Pathlib vs. os.path Performance

Reasons for Path from pathlib being slower than os.path

• Object creation overhead: Path objects store more information and provide additional methods compared to os.path functions, which can lead to a slight overhead when creating and manipulating Path objects.
• Method calls vs. functions: Method calls on Path objects can be slower than direct function calls from the os.path module, since Python method calls generally have some extra overhead compared to function calls.
• Additional functionality: Some pathlib methods may perform more work than their equivalent os.path functions to provide additional functionality or to handle corner cases, which can result in slower performance.

Tips to minimize performance difference

• Use the most appropriate method or function for your use case. Sometimes pathlib provides a more efficient way to perform a certain operation than os.path does, or vice versa.
• Minimize the creation of unnecessary Path objects. If you need to manipulate paths in a performance-critical loop, consider using os.path functions or caching Path objects where possible to avoid creating new objects repeatedly.
• Profile your code to identify performance bottlenecks. If you find that pathlib is causing a significant slowdown in your code, you can consider switching to os.path for those specific operations.

General Advice

In most cases, the performance difference between pathlib and os.path is negligible for typical use cases. It’s usually more beneficial to prioritize code readability and maintainability, which pathlib often provides, over minor performance optimizations.