# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: 2016-2024 PyThaiNLP Project
# SPDX-License-Identifier: Apache-2.0
"""
Common lists of words.
"""
__all__ = [
"countries",
"find_synonyms",
"provinces",
"thai_family_names",
"thai_female_names",
"thai_male_names",
"thai_negations",
"thai_dict",
"thai_stopwords",
"thai_syllables",
"thai_synonym",
"thai_synonyms",
"thai_words",
"thai_wsd_dict",
]
from typing import FrozenSet, List, Union
import warnings
from pythainlp.corpus import get_corpus, get_corpus_as_is, get_corpus_path
_THAI_COUNTRIES: FrozenSet[str] = frozenset()
_THAI_COUNTRIES_FILENAME = "countries_th.txt"
_THAI_THAILAND_PROVINCES: FrozenSet[str] = frozenset()
_THAI_THAILAND_PROVINCES_DETAILS: List[dict] = []
_THAI_THAILAND_PROVINCES_FILENAME = "thailand_provinces_th.csv"
_THAI_SYLLABLES: FrozenSet[str] = frozenset()
_THAI_SYLLABLES_FILENAME = "syllables_th.txt"
_THAI_WORDS: FrozenSet[str] = frozenset()
_THAI_WORDS_FILENAME = "words_th.txt"
_THAI_STOPWORDS: FrozenSet[str] = frozenset()
_THAI_STOPWORDS_FILENAME = "stopwords_th.txt"
_THAI_NEGATIONS: FrozenSet[str] = frozenset()
_THAI_NEGATIONS_FILENAME = "negations_th.txt"
_THAI_FAMLIY_NAMES: FrozenSet[str] = frozenset()
_THAI_FAMLIY_NAMES_FILENAME = "family_names_th.txt"
_THAI_FEMALE_NAMES: FrozenSet[str] = frozenset()
_THAI_FEMALE_NAMES_FILENAME = "person_names_female_th.txt"
_THAI_MALE_NAMES: FrozenSet[str] = frozenset()
_THAI_MALE_NAMES_FILENAME = "person_names_male_th.txt"
_THAI_ORST_WORDS: FrozenSet[str] = frozenset()
_THAI_DICT = {}
_THAI_WSD_DICT = {}
_THAI_SYNONYMS = {}
[docs]def countries() -> FrozenSet[str]:
"""
Return a frozenset of country names in Thai such as "แคนาดา", "โรมาเนีย",
"แอลจีเรีย", and "ลาว".
\n(See: `dev/pythainlp/corpus/countries_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/countries_th.txt>`_)
:return: :class:`frozenset` containing country names in Thai
:rtype: :class:`frozenset`
"""
global _THAI_COUNTRIES
if not _THAI_COUNTRIES:
_THAI_COUNTRIES = get_corpus(_THAI_COUNTRIES_FILENAME)
return _THAI_COUNTRIES
[docs]def provinces(details: bool = False) -> Union[FrozenSet[str], List[dict]]:
"""
Return a frozenset of Thailand province names in Thai such as "กระบี่",
"กรุงเทพมหานคร", "กาญจนบุรี", and "อุบลราชธานี".
\n(See: `dev/pythainlp/corpus/thailand_provinces_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/thailand_provinces_th.txt>`_)
:param bool details: return details of provinces or not
:return: :class:`frozenset` containing province names of Thailand \
(if details is False) or :class:`list` containing :class:`dict` of \
province names and details such as \
[{'name_th': 'นนทบุรี', 'abbr_th': 'นบ', 'name_en': 'Nonthaburi', \
'abbr_en': 'NBI'}].
:rtype: :class:`frozenset` or :class:`list`
"""
global _THAI_THAILAND_PROVINCES, _THAI_THAILAND_PROVINCES_DETAILS
if not _THAI_THAILAND_PROVINCES or not _THAI_THAILAND_PROVINCES_DETAILS:
provs = set()
prov_details = []
for line in get_corpus_as_is(_THAI_THAILAND_PROVINCES_FILENAME):
p = line.split(",")
prov = {}
prov["name_th"] = p[0]
prov["abbr_th"] = p[1]
prov["name_en"] = p[2]
prov["abbr_en"] = p[3]
provs.add(prov["name_th"])
prov_details.append(prov)
_THAI_THAILAND_PROVINCES = frozenset(provs)
_THAI_THAILAND_PROVINCES_DETAILS = prov_details
if details:
return _THAI_THAILAND_PROVINCES_DETAILS
return _THAI_THAILAND_PROVINCES
[docs]def thai_syllables() -> FrozenSet[str]:
"""
Return a frozenset of Thai syllables such as "กรอบ", "ก็", "๑", "โมบ",
"โมน", "โม่ง", "กา", "ก่า", and, "ก้า".
