mrs-spellings 1.0.2

a micro utility for generating plausible misspellings

MrS SpELliNgS

a micro utility to procedurally generate plausible misspellings

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Table of Contents

• MrS SpELliNgS
• Install
  • from pypi
  • from source
• Use Cases
• Usage
• Methods
  • deletion
  • swapping
  • qwerty distance (taxi-cab) based swapping
  • What is QWERTY distance?

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Install

from pypi

pip install mrs-spellings

from source

python -m pip install git+https://github.com/CircArgs/mrs_spellings.git

Use Cases

• Generate misspellings to replace during the text cleaning process with low overhead
• Replace words with their potential misspellings as an augmentation during
  • training to make your model less susceptible to misspellings
  • during test time as part of TTA
• Supplement an existing solution for out-of-vocabulary words/ words that do not appear in an existing replacement dictionary

Usage

There are 3 primary methods currently supported:

• deletion
• swapping
• qwerty distance (taxi-cab) based swapping

In [1]: from mrs_spellings import MrsWord, MrsSpellings                                                                                                                                                            
#methods return MrsSpellings
In [2]: MrsWord("hello").swap()                                                                                                                                                                      
Out[2]: {'ehllo', 'hello', 'helol', 'hlelo'}

In [3]: MrsWord("hello").delete(number_deletes=1)                                                                                                                                                    
Out[3]: {'ello', 'hell', 'helo', 'hllo'}

In [4]: MrsWord("hello").qwerty_swap(max_distance=1)                                                                                                                                                 
Out[4]: 
{'gello',
 'h3llo',
 'hdllo',
 'he,lo',
 'he:lo',
  ...
 'jello',
 'nello',
 'yello'}
# simply chain methods
In [5]: MrsWord("hello").swap().delete()                                                                                                                                                             
Out[5]: 
{'ehll',
 'ehlo',
 'ello',
  ...
 'hllo',
 'hlol',
 'lelo'}
 
# MrsWord is a string
In [6]: MrsWord("Hello") + " " + MrsWord("World")                                                                                                                                                        
Out[6]: 'Hello World'

In [7]: MrsWord("Hello {}").format("world")                                                                                                                                                      
Out[7]: 'Hello world'

# MrsSpellings work as sets
In [8]: MrsWord("hello").swap().union(MrsWord("world").delete())                                                                                                                        
Out[8]: {'ehllo', 'hello', 'helol', 'hlelo', 'orld', 'wold', 'word', 'worl', 'wrld'}

In [9]: MrsWord("hello").delete(1)-MrsWord("hello").delete(1)                                                                                                                                        
Out[9]: set()

In [10]: " ".join(MrsWord("Hello").qwerty_swap())                                                                                                                                                     
Out[10]: 'Helko Hdllo Yello He,lo Helll Hellp Hel,o Nello Heklo Hrllo H3llo Gello Heolo He:lo Helli Hell9 Heloo Hel:o Jello Hwllo'

Methods

deletion

Signature: MrsWord.delete(number_deletes=1)
Docstring:
delete some number `number_deletes` from this word

Args:
    number_deletes (int): number of deletions to perform

Returns:
    MrsSpellings (set): all possible misspellings that form as a result of `number_deletes` deletions

swapping

Signature: MrsWord.swap()
Docstring:
swap some consecutive characters

Args:

Returns:
    MrsSpellings (set): all possible misspellings that form as a result of swapping consecutive characters

qwerty distance (taxi-cab) based swapping

Signature: MrsWord.qwerty_swap(max_distance=1)
Docstring:

swap characters with their qwerty neighbors

Args:
    max_distance (int): the max distance (taxi-cab) of keys on the keyboard to swap
                        e.g. `max_distance=1` then "g" could become one of ["f", "h"]
                            `max_distance=2` then "g" could become one of ['f', 'h', 't', 'y', 'v', 'b']
                            Note: The number of swaps possible increases with distance however the increase is not always uniform.
                            For example, the 3rd set of keys from g is ['6', 'd', 'j'] while the second was ['t', 'y', 'v', 'b']
Returns:
    MrsSpellings (set): all possible misspellings that form as a result of swapping characters with qwerty neighbors

what is qwerty distance?

Qwerty distance is the distance between keys on the typical keyboard. For the purposes of this package, the following assumptions are made:

• each row has half a key offset
• the l1 distance is a good estimate of the natural travel distance between keys on the keyboard
• the shift key can add distance by virtue of requiring a hold-down

Here is an example of the results of these assumptions. The closest keys grouped by equal distance (groups in ascending order to furthest distance) to the g key are:

[['f', 'h'],
 ['t', 'y', 'v', 'b'],
 ['6', 'd', 'j'],
 ['r', 'u', 'c', 'n'],
 ['^', '5', '7', 's', 'k'],
 ['e', 'i', 'x', 'm'],
 ['%', '&', '4', '8', 'a', 'l'],
 ['w', 'o', 'z', '<'],
 ['$', '*', '3', '9', ':'],
 ['q', 'p', ','],
 ['#', '(', '2', '0', ';'],
 ['[', '>'],
 ['@', ')', '1', '-', '"'],
 [']', '.'],
 ['!', '_', '`', '=', "'"],
 ['\\', '?'],
 ['~', '+', '{'],
 ['/'],
 ['}'],
 ['|']]