How to check if a word is an English word with Python?

Question

I want to check in a Python program if a word is in the English dictionary.

I believe nltk wordnet interface might be the way to go but I have no clue how to use it for such a simple task.

def is_english_word(word):
    pass # how to I implement is_english_word?

is_english_word(token.lower())

In the future, I might want to check if the singular form of a word is in the dictionary (e.g., properties -> property -> english word). How would I achieve that?

Answer 1

For (much) more power and flexibility, use a dedicated spellchecking library like PyEnchant. There's a tutorial, or you could just dive straight in:

>>> import enchant
>>> d = enchant.Dict("en_US")
>>> d.check("Hello")
True
>>> d.check("Helo")
False
>>> d.suggest("Helo")
['He lo', 'He-lo', 'Hello', 'Helot', 'Help', 'Halo', 'Hell', 'Held', 'Helm', 'Hero', "He'll"]
>>>

PyEnchant comes with a few dictionaries (en_GB, en_US, de_DE, fr_FR), but can use any of the OpenOffice ones if you want more languages.

There appears to be a pluralisation library called inflect, but I've no idea whether it's any good.

Answer 2

It won't work well with WordNet, because WordNet does not contain all english words. Another possibility based on NLTK without enchant is NLTK's words corpus

>>> from nltk.corpus import words
>>> "would" in words.words()
True
>>> "could" in words.words()
True
>>> "should" in words.words()
True
>>> "I" in words.words()
True
>>> "you" in words.words()
True

Answer 3

Using NLTK:

from nltk.corpus import wordnet

if not wordnet.synsets(word_to_test):
  #Not an English Word
else:
  #English Word

You should refer to this article if you have trouble installing wordnet or want to try other approaches.

Answer 4

Using a set to store the word list because looking them up will be faster:

with open("english_words.txt") as word_file:
    english_words = set(word.strip().lower() for word in word_file)

def is_english_word(word):
    return word.lower() in english_words

print is_english_word("ham")  # should be true if you have a good english_words.txt

To answer the second part of the question, the plurals would already be in a good word list, but if you wanted to specifically exclude those from the list for some reason, you could indeed write a function to handle it. But English pluralization rules are tricky enough that I'd just include the plurals in the word list to begin with.

As to where to find English word lists, I found several just by Googling "English word list". Here is one: http://www.sil.org/linguistics/wordlists/english/wordlist/wordsEn.txt You could Google for British or American English if you want specifically one of those dialects.

Answer 5

For All Linux/Unix Users

If your OS uses the Linux kernel, there is a simple way to get all the words from the English/American dictionary. In the directory /usr/share/dict you have a words file. There is also a more specific american-english and british-english files. These contain all of the words in that specific language. You can access this throughout every programming language which is why I thought you might want to know about this.

Now, for python specific users, the python code below should assign the list words to have the value of every single word:

import re
file = open("/usr/share/dict/words", "r")
words = re.sub("[^\w]", " ",  file.read()).split()
file.close()
    
def is_word(word):
    return word.lower() in words
 
is_word("tarts") ## Returns true
is_word("jwiefjiojrfiorj") ## Returns False

Hope this helps!

EDIT: If you can't find the words file or something similiar, see the comment from Dr Phil below.

Answer 6

For a faster NLTK-based solution you could hash the set of words to avoid a linear search.

from nltk.corpus import words as nltk_words
def is_english_word(word):
    # creation of this dictionary would be done outside of 
    #     the function because you only need to do it once.
    dictionary = dict.fromkeys(nltk_words.words(), None)
    try:
        x = dictionary[word]
        return True
    except KeyError:
        return False

Answer 7

I find that there are 3 package-based solutions to solve the problem. They are pyenchant, wordnet and corpus(self-defined or from ntlk). Pyenchant couldn't installed easily in win64 with py3. Wordnet doesn't work very well because it's corpus isn't complete. So for me, I choose the solution answered by @Sadik, and use 'set(words.words())' to speed up.

First:

pip3 install nltk
python3

import nltk
nltk.download('words')

Then:

from nltk.corpus import words
setofwords = set(words.words())

print("hello" in setofwords)
>>True

Answer 8

With pyEnchant.checker SpellChecker:

from enchant.checker import SpellChecker

def is_in_english(quote):
    d = SpellChecker("en_US")
    d.set_text(quote)
    errors = [err.word for err in d]
    return False if ((len(errors) > 4) or len(quote.split()) < 3) else True

print(is_in_english('“办理美国加州州立大学圣贝纳迪诺分校高仿成绩单Q/V2166384296加州州立大学圣贝纳迪诺分校学历学位认证'))
print(is_in_english('“Two things are infinite: the universe and human stupidity; and I\'m not sure about the universe.”'))

> False
> True

Answer 9

For a semantic web approach, you could run a sparql query against WordNet in RDF format. Basically just use urllib module to issue GET request and return results in JSON format, parse using python 'json' module. If it's not English word you'll get no results.

As another idea, you could query Wiktionary's API.

Answer 10

use nltk.corpus instead of enchant. Enchant gives ambiguous results. For example : for benchmark and bench-mark enchant is returning true. It should suppose to return false for benchmark.

Answer 11

Download this txt file https://raw.githubusercontent.com/dwyl/english-words/master/words_alpha.txt

then create a Set out of it using the following python code snippet that loads about 370k non-alphanumeric words in english

>>> with open("/PATH/TO/words_alpha.txt") as f:
>>>     words = set(f.read().split('\n'))
>>> len(words)
370106

From here onwards, you can check for existence in constant time using

>>> word_to_check = 'baboon'
>>> word_to_check in words
True

Note that this set might not be comprehensive but still gets the job done, user should do quality checks to make sure it works for their use-case as well.

Answer 12

None of the above libraries contains all english words, so I imported a csv file containing all english words from link:--> https://github.com/dwyl/english-words

And simply made that into a pandas dataframe and compared them