psutil

psutil is one of those rare libraries that just works reliably in production. The API is straightforward—calling `psutil.cpu_percent()`, `psutil.virtual_memory()`, or `psutil.Process(pid)` returns exactly what you expect with minimal overhead. Memory footprint is negligible even when monitoring hundreds of processes, and the C extensions are well-optimized so you're not burning cycles to measure cycles.

Error handling is pragmatic: permission errors raise `AccessDenied`, missing processes raise `NoSuchProcess`, and both inherit from `psutil.Error` for easy catching. The library handles edge cases like processes dying mid-measurement gracefully. One gotcha: `cpu_percent()` needs an interval or prior call to return meaningful data—first call with interval=None returns 0.0, which catches people initially.

Timeout behavior is synchronous and blocking by design, which is fine for most monitoring use cases but means you need to wrap calls in threads/async if you're polling aggressively. Cross-platform consistency is excellent—code written on Linux generally works identically on Windows/macOS with only minor platform-specific attribute differences clearly documented.

psutil is one of those rare libraries that just works exactly as you'd expect. The API is incredibly intuitive - functions like `psutil.cpu_percent()`, `psutil.virtual_memory()`, and `psutil.disk_usage('/')` return simple, well-structured objects with named attributes. No digging through nested dictionaries or dealing with platform-specific quirks. The library handles cross-platform differences internally, so your code works identically on Linux, Windows, and macOS.

Type hints are excellent throughout, making IDE autocomplete incredibly helpful. You'll see exactly what attributes are available on each object without constantly checking docs. Error messages are clear and actionable - if you try to access a process that doesn't exist, you get a NoSuchProcess exception with the PID clearly stated. The documentation is comprehensive with practical examples for every function.

The process iteration API (`psutil.process_iter()`) is particularly well-designed, letting you filter by attributes upfront to avoid unnecessary system calls. I've used this in production monitoring tools, CLI utilities, and debugging scripts - it's consistently reliable and performant.

psutil has been one of the easiest Python libraries I've picked up. The API is incredibly intuitive - if you want CPU usage, you call `psutil.cpu_percent()`. Memory info? `psutil.virtual_memory()`. Process details? `psutil.Process(pid)`. The naming conventions are predictable, and most common tasks require just 2-3 lines of code. I was monitoring system resources in production within 30 minutes of first encountering the library.

The documentation is exceptional, with clear examples for every function and well-organized sections. Error messages are helpful - when you try to access a process that doesn't exist, you get a clear `NoSuchProcess` exception with the PID. Cross-platform quirks are well-documented (like certain Windows/Linux differences), which saves hours of debugging.

Debugging is straightforward because the library returns simple data structures (named tuples, floats, integers). When something breaks, it's usually a permission issue, and psutil makes that obvious with `AccessDenied` exceptions. The consistency across different OS platforms means code written on macOS generally works identically on Linux servers.