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Schedule
See 2.2 Milestone.
_onecut()
thaiword_to_date()
thaiword_to_time()
countthai()
thaicheck()
is_native_thai()
deletetone()
remove_tonemark()
dict_word_tokenize()
word_tokenize(custom_dict=)
pythainlp.tokenize.Trie
pythainlp.util.Trie
add()
Trie
numpy
pandas
nltk
pip install pythainlp[wordnet]
sklearn-crfsuite
python-crfsuite
dill
tqdm
__init__.py
NorvigSpellChecker
custom_dict
NLTK
words_th.txt
The text was updated successfully, but these errors were encountered:
how I can install pythainlp 2.2 ?
Sorry, something went wrong.
Hi @korntawat,
We can use this approach:
pip install --upgrade https://github.com/PyThaiNLP/pythainlp/archive/<BRANCH-NAME>
In this case, as those referred issues have been merged to dev already. So, you can just do
dev
pip install --upgrade https://github.com/PyThaiNLP/pythainlp/archive/dev
@bact @wannaphong please correct me if I'm wrong.
Tentative release date: 24 June 2020
2.2.0 production release: 24 June 2020 https://github.com/PyThaiNLP/pythainlp/releases/tag/v2.2.0
bact
No branches or pull requests
Schedule
See 2.2 Milestone.
Tokenization
_onecut()
to avoid long wait for ambiguous text (also back ported to 2.1.1)Transliteration
Normalization
Utilities
thaiword_to_date()
andthaiword_to_time()
countthai()
to handle a case where the text has only numbers and symbols -- thanks @opalthailand for the reportCommand line
Deprecation and other API changes
thaicheck()
-- useis_native_thai()
insteaddeletetone()
-- useremove_tonemark()
dict_word_tokenize()
-- useword_tokenize(custom_dict=)
pythainlp.tokenize.Trie
, usepythainlp.util.Trie
insteadadd()
toTrie
class. Now can add more words after the instantiation of Trie objectDependencies
numpy
andpandas
requirements from base install -- thanks @mmaybeno and @PNNutkung for the reportnltk
requirements from base install. WordNet API needs NLTK, to use itpip install pythainlp[wordnet]
sklearn-crfsuite
requirements. Port Thai NER fromsklearn-crfsuite
topython-crfsuite
.dill
requirementstqdm
requirements. tqdm will be use to show progress bar when found. If not found, use a fallback progress reportOthers
__init__.py
files, etc.NorvigSpellChecker
class, add more type supports forcustom_dict
in the constructorNLTK
modulewords_th.txt
(used in dictionary-based word segmentation)The text was updated successfully, but these errors were encountered: