https://github.com/pirate/spellchecker

:book: A spell-checker extending Peter Norvig's with multi-typo correction, hamming distance weighting, and more.
https://github.com/pirate/spellchecker

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:book: A spell-checker extending Peter Norvig's with multi-typo correction, hamming distance weighting, and more.

• Host: GitHub
• URL: https://github.com/pirate/spellchecker
• Owner: pirate
• Created: 2014-07-17T15:52:31.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2020-10-01T19:16:25.000Z (over 3 years ago)
• Last Synced: 2023-06-09T05:55:16.608Z (about 1 year ago)
• Language: Python
• Homepage: http://norvig.com/spell-correct.html
• Size: 776 KB
• Stars: 95
• Watchers: 6
• Forks: 22
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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• awesome-stars - pirate/spellchecker - :book: A spell-checker extending Peter Norvig's with multi-typo correction, hamming distance weighting, and more. (Python)

README

        
# Simple Python Spell-Checker

## Quickstart

```bash

git clone https://github.com/pirate/spellchecker

cd spellchecker/

python spellchecker.py

# type interactively to get suggestions

Total Word Set: 285750

Model Precision: 1.62249168854

>manster

[('monster', 2), ('minster', 2)]

# or try some preset mispelled words

python misspeller.py | python spellchecker.py 

```

You can edit `spellchecker.py` and add more files to the training list to increase the word-frequency model precision.

## Background

Peter Norvig wrote an amazing article titled [How to Write a Spelling Corrector](http://norvig.com/spell-correct.html) detailing a basic approach to this deceivingly simple problem.

I had to write a spellchecker as an interview question for [Disqus](https://disqus.com/), and this repo details my efforts.

The core code that I borrow from [Darius Bacon](https://github.com/darius) & Norvig is this beautiful block:

```python

def variants(word):

    """get all possible variants for a word"""

    splits     = [(word[:i], word[i:]) for i in range(len(word) + 1)]

    deletes    = [a + b[1:] for a, b in splits if b]

    transposes = [a + b[1] + b[0] + b[2:] for a, b in splits if len(b)>1]

    replaces   = [a + c + b[1:] for a, b in splits for c in alphabet if b]

    inserts    = [a + c + b for a, b in splits for c in alphabet]

    return set(deletes + transposes + replaces + inserts)

```

Of course that wasn't my only code, I added a lot more on top of Norvig's implementation.

My additions are:

  - short-circuiting options for faster checking

  - hamming distance and word-frequency model based chooser for suggestions

  - double word variants for catching more complex multi-typos

  - vowel-swapping detection

  - a reductions function to efficiently store word variants like `monster: ['m',['o', 'a'], 'n', 's', 't', 'e', 'r']`

## Faster Algorithm

A faster spellchecking algorithm exists, see: https://github.com/wolfgarbe/SymSpell