abbr

A tool to find and expand abbreviations within a string. Designed for scientific writing.

abbr is an abbreviation of "abbreviations." It is a regular expression based tool to find and expand abbreviations in text, and it is designed for use with scientific writing. Use cases may include counting terms within a scientific article when the relationship between full term and abbreviation is not known ahead of time or improving meta-analytic estimates of term frequency.

Abbreviations are expected to be presented using parentheses, as is standard in APA format.

Currently supported:

• Initialisms/Acronyms in parentheses: E.g., full term (FT)
  • This includes acronyms using non-initial letters: E.g., full term (fuTE)
  • All letters within the abbreviation must occur in the words preceding the abbreviation's first use.
• The above, with citations after the abbreviation: E.g., full term (FT; Example et al., 2016)

Installation

git clone git@github.com:NBCLab/abbr.git
cd abbr/

# for users:
python setup.py install

# for developers:
python setup.py develop

Usage

abbr can be used both to generate a dictionary of terms used in a text, as well as to expand those terms within the text. We can use abbr to find all abbreviations within a text, and return a dictionary of terms as well as identified definitions:

from abbr import findall
d = findall(text)

Where d will be a dictionary similar to the following:

{
"RMTg": "rostromedial tegmental nucleus",
"CRF": "corticotropin-releasing factor",
"VTA/SN": "ventral tegmental area/substantia nigra compacta",
"VS": "ventral striatum",
"LHb": "lateral habenula",
"nAChR": "nicotinic acetylcholine receptors"
}

abbr can also be used directly to expand abbreviations within a text and return the expanded text.

from abbr import expandall
text = expandall(text)

Next steps

Ultimately, we would like to shift away from regular expressions toward NLP and ML, but we have no immediate plans to do so. If you would like to help with this transition, feel free to open a pull request!

Reporting Issues and Feature Requests

We welcome all issue reports and pull requests! When opening an issue, we ask that you provide all necessary detail to reproduce the bug. Specifically:

1. Expected result
2. Steps you took to achieve expected result
3. Actual result

If we can reproduce your error, there is a much greater chance we can help to fix it!