Improve English grammar and clarity across all documentation and Python docstrings

.github/ISSUE_TEMPLATE/feature_request.md

@@ -1,6 +1,6 @@
 ---
 name: Feature request
-about: Propose a change or an addition เสนอความสามารถใหม่
+about: Propose a change or addition เสนอความสามารถใหม่
 ---
 
 ## Detailed description

.github/copilot-instructions.md

@@ -113,14 +113,14 @@
 - [ ] Be defensive on variable expansion.
 - [ ] Use quotes or other constructs to encapsulate paths, make it compatible
       with different kinds of shells.
-- [ ] Be mindful about semantic of different types of quotation marks.
+- [ ] Be mindful about the semantics of different types of quotation marks.
 
 ## Library imports and dependencies
 
-- [ ] Recheck the correctness of library/module/package name.
+- [ ] Check the correctness of library/module/package names.
       Be very careful of slopsquatting and typosquatting attacks.
 - [ ] Use the most updated version of the library that is supported
-      by the OS/compiler/framework currently being in used.
+      by the OS/compiler/framework currently being used.
 - [ ] In source code, group and sort imports by the programming language
       convention (e.g., in Python, typically by standard library first,
       then by third-party libraries)
@@ -130,8 +130,8 @@
 - [ ] Remove unused imports.
 - [ ] In build metadata (like pyproject.toml in Python) or
       dependency list (like requirements.txt in Python), sort dependencies.
-- [ ] Warn users about abandoned dependency with no maintenance
-      for long time and suggest equivalent drop-in replacement.
+- [ ] Warn users about abandoned dependencies with no maintenance
+      for a long time and suggest equivalent drop-in replacements.
 
 ## Security
 
@@ -153,15 +153,15 @@
 - [ ] Avoid the deserialization of untrusted data (CWE-502).
   - [ ] In Python, avoid using `pickle` module for
         serialization/deserialization.
-- [ ] When handling file and path, be careful of path traversal vulnerabilities
+- [ ] When handling files and paths, be careful of path traversal vulnerabilities
       like CWE-22.
 
 ## API
 
-- [ ] The overall architecture, code, API endpoints to follow the latest
+- [ ] The overall architecture, code, and API endpoints should follow the latest
       version of OpenAPI specification at https://spec.openapis.org/oas/
-- [ ] API endpoints must use proper HTTP return code
-- [ ] Follows web best practices as recommended by OpenAPI, IETF, W3C, etc.
+- [ ] API endpoints must use proper HTTP return codes.
+- [ ] Follow web best practices as recommended by OpenAPI, IETF, W3C, etc.
 
 ## Python
 

.github/pull_request_template.md

@@ -1,4 +1,4 @@
-### What does this changes
+### What do these changes do
 
 <!--- Brief summary of the changes -->
 

CHANGELOG.md

@@ -15,7 +15,7 @@ Notable changes between versions.
 
 ## Version 5.2.0 -> dev
 
-Some features and fixes in this version are AI assisted.
+Some features and fixes in this version are AI-assisted.
 See PR for prompt and details.
 
 - Lazy load dictionaries to reduce memory usage #1186

CODE_OF_CONDUCT.md

@@ -3,7 +3,7 @@
 ## Our Pledge
 
 In the interest of fostering an open and welcoming environment,
-we as contributors and maintainers pledge to making participation
+we as contributors and maintainers pledge to make participation
 in our project and our community a harassment-free experience for everyone,
 regardless of age, body size, disability, ethnicity, sex characteristics,
 gender identity and expression, level of experience, education,

CONTRIBUTING.md

@@ -32,7 +32,7 @@ Please refer to our [Contributor Covenant Code of Conduct](https://github.com/Py
   (see "Testing" section below);
 - Run all tests before pushing (just execute `tox`) so you will know if your
   changes broke something;
-- Commented out codes are [dead codes][dead-codes];
+- Commented-out code is [dead code][dead-codes];
 - All `#TODO` comments should be turned into [issues][issues] in GitHub;
 - When appropriate, use [f-string][pep0498]
   (use `f"{a} = {b}"`,

INTHEWILD.md

@@ -1,6 +1,6 @@
 # Who uses PyThaiNLP?
 
