PyLangAcq is a Python library for language acquisition research. It allows flexible handling of the CHILDES data.

Full documentation: http://pylangacq.org/

• Comprehensive capabilities of handling CHAT transcripts as used in CHILDES
• Intuitive data structures for flexible data access and all sorts of modeling work
• Standard developmental measures such as TTR, MLU, and IPSyn readily available
• More benefits from Python: fast coding, numerous libraries for computational modeling and machine learning
• Powerful extensions for research with conversational data in general

PyLangAcq is available via pip:

$ pip install -U pylangacq

PyLangAcq works with Python 2.7 and 3.4+.

PyLangAcq is maintained by Jackson Lee. If you use PyLangAcq in your research, please cite the following:

Lee, Jackson L., Ross Burkholder, Gallagher B. Flinn, and Emily R. Coppess. 2016. Working with CHAT transcripts in Python. Technical report TR-2016-02, Department of Computer Science, University of Chicago.

@TechReport{lee-et-al-pylangacq:2016,
   Title       = {Working with CHAT transcripts in Python},
   Author      = {Lee, Jackson L. and Burkholder, Ross and Flinn, Gallagher B. and Coppess, Emily R.},
   Institution = {Department of Computer Science, University of Chicago},
   Year        = {2016},
   Number      = {TR-2016-02},
}

See CHANGELOG.md.

The MIT License. Please see LICENSE.txt. The test data files included have a CC BY-NC-SA 3.0 license instead -- please see pylangacq/tests/test_data/README.md.