technical nature. It's good to know about all three, as they have uses beyond our needs here, so let's review them.

String addition seems like an odd concept at first, as it would not seem possible to "add" strings together, unlike integers or floats which are numbers. However, within Python and other programming languages, this is a normal step. Using the plus sign "+", strings are "added" together to make longer strings, or to allow variables to be added into the middle of existing strings. Here are...

After the import statements and the variable definitions, the next section of the script is where the analysis is executed. The same tools that we created in the model--the Select, Buffer, and Intersect tools--are included in this section. The same parameters that we supplied in the model are also included here: the inputs and outputs, plus the SQL statement in the Select tool, and the buffer distance in the Buffer tool.

The tool parameters are supplied to the tools in the script in the same order as they appear in the tool interfaces in the model. Here is the Select tool in the script:

arcpy.Select_analysis(Bus_Stops, Inbound71, "NAME = '71 IB' AND BUS_SIGNAG = 'Ferry Plaza'")  

It works like this: the arcpy module has a "method", or tool, called Select_analysis. This method, when called, requires three parameters: the input...

Here is how the script should look in the end:

# Chapter2Model1Modified.py 
# Import arcpy module 
import arcpy 
import csv 

arcpy.env.overwriteOutput = True

# Local variables: 
Bus_Stops = r"C:\Projects\SanFrancisco.gdb\SanFrancisco\Bus_Stops" 
CensusBlocks2010 = 
 r"C:\Projects\SanFrancisco.gdb\SanFrancisco\CensusBlocks2010" 
Inbound71 = r"C:\Projects\SanFrancisco.gdb\Chapter2Results\Inbound71" 
Inbound71_400ft_buffer = 
 r"C:\Projects\SanFrancisco.gdb\Chapter2Results\Inbound71_400ft_buffer"
Intersect71Census = 
 r"C:\Projects\SanFrancisco.gdb\Chapter2Results\Intersect71Census" 
 
# Process: Select 
arcpy.Select_analysis(Bus_Stops,  
                      Inbound71,  
                      "NAME = '71 IB' AND BUS_SIGNAG = 'Ferry Plaza'")
 
# Process: Buffer 
arcpy.Buffer_analysis(Inbound71,  
       ...

In this chapter, you learned how to craft a model of an analysis and export it out to a script. In particular, you learned how to use ModelBuilder to create an analysis and export it out as a script and how to adjust the script to be more "Pythonic". After explaining about the auto-generated script, we adjusted the script to include a results analysis and summation, which was outputted to a CSV file. We also briefly touched on the use of Search Cursors, which will be covered in greater detail in Chapter 3, ArcPy Cursors: Search, Insert, and Update. Also, we saw how built-in modules such as the csv module can be used along with ArcPy to capture analysis output in formatted spreadsheets.

In the next chapter, we will investigate the powerful data access module and its Search Cursors, Update Cursors, and Insert Cursors.