-We would like to keep track of who are using the package.
+We would like to keep track of who is using the package.
 Please send a PR with your company name or `@githubhandle`
 or both company name and `@githubhandle`.
 

README.md

@@ -273,5 +273,5 @@ and its BibTeX entry:
 </div>
 
 <div align="center">
-  <strong>Beware of malware if you use codes from mirrors other than the official two on GitHub and GitLab.</strong>
+  <strong>Beware of malware if you use code from mirrors other than the official two on GitHub and GitLab.</strong>
 </div>

SECURITY.md

@@ -18,7 +18,9 @@
 
 ## Future Security Recommendations
 
-- Migrate from pickle to a safer serialization format like JSON or MessagePack.
+The following security improvements are planned for future releases:
+
+- Migrate from pickle to a safer serialization format such as JSON or MessagePack.
 - Upgrade the hashing algorithm for integrity verification from MD5 to SHA-256 or SHA-3.
 - Implement digital signatures for corpus files to ensure authenticity.
 - Add version tracking to the corpus to prevent rollback attacks.

docs/notes/installation.rst

@@ -42,7 +42,7 @@ The extras can include:
   - ``abbreviation`` — abbreviation expansion utilities
   - ``full`` — install all optional dependencies
 
-For dependency details, see the `extras` variable in `setup.py <https://github.com/PyThaiNLP/pythainlp/blob/dev/setup.py>`_.
+For dependency details, see the `project.optional-dependencies` section in `pyproject.toml <https://github.com/PyThaiNLP/pythainlp/blob/dev/pyproject.toml>`_.
 
 Notes for Windows installation
 -----------------------------

docs/notes/start.rst

@@ -13,7 +13,7 @@ PyThaiNLP is a Python library for Thai natural language processing (NLP). With t
 
 Thai NLP faces several challenges. A brief list includes:
 
-#. **Sentence boundary detection** — This is one of the biggest challenges in Thai NLP. The lack of explicit end-of-sentence markers makes it difficult to create training sets for many tasks. The issue is twofold: in the writing system, Thai punctuation and spacing do not always indicate sentence endings; in language use, sentences often begin with conjunctions such as 'because' or 'but', which can make sentence boundaries ambiguous even for native speakers.
+#. **Sentence boundary detection** — This is one of the biggest challenges in Thai NLP. The lack of explicit end-of-sentence markers makes it difficult to create training sets for many tasks. The issue is twofold: (1) in the writing system, Thai punctuation and spacing do not always indicate sentence endings; (2) in language use, sentences often begin with conjunctions such as 'because' or 'but', which can make sentence boundaries ambiguous even for native speakers.
 
 #. **Word segmentation** — Thai does not use spaces to separate words, so segmentation is challenging. Solving it often requires understanding context to rule out unlikely word breaks. This is similar to issues in other Asian languages such as Japanese and Chinese. Recently, techniques that represent words, subwords, and characters as vectors (embeddings) have improved performance and help address this problem.
 

