Skip to main content

Multimodal item feature extraction for K-12 math assessment

Project description

MathiPy Logo

PyPI version Python versions License: MIT

Multimodal item feature extraction for K-12 math assessment. Analyze readability with math-aware normalization via textstat and NLTK, classify math content by Common Core State Standards for Mathematics domain, estimate cognitive load components, extract visual complexity features from images using OpenCV and Pillow, and perform multimodal optical character recognition (OCR) through Gemini and OpenAI vision APIs.

Installation

pip install mathipy

With optional dependencies:

pip install mathipy[nlp]        # readability (textstat, nltk)
pip install mathipy[vision]     # visual analysis (opencv, pillow)
pip install mathipy[ocr]        # OCR via vision LLMs (httpx)
pip install mathipy[documents]  # document parsing (python-docx, pdfplumber)
pip install mathipy[all]        # all features

From GitHub:

pip install git+https://github.com/mshin77/mathipy.git[all]

Getting Started

See Quick Start and Analyzing Math Items for tutorials.

Citation

  • Shin, M. (2026). MathiPy: Multimodal item feature extraction for K-12 math assessment (Python package version 0.1.0) [Computer software]. https://github.com/mshin77/mathipy

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mathipy-0.1.0.tar.gz (365.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mathipy-0.1.0-py3-none-any.whl (356.0 kB view details)

Uploaded Python 3

File details

Details for the file mathipy-0.1.0.tar.gz.

File metadata

  • Download URL: mathipy-0.1.0.tar.gz
  • Upload date:
  • Size: 365.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for mathipy-0.1.0.tar.gz
Algorithm Hash digest
SHA256 8f42bd642d2a53b5374c91c6658a2f04bff25a2dd4f290dd15eeb6ef5809c380
MD5 358e7c30d1c17bd709525742684b8a78
BLAKE2b-256 009f84489dbb08e8741411703f1fcee28e33a340de67ec5f6e68b55cab56ed81

See more details on using hashes here.

File details

Details for the file mathipy-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: mathipy-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 356.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for mathipy-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 857d1157a785acc78f58bad54dbe089b0d7852b311d869060990f156381bb3ba
MD5 1d3a8f9c383ce5b63cdca6e0dd41ed3e
BLAKE2b-256 0353fe8aec8a679c1e9ed1949c2737453ea506ab5d6ac61f659b469c9a50108c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page