Module 3: Debugging and Error Handling in Python Scripts

 

This week’s assignment centered around improving our ability to identify and fix errors in Python scripts used with ArcGIS, as well as making our scripts handle exceptions without crashing. The tasks were designed to build both confidence in debugging and a deeper understanding of error management in real-world GIS programming.

In the first part, I worked on a script that printed all the field names from a shapefile’s attribute table. After reviewing the dataset in ArcGIS Pro, I opened the script in IDLE and used the syntax checking tool to quickly find and fix errors such as variable name typos and incorrect capitalization, which are a common pitfall in Python. Once corrected, the script ran smoothly and printed the expected field names (Figure 1). It was a good reminder that even tiny inconsistencies in naming or indentation can completely stop a script.

Figure 1

The second script required listing all layers in an ArcGIS project file. Here, debugging went beyond syntax, several runtime issues appeared, such as incorrect file paths and handling data locked by other applications. I learned that errors like OSError can happen if a project file is open elsewhere, such as ArcGIS Pro. After closing the project, the script ran properly and listed each layer by name (Figure 2). This script helped reinforce how external files can affect script behavior and the importance of verifying that file paths and object names match exactly.

Figure 2

The third script required a different approach. Instead of fixing the error in Part A, we were instructed to use a try-except block to let it fail while still allowing Part B to run. I created a flowchart to illustrate the process (Figure 3). I located the error and wrapped Part A in a try-except structure. By printing a custom message along with the exception itself using Exception as e, I was able to clearly display the error without stopping the script from running. Part B, which prints layer names, data sources, and spatial references, then ran as intended (Figure 4).

Figure 3

Figure 4

Overall, this module strengthened my ability to debug Python scripts, implement error handling effectively, and build scripts that continue running even when encountering issues. These are critical skills for creating reliable GIS tools that can handle real-world data complexities.