---
id: pyobjc-framework-latentsemanticmapping
version: "12.2.2"
license: MIT
license_treatment: permissive
maintenance: active
---

# pyobjc-framework-LatentSemanticMapping — Wrappers for the framework LatentSemanticMapping on macOS

License: permissive · Maintenance: active · Downloads: 656.4K/mo

## What it is and what it does

This package wraps Apple's LatentSemanticMapping framework for use in Python, enabling text and token-based content classification into custom categories on macOS. It is part of the PyObjC project, which bridges Objective-C frameworks to Python, and requires both pyobjc-core and pyobjc-framework-Cocoa as runtime dependencies.

The package is production-stable and actively maintained, supporting Python 3.10 through 3.15. However, the underlying macOS framework has minimal Apple documentation, which significantly limits practical usability. Users will need to consult both PyObjC's translation documentation and Apple's sparse framework guides to implement classification workflows effectively.

Use it for:

- Build text classification systems on macOS that leverage native framework APIs without reimplementing semantic analysis.
- Integrate macOS-native text categorization into Python applications that need to run on Apple platforms.
- Prototype semantic text analysis workflows using Python while accessing low-level macOS framework capabilities.
- Develop cross-language applications that bridge Python logic with Objective-C framework functionality on macOS.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Python bindings to macOS's LatentSemanticMapping framework for classifying text and token-based content into developer-defined categories.

Yes, if you are developing on macOS and need to classify text using the native LatentSemanticMapping framework from Python. The package is actively maintained, has no known vulnerabilities, and installs with low friction. However, be aware that Apple's minimal documentation for the underlying framework makes practical implementation challenging—you will need to invest time in understanding both PyObjC's translation layer and Apple's sparse framework documentation before productive use.

## Install

pip install pyobjc-framework-latentsemanticmapping
uv add pyobjc-framework-latentsemanticmapping
poetry add pyobjc-framework-latentsemanticmapping

## Installing pyobjc-framework-LatentSemanticMapping

Before you install: Low friction installation with a pure-wheel distribution. Actively maintained as of 3 days ago with recent commits and no known vulnerabilities. Requires pyobjc-core and pyobjc-framework-Cocoa as dependencies.

License in practice: MIT license permits unrestricted use, modification, and distribution with minimal legal friction for commercial or private projects.

Quickstart:

pip install pyobjc-framework-latentsemanticmapping

from LatentSemanticMapping import LSMCategory
# Access macOS LatentSemanticMapping framework via Python

Requires macOS 10.5 or later and Python 3.10+; framework is not available on other operating systems.

Verify before relying:

- Practical usability of the underlying LatentSemanticMapping framework given Apple's minimal documentation, as noted in the package description.
- Whether the framework remains actively maintained by Apple or is deprecated on modern macOS versions.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 656.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

text classification macOS, latent semantic mapping python, pyobjc framework bindings, macos text categorization, token-based content classification, objective-c framework wrapper, semantic text analysis mac, macos-only, objective-c-bridge, text-classification

[View on SkillFed](https://skillfed.io/packages/pyobjc-framework-latentsemanticmapping) · [View on PyPI](https://pypi.org/project/pyobjc-framework-latentsemanticmapping/)