profimp

To profile Python import time, you can execute a command that measures the timing breakdown of nested imports for a specific statement, helping you identify exactly which modules cause slow startup.

Slow Python startup performance is typically caused by expensive nested sub-imports within import-heavy libraries, where deep dependency chains consume significant initialization time when the modules are first loaded.

Yes, you can generate an interactive HTML waterfall report to visualize Python import costs, allowing you to quickly pinpoint the most expensive dependency chains and sub-imports.

You can debug a sluggish import statement by running a profiling command that outputs an HTML file, then opening the generated report using standard OS methods to inspect the timing breakdown.

Yes, this import profiling approach applies to comparing before and after performance changes by running the import timing breakdown on your target statement to measure the impact of your optimizations.