This library provides Python wrappers for Apple's LatentSemanticMapping framework on macOS, enabling Python applications to leverage latent semantic analysis capabilities for tasks like text similarity and natural language processing. It is part of the larger PyObjC project, currently at version 12.1, with releases typically tied to macOS SDK updates and Python version support cycles.
pip install pyobjc-framework-latentsemanticmappingVerified import paths — ran on the pinned version, not inferred.
This quickstart demonstrates how to import and instantiate a basic object from the LatentSemanticMapping framework using PyObjC.
Upgrade your Python interpreter to a supported version (e.g., Python 3.10+ for PyObjC 12.x) or use an older PyObjC version that supports your Python environment.
Review any code that explicitly manages references to objects returned by `init` methods or that relies on specific reference counts for `self` within `init`-like methods. Adjust memory management logic if necessary.
Thoroughly test multi-threaded PyObjC applications on Python 3.13. If encountering issues, consider using an earlier Python version or isolating PyObjC calls to a single thread until free-threading support matures.
If you override `__new__` in a PyObjC-bridged class, ensure your `__init__` correctly handles object initialization, and be aware that `__init__` will not be called if you rely on PyObjC's default `__new__` for new instances.
If KVO on Python-defined `NSProxy` subclasses is critical, you may need to implement custom observation mechanisms or reconsider your class design to avoid `NSProxy` for observable objects.