pythainlp/corpus/corpus_license.md

@@ -1,8 +1,8 @@
 # Corpus License
 
-- Corpora, datasets, and documentation created by PyThaiNLP project are released under [Creative Commons Zero 1.0 Universal Public Domain Dedication License](https://creativecommons.org/publicdomain/zero/1.0/) (CC0).
-- Language models created by PyThaiNLP project are released under [Creative Commons Attribution 4.0 International Public License](https://creativecommons.org/licenses/by/4.0/) (CC-by).
-- For more information about corpora that PyThaiNLP use, see [https://github.com/PyThaiNLP/pythainlp-corpus/](https://github.com/PyThaiNLP/pythainlp-corpus/).
+- Corpora, datasets, and documentation created by the PyThaiNLP project are released under [Creative Commons Zero 1.0 Universal Public Domain Dedication License](https://creativecommons.org/publicdomain/zero/1.0/) (CC0).
+- Language models created by the PyThaiNLP project are released under [Creative Commons Attribution 4.0 International Public License](https://creativecommons.org/licenses/by/4.0/) (CC-by).
+- For more information about corpora that PyThaiNLP uses, see [https://github.com/PyThaiNLP/pythainlp-corpus/](https://github.com/PyThaiNLP/pythainlp-corpus/).
 
 ## Dictionaries and Word Lists
 
@@ -13,7 +13,7 @@ The following word lists are created by the PyThaiNLP project and released under
 | Filename                     | Description                                            |
 | ---------------------------- | ------------------------------------------------------ |
 | countries_th.txt             | List of countries in Thai                              |
-| etcc.txt List of             | Enhanced Thai Character Clusters                       |
+| etcc.txt                     | List of Enhanced Thai Character Clusters               |
 | negations_th.txt             | Negation word list                                     |
 | stopwords_th.txt             | Stop word list                                         |
 | syllables_th.txt             | List of Thai syllables                                 |

pythainlp/soundex/core.py

@@ -23,7 +23,7 @@
 def soundex(
     text: str, engine: str = DEFAULT_SOUNDEX_ENGINE, length: int = 4
 ) -> str:
-    """This function converts Thai text into phonetic code.
+    """Converts Thai text into phonetic code.
 
     :param str text: word
     :param str engine: soundex engine

pythainlp/soundex/lk82.py

@@ -38,7 +38,7 @@
 
 
 def lk82(text: str) -> str:
-    """This function converts Thai text into phonetic code with the
+    """Converts Thai text into phonetic code with the
     Thai soundex algorithm named **LK82** [#lk82]_.
 
     :param str text: Thai word

pythainlp/soundex/metasound.py

@@ -26,7 +26,7 @@
 
 
 def metasound(text: str, length: int = 4) -> str:
-    """This function converts Thai text into phonetic code with the
+    """Converts Thai text into phonetic code with the
     matching technique called **MetaSound**
     [#metasound]_ (combination between Soundex and Metaphone algorithms).
     MetaSound algorithm was developed specifically for the Thai language.

pythainlp/soundex/prayut_and_somchaip.py

@@ -31,7 +31,7 @@
 
 
 def prayut_and_somchaip(text: str, length: int = 4) -> str:
-    """This function converts English-Thai Cross-Language Transliterated Word into
+    """Converts English-Thai Cross-Language Transliterated Words into
     phonetic code with the matching technique called **Soundex** [#prayut_and_somchaip]_.
 
     :param str text: English-Thai Cross-Language Transliterated Word

pythainlp/soundex/udom83.py

@@ -49,7 +49,7 @@
 
 
 def udom83(text: str) -> str:
-    """This function converts Thai text into phonetic code with the
+    """Converts Thai text into phonetic code with the
     Thai soundex algorithm named **Udom83** [#udom83]_.
 
     :param str text: Thai word

pythainlp/spell/core.py

@@ -24,8 +24,8 @@ def default_spell_checker() -> "NorvigSpellChecker":
 
 def spell(word: str, engine: str = "pn") -> list[str]:
     """Provides a list of possible correct spellings of the given word.
-    The list of words are from the words in the dictionary
-    that incurs an edit distance value of 1 or 2.
+    The list of words is from words in the dictionary
+    that have an edit distance value of 1 or 2.
     The result is a list of words sorted by their occurrences
     in the spelling dictionary in descending order.
 

pythainlp/summarize/core.py

@@ -24,7 +24,7 @@ def summarize(
     engine: str = DEFAULT_SUMMARIZE_ENGINE,
     tokenizer: str = "newmm",
 ) -> list[str]:
-    """This function summarizes text based on frequency of words.
+    """Summarizes text based on frequency of words.
 
     Under the hood, this function first tokenizes sentences from the given
     text with :func:`pythainlp.tokenize.sent_tokenize`.
@@ -126,12 +126,12 @@ def extract_keywords(
     tokenizer: str = "newmm",
     stop_words: Optional[Iterable[str]] = None,
 ) -> list[str]:
-    """This function returns most-relevant keywords (and/or keyphrases) from the input document.
+    """Returns most-relevant keywords (and/or keyphrases) from the input document.
     Each algorithm may produce completely different keywords from each other,
     so please be careful when choosing the algorithm.
 
     *Note*: Calling :func: `extract_keywords()` is expensive. For repetitive use of KeyBERT (the default engine),
-    creating KeyBERT object is highly recommended.
+    creating a KeyBERT object is highly recommended.
 
     :param str text: text to be summarized
     :param Tuple[int, int] keyphrase_ngram_range: Number of token units to be defined as keyword.

pythainlp/tokenize/core.py

@@ -35,7 +35,7 @@ def word_detokenize(
 ) -> Union[list[str], str]:
     """Word detokenizer.
 
-    This function will detokenize the list of words in each sentence into text.
+    Detokenizes the list of words in each sentence into text.
 
     :param str segments: List of sentences, each with a list of words.
     :param str output: the output type (str or list)

pythainlp/tokenize/nlpo3.py

@@ -44,7 +44,7 @@ def load_dict(file_path: str, dict_name: str) -> bool:
     """Load a dictionary file into an in-memory dictionary collection.
 
     The loaded dictionary will be accessible through the assigned dict_name.
-    *** This function will not override an existing dict name. ***
+    **Note: This function will not override an existing dict name.**
 
     :param file_path: Path to a dictionary file
     :type file_path: str

pythainlp/transliterate/core.py

@@ -15,7 +15,7 @@ def romanize(
     engine: str = DEFAULT_ROMANIZE_ENGINE,
     fallback_engine: str = DEFAULT_ROMANIZE_ENGINE,
 ) -> str:
-    """This function renders Thai word in the Latin alphabet or "romanization",
+    """Renders Thai words in the Latin alphabet or "romanization",
     using the Royal Thai General System of Transcription (RTGS)
     [#rtgs_transcription]_. RTGS is the official system published
     by the Royal Institute of Thailand. (Thai: ถอดเสียงภาษาไทยเป็นอักษรละติน)
@@ -104,7 +104,7 @@ def select_romanize_engine(engine: str) -> Callable[[str], str]:
 def transliterate(
     text: str, engine: str = DEFAULT_TRANSLITERATE_ENGINE
 ) -> str:
-    """This function transliterates Thai text.
+    """Transliterates Thai text.
 
     :param str text: Thai text to be transliterated
     :param str engine: 'icu', 'ipa', or 'thaig2p' (default)
@@ -187,7 +187,7 @@ def transliterate(
 
 
 def pronunciate(word: str, engine: str = DEFAULT_PRONUNCIATE_ENGINE) -> str:
-    """This function pronunciates Thai word.
+    """Pronunciates Thai words.
 
     :param str word: Thai text to be pronunciated
     :param str engine: 'w2p' (default)

pythainlp/transliterate/spoonerism.py

@@ -12,7 +12,7 @@
 def puan(word: str, show_pronunciation: bool = True) -> str:
     """Thai Spoonerism
 
-    This function converts Thai word to spoonerism word.
+    Converts a Thai word to a spoonerism word.
 
     :param str word: Thai word to be spoonerized
     :param bool show_pronunciation: True (default) or False

pythainlp/util/abbreviation.py

@@ -12,10 +12,10 @@
 def abbreviation_to_full_text(
     text: str, top_k: int = 2
 ) -> list[tuple[str, Optional[float]]]:
-    """This function converts Thai text (with abbreviation) to full text.
+    """Converts Thai text (with abbreviations) to full text.
 
