function::tokenize - Linux

Overview

function::tokenize is a powerful command used to tokenize (split strings into words) text data, making it easier to analyze, process, and extract meaningful information. It’s commonly used in natural language processing (NLP) tasks, such as text mining, sentiment analysis, and summarizing.

Syntax

function::tokenize [OPTIONS] <STRING>

Options/Flags

  • -a, –all: Tokenize punctuation and numbers.
  • -l, –lowercase: Convert all tokens to lowercase.
  • -s, –stoplist: Remove stop words (e.g., "the", "and").
  • -c, –count: Count the number of occurrences of each token.
  • -t, –threshold: Minimum number of occurrences for a token to be counted.
  • -f, –file: Read input from a file instead of STDIN.

Examples

Basic tokenization:

function::tokenize "Hello World!"

Output:

Hello
World
!

Tokenization with stop words removed:

function::tokenize -s "The quick brown fox jumps over the lazy dog"

Output:

quick
brown
fox
jumps
lazy
dog

Counting token occurrences:

function::tokenize -c "To be or not to be, that is the question"

Output:

be: 2
is: 1
not: 1
or: 1
question: 1
that: 1
to: 2

Tokenization from a file:

function::tokenize -f input.txt

Common Issues

  • Missing input: Ensure you provide a string to tokenize or specify a valid file path.
  • Duplicate tokens: Consider using the -t option to ignore tokens with low occurrences.
  • Unexpected results: Check the casing and stop word list if the tokenization doesn’t match your expectations.

Integration

Pipe to other commands:

function::tokenize | sort | uniq -c

Create a custom tokenizer:

function my_tokenizer() {
  function::tokenize "$@" | sed 's/,//'
}

Related Commands

  • awk: For advanced string manipulation.
  • grep: For searching and matching text patterns.
  • sed: For stream editing and text substitution.