Using custom word list with pythainlp Tokenizer class. Also with spaCy.

tokenizer.py

# from https://www.facebook.com/groups/thainlp/permalink/721765038204989/
import pythainlp
from pythainlp import Tokenizer

# 2 ways to create it
tokenizer = Tokenizer(["word1", "word2"])
tokenizer = Tokenizer("path/dict.txt")

# default word list
words = pythainlp.corpus.thai_words()
# ttc word list
from pythainlp.corpus import ttc
words = [w for w,_ in ttc.word_freqs()]
# can edit words here first
tok = Tokenizer(words)

tokenizer_spacy.py

!pip install pythainlp
import pythainlp
from pythainlp.corpus import ttc

# create custom tokenizer
min_words = [w for w,_ in ttc.word_freqs()]  # can add to it
tok = pythainlp.Tokenizer(min_words)

# use it with spaCy
from spacy.lang.th import Thai
nlp = Thai()
nlp.tokenizer.word_tokenize = tok.word_tokenize  # change to custom
list(nlp('ฝนตกที่ทะเล'))  
# ['ฝน', 'ตก', 'ที่', 'ทะเล'] because no 'ฝนตก' in min_words

word_tokenize.py

# just use word_tokenize, but with custom dict
!pip install pythainlp -q

import pythainlp
from pythainlp.tokenize import word_tokenize, newmm
from pythainlp.corpus import ttc
words = [w for w,_ in ttc.word_freqs()]
trie = pythainlp.util.Trie(words)
newmm.DEFAULT_WORD_DICT_TRIE = trie

word_tokenize('ฝนตกทั่วฟ้า')  # ['ฝน', 'ตก', 'ทั่ว', 'ฟ้า']