\n(See: `dev/pythainlp/corpus/syllables_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/syllables_th.txt>`_)
We use the Thai syllable list from `KUCut <https://github.com/Thanabhat/KUCut>`_.
:return: :class:`frozenset` containing syllables in the Thai language.
:rtype: :class:`frozenset`
"""
global _THAI_SYLLABLES
if not _THAI_SYLLABLES:
_THAI_SYLLABLES = get_corpus(_THAI_SYLLABLES_FILENAME)
return _THAI_SYLLABLES
[docs]def thai_words() -> FrozenSet[str]:
"""
Return a frozenset of Thai words such as "กติกา", "กดดัน", "พิษ",
and "พิษภัย". \n(See: `dev/pythainlp/corpus/words_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/words_th.txt>`_)
:return: :class:`frozenset` containing words in the Thai language.
:rtype: :class:`frozenset`
"""
global _THAI_WORDS
if not _THAI_WORDS:
_THAI_WORDS = get_corpus(_THAI_WORDS_FILENAME)
return _THAI_WORDS
[docs]def thai_orst_words() -> FrozenSet[str]:
"""
Return a frozenset of Thai words from Royal Society of Thailand
\n(See: `dev/pythainlp/corpus/thai_orst_words.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/orst_words_th.txt>`_)
:return: :class:`frozenset` containing words in the Thai language.
:rtype: :class:`frozenset`
"""
global _THAI_ORST_WORDS
if not _THAI_ORST_WORDS:
_THAI_ORST_WORDS = get_corpus("orst_words_th.txt")
return _THAI_ORST_WORDS
[docs]def thai_stopwords() -> FrozenSet[str]:
"""
Return a frozenset of Thai stopwords such as "มี", "ไป", "ไง", "ขณะ",
"การ", and "ประการหนึ่ง". \n(See: `dev/pythainlp/corpus/stopwords_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/stopwords_th.txt>`_)
We use stopword lists by thesis's เพ็ญศิริ ลี้ตระกูล.
:See Also:
เพ็ญศิริ ลี้ตระกูล . \
การเลือกประโยคสำคัญในการสรุปความภาษาไทยโดยใช้แบบจำลองแบบลำดับชั้น. \
กรุงเทพมหานคร : มหาวิทยาลัยธรรมศาสตร์; 2551.
:return: :class:`frozenset` containing stopwords.
:rtype: :class:`frozenset`
"""
global _THAI_STOPWORDS
if not _THAI_STOPWORDS:
_THAI_STOPWORDS = get_corpus(_THAI_STOPWORDS_FILENAME)
return _THAI_STOPWORDS
[docs]def thai_negations() -> FrozenSet[str]:
"""
Return a frozenset of Thai negation words including "ไม่" and "แต่".
\n(See: `dev/pythainlp/corpus/negations_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/negations_th.txt>`_)
:return: :class:`frozenset` containing negations in the Thai language.
:rtype: :class:`frozenset`
"""
global _THAI_NEGATIONS
if not _THAI_NEGATIONS:
_THAI_NEGATIONS = get_corpus(_THAI_NEGATIONS_FILENAME)
return _THAI_NEGATIONS
[docs]def thai_family_names() -> FrozenSet[str]:
"""
Return a frozenset of Thai family names
\n(See: `dev/pythainlp/corpus/family_names_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/family_names_th.txt>`_)
:return: :class:`frozenset` containing Thai family names.
:rtype: :class:`frozenset`
"""
global _THAI_FAMLIY_NAMES
if not _THAI_FAMLIY_NAMES:
_THAI_FAMLIY_NAMES = get_corpus(_THAI_FAMLIY_NAMES_FILENAME)
return _THAI_FAMLIY_NAMES
[docs]def thai_female_names() -> FrozenSet[str]:
"""
Return a frozenset of Thai female names
\n(See: `dev/pythainlp/corpus/person_names_female_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/person_names_female_th.txt>`_)
:return: :class:`frozenset` containing Thai female names.
