Add type hints to modules in extra test suite

[Copilot]

What do these changes do

Adds complete type annotations to 8 modules tested in the "extra" test suite: corpus.wordnet, spell.{tltk,phunspell}, word_vector.core, transliterate.{tltk,ipa}, tag.tltk, augment.word2vec.bpemb_wv, augment.lm.wangchanberta, and benchmarks.word_tokenization.

What was wrong

Functions lacked type hints, causing mypy errors and poor IDE support. External libraries (NLTK, tltk, epitran, phunspell, bpemb) return Any without type stubs.

How this fixes it

Approach:

• Analyzed NLTK wordnet source to verify return types match annotations (e.g., synsets() returns list, langs() returns list)
• Used # type: ignore[no-any-return] only when external libraries genuinely lack type stubs
• Applied proper numpy types (np.intp, np.ndarray) in benchmarks module instead of generic annotations

Key changes:

• wordnet.py: Added type ignores to 10 wrapper functions after verifying NLTK source
• benchmarks/word_tokenization.py: Explicit np.intp annotations for sum operations, np.ndarray for binary representation
• spell/, transliterate/, tag/, augment/: Type ignores for external library returns

Example:

# Before
def synsets(word: str, pos: Optional[str] = None, lang: str = "tha"):
    return wordnet.synsets(lemma=word, pos=pos, lang=lang)  # mypy error: Returning Any

# After  
def synsets(word: str, pos: Optional[str] = None, lang: str = "tha") -> list[wordnet.Synset]:
    return wordnet.synsets(lemma=word, pos=pos, lang=lang)  # type: ignore[no-any-return]

Your checklist for this pull request

• Passed code styles and structures
• Passed code linting checks and unit test

Original prompt

Type hints

Iterating to incrementally add type hints to submodules,
based on works done in these PRs:
#1262
#1263
#1264
#1265
#1266

Strategy

• Start with small functions/classes and functions/classes that require few external dependencies.
• Moving gradually one function by one function, in the four test suites: starting from "core", then "compact", then "extra", and "noauto".

Goals

• Immediate goal for this session - 100% type hints for functions/classes being called in "extra" test suite.
• Ultimate goal (outside of this session) is to reach 100% type hints in the entire repo, make the package a typed package, while keeping maintainability.

Instructions

• Follow best practices and standard Python type hint patterns.
• Start small in the area with high confidence (like highly tested submodules or functions), then gradually grow one submodule at a time.
• Use mypy as main assistant.
  • mypy is already in "dev" extra dependencies in pyproject.toml
  • mypy configuration is in pyproject.toml
  • Sometimes mypy may report errors wrongly due to cache issues. Try to reset the cache.
• Use pyright, pyrefly, and pytype for second opinions.
• Required dependencies for each test suite are in pyproject.toml. Install them to avoid errors. See https://github.com/PyThaiNLP/pythainlp/blob/dev/tests/README.md
• Use native type in type hint (list, tuple, .. instead of List, Tuple, ..)
• Do not use A | B style Union, use full Union[] instead.
• We want to keep compatibility with Python 3.9 strict and allow type inspection tools to work correctly.
• When insert typing imports, put it in appropriate location and order
• Use "if TYPE_CHECKING import" block when possible.
• When reordering the imports, beware of circular import. Read comments near imports to get more information.
• Remove unused imports
• Do not allow the use of assert in production code (it is only allowed for testing and debugging).
• Try to fix the type, the scope logic, or do the casting, before putting #type: ignore comment.
• When dealing with types from external libraries:
  • Check if type information is provided (maybe through stubs). If it is, cast wrapper may not necessary.
  • If return type is not provided, may be it is appropriate to use # type: ignore[no-any-return] annotation for clarity.
• Recheck necessity when do casting.
• Recheck necessity of # noqa: and # type: ignore
• Provide type stubs as necessary.
• After changes for type hints, recheck for functionality correctness.
• Recheck docstring and documentation consistency with the code; They should match the updated type hints.
• Recheck formatting with ruff
• Do another code review
• Address code review feedback

---

💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more Copilot coding agent tips in the docs.

[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud

[coveralls]

coverage: 65.762%. remained the same
when pulling c2edfb3 on copilot/add-type-hints-to-submodules-one-more-time
into a22ff19 on dev.