wordsworth

Here is an example of some typical output you can expect to see. ###Setup Before you get started you need to install the python blessings library to colorize the terminal output.

$ sudo pip install blessings

###Basic Usage: ####Example 1: Print the top 50 n-grams in textfile.txt

$ python wordsworth.py --filename textfile.txt --top 50

$ python wordsworth.py -f textfile.txt -t 50

####Example 2: Print the top n-grams of up to 10 words in textfile.txt

$ python wordsworth.py --filename textfile.txt --ntuple 10

$ python wordsworth.py -f textfile.txt -n 10

####Example 3: Ignore the words 'the', 'a' and '--'.

$ python wordsworth.py --filename textfile.txt --ignore the,a,--

$ python wordsworth.py -f textfile.txt -i the,a,--

####Example 4: Ignore just '--'.

$ python wordsworth.py --filename textfile.txt --ignore ,--

$ python wordsworth.py -f textfile.txt -i ,--

###NLTK-enabled wordsworth: wordsworth-nltk.py provides extended analysis, including a frequency analysis of verbs, nouns, adjectives, pronouns etc. To run this script you will need to install the python Natural Language Toolkit (NLTK) and the Brown dataset which is used for token tagging. Fortunately this is very simple to install.

Step 1. Install NLTK

$ sudo pip install nltk

Step 2. Launch the python interpreter

$ python

Step 3. Download the Brown and Punkt dataset

>>> import nltk
>>> nltk.download('brown')
>>> nltk.download('punkt')

###Example output:

hffqyd/wordsworth

wordsworth