:rtype: :class:`frozenset`
"""
global _THAI_FEMALE_NAMES
if not _THAI_FEMALE_NAMES:
_THAI_FEMALE_NAMES = get_corpus(_THAI_FEMALE_NAMES_FILENAME)
return _THAI_FEMALE_NAMES
[docs]def thai_male_names() -> FrozenSet[str]:
"""
Return a frozenset of Thai male names
\n(See: `dev/pythainlp/corpus/person_names_male_th.txt\
<https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/person_names_male_th.txt>`_)
:return: :class:`frozenset` containing Thai male names.
:rtype: :class:`frozenset`
"""
global _THAI_MALE_NAMES
if not _THAI_MALE_NAMES:
_THAI_MALE_NAMES = get_corpus(_THAI_MALE_NAMES_FILENAME)
return _THAI_MALE_NAMES
[docs]def thai_dict() -> dict:
"""
Return Thai dictionary with definition from wiktionary.
\n(See: `thai_dict\
<https://pythainlp.github.io/pythainlp-corpus/thai_dict.html>`_)
:return: Thai words with part-of-speech type and definition
:rtype: dict
"""
global _THAI_DICT
if not _THAI_DICT:
import csv
_THAI_DICT = {"word": [], "meaning": []}
with open(
get_corpus_path("thai_dict"), newline="\n", encoding="utf-8"
) as csvfile:
reader = csv.DictReader(csvfile, delimiter=",")
for row in reader:
_THAI_DICT["word"].append(row["word"])
_THAI_DICT["meaning"].append(row["meaning"])
return _THAI_DICT
[docs]def thai_wsd_dict() -> dict:
"""
Return Thai Word Sense Disambiguation dictionary with definition from wiktionary.
\n(See: `thai_dict\
<https://pythainlp.github.io/pythainlp-corpus/thai_dict.html>`_)
:return: Thai words with part-of-speech type and definition
:rtype: dict
"""
global _THAI_WSD_DICT
if not _THAI_WSD_DICT:
_thai_wsd = thai_dict()
_THAI_WSD_DICT = {"word": [], "meaning": []}
for i, j in zip(_thai_wsd["word"], _thai_wsd["meaning"]):
_all_value = list(eval(j).values())
_use = []
for k in _all_value:
_use.extend(k)
_use = list(set(_use))
if len(_use) > 1:
_THAI_WSD_DICT["word"].append(i)
_THAI_WSD_DICT["meaning"].append(_use)
return _THAI_WSD_DICT
[docs]def thai_synonyms() -> dict:
"""
Return Thai synonyms.
\n(See: `thai_synonym\
<https://pythainlp.github.io/pythainlp-corpus/thai_synonym.html>`_)
:return: Thai words with part-of-speech type and synonym
:rtype: dict
"""
global _THAI_SYNONYMS
if not _THAI_SYNONYMS:
import csv
_THAI_SYNONYMS = {"word": [], "pos": [], "synonym": []}
with open(
get_corpus_path("thai_synonym"), newline="\n", encoding="utf-8"
) as csvfile:
reader = csv.DictReader(csvfile, delimiter=",")
for row in reader:
_THAI_SYNONYMS["word"].append(row["word"])
_THAI_SYNONYMS["pos"].append(row["pos"])
_THAI_SYNONYMS["synonym"].append(row["synonym"].split("|"))
return _THAI_SYNONYMS
def thai_synonym() -> dict:
warnings.warn("Deprecated: Use thai_synonyms() instead.", DeprecationWarning)
return thai_synonyms()
def find_synonyms(word: str) -> List[str]:
"""
Find synonyms
:param str word: Thai word
:return: List of synonyms of the input word or an empty list if it isn't exist.
:rtype: List[str]
:Example:
::
from pythainlp.corpus import find_synonyms
print(find_synonyms("หมู"))
# output: ['จรุก', 'วราหะ', 'วราห์', 'ศูกร', 'สุกร']
"""
synonyms = thai_synonyms() # get a dictionary of {word, synonym}
list_synonym = []
if word in synonyms["word"]: # find by word
list_synonym.extend(synonyms["synonym"][synonyms["word"].index(word)])
for idx, words in enumerate(synonyms["synonym"]): # find by synonym
if word in words:
list_synonym.extend(synonyms["synonym"][idx])
list_synonym.append(synonyms["word"][idx])
list_synonym = sorted(list(set(list_synonym)))
if word in list_synonym: # remove same word
list_synonym.remove(word)
return list_synonym