The Madman Mad Lib Generator

Replace words in a sentence with words chosen from a Markov chain generated from your favorite source material. Or, in non-technical terms, automatic Mad Libs!

Provide a source file of thousands of words of text; Madman will use this as inspiration when choosing its Mad Libs.

Requires NLTK.

Usage

1. Install NLTK for your Python version.
2. Install the wordnet, maxent_treebank_pos_tagger, and punkt datasets for NLTK, using nltk.download. (That is, run the Python CLI, import nltk, and then run nltk.download() and select the datasets.)
3. Place your favorite source material in sources/ as plain text files, named in the format sourcename-raw.txt. Large files (50,000 words or more) are good. As an example, Madman comes with some Mark Twain novels (twain.txt) to try out.
4. Use the sources/format.pl script to turn the files into one-sentence-per-line files (e.g ./format.pl sourcename).
5. Run python makeChains.py sourcename to build the Markov chain.

Now you're ready to make some mad libs. You can do this two ways: interactively in Python, or at the command line.

For interactive mode, just run python or ipython in this directory, and then just use

import madman
m = madman.Madman("sourcename")
m.madlib("Your text goes here.") # Only one sentence at a time

Alternately, to madlibify an entire text file in one shot, just run

python madfile.py yourfile.txt

Each sentence will be printed with strategic mad lib replacements.

Enjoy.

Examples

Using Mark Twain for the mad libs:

>>> m.madlib("This is a test, so please do not panic.")
'This is a giant, so please do there well.'

>>> m.madlib("Four score and seven years ago our forefathers brought forth on this continent a new nation.")
'Four score and seven dollars there our forefathers brought forth on this sign a runaway nation.'

>>> m.madlib("Ask not what your country can do for you -- ask what you can do for your country.")
'Ask not what your country can get for you-- ask what you can do for your uncles.'

For extra blasphemy, here's something based on source material I collected myself:

'Ask not what your country can do for you-- ask what you can do for your thighs.'