-    This function uses KhamYo for handles abbreviations.
-    See more `KhamYo <https://github.com/wannaphong/KhamYo>`_.
+    Uses KhamYo to handle abbreviations.
+    See more: `KhamYo <https://github.com/wannaphong/KhamYo>`_.
 
     :param str text: Thai text
     :param int top_k: Top K

pythainlp/util/collate.py

@@ -24,7 +24,7 @@ def _thkey(word: str) -> str:
 
 
 def collate(data: Iterable, reverse: bool = False) -> list[str]:
-    """This function sorts strings (almost) according to Thai dictionary.
+    """Sorts strings (almost) according to Thai dictionary.
 
     Important notes: this implementation ignores tone marks and symbols
 

pythainlp/util/digitconv.py

@@ -64,7 +64,7 @@
 
 
 def thai_digit_to_arabic_digit(text: str) -> str:
-    """This function converts Thai digits (i.e. ๑, ๓, ๑๐) to Arabic digits
+    """Converts Thai digits (i.e. ๑, ๓, ๑๐) to Arabic digits
     (i.e. 1, 3, 10).
 
     :param str text: Text with Thai digits such as '๑', '๒', '๓'
@@ -89,7 +89,7 @@ def thai_digit_to_arabic_digit(text: str) -> str:
 
 
 def arabic_digit_to_thai_digit(text: str) -> str:
-    """This function converts Arabic digits (i.e. 1, 3, 10) to Thai digits
+    """Converts Arabic digits (i.e. 1, 3, 10) to Thai digits
     (i.e. ๑, ๓, ๑๐).
 
     :param str text: Text with Arabic digits such as '1', '2', '3'
@@ -143,7 +143,7 @@ def digit_to_text(text: str) -> str:
 
 
 def text_to_arabic_digit(text: str) -> str:
-    """This function converts spelled out digits in Thai to Arabic digits.
+    """Converts spelled out digits in Thai to Arabic digits.
 
     :param text: A digit spelled out in Thai
     :return: An Arabic digit such as '1', '2', '3' if the text is
@@ -180,7 +180,7 @@ def text_to_arabic_digit(text: str) -> str:
 
 
 def text_to_thai_digit(text: str) -> str:
-    """This function converts spelled out digits in Thai to Thai digits.
+    """Converts spelled out digits in Thai to Thai digits.
 
     :param text: A digit spelled out in Thai
     :return: A Thai digit such as '๑', '๒', '๓' if the text is digit

pythainlp/util/emojiconv.py

@@ -1834,7 +1834,7 @@
 
 
 def emoji_to_thai(text: str, delimiters=(_delimiter, _delimiter)) -> str:
-    """This function converts emojis to their Thai meanings
+    """Converts emojis to their Thai meanings.
 
     :param str text: Text with emojis
     :return: Text with emojis converted to their Thai meanings

pythainlp/util/keywords.py

@@ -73,8 +73,8 @@ def rank(words: list[str], exclude_stopwords: bool = False) -> Optional[Counter]
 
 
 def find_keyword(word_list: list[str], min_len: int = 3) -> dict[str, int]:
-    """This function counts the frequencies of words in the list
-    where stopword is excluded and returns a frequency dictionary.
+    """Counts the frequencies of words in the list
+    where stopwords are excluded and returns a frequency dictionary.
 
     :param list word_list: a list of words
     :param int min_len: the minimum frequency for words to be retained

pythainlp/util/normalize.py

@@ -246,7 +246,7 @@ def reorder_vowels(text: str) -> str:
 def remove_repeat_vowels(text: str) -> str:
     """Remove repeating vowels, tone marks, and signs.
 
-    This function will call reorder_vowels() first, to make sure that
+    Calls reorder_vowels() first to ensure that
     double Sara E will be converted to Sara Ae and not be removed.
 
     :param str text: input text