This filter changes a given text to Title Caps, and attempts to be clever about SMALL words like a/an/the in the input. The list of "SMALL words" which are not capped comes from the New York Times Manual of Style, plus some others like 'vs' and 'v'.
The filter employs some heuristics to guess abbreviations that don't need conversion.
| Original | Conversion |
|---|---|
| this is a test | This Is a Test |
| THIS IS A TEST | This Is a Test |
| this is a TEST | This Is a TEST |
More examples and expected behavior for corner cases are available in the package test suite.
This library is a resurrection of Stuart Colville's titlecase.py, which was in turn a port of John Gruber's titlecase.pl.
Issues, updates, pull requests, etc should be directed to github.
The easiest method is to simply use pip:
(sudo) pip install titlecase
Titlecase provides only one function, simply:
>>> from titlecase import titlecase
>>> titlecase('a thing')
'A Thing'A callback function may also be supplied, which will be called for every word:
>>> def abbreviations(word, **kwargs):
... if word.upper() in ('TCP', 'UDP'):
... return word.upper()
...
>>> titlecase.titlecase('a simple tcp and udp wrapper', callback=abbreviations)
'A Simple TCP and UDP Wrapper'The callback function is supplied with an all_caps keyword argument, indicating
whether the entire line of text was entirely capitalized. Returning None from
the callback function will allow titlecase to process the word as normal.
Titlecase also provides a command line utility titlecase:
$ titlecase make me a title Make Me a Title $ echo "Can pipe and/or whatever else" | titlecase Can Pipe and/or Whatever Else # Or read/write files: $ titlecase -f infile -o outfile
In addition, commonly used acronyms can be kept in a local file at ~/.titlecase.txt. This file contains one acronym per line. The acronym will be maintained in the title as it is provided. Once there is e.g. one line saying TCP, then it will be automatically used when used from the command line.
$ titlecase I LOVE TCP I Love TCP
This is a best-effort library that uses regexes to try to do intelligent things, but will have limitations. For example, it does not have the contextual awareness to distinguish acronyms from words: us (we) versus US (United States).
The regexes and titlecasing rules were written for American English. While there is basic support for Unicode characters, such that something like "El Niño" will work, it is likely that accents or non-English phrases will not be handled correctly.
If anyone has concrete solutions to improve these or other shortcomings of the library, pull requests are very welcome!