Logging and Error Handling in Operational Systems

Operational systems, by definition, need to work without human input. Systems are considered “operational” after they have ben thoroughly tested and shown to work properly with a variety of input.

However, no software is perfect and no real-world system operates with 100% availability or 100% consistent input. Things occasionally go wrong – perhaps intermittently. In a situation with occasional failures it is vitally important to have good logging and error handling. The newly released MazamaCoreUtils package helps with these tasks.   read more …

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PWFSLSmoke 1.0: Visualizing Wildfire Smoke Data

Mazama Science has released the first official version (1.0) of the PWFSLSmoke R package for working with PM2.5 monitoring data. A beta version was released last year, along with an accompanying blog post. In this post, we discuss the purpose and uses of the PWFSLSmoke package and demonstrate some of the core functionality.   read more …

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Improved Python-style Logging in R

Last August, in Python-style Logging in R, we described using an R script as a wrapper around the futile.logger package to generate log files for an operational R data processing script. Today, we highlight an improved, documented version that can be sourced by your R scripts or dropped into your package’s R/ directory to provide easy file and console logging.

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Python-style Logging in R

We are increasingly using R in “operational” settings that require robust error handling and logging. In this post we describe a quick-and-dirty way to get python style multi-level log files by wrapping the futile.logger package.

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