Delay external dependency imports to class initialization

[Copilot]

What do these changes do

Moves module-level imports of heavy external dependencies (transformers, torch, gensim, numpy, spacy) to class initialization methods, enabling module imports without requiring optional dependencies.

What was wrong

Module-level imports forced dependency resolution at import time, blocking:

• Documentation tools from importing modules without full dependency installation
• Module-level helper functions from working independently
• Clear error context (failures at import vs. instantiation)

Example failure case:

from pythainlp.word_vector import core  # Fails if gensim not installed
# Even if you only wanted to use a helper function, not WordVector class

How this fixes it

Defers dependency imports to where they're actually needed:

Pattern 1: Import in __init__

class KeyBERT:
    def __init__(self, model_name: str):
        from transformers import pipeline  # Loaded only when class instantiated
        self.ft_pipeline = pipeline(...)

Pattern 2: Import in method

def sentence_vectorizer(self, text: str) -> ndarray:
    from numpy import zeros  # Loaded only when method called
    vec = zeros((1, self.WV_DIM))

Pattern 3: Lazy module-level via getter

_tokenizer = None

def _get_tokenizer():
    global _tokenizer
    if _tokenizer is None:
        from transformers import CamembertTokenizer
        _tokenizer = CamembertTokenizer.from_pretrained(...)
    return _tokenizer

Used TYPE_CHECKING guards to preserve type hints without runtime imports. Updated type hints to use native Python 3.9+ lowercase types (list, dict) with Union from typing module for compatibility with Python 3.9 strict mode and type inspection tools.

Modified modules (9):

• word_vector/core.py - gensim, numpy
• summarize/keybert.py - numpy, transformers
• summarize/mt5.py - transformers
• wangchanberta/core.py - transformers (tokenizer)
• coref/_fastcoref.py - spacy
• coref/han_coref.py - spacy
• parse/transformers_ud.py - transformers, numpy, torch, ufal (uses Union[list[list[str]], str] syntax)
• augment/lm/wangchanberta.py - transformers
• augment/lm/fasttext.py - gensim

Your checklist for this pull request

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

Original prompt

Find the module level imports of external dependencies that could be import at the initialization step of the class inside that module instead.

Basically try to delaying the import until the point of creating an object, instead of immediately import external dependencies at the point of the module import.

this will

• Allows helper functions in that module (if any) to work without external dependencies
• Module can be imported for documentation generation
• Clear error only when class is instantiated

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[Copilot]

Pull request overview

Copilot reviewed 10 out of 10 changed files in this pull request and generated 2 comments.

[bact]

@copilot review again

[Copilot]

@copilot review again

All review comments have been addressed in commit 6a2a398:

• Restored tests/data/text-misspelled-r0.05-seed1.txt that was accidentally deleted
• Updated pythainlp/parse/transformers_ud.py to use Python 3.9+ native union syntax (list[list[str]] | str)
• Removed unused typing.Union and typing.List imports

All 111 core tests pass and Ruff linting checks succeed.

[bact]

@copilot
Use native type in type hint.
But do not use A | B style Union.
We want to keep compatibility with Python 3.9 strict and allow type inspection tools to work correctly.

[Copilot]

@copilot
Use native type in type hint.
But do not use A | B style Union....

Updated in commit 0ec00ae to use Union[list[list[str]], str] instead of PEP 604 union syntax (|). This maintains Python 3.9 strict compatibility while using native lowercase list types. All 111 core tests pass and Ruff linting succeeds.

[sonarqubecloud]

Quality Gate passed

Issues
1 New issue
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