2025 WA GIS Conference

One of the most challenging things about using Python in GIS is, it's hard to know if you're really getting better. Or rather, knowing how to get better is hard. In the same way that many of us spent a lot of time, ""wanting to learn Python"" but not knowing where to start. Or ""learning Python"" and not knowing how to apply the language at work.

This presentation is the presentation that I wished I would have had when starting my geospatial Python journey. It is a brief review of the developer practices that I've picked up along the way. We'll cover the following:

• Conda & Using ArcPy in an IDE
• Formatters & Linters
• Logging
• Version Control
• Functions & Type Hinting
• Secrets Management

Esri’s support for Python offers a number of opportunities for automating everyday tasks and generating reports. From reporting to pushing data around, generating ID values in ArcGIS Online or making calls to web APIs, this presentation is intended to introduce you to some of the tools and approaches to automating common (and not so common) tasks. Using lots of examples, the presenter will walk you through resources, how you can get started, things to watch out for, and how to run your automation tools effectively.

In this presentation, I'll share how I developed an automated workflow using ArcGIS Pro ModelBuilder and Python scripting to tackle the challenge of integrating and spatially aligning sewer tap data for the City of Kent. I aimed to create a robust solution that seamlessly merges tabular data from external sources with our existing spatial datasets, ensuring accuracy and consistency across our databases. My process started by importing and processing the tabular sewer tap information, which includes details such as asset IDs, measurement values, and timestamps. I then joined this data with the spatial sewer main features, enabling me to calculate precise tap locations along the sewer lines. I incorporated data filtering and statistical analysis to determine maximum distances, and I established a linear referencing system to accurately position tap points. I utilized custom Python scripts and Arcade expressions to derive attributes such as the directionality of the tap point from the line (DownLRC – left, right, or center) and identifying the most recent tap record (IsLatest). I focused on achieving accurate spatial alignment by generating route event layers, accounting for both on-line and offset tap locations. Finally, this process is scheduled to run on a weekly basis using VisualCron, where the newly processed tap data is appended to the existing sewer tap point feature class, effectively updating our geodatabase. This automated solution has significantly reduced manual data entry and processing time, minimized errors, and enhanced the spatial accuracy of Kent’s sewer infrastructure data. By integrating external data sources and implementing rigorous spatial analysis, I've created a reliable and efficient method for displaying up-to-date and accurate sewer tap information, thus assisting our field crews with regular pipeline inspections and maintenance.