Reasons for Path
from pathlib
being slower than os.path
- Object creation overhead:
Path
objects store more information and provide additional methods compared toos.path
functions, which can lead to a slight overhead when creating and manipulatingPath
objects. - Method calls vs. functions: Method calls on
Path
objects can be slower than direct function calls from theos.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 equivalentos.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 thanos.path
does, or vice versa. - Minimize the creation of unnecessary
Path
objects. If you need to manipulate paths in a performance-critical loop, consider usingos.path
functions or cachingPath
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 toos.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.