[파이썬] `sys.path_importer_cache`: 경로 임포터 캐시

In Python, the sys.path_importer_cache is a special cache that stores the importers for the different paths used when importing modules. This cache helps improve the import performance by avoiding the need to search the file system for the same module multiple times.

What is an importer?

In Python, an importer is a mechanism that is responsible for finding and loading modules. When you import a module, Python looks for it in the directories specified in the sys.path list. The sys.path_importer_cache caches the result of this search, so that subsequent imports from the same path can be resolved much faster.

How does it work?

When you import a module, Python first checks the sys.path_importer_cache to see if the importer for the given path is already cached. If not, it goes through a sequence of steps to find and load the module. Once the importer is found, it is cached in the sys.path_importer_cache for future use.

Example

Let’s say you have a module named my_module located in the /path/to/my_module directory. The first time you import it, Python will search for the module and cache the importer in the sys.path_importer_cache. Here’s how you can check the cache:

import sys

importer = sys.path_importer_cache.get('/path/to/my_module')
print(importer)  # Output: None

import my_module

importer = sys.path_importer_cache.get('/path/to/my_module')
print(importer)  # Output: <_frozen_importlib_external.FileFinder object at 0x7fbed037f9e8>

As you can see, the first sys.path_importer_cache.get() call returns None because the importer is not cached yet. But after importing my_module, the second call returns the cached importer.

Benefits of sys.path_importer_cache

The sys.path_importer_cache provides the following benefits:

Conclusion

The sys.path_importer_cache in Python is a useful mechanism that enhances import performance by caching the importers for different paths. It improves the loading time of modules by avoiding redundant file system searches. Understanding and utilizing this cache can greatly benefit your